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UNIVERSIDADE FEDERAL DE GOIÁS
PROGRAMA DE PÓS-GRADUAÇÃO EM MEDICINA TROPICAL
E SAÚDE PÚBLICA
EDILÂNIA GOMES ARAÚJO CHAVES
Análise proteômica de Paracoccidioides spp. durante interação com
macrófagos: adaptação metabólica e fatores de virulência
Goiânia
2018
EDILÂNIA GOMES ARAÚJO CHAVES
Análise proteômica de Paracoccidioides spp. durante interação com
macrófagos: adaptação metabólica e fatores de virulência
Tese de Doutorado apresentado ao Programa
de Pós-Graduação em Medicina Tropical e
Saúde Pública da Universidade Federal de
Goiás para obtenção do Título de Doutora
em Medicina Tropical e Saúde Pública.
Orientadora: Célia Maria de Almeida
Soares
APOIO FINANCEIRO: CAPES/ CNPq/ FAPEG
Goiânia
2018
Ficha de identificação da obra elaborada pelo autor, através doPrograma de Geração Automática do Sistema de Bibliotecas da UFG.
CDU 579
Chaves, Edilânia Gomes Araújo Análise proteômica de Paracoccidioides spp. durante interação commacrófagos: adaptação metabólica e fatores de virulência [manuscrito] /Edilânia Gomes Araújo Chaves. - 2018. ccii, 202 f.: il.
Orientador: Prof. Célia Maria de Almeida Soares. Tese (Doutorado) - Universidade Federal de Goiás, Instituto deCiências Biológicas (ICB), Programa de Pós-Graduação em MedicinaTropical e Saúde Pública, Goiânia, 2018. Anexos. Inclui siglas, símbolos, lista de figuras.
1. Paracoccidioides spp. 2. proteoma. 3. metabolismo. 4.macrófagos. 5. interferon gama. I. Soares, Célia Maria de Almeida,orient. II. Título.
III
Dedico este trabalho à minha querida mãe!
Sua fé me inspira, sua oração me sustenta, seu amor me enobrece!
IV
AGRADECIMENTOS
Mais uma etapa se finda! É com muita alegria que deixo aqui minhas palavras!
Professora Célia, minha orientadora desde o mestrado, obrigada por todas as
experiências proporcionadas ao longo destes sete anos. Os desafios, as críticas, as
exigências, foram necessárias para me moldar como profissional. Seu lado humano,
aconselhador e otimista me ensinou a ser mais forte! À senhora, minha admiração e votos
de felicidade e sucesso!
Aos meus queridos colegas de laboratório, minha saudade e minha gratidão por todos os
momentos, congressos, experimentos e almoços partilhados! Karla, Nojosa, Igor, Marta,
Vanessa, Juliana, Marielle, André, Luiz, Kassyo, Lana, Santiago, Danielle, Lilian... são
muitos e todos especiais, mas vocês ficaram marcados! Obrigada pelo ombro amigo (eu
precisei), por me ouvirem e principalmente por trazerem felicidade e coragem aos meus
dias! Desejo a vocês muita determinação e que colham os frutos que ela traz!
Minha enorme gratidão aos meus colegas de bancada, que madrugaram, sofreram e
comemoram comigo toda a saga dos mutantes, da cinética de infecção e a tensão na reta
final! Amanda, Lucas Nojosa, Danielle, Karla, Vanessa e Lilian vocês foram essenciais!
Agradeço o apoio dos professores Alexandre Bailão, Clayton Borges e Juliana Parente
que desde meus primeiros dias foram mais próximos, acessíveis e de uma inteligência
fascinante! Deixo meu agradecimento também à Simone Weber, minha eterna co-
orientadora que me pegou para criar e nunca mais largou, rendendo mais e mais
colaborações, você é um exemplo para mim!
Aos funcionários da Secretaria de Pós-graduação, Zezinho e Kariny, parabéns pela
competência e obrigada por todo o auxílio e ajuda prestados! Nota dez!
Agradeço também aos membros da banca examinadora, professor Milton Oliveira e
professor Juliano Paccez pela presença e contribuições a este trabalho!
Agradeço aos órgãos de fomento CAPES, CNPq e FAPEG pelo apoio financeiro.
Agradeço à Universidade Federal de Goiás, onde habito desde a graduação e vivi 11 anos
de muito aprendizado! Agradeço também ao Instituto de Patologia Tropical e Saúde
Pública pela excelência na formação de seus alunos! É uma honra ter sido aprendiz desse
instituto!
Gratidão!
V
SUMÁRIO
FIGURAS E ANEXOS ....................................................................................................... VI
SÍMBOLOS, SIGLAS E ABREVIATURAS ..................................................................... VII
RESUMO ............................................................................................................................ IX
ABSTRACT ......................................................................................................................... X
1. INTRODUÇÃO ........................................................................................................... 11
1.1. O gênero Paracoccidioides ................................................................................... 11
1.2. A Paracoccidioidomicose...................................................................................... 12
1.3. Interação de Paracoccidioides spp. com células do hospedeiro: estratégias de
evasão ...............................................................................................................................15
1.4. O ambiente intracelular: fagossomo ..................................................................... 21
1.5. Adaptações metabólicas e secreção de fatores de virulência de Paracoccidioides
spp. durante infecção de macrófagos ............................................................................... 23
2. JUSTIFICATIVA ......................................................................................................... 31
3. OBJETIVOS............................................................................................................... 32
3.1. Objetivos gerais .................................................................................................... 32
3.2. Objetivos específicos ............................................................................................ 32
4. RESULTADOS ............................................................................................................ 33
5. DISCUSSÃO .............................................................................................................. 114
6. CONCLUSÕES .......................................................................................................... 119
REFERÊNCIAS ................................................................................................................ 120
ANEXOS ........................................................................................................................... 135
VI
FIGURAS E ANEXOS
Figura 1. Interação de fungos com macrófagos...................................................................17
Figura 2. Mecanismos antimicrobianos de fagócitos...........................................................23
Figura 3. Resposta metabólica adaptativa de P. brasiliensis após infecção em camundongos..........24
Figura 4. Visão geral dos mecanismos de desintoxicação contra o estresse oxidativo em
P.brasiliensis durante a infecção pulmonar..........................................................................27
Anexos – Produtos do período ...........................................................................................135
VII
SÍMBOLOS, SIGLAS E ABREVIATURAS
% - porcentagem
°C – graus Celsius
CatA – catalase A
CatB – catalase B
CatP – catalase P
CCP – citocromo C peroxidase
CLR – receptores tipo C
Cu – cobre
DNA – ácido desoxirribonucleico
EBP – proteína ligante de estradiol
Fe – ferro
GAPDH – gliceraldeído-3-fosfato desidrogenase
GR – glutationa redutase
GP43 – glicoproteína de 43 quilodaltons
GPX - glutationa peroxidase
H2O2 – peróxido de hidrogênio
HOCl - ácido hipocloroso
IL - interleucina
INF- − interferon gama
iNOS - óxido nítrico sintase induzida
kDa - quilodaltons
MHC-II – principal complexo de histocompatibilidade 2
MEC – matriz extracelular
mL – mililitros
NanoUPLC-MSE – Cromatografia líquida ultra alta performance acoplada à espectrometria
de massa
NO – óxido nítrico
O2- • - radicais superóxido
ONOO- - peroxinitrito
PAMP – padrão molecular associado ao patógeno
VIII
PCM – paracoccidioidemicose
PRR - receptores de reconhecimento padrão
PS2 - espécie filogenética 2
PS3 – espécie filogenética 3
PS4 – espécie filogenética 4
RNA – ácido ribonucleico
RNS - espécies reativas de nitrogênio
ROS - espécies reativas de oxigênio
spp. - várias espécies
S1a – espécie filogenética 1 subgrupo a
S1b – espécie filogenética 1 subgrupo b
SOD - superóxido dismutase
Th1 – do inglês “T helper” tipo 1
Th2 – do inglês “T helper” tipo 2
TNF- – fator de necrose tumoral alfa
TPI - triosefosfato isomerase
TLR – receptores tipo “toll”
Trx – tioredoxina
TrxR - tioredoxina redutase
UFC – unidade formadora de colônia
IX
RESUMO
Análise proteômica de Paracoccidioides spp. durante interação com macrófagos: adaptação
metabólica e fatores de virulência
Paracoccidioides spp., apesar de não ser um patógeno exclusivamente intracelular,
possui a capacidade de multiplicar no interior de fagócitos e células epiteliais de mamíferos,
subvertendo as defesas fagocíticas para disseminar-se pelos tecidos. Macrófagos ativados
são capazes de eliminar micro-organismos invasores através da produção de espécies
reativas de oxigênio e nitrogênio. Para sobreviver ao ambiente intracelular,
Paracoccidioides é capaz de remodelar seu metabolismo e aumentar a produção de
moléculas responsivas aos estresses, incluindo um sistema antioxidante. Além disso, tem
sido descrito diversas adesinas de superfície e proteínas secretadas que interagem com
componentes do hospedeiro e favorecem a adesão e o parasitismo celular. Através da
tecnologia NanoUPLC-MSE, analisamos a resposta proteômica de P. brasiliensis, Pb18
durante a infecção de macrófagos alveolares ativados e não ativados por interferon gama.
Enquanto macrófagos ativados apresentaram atividade fungicida após nove horas de
interação com o fungo, em macrófagos não ativados P. brasiliensis apresentou maior índice
de sobrevivência e rápida adaptação metabólica. Foram observadas particularidades na
resposta proteômica do fungo entre as condições analisadas, como a ativação de vias
alternativas de consumo de carbono (via das pentoses-fosfato e ciclo do metil citrato), síntese
de componentes da parede celular e maior atividade mitocondrial apenas nas células fúngicas
recuperadas de macrófagos não ativados. Em as ambas condições analisadas, houve aumento
na expressão de proteínas de resposta estresse oxidativo, choque térmico e proteínas
descritas como fatores de virulência. Porém, uma maior abundância dessas proteínas de
defesas foi detectada em fungos recuperados de macrófagos não ativados. Esses dados
indicam que macrófagos não ativados são passíveis à adaptação e sobrevivência de P.
brasiliensis, podendo servir como meio de escape ao sistema imunológico e disseminação
pelos tecidos do hospedeiro. A identificação de moléculas chaves para o estabelecimento da
infecção, nos ajuda a compreender a natureza da relação parasito-hospedeiro.
Palavras-chaves: Paracoccicioides spp., proteoma, metabolismo, macrófagos,
interferon gama
X
ABSTRACT
Proteomic analysis of Paracoccidioides spp. during interaction with macrophages:
metabolic adaptation and virulence factors
Paracoccidioides spp., although not exclusively a intracellular pathogen, has the
ability to multiply inside phagocytes and epithelial cells of mammals, subverting the host
phagocytic defenses to spread through the tissues. Activated macrophages are able to
eliminate invading microorganisms through the production of reactive oxygen and nitrogen
species. To survive the intracellular environment, Paracoccidioides is able to reshape its
metabolism and increase the production of molecules responsive to stress, including an
antioxidant system. In addition, various surface adhesins and secreted proteins have been
described that interact with host components and favor cell adhesion and parasitism.
Through the NanoUPLC-MSE technology, we analyzed the proteomic response of P.
brasiliensis, Pb18 during the infection of alveolar macrophages activated and not activated
by interferon gamma. While activated macrophages showed fungicidal activity after nine
hours of interaction with the fungus, in non-activated macrophages P.brasiliensis had a
higher survival rate and a rapid metabolic adaptation. Particularities were observed in the
proteomic response of the fungus between the conditions analyzed, such as the activation of
alternative pathways of carbon consumption (pentoses-phosphate pathway and methyl
citrate cycle), synthesis of cell wall components and increased mitochondrial activity only
in fungal cells recovered from non-activated macrophages. In both analyzed conditions,
there was increase in protein expression of oxidative stress response, thermal shock and
proteins described as virulence factors. However, a greater abundance of these defensive
proteins was detected in fungi recovered from non-activated macrophages. These data
indicate that nonactivated macrophages are susceptible to the adaptation and survival of P.
brasiliensis, which can serve as a means of escape to the immune system and dissemination
through host tissues. The identification of key molecules for the establishment of infection
helps us to understand the nature of the parasite-host relationship.
Key words: Paracoccicioides spp., proteome, metabolism, macrophages, interferon
gamma
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1. INTRODUÇÃO
1.1. O gênero Paracoccidioides
O gênero Paracoccidioides pertence ao filo Ascomycota, classe Euromycetes,
ordem Onygenales, família Ajellomycetaceae. Membros dessa família possuem a
característica de serem sapróbicos (UNTEREINER et al., 2004). O fungo foi descrito pela
primeira vez em 1908 por Adolf Lutz, com denominação diferente (Zymonema
brasiliensis) e ainda classificado como uma espécie única (LUTZ, 1945). Recentemente,
após análises moleculares e morfológicas de diferentes isolados, foi proposto que o
gênero abrange cinco espécies filogenéticas: Paracoccidioides brasiliensis, que
compreende um complexo de cinco grupos (S1a, S1b, PS2, PS3 e PS4), Paracoccidioides
americana, Paracoccidioides restrepiensis, Paracoccidioides venezuelensis e
Paracoccidioides lutzii, que inclui o isolado Pb01-like (CARRERO et al., 2008;
MATUTE, 2006; MUÑOZ et al., 2016; TEIXEIRA et al., 2009; TURISSINI et al., 2017).
As diferenças entre as espécies vão desde características evolucionárias, como o tamanho
do genoma e seu conteúdo, morfologia dos conídios até às distribuições geográficas. P.
lutzii é encontrado em algumas regiões do Brasil (central, sudoeste e noroeste) e Equador.
P. brasiliensis é amplamente distribuído pela América latina e tem sido associada à
maioria dos casos registrados de PCM. Membros do grupo PS2 só foram identificados no
Brasil e na Venezuela, PS3 somente na Colômbia e PS4 parece ter sido recuperado da
Venezuela. No entanto, ainda há muitas incertezas quanto à localização exata dos
isolados, uma vez que muitos fatores, como o período de latência, migração dos
hospedeiros e falta de notificação compulsória interferem nas investigações (BOCCA et
al., 2013).
Paracoccidioides spp. é um fungo termodimórfico que pode ser encontrado na
forma de micélio ou levedura, de acordo com a temperatura (BRUMMER et al., 1993).
Em temperaturas inferiores a 28 °C, como pode ocorrer em solos, o fungo é encontrado
na forma miceliana. Acredita-se que os micélios sejam uma forma sapróbica do fungo,
alimentando-se de matéria orgânica em decomposição. Essa é caracterizada por hifas
septadas e multinucleadas produtoras de conídios infecciosos (TERÇARIOLI et al.,
2007). Os conídios podem ser inalados e alcançar os pulmões do hospedeiro, onde
encontram certas condições que induzem a sua diferenciação em levedura, como por
12
exemplo, a temperatura de 36 °C (SAN-BLAS; NIÑO-VEGA; ITURRIAGA, 2002). A
fase leveduriforme, forma parasitária do fungo, apresenta múltiplos brotamentos
formados por evaginações da célula-mãe, conferindo uma de suas principais
características microscópicas, o aspecto de roda de leme de navio. A capacidade de
transição é considerada um fator determinante na virulência da cepa, uma vez que
somente isolados capazes de transitar da fase miceliana para a fase leveduriforme
conseguem estabelecer a infecção (SAN-BLAS; NIÑO-VEGA; ITURRIAGA, 2002).
1.2. A Paracoccidioidomicose
Fungos do gênero Paracoccidioides são os agentes etiológicos da
paracoccidioidomicose (PCM), uma micose granulomatosa sistêmica. Dada a inalação de
conídios infectantes e a transição para levedura, a apresentação e o curso da doença
podem variar. O paciente infectado pode ou não apresentar sinais e sintomas (SEVERO
et al., 1979). A doença apresenta-se sob duas principais formas clínicas: aguda ou
subaguda (PCM juvenil) e crônica (PCM adulta) (FRANCO, 1987; SAN-BLAS, 1993).
A forma aguda ou subaguda representa cerca de 5% dos casos. É a forma mais grave da
doença e atinge principalmente indivíduos jovens, afetando igualmente ambos os sexos.
Nestes casos, a infecção progride rapidamente com disseminação linfática e/ou
hematogênica do pulmão para outros órgãos como fígado, baço, linfonodos e medula
óssea. O paciente pode apresentar disfunção da medula óssea, manifestações digestivas,
hepatoesplenomegalia e lesões cutâneas, depressão da imunidade celular, o que torna a
PCM aguda potencialmente letal (VICENTINI et al., 1994). A forma crônica da PCM é
a mais comum na prática clínica e ocorre após um longo período de latência do fungo. A
infecção pode ocorrer durante a infância e apresentar sinais e sintomas da doença somente
quando o paciente atinge a idade adulta. Nesta fase, ocorre uma infecção sistêmica
granulomatosa de progressão lenta com comprometimento pulmonar e tegumentar (pele
e mucosas). A doença atinge primeiramente os pulmões, provocando tosse, dificuldade
respiratória e lesões na região orofaríngea (BOCCA et al., 2013; BRUMMER et al., 1993;
MARQUES, 2013; SHIKANAI-YASUDA et al., 2006). As lesões apresentam-se como
úlceras pouco profundas de superfície granular, com múltiplos pontos hemorrágicos com
pápulas. É possível que ocorra a reativação de um foco quiescente pulmonar e a partir
dali o fungo pode provocar lesões localizadas ou disseminar-se para outros órgãos e
13
tecido. Com isso, a PCM pode ser subclassificada como unifocal ou multifocal, de acordo
com a quantidade de órgãos afetados (SEVERO et al., 1979). Frequentemente nódulos
linfáticos e glândulas adrenais estão envolvidos. O intestino, ossos, baço, olhos, os
sistemas genitourinário, cardiovascular e nervoso central também podem ser afetados, em
menor frequência. O comprometimento do SNC pode ocasionar epilepsias, lesões
expansivas e sinais e sintomas cerebelares (BOCCA et al., 2013; MARQUES, 2013;
REIS et al., 2013). Esses dados revelam que a forma crônica, apesar de apresentar uma
progressão mais lenta, pode ser fatal devido às inúmeras sequelas que comprometem
funções vitais.
Um rápido diagnóstico e aplicação do tratamento com antifúngicos apresentam
grande eficiência no combate à infecção. Porém, os problemas começam já na
identificação da micose, que muitas vezes é confundida com outra doença granulomatosa
de envolvimento pulmonar, a tuberculose. Sendo assim, é necessário um diagnóstico
diferencial, que pode ser realizado através de radiografia de tórax e achados do fungo em
espécimes clínicos como escarro, raspado de lesão, aspirado de linfonodos ou biópsia de
tecidos. Outras doenças também devem ser consideradas no diagnóstico diferencial da
PCM, como a histoplasmose, pneumoconiose, criptococose e coccidioidomicose
(MARQUES, 2013; SHIKANAI-YASUDA et al., 2006). Testes sorológicos e técnicas
de biologia molecular têm sido de grande importância, pois possuem alta afinidade e
sensibilidade no diagnóstico. Além disso, podem servir como acompanhamento do
quadro clínico do paciente e evolução do tratamento (BERTONI et al., 2012; PERENHA-
VIANA et al., 2012; ZANCOPE-OLIVEIRA et al., 2014). O tratamento da PCM é
mediado pelo uso prolongado de antifúngicos. Há uma variedade de opções disponíveis
como azóis (ketoconazol, itraconazol, fluconazol, voriconazol e posaconazol), derivados
de sulfonas (suladiazina, sulfadoxina, sulfametoxipiridazina, cotrimazina e trimetoprim-
sulfametoxazol), anfotericina B e terbinafina. A escolha do fármaco é feita de acordo com
a gravidade da doença e pode durar até 2 anos de uso contínuo, o que pode ser mais um
problema devido o não cumprimento do tratamento, resultando em uma alta frequência
de recidivas (BOCCA et al., 2013). Recentemente, tem sido proposto a terapia combinada
de itraconazol e pentoxifilina. A combinação resultou em uma rápida redução da
inflamação granulomatosa e da fibrose pulmonar (NARANJO et al., 2011). Também sido
investigada uma estratégia de tratamento com vacinas de DNA. Vacinas produzidas a
partir de antígenos fúngicos, peptídeos ou fragmentos de DNA podem ser úteis na
14
proteção e no combate à PCM, principalmente de indivíduos imunocomprometidos (DE
BASTOS ASCENÇO SOARES et al., 2008; TRAVASSOS et al., 2008; RIBEIRO et al.,
2009). A expectativa é que a vacina aumente a resposta imune celular dos pacientes e isso
foi testado experimentalmente em camundongos. Os resultados mostraram a formação de
granulomas menores, mas não menos eficientes, diminuição da carga fúngica e da
formação de fibrose (RIBEIRO et al., 2009, 2013). Imunoterapia com vacinas de DNA e
peptídeos da glicoproteína antigênica gp43 geraram uma resposta imune celular e
humoral Th1 / Th2 específica e duradoura contra a PCM, aumentando os nível de IFN-γ
e de IL-12 e eliminando completamente o fungo (PINTO et al., 2000; RITTNER et al.,
2012). Apesar dos avanços, essas estratégicas requerem maiores investigações e testes
clínicos.
A PCM é uma doença predominante em regiões tropicais e subtropicais,
geograficamente restrita à América do Sul. Dados apontam uma distribuição que se
estende desde o México até a Argentina, com maior incidência na Colômbia, Venezuela
e principalmente Brasil (SAN-BLAS; NIÑO-VEGA; ITURRIAGA, 2002; SHIKANAI-
YASUDA et al., 2006). Alguns casos importados já foram notificados nos EUA, África
e Europa, porém os números não se comparam aos mais de 15.000 casos relatados da
paracoccidioidomicose entre os anos de 1930 e 2012, na América latina. No Brasil, entre
os anos de 1996 a 2006, a doença foi classificada como a décima causa de mortalidade
entre as doenças infecciosas e parasitárias e a primeira entre as micoses sistêmicas
(MARTINEZ, 2015; PRADO et al., 2009). A incidência varia de um a quatro novos casos
/ 100.000 habitantes / ano de paracoccidioidomicose. Apesar da doença não ser de
notificação compulsória, é possível determinar que a maior incidência da PCM se
concentra em cidades dos estados de São Paulo e Rio de Janeiro (MARTINEZ, 2015).
A grande maioria dos casos de PCM crônica é oriunda da população rural.
Acredita-se que o fungo na sua forma miceliana seja sapróbico e que, sob certas
condições, produza conídios infectantes. Os conídios podem espalhar-se pelo solo, água
e plantas e este pode ser o motivo da maior frequência de casos da PCM em pessoas que
têm maior contato com o solo (RESTREPO; MCEWEN; CASTAÑEDA, 2001). Outros
elementos também poderiam justificar a maior incidência nesta população, dentre eles o
consumo abusivo de álcool, tabagismo, desnutrição e a falta de cuidados higiênicos
(MARQUES et al., 2007). Esses hábitos interferem nos mecanismos de defesa do
hospedeiro e influenciam na evolução do estado de infecção para doença. Estudos
15
observaram que pacientes que consumiam diariamente álcool etílico (acima de 100 mL),
apresentavam maior recorrência da PCM durante ou após a terapia antifúngica. Assim, o
alcoolismo também tem sido considerado um fator que predispõe à
paracoccidioidomicose e representa o pior prognóstico da infecção (MARTINEZ;
MOYA, 1992).
Há ainda uma maior predominância de homens afetados pela PCM, numa
proporção de 10 a 25 homens para cada mulher (BOCCA et al., 2013). A baixa incidência
da doença em mulheres está relacionada à ação protetora do hormônio feminino β-
estradiol que inibe a transição do fungo para fase leveduriforme e assim o patógeno não
consegue estabelecer a infecção (RESTREPO; JIMÉNEZ, 1980; SAN-BLAS; NIÑO-
VEGA; ITURRIAGA, 2002; SHANKAR et al., 2011a, 2011b). Paracoccidioides spp.
codifica uma proteína de ligação ao estradiol, a EBP (Estradiol Binding Protein), a qual
é expressa preferencialmente durante a fase leveduriforme (FELIPE, 2005; LOOSE et al.,
1983). Foi observada a participação do hormônio β-estradiol na proteção de fêmeas de
camundongos contra a evolução da doença (ARISTIZÁBAL et al., 2002). Um estudo
revelou ainda, que macrófagos oriundos de fêmeas de camundongos apresentam maior
produção óxido nítrico e de citocinas como IL-12, IFN-γ e TNF-α, em comparação com
células de camundongos machos, portanto, podem ser mais eficientes no combate aos
invasores patogênicos (PINZAN et al., 2010). Esses dados indicam que tanto os fatores
imunológicos como os fatores hormonais do hospedeiro são determinantes na evolução
da PCM (FORTES et al., 2011).
1.3. Interação de Paracoccidioides spp. com células do hospedeiro: estratégias de
evasão
Atualmente, sabe-se que os macrófagos são um dos principais mecanismos de
defesa contra a infecção causada por Paracoccidioides (KASHINO et al., 1995). Mas
para McEwen e colaboradores em 1987, isso ainda era um mistério. Os pesquisadores
então desenvolveram um dos trabalhos pioneiros na avaliação dos eventos iniciais da
PCM. Aparentemente, o objetivo do grupo era demonstrar que a forma infectante do
fungo eram os conídios e acabaram descrevendo toda a ação das células de defesa. Após
infecção por inalação de conídios, foram realizadas análises histopatológicas e cultura de
órgãos. Os resultados mostram que na primeira hora de infecção ocorreu o alojamento
16
dos conídios no tecido pulmonar e sua distribuição pelos bronquíolos terminais e
alvéolos. Após 6 h, já era possível detectar a presença de linfócitos e leucócitos
polimorfonucleares indicando uma resposta inflamatória, com focos broncopneumônicos
em torno dos esporos inalados. No tempo de 12 h, foi observado que os conídios
começaram a diferenciação em levedura e que algumas células possuíam brotos,
sinalizando a multiplicação celular. O organismo hospedeiro, por sua vez, intensificou a
resposta imunológica recrutando mais plasmócitos e macrófagos a fim de combater as
células fúngicas. Com 18 h de infecção, os focos broncopneumônicos adquiriram um
aspecto nodular, exibindo um infiltrado celular denso composto de células inflamatórias
e leveduras. Após 6 dias, foi evidente a formação de granulomas nos pulmões. Com 20
semanas, observou-se a disseminação do fungo para órgãos envolvidos secundariamente
(baço, fígado, linfonodos), os quais apresentaram inúmeros granulomas. Ao final da
infecção, foram detectadas células gigantes multinucleadas, formadas pela fusão de
macrófagos, fenômeno característico de doenças granulomatosas, na tentativa de
bloquear e restringir o fungo, impedindo sua multiplicação e disseminação pelos tecidos
(MCEWEN et al., 1987). Ali estavam os primeiros relatos do papel primordial das células
fagocíticas na defesa contra a PCM.
Ao longo dos anos, outros trabalhos complementaram e esclareceram a dinâmica
entre Paracoccidioides e células do hospedeiro. Nos pulmões, as primeiras medidas
protetivas incluem a secreção de substâncias antimicrobianas pelo epitélio pulmonar e a
atividade fagocítica dos macrófagos alveolares residentes (CALICH et al., 2008;
MARTIN, 2005). A interação inicial com macrófagos pode resultar na internalização do
patógeno ou na formação de contenções extracelulares, os granulomas. Enquanto isso,
ocorre a liberação de quimiocinas e citocinas que recrutam mais monócitos, neutrófilos e
células dendríticas para o local de infecção. Essas células expressam receptores capazes
de reconhecer, ligar e desencadear a fagocitose de Paracoccidioides (ALVES et al., 2009;
CALICH et al., 2008). Este reconhecimento se dá através de receptores de
reconhecimento padrão (PRR) de fagócitos, principalmente do tipo “toll-like receptors”
(TLR) e do tipo “C-like receptors” (CLR). Esses receptores interagem com estruturas
conservadas presentes na superfície de micro-organismos, os chamados padrões
moleculares associados a patógenos (PAMP), como -glucana, quitina e manoproteínas
(JANEWAY, 1992; ROMANI, 2004).
Após o reconhecimento iniciam-se cascatas de sinalização nos fagócitos,
resultando na internalização do fungo, secreção de compostos microbicidas e produção
17
de mediadores pró-inflamatórios. Entretanto, a eficiência do reconhecimento e posterior
internalização de fungos depende do tamanho, forma e composição da membrana ou
parece celular, além dos mecanismos de evasão do patógeno (SEIDER et al., 2010). A
variação desses parâmetros pode levar à inibição da fagocitose ou a três destinos: morte
do patógeno, expulsão não lítica ou escape através da lise do fagócito como mostrado na
Figura 1 (ERWIG; GOW, 2016).
Figura 1. Interação de fungos com macrófagos. Reconhecimento, fagocitose e possíveis
destinos de fungos internalizados por macrófagos. Fonte: Adaptado de ERWIG, GOW, 2016.
Evitar a detecção dos carboidratos presentes na superfície pode ser considerada
a estratégia de evasão imune mais simples, porém não é uma tarefa fácil, uma vez que a
resistência ao ambiente intracelular é favorecida pela estabilidade da parede celular
(BERNARD; LATGÉ, 2001; DAVIS; DOMER; LI, 1977; EISSENBERG; MOSER;
GOLDMAN, 1997). Alguns fungos são capazes de proteger moléculas
imunomoduladores como -glucana do reconhecimento de macrófagos. Em Candida
albicans, foi observado uma espécie de “casaco” de manoproteínas sobre -glucana a fim
de diminuir a ativação da resposta imune (MCKENZIE et al., 2010). Histoplasma
18
capsulatum e Paracoccidioides, durante a fase parasitária como levedura, remodelam a
parede celular induzindo a produção de α-glucana, o que contribui para latência do fungo
(BORGES-WALMSLEY et al., 2002; RAPPLEYE; EISSENBERG; GOLDMAN, 2007).
Proteínas do sistema do complemento também tem sido alvo estratégico de invasores.
Esse sistema é composto por proteínas que participam da defesa imunológica,
opsonizando os micro-organismos invasores e desencadeando uma resposta inflamatória.
Fungos patogênicos produzem moléculas que interagem com fatores de regulação do
sistema complemento, bloqueando a ação dos mesmos e reduzindo a eficiência da
resposta imunológica (LUO et al., 2009; STANO et al., 2009). Paracoccidioides utiliza
seu principal componente antigênico gp43, para regular negativamente a ativação células
dendríticas. Apesar de apresentar função microbicida, essas células são aprimoradas para
a apresentação de antígenos e posterior ativação da resposta imune adaptativa. O fungo
foi capaz reduzir a capacidade de fagocitose, a produção de citocinas como IL-12 e TNF-
e inibiu a regulação do complexo principal de histocompatibilidade (MHC-II), o que
desestabiliza a eficiência da resposta imune (FERREIRA; LOPES; ALMEIDA, 2004).
Porém, quando essas estratégias falham e ocorre a fagocitose, é necessário outros
mecanismos de sobrevivência ou escape intracelular. As principais manobras observadas
envolvem a inibição do processo de maturação do fagolisossomo, lise da célula
hospedeira, eliminação de compostos desintoxicantes e adaptação metabólica (SEIDER
et al., 2014). Fungos como C. albicans, Aspergillus fumigatus, Coccidioides immitis,
espécies de Crytopococcus, são capazes de produzir hifas, pseudohifas, grandes esporos
ou células “titans”, que atingem um tamanho maior do que o macrófago consegue
comportar, provocando rupturas na membrana da célula hospedeira (INGHAM;
SCHNEEBERGER, 2012; LEWIS et al., 2012; ZARAGOZA; NIELSEN, 2013).
Também tem sido descrito um mecanismo de evasão do fagossomo por vias não líticas,
envolvendo uma remodelação das moléculas de actina de macrófagos. Ainda não está
claro como e porque este evento acontece, nem os reais beneficiados, uma vez que
patógeno e fagócito saem ilesos. Este processo que foi observado pela primeira vez em
Cryptococcus neoformans, foi descrito em algumas espécies de Candida, porém não há
registros em Paracoccidioides spp. (ALVAREZ; CASADEVALL, 2006; BAIN et al.,
2012; GARCÍA-RODAS et al., 2011; NICOLA et al., 2011).
Estudos mostram que fungos também são capazes de lidar com as adversidades
intracelulares manipulando estruturas do fagossomo. Durante ensaios de infecção celular,
19
C. neoformans provocou a formação de poro na membrana do fagossomo, o que permite
acesso aos nutrientes citoplasmáticos (TUCKER; CASADEVALL, 2002). Fatores como
esse favorecem a sobrevivência e multiplicação desses micro-organismos no interior de
macrófagos. Apesar de Paracoccidioides não ser um patógeno predominantemente
intracelular, há registros de sua capacidade de invadir e parasitar células dendríticas,
neutrófilos, macrófagos e células epiteliais de mamíferos (BRITO; CASTRO, 1973;
BRUMMER et al., 1989; MENDES-GIANNINI et al., 2008). Os mecanismos de
aderência e invasão celulares têm sido descritos em diversos fungos patogênicos
(KASPER; SEIDER; HUBE, 2015b; SEIDER et al., 2010). O processo de invasão celular
está intensamente relacionado com a capacidade do fungo interagir com moléculas do
hospedeiro, como plasminogênio e componentes da matriz extracelular (MEC) que
circundam os tecidos (BAILÃO et al., 2012; CHAVES et al., 2015; GONZALEZ et al.,
2005; GONZÁLEZ et al., 2008). Diversas proteínas de Paracoccidioides têm sido
descritas como adesinas que medeiam a invasão de células do hospedeiro. Dentre elas
podemos destacar a enolase (DONOFRIO et al., 2009; NOGUEIRA et al., 2010), gp43
(MENDES-GIANNINI et al., 2004), proteína 14-3-3 (30 kDa) (ANDREOTTI et al.,
2005), gliceraldeído-3-fosfato desidrogenase (GAPDH) (BARBOSA et al., 2006),
triosefosfato isomerase (TPI) (PEREIRA et al., 2007), malato sintase (DA SILVA NETO
et al., 2009). Tem sido proposto que fungos patogênicos podem induzir a sua fagocitose
através de suas proteínas de superfície e secretadas, utilizando a célula imune como um
"cavalo de Tróia" para sua disseminação dentro do hospedeiro (GEUNES-BOYER et al.,
2009). Ao favorecer o parasitismo intracelular, essas adesinas não auxiliam apenas na
sobrevivência do fungo, mas também podem contribuir para períodos prolongados de
latência.
As células epiteliais representam uma barreira física do hospedeiro contra a
penetração e disseminação de patógenos. Paracoccidioides é capaz de penetrar na
superfície mucocutânea e parasitar as células epiteliais (BRITO; CASTRO, 1973). Testes
in vitro mostram que após invadir células Vero, HeLa e células do epitélio alveolar A549,
o fungo é capaz de multiplicar-se, provocar alterações no citoesqueleto da célula
hospedeira e posteriormente induzir o processo de apoptose das mesmas. Essas células
não apresentam atividade microbicida, o que as torna um potente meio de disseminação
fúngica (HANNA; MONTEIRO DA SILVA; GIANNINI, 2000; MENDES-GIANNINI
et al., 2004, 2008). Os neutrófilos também se encontram presentes em grande quantidade
20
nos tecidos infectados e, quando não ativados, podem ser hospedeiras de
Paracoccidioides. Ainda assim, quando são previamente ativadas e incubadas na
presença do fungo, essas células produzem altos níveis de IL-8. Neutrófilos têm uma vida
curta, de aproximadamente 6 h, porém a produção dessa citocina pode desencadear um
processo antiapoptótico dos neutrófilos e favorecer a multiplicação e sobrevivência do
fungo durante a infecção (ACORCI et al., 2009; RODRIGUES et al., 2007).
Em contato com macrófagos não ativados, o fungo também apresentou um
potencial de adesão e multiplicação celular. Em 1989, Brummer e colaboradores
descreveram: “Esta é a primeira demonstração de que Paracoccidioides pode crescer
intracelularmente e esse novo achado tem implicações relevantes para a patogênese”. Eles
observaram que em longo prazo, macrófagos peritoneais e pulmonares, não apenas
permitem, mas estimulam a multiplicação do fungo. O número de células fúngicas
aumentou significativamente após interação, diferente do observado em ensaios
utilizando apenas meio de cultura. Além disso, o fungo foi cultivado na presença de
secretoma de macrófagos e alcançou uma taxa de sobrevivência maior em comparação
ao fungo cultivado em meio de cultura. Esta habilidade parece ser exclusiva de fagócitos,
pois a mesma não foi observada em co-cultura com linfócitos (BRUMMER et al., 1989).
Entretanto, vale ressaltar que em contato com macrófagos e neutrófilos ativados, o fungo
foi eliminado logo nas primeiras horas de interação. A adição de interfeton gama não
aumenta o índice de fagocitose, porém confere atividade microbicida aos macrófagos de
forma dose-dependente; é o que indicam estudos realizados com vários isolados de
Paracoccidioides (BRUMMER et al., 1988; BRUMMER; HANSON; STEVENS, 1988).
A morfologia do fungo também apresentou diferenças após internalização por
macrófagos peritoneais ativados e não ativados. Logo após as primeiras 4 h de interação
em macrófagos ativados foi possível observar desgastes na parede do fungo até sua
completa digestão e eliminação, enquanto houve surgimento de brotos nas células
internalizadas por macrófagos não ativados (BRUMMER et al., 1990).
Esses dados reforçam o papel crucial dos macrófagos e a importância da ativação
da resposta imunológica na resistência à Paracoccidioides. Este fato também tem sido
observado na clínica, onde deficiências no sistema imunológico, relacionadas à baixa
produção de citocinas, foram associadas à evolução da PCM. Estudos revelaram que a
produção de IL-2 e INF-γ por células mononucleares de sangue periférico de pacientes
afetados por PCM aguda ou crônica foi menor em comparação com pacientes saudáveis
21
(BENARD et al., 2001). INF-γ também desempenha um papel importante no
recrutamento de células de defesa para os pulmões e na eficiência de granulomas
(SOUTO et al., 2003). Grandes quantidades dessa citocina foram detectadas em
granulomas compactos de rato resistentes à PCM, diferente do que foi observado em
granulomas frouxos e em lesões multifocais detectadas em animais suscetíveis
(NISHIKAKU et al., 2011).
Em resumo, a sobrevivência de Paracoccidioides no ambiente intracelular pode
conferir proteção contra a resposta imunológica adaptativa do hospedeiro. Assim, o fungo
parece subverter as defesas fagocíticas do sistema imunológico e utilizá-las como
estratégia de escape. Por outro lado, fagócitos ativados são exímios microbicidas com os
quais o fungo deve lidar para estabelecer a infecção e atravessar barreiras teciduais. As
dificuldades impostas no interior de macrófagos ativados e as demais estratégias de
sobrevivência de Paracoccidioides serão discutidas adiante.
1.4. O ambiente intracelular: fagossomo
Como vimos, a fagocitose pode ser considerada uma oportunidade ou um
obstáculo para os agentes patogênicos. O potencial microbicida de fagócitos ativados é
um desafio que requer dos micro-organismos invasores estratégias evoluídas para
sobrevivência intracelular. Após o reconhecimento, os agentes patogênicos são
confinados dentro dos fagossomos, que são vacúolos derivados da invaginação da
membrana celular, contendo o material ingerido. Essas estruturas sofrem acidificação
progressiva do lúmen e uma remodelação extensa de membrana até chegar ao seu
amadurecimento. Através da fusão de membranas e eventos de fissão com organelas
denominadas lisossomos, enzimas microbicidas e líticas são adicionadas ao fagossomo,
formando o fagolisossomo (FAIRN; GRINSTEIN, 2012). Não bastasse a acidez e a ação
de enzimas hidrolíticas, o fagolisossomo maduro também apresenta baixa disponibilidade
de nutrientes e alta quantidade de moléculas tóxicas reativas derivadas de oxigênio e
nitrogênio. A repressão da via glicolítica em patógenos durante a passagem intracelular
corrobora com a escassez de fontes de carbono no fagossomo (FERNÁNDEZ-ARENAS
et al., 2007; PARENTE-ROCHA et al., 2015). Além disso, macrófagos ativados com
INF- apresentam concentração diminuída de íons de ferro e de outros nutrientes
essenciais que poderiam alimentar o patógeno. A ativação por INF- também aumentou
22
a expressão de indoleamina 2,3-dioxigenase, uma enzima que catalisa a degradação de L-
triptofano em N-formilkirunenina, esgotando assim o aminoácido essencial triptofano das
células infectadas (GRIESHABER; SWANSON; HACKSTADT, 2002; WAGNER et al.,
2005).
A atividade microbicida de fagócitos também tem sido associada à explosão de
consumo de oxigênio durante a interação com patógenos, que produz grandes quantidades
de espécies tóxicas de oxigênio (FANG, 2004). A Figura 2 mostra um esquema
simplificado da geração de espécies reativas de oxigênio, do inglês “reactive oxygen
species” (ROS) e espécies reativas de nitrogênio, do inglês “reactive nitrogen species”
(RNS). Os radicais superóxido (O2- •) são gerados pela enzima NADPH oxidase de
fagócitos e podem ser convertidos em peróxido de hidrogênio (H2O2), ácido hipocloroso
(HOCl por mieloperoxidase) ou peroxinitrito (ONOO-) por interação com óxido nítrico,
formando as ROS. Esses radicais também podem impulsionar o influxo de potássio (K+)
no fagossomo e promover a liberação de proteases. O óxido nítrico (NO•), uma RNS, é
gerado pela ação da óxido nítrico sintase induzida (iNOS). O papel de ROS e RNS na
biologia está relacionado com a transdução de sinal, ativação de fagócitos, metabolismo
do ferro, proliferação celular e apoptose. O aumento da produção dessas moléculas
representa uma importante linha de defesa antimicrobiana (MISSALL; LODGE;
MCEWEN, 2004; RADA et al., 2008). Essas moléculas estressoras provocam oxidação
de proteínas, lipídios e DNA interferem na replicação dos patógenos (FERRARI et al.,
2011). Juntos, esses fatores podem sentenciar a morte do micro-organismo fagocitado
(HAAS, 2007).
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Figura 2. Mecanismos antimicrobianos de fagócitos. Esquema simplificado da geração de ROS
e RNO pela ação das enzimas NADPH oxidase de fagócitos e óxido nítrico sintase induzida
(iNOS), respectivamente, além da ação de proteases dentro do fagolisossomo. Fonte: Adaptado
de FANG, 2004.
1.5. Adaptações metabólicas e secreção de fatores de virulência por
Paracoccidioides spp. durante infecção de macrófagos
Muitos estudos têm buscado respostas sobre as estratégias de sobrevivência de
micro-organismos patogênicos durante sua permanência no hospedeiro (KASPER;
SEIDER; HUBE, 2015a, 2015b; PRICE et al., 2011; SEIDER et al., 2014). Análises
transcriptômicas e proteômicas são ricas fontes de identificação de moléculas chaves da
relação patógeno-hospedeiro, as quais têm rendido valiosas descobertas (FAN et al.,
2005a; GEDDES et al., 2015; KOMALAPRIYA et al., 2015; KUSCH et al., 2007;
SCHMIDT et al., 2018). Nosso grupo inicialmente desenvolveu estudos onde
Paracoccidioides spp. foi submetido às situações que mimetizam o ambiente intracelular,
como privação de fontes de carbono (BAEZA et al., 2017; LIMA et al., 2014) e
micronutrientes (BAILÃO et al., 2015; PARENTE et al., 2011), hipóxia (LIMA et al.,
2015) e estresses oxidativo e nitrosativo (DE ARRUDA GROSSKLAUS et al., 2013).
Também investigamos a interação direta de Paracoccidioides spp. com células e tecidos
do hospedeiro (PARENTE-ROCHA et al., 2015; PIGOSSO et al., 2017). A Figura 3 traz
24
o esquema representativo das adaptações metabólicas que o fungo utiliza para sobreviver
em situações de estresse.
Figura 3. Resposta metabólica adaptativa de P. brasiliensis após infecção em camundongos.
Esquema representativo das principais vias metabólicas de P. brasiliensis, Pb18 reguladas
positivamente após 6 h de infecção em camundongos. Fonte: Adaptado de PIGOSSO et al., 2017.
Para sobreviver e colonizar em um ambiente hostil, Paracoccidioides deve
apresentar flexibilidade metabólica para assimilar os nutrientes disponíveis e diferentes
fontes de carbono. Processos autofágicos têm sido descritos como uma maneira de
sobrevivência no hospedeiro através da degradação e reciclagem de componentes
celulares endógenos (HU et al., 2008; INOUE; KLIONSKY, 2010; ROETZER et al.,
2010). Durante infecção in vitro de macrófagos, Paracoccidioides e outros fungos
reprogramam seu metabolismo para fontes alternativas de carbono refletidas pela indução
da gliconeogênese, ciclo do glioxalato e degradação de lipídeos (FERNÁNDEZ-
ARENAS et al., 2007). Observou-se a inibição da via glicolítica e da síntese de proteínas
e ativação da degradação de aminoácidos e ácidos graxos como fontes alternativas de
energia e de intermediários necessários para alimentar vias básicas de energia como o
25
ciclo do ácido tricarboxílico (PARENTE-ROCHA et al., 2015). A resposta adaptativa de
Paracoccidioides parece estar relacionada ao estágio da infecção e ao nincho em que o
fungo se encontra. Ensaios in vivo com um tempo de 6 h de infecção em camundongos
não mostraram a regulação positiva da gliconeogênese, como observado em ensaios in
vitro de 24 h (PARENTE-ROCHA et al., 2015; PIGOSSO et al., 2017). Entretanto, esta
via tem sido descrita como uma estratégia crucial durante os primeiros passos da infecção
por fungos patogênicos. A glicólise tem uma importância posterior, sendo fundamental
para a permanência do patógeno no hospedeiro (PRICE et al., 2011).
O metabolismo de carboidratos também está associado à síntese de precursores
da parede celular. Paracoccidioides reprimiu intensamente a transcrição de genes
envolvidos neste processo durante infecção in vivo e alguns isolados foram capazes de
degradar componentes da parede celular para adquirir glicose, quando a única fonte de
carbono disponível era o acetato, uma molécula de dois carbonos presente em fagossomos
(BAEZA et al., 2017; PIGOSSO et al., 2017). Outros trabalhos porém, mostraram que
durante infecção de macrófagos não ativados, o fungo ativou enzimas que sintetizam
componentes da parede celular, o que pode ser uma estratégia de resistência importante
(TAVARES et al., 2007). C. neoformans também aumentou a expressão de genes
envolvidos na síntese de polissacarídeos durante infecção em macrófagos ativados,
podendo estar associado à formação de componentes da parede ou da cápsula (FAN et
al., 2005a).
Outra alternativa utilizada por Paracoccidioides durante privação de fontes de
carbono, é a produção de etanol. Enzimas chaves deste processo como a álcool-
desidrogenase tem relação direta com a virulência de fungos (GRAHL et al., 2011). Esta
via é suportada pela degradação de aminoácidos, -oxidação e por modulação dos ciclos
de glioxilato e tricarboxílico (BAEZA et al., 2017; LIMA et al., 2014). O ciclo do
glioxalato também é um recurso importante para sobrevivência em macrófagos. Este
processo é reprimido pela glicose e, portanto, ativo apenas em situações de privação de
nutrientes, tornando-se essencial para virulência de fungos (LORENZ; FINK, 2002).
Além disso, as enzimas do ciclo do glioxilato são alvos valiosos para o desenvolvimento
de drogas antimicrobianas, uma vez que esta via não existe em mamíferos.
Os fungos também apresentam um poderoso mecanismo antioxidante capaz de
reverter os danos causados pelos estresses oxidativo e nitrosativo. C. albicans e Candida
26
glabrata são capazes de diminuir a produção de ROS em fagócitos (WELLINGTON;
DOLAN; KRYSAN, 2009). Enzimas antioxidantes como superóxido dismutase,
tioredoxina, tioredoxina redutase, catalase e citocromo C peroxidase, estão entre as
principais responsáveis pela proteção de fungos contra as espécies reativas (Figura 4)
(CAMPOS et al., 2005; COX et al., 2003; DE ARRUDA GROSSKLAUS et al., 2013;
TILLMANN; GOW; BROWN, 2011; YOSHIDA et al., 2003).
As superóxido dismutases (SODs) são metaloproteínas classificados com base
nos metais localizados em seus sítios ativos (Fe, Mn, Ni e Cu / Zn) (GRALLA;
KOSMAN, 1992). Essas proteínas atuam na remoção de radicais superóxidos e são
essenciais para a virulência de vários fungos (COX et al., 2003; FROHNER et al., 2009;
LAMBOU et al., 2010; YOUSEFF et al., 2012). Em Paracoccidioides, a expressão de
superóxido dismutase (SOD) é aumentada durante estresse oxidativo (CAMPOS et al.,
2005; DE ARRUDA GROSSKLAUS et al., 2013). Foram identificadas seis isoformas de
SODs codificadas pelo genoma do fungo, as quais apresentam diferentes níveis de
expressão gênica entre isolados do gênero. Cepas silenciadas por RNA antisentido para
essas proteínas foram mais suscetíveis à ação de macrófagos e neutrófilos do que as
leveduras selvagens, sendo o mutante para SOD3 o menos virulento, destacando a
relevância dessa isoforma para o estabelecimento da PCM. Mutantes para SOD1 foram
capazes de infectar os pulmões mas incapaz de disseminar por outros tecidos (TAMAYO
et al., 2016).
27
Figura 4. Visão geral dos mecanismos de desintoxicação contra estresse oxidativo em P.
brasiliensis durante a infecção pulmonar. Descrição das principais reações catalisadas pelas
enzimas antioxidamtes. A NADPH oxidase de fagócito produz radicais superóxidos (O2-), os
quais são convertidos em peróxido de hidrogênio (H2O2) pela ação da superóxido dismutase
(SOD). Essa reação de desintoxicação é finalizada pelas enzimas glutationa redutase (GR) e
glutationa peroxidase (GPX), catalase P (CatP), citocromo C peroxidase (CCP) que são capazes
de decompor H2O2 em água e oxigênio. A tioredoxina redutase (TrxR) se liga ao NADPH e reduz
a tioredoxina (Trx) favorecendo, ao final da reação, o catabolismo de H2O2. Fonte: Adaptado de
PIGOSSO et al., 2017.
Em fungos, os genes CAT codificam para três catalases: CATA, CATB e CATP,
enzimas que promovem a decomposição de peróxido de hidrogênio (H2O2) em oxigênio
e água, colaborando com o sistema de detox (HOLBROOK et al., 2013). Em
Paracoccidioides, a catalase P protege as células de levedura da ação do H2O2, sendo
mais relevante para a infecção pulmonar. Enquanto CATA e CATB parecem estar
relacionadas à homeostase de ROS endógeno (TAMAYO et al., 2017).
28
A citocromo C peroxidase (CCP) é uma enzima antioxidante mitocondrial que
reduz peróxido de hidrogênio à água (KATHIRESAN; ENGLISH, 2016). Em
Paracoccidoides é super expressa durante ensaios de infecção e o silenciamento dessa
proteína revelou sua participação na sobrevivência e virulência durante infecção de
macrófagos e camundongos (PARENTE-ROCHA et al., 2015; PIGOSSO et al., 2017).
Em C. neoformans e Sacchromyces cerevisiae no entanto, a CCP1 apesar de conferir
resistência ao estresse oxidativo exógeno, não influencia na virulência dos fungos durante
infecção em camundongos (GILES; PERFECT; COX, 2005; MINARD; MCALISTER-
HENN, 2001).
A tioredoxina redutase (TrxR), que atua em conjunto com a tioredoxina (Trx),
também é importante para a viabilidade de fungos durante a infecção e encontra-se
induzida em Paracoccidioides durante situações de estresse oxidativo e ensaios de
infecção (DE ARRUDA GROSSKLAUS et al., 2013; PIGOSSO et al., 2017). A TrxR é
uma molécula de resistência antioxidante, uma vez que se liga a NADPH e reduz a
tioredoxina formando dissulfeto de tioredoxina e NADP+. A reação final contribui para
remoção de peróxido de hidrogênio, como mostra a Figura 4 (DANTAS et al., 2015;
MISSALL; LODGE, 2005). A ação dessa enzima confere maior viabilidade aos fungos e
tem chamado a atenção como possível alvo de antifúgicos contra Paracoccidioides
(ABADIO et al., 2015; MISSALL; LODGE, 2005).
Outro quesito que tem chamado a atenção dos pesquisadores é a participação de
proteínas extracelulares na virulência de micro-organismos patogênicos (NIMRICHTER
et al., 2016). A secreção pode ocorrer de forma clássica através da adição do peptídeo
sinal ou através de vesículas, as quais alguns autores adotaram o termo “virulence bags”
para destacar sua importância na patogenia da infecção (RODRIGUES et al., 2013). A
produção e secreção de enzimas, como as fosfolipases, parece ser uma estratégia comum
entre bactérias, parasitas e fungos patogênicos durante invasão do hospedeiro
(GHANNOUM, 2000). Os fungos H. capsulatum e C. neoformans produzem vesículas
ricas em fatores de virulência, incluindo lacases, ureases, fosfatases e proteínas de
resposta ao estresse oxidativo. Também se observou a indução genes que codificam
lipases extracelulares, que podem digerir os lipídios do hospedeiro e utilizá-los fonte de
energia (ALBUQUERQUE et al., 2008; FAN et al., 2005a; RODRIGUES et al., 2008).
O papel exato dessas proteínas no meio externo ainda não está bem esclarecido,
mas os dados indicam que pode ser mais uma estratégia que patógenos utilizam para
29
aperfeiçoar o estabelecimento da infecção. Sua ação tem sido relacionada com a resposta
adaptativa contra infecções fúngicas. Paracoccidioides e H. capsulatum liberam em suas
vesículas, moléculas antigênicas que podem ser reconhecidas por soros humanos de
pacientes infectados (MATOS BALTAZAR et al., 2016; VALLEJO et al., 2011). Um
estudo mostrou também que vesículas extracelulares de Paracoccidioides podem
modular a resposta imune inata e afetar a relação do fungo com células imunes do
hospedeiro. A adição dessas proteínas à cultura de macrófagos induziu a produção de
citocinas em macrófagos de uma maneira dose-dependente, promovendo uma polarização
do tipo M1 observada pela produção de TNF-α, IL-6 e IL-12. Esse fenômeno foi
observado inclusive em células já polarizadas do tipo M2, onde ocorreu a reversão para
o perfil de ativação M1 (DA SILVA et al., 2016). Este fenômeno também foi observado
em C. albicans e C. neoformans. Foi demonstrado que macrófagos fagocitam as vesículas
fúngicas e posteriormente ocorre a ativação essas células, observada pela produção de
óxido nítrico e expressão de citocinas (OLIVEIRA et al., 2010; VARGAS et al., 2015).
A secreção de fosfolipase B tem ganhado destaque, sendo descrita em diversos
fungos como um importante fator de virulência, embora os mecanismos subjacentes ainda
não tenham sido esclarecidos (COX et al., 2001; MA et al., 2008). Esta enzima também
foi descrita entre as proteínas secretadas in vitro por Paracoccidioides e postulada como
um potencial fator de virulência por análise in silico (DE ASSIS; GAMBALE; PAULA,
1999; TAVARES et al., 2005). Ensaios experimentais mostraram que a proteína é
importante para a adesão e internalização de macrófagos alveolares. Os dados também
indicam um aumento na virulência de fungos e subsequente redução na regulação da
ativação de macrófagos (SOARES et al., 2010).
Além de adesinas superficiais, descritas anteriormente, Paracoccidioides conta
com a secreção de proteínas que podem interagir com componentes do hospedeiro e
favorecer sua disseminação. A proteína enolase foi descrita como ligante de
plasminogênio presente na superfície do fungo, sendo também secretada pela levedura
quando internalizada em macrófagos (NOGUEIRA et al., 2010; WEBER et al., 2012).
Nosso grupo identificou outras 15 proteínas no secretoma do fungo, com habilidade de
ligar-se ao plasminogênio humano (hPlg). O plasminogênio quando ativado em plasmina,
possui atividade fibrinolítica. Dessa forma, proteínas ligantes de plasminogênio
favorecem a degradação de componentes da MEC, aumentam a interação do fungo com
macrófagos e podem atuar na disseminação de Paracoccidioides pelos tecidos do
30
hospedeiro (CHAVES et al., 2015; NOGUEIRA et al., 2010). A enzima serino proteinase
também tem sido relacionada à patogênese de Paracoccidioides, sendo induzida durante
privação de nitrogênio, infecção de camundongos e está presente no secretoma do fungo
(PARENTE et al., 2010; PIGOSSO et al., 2017). Pigosso e colaboradores (2017),
mostraram através de análises proteômicas e imuno-histoquímica que o fungo secreta
grandes quantidades dessa proteína em pulmão de camundongos durante infecção in vivo.
Esses dados reforçam a importância dos modelos experimentais de infecção, combinados
a análises proteômicas que identificam e esclarecem os mecanismos de sobrevivência e
virulência de patógenos, os quais são mediados por proteínas, sejam elas adesinas
superficiais, fatores de virulência extracelulares, proteínas de resposta aos estresses ou
enzimas de vias metabólicas.
31
2. JUSTIFICATIVA
A paracoccidioidomicose (PCM) é uma doença endêmica da América do Sul que
infecta atualmente pelo menos 10 milhões de pessoas. Considerando a patogênese desta
doença, explorar os estágios iniciais é fundamental, uma vez que macrófagos alveolares
são a primeira linha de defesa contra Paracoccidioides. Entretanto uma resposta
microbicida eficiente depende do grau de ativação das células do sistema imunológico.
Pacientes com PCM apresentam um déficit na produção de citocinas e isso nos levou a
investigar a resposta proteômica de Paracoccidioides durante a infecção de macrófagos
com diferentes padrões de ativação. Estudos realizados anteriormente, analisaram as
estratégias de sobrevivência do fungo sob diferentes tipos estresses, auxiliando na
compreensão das adaptações metabólicas e resposta ao estresse oxidativo, mas os estudos
não abordam o papel da ativação de macrófagos na expressão de genes em
Paracoccidioides. Através de modelos experimentais de infecção e análises proteômicas,
objetivamos identificar e caracterizar as particularidades metabólicas de fungos
internalizados por macrófagos ativados e não ativados por interferon gama. A
identificação de moléculas chaves da interface parasito-hospedeiro contribui para o
entendimento da patogênese da doença e pode preparar o cenário para novas abordagens
de tratamento.
32
3. OBJETIVOS
3.1. Objetivo geral
• Analisar a resposta proteômica de Paracoccidioides durante a infecção de
macrófagos ativados e não ativados por interferon gama;
3.2. Objetivos específicos
• Analisar a resposta proteômica de P.brasiliensis, Pb18 durante infecção de
macrófagos alveolares ativados e não ativados em relação à condição controle;
• Identificar as principais diferenças metabólicas entre as condições analisadas;
• Realizar ensaios confirmatórios através de imunoblotting e microscopia de
fluorescência.
33
4. RESULTADOS
Artigo 1 – Proteomic analysis of Paracoccidioides brasiliensis during infection in
activated and non-activated macrophages
Autores: Edilânia G. A. Chaves, Lilian C. Baeza, Danielle S. Araújo, Juliana A.
Parente-Rocha, Clayton Luiz Borges, Milton A. P. Oliveira, Célia M. A. Soares.
Frontiers in Microbiology
Artigo 2 – Characterization of extracellular proteins in members of the
Paracoccidioides complex
Autores: Amanda Rodrigues de Oliveira, Lucas Nojosa Oliveira, Edilânia Gomes
Araújo Chaves, Simone Schneider Weber, Alexandre Melo Bailão, Juliana Alves
Parente-Rocha, Lilian Cristiane Baeza, Célia Maria de Almeida Soares, Clayton Luiz
Borges.
Fungal Biology (Aceito)
Artigo 3 – Analysis of Paracoccidioides secreted proteins reveals fructose 1,6-
bisphosphate aldolase as a plasminogen binding protein
Autores: Edilânia Gomes Araújo Chaves, Simone Schneider Weber, Sonia Nair Báo,
Luiz Augusto Pereira, Alexandre Melo Bailão, Clayton Luiz Borges, Célia Maria de
Almeida Soares.
BMC Microbiology (Publicado)
34
Proteomic analysis of Paracoccidioides brasiliensis during
infection of alveolar macrophages activated and non-activated by
interferon gamma
Edilânia G. A. Chaves1, Lilian C. Baeza1,2, Danielle S. Araújo1, Clayton L. Borges1, Juliana
A. Parente-Rocha1, Milton A. P. de Oliveira3, Célia M. A. Soares1,*
1Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, Universidade Federal
de Goiás, Goiânia, Brazil,
2Centro de Ciências Médicas e Farmacêuticas, Universidade Estadual do Oeste do Paraná,
Cascavel, Brazil,
3Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia,
Brazil.
*Correspondence:
Célia M. de Almeida Soares
35
Abstract
Although members of the Paracoccidioides complex, are not obligate intracellular pathogens,
they present the ability to survive and multiply inside epithelial cells and mammalian
phagocytes, which may favor its dissemination in tissues. Macrophages resident in the lung are
the first line of defense against paracoccidioidomycosis (PCM) and present mechanisms to
control the spread of the fungus through the granuloma formation or eliminating the pathogen
through phagocytosis. This last process triggers an oxidative burst in which there is an increase
in the production of toxic species, caused by the respiratory burst process. Inside
phagolysosome, in addition to the oxygen and nitrogen reactive species, the fungus faces
nutrient shortages and proteases activity. However, Paracoccidioides reprograms its
metabolism for a starvation mode and activates an antioxidant system that can favors its survival
within these cells. The activation profile of macrophages directly affects the viability of the
internalized yeast cells and is crucial in the evolution from the infection state to the established
disease. Through the NanoUPLC-MSE technology, we analyzed the proteomic response of
Paracoccidioides brasiliensis during the infection of alveolar macrophages activated and non-
activated by interferon gamma. The data reveal that the fungus presents a similar metabolic
adaptation in both conditions, inducing the degradation of some amino acids and the glyoxylate
cycle, and down-regulating protein synthesis and oxidation of fatty acids at 6 hours post
infection. In addition, we observed the up-regulation of protein defense and response to
oxidative stress, as well as overexpression of virulence factors such as serine preoteinase.
However, some peculiarities such as activation of methylcitrate cycle, synthesis of cell wall
components and increased mitochondrial activity were observed mainly in yeast cells recovered
from non-activated macrophages, which indicates that the intracellular environment of non-
activated macrophages could be more permissive to the survival and multiplication of P.
brasiliensis. The identification of key molecules for the establishment of infection can help the
understanding of the nature of the parasite-host relationship and pathogenesis of PCM.
Keywords: Paracoccidioides spp., proteome, metabolism, oxidative stress, alveolar
macrophages, interferon gamma.
36
INTRODUCTION
Paracoccidioidomycosis (PCM) is a systemic granulomatous mycosis caused by
thermodymorphic fungi of the genus Paracoccidioides. This genus comprises five species, as
following: Paracoccidioides brasiliensis, Paracoccidioides americana, Paracoccidioides
restrepiensis, Paracoccidioides venezuelensis, and Paracoccidioides lutzzi (Carrero et al.,
2008; Matute, 2006; Muñoz et al., 2016; Teixeira et al., 2009; Turissini et al., 2017). PCM is
an endemic disease of South America that currently infects at least 10 million people (Martinez,
2015; Turissini et al., 2017). The fungus mainly attacks the lungs, since the infection occurs
through inhalation of infectious conidia or mycelia propagules. In the first hours of contact with
the pulmonary tissue, the fungus converts to the yeast phase, it´s parasitic form (McEWEN et
al., 1987). One of the main features of PCM is the formation of granulomas, since macrophages
are one of the primary defense elements against Paracoccidioides. Macrophages form a giant
multinucleated agglomerate capable of limiting the spread of yeast cells, besides eliminating
the pathogens through phagocytosis (Brummer et al., 1989; Fortes et al., 2011; McEWEN et
al., 1987).
The intracellular environment is a challenge for fungal survival. In addition to the low
availability of nutrients and the action of proteases, there is explosion of oxygen consumption
during host-pathogen interaction that has been associated with the microbicidal activity of
phagocytes (Fang, 2004; Haas, 2007; Philippe et al., 2003). This reaction produces large
amounts of the reactive species of oxygen (ROS) and reactive species of nitrogen (RNS). The
oxidative and nitrosative stresses cause oxidation of proteins, lipids and DNA which interferes
in the replication of pathogens (Fang, 2004; Ferrari et al., 2011). Despite this, Paracoccidioides
is able to survive and multiply inside epithelial cells and mammalian phagocytes, which
indicates that the fungus can subvert the phagocytic defenses to promote its spread through host
tissues (Brummer et al., 1989; Hanna et al., 2000; Mendes-Giannini et al., 2004; Moscardi-
Bacchi et al., 1994).
The intracellular survival of fungi has motivated several studies to investigate which are the
strategies used by those pathogens to survive inside macrophages (Camacho and Niño-Vega,
2017; Erwig and Gow, 2016; Kasper et al., 2015; Miramo et al., 2010; Seider et al., 2014).
Proteomic and transcriptomic studies analyzed the metabolic adaptation of fungi to in vitro
conditions of deprivation of carbon sources (Askew et al., 2009; Baeza et al., 2017; Lima et al.,
2014; Szilagyi et al., 2013; Yin et al., 2004). Overall, those studies, show that fungi, including
Paracoccidioides, present a metabolic reprogramming for alternative carbon pathways as
amino acid degradation, gluconeogenesis, beta oxidation of fatty acids and glyoxylate cycle.
Fungal strains that present mutations in genes encoding proteins of these pathways, have
attenuated virulence (Lorenz and Fink, 2002; Ramirez and Lorenz, 2007).
The data on metabolic adaptations and the response to oxidative stress obtained in vitro
corroborate with experiments of interaction of fungi with macrophages and in vivo assays of
infection in murines (Fan et al., 2005; García-Rodas et al., 2011; Parente-Rocha et al., 2015;
Pigosso et al., 2017). In oxidative and nitrosative stresses conditions, Paracoccidioides presents
an overexpression of enzymes as catalases, superoxide dismutases, cytochrome c peroxidase
and thioredoxin (Campos et al., 2005; de Arruda Grossklaus et al., 2013; Parente-Rocha et al.,
2015; Parente et al., 2015; Pigosso et al., 2017). Those proteins act in the detoxification of ROS
and RNS and are important for the virulence of the fungus during infection (Parente-Rocha et
al., 2015; Tamayo et al., 2016, 2017). The expression of the proteins cited above, has been
described in several fungi, such as Aspergillus fumigatus, Cryptococcus neoformans,
Histoplasma capsulatum, Saccharomyces cerevisiae and Candida species, indicating that those
pathogens have a powerful antioxidant defense system that promotes its survival in the
37
intracellular environment (Cuéllar-Cruz et al., 2008; Dantas et al., 2015; Giles et al., 2005;
Holbrook et al., 2013; Kwon et al., 2003; Lambou et al., 2010; Missall and Lodge, 2005).
The success of mechanisms of intracellular evasion of pathogens depends of the
activation profile of macrophages. Activation of phagocytes with interferon gamma (INF-)
affects directly the viability of internalized Paracoccidioides cells, and is crucial to prevent the
progression of disease (Brummer et al., 1988, 1989; Rodrigues et al., 2007). Infection assays
performed with several isolates of Paracoccidioides showed that the addition of INF- does not
increase the phagocytosis index, but it confers microbicide activity to the macrophages in a
dose-dependent manner. (Brummer et al., 1989; Moscardi-Bacchi et al., 1994; Rodrigues et al.,
2007). Moreover, deficiency in the immune system, related to low production of cytokines,
have been associated with the evolution of PCM. Studies revealed that the production of IL-2
and INF-γ by peripheral blood mononuclear cells from patients affected by acute or chronic
PCM, was lower compared to healthy patients. INF-γ also plays an important role in the
recruitment of defense cells to the lungs and for the efficiency of granulomas. Large amounts
of interferon gamma were detected in compact granulomas of PCM-resistant mouse in relation
to loose granulomas and multifocal lesions detected in susceptible animals (Benard et al., 2001;
Nishikaku et al., 2011; Souto et al., 2000, 2003).
Proteomic analysis of Paracoccidioides phagocytosed by macrophages with different
activation patterns has not been performed. Previous studies of macrophage-P. brasiliensis
interaction for 24 h, revealed the repression of the glycolytic pathway and activation of enzymes
related to gluconeogenesis, degradation of amino acids and fatty acids, ethanol production, as
well as tricarboxylic acid (TCA), glyoxalate, methylcitrate cycles, respiratoty chain and ATP
synthesis, as metabolic adaptations (Parente-Rocha et al., 2015). In this study, we compared the
proteomic response of P. brasiliensis, Pb18 during infection of alveolar macrophages activated
and non-activated by INF- through the NanoUPLC-MSE technology. In both analyzed
conditions, P. brasiliensis presented decrease of -oxidation of fatty acids and protein
synthesis, and increase in enzymes related to glutamate degradation, TCA and glyoxilate cycles,
as alternative energy pathways, at 6 h post infection. The induction of proteins related to heat
shock response, antioxidant response and virulence factors, such as serine proteinase, was also
observed. Metabolic peculiarities between the two conditions, such as the activation of pentose-
phosphate pathway, methylcitrate cycle, synthesis of cell wall components and intense
mitochondrial activity, were observed only in fungal cells recovered from non-activated
macrophages. While the activated macrophages showed fungicidal activity in the first six hours
of interaction, the interior of non-activated phagocytes appears to be a favorable environment
to the survival and multiplication of P. brasiliensis. The identification of key molecules for the
establishment of infection helps us to understand the nature of the parasite-host relationship and
the factors that determine the evolution from asymptomatic infection to manifested disease.
2. MATERIAL AND METHODS
2.1. Cultivation and maintenance of microorganism
The P. brasiliensis, Pb18 strain (chronic PCM; São Paulo, Brazil; P. brasiliensis, Pb18)
(Turissini et al., 2017) was used in all experiments. The yeast cells were maintained by sub
culturing at 36°C in Fava Netto’s solid medium every 7 days (Fava-Netto, 1955). After this
period, the cells were transferred to Fava Netto´s liquid medium for 72 h at 36°C under agitation
at 150 rpm, for performing experiments
38
2.2. Cultivation and maintenance of alveolar macrophages
The alveolar macrophages AMJ2-C11 (Rio de Janeiro Cell Bank - BCRJ/UFRJ, accession
number 0039) are originated from murine. The cells were maintained in DMEM medium
(Vitrocell Embriolife, Campinas, SP, Brazil) containing bovine fetal serum 10% (v/v) at 36°C
and 5% CO2. The culture medium was changed after the cells reach complete confluence.
2.3. Macrophage infection assays
P. brasiliensis, Pb18 infection in AMJ2-C11 alveolar macrophages was performed in triplicates
on 12-well polypropylene plates. In each well was plated a total of a total of 106 macrophages
cells in DMEM medium containing or not IFN-γ (1 U/mL) (Sigma Aldrich, Missouri, USA)
and bovine fetal serum 10% (v/v). The plates were incubated 12 h at 36°C and 5 % CO2 until
complete confluence. The medium was removed and a fresh DMEM medium containing or not
IFN-γ (1 U/mL) and bovine fetal serum 10% (v/v) plus 5x106 Pb18 cells, were added to the
macrophages. For all infection assays, the yeast cells obtained from a 72 h inoculum in Fava
Netto's liquid medium were filtered through 0.70 µm-pore membrane filters, with the aid of
syringe and needle. The plates were incubated at 36°C and 5% CO2 during 3 h, 6 h, 9 h and 12
h. The wells were gently washed three times with sterile phosphate buffered saline (PBS 1X)
and the macrophages were lysed by the addition of sterile water. The yeast cells were recovered
by centrifugation at 8,000 × g for 10 min (Parente-Rocha et al., 2015). The pellet was diluted
(1:100) and plated in solid BHI medium, supplemented with bovine fetal serum 4% (v/v) and
glucose 4% (v/v). Yeast cells viability was evaluated based on the number of colony-forming
units (CFU), determined after growth at 36°C for 10 days. The control was obtained by
incubating 5x106 cells/mL in DMEM medium, added of bovine fetal serum 10% (v/v) for 6 h
at 36°C and 5% CO2.
2.4. Obtaining protein extracts
Infection time of 6 h was selected to carry out the proteomic analysis. Protein extracts were
obtained in biological triplicates from the three conditions to be analyzed: Pb18 cells recovered
of activated macrophages (Pb18_A); Pb18 cells recovered of non-activated macrophages
(Pb18_NA) and control cells. The yeast cells were collected by centrifugation at 8,000 × g for
10 min and washed once with RapiGEST SF Surfactant 0.1% (v/v) (Waters Corporation,
Billerica, MA, USA), followed by washing with ultrapure water and PBS 1X, in order to
remove any contamination of the macrophage cells (Parente-Rocha et al., 2015; Pigosso et al.,
2017). The pellet was ressuspended in extraction buffer (20 mM Tris-HCl, pH 8.8, and 2 mM
CaCl2) and distributed in tubes containing glass beads (Sigma Aldrich) in equal volume of the
material. The suspension was processed on ice in BeadBeater equipment (BioSpec, Products
Inc., Bartlesville, OK, USA) during 3 cycles of 30 sec. The cell lysate was centrifuged at 10,000
x g during 15 min at 4°C and the protein content in the supernatant was quantified using the
Bradford reagent (Sigma Aldrich), and bovine serum albumin (BSA) was used as standard
(Bradford, 1976).
2.5. Protein digestion for nanoUPLC-MSE analysis
39
Proteins were enzymatically digested with tripsin as described previously, with some
modifications (Murad et al., 2011). Briefly, a total of 150 µg of protein (previous item) of each
sample was added to 10 µL of 50 mM ammonium bicarbonate, pH 8.5, in a microcentrifuge
tube. Next, 75 µL of RapiGESTTM SF Surfactante (0.2 % v/v) (Waters Corporation) was added
and the sample was vortexed and incubated in a dry bath at 80 °C for 15 min. In each sample
were added 2.5 µL of 100 mM dithiothreitol (GE Healthcare, Piscataway, NJ, USA), at 60°C
for 30 min, while cysteines were alkylated by the addition of 2.5 µL of 300 mM iodoacetamide
(GE Healthcare) for 30 min, at room temperature in the dark. The digestion of proteins was
performed by the addition of 30 μl of trypsin 0.05 µg/µL (Promega, Madison, WI, USA) at
37°C, in dry bath, for 16 h. Then, 30 μL of trifluoroacetic acid (TFA) solution 5 % (v/v) was
added to the samples, followed by incubation for 90 min at 37°C, for digestion stop and
precipitation of the RapiGEST reagent. The samples were centrifuged at 18,000 × g for 30 min
and the supernatant was transferred to a new tube and dried in a speed vacuum (Eppendorf,
Hamburg, Germany) for 2 h. The pellet containing peptides was suspended in 80 μL of a
solution containing 20 mM of ammonium formiate and 150 fmol/μL of PHB (Rabbit
Phosphorylase B) (Waters Corporation) (MassPREP protein), as internal standard. The tryptic
peptides were analyzed using a nanoACQUITY UPLC® M-Class system (Waters Corporation)
coupled to Synapt G1 MS™ mass spectrometer (Waters Corporation), equipped with a
NanoElectronSpray source and two mass analyzers: a quadrupole and a time-of-flight (TOF)
operating in the V-mode. Nanoscale LC separation of tryptic peptides was performed with two
reverse phase columns. The peptides were separated using a gradient of 11.4%, 14,7%, 17.4%,
20.7% and 50% (v/v) of acetonitrile/0.1% (v/v) formic acid, with a flow rate of 2.000 µL/min.
Data were obtained using the instrument in the MSE mode, which switches the low energy (6
V) and elevated energy (40 V) acquisition modes every 0.4 s. The lock mass was used for
calibration of the apparatus, using a constant flow rate of 0.2 µL/min at concentration of 200
fmol protein GFP [Glu]1-Fibrinopeptide B human (m/z 785.8426) (Sigma-Aldrich). The
samples were analyzed in triplicate, from three independent experiments.
2.6. Data processing and protein identification
Mass spectrometry raw data of peptide fractions were processed using the ProteinLynx Global
SERVER (PLGS) platform (Waters Corporation). Then, the processed spectra were searched
against P. brasiliensis, Pb18 protein sequences
(http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/Multiome.tm
l) together with reverse sequences. The mass error tolerance for peptide identification was under
50 ppm. Protein identification criteria were as following: detection of at least 2 fragment ions
per peptide; 5 fragments per protein; the determination of at least 1 peptide per protein;
carbamidomethylation of cysteine as a fixed modification; phosphorylation of serine, threonine
and tyrosine, and oxidation of methionine were considered as variable modifications;
maximum protein mass (600 kDa); one missed cleavage site was allowed for trypsin;
maximum false positive ratio (FDR) of 5% was allowed. For the analysis of the level of protein
quantification, the observed intensity measures were normalized using a protein that showed
lower coefficient of variance between the different conditions analyzed and present in all
replicates. ExpressionE informatics v.3.0.2 was used for proper quantitative comparisons. The
identified proteins were organized by the expression algorithm, into a statistically significant
list, corresponding to induced and reduced regulation ratios between the different conditions
analyzed. The mathematical model used to calculate the ratios was a part of the Expression
algorithm inside the PLGS software from the Waters Corporation (Geromanos et al., 2009).
The minimum repeat rate for each protein in all replicates (nine in total for each condition) was
40
6. Proteins that presented 40% of differences in expression values, when compared among the
different conditions, were considered regulated. Tables of peptides and proteins generated by
the PLGS were merged, and the data of dynamic range, peptide detection type, and mass
accuracy were calculated for each sample, as previously described using the software
MassPivot v1.0.1(Murad and Rech, 2012). FBAT (Lange et al., 2004), Spotfire® v8.0 program
(TIBCO software), and Microsoft Excel® (Microsoft) was used for table manipulations. Uniprot
(http://www.uniprot.org) and Pedant on MIPS (http://mips.helmholtz-muenchen.de/funcatDB/)
database were used for functional classification. NCBI database was employed for annotation
of uncharacterized proteins (https://www.ncbi.nlm.nih.gov/).
2.7. Western blotting
Protein samples were fractionated by one-dimensional 12% SDS-PAGE gel electrophoresis.
The gels were run at 150 V for 3 h and the proteins were transferred to nitrocellulose membranes
at 40 V for 16 h, in buffer containing 25 mM Tris–HCl (pH 8.8), 190 mM glycine and 20%
(v/v) methanol. Through the staining of the membranes with Ponceau red, the complete protein
transfer was verified. Next, the membranes were incubated in blocking buffer [1X PBS, 1.4
mM KH2PO4, 8 mM Na2HPO4, 140 mM NaCl, 2.7 mM KCl (pH 7.3), 5% (w/v) nonfat dried
milk and 0.1% (v/v) Tween 20], for 2 h. After three washes with PBS 1X containing 0.1% (v/v)
Tween 20 (PBS-T), the membranes were incubated with the polyclonal antibodies directed to
isocytrate lyase (da Silva Cruz et al., 2011) and HPS30 (PADG_03963) in the concentrations
1:1000 for anti-ICL and 1:500 for anti-HSP30 in blocking buffer, for 1 h. Subsequently,
membranes were washed three times with PBS-T and were incubated with the secondary
antibodies anti-mouse or anti-rabbit immunoglobulin G (IgG) coupled to alkaline phosphatase
(Sigma Aldrich) diluted 1:5000 in blocking buffer, for 1 h. After that, the membranes were
washed, and the reaction was developed using 5-Bromo-4-chloro-3-indolyl phosphate (BCIP)
and Nitro Blue Tetrazolium (NBT).
2.8. Analysis of cell wall components by fluorescence microscopy
To evaluate the cell wall components, as glucans, glycosylated proteins and chitin contents, the
yeast cells recovered of macrophages were stained with aniline blue (AB) (Sigma-Aldrich) for
5 min, concanavalin A (ConA) TYPE VI conjugated to FITC 100 μg/ml (Sigma-Aldrich) for
30 min and with calcofluor white (CFW) 100 μg/ml (Sigma-Aldrich) for 30 min (de Curcio et
al., 2017). Samples stained were visualized under a fluorescence microscope (Zeiss Axiocam
MRc-Scope A1, Oberkochen, Germany). Images were obtained at bright field, at 340-380 nm
for AB, 470-480 nm for Con A and at 395-440 nm for CFW. A minimum of 100 cells on each
microscope slide were used to evaluate fluorescence intensity in triplicates. The AxioVision
Software (Carl Zeiss AG, Germany) determined the fluorescence intensity (in pixels) and
standard error of each analysis. Statistical comparisons were performed using the Student’s t-
test and p ≤ 0.05 was considered statistically significant.
2.9. Evaluation of mitochondrial activity
P. brasiliensis, Pb18 cells recovered from macrophages and control cells (as previously
described) were centrifuged at 8,000 × g for 10 min. The pellet was diluted in PBS 1X to a
concentration of 1x106 cells/mL. To label mitochondria, the cells were stained with Mitotracker
Green FM (400 nM; Molecular Probes, M7514) for 45 min at 37°C. Then, the cells were washed
three times with PBS 1X and labeled with rodhamine (2.4 µM) for 45 min at 37°C, according
41
to the manufacturer's protocol (Invitrogen, Carlsbad, CA, USA) and washed three times with
PBS 1X. Labelled cells were observed under a fluorescence microscope (Zeiss Axiocam MRc-
Scope A1, Oberkochen, Germany) and photographed at bright field, and at 450-490 nm for the
Mitotracker and 546-512 nm for rosamine dye probes. A minimum of 100 cells on each
microscope slide were used to evaluate fluorescence intensity in triplicate. The AxioVision
Software (Carl Zeiss AG, Germany) determined the fluorescence intensity (in pixels) and
standard error of each analysis. Statistical comparisons were performed using the Student’s t-
test and p ≤ 0.05 was considered statistically significant.
3. RESULTS
3.1. P. brasiliensis survival into alveolar macrophages
Activation of macrophages by INF-γ does not significantly influence the rate of phagocytosis,
but increases the microbicide activity (Brummer et al., 1988). P. brasiliensis, Pb18 infection in
AMJ2-C11 alveolar macrophages was performed in order to determine the best time of
infection, with higher rate of internalization of viable fungi cells, that is, phagocytosed but not
killed cells, and thus carry out the extraction of proteins. Times of 3 h, 6 h, 9 h and 12 h of
infection were analyzed regarding to the number of CFUs in Pb18 yeast cells recovered of
activated macrophages (Pb18_A) and non-activated macrophages (Pb18_NA). The Fig. 1
shows that the number of viable fungal cells increases inside the macrophage until 6 h. After
this time, the number of viable fungal decreases, suggesting the macrophages kill fungal cells
after 9 h of interaction. In this way, the proteomic response of P. brasiliensis, after 6 h of
infection in macrophages, was investigated with the objective of analyzing the differences in
the initial proteomic response of the fungus during infection of macrophages with different
activation patterns.
3.2. Proteomic data quality analysis
Protein extracts were obtained in biological triplicates. Protein quantification was performed
using Nano-UPLCMSE and the protein and peptide data were generated by the PLGS (Fig. S1).
The false positive rates of proteins obtained from Pb18_A were 3.80%, Pb18_NA were 5.88%
and control were 2.99%. Those experiments resulted in 53,745; 47,941 and 61,561 identified
peptides, from Pb18_A, Pb18_NA and control, respectively. The values of 50.1%, 49.2% and
53.9% were obtained from peptide match type data in the first pass and 7.5%, 7.6% and 9.7%
from the second pass, for Pb18_A, Pb18_NA and control, respectively. A total of 16.2%, 16,
5% and 14% of total peptides were identified by a missed trypsin cleavage, whereas an in-
source fragmentation was 11%, 11.2% and 11.8% for Pb18_A, Pb18_NA and control,
respectively. The peptides identification within the first and second pass (PepFrag 1 and 2) were
predominant higher than 56%, and source fragmentation and missed cleavage values did not
exceed 20% in all analyzed conditions (Fig S1. A) (Murad and Rech, 2012). The peptide parts
per million errors (ppm) indicated that the majority, 82%, 83.9% and 79.3% of identified
peptides were detected with an error of less than 10 ppm for Pb18_A, Pb18_NA and control,
respectively (Fig S1. B). The obtained results from dynamic range detection indicated that a 3-
log range concentration and a good detection distribution of high and low molecular weights
were obtained in all analyzed conditions (Fig S1. C).
3.3. Proteomic profile of P. brasiliensis during infection of alveolar macrophages
activated and non-activated by INF-
42
Protein extracts of P. brasiliensis, Pb18 recovered of activated or non-activated macrophages
were compared with control samples by using MSE technology. A total of 288 regulated
proteins were detected in Pb18_A, being 187 up-regulated proteins (Table S1) and 101 down-
regulated proteins (Table S2). A total of 341 regulated proteins were detected in Pb18_NA,
being 277 up-regulated proteins (Table S3) and 64 down-regulated proteins (Table S4).
Western blotting assays were performed to confirm the expression of some up-regulated
proteins such as isocitrate lyase and 30 kDa heat shock protein. The results of those analyzes
are shown in Figure S2.
3.4. Regulated proteins in P. brasiliensis during infection of activated macrophages
Table S1 shows that after 6 hours of interaction with activated macrophages, P. brasiliensis
presents accumulation of enzymes related to glutamate degradation, glycolysis, TCA cycle,
glyoxylate cycle, electron transport chain and ATP synthesis. Heat shock proteins, enzymes
related to oxidative stress protection, as thioredoxin reductase and superoxide dismutases, and
virulence factors as serine proteinase were also up-regulated. Down-regulated proteins are
described in the Table S2, in which enzymes related to the -oxidation of fatty acids,
fermentation process, synthesis of proteins are highlighted.
3.5. Regulated proteins in P. brasiliensis during infection of non-activated macrophages
Paracoccidioides, Pb18 cells recovered from non-activated macrophages showed an increase
of proteins related to amino acid degradation, glycolysis, pentose-phosphate pathway, TCA,
glyoxylate and methylcitrate cycles, electron transport and ATP synthesis. Enzymes of
carbohydrate metabolism, related to the synthesis of cell wall precursors, were also induced.
Interestingly, the fungus increased the expression of enzymes responsive to oxidative stress
during infection of non-activated macrophages (Table S3). Table S4 depicts the negatively
regulated proteins that are related to protein synthesis and beta oxidation, principally.
3.6. Comparative proteome of P. brasiliensis recovered from activated and non-
activated macrophages
Despite the similarity in the adaptation pattern of Pb18 cells in activated and non-activated
macrophages at 6 h post infection, it is worth mentioning some metabolic peculiarities that
apparently favors the survival of fungus only in non-activated macrophages. Many adaptation
strategies have been described as essential for the viability of fungi under nutrient deprivation
conditions, as gluconeogenesis, fatty acids degradation, glyoxylate cycle (Seider et al., 2014).
However, apparently, in the first few hours of infection P. brasiliensis it is not able to activate
these pathways within activated macrophages (Table S1). Yeast cells interacting with non-
activated macrophages, depicted faster metabolic adaptation, activating alternative energy
routes as methyl citrate cycle, in addition to the amino acid degradation, glyoxylate cycle and
pentose phosphate pathway, above mentioned (Table S3). These data indicate that the
intracellular environment of activated macrophages presents barriers that may hinder the
adaptation of the fungus to the cell environment.
Corroborating this hypothesis, the Pb18_NA cells presents a higher number of proteins and
abundance of enzymes related to response to oxidative stress and virulence factors, as shown
in Table 1. SOD2, for example, had its expression about twice as high in Pb18_NA compared
43
to Pb18_A. Other metabolic peculiarities were investigated, such as the induction of cell wall
synthesis components and increased mitochondrial activity detected mainly in Pb18 recovered
of non-activated macrophages, as following.
3.7. P. brasiliensis, Pb18 is apparently synthesizing cell wall components in non-activated
macrophage infection
We observed an increase of enzymes that participate of the synthesis of precursors of cell wall
components as chitin, glycan, glycoproteins and glycosylated compounds, mainly in Pb18_NA
(Table 2). Enzymes as neutral alpha-glucosidase AB, mannosil-oligosaccharide glucosidase
and alpha-mannosidase are involved in glycoprotein biosynthesis through the N-glycosylation
process (Almeida et al., 2016). The UDP-galactopyranose mutase, UTP-glucose-1-phosphate
uridylyltransferase and UDP-N-acetylglucosamine pyrophosphorylase form UDP-sugars,
substrates used in hundreds of glycosylation reactions (e.g. for protein and lipid glycosylation,
synthesis of sucrose and cell wall polysaccharides. The UDP-N-acetylglucosamine
pyrophosphorylase generates UDP-N-acetyl-D-glucosamine, which is used in the synthesis of
chitin, for example. (Decker et al., 2017). These data indicate that P. brasiliensis may be
synthesizing components of the cell wall during infection, especially within non-activated
macrophages, which may confer resistance to the fungus.
Our proteomic data were confirmed by fluorescence microscopy using aniline blue,
concanavalin A and calcofluor as markers for glucans, carbohydrates residues in proteins and
chitin, respectively (Figure 2). P. brasiliensis yeast cells recovered from non-activated
macrophages presented higher fluorescence intensity for labeled cell wall components, as
demonstrated by treatment of cells with the reagents cited above.
3.8. P. brasiliensis, Pb18 is apparently shows greater mitochondrial activity in non-
activated macrophage infection
Increase of proteins related to the electron transport chain and ATP synthesis complex were
observed in yeast cells recovered from non-activated macrophages. It was observed that, in
relation to the control, both conditions showed an increase in mitochondrial activity, however,
a higher number of subunits for those proteins and their abundance was higher in Pb18_NA
(Table 3). We used MitoTracker Green FM as a total mitochondrial dye (green) and the
mitochondrial activity was evaluated by using rhodamine dye (red), which stains selectively
according to mitochondrial membrane potential (Figure 3). The fluorescence intensity of
rhodamine was significantly increased in Pb18_NA compared to Pb18_A. This data
corroborates with the data of the Table S5, where the MSE technology was used to compare
Pb18_A and Pb18_NA proteins.
4. DISCUSSION
The intracellular environment imposes numerous difficulties to pathogens, such as the action
of hydrolytic enzymes, nutrient deprivation and presence of reactive species of oxygen and
nitrogen (Haas, 2007). To establish the infection, pathogens require a metabolic flexibility to
assimilate the available nutrients and a powerful antioxidant system that allows them to survive
intracellularly (Camacho and Niño-Vega, 2017; Kasper et al., 2015; Seider et al., 2014). The
cells of the innate immune system, mainly macrophages and neutrophils, are the primary line
of defense against Paracoccidioides infection (Calich et al., 2008; Franco, 1987; Mendes-
Giannini et al., 2008). However, microscopic findings show that Paracoccidioides is able to
44
survive and multiply in phagocytes, although this ability is inhibited by the activation of these
cells (Brummer et al., 1988; Rodrigues et al., 2007). Those findings were confirmed in our
work, where we determined a time-course survival of P. brasiliensis in non-activated
macrophages. The activated cells showed a microbicidal activity in the first 6 h of interaction,
while the survival of the fungus in non-activated macrophages was not affected (Fig 1). This
difference in the fungicidal potential between activated and non-activated phagocytes was
observed in infection assays with several Paracoccidioides isolates. The addition of INF- did
not increase the phagocytosis index, but it confers microbicidal activity to the macrophages in
a dose-dependent manner (Brummer et al., 1988, 1989).
Proteomic and transcriptomic analysis reveal that pathogenic bacteria and fungi reprogram their
metabolism, regulating negatively the glycolytic pathway and activating alternative routes of
carbon consumption, as gluconeogenesis, amino acid degradation, fatty acids oxidation,
glyoxylate cycle and ethanol production, during macrophage infection (Sprenger et al., 2017).
Gluconeogenesis has been described as a crucial strategy during the first steps of fungal
infections, whereas glycolysis has importance later, being fundamental for the permanence of
the pathogen in the host (Price et al., 2011). Our proteomic analyzes showed that, in activated
macrophage and non-activated infection, Pb18 cells did not exhibit up-regulation of
gluconeogenesis (Table S1 and S3). This data was also observed after 6 h murine infection and
may be due to glucose reserve, since the fungus was grown in a nutrient rich medium prior to
infection (Pigosso et al., 2017). In this sense, activation of gluconeogenesis has been observed
in Pb18 after a longer period of infection in macrophages (Parente-Rocha et al., 2015).
In both analyzed conditions, we observed that degradation of amino acids and pyruvate
dehydrogenase complex enzymes are up-regulated. Those pathways can provide intermediary
molecules that fuel the TCA and glyoxylate cycles (Table S1 and S3). The up-regulation of
proteins related to TCA, electron transport and ATP synthesis was also observed when the
fungus was cultivated in carbon deprivation (Lima et al., 2014). When growing in acetate, as
the only carbon source, different levels of expression of the proteins components of those
pathways were observed among Paracoccidioides isolates (Baeza et al., 2017). An increase in
the expression of isocitrate lyase enzyme was observed in Pb18_A and Pb18_NA, which
indicates that the fungus is in a nutrient-limited environment (Table S1 and S3). This enzyme
catalyzes reactions of the glyoxylate cycle and this pathway has been associated with fungal
virulence, since it is essential for survival in phagosome (Lorenz and Fink, 2002). The
glyoxylate cycle shunt from TCA cycle is a metabolic adaptation that fungus to use to
compensate for the lack of carbohydrates in the medium, since the enzymes this cycles allow
the use of compounds two carbons, as acetate (Barelle et al., 2006).
Dihydrolipoamide dehydrogenase (DLD) is a multifunctional protein well characterized as the
E3 component of the pyruvate dehydrogenase and α-ketoglutarate dehydrogenase complexes
(Hiromasa et al., 2004). This protein was identified in P. brasiliensis, Pb18 as an adhesin that
promotes interaction with macrophages and is capable of enhancing the microbicidal activity
of these cells (Landgraf et al., 2017). Interestingly, the expression of this enzyme was induced
only in P. brasiliensis recovered of activated macrophages (Table S1). There are few reports
on this protein, which seems to be a great candidate to be characterized in later studies.
It is also noted an accumulation of enzymes related to pentose-phosphate pathway,
methylcitrate cycle and synthesis of cell wall precursors only in yeast cells derived from non-
activated macrophages (Table S3). The activation of those pathways may favor the fungus
survival in the hostile environment in which it is found. The pathway of phosphate pentoses
also contributes to the defense against oxidative stress since it provides redox equivalents, as
NADPH. The enzyme methyl citrate synthase is essential for the degradation of toxic
45
compounds as propionyl-CoA, and is necessary for the pathogen as A. fumigattus to establish
infection in murines (Ibrahim-Granet et al., 2008). Similar data were also observed during 6 h
of infection of murine and after 24 h of infection in J774 macrophages by P. brasiliensis
(Parente-Rocha et al., 2015; Pigosso et al., 2017). Those metabolic peculiarities indicate that
the intracellular environment of activated macrophages prevents the fungus from activating
strategic pathways of metabolic adaptation rapidly, as it does in non-activated macrophages.
The fungus also increased the expression of proteins involved in cell rescue, defense and
virulence in both conditions (Table 1). Autophagic proteins as serine proteinase, vacuolar
aminopeptidase, carboxypeptidase Y were up-regulated. These enzymes have been described
as important virulence factors that promote the recycling of cytoplasmic components in
pathogen starvation mode. Autophagic processes have been described in S. cerevisiae and
Candida glabrata as a way of survival in the host and during nitrogen starvation and depletion
of nutrients (Inoue and Klionsky, 2010; Roetzer et al., 2010). Serine proteinase has recently
been described in P. brasiliensis as a virulence factor that favors survival upon nitrogen
deprivation, as well as tissue invasion , since it is secreted in large amounts in the host during
murine infection (Parente et al., 2010; Pigosso et al., 2017). Our data corroborate with analyzes
of Paracoccidioides transcripts and proteins induced during oxidative and nitrosative stresses
conditions, as well as during in vitro and in vivo infection assays (de Arruda Grossklaus et al.,
2013; Parente-Rocha et al., 2015; Parente et al., 2015; Pigosso et al., 2017).
Here, it was also observed, an increased expression of heat shock proteins and proteins involved
in detoxification and stress response, as thioredoxin reductase (TrxR) and superoxide dismutase
(SOD) in P. brasiliensis recovered of activated and non-activated macrophages, although the
higher expression was observed in the last condition (Table 1). TrxR, which works in
conjunction with thioredoxin, is induced in Paracoccidioides during oxidative stress and
infection assays (Table 1). The TrxR, which works in conjunction with thioredoxin, is induced
in Paracoccidioides during oxidative stress situation and infection assays (de Arruda
Grossklaus et al., 2013; Pigosso et al., 2017). TrxR is a molecule of antioxidant resistance, since
it binds to NADPH and reduces thioredoxin, forming thioredoxin disulfide and NADP+; the
final reaction contributes to the removal of superoxide radicals (Missall and Lodge, 2005;
Yoshida et al., 2003). Some fungi such as members of Candida species increase the expression
of the thioredoxin system during oxidative and nitrosative stresses (Brown et al., 2009). In C.
neoformans the action of this enzyme also gives high virulence to the fungus. This enzyme has
called attention as a possible target of antifungal drugs against Paracoccidioides infection
(Abadio et al., 2015; Missall and Lodge, 2005).
SODs have been characterized in Paracoccidioides as responsive enzymes to
oxidative and nitrosative stresses (Campos et al., 2005; Parente et al., 2015; Tamayo et al.,
2016). SODs are metalloproteins classified on the basis of metals located at their active sites
(Fe, Mn, Ni and Cu / Zn) (Gralla and Kosman, 1992) and contribute to virulence of various
fungi (Cox et al., 2003; Frohner et al., 2009; Lambou et al., 2010; Youseff et al., 2012). Six
isoforms of SODs encoded by the genome Paracoccidioides have been identified, which have
different levels of gene expression among isolates of the genus. Cells silenced by antisense-
RNA for those proteins were more susceptible to the action of macrophages and neutrophils
compared to the wild type. The mutant for SOD3 was described as the less virulent, highlighting
the relevance of this isoform for the establishment of PCM. Mutants for SOD1 were able to
infect the lungs but were unable to disseminate through other tissues (Tamayo et al., 2016).
SODs are a primary antioxidant defense against ROS which dismutates the superoxide radicals
and convert them into less harmful molecules such as hydrogen peroxide and oxygen molecules.
The Paracoccidioides genome database lists six SOD isoforms. SOD1 knock down of
46
Paracoccidioides are less resistant to oxidative stress and have decreased virulence (Tamayo et
al., 2016). SODs are a primary antioxidant defense against ROS which dismutates the
superoxide radicals and convert them into less harmful molecules such as hydrogen peroxide
and oxygen molecules. The predominance of those proteins in P. brasiliensis recovered of non-
activated macrophages reinforces the evidence that the fungus has difficulty to adapt to the
intracellular environment of activated macrophages, which culminates in its death.
Corroborating the suggestion above, accumulation of glycolytic enzymes that can
generate precursors of Paracoccidioides cell wall components, was observed in P. brasilensis
recovered of non-activated macrophages (Table 2). Proteomic data were confirmed by
fluorescence microscopy, since higher amounts of glucans, glycosylated proteins and chitin
were observed in the cell wall of yeasts recovered from non-activated macrophages (Figure 2).
The fungal cell wall is composed by glycoproteins and polysaccharides, such as chitin, glucan
and glycosylated proteins and confer virulence to those pathogens (Bernard and Latgé, 2001;
Jung et al., 2018; San-Blas and San-Blas, 1977). Proteomic studies of Paracoccidioides spp.
cultivated in presence of acetate, a predominant two-carbon molecule in phagosome, revealed
the utilization of cell wall components for gluconeogenesis in Pb03 and PbEPM83, after 48 h
de incubation (Baeza et al., 2017). Pigosso, et al. (2017) identified down-regulation of
transcripts related to cell wall homeostasis in yeast cells during lung infection.
Our data corroborated with studies conducted by Brummer et al., 1990 in which the morphology
of P. brasiliensis presented differences after internalization by activated and non-activated
peritoneal macrophages. During infection of activated macrophages was observed deterioration
of cell wall of fungus until complete digestion and elimination, while in non-activated
macrophages the P. brasiliensis cell wall remained intact. Other studies performed infection in
non-activated macrophages, and it was also observed that Paracoccidioides activated enzymes
that synthesize components of the cell wall. This strategy can be an important form of fungus
resistances (Tavares et al., 2007). C. neoformans also depicted induction in the expression of
genes encoding enzymes involved in polysaccharide synthesis, during activated macrophages
infection, which may be associated with the formation of cell wall or capsule components (Fan
et al., 2005). Phosphomannomutase performs the conversion of mannose-6-phosphate to
mannose-1-phosphate to produce GDP-mannose and is associated with an increase in the
interaction of pathogens with human macrophages (McCarthy et al., 2005). The N-glycosylated
proteins are essential for growth, morphogenesis and for the biological activities of some
Paracoccidioides proteins (Dos Reis Almeida et al., 2011). Apparently, while are available, the
fungus uses C-compounds for cell wall synthesis, which confers more resistance. Changes in
the cell wall contribute to resistance and virulence in the yeast phase of Paracoccidioides
through increased α-glucan, which protects yeast cells from β-glucan recognition by
macrophages and contributes to fungal latency (Kanetsuna and Carbonell, 1970; Lara-Lemus
et al., 2014). Since non-activated macrophage allows the survival and multiplication of the
fungus, they can be used as a means of fungal dissemination.
In addition, although electron carrier chain and ATP synthesis were up-regulated under
conditions, a higher number of subunits and a higher abundance of proteins related to these
pathways were detected in P. brasiliensis derived from non-activated macrophages (Table 3).
We evaluated the mitochondrial activity of P. brasiliensis by labeling with mitotracker and
rhodamine. The latter, dyes mitochondria according to membrane potential. The fluorescence
intensity of rhodamine was highest for yeast cells during infection of non-activated
macrophages, which indicates an increased mitochondrial activity (Figure 3). Among the
functions performed by mitochondria, we can highlight the supply of cellular energy, cross-talk
between pro-survival and pro-death pathways and also role in the response to metabolic stress
47
(Nunnari and Suomalainen, 2012). In proteomic analysis of Paracoccidioides mitochondria
were detected detoxification enzymes as superoxide dismutase, cytochrome c peroxidase and
thioredoxin (Casaletti et al., 2017). A study with Aspergillus nidulans demonstrated that the
mutant strain of a gene related to mitochondrial function and cellular respiration, caused a
decrease in the mass and function of mitochondria and of oxidative phosphorylation process,
which influenced glucose uptake. This deletion also led to an increase in endogenous ROS
levels, which is toxic to the cell (Krohn et al., 2014). These data reinforce that the interior of
non-activated macrophages is favorable to the metabolic activity of P. brasiliensis.
In synthesis, all the data indicate that the P. brasiliensis, adapts rapidly within not activated
macrophages, where it can multiply and spread through the tissues of the host. The data
corroborate with clinical data, that report patients with acute or chronic PCM presenting low
production of phagocyte activating cytokines, such as INF-, IL-12 and TNF- (Benard et al.,
2001). These cytokines play an important role in the microbicidal activity of macrophages,
recruitment of defense cells to the site of infection and formation of efficient granulomas to
contain the dissemination of Paracoccidioides (Nishikaku et al., 2011). This comparative
proteomic study contributes to the understanding of factors that can lead to the inhibition or
evolution of PCM as well as its pathogenesis.
CONCLUDING REMARKS
In this study, we observe that P. brasiliensis can survive inside non-activated macrophages, but
it is not able to adapt to the intracellular environment of macrophages activated by INF-.
Comparative proteomic analysis of the fungus during phagocyte infection revealed metabolic
peculiarities that favor the survival of P. brasiliensis in the intracellular environment of non-
activated macrophages. In both conditions the fungus increased the expression of enzymes
related to amino acid degradation, TCA and glyoxylate cycle, antioxidant enzymes and
virulence factors. However, activation of the pentoses phosphate pathway, methylcytrate cycle,
synthesis of cell wall precursors and intense mitochondrial activity was observed only in yeast
cells recovered from non-activated macrophages. These pathways may favor the viability of the
fungus in relation to yeasts internalized by activated phagocytes. These data indicate that the
process of phagocytosis by non-activated macrophages may be a strategy used by P. brasiliensis
to promote their evasion to the immune system and dissemination by deep host organs.
AUTHOR CONTRIBUTIONS
CdAS conceived and finalized the manuscript. EGAC and DSA performed the experiments.
LCB carried out proteomic data. EGAC, DSA, LCB, JAPR, CLB, MAPO and CdAS designed
the study, discussed, analyzed, and interpreted the data and wrote the manuscript.
ACKNOWLEDGMENTS
This work at Universidade Federal de Goiás was supported by grants from Conselho Nacional
de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do
Estado de Goiás (FAPEG), Instituto Nacional de Ciência e Tecnologia da Interação Patógeno
Hospedeiro (IPH) and Programa Nacional de Pós-Doutorado - Coordenação de
Aperfeiçoamento de Pessoal de Nível Superior (PNPD-CAPES). This work is part of the INCT
48
program of Strategies of Host Pathogen Interaction (HPI) and is part of the EGAC Doctoral
Thesis.
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PLoS Pathog. 8, e1002713. doi:10.1371/journal.ppat.1002713.
55
Figure 1. P. brasiliensis, Pb18 infection in alveolar macrophages. P. brasiliensis, Pb18 was
recovered from AMJ2-C11 activated (Pb18_A) and non-activated (Pb18_NA) alveolar
macrophages, by INF-γ after: 3 h, 6 h, 9 h and 12 h of interaction. The viable cells recovered
from macrophages were determined based on the number of colony-forming units (CFU). The
error bars indicate the mean ± standard deviation of the values obtained from the triplicate of
independent experiments. *: significantly different results; P value ≤0.05.
56
Figure 2. Evaluation of cell wall components of P. brasiliensis Pb18 recovered from
alveolar macrophages. The yeast cells recovered of macrophages were incubated with (A)
aniline blue to evaluate the contents of glucans; (C) concanavalin A to evaluate the glycosylated
proteins and (E) calcofluor white to evaluate chitin amount in the cell wall. (B, D and F)
Fluorescence intensity graph. The values of fluorescence intensity (in pixels) and the standard
error of each analysis were used to plot the graph. Data are expressed as mean ± standard error
(represented using error bars). * Significantly different comparison between treated cells in a P
value of ≤ 0.05. All representative images were obtained with 400X magnified.
57
Figure 3. Mitochondrial activity of P. brasiliensis, Pb18 recovered from alveolar
macrophages. (A) Pb18 yeast cells recovered from activated (Pb18_A) and non-activated
macrophages (Pb18_NA) were incubated with MitoTracker Green FM and rosamine
Mitotracker probes. The mitochondrial activity was evaluated by using rhodamine as a dye
for mitochondrial membrane potential. (B) The rhodamine fluorescence intensity was
measured using the AxioVision Software (Carl Zeiss). The values of fluorescence intensity
(in pixels) and the standard deviation of each analysis were used to plot the graph. Data are
expressed as mean ± standard deviation (represented using error bars) of the minimum of
100 cells for each microscope slide, in triplicates, for each condition. * Significantly
different comparison between treated cells in a P value of ≤ 0.05. All representative images
were taken using an Axioscope (Carl Zeiss) microscope and 400X magnified.
58
Table 1. Up-regulated proteins putatively related to cell rescue, defense and virulence in Pb18_A and Pb18_NA
Accession number1 Protein description Pb18_A2 Pb18_NA2
Defense and virulence
PADG_01479 gamma-glutamyltransferase 1.76 2.46
PADG_06314 carboxypeptidase Y - 1.97
PADG_07460 vacuolar aminopeptidase 1.53 1.82
PADG_07422 serine proteinase 1.8 2.17
PADG_07674 carbonic anhydrase - 1.55
Stress response
PADG_00778 Hsp70 - 1.43
PADG_02030 Hsp90 co-chaperone Cdc37 2..22 2.71
PADG_02785 heat shock protein Hsp88 1.5 1.48
PADG_03963 30 kDa heat shock protein 1.84 2.05
PADG_04379 heat shock protein STI1 1.99 2.09
Detoxification
PADG_01551 thioredoxin reductase 1.56 1.84
PADG_01954 superoxide dismutase 2 Fe-Mn, mitochondrial 1.99 4.72
PADG_07418 superoxide dismutase 1 Cu-Zn, cytosolic 1.99 2.78 1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated and non-activated
macrophages, by the abundance in control. Proteins with a minimum fold change of 40% were considered regulated.
59
Table 2. Up-regulated proteins putatively related to synthesis of cell wall componets in Pb18_A and Pb18_NA
Accession number1 Protein description Pb18_A2 Pb18_NA2
N-glycosylation
PADG_07523 neutral alpha-glucosidase AB 1.91 2.54
PADG_04761 mannosyl-oligosaccharide glucosidase 1.84 2.25
PADG_04148 alpha-mannosidase - 1.7
UDP-sugars
PADG_00912 UDP-galactopyranose mutase - 2.46
PADG_04374 UTP-glucose-1-phosphate uridylyltransferase * *
PADG_04312 UDP-N-acetylglucosamine pyrophosphorylase - 1.4
Mannan
PADG_03943 phosphomannomutase * * 1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated and non-activated
macrophages, by the abundance in control. Proteins with a minimum fold change of 40% were considered regulated.
*Proteins detected in P. brasiliensis Pb18 only during respective macrophage infection.
60
Table 3. Up-regulated proteins related with mitochondrial activity in Pb18_A and Pb18_NA
Accession number1 Protein description Pb18_A2 Pb18_NA2
ATP synthesis
PADG_04729 ATP synthase subunit D, mitochondrial 2.09 3.24
PADG_07042 ATP synthase F1, delta subunit * *
PADG_07813 ATP synthase F1, gamma subunit 2.38 2.02
PADG_08349 ATP synthase subunit beta, mitochondrial 3.38 2.92
PADG_07789 ATP synthase subunit delta, mitochondrial 1.84 2.53
PADG_07964 vacuolar ATP synthase subunit E - 1.52
Electron transport and membrane-associated energy conservation
PADG_11981 V-type proton ATPase catalytic subunit A 2.36 1.81
PADG_04319 V-type ATPase, G subunit 1.75 2.08
PADG_00688 F-type H+-transporting ATPase subunit H 2.11 2.56
PADG_03175 V-type proton ATPase subunit F 1.87 2.88
PADG_08391 plasma membrane ATPase - 1.41
PADG_07081 electron transfer flavoprotein subunit alpha - 1.74
PADG_11468 electron transfer flavoprotein beta-subunit * *
PADG_06978 cytochrome C - 1.68
PADG_04397 cytochrome c oxidase subunit 4, mitochondrial 2.88 3.55
PADG_05750 putative cytochrome c oxidase subunit Via 2.5 3.89
PADG_02745 NADH-ubiquinone oxidoreductase Fe-S protein 6 - *
PADG_07749 NAD(P)H:quinone oxidoreductase, type IV 1.59 2.34
PADG_01366
NADH-ubiquinone oxidoreductase 1 alpha subcomplex
subunit 5 1.82 2.21 1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated and non-activated
macrophages, by the abundance in control. Proteins with a minimum fold change of 40% were considered regulated.
*Proteins detected in P. brasiliensis Pb18 only during respective macrophage infection.
61
Supplementary Figure 1. Proteomic data quality analysis. (A) Peptide detection type. The pie graphs show the percentage of peptides matched
against the P. brasiliensis, Pb18 database by PLGS (PepFrag 1 and PepFrag 2), variables modifications (VarMod), fragmentation that occurred on
ionization source (InSource), missed cleavage performed by trypsin (Missed Cleavage) and Neutral loss H2O and NH3 corresponding to water and
ammonia precursor losses. The SpotFire Decision Site 8.0 v program was used. (B) Peptide mass accuracy analyzes. Peptides data were used to
make the bar graph showing the accuracy of mass for peptides. (C) Detection of dynamic range of proteomic analyzes. The dynamic range the
proteomic experiments for each condition was determined. Regular, reverse and standard proteins were indicated by white, grey and black circles,
respectively. The regular and reverse proteins indicate identified proteins using regular and reverse genomic database from P. brasiliensis, Pb18.
The standard protein was used to normalize the expression data and compare the control and infection related proteins. Our data showed an
acceptable quantification to standard protein between both conditions.
62
Supplementary Figure 2. Immunoblotting analysis. (A) Proteins (50 µg) of
P.brasiliensis, Pb18 yeast cells recovered from macrophages activated (Pb18_A) and
non-activated (Pb18_NA) and control were analyzed by western blotting. The proteins
were fractionated by one-dimensional gel electrophoresis. The proteins were
transferred a nitrocellulose membrane and incubated with antibodies directed to
isocitrate lyase (ICL) and 30 kDa heat shock protein (HSP30) produced in mouse.
Immunoglobulin G (IgG) coupled to alkaline phosphatase was the secondary antibody.
The reaction was developed using 5-Bromo-4-chloro-3-indolyl phosphate (BCIP) and
Nitro Blue Tetrazolium (NBT). (B) Densitometry of immunoblotting performed using
the ImageJ 1.51 software. Pixel intensity generated and expressed as arbitrary units
from Raw Tiff images. The error bars indicate the mean ± standard deviation of the
values obtained from the triplicate of independent experiments. *: significantly
different results; P value ≤0.05.
63
Supplementary Table 1. Up-regulated proteins of P. brasiliensis, Pb18 after 6 h infection in activated alveolar macrophages by INF-γ
Accession number1 Protein description Score2 Pb18_A x CTRL
Ratio3
Functional categories4
AMINO ACID METABOLISM
Amino acid degradation
PADG_00822 glutaminase A 651.49 *
PADG_04686 glutamine synthetase 496.27 *
PADG_05922 glutamate carboxypeptidase 3500.33 1.75
PADG_04516 NADP-specific glutamate dehydrogenase 651.57 1.59
PADG_05085 1-pyrroline-5-carboxylate dehydrogenase 3215.32 1.44
PADG_06546 puromycin-sensitive aminopeptidase 499.08 1.59
PADG_04689 N-acetyl-gamma-glutamyl-phosphate reductase 686.12 *
Amino acid biosynthesis
PADG_07029 acetylornithine aminotransferase 522.48 *
PADG_00888 argininosuccinate synthase 652.7 1.97
PADG_01615 homocitrate synthase, mitochondrial 559.95 3.18
PADG_08376 aspartate-semialdehyde dehydrogenase 696.7 1.68
PADG_05111 serine hydroxymethyltransferase, cytosolic 1716.94 2.01
PADG_02914 glycine cleavage system T protein 1568.09 1.4
64
PADG_05896 phosphoglycerate dehydrogenase 313.7 *
PADG_02726 cysteine synthase 898.45 1.43
PADG_03522 methylthioadenosine phosphorylase 479.79 1.44
PADG_08662 cystathionine beta-lyase 398.91 *
PADG_08328 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase 4196.01 1.89
PADG_07907 acetolactate synthase 1231.54 1.46
PADG_07609 dihydroxy-acid dehydratase 505.55 2.18
PADG_03114 3-deoxy-7-phosphoheptulonate synthase 523.88 *
NITROGEN METABOLISM
PADG_06490 formamidase 1170.68 1.47
PADG_07010 urease accessory protein UreG 643.89 *
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
PADG_08066 purine nucleoside phosphorylase I, inosine and guanosine-specific 1433.7 1.46
PADG_01424 inosine-uridine preferring nucleoside hydrolase 435.72 *
PADG_02246 adenosine kinase 1864.44 1.43
PADG_04828 adenylosuccinate lyase 614.73 1.91
PADG_06297 phosphoribosylamine-glycine ligase 410.55 *
PADG_07585 inosine-5'-monophosphate dehydrogenase 914.88 1.8
65
PADG_07970 dihydroorotase, homodimeric type 580.91 *
C-COMPOUND AND CARBOHYDRATE METABOLISM
PADG_04374 UTP-glucose-1-phosphate uridylyltransferase 722.26 *
PADG_11132 Phosphoglucomutase 367.02 *
PADG_03943 Phosphomannomutase 388.32 *
PADG_04761 mannosyl-oligosaccharide glucosidase 667.61 1.84
PADG_07523 neutral alpha-glucosidase AB 600.23 1.91
PENTOSE-PHOSPHATE PATHWAY
PADG_03651 6-phosphogluconate dehydrogenase, decarboxylating 1 567.53 2.27
GLYCOLYSIS/GLUCONEOGENESIS
PADG_03813 Hexokinase 587.08 2.45
PADG_07950 glucokinase 433.94 1.78
PADG_00451 glucose-6-phosphate isomerase 919.44 1.87
PADG_05109 2,3-bisphosphoglycerate-independent phosphoglycerate mutase 1255.36 1.71
PADG_08503 phosphoenolpyruvate carboxykinase 3649.92 1.55
PYRUVATE METABOLISM
66
PADG_01797 pyruvate dehydrogenase protein X component 576.86 2.05
PADG_04165 pyruvate dehydrogenase complex component Pdx1 691.24 1.43
PADG_06494 dihydrolipoyl dehydrogenase 3577,44 1.4
TRICARBOXYLIC ACID CYCLE
PADG_08387 citrate synthase, mitochondrial 665.29 1.84
PADG_11845 aconitate hydratase, mitochondrial 2588.05 1.76
PADG_00317 succinyl-CoA ligase subunit beta 356.85 4.09
PADG_01762 oxoglutarate dehydrogenase (succinyl-transferring), E1 component 566.44 1.40
PADG_00052 succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial 1339.48 1.61
PADG_08013 succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrial 768.68 2.48
PADG_08119 fumarate hydratase, mitochondrial 596.3 2.31
METHYLCITRATE CYCLE
PADG_04718 2-methylcitrate dehydratase 11210.66 1.55
PADG_04709 methyl-isocitrate lyase 900.43 1.55
GLYOXALATE CYCLE
PADG_01483 isocitrate lyase 1754.4 1.4
67
ELECTRON TRANSPORT AND RESPIRATION
PADG_01366 NADH-ubiquinone oxidoreductase 3175.48 1.82
PADG_07749 NAD(P)H:quinone oxidoreductase, type IV 41840.44 1.59
PADG_05750 putative cytochrome c oxidase subunit Via 4381.04 2.5
PADG_04397 cytochrome c oxidase subunit 4, mitochondrial 1429.9 2.88
PADG_11468 electron transfer flavoprotein beta-subunit 471.59 *
PADG_11981 V-type proton ATPase catalytic subunit A 430.31 2.36
PADG_03175 V-type proton ATPase subunit F 877.44 1.87
PADG_04319 V-type ATPase, G subunit 448.84 1.75
PADG_00688 F-type H+-transporting ATPase subunit H 2589.81 2.11
PADG_08391 plasma membrane ATPase 442.15 1.76
ATP SYNTHESIS
PADG_07042 ATP synthase F1, delta subunit 514.91 *
PADG_04729 ATP synthase subunit D, mitochondrial 2219.02 2.09
PADG_07813 ATP synthase F1, gamma subunit 1367.33 2.38
PADG_08349 ATP synthase subunit beta, mitochondrial 17882.4 3.38
PADG_07789 ATP synthase subunit delta, mitochondrial 2026.9 1.84
FATTY ACID BIOSYNTHESIS
68
PADG_00255 fatty acid synthase subunit beta dehydratase 889.54 1.75
PADG_05783 farnesyl pyrophosphate synthetase 3596.45 *
DEGRADATION OF KETONE BODIES
PADG_04939 succinyl-CoA:3-ketoacid-coenzyme A transferase subunit B 1703.1 1.68
METABOLISM OF VITAMINS. COFACTORS. AND PROSTHETIC GROUPS
PADG_00443 dihydropteroate synthase 1863.88 1.52
PADG_01886 adenosylhomocysteinase 3209.32 1.69
PADG_00513 2-succinylbenzoate-CoA ligase 567.59 *
SECONDARY METABOLISM
PADG_04899 metallo-beta-lactamase domain-containing protein 1103.5 *
PADG_08108 coproporphyrinogen III oxidase 526.04 *
PADG_04636 dienelactone hydrolase family protein 1042.89 1.43
PADG_04175 inorganic pyrophosphatase 2372.74 1.41
SIGNAL TRANSDUCTION
PADG_02017 calmodulin 917.7 2.58
PADG_01565 calnexin 1309.53 1.89
69
PADG_01243 rab GDP-dissociation inhibitor 838.81 2.15
PADG_05517 rho GDP-dissociation inhibitor 620.8 2.69
PADG_04440 14-3-3-like protein 2 22781.86 1.41
PADG_05608 GTP-binding protein ypt7 512.66 *
PADG_03544 ser/Thr protein phosphatase family protein 456.22 1.99
CYTOSKELETON
PADG_00945 actin like protein 2/3 complex, subunit 5 1210.25 1.52
PADG_00422 actin cytoskeleton protein (VIP1) 3501.22 1.69
PADG_05538 actin 517.74 1.99
PADG_05239 tubulin-specific chaperone Rbl2 949.14 1.64
CELL CYCLE
PADG_05683 cell division control protein 48 3099.11 1.95
PADG_05875 centromere/microtubule-binding protein cbf5 473.9 *
PADG_04056 14-3-3 family protein épsilon 11315.76 1.43
PADG_07930 ARP2/3 complex 20 kDa subunit 1565.37 *
DNA PROCESSING
PADG_02683 UV excision repair protein Rad23 1951.91 1.58
70
PADG_00656 non-histone chromosomal protein 6 6855.17 1.64
PADG_00718 histone chaperone asf1 625.3 1.89
PADG_00872 Histone 3651.58 3.45
PADG_00873 histone H3 2817.56 3.93
PADG_07134 histone H4 3673.03 4.13
PADG_08423 RuvB-like helicase 2 443.26 *
TRANSCRIPTION
PADG_11711 ATP-dependent RNA helicase eIF4A 523.13 3.59
PADG_00067 polymerase II polypeptide D 1667.1 *
PADG_01151 DNA-directed RNA polymerase II subunit RPB11 475.45 *
PADG_04657 nascent polypeptide-associated complex subunit beta 2060.21 3.32
PADG_04730 nascent polypeptide-associated complex subunit alpha 2511.44 1.89
PADG_07888 eukaryotic translation initiation factor 5A 938.57 *
PADG_02825 small nuclear ribonucleoprotein Lsm8 936.12 1.52
PADG_03696 nuclear polyadenylated RNA-binding protein Nab2 580.16 *
PADG_04981 nucleoporin p58/p45 881.57 *
PADG_05393 mRNA decapping hydrolase 487.75 2.8
PADG_04672 ATP-dependent RNA helicase SUB2 1324.65 *
PADG_04796 pre-mRNA-splicing factor rse1 687.99 *
71
PADG_06734 U6 snRNA-associated Sm-like protein LSm7 2200.35 *
PADG_00676 RNApii degradation factor def1 568.85 1.89
PADG_11958 small nuclear ribonucleoprotein 860.29 *
PADG_11062 bZIP transcription factor 817.23 2.22
PROTEIN SYNTHESIS
PADG_02759 ribosome recycling factor 787.37 3.42
PADG_00784 40S ribosomal protein S0 4550.38 1.43
PADG_00995 ubiquitin-40S ribosomal protein S27a 2933.72 2.33
PADG_02056 ribosomal protein L7/L12 6872.26 1.93
PADG_02446 60S acidic ribosomal protein P2 14965.78 5.00
PADG_04030 60S acidic ribosomal protein P0 1428.5 1.89
PADG_05939 60S ribosomal protein L27a 1823.21 1.8
PADG_07891 ubiquitin-60S ribosomal protein L40 2561.7 2.58
PADG_08244 60S acidic ribosomal protein P1 14587.27 1.58
PADG_08605 40S ribosomal protein S28 5195.73 1.71
PADG_02206 DnaJ domain protein Psi 707.66 1.5
PADG_01949 translation elongation factor Tu 3152.3 1.64
PADG_02296 eukaryotic translation initiation factor 3 subunit F 1272.06 *
PADG_04083 eukaryotic translation initiation factor 2 subunit gamma 904.31 *
72
PADG_07977 eukaryotic translation initiation factor 1A, Y-chromosomal 703.74 *
PADG_08033 eukaryotic translation initiation factor 3 subunit B 557.3 1.63
PADG_01558 histidyl-tRNA synthetase 469.31 2.03
PADG_07582 phenylalanine-tRNA ligase, alpha subunit 691.71 1.75
PADG_00066 tRNA (guanine(37)-N1)-methyltransferase 384.07 *
PROTEIN FOLDING, MODIFICATION, DESTINATION
PADG_07515 UBX domain-containing protein 573.32 1.49
PADG_01852 small glutamine-rich tetratricopeptide repeat-containing protein 991 2.2
PADG_04034 chaperone DnaJ 924.8 1.5
PADG_02637 ubiquitin-conjugating enzyme 795.87 *
PADG_01605 polyubiquitin 2988.76 2.24
PADG_03424 ubiquitin-activating enzyme E1 1565.4 1.52
PADG_07558 ubiquitin carboxyl-terminal hydrolase 735.58 1.49
PROTEIN DEGRADATION
PADG_00599 26S protease regulatory subunit 6A 436.54 *
PADG_01935 26S proteasome non-ATPase regulatory subunit 10 726.98 1.5
PADG_03192 proteasome component PUP2 484.74 1.59
PADG_03221 thimet oligopeptidase 769.99 2.03
73
PADG_03735 proline iminopeptidase 574.84 *
PADG_03967 proteasome component C5 3676.41 1.44
PADG_04952 AAA ATPase 491.31 *
PADG_05160 dipeptidyl-peptidase 435.87 1.87
PADG_04167 aspartyl aminopeptidase 456.35 1.43
PADG_05193 xaa-Pro aminopeptidase 465.6 *
PADG_05560 26S proteasome regulatory subunit rpn-1 757.72 *
PADG_05820 xaa-Pro aminopeptidase 606.66 1.59
PADG_06766 mitochondrial-processing peptidase subunit beta 944.78 3.18
PADG_05837 E3 ubiquitin ligase complex SCF subunit sconC 3142.06 1.55
PROTEIN BINDING
PADG_07884 polyadenylate-binding protein, cytoplasmic and nuclear 459.2 2.63
PADG_07249 actin binding protein 460.77 1.99
PADG_01529 TPR repeat protein 640.89 *
CELLULAR TRANSPORT
PADG_03203 BAR domain-containing protein 1831.27 1.71
PADG_08188 vacuolar-sorting protein snf7 895.93 *
74
CELL RESCUE, DEFENSE AND VIRULENCE
PADG_01551 thioredoxin reductase 976.26 1.56
PADG_01954 superoxide dismutase 2 Fe-Mn 1379.02 1.99
PADG_07418 superoxide dismutase 1 Cu-Zn 2464.72 1.99
PADG_02030 Hsp90 co-chaperone Cdc37 2932.07 2.22
PADG_02785 heat shock protein Hsp88 9518.65 1.5
PADG_03963 30 kDa heat shock protein 6432.9 1.84
PADG_04379 heat shock protein STI1 4552.74 1.99
PADG_01479 gamma-glutamyltransferase 545.4 1.76
PADG_07422 serine proteinase 380.41 1.8
PADG_07460 vacuolar aminopeptidase 487.7 1.53
CELL DEATH
PADG_06087 programmed cell death protein 5 578.79 2.22
UNCLASSIFIED
PADG_06289 hypothetical protein 749.22 1.4
PADG_03869 hypothetical protein 785.98 *
PADG_03827 hypothetical protein 2531.19 *
PADG_01010 hypothetical protein 690.72 2.20
75
PADG_01871 hypothetical protein 725.03 *
PADG_03210 hypothetical protein 1477.99 1.85
PADG_00496 hypothetical protein 515.07 *
PADG_08480 hypothetical protein 646.53 3.85
PADG_11936 hypothetical protein 1140.44 *
PADG_02307 hypothetical protein 740.98 *
PADG_04442 hypothetical protein 452.53 *
PADG_04229 hypothetical protein 583.82 1.56
PADG_07627 4-carboxymuconolactone decarboxylase family protein 628.84 1.93
PADG_12437 EF hand domain-containing protein 391.93 *
PADG_05837 E3 ubiquitin ligase complex SCF subunit sconC 3142.06 1.55
PADG_03526 M protein repeat protein 467.91 *
1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2PLGS score is the result of different mathematical models for peptide and fragment assign prediction. Acceptable score values consider protein
identification with a minimum confidence level of 95% and a false discovery rate of 6%. 3Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated macrophages by the
abundance in control. Proteins with a minimum fold change of 40% were considered regulated. 4Biological process of differentially expressed proteins from MIPS (http://mips.helmholtz-muenchen.de/funcatDB/) and Uniprot databases
(http://www.uniprot.org/).
* Proteins detected in P. brasiliensis Pb18 only during activated macrophage infection.
76
Supplementary Table 2. Down-regulated proteins of P. brasiliensis. Pb18 after 6 h infection in activated alveolar macrophages by INF-γ
Accession number1 Protein description Score2 Pb18_A x CTRL
Ratio3
Functional categories4
AMINO ACID DEGARADATION
PADG_02214 4-aminobutyrate aminotransferase 4656.87 0.44
PADG_03627 2-oxoisovalerate dehydrogenase subunit beta 674.79 0.64
PADG_03466 3-hydroxyisobutyrate dehydrogenase 504.5 *
PADG_07369 isovaleryl-CoA dehydrogenase 3828.73 0.52
PADG_07370 methylcrotonoyl-CoA carboxylase beta chain 1047.22 0.6
PADG_00637 arginase 1161.3 0.37
PADG_01418 cysteine dioxygenase 767.22 *
PADG_03686 aspartate aminotransferase 395.76 *
PADG_00832 adenylosuccinate synthetase 969.84 *
PADG_01718 saccharopine dehydrogenase [NADP+, L-glutamate-forming] 584.09 *
PADG_08468 4-hydroxyphenylpyruvate dioxygenase 5519.57 0.71
PADG_08464 maleylacetoacetate isomerase 1624.24 0.71
PADG_00215 aromatic-L-amino-acid decarboxylase 579.63 *
PADG_08466 homogentisate 1,2-dioxygenase 1254.23 0.53
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
77
PADG_04288 endoribonuclease L-PSP 22381.84 0.67
C-COMPOUND AND CARBOHYDRATE METABOLISM
PADG_06221 formate dehydrogenase 632.87 *
PENTOSE-PHOSPHATE PATHWAY
PADG_07420 transaldolase 3551.69 0.71
GLYCOLYSIS / GLUCONEOGENESIS
PADG_02411 glyceraldehyde-3-phosphate dehydrogenase 29527.63 0.42
PADG_01896 phosphoglycerate kinase 6553.54 0.58
PYRUVATE METABOLISM
PADG_00714 pyruvate decarboxylase 2477.21 0.61
PADG_03276 S-(hydroxymethyl)glutathione dehydrogenase 1082.77 *
FERMENTATION
PADG_00171 L-lactate dehydrogenase 3625.04 0.71
TRICARBOXYLIC-ACID PATHWAY
PADG_04994 citrate synthase subunit 1 2691.59 0.63
78
METHYLCITRATE CYCLE
PADG_04710 2-methylcitrate synthase, mitochondrial 1868.25 0.65
ELECTRON TRANSPORT AND RESPIRATION
PADG_08394 cytochrome b-c1 complex subunit 2 904.65 0.61
OXIDATION OF FATTY ACIDS
PADG_01209 enoyl-CoA hydratase 5708.9 0.36
PADG_03194 3-ketoacyl-CoA thiolase B 2030.96 0.57
PADG_01687 3-ketoacyl-CoA thiolase 3955.45 0.67
PADG_03449 isopentenyl-diphosphate delta-isomerase 795.96 *
PADG_04343 short chain dehydrogenase/reductase 620.43 *
PADG_02751 acetyl-CoA acetyltransferase 2879.73 0.41
SECONDARY METABOLISM
PADG_02981 ThiJ/PfpI family protein 2110.74 0.65
SIGNAL TRANSDUCTION
PADG_11275 CMGC/MAPK protein kinase 439.81 *
PADG_00172 ras-like GTP-binding protein 506.63 *
79
CELL CYCLE
PADG_07733 ARP2/3 complex 34 kDa subunit 693.88 *
PADG_02763 cyclin-dependent kinase regulatory subunit 763.95 *
PROTEIN SYNTHESIS
PADG_00333 40S ribosomal protein S16 1144.09 0.71
PADG_00335 40S ribosomal protein S14 4602.27 0.66
PADG_00354 40S ribosomal protein S17 1524.81 0.51
PADG_00942 40S ribosomal protein S7 4390.69 0.63
PADG_01083 60S ribosomal protein L32 1109.4 0.44
PADG_01267 40S ribosomal protein S11 5706.97 0.41
PADG_01281 mitochondrial 37S ribosomal protein MRPS8 463.22 *
PADG_01407 40S ribosomal protein 7497.56 0.62
PADG_01654 40S ribosomal protein S6-A 2963.94 0.58
PADG_01914 60S ribosomal protein L35 1408.15 0.67
PADG_02445 40S ribosomal protein S15 6405.8 0.58
PADG_02797 mitochondrial 54S ribosomal protein YmL3 428.68 *
PADG_03315 40S ribosomal protein S4 3899.5 0.58
PADG_03326 40S ribosomal protein S9 4494.77 0.39
PADG_03778 60S ribosomal protein L10-A 3782.16 0.55
80
PADG_03781 60S ribosomal protein L30 2485.54 0.71
PADG_12253 60S ribosomal protein L3 1750.4 0.63
PADG_12365 40S ribosomal protein S8-A 2524.96 0.53
PADG_03856 60S ribosomal protein L15 2106.51 0.48
PADG_04106 60S ribosomal protein L11 4743.63 0.50
PADG_07469 RNase III domain-containing protein 465.89 *
PADG_04848 60S ribosomal protein L8-B 6589.56 0.68
PADG_05025 ribosomal protein L24 1716.08 *
PADG_05338 60S ribosomal protein L18-B 4386.56 0.2
PADG_06313 40S ribosomal protein S18 2306.16 0.57
PADG_06525 40S ribosomal protein S1 4906.3 0.64
PADG_06680 40S ribosomal protein S2 3503.9 0.61
PADG_06838 40S ribosomal protein S5 5075.18 0.53
PADG_07583 40S ribosomal protein S21 3306.23 0.65
PADG_07803 60S ribosomal protein L12 4692.42 0.65
PADG_07870 30S ribosomal protein S7 638.76 *
PADG_08213 ribosomal protein S2 593.74 *
PADG_08602 40S ribosomal protein S2 3621.3 0.46
PADG_11832 60S ribosomal protein L31 3256.39 0.39
PADG_00355 40S ribosomal protein S17 802.28 *
PADG_00692 elongation factor 1-alpha 7568.61 0.29
81
PADG_06265 elongation factor 1 gamma domain-containing protein 5531 0.57
PADG_08125 elongation factor 2 3952.23 0.48
PADG_07105 arginine-tRNA ligase 554.11 *
PADG_08472 lysine-tRNA ligase 503.01 *
PROTEIN FOLDING AND STABILIZATION
PADG_07715 hsp90-like protein 21307.69 0.35
PADG_08369 hsp60-like protein 31486.72 0.69
PROTEIN DEGRADATION
PADG_03727 proteasome component PUP1 2198.59 0.67
CELLULAR TRANSPORT
PADG_02833 ADP-ribosylation fator 2358.28 *
CELL RESCUE, DEFENSE AND VIRULENCE
PADG_00324 catalase P 1207.99 0.60
PADG_03095 mitochondrial peroxiredoxin PRX1 2391.55 0.67
PADG_03163 cytochrome c peroxidase mitochondrial 7277.58 0.47
PADG_08651 peroxisomal hydratase-dehydrogenase-epimerase 724.34 *
PADG_07946 peroxisomal matrix protein 4560.11 0.6
82
PADG_02048 nitroreductase family protein 636.86 *
UNCLASSIFIED
PADG_00344 hypothetical protein 1008.02 *
PADG_00211 hypothetical protein 2047.72 *
PADG_00921 hypothetical protein 2142.99 0.637628159
PADG_01488 hypothetical protein 1980.81 *
PADG_03660 hypothetical protein 860.43 *
PADG_02764 hypothetical protein 2170.39 0.71
PADG_08212 hypothetical protein 2557.19 0.26
PADG_08368 hypothetical protein 716.93 0.34
PADG_01849 GTP-binding protein YchF 416.64 *
PADG_07287 WD repeat-containing protein 579.21 *
PADG_08483 chromobox protein 1 411.76 0.58
PADG_07412 DUF1479 domain-containing protein 861.11 *
PADG_05356 isochorismatase domain-containing protein 871.15 0.55
PADG_04559 progesterone binding protein 1333.07 *
PADG_06196 12-oxophytodienoate reductase 2364.81 0.63
1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2PLGS score is the result of different mathematical models for peptide and fragment assign prediction. Acceptable score values consider protein
identification with a minimum confidence level of 95% and a false discovery rate of 6%.
83
3Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated macrophages by the
abundance in control. Proteins with a minimum fold change of 40% were considered regulated. 4Biological process of differentially expressed proteins from MIPS (http://mips.helmholtz-muenchen.de/funcatDB/) and Uniprot databases
(http://www.uniprot.org/).
* Proteins detected in P. brasiliensis Pb18 only in the control condition.
84
Supplementary Table 3. Up-regulated proteins of P. brasiliensis. Pb18 after 6 h infection in non-activated alveolar macrophages by INF-γ
Accession number1 Protein description Score2 Pb18 x CTRL
Ratio3
Functional categories4
AMINO ACID METABOLISM
Amino acid degradation
PADG_00822 glutaminase A 439.09 *
PADG_04516 NADP-specific glutamate dehydrogenase 1576.71 1.90
PADG_06429 ketol-acid reductoisomerase, mitochondrial 1960.68 1.82
PADG_05922 glutamate carboxypeptidase 5325.3 2.09
PADG_05085 1-pyrroline-5-carboxylate dehydrogenase 1535.16 1.62
PADG_06546 puromycin-sensitive aminopeptidase 739.86 1.43
PADG_03020 alanine-glyoxylate aminotransferase 565.67 1.98
PADG_08465 Fumarylacetoacetase 718.43 1.48
PADG_03671 phenylpyruvate tautomerase 789.12 1.5
Amino acid biosynthesis
PADG_06382 acetyl-CoA acetyltransferase 3416.52 1.65
PADG_04689 N-acetyl-gamma-glutamyl-phosphate reductase 532.7 *
PADG_00602 type I protein arginine methyltransferase 1103.03 1.8
PADG_01615 homocitrate synthase, mitochondrial 2141.48 2.39
85
PADG_08376 aspartate-semialdehyde dehydrogenase 2633.05 2.37
PADG_02914 glycine cleavage system T protein 1013.86 1.51
PADG_07609 dihydroxy-acid dehydratase 1382.4 2.73
PADG_07907 acetolactate synthase 2642.52 2.29
PADG_00663 homoserine dehydrogenase 898.23 1.51
PADG_04522 homoserine kinase 1291.2 *
PADG_02456 cystathionine gamma-lyase 645.01 1.47
PADG_05111 serine hydroxymethyltransferase, cytosolic 2403.18 2.44
PADG_05277 serine hydroxymethyltransferase 6324.08 1.64
PADG_00210 glycine dehydrogenase 3064.66 1.56
PADG_00402 betaine aldehyde dehydrogenase 453.52 1.45
PADG_08406 O-acetylhomoserine (thiol)-lyase 16850.46 2.01
PADG_03522 methylthioadenosine phosphorylase 1437.78 3.01
PADG_08328 5-methyltetrahydropteroyltriglutamate-homocysteine S-methyltransferase 9967.91 2.37
PADG_08662 cystathionine beta-lyase 345.82 *
PADG_02726 cysteine synthase 1818.8 1.76
PADG_01928 S-adenosylmethionine synthase 1737.8 1.47
PADG_07274 anthranilate synthase component 2 730.39 1.68
PADG_01530 guanine nucleotide-binding protein subunit beta-like protein 11353.25 1.48
86
UREA CYCLE
PADG_01305 argininosuccinate lyase 551.69 *
NITROGEN METABOLISM
PADG_00446 oxidoreductase 2-nitropropane dioxygenase family 1406.89 1.56
PADG_06490 formamidase 4731.69 2.02
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
PADG_02183 ADP-ribose pyrophosphatase 1018.86 1.72
PADG_02246 adenosine kinase 1023.67 1.75
PADG_04828 adenylosuccinate lyase 1267.14 1.97
PADG_07585 inosine-5'-monophosphate dehydrogenase 1285.04 1.97
C-COMPOUND AND CARBOHYDRATE METABOLISM
PADG_11132 Phosphoglucomutase 1205.72 1.61
PADG_00298 FGGY-family carbohydrate kinase 573.38 *
PADG_03278 inositol-3-phosphate synthase 687.16 *
PADG_04374 UTP-glucose-1-phosphate uridylyltransferase 934.38 *
PADG_07435 sorbitol utilization protein SOU2 3257.33 1.76
PADG_03943 Phosphomannomutase 736.23 *
87
PADG_00912 UDP-galactopyranose mutase 1876.92 2.46
PADG_04312 UDP-N-acetylglucosamine pyrophosphorylase 435.09 1.4
PADG_07523 neutral alpha-glucosidase AB 2916.74 2.54
PADG_04761 mannosyl-oligosaccharide glucosidase 1036.62 2.25
PADG_04148 alpha-mannosidase 1272.3 1.7
PADG_12426 1,4-alpha-glucan-branching enzyme 908.18 1.86
PENTOSE-PHOSPHATE PATHWAY
PADG_04604 Transketolase 1424.25 1.56
PADG_07771 6-phosphogluconolactonase 619.03 1.43
PADG_03651 6-phosphogluconate dehydrogenase, decarboxylating 1 1094.46 2.41
GLYCOLYSIS/GLUCONEOGENESIS
PADG_03813 Hexokinase 1973.12 1.44
PADG_07950 Glucokinase 622.95 1.87
PADG_00451 glucose-6-phosphate isomerase 526.87 1.77
PADG_05109 2,3-bisphosphoglycerate-independent phosphoglycerate mutase 709.59 1.63
PADG_04059 Enolase 29089.92 1.53
PADG_01278 pyruvate kinase 1317.95 1.43
PADG_08503 phosphoenolpyruvate carboxykinase 1337.49 1.63
88
PYRUVATE METABOLISM
PADG_01797 pyruvate dehydrogenase protein X componente 536.58 1.52
PADG_04165 pyruvate dehydrogenase complex component Pdx1 4691.21 2.12
TRICARBOXYLIC ACID CYCLE
PADG_08387 citrate synthase mitochondrial 567.91 1.46
PADG_11845 aconitate hydratase mitochondrial 1337.16 1.65
PADG_00317 succinyl-CoA ligase subunit beta 1165.76 2.65
PADG_04939 succinyl-CoA:3-ketoacid-coenzyme A transferase subunit B 1187.44 1.63
PADG_01762 oxoglutarate dehydrogenase (succinyl-transferring), E1 component 1134.35 1.59
PADG_00052 succinate dehydrogenase [ubiquinone] flavoprotein subunit, mitochondrial 2588.78 1.81
PADG_08119 fumarate hydratase, mitochondrial 949.77 2.25
PADG_08054 malate dehydrogenase, NAD-dependent 6213.22 1.46
METHYLCITRATE CYCLE
PADG_04710 2-methylcitrate synthase, mitochondrial 4668.51 1.95
PADG_04718 2-methylcitrate dehydratase 13900.44 1.53
PADG_04709 methyl-isocitrate lyase 1366.54 1.55
89
GLYOXALATE CYCLE
PADG_01483 isocitrate lyase 782.07 1.59
ELECTRON TRANSPORT AND RESPIRATION
PADG_07749 NAD(P)H:quinone oxidoreductase, type IV 63456.09 2.34
PADG_01366 NADH-ubiquinone oxidoreductase 1 alpha subcomplex subunit 5 8527.01 2.21
PADG_02745 NADH-ubiquinone oxidoreductase Fe-S protein 6 3903.78 *
PADG_06978 cytochrome C 2091.97 1.68
PADG_04397 cytochrome c oxidase subunit 4, mitochondrial 16957.84 3.55
PADG_05750 putative cytochrome c oxidase subunit Via 40028.16 3.89
PADG_07081 electron transfer flavoprotein subunit alpha 1912.68 1.74
PADG_11468 electron transfer flavoprotein beta-subunit 457.76 *
PADG_11981 V-type proton ATPase catalytic subunit A 452.37 1.81
PADG_04319 V-type ATPase, G subunit 1496.06 2.08
PADG_03175 V-type proton ATPase subunit F 5509.99 2.88
PADG_00688 F-type H+-transporting ATPase subunit H 1411.4 2.56
PADG_08391 plasma membrane ATPase 1062.2 1.41
ATP SYNTHESIS
PADG_07042 ATP synthase F1, delta subunit 2655.74 *
90
PADG_07813 ATP synthase F1, gamma subunit 5080.46 2.02
PADG_04729 ATP synthase subunit D, mitochondrial 10759.93 3.24
PADG_08349 ATP synthase subunit beta, mitochondrial 44454.03 2.92
PADG_07789 ATP synthase subunit delta, mitochondrial 18673.08 2.53
PADG_07964 vacuolar ATP synthase subunit E 866.17 1.52
FATTY ACID BIOSYNTHESIS
PADG_00254 fatty acid synthase subunit alpha 524.97 1.62
PADG_00255 fatty acid synthase subunit beta dehydratase 1306.32 2.15
PADG_05310 leukotriene A-4 hydrolase 2329.58 2.17
PADG_00608 formyl-coenzyme A transferase 457.47 1.93
PADG_05783 farnesyl pyrophosphate synthetase 752.27 *
METABOLISM OF VITAMINS, COFACTORS AND PROSTHETIC GROUPS
PADG_00443 dihydropteroate synthase 2037.91 1.55
PADG_01886 adenosylhomocysteinase 5114.94 2.08
PADG_04032 uroporphyrinogen decarboxylase 562.49 *
PADG_05947 nicotinate-nucleotide diphosphorylase (carboxylating) 11884.09 1.72
PADG_00513 2-succinylbenzoate-CoA ligase 484.5 *
91
SECONDARY METABOLISM
PADG_04175 inorganic pyrophosphatase 3036.59 1.62
PADG_04899 metallo-beta-lactamase domain-containing protein 614.27 *
PADG_04603 spermidine synthase 7353.23 1.45
PADG_08108 coproporphyrinogen III oxidase 714.31 *
PADG_04636 dienelactone hydrolase family protein 1618.93 1.56
PADG_08034 dienelactone hydrolase family protein 1892.29 2.09
SIGNAL TRANSDUCTION
PADG_02017 calmodulin 6723.5 2.7
PADG_01565 calnexin 1281.42 1.72
PADG_06273 calcineurin subunit B 845.86 *
PADG_04440 14-3-3-like protein 2 23558.55 1.68
PADG_04056 14-3-3 family protein épsilon 18174.25 1.9
CYTOSKELETON
PADG_00128 tubulin alpha-2 chain 1787.02 1.45
PADG_05239 tubulin-specific chaperone Rbl2 1188.96 1.70
PADG_00422 actin cytoskeleton protein 12255.21 2.37
PADG_02157 actin cytoskeleton-regulatory complex protein END 636.1 *
92
PADG_12076 actin beta/gamma 1 2871.4 1.71
PADG_05538 actin 2068.43 2.82
PADG_03219 myosin regulatory light chain cdc4 2427.08 1.9
PADG_08615 Tropomyosin 681.04 1.47
CELL CYCLE
PADG_12437 EF hand domain-containing protein 604.69 *
PADG_03073 nuclear movement protein nudC 8082.11 1.76
PADG_00849 nuclear segregation protein Bfr1 1157.96 1.64
PADG_05683 cell division control protein 48 906.88 1.76
PADG_11679 proliferating cell nuclear antigen (pcna) 4415.85 1.95
DNA PROCESSING
PADG_05798 single-strand binding protein family 27710.18 1.61
PADG_02683 UV excision repair protein Rad23 8139.56 2.37
PADG_00656 non-histone chromosomal protein 6 2992.07 2.11
PADG_00615 proteasome component C7-alpha 3316.5 1.61
PADG_05906 histone H2A 1859.72 1.93
PADG_05907 histone H2B 18240.2 1.68
PADG_00718 histone chaperone asf1 2760.63 1.76
93
PADG_00872 histone 18101.32 2.78
PADG_00873 histone H3 4340.91 2.71
PADG_07134 histone H4 17501.65 3.53
TRANSCRIPTION
PADG_07888 eukaryotic translation initiation factor 5ª 628.13 *
PADG_11711 ATP-dependent RNA helicase eIF4A 1321.54 2.67
PADG_05034 RNA binding domain-containing protein 867.11 1.54
PADG_01455 KH domain RNA-binding protein 409.15 1.59
PADG_06180 cap binding protein 582.21 1.62
PADG_00067 polymerase II polypeptide D 3632.22 *
PADG_01151 DNA-directed RNA polymerase II subunit RPB11 551.42 *
PADG_04657 nascent polypeptide-associated complex subunit beta 5769.23 3.78
PADG_04730 nascent polypeptide-associated complex subunit alpha 18126.22 1.87
PADG_04966 DNA-directed RNA polymerase II subunit RPB11 728.43 1.72
PADG_02825 small nuclear ribonucleoprotein Lsm8 1929.44 2.26
PADG_03696 nuclear polyadenylated RNA-binding protein Nab2 1527.97 *
PADG_05393 mRNA decapping hydrolase 1092.36 3.20
PADG_04672 ATP-dependent RNA helicase SUB2 697.62 *
PADG_04796 pre-mRNA-splicing factor rse1 445.01 *
94
PADG_05587 U2 small nuclear ribonucleoprotein B 617.42 1.44
PADG_06734 U6 snRNA-associated Sm-like protein LSm7 2246.48 *
PADG_11424 cleavage and polyadenylation specific subunit 550.08 1.56
PADG_11958 small nuclear ribonucleoprotein 2502.26 *
PADG_00676 rnapii degradation factor def1 1208.35 2.53
PADG_07469 RNase III domain-containing protein 797.44 1.93
PADG_04981 nucleoporin p58/p45 531.32 *
PADG_11062 bZIP transcription fator 6178.35 2.78
PROTEIN SYNTHESIS
PADG_07515 UBX domain-containing protein 614.94 1.95
PADG_04057 translation initiation factor 3 subunit J 2426.37 1.9
PADG_02759 ribosome recycling fator 3731.33 3.75
PADG_05939 60S ribosomal protein L27a 2405.32 1.4
PADG_00995 ubiquitin-40S ribosomal protein S27a 1131.09 1.75
PADG_01427 40S ribosomal protein S12 3942.19 1.69
PADG_02056 ribosomal protein L7/L12 9257.25 1.76
PADG_02446 60S acidic ribosomal protein P2 17861.02 4.56
PADG_04866 40S ribosomal protein S10-A 1188.82 1.5
PADG_06680 40S ribosomal protein S22 6671.03 2.29
95
PADG_01949 translation elongation factor Tu 8904.08 1.97
PADG_04034 chaperone DnaJ 2904.89 1.54
PADG_00207 DnaJ like subfamily C member 2 793.49 1.42
PADG_02206 DnaJ domain protein Psi 613.07 2.07
PADG_01079 translation initiation factor 4B 1039.02 1.76
PADG_02691 eukaryotic translation initiation factor 6 2002.04 1.61
PADG_08033 eukaryotic translation initiation factor 3 subunit B 489.21 1.97
PADG_01558 histidyl-tRNA synthetase 556.29 2.63
PROTEIN FOLDING, MODIFICATION, DESTINATION
PADG_01605 polyubiquitin 1112.16 1.4
PADG_01852 small glutamine-rich tetratricopeptide repeat-containing protein 1537.32 2.49
PADG_05183 Grx4 family monothiol glutaredoxin 1644.83 2.12
PADG_12323 peptidyl-prolyl cis-trans isomerase 804.14 1.85
PADG_06488 peptidyl-prolyl cis-trans isomerase D 19095.81 1.42
PADG_06992 mitochondrial co-chaperone GrpE 8275.4 1.76
PADG_05032 Hsp90 binding co-chaperone (Sba1) 4917.89 1.59
PADG_03424 ubiquitin-activating enzyme E1 1345.75 1.72
PADG_07558 ubiquitin carboxyl-terminal hydrolase 523.42 1.55
PADG_08270 UBX domain-containing protein 493.3 *
96
PROTEIN DEGRADATION
PADG_06766 mitochondrial-processing peptidase subunit beta 3201 2.31
PADG_03221 thimet oligopeptidase 1073.19 2.08
PADG_04167 aspartyl aminopeptidase 1162.18 1.7
PADG_03735 proline iminopeptidase 422.42 *
PADG_05160 dipeptidyl-peptidase 567.55 2.29
PADG_00599 26S protease regulatory subunit 6A 602.27 *
PADG_02735 proteasome component PRE6 5654.91 1.59
PADG_03192 proteasome component PUP2 713.27 2.36
PADG_04952 AAA ATPase 571.94 *
PADG_05193 xaa-Pro aminopeptidase PEPP 1126.68 *
PADG_05820 xaa-Pro aminopeptidase P 1428.19 1.91
PADG_03680 proteasome component PRE2 1506.31 1.61
PADG_03965 proteasome component PRE4 2323.35 1.80
PADG_03967 proteasome component C5 9826.24 1.62
PADG_03982 proteasome component C1 3157.46 1.75
PADG_04067 proteasome component PUP3 1678.89 1.63
PADG_07190 proteasome component Y7 811.6 1.61
PADG_08087 proteasome component PRE3 5539.32 1.53
97
PADG_00634 vacuolar protease A 329.52 *
PROTEIN/NUCLEOTIDE/METAL BINDING
PADG_04934 RNP domain protein 619.2 1.63
PADG_07249 actin binding protein 989.85 2.34
PADG_01032 DNA-binding protein, 42 kDa 1140.68 *
PADG_02652 Grp1p 36483.8 1.71
PADG_04311 cellular nucleic acid-binding protein 1688.29 1.91
PADG_07884 polyadenylate-binding protein, cytoplasmic and nuclear 490.6 1.8
PADG_01529 TPR repeat protein 645.78 *
CELLULAR TRANSPORT
PADG_07023 carnitine O-acetyltransferase 1083.11 1.45
PADG_02022 clathrin light chain 3539.13 1.79
PADG_06165 glycolipid transferprotein HET-C2 883.23 2.29
PADG_01994 mitochondrial import receptor subunit tom22 1001.71 *
PADG_03274 mitochondrial import inner membrane translocase subunit tim9 3109.89 *
PADG_02352 copper chaperone 2443.46 *
PADG_11950 Ran-specific GTPase-activating protein 1 3845.45 1.84
PADG_03203 BAR domain-containing protein 6023.64 2.73
98
PADG_08188 vacuolar-sorting protein snf7 1229.57 *
CELL RESCUE, DEFENSE AND VIRULENCE
PADG_01551 thioredoxin reductase 1081.7 1.84
PADG_01954 superoxide dismutase 2 Fe-Mn 2543.95 4.72
PADG_07418 superoxide dismutase 1 Cu-Zn 13608.78 2.78
PADG_00778 Hsp70 482.87 1.43
PADG_02030 Hsp90 co-chaperone Cdc37 4849.77 2.71
PADG_02785 heat shock protein Hsp88 6273.21 1.48
PADG_03963 30 kDa heat shock protein 15324.12 2.05
PADG_04379 heat shock protein STI1 11812.75 2.09
PADG_01479 gamma-glutamyltransferase 1862.55 2.46
PADG_06314 carboxypeptidase Y 924.76 1.97
PADG_07422 serine proteinase 656.45 2.17
PADG_07460 vacuolar aminopeptidase 1941.91 1.82
PADG_07674 carbonic anhydrase 2074.37 1.55
CELL DEATH
PADG_06336 cell lysis protein cwl1 1040.98 *
99
UNCLASSIFIED
PADG_00824 hypothetical protein 1685.96 1.52
PADG_05474 hypothetical protein 1067.5 1.58
PADG_03869 hypothetical protein 639.41 *
PADG_03788 hypothetical protein 833.59 *
PADG_05884 hypothetical protein 7917.75 2.28
PADG_07064 hypothetical protein 1199.21 1.94
PADG_04934 hypothetical protein 619.2 1.63
PADG_00828 hypothetical protein 837.5 2.41
PADG_11936 hypothetical protein 600.69 *
PADG_00496 hypothetical protein 941.2 *
PADG_03827 hypothetical protein 2950.62 *
PADG_01010 hypothetical protein 1473.23 2.96
PADG_05703 hypothetical protein 1162.77 1.77
PADG_08368 hypothetical protein 3283.04 2.11
PADG_03210 hypothetical protein 2128.5 2.56
PADG_08480 hypothetical protein 631.36 2.8
PADG_00921 hypothetical protein 8475.1 1.87
PADG_07670 hypothetical protein 841.85 1.79
PADG_01867 hypothetical protein 453.9 1.51
100
PADG_03176 hypothetical protein 520.17 1.49
PADG_08436 hypothetical protein 1263.02 *
PADG_05556 hypothetical protein 1218.06 *
PADG_06547 hypothetical protein 1233.13 *
PADG_02307 hypothetical protein 473.88 *
PADG_02092 hypothetical protein 1528.71 1.89
PADG_08666 hypothetical protein 1921.5 *
PADG_02967 hypothetical protein 5909.55 1.76
PADG_04229 hypothetical protein 646.38 2.04
PADG_04439 hypothetical protein 11250.78 1.41
PADG_03827 hypothetical protein 2950.62 *
PADG_02343 MYG1 protein 2421.65 1.68
PADG_00694 ankyrin repeat protein 1375.38 1.84
PADG_00463 DUF833 domain-containing protein 625.24 1.61
PADG_02845 diploid state maintenance protein chpA 2809.36 1.5
PADG_07714 NTF2 and RRM domain-containing protein 1009.12 1.59
PADG_06515 suaprga1 28036.56 1.48
PADG_03526 M protein repeat protein 694.82 *
PADG_06182 WD repeat-containing protein 1138.44 1.63
101
1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2PLGS score is the result of different mathematical models for peptide and fragment assign prediction. Acceptable score values consider protein
identification with a minimum confidence level of 95% and a false discovery rate of 6%. 3Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated macrophages by the
abundance in control. Proteins with a minimum fold change of 40% were considered regulated. 4 Biological process of differentially expressed proteins from MIPS (http://mips.helmholtz-muenchen.de/funcatDB/) and Uniprot databases
(http://www.uniprot.org/).
*Proteins detected in P. brasiliensis Pb18 only during non-activated macrophage infection.
102
Supplementary Table 4. Down-regulated proteins of P. brasiliensis. Pb18 after 6 h infection in non-activated alveolar macrophages by
INF-γ
Accession number1 Protein description Score2 Pb18_NA x CTRL
Ratio3
Functional categories4
AMINO ACID METABOLISM
Amino acid degradation
PADG_01963 glycine cleavage system H protein 1151.78 *
PADG_02214 4-aminobutyrate aminotransferase 1496.37 0.68
PADG_04570 branched-chain amino acid aminotransferase 979.87 0.7
PADG_03514 2-oxoisovalerate dehydrogenase subunit alpha. mitochondrial 761.58 *
PADG_03466 3-hydroxyisobutyrate dehydrogenase 504.5 *
PADG_01621 aspartate aminotransferase mitochondrial 710.05 *
PADG_03686 aspartate aminotransferase cytoplasmic 395.76 *
PADG_00832 adenylosuccinate synthetase 969.84 *
PADG_00215 aromatic-L-amino-acid decarboxylase 579.63 *
PADG_05337 glutamate-5-semialdehyde dehydrogenase 487.9 *
Amino acid biosynthesis
PADG_06740 betaine aldehyde dehydrogenase 1292.59 0.75
PADG_01418 cysteine dioxygenase 767.22 *
PADG_04193 cystathionine beta-synthase 532.75 *
103
UREA CYCLE
PADG_00637 Arginase 463.97 0.68
PADG_00888 argininosuccinate synthase 652.7 *
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
PADG_01100 uracil phosphoribosyltransferase 1806.58 *
C-COMPOUND AND CARBOHYDRATE METABOLISM
PADG_06221 formate dehydrogenase 632.87 *
PENTOSE-PHOSPHATE PATHWAY
PADG_07420 transaldolase 1467.82 *
GLYCOLYSIS / GLUCONEOGENESIS
PADG_01896 phosphoglycerate kinase 2190.5 0.66
TRICARBOXYLIC-ACID PATHWAY
PADG_04994 ATP-citrate-lyase 503.4 0.65
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ELECTRON TRANSPORT AND RESPIRATION
PADG_08394 cytochrome b-c1 complex subunit 2 904.65 *
OXIDATION OF FATTY ACIDS
PADG_01486 short chain dehydrogenase/reductase family 1481.15 *
PADG_01209 enoyl-CoA hydratase 4337.27 0.61
PADG_03194 3-ketoacyl-CoA thiolase B 906.43 0.5
PADG_03449 isopentenyl-diphosphate delta-isomerase 795.96 *
PADG_04343 short chain dehydrogenase/reductase 620.43 *
SIGNAL TRANSDUCTION
PADG_11275 CMGC/MAPK protein kinase 439.81 *
PADG_00172 ras-like GTP-binding protein 506.63 *
CELL CYCLE
PADG_02763 cyclin-dependent kinase regulatory subunit 763.95 *
TRANSCRIPTION
PADG_07416 transcription factor 474.55 *
PADG_06768 rRNA 2'-O-methyltransferase fibrillarin 836.55 *
105
PROTEIN SYNTHESIS
PADG_00514 60S ribosomal protein L16 4223.18 *
PADG_07924 60S ribosomal protein L24 433.47 *
PADG_01083 60S ribosomal protein L32 649.58 0.61
PADG_01267 40S ribosomal protein S11 7018.59 0.48
PADG_01281 mitochondrial 37S ribosomal protein MRPS8 463.22 *
PADG_02797 mitochondrial 54S ribosomal protein YmL3 428.68 *
PADG_04449 60S ribosomal protein L23 1563.11 *
PADG_05338 60S ribosomal protein L18-B 7862.46 0.52
PADG_06875 50S ribosomal protein L4 417.91 *
PADG_00355 40S ribosomal protein S17 802.28 *
PADG_08213 ribosomal protein S2 593.74 *
PADG_07105 arginine-tRNA ligase 554.11 *
PADG_08472 lysine-tRNA ligase 503.01 *
PROTEIN FOLDING AND STABILIZATION
PADG_00430 hsp7-like protein 5500.47 0.59
CELLULAR TRANSPORT
106
PADG_00622 ATPase GET3 514.77 *
SECONDARY METABOLISM
PADG_01052 3-demethylubiquinone-9 3-methyltransferase 1096.69 *
CELL RESCUE, DEFENSE AND VIRULENCE
PADG_07946 peroxisomal matrix protein 2670.46 0.35
PADG_08651 peroxisomal hydratase-dehydrogenase-epimerase 724.34 *
UNCLASSIFIED
PADG_01488 hypothetical protein 1980.81 *
PADG_04475 hypothetical protein 1040.31 *
PADG_07870 hypothetical protein 638.76 *
PADG_00211 hypothetical protein 2047.72 *
PADG_03631 hypothetical protein 1247.15 *
PADG_03660 hypothetical protein 860.43 *
PADG_08212 hypothetical protein 1071 0.59
PADG_01849 GTP-binding protein YchF 416.64 *
PADG_00282 GTP-binding protein ypt2 2005.04 *
PADG_07627 4-carboxymuconolactone decarboxylase family protein 628.84 *
107
PADG_08483 chromobox protein 1 816.66 0.75
PADG_07412 DUF1479 domain-containing protein 861.11 *
PADG_05356 isochorismatase domain-containing protein 871.15 *
PADG_07287 WD repeat-containing protein 579.21 *
PADG_02719 dTDP-4-dehydrorhamnose reductase 513.83 *
1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2PLGS score is the result of different mathematical models for peptide and fragment assign prediction. Acceptable score values consider protein
identification with a minimum confidence level of 95% and a false discovery rate of 6%. 3Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated macrophages by the
abundance in control. Proteins with a minimum fold change of 40% were considered regulated. 4 Biological process of differentially expressed proteins from MIPS (http://mips.helmholtz-muenchen.de/funcatDB/) and Uniprot databases
(http://www.uniprot.org/).
* Proteins detected in P. brasiliensis Pb18 only in the control condition.
108
Supplemental Table 5. Regulated proteins of P. brasiliensis, Pb18 after 6 h infection in macrophages activated and non-activated by INF-
Accession number1 Protein description Score2
Pb18_A x
Pb18_NA
Ratio3
Functional categories4
UP-REGULATED PROTEINS
AMINO ACID METABOLISM
PADG_07029 acetylornithine aminotransferase 522.48 1.2
PADG_08662 cystathionine beta-lyase 398.91 1.32
PADG_05896 phosphoglycerate dehydrogenase 313.7 *
PADG_06756 histidinol dehydrogenase 1134.88 1.25
PADG_05337 glutamate-5-semialdehyde dehydrogenase 523.99 *
PADG_00888 argininosuccinate synthase 778.36 *
PADG_06546 aminopeptidase 588.18 1.22
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
PADG_06297 phosphoribosylamine-glycine ligase 410.55 *
PADG_05321 mitochondrial nuclease 517 *
TRICARBOXYLIC ACID CYCLE
PADG_08387 citrate synthase, mitochondrial 1265.08 1.32
109
PADG_04994 ATP-citrate-lyase 990.79 1.25
ELECTRON TRANSPORT AND RESPIRATION
PADG_08394 cytochrome b-c1 complex subunit 2 556.36 *
BETA-OXIDATION OF FATTY ACID
PADG_05081 aldehyde dehydrogenase 4282.44 1.23
LIPID, FATTY ACID AND ISOPRENOID METABOLISM
PADG_05783 farnesyl pyrophosphate synthetase 3596.45 3.05
TRANSCRIPTION
PADG_08423 RuvB-like helicase 2 443.26 *
PROTEIN SYNTHESIS
PADG_07803 60S ribosomal protein L12 1836.35 1.32
PROTEIN FOLDING AND STABILIZATION
PADG_02761 hsp75-like protein 1452.82 1.35
PADG_03715 FK506-binding protein 520.18 1.3
PADG_00937 vacuolar sorting-associated protein 733.09 1.63
PROTEIN DEGRADATION
PADG_01935 26S proteasome non-ATPase regulatory subunit 10 1397.58 1.21
PROTEIN/NUCLEOTIDE BINDING
PADG_03895 dynein light chain, cytoplasmic 1406.92 1.29
PADG_08342 GTP-binding protein ypt1 440.33 1.36
110
CELL RESCUE, DEFENSE AND VIRULENCE
PADG_08118 hsp72-like protein 34646.25 1.81
UNCLASSIFIED
PADG_05356 isochorismatase domain-containing protein 845.52 -
PADG_07627 4-carboxymuconolactone decarboxylase family protein 809.8 -
DOWN-REGULATED PROTEINS
AMINO ACID METABOLISM
PADG_01718 saccharopine dehydrogenase [NADP+, L-glutamate-forming] 489.68 **
PADG_08376 aspartate-semialdehyde dehydrogenase 2827.17 0.77
PADG_00402 betaine aldehyde dehydrogenase 664.11 0.68
PADG_06740 betaine aldehyde dehydrogenase 856.8 0.62
PADG_02456 cystathionine gamma-lyase 481.74 0.76
NUCLEOTIDE/NUCLEOSIDE/NUCLEOBASE METABOLISM
PADG_08066 purine nucleoside phosphorylase I, inosine and guanosine-specific 2642.62 0.8
GLYCOLYSIS / GLUCONEOGENESIS
PADG_02411 glyceraldehyde-3-phosphate dehydrogenase 25282.24 0.78
FERMENTATION
PADG_04701 *alcohol dehydrogenase 566.97 0.71
PADG_02733 *D-lactate dehydrogenase 1229.76 0.70
111
ELECTRON TRANSPORT AND RESPIRATION
PADG_01366 NADH-ubiquinone oxidoreductase 785.94 0.55
PADG_07749 NAD(P)H:quinone oxidoreductase, type IV 52701.54 0.82
PADG_04501 ubiquinol-cytochrome c reductase subunit 7 747.17 0.43
PADG_05750 putative cytochrome c oxidase subunit Via 1730.47 0.71
PADG_07042 ATP synthase F1, delta subunit 514.91 0.77
PADG_04729 ATP synthase subunit D, mitochondrial 1197.51 0.71
FATTY ACID BIOSYNTHESIS
PADG_00244 trans-2-enoyl-CoA reductase 596.86 **
CELL CYCLE AND DNA PROCESSING
PADG_05798 single-strand binding protein family 2969.63 0.82
PADG_00849 nuclear segregation protein Bfr1 1322.91 0.75
TRANSCRIPTION
PADG_05034 RNA binding domain-containing protein 1244.05 0.81
PADG_03788 polyadenylation factor 833.59 **
PADG_07469 RNase III domain-containing protein 985.14 **
PROTEIN SYNTHESIS
PADG_01427 40S ribosomal protein S12 2665.61 0.79
PADG_02445 40S ribosomal protein S15 24765.47 0.74
112
PADG_03326 40S ribosomal protein S9 4724.49 0.8
PADG_03778 60S ribosomal protein L10-A 2089.25 0.8
PADG_05338 60S ribosomal protein L18-B 8399.5 0.76
PADG_08244 60S acidic ribosomal protein P1 28130.45 0.81
PADG_02206 DnaJ domain protein 653.86 0.74
PADG_07977 eukaryotic translation initiation factor 1A, Y-chromosomal 703.75 0.81
PROTEIN FOLDING AND STABILIZATION
PADG_05203 peptidyl-prolyl cis-trans isomerase ssp1 1171.38 0.77
NUCLEIC ACID BINDING
PADG_02652 Grp1p 7413.59 0.82
PADG_03459 replication factor-A protein 502.19 0.68
PADG_11958 small nuclear ribonucleoprotein 860.29 0.77
PADG_06861 ssDNA binding protein Ssb3 1109.33 0.81
SECONDARY METABOLISM
PADG_08108 coproporphyrinogen III oxidase 526.04 0.65
UNCLASSIFIED
PADG_00440 predicted protein 778.06 **
PADG_05474 hypothetical protein 426.04 0.78
PADG_00921 hypothetical protein 1191.48 0.65
PADG_01010 hypothetical protein 847.11 0.81
113
PADG_03115 hypothetical protein 1261.68 0.62
PADG_03210 hypothetical protein 740.97 0.77
PADG_03827 hypothetical protein 2531.19 0.79
PADG_04442 hypothetical protein 452.53 0.77
PADG_04981 hypothetical protein 881.57 0.75
PADG_06080 hypothetical protein 1207.37 0.62
PADG_08152 hypothetical protein 1127.34 0.73
PADG_08034 dienelactone hydrolase family protein 2431.86 0.81
PADG_04912 AhpC/TSA family protein 741.6 **
1Accession number obtained in the Paracoccidioides database available at
http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHome.html. 2PLGS score is the result of different mathematical models for peptide and fragment assign prediction. Acceptable score values consider protein
identification with a minimum confidence level of 95% and a false discovery rate of 6%. 3Ratio values were obtained by dividing the values of protein abundance (in fmol) from Pb18 during infection of activated macrophages by the
abundance in control. Proteins with a minimum fold change of 40% were considered regulated. 4 Biological process of differentially expressed proteins from MIPS (http://mips.helmholtz-muenchen.de/funcatDB/) and Uniprot databases
(http://www.uniprot.org/).
* Proteins detected only in Pb18_A.
** Proteins detected only in Pb18_NA.
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5. DISCUSSÃO
A PCM apresenta polimorfismo clínico que varia de infecção assintomática a
doença granulomatosa unifocal ou sistêmica. A virulência do patógeno e a resposta imune
do hospedeiro são fatores determinantes na evolução da doença (FORTES et al., 2011).
As células do sistema imune inato, principalmente macrófagos e neutrófilos, são a
principal linha de defesa contra a infecção por Paracoccidioides (CALICH et al., 2008).
Entretanto, Paracoccidioides é capaz de sobreviver e multiplicar no interior desses
fagócitos e também de células epiteliais. Tal habilidade é inibida eficazmente quando os
fagócitos são ativados por interleucinas como INF- e IL-12 (BRUMMER; HANSON;
STEVENS, 1988; RODRIGUES et al., 2007). Essas observações corroboram com nossos
resultados, nos quais avaliamos a sobrevivência de P. brasiliensis em macrófagos
alveolares ativados e não ativados por INF-. Os macrófagos ativados apresentaram
atividade microbicida após 9 h de interação com o fungo, observados pela diminuição no
número de unidades formadoras de colônia (UFC) recuperadas após a fagocitose.
Entretanto, a sobrevivência do fungo em células não ativados não foi afetada,
apresentando um número crescente de UFCs viáveis recuperadas dos macrófagos. A
diferença no potencial microbicida entre macrófagos ativados ou não, também foi
observada em ensaios de infecção com diferentes isolados de Paracoccidioides. A adição
de INF- não aumenta o índice de fagocitose, mas confere atividade microbicida aos
macrófagos de maneira dose-dependente (BRUMMER et al., 1989; BRUMMER;
HANSON; STEVENS, 1988).
Para estabelecer a infecção, os patógenos devem apresentar flexibilidade
metabólica para assimilar os nutrientes disponíveis e um poderoso sistema antioxidante
que lhes permite sobreviver intracelularmente (CAMACHO; NIÑO-VEGA, 2017;
KASPER; SEIDER; HUBE, 2015a; SEIDER et al., 2014). Análises proteômicas e
transcriptômicas revelam que bactérias e fungos patogênicos reprogramam seu
metabolismo, regulando negativamente a via glicolítica e ativando rotas alternativas de
consumo de carbono, como gliconeogênese, degradação de aminoácidos, oxidação de
ácidos graxos, ciclo glioxilado e produção de etanol, durante a infecção de macrófagos
(SPRENGER et al., 2017). Realizamos o estudo do proteoma de P. brasiliensis após 6 h
de infecção em macrófagos alveolares ativados e não ativados por INF-. Nossas análises
115
mostraram que em ambas as condições o fungo não ativou a gliconeogênese, como
observado em estudos anteriores de 24 h de infecção em macrófagos J774 (PARENTE-
ROCHA et al., 2015). Entretanto, esta via também não foi regulada positivamente durante
6 h de infecção em pulmões de camundongos (PIGOSSO et al., 2017). Provavelmente,
esse fato seja devido o fungo ainda possuir reserva de glicose, uma vez que o patógeno
foi cultivado em meio rico em nutrientes antes da infecção. Nesse sentido, a ativação da
gliconeogênese ocorre após um período mais longo de infecção (PARENTE-ROCHA et
al., 2015).
P. brasiliensis regulou positivamente, em ambas as condições analisadas, a
degradação de aminoácidos, ciclo do ácido tricarboxílico e do glioxalato, bem como a
cadeia transportadora de elétrons e síntese de ATP. Esses dados corroboram com estudos
proteômicos que submeteram o fungo à privação de carbono ou ao acetato como única
fonte de carbono, condições que mimetizam o ambiente intracelular (BAEZA et al., 2017;
LIMA et al., 2014). O aumento na expressão da isocitrato liase, que atua no ciclo do
glioxalato, favorece a sobrevivência do fungo em ambientes de baixa disponibilidade de
nutrientes, uma vez que permite a assimilação de compostos de dois carbonos, com o
acetato (BARELLE et al., 2006; LORENZ; FINK, 2002).
Interessantemente, notamos um acúmulo de enzimas relacionadas às vias
alternativas de consumo de carbono, como via das pentoses fosfato e ciclo do metil
citrato, somente em células fúngicas recuperadas de macrófagos não ativados. A ativação
dessas vias pode favorecer a sobrevivência do fungo no ambiente hostil que é o
fagossomo. A via das pentoses de fosfato contribui para a defesa contra o estresse
oxidativo, fornecendo equivalentes redutores como o NADPH. Enquanto, o ciclo do metil
citrato é necessário para a degradação de compostos tóxicos, como propionil-CoA. Em
A. fumigattus, esse ciclo é essencial para o estabelecimento da infecção fúngica
(IBRAHIM-GRANET et al., 2008). Essas peculiaridades metabólicas indicam que o
ambiente intracelular dos macrófagos não ativados é favorável à adaptação de P.
brasiliensis, o que justifica a sobrevivência do fungo durante infecção dessas células.
Em ambas as condições analisadas, o fungo aumentou a expressão de proteínas
envolvidas na defesa e virulência, como enzimas de proteção ao choque térmico e
proteínas autofágicas, como a carboxypeptidase Y, vacuolar aminopeptidase e serino
proteinase, que promovem a reciclagem de componentes citoplasmáticos em modo de
inativação de patógenos, que favorecem a viabilidade de fungos em privação de nutrientes
116
(INOUE; KLIONSKY, 2010; ROETZER et al., 2010). A serino proteinase foi
recentemente descrita em P. brasiliensis como um fator de virulência que favorece a
sobrevivência do fungo durante a privação de nitrogênio e também na invasão tecidual,
uma vez que é secretada em grandes quantidades nos tecidos pulmonares de
camundongos durante infecção in vivo (PARENTE et al., 2010; PIGOSSO et al., 2017).
Observamos ainda, a indução da expressão de proteínas envolvidas na desintoxicação e
resposta ao estresse, como a tioredoxina redutase (TrxR) e a superóxido dismutase (SOD),
ressaltando que maiores quantidades dessas proteínas foram detectadas no fungo durante
interação com macrófagos não ativados. O predomínio dessas proteínas em P. brasiliensis
recuperadas de macrófagos não ativados reforça a evidência de que o fungo enfrenta
maiores dificuldades no ambiente intracelular de macrófagos ativados, o que impede sua
adaptação e pode resultar em sua morte.
Corroborando a esses dados, observamos o acúmulo de enzimas glicolíticas em
maior quantidade em células de P. brasiliensis recuperadas de macrófagos não ativados.
Essas proteínas podem estar envolvidas na síntese de precursores da parede celular do
fungo e favorecer sua resistência e virulência (BERNARD; LATGÉ, 2001; JUNG et al.,
2018; SAN-BLAS; SAN-BLAS, 1977). Através de ensaios de microscopia de
fluorescência, detectamos maiores quantidades de glucanos, proteínas glicosiladas e
quitina na parede celular de leveduras recuperadas de macrófagos não ativados. Brummer
et al., (1990), também observou que a morfologia de P. brasiliensis apresentou diferenças
após a internalização por macrófagos peritoneais ativados e não ativados. Durante a
infecção dos macrófagos ativados ocorreu deterioração da parede celular dos fungos até
completa digestão e eliminação, enquanto que nos macrófagos não ativados a parede
celular de P. brasiliensis permaneceu intacta. Outros estudos realizaram infecção em
macrófagos não ativados, e também foi observado que Paracoccidioides induziu a
expressão enzimas que sintetizam componentes da parede celular. Esta estratégia pode
ser uma importante forma de resistência do fungo (TAVARES et al., 2007). Outros
fungos, como C. neoformans, induzem a expressão de genes que codificam enzimas
envolvidas na síntese de polissacarídeos, durante a infecção de macrófagos ativados, o
que pode estar associado à formação de componentes da parede celular ou da cápsula
(FAN et al., 2005b). Mudanças na parede celular podem contribuir para a virulência de
Paracoccidioides na fase leveduriforme, através do aumento de α-glucano, que protege
células de leveduras do reconhecimento de β-glucanos por macrófagos e contribui para a
117
latência de fungos (KANETSUNA; CARBONELL, 1970; LARA-LEMUS et al., 2014).
Uma vez que os macrófagos não ativados permitem a sobrevivência e multiplicação do
P. brasiliensis, eles podem ser usados como meio de disseminação do fungo.
Além disso, embora a cadeia transportadora de elétrons e a síntese de ATP
tenham sido reguladas positivamente e ambas as condições analizadas, um maior número
de subunidades e uma maior abundância de proteínas relacionadas a essas vias foram
detectadas em P. brasiliensis derivados de macrófagos não ativados. A atividade
mitocondrial de P. brasiliensis foi avaliada por marcação com sondas mitotracker e
rodamina. A fluorescência da rodamina foi detectada com maior intensidade em células
do fungo após a infecção de macrófagos não ativados, o que indica um aumento do
potencial de membrana, consequentemente, um aumento da atividade mitocondrial.
Dentre as funções desempenhadas pelas mitocôndrias, podemos destacar o suprimento de
energia celular, o equilíbrio entre as vias de pró-sobrevivência e pró-morte e também o
papel na resposta ao estresse metabólico. (NUNNARI; SUOMALAINEN, 2012).
Análises proteômicas de mitocôndrias de Paracoccidioides revelaram a presença de
enzimas de desintoxicação como superóxido dismutase, citocromo c peroxidase e
tiorredoxina. (CASALETTI et al., 2017). Um estudo com Aspergillus nidulans
demonstrou que a cepa mutante de um gene relacionado à função mitocondrial e
respiração celular, causou uma diminuição na massa e função das mitocôndrias e do
processo de fosforilação oxidativa. Esta deleção também levou a um aumento nos níveis
endógenos de ROS, que é tóxico para a célula (KROHN et al., 2014). Esses dados
reforçam que o interior dos macrófagos é favorável à atividade metabólica de P.
brasiliensis.
Em síntese, os dados indicam que o P. brasiliensis é capaz de adaptar-se e
sobreviver ao ambiente intracelular de macrófagos não ativados, o que
,consequentemente, pode favorecer sua multiplicação e disseminação pelos tecidos do
hospedeiro. Essa observação corrobora com dados clínicos que relatam pacientes com
PCM aguda ou crônica apresentam baixa produção de citocinas ativadoras de fagócitos,
como INF-, IL-12 e TNF- (BENARD et al., 2001). Essas citocinas desempenham um
papel importante na atividade microbicida dos macrófagos, no recrutamento de células
de defesa para o local da infecção e na formação de granulomas eficientes para conter a
disseminação de Paracoccidioides (NISHIKAKU et al., 2011). Este estudo proteômico
comparativo de P. brasiliensis, durante infecção de macrófagos ativados e não ativados,
118
pode contribuir para a compreensão de fatores que podem levar à inibição ou evolução
da PCM, bem como sua patogênese.
119
6. CONCLUSÕES
Neste estudo, constatamos que P. brasiliensis é capaz de adaptar e sobreviver ao
ambiente intracelular de macrófagos não ativados, mas não é incapaz sobreviver após a
fagocitose de macrófagos ativados por INF-. A análise proteômica comparativa do
fungo durante a infecção de macrófagos ativados e não ativados, revelou peculiaridades
metabólicas que favorecem a sobrevivência do P. brasiliensis no ambiente intracelular de
células não ativadas. Em ambas as condições o fungo aumentou a expressão de enzimas
relacionadas à degradação de aminoácidos, ciclo de TCA e glioxalato, enzimas
antioxidantes e fatores de virulência. No entanto, a ativação da via de fosfato de pentoses,
ciclo do metil citrato, síntese de precursores da parede celular e intensa atividade
mitocondrial foi observada apenas em células de levedura recuperadas de macrófagos não
ativados. Essas vias podem favorecer a viabilidade do fungo em relação às leveduras
internalizadas por fagócitos ativados. Esses dados indicam que o processo de fagocitose
por macrófagos não ativados pode ser uma estratégia utilizada por P. brasiliensis para
promover sua evasão ao sistema imune e disseminação por órgãos hospedeiros.
120
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135
ANEXOS
PRODUTOS DO PERÍODO
Artigo 2 – Characterization of extracellular proteins in members of the
Paracoccidioides complex
Autores: Amanda Rodrigues de Oliveira, Lucas Nojosa Oliveira, Edilânia Gomes
Araújo Chaves, Simone Schneider Weber, Alexandre Melo Bailão, Juliana Alves
Parente-Rocha, Lilian Cristiane Baeza, Célia Maria de Almeida Soares, Clayton Luiz
Borges.
Fungal Biology (Aceito)
Artigo 3 – Analysis of Paracoccidioides secreted proteins reveals fructose 1,6-
bisphosphate aldolase as a plasminogen binding protein
Autores: Edilânia Gomes Araújo Chaves, Simone Schneider Weber, Sonia Nair Báo,
Luiz Augusto Pereira, Alexandre Melo Bailão, Clayton Luiz Borges, Célia Maria de
Almeida Soares.
BMC Microbiology (Publicado)
Accepted Manuscript
Characterization of extracellular proteins in members of the Paracoccidioides complex
Amanda Rodrigues de Oliveira, Lucas Nojosa Oliveira, Edilânia Gomes AraújoChaves, Simone Schneider Weber, Alexandre Melo Bailão, Juliana Alves Parente-Rocha, Lilian Cristiane Baeza, Célia Maria de Almeida Soares, Clayton Luiz Borges
PII: S1878-6146(18)30062-X
DOI: 10.1016/j.funbio.2018.04.001
Reference: FUNBIO 916
To appear in: Fungal Biology
Received Date: 24 November 2017
Revised Date: 11 March 2018
Accepted Date: 3 April 2018
Please cite this article as: Rodrigues de Oliveira, A., Oliveira, L.N., Araújo Chaves, E.G., Weber, S.S.,Bailão, A.M., Parente-Rocha, J.A., Baeza, L.C., Almeida Soares, C.M.d., Borges, C.L., Characterizationof extracellular proteins in members of the Paracoccidioides complex, Fungal Biology (2018), doi:10.1016/j.funbio.2018.04.001.
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Characterization of extracellular proteins in members of the Paracoccidioides 1
complex 2
3
Amanda Rodrigues de Oliveira1,ǂ, Lucas Nojosa Oliveira1,2,ǂ, Edilânia Gomes Araújo 4
Chaves1, Simone Schneider Weber3,4, Alexandre Melo Bailão1, Juliana Alves Parente-5
Rocha1, Lilian Cristiane Baeza1, Célia Maria de Almeida Soares1, Clayton Luiz Borges1* 6
7
1 Laboratório de Biologia Molecular; Instituto de Ciências Biológicas; Universidade 8
Federal de Goiás, Goiânia, Goiás, Brazil 9
2 Programa de Pós-graduação em Patologia Molecular; Faculdade de Medicina; 10
Universidade de Brasília, Brasília, Distrito Federal, Brazil 11
3 Instituto de Ciências Exatas e Tecnologia; Universidade Federal do Amazonas, 12
Itacoatiara, Amazonas, Brazil 13
4 Faculdade de Ciências Farmacêuticas, Alimentos e Nutrição; Universidade Federal do 14
Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil 15
16
ǂThese authors have contributed equally to this work. 17
18
*Corresponding author 19
Clayton Luiz Borges 20
Laboratório de Biologia Molecular 21
Instituto de Ciências Biológicas II 22
Campus II 23
Universidade Federal de Goiás 24
790-900, Goiânia, Goiás, Brazil. 25
Tel/Fax: +55 62 3521-1110 26
E-mail address: [email protected] (C. L. Borges) 27
28
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Abstract 30
Paracoccidioides is a thermodimorphic fungus that causes Paracoccidioidomycosis 31
(PCM) – an endemic systemic mycosis in Latin America. The genus comprises several 32
phylogenetic species which present some genetic and serological differences. The 33
diversity presented among isolates of the same genus has been explored in several 34
microorganisms. There have also been attempts to clarify differences that might be related 35
to virulence existing in isolates that cause the same disease. In this work, we analyzed the 36
secretome of two isolates in the Paracoccidioides genus, isolates Pb01 and PbEpm83, and 37
performed infection assays in macrophages to evaluate the influence of the secretomes of 38
those isolates upon an in vitro model of infection. The use of a label-free proteomics 39
approach (LC-MSE) allowed us to identify 92 proteins that are secreted by those strains. Of 40
those proteins, 35 were differentially secreted in Pb01, and 36 in PbEpm83. According to 41
the functional annotation, most of the identified proteins are related to adhesion and 42
virulence processes. These results provide evidence that different members of the 43
Paracoccidioides complex can quantitatively secrete different proteins, which may 44
influence the characteristics of virulence, as well as host-related processes. 45
46
Keywords: Paracoccidioides species; macrophage infection; secretome; label-free 47
proteomics; virulence factors. 48
49
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1. Introduction 50
Fungi of the Paracoccidioides genus are the causative agents of 51
paracoccidioidomycosis (PCM) – a prevalent systemic mycosis in Latin America (Restrepo 52
& Tobon 2005). These fungi present thermal dimorphism, growing in the environment as 53
mycelium, the saprobiotic form, in temperatures below 28°C, and as yeast cells at 36°C in 54
human host tissues (Restrepo 1985). The mycelia form produces conidia that act as 55
infectious propagules, which, when inhaled, suffer dimorphic transition in the lungs, 56
resulting in the pathogenic yeast form (Brummer et al. 1993; Borges-Walmsley et al. 57
2002). The disease evolution and the manifestation of clinical forms depend on 58
immunological factors (Franco et al. 1987), the virulence levels of the fungus isolates 59
(San-Blas & Niño-Vega 2001), and the host gender (Restrepo et al. 1984). 60
The Paracoccidioides genus is currently subdivided into five species, namely P. 61
lutzii, P. brasiliensis, P. americana, P. restrepiensis and P. venezuelensis (Turissini et al. 62
2017), based on genotypic studies and geographic distribution. Diversity presented among 63
isolates of the same genus has been explored with regard to various microorganisms, 64
including Paracoccidioides. These studies have used various approaches in an attempt to 65
characterize biochemical and molecular differences that can reflect on the virulence of 66
isolates that cause the same disease (Kurokawa et al. 2005; Carvalho et al. 2005; Pigosso 67
et al. 2013; Siqueira et al. 2016). 68
Many of the virulence factors of medically-important pathogenic fungi are related to 69
extracellular proteins. These act on the adverse environment of the host, combatting the 70
immune response, and leading to successful infection (Kniemeyer & Brakage 2008; 71
Ranganathan & Garg 2009; Holbrook et al. 2011). It is clear that extracellular proteins play 72
an essential role in fungal-infection strategies, acting on the molecular dialogue with the 73
host cells, enabling survival, multiplication, pathogen dissemination, as well as in 74
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modulation of host defenses (Ranganathan & Garg 2009; Silva et al. 2012). Secretome 75
characterization of microorganisms has been widely explored (Sorgo et al. 2010; 76
Rampitsch et al. 2013; Campbell et al. 2015), and through this characterization it is 77
possible to identify new fungal virulence factors. In Paracoccidioides, proteins such as 78
heat shock proteins, thioredoxin, superoxide dismutase, catalases, TCTP family proteins, 79
disulfide isomerase, secreted serine proteinase - are all involved in cell rescue, defense, and 80
virulence, and have been described in this milieu (Vallejo et al. 2012; Weber et al. 2012; 81
Pigosso et al. 2017). 82
Some Paracoccidioides spp. proteins that play an important role in the virulence of 83
the fungus against the host have been identified in extracellular environments. In this 84
context, adhesion can mediates host-fungi interactions during infection. Enolase, 14-3-3 85
protein, fructose-1,6-bisphosphate aldolase, triose phosphate isomerase, glyceraldeyde-3-86
phosphate dehydrogenase, and glycoprotein gp43 have been described as Paracoccidioides 87
adhesins (Barbosa et al. 2006; Pereira et al. 2007; Donofrio et al. 2009; Nogueira et al. 88
2010; Chaves et al. 2015; Oliveira et al. 2015). A recent study has provided molecular 89
details of the interaction between P. brasiliensis and extracellular matrix (ECM) 90
components, using in vitro cellular models and adherence assays. It has shown that the 91
peptide 1 (NLGRDAKRHL) from gp43 contributes to P. brasiliensis’ adhesion to Vero 92
cells (Mendes-Giannini et al. 2006). Using antisense RNA (aRNA) technology, Torres and 93
collaborators correlated low gp43 expression with lower P. brasiliensis pathogenicity in 94
the mice model of infection, noting the protein involvement in fungal virulence (Torres et 95
al. 2013). The role of the 30 kDa protein of P. brasiliensis as adhesin was also 96
demonstrated in the ex vivo model of infection (Andreotti et al. 2005). In addition, 97
Paracoccidioides secretes a serine proteinase during the murine model of infection 98
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(Pigosso et al. 2017). However, a comparison between members of the genus has not yet 99
been established. 100
The majority of information about the eco-epidemiology, infection, and 101
Paracoccidioidomycosis has been obtained in studies that did not distinguish between the 102
species involved (Martinez 2017). Taking this into account, we performed the 103
characterization of the extracellular proteome profile between two members of the genus 104
Paracoccidioides, namely Pb01 (P. lutzii) and PbEpm83 (P. restrepiensis). In addition, we 105
performed infection assays in macrophages, which allowed us to suggest that the fungus 106
can modify their secretome, influencing their behavior in infection. This is the first 107
comparative study between Paracoccidioides members of the extracellular proteome, and 108
it will provide a significant set of data for future research. Finally, our data brings an 109
important dataset of putative virulence/antigenic molecules from the Paracoccidioides 110
genus. These data serve to highlight molecules that need to be explored further in order to 111
better understand Paracoccidioides pathobiology. 112
113
2. Material and methods 114
2.1. Microorganisms and culturing conditions 115
Paracoccidioides, isolates Pb01 (ATCC MYA-826) (Carrero et al. 2008) and 116
PbEpm83 (Theodoro et al. 2008; Machado et al. 2013) were used in this study. 117
Paracoccidioides isolates were both from chronic PCM. Pb01 was isolated from a patient 118
from the state of Goiás, Brazil (Central-Western region), and PbEpm83 from a patient 119
from Bogota (Colombia). The conidia production also differs between these two species. 120
Paracoccidioides lutzii isolates produced an intermediate to high number of conidia, while 121
P. restrepiensis isolates were unable to generate conidia, when incubated in the media 122
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containing potato dextrose agar and Soil Extract Agar. This may explain the delimited 123
distribution of this species (Theodoro et al. 2012). 124
The yeast cells were maintained in BHI solid medium [Brain Heart Infusion] (pH 125
7.0), plus 4% glucose (w/v), 1% agar (w/v) in weekly samplings at 36 ºC for 5 days. The 126
viability, cell growth and vitality assays were performed with a Trypan Blue (Sigma 127
Aldrich), cell counting on hemacytometer and quantification of glucose consumption 128
(Doles), respectively. 129
130
2.2. Preparation of extracellular extracts 131
The yeast extracellular proteins from Paracoccidioides isolates Pb01 and PbEpm83 132
were prepared as previously described (Weber et al. 2012). In brief, the yeast cells from 133
the isolates were obtained by inoculating 50 µg/mL of wet weight cells in BHI liquid 134
medium. They were then maintained at 36ºC for 24 hours under shaking (150 rpm). 135
Afterwards, the cells were removed by centrifugation at 10,000 x g at 4°C for 30 minutes. 136
The culture supernatants were sequentially filtered through 0.45 and 0.22 µm-pore-size 137
membrane filters. The filtrates were concentrated and then washed three times with 138
ultrapure water by centrifugation through a 10 kDa molecular weight cut-off in Ultracel® 139
regenerated membrane (Amicon Ultra centrifugal filter, Millipore, Bedford, MA, USA). 140
The absence of cell lysis was performed as previously described (Weber et al. 2012) (data 141
not shown). Protein concentrations were determined by the Bradford method (Bradford 142
1976). For the proteomic analysis, three biological replicates of protein samples from three 143
independent experiments were obtained for each Paracoccidioides isolate. 144
145
2.3. Mass spectrometry analysis by nanoUPLC-MSE 146
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The yeast extracellular proteins from Paracoccidioides isolates were analyzed by 147
using the label-free nanoUPLC-MSE approach. An equal amount of each sample (150 µg) 148
was prepared for nanoUPLC-MSE, as previously described (Murad et al. 2011; Lima et al. 149
2014; Bailão et al. 2014). Samples were subjected to the action of 0.2% (v/v) of RapiGest 150
SF™ surfactant (Waters Corporation, Milford, MA) at 80°C for 15 minutes. In order to 151
make the protein more accessible to alkylation and digestion, 2.5 µL of 100 mM DTT 152
(Dithiotreitol, GE Healthcare) was added at 60°C for 15 minutes. Next, 2.5 µL of 300 mM 153
iodoacetamide (GE Healthcare) was added, and the samples were incubated at room 154
temperature for 30 minutes for cysteines alkylation, while being protected from the light. 155
The protein samples were digested with 40 µL of 50 ng/µL trypsin (Promega, Madison, 156
WI, USA) at 37°C for 16 hours. After digestion, 30 µL of trifluoroacetic acid (TFA) 157
(Sigma-Aldrich) 5% (v/v) was added to the samples. The mixture was left at 37°C for 90 158
minutes in order to precipitate the surfactant. Afterwards, the samples were submitted to 159
centrifugation at 18,000 x g, at 6°C for 30 minutes. The supernatant was transferred to new 160
tubes and dried under vacuum. The precipitate was resuspended in 30 µL of ultrapure 161
water and submitted to further purification with ZipTips® Pipette Tips (ZipTips® Pipette 162
Tips C18, Millipore, Bedford, MA, USA). Peptides were dried again under vacuum and 163
resuspended in ammonium formate (20 mM). In order to quantify the proteins, rabbit 164
phosphorylase B (PHB) (MassPREPTM Digestion Standard) was used. The final 165
concentration of PHB was 200 fmol/µL to Pb01 sample and 250 fmol/µL to PbEpm83 166
sample. 167
The digested peptides were further analyzed via nanoUPLC-MSE by using a 168
nanoACQUITYTM system coupled to Synapt G1 MS™ mass spectrometer (Waters 169
Corporation, Manchester, UK). The [GLU1]-Fibrinopeptide B (GFB) was used as a lock 170
mass for calibration during the sample’s analysis. The UPLC-MSE spectra that was 171
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obtained was then processed and examined using the ProteinLynx Global Server (PLGS) 172
version 2.4 (Waters Corporation, Manchester, UK). The raw data were searched against the 173
Paracoccidioides spp. database 174
(http://www.broadinstitute.org/annotation/genome/paracoccidioides_brasiliensis/MultiHo175
me.html) using algorithms previously described in correct and reverse sequences (Li et al. 176
2009). The tables generated by PLGS were processed as previously described (Murad & 177
Rech 2012; Lima et al. 2014; Bailão et al. 2014). Graphics indicating the quality of the 178
proteomic data (dynamic detection range, type of peptides fragmentation and peptide mass 179
identification accuracy) were generated using the FBAT software (Laird and Horvath, 180
2000), MassPivot (kindly provided by Dr. Andrew M. Murad) Spotfire® (TIBCO Software 181
Inc. ©) and Microsoft Office Excel (Microsoft ©) programs. Furthermore, only those 182
proteins that presented 1.3-fold differences in expression values were considered to be 183
regulated. 184
185
2.4. Bioinformatics Analysis 186
The identified proteins were functionally classified according to the MIPS Functional 187
Catalogue Database (http://mips.helmholtz-muenchen.de/funcatDB/) using query tools 188
available online, such as Pedant 189
(http://pedant.gsf.de/pedant3htmlview/pedant3view?Method=analysis&Db=p3_r48325_Pa190
r_lutzi), UniProt (http://www.uniprot.org/) and the National Center for Biotechnology 191
Information (NCBI) (https://www.ncbi.nlm.nih.gov/). Hypothetical and conserved 192
proteins were submitted to the BlastP tool (Basic Local Alignment Search Tool; 193
https://blast.ncbi.nlm.nih.gov/Blast.cgi) from NCBI to search for sequence similarities and 194
conserved domains in order to find some function related to non-classified proteins. Venn 195
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diagrams were constructed by using the Venny 2.1 tool 196
(http://bioinfogp.cnb.csic.es/tools/venny/index.html). 197
With regard to the secretion pathways prediction, the detected proteins were also 198
subjected to analysis in the online algorithm SignalP 3.0 199
(http://www.cbs.dtu.dk/services/SignalP) in order to determine the presence of the signal 200
peptide. Proteins with a signal peptide sequence were considered as being secreted by a 201
classical pathway, and the standard cut-offs of the algorithm were adopted. In addition, we 202
used the SecretomeP 2.0 algorithm (http://www.cbs.dtu.dk/services/SecretomeP) to predict 203
proteins secreted by non-classical or alternative pathways, adopting the cut-off suggested 204
by the software. In addition, TargetP 1.0 (http://www.cbs.dtu.dk/services/TargetP-1.0/), 205
TMHMM 2.0 (http://www.cbs.dtu.dk/services/TMHMM/), PredGPI 206
(http://gpcr.biocomp.unibo.it/predgpi/pred.htm), and WolF PSORT 207
(http://wolfpsort.seq.cbrc.jp/) predictive servers were also used in order to evaluate the 208
subcellular location, contributing to discard false positive, as employed previously by 209
Beys-da-Silva et al. (2014). 210
Moreover, the identified protein sequences were analyzed by Antigenics Pasteur 211
software (http://mobyle.pasteur.fr/cgi-bin/portal.py?#forms::antigenic), which searched for 212
potential antigenic epitopes within the protein sequences. The adhesin prediction analysis 213
was also performed by using the FaaPred server (Fungal adhesins and Adhesin-like 214
Proteins Prediction; http://bioinfo.icgeb.res.in/faap/) (Ramana & Gupta 2010) by adopting 215
software default settings. 216
217
2.5. Immunoblotting analysis 218
Extracellular extracts (40 µg) were fractionated by 12% SDS-polyacrylamide gel 219
electrophoresis (SDS-PAGE). After gel electrophoresis, proteins were stained with 220
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Coomassie Blue R or transferred to a Hybond™ ECL™ Membrane (GE Healthcare Life 221
Sciences). Membranes were blocked with blocking buffer [1X PBS, 10% (w/v) skim milk, 222
0.1% (v/v) Tween 20] for 2 hours at room temperature. After blocking, the membranes 223
were washed with wash buffer [1X PBS, 0.1% (v/v) Tween 20] and incubated under 224
agitation with specific primary antibodies for 1 hour at room temperature. Afterwards, the 225
membranes were washed three times, followed by incubation with secondary antibodies 226
conjugated with alkaline phosphatase for 1 hour at room temperature. Labelled bands 227
detection was carried out using a 5-bromo-4-chloro-3-indolylphosphate/nitroblue 228
tetrazolium (BCIP/NBT) protocol. The antibodies used for this analysis were: anti-enolase 229
(1:40,000) (Nogueira et al. 2010); anti-triosephosphate isomerase (1:1,000) (Pereira et al. 230
2007), anti-glyceraldehyde 3-phosphate dehydrogenase (1:5,000) (Barbosa et al. 2006), 231
anti-aldolase (1:5,000) (Chaves et al. 2015), and anti-formamidase (1:1,000) (Borges et al. 232
2010). Raw Tiff images were analyzed by densitometry of immunoblotting bands using the 233
ImageJ 1.51 software. The pixel intensity of the analyzed bands was generated and 234
expressed as arbitrary units. 235
236
2.6. Measurement of formamidase activity 237
Formamidase activity (FMD) was assessed by the ammonia formation from the 238
formamide hydrolysis (Borges et al. 2005). The test was performed with 1µg of total 239
protein extract. The volume was adjusted to 250 µL with formamide + PEB buffer (100 240
mM formamide, 100 mM sodium phosphate and 10 mM EDTA, pH 7.4). The samples 241
were incubated at 37°C for 30 minutes to allow formamidase enzymatic activity. After 242
that, 400 µL of sodium phenol-nitroprusside and 400 µL of alkaline solution (Sigma 243
Aldrich, Co.) were added. The samples were incubated at 50°C for 6 minutes and the 244
absorbance read at 625nm. The amount of ammonia formed was determined by 245
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comparison with a standard curve. One unit (U) of formamidase-specific activity 246
corresponds to the amount of enzyme required to hydrolyze 1 mmol of formamide 247
(corresponding to the formation of 1 mmol of ammonia)/min/mg of total protein (Bury-248
Moné et al. 2003). 249
250
2.7. Macrophage model of infection 251
The macrophage infection assay was conducted as previously described (Lima et al. 252
2014; Bailão et al. 2014), with some modifications. Macrophages, cell line J774 A.1 (Rio 253
de Janeiro Cell Bank – BCRJ/UFRJ, accession number: 0121), were maintained in RPMI 254
medium (RPMI 1640, Vitrocell, Brazil), with 10% (v/v) FBS at 37°C in a 5% CO2 255
incubator chamber. The assay in J774 macrophage cells was conducted in the proportion of 256
1:5 (macrophages:fungi cells) in order to favor the fungal internalization. A total of 1 x 106 257
macrophages cells was distributed in 12 well culture plates, with RPMI medium, plus 100 258
U/mL IFN-γ (PeproTech, Rocky Hill, NJ, USA) and incubated at 37°C, 5% CO2 for 16 259
hours. For infection, 5 x 106 Paracoccidioides yeast cells were added to plate wells 260
presenting adherent macrophages. The experimental infection had a course of 12 and 24 261
hours, incubated at 5% CO2 and at 37°C. The recovered Paracoccidioides cells inside 262
macrophages were plated on BHI solid medium (4% glucose and 4% FBS), and the growth 263
of colonies was evaluated on the 12th day after infection. 264
To evaluate the secretome influence on the Paracoccidioides-macrophages 265
adhesion/interaction, a phagocytosis assay was conducted as described above by adding 266
100 µg of secreted protein extract together with Paracoccidioides yeast cells, followed by 267
incubation at 37°C and 5% CO2, for 12 hours and 24 hours. After incubation, the cells were 268
washed 3 times with 1X PBS to remove Paracoccidioides non-adhered cells. Then, the 269
macrophage cells were lysed with cold ultrapure water 3 times for 5 minutes. Fungal cells 270
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were recovered in 500 µL of saline solution (NaCl 0.9%), and 100 µL were plated on BHI 271
solid medium supplemented with 4% FBS, which was incubated at 37°C. The growth of 272
the colonies could be observed from the 5th day, and the counting of colony-forming units 273
(CFUs) was performed on the 12th day. All infection assays were performed in biological 274
and experimental triplicates and the data were presented as the mean ± standard deviation 275
of replicates. Statistical analysis was carried out using the Student’s t-test, and p-values ≤ 276
0.05 were considered statistically significant. 277
278
3. Results 279
3.1. Label-free Proteomic analysis of Paracoccidioides isolates 280
In order to verify the in vitro cellular behavior between strains, viability, growth, and 281
vitality assays were performed. As shown in Supplementary Figure S1, the strains behave 282
similarly. These data demonstrate that the in vitro conditions do not show any experimental 283
bias on the analyzes. In addition, the quality of the extracellular protein extracts was 284
evaluated by using SDS-PAGE assay. Supplementary Figure S2 shows good protein 285
extract integrity, as well as it was possible to observe a distinct protein pattern between the 286
samples of isolates. The dynamic range chart depicted measure abundance of 3 to 3.5 287
orders of magnitude, indicating a satisfactory detection distribution of a high and low 288
proteins concentrations levels (Supplementary Figure S3 panel A). Most of the peptides 289
identified in Pb01 and PbEmp83 secretomes presented less than 15 ppm of error, which 290
can be seen in Supplementary Figure S3 panel B. Supplementary Figure S3 panel C depicts 291
that 44 and 50% of those peptides were obtained from peptide match type data in the first 292
pass (PepFrag 1) to Pb01 and PbEpm83, respectively; a total of 6% of the peptides were 293
obtained for both isolates in the second pass (PepFrag 2); 16 and 15% were identified by a 294
missed trypsin cleavage, whereas insource fragmentation rates of 17 and 13% were related 295
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to Pb01 and PbEpm83, respectively. Altogether, these results show that all proteomic data 296
is of a good quality. 297
298
3.2. An overview of the extracellular proteome profiles 299
Proteomic data from the Paracoccidioides spp. extracellular extract acquired by 300
nanoUPLC-MSE resulted in the identification of 92 proteins (Supplementary Table S1). 301
From the 92 proteins identified, 35 were upregulated in Pb01 (Fig. 1 panel A, Table 1) 302
and 36 were upregulated in PbEpm83 (Fig. 1 panel A, Table 2). The remaining 21 303
proteins, which showed no statistical differences in the detected amounts between the 304
isolates, were grouped as constitutive proteins (Fig. 1 panel A, Supplementary Table S2). 305
Additionally, all identified protein sequences were subjected to prediction software 306
of protein secretion pathways and subcellular location, revealing concordant results. Of 35 307
proteins differentially secreted in Pb01, 15 (42.8%) possess a signal peptide predicted by 308
SecretomeP (Fig. 1 panel B, Table 1). Of 36 extracellular proteins differentially secreted 309
in PbEpm83, 2 (5.5%) proteins possess a signal peptide predicted by SignalP, whereas 13 310
(36.1%) proteins were predicted by SecretomeP (Fig. 1 panel B, Table 2). These data 311
were compared with the Fungal Secretome Database (FSD), which is a platform of several 312
secretomes of fungal species that provides information on protein secretion pathways in 313
these microorganisms. The FSD describes that 58% of the genome-encoded proteins of 314
Pb01 are secreted by presumably non-classical routes and 14% by the conventional route, 315
being 4.4% predicted by SignalP. This highlights the fact that the vast majority of proteins 316
secreted by this species use alternatives routes of secretion, which is in accordance with 317
our data. 318
The eight most abundant extracellular proteins in each isolate, which correspond to 319
30% of the total number of secreted proteins, include: enolase (7%), fructose-1,6-320
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bisphosphate aldolase (5.5%), nucleoside diphosphate kinase (5%), 2-methylcitrate 321
synthase (3.5%), phosphoglycerate kinase (2.5%), heat shock protein SSC1 (2.4%), 322
thioredoxin (2.2%), and transaldolase (2%) in PbEpm83; while hsp70-like protein (10%), 323
enolase (5%), 2-methylcitrate dehydratase (3%), 2-methylcitrate synthase (2.7%), 324
nucleoside diphosphate kinase (2.5%), heat shock protein SSC1 (2.6%), malate 325
dehydrogenase (2.4%), and phosphoglycerate kinase (2.3%) were abundant in Pb01. 326
The extracellular proteins were also classified into functional categories according to 327
the MIPS Functional Catalogue database (FunCatDB) (Fig. 1 panel C). The main classes 328
identified were related to metabolism, energy, protein synthesis, protein fate, and cell 329
rescue/defense/virulence. Among the identified proteins are many defense proteins which 330
function as chaperones (heat shock proteins). They form an important part of the cellular 331
machinery to make the correct protein folding and help to protect cells against stress. Pb01 332
isolate was shown to differ from PbEpm83 with regard to two functions, namely transport 333
and proteins with binding functions. While biogenesis of cellular compounds and 334
differentiation of cell types was detected only in PbEpm83. Proteins with unusual 335
functional categories in the extracellular milieu were described in other Paracoccidioides 336
extracellular proteomes. This indicates that these proteins may have a secondary function 337
outside of the fungal cells. 338
Next, we compared the identified extracellular proteins of Pb01 and PbEpm83 with 339
orthologous proteins described in Pb18 (Vallejo et al. 2012) and H. capsulatum 340
(Albuquerque et al. 2008), as depicted in Figure 2. The comparison demonstrated that 14 341
secreted proteins were identified in the four strains analyzed. On the other hand, some 342
extracellular proteins were only detected in Pb01 secretome (decarboxylase family protein 343
- PAAG_03537; homogentisate 1,2-dioxygenase - PAAG_08164; nuclear transcription 344
factor Y subunit C - PAAG_08441, suaprga1 - PAAG_03309), while others 17 345
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extracellular proteins were detected only in PbEpm83 (isochorismatase family hydrolase - 346
PAAG_04083; ssDNA binding protein- PAAG_07296; 12-oxophytodienoate reductase - 347
PAAG_03631; aromatic-L-amino-acid decarboxylase - PAAG_01563; cysteine synthase - 348
PAAG_07813; glutathione S-transferase Gst3 - PAAG_03931; heat shock protein - 349
PAAG_05679; HET-C domain containing protein HetC - PAAG_03921; hexokinase - 350
PAAG_01015; sulfate adenylyltransferase - PAAG_05929; uracil 351
phosphoribosyltransferase - PAAG_06643; UTP-glucose-1-phosphate uridylyltransferase - 352
PAAG_06817; two conserved hypothetical protein - PAAG_00340/PAAG_07921 and 353
three hypothetical proteins – PAAG_02985/PAAG_05550/PAAG_07158). This analysis 354
demonstrates that isolates of Paracoccidioides genus present many common proteins when 355
compared with the characterized Histoplasma extracellular proteome. The data reinforce 356
the sharing of extracellular proteins between Paracoccidioides species and the pathogenic 357
fungus H. capsulatum (Xavier et al. 2009). 358
For the purpose of validate the proteomic data, we performed immunoblot and 359
enzymatic activity assays. The proteomic data revealed the enzymes formamidase and 360
fructose-1,6-bisphosphate aldolase as differentially secreted in PbEpm83. Triosephosphate 361
isomerase and glyceraldehyde-3-phosphate dehydrogenase were found as differentially 362
secreted in Pb01. These results can be confirmed by the fact that the protein species reacts 363
against to its respective antibodies with a high intensity, as depicted in the immunoblotting 364
analysis (Fig. 3). Enolase, which is a very abundant protein in Paracoccidioides, was 365
identified as constitutive in our analyses. It reacted strongly and similarly in 366
immunoblotting, corroborating its constitutive expression between the two isolates (Fig. 367
3). In addition, the specific activity of enzyme formamidase was measured in extracellular 368
extracts of Pb01 and PbEpm83 by enzymatic assay. The test showed that this enzyme is 369
functionally active in both extracts. A higher activity was detected in the PbEpm83 370
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secreted sample, indicating increased enzyme activity in this condition compared with the 371
Pb01 isolate, corroborating the proteomic results (Fig. 4). 372
373
3.4. Proteins involved in adherence and virulence 374
In order to list possible proteins involved in adherence, the proteins were submitted 375
to FaaPred software (Fungal adhesins and adhesin-like proteins prediction tool) which is 376
designed to predict adhesins from human pathogenic fungi. The analysis showed 17 377
adhesin-like proteins, representing almost 20% of the total of identified proteins, amongst 378
them 3 hypothetical proteins, 1 thioredoxin, and 1 heat shock protein. Eight proteins were 379
differentially secreted in Pb01, 6 differentially secreted in PbEpm83, and 3 with no 380
differential expression between the isolates (Table 3). 381
In addition, the search for proteins related to antigenicity and virulence was carried 382
out using Antigenics Pasteur software. It was possible to verify that all identified proteins 383
present antigenic hits that may be important in host–fungus interaction. Also, the proteins 384
identified in Paracoccidioides isolates were searched in digital databases such as PubMed 385
of the National Center for Biotechnology Information (NCBI) for the identification of 386
virulence factors already described in other pathogenic fungi in literature. We found that 387
18 proteins detected in our analysis are described as virulence factors, such as: mannitol-1-388
phosphate 5-dehydrogenase, dipeptidyl peptidase, alcohol dehydrogenase, mitochondrial 389
peroxiredoxin PRX1, fructose-1,6-bisphosphate aldolase, enolase, and heat shock protein 390
Hsp88. These proteins are involved in many processes related to virulence, such as 391
antioxidant activities, protection against reactive oxygen species (ROS), decreased 392
susceptibility to phagocytes, adhesive properties, as well as interaction with components of 393
the extracellular matrix (ECM) (Table 4). 394
395
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3.5. Macrophage Infection Assay 396
It is known that species from the same genus can present morphological and 397
biochemical differences that may reflect in different behaviors and skills with regard to 398
infection. As a result, we sought to evaluate the behavior of two members of different 399
phylogenetic species of Paracoccidioides, Pb01 and PbEpm83, with reference to 400
macrophage infection. The results show that Paracoccidioides species display similar 401
behaviors within 12 hours of infection with regard to the number of recovered cells. It is 402
similar in both species (360 and 362 CFU/mL from Pb01 and PbEpm83 respectively) (Fig. 403
5 panel A). However, with the course of infection, Pb01 was shown to be more resistant to 404
the macrophage environment compared with PbEpm83, and had a higher number of 405
recovered cells after 24 hours of infection (436 and 252 CFU/mL from Pb01 and 406
PbEpm83, respectively) (Fig. 5 panel B). Taking into account that the secretome of 407
pathogenic microorganisms can be directly involved in the host cell interaction, it is 408
evident that the secretome is very important in the early stages of infection. To evaluate the 409
effect of the secretome, the extracellular protein extract from both isolates was added to 410
macrophage infection assay (Fig. 5 panels A, B, C and D). The results showed that the 411
CFU increased slightly considering both evaluated times of infection. This data reinforces 412
the influence of secreted proteins in Paracoccidioides adhesion/internalization/survival in 413
activated macrophages. 414
In order to assess the secretome influence between the species, the secretome protein 415
extracts were cross-tested between species to check the effect of secretomes in this in vitro 416
model of infection. After 12 hours of phagocytosis assay of Pb01 + SPb01 (secretome 417
from Pb01), and Pb01 + SPbEpm83 (secretome from PbEpm83), it was possible to 418
visualize a survival increase of 30 and 7 %, respectively (Fig. 5 panel C). In addition, we 419
tested PbEpm83 + SPbEpm83 and PbEpm83 + SPb01, which presented an increasing rate 420
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of 26 and 16%, respectively (Fig. 5 panel D). After 24 hours of assay we detected an 421
increasing rate of 60 and 29% to Pb01 + SPb01 and Pb01 + SPbEpm83 (Fig.5 panel C) 422
and 45 and 13% to PbEpm83 + SPbEpm83 and PbEpm83 + SPb01, respectively (Fig. 5 423
panel D). Statistical differences between the confronted conditions are presented in bars. 424
Both secretomes also increased the number of CFU recovered, but this effect was less 425
pronounced than when exposed to the additional secretome of their own species. 426
427
5. Discussion 428
Several factors may influence the isolate’s virulence at the time of infection, and 429
these factors may act differently in members of a defined genus. A recent work has shown 430
that P. brasiliensis presents a faster conversion of yeast to mycelium, larger colonies and 431
greater conidia production. In addition, P. brasiliensis and P. lutzzi presented different 432
abilities to grow after long periods under stress conditions, being P. brasiliensis more 433
tolerant in these conditions, suggesting increased chances of causing infection (Hrycyk et 434
al. 2017). In the current study, the secretome profile comparison between two 435
Paracoccidioides complex members was described to search for secreted molecules that 436
may be related to the mechanisms of virulence released by different species from the same 437
genus. Using a label-free MSE proteomics approach, we identified a total of 92 proteins, 71 438
of which were differentially expressed between the strains, while 21 were described as 439
constitutive (considering a cut-off of 1.3-fold change). Among the proteins identified in 440
this study, there are proteins related to various biological functions, such as carbohydrate 441
metabolism, energy processes, synthesis and protein fate, oxidation/reduction, transport, 442
cell signaling, defense and virulence, which is in accordance with descriptions of 443
secretome profiles in previous works (Holbrook et al. 2011; Vallejo et al. 2012; Weber et 444
al. 2012; Gil-Bona et al. 2015). 445
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Many of the proteins found in our work, such as heat shock proteins, glyceraldehyde-446
3-phosphate dehydrogenase, mannitol-1-phosphate 5-dehydrogenase, triose phosphate 447
isomerase, fructose-1,6-bisphosphate aldolase, peptidyl-prolyl cis-trans isomerase, and 448
disulfide isomerase, were also found in vesicles secreted by Histoplasma capsulatum 449
(Albuquerque et al. 2008). Characterization studies of extracellular vesicles have also been 450
widely explored in Cryptococcus neoformans (Rodrigues et al. 2008, 2014; Oliveira et al. 451
2010); proteomic analysis of vesicles revealed a further 76 proteins and various others 452
related to virulence and protection against oxidative stress, such as capsule synthesis, 453
urease, laccase, heat shock proteins, superoxide dismutase, thioredoxin reductase, and 454
catalase A (Rodrigues et al. 2008). Some of them were also found in our secretome 455
analysis. These findings reinforce the idea that fungi have mechanisms for removing some 456
classical cytoplasmic proteins from their cells in order to help the microorganisms in non-457
classical functions in this milieu. 458
The classical mechanism of secretion involves release via endoplasmic reticulum 459
(ER) and Golgi apparatus, guided by the signal peptide (Blobel & Dobberstein 1975). 460
However, it has been shown that numerous proteins are secreted without the signal 461
sequence, suggesting the existence of non-classical transport routes (Nombela et al. 2006; 462
Nickel & Rabouille 2009). Our prediction analysis shows that most extracellular proteins 463
identified in this work use alternative mechanisms of secretion (Fig. 1 panel B), which is 464
consistent with the literature (Cuervo et al. 2009). In Paracoccidioides, glyceraldehyde-3-465
phosphate dehydrogenase – GAPDH (Barbosa et al. 2006), triose phosphate isomerase – 466
TPI (Pereira et al. 2007), and enolase - ENO (Nogueira et al. 2010), have been described 467
in the extracellular environment, where their behavior is supposed to differ from the 468
classical behaviors. 469
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A variety of studies have addressed secreted proteins and their functions in the 470
extracellular environment (Tsang et al. 2009; Sorgo et al. 2010; Wang et al. 2011; Fekkar 471
et al. 2012; Rampitsch et al. 2013; Campbell et al. 2015) including in Paracoccidioides 472
(Vallejo et al. 2012; Weber et al. 2012; Chaves et al. 2015). A vesicle and vesicle-free 473
protein study in Paracoccidioides brasiliensis isolated Pb18, and revealed some secreted 474
proteins performing functions related to infection, immune response modulation, as well as 475
adhesion to the extracellular matrix components (Vallejo et al. 2012). 476
Adhesion is an important pathogenicity factor in a variety of pathogenic 477
microorganisms. A study in Paracoccidioides demonstrated that 14-3-3 and enolase are the 478
most highly expressed adhesins during pathogen-host interaction and identified higher 479
levels of adhesin expression in P. brasiliensis when compared with P. lutzii, and correlated 480
this with the increased in vivo virulence of the fungus (Oliveira et al. 2015). Among the 481
most abundant extracellular proteins that we identified in the Paracoccidioides species, the 482
adhesion skill is the most relevant of them. Our findings showed a similar amount of 483
adhesin expressed for both Pb01 and PbEpm83 isolates. 484
Secretome analysis of P. lutzii showed that approximately 21% of identified proteins 485
were predicted as adhesin-like proteins. Also, eighteen extracellular proteins were found in 486
the cytoplasm of macrophages experimentally infected by P. lutzii, suggesting that the 487
fungus uses secreted proteins as one of the strategies to gain a successful infection (Weber 488
et al. 2012). The proteins ATPase alpha, elongation factor 1-alpha subunit, and malate 489
dehydrogenase were found as being up-regulated in PbEpm83. The proteins DNA damage 490
checkpoint rad24, glyceraldehyde-3-phosphate dehydrogenase, nucleoside diphosphate 491
kinase, and peptidyl-prolyl cis-trans isomerase D, were found as up-regulated in Pb01. 492
These findings reinforce the hypothesis that these secreted proteins can help fungal 493
survival within macrophages/host tissues. 494
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The infectious process involves the adhesion of fungus to host cells and theirs 495
components. In this context, pathogens express molecules that can interact, for example, 496
with human plasminogen and end up favoring the pathogen spread to deeper tissues. 497
Studies show fructose-1,6-bisphosphate aldolase, 2-methylcytrate synthase, malate 498
dehydrogenase and phosphoglycerate kinase as plasminogen binders in the 499
Paracoccidioides secretome (Chaves et al. 2015); phosphoglycerate kinase, fructose-1,6-500
bisphosphate aldolase and thioredoxin, also as a plasminogen ligant, found on Candida cell 501
wall (Crowe et al. 2003). The fructose-1,6-bisphosphate aldolase, enolase, heat shock 502
SSC1, and nucleoside diphosphate kinase, were described as adhesin-like molecules, 503
identified during copper-deprivation conditions in Paracoccidioides lutzii (Pb01) in the 504
presence of extracellular matrix components (Oliveira et al. 2014). Our group identified 505
fifteen extracellular proteins with plasminogen binding ability. Of these, fructose-1,6-506
bisphosphate aldolase (FBA) was able to increase the fungus-macrophages interaction and 507
was found in vesicles in the releasing process (Chaves et al. 2015). In this work FBA was 508
identified suggesting its participation in the invasiveness capacity of fungal. 509
Many extracellular identified proteins related to defense and virulence were 510
identified in our analysis. Among the virulence functions described in other fungi (Hogan 511
et al. 1996; Crowe et al. 2003; Brown et al. 2007; Karkowska-kuleta et al. 2009; Oh et al. 512
2010; Viefhues A, Heller J, Temme N 2014) there is the ability of secreted proteins to act 513
as adhesins, allowing pathogen invasion of the host tissues, such as glucose-6-phosphate 514
isomerase in Cryptococcus neoformans, which interacts with plasminogen (Stie et al. 515
2009) or cellular detoxification with GST in Candida albicans (Garcerá et al. 2010). In the 516
category of cell rescue, defense and virulence (RDV) protection proteins such as 517
chaperones and foldases are included. They comprise part of the machinery of cells against 518
stress, and assist in the correct folding of nascent secretory proteins. Peptidyl-prolyl 519
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isomerases are foldases which catalyze the cis - trans isomerization of peptide bonds N-520
terminal proline residues in polypeptide chains. They play a role in correct folding of 521
newly synthesized proteins, which is an important step in maintaining the structure and 522
function of proteins (Shaw 2002). In our analysis many chaperones (six heat shock 523
proteins) and foldases (three peptidyl-prolyl cis-trans isomerase and one disulfide 524
isomerase) were identified. Of these, peptidyl-prolyl cis-trans isomerase D was also found 525
as secreted protein in Pb01 yeast cells infecting macrophages (Weber et al. 2012), 526
suggesting that its appearance in the secretome may be related to the maintenance and/or 527
acceleration of the formation of the final and correct structure of proteins in this 528
environment. 529
During the adaptation of Paracoccidioides cells to changes in temperature and stress 530
conditions in general, there is a significant increase in expression of heat shock proteins 531
(HSPs). In Paracoccidioides, a study using antisense RNA technology described the 532
protective role of heat shock protein HSP90 during adaptation to hostile environments; it 533
promotes the survival of the fungus during host-pathogen interactions (Tamayo et al. 534
2013). The Hsp90 co-chaperone AHA1 and the Hsp90 binding co-chaperone Sba1 were 535
found in this work to be up-regulated in Pb01 isolate. In addition, HSP70 was the most 536
abundant protein in Pb01 secretome. HSP70 was identified as a major target of antibodies 537
in cryptococcose patients (Kakeya et al. 1999), and was previously identified serving as a 538
plasminogen-binding receptor in C. albicans and C. neoformans (Crowe et al. 2003; Stie et 539
al. 2009). 540
In our findings we also found some proteins that present the classical localization on 541
cytosol compartment. Many cytoplasmic proteins have been described in other 542
compartments as having non classical functions; they are known as moonlighting proteins 543
(Karkowska-Kuleta & Kozik 2014; Gil-Bona et al. 2015). A study of virulent and hypo-544
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virulent Cryptococcus strains detected that the secretome of virulent strains has largely 545
been limited to proteolytic and hydrolytic enzymes, while the hypo-virulent strains have a 546
diverse secretome, including non-conventionally secreted cytosolic canonical and 547
immunogenic proteins that have been implicated in virulence (Campbell et al. 2015). In 548
our work, both isolates presented a similar number of identified virulence factors. Until 549
now, it hasn’t been possible to correlate, whether quantitatively or qualitatively, the 550
influence of secretome content on the fitness of the fungus. However, during infection the 551
secretome can act differently for each isolate. In addition, it can also be affected when 552
combined with others factors present in the host milieu. These changes assist the fungus in 553
combating the host defenses, and enables it to achieve infection successfully. 554
Paracoccidioides-secreted proteins such as aconitase, aldolase, glyceraldehyde-3-555
phosphate dehydrogenase, isocitrate lyase, malate synthase, triose phosphate isomerase, 556
fumarase and enolase have also been described as not performing classic functions 557
(Marcos et al. 2014). Of these, aldolase, glyceraldehyde-3-phosphate dehydrogenase, triose 558
phosphate isomerase and enolase were found in our analysis. Besides the glycolytic 559
activities performed by Paracoccidioides enolase, this enzyme presents an affinity for 560
extracellular matrix (ECM) proteins such as fibronectin and laminin. In addition, enolase 561
has the capacity to bind plasminogen, thus facilitating fungal invasion and distribution 562
(Nogueira et al. 2010). Triose phosphate isomerase, which also belongs to the glycolytic 563
pathway, interacts with the ECM components fibronectin and laminin (Pereira et al. 2007; 564
Ikeda & Ichikawa 2014). This enzyme was found up-regulated in Pb01 secretome. Despite 565
not being detected as an adhesin by FaaPred software, it has previously been shown that 566
fructose bisphosphate aldolase interacts with human plasminogen. This interaction 567
promotes an increase in the fibrinolytic ability of the fungus (Chaves et al. 2015), which 568
can play an important role in the establishment of the fungus in host tissues. In addition to 569
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its role in the metabolism of carbohydrates and other cellular functions, the GAPDH 570
enzyme also binds to ECM proteins and is associated with Paracoccidioides infection 571
establishment (Barbosa et al. 2006). The GAPDH enzyme was identified in this work as 572
being up-regulated in Pb01 isolate. 573
In addition, it has been assumed that oxidative stress in response to pathogens 574
includes the production of antioxidants, which are related to pathogenicity. The glutathione 575
S-transferase enzyme found in this work as differentially secreted in PbEpm83 is involved 576
in cellular detoxification processes and protection against oxidative stress produced by the 577
host cell’s defenses (Garcerá et al. 2010). The identification of proteins involved in the 578
oxidative stress response in Paracoccidioides’ extracellular proteome contributes to the 579
possibility that pathogenic fungi release defense molecules that possibly act as virulence 580
factors. DNA damage checkpoint protein rad24, glutathione S-transferase, thioredoxin, 581
alcohol dehydrogenase, thimet oligopeptidase, heat shock proteins and disulfide isomerase, 582
which were identified in this work, have already been described as upregulated expression 583
in Paracoccidioides, after exposure to oxidative stress (Grossklaus et al. 2013). It 584
demonstrates that both isolates studied present mechanisms for reacting against oxidative 585
stress, and that these mechanisms can be produced by the host. 586
Formamidase (FMD), an enzyme involved in nitrogen metabolism, was our target 587
chosen for confirmation of proteomic data by enzymatic assay. The findings show that the 588
enzyme is active in the extracellular environment and also prove that it is differentially 589
expressed in PbEpm83 secretome. This enzyme may be associated with fungal 590
pathogenesis once is reactive with antibodies present in sera from patients with 591
Paracoccidioidomycosis (Borges et al. 2005). In addition, as a functional enzyme that 592
produces ammonia, this enzyme can be related to invasion processes through ammonia-593
mediated tissue injury. 594
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By searching the literature, we were able to point to various proteins related to 595
processes associated with infection establishment and considered as virulence factors. The 596
proteins induced in PbEpm83 secretome, compared with those in Pb01, were: heat shock 597
protein, elongment translation factor 1-alpha, alcohol dehydrogenase, mitochondrial 598
peroxiredoxin PRX 1, glutathione S-transferase-3, mitochondrial ATP synthase D chain, 599
fructose-1,6-bisphosphate aldolase and dipeptidyl peptidase. These, in general, relate to 600
motility processes, adhesion and colonization, as well as antioxidant activity. Among the 601
proteins up-regulated in Pb01 were: glyceraldehyde-3-phosphate dehydrogenase, triose 602
phosphate isomerase, thioredoxin, TCTP family protein, glucose-6-phosphate isomerase, 603
and three heat shock proteins. Its relations with the virulence are based on interactions 604
reports with plasminogen, cellular redox homeostasis and adhesive properties. Therefore, 605
our findings showed that PbEpm83 and Pb01 use several proteins related to adhesion and 606
virulence at the time of infection. Even though they share some expressed proteins, each 607
species was shown to adopt different expression levels of these. 608
It is clear that secretome plays an essential role in fungal infection strategy, working 609
in the molecular dialogue with the host cells, enabling survival, multiplication and 610
pathogen dissemination (Silva et al. 2012). Therefore, the importance of fungal 611
secretome’s characterization as a tool for host-pathogen interaction studies has been 612
demonstrated (Kniemeyer & Brakage 2008; Holbrook et al. 2011; Weber et al. 2012; 613
Girard et al. 2013). This is the first comparative extracellular proteome study between 614
members of Paracoccidioides complex, and it will provide a significant set of data for 615
future research regarding the importance of secreted proteins in host-pathogen interactions. 616
Our proteomic analysis showed a range of secreted proteins expressed by the isolates, with 617
most of them being related to adhesion and virulence. In this sense, we can speculate that 618
the secretome has an important role regarding infection, and that, together with the protein 619
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expression of the other compartments, it comprises the necessary set adopted by each 620
isolate to develop effective infection strategies. However, the progression of the disease 621
depends on multiplex parameters, not only the fungal strain, and therefore it is still not 622
enough to infer which specie studied here is really more virulent and/or which molecules 623
are crucial for that. Additional studies are needed to explore our findings regarding the 624
fractionation of secretomes, including functional studies using genetics tools, as well as 625
production and evaluation of secreted proteins and its influence in Paracoccidioides 626
biology and pathogenesis. 627
628
Acknowledgments 629
This work at Universidade Federal de Goiás was supported by grants from Conselho 630
Nacional de Desenvolvimento Científico e Tecnológico (CNPq - Processo 477962/2010-631
6), and Fundação de Amparo à Pesquisa do Estado de Goiás (FAPEG) (INCT-IPH). ARO 632
has a fellowship from Fundação de Amparo à Pesquisa do Estado de Goiás (FAPEG). 633
LNO and EGAC have fellowships from Coordenação de Aperfeiçoamento de Pessoal de 634
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Figures legends 937
Figure 1. Graphic summary of bioinformatic analysis. A) Venn diagram showing the 938
number of proteins up regulated in Pb01 and PbEpm83 isolates; at intersection showing the 939
number of proteins without statistical differences. B) Number of proteins predicted to be 940
secreted by classical and non-classical secretory pathways. SP: SignalP tool; ScP: 941
SecretomeP tool; NP: no prediction. C) Functional categories of the proteins differentially 942
secreted with significant statistical alteration in Pb01 (left) and PbEpm83 (right) identified 943
protein by nanoUPLC-MSE classified into functional categories according to the database 944
MIPS Functional Catalogue (FunCatDB). 945
946
Figure 2: Analysis of orthologous proteins found in fungal extracellular proteome. 947
The Venn diagram shows the number of proteins that overlap and not between Pb01 (this 948
work), PbEpm83 (this work), Pb18 (Vallejo et al. 2012) and H. capsulatum (Albuquerque 949
et al. 2008). 950
951
Figure 3. Immunoblotting analysis. Immunoblotting analysis of Pb01 and PbEpm83 952
secreted extracts. The transferred membrane was incubated with polyclonal antibodies 953
against proteins tested. ENO - PbEnolase; FMD - PbFormamidase; ALD - PbAldolase; 954
GAPDH - PbGlyceraldehyde-3-phosphate dehydrogenase; TPI - PbTriose phosphate 955
isomerase. Raw Tiff images were analyzed by densitometry of immunoblotting bands 956
using the ImageJ 1.51 software. Pixel intensity for the analyzed bands was generated and 957
expressed as arbitrary units. ‘*’ indicates statistically significant difference. The 958
densitometry p-values are: ENO: p=0.2033; FMD: p=0.0004; ALD: p=0.0001; GAPDH: 959
p=0.0073; TPI: p=0.0005. 960
961
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36
Figure 4. Formamidase activity assay. The FMD activity was determined by the 962
measuring the amount of ammonia formation at 37°C. Data was expressed as the mean ± 963
standard deviation of the biological triplicates of independent experiments. Student’s t-test 964
was used. ‘*’ differences statistically significant (p ≤ 0.05). 965
966
Figure 5. Macrophage Infection Assay. Fungal cells of Pb01 and PbEpm83 were 967
incubated for 12h and 24h with the J774 macrophage lineage for fungal 968
adhesion/internalization. After this period, the infected macrophages were lysed and the 969
lysis products were plated on BHI medium to recover fungi. The colony forming units 970
(CFUs) were counted after 12 days of growth and subjected to analysis of the standard 971
deviation of the triplicates. A) Results presented comparing both isolates in 12h infection. 972
B) Results presented comparing both isolates in 24 h infection. C) Results presented in 973
function of time of infection (12 and 24 h) to Pb01 isolate. D) Results presented in 974
function of time of infection (12 and 24 h) to PbEpm83 isolate. ‘S’ indicates addition of 975
50µL of secreted extracts of Paracoccidioides yeast cells (2 mg/mL) to the time of 976
infection (S01 to Pb01 and S83 to PbEmp83). 977
978
Supplementary Figure S1. Cell viability, growth and vitality assay. Yeast cells of Pb01 979
and PbEpm83 were grown in identical experimental conditions and obtained in biological 980
triplicates. For all experiments the timepoints of 0, 12, 24 and 36 hours were evaluated. A) 981
The cells were stained with Trypan Blue and counted in hemocytometer. B) Equivalent 982
amounts of cells were initially inoculated and at time-points were counted in 983
hemocytometer. C) The amount of glucose was measured by the enzymatic action of 984
Glucose Oxidase method. 985
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Supplementary Figure S2. Extracellular extract quality analysis. Protein extract of the 986
secretome of Pb01 and PbEpm83 using 12% gel electrophoresis (SDS-PAGE). Molecular 987
mass protein standards (kDa) are indicated on the left of the gels. MW: molecular weight 988
marker. 989
990
Supplementary Figure S3. Global analysis of NanoUPLC-MSE proteomic data. A) 991
Dynamic detection range of proteins according to their abundance and molecular weight of 992
Pb01 (left) and PbEpm83 (right). Identified proteins regularly (open square) and reverse 993
form (closed circle) and endogenous default PHB (phosphorylase B, yellow triangle). B) 994
The graphics show accuracy mass analysis in the detection of Pb01 (left) and PbEpm83 995
(right) proteins. C) The pie charts show the percentages of the type of detection of peptides 996
in of Pb01 (left) and PbEpm83 (right). PepFrag1 and PepFrag2 indicates the type of 997
identification using the database of Paracoccidioides by PLGS applying the algorithms 998
described (Geromanos et al. 2009; Li et al. 2009); VarMod, variable modifications; 999
InSource corresponds fragmentation occurred in the ionization source; MissedCleavage, 1000
loss of cleavage by trypsin; NeutralLoss H2O, NH3 and H3PO4, corresponding to loss of 1001
water precursors, ammonia and phosphoric acid, respectively. 1002
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Table 1. Protein preferentially secreted in Pb01, compared with PbEpm83 secretome identified by UPLC-MSE.
Access numbers1 Protein description Score Log2 FunCat2 Protein Function Signal
P3 Secretome
P4 Antigenics Pasteur5
Metabolism
PAAG_05019 HIT domain protein 3079.07 -0.62 1.03 nucleotide/nucleoside/nucleobase metabolism
- - 17
PAAG_02869 phosphoglycerate kinase 6335.24 -0.9 1.05 C-compound and carbohydrate metabolism
- 0.66268 17
PAAG_06526 glucose-6-phosphate isomerase 2453.99 -0.66 1.05 C-compound and carbohydrate metabolism
- - 22
PAAG_08313 L-PSP endoribonuclease family protein Hmf1
43258.32 -1.12 01.01.11.02.01
biosynthesis of isoleucine - - 6
PAAG_00433 adenosine kinase 1719.2 -0.62 01.03.01 purin nucleotide/nucleoside/nucleoba
se metabolism
- - 16
PAAG_02859 adenosylhomocysteinase 8659.62 -1.37 01.07.01 biosynthesis of vitamins, cofactors, and prosthetic groups
- - 25
PAAG_00588 fumarate hydratase 1100.07 Pb01 1.05 C-compound and carbohydrate metabolism
- - 17
PAAG_00889 phosphomannomutase 676.36 Pb01 1.05 C-compound and carbohydrate metabolism
- - 12
PAAG_02585 triosephosphate isomerase 3332.27 Pb01 1.05 C-compound and carbohydrate metabolism
- - 13
PAAG_03537 decarboxylase family protein 2795.32 Pb01 01.01.06.06.02
biosynthesis of lysine - - 10
PAAG_08164 homogentisate 1,2-dioxygenase 2550.28 Pb01 01.01.09.05.02
degradation of tyrosine - 0.908391 19
Energy
PAAG_08468 glyceraldehyde-3-phosphate dehydrogenase
1412.95 -0.67 2.01 glycolysis and gluconeogenesis - 0.912034 18
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PAAG_03309 suaprga1 1400.53 Pb01 02.13.03 aerobic respiration - 0.662756 12 Cell Cycle and DNA Processing
PAAG_01986 nucleosome binding protein 3314.72 Pb01 10.01.09.05
DNA conformation modification (e.g. chromatin)
- 0.918277 4
PAAG_00773 DNA damage checkpoint protein rad24
4186.77 Pb01 10.03.01.03
cell cycle checkpoints (checkpoints of morphogenesis,
DNA-damage,-replication, mitotic phase and spindle)
- - 13
Transcription
PAAG_08441 nuclear transcription factor Y subunit C
967.29 Pb01 11.02.03.04
transcriptional control - 0.901699 12
Protein Synthesis
PAAG_04425 60S ribosomal protein L22 8074.72 -0.9 12.01 ribosome biogenesis - 0.651432 5 PAAG_06536 ubiquitin 1020.18 -1.99 12.01.01 ribosomal proteins - 0.718675 6 PAAG_07841 60S acidic ribosomal protein P1 13221.49 -1.26 12.01.01 ribosomal proteins - 0.65348 4 PAAG_09096 40S ribosomal protein S28 9916.27 -0.66 12.01.01 ribosomal proteins - - 3 PAAG_09083 TCTP family protein 1799.46 Pb01 12.01 ribosome biogenesis - - 7 Protein Fate (folding, modification and destination)
PAAG_02686 Hsp90 co chaperone AHA1 2707.78 -1.68 14.01 protein folding and stabilization - 0.94122 15 PAAG_03334 peptidyl-prolyl cis-trans isomerase
D 4356.69 -0.96 14.01 protein folding and stabilization - 0.864046 16
PAAG_06168 peptidyl-prolyl cis-trans isomerase cypE
5744.41 -0.93 14.01 protein folding and stabilization - 0.871257 8
PAAG_05226 Hsp90 binding co-chaperone Sba1 3920.94 -0.83 14.01 protein folding and stabilization - - 6 PAAG_08059 heat shock protein 3431.9 -0.8 14.01 protein folding and stabilization - - 26 PAAG_05643 nuclear protein localization
protein 4 8273.84 -0.63 14.04 protein targeting, sorting and
translocation - 0.936126 42
PAAG_04291 nucleoside diphosphate kinase 5951.87 -0.75 14.07.03 modification by phosphorylation,
dephosphorylation,
- - 9
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autophosphorylation Protein with ligation function
PAAG_07750 heat shock protein Hsp88 6682.68 Pb01 16.01 protein binding - - 27 PAAG_05518 cell division cycle protein 1751.52 -0.59 16.19.03 ATP binding - - 32 Regulation of Protein Activity
PAAG_06344 rab GDP-dissociation inhibitor 3475.8 Pb01 18.01.07 regulation by binding / dissociation
- - 18
Cellular Transport and Transport Routes
PAAG_02364 thioredoxin 40461.62 -1.34 20.01.15 electron transport - 0.933168 5 PAAG_02515 cytochrome P450 55A1 2581.77 Pb01 20.01.15 electron transport - - 17 Cell Rescue, Defense and Virulence
PAAG_08003 hsp70 like protein 44260.87 -0.67 32.01 stress response - - 26 Unclassified
PAAG_03243 conserved hypothetical protein 7366.56 -1.48 - - - 0.924308 11
1 Number of general information in the Broad Institute Database (http://archive.broadinstitute.org/ftp/pub/annotation/fungi/paracoccidioides/genomes/). 2 Number of functional category according to the MIPS Functional Catalogue (FunCat2). 3 Prediction secretion according to SignalP 3.0. The number represents the probability of a signal peptide (http://www.cbs.dtu.dk/services/SignalP/). 4 Prediction secretion according to SecretomeP 2.0. The number corresponds to the neural network that exceeds the value 0.5 (http://www.cbs.dtu.dk/services/SecretomeP/). 5 Number of antigenic hits found by the Antigenics Software (http://mobyle.pasteur.fr/cgi-bin/portal.py?#forms::antigenic).
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Table 2. Protein preferentially secreted in PbEpm83, compared with Pb01 secretome identified by UPLC-MSE.
Access numbers1 Protein description Score Log2 FunCat2 Protein Function Signal
P3 Secretome
P4 Antigenics Pasteur5
Metabolism
PAAG_00053 malate dehydrogenase 1772.66 0.82 1.05 C-compound and carbohydrate metabolism
- 0.816364 17
PAAG_03333 formamidase 1774.38 1.54 1.02 nitrogen, sulfur and selenium metabolism
- - 17
PAAG_03279 aminopeptidase 976.46 PbEpm83 1.01 amino acid metabolism - - 35 PAAG_05929 sulfate adenylyltransferase 4689.2 PbEpm83 1.01 amino acid metabolism - - 26 PAAG_01015 hexokinase 1413.37 PbEpm83 1.05 C-compound and carbohydrate
metabolism - - 18
PAAG_04541 alcohol dehydrogenase 660.42 PbEpm83 1.05 C-compound and carbohydrate metabolism
- 0.837883 11
PAAG_06817 UTP-glucose-1-phosphate uridylyltransferase
798.05 PbEpm83 1.05 C-compound and carbohydrate metabolism
- - 22
PAAG_07813 cysteine synthase 1505.8 PbEpm83 01.01.09.03.01 biosynthesis of cysteine - 0.507512 15 PAAG_01563 aromatic-L-amino-acid
decarboxylase 1930.43 PbEpm83 01.01.09.04.01 biosynthesis of phenylalanine - - 27
PAAG_06643 uracil phosphoribosyltransferase 908.32 PbEpm83 01.03.04 pyrimidine nucleotide/nucleoside/nucleobase
metabolism
- - 10
PAAG_01995 fructose-1,6-bisphosphate aldolase 1
8664.16 PbEpm83 01.05.02.07 sugar, glucoside, polyol and carboxylate catabolism
- 0.66289 11
PAAG_09004 puromycin sensitive aminopeptidase
704.74 PbEpm83 01.05.25 regulation of C-compound and carbohydrate metabolism
- - 35
PAAG_04083 isochorismatase family hydrolase 1607.68 PbEpm83 01.20.15.03 metabolism of ubiquinone - - 9 Energy
PAAG_03330 dihydrolipoyl dehydrogenase 1824.05 PbEpm83 2.1 tricarboxylic-acid pathway (citrate cycle, Krebs cycle, TCA
- - 26
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cycle) PAAG_08075 citrate synthase 907.93 PbEpm83 2.1 tricarboxylic-acid pathway
(citrate cycle, Krebs cycle, TCA cycle)
- - 20
PAAG_04820 ATPase alpha subunit 905.42 PbEpm83 2.11 electron transport and membrane-associated energy conservation
- - 20
PAAG_04570 ATP synthase D chain mitochondrial
1673.84 PbEpm83 2.13 respiration - - 7
PAAG_03631 12-oxophytodienoate reductase 7223.48 PbEpm83 2.45 energy conversion and regeneration
- 0.739896 15
Cell Cycle and DNA processing
PAAG_07296 ssDNA binding protein 7652.94 PbEpm83 10.01.03 DNA synthesis and replication - 0.542166 5 Transcription
PAAG_04496 nascent polypeptide associated complex subunit beta
1946.27 PbEpm83 11.02.03.04 transcriptional control - 0.903215 6
Protein Synthesis
PAAG_02024 elongation factor 1-alpha 590.47 PbEpm83 12.04 translation - 0.683646 19 PAAG_00801 60S acidic ribosomal protein P0
lyase 1506.82 PbEpm83 12.01.01 ribosomal proteins - - 11
PAAG_04691 60S acidic ribosomal protein P2 5899.09 PbEpm83 12.01.01 ribosomal proteins 0,386 - 4 PAAG_07707 60S ribosomal protein L10a 600.64 PbEpm83 12.01.01 ribosomal proteins - - 10 Protein Fate
PAAG_00986 disulfide isomerase Pdi1 2079.57 PbEpm83 14.01 protein folding and stabilization 0,772 - 20 PAAG_05679 heat shock protein 693.39 PbEpm83 14.01 protein folding and stabilization - 24 PAAG_03719 thimet oligopeptidase 561.54 PbEpm83 14.13 protein/peptide degradation - - 35 PAAG_07467 dipeptidyl peptidase 954.06 PbEpm83 14.13.01 cytoplasmic and nuclear protein
degradation - - 34
Cell Rescue, Defense and Virulence
PAAG_03216 mitochondrial peroxiredoxin PRX1 2950.48 PbEpm83 32.01.01 oxidative stress response - - 10
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Biogenesis of cellular compounds
PAAG_03931 glutathione S-transferase Gst3 1956.35 PbEpm83 42.01 cell wall - - 17 Differentiation of cell types
PAAG_03921 HET-C domain containing protein HetC
10 PbEpm83 43.01.03 fungal and other eukaryotic cell type differentiation
- 0.941415 32
Unclassified PAAG_00340 conserved hypothetical protein 1154.2 PbEpm83 - - - 0.883262 6 PAAG_02985 hypothetical protein 1186.76 PbEpm83 - - - 0.936902 8 PAAG_05550 hypothetical protein 1026.17 PbEpm83 - - - 5 PAAG_07158 hypothetical protein 5971.67 PbEpm83 - - - 0.518989 5 PAAG_07921 conserved hypothetical protein 1765.91 PbEpm83 - - - 0.952615 2
1 Number of general information in the Broad Institute Database (http://archive.broadinstitute.org/ftp/pub/annotation/fungi/paracoccidioides/genomes/). 2 Number of functional category according to the MIPS Functional Catalogue (FunCat2). 3 Prediction secretion according to SignalP 3.0. The number represents the probability of a signal peptide (http://www.cbs.dtu.dk/services/SignalP/). 4 Prediction secretion according to SecretomeP 2.0. The number corresponds to the neural network that exceeds the value 0.5 (http://www.cbs.dtu.dk/services/SecretomeP/). 5 Number of antigenic hits found by the Antigenics Software (http://mobyle.pasteur.fr/cgi-bin/portal.py?#forms::antigenic).
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Access numbers1 Protein description FAApred2 Isolate3
PAAG_08313 L-PSP endoribonuclease family protein Hmf1 0.32413393 Pb01
PAAG_02585 triosephosphate isomerase 0.475649 Pb01
PAAG_08468 glyceraldehyde-3-phosphate dehydrogenase 0.6656069 Pb01
PAAG_09096 40S ribosomal protein S28 0.45667675 Pb01
PAAG_02686 Hsp90 co-chaperone AHA1 0.49974454 Pb01
PAAG_08059 heat shock protein 0.75891651 Pb01
PAAG_05643 endoplasmic reticulum and nuclear membrane protein Npl4
0.64670755 Pb01
PAAG_02364 thioredoxin 0.72402533 Pb01
PAAG_07813 cysteine synthase 0.49329971 PbEpm83
PAAG_06643 uracil phosphoribosyltransferase 0.54851004 PbEpm83
PAAG_07296 ssDNA binding protein 0.41982781 PbEpm83
PAAG_02985 hypothetical protein 0.74640492 PbEpm83
PAAG_05550 hypothetical protein 0.64984866 PbEpm83
PAAG_07921 conserved hypothetical protein 0.29603461 PbEpm83
PAAG_00771 enolase NO* C
PAAG_04571 nascent polypeptide associated complex subunit alpha
0.34804424 C
PAAG_04913 RNP domain protein 0.67499902 C
1 Number of general information on the Broad Institute database. (http://archive.broadinstitute.org/ftp/pub/annotation/fungi/paracoccidioides/genomes/). 2 Prediction of the adhesins by FAApred software (http://bioinfo.icgeb.res.in/faap/query.html). 3 Isolate of Paracoccidioides in that the protein was found. C = refers to the constituent proteins (no
differences in expression levels for the parameters adopted).
*Protein predicted to be non-adhesin by the FAApred software, but predicted to be adhesin in the FungalRV
software -Adhesin Prediction and Immunoinformatics portal for human fungal pathogens
(http://fungalrv.igib.res.in/query.php) and supported by literature.
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Table 4. Identification of proteins secreted in Paracoccidioides Pb01 and PbEpm83, putatively related to virulence.
Access numbers1 Protein description Expression2 Microorganism3 Important findings4 References
PAAG_04559 2-metilcitratre dehydratase C Aspergillus spp Reduction in pathogenicity
(Biosynthesis Lysine) (Hogan et al.
1996)
PAAG_06473 mannitol-1-phosphate 5-dehydrogenase C Cryptococcus neoformans
Increased susceptibility to human neutrophils with low strains in vitro
production mannitol;
(Hogan et al. 1996)
PAAG_08059 PAAG_06811 PAAG_05679
heat shock proteins-Hsp Pb01
C PbEpm83
Candida albicans Adaptive response to stress. (Brown et al.
2007)
PAAG_07467 dipeptidyl peptidase PbEpm83 Aspergillus fumigatus It facilitates the colonization of the
lungs and other tissues
(Karkowska-kuleta et al.
2009)
PAAG_08468 glyceraldehyde-3-phosphate
dehydrogenase Pb01 Paracoccidioides Binding to fibronectin and laminin
(Barbosa et al. 2006; Seidler
2013)
PAAG_00771 enolase C Paracoccidioides Fibronectin binding protein (Donofrio et al. 2009; Nogueira
et al. 2010)
PAAG_02585 triose phosphate isomerase Pb01 Paracoccidioides Adhesive properties; Connection epithelial cells cultured in vitro
(Pereira et al. 2007)
PAAG_01995 fructose-1,6-bisphosphate aldolase 1 PbEpm83 Candida albicans Motility and adhesion (interactions
with plasminogen) (Crowe et al.
2003)
PAAG_02364 thioredoxin Pb01 Botrytis cinerea Cellular redox homeostasis (Viefhues A,
Heller J, Temme N 2014)
PAAG_03216 mitochondrial peroxiredoxin PRX1 PbEpm83 Candida albicans Antioxidant activity; (Srinivasa et al.
2012)
PAAG_03931 glutathione S-transferase 3 (GST) PbEpm83 Candida albicans Cellular detoxification; (Garcerá et al.
2010)
PAAG_04541 alcohol dehydrogenase PbEpm83 Candida albicans Interactions with plasminogen (Crowe et al.
2003)
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PAAG_02024 elongation factor 1-alpha PbEpm83 Candida albicans Interactions with plasminogen (Crowe et al.
2003) PAAG_08003 PAAG_01262
Hsp70-like protein Pb01
C Cryptococcus neoformans
Interactions with plasminogen (Stie et al. 2009)
PAAG_06526 glucose-6-phosphate isomerase Pb01 Cryptococcus neoformans
Interactions with plasminogen (Stie et al. 2009)
PAAG_04570 mitochondrial ATP synthase D chain PbEpm83 Cryptococcus neoformans
Interactions with plasminogen (Stie et al. 2009)
PAAG_09083 TCTP family protein Pb01 Aspergillus nidulans Induced in early stages of germination
of conidia (Oh et al. 2010)
PAAG_07750 heat shock protein Hsp 88 Pb01 Aspergillus nidulans Induced in early stages of germination
of conidia (Oh et al. 2010)
1 Number of general information on the Broad Institute database (http://archive.broadinstitute.org/ftp/pub/annotation/fungi/paracoccidioides/genomes/). 2 Isolate of Paracoccidioides in that the protein was found. C - refers to the constituent proteins (no differences in expression levels for the parameters adopted). 3 Microorganism in which the virulence factor was already described. 4 Description in the literature of the protein action as a virulence factor.
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• Paracoccidioides species exhibit different extracellular protein profiles
• P. lutzii shown to be more resistant to macrophage infection
• Secreted proteins are request to Paracoccidioides survival in activated macrophages
Chaves et al. BMC Microbiology (2015) 15:53 DOI 10.1186/s12866-015-0393-9
RESEARCH ARTICLE Open Access
Analysis of Paracoccidioides secreted proteinsreveals fructose 1,6-bisphosphate aldolase as aplasminogen-binding proteinEdilânia Gomes Araújo Chaves1, Simone Schneider Weber1, Sonia Nair Báo2, Luiz Augusto Pereira1,Alexandre Melo Bailão1, Clayton Luiz Borges1 and Célia Maria de Almeida Soares1*
Abstract
Background: Despite being important thermal dimorphic fungi causing Paracoccidioidomycosis, the pathogenicmechanisms that underlie the genus Paracoccidioides remain largely unknown. Microbial pathogens expressmolecules that can interact with human plasminogen, a protein from blood plasma, which presents fibrinolyticactivity when activated into plasmin. Additionally, plasmin exhibits the ability of degrading extracellular matrixcomponents, favoring the pathogen spread to deeper tissues. Previous work from our group demonstrated thatParacoccidioides presents enolase, as a protein able to bind and activate plasminogen, increasing the fibrinolyticactivity of the pathogen, and the potential for adhesion and invasion of the fungus to host cells. By usingproteomic analysis, we aimed to identify other proteins of Paracoccidioides with the ability of binding toplasminogen.
Results: In the present study, we employed proteomic analysis of the secretome, in order to identifyplasminogen-binding proteins of Paracoccidioides, Pb01. Fifteen proteins were present in the fungal secretome,presenting the ability to bind to plasminogen. Those proteins are probable targets of the fungus interaction withthe host; thus, they could contribute to the invasiveness of the fungus. For validation tests, we selected theprotein fructose 1,6-bisphosphate aldolase (FBA), described in other pathogens as a plasminogen-bindingprotein. The protein FBA at the fungus surface and the recombinant FBA (rFBA) bound human plasminogenand promoted its conversion to plasmin, potentially increasing the fibrinolytic capacity of the fungus, asdemonstrated in fibrin degradation assays. The addition of rFBA or anti-rFBA antibodies was capable of reducingthe interaction between macrophages and Paracoccidioides, possibly by blocking the binding sites for FBA.These data reveal the possible participation of the FBA in the processes of cell adhesion and tissue invasion/dissemination of Paracoccidioides.
Conclusions: These data indicate that Paracoccidioides is a pathogen that has several plasminogen-bindingproteins that likely play important roles in pathogen-host interaction. In this context, FBA is a protein that mightbe involved somehow in the processes of invasion and spread of the fungus during infection.
Keywords: Paracoccidioides, Proteome, Secretome, Plasminogen-binding proteins, Fructose 1,6-bisphosphate aldolase
* Correspondence: [email protected]ório de Biologia Molecular, Instituto de Ciências Biológicas, ICBII,Campus II, Universidade Federal de Goiás, 74001-970 Goiânia, Goiás, BrazilFull list of author information is available at the end of the article
© 2015 Chaves et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly credited. The Creative Commons Public DomainDedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article,unless otherwise stated.
Chaves et al. BMC Microbiology (2015) 15:53 Page 2 of 14
BackgroundThe Paracoccidioides genus comprises a complex ofpathogenic fungi, classified in at least four distinctphylogenetic lineages: S1, PS2, PS3 and Pb01-like [1-3].These fungi are thermally dimorphic, growing at roomtemperatures as mycelium, which produces infectiousconidia. The inhalation of conidia or mycelia propagulesby the human host and their differentiation to yeast cellsinitiates paracoccidioidomycosis (PCM), a major healthproblem in South America. This human systemic myco-sis is considered the tenth leading cause of chronic dis-ease mortality among infectious and parasitic diseases,and the first among the systemic mycoses in Brazil(51.2% of cases of deaths) [4-6].Pathogenic microorganisms are able to penetrate and
colonize host tissues by establishing complex interac-tions with the host molecules. Some microorganisms de-grade extracellular matrix components (ECM) by usingproteins that subvert proteases of the host itself [7-9].Reports have shown that pathogens can capture plas-minogen (Plg) and its activation could substantiallyaugment the organism’s potential to tissue invasion andnecrosis [10-20]. In eukaryotes, Plg is converted to itsproteolytic form, plasmin, by physiological activatorssuch as tissue type plasminogen activator (tPA) and uro-kinase type (uPA) [16]. Plasmin dissociates blood clotsdue to its role in the degradation of fibrin polymers andpromotes the dissociation of the ECM components, whichis relevant for dissemination of pathogens [17-22].There is a variety of Plg-binding proteins and activation
mechanisms used by pathogens. Besides the physiologicalactivators, molecules produced by microorganisms, canalso activate plasminogen. Studies describe various Plg-binding and activating proteins involved in the degrad-ation of host tissues, components of ECM, which favorsthe spread and dissemination of different pathogens[14,23-25]. In bacteria, Plg-binding and activating proteinshave been characterized [12-14,24,26-37]. Those proteinscan increase the bacteria fibrinolytic activity, which favorstissue degradation and rapid progression of infection[35,38,39]. The importance of Plg in fungi is indicated bythe Plg-binding properties of human pathogens, includingCandida albicans [40,41], Cryptococcus neoformans [15],Pneumocystis carinii and Aspergillus fumigatus [42,43]that depict proteins at surface, which make them able tobind Plg, and improve ther infectiveness.The high dissemination of Paracoccidioides spp. from
the site of infection to different tissues, underscores theimportance of understanding the fungi virulence factorsand their effects in human host. In a previous study de-veloped by our group, we reported the recruitment ofPlg and its activation into plasmin, by Paracoccidioides,Pb01, through tPA, in a process mediated by the proteinenolase [10]. The enolase of Paracoccidioides is a surface
associated protein that promotes an increase in theadhesion and invasion of the fungus to host cells inin vitro models of infection [10,44,45]. The recombinantParacoccidioides enolase is able to adhere to some ECMcomponents and to the surface of macrophages, reinfor-cing the role of this molecule in the host-pathogen inter-action [46]. These data highlight that Plg-binding proteinsincrease the potential for invasion and pathogenicity ofParacoccidioides through the fibrinolytic activity of plas-min. Proteins with this ability may be transported to thesurface of the fungus and secreted into the externalmedium and promote plasmin formation, which also con-tributes to the pathogen dissemination [47]. In this sense,the enolase of Paracoccidioides is constitutively secretedby the yeast and mycelia phases [48], and is detected inthe fungal cell wall [10].In the present study, we employed proteomic analysis
of the secretome, in order to identify Plg-binding pro-teins of Paracoccidioides, Pb01. Fifteen Plg-binding pro-teins were present in the fungal secretome. Proteins ofthe glycolytic pathway, such as phosphoglycerate kinase,glyceraldehyde-3-phosphate dehydrogenase and fructose1,6-bisphosphate aldolase (FBA) were identified; the lastwas selected for further characterization. FBA has beendescribed in various microorganisms as a Plg-bindingprotein, but its role has not been described in thermallydimorphic fungi. Here we show that Paracoccidioidesbinds Plg via FBA, that is found at the surface andsecreted by the fungus. The protein binds human plas-minogen (hPlg) and converts it into plasmin, in the pres-ence of tPA. The interaction of the protein with hPlg,promoted increased fibrinolytic capacity of the fungus,as tested in fibrin degradation assays. The addition of re-combinant FBA (rFBA) or anti-rFBA antibodies was cap-able of reducing the interaction between macrophagesand Paracoccidioides, possibly by blocking the bindingsites for FBA. These data reveal the possible participationof the FBA in the Paracoccidioides adhesion and invasionprocesses. The identification of novel surface/secretedproteins that can be involved in host-pathogen interactionis central to understand Paracoccidioides pathogenesis.
Results and discussionIdentification of plasminogen-binding proteins of Para-coccidioides, Pb01 yeast cellsIn order to identify Plg-binding proteins in the secre-tome of Paracoccidioides, Pb01, we obtained 2-DE gels.The gels ran in parallel, were (i) stained with Coomassiebrilliant blue or (ii) transferred to nitrocellulose mem-brane and reacted with Plg, in a Far-western blottingassay, as demonstrated in Figure 1, panel B. Image ana-lysis were produced allowing the pairing of the proteinsspots between the 2-DE gel and the membrane obtainedby Far-western blotting.
Figure 1 Detection of plasminogen-binding proteins of Paracoccidioides, Pb01. Secreted proteins (500 μg) of Paracoccidioides, Pb01, weresubjected to 2-DE [first dimension: IEF pH range 3–11 non-linear, second dimension: 12% (w/v) SDS-PAGE)]. 2-DE gels were stained usingCoomassie brilliant blue (Panel A) or transferred to nitrocellulose membranes that were processed for Far-western blotting (Panel B). Negativecontrols include a membrane not incubated with Plg (Panel C). Membrane in panel B was incubated with 35 μg/ml of hPlg, followed by theincubation with the anti-hPlg antibody (1 μg/mL) and the reaction was developed with BCIP/NBT. To identify in the 2-DE gel, the proteins spotsthat were visualized in the membrane, a pairing of proteins spots was performed, using Image master 2D Platinum software (GE Healthcare). ThepH gradient is shown above the gel, and the molecular mass protein standards (kDa) are indicated to the left of the gels.
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The detected spots in the membrane (Figure 1B) werecompared to the Coomassie blue partners in order tofind their corresponding proteins spots in the 2-DE gel(Figure 1A). Subsequently, protein spots were manuallyexcised of the gel, and identified by mass spectrometry.It was possible to identify in the secretome of yeast cells,22 protein spots, which bound Plg, as depicted inFigure 1B. Figure 1, panel C, depicts the images of thenegative control assay, in which the membrane was notpreviously incubated with Plg, indicating no cross-reactivity of the proteins with the antibody to Plg.Spots identified as Plg-binding proteins were cut from
the gel and subjected to tryptic digestion and mass spec-trometry analysis. The data were used to search theMascot, and provided the identification of 15 proteins/isoforms. Table 1 describes the secreted proteins ofParacoccidioides, identified as Plg-binding molecules.Several enzymes were detected in this category, some ofthem presenting several isoforms, such as homogentisate1,2-dioxygenase (spots 4,5), NADP-specific glutamatedehydrogenase (spots 6,7), phosphoglycerate kinase (spots8,16) 2-methylcitrate synthase (spots 9,10,11), FBA (spots13,14,15) and malate dehydrogenase (spots 20,21). Thus,the 22 protein spots identified are summed up in 15 differ-ent proteins.While much of the proteins described in this work are not
annotated in the database Psort (http://www.genscript.com/psort/wolf_psort.html) as extracellular proteins, we foundcompatible data in other studies. The proteins: 2-methylcitratesynthase, FBA, glyceraldehyde 3-phosphate dehydrogenase,formamidase, acetyl-CoA acetyltransferase and phosphoglycer-ate kinase were detected in the secretome of Paracoccidioides,Pb01 yeast and mycelia [48]. Other proteins were identified in
the secretome of Paracoccidioides, Pb18: FBA, glyceraldehyde3-phosphate dehydrogenase and phosphoglycerate kinase [49].These data corroborate the in silico analysis performed in thesoftware Signal P and Secretome P, where we can observe thatmost of the proteins described here are secreted by nonclassi-cal pathways (Table 1).Some of the proteins identified in this study have also
been described in other systems as Plg-binding proteins.In this way, acetyl-CoA acetyltransferase was identifiedin the bacteria Leptospira interrogans [50]; phosphoglycer-ate kinase was described in C. albicans [40], Streptococcuspneumoniae [51], as well as in C. neoformans [15]. Inaddition, FBA and glyceraldehyde 3-phosphate dehydro-genase were also described as Plg-binding proteins in C.albicans [40].Formamidase is a highly abundant protein in Paracoc-
cidioides, as previously described by our group [52,53].The protein gp43 also detected in our binding assays,binds to laminin, putatively contributing to the fungusvirulence and facilitating the process of infection [54,55].The proteomic binding assays, also allowed the identi-
fication of enolase as a Plg-binding protein. The pres-ence of glycolytic enzymes as Plg-binding proteins isreported in several pathogens, including bacteria andfungi. In Paracoccidioides, enolase is present at the yeastcells surface, where it binds and activates hPlg, presum-ably contributing to the fungus pathogenesis [10]. Otherglycolytic enzymes, such as glyceraldehyde 3-phosphatedehydrogenase, phosphoglycerate kinase and FBA, werefound here as Plg-binding proteins (Figure 1B, Table 1).Glyceraldehyde 3-phosphate dehydrogenase (GAPDH),is a molecule that binds Plg and is present on the surfaceand secretome of bacteria [56-58] and fungi [40]. In C.
Table 1 Secreted proteins of Paracoccidioides that bind plasminogenSpot number1 General information
number (NCBI)2Protein description pItheor/exp3 MM (kDa)
theor/exp4PMFscore5
Coveragesequence (%)6
MS/MSIons score7
Matchedpeptides8
Psortprediction9
SignalPValue ≥ 0.510
SecretomePValue ≥ 0.511
big-PI12
1 gi|226285916 aminomethyl transferase 9.67/4.42 53.35/45.56 121 37 84 4 mito: 23.0 NO 0.516 NO
2 gi|226278634 aldehyde dehydrogenase 5.92/6.94 54.69/45.97 94 59 114 6 cyto: 21.5 NO 0.562 NO
3 gi|295668479 formamidase 6.10/7.13 46.14/45.71 144 44 109 5 cyto: 12.0 NO 0.565 NO
4 gi|295658700 homogentisate 1,2-dioxygenase 6.25/7.62 50.85/45.51 78 35 - - cyto: 13.0 NO 0.601 NO
5 gi|295658700 homogentisate 1,2-dioxygenase 6.16/7.76 50.86/45.35 76 26 89 4 cyto: 13.0 NO 0.621 NO
6 gi|295659664 NADP-specific glutamatedehydrogenase
7.66/8.48 50.38/45.35 102 53 72 4 cyto: 11.0 NO NO NO
7 gi|295659664 NADP-specific glutamatedehydrogenase
7.17/8.75 50.46/45.45 101 56 117 2 cyto: 11.0 NO NO NO
8 gi|295669690 phosphoglycerate kinase 6.48/9.49 45.31/ 44.54 83 61 151 5 cyto: 25.0 NO NO NO
9 gi|295666179 2-methylcitrate synthase 9.02/9.73 51.51/45.00 - - 226 6 mito: 27.0 NO NO NO
10 gi|295666179 2-methylcitrate synthase 9.02/9.96 51.51/ 44.92 95 62 95 4 mito: 27.0 NO NO NO
11 gi|295666179 2-methylcitrate synthase 9.02/10.66 51.58/47.76 78 57 88 4 mito: 27.0 NO NO NO
12 gi|295658119 glyceraldehyde-3-phosphatedehydrogenase
10.18/10.67 33.92/43.65 - - 93 2 cyto: 27.0 NO 0.532 NO
13 gi|295671120 fructose 1,6-bisphosphate aldolase 6.09/6.41 39.72/41.29 - - 154 5 cyto: 21.0 NO 0.505 NO
14 gi|295671120 fructose 1,6-bisphosphatealdolase
6.09/6.60 39.72/41.29 - - 670 5 cyto: 21.0 NO 0.505 NO
15 gi|295671120 fructose 1,6-bisphosphate aldolase 6.09/6.88 39.72/40.94 - - 555 9 cyto: 21.0 NO 0.505 NO
16 gi|295669690 phosphoglycerate kinase 6.48/7.75 45.31/42.67 86 59 56 3 cyto: 25.0 NO NO NO
17 gi|295668707 acetyl-CoA acetyltransferase 8.98/7.88 46.65/42.67 - - 102 3 mito: 24.5 NO 0.692 NO
18 gi|11496183 immunodominant antigen Gp43 7.17/8.15 45.77/42.42 97 43 102 4 extr: 24.0 NO 0.746 NO
19 gi|226285552 ketol-acid reductoisomerase 9.12/8.46 44.86/42.17 172 62 134 7 mito: 27.0 NO 0.683 NO
20 gi|295658218 malate dehydrogenase 6.36/7.18 34.67/33.98 73 47 69 5 cyto: 17.0 NO 0.674 NO
21 gi|295658218 malate dehydrogenase 6.36/7.85 34.67/33.75 129 41 344 9 cyto: 17.0 NO 0.674 NO
22 gi|226279168 2,5-diketo-D-gluconic acid reductase A 7.71/8.40 34.78/33.36 81 48 50 3 cyto: 20.5 0.5 NO NO
1Spots numbers indicated in Figure 1A.2NCBI database general information number (http://www.ncbi.nlm.nih.gov/).3Isoelectric point (theoretical/experimental).4Molecular Mass in kDa (theoretical/experimental);5Mascot PMF score for fragmentation data (http://www.matrixscience.com).6Sequence coverage percentage.7Mascot MS/MS score for fragmentation data (http://www.matrixscience.com).8Number of identified peptides (MS/MS).9Subcellular localization prediction of proteins according Psort (http://www.genscript.com/psort/wolf_psort.html).10Secretion prediction according to Signal P 3.0 server. The number corresponds to signal peptide probability (Score³ 0.5) (http://www.cbs.dtu.dk/services/SignalP/).11Secretion prediction according to Secretome P 1.0 server; the number corresponds to neural network that exceeded a value of 0.5 (NN-score ³ 0.50) (http://www.cbs.dtu.dk/services/SecretomeP/).12GPI Modification Site Prediction of proteins according big-PI (http://mendel.imp.ac.at/gpi/gpi_server.html).cyto: cytoplasm.extr: extracellular.mito: mitochondria.
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Figure 2 Paracoccidioides FBA is a plasminogen-binding protein.(A) SDS-PAGE analysis of the rFBA of Paracoccidioides. The recombinantprotein was obtained by heterologous expression in E. coli. Thebacteria total protein extract, before (lane 1), and after (lane 2) theinduction with IPTG; the recombinant protein fused to gluthationeS-transferase (GST) (lane 3) and the purified rFBA (lane 4). (B) Far-westernanalysis. Increasing concentrations of the rFBA (0.1 to 3.0 μg) werefractionated by SDS-PAGE (12%) and transfered to a nitrocellulosemembrane that was subsequently incubated with hPLg, anti-hPlgantibodies produced in mouse and anti-mouse immunoglobulin G(IgG) coupled to alkaline phosphatase. The reaction was developedusing 5-Bromo-4-chloro-3-indolyl phosphate (BCIP) and Nitro BlueTetrazolium (NBT).
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albicans, this molecule is an adhesin that participates inthe process of adherence to human cells, and binds toECM components [40,59-61]. In studies conducted byour group, GAPDH is located at the surface of Paracoc-cidioides, where could mediate the adhesion and intern-alization of the fungus to host cells, binding to ECMcomponents [62].Phosphoglycerate kinase is an adhesin in both, bacteria
[63] and fungi [15,40]. On the surface of group Bstreptococcus, phosphoglycerate kinase binds the hostactin and Plg. Binding of ECM components to bacterialproteins, including phosphoglycerate kinase, promotesthe activation of specific proteins on its surface, whichinduces bacterial adhesion [63,64]. Also, proteolytic deg-radation of ECM by phosphoglycerate kinase - recruitedplasmin activity, promotes adherence to endothelial cellsand bacterial dissemination in the host tissues [36]. In C.neoformans, phosphoglycerate kinase localizes to thefungal cell wall, where exhibits accessible carboxyl-terminal lysine residues for Plg-binding [65].FBA is cytoplasmic and also localized at the surface of
several bacteria [66,67], as well as in pathogenic fungi[15,40] where it binds host molecules and depicts adhe-sin function, beyond its glycolytic activity. In this work,three isoforms of FBA were detected (Table 1, spots 13,14 e 15). The FBA of Paracoccidioides, Pb01 was previ-ously characterized in our laboratory [68,69]. The pro-tein is as an antigenic molecule, reactive with sera ofPCM patients, as demonstrated [68]. Studies revealedthe role of FBA in cell adhesion and invasion [67]. TheFBA-deficient mutant of Neisseria meningitides was notaffected in its ability to grow in vitro, but depicted asignificant reduction in adhesion to human brain micro-vascular endothelial and HEp-2 cells, suggesting partici-pation in adhesion of meningococci to human cells [67].In C. neoformans, analysis of the Plg-binding proteins,allowed the identification of a FBA surface protein, thatserves as a Plg receptor [15]. So, due to the relevance ofFBA as an adhesin and a Plg-binding protein that pro-motes the virulence of microorganisms, the protein wasselected for further investigation in Paracoccidioides.
Confirmatory assays of FBA as a plasminogen-bindingproteinWe selected FBA for further analysis, since the proteinis a Plg-binding protein in several pathogens, as previ-ously described [15,40,70]. To verify if the FBA of Para-coccidioides also has this ability, a recombinant proteinwas obtained by cloning the cDNA (GenBank Acces-sion Number AY233454) into the expression vectorpGEX-4 T-3 (GE Healthcare) as described in Materialand Methods. The fusion protein was obtained in E.coli. As observed in Figure 2A, the recombinant pro-tein was purified (lane 3) and cleaved from the fusion
with GST by the addition of thrombin, rendering a 40-kDaprotein (lane 4). A Far-western blotting with increasingconcentrations of rFBA was obtained, and depicted inFigure 2B. Concentrations of 0.1 μg to 3 μg of the re-combinant protein were subjected to Far-western, dem-onstrating a dose-dependent binding of the protein withPlg, showing that, in fact, the FBA of Paracoccidioidesbinds to the Plg.
Detection of FBA at the Paracoccidioides surfaceIn order to determine the localization of the FBA inParacoccidioides, Pb01, we performed a western blottingwith cellular fractions of Paracoccidioides and polyclonalantibodies raised in mice to the recombinant protein. Asshown in Figure 3A, the FBA is present in the cyto-plasm, secretome and cell wall (fractions 1 and 2). Thefraction 1 contains proteins associated with the cell sur-face by non-covalent bonds or by disulfide bridges, asdescribed [71,72]. The fraction 2 represents cell wallproteins sensitive to treatment with alkali (ASL-CWPs),including cell wall proteins with internal repeats (PIR-CWPs). Fraction 3 represents proteins with glycosyl-phosphatidylinositol (GPI) anchors linked to the wall
Figure 3 Detection of FBA in Paracoccidioides. (A) Western blotting analysis. Different protein samples (15 μg) of Paracoccidioides comprehendingthe soluble and secreted proteins, cell wall fractions 1, 2 and 3 were obtained by sequential treatments as described in Materials and Methods. Fornegative and positive controls, we employed 3 μg of samples of bovine serum albumin (BSA) and the rFBA, respectively. The immunoblot was probedwith the polyclonal antibodies directed to the rFBA. (B) Immunoelectron microscopy. Panel 1 - Transmission electron microscopy of Paracoccidioidesyeast cells showing the cell wall (w), intracytoplasmic vacuoles (v), nucleus (n) and mitochondria (m). Panel 2 - Gold particles are observed in thecytoplasm region (arrows) and vesicles in release process (arrowheads). * corresponds to the region which has been expanded from panel 2. Panels 3and 4 - Negative controls with anti-rabbit-igG-Au-conjugated and rabbit non immune sera, respectively. The bars indicate: 1.0 μm (Panel 1), 1.0 μm(Panel 2), 0.5 μm (Panel 3), 1.0 μm (Panel 4) and 0.5 μm (Zoom panel).
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(GPI-CWPs) [73,74], but rFBA was not detected in thisfraction. Furthermore, the immunoelectron micros-copy analysis revealed the presence of FBA in the cyto-plasm, in vesicles in releasing process and at the cellsurface, as depicted in Figure 3B, panel 2. The releaseof vesicles to the external environment is used by manypathogens to increase their invasive potential. Vesiclescontain many virulence factors, including moleculesthat bind to and activate Plg [27,70,75]. The presenceof FBA at the surface and vesicle of the fungus canallow the capture of hPlg and plasmin generation,
forming a highly fibrinolytic layer around the fungalcell. These data suggest that FBA, can somehow influ-ence fibrinolytic activity of yeast cells. Cell wall and se-creted proteins, may participate in the process.
Paracoccidioides and rFBA bind and activate plasminogen,promoting fibrinolytic activityWe next investigated whether the capture of Plg byFBA, favors the generation of plasmin. Previous workfrom our group have demonstrated that yeast cells ofParacoccidioides bind to Plg [10]. As described in
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Materials and Methods the test was performed by fix-ation of yeast cells or the rFBA, followed by incubationswith hPlg and tPA. In the presence of tPA, the yeast cellsand the rFBA were able to generate plasmin. This abilitywas inhibited by the lysine analogue (εACA), whichcompetes for the binding sites of Plg (Figure 4A). Com-petition experiments were developed by adding increas-ing concentrations of εACA, which inhibits plasmingeneration in a dose dependent manner (Figure 4B).These data suggest that yeast cells, as well as the recom-binant protein bind hPlg, converting into plasmin in thepresence of tPA.Fibrinogen is a major substrate of plasmin in vivo and
for that, we examined plasmin activity in jellified matri-ces containing fibrinogen (Figure 4C). Fibrin degradationtests were performed in triplicate (data not shown),where yeast cells were incubated in the presence of hPlgand tPA. It was observed the formation of hydrolysis
Figure 4 Plasminogen-binding and activation and fibrin degradationwith hPlg in the presence or absence of tPA and εACA. We used a plasminto dose the amidolytic activity of the reaction of converting plasminogen iincreasing concentrations of εACA (50 mM to 1 M), followed by the additioMaterials and Methods. The error bars indicate the standard deviations betp value < 0.05. (C) The fibrinolytic activity of Paracoccidioides was analysedjellified-fibrin-containing matrix. Panel 1: Paracoccidioides yeast cells in the a1 and 2, but reflecting the presence of tPA. The fungus was incubated in tand proteases inhibitors, aprotinin and PMSF (panels 5 and 6). Controls con
haloes within the jellified-fibrin-containing matrix (Fig-ure 4C, panel 3). In an attempt to block the receptor ofplasminogen on the surface of the fungus, yeast cellswere incubated with anti-rFBA polyclonal antibodies(Figure 4C, panel 4). A decrease in the hydrolysis halocomparing the panels 3 to 4, can be observed. Theaddition of protease inhibitors resulted in no halo forma-tion, due to inactivation of plasmin activity (Figure 4C,panels 5 and 6). Negative controls are presented in panels1 and 2, whereas positive control is presented in panel 7.Thus, we can conclude that FBA of Paracoccidioides mayhave an important role in the host tissues invasion by thefungus, besides participating in metabolic processes. Cor-roborating other studies on this subject, the secondaryrole of this protein makes it an important virulence factor.By capturing and activating Plg, FBA can promote thespread of the fungus, certainly by matrix degradation, pav-ing the way for infection toward internal organs.
assays. (A) Paracoccidioides yeast cells and the rFBA were incubatedsubstrate (D-valyl-L-lysyl-p-nitroaniline hydrochloride) (Sigma-Aldrich)nto plasmin. (B) In competition experiments we added to the wellsn of hPlg. Experiments were performed in triplicate as described inween the results. *: results significantly different from control, at aby the observation of clear hydrolysis haloes within the opaquebsence of hPlg; 2: the fungus after binding to hPlg; 3: Similar tohe presence of hPlg and tPA, with the addition of anti-rFBA (panel 4)sisting of plasminogen and tPA (panel 7).
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rFBA influences the interaction of Paracoccidioides withmacrophagesThe rFBA of Paracoccidioides behaved as an adhesin ina binding assay between J774 and rFBA. Macrophageswere able to bind/internalize the rFBA after 5 h incuba-tion (Figure 5A, line 2). Control is depicted in Figure 5A,line 1, in which no reaction was obtained in macrophagesnot incubated with rFBA. Positive (rFBA, Figure 5A, line3) and negative (BSA, Figure 5A, line 4) controls, aredepicted. Next, we investigated the putative role of FBA inthe interaction between Paracoccidioides and macro-phages. Data represent the percentage of CFUs recoveredfrom infected macrophages, in relation to the control(Figure 5B). The results show that infection of J774 byParacoccidioides was reduced by 79% when the macro-phages were pre incubated with rFBA, and 86% whenthe yeast cells were pre incubated with anti-rFBA anti-bodies. The data strongly suggest a role for the FBA inthe infective process in macrophages.
Figure 5 Paracoccidioides adhesion/internalization bymacrophage: Effects of plasminogen and FBA. (A) Westernblotting analysis of binding of J774 macrophages and rFBA.Macrophages were incubated with 50 μg rFBA (line 2). Additionallycontrols were performed with 5 μg of rFBA for the positive control(line 3), and 5 μg of BSA for negative control (line 4). Line 1 depictsmacrophages, without incubation with the rFBA. The immunoblotwas probed with the polyclonal antibodies directed to the rFBA.(B) Macrophages were or not pre-incubated with the rFBA (50 μg)for 1 h, before infection. Yeast cells (Pb01) were or not treated withthe antibodies to the rFBA (Ab, 1:1000 diluted), with hPlg (50 μg)and tPA (50 ng), for 1 h, or with the antibodies to the rFBA (Ab,1:1000 diluted) and subsequently with Plg (50 μg), and tPA (50 ng),for 1 h. Macrophages were incubated with the yeast cells above for12 h at 36°C. * : results significantly different from control, at ap value < 0.05.
Similar experiments with other proteins such as glyc-eraldehyde 3-phosphate dehydrogenase and triose phos-phate isomerase, that promoted reduced interaction ofParacoccidioides with pneumocytes and Vero cells, werereported [62,76]. Regarding to Plg, the pre-incubationwith Paracoccidioides, in the presence of tPA, promotedincreased macrophage infection (Figure 5B). The additionof the antibodies to rFBA and Plg, prompted inhibited themacrophage infection. This data is consistent with the roleof FBA in activating Plg to plasmin, as previously demon-strated in Figure 4C. Our data suggest that binding of theFBA to Plg, may increase the virulence of this pathogen.
ConclusionsMany microorganisms express proteins that are able tosubvert the host proteases and use them in their favor.Once activated to plasmin, Plg acquires fibrinolytic ac-tivity. Pathogens able to capture Plg can increase theirpotential for dissemination in the host tissues. This workidentified several secreted proteins of Paracoccidioideswith ability to bind to hPlg. These proteins are probabletargets of the interaction of the fungus with the host,probable acting as mediators of plasmin formation,which may contribute to the invasion of the fungus inthe host tissues. The FBA, was detected at the Paracocci-dioides surface and secretory vesicles, in addition to theconventional cytoplasmatic localization. The protein canbind to hPlg, converting it to plasmin in the presence oftPA. This interaction promoted increased fibrinolyticcapacity of the fungus, as demonstrated in fibrin degrad-ation assay. Moreover, we demonstrated that FBA adheredto macrophages and contribute in some way to the inter-action of the fungus with these defense cells. These datasuggest that FBA is a Plg-binding protein, and may be im-portant virulence factor involved in the process of adhe-sion, invasion and spread of the fungus.
MethodsStrains and mediaParacoccidioides, Pb01 (ATCC MYA-826) was used inall experiments. The yeast phase was maintained in vitroby sub culturing at 36°C during 7 days in Fava Netto’ssolid medium [1% (w/v) peptone, 0.5% (w/v) yeast extract,0.3% (w/v) proteose peptone, 0.5% (w/v) beef extract, 0.5%(w/v) NaCl, 4% (w/v) glucose, 1.2% (w/v) agar, pH 7.2].
Preparation of Paracoccidioides protein fractionsTo obtain the secreted proteins, the yeast cells of Para-coccidioides, Pb01 were inoculated in Fava Netto’s liquidmedium and cultured at 36°C for 24 h with shaking at200 rpm, as previously described [48]. The proportion ofcells used to obtain the inoculum was 2.5 g wet weightof yeast cells per 50 mL of liquid medium, or 50 mg/mL.After the incubation for 24 h, microscopic analysis was
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performed to check fungal viability, followed by cellscentrifugation at 10,000 × g, for 30 min at 4°C. Thesupernatant was used for obtain the secreted proteins[48]. The culture supernatant was sequentially filteredthrough 0.45 mm-pore and 0.22 mm-pore membrane fil-ters. Culture filtrates were concentrated and subse-quently washed three times with ultrapure water viacentrifugation 10,000 × g through a 10-kDa molecularweight cut off membrane (Amicon ultra centrifugal filter,Millipore, Bedford, MA, USA). The obtained pellet,which contains the yeast cells, was used to the extractionof Paracoccidioides soluble [77] and cell wall proteins.Briefly, yeast cells were washed five times with 10 mMTris–HCl, pH 8.5, 2 mM CaCl2 added of the 1:1000 pro-tease inhibitor phenyl methyl sulfonyl fluoride (PMSF)and centrifuged at 10,000 × g for 30 min at 4°C. Thecells were frozen in liquid nitrogen and disrupted by ma-ceration. Subsequently, the precipitate was resuspendedin lysis buffer (20 mM Tris–HCl pH 8.8; 2 mM CaCl2)added of the protease inhibitor PMSF (1:1000) and glassbeads; the mixture was agitated for 1 h. After centrifuga-tion 10,000 × g for 30 min at 4°C, the supernatant andpellet were used to obtain the Paracoccidioides solubleand cell wall proteins, respectively. The cell wall proteinswere extracted by sequential treatments according to thetype of connection that these proteins establish withother cell wall components, as previously described, withsome modifications [10,71,74,78]. Briefly, the pellet waswashed 5 times as following: with cold sterile distilledwater, with 5% (w/v) NaCl, with 2% (w/v) NaCl and with1% (w/v) NaCl. After the washes, the pellet was treatedwith extraction buffer [50 mM TrisHCl, pH 7.8, 2% (w/v)SDS, 100 mM EDTA and 40 mM β-mercaptoethanol] for10 min at 100°C. The supernatant from centrifugationconstitutes the first fraction (Fraction 1). The pellet resist-ant to extraction with SDS was washed 5 times with 0.1 Msodium acetate pH 5.5. The obtained solution was centri-fuged at 10,000 × g for 30 min at 4°C and the pellet wastreated with 30 mM NaOH for 24 h at 4°C, to obtain thesecond fraction, that after centrifugation at 10,000 × g for30 min at 4°C, constituted the fraction 2. The pellet wastreated with pyridine-hydrogenated fluoride (HF-pyridine)on ice for 24 h to give the third fraction (Fraction 3).All the obtained protein extracts described above were
concentrated and washed three times with ultrapure watervia centrifugation through a 10 kDa molecular weight cutoff in ultracel regenerated membrane (Amicon ultra cen-trifugal filter, Millipore, Bedford, MA, USA). The proteinconcentrations were determined by the Bradford assayusing bovine serum albumin as standard [79].
Two-dimensional gel electrophoresisTwo-dimensional fractionation (2-DE) of secreted pro-teins was performed, as described [77,80]. The 2-DE gels
were obtained in duplicates, using 500 μg of proteins, foreach one. The samples were treated with the commercialsystem of purification 2D Clean-up Kit (GE Healthcare,Uppsala, Sweden) for removing interferences according tothe manufacturer’s instructions, before protein isoelectricfocusing. Proteins samples were treated with 250 μL ofbuffer containing 7 M urea, 2 M thiourea, 130 mM 3- [(3-cholamidopropyl) dimethylammonio]-1-propanesulfonate(CHAPS), 0.002% (w/v) dithiothreitol (DTT), ampholyte-containing buffer (IPG buffer, GE Healthcare), and traceamounts of bromophenol blue. Then the samples wereloaded onto a 13 cm ImmobilineTM DryStrip gel (GEHealthcare) with a pH range of 3–11 for separation ofproteins according to their isoelectric points (pI) with anelectric current of 50 μA / strip at 20°C. In order to per-form the first separation of secreted proteins, isoelectricfocusing was conducted as following: 30 V for 14 h, 250 Vfor 1 h (step), 1 kV for 1 h (step), 2 kV for 1 h (step), 5 kVfor 3 h (gradient), 8 kV for 8 h (gradient) and 8 kV for 1 h(step). Strips were reduced with 18 mM DTT (dithiothrei-tol) and alkylated with 135 mM iodoacetamide in equili-bration buffer [50 mM Tris–HCl pH 8.8, 6 M urea, 30%(v/v) glycerol, 2% (w/v) sodium dodecyl sulfate (SDS) and0.002% (w/v) bromophenol blue] during 40 min. The sec-ond dimension was performed in 12% polyacrylamide gelelectrophoresis under denaturing conditions (SDS-PAGE)in running buffer [25 mM Tris–HCl, 192 mM glycine,0.1% (w/v) SDS], using a vertical system (GE Healthcare)at 12°C during 1 h at 150 V, and after at 250 V. Two gelswere stained by Commassie brilliant blue (Plus OneCoomassie Tablets Phast Gel Blue R-350, GE Healthcare)according to manufacturer’s instructions to visualize theproteins.
Far-westernFor the Far-western experiments, the 2-DE gels wereproduced in duplicates. The secreted proteins, after oneor two-dimensional fractionation, were transferred tonitrocellulose membranes for ligand binding with Plg, toidentify Plg-binding receptors. The results were com-pared to the protein pattern of the Coomassie bluestained counterpart. The membranes were incubated inblocking buffer [0.1% (v/v) Tween 20, 5% (w/v) skimmedpowder milk, in 10 mM PBS (0.14 M NaCl, 2.7 mMKCl, 10 mM Na2HPO4, 1.8 mM KH2PO4, pH 7.3)] for1 h at room temperature. Subsequently, the membraneswere washed three times with PBS containing 0.05% (v/v)Tween 20 (PBS-T) and, except for the negative control,the membranes were incubated with 35 μg/mL of hPlg(Sigma-Aldrich) diluted in blocking buffer, for 1 h undershaking, as described [10]. Subsequently, the membraneswere washed three times with PBS-T and incubated with1 μg/mL anti-human plasminogen (Anti-hPlg) producedin mice (Sigma-Aldrich) diluted 1:100 in blocking buffer.
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After three washes in PBS-T, the membranes were incu-bated with the secondary antibody (anti-mouse IgGcoupled to alkaline phosphatase) (Sigma-Aldrich) di-luted 1:5000 in blocking buffer, for 1 h. After that, themembranes were washed and the reaction was devel-oped using 5-Bromo-4-chloro-3-indolyl phosphate(BCIP) and Nitro Blue Tetrazolium (NBT).
Expression of the rFBA by Escherichia coli, purification ofthe recombinant protein and polyclonal antibodiesproductionThe cDNA that encodes FBA of Paracoccidioides, Pb01(GenBank Accession Number AY233454) was previouslyobtained [69]. Oligonucleotide primers were designed:sense S (5’-GAATTCCATGGGCGTGAAAGACA-3’) andantisense AT (5’-GCGGCCGCCTACAACTGGTTAGAA-3’) in order to obtain the cDNA. The cDNA productobtained by RT-PCR was cloned into the expression vec-tor pGEX-4 T-3 (GE Healthcare) and transformed intoEscherichia coli XL1 blue competent cells. Bacterial cellswere grown in Luria-Bertani (LB) medium supplementedwith 100 μg/ml ampicillin under agitation at 37°C untilthe OD reaches an absorbance of 0.6 at a wavelength of600 nm. The reagent Isopropyl-β-D-thiogalactopyranoside(IPTG) was added to the growing culture to a final con-centration of 0.1 mM. After 16 h incubation at 15°C, thebacterial cells were harvested by centrifugation at10,000 × g for 10 min and resuspended in PBS. Solubleproteins were obtained by sonication, followed by centri-fugation at 10,000 × g during 10 min. FBA linked to GST(glutathione-S-transferase) was affinity purified usingglutathione Sepharose 4B resin (GE Healthcare). The resinwas washed 10 times in PBS and the GST was cleaved byaddition of thrombin (50 U/ml) (Sigma-Aldrich). The pur-ity and size of the recombinant protein were assessed bySDS-PAGE followed by staining with Coomassie Blue.The rFBA was used for production of polyclonal anti-bodies in mice. The purified protein (300 μg) was injectedinto mice along with Freund’s adjuvant three times at in-tervals of 15 days. Serum containing polyclonal antibodieswas collected and stored at −20°C.
Western blottingFor western blotting analysis, the Paracoccidioides pro-tein samples were probed using polyclonal antibodiesproduced to the rFBA. Protein samples were loaded ontoa 12% SDS-PAGE gel and separated by electrophoresis.The gels were run at 150 V for approximately 2 h andthe proteins were transferred to nitrocellulose mem-branes at 30 V for 16 h in a buffer containing 25 mMTris–HCl (pH 8.8), 190 mM glycine and 20% (v/v)methanol. The gels were stained with Ponceau red toverify complete protein transfer. Next, each membranewas incubated in blocking buffer [1X PBS, 1.4 mM
KH2PO4, 8 mM Na2HPO4, 140 mM NaCl, 2.7 mM KCl(pH 7.3), 5% (w/v) nonfat dried milk and 0.1% (v/v)Tween 20] for 2 h. The membranes were washed withPBS-T, and incubated with anti-rFBA polyclonal anti-bodies (1:1000), followed by washing in blocking bufferthree times, during 15 min each wash. The membraneswere incubated with the secondary antibody anti-mouseimmunoglobulin G (IgG) coupled to alkaline phosphatase(Sigma Aldrich) diluted 1:5000 in blocking buffer, for 1 h.After that, the membranes were washed and the reactionwas developed using 5-Bromo-4-chloro-3-indolyl phos-phate (BCIP) and Nitro Blue Tetrazolium (NBT).
Image analysesThe comparative analysis between the images of the pro-teins stained with Coomassie Blue and the membranesof the Far Western assay were performed using theImage Master 2D Platinum software v7.0 (GE Health-care) in order to identify in the 2-DE gels the proteinspots that were visualized in the membranes through thepairing. The gels and membranes were aligned and thespots were compared according to their isoelectricpoints and molecular masses.
Mass spectrometry analysisThe spots of interest were manually excised from the 2-DE gels and treated with trypsin as previously described[48,77,80]. The spots were removed, washed three timeswith ultrapure water, resuspended in 100 μL of 100%acetonitrile (ACN) and dried in a vacuum centrifuge.Subsequently, the samples were reduced with 10 mMDDT in 25 mM ammonium bicarbonate (NH4HCO3),and alkylated with 55 mM iodoacetamide in 25 mMNH4HCO3, protected from light. The supernatant wasremoved and the gel pieces were washed with 100 μL ofa solution containing 25 mM ammonium bicarbonate/50% ACN (v/v), vortexed for 5 min, and centrifuged. En-zymatic digestion was performed by incubation at 37°Cfor 16 h in buffer containing trypsin (12.5 ng/μL) and25 μL of 25 mM NH4HCO3. The supernatant was trans-ferred to a new tube and the gel pieces were shaken for30 min in 50% ACN (v/ v), and 1% trifluoroacetic acid(TFA) (v/v), followed by sonication for 5 min, afterwhich the supernatant was combined with the one ob-tained in the previous step. The dried samples were re-suspended in 10 μL of ultrapure water and subsequentlypurified using a pipette tip with a bed of chromato-graphic media (ZipTips® C18 Pipette Tips, Millipore,Bedford, MA, USA). Two microliters of each peptidesample were deposited onto a matrix-assisted laserdesorption ionization quadrupole time-of-flight massspectrometry (MALDI-Q-TOF MS) target plate. Next,2 μL of matrix solution (10 μg/μL a-cyano-4-hydroxy-ciannamic acid matrix in 50% (v/v) ACN and 5% (v/v)
Chaves et al. BMC Microbiology (2015) 15:53 Page 11 of 14
TFA) was added. The mass spectra were performed inthe positive reflectron mode on a MALDI-Q-TOF massspectrometer (SYNAPT, Waters Corporation, Manchester,UK). The MS/MS and PMF analysis was performed usingMascot software v. 2.4 (http://www.matrixscience.com)(Matrix Science, Boston, USA). The ion search parameterswere: tryptic peptides with one missed cleavage allowed;fungi taxonomic restrictions; fixed modifications: carba-midomethylation of Cys residues; variable modifications:oxidation of methionine and a tolerance of 0.6 Da. In silicoanalyzes were performed to validate the results obtainedin vitro. In order to predict the location of proteins weused the program Psort (http://www.genscript.com/psort/wolf_psort.html). The software big-PI Fungal Predictor(http://mendel.imp.ac.at/gpi/fungi_server.html) was usedto predict glycosylphosphatidylinositol (GPI) protein an-chors. In order to predict proteins to be secreted weemployed the Signal P (http://www.cbs.dtu.dk/services/SignalP/) that predicts the classical pathway secretion andSecretome P (http://www.cbs.dtu.dk/services/SecretomeP/) that predicts nonclassical pathway secretion.
Ultrastructure of the yeast cells and immunocytochemistryof FBAFor the ultrastructural and immunocytochemistry stud-ies, previously described protocols were employed[76,81,82]. The yeast cells were fixed in solution contain-ing 2% (v/v) glutaraldehyde, 2% (w/v) paraformaldehyde,and 3% (w/v) sucrose in 0.1 M sodium cacodylate bufferpH 7.2. Ultrathin sections were stained with 3% (w/v)uranyl acetate and lead citrate. For ultra-structural im-munocytochemistry studies, the ultrathin sections wereincubated for 1 h with the polyclonal antibodies raisedagainst the rFBA (diluted 1:100) and for 1 h at roomtemperature with the labeled secondary antibody antimouse IgG, Au-conjugated (10 nm average particle size;1:20 dilution). The grids were stained as describedabove, and observed with a Jeol 1011 transmission elec-tron microscope (Jeol, Tokyo, Japan). Controls were in-cubated with mouse preimmune serum (1:100 dilution).
Plasminogen activation assayThe wells of multitier plates were coated with 1 μg ofrFBA or fixed with 1 × 108 yeast cells during 1 h. Afterthat, the wells were incubated with 1 μg of hPlg(Sigma-Aldrich), followed by incubation with 3 μg ofplasmin substrate (D-valyl-L-lysyl-p-nitroaniline hydro-chloride) (Sigma-Aldrich) and 15 ng of tPA (Sigma-Aldrich). Competition and control experiments wereperformed by blocking the generation of plasmin inthe absence of tPA (Sigma-Aldrich) or in the presence ofthe lysine analogue ε-aminocaproic acid (εACA). The ami-dolytic activity of the generated plasmin was measured at405 nm.
Fibrin matrix-gel degradation analysisThe matrix gel contained 1.25% (w/v) low-melting-temperature agarose, 100 μg of hPlg (Sigma- Aldrich) and4 mg of fibrinogen (Sigma- Aldrich) in a final volume of2 mL. To detect fibrinolysis activity, a total 1 × 107 cells ofParacoccidioides, Pb01 were incubated with 50 μg of hPlgfor 3 h in the presence or absence of tPA (50 ng). Theyeast cells were also incubated with the serine proteinaseinhibitors aprotinin (1 μg), PMSF (50 mM) and with anti-rFBA antibodies in a final volume of 1 mL. Thereafter, themixtures were washed three times with PBS and thepellets were placed in wells of a fibrin substrate matrixgel. Plasmin activity was detected by the observation ofclear hydrolysis haloes within the opaque jellified fibrin-containing matrix, after incubation in a humidified cham-ber at 37°C for 12 h.
Binding assays of the rFBA to in vitro cultured macrophagesJ774 1.6 macrophages (Rio de Janeiro Cell Bank – BCRJ/UFRJ, accession number 0273) were used for phagocyt-osis assays. The J774 1.6 cells were cultured in RPMImedium containing bovine fetal serum 10% (v/v) (Vitro-cell Embriolife,) containing IFN-γ (1U per mL) andMEM non-essential amino acid solution (Sigma Aldrich,Missouri, USA) at 36°C and 5% CO2, until completeconfluence. The macrophages were incubated with50 μg/mL of rFBA, at 36°C for 5 h, and washed. Next,the cells were lysed by incubating with distilled water for1 h. The lysate was centrifuged at 1,400 × g for 5 min.The proteins contained in the supernatant were submit-ted to SDS-PAGE and transferred to nitrocellulosemembrane. The membrane was incubated blocking buf-fer [PBS 1X with 5% (w/v) nonfat dried milk and 0.1%(v/v) Tween 20] for 2 h, and then successively with anti-rFBA polyclonal antibodies (1:1000) and with the anti-mouse immunoglobulin G (IgG) coupled to alkalinephosphatase (Sigma Aldrich). The reactions were devel-oped with BCIP-NBT.
rFBA and anti rFBA-antibodies decrease Paracoccidioidesmacrophages interactionWe tested the interference of the rFBA and antibodies toadhesion/infection of Paracoccidioides in macrophages. Inaddition, we tested the ability of Plg-treated yeast cells toadhere/infect macrophages. A total of 5 × 106 yeast cells,per well, were added to the macrophages, reaching ayeast:macrophages cells ratio of 5:1, followed by incuba-tion for 12 h at 36°C, in 5% CO2, in RPMI medium con-taining IFN-γ (1U per mL). The J774 cells were preincubated for 1 h at 36°C with the rFBA (50 μg/ml), or theyeast cells were pre- incubated with anti-rFBA antibody(1:1000) and then the infection was performed. In parallel,yeast cells were incubated with the polyclonal antibodyanti-rFBA (1:1000 diluted) for 1 h at 36°C, and then
Chaves et al. BMC Microbiology (2015) 15:53 Page 12 of 14
incubated with plasminogen (50 μg) and tPA (50 ng) for1 h at 36°C. After that, the yeast cells were washed threetimes in PBS 1X and incubated with the macrophages.At the end of the infection, the adhered macrophages
were washed, lysed by addition of distilled water andcentrifuged. The pellet was diluted 1:10 and plated insolid BHI medium supplemented with inactivated fetalcalf serum (4% v/v). After 7 days at 37°C the number ofCFU’s was counted.
Statistical analysisThe experiments were performed in triplicate, with sam-ples in triplicates. Results are presented as means ± stand-ard deviations. Statistical comparisons were performedusing Student’s t test and the statistical significance wasaccepted for P value of < 0,05.
Authors’ contributionsEGAC participated in the design of the study, participated actively in allexperiments and drafted the manuscript. SSW obtained protein samples,assisted in the production of 2-DE gels, cooperated in the identification andin silico analysis of proteins. SNB performed the immunoelectron microscopyassay. LAP was responsible for the production of bacteria clones expressingthe rFBA and the production of polyclonal antibodies. CLB and AMB helpedin the preparation of the figures of the article, in analysis and suggestionsduring the course of the experiments and critically revised the manuscript.CMAS designed the experiments, provided guidance during all parts of thework, and wrote the manuscript. All authors read and approved the finalversion of the manuscript.
AcknowledgementsThe authors wish to thank the funding agencies: Coordenação deAperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacionalde Desenvolvimento Científico e Tecnológico (CNPq), and Fundação deAmparo à Pesquisa do Estado de Goiás (FAPEG) by financial support.
Author details1Laboratório de Biologia Molecular, Instituto de Ciências Biológicas, ICBII,Campus II, Universidade Federal de Goiás, 74001-970 Goiânia, Goiás, Brazil.2Laboratório de Microscopia, Departamento de Biologia Celular, Instituto deCiências Biológicas, Universidade de Brasília, Brasília, Distrito Federal, Brazil.
Received: 19 August 2014 Accepted: 18 February 2015
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