ARTICLE

Loss of the E3 ubiquitin ligase MKRN1 repressesdiet-induced metabolic syndrome through AMPKactivationMin-Sik Lee1, Hyun-Ji Han2, Su Yeon Han2, Il Young Kim3,4, Sehyun Chae5, Choong-Sil Lee2, Sung Eun Kim2,

Seul Gi Yoon4, Jun-Won Park4, Jung-Hoon Kim2, Soyeon Shin2, Manhyung Jeong2, Aram Ko2, Ho-Young Lee6,

Kyoung-Jin Oh 7, Yun-Hee Lee 8, Kwang-Hee Bae7, Seung-Hoi Koo9, Jea-woo Kim10, Je Kyung Seong3,4,

Daehee Hwang5 & Jaewhan Song 2

AMP-activated protein kinase (AMPK) plays a key role in controlling energy metabolism in

response to physiological and nutritional status. Although AMPK activation has been pro-

posed as a promising molecular target for treating obesity and its related comorbidities, the

use of pharmacological AMPK activators has been met with contradictory therapeutic

challenges. Here we show a regulatory mechanism for AMPK through its ubiquitination and

degradation by the E3 ubiquitin ligase makorin ring finger protein 1 (MKRN1). MKRN1

depletion promotes glucose consumption and suppresses lipid accumulation due to AMPK

stabilisation and activation. Accordingly, MKRN1-null mice show chronic AMPK activation in

both liver and adipose tissue, resulting in significant suppression of diet-induced metabolic

syndrome. We demonstrate also its therapeutic effect by administering shRNA targeting

MKRN1 into obese mice that reverses non-alcoholic fatty liver disease. We suggest that

ubiquitin-dependent AMPK degradation represents a target therapeutic strategy for meta-

bolic disorders.

DOI: 10.1038/s41467-018-05721-4 OPEN

1 Harvard Medical School, Boston Children’s Hospital, 3 Blackfan Circle CLS-16060.2, Boston, MA 02115, USA. 2Department of Biochemistry, College of LifeScience and Biotechnology, Yonsei University, Seoul 03722, Republic of Korea. 3 Laboratory of Developmental Biology and Genomics, Research Institute forVeterinary Science and BK21 Program for Creative Veterinary Science and Research, College of Veterinary Medicine, Seoul National University, Seoul 08826,Republic of Korea. 4 Korea Mouse Phenotyping Center (KMPC), Seoul National University, Seoul 08826, Republic of Korea. 5 Center for Plant Aging Research,Institute for Basic Science, and Department of New Biology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Republic ofKorea. 6 Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam 13620, Republic of Korea. 7Metabolic Regulation ResearchCenter, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea. 8 College of Pharmacy, Yonsei Institute ofPharmaceutical Sciences, Yonsei University, Incheon 21983, Republic of Korea. 9Division of Life Sciences, College of Life Sciences & Biotechnology, KoreaUniversity, Seoul 02841, Republic of Korea. 10 Department of Biochemistry and Molecular Biology, Brain Korea 21 PLUS Project for Medical Science, YonseiUniversity College of Medicine, Seoul 03722, Republic of Korea. These authors contributed equally: Min-Sik Lee, Hyun-Ji Han. Correspondence and requestsfor materials should be addressed to J.S. (email: jso678@yonsei.ac.kr)

NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications 1

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Metabolic syndrome is associated with the risk of devel-oping a number of disorders, including type 2 diabetes(T2D), non-alcoholic fatty liver disease (NAFLD) and

cardiovascular disease, and has become a common pathologicalcondition due to the increased prevalence of obesity associatedwith the western lifestyle1–3. The syndrome develops in responseto chronic disturbances in the balance between energy intake andexpenditure4. From a therapeutic perspective, cellular energyexpenditure (EE) has emerged as an attractive strategy for thetreatment of obesity and diabetes1. Although the molecularmechanisms implicated in regulating the energy-wasting processin brown fat and skeletal muscle have been identified, new andeffective drugs for the treatment of obesity that stimulate cellularEE remain to be developed2.

AMP-activated protein kinase (AMPK), a cellular energy-sensing enzyme, is a key regulator of metabolic syndrome andcomprises diverse heterotrimeric complexes containing a catalytic(α1 or α2) subunit and two other regulatory subunits (β1 or β2and γ1, γ2 or γ3)5,6. Under various conditions of energy stressthat elevate the AMP/ATP ratio, the binding of AMP to the γsubunit maintains the enzyme in an activated state due to allos-teric activation, which promotes phosphorylation by theupstream kinases liver kinase B1 and calcium calmodulin-dependent protein kinase kinase β6. Consequently, AMPK acti-vation generates ATP to restore energy homeostasis by upregu-lating catabolic processes and inhibiting energy-consuminganabolic processes5–7.

AMPK, an attractive anti-obesity target for exploiting cellularEE, integrates nutritional, hormonal and pharmacological inputsto maintain the cellular energy balance8,9. In many genetic rodentmodels, including leptin-deficient (ob/ob) mice, sustaineddecreases in AMPK activity accompany metabolic syndrome10,11.AMPK activation mitigates metabolic syndrome in peripheraltissues. AMPK activation in the liver promotes the phosphor-ylation of acetyl-CoA carboxylase (ACC) to restrain fatty acidsynthesis5,7 and suppresses the activity of the transcription factorssterol regulatory element-binding protein 1 (SREBP-1) and car-bohydrate response element-binding protein (ChREBP)12–14,which inhibit hepatic lipogenesis. AMPKα2 deficiency causeshypertriglyceridemia15, whereas liver-specific AMPK activationprevents diet-induced NAFLD in mice16. Pharmacological AMPKactivators, such as 5-aminoimidazole-4-carboxamide (AICA)riboside, ameliorate insulin resistance in rodent models5,17,18,although poor bioavailability limits their biological effects in vivo.Furthermore, a lack of both AMPKβ1 and β2 in adipocytesopposes the thermogenic responses of brown and beige fat andintensifies diet-induced NAFLD and glucose intolerance19, sup-porting the physiological role of AMPK in lipid metabolism andits clinical relevance. In contrast, the activation of hypothalamicAMPK is associated with the promotion of appetite in response tofasting and results in increased food intake and body weight20–22.Given the role of AMPK in the maintenance of the whole-bodyenergy balance, it is not surprising that AMPK activationincreases the orexigenic effect related to the energy supply23.Thus, despite a wide array of salutary effects of AMPK activationon metabolic syndrome, the systemic effect of chronic AMPKactivation presents a unique challenge24. The identification of atissue-specific AMPK regulatory mechanism would be an alter-native strategy for the development of potent and selective AMPKactivators25,26.

Although AMPK phosphorylation is the best-delineated systemthrough which AMPK enzymatic activity is regulated, theubiquitin-proteasome system has begun to attract attention as apossible regulatory mechanism that controls AMPK function inenergy metabolism27–29. Tripartite motif-containing 28, an E3ubiquitin ligase, and UBE2O, an E2 ubiquitin-conjugating

enzyme, ubiquitinate and degrade AMPKα1 and α2, respec-tively, resulting in AMPK dysfunction in cancer30,31. However, anE3 ubiquitin ligase for AMPK that controls systemic metabolismhas yet to be reported.

As shown in this study, makorin ring finger protein 1(MKRN1) is an E3 ubiquitin ligase for AMPK in the liver andadipocyte tissues. AMPK activation in mice lacking MKRN1prevents NAFLD, insulin resistance and obesity associated with ahigh-fat diet (HFD). The possible curative effects of MKRN1inhibition on hepatic steatosis and hyperglycaemia were furtherobserved using an adenoviral gene delivery system. Our studyprovides new therapeutic opportunities for treating metabolicsyndrome by hijacking the E3 ubiquitin ligase for AMPK.

ResultsMKRN1 inhibition induces AMPK-dependent catabolicprocesses. The physiological role of MKRN1 has been well deli-neated in cancer based on its ability to degrade several tumoursuppressors32–35. MKRN1 is also associated with adipocyte dif-ferentiation in vitro36. However, the implications of MKRN1 forsystemic energy metabolism have yet to be studied. We initiallymeasured glucose metabolic activity in MKRN1-deficient mouseembryonic fibroblasts (MEFs) to further define the metabolicfunctions of MKRN1. Intriguingly, increased glucose uptake wasobserved in MEFs lacking MKRN1 or HepG2 cells depleted ofMKRN1 (Fig. 1a, f and Supplementary Fig. 1a). Accordingly, weobserved increased levels of metabolites of glycolysis andthe tricarboxylic acid cycle (Fig. 1b, c) in MEFs lacking MKRN1.The data suggest that MKRN1 depletion promotes energy pro-duction via cellular glucose utilisation. In addition, our previousreports indicated that MKRN1 suppression might promoteAMPKα1 and α2 phosphorylation35. Based on these observations,we reasoned that the activation of AMPK signalling might beinvolved in promoting glucose metabolism in MKRN1-nullMEFs. As expected, MKRN1 deficiency increased the levels ofactivated AMPKα (phosphorylated at T172), which suppressedthe activity of its downstream target, acetyl coenzyme A ACC, viaphosphorylation (Fig. 1d). Additionally, MKRN1 ablationinduced an increase in AMPKα protein level without affectingmessenger RNA levels, suggesting that these events depend onpost-translational processes (Fig. 1d). Similar results were alsoobserved in MKRN1-depleted HepG2 and Hep3B cells followingtransfection with two independent small interfering RNAs (siR-NAs) (Fig. 1f and Supplementary Fig. 1b). In accordance withAMPK activation under MKRN1 depletion, alterations in theexpression of genes that activate glycolysis and suppress fatty acidsynthesis were further observed (Fig. 1e)7,37,38. AMPKα ablationcompletely reversed the effects of MKRN1 on glycolytic andlipogenic gene expression (Supplementary Fig. 1c, d). Theimplications of MKRN1 for the modulation of AMPK-mediatedregulation of glucose metabolism were further revealed by theincreased glucose uptake MKRN1-null MEFs, which was reversedby AMPKα knockdown (Supplementary Fig. 1e, f). Given thesuppression of lipogenic gene expression, we further investigatedthe effect of MKRN1 ablation on HepG2 cellular steatosisinduced by free fatty acids (FFAs). MKRN1 knockdown reducedlipid accumulation in HepG2 cells, as indicated by Oil Red Ostaining (Fig. 1g) and the triglyceride (TG) mass (Fig. 1h). Theseeffects were completely reversed upon AMPKα2 ablation (Sup-plementary Fig. 1g). Corroborating these findings, fatty acidoxidation (FAO) was enhanced in MEFs lacking MKRN1 orHepG2 cells in which MKRN1 was ablated (Fig. 1i–k and Sup-plementary. Fig. h–j). Thus, MKRN1 deficiency induces activa-tion of the AMPK signalling pathway, leading to a metabolicswitch from anabolism to catabolism.

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05721-4

2 NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications

MKRN1 acts as an E3 ubiquitin ligase for AMPKα. As MKRN1depletion induced AMPKα stabilisation without affecting itsmRNA levels, the potential role of MKRN1 as an E3 ligase forAMPKα was further investigated. The results of co-immunoprecipitation analyses using overexpressed proteinsshowed that both the N and C termini of MKRN1 bound to the β-subunit-interacting domain of AMPKα (Supplementary Fig. 2a, b,d, e). Recombinant MKRN1 directly interacted with AMPKα(Supplementary Fig. 2c). Endogenous interactions betweenAMPK and MKRN1 were further observed in MEFs (Supple-mentary Fig. 2f). MKRN1 knockdown resulted in increasedAMPKα protein levels, without affecting AMPKβ and γ,

indicating that the α subunits are specific targets of MKRN1(Fig. 2a). In addition to these observations, the AMPKα proteindisplayed an extensively prolonged half-life in cycloheximide(CHX)-treated MKRN1-null MEFs compared with that of thecontrol (Fig. 2b). Conversely, MKRN1 overexpression promotedthe degradation of the AMPKα1 and α2 proteins, but not of the βand γ proteins (Fig. 2c). Further confirming these findings,AMPKα stabilised by MKRN1 depletion was degraded uponoverexpression of MKRN1 resistant to MKRN1-targeting siRNAbut was not affected by the expression of MKRN1 H307E, an E3ligase-defective MKRN1 mutant32 (Supplementary Fig. 3a). Fur-thermore, the levels of the AMPKα1 and α2 proteins were rescued

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Fig. 1 MKRN1 depletion stimulates glucose metabolism by activating AMPK signalling. Analysis of wild-type (WT) or MKRN1-knockout (MK1−/−)littermate primary mouse embryonic fibroblasts (MEFs) and HepG2 cells transduced with two independent siRNAs targeting MKRN1 (siMK1 #6 and siMK1#7) or a control siRNA for 48 h. a Glucose consumption in MK1−/− MEFs (left) or MKRN1-depleted HepG2 cells (right) was measured based on theabsorption of 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxy-D-glucose (2-NBDG) by the cells. b, c Intracellular levels of glycolytic and citric acidcycle intermediates were determined by capillary electrophoresis–time-of-flight mass spectrometry of the MEFs. Each bar represents the relative amountof a metabolite for WT MEFs. G6P glucose-6-phosphate, F6P fructose-6-phosphate, F1,6-BP fructose-1,6-bisphosphate, G3P glucose-3-phosphate, 1,3-BG1,3-bisphosphoglycerate, 3PG 3-phosphoglycerate, 2PG 2-phosphoglycerate, AcCoA acetyl-CoA, α-KG α-ketoglutarate. d, f To validate the AMPKsignalling pathway or mRNA levels of AMPKα subunits, immunoblotting or quantitative real-time PCR analysis was performed using MEFs (d) and HepG2cells (f). Cell lysates were immunoblotted with antibodies against pAMPKα, AMPKα, pACC, ACC, MKRN1 and actin. e The mRNA levels of glycolytic orlipogenic enzymes in MEFs were analysed by quantitative real-time PCR. g, h FFA-induced steatosis in HepG2 cells. Oil Red O staining (g) and TG levels(scale bar= 100 µm (top), 50 µm (bottom) (h) of the cells treated with FFA/FFA-free bovine serum albumin (BSA), which served as controls. All theexperiments with MEFs were conducted in cells within the first 3–6 passages. i Fatty acid oxidation was analysed in MKRN1-depleted HepG2 cells. j Thebasal oxygen consumption rate (OCR) was measured in WT and MK1−/− MEFs. k After sequential treatment with oligomycin, FCCP and rotenone/antimycin-A in the presence of BSA or BSA conjugated to palmitate, OCR was measured in WT orMK1−/− MEFs. The results were normalised against totalprotein levels using XF-Analyze. All data are presented as the mean ± standard deviation (s.d.) of triplicate samples and are representative of at least threeindependent experiments. two-tailed Student’s t-test; *P≤ 0.05, **P≤ 0.01, ***P≤ 0.001

NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05721-4 ARTICLE

NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications 3

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Fig. 2 The E3 ubiquitin ligase MKRN1 ubiquitinates and degrades AMPKα subunits. a MKRN1 knockdown increases AMPKα1 protein levels. TheHepG2 cells were transfected with MKRN1 siRNAs (#6 and #7). b MKRN1 knockout stabilises AMPKα. WT or MK1−/− MEFs were treated with CHX(100mgml−1) at the indicated time points. c, d MKRN1 expression promotes the proteasomal degradation of AMPKα subunits. The protein levels ofectopically expressed AMPK subunits were analysed using HEK293T cells. GFP was used as a transfection control (c). HepG2 cells were infected withretrovirus expressing MKRN1, followed by selection using puromycin. The cells were treated with 20 µM of MG132 for 6 h, and AMPKα1, α2, MKRN1 andactin were detected with the indicated antibodies (d). eMKRN1 induces both AMPKα1 and α2 ubiquitination. Constructs expressing FLAG/AMPKα1, α2, β1,γ1, 3.1/MKRN1 and HA/Ub were transfected into 293T cells. The ubiquitination assay was performed using cell lysates under denaturing conditions (in 1%SDS buffer). f, g MKRN1 directly ubiquitinates AMPKα subunits. In vitro ubiquitination of AMPKα1 (f) and α2 (g). h, i MKRN1 is required for theubiquitination of AMPKα. Ubiquitinated endogenous AMPKα was determined under denaturing conditions using MG132-treated MEFs (h) and HepG2 cells(i). All the experiments with MEFs were conducted in cells within the first 3–6 passages. The data are representative of at least three independentexperiments

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05721-4

4 NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications

by the addition of an MG132 proteasome inhibitor (Fig. 2d),suggesting that MKRN1 degrades AMPKα in a proteasome-dependent manner.

Consistent with these results, MKRN1 promoted the ubiqui-tination of both AMPKα1 and α2 predominantly through K48-linked polyubiquitination (Fig. 2e and Supplementary Fig. 3b, c).In vitro ubiquitination reactions using recombinant proteinsrevealed that MKRN1 directly facilitated the ubiquitination ofAMPKα1 and α2, but not of AMPKβ and γ (Fig. 2f, g andSupplementary Fig. 3d). In contrast to wild-type (WT) MKRN1,the enzymatically inert H307E MKRN1 mutant failed to promoteAMPK ubiquitination, despite its ability to bind to AMPK(Fig. 2f, g and Supplementary Fig. 2b). Notably, MKRN1-nullMEFs and MKRN1-depleted HepG2 cells displayed decreasedubiquitination of endogenous AMPKα compared with that of thecontrol, indicating that MKRN1 might be a pivotal E3 ligase forAMPKα (Fig. 2h, i). Based on these results, both AMPKα1 and α2are direct and robust targets of the MKRN1 E3 ubiquitin ligase.

MKRN1 deficiency reduces HFD-induced obesity. The findingthat the metabolic functions of MKRN1 are implicated in reg-ulating AMPK activity and thus in cellular metabolic home-ostasis, regardless of nutritional and pharmacological cues, led usto explore the physiological roles of MKRN1 in MKRN1-nullmice, which do not exhibit apparent developmental deficits orovert phenotypes39. We first compared the body weights of maleMKRN1-null mice to WT mice that were fed standard chow or anHFD to elucidate any potential role of MKRN1 in fat depositionand obesity. No differences in body weight were observed underthe standard chow feeding conditions. On the other hand,MKRN1-null mice fed an HFD exhibited 25–30% lower bodyweights than those of WT mice, without any obvious differencesin food intake (Fig. 3a–c and Supplementary Fig. 4a, b). Weobserved similar results for female MKRN1-null mice comparedwith WT mice under HFD conditions (Supplementary Fig. 5a–d).Little difference was observed between MKRN1-null and WTmice in plasma leptin levels, supporting the finding that there wasno difference in the amount of feeding (Supplementary Fig. 4c).In addition, there were no significant changes in gross faecalenergy, the levels of TG and FFA in faeces or bone length(Supplementary Fig. 4d, e), suggesting that the decreased bodyweights of the MKRN1-null mice were not due to changes innutritional excretion or morphology. Notably, micro-computedtomography (micro-CT) revealed a reduction in the total body fatcontent, including the volume of subcutaneous, visceral andabdominal fat, and an increase in the lean mass/body weight ratio(Fig. 3d, e). Accordingly, decreased sizes of individual adipocytesin epididymal and subcutaneous fat pads were observed inMKRN1-null mice (Fig. 3f, g). Consequently, HFD-inducedhyperlipidaemia was almost completely normalised in MKRN1-null mice, which displayed similar plasma lipid concentrations tothose of WT mice fed a standard chow diet (Fig. 3h). We furthertested whether a lack of MKRN1 induces AMPK activationin vivo, contributing to the metabolic phenotype of MKRN1-nullmice. MKRN1 is widely expressed throughout the body40,41.Intriguingly, MKRN1-null mice exhibited chronic AMPK acti-vation in the liver and white (WAT) and brown (BAT) adiposetissues (Fig. 4g, Supplementary Fig. 6a–c, Supplementary Fig. 10b,and Supplementary Fig. 11c), regardless of nutritional status.However, no changes in AMPK activity were observed amongother metabolic organs, including the hypothalamus, skeletalmuscle and pancreas (Supplementary Fig. 6d–f). In particular, thelack of an apparent change in hypothalamic AMPK activity andits downstream target, pACC, strongly supported the near-equalfood intake observed in WT and MKRN1-null mice, as previously

reported23 (Supplementary Fig. 6d). Notably, there was noobvious difference in the liver mRNA levels of MKRN1 betweenmice fed normal chow and mice fed an HFD, indicating thepossible existence of pathway regulating the interaction betweenMKRN1 and AMPK (Supplementary Fig. 6g). Together, thesedata support the hypothesis that MKRN1 deficiency potentiallyprotects against nutrient overload-induced obesity through thetissue-specific regulation of AMPK.

Hepatic AMPK activation prevents steatosis in MKRN1-knockout mice. The reduction in FFA-induced hepatic steatosisin MKRN1-ablated HepG2 cells and the chronic AMPK activa-tion in the livers of MKRN1-null mice led us to investigate theeffect of MKRN1 deficiency on HFD-induced NAFLD. The lackof MKRN1 dramatically changed the morphology (Fig. 4a), his-tological appearance (Fig. 4b) and weight (Fig. 4c) of the fattyliver associated with an HFD. Notably, size and morphology ofthe livers from MKRN1-null mice fed an HFD were similar tothose of mice maintained on a chow diet. A substantial reductionin the number and volume of enlarged lipid droplets wasobserved inMKRN1-null mice (Fig. 4b, d). Likewise, a decrease inthe hepatic TG content was observed in MKRN1-null liverscompared with that in the WT livers (Fig. 4e). No significantdifference in the F4/80-positive macrophage populations wasobserved, indicating that immune responses did not occur(Fig. 4f). Despite the suppression of AMPK activity under con-ditions of nutrient overload5,10, the lack of MKRN1 caused theremarkable stabilisation of AMPK, which was accompanied byincreases in AMPK and ACC phosphorylation (Fig. 4g).Accordingly, the expression levels of transcription factors such asSREBP-1 and ChREBP were suppressed in MKRN1-null livers(Fig. 4h). Furthermore, in response to the HFD, plasma levels ofaspartate aminotransferase (AST) and alanine aminotransferase(ALT), which are biomarkers employed to diagnose hepaticdamage, were elevated in WT mice but were significantly reducedin MKRN1-null mice (Fig. 4i). There was no obvious difference inglycogen accumulation or the generation of lactate in the liverbetween MKRN1-null and WT mice, suggesting that metabolicpathways related to lipogenesis are most strongly affected byMKRN1 depletion in the liver (Supplementary Fig. 7). Based onthese data, MKRN1 deficiency promotes hepatic AMPK activa-tion, possibly resulting in reduced hepatic lipid accumulation andthe prevention of NAFLD.

Next, AMPK activity was inhibited through adenoviral deliveryof small hairpin RNAs (shRNAs) targeting AMPKα2 todetermine the role of hepatic AMPK activation in the preventionof hepatic steatosis in MKRN1-null mice (Fig. 4j and Supple-mentary Fig. 8). AMPK activation in the MKRN1-null liver wascompletely reversed by AMPKα2 knockdown (SupplementaryFig. 8b). Notably, the substantial reductions in lipid droplets andTG contents observed in the MKRN1-null liver were dramaticallyrestored by hepatic AMPKα2 knockdown (Fig. 4k, l), withoutaffecting the body weights ofMKRN1-null mice. Finally, the levelsof the lipogenesis markers SREBP-1 and ChREBP, which weredecreased in MKRN1-null mice, were restored upon AMPKα2knockdown, corroborating the physiological data (Fig. 4m). Thus,MKRN1 deficiency protects against diet-induced hepatic steatosisin an AMPK-dependent manner.

MKRN1 ablation alters metabolism in the liver and adipocytes.To investigate how cellular processes are influenced by MKRN1ablation at the global level, we performed mRNA-sequencinganalysis of the liver and adipose tissues from MKRN1-null andWT mice. Using mRNA-sequencing data, we identified 2310 (492upregulated and 1879 downregulated) and 3383 (1379

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upregulated and 2121 downregulated) differentially expressedgenes (DEGs) between MKRN1-null and WT mice in the liverand adipose tissues, respectively (Supplementary Data 1).

To examine how metabolic processes are affected by MKRN1ablation, further functional enrichment analyses of the DEGs inthe liver and adipose tissue were carried out. Among differentfunctional categories, the DEGs were found to be most stronglyassociated (41.4% in the liver and 41.5% in the adipose tissue)with metabolism, suggesting that MKRN1 depletion significantlyimpacts metabolic processes in the liver and the adipose tissue(Fig. 5a). Notably, lipid metabolism (41.7% in the liver and 33.9%in the adipose tissue) was one of the processes that was mostinfluenced by MKRN1 ablation, together with carbohydratemetabolism (20.9% in the liver and 24.5% in the adipose tissue)(Fig. 5b). Among cellular processes related to lipid metabolism,lipid anabolism pathways (i.e., lipid and fatty acid biosyntheticprocesses) were significantly (P < 0.05) downregulated in bothMKRN1-null liver and adipose tissues (Fig. 5c–f). In the liver, thegenes involved in the biosynthesis of saturated and unsaturatedfatty acids from acetyl-CoA (Acaca/b, Fasn, Tecr, Hsd17b12,Elovl1/2/5/6/7, Scd1/2 and Acot2) were downregulated, as were

the genes involved in the conversion of glycerol to fatty acids (Gk,Agpat4, Gpam, Lpin2, Plpp2/5, Pnpla3 and Lpl), suggestingsystematic suppression of fatty acid biosynthetic pathways byMKRN1 ablation (Fig. 5e). In adipose tissue, similar down-regulation of fatty acid biosynthetic pathways was observed(Fig. 5f). On the other hand, the genes involved in lipolysis (Acsl3/4/5 and Cpt1b) were downregulated in the liver, but those (Acsl3/6 and Cpt1b) in the same pathway were upregulated in theadipose tissue (Fig. 5e, f). These data suggest that MKRN1ablation results in stricter regulation of fatty acids in the adiposetissue by decreasing lipogenesis and increasing lipolysis withrespect to the regulation of these processes in the liver, by whichboth lipolysis and lipogenesis are decreased.

In addition to lipid metabolism, carbohydrate metabolism wassignificantly influenced by MKRN1 ablation (Fig. 5b). In the liver,the genes involved in glycolysis (Hk1/2, Gpi1, Pfkp, Aldoa, Gapdh,Eno1, Pkm and Pklm) and gluconeogenesis (G6pc and Pck2) weredownregulated (Fig. 5e). In the adipose tissue, however, the genesinvolved in glucose uptake (Slc2a4/Glu4) and glycolysis wereupregulated (Fig. 5f), as were those involved in lipolysis. On theother hand, lactate dehydrogenase was upregulated in the adipose

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Fig. 3 A lack of MKRN1 expression reduces obesity in mice placed on an HFD. Male WT and MK1−/− mice fed a chow diet or an HFD for 16 weeks.a Representative images of male WT and MK1−/− mice fed a chow diet (left) or an HFD (right). b The body weights of male mice on a chow diet (left) oron an HFD (right) were measured every 4 days. c Body weight gain in male mice fed a chow diet or an HFD for 12 weeks (chow, WT n= 10 and MK1−/−

n= 12; HFD, WT n= 16 and MK1−/− n= 18). d, e Fat volume (Vis visceral, SQ subcutaneous, Abd abdominal adipose tissue) and lean mass weight werecalculated (e) through micro-CT imaging (d) of WT and MK1−/− mice on an HFD (n= 5 mice per group). P-value compared with WT. f, g Representativeimages of epididymal fat (left), subcutaneous fat (right) (top, scale bar= 1 cm) and H&E staining (bottom, scale bar= 50 (Epi) or 100 (Sub) µm) (f) andquantitative analysis of the adipocyte area (g) in male WT and MK1−/− mice fed an HFD (n= 5 mice per group). P-value compared with WT. h Plasmaconcentrations of TG and cholesterol in 24 h-fasted male mice fed an HFD (n= 6 mice per group). The images in a, d and f are representative images fromthe respective experiments. Two-tailed Student’s t-test; *P≤ 0.05, **P≤ 0.01, ***P≤ 0.001, n.s. not significant. Mean ± s.d.

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05721-4

6 NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications

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Fig. 4 Effect of MKRN1 deficiency on hepatic AMPK signalling and diet-induced NAFLD. Livers from male WT andMK1−/− mice fed a chow diet or an HFDfor 16 weeks were analysed. a Representative livers from mice on an HFD (upper left; fatty livers of HFD-fed WT mice) or a chow diet (upper right; normallivers of chow-fed WT mice). Scale bar= 1 cm. b H&E staining of livers. Scale bar= left, 250 µm; middle, 100 µm; and right, 25 µm. c Liver weights (n= 9HFD-fed mice, n= 6 chow-fed mice per group). d Representative images of Oil Red O-stained livers (n= 6 mice per group). Scale bar= 100 and 25 µm.e Liver TG contents (WT n= 6 and MK1−/− n= 7). f Representative images of immunohistochemical staining for macrophage antigens (F4/80) in liversections. Scale bar= 100 µm. g Hepatic AMPK signalling in WT or MK1−/− mice. h Relative mRNA levels of genes related to hepatic lipogenesis (WT n= 5and MK1−/− n= 6). i ALT and AST serum levels (WT n= 7 and MK1−/− n= 8). j Schedule of AMPKα2 knockdown. WT and MKRN1-null mice wereinjected with Ad_US (as control) or Ad_shα2 (shRNA targeting AMPKα2) via the tail vein. k–m Hepatic steatosis induced by MKRN1 deficiency wasrescued by the ablation of AMPKα2 using adenovirus. k Representative image of H&E staining. Scale bar= up, 50 µm; middle, 100 µm; and bottom,500 µm. l Plasma TG contents were measured. m Lipogenic enzymes were analysed by quantitative real-time PCR in livers from WT and MK1−/− miceinfected with adenoviruses. The data in c, e, h, i, l and m are presented as the mean ± s.d. Two-tailed Student’s t-test; *P≤ 0.05, **P≤ 0.01, ***P≤ 0.001, n.s.not significant

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NATURE COMMUNICATIONS | (2018) 9:3404 | DOI: 10.1038/s41467-018-05721-4 | www.nature.com/naturecommunications 7

tissue (Ldha), but downregulated (Ldhb) in the liver (Fig. 5e, f).Glucose metabolism is linked to fatty acid metabolism throughacetyl-CoA. Up- and downregulation of glucose utilisation in theadipose tissue and the liver, respectively, reflect an increasedamount of acetyl-CoA and, thus, a larger supply of acetyl-CoA forfatty acid biosynthesis in the adipose tissue than in the liver,which might lead to the upregulation of lipolysis in the adiposetissue (Fig. 5f). Furthermore, the genes involved in BAT

thermogenesis (Ucp1, Clic5 and Ppargc1a) were significantlyupregulated in MKRN1-null adipose tissue (Fig. 5d). mTORsignalling was previously shown to be one of the main targets ofAMPK42,43. Analyses of the mTOR pathway showed that mTORand its upstream (Hras, Mapk3, Pik3r1 and Rheb) and down-stream (Eif4e, Sgk1, Pparg and Srebf1) genes were downregulatedin the liver, while its upstream (Pik3r1/3, Pik3cb and Akt2) anddownstream (Rps6kb2, Eif4e, Prkca/g and Pparg) genes were

Hexadecanoyl-[acp]

Extracellularmatrix

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Glucose

Glucose

Glucose-6P

Fructose-6P

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Glycolysis /Gluconeogenesis

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Gluco-neogenesis

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Fatty acidoxidation

Fatty acidoxidation

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Metabolic processDevelopmental processImmune system processCell proliferationCell migration

Lipid metabolic processCarbohydrate metabolic processNucleobase-containing small-molecule metabolic process Cofactor metabolic process

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24.5%

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15.1%

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Gucose catabolic process

Up-regulatedDown-regulated

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Oxidative phosphorylation

Lipid biosynthetic process

Lipid transport

Lipid storage

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Ppa

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Fatty acid biosynthetic process

dLiver

Liver

Adipose

Adipose

–Log10(P)

ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-05721-4

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downregulated in the adipose tissue (Supplementary Fig. 9).These findings suggest that the activation of AMPK by MKRN1ablation negatively regulates mTOR signalling in the liver and theadipose tissue. Taken together, these data suggest systematiccustomised regulation of fatty acid and glucose metabolism in theliver and the adipose tissue by MKRN1 and AMPK.

MKRN1 deficiency suppresses HFD-induced diabetes. MKRN1depletion promoted AMPK activation in adipose tissue, in addi-tion to hepatocytes (Fig. 4g and Supplementary Fig. 6a–c). A lackof AMPK in adipocytes exacerbated the detrimental effects of anHFD, including NAFLD and insulin resistance, due to reductionsin the metabolic activity of BAT19. In addition, AMPK activity inBAT has been implicated in the regulation of uncoupling protein1 (UCP1) induction during thermogenesis44. Therefore, we pos-tulated that AMPK activation in adipocytes would protect againstobesity-induced BAT dysfunction45–47 and contribute to the anti-obesity effects on MKRN1-null mice. Consistent with the bodyweight results, the morphology of BAT (Supplementary Fig. 10a),UCP1 expression (Supplementary Fig. 10b), EE and oxygenconsumption (VO2) (Supplementary Fig. 10c) did not differbetween different genotypes fed a chow diet. In contrast,MKRN1-null mice fed an HFD showed reduced numbers of lipiddroplets in BAT (Supplementary Fig. 11a, b), along with AMPKstabilisation and activation (Supplementary Fig. 11c) andexpression of thermogenic genes in BAT, such as UCP1 (Sup-plementary Fig. 11c, d). Under HFD feeding conditions, therespiratory exchange ratio of both WT and MKRN1-null micevaried in the range of 0.7–0.8, indicating complete dependence onfatty acid metabolism (Supplementary Fig. 11f). Contrary to ourexpectations, indirect calorimetry measurements performed for2 days showed no significant difference in EE among genotypeswhen the mice were fed an HFD (Supplementary Fig. 11g). Theoverall data show that MKRN1-null mice maintain BAT activityas a result of resistance to weight gain when fed an HFD.

AMPK activation has been implicated in the regulation of BATactivity and hepatic gluconeogenesis, which are closely linked toinsulin resistance7,19. We observed a decrease of rate-limitingenzymes, including glucose-6-phosphatase and phosphoenolpyr-uvate carboxykinase, in hepatic gluconeogenesis (Fig. 5d), and anincrease in the thermogenic function of BAT and WAT inMKRN1-null mice (Fig. 5 and Supplementary Fig. 11). Consistentwith these findings, MKRN1-null mice placed on an HFDdisplayed lower fasting plasma insulin levels (SupplementaryFig. 12a), a decrease in the HFD-induced enlargement ofpancreatic islets (Supplementary Fig. 12b), increased glucoseclearance, as indicated by glucose tolerance testing in both maleand female mice (Supplementary Fig. 12c), and greater insulinsensitivity, as indicated by insulin tolerance testing (Supplemen-tary Fig. 12d). Moreover, MKRN1 deficiency promoted insulin-stimulated AKT phosphorylation, a signature signalling pathway

that reflects insulin sensitivity in the liver (SupplementaryFig. 12e). However, these pathways were not specifically activatedin the skeletal muscle or WAT (Supplementary Fig. 12e).Collectively, AMPK activation alleviates obesity-induced insulinresistance and T2D in MKRN1-null mice.

An acute reduction of hepatic MKRN1 level improves NAFLD.The metabolic consequences of chronic AMPK activationexhibited by MKRN1-null mice led us to investigate whetherhepatic AMPK activation was sufficient to improve NAFLDwithout affecting the activation of AMPK in adipose tissue andwhether the acute reduction of MKRN1 expression would alle-viate the symptoms of hepatic steatosis in obese mice. We gen-erated adenoviruses expressing two independent shRNAstargeting MKRN1 (Ad-shMKRN1 #1 and #2) and injected theseviruses into diet-induced obese mice via the tail vein to answerthese questions (Fig. 6a). Following the delivery of adenovirus tomice, which was confirmed by green fluorescent protein (GFP)co-expression, the adenovirus was predominantly observed in theliver (Fig. 6b). The administration of both Ad-shMKRN1 #1 and#2 successfully ablated MKRN1 expression and led to the acti-vation of hepatic AMPK and ACC phosphorylation (Fig. 6c). Noapparent changes in BAT were observed (Fig. 6d). Notably, whilethere was no effect on the body weight of the mice, hepaticMKRN1 knockdown in obese mice dramatically reversed thegeneration of enlarged lipid droplets and reduced TG levels in theliver (Fig. 6e–g). In addition, the alleviation of hepatic steatosisaccompanied the salutary effects on hyperlipidaemia in Ad-shMKRN1-injected obese mice (Fig. 6k). The decreases inSREBP-1 and ChREBP support the reduction of lipid dropletsand hypolipidaemia observed in the liver upon MKRN1 knock-down (Fig. 6h). On the other hand, the knockdown of MKRN1 inthe liver had no apparent effect on the adipose tissues (Fig. 6i, j).These observations reveal that MKRN1 could be a potentialtherapeutic target for alleviating the symptoms of hepaticsteatosis.

DiscussionThe pharmacological and genetic activation of AMPK is asso-ciated with a wide range of effects on whole-body metabolism,including the suppression of gluconeogenesis and lipogenesis inthe liver, promotion of glucose consumption in the skeletalmuscle and potential functions in FAO and lipolysis in the liverand BAT5,26,48. Thus, AMPK has been suggested as an attractivetarget for the treatment of metabolic disorders. However, exten-ded follow-up studies have presented issues and challengesbecause of the complexities of chronic activation of AMPK andAMPK-independent actions. Here the inhibition of the E3 ubi-quitin ligase MKRN1 was sufficient to chronically activate AMPKin the liver and adipose tissues and subsequently led to systemiceffects by preventing hepatic lipid accumulation and insulin

Fig. 5 Regulation of lipid and glucose metabolism by MKRN1 and AMPK. a, b Relative proportions of DEGs in MKRN1-null liver and adipose tissuesaccording to their associated GOBPs. The GOBP terms at level 1 (a) and levels 2–4 (b) were used for general cellular processes and metabolic processes,respectively. c Cellular processes related to lipid and carbohydrate metabolism enriched by the up- and downregulated genes identified in MKRN1-null liveror adipose tissue. The bars represent −log10 (P-value), where the P-value is the significance of the processes being enriched by the up- or downregulatedgenes. d Heat maps showing the changes in the expression of DEGs involved in fatty acid biosynthesis and β-oxidation, gluconeogenesis andthermogenesis. The colour bar shows the gradient of the log2 fold changes of mRNA expression levels in MKRN1-depleted samples relative to those in WTsamples. e, f Network models describing alterations of metabolic reactions regulated by DEGs in MKRN1-null livers (e) and adipose tissue (f). Arrowsdenote metabolic reactions, and dotted lines denote the transportation of molecules or regulation involving intermediate regulators between the linkedmolecules. Node colours represent up- (red) or downregulation (green) in MKRN1-null livers or adipose tissue. The colour bar represents the gradient ofthe log2 fold changes of mRNA expression levels induced by MKRN1 ablation relative to those in WT

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resistance and promoting anti-obesity effects on diet-inducedobese mice. Our findings highlight a therapeutically exploitableaxis regulating AMPK, without the ramifications of activation incentral circuits.

Substantial evidence supporting the beneficial effects of AMPKactivation on peripheral tissues has rapidly emerged. Chronictreatment with direct AMPK activators, such as A76966217, PF-73949 or AICA [5-aminoimidazole-4-carboxamide] riboside18,restrains hepatic lipid accumulation and promotes glucose dis-posal. In a more recent study, genetic activation of hepatic AMPKthrough the γ1 mutation (γ1D316A) compellingly preventedhepatic TG accumulation in mice placed on a high-fructosediet16. AMPK has also been implicated in BAT functions andenergy metabolism44,50, suggesting its possible therapeutic use forobesity. Recently, Mottillo et al.19 reported a role for adipocyteAMPK in BAT thermogenesis, with implications for hepaticsteatosis and insulin resistance. However, in this study, diet-induced obesity was not significantly affected by the loss ofAMPK. Because mice placed on a long-term HFD show adecrease in adipose AMPK activity5,10, the additional effect ofAMPK deficiency on obesity might not be reflected in thesemodels. Supporting this hypothesis, greater weight gain after a

relatively short-term HFD challenge has been observed in theadipose tissue of AMPK-null mice19. The MKRN1-null mousedisplays liver- and adipose tissue-specific AMPK activation. Thus,hepatic AMPK activation induced by MKRN1 depletion protectsthe liver from lipid accumulation, while simultaneously sup-pressing the expression of gluconeogenic genes.

Functional enrichment and network analyses revealed thedifferential regulation of AMPK, mTOR and fatty acid and glu-cose metabolism between the liver and the adipose tissue.Although we showed that AMPKs were regulated at the proteinlevel by MKRN1, the mRNA expression levels of Prkaa2/AMPKα2, Prkab2/AMPKβ2 and Prkag3/AMPKγ3 were increasedin adipose tissue by MKRN1 ablation but showed no change inthe liver, suggesting that there are additional metabolic needs tobe accommodated by the increases of AMPKs, even at the mRNAlevel in adipose tissue (Supplementary Fig. 9a, b). In mTORsignalling, the MAPK pathway (Hras, Mapk3, Pik3r1 and Rheb)and its upstream and downstream factors (Eif4e, Sgk1, Pparg andSrebf1) were predominantly downregulated in the liver, while thePI3K-AKT pathway (Pik3r1/3, Pik3cb and Akt2) and its down-stream factors (Rps6kb2, Eif4e, Prkca/g and Pparg) were pre-dominantly downregulated in the adipose tissue (Supplementary

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Fig. 6 Ablation of hepatic MKRN1 improves hepatic steatosis in diet-induced obese mice. a Male B6 mice (6 weeks old) were fed an HFD for 9 weeks andthen injected with either PBS or adenoviruses expressing GFP via the tail vein (Ad_control, Ad_shMK1 #1 and #2 (shRNA targeting MKRN1)). After 1 weekof continuous HFD feeding, the mice were sacrificed and analysed. b Immunoblot analysis of GFP expression in extracts from the indicated tissues (Subsubcutaneous fat, Epi epididymal fat) of mice infected with adenovirus (n= 2). c, d Liver (e) and BAT (d) lysates from adenovirus-injected mice wereanalysed by immunoblotting as indicated. e Body weights of male mice fed with an HFD were measured in every 2 days for 8 days (n= 5 mice per group).f Representative H&E staining of liver sections. Scale bar= 50, 100 and 500 µm. g Liver TG levels were measured. h Lipogenic enzymes were analysed viaquantitative real-time PCR (n= 5 mice per group). i Representative H&E staining of epididymal fat (top) and subcutaneous fat (bottom) sections. Scalebar= 500 µm. j The weights of fat tissues were recorded following sacrifice. k Liver TG levels (n= 5 mice per group). Plasma lipid (TG, cholesterol andFFA) concentrations in 24-h-fasted mice (n= 5 mice per group). The data are presented as the mean ± s.d. Two-tailed Student’s t-test; *P≤ 0.05,**P≤ 0.01, ***P≤ 0.001.

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Fig. 9a, b). Although Pparα is one of the major transcriptionfactors involved in lipid metabolism, there was no apparentchange in the expression of Pparα in the liver or adipose tissue.We cannot, however, exclude the possibility that MKRN1 reg-ulates Pparα at the post-translational level, since Pparγ is knownto be a target of MKRN136. Further studies are required toaddress this issue in the future. Although genes related to lipo-genesis was consistently downregulated in both the liver and theadipose tissue, the catabolism of fatty acids and glucose wasupregulated in the adipose tissue but downregulated in the liver,indicating the differential regulation of metabolic pathways inMKRN1-null mice (Fig. 5e, f). Importantly, further experimentsincluding direct measurements of the lipid components in theliver should be carried out to reach explicit conclusions about thereduction of actual biochemical outcomes derived from com-prehensive changes of the lipogenic genes. Of note most of thephenotypes observed in the MKRN1-null mouse could also bedriven by AMPK-mediated phosphorylation of ACC, whichsuppresses its function. Thus, we cannot exclude the possibilitythat this process might have considerable negative effects on theaccumulation of lipids in MKRN1-null mice, in addition to thedownregulation of lipogenic gene expression. Taken together, thedifferential regulation of the above processes by MKRN1 might beascribed to additional metabolic needs arising from the increaseduptake and utilisation of glucose in adipose tissue.

Collectively, our findings illuminate a previously undescribedpost-translation mechanism in which AMPK activity is regulatedby E3 ubiquitin ligase and provides an attractive therapeuticstrategy for the treatment of obesity and its related comorbidities.Because MKRN1 is able to degrade both of α subunits, a com-petitive antagonist capable of interfering with the interactionsbetween AMPKα and MKRN1 or an enzyme inhibitor targetingubiquitin ligase activity may lead to potent AMPK activation inan organ-specific manner. This strategy may represent an effec-tive means of ameliorating diet-induced obesity and insulinresistance by exploiting not only hepatic AMPK activation and itssubsequent contributions to de novo lipogenesis but also adiposeAMPK activation, leading to an increase in the energy-burningcapacity of BAT.

MethodsMice. MKRN1-null (MKRN1−/−) mice were obtained from T. A. Gray (DavidAxelrod Institute, USA)39 and were further backcrossed with C57BL/6 mice untilN10. MKRN1-null mice and their WT littermates (MKRN1+/+) were bred fromMKRN1+/− mice and were randomly grouped for all the experiments. The primersemployed for MKRN1 genotyping were 5′-TGA CAGGCCACAGTGAACTC-3′,5′- GGCAAAGCTGCTTCTTTGTCTCC-3′ and 5′-CAA AGGGAAAGGGTAAAGTGGTAGGG-3′, which amplified an approximately 1000-bp DNA fragment inMKRN1−/− mice and an 820-bp DNA fragment in MKRN1+/+ mice. For HFD-induced obesity experiments, male and female MKRN1+/+ and MKRN1−/− micewere placed on either an HFD (60% calories from fat; D12492, Research DIET Inc.,NJ, USA) or a standard chow diet (17% calories from fat; 38057, Cargill AgriPurina Inc., Republic of Korea) for 16 weeks starting at 6–8 weeks of age. Foradenovirus experiments, male C57BL/6 mice (6 weeks old) were placed in indi-vidual cages, treated with an HFD for 9 weeks and injected with adenovirus via thetail vein. After 1 week of continuous HFD feeding, the mice were sacrificed. All themice were maintained under temperature-controlled and light-controlled (standard12-h light–dark cycles) conditions and provided with food and water ad libitum.All the procedures were reviewed and approved by the Institutional Animal Careand Use Committees (IACUC) of the Laboratory Animal Research Center atYonsei University (IACUC-A-201506-311-01).

Cell lines and transfection. MKRN1+/− mice with FBV/NJ × C57BL/6J back-ground were backcrossed with the B6 background mice until N6. MKRN1+/− micewere mated to produce MEFs with or without MKRN1. To acquire MEFs of 13.5embryo day, embryos washed with phosphate-buffered saline (PBS; Welgene) wereminced followed by incubation with the treatment of 3 ml trypsin/EDTA (Gibco)at 37 °C for 15 min. The MEFs were grown in 20 ml Dulbecco’s modified Eaglemedium (DMEM) containing 10% foetal bovine serum (FBS; GIBCO) for 4–8 hfollowed by the change of media with DMEM containing 10% FBS. The confluentMEFs were then subcultured at 1:3 ratio33. HEK293T (a human embryonic kidney

cell line) and HepG2 (a human hepatocellular carcinoma cell line) cells wereacquired from the American Type Culture Collection (ATCC, Manassas, VA). Thephenotypes of these cell lines were authenticated by ATCC on a regular basis. Allthe cell lines employed here were negative for mycoplasma when detected using ane-Myco plus Mycoplasma PCR Detection Kit (Intron, Gyeonggi-do, Republic ofKorea) and were protected from mycoplasma infection by treatment with Plas-mocinTM (InvivoGen, CA, USA). Lipofectamine 2000 (Invitrogen, Carlsbad, CA,USA), PEI (Sigma-Aldrich, St. Louis, MO, USA) or Lipofectamine RNAiMAX(Invitrogen) were employed to transfect plasmid DNA or siRNA.

Reagents. Phospho-AMPKα (1:1000, Thr 172) (2535), AMPKα (1:1000, 2603),AMPKα1 (1:1000, 2795), AMPKα2 (1:1000, 2757), AMPKβ1 (1:1000, 4178),AMPKγ1 (1:1000, 4187), phospho-ACC (1:1000, 3661), ACC (1:1000, 3676),phospho-AKT (1:1000, Ser 473) (9271) and AKT1 (1:2000, 2967) antibodies wereacquired from Cell Signaling Technology (Danvers, MA, USA). The UCP1 anti-body (1:1000, ab10983) and mouse AMPKα1 (1:1000, ab3759) were procured fromAbcam (Cambridge, MA, USA). Mouse AMPKα2 (1:1000, AF2850) was purchasedfrom R&D systems Inc. (MN, USA). FLAG (1:3000, F3165 and F7425) and β-actin(1:10000, A5316) antibodies were procured from Sigma-Aldrich. The MKRN1antibody (1:3000, A300-990A) was procured from Bethyl Laboratories. The mono-and polyubiquitin chain antibodies (1:1000, FK2, Biomol, PW0150) were pur-chased from Enzo Life Sciences. The HA antibody (1:3000, 12013819001) wasobtained from Roche. GAPDH (1:5000, sc-25778), GFP (1:5000, sc-8334) andHA (hemagglutinin) (1:3000, sc-7392 and sc-805) antibodies were procured fromSanta Cruz Biotechnology (Dallas, TX, USA). MG132 (M-1157) was purchasedfrom A.G. Scientific (CA, USA). CHX (C4859) was purchased from Sigma-Aldrich.

Indirect calorimetry. Metabolic performance (energy intake and EE) was studiedusing a PHENOMASTER automated combined indirect calorimetry system (TSESystem GmBH, Bad Homburg, Germany). For the experiment, the mice firstacclimated for 48 h in a metabolic chamber provided with food and water weresubsequently evaluated for 3 days for oxygen consumption (VO2), carbon dioxideproduction (VCO2) and food consumption. The temperature for these studies waskept at 22 °C, with a 12-h-light/dark cycle. Standard in-house software was used forEE.

Micro-positron emission tomography/-CT image acquisition and analysis.After 6 h of fasting, each mouse was intravenously injected with 200 µCi of F-18fluorodeoxyglucose via the tail vein and then maintained in a box at 4 °C for 1 h.Each mouse was anaesthetised during the scan with isoflurane (2.5% flow rate). Theanimals were placed in a prone position on a standard mouse bed. The limbs of themice were positioned laterally from the body to obtain uniform CT images. Whole-body CT images were obtained employing a micro-positron emission tomography(PET)/-CT scanner (nanoScan PET/CT, Mediso Inc., Budapest, Hungary). The X-ray source was fixed at 200 µA and 45 kVp with 0.5 mm for CT image acquisition.The CT images were recreated through cone beam reconstruction using a Sheppfilter with a cutoff at the Nyquist frequency and a binning factor of 4, whichresulted in an image matrix of 480 × 480 × 632 with a voxel size of 125 µm. ThePET images were recreated using the Tear-Tomo Real 3D PET engine (nanoScanPET/CT, Mediso Inc.). The weight of each mouse was determined before takingimage of lean body mass (LBM). The overall body image, including total andvisceral adipose tissue volume was measured as reported previously51. The LBM isdefined as the weight of the body without the weight of fat. Here LBM was analysedaccording to the following equation, where the density of fat was 0.9 g cm−3.Detailed methods are described in a previous report51.

LBM ¼ fbody weight gð Þ � ðtotal adipose tissue volume ðcm3Þ ´ 0:9 ðg cm�3ÞÞgð1Þ

Glucose tolerance test (GTT), insulin tolerance test (ITT) and insulin sti-mulation. The mice were treated with an HFD for 16 weeks and tested after anovernight (16-h) fast. The glucose tolerance test (GTT) was performed via oralglucose (G8769, Sigma-Aldrich) administration at a dose of 1 g kg−1 after anovernight fast. The blood glucose levels were analysed at 0, 15, 30, 60 and 120 minpost-injection using GlucoDr. Plus (AGM-3000, Allmedicus). For insulin tolerancetest assays insulin (I9278, Sigma-Aldrich) stimulation was accomplished viaintraperitoneal insulin injection at a dose of 0.75 U kg−1 (final volume 125 μl) afteran overnight fast. Glucose levels were measured at 0, 15, 30, 60, 90 and 150 minafter injection. Protein samples of skeletal muscle, liver and epididymal fat padswere collected 10 min after injection for western blot analysis.

Faecal energy content. Faeces were collected and dried in a drying oven until thesamples were completely free of water. The energy contents of 0.5–1 g of driedsamples were measured using a bomb calorimeter (Parr6400 Calorimeter, IL,USA). TG and fatty acid contents were measured using enzymatic methods(AU680, Beckman Coulter, USA).

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Metabolomic analysis. Metabolomic analysis was performed employing the BasicScan package from Human Metabolome Technologies (HMT) Inc. (Tsuruoka,Japan) and capillary electrophoresis–time-of-flight mass spectrometry (CE-TOFMS) as described previously52. Metabolites were extracted from MKRN1−/−

MEFs and the MEFs of WT littermates as the manufacturer suggested (E-130637;HMT). Briefly, the cells were washed twice using a 5% (w/w) mannitol solution,added to methanol to extract metabolites and treated with internal standardssolution 1 (HMT). The extracted solution was centrifuged for 5 min at 2300 × g and4 °C. The proteins of the upper aqueous layer were removed using a Millipore 5-kDa cutoff filter. The filtrate was subsequently lyophilised and dissolved in 50 µl ofMilli-Q water and analysed via CE-TOFMS. Automatic integration software(MasterHands ver. 2.16.0.15 developed at Keio University) was employed to pro-cess peaks from CE-TOFMS analysis and to acquire information of m/z, migrationtime (MT) and a relative peak area. The HMT metabolite database based on thepeak MTs andm/z values established using TOFMS were employed to assign all thetarget metabolite.

Glucose consumption measurements. HepG2 cells and MEFs were cultured infresh high-glucose (4500 mg l−1) medium for 24 or 48 h at 24 h after siRNAtransfection. Live cells were treated with 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-D-glucose for 30 min (20 μM), and glucose uptake was measuredby quantifying fluorescence using flow cytometry.

FFA-induced steatosis. For the FFA stock solution, oleic acid (OA, 100 mM) wasconjugated with 1% (w/v) bovine serum albumin (BSA). The required volume ofthe FFA stock was added to the medium to obtain a 0.5 or 1 mM concentration offatty acids for experiments. HepG2 cells were treated with OA complexed with BSAor fatty acid-free BSA (as the control) for 24 h and then stained with ORO (Oil RedO staining) . Images were procured using aNikon eclipse 80i light microscope(Nikon, Tokyo, Japan) and analysed with Nikon NIS-Elements F 3.2 software.Cellular TGs were also extracted from FFA-treated HepG2 cells and measured.

TG measurement. For TG measurement, 0.2-g liver samples from maleMKRN1+/+

andMKRN1−/− mice or FFA-treated HepG2 cells were homogenised in 5% NP-40 inwater, and the samples were then heated to 95 °C and cooled to room temperaturetwice. TG contents were analysed using the Triglyceride Quantification ColorimetricKit (Bio Vision, CA, USA). TG levels were calculated from measurements of theabsorbance at 570 nM.

FAO measurement. For FAO measurement in HepG2 cells, the cells were platedin triplicate in 96-well plates at a density 6 × 104 cells per well. The culture mediumwas changed to glucose deprivation medium (1 mM of glucose, 1 mM of L-gluta-mine, 0.5 mM of L-carnitine, 1% FBS, penicillin/streptomycin solution, pH 7.4)overnight, followed by replacement of the medium with FA/FA-free measurementmedium (ab217602) with or without carbonyl cyanide p-trifluoro-methox-yphenylhydrazone (FCCP) in the presence of an O2 consumption reagent(ab197243). Measurements were performed using a fluorescent plate reader(GloMAX-Discover, Promega). For FAO measurement in MEFs, an extracellularflux (XF24) analyser (Seahorse Bioscience) was used to measure oxygen con-sumption rates (OCR). The MEFs were plated at a density of 6 × 104 cells per wellin triplicate in custom-designed 24-well plates (Cat. No. 103010-100). OCR wasevaluated over time with or without the addition of oligomycin (2.5 μM), followedby the addition of FCCP (1.6 µM), and rotenone/antimycin-A (0.5 μM) with orwithout palmitate-conjugated BSA (Cat. No. 102720-100).

Lactate measurement. The L-Lactate Assay Kit II (1200051002, Eton Bioscience)was employed to quantitate the amount of lactate.

Serum biochemistry. Fasting plasma insulin levels were measured in mice fastedfor 16 h using the Mouse Metabolic Hormone Magnetic Bead Panel (MetabolismMultiplex Assay, MMHMAG-44K, Millipore). Plasma TG, cholesterol and FFAconcentrations were determined using enzymatic methods (Roche Diagnostics,Mannheim, Germany) with a Hitachi 7600 clinical chemistry analyser (HitachiLtd., Tokyo, Japan) in overnight-fasted mice. Serum AST and ALT levels weremeasured via ultraviolet methods (Roche Diagnostics) with a Hitachi 7600 ana-lyser, according to the recommended protocols from the International Federationof Clinical Chemistry.

Histology and immunohistochemistry. Tissues fixed in 10% buffered formalinwere embedded in paraffin followed by staining with haematoxylin and eosin orperiodic acid Schiff for glycogen detection. Images were obtained using a LeicaDM2500 microscope (Leica Microsystems, IL, USA) and analysed with Leica LASV4.7 software. For immunohistochemistry, the ImmPRESS Peroxidase Polymer kit(Vector Laboratories, Burlingame, CA, USA) was employed. Briefly, the slidesblocked with 2.5% horse serum were incubated overnight at 4 °C with the F4/80antibody (1:200; sc-377009; Santa Cruz Biotechnology) followed by washing. Slideswere then incubated for 30 min with an appropriate peroxidase polymer-linkedsecondary antibody. For colorimetric detection the slides were stained with

ImmPact DAB substrate (SK-4105, Vector Laboratories) followed by counter-staining with Meyer’s haematoxylin for 10 s. For Oil Red O staining, formalin-fixedtissues were equilibrated in 30% sucrose, embedded in OCT compound and snap-frozen in liquid nitrogen. Frozen sections were stained with Oil Red O (Sigma-Aldrich). Images were obtained using a Nikon eclipse 80i microscope and analysedwith Nikon NIS-Elements F 3.2 software. The freehand area selection tool inImageJ were employed to determine adipocyte size (mean area of white adiposecells, minimum n= 3 samples per group and n= 3 fields per section).

Ubiquitination assay. The ubiquitination assay was conducted under denaturingconditions to detect ubiquitinated endogenous and overexpressed AMPKα proteins.Briefly, to detect proteins ubiquitinated with HA-conjugated ubiquitin or endogen-ously ubiquitinated proteins under denaturing conditions, cells were lysed by boilingfor 10min in PBS containing 1% SDS and 5mM NEM (N-ethylmaleimide). Thelysates were immunoprecipitated in lysis buffer (a final concentration of 0.1% SDS).For immunoblotting, proteins were transferred to polyvinylidene difluoride mem-branes and denatured using 6M guanidine-HCl containing 20mM Tris-HCl (pH7.5), 5 mM mercaptoethanol and 1mM phenylmethyl sulphonyl fluoride for 30minat 4 °C. Ubiquitinated proteins were identified by horseradish peroxidase-conjugatedanti-Ub antibodies (FK2, PW0150, Biomol)35. For in vitro ubiquitination assays, a0.5-µg sample of bacterially purified recombinant proteins was incubated with 100 ngof E1 (UBE1, E-305, Boston Biochem, Cambridge, MA, USA), 250 ng of E2 (UbcH5c,E2-627, Boston Biochem) and 5 µg of ubiquitin (U-100H, Boston Biochem) in 20 µl ofreaction buffer (40mM of Tris, 50mM of NaCl, 5mM of MgCl2, 2 mM of ATP and1mM of dithiothreitol, pH 7.6) as indicated. The reaction was stopped after 3 h at37 °C by the addition of SDS sample buffer and boiling.

Protein purification and immunoprecipitation. Glutathione S-transferase (GST)-tagged recombinant MKRN1 and the AMPKα1, α2, β1 and γ1 proteins werepurified from bacteria using GST Sepharose beads according to the manufacturer’sprotocol (GE Healthcare).

Immunoprecipitation assay: The cells were lysed in lysis buffer (50 mM of Tris-HCl (pH 7.5), 150 mM of NaCl, 0.5% Triton X-100 and 1 mM of EDTA)containing a protease inhibitor cocktail. The cell lysates were then incubated with1 µg of antibody with rotation, followed by incubation with 25 µl of protein Gagarose (Invitrogen), and the precipitated proteins were eluted in SDS samplebuffer under boiling conditions53.

Recombinant adenoviruses. The adenoviral clone pAV-U6-GFP (control vector,Ad_control) and an adenoviral clone containing an shRNA for murine MKRN1(Ad_shMKRN1) were purchased from ViGene Biosciences Inc. (Rockville, MD,USA). The adenoviruses were propagated in HEK293 cells according to the manu-facturer’s protocol. Adenoviruses expressing a nonspecific RNAi control (Ad_US) andshRNA for murine AMPKα2 (Ad_shα2) were generated via homologous recombi-nation between the adenovirus backbone vector pAD-Easy and the linearised transfervector pADTrack. For animal experiments, the viruses were purified in a CsCl gra-dient, dialysed against PBS buffer containing 10% glycerol and stored at −80 °C. Themice were tail vein-injected with the recombinant adenovirus (0.5 × 109 pfu per mice).Plasma ALT and AST levels were not significantly different between the mice in thesame experimental groups that were injected with various adenoviruses. The shRNAsequences were as follows: Ad_shMKRN1 #1: 5′-CCGGGCGAGATGTTGCTTATGCTTTCTCGAGAAAGCATAAGCAACATCTCGC TTTTTG-3′; Ad_shMKRN1#2: 5′-CCGGGAGTGGGACTTGTTTCACGATCTCGAGATC GTGAAACAAGTCCCACTCTTTTTG-3′; and Ad_shα2: 5′-CCATAAAGTGGCAGTTAAG ATCTTAAA-3′.

Statistical analysis. All statistical tests were two sided, and the values areexpressed as the means with 95% confidence intervals. The normality of the dis-tribution was assessed with the Kolmogorov–Smirnov method. Statistically sig-nificant differences between any two groups were examined using unpaired two-tailed t-tests or Mann-Whitney U tests, depending on normality. Data involvingmore than two groups were assessed via analysis of variance using GraphPad Prismsoftware (version 7; GraphPad Software Inc., La Jolla, CA). Analysis of covariance(ANCOVA) was employed to compare genotypes, with adjustment for the con-founding effect of mouse body weight for EE. The EE ANCOVA method used inthis work was provided by the NIDDK Mouse Metabolic Phenotyping Centers(MMPC, www.mmpc.org) on their Energy Expenditure Analysis page (http://www.mmpc.org/shared/regression.aspx) and supported by grants DK076169 andDK115255. A value of P < 0.05 was considered statistically significant.

mRNA-sequencing and data analysis. Total RNAs were obtained from the liverand adipose tissues of MKRN1-null and WT mice. Poly(A) mRNA isolation fromtotal RNA and fragmentation was performed using the Illumina TruSeq RNASample Prep Kit v2, according to the manufacturer’s instructions. Reverse tran-scription of RNA fragments was performed using Superscript II reverse tran-scriptase (Life Technologies). The adaptor-ligated libraries were sequenced on theIllumina HiSeq 4000 platform (Marcrogen, Korea). mRNA-sequencing analysiswas performed with two independent replicates from each condition. Adaptersequences (TruSeq universal and indexed adapters) were removed from the

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resulting read sequences for each sample using cutadapter software54. Then, theremaining reads were aligned to the mouse GRCh38 genome usingTophat2 software (version 2.1.1) with the default parameters55. After alignment, wecomputed RPKM (reads per kilobase of target per million mapped reads) for thegene features (GTF file of GRCm38.91) using Cufflinks56.

Identification of DEGs. The numbers of reads counted by HTseq were convertedto log2 read counts after adding one to the read counts. The log2 read counts for thesamples from each condition were then normalised via the trimmed mean of M-values normalisation in the edgeR package57. To identify DEGs, we performedintegrative statistical hypothesis tests as previously described58. Briefly, for eachgene, we calculated a T-statistic value using Student’s t-test as well as the log2 foldchange in the comparison of MKRN1-null versus WT. We then estimated theempirical distributions of T-statistic values and the log2-fold-change for the nullhypothesis (i.e., the genes are not differentially expressed) by performing all pos-sible combinations of random permutations of the four samples. Using the esti-mated empirical distributions, we computed adjusted P-values for the two tests foreach gene and then combined these P-values using Stouffer’s method59. Finally, weidentified DEGs as those genes showing combined P-values ≤ 0.05 and absolutelog2 fold changes ≥ 0.58 (1.5-fold). To identify the cellular processes represented bythe DEGs, we performed enrichment analysis of gene ontology biological processes(GOBPs) using DAVID software60 and selected the GOBPs with P-values < 0.05 asthe processes enriched by the DEGs.

Reconstruction of a network model. To construct a network model for the DEGs,we first selected a subset of the DEGs involved in the GOBPs related to mTORsignalling (Supplementary Fig. 9a, b) and glucose and fatty acid metabolism (Fig. 5c).We then collected the protein–protein interactions for these genes from five inter-actome databases: Biomolecular Interaction Network Database, Human ProteinReference Database, Biological General Repository for Interaction Datasets, MolecularINTeraction Database and Search Tool for Recurring Instances of NeighbouringGenes61–65. The initial network model was built with the target genes and theirinteractors using Cytoscape66. We then arranged the nodes according to their asso-ciated GOBPs and Kyoto Encyclopedia of Genes and Genomes pathways67 related toglucose and fatty acid metabolism, such that the nodes involved in the same GOBPsand pathways were located close to each other.

Data availability. Uncropped gels and blots are available in the SupplementaryInformation (Supplementary Figs. 13–22).

RNA-seq data generated for this study have been deposited in the GeneExpression Omnibus database under accession number GSE115012.

Received: 1 September 2017 Accepted: 19 July 2018

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AcknowledgementsWe thank I.Y.K. and J.K.S. for the productive discussions and K.-J.O., S.-H.K. and J.-W.K. for providing technical support. We specifically thank Deyu Feng (NorthwesternUniversity) and T. A. Gray (David Axelrod Institute) for their support in providingMKRN1-null mice. This research was supported by grants from the National R&DProgram for Cancer Control, Ministry of Health & Welfare, Republic of Korea (NCC-1420300) and the Ministry of Science, ICT and Future Planning (NRF-2015R1A3A2066581). Additionally, this research was partially supported by the BK21Plus project of the National Research Foundation of Korea Grant) and by grants fromthe Korea Mouse Phenotyping Project (2013M3A9D5072550 and 2013M3A9D507256) and the Institute for Basic Science (IBS-R013-A1) of the Ministry of Science,ICT and Future Planning through the National Research Foundation of Korea.

Author contributionsJ.S. conceived and supervised the experiments. M.-S.L. designed and conducted theexperiments. H.-J.H., J.-H.K., S.S., I.Y.K., S.G.Y. and J.-W.P. performed the in vivoexperiments. C.-S.L., S.Y.H., S.E.K., M.J. and A.K. performed the biochemistry experi-ments. H.-Y.L. generated the micro-CT data; K.-J.O. helped generate adenoviruses. S.C.and D.H. analysed mRNA-sequencing data. K.-H.B., S.-H.K., J.-W.K. Y.-H.L and J.K.S.interpreted the significance of the study; M.-S.L. and J.S. analysed and organised the dataand wrote the manuscript.

Additional informationSupplementary Information accompanies this paper at https://doi.org/10.1038/s41467-018-05721-4.

Competing interests: The authors declare no competing interests.

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