MCB Accepted Manuscript Posted Online 26 January 2015 Mol. Cell. Biol. doi:10.1128/MCB.01404-14 Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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(Article, Molecular and Cellular Biology)

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Lysine-specific demethylase LSD2 suppresses lipid influx and

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metabolism in hepatic cells

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Katsuya Nagaoka1,2, Shinjiro Hino1*, Akihisa Sakamoto1, Kotaro Anan1, Ryuta Takase1,

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Takashi Umehara3, Shigeyuki Yokoyama3, Yutaka Sasaki2 & Mitsuyoshi Nakao1,4*

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Department of Medical Cell Biology, Institute of Molecular Embryology and Genetics, 2 Department of Gastroenterology and Hepatology, Graduate School of Medical

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Sciences, Kumamoto University, Kumamoto, 860-0811, Japan, RIKEN Systems and Structural Biology Center, Yokohama, Japan, 4 Core Research for Evolutional Science and Technology (CREST), Japan Science and

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Technology Agency, Tokyo, Japan.

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*Address correspondence to:

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Mitsuyoshi Nakao M.D., Ph.D. Shinjiro Hino Ph.D.

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Department of Medical Cell Biology, Institute of Molecular Embryology and Genetics, Kumamoto University 2-2-1 Honjo, chuo-ku, Kumamoto 860-0811, Japan. Phone: +81-96-373-6800; Fax: +81-96-373-6804 E-mail: [email protected] or [email protected]

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ABSTRACT

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Cells link environmental fluctuations such as nutrition to metabolic remodeling.

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Epigenetic factors are thought to be involved in such cellular process, but the molecular

29

basis remains unclear. Here we report that the lysine-specific demethylase LSD2

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suppresses the flux and metabolism of lipids to maintain the energy balance in hepatic

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cells. Using transcriptome and chromatin immunoprecipitation-sequencing analyses, we

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reveal that LSD2 represses the genes involved in lipid influx and metabolism, through

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demethylation of histone H3K4. Selective recruitment of LSD2 at lipid metabolism

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gene loci was mediated in part by a stress-responsive transcription factor c-Jun.

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Intriguingly, LSD2 depletion increased the intracellular levels of many lipid metabolites,

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which was accompanied by an increased susceptibility to toxic cell damage in response

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to fatty acid exposure. Our data demonstrate that LSD2 maintains metabolic plasticity

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under fluctuating environment in hepatocytes, by mediating the crosstalk between the

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epigenome and metabolism.

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INTRODUCTION

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Organisms and cells must adjust their energy strategy to fluctuating nutrient

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availability and other environmental conditions. Epigenetic mechanisms have been

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implicated in the phenotypic plasticity in response to environmental changes, as well as

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in consistent execution of the developmental program (1). It has been shown that

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nutrients and dietary composition potently influence epigenetic marks including DNA

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methylation and histone methylation/acetylation in both humans and animal models (2).

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Because chromatin-modifying enzymes utilize nutrient-derived metabolites as

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substrates and coenzymes, epigenome formation is, by nature, influenced by nutritional

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and metabolic conditions (3-6). Lysine-specific demethylase 1 and 2 (LSD1 and LSD2),

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also respectively known as KDM1A and KDM1B, comprise the flavin-dependent amine

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oxidase family of histone demethylases (7). These enzymes require flavin adenine

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dinucleotide (FAD) as a coenzyme for the removal of methyl groups from the lysine

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residue of histone H3 and other proteins (8, 9). FAD is a vitamin B2-derived metabolite

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that serves as a redox cofactor in key metabolic processes such as fatty acid oxidation

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and succinate dehydrogenation in the tricarboxylic acid cycle (10). Thus, the cellular

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metabolic state may influence the demethylase activity of these proteins. Indeed, we and

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others have previously demonstrated that LSD1 controls energy metabolism genes in

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response to extracellular conditions (11, 12), suggesting that FAD-dependent epigenetic

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factors may link environmental information to metabolic programming. LSD2 was

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identified as a second flavin-dependent histone demethylase that targets methylated

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lysines 4 and 9 of histone H3 (H3K4 and H3K9, respectively) (8, 13-15). Although

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LSD2 has been implicated in the establishment of maternal genomic imprinting in

3

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oocytes (16), little is known about its biological functions, particularly in relation to

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metabolic control.

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In the liver, hepatocytes play a crucial role in the homeostatic control of lipid

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metabolism (17). Hepatocytes incorporate adipose- and diet-derived fatty acids, which

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are either stored by themselves as neutral lipids or redistributed to other tissues in the

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form of very low-density lipoproteins (18). When hepatocytes are exposed to an

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intolerably high amount of fatty acids, for example due to over-feeding, excessive fatty

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acids and their toxic metabolites accumulate in the cells, often leading to the lipotoxic

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liver injury known as nonalcoholic fatty liver disease (NAFLD) (19, 20). Epigenetic

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alterations in the liver have been linked to insulin resistance and NAFLD in humans

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(21), and diet-induced steatosis in mice (22). A recent report by Ahrens et al. examined

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the DNA methylation profiles of liver biopsies from patients with NAFLD and

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non-alcoholic steatohepatitis (NASH), an advanced form of NAFLD (23). Of particular

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note, some disease-state dependent methylation patterns could be reversed after

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improvement of the disease condition by bariatric surgery (23), suggesting that hepatic

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lipid homeostasis is associated with epigenetic plasticity. However, we still lack

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knowledge of whether a specific epigenetic factor could be involved in the homeostatic

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control of hepatic lipid metabolism.

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In the present study, we provide direct evidence that LSD2 plays an essential

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role in the homeostatic control of lipid metabolism in hepatocytes. Our integrative

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investigations

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immunoprecipitation-sequencing (ChIP-seq) analyses reveal that LSD2 suppresses lipid

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transport and metabolism by repressing key metabolic genes through the regulation of

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methylated H3K4 (H3K4me). We further show that LSD2 depletion leads to enhanced

using

the

transcriptome,

4

metabolome

and

chromatin

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lipotoxic cell damage under fatty acid exposure. We propose an epigenetic mechanism

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for ensuring metabolic plasticity in response to lipid overload, in which LSD2 maintains

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the proper expression of lipid metabolism genes in hepatocytes.

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MATERIALS and METHODS

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Cell culture

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HepG2 cells were cultured in high glucose (25 mM D-glucose) Dulbecco’s

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modified Eagle’s medium (Sigma) supplemented with 10% (v/v) heat-inactivated fetal

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bovine serum and penicillin/streptomycin. For the knockdown experiments, specific

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siRNAs were introduced to the cells using RNAiMAX reagent (Invitrogen) when they

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were approximately 50% confluent. After being cultured for 3 to 4 days, semiconfluent

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cells were harvested for subsequent analyses. Target sequences used for siRNA design

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are listed in Table S1. siRNA against firefly luciferase gene was used as a control. For

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the knockdown of c-Jun gene, siGENOME Human JUN siRNA SMARTpool

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(Dharmacon) was used, while siGENOME Non-Targeting siRNA SMARTpool #1

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(Dharmacon) was used as a control.

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Antibodies

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Anti-LSD2 polyclonal antibody was raised in rabbits by administering

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recombinant human LSD2 protein (region 26 – 822), which was prepared using a

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baculovirus expression system. Anti-LSD2 antisera were purified by affinity

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chromatography of the IgG fraction, and were titrated prior to use. Anti-histone H3 5

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(ab1791), anti-H3K4me1 (ab8895) and anti-H3K27ac (ab4729) antibodies were

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purchased from Abcam. The following antibodies were also used: anti-histone

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H3K4me2 (07-030, Millipore), anti-normal rabbit IgG (sc-2027, Santa Cruz), anti-Flag

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M2 (F1804, Sigma-Aldrich).

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Plasmid construction

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To construct pcDNA3-Flag-hLSD2, an LSD2 expression vector, a fragment

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(from +1 to +2,469) of the human LSD2 gene was PCR-amplified using cDNAs from

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HepG2 cells, and cloned into EcoRV and XbaI sites of the pcDNA3-Flag-mock vector.

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Gene expression analysis

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Total RNA from tissues and cells was extracted using Trizol reagent

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(Invitrogen). cDNAs were produced using a ReverTra Ace qPCR RT-Kit (Toyobo).

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Quantitative RT-PCR was performed by the SYBR green method using Thunderbird

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reagents (Toyobo) and an ABI 7300 Sequence Detector (Applied Biosciences). Data are

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presented as mean ± SD. Statistical analyses were performed using two-tailed Student’s

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t-test. Primers used in this study are listed in Table S1.

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Microarray analysis

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Genome-wide expression analysis was performed using a GeneChip Human

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Genome Array U133 Plus 2.0 in combination with a GeneChip Hybridization, Wash and

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Stain Kit (Affymetrix). We prepared three HepG2 samples, by introducing each of three

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different siRNAs against LSD2. We also prepared two control-KD samples. Total RNA

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from cells was extracted, and the sample integrity was confirmed using a Bioanalyzer 6

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RNA 6000 Nano Assay (Agilent). Data annotation analysis was performed using

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GeneSpring GX software (Agilent). GSEA was done using GSEA ver. 2.0 software

139

provided

140

(http://www.broadinstitute.org/gsea/).

by

the

Broad

Institute

of

MIT

and

Harvard

141 142

Chromatin immunoprecipitation

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In the ChIP experiments for detecting modified histones, cells were

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cross-linked with 1% formaldehyde. Following cell lysis, isolated nuclei were subjected

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to sonication for chromatin fragmentation. Chromatin fragments were incubated at 4 °C

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overnight with appropriate antibodies, followed by a pull-down assay using protein

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A/G-conjugated agarose beads. Purified DNAs were subjected to quantitative PCR

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(qPCR) using the primer sets listed in Table S1. To detect LSD2 enrichment on

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genomic DNA, we employed a protocol for detecting indirect associations between

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protein and DNA (24). Briefly, enhanced cross-linking of chromatin using

151

formaldehyde

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3′-dithiobispropionimidate 2HCl (Sigma) was performed to increase the stability of

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protein-DNA complexes. Chromatin fragmentation was done by sonication in regular

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RIPA buffer containing 0.1% SDS, followed by immunoprecipitation, as described

155

above.

and

the

protein-protein

chemical

cross-linker

dimethyl

3,

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ChIP-seq analysis

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For ChIP-seq analysis to detect LSD2 or H3K4me1/DNA interactions, 1×107

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HepG2 cells were collected for a ChIP experiment. After crosslinking, chromatin DNA

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was fragmented using a Covaris S220 sonicator (Covaris Inc.), followed by 7

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immunoprecipitation with either an anti-LSD2 or an anti-H3K4me1 polyclonal antibody.

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The protein-bound chromatin fraction was collected using Dynabeads Protein A/G (Life

163

Technologies), and the DNA was purified. A DNA fragment library for sequencing was

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constructed using an Ion Fragment Library Kit (Life Technologies). Adopter-ligated

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DNA fragments were purified using Agencourt AMPure XP (Beckman Coulter Inc.).

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High throughput sequencing was performed using Ion PGM and Ion Proton

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semiconductor sequencers (Life Technologies), according to the manufacturer’s

168

instruction. All sequence data obtained from Ion PGM and Proton were merged before

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alignment onto the human reference genome hg19 using the BWA algorithm (CLC

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Genomics Workbench Software). With the same software, the duplicate reads and low

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read/mapping quality reads were trimmed out. For LSD2 ChIP-seq, final numbers of

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mapped reads were 36,409,704 reads for LSD2, and 27,141,872 reads for Input. For

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H3K4me1 ChIP-seq, final numbers of mapped reads were 33,087,078 reads for the

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control siRNA sample, and 53,725,212 reads for input of the control siRNA sample;

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49,410,448 reads for the LSD2-KD sample, and 58,829,288 reads for input of the

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LSD2-KD sample.

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Peak detection was done using the MACS algorithm in Avadis NGS software.

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LSD2 binding sites were detected based on the LSD2 peaks significantly enriched over

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input peaks at a cutoff value of p=10-5. H3K4me1 peaks enhanced by LSD2-KD were

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detected based on the H3K4me1 peaks in LSD2-KD samples significantly enriched over

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H3K4me1 peaks in control siRNA sample peaks at a cutoff value of p=10-5.

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For identification of the direct regulatory target genes of LSD2, we first

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detected 414,095 LSD2 peaks using the MACS algorithm (25) and selected 15,532

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robust peaks that met the criteria of >25 reads and >5-fold enrichment. Based on this 8

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peak detection, 6,079 neighboring genes were identified within 5,000 bases of the LSD2

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peaks using Avadis NGS software with the gene annotation provided by Ensembl.

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Among these genes, we identified 226 genes with >1.5-fold expression change in

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response to LSD2-KD.

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For identifying genes with both increased H3K4me1 and expression change in

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response to LSD2-KD, we first detected 180,505 exclusive H3K4me1 peaks under

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LSD2-KD using the MACS algorithm, and selected 12,735 robust peaks that met the

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criterion of >30 reads and >5-fold enrichment. Based on this peak detection, 5,768

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neighboring genes were identified within 5,000 bases of the H3K4me1 peaks using

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Avadis NGS with the gene annotation provided by Ensembl. Of these genes, we

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identified 207 with >1.5-fold expression change in response to LSD2-KD.

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Visualization of ChIP-Seq data with smoothing (smoothing window size = 2

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bp) was done using Avadis NGS. ChIP-seq data for chromatin modifications in HepG2

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cells were obtained from the ENCODE/Broad Institute via the UCSC Genome Browser

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website (http://genome.ucsc.edu/). The accession numbers of the files are as follows:

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wgEncodeEH000082

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(GSM733743) for H3K27ac. ChIP-seq data for p300 enrichment in HepG2 cells was

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from ENCODE/Stanford/Yale/USC/Harvard (wgEncodeEH001862), FAIRE data was

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from ENCODE/OpenChrom (UNC Chapel Hill) (wgEncodeEH000546 (GSM864354)),

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c-Jun data was from ENCODE/Stanford/Yale/USC/Harvard (wgEncodeEH001794) and

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c-Myc data was from ENCODE/Open Chrom (UT Austin) (wgEncodeEH000542

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(GSM822286)).

(GSM733693)

for

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Correlation analyses of ChIP-seq peaks 9

H3K4me2

and

wgEncodeEH000094

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Correlations of LSD2 peaks with histone modifications were analyzed using

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GenomeInspector

(Genomatix)

according

to

the

manufacturer’s

instructions

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(https://www.genomatix.de/online_help/help_regionminer/GenomeInspector.html).

212

reference data sets, histone modification data of HepG2 cells were obtained from the

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ENCODE/Broad Institute via the UCSC Genome Browser website. The accession

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numbers of the files used in the analyses are as follows: wgEncodeEH001749

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(GSM798321) for H3K4me1, wgEncodeEH001023 (GSM733754) for H3K27me3.

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LSD2 peaks were selected using the criteria of >28 reads and >5-fold enrichment from

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the peaks detected using the MACS algorithm. Peaks for H3K4me1 and H3K27me3

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were detected using NGS analyzer (Genomatix) or the MACS algorithm in Avadis

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NGS.

As

220 221

Metabolomic analysis

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Metabolomic analyses were performed using CE-TOFMS and LC-TOFMS at

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Human Metabolome Technologies (HMT, Japan, http://humanmetabolome.com).

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Triplicate samples of control and LSD2-KD2 cells were subjected to both CE-TOFMS

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and LC-TOFMS, while LSD2-KD1 was analyzed by LC-TOFMS. Cells were washed

226

with PBS and collected by trypsinization, then washed twice with 5% (w/w) mannitol

227

solution at room temperature. Cells were re-dispersed in LC/MS grade methanol

228

(Wako) for CE-TOFMS or LC/MS grade ethanol (Wako) for LC-TOFMS, both

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containing HMT’s Internal Standard Solution 1. Peaks were extracted as previously

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described (26). After quantification, metabolite concentrations were normalized by cell

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number. Of ~900 (for CE-TOFMS) and ~500 (for LC-MS) metabolites from the HMT

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databases, 275 metabolites were detected above the signal-to noise threshold (listed in 10

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Table S4). The databases include glycolysis and TCA cycle intermediates, amino acids,

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nucleic acids, nucleotides, nucleosides, Coenzyme A, organic acids, nicotinamide

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coenzymes, fatty acids, bile acids, lipids, steroid derivatives and polyphenols.

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Clustering of metabolites according to changes in concentration was

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performed using Cluster 3.0, which was obtained from the Laboratory of DNA

238

Information Analysis of the Human Genome Center in the Institute of Medical Science,

239

The

240

(http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm#ctv/).

241

clustering was calculated using Pearson correlation (centered correlation) and complete

242

Linkage. Clustering results were visualized using Java TreeView software (27).

University

of

Tokyo Hierarchical

243 244

Fatty acid uptake assay

245

Cellular fatty acid uptake was tested using QBT Fatty Acid Uptake Assay Kit

246

(Molecular Devices), which uses dodecanoic acid conjugated with BODIPY, a

247

fluorescent dye (BODIPY-DA). Fatty acid uptake assay stock solutions were dissolved

248

completely by adding 10 ml of 1× HBSS buffer (1× Hank’s balanced salt solution with

249

20 mM HEPES and 0.2% fatty acid-free bovine serum albumin). HepG2 cells were

250

cultured in the medium containing the assay reagent for 10 min at 37 °C. Cells were

251

either subjected to microscopic analysis, or trypsinized for fluorescence-activated cell

252

sorting analysis, using a FACS Canto cytometer (Becton Dickinson).

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Lipotoxicity analysis

255

To analyze cellular lipotoxicity, siRNA-introduced HepG2 cells were treated

256

with bovine serum albumin (BSA)-conjugated oleic acid for 48 hours. Following 11

257

trypsinization, cells were counted using an automatic cell imaging counter, Cytorecon

258

(GE Healthcare). For oleic acid conjugation to BSA, a sodium oleate (≥99% (capillary

259

GC), Sigma) solution in 150 mM NaCl was added to a fatty acid-free BSA solution

260

(Wako). The final molar ratio of oleic acid to BSA was 6:1.

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Animal studies

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Animal experiments were conducted in accordance with the guidelines of the

264

Animal Care and Use Committee of Kumamoto University. For NAFLD induction,

265

7-week-old male C57BL/6J mice were fed a high fat diet (HFD) containing 21% kcal

266

fat (A02082003BP: Research Diets Inc.) or a methionine/choline-deficient diet (MCD,

267

A02082002BG: Research Diets Inc.), which also contains 21% kcal fat for four weeks.

268

Body weight was monitored weekly throughout the test period. After 16-hour fasting,

269

liver tissues were dissected, and the sections were either snap-frozen in liquid nitrogen

270

for RNA analyses or fixed with formalin for histological analyses.

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Statistical analyses All statistical analyses between two groups were done by Student’s t-test unless otherwise stated. Equality of variance was examined using F-test.

275 276

Accession Number

277

The accession number of microarray and ChIP-seq data in GEO is GSE59695.

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RESULTS 12

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LSD2 selectively represses lipid metabolism genes in hepatocytes

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Because LSD1 regulates the metabolic genes under diverse cellular contexts

284

(11, 12, 28), we tested, in this study, whether another FAD-dependent demethylase

285

LSD2 could be involved in the metabolic programming. During our initial examinations

286

in mouse tissues, we found that LSD2 was expressed more highly in the liver than in

287

other metabolic tissues (Fig. 1A). To gain insight into the role of LSD2 function in

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hepatocytes, we depleted LSD2 in HepG2 human hepatic cells using three different

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siRNAs (Fig. 1B), then carried out an expression microarray experiment. We detected

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1,362 probe sets with more than 1.5-fold difference between the control and

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LSD2-knockdown (KD) cells (Fig. 1C). Of these, 906 probe sets were up-regulated,

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while 456 were down-regulated. Using gene set enrichment analysis (GSEA) (29, 30),

293

we established that genes associated with “metabolism of lipids and lipoproteins” were

294

significantly enriched in the probe sets that were up-regulated by LSD2-KD (statistical

295

threshold, p-values

Lysine-specific demethylase 2 suppresses lipid influx and metabolism in hepatic cells.

Cells link environmental fluctuations, such as nutrition, to metabolic remodeling. Epigenetic factors are thought to be involved in such cellular proc...
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