The Landscape of Histone Modifications in a High-Fat Diet-Induced Obese (DIO) Mouse Model

Litong Nie; Lin Shuai; Mingrui Zhu; Ping Liu; Zhi-Fu Xie; Shangwen Jiang; Hao-Wen Jiang; Jia Li; Yingming Zhao; Jing-Ya Li; Minjia Tan

doi:10.1074/mcp.M117.067553

. 2017 Apr 27;16(7):1324–1334. doi: 10.1074/mcp.M117.067553

The Landscape of Histone Modifications in a High-Fat Diet-Induced Obese (DIO) Mouse Model^*

Litong Nie ^‡,^§,^¶,^‡‡, Lin Shuai ^§,^¶,^‡‡, Mingrui Zhu ^‡,^§,^¶,^‡‡, Ping Liu ^‡,^§, Zhi-Fu Xie ^§,^¶, Shangwen Jiang ^‡,^§, Hao-Wen Jiang ^‖, Jia Li ^§, Yingming Zhao ^‡,^§,^**, Jing-Ya Li ^§,^§§, Minjia Tan ^‡,^§,^§§

PMCID: PMC5500764 PMID: 28450421

Abstract

Type 2 diabetes (T2D) is a major chronic healthcare concern worldwide. Emerging evidence suggests that a histone-modification-mediated epigenetic mechanism underlies T2D. Nevertheless, the dynamics of histone marks in T2D have not yet been carefully analyzed. Using a mass spectrometry-based label-free and chemical stable isotope labeling quantitative proteomic approach, we systematically profiled liver histone post-translational modifications (PTMs) in a prediabetic high-fat diet-induced obese (DIO) mouse model. We identified 170 histone marks, 30 of which were previously unknown. Interestingly, about 30% of the histone marks identified in DIO mouse liver belonged to a set of recently reported lysine acylation modifications, including propionylation, butyrylation, malonylation, and succinylation, suggesting possible roles of these newly identified histone acylations in diabetes and obesity. These histone marks were detected without prior affinity enrichment with an antibody, demonstrating that the histone acylation marks are present at reasonably high stoichiometry. Fifteen histone marks differed in abundance in DIO mouse liver compared with liver from chow-fed mice in label-free quantification, and six histone marks in stable isotope labeling quantification. Analysis of hepatic histone modifications from metformin-treated DIO mice revealed that metformin, a drug widely used for T2D, could reverse DIO-stimulated histone H3K36me2 in prediabetes, suggesting that this mark is likely associated with T2D development. Our study thus offers a comprehensive landscape of histone marks in a prediabetic mouse model, provides a resource for studying epigenetic functions of histone modifications in obesity and T2D, and suggest a new epigenetic mechanism for the physiological function of metformin.

Diabetes mellitus type 2 (type 2 diabetes, T2D)¹, which accounts for about 90% of diabetes cases, is a global chronic metabolic disorder. Over 300 million people worldwide suffer from T2D, and the number is increasing in most countries (1). Hyperglycemia is the characteristic clinical hallmark of T2D. This chronic illness is caused by a combination of lifestyle and genetic factors. Among the major risk factors for development of T2D are lifestyle-driven overweight and obesity. Efficient new therapeutics are urgently needed to treat this disease.

Mounting evidence suggests that dysregulation of epigenetic mechanisms, such as DNA methylation and protein posttranslational modifications (PTMs) in histones, play an important role in the development of T2D (2, 3). Earlier studies show that histone PTMs (or histone marks), such as acetylation and methylation, contribute to diverse T2D phenotypes, including insulin resistance, gluconeogenic and lipogenic dysfunction (3). The regulatory enzymes for histone lysine acetylation, histone acetyltransferases and histone deacetylases (HDACs), are known to be associated with metabolic homeostasis (4–6). Sirtuins, the class III HDACs, have been a group of metabolic sensors (7). SIRT1 regulates glucose homeostasis by affecting diverse protein targets, such as forkhead box O (FOXO) transcription factors, PPAR-γ coactivator PGC-1α, and mitochondrial uncoupling protein 2 (UCP2), to control insulin secretion, gluconeogenesis, and mitochondrial metabolism (4, 8). Alterations in the NAD+/NADH ratio caused by glucose starvation lead to SIRT1-catalyzed deacetylation of acetyllysine at position 9 of histone H3 (or H3K9ac), which triggers energy-dependent transcriptional changes (9). The class IIa HDACs (HDAC4/5/7) regulate cellular metabolism by modulation of FOXO activity (5, 10). In addition to histone acetylation, histone methylation has been reported to regulate glucose homeostasis. Jhdm1a, a histone H3K36 demethylase, regulates gluconeogenesis by suppressing expression of the master gluconeogenic regulator C/EBPα (11). These previous efforts are mainly focused on a few widely studied histone marks and their corresponding regulatory enzymes. A comprehensive analysis of histone modifications and their dynamic changes in obesity or T2D is rare, hindering our understanding of epigenetic mechanisms in obesity and T2D.

Metformin is one of the most widely used oral drugs for treatment of T2D (12). Although hepatic gluconeogenesis suppression is considered as the primary therapeutic action of metformin, the exact molecular mechanisms by which metformin acts remain elusive. Recent studies showed that metformin could trigger phosphorylation of a lysine acetyltransferase, CREB-binding protein (CBP), to break apart the CREB-CBP-TORC2 transcriptional complex that in turn inhibits gluconeogenesis (13). Hepatic SIRT1, a lysine deacetylase, and GCN5, a lysine acetyltransferase, were also reported to be regulated by metformin to suppress gluconeogenesis via deacetylation of transcription coactivator 2 (TORC2) and PGC-1α, respectively (14). Nevertheless, changes in histone marks in response to metformin have not been fully examined to date.

Global analysis of histone marks and their dynamics is challenging, as amino acid residues in histones can be heavily modified by over a dozen different types of modifications (15). The same type of modification can occur at different residues of the same histone polypeptide. In addition, the same histone residue of different histone molecules in a single cell can be subject to different types of modification simultaneously. The combining of multiple histone modifications dramatically expands the degree to which chromatin can be regulated. In addition, the stoichiometry of histone marks can be very low and may not be easily identified. For example, even though it can be difficult to detect H3K4me3 and H3K79me3 (16, 17), these modifications have their important roles in chromatin structure and function (18–20). Nevertheless, positive identification of histone marks, either using mass spectrometry (MS) or Western blotting, provides confidence that they exist in cells. The rapid advancement of high-resolution MS in recent years has made it the preferred method for system-wide analysis of histone PTMs, especially its high mass accuracy and high sensitivity for confident identification of most, if not all, types of PTMs.

In this study, we report a comprehensive analysis of histone modifications in liver tissues from diet-induced obese (DIO) mice and metformin-treated DIO (DIO-Met) mice using a mass spectrometry-based label-free and chemical stable isotope labeling quantitative proteomic approach. We identified 170 histone marks, including 30 histone marks that have not been previously reported. Over 30% of the histone marks were among newly reported lysine acylation pathways, including histone propionylation, butyrylation, malonylation, and succinylation. Fifteen histone marks were changed by more than 1.5-fold in DIO mice relative to mice fed normal chow in label-free quantitative result, and six histone marks were changed by more than 1.5-fold in DIO mice relative to mice fed normal chow in chemical stable isotope-labeling approach, suggesting a link between these marks and prediabetes. Notably, we found that histone H3K36me2 level was associated with development of prediabetes and the antidiabetic activity of metformin. Our study presents a landscape of hepatic histone marks and their dynamic changes in response to diet-induced obesity and metformin, providing a resource for the study of epigenetic mechanisms of diet-induced obesity and T2D.

MATERIALS AND METHODS

Materials

Modified sequencing grade trypsin was purchased from Promega (Madison, WI); mass spectrometry grade water and acetonitrile was purchased from Thermo Fisher Scientific, Inc. (Waltham, MA). Other chemicals including trifluoroacetic acid (99%), formic acid (98%), ammonium bicarbonate (NH₄HCO₃, 99%), HEPES, potassium chloride (KCl), magnesium chloride (MgCl₂), sucrose, propionic anhydride, and Nonidet P-40 were obtained from Sigma-Aldrich, Inc. (St. Louis, MO). D10 propionic anhydride was purchased from Cambridge Isotope Laboratories, Inc. (Tewksbury, MA). Protease inhibitor mixture was purchased from Roche Diagnostics Ltd. (Shanghai, China). Metformin was purchased from MedChemExpress (MCE) (HY-17471A, Shanghai, China).

Animal Experiments

Male C57BL/6J mice were purchased from Shanghai SLAC Laboratory Animal Co. Ltd (Shanghai, China) and housed in a temperature-controlled room (22 ± 2 °C) with a 12 h light-dark cycle. These mice were either maintained on chow or switched to a high-fat diet (60 kcal % fat, Research Diets (New Brunswick, NJ)) for 8 weeks. Thereafter, the diet-induced obese (DIO) mice were randomized into two groups based on their body weight for chronic treatment. Chow-fed and DIO mice received oral administration of either vehicle (0.5% methylcellulose) or metformin (250 mg/kg/day) for 5 weeks. Body weight and food intake were recorded daily. Fasting blood glucose levels were measured after 6 h of fasting. The glucose tolerance test (1.5 g/kg glucose i.p.), the insulin tolerance test (1 unit/kg insulin i.p.) and the pyruvate tolerance test (2 g/kg sodium pyruvate i.p.) were performed after 6 h of starvation. At the end of treatment, the animals were sacrificed, and their tissues were collected for further experiments. The animal experiments were approved by the Animal Ethics Committee of the Shanghai Institute of Materia Medica.

Experimental Design and Statistical Rationale

For label-free quantification, DIO mouse liver with Chow-fed mouse liver histone samples were analyzed in 3 technical replicates. For stable isotope propionic anhydrite labeling quantification, 4 pairs of histone samples extracted from DIO mouse livers and Chow-fed mouse livers, and 4 pairs of histone samples extracted from metformin treated DIO mouse (DIO-Met) livers and vehicle treated DIO mouse (DIO-Veh) livers were analyzed in 3 technical replicates. At least 1.5-fold change and p value < 0.05 were considered significant difference.

Histone Extraction from Liver Tissues

Histones were extracted from livers of DIO or chow-fed mice as previously described (21). Briefly, livers were quickly dissected into pieces, rinsed with cold PBS, and then dissociated gently using a Dounce homogenizer in PBS containing 5 mm sodium butyrate for cell isolation. The isolated cells were lysed with 3 volumes of extraction buffer (10 mm HEPES pH 7.0, 10 mm KCl, 1.5 mm MgCl₂, 0.34 m sucrose, 0.5% Nonidet P-40 and 1× protease inhibitor mixture). After centrifugation, the pellets were washed with extraction buffer without Nonidet P-40, and then resuspended in 0.2 m H₂SO₄ overnight at 4 °C. After centrifugation, the supernatant was collected for trichloroacetic acid precipitation. The precipitate was washed with chilled (−20 °C) acetone containing 0.1% (v/v) HCl, followed by two washes with ice-cold 100% acetone. The precipitate was dried completely at room temperature, and then dissolved in water for further experimentation.

In-gel Digestion and Chemical Derivatization

Five micrograms of each histone sample (one pair of mice from chow-fed versus DIO) were resolved by SDS-PAGE and visualized by Coomassie Brilliant Blue staining. Bands of histones (H1, H2A, H2B, H3, and H4) were excised, destained with 50% ethanol, and dehydrated with acetonitrile. Samples were then subjected to in-gel digestion with or without chemical derivatization as follows (22). (1) In-gel digestion without chemical derivatization: Gel bands were digested with trypsin (1:50, enzyme:protein) at 37 °C overnight. After MS analysis, tryptic peptides were used to quantify histone marks of H2A, H2B, H3 and H4 by label-free quantification. (2) Chemical derivatization before digestion: Destained and dehydrated gel bands were propionylated using propionic anhydride in buffer (100 mm NH₄HCO₃, 100 mm NaHCO₃, pH 8.0) at 37 °C for 1 h, and the propionylation reaction was then repeated. The gel band was then digested with trypsin at 37 °C overnight. (3) Chemical derivatization after digestion: After in-gel digestion of histone bands, tryptic peptides were propionylated using propionic anhydride in buffer (100 mm NH₄HCO₃, pH 8.0) at 37 °C for 1 h, and the propionylation reaction was then repeated.

In-solution Digestion and Chemical Derivatization with Stable Isotope Propionic Anhydride for Stable Isotope Labeling Quantitative Analysis

Histone chemical derivatization was carried out as previously described (22). Twenty micrograms of each histone sample from four pairs of mice (chow-fed versus DIO, DIO-Met versus DIO-Veh) were propionylated with D0 or D10 propionic anhydride in buffer (100 mm NH₄HCO₃, 100 mm NaHCO₃, pH 8.0) at 37 °C for 1 h, and the propionylation reaction was then repeated. The sample was then digested with trypsin at 37 °C overnight. After digestion, N-terminal of tryptic peptides were propionylated with D0 or D10 propionic anhydride, respectively. And the propionylation reaction was then repeated. Then the light and heavy labeling peptides were mixed, and subject to MS analysis.

Nano-HPLC-MS/MS Analysis

Peptides were dissolved in HPLC solvent A (0.1% formic acid in 2% acetonitrile and 98% H₂O), injected onto a manually packed reversed phase C18 column (170 mm × 79 μm, 3-μm particle size, Dikma, China) coupled to an Easy-nLC 1000 chromatography system (Thermo Fisher Scientific, Waltham, MA). Peptides were eluted using a 2-h gradient of 8% to 80% solvent B (0.1% formic acid in 90% acetonitrile and 10% H₂O) in solvent A at a flow rate of 300 nl/min. Peptides eluted from HPLC were ionized using a nanospray source and analyzed in an Orbitrap Elite mass spectrometer (Thermo Fisher Scientific, San Jose, CA). For full MS spectra, the scan range was 350 to 1800 with a resolution of 240,000 at m/z 400 and lockmass enabled (m/z at 536.165369). For MS/MS scans, the twenty most intense ions with intensity greater than 5000 and charge states of +1, +2, or +3 in each full MS spectrum were sequentially fragmented in a linear ion trap by collision-induced dissociation, using a normalized collision energy of 35%. The dynamic exclusion duration was set to be 15 s, and the isolation window was 1.5 m/z. All histone samples were analyzed in triplicate.

Mass Spectrometric Data Analysis

All acquired MS raw files were transformed into MGF format by Proteome Discoverer software (version 1.4, Thermo Fisher Scientific), then all MGF files were analyzed by Mascot software (version 2.3.01, Matrix Science Ltd., London, UK) against an in-house mouse histone sequence database (94 sequences, 14,024 residues) generated from the UniProt database (updated on 09/24/2014). Four groups of parameters were used to search for histone modifications, as follows. (1) For histone proteolytic peptides with no chemical derivatization, acetyl (K), methyl (KR), dimethyl (KR), trimethyl (K), propionyl (K), butyryl (K), malonyl (K), succinyl (K), crotonyl (K), ubiquitinyl (K) and phosphoryl (ST) groups were specified as variable modifications. (2) For samples chemically propionylated before tryptic digestion, propionylation-methylation (K) was additionally specified as variable modification. (3) For samples chemically propionylated after tryptic digestion, propionylation-methylation (K) was specified as an additional variable modification and propionyl (N-terminal of peptide) as a fixed modification. (4) For stable isotope labeling samples, propionyl (N-terminal of peptide), propionyl_D5 (N-terminal of peptide), propionyl (K), propionyl_D5 (K), propionylation-methylation (K), propionylation_D5-methylation (K), dimethyl (K) and acetyl (K) were specified as variable modifications. Other parameters for all analyses were specified as follows: mass error was ±10 ppm for parent ions and ±0.5 Da for fragment ions. The enzyme was specified as trypsin with a maximum of 5 missing cleavages. Peptide ion score cutoff was 20, and the spectra of all identified peptides were checked manually according to criteria reported previously to ensure the accuracy of peptide identification (23, 24).

Quantification of Histone PTMs

Histone PTM quantification was processed using Skyline (version 3.1.0) and manually checked as previously described (25). Briefly, redundant spectral libraries were generated from Mascot searches. The resulting Mascot dat files, as well as raw MS files, were imported into Skyline for extraction of precursor ions of peptides identified in the spectral libraries. The count of precursor isotope peak was set at three (M, M+1, M+2) at resolution 240,000 at m/z 400. Chromatographic traces of precursor ions were manually checked and adjusted in some cases for accurate peak selection. Quantitative comparisons were based on the area (area under the curve, AUC) of the monoisotopic peak of the precursor ion of each peptide. Peak areas of monoisotopic peaks having different charge states were added together. For PTM site quantification, peak areas of different peptides bearing the same modification were summed together according to previous reports (26–28). Trypsin digestion without chemical propionylation samples was used for label-free quantification. D0 and D10 propionylation peptides were used for stable isotope labeling quantification. AUCs of MS1 intensities of the modified peptide forms were calculated by Skyline software. Each AUC of modified peptide forms of a given histone PTM site were then summed. Then the summed AUC of a given histone mark was normalized by the corresponding unmodified C-terminal peptide. The normalized AUC of each histone mark in DIO or chow-fed mouse and DIO-Met versus DIO-Veh was used for quantification. Precursor ion AUC of C-terminal unmodified histone peptides (DAVTYTEHAK and VFKENVIR for H4, DIQLAR and STELLIR for H3, LLLPGELAK and ESYSVYVYK for H2B, HLQLAIR and AGLQFPVGR for H2A) were used to normalize the amount of each histone in label-free quantification. Precursor ion AUC of prDNIQGITKprPAIR for H4, prKprLPFOR and prVTIMPKprDLQLAR for H3 and prAGLQFPVGR for H2A were used to normalize the amount of each histone in stable isotope labeling quantification. In stable isotope labeling quantification, four biological replicates were used to quantify histone marks, and each biological replicate has three technical replicates. t test was used to test significant change of histone marks. At least 1.5-fold change and p value < 0.05 were considered significant difference.

All mass spectrometry raw data, Mascot searching data (dat files) and Skyline files have been deposited to the iProX Consortium with the dataset identifier “Raw Data and Analysis by Skyline” (Project ID: IPX0000855000, http://www.iprox.org/page/SCV017.html).

Western Blotting Analysis

Histones extracted from liver or primary hepatocytes (prepared by collagenase perfusion as previously described (29) from DIO mice and chow-fed mice were dissolved in loading buffer, then resolved by 15% SDS-PAGE. Histones were transferred to nitrocellulose, and the membrane was blocked with BSA. The membrane was incubated with specific primary antibodies, and then detected using horseradish peroxidase-conjugated affinipure goat anti-rabbit or mouse IgG antibody (Jackson ImmunoResearch, Suffolk, United Kingdom) with an enhanced chemiluminescence kit (Merck Millipore, Darmstadt, Germany). The specific primary antibodies in this experiment were H3K9me2, H3K14ac, H3K27me2, H3K27me3, and H3K36me2 (Cell Signaling Technology, Danvers, MA); H3K9ac (PTM Biolab, Hangzhou, China); and H3 (Abcam, Cambridge, United Kingdom).

Quantitative RT-PCR

Total RNA was prepared from mouse tissues using Trizol reagents (Invitrogen, Carlsbad, CA). Purified RNA was reverse-transcribed using a PrimeScriptTM RT Reagent Kit (TaKaRa). The resulting cDNAs were quantified with Sybr-Green assays on the Stratagene Mx30005PTM Q-PCR system (Agilent Technologies). Measurements were performed using GAPDH as the control. The PEPCK primer sequences used in qPCR assays were as follows: Forward: CATATGCTGATCCTGGGCATAAC; Reverse: CAAACTTCATCCAGGCAATGTC.

RESULTS

Histone Marks in Liver from Diet-induced Obese Mice

To systematically analyze changes of histone marks caused by a high-fat diet, we generated the DIO mice. As expected, these mice exhibited impaired glucose tolerance and enhanced pyruvate tolerance (Fig. 1A and supplemental Fig. S1). We chose liver tissues from DIO and chow-fed mice to study histone marks because aberrant hepatic gluconeogenesis is considered a predominant factor in T2D development.

Fig. 1. — **A, Glucose tolerance test in DIO mice.** Blood glucose levels were measured following intraperitoneal administration of 2 mg/g glucose (n = 8 per group, upper panel). The areas under the curve are indicators of glucose clearance capacity (bottom panel). Differences between the groups were analyzed with the one-side Student's t test; *p < 0.05, **p < 0.01. B, SDS-PAGE separation of hepatic histone extracts. C, Experimental design for label-free quantification of histone marks in livers derived from chow-fed and DIO mouse livers.

Histones of interest were isolated from liver tissue by acid extraction (21). To improve detection sensitivity, we resolved the individual histone proteins by SDS-PAGE (Fig. 1B). Each histone band was then tryptically digested and subjected to nano-HPLC-MS/MS analysis (Fig. 1C). We carried out chemical propionylation of histone peptides prior to HPLC-MS/MS analysis. This method was first reported by Garcia and colleagues to improve sequence coverage for histone peptides (22, 30). Mass spectrometric data were analyzed by Mascot software using the reported histone PTMs as variable modifications (15). All identified MS/MS spectra were manually verified according to previously reported stringent criteria (23).

We identified 170 histone marks, including 149 in core histones and 21 in linker histone H1, consisting of 10 types of histone modifications (Fig. 2 and supplemental Table S1). A literature search (15, 31) and a comparison with UniProt database indicate that 30 of the 170 histone marks are new ones, including 29 sites (associated with 8 types of histone modifications) that have not previously been reported (Fig. 2B and supplemental Fig. S2 for annotated MS/MS spectra), and 1 new site, H4K8me1, that was firstly identified in mammalian cells (previously reported in yeast (32)). The new histone marks included not only previously unreported sites of the well-studied PTMs acetylation and methylation, but also 5 types of less characterized histone modifications: lysine propionylation, butyrylation, malonylation, succinylation, and serine acetylation (Fig. 2B).

Verification of New Histone Marks

We validated the identities of a few selected peptides bearing new histone marks. Our previous study showed that peptides containing malonylated lysine show characteristic neutral losses of carbon dioxide (CO₂) during MS/MS fragmentation (33). This characteristic MS/MS fragmentation pattern, together with high-resolution MS precursor ion data, enabled the confident identification of lysine malonylation sites. In our analysis, we identified 7 lysine malonylated histone marks, all of which show specific CO₂-loss peaks.

To validate other types of new histone marks identified in this analysis, we chemically synthesized four peptides (KESacYSVYVYK, GVLKacVFLENVIR, GKGGKme1GLGK, and KprSTGGKacAPR) corresponding to H2BS36ac, H4K59ac, H4K8me1, and H3K9pr, respectively (Fig. 2C and supplemental Fig. S3). The MS/MS fragmentation patterns of the synthetic peptides were almost identical to those of their counterparts derived from mouse liver. These results therefore confirmed the identification of the four modified peptides.

Quantification of histone marks in DIO and chow-fed mice

To systematically reveal the changes of histone marks caused by prediabetes and globally profile the new histone marks in DIO mouse, we first quantified histone samples from one pair of mice from chow-fed versus DIO mouse by label-free quantification based on precursor ion signals of PTM-containing histone peptides according to previously reported methods using Skyline software (25, 26, 28). This semiquantification method is able to cover as many identified histone PTMs as possible based on our current MS data, including those relatively low abundant acyl modifications, such as propionylation and butyrylation. To reduce bias in sample processing, we normalized the amount of each sample by running SDS-PAGE (Fig. 1C) and by MS signals of C-terminal histone peptides that did not bear any known modifications. In this analysis, we were able to quantify more than 100 histone modifications by label free quantification. Among them, 15 histone marks showed significant changes in abundance of at least 1.5-fold change and p value < 0.05 in triplicate analyses (Table I and supplemental Table S1 and S2). These histone marks represented 5 types of histone modifications: arginine methylation, and lysine methylation, propionylation, malonylation, and butyrylation (Table I). Five histone marks were up-regulated whereas 10 were down-regulated in DIO mice compared with chow-fed mice, suggesting that these histone marks may be associated with the development of obesity and T2D. Interestingly, all the up-regulated histone marks were methylations, whereas the down-regulated histone marks were more diverse and included one new PTMs (H3R49me1).

Table I. Histone marks altered in DIO mouse liver relative to liver from chow-fed mice by label-free quantification. Histone marks that changed at least 1.5-fold and p value < 0.05 in DIO mouse livers in triplicate technical analyses. *p < 0.05, **p < 0.01.

Ratio of change (DIO/Chow fed)
Sites	Average ratio
H3K23mal	0.44 ± 0.12**	Downregulated
H3K122ac	0.45 ± 0.27*
H3K18me2	0.51 ± 0.06**
H3R26me1	0.51 ± 0.07**
H2BK43me1	0.58 ± 0.10**
H3R49me1	0.58 ± 0.09**
H2AK118me1	0.62 ± 0.07**
H3K18bu	0.64 ± 0.01**
H2BK108me2	0.67 ± 0.13*
H3K23pr	0.67 ± 0.12*
H4K31me1	1.51 ± 0.17*	Upregulated
H4R35me1	1.52 ± 0.19*
H3R128me1	1.63 ± 0.27*
H3K36me2	1.79 ± 0.14**
H3R63me1	2.50 ± 0.24**

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Label free quantification of MS data is less reliable than stable isotope labeled approach, especially for quantifying protein modifications (34). To more accurately quantify the change of histone marks, we conducted chemical stable isotope-labeling approach using propionic anhydride to quantify four additional pairs of chow-fed versus DIO mice. Unmodified ε-amino group of lysine residues and N-terminal amino group of histones from DIO and chow-fed mice were chemically labeled with D10 and D0 propionyl group, respectively (Fig. 3A). Similarly, the areas under the MS intensities of C-terminal histone peptides with no known modifications were used to normalize the amounts of individual histones. The total quantifiable histone PTM sites and significantly changed sites were less than the label free quantification method (Fig. 3B). In this method, we quantified 22 histone PTM sites (supplemental Table S3–S5), and 6 sites significantly changed between chow-fed and DIO mice livers (Fig. 3B and supplemental Table S3–S5). Notably, H3K36me2 was up-regulated in DIO mice liver (Fig 3C and supplemental Fig. S4), consistent with the label-free quantification result. Jhdm1, a histone demethylase, was previously reported to be a negative regulator of gluconeogenic gene expression possibly by demethylating H3K36me2 at the C/EBPα locus (11). Our data showed ∼80% increase of H3K36me2 in DIO mice by mass spectrometry analysis (an average DIO/chow-fed ratio of 1.73, Fig. 3B), suggesting that dimethylation at H3K36 could be involved in prediabetes development. To further verify this finding, we isolated primary hepatocytes from DIO mice and chow-fed mice. Western blotting analysis showed that H3K36me2 was markedly increased in primary hepatocytes from DIO mice relative to hepatocytes from chow-fed mice (Fig. 3D). In addition, we carried out Western blotting analysis of 6 other histone PTMs using commercially available antibodies (supplemental Fig. S5). Our Western blotting data were mostly consistent with the mass spectrometric data.

Fig. 3. — **The quantification of histone marks in DIO *versus* chow-fed mouse livers by stable isotope propionic anhydrite labeling.** A, Experimental design for quantifying histone marks in chow fed *versus* DIO mice liver. B, Histone marks that changed at least 1.5-fold and p value < 0.05 in four pair of DIO *versus* Chow fed livers. *p < 0.05, **p < 0.01. C, Extracted ion chromatograms (XIC) for H3K36me2 (peptide prKme2SAPATGGVKme2KprPHR) in chow fed *versus* DIO mice liver by Skyline. D, Western blotting analysis of histone H3K36me2 of chow-fed livers, DIO mouse livers and primary hepatocytes isolated from chow-fed and DIO mouse livers.

Metformin-induced Changes of Histone Marks

To investigate histone PTMs possibly affected by metformin in the prediabetes condition, we treated DIO mice with metformin (250 mg/kg/day, q.d.) for 5 weeks. As expected, insulin resistance was significantly improved when challenged by i.p. injection of insulin, while fasting blood glucose was ameliorated (Fig. 4A–4B). When the DIO mice were challenged with pyruvate, blood glucose level, which represents the capacity of hepatic gluconeogenesis, was significantly decreased after metformin treatment (Fig. 4C). We further monitored expression of phosphoenolpyruvate carboxykinase (PEPCK), a rate-limiting enzyme in gluconeogenesis, by qPCR analysis. PEPCK mRNA levels dramatically decreased by ∼60% after treatment (Fig. 4D), indicating that metformin decreased the blood glucose level, likely through suppression of hepatic gluconeogenesis. Thus, our results confirmed that metformin exerted antidiabetic functions in the DIO mice.

Fig. 4. — **Efficacy impact of metformin on DIO mice.** DIO mice were treated with vehicle (0.5% methylcellulose) or metformin (250 mg/kg per day), and chow-fed mice were treated with vehicle (n = 5–8 per group). *In vivo* tests were performed on two-month-old mice after 5 weeks of treatment. A, Insulin tolerance test. Blood glucose levels after an intraperitoneal insulin load (1 unit insulin/kg) (left panel). The area under the curve (AUC) indicates insulin sensitivity (right panel). B, Fasting blood glucose levels. C, Pyruvate challenge test. Blood glucose levels were measured at the indicated time points after intraperitoneal injection of 2 mg/g sodium pyruvate. D, mRNA expression of gluconeogenic PEPCK from liver tissues. *p < 0.05, **p < 0.01 compared with vehicle-treated DIO mice. Differences between the groups were analyzed with the one-side Student's t test.

To reveal the dynamics of histone marks in response to metformin, we compared the levels of histone PTMs in four pairs of DIO mice with or without treatment of metformin by stable isotope propionic anhydrite labeling quantification method (Fig. 5A). In this experiment, 22 histone modification sites were quantified (supplemental Tables S6–S8), and 3 sites were significantly down-regulated in metformin-treated DIO mice liver (Fig. 5B).

Intriguingly, we found that metformin can reverse the elevated level of H3K36me2 in DIO mouse livers (Fig. 5B–5C and supplemental Fig. S4), suggesting a metformin-regulated epigenetic change. To further validate the MS quantification results, we carried out Western blot analysis using an anti-H3K36 dimethylation antibody. Consistent with the mass spectrometric data, H3K36 dimethylation was elevated in DIO mouse livers, whereas metformin treatment can significantly decrease histone H3K36 dimethylation in DIO mice to a level close to that of the chow-fed control mice (Fig. 5D). In addition, our data showed dimethylation of H3K27 was slightly reduced by metformin, whereas H3K27me2 was slightly up-regulated in DIO mouse liver (supplemental Fig. S5A–S5B and supplemental Table S4 and S7).

DISCUSSION

In this study, we carried out a comprehensive proteomic analysis of histone PTM sites in a prediabetic DIO mouse model, with or without metformin treatment. We identified 170 histone marks (149 on core histones and 21 on linker histone H1), including 30 that were previously unreported in mammalian cells. Among the newly identified core histone PTMs (Fig. 2B), 1 lysine acetylation site, 2 lysine monomethylation sites, 1 arginine monomethylation site, 8 lysine propionylation sites, 1 lysine butyrylation site, and 1 lysine malonylation site were located in the N-terminal histone regions. In addition, we identified 1 serine acetylation site, 1 lysine monomethylation site, 1 arginine dimethylation site, and 2 propionylation sites that were localized in either the globular domains or C-terminal regions.

Strikingly, 45 histone marks belonged to a recently discovered family of histone lysine acylation marks, including 15 propionylation, 12 butyrylation, 7 malonylation, 9 succinylation and 2 crotonylation sites, accounting for about 30% of the identified histone marks (24, 30, 35). Some types of lysine acylation histone marks, such as lysine butyrylation and malonylation, were difficult to detect in some differentiated cell lines, such as HeLa cells, when core histones were analyzed without antibody enrichment (24). Our results indicate that they are likely to be present at low stoichiometry in these cell lines. Two lines of evidence suggest that the newly discovered histone acylation marks have reasonable high stoichiometry in DIO mouse livers. First, our analysis of DIO mice did not involve affinity enrichment using a pan antibody against a PTM of interest. Second, our study did not detect some low stoichiometry histone marks with important roles in transcriptional control, such as H3K4me3 and H3K79me3 (16, 17). In contrast, consistent with our results, histone propionylation, butyrylation, crotonylation, and malonylation were also detected by others when antibody enrichment was not performed (36–39). Collectively, these results clearly show that the newly discovered histone modifications can have reasonable good stoichiometry in histone proteins, depending on cell type and cellular physiology.

Emerging evidence suggests that short-chain acylation pathways have diverse functions. They regulate activities of metabolic enzymes, thereby contributing to multiple inborn metabolic diseases (40). Histone acylations, including crotonylation (30, 41, 42), 2-hydroisobutyrylation (43), and butyrylation (44), are associated with gene expression. A recent study showed that the intracellular concentration of crotonyl-CoA affected histone crotonylation and transcriptional activities (45). We previously showed that propionyl-CoA, butyryl-CoA, malonyl-CoA, and crotonyl-CoA are the cofactors for these new lysine acylation modifications (24, 30, 35). Dysregulation of the homeostasis of short-chain CoAs, such as malonyl-CoA, contributes to diabetes development (46, 47). Altered cellular fatty acid utilization is important in insulin resistance and obesity. Because these acyl-CoAs are also vital intermediary metabolites in fatty acid metabolism, it is likely that dynamic changes of their levels in DIO mice, either locally or globally, may regulate histone lysine acylations, which in turn modulate transcription and contribute to pathophysiology. Our study offers additional lines of evidence on the possible links between cellular metabolism and epigenetic regulation through new histone acylations in the context of diabetes development.

Our studies identified 15 core histone marks for which a change of at least 1.5-fold was induced in DIO mice by label-free quantification and 6 core histone marks marks for which a change of at least 1.5-fold was induced in DIO mice by chemical stable isotope-labeling approach (Table I and Fig. 3B). These altered histone marks were quite diverse, including a new histone mark H3R49me1 that were down-regulated. We quantified the up-regulation of H3K36me2 in both label-free and stable isotope labeling quantification, and validated by Western blotting analysis in both DIO mouse liver tissues and primary hepatocytes. Methylation at H3K36 is associated with active chromatin and regulated by a variety of methyltransferases and demethylases (48). The histone H3K36 demethylase Jhdm1a has been reported to negatively regulate gluconeogenesis, an effect which is likely associated with histone H3K36 demethylation on the C/EBPα locus (11). Our study revealed an increase of H3K36me2 in DIO mouse liver. This result suggests that H3K36 hyper-dimethylation, rather than affecting only a few genes such as C/EBPα, likely has a wider impact on multiple genes in prediabetes. Interestingly, the increase of H3K36me2 can be reversed by metformin. Nevertheless, trimethylation of H3K36 was not identified in our mass spectrometry analysis. In the future, it would be worthwhile to investigate the interplay among mono-, di- and trimethylation of H3K36 in prediabetes development.

Metformin, a first-line oral drug for T2D, has shown great benefits for lowering blood glucose and ameliorating diabetes-related cardiovascular impairment. Metformin is suggested to inhibit hepatic gluconeogenesis via transcriptional regulation of gluconeogenic genes in an AMPK-dependent manner (12). In our study, both mass spectrometry (Fig. 5B-5C) and Western blotting analysis (Fig. 5D) showed that metformin can reduce the level of H3K36 dimethylation in a DIO mouse model. These results suggest that metformin could have an impact on histone H3K36 methylation that in turn contributes to transcriptional regulation. Previous studies showed that the gluconeogenesis-suppression activity of metformin is associated with histone acetylation regulatory enzymes such as CBP, SIRT1, and GCN5 (13, 14). Further biological studies are needed to characterize metformin-mediated epigenetic changes.

DATA AVAILABILITY

Supplementary Material

Supplemental Data

supp_16_7_1324__index.html^{(1.5KB, html)}

Footnotes

Author contributions: J.L., Y.Z., J.-Y.L., and M.T. designed research; L.N., L.S., M.Z., P.L., Z.X., S.J., and H.J. performed research; L.N., L.S., M.Z., P.L., Z.X., S.J., and H.J. contributed new reagents or analytic tools; L.N., L.S., and M.Z. analyzed data; L.N., L.S., M.Z., Jing-ya Li, and M.T. wrote the paper.

* This work was supported by the National Basic Research Program of China (973 Program) (Grant 2014CBA02004), the Natural Science Foundation of China (Grant 31370814), the Strategic Priority Research Program of the Chinese Academy of Sciences, “Personalized Medicines—Molecular Signature-based Drug Discovery and Development” (Grant XDA12020314), and the Shanghai Municipal Science and Technology Commission (Grant 14DZ2261100 and 15410723100) to M.T., and by the National Institute of Health (NIH) of the United States (GM105933 and CA160036) to Y.Z. This work was also supported by the National Basic Research Program of China Grant 2016YFC1305500, the Natural Science Foundation of China (Grant 81470166 and 81302820) to J.L.

This article contains supplemental materials.

¹ The abbreviations used are:

T2D: type 2 diabetes
PTM: post-translational modification
DIO: diet-induced obese
HDAC: histone deacetylase
FOXO: forkhead box O
UCP2: mitochondrial uncoupling protein 2
XIC: extracted ion chromatograms
AUC: area under the curve
CBP: CREB-binding protein
TORC2: transcription coactivator 2
DIO-Met: metformin-treated DIO
NH4HCO3: ammonium bicarbonate
KCl: potassium chloride
MgCl2: magnesium chloride
MCE: MedChemExpress
DIO-Veh: vehicle treated DIO mouse
PEPCK: phosphoenolpyruvate carboxykinase.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Data

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10.1074_M117.067553_mcp.M117.067553-1.pptx^{(126.1KB, pptx)}

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Data Availability Statement

[B1] 1. Federation I. D. (2014) IDF Diabetes Atlas update poster, 6th edn.

[B2] 2. Slomko H., Heo H. J., and Einstein F. H. (2012) Minireview: Epigenetics of obesity and diabetes in humans. Endocrinology 153, 1025–1030 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B3] 3. Raciti G. A., Nigro C., Longo M., Parrillo L., Miele C., Formisano P., and Beguinot F. (2014) Personalized medicine and type 2 diabetes: lesson from epigenetics. Epigenomics 6, 229–238 [DOI] [PubMed] [Google Scholar]

[B4] 4. Guarente L. (2006) Sirtuins as potential targets for metabolic syndrome. Nature 444, 868–874 [DOI] [PubMed] [Google Scholar]

[B5] 5. Karpac J., and Jasper H. (2011) Metabolic homeostasis: HDACs take center stage. Cell 145, 497–499 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B6] 6. Sabari B. R., Zhang D., Allis C. D., and Zhao Y. (2016) Metabolic regulation of gene expression through histone acylations. Nature reviews. Molecular cell biology 18, 90–101 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B7] 7. Gut P., and Verdin E. (2013) The nexus of chromatin regulation and intermediary metabolism. Nature 502, 489–498 [DOI] [PubMed] [Google Scholar]

[B8] 8. Canto C., and Auwerx J. (2012) Targeting sirtuin 1 to improve metabolism: all you need is NAD(+)? Pharmacol. Rev. 64, 166–187 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B9] 9. Murayama A., Ohmori K., Fujimura A., Minami H., Yasuzawa-Tanaka K., Kuroda T., Oie S., Daitoku H., Okuwaki M., Nagata K., Fukamizu A., Kimura K., Shimizu T., and Yanagisawa J. (2008) Epigenetic control of rDNA loci in response to intracellular energy status. Cell 133, 627–639 [DOI] [PubMed] [Google Scholar]

[B10] 10. Mihaylova M. M., Vasquez D. S., Ravnskjaer K., Denechaud P. D., Yu R. T., Alvarez J. G., Downes M., Evans R. M., Montminy M., and Shaw R. J. (2011) Class IIa histone deacetylases are hormone-activated regulators of FOXO and mammalian glucose homeostasis. Cell 145, 607–621 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B11] 11. Pan D., Mao C., Zou T., Yao A. Y., Cooper M. P., Boyartchuk V., and Wang Y. X. (2012) The histone demethylase Jhdm1a regulates hepatic gluconeogenesis. PLoS Genetics 8, e1002761. [DOI] [PMC free article] [PubMed] [Google Scholar]

[B12] 12. Foretz M., Guigas B., Bertrand L., Pollak M., and Viollet B. (2014) Metformin: from mechanisms of action to therapies. Cell Metab. 20, 953–966 [DOI] [PubMed] [Google Scholar]

[B13] 13. He L., Sabet A., Djedjos S., Miller R., Sun X., Hussain M. A., Radovick S., and Wondisford F. E. (2009) Metformin and insulin suppress hepatic gluconeogenesis through phosphorylation of CREB binding protein. Cell 137, 635–646 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B14] 14. Caton P. W., Nayuni N. K., Kieswich J., Khan N. Q., Yaqoob M. M., and Corder R. (2010) Metformin suppresses hepatic gluconeogenesis through induction of SIRT1 and GCN5. J. Endocrinol 205, 97–106 [DOI] [PubMed] [Google Scholar]

[B15] 15. Huang H., Sabari B. R., Garcia B. A., Allis C. D., and Zhao Y. (2014) SnapShot: histone modifications. Cell 159, 458–458 e451 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B16] 16. Sridharan R., Gonzales-Cope M., Chronis C., Bonora G., McKee R., Huang C., Patel S., Lopez D., Mishra N., Pellegrini M., Carey M., Garcia B. A., and Plath K. (2013) Proteomic and genomic approaches reveal critical functions of H3K9 methylation and heterochromatin protein-1gamma in reprogramming to pluripotency. Nat. Cell. Biol. 15, 872–882 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B17] 17. Jaffe J. D., Wang Y., Chan H. M., Zhang J., Huether R., Kryukov G. V., Bhang H. E., Taylor J. E., Hu M., Englund N. P., Yan F., Wang Z., Robert McDonald E. 3rd, Wei L., Ma J., Easton J., Yu Z., deBeaumount R., Gibaja V., Venkatesan K., Schlegel R., Sellers W. R., Keen N., Liu J., Caponigro G., Barretina J., Cooke V. G., Mullighan C., Carr S. A., Downing J. R., Garraway L. A., and Stegmeier F. (2013) Global chromatin profiling reveals NSD2 mutations in pediatric acute lymphoblastic leukemia. Nat. Genet. 45, 1386–1391 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B18] 18. Ruthenburg A. J., Allis C. D., and Wysocka J. (2007) Methylation of lysine 4 on histone H3: intricacy of writing and reading a single epigenetic mark. Mol. Cell 25, 15–30 [DOI] [PubMed] [Google Scholar]

[B19] 19. Lauberth S. M., Nakayama T., Wu X., Ferris A. L., Tang Z., Hughes S. H., and Roeder R. G. (2013) H3K4me3 interactions with TAF3 regulate preinitiation complex assembly and selective gene activation. Cell 152, 1021–1036 [DOI] [PMC free article] [PubMed] [Google Scholar]

[B20] 20. Nguyen A. T., and Zhang Y. (2011) The diverse functions of Dot1 and H3K79 methylation. Genes Develop. 25, 1345–1358 [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

The Landscape of Histone Modifications in a High-Fat Diet-Induced Obese (DIO) Mouse Model*

Litong Nie

Lin Shuai

Mingrui Zhu

Ping Liu

Zhi-Fu Xie

Shangwen Jiang

Hao-Wen Jiang

Jia Li

Yingming Zhao

Jing-Ya Li

Minjia Tan