Global Profiling of Protein Lysine Malonylation in Escherichia coli

May 16, 2016 - In prokaryotes, little is known about the global substrates and potential biological functions of lysine malonylation. Only three Kmal ...
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Global Profiling of Protein Lysine Malonylation in Escherichia coli Reveals Its Role in Energy Metabolism Lili Qian,†,‡,∥ Litong Nie,†,‡,∥ Ming Chen,†,‡ Ping Liu,†,‡ Jun Zhu,# Linhui Zhai,†,‡ Sheng-ce Tao,⊥ Zhongyi Cheng,# Yingming Zhao,†,‡,§ and Minjia Tan*,†,‡

J. Proteome Res. 2016.15:2060-2071. Downloaded from pubs.acs.org by OPEN UNIV OF HONG KONG on 01/23/19. For personal use only.

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The Chemical Proteomics Center and State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, PR China ‡ University of Chinese Academy of Sciences, Beijing 100049, PR China # Jingjie PTM BioLab (Hangzhou) Co. Ltd, Hangzhou 310018, PR China ⊥ Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200240, PR China § Ben May Department for Cancer Research, University of Chicago, Chicago, Illinois 60637, United States S Supporting Information *

ABSTRACT: Protein lysine malonylation is a recently identified post-translational modification (PTM), which is evolutionarily conserved from bacteria to mammals. Although analysis of lysine malonylome in mammalians suggested that this modification was related to energy metabolism, the substrates and biological roles of malonylation in prokaryotes are still poorly understood. In this study, we performed qualitative and quantitative analyses to globally identify lysine malonylation substrates in Escherichia coli. We identified 1745 malonylation sites in 594 proteins in E. coli, representing the first and largest malonylome data set in prokaryotes up to date. Bioinformatic analyses showed that lysine malonylation was significantly enriched in protein translation, energy metabolism pathways and fatty acid biosynthesis, implying the potential roles of protein malonylation in bacterial physiology. Quantitative proteomics by fatty acid synthase inhibition in both auxotrophic and prototrophic E. coli strains revealed that lysine malonylation is closely associated with E. coli fatty acid metabolism. Protein structural analysis and mutagenesis experiment suggested malonylation could impact enzymatic activity of citrate synthase, a key enzyme in citric acid (TCA) cycle. Further comparative analysis among lysine malonylome, succinylome and acetylome data showed that these three modifications could participate in some similar enriched metabolism pathways, but they could also possibly play distinct roles such as in fatty acid synthesis. These data expanded our knowledge of lysine malonylation in prokaryotes, providing a resource for functional study of lysine malonylation in bacteria. KEYWORDS: lysine malonylation, Escherichia coli, affinity enrichment, mass spectrometry, protein post-translational modification (PTM), energy metabolism

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INTRODUCTION Lysine acetylation is an important post-translational modification (PTM) in bacteria, which is closely related to various physiological processes, such as DNA binding, transcription and energy metabolism.1−5 More and more recent studies showed that lysine can be subjected to diverse acylation modifications beyond acetylation, such as propionylation, butyrylation, succinylation, crotonylation, malonylation, glutarylation and 2-hydroxyisobutyrylation.6−12 Among them, lysine malonylation (Kmal) is one of the novel lysine acylations recently reported by us and others.6,12 This modification utilizes malonyl-CoA as its cofactor, and was demonstrated to exist widely in different species from prokaryotes to eukaryotes. In contrast to acetylation’s uncharged status under physio© 2016 American Chemical Society

logical condition, malonylated lysine has a negative charge due to the existence of a carboxylic group (Figure 1A), suggesting that lysine malonylation may have distinct impacts on protein functions.13 Up to date, most studies on lysine malonylation were performed in mammalian systems. Thousands of malonylated lysine sites have been identified from cultured mammalian cells and mouse tissues.6,12,14−16 We and others also demonstrated that SIRT5, a member of the class III lysine deacetylases, is a regulatory enzyme for lysine desuccinylation, demalonylation and deglutarylation.6,10,12 Our recent quantitative lysine Received: March 29, 2016 Published: May 16, 2016 2060

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Figure 1. Lysine malonylation and malonyl-CoA. (A) The structures of acetyllysine and malonyllysine. (B) Schematic of fatty acid synthesis in E. coli. (C) Western blotting analysis of the malonyllysine level in whole cell lysate extracted from E. coli K12 DH10B. Coomassie blue staining was used as a reference. WCL, whole cell lysate.

malonylation analysis in human fibroblast cells identified 4943 Kmal sites in 1822 proteins in total.15 Further biochemical experiments showed that this modification had impact on mitochondrial function and fatty acid oxidation.15 In another study on wild-type and Sirt5−/− mouse liver, more than 1000 malonyllysine sites were identified.16 This study also revealed a role of lysine malonylation in energetic flux regulation via glycolysis. In addition, malonylation also contributes to pathophysiology in mammalian system. Our study revealed that lysine malonylation was associated with malonic aciduria, an inherited metabolic disorder caused by malonyl-CoA decarboxylase deficiency.15 Another recent study showed lysine malonylation level was elevated in db/db mice and ob/ob mice, two typical type 2 diabetes (T2D) mouse models, implying that lysine malonylation was related to T2D development.14 In prokaryotes, little is known about the global substrates and potential biological functions of lysine malonylation. Only three Kmal sites from three proteins (glycerol kinase, fructosebisphosphate aldolase class II and glyceraldehyde-3-phosphate dehydrogenase A) were reported in E. coli in our previous study.6 The limited information on lysine malonylome hinders our understanding of its molecular functions and biological roles in bacteria. Therefore, a global profiling of lysine malonylome in the classical prokaryotic model organism Escherichia coli will give us important insight on the role of malonylation in bacteria. Our previous study showed that malonylation of lysine residue relies on the existence of malonyl-CoA,6 a high-energy cofactor important for fatty acid biosynthesis. In E. coli, malonyl-CoA serves as both the precursor of malonyl-acyl carrier protein (malonyl-ACP) for synthesis initiation and the two-carbon unit donor for fatty acid elongation via 3-oxoacyl-

[acyl-carrier-protein] synthase II (fabF) catalysis (Figure 1B). These lines of evidence suggest that lysine malonylation is likely linked to fatty acid metabolism in bacteria. However, current limited knowledge of lysine malonylation substrates in E. coli impedes our understanding of the role of lysine malonylation in fatty acid synthesis. With the recent development of high-resolution mass spectrometer and high-quality pan antiacyl-lysine antibody, proteome wide in-depth mapping substrates of a certain lysine modification was possible.2,15,17,18 By integrating high-pH HPLC fractionation, antibody-based affinity enrichment and nano-HPLC−MS/MS analysis, we identified more than 4000 Kmal sites in both mouse and human samples,15 representing the largest malonylome in mammal samples in a single experiment up to date. In this study, we performed our global lysine malonylation substrate profiling in E. coli using this workflow. Our study identified 1745 malonylation sites in 594 corresponding malonylated proteins from E. coli. Bioinformatic analyses demonstrated that lysine malonylation was significantly enriched in bacterial protein translation and energy metabolism pathways. We also showed that malonylation levels of predominant substrates were increased after fatty acid synthase inhibition, and lysine malonylation is likely to have an impact on the activity of metabolic enzymes. This study expanded the scope of malonylated substrates in E. coli, and revealed its biological roles in bacterial energy metabolism. 2061

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EXPERIMENTAL SECTION

was subjected to a 4-fold dilution with 50 mM NH4HCO3 (pH 8.0) and then sequencing grade trypsin was added at a trypsinto-protein ratio of 1:50 (w/w) for digestion at 37 °C for 16 h. Trypsin was then added at trypsin-to-protein ratio of 1:100 (w/ w) at 37 °C for another 4 h to complete the digestion cycle. The tryptic peptides were desalted through SepPak C18 cartridges (Waters, Milford, MA) and vacuum-dried before fractionation.

Reagent and Materials

E. coli strain DH10B was purchased from Invitrogen Life Technologies (Carlsbad, CA); strain AT713 and strain BW25113 were obtained from the Coli Genetic Stock Center (New Haven, CT). Modified sequencing grade trypsin was purchased from Promega (Madison, WI); pure water and acetonitrile from Burdick and Jackson (Meskegon, MI). Cerulenin was purchased from J&K (Beijing, China). Pan antimalonyllysine antibody beaded agarose was purchased from PTM Biolabs (Hangzhou, China). Other chemicals were obtained from Sigma-Aldrich: trifluoroacetic acid (TFA, 99%), formic acid (FA, 98%), ammonium bicarbonate (NH4HCO 3, 99%), iodoacetamide (IAA), dithiothreitol (DTT), Tris-HCl, NaCl (ACS grade), MeOH (ACS grade), acetone (ACS grade).

HPLC Fractionation

Tryptic peptides (30 mg) were fractionated by high pH reversephase HPLC using Waters XBridge Prep C18 column (5 μm particles, 19 × 150 mm). Peptides were separated with a gradient of 2% to 60% acetonitrile in 10 mM ammonium bicarbonate (pH 8.5) in 80 min. The peptides were then combined into 10 fractions and vacuum-dried for further affinity enrichment. Affinity Enrichment of Kmal Peptides

E. coli Culture and Protein Extraction

To enrich lysine malonylated peptides, fractionated peptides were dissolved in NETN buffer (100 mM NaCl, 1 mM EDTA, 50 mM Tris-HCl, 0.5% NP-40, pH 8.0) and incubated with 10 μL drained prewashed antibody beads (PTM Biolabs) at 4 °C overnight with gentle shaking. The beads were gently washed four times with NETN buffer and twice with ddH2O. The bound peptides were eluted from the beads with 0.2% TFA and vacuum-dried. The eluted peptides were desalted with C18 ZipTips (Millipore, Billerica, MA) according to the manufacturer’s instructions.

E. coli strain DH10B was cultured in LB medium at 37 °C and then collected at the exponential phase. For SILAC labeling, biological replicate was performed in both E. coli auxotrophic strain AT713 and prototrophic strain BW25113. E. coli strain AT713 was inoculated in M9 medium (M9 salt medium supplemented with 20 amino acids at 100 mg/L, except for four amino acids (proline, phenylalanine, histidine and tyrosine) at 200 mg/L) and cultured at 37 °C overnight. Equal amount of activated E. coli was inoculated into “light” medium (M9 medium containing 12C614N2 Lysine and 12C614N4 Arginine) and “heavy” medium (M9 medium containing 13C614N2 Lysine and 13C615N4 Arginine), respectively. When OD600 reached 0.8, “heavy” E. coli cells were treated with 100 μM cerulenin (dissolved in ethanol) for another 2 h at 37 °C while “light” E. coli was treated with equal volume of ethanol (0.5‰ of the culture medium) as control. When isotopic labeling wild-type E. coli strain BW25113, cells were first activated in LB medium and equal amount of activated cells were cultured in “light” and “heavy” M9 medium overnight at 37 °C, respectively. The next day, cells were inoculated into corresponding medium to OD600 = 0.005 and cultured to approximately OD600 = 0.8. “Light” E. coli was treated with 200 μM cerulenin (dissolved in ethanol) for another 2 h at 37 °C while “heavy” E. coli was treated with equal volume of ethanol before collection. Cells were washed with cold PBS twice before lysis. The pellet was resuspended in the lysis buffer (8 M Urea in 50 mM NH4HCO3, pH 8.0, containing protease inhibitor cocktail) and sonicated for 5 min. After incubation on ice for 30 min, the lysate was sonicated again in order to disrupt the DNA clump. After centrifugation at 21,130 g at 4 °C for 10 min, the supernatant was transferred to a new tube and quantified by BCA protein assay kit (Beyotime Biotechnology, China). Equal amount of both “heavy” and “light” protein lysates were combined together for further experiment. The labeling efficiency of E. coli cultured in “heavy” medium was checked prior to the sequential proteomic experiments.

HPLC−MS/MS Analysis

Enriched Kmal peptides were dissolved in solvent A (0.1% FA in 2% ACN) and directly loaded onto a homemade reversedphase precolumn (75 μm ID × 4 cm length, 5 μm particle size). Peptide separation was performed using a homemade reversephase C18 analytical column (75 μm ID × 16 cm length, 3 μm particle size) with a linear gradient of 5−35% solvent B (0.1% FA in 98% ACN) for 30 min and 35−80% solvent B for 10 min at a constant flow rate of 300 nL/min on an EASY-nLC 1000 system. The eluted peptides were ionized and introduced to a Q Exactive (Thermo Fisher Scientific, Waltham, MA) using NSI source. Intact peptides with m/z 350−1600 were detected in the Orbitrap at a resolution of 70 000 at m/z 200. The 16 most intense ions above 2 × 104 were isolated and sequentially fragmentized by Higher Collision Dissociation (HCD) with normalized collision energy of 28%, then ion fragments were detected in the Orbitrap at a resolution of 17 500 at m/z 200. The dynamic exclusion duration was set as 30 s, and the isolation window was 2 m/z. Automatic gain control (AGC) was used to prevent overfilling of the ion trap. Database Search

All the acquired MS/MS data files (.raw) were processed with MaxQuant (version 1.4.1.2) based on Andromeda search engine. Escherichia coli (strain K12) database from Uniprot (proteome ID: UP000000625, 4306 sequences, last modified on Jul 30th, 2015) with a reversed decoy database was used for data processing. For SILAC labeling samples, Lys6 and Arg10 were set as “Heavy labels”. Trypsin/P was chosen as the digestion enzyme and two maximum missing cleavages was allowed. Precursor error tolerance was ±10 ppm with fragment ion ±0.02 Da. Carbamidomethyl (C) was specified as the fixed modification and variable modifications were oxidation (M), acetylation (Protein N-term) and malonylation (K). False discovery rates (FDR) at protein, peptide and modification

In-Solution Trypsin Digestion

Reduction and alkylation reaction was performed before trypsin digestion. Dithiothreitol was added to the protein solution to a final concentration of 5 mM and then the lysate was incubated at 56 °C for 30 min, followed by incubation with 15 mM iodoacetamide at room temperature in the darkness for 30 min. The alkylation reaction was quenched with 30 mM cysteine at room temperature for another 30 min. The protein solution 2062

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Figure 2. Lysine malonylation was broad and dynamic in Escherichia coli. (A) The integrated workflow for large-scale profiling of lysine malonylation in E. coli. (B) Western blotting analysis of the malonyllysine level in protein lysates from IPTG-induced FabF overexpression and wild-type. Coomassie blue staining was used as the loading control. (C) Western blotting analysis of the malonyllysine level in E. coli lysates treated with cerulenin or not. Coomassie blue staining was used as the loading control.

INTERPRO database.20 P values were adjusted with a Benjamini-Hochberg FDR.

level were all set as 1%. All the lysine malonylation modification sites were filtered with localization probability over 0.75. Neutral loss of CO2 in MS/MS spectrum were specified for Kmal peptide identification. Identified lysine malonylated peptides with MaxQuant Andromeda score below than 50 were filtered prior to bioinformatic analysis. For quantitative analysis, the normalized H/L ratio of each modified peptide exported by MaxQuant software was corrected at the protein level to eliminate the protein abundance difference.

Flanking Sequence Analysis

The iceLogo (version 1.2) was used to analyze the preference of the flanking sequence of Kmal sites.21 Peptides containing the Kmal sites in the central site, together with ten neighboring amino acid residues on both sides (21 amino acids in total) were selected as the positive set for analysis. Meanwhile, the embedded Swiss-Prot “Escherichia coli” data set was used as the negative set. P value was set as 0.05.

Data Accession

Raw data together with the files exported by MaxQuant software were available on the integrated Proteome resources (iProx) (URL: http://www.iprox.org/index) with project ID: IPX00074200.

Protein−Protein Interaction Network Analysis

We utilized Cytoscape (version 3.3.0) software based on STRING database (version 10) to analyze protein−protein interactions of the identified malonylated proteins.22,23 Interactions with the confidence score exported from STRING higher than or equal to 0.7 were picked out for Cytoscape analysis. Molecular Complex Detection (MCODE), a plugin of Cytoscape, was further utilized to analyze highly connected regions.24 Analysis result was visualized in Cytoscape.

Functional Annotation Based on DAVID

Enrichment analysis including Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and domain annotation was performed using DAVID 6.7 (The Database for Annotation, Visualization and Integrated Discovery) tools with the total Escherichia coli genome information as the background.19 For Gene Ontology annotation, biological process, molecular function and cellular compartment categories were analyzed on the basis of GO FAT database. Domain annotation was performed by using

Western Blot

Protein lysate was separated by 10% SDS-PAGE and then transferred to the nitrocellulose membrane. After blocking with 5% BSA in PBST (phosphate buffered saline containing 0.1% Tween-80) at room temperature for 1 h, the membrane was 2063

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Figure 3. Dynamics of the E. coli malonylome in response to fatty acid synthase inhibitor cerulenin. (A) Scatter plot of the quantifiable malonylated sites identified in AT713 strain. Log2 of the correctedized H/L ratios of the quantifiable sites were used for X axis and log10 of summed intensities (heavy plus light) for each peptide for Y axis. Orange dots represent the sites of corrected H/L ratio beween 0.5 and 2; blue dots represent the sites of corrected H/L ratio higher than 2. (B) Venn diagram of the identified malonylated sites in auxotrophic E. coli strain AT713 and protophic strain BW25113. (C) Scatter plot of the Kmal sites identified in both quantitative malonylome analyses. Log2 of the corrected H/L ratio in AT713 strain and BW25113 strain was used as the values for x axis and y axis, respectively.

was removed after centrifugation at 4 °C at 12 000g for 15 min. Expressed proteins were purified by Ni-NTA agarose (QIAGEN, Germany) from the supernatant. Enzymatic activity was evaluated by photometrical citrate synthase activity assay.25 Briefly, equal amounts of both wild-type and mutated GltA proteins (K310E or K295E) were subjected to the detection system containing 50 mM Tris (pH 7.5), 200 mM potassium glutamate, 0.1 mM 5,5′-dithiobis (2-nitrobenzoic acid) (DTNB), 0.15 mM acetyl-CoA and 0.2 mM oxaloacetate. Absorbance at 412 nm at 25 °C was read by microplate reader and relative enzyme activity was then calculated. Triplicate for each protein were performed.

incubated with pan antiacetyllysine (Kac), pan antimalonyllysine (Kmal) or pan antisuccinyllysine (Ksucc) antibody at 4 °C overnight. The membranes were washed with PBST and then incubated with diluted HRP conjugated secondary antibody for 1 h at room temperature with gentle shaking. The blot was imaged via ImageQuant LAS 4000 system (GE Healthcare, UK) after chemiluminescent HRP substrate treatment (Immobilon Western, Millipore, Germany). Protein Mutagenesis and Enzymatic Activity Evaluation

The wild-type citrate synthase (gltA) gene was PCR-amplified from E. coli BW25113 and cloned into the pET-28a(+) vector using the Hind III and EcoRI restriction sites. The mutant K310E and K295E were introduced into the same vector by a QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA), respectively, followed by DNA sequencing for confirmation. The wild-type and two mutated GltA plasmids were transformed into E. coli BL21 (DE3) cells and selected on LB plates containing kanamycin (50 mg/L). Single colony was selected and grown at 37 °C to OD600 at about 0.8. Cells were cultured at 20 °C for another 6 h after 0.5 mM isopropyl-β-Dthiogalactoside (IPTG) treatment to induce the expression of target protein. Cells were harvested by centrifugation and washed in phosphate buffered saline buffer (PBS). The cells were resuspended in PBS and disrupted by sonication. Debris

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RESULTS

Lysine Malonylation Was Broad and Dynamic in Escherichia coli

To identify the lysine malonylome in E. coli, we first cultured wild-type E. coli strain DH10B in LB medium for a preliminary lysine malonylation substrate profiling. The cells were collected at the exponential phase. Western blotting analysis of the whole cell lysate using pan antimalonyllysine antibody showed that lysine malonylation widely existed in E. coli proteome (Figure 1C). Next, we carried out E. coli lysine malonylome profiling by peptide enrichment using specific antimalonyllysine pan2064

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Figure 4. Bioinformatics analysis of the malonylated proteins. (A) Pie chart of the distribution of lysine-malonylated sites per protein. (B) Flanking sequence analysis of the malonylated lysine sites. (C) Gene ontology analysis of malonylated proteins in biological process. (D) KEGG pathway analysis of lysine-malonylated proteins.

Dynamics of the E. coli Malonylome in Response to Fatty Acid Synthase Inhibitor Cerulenin

antibody and high-resolution Orbitrap mass spectrometry analysis as previously reported (Figure 2A).15 In this analysis, we identified 289 Kmal sites in 145 proteins in wild-type E. coli strain DH10B (Table S1A). To gain an initial scope of lysine malonylation in E. coli, we carried out a preliminary gene ontology analysis using DAVID bioinformatics tool. The analysis showed that malonylated proteins were involved in several metabolic pathways such as translation and TCA cycle (Table S2). In line with the study on lysine malonylation of mouse liver,16 glycolysis was also enriched in our preliminary malonylome data. Also importantly, we found that malonylated proteins were enriched in fatty acid metabolism, which was consistent with the role of the malonylation cofactor malonylCoA in energy metabolism. These results led us to further investigate the potential role of lysine malonylation substrates in bacterial fatty acid biosynthesis. On the basis of the fact that overexpression of protein FabF in E. coli led to the accumulation of malonyl-CoA,26 we carried out Western blotting analysis of lysine malonylation level in FabF overexpressed E. coli strain. The result showed that malonylation signals were significantly increased in FabF overexpressed E. coli whole cell lysate as compared with those of wild-type sample (Figure 2B). In consistency, when we treated E. coli cells with cerulenin, an antibiotic with the function of fatty acid synthesis inhibition and consequent malonyl-CoA accumulation,27,28 a higher level of malonylated lysine signals could be detected (Figure 2C). These results suggested that dysregulation of fatty acid biosynthesis was closely related to lysine malonylation.

To further investigate the relation between lysine malonylation and fatty acid biosynthesis, we performed a quantitative lysine malonylome analysis by SILAC based approach in auxotrophic E. coli strain AT713 (which is incapable of lysine and arginine self-biosynthesis) with or without cerulenin treatment. E. coli cells cultured in “heavy” medium were treated with cerulenin for 2 h before collection, whereas E. coli cells cultured in “light” medium were treated with equal volume of solvent as control. We then used the similar peptide affinity enrichment workflow for lysine malonylome identification and quantification. In this experiment, we identified 487 lysine malonylation sites in 275 proteins (Table S1B). Among them, 463 modification sites were quantifiable by MaxQuant software. We corrected the normalized H/L ratio for each Kmal peptide at the protein level prior to the quantitative analysis in order to eliminate protein abundance difference. The SILAC ratio distribution of these quantifiable sites was shown in Figure 3A. The average SILAC ratio was 17.31 and the ratios of 420 sites (90.7%, blue dots) were higher than 2 (Figure 3A and Table S1B), further indicating that inhibition of fatty acid synthesis had a significant impact on lysine malonylation. The top upregulated malonylation substrates were mainly related to carbohydrate metabolism and pyruvate metabolism processes, including phosphate acetyltransferase (pta) (Lys115 with a corrected H/L ratio of 97.12, belonging to the region important for proper quaternary structure), pyruvate kinase II (pykA) (Lys351 with a corrected H/L ratio of 83.40) and glyceraldehyde-3-phosphate dehydrogenase A (gapA) (Lys124 2065

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Journal of Proteome Research Gene Ontology Annotation of Lysine Malonylome

with a corrected H/L ratio of 77.33, close to NAD binding sites). As E. coli strain AT713 is an auxotrophic mutant strain deficient for argA and lysA genes, such deficiency is likely to have more or less impact on cellular pathways and bacterial physiology compared to wild-type strain. To further validate our quantification results, we used prototrophic E. coli strain BW25113 to perform another quantitative malonylome analysis based on a modified SILAC approach as previously reported,29,30 also as a biological replicate. The “light” E. coli cells were treated with 200 μM cerulenin for 2 h before collection. Ninety-five percent SILAC labeling efficiency was achieved. In this analysis, we identified 1927 Kmal sites in 651 proteins in total, 1740 of which were quantifiable (Table S1C). Similar to AT713 strain, 1381 sites (71.7%) were upregulated by 2 fold or more (corrected H/L ratio lower than 0.5) after cerulenin treatment. 314 Kmal sites overlapped with those identified in AT713 strain (65.5% of all Kmal sites in AT713 strain) (Figure 3B). These sites showed a similar tendency after cerulenin treatment (coefficient of determination was 0.70) (Figure 3C), suggesting lysine malonylation is closely associated with fatty acid biosynthesis in both prototrophic and auxotrophic E. coli strain.

To further understand the functional insight of malonylation, we carried out enrichment analysis to classify all the malonylated protein groups based on Gene Ontology (GO) annotation database (Table S3). The GO-based functional enrichment analysis of cellular component showed that the malonylated proteins in E. coli were significantly enriched in cytosol (adjusted P = 1.42 × 10−88) and ribosome (adjusted P = 1.03 × 10−66) (Figure S2A, Table S3A). The enrichment analysis of GO biological processes related to malonylated proteins revealed that these modified proteins were involved in a variety of processes including translation (adjusted P = 5.57 × 10−78), tricarboxylic acid cycle (adjusted P = 3.28 × 10−8) and glucose metabolic process (Figure 4C, Table S3B). In particular, fatty acid biosynthetic process was enriched (adjusted P = 2.81 × 10−4), which was consistent with our Western blot (Figure 2B, 2C) and quantitative malonylome analysis data (Table S1). Molecular function annotation using GO databases showed that malonylated proteins were significantly enriched in structure constituent of ribosome and RNA binding, suggesting a role of protein malonylation in bacterial protein synthesis (Figure S2B, Table S3C). Additionally, dozens of malonylated substrates were classified as proteins with the function of nucleotide binding. To further characterize whether there is any protein functional domain specifically associated with malonylation, we carried out enrichment analysis using INTERPRO database, which is an integrated database for protein domain prediction (Figure S2C, Table S3D).20 The enriched domains are mainly associated with nucleic acid binding and aminoacyl-tRNA synthetase. These functional annotation analyses demonstrated that malonylated proteins execute different functions and participate in different biological processes in E. coli.

Characterization of the Lysine Malonylome in Escherichia coli

To ensure the confident identification of E. coli lysine malonylation substrates for subsequent bioinformatic analysis, we removed the identified Kmal peptides with Andromeda score below 50, which is a strict criterion for global PTM substrate analysis that we used before.15 In addition, we manually verified the MS/MS spectra of Kmal peptides based on the characteristic neutral loss of CO2 in MS/MS fragmentation for Kmal peptide (typical spectra were shown in Figure S1), as well as other stringent criteria for peptide identification that we previously reported.6,31 We also removed those Kmal sites only identified from cerulenin treated sample to ensure that all Kmal sites in our final data set existed in normal cellular conditions. Using these criteria, we obtained a combined Kmal data set including 1745 malonylation sites in 594 corresponding malonylated proteins in E. coli as listed in Table S1D. To our knowledge, this is the first and largest bacterial malonylome data set up to date. Among these malonylated proteins, 262 proteins (44.1%) contain a single Kmal site, 113 proteins (19.0%) contain two Kmal sites, and the rest contain three or more Kmal sites (Figure 4A). We found that formate acetyltransferase 1 (pflB, also known as pyruvate formate-lyase 1) was the highest malonylated protein with 34 malonylation sites identified. Enolase (eno) was also highly malonylated with 18 modified sites. To check whether there was any particular amino acid bias adjacent to Kmal sites and to assess the sequence preference for malonylation, we analyzed the flanking sequences of Kmal sites by iceLogo software.21 The result revealed a strong bias for particular amino acids (Figure 4B). Notably, glycine was overrepresented at −1 position and alanine at +1 position, which is similar to the pattern of lysine malonylation regulated by SIRT5 in mouse liver.15 Also, alanine was over-represented close to the malonylated lysine. In addition, glutamic acid showed relatively high abundance adjacent to malonylated lysine, slightly similar to the patterns of lysine acetylation and succinylation.17,32

KEGG Pathway Analysis of Lysine Malonylome

We further investigated the metabolic pathways in which lysine malonylation was likely to be involved using KEGG database. Our result showed that malonylation was closely related to multiple metabolic pathways (Figure 4D, details in Table S3E) including ribosome, pyruvate metabolism, TCA cycle and glycolysis, which is similar to previous reports on lysine acetylation and succinylation.4,17 Ribosome is the most significantly enriched pathway, which was consistent with GO annotation, further implying a potential role of lysine malonylation in protein synthesis. In addition, 19 malonylated proteins, including isocitrate dehydrogenase (icd) and citrate synthase (gltA), were associated with Tricarboxylic acid (TCA) cycle, the key metabolic pathway for carbohydrate, fat and protein metabolism (Table S3E). Among these enzymes, 17 and 16 were also reported to be acetylated and succinylated, respectively.4,17 Interestingly, we found that some of these proteins were pretty highly malonylated. For example, dihydrolipoyl dehydrogenase (lpdA, a subunit of pyruvate dehydrogenase) contained 15 malonylated lysine residues. We identified that Lys54 residue of this protein could be malonylated, which was reported to be one of the binding sites of flavin adenine dinucleotide. These results suggested that lysine malonylation may potentially regulate the functions of some metabolic proteins and thus impact TCA cycle. 2066

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Figure 5. Protein−protein interaction network of lysine malonylome. The top four clusters of highly interconnected lysine-malonylated protein networks. Interaction network of lysine-malonylated proteins were listed in gene names, based on STRING database. (A) Cluster 1: MCODE score = 62.597, nodes = 68, edges = 2097. (B) Cluster 2: MCODE score = 10, nodes = 29, edges = 140. (C) Cluster 3: MCODE score = 8.81, nodes = 43, edges = 185. (D) Cluster 4: MCODE score = 6.25, nodes = 17, edges = 50. The detailed cluster information was listed in Supplemental Table S4.

Protein−Protein Interaction Network Analysis of Lysine Malonylome

Importantly, in line with our quantitative malonylome analysis result, fatty acid biosynthesis pathway was enriched in KEGG pathway analysis. Malonylated protein AccA, AccC and AccD belong to the acetyl-CoA carboxylase complex, which converts acetyl-CoA into malonyl-CoA. Also, malonylation residues Lys201 and Lys205 of protein FabI, a key enzyme catalyzing fatty acid elongation, are involved in its acyl-ACP binding activity. Our quantitative malonylome analysis further showed that malonylation level of these two sites could be increased by fatty acid synthase inhibition, suggesting malonylation was likely to have an impact on the activity of this enzyme in fatty acid biosynthesis. Similarly, three lysine malonylation sites (Lys184, Lys206 and Lys286) were identified in malonyl CoA-acyl carrier protein transacylase (fabD). This enzyme transfers a malonyl group from malonylCoA to an acyl carrier protein and thus forms malonyl-ACP. These results leading to a possible hypothesis that lysine malonylation can regulate the function of enzymes involved in fatty acid biosynthesis. Taken together, malonylated proteins were found to be involved in a variety of important cellular pathways, and several lysine malonylation sites could be important for the protein substrate activities, implying that malonylation may modulate the biological functions of these proteins.

To better understand the function and regulation of lysine malonylation in cellular physiology, we analyzed protein− protein interaction networks of the malonylated proteins using the Cytoscape software on the basis of the STRING database.22,23 Parameters used in this analysis were listed in Table S4. Our data set showed a vast and densely connected network, in which 555 malonylated proteins were identified as nodes and connected by 5820 identified direct physical interactions. A complete network of malonylated proteins was created (Figure S3). Figure 5 offers an insight into the top four interaction clusters of malonylated proteins in E. coli (Figure 5A−5D). Our data demonstrated that malonylated proteins were enriched in a variety of cellular physiology related interaction networks. Unsurprisingly, the most highly enriched cluster consisted of 68 ribosome-associated proteins with 2097 edges (Figure 5A), which were mainly RNA polymerases, elongation factor proteins, 30S ribosome and 50S ribosome protein subunit components (Table S4). Seventeen and 16 Kmal sites were identified in elongation factor G (f usA) and elongation factor Tu 1 (tufA), which represented the two most highly 2067

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Figure 6. Amino acid mutation of citrate synthase. (A) Sequence alignment of citrate synthase in E. coli, yeast, mouse and human. The sequences surrounding Lys310 were presented. (B) Crystal structure of citrate synthase in E. coli (MMDB ID: 115266, partial). Lys310, Lys295 and two active sites (His306 and Asp363) were highlighted. (C) Relative enzyme activity of wild-type and K310E mutated citrate synthase (*: p < 0.05).

Figure 7. The comparison of lysine malonylome with succinylome and acetylome. (A) Venn diagram showed the overlaps among the lysine malonylated, acetylated and succinylated sites. (B) Western blotting analysis of the acetyllysine level and succinyllysine level in E. coli lysates with or withour cerulenin treatment. Coomassie blue staining was used as the loading control.

malonylated proteins in this top cluster and suggested the potential role of malonylation in protein biosynthesis. Transfer RNA aminoacylation related proteins constituted the second highest enriched cluster (Figure 5B). For example, C-terminal coiled-coil domain is critical for the aminoacylation activity of valine-tRNA ligase (valS) and we identified three malonylated residues within this domain. The next two highly interconnected clusters were involved in glucose catabolic process and tricarboxylic acid cycle (Figure 5C, 5D), suggesting lysine malonylation could participate in the regulation of energy metabolism.

protein were identified in our study: Lys283, Lys295, Lys310, Lys328 and Lys422. Sequence alignment analysis of citrate synthase in four different species from bacteria to human showed that although these five sites were not completely conserved, the regions surrounded Lys310 (GXGHXVXK310XXDPR, X represents different amino acids at this site) were highly conserved (Figure 6A, S4). Also, threedimensional structural analysis (MMDB ID: 115266) showed that Lys310 is close to its key catalytic active site His306 (Figure 6B), suggesting that malonylation at Lys310 could potentially impact the catalytic activity of citrate synthase. We next mutated the site Lys310 into glutamate, which structurally mimicked lysine malonylation with a negative charge at physiological condition, to investigate the potential impact of malonylation on its enzymatic activity. The purities of the mutant protein and its wild-type counterpart were both over 95% as shown in Figure S5A. Photometrical activity assay showed a significant decrease of enzymatic activity on the K310E mutated citrated synthase (Figure 6C). Similarly, when we mutated Lys295, another malonylated residue spatially close to the active site Asp363, into glutamate, the activity of the K295E mutated citrate synthase significantly decreased (Figure

Malonylation Potentially Impacts the Activity of Citrate Synthase

Our bioinformatic analyses showed that lysine malonylation not only participated in fatty acid synthesis, but also in multiple metabolic pathways including tricarboxylic acid cycle (Figure 4C, 4D). To further investigate possible functional consequence of lysine malonylation in metabolism-related proteins, we examined a rate limiting enzyme in TCA cycle, citrate synthase (gltA), which catalyzes the synthesis of citrate from oxaloacetate and acetyl-CoA. Five malonylated sites in this 2068

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malonylome profiling in auxotrophic strain AT713, which led to the identification of 463 quantifiable sites in response to fatty acid synthase inhibition. Due to the mutations in lysine and arginine synthases, the proteome and the post-translational modification level in auxotrophic strain is possibly to some extent different from those of the wild-type strain. To overcome this drawback, two groups recently reported a modified SILAC approach for efficient isotopic amino acid labeling in the wildtype E. coli strains.29,30 Therefore, by adopting this modified SILAC approach, we performed another quantitative malonylome analysis on the wild-type E. coli strain BW25113. In this analysis, we identified 1,927 Kmal sites in 651 proteins in total, 1740 sites of which were quantifiable. The number of Kmal sites increased to a large extent in this approach when compared with the analysis in the auxotrophic strain alone. Of particular note, the cofactor of lysine malonylation malonyl-CoA is also a vital building block for fatty acid biosynthesis, which suggests the potential role of malonylation in fatty acid metabolism. Both our Western blot and quantitative malonylome analysis using fatty acid synthase inhibitor cerulenin treatment revealed the close linkage between lysine malonylation and fatty acid biosynthesis in E. coli. Fatty acid synthase inhibition could have a profound impact on the malonylome of E. coli. More than 80% of the identified malonylated sites increased by over 2-fold with cerulenin treatment in both auxotrophic AT713 strain and prototrophic BW25113 strain. In our analysis, we identified 11 enzymes in fatty acid synthesis pathway that can be malonylated. An obvious increase of malonylation level could be observed on several lysine residues of these enzymes, such as Lys201 and Lys205 in protein FabI and Lys286 in protein FabD. It is likely that the change of malonyl-CoA level in fatty acid biosynthesis will lead to malonylation of these enzymes, which in turn will have an impact on the activities of these enzymes themselves. Similar to the key enzymes in fatty acid synthase pathway, we also identified dynamic changes of lysine malonylation level in enzymes involved in citric acid cycle. In total, we identified 129 malonylated lysine residues in 19 proteins related to citric acid cycle. Among them, five lysine residues of citrate synthase, a rate limiting enzyme in TCA cycle, can be malonylated. Of these Kmal sites, our data showed that the malonylated levels of Lys310 and Lys295 increased by more than 7-fold by fatty acid synthesis inhibition. The mutagenesis experiment on these two lysine residues into glutamate (K310E and K295E) suggested malonylation was likely to potentially inhibit the enzymatic activity of citrate synthase. This data further suggested that lysine malonylation could play an important role in protein functional regulation. Interestingly, we identified tens of malonylated proteins that were involved in coenzyme metabolic process. Among them, some proteins directly interacts with acetyl-CoA or succinylCoA, such as AccA and SucC (Succinyl-CoA ligase [ADPforming] subunit beta). It is possible that due to lysine malonylation, the activities of these proteins are impacted, leading to the level change of other coenzymes. It is demonstrated that cerulenin could inhibit the function of fatty acid synthase in E. coli and lead to the accumulation of malonyl-CoA.27,28 From a chemical point of view, malonyl-CoA is more reactive than acetyl-CoA. Also, it was demonstrated that the physiologic pH and acyl-CoA concentrations could cause enzyme-independent protein acetylation and succinylation in vitro.33 Therefore, for our malonylome data set, we can

S5B). These results suggested that lysine malonylation was a potential way to regulate the activity of citrate synthase, which in turn is likely to affect TCA cycle in central metabolism. Comparison among Acetylome, Succinylome and Malonylome in E. coli

As malonyl group bears a similar carboxylic structure to succinyl group, we further compared our malonylome data set with lysine succinylome and acetylome data set in E. coli in our previous studies to investigate the similarities and differences between these lysine acylation modifications.17 It was found that 48.4% and 44.7% of the malonylation sites in E. coli can also be succinylated and acetylated, respectively (Figure 7A). These three kinds of modifications are highly overlapping in several proteins, which were mainly involved in translation and glucose metabolic processes. For example, 34 lysine malonylation sites were identified in PflB, and also 24 succinylated sites and 17 acetylated sites in this protein were reported previously. Among them, 13 sites were able to be modified by all these three types of modifications. These lysine residues all belong to the pyruvate formate lyase (PFL) domain, catalyzing the formation of formate and acetyl-CoA from pyruvate and CoA. This analysis suggested that these three acylation modifications could possibly participate in some similar cellular pathways. On the other side, 714 Kmal sites (40.9%) were only identified in lysine malonylome data set, suggesting lysine malonylation could have distinct physiological roles from the other two modifications. Given that malonyl-CoA plays a unique role in fatty acid biosynthesis process, it was likely that roles of these modifications in fatty acid metabolism could be different. To test this hypothesis, we examined the dynamics of these modification in response to fatty acid synthase inhibitor cerulenin by Western blot. The results showed that lysine malonylation level increased drastically (Figure 2C), whereas there was no obvious change at the acetylation and succinylation level (Figure 7B), indicating that these three modifications had different responses to fatty acid synthesis inhibition. Also, in our previous study, both lysine acetylation and succinylation level significantly increased by glucose or pyruvate treatment as additional carbon sources,17 whereas we did not observe obvious change of lysine malonylation signal in this analysis (Figure S6). These data suggested the different roles of these modification in different metabolic environments.

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DISCUSSION Our previous study demonstrated malonylation as a new acylation modification on protein lysine residue, which was dynamically regulated by SIRT5 in mammalian cells. Recent proteome wide studies identified thousands of lysine malonylation sites in mammals, revealing the intimate link between malonylation and energy metabolism. Nevertheless, the study of lysine malonylation in prokaryotes was very limited. Only three malonylation substrates were identified in E. coli in our previous study.6 To this end, we performed the first in-depth proteome wide malonylome profiling in E. coli. We identified 1745 malonylated sites in 594 proteins in E. coli, representing the largest lysine malonylome data set in bacteria up to date. Current most widely adopted approach for quantitative analysis of E. coli is SILAC based culture of auxotrophic E. coli strain, which is incapable of lysine and arginine self-biosynthesis. Therefore, we carried out the SILAC-based quantitative 2069

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broadened our understanding of lysine malonylation in prokaryotes, revealing its role in several important cellular pathways such as fatty acid synthesis and TCA cycle. This study therefore provides a resource for further functional study of lysine malonylation in bacteria.

not rule out the possibility that enzyme-independent lysine malonylation exists. It was previously reported that lysine acetylation overlaps succinylation in both prokaryotes and eukaryotes.17,34 It remains interesting to compare lysine malonylome to acetylome and succinylome in bacteria. With this aim, we compared our lysine malonylome data set with our previous acetylome and succinylome data sets.17 We found that approximate one-third of the malonylated sites were overlapping with both acetylation and succinylation. These proteins are mainly involved in ribosome, glycolysis, TCA cycle and some other cellular processes, suggesting these three modifications may have some similar cellular functions. However, given the different roles of their cofactors in cellular metabolism, it is likely that these modifications could also have unique functions of their own in bacterial physiology. Indeed, our data showed that when fatty acid synthesis was disturbed in E. coli, these modifications showed different dynamic responses (Figure 2C, 7B). In addition, we also observed different dynamic patterns among Kac, Ksucc and Kmal in response to different carbon sources, such as glucose or pyruvate (Figure S6). This implied a possibility that there were potential crosstalks and balances among these three modifications in different metabolic conditions. These different kinds of modifications were likely to dynamically occur in different cellular environments, by which the activities of their substrates can be regulated to maintain E. coli cell homeostasis. Nevertheless, the detailed biological roles of these modifications in bacteria remains to be further investigated. Our bioinformatic analysis of malonylome showed that lysine malonylation was highly enriched in multiple cellular pathways, particular in protein synthesis and energy metabolism pathways, suggesting its important role in bacterial physiology. These enrichment analysis results were to some extent similar to those of lysine acetylation and succinylation. This similarity may be due to some common shared pathways among these three protein modifications. It is also possibly due to the intrinsic antibody enrichment based methodology bias toward the capture and analysis of lysine modified peptides from abundant proteins. Our bioinformatic analysis used whole genome as the background, which is the most widely adopted way for PTM analysis. We did not take into consideration the information on Kmal peptide intensity or the number of Kmal sites each protein. It is possible that our enrichment analysis results were biased toward high abundant proteins. Therefore, it does not necessarily mean that the more statistically significant enriched pathways are functionally more important for lysine malonylation. Detailed functional importance of lysine malonylation in E. coli remains to be further investigated.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jproteome.6b00264. Figure S1. Annotated MS/MS spectra of malonylated peptides. Figure S2. Gene ontology and protein domain analysis of malonylated proteins. Figure S3. Protein− protein interaction network analysis. Figure S4. Sequence alignment of citrate synthase. Figure S5. Purified citrate synthase and enzyme activity evaluation. Figure S6. Western blotting analysis of the malonyllysine level in E. coli in response to different carbon sources. (PDF) Table S1. The list of identified Kmal sites in different E. coli strains. Table S2. Biological process analysis by Gene Ontology Database of the identified malonylated proteins in preliminary experiment. Table S3. Bioinformatic analysis of the malonylome in E. coli. Table S4. Protein−protein interaction network analysis of the malonylome in E. coli. (XLSX)

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AUTHOR INFORMATION

Corresponding Author

*Tel.: 86-21-50800172. Fax: 86-21-50800172. E-mail: mjtan@ simm.ac.cn. Author Contributions ∥

Lili Qian and Litong Nie contributed equally.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the National Basic Research Program of China (973 Program) (No. 2014CBA02004), the Natural Science Foundation of China (No. 31370814 and No. 31370813), the National Science & Technology Major Project (No. 2014ZX09507-002), the Shanghai Municipal Science and Technology Commission (No. 14DZ2261100 and No. 15410723100). The Y. Z. laboratory is supported by and the National Institute of Health (NIH) of the United States (GM105933, DK107868 and GM115961).

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CONCLUSION In this study, we performed a global lysine malonylation substrate analysis on Escherichia coli, which led to the identification of 1745 malonylation sites in 594 corresponding proteins in E. coli. Our data set represents the first and largest malonylome data set in prokaryotes up to date. Quantitative malonylome analysis in response to fatty acid synthase inhibition revealed that lysine malonylation is closely associated with fatty acid metabolism. Bioinformatic analyses suggested the potential roles of lysine malonylation in multiple bacterial cellular pathways. Our comparative analysis suggested lysine malonylation, succinylation and acetylation could possibly play distinct roles in cellular physiology. In conclusion, these data

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