New insights into the mechanisms of acetic acid resistance in Acetobacter pasteurianus using iTRAQ-dependent quantitative proteomic analysis

International Journal of Food Microbiology 238 (2016) 241–251

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International Journal of Food Microbiology journal homepage: www.elsevier.com/locate/ijfoodmicro

New insights into the mechanisms of acetic acid resistance in Acetobacter pasteurianus using iTRAQ-dependent quantitative proteomic analysis Kai Xia a, Ning Zang b, Junmei Zhang a, Hong Zhang a, Yudong Li a, Ye Liu c, Wei Feng c, Xinle Liang a,⁎ a b c

Department of Biochemical Engineering, School of Food Science and Biochemical Engineering, Zhejiang Gongshang University, Hangzhou 310025, China Medical Scientific Research Center, Guangxi Medical University, Nanning 530021, China Zhejiang Wuweihe Food Co. Ltd., Huzhou 313213, China

a r t i c l e

i n f o

Article history: Received 26 May 2016 Received in revised form 20 September 2016 Accepted 21 September 2016 Available online 22 September 2016 Keywords: iTRAQ Proteomic analysis Acetobacter pasteurianus Vinegar fermentation

a b s t r a c t Acetobacter pasteurianus is the main starter in rice vinegar manufacturing due to its remarkable abilities to resist and produce acetic acid. Although several mechanisms of acetic acid resistance have been proposed and only a few effector proteins have been identified, a comprehensive depiction of the biological processes involved in acetic acid resistance is needed. In this study, iTRAQ-based quantitative proteomic analysis was adopted to investigate the whole proteome of different acidic titers (3.6, 7.1 and 9.3%, w/v) of Acetobacter pasteurianus Ab3 during the vinegar fermentation process. Consequently, 1386 proteins, including 318 differentially expressed proteins (p b 0.05), were identified. Compared to that in the low titer circumstance, cells conducted distinct biological processes under high acetic acid stress, where N 150 proteins were differentially expressed. Specifically, proteins involved in amino acid metabolic processes and fatty acid biosynthesis were differentially expressed, which may contribute to the acetic acid resistance of Acetobacter. Transcription factors, two component systems and toxinantitoxin systems were implicated in the modulatory network at multiple levels. In addition, the identification of proteins involved in redox homeostasis, protein metabolism, and the cell envelope suggested that the whole cellular system is mobilized in response to acid stress. These findings provide a differential proteomic profile of acetic acid resistance in Acetobacter pasteurianus and have potential application to highly acidic rice vinegar manufacturing. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Acetic acid bacteria (AAB) are gram-negative, strictly aerobic microorganisms belonging to Acetobacteraceae (Cleenwerck and De Vos, 2008; Yamada and Yukphan, 2008). The species belonging to genera Acetobacter and Gluconacetobacter (some species are now relocated into Komagataeibacter) are mainly used in industrial vinegar production because of their specific acetic acid and ethanol tolerance and remarkable ability to oxidize ethanol to acetic acid via alcohol dehydrogenase and aldehyde dehydrogenase (Matsushita et al., 1994; Thurner et al., 1997). In particular, Acetobacter pasteurianus is a predominant starter in traditional rice vinegar production in China and Japan, where the acetic acid titer does not often exceed 6% (v/v) (Matsutani et al., 2011). Because acetic acid is well known as a metabolite that produces cellular toxicity at concentrations as low as 0.5% (v/v), it is important to elucidate the molecular mechanisms of acetic acid resistance in terms of AAB exploration and industrial vinegar production (Steiner and Sauer, 2001). ⁎ Corresponding author. E-mail address: [email protected] (X. Liang).

http://dx.doi.org/10.1016/j.ijfoodmicro.2016.09.016 0168-1605/© 2016 Elsevier B.V. All rights reserved.

During the past few decades, numerous studies have been performed to explore the mechanisms of acetic acid resistance in AAB, and Acetobacter and Gluconacetobacter are usually the predominant bacteria studied. Currently, proposals about acid resistance mechanisms have been focused on four main aspects: (i) proteins involved in alcohol oxidation into acetic acid (Nakano and Fukaya, 2008; Trcek et al., 2007; Trcek et al., 2006), (ii) pathways involved in the detoxification of intracellular acetate anion and H+ by efflux pumps or assimilation of acetate through TCA cycle (Matsushita et al., 2005; Mullins et al., 2012; Nakano et al., 2006; Sakurai et al., 2013; Soemphol et al., 2015), (iii) acid shock responses, such as GroESL, DnaKJ (Ishikawa et al., 2010; Nakano and Fukaya, 2008), and (iv) cell envelope adaptions, such as outer membrane structures, pellicle polysaccharides, etc., which function as barriers to passive diffusion of undissociated acetic acid molecules into the cells (Deeraksa et al., 2005). Additionally, changes in the membrane lipids along with the titer stress accumulation, may suggest an underlying effect on the influx of undissociated acetic acid molecules, thus conferring acid resistance (Hanada et al., 2001; Trcek et al., 2007). By reviewing the bacterial acid tolerance mechanisms in E. coli, Listeria monocytogenes, and lactic acid bacteria, etc., the contribution of amino acid deamination to acid resistance of AAB was first proposed

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by Trcek et al. (2015). Although substantial progress has been achieved (Andres-Barrao et al., 2012; Wang et al., 2015a), the insights into the acetic acid resistance seem scattered, suggesting that multiple adaptions or modulatory pathways cooperate in the cellular acid resistance. Actually, the available genomic, transcriptomic and proteomic data and methods are becoming feasible to support a more global and comprehensive study of the biological metabolism of AAB. So far, eighteen genomes of Acetobacter or Gluconacetobacter have been sequenced; and a transcriptome analysis of the ethanol and glucose switches further confirmed the role of energy metabolism and glyoxylate pathway in acid resistance (Sakurai et al., 2011; Zhong et al., 2014). Upon analysis of the functions of 52 identified proteins, it was concluded that A. pasteurianus LMG 1262T differentially modulated the following processes: (1) protein folding, (2) stress response, (3) oxidation-reduction processes, (4) metabolic processes, (5) protein biosynthesis, and (6) membrane modifications. Recently, the comparative proteome studies of A. pasteurianus and Komagataeibacter spp., which face much higher acetic acid titers (N 9%, w/v) during vinegar fermentation, were reported (Andrés-Barrao et al., 2015; Wang et al., 2015b). Although several novel protein targets were identified, the limited number greatly restricts any downstream analysis aiming at high resolution determination of the adaption mechanisms by Gene Ontology (GO) annotation and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Recently, the iTRAQ-based proteomic analysis has emerged to identify protein expression more qualitatively and quantitatively, and thus can provide more comprehensive proteome information (Evans et al., 2012; Miao et al., 2015). Compared to conventional proteomics techniques, iTRAQ possesses unique advantages in identifying and quantifying proteins by using labeled peptides identifiable by mass spectrometers (Evans et al., 2012; Zhang et al., 2014). In addition, iTRAQ analysis is further enhanced by adopting sturdy bioinformatics tools and statistical analysis to specifically annotate the results (Herbrich et al., 2013). In current study, the iTRAQ-based quantitative proteomic analysis technique was adopted to further examine the acetic acid resistance mechanism in A. pasteurianus Ab3.

2.2. Protein extraction and quantification The total cellular proteins from the pooled sample were extracted according to instructions provided with the bacterial protein extraction kit (Liu et al., 2015). Briefly, the cells were collected by centrifugation, and the precipitates were resuspended and washed 3 times with PBS buffer (phosphate buffer saline). The Lysis solution (1 mL of lysis buffer included 1 μL of protease inhibitor, 10 μL of DTT (1 M) and 10 μL of PMSF (100 mM)) was added to one-fifth of the original volume of the cell cultures, and the mixture was incubated at 4 °C for 10 min. The cells were further lysed by ultra-sonication and centrifuged at 14,000 r/min for 15 min at 4 °C. The supernatant was collected and the protein concentration was quantified using the Bradford method (Bradford, 1976). 2.3. Protein digestion and iTRAQ labeling Protein digestion was conducted as previously described (Liu et al., 2015). Approximately 60 μg of protein were dissolved in a 5-fold volume of dissolution buffer (8 M urea and 100 mM Tris-HCl). Then, 4 μL of reducing reagent were added to the mixture and incubated at 37 °C for 2 h. Another 2 μL of cysteine-blocking reagent were added and incubated for 15 min at room temperature; the alkylated protein were collected by centrifugation at 12,000 r/min for 20 min. After three washes, the pellet was digested with Trypsin and incubated at 37 °C for 16 h. Following — trypsin digestion, the peptide samples were lyophilized and then labeled using the iTRAQ reagents 8-plex kit (AB Sciex) according to the manufacturer's instructions. iTRAQ reagents 113 and 114 were used to coordinately label the peptides from the control P3 samples, whereas iTRAQ reagents 115, 116 and 117 were used to coordinately label the peptides from the P7 sample and reagents 118, 119 and 121 were used to label the peptides from the P9 sample. The labeled peptides were incubated at room temperature for 2 h, and the reaction was stopped by adding 100 μL of ultrapure water. Then, 1 μL of sample was removed from each of the 8 groups and mixed to confirm that the samples had been successfully labeled, after which the labeled peptides were pooled and lyophilized. 2.4. SCX fractionation and LC-ESI-MS/MS analysis using a triple TOF 5600

2. Materials and methods 2.1. Bacterial strain and samples A. pasteurianus Ab3 (deposited in the China Center for Type Culture Collection, NO M 2013116) was stored lyophilized in the laboratory. A. pasteurianus Ab3 was isolated from the traditional rice vinegar in Zhejiang Wuweihe Food Co. Ltd., Huzhou, China. Because of its high acetic acid resistance, strain Ab3 is applied to high titer rice vinegar manufacturing (N 9%, w/w). To activate the lyophilized culture, it was first dissolved in 0.5 mL fresh sterilized YPD medium (10 g/L yeast extract, 5 g/L peptone, 10 g/L D-glucose, pH 6.5) without ethanol. The activated culture was then inoculated into fresh YPD medium containing 2% ethanol (v/v) and 0.5% acetic acid (v/v) with shaking (160 r/min) at 30 °C for 24 h. The seed culture are prepared in a 500 L self-priming fermenter (Nanjing Biological Engineering Equipment Co., LTD, Jiangsu, China). When the titer accumulates to ~3% (w/v), seeds are transferred into a 30 m3 fermenter for vinegar fermentation. The ethanol concentration was automatically maintained at 3% (v/v) by addition of ethanol during cultivation. The acetic acid concentration was determined by titration. Three cell samples with acidic titers at 3.6%, 7.1%, and 9.3% (w/v) vinegar fermentation were collected and cognately prepared, with the pooled sample being designated as P3, P7 and P9 respectively. The P3 sample was used as the control and P7 and P9 were regarded as the experimental groups in the iTRAQ 8 plex quantitative analysis. All processes were repeated three times, and the sampled cells were mixed to prepare the pool for analysis (Fig. S1).

The iTRAQ-labeled peptides were dissolved in 100 μL of buffer A (25 mM NaH2PO4 in 25% CAN, pH 2.7) and purified on a strong cation exchange chromatography (SCX) column (2.0 × 150 mm, 5 μm, michrom) using an Agilent 1200 HPLC (Agilent). The samples were eluted using a binary linear gradient of 5% buffer B (25 mM NaH2PO4 and 1 M KCl in 25% CAN, pH 2.7) for 5 min, 5–50% buffer B for 35 min, 50– 80% buffer B for 5 min, 80% buffer B for 5 min, 80–5% buffer B for 0.01 min and 5% buffer B for 9.99 min. The flow rate was set at 0.3 mL/min, and the detection wavelengths were 215 nm and 280 nm. The first tube of eluted peptides was collected from 0 to 5 min, and the eluted peptides were collected every 4 min from 5 to 44 min. The peptides that eluted from 35 to 46 min were collected as one tube. Equal amounts of peptides from the first and second tubes were mixed. All of the eluted peptides were pooled in 10 fractions and dried using vacuum freeze drying. The dried peptides were re-dissolved in Nano-RPLC buffer A and desalted using a C18 column (100 μm × 3 cm, 3 μm) for 10 min. The analytical separation was performed using an Eksigent nanoLC-Ultra™ 2D system (AB SCIEX) coupled to a triple TOF 5600 system (AB SCIEX) fitted with a Nanospray III source (AB SCIEX, USA) and a pulled quartz tip as the emitter (New Objectives, USA). The system was equipped with a C18 reverse chromatography column (75 μm × 15 cm, 3 μm) for analysis. Separation was achieved using gradient elution and performed as previously reported (Miao et al., 2015), with some modifications. The data were acquired using an ion spray voltage of 2.4 kV, curtain gas of 30 psi, nebulizer gas of 15 psi, and a heater temperature of 150 °C. The information-dependent acquisition (IDA) method was used to acquire the data; the secondary scans were

K. Xia et al. / International Journal of Food Microbiology 238 (2016) 241–251

acquired in 250 ms and no N35 product ion scans were collected if they exceeded a threshold of 150 counts per second (counts/s) with a 2+ to 5+ charge, and the cumulative time of each secondary scan was 60 ms. The total time of each cycle was fixed at 2.5 s, and a rolling collision energy setting was applied to all precursor ions for collision-induced dissociation (CID). Dynamic exclusion was set for a 1/2 peak width (18 s) (Zhang et al., 2014). 2.5. Data analysis The original data files gathered by the MS in wiff format were processed with Protein Pilot Software v4.5 (AB SCIEX, USA) against the A. pasteurianus protein database (including 2906 protein sequences, Uniprot) using the Paragon algorithm (Shilov et al., 2007). Protein identification was performed on the Triple TOF 5600 by searching against the database using the following search parameters: iTRAQ 8 plex quantification (N-term, K), cysteine modified with iodoacetamide, and trypsin digestion. Enzyme specificity was set to trypsin with one missed cleavage, the peptide mass tolerance was set to ±0.05 Da, the fragment mass tolerance was set to ±0.1 Da, and the charge states of the peptides were set to +2 and +3. The FDR (false discovery rate) was calculated as the number of false positive matches divided by the number of total matches. Peptides with a global FDR value of b 1% were selected for the subsequent analyses when iTRAQ was chosen as the quantitative analysis for the proteins (Miao et al., 2015; Zhang et al., 2014). Moreover, protein which expression is increased by 1.5-fold, or decreased by 0.67-fold, and a p value b 0.05, is considered to as one significantly differential species. The Gene Ontology (Go) annotation (http://www.geneontology. org/) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (http://www.genome.jp/kegg/) enrichment analysis were used to define the functional subcategories and metabolic processes of the differentially expressed proteins. Firstly, for the homology search, all query proteins were used to match with blastp against the annotated A. pasteurianus protein database (Uniprot database), the best hits with the highest identity was picked (E-value b 1e−10). The GO enrichment analyses were performed with different mapping steps to link all best hit sequences to the functional information stored in the Gene Ontology database using DAVID toolkit (Huang da et al., 2009b). Simultaneously, the public database NCBI, PIR and GO were used to create links among protein IDs and corresponding gene ontology information. For KEGG enrichment analysis, the annotated proteins in query dataset were used in pathway enrichment against public available database (Huang da et al., 2009a; Kanehisa and Goto, 2000; Zhang et al., 2014). The KEGG pathway and module mapping analyses were performed with KEGG Mapper tools which were linked to the KEGG public website, and sequence similarity search was also completed with BLAST/FASTA tools. Additionally, the software KOBAS 2.0 (http://kobas.cbi.pku.edu.cn) was used to identify significant pathways (Xie et al., 2011).

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The amplification procedure included: denaturation at 95 °C for 12 min; 30 cycles of 95 °C for 30 s, 53 °C for 30 s and 72 °C for 20 s; and 72 °C for 10 min. At the end of the PCR cycles, melting curve analyses were also performed using the LightCycler® Nano qRT-PCR system (LightCycler, England). Each sample was run in triplicate for the purpose of analysis, and 16 s rRNA was used as the reference gene. The relative fold change in mRNA concentration compared to the control (sample P3) was analyzed using the △△Ct method, and the error bars represent the standard deviations. The primer sequences were listed in Table S1. 3. Results and discussions 3.1. Proteome profile of A. pasteurianus Ab3 adapted to acetic acid accumulation during vinegar fermentation It is important to explore the acid resistance of bacteria, not only in industrial weak acid-producing strains but also in spoilage or pathogenic bacteria in concerns of food safety (Sengun and Karabiyikli, 2011). Current progresses in investigating the acid resistance mechanism of A. pasteurianus have come from 2-DE or 2-DIGE proteome and transcriptome studies (Andres-Barrao et al., 2012; Nakano and Fukaya, 2008; Wang et al., 2015b). Using the iTRAQ-based technology in this study enabled us to further extend the search landscape, and as a result, here we identified a panel of proteins that are differentially expressed during acid production transitions. A total of 1386 proteins were specifically identified from 70,776 MS/ MS spectra and 17,745 peptides using a 1% false discovery rate (FDR) as the cutoff in three independent experiments, showing a very wide coverage for the protein identification method utilized in this study. Of the identified proteins, 1224 proteins were quantified. In the comparative analysis among the samples, 41 and 153 differentially expressed proteins were identified in samples P7 and P9, respectively (Fig. 1). Specifically, there were 15 differentially expressed proteins that were observed in both comparative tests. Of these, ten proteins were upregulated with increasing titer, and two (C7JIA3 and C7JBV3) were downregulated consistently. Representative proteins were summarized in Table 1 and the detailed lists were provided in Tables S2 and S3. A GO enrichment analysis was performed to classify the differentially expressed proteins according to their biological process, cellular component, and molecular function. In the P7:P3 test, most of the differentially expressed proteins, which are located in intracellular cytosol and mainly execute oxidoreductase or antioxidant biological functions,

2.6. RNA extraction and quantitative transcriptional analysis All gene manipulation is based on genome of A. pasteurianus Ab3 deposited in NCBI (accession: CP012111). RNA was extracted using TaKaRa MiniBEST Universal RNA extraction Kit (TaKaRa, China) according to the manufacturer's instructions. The RNA yield and quality were evaluated with a NanoDrop UV spectrometer (Thermo Scientific, USA). Then, approximately 2 μg of RNA were reverse transcribed by the PrimeScript Reverse Transcriptase using the PrimeScript™ II 1st Strand cDNA Synthesis Kit (TaKaRa, China). Quantitative real-time PCR (qRTPCR) was performed using the SYBR Premix Ex Taq™ II Kit (TaKaRa, China) with a final volume of 20 μL in each reaction system, which included 10 μL of SYBR Premix Ex Taq II, 0.4 μL of each primer (final concentration 0.4 μM), 2 μL of cDNA, and 7.2 μL of dH2O. The target genes involved in genome sequence of Ab3 and primers (designed by Sangon Biotech (Shanghai) Co., Ltd.) used for qRT-PCR were listed in Table S1.

Fig. 1. Numbers of unique differentially expressed proteins among the samples from different acidity conditions. In the Venn diagram, A and B represented the number of significantly regulated proteins in the pooled sample P7 compared with P3, and P9 compared with P3, respectively. The overlap indicated the numbers of differentially expressed proteins detected in both samples.

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Table 1 The representative differential protein species in the pooled samples against high titer stress. Accession (Uniprot)

Ribosome and protein metabolism C7JEZ1 C7JC24 C7JBN6 C7JC48 C7JC78 C7JBF2 C7JE06 C7JG41 C7JCS4 C7JBQ2 Fatty acids and cell envelope metabolism C7JH67 C7JGY1 C7JG56 C7JGU2 C7JE12 C7JGY2 C7JH69 C7JDF2 Amino acid metabolism and deamination C7JG72 C7JGC9 C7JFW0 C7JD63 C7JI10 C7JDY6 C7JGR6 C7JB84 C7JD38 C7JCD6 Oxidative stress response C7JF76 C7JAX6 C7JGR1 C7JAP7 C7JHL0 C7JBX8 C7JHK8 Transcriptional regulators C7JH77 C7JC81 C7JID8 C7JGZ0 C7JB22 C7JBT2 C7JBS7 C7JH94 TCS/TAS C7JBU0 C7JIA3 C7JIY9 Sugar metabolism C7JD10 C7JE88 C7JHZ4 C7JF72 C7JAU2 C7JAW8 C7JG48 C7JAR8 Others C7JIF9 C7JBB5 C7JFU5 C7JD70 C7JBD6 C7JAW7 C7JD12 C7JHL8

Proteins

Fold changesa P7:P3b

P9:P3c

Histone H1-like protein Protein GrpE Trigger factor RNA-binding protein Hfq Elongation factor P Translation initiation inhibitor YjgF Ribosome-recycling factor Ribosome maturation factor RimP Ribosomal silencing factor RsfS Elongation factor G

– – – – – 0.29 – – – –

13.60 13.32 8.68 5.63 5.27 4.18 4.97 3.40 2.06 0.48

Acyl carrier protein Peptidoglycan-associated lipoprotein Acetyl-CoA carboxylase biotin carboxyl carrier Osmotically inducible protein OsmC Outer membrane protein OmpH Protein TolB Malonyl CoA-acyl carrier protein transacylase Oxidoreductase

– – – 3.36 – – – –

10.44 7.74 4.16 2.33 2.23 0.47 0.43 0.40

Aspartyl/glutamyl-tRNA(Asn/Gln) amidotransferase subunit C Amidotransferase GatB/YqeY subunit for mischarged Glu-tRNA(Gln) Glycine cleavage system H protein Translation initiation inhibitor YjgF Glutamate synthase [NADPH] small subunit Glutamine synthetase Aspartokinase Aspartate aminotransferase Ketol-acid reductoisomerase O-succinylhomoserine sulfhydrylase

– – – – – – – – – –

7.74 5.48 14.66 4.18 2.26 0.46 0.42 0.34 0.32 0.29

Bacterioferritin Ferredoxin Glutaredoxin Nitrogen fixing thioredoxin-like protein NifU Catalase Superoxide dismutase NADH:flavin oxidoreductase

– – – – 3.23 2.04 1.57

22.59 8.5 7.16 7.72 2.76 – –

Transcriptional regulator cold shock protein Transcriptional regulator cold shock protein Transcriptional regulator AbrB Probable transcriptional regulatory protein Transcriptional regulator cold shock protein Transcriptional regulator MerR Transcriptional regulator Ros/MucR BolA-like protein

– – – – – – – –

9.45 9.26 7.86 6.66 6.0 5.74 4.22 3.32

Two component response regulator OmpR Alcohol dehydrogenase NADH-dependent iron-containing Translation repressor RelE/RelB/StbE

– 0.55 –

2.67 0.22 3.29

2,5-diketo-D-gluconate reductase Malonate semialdehyde decarboxylase Fumarate hydratase class II Pyruvate decarboxylase Gluconolactonase Alcohol dehydrogenase large subunit Aconitate hydratase Phosphoglycerate kinase

2.42 1.84 1.84 1.75 1.71 1.64 1.58 1.54

– – – – – – – –

Arylesterase Uncharacterized protein Uncharacterized protein Cation/copper resistance transporter ATPase CopZ Inorganic pyrophosphatase Alcohol dehydrogenase cytochrome c subunit Aldehyde/betaine dehydrogenase Uncharacterized protein

5.55 2.93 2.09 1.95 1.90 1.80 1.70 1.53

3.15 10.84 11.24 6.16 7.94 2.86 2.33 10.30

K. Xia et al. / International Journal of Food Microbiology 238 (2016) 241–251

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Table 1 (continued) Accession (Uniprot)

C7JG70 C7JG51 C7JBV3 a b c

Fold changesa

Proteins

Uncharacterized protein Uncharacterized protein Uncharacterized protein

P7:P3b

P9:P3c

0.55 0.55 0.19

4.16 4.26 0.38

Fold changes, – means no differential expression detected. P7:P3 means the proteins expression ratio of the pooled samples (7.4%, w/v) compared to that of the pooled samples (3.6%, w/v). P9:P3 means the proteins expression ratio of the pooled samples (9.4%, w/v) compared to that of the pooled samples (3.6%, w/v).

were involved in responses to oxidative stress and carbohydrate metabolic processes (Fig. 2A1); others such as cell envelope components were involved in response to stress binding function (Fig. 2A2 and A3). However, in the P9:P3 trial, the altered proteins mainly belonged to cellular protein metabolic processes, gene expression, and cellular biosynthetic processes (Fig. 2B1). The cell components mainly function in intracellular structures, including ribosomes, the ribonucleoprotein complex, and cytosolic region (Fig. 2B2), which were consistent with the specific molecular functions, such as ribosome structure constituents, structural molecular activity, RNA binding, nucleic acid binding, and organic cyclic compound binding, etc. (Fig. 2B3). The KEGG

pathway enrichment analysis was conducted to determine the biological pathways to which the differentially expressed proteins belonged, as shown in Fig. 3. In the P7:P3 test, the 9 differentially expressed proteins were mainly involved in carbon metabolism, such as the citrate cycle, glyoxylate and dicarboxylate metabolism (Fig. 3A). As the titer increased to 9% (w/v), ribosome and proteins metabolism may become the critical biological process for cell viability (Fig. 3B); there were approximate 44 proteins involved in ribosome and protein metabolism which were differentially expressed (Tables S2 and S3). Additionally, proteins involved in fatty acid biosynthesis, amino acid metabolism, oxidative response, and transcriptional regulatory factors were also

Fig. 2. GO enrichment analysis of the differentially expressed proteins between the pooled samples P3, P7 and P9. The representative components of the differentially expressed proteins were displayed, along with their enrichment score, which was presented as a −log (p value). A1–3, comparisons between P7 and P3. B1–3, comparisons between P9 and P3.

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Fig. 3. KEGG pathway enrichment analysis of the differentially expressed proteins among different samples. The representative components of the differentially expressed proteins were displayed, along with their enrichment score, which was presented as a −log (p value). (A) Comparisons between P7 and P3. (B) Comparisons between P9 and P3.

differentially expressed (Table 1). Our findings are categorically in line with previous reports, and together, we outlined the potential acetic resistance mechanisms of A. pasteurianus in Fig. 5.

Fig. 4. Comparative analysis of the transcript and protein levels of specific differentially expressed proteins revealed by qRT-PCR and iTRAQ, respectively. Candidate genes involved in the reactive oxygen species response (bfr, grxC), miscellaneous (aes), metabolic process (yqhD), fatty acid biosynthesis (fabD, acpP), amino acid metabolic process (gcvH, glnA), and protein biosynthesis process (Histone H1-like protein, C7JEZ1) were assessed. The relative expression level was obtained by comparing sample P9 to the control P3.

3.2. Correlation between protein production and gene expression To confirm the accuracy of the iTRAQ ratio obtained from the present proteomics study, we analyzed the correlation between productions of some representative protein with their cognate gene expressions. RNA was extracted from two biological processes, P3 and P9, then qRT-PCR experiments were performed using three technical replicates. Significant differences in the data were determined using one-way ANOVA (p b 0.05). The results were shown as the mean fold changes ± standard deviation (SD). The bfr, aes, acpP, gcvH, C7JEZ1, and grxC transcripts were upregulated, which was consistent with the results from the iTRAQ proteomic analysis; however the yqhD, fabD and glnA transcripts were down-regulated (Fig. 4). Despite the differences in the fold change values (relative expression level) obtained from the qRT-PCR and iTRAQ analyses, the overall trends in the gene expression levels were consistent, indicating the stability and credibility of the iTRAQ ratios in the present study.

3.3. The ribosome and protein biosynthesis process respond to high titer stress Here, we observed that 44 protein involved in the ribosome or protein metabolism were differentially upregulated (Tables S2 and S3), implying that the cell would tend to increase protein synthesis under high titer stress. The representative proteins were listed in Table 1.

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Specifically, it is worth noting the identification of factors related to ribosome maturation, recycling and silencing. Ribosome assembly and efficient utility may trade off the decreased ability of protein biosynthesis. This was exemplified by the increased expression of C7JCS4 (2.06-fold) that can prevent the formation of functional ribosomes and thus repress translation, together with the decreased expression of the 7 ribosomal proteins (including elongation factor G, EF-G). Consistently, decreased protein synthesis was observed in a previous report when the cells switch from zero acid titer to 4% (w/v) titer, most of the proteins involved in protein biosynthesis and translation processes such as ribosomal protein L5, S6, and ribosome recycling factor (RRF) were dysregulated under the 4% (w/v) titer, while GrpE and HSP 70 are upregulated (Andres-Barrao et al., 2012). Interestingly, only four protein species (L5, GrpE, Heat shock protein, and ribosome recycling factor) were detected in both of Andres-Barrao's report and ours (AndresBarrao et al., 2012). Of which, the expression of ribosome recycling factor (RRF) showed a 4.97-fold increase in our study but a cognate downregulation in the Andres-Barrao's report. The discrepancy may either be attributed to certain differences in the technical specificities, or more likely, result from critical implications of this factor during the transition to high acid stress. Functionally, RRF works with the elongation factor G (EF-G) to catalyze the last step of protein synthesis during ribosome recycling (Hirokawa et al., 2005). The increased expression of RRF may facilitate the ribosome recycling and protein synthesis, while the downregulation of its protein partner EF-G may counter these functions and have an adverse effect. In addition, the increased expression of histone H1-like proteins (C7JEZ1) (13.6-fold) may lead to a down regulation of transcription, translation, and bacterial replication in conjunction with condensation of the chromatin (Yang et al., 2015), thus decreasing the protein synthesis. Similarly, the increased expression (5.63-fold) of Hfq (C7JC48), a pleiotropic regulator of bacterial gene expression that modulates mRNA translation, indicates increased alteration in protein synthesis (Vogel and Luisi, 2011). The increased expression (5.37-fold) of EF-P (C7JC78), a translation elongation factor that prevents the ribosome from stalling during the synthesis of proteins, may support the fitness of the bacteria, such as bacterial growth, motility, virulence, and stress response under stressful conditions (Doerfel and Rodnina, 2013). Meanwhile, the upregulation of certain heat shock proteins, such as HspA (C7JDV3), GrpE (C7JC24), DnaK (C7JC25), DnaJ (C7JGZ9) and trigger factor (C7JBN6), indicates enhancement in protein refolding (Table 1 and Table S3). Collectively, these findings suggest that the titer accumulation particularly puts pressures on the ribosome integrity and protein biosynthesis. 3.4. Fatty acid biosynthesis and cell envelope respond to high titer resistance In a previous similar study on A. pasteurianus, alterations in the fatty acids species have been described (Trcek et al., 2007). Our current study showed the differential expression of proteins of the lipid pathway in response to the increasing titer (Fig. 3). The upregulation of acyl carrier protein (C7JH67) and acetyl-CoA carboxylase biotin carboxyl carrier protein (C7JG56) suggested an increased capacity of transporting starting materials and intermediates for lipid synthesis (Nguyen et al., 2014). On the other hand, the downregulation of FabD (C7JH69) and FabG (C7JDF2) would attenuate the flux of fatty acid pathway and subsequently reduce the total lipid content. FabD is essential to the initiation of fatty-acid biosynthesis in bacteria and also provides the malonyl groups for polyketide biosynthesis (Szafranska et al., 2002). FabG involves in fatty acid chain elongation process (Nanson and Forwood, 2015). Indeed, the total lipid contents decreased when Komagataeibacter europaeus and Listeria monocytogenes were put under acetic acid stress (Mastronicolis et al., 2010; Trcek et al., 2007), implying the altered lipid content or species may influence the membrane buffering capacity to toxic acetic acid molecules. Our observations clearly indicated an active engagement of these two effector proteins.

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In addition to fatty acids, outer membrane proteins also contribute to membrane function. OmpA is a major component of the outer membrane that acts as a porin with low, non-specific permeability for a variety of small solutes and functions to maintain the stable outer membrane structure (Confer and Ayalew, 2013; Smith et al., 2007). OmpH is another important outer membrane protein that is abundantly located on the bacterial surface and functions as a molecular sieve to allow the diffusion of small hydrophilic solutes through the outer membrane (Ganguly et al., 2015). It has been reported that OmpH expression at the later growth stages may be similar to E. coli OmpC and OmpF, which function in a dilute nutrient environment and then enhance the growth and survival of cells (Bartlett and Welch, 1995). In this study, the outer membrane protein OmpA (C7JEV4) was downregulated for 0.4-fold, whereas OmpH and OsmC were upregulated for 2.23- and 3.36-fold, respectively. These changes in expression implied that the cells may attempt to balance nutrient uptake and resistance to the toxicity of a small molecular stressor in response to the high acid titer. Simultaneously, the surface of the cells changed significantly (Andres-Barrao et al., 2012; Trcek et al., 2007; Wang et al., 2015b). In addition to the outer membrane protein, Pal (C7JGY1) and lipoprotein MetQ (C7JEC4) were also upregulated for 7.74-fold, which played crucial roles in maintaining outer membrane integrity, promoting cell division, and improving salt and alkaline tolerance of E. coli (Zhai et al., 2014). On the other hand, TolB (C7JGY2), one component of the TolPal system, was down-regulated for 0.47-fold. TolB is essential for P. aeruginosa growth, and TolB-depleted cells were strongly defective in cell-envelope integrity (Lo Sciuto et al., 2014). When facing the high titer stress, the structural components on the cell surface or membrane of A. pasteurianus Ab3 showed diverse and even contradictory responses, reflecting an unhealthy cellular status. The overall homeostasis of cell envelope integrity and rigidity may compromise the nutrient requirements and cellular toxicity of ethanol and acetic acid, contributing to acetic acid resistance. 3.5. Differential proteins involved in amino acid deamination In E. coli, it has been universally described that glutamine is converted into glutamate, with a concomitant release of gaseous ammonia, thereby neutralizing a proton to control the internal pH under extreme acid stress (Lu et al., 2013). Although the potential contribution of amino acid deamination in acetic acid bacteria was only hypothesized in previous studies (Lu et al., 2013; Trcek et al., 2015), our current study experimentally detected the biological processes involved in the deamination for the first time (Table 1). Glycine cleavage system H protein (C7JFW0) was markedly upregulated for 14.66-fold, implying the increased production of ammonia from Gly cleavage (Table 1). Likewise, the upregulation of Aspartyl/glutamyl-tRNA (Asn/Gln) amidotransferase subunit C (C7JG72) and the amidotransferase GatB/ YqeY subunit for mischarged Glu-tRNA(Gln) (C7JGC9) may result in more glutamine cleavage into glutamate and ammonia; on the other hand, the downregulation of aspartate aminotransferase (C7JB84) may lead to ammonia accumulation in the cytoplasm (Mowbray et al., 2014). The output of ammonia may neutralize the acidification of the intracellular acetate anion and improve resistance. It is worth noting that the combination of reduced glutamine synthesis with increased cleavage may disturb the amino acid synthesis network and then hinder cell viability. In fact, C7JDY6 (glutamine synthetase, catalysis of the transfer of L-glutamate and L-glutamine), C7JGR6 (aspartokinase, catalysis of the transformation of L-aspartate and 4-phospho-L-aspartate), C7JD38 (ketol-acid reductoisomerase, involving in synthesis of L-isoleucine from 2-oxobutanoate), and C7JB84 (aspartate aminotransferase, catalysis of the transfer of an alpha-amino group from an amino acid to an alpha-keto acid) were all downregulated, which would attenuate both amino acid synthesis and the related carbon flux linked to the citrate cycle (Fig. 5). Additionally, we also identified YjgF (C7JD63), a member of YjgF/YER057c/UK114 family. To date, the biochemical

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Fig. 5. The global responses of strain Ab3 under high acid titer stress. The main differentially expressed proteins that were upregulated (red arrows) and downregulated (green arrows) were listed. ADH: alcohol dehydrogenase; ALDH: acetaldehyde dehydrogenase; PQQ-ADH: PQQ-dependent alcohol dehydrogenase; NAD-ADH: NAD-dependent alcohol dehydrogenase; NAD-ALDH: NAD-dependent acetaldehyde dehydrogenase; YqhD: alcohol dehydrogenase NADH-dependent iron-containing; Sad: aldehyde dehydrogenase; MetQ: Lipoprotein; Pal: peptidoglycan-associated lipoprotein; TolB: TolB protein; OmpA: outer membrane protein OmpA; OmpH: outer membrane protein OmpH; GreA: transcription elongation factor GreA; Tig: trigger factor; GrpE: GrpE protein; DnaJ: heat shock protein DnaJ; DnaK: chaperone protein DnaK; GroESL: chaperonin protein GroESL; Bfr: bacterioferritin; OsmC: osmotically inducible protein OsmC; KatE: catalase; SodB: superoxide dismutase; GcvH: glycine cleavage system H protein; GlnA: glutamine synthetase; ThrA: aspartokinase; AcnA: aconitate hydratase; IcD: isocitrate dehydrogenase; FumC: fumarate hydratase class II; OmpR: two component response regulator OmpR; CusC: secretion system type I outer membrane efflux pump lipoprotein NodT; AcpP: acyl carrier protein; AccB: acetyl-CoA carboxylase biotin carboxyl carrier protein; FabD: malonyl CoA-acyl carrier protein transacylase; FabG: oxidoreductase; CspE: transcriptional regulator cold shock protein; CspG: transcriptional regulator cold shock protein DNA-binding protein; CspA: transcriptional regulator cold shock protein DNA-binding protein; transcriptional regulator MerR; AbrB: transcriptional regulator AbrB; Ros/MucR: transcriptional regulator Ros/MucR; RimP: ribosome maturation factor RimP; Hfq: RNA-binding protein Hfq; Frr: ribosome-recycling factor; Efp: elongation factor P; FusA: elongation factor G; RelE/RelB: translation repressor RelE/RelB/StbE; YoaB: translation initiation inhibitor of YjgF; C7JD70: cation/copper resistance transporter ATPase CopZ; MerR: transcriptional regulator MerR; C7JAX6: ferredoxin; C7JGR1: glutaredoxin; (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

functions of the YjgF/YER057c/UK114 family has been infrequently reported, and its known functions include deaminating reactive enamines or imines to release ammonia in bacteria (Lambrecht et al., 2012) and sequestering small potential toxic molecules in E. coli (Parsons et al., 2003). Furthermore, the phylogenetic distribution and sequence diversity of the YjgF/YER057c/UK114 family indicates its multiple functions (Niehaus et al., 2015), while the detailed functions of this family in A. pasteurianus requires further study.

Kainuma et al., 2008). In the current work, the upregulation of these proteins implied that the cells faced substantial oxidative stresses during high acid titer fermentation; the oxygen supply exhibited increased acid yield and decreased cell viability. Redox homeostasis may be one valuable approach to modulate vinegar fermentation.

3.6. Alterations in proteins involved in oxidative stress or reactive oxygen species responses

In the current study, eight proteins were identified as transcriptional regulators (Table 1). Of these, CspE (C7JH77), CspG (C7JC81) and CspA (C7JB22) were upregulated by an average of 8.27-fold. These cold shock nucleotide binding proteins exhibit nucleic acid and RNA binding and transcription factor activities, as well as protecting the DNA against oxidative damage (Nair and Finkel, 2004). Five additional transcriptional regulators, including transcriptional regulator AbrB (C7JID8, 7.86fold), probable transcriptional regulatory protein APA01_26280 (C7JGZ0, 6.66-fold), transcriptional regulator MerR (C7JBT2, 5.74fold), transcriptional regulator Ros/MucR (C7JBS7, 4.22-fold), and BolA (C7JH94, 3.32-fold), were all upregulated in response to the high titer stress. AbrB negatively modulated the expression of over 200 genes with different biological functions, and the diversity in AbrB levels generated heterogeneous growth rates during the exponential growth phase in Bacillus subtilis (Mars et al., 2015). Specially, citB (encoding acotinase) expression was reduced in an abrB null mutation (Chumsakul et al., 2011). In A. pasteurianus, it has been reported that aconitase activity and growth heterogeneity contributed to the acid resistance (Nakano and Fukaya, 2008). Our results confirmed the differential expression of abrB. MerR family regulators were related to metal ion efflux for detoxification; currently, their transcriptional modulatory activities have been extensively developed to provide resistance to toxins via the induction of multidrug transporters (Chang et al., 2015; Hobman, 2007; Scoffone et al., 2015). In the current study, the increased MerR expression may be involved in inducing the expression of multidrug transporters in A. pasteurianus, which improves the cellular resistance to multiple stresses, including acid stress. Ros/MucR proteins

A. pasteurianus is an obligate aerobe and conducts incomplete ethanol oxidation and acetic acid peroxidation in the presence of oxygen, and a variety of reactive oxygen species are produced (OkamotoKainuma et al., 2008). Here, catalase (C7JHL0), superoxide dismutase (C7JBX8), ferredoxin (C7JAX6), glutaredoxin GrxC (C7JGR1), and bacterioferritin (C7JF76) were strongly upregulated as the titer increased (Table 1). Although redox homeostasis inside cells is a common sense mechanism, the differential expression of these proteins indicated its unique role in A. pasteurianus. A 22.59-fold change has been documented in bacterioferritin that can store iron in the ferric form and is involved in resisting redox stress, such as protection from O2 and radical products or detoxification of excess iron (Figueiredo et al., 2012; Honarmand Ebrahimi et al., 2015). In our study, ferredoxin was also upregulated 8.5-fold, which was consistent with the expression of proteins involved in redox homeostasis in response to environmental stress. Glutaredoxin (7.16-fold), which was originally identified as a thiol transferase responsible for the reduction of protein disulfides, also comprises NADPH, GSH, and peroxidase activity, as well as the glutathione reductase activity involved in redox sensing and regulation of gene expression (Kalinina et al., 2014; Rouhier et al., 2010). Moreover, the katE and oxyR mutant strains of A. pasteurianus NBRC3283 showed greater sensitivity to hydrogen peroxide; their growth was similar to that of the parental strain in the ethanol oxidizing phase, but was delayed in the presence of acetic acid in the peroxidation phase (Okamoto-

3.7. Transcriptional regulators respond to high titer stress

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(C7JBS7, 4.22-fold) have exhibited transcriptional repressor activity and regulate a variety of genes involved in bacteria motility, exopolysaccharide biosynthesis, and quorum sensing. The overexpression of mucR led to an increase in mucoid colonies of Sinorhizobium meliloti (Caswell et al., 2013; Janczarek and Urbanik-Sypniewska, 2013). Its high expression (4.22-fold) may confer a highly resistant cell envelope to the cell, further clarifying the molecular modulatory component involved in pellicle polysaccharide formation during acid resistance in A. pasteurianus (Kanchanarach et al., 2010). In addition, BolA modulated cell morphology and biofilm formation by interacting with the promoter regions of dacA, dacC, and mreB, and it also modulated the balance of OmpF/OmpC to change bacterial permeability (Freire et al., 2006). Currently, it is regarded as a master and global transcriptional regulator (Dressaire et al., 2015). The upregulation of BolA and Ros/MucR may help strengthen the whole cell envelope and lead to resistance. Actually, the transcriptional regulators described above were involved in DNA protection, growth heterogeneity/citrate cycle in the cytoplasm, multidrug transporters in the membrane, and the outer surface of the cell envelope, respectively, indicating multiple levels of transcriptional regulation in response to titer stress.

3.8. The two component system and toxin-antitoxin system respond to high titer stress It is an interesting issue how the A. pasteurianus cells sense and modulate the acetic acid stress signal. Bacterial two component system (TCS) consists of two protein components: a sensor that monitors some environmental parameter and a response regulator that mediates a change in gene expression as feedbacks to the sensor signals (Li et al., 2002). Toxin-antitoxin systems (TAS) are small genetic modules widely distributed in chromosome and plasmid in bacteria and archaea that are generally consisted of a pair of genes encoding a stable toxin and a labile antitoxin that counteracts toxin activity (Hayes et al., 2014; Maisonneuve et al., 2013). Although a two component system (TCS) and toxin-antitoxin system (TAS) have been implicated in environmental signals and the global regulatory network in most bacteria (Foo et al., 2015; Shimada et al., 2015; Norton and Mulvey, 2012; Butt et al., 2014), their differential expression in A. pasteurianus have been rarely been reported. Our previous work showed that special TAS and TCS were existed in the genome sequence of A. pasteurianus Ab3 (Xia et al., 2016). In the current study, NAD-dependent iron-containing ADH (C7JIA3) was downregulated at high acidic titer, which had an essential regulatory role in the two component systems (ErcS, EraSR, ErbR and ErdR) involved in the signal transduction of ethanol oxidation in P. aeruginosa. Its mutant, NH1, showed an extreme long lag phase and apparent reduction in the transcription of structural genes encoding ethanol oxidation proteins (Hempel et al., 2013). Additionally, our study also detected OmpR (C7JBU0, 2.67-fold up-regulated), one subunit of the two component system EnvZ-OmpR, which modulated OmpC and OmpF expression in response to osmotic and acid stress (Foo et al., 2015; Shimada et al., 2015). The RelE/RelB system belongs to the type II toxin-antitoxin system (Leplae et al., 2011). The antitoxin protein RelB (C7JIY9) was upregulated 3.29-fold under high titer stress. In E. coli, toxin-antitoxin systems have been proven to function in stress responses (Norton and Mulvey, 2012), the persister phenotype (Butt et al., 2014), and stabilization of horizontally acquired genetic elements (Bustamante et al., 2014). In Komagataeibacter europaeus, Dinj2 and Dinj1 contained in the plasmid pJT2, a homologous toxin-antitoxin module, was confirmed to contribute to module the growth of cells facing 5% acetic acid stress (Trcek 2015a). However, there is currently not much more direct experimental information about either the TAS or TCS network in A. pasteurianus. Nevertheless, it is rational that both TAS and TCS may be implicated in the acetic acid signaling modulatory pathway in A. pasteurianus.

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3.9. Miscellaneous In the acetic acid fermentation process, A. pasteurianus can utilize glucose and ethanol for growth and as an energy supply (Sakurai et al., 2013). In this previous report, the transcriptome analysis has shown an apparent difference in primary sugar metabolism in response to a relatively low titer; and our recent study of A. pasteurianus Ab3 also showed an altered bioprocess when the titer was switched from 3% to 7% (w/v). Interestingly, the higher titer of up to 9% (w/v) did not significantly increase the number of differentially expressed proteins, with the exception of C7JGI2 and C7JHB8, implying that the dominant cellular processes have already been adjusted in response to the current stress (Table 1). It suggested that A. pasteurianus Ab3 may initiate a distinct biological process in higher titer conditions compared with the normal conditions (often b7% titer, w/v). Cation/copper resistance transporter ATPase CopZ (C7JD70) is involved in cation resistance and required for normal cellular cation content (Radford et al., 2003). PPase (C7JBD6) catalyzes the hydrolytic cleavage of inorganic pyrophosphate (PPi) in all living organisms; its defect led to yeast cell cycle arrest and autophagic cell death. Thus, PPi homeostasis becomes a critical issue for the cell (Serrano-Bueno et al., 2013). Therefore, PPi homeostasis resembles a socalled housekeeping cell process and may be a clue to the underlying acid resistance mechanism in A. pasteurianus. Moreover, a larger number of uncharacterized protein species (approximately 38) were differentially expressed in the P9:P3 test. In particular, C7JBB5, C7JFU5, C7JHL8, C7JG70, and C7JG51 were upregulated 2.33- to 11.24-fold under high titer stress, whereas C7JBV3 was continuously downregulated. Although their exact functions in acetic production and resistance are unknown, they are exclusively membrane binding proteins that should be focused on in future investigations. In conclusion, A. pasteurianus Ab3 samples from high acidic titer rice vinegar fermentation were analyzed using an iTRAQ-based comparative proteome technique in the current study. Many more novel and differentially expressed proteins were identified, which provides a global view of the systemic alterations of the proteomic profile during acetic acid titer transition. Accordingly, amino acid deamination and fatty acid synthesis may be implicated in the acid shock responses, and the two component systems and toxin-antitoxin system may participate the signaling network. The homeostasis of oxidative stress, protein biosynthesis and folding, and cell envelope may reflect a bet-hedging strategy for enhanced survival to acid stress and substantially increase the fitness of the cell (Okamoto-Kainuma et al., 2008). Combining with the previous observations, we agree that the improved acid resistance of industrial A. pasteurianus may not be simply achieved by modifying one protein or pathway, but a long-term adaption of the entire physiological network may promote the interests of industrial strains with the capacity of a high-yielding titer and acid resistance. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.ijfoodmicro.2016.09.016. Funding The work was financially supported by grants from the National Nature and Science Foundation of China (31171745) and the Nature and Science Foundation of Zhejiang Province (LY15C200006) to X. Liang.

Conflicts of interest The authors declare that they have no conflicts of interest.

Ethical approval This paper does not contain any studies with human participants or animals.

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Acknowledgement We are also indebted to Dr. Shaoyong Chen (BIDMC, Harvard Medical School, Boston, USA) for reading through our manuscript.

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