Global transcriptomic analysis of Cronobacter sakazakii CICC 21544 by RNA-seq under inorganic acid and organic acid stresses

Journal Pre-proofs Global transcriptomic analysis of Cronobacter sakazakii CICC 21544 by RNA-seq under inorganic acid and organic acid stresses Ailian Zhou, Yifang Cao, Donggen Zhou, Shuangfang Hu, Wanjing Tan, Xinglong Xiao, Yigang Yu, Xiaofeng Li PII: DOI: Reference:

S0963-9969(19)30849-X https://doi.org/10.1016/j.foodres.2019.108963 FRIN 108963

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Food Research International

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Please cite this article as: Zhou, A., Cao, Y., Zhou, D., Hu, S., Tan, W., Xiao, X., Yu, Y., Li, X., Global transcriptomic analysis of Cronobacter sakazakii CICC 21544 by RNA-seq under inorganic acid and organic acid stresses, Food Research International (2019), doi: https://doi.org/10.1016/j.foodres.2019.108963

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Title page Global transcriptomic analysis of Cronobacter sakazakii CICC 21544 by RNA-seq under inorganic acid and organic acid stresses Ailian Zhoua1, Yifang Cao

a1

, Donggen Zhoub, Shuangfang Huc, Wanjing Tan a,

Xinglong Xiaoa*, Yigang Yua, Xiaofeng Lid* a. School of Food Sciences and Engineering, South China University of Technology, Guangzhou City, Guangdong Province 510640, China. b. Ningbo International Travel Healthcare Center. No.336 Liuting street, Haishu district, Ningbo city, Zhejiang province, 315012, China. c. Key Laboratory of Molecular Epidemiology of Shenzhen, Shenzhen Center for Disease Control and Prevention, Shenzhen City, Guangdong Province, 518055, P.R. China d. State Key Laboratory of Pulp and Paper Engineering, College of Light Industry and Food Sciences, South China University of Technology, 381Wusan Road, Tianhe District, Guangzhou City 510640, Guangdong Province, China

1. These authors contributed equally to this work. *Corresponding author: Xinglong Xiao Postal address: Research Center of Food Safety and Detection, School of Food Science and Engineering, South China University of Technology, 381Wushan Road, Tianhe District, Guangzhou City, Guangdong Province, 510640, China. 1

E-mail: [email protected]

Tel: +86-20-22236819, +86-13826279058

Fax: +86-20-22236819 Xiaofeng Li Postal address: State Key Laboratory of Pulp and Paper Engineering, College of Light Industry and Food Sciences, South China University of Technology, 381Wusan Road, Tianhe District, Guangzhou City 510640, Guangdong Province, China E-mail: [email protected]

Tel: +86-13760716620

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Global transcriptomic analysis of Cronobacter sakazakii CICC 21544 by RNA-seq under inorganic acid and organic acid stresses Abstract Cronobacter sakazakii is a common foodborne pathogen that can tolerate various stress conditions. Acidic environment is a common stress condition encountered by bacteria in food processing and gastrointestinal digestion, including both inorganic and organic acids. In order to elucidate the Acid Tolerance Response (ATR) of C. sakazakii, we performed high-throughput RNA-seq to compare gene expression under hydrochloric acid and citric acid stresses. In this study, 107 differentially expressed genes (DEGs) were identified in both acids, of which 85 DEGs were functionally related to the regulation of acid tolerance. Multiple layers of mechanisms may be applied by C. sakazakii in response to acid stress: Firstly, in order to reduce excessive intracellular protons, C. sakazakii pumps them out through trans-membrane proteins or consumes them through metabolic reactions. Secondly, under acidic conditions, a large amount of reactive oxygen species and hydroxyl radicals accumulate in the cells, resulting in oxidative damage. C. sakazakii protects cells by up-regulating the antioxidant stress genes such as soxS and madB. Thirdly, C. sakazakii chooses energy efficient metabolic pathways to reduce energy consumption and maintain necessary processes. Finally, genes involved in chemotaxis and motility were differentially expressed to respond to different acidic conditions. This study systematically analyzed the acid-resistant mechanism

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of C. sakazakii under the stress of organic and inorganic acids, and provided a theoretical basis for better control of its contamination in food. Keywords Cronobacter sakazakii; RNA-sequence; acid tolerance response; proton consumption; chemotaxis Chemical compounds studied in this article Hydrochloric acid (PubChem CID 313); Citric acid (PubChem CID 311); Chloroform (PubChem CID 6212); Isopropanol (PubChem CID 3776); Agarose (PubChem CID 73557002) 1. Introduction Cronobacter sakazakii is a Gram-negative, non-spore-forming bacterium that has been associated with rare but life-threatening infections especially in premature infants and immunocompromised adults, with a reported mortality rate of 27% (Friedemann, 2009). C. sakazakii has been frequently isolated from acidic foods such as fresh-cut fruits, yogurt and cheese products, suggesting that C. sakazakii is relatively resistant to acidic growth conditions (Jaradat, Al Mousa, Elbetieha, Al Nabulsi, & Tall, 2014; Ueda, 2017). It was reported that C. sakazakii is similar to Salmonella spp. but less than Escherichia coli in tolerance to acid, which also varies with different types of acids (EdelsonMammel, Porteous, & Buchanan, 2006). A series of experiments were conducted to measure the survival curves of C. sakazakii in nine fruit and

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vegetable juices. Results showed that most fruit and vegetable juices support the growth of C. sakazakii (Beuchat et al., 2009). It was reported that the antibacterial activity of Kefir is mainly attributed to the metabolites produced during the fermentation process instead of pH and acidity. Further analysis showed that organic acids play the key role (D. H. Kim et al., 2018). Similar results were obtained in another study comparing the antibacterial effects of Kefir and common fermented yoghurt. Even though the pH of ordinary fermented yogurt is lower than that of Kefir, ordinary fermented yogurt cannot completely inactivate pathogens like Kefir (Chang et al., 2018). Therefore, we can guess that the antibacterial effects of organic acids and inorganic acids are quite different. It is necessary to study the differences between them. Up to now, the response of C. sakazakii exposed to various stresses and the resistance mechanisms have been well documented, mainly including desiccation stress, cold or heat shock and osmotic stress (Burgess et al., 2016; Fei et al., 2017; Hu, Yu, & Xiao, 2018). Moreover, studies of virulence related genes showed that they also contribute to the environmental stress resistance of C. sakazakii (Bao et al., 2017; Aly, Domig, Kneifel, & Reimhult, 2019). However, there are few studies on the acid response of C. sakazakii and the underlying mechanisms still remain unclear. To assess the role of yellow pigmentation on the growth of C. sakazakii under acid stress, experiments were conducted to compare colorless mutants with wild-type strains. These strains exhibited similar tolerance to acid stress at pH 4.5, but mutants became more sensitive when incubated at pH 2.0 (Johler, Stephan, Hartmann, Kuehner, & Lehner, 2010). The analyses on the ompR defective mutant demonstrated that this gene is a key

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player in the response of C. sakazakii to acid stress (Alvarez-Ordonez et al., 2014). Ling et al. (2018) concluded that gene grxB seems to contribute to the survival and biofilm formation of C. sakazakii under acidic growth conditions by investigating cellular morphology, surface hydrophobicity and motility. Acids can be classified into organic acids and inorganic acids according to their constituent elements. Organic acids are generally recognized as safe and have been widely used in reducing pathogens in foods. According to reports, the fact that organic acids inactivate microorganism more effectively is due to the undissociated form (Cherrington, Hinton, Mead, & Chopra, 1991). They penetrate bacterial cell membranes more easily and dissociate into anions and protons within cells to decrease cytoplasmic pH, thus affecting cell metabolic activity. According to several researches, the order of inhibition of acids against C. sakazakii was acetic acid ≈ butyric acid ≈ propionic acid > lactic acid > citric acid > malic acid >formic acid > hydrochloric acid (Oshima et al., 2012; Kim & Park, 2018). Obviously, C. sakazakii may have different resistant mechanisms for inorganic acids and organic acids. However, there has been no systematic analysis about the tolerant mechanisms of C. sakazakii under acidic stress so far, let alone the differences between organic acids and inorganic acids. We compared the transcriptomic

differentiations between control group and acid treatment groups by using high throughout RNA-

sequencing (RNA-seq). The aim of our study is to elucidate the major transcriptomic features of acid tolerance response (ATR) in C. sakazakii

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under different acidic environments. 2. Materials and methods 2.1 Culture conditions of strains and assessment of growth ability in acids C. sakazakii CICC 21544 was obtained from Guangdong Culture Collection Center. It was stocked at −80°C in Tryptic Soy Broth (TSB, HuanKai, Guangzhou, China) with 30% glycerol and activated after inoculated twice onto Tryptic Soy Agar (TSA, HuanKai, Guangzhou, China) plate and incubated at 37°C for 24h. Cells were collected by centrifugation at 5000×g for 5min when grown to exponential phase (OD600=0.5). The cells were washed three times with phosphate buffer and then resuspended to a final concentration of 8 log CFU/ml. 1 ml culture was transferred into 100 ml TSB broth which was pre-adjusted with HCl (1M, Damao, Tianjin, China) or citric acid (1M, Macklin, Shanghai, China) to 4.0, 4.2 or 4.5 (non-acidified TSB (pH 7.0) was used as negative control). The broth was cultured at 37℃ for 24h and the sample was taken at intervals of 1h to measure the optical density at 600 nm. The growth curves were drawn with time as abscissa and OD600 as ordinate. When the groups (pH 4.5) reached a concentration of 106 CFU/ml, the above centrifugation and washing operations were repeated. The cells obtained were immediately inactivated with liquid nitrogen and temporarily stored for the following transcriptome analysis. 2.2 RNA extraction, library construction and sequencing

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The total RNA was extracted and isolated by Trizol method. Firstly, appropriate amount of bacteria was ground fully with a mortar and pestle in liquid nitrogen and then immediately transferred to a 1.5 ml centrifuge tube to mix well with 1 ml Trizol (Life technologies, Guangzhou, China). The mixture was placed at room temperature for 10 min to allow sufficient lysis. Chloroform (Guangzhou Chemical Reagent Factory, Guangzhou, China) was added, vortexed, and spun at 12000 rpm for 10min. The upper aqueous phase was taken and isopropanol (Guangzhou Chemical Reagent Factory, Guangzhou, China) of equal volume was added, then it was centrifuged after standing for 1 h at -20℃. Discarded the supernatant and washed the precipitate with 75% ethanol (Guangzhou Chemical Reagent Factory, Guangzhou, China). The RNA was dried under vacuum after repeating the above operation. Finally, 20-50 μl RNase-FreeWater (Magen, Guangzhou, China) was added to dissolve RNA under room temperature for 10 min before centrifugation (12000 rpm， 1min). Nanodrop micro spectrophotometer (Thermo Fisher Scientific, Nanodrop 2000, China), Agarose gel electrophoresis and Agilent 2100 Bio-analyzer (Agilent Technologies, Santa Clara, China) were used to verify the RNA quality and integrity. After RNA extraction, the mRNA was enriched and broke into 200 nt fragments in fragmentation buffer after removing ribosomal RNA. The first strand of cDNA was synthesized and subsequently the second strand was synthesized with the help of dUTP. After purified with 1.8X Agencourt AMPure XP Beads, cDNA fragments were end repaired, added with poly (A) and ligated to sequencing linkers. The products were screened using agarose gel electrophoresis, purified and enriched by PCR to construct the final cDNA library. The cDNA library was sequenced using the Illumina

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HiSeq™2500 (Guangzhou, China) from Gene Denovo Co. 2.3 Read alignment and normalization of gene expression levels In order to ensure reliable analysis results, the quality control software fastp is used to control the raw data to reduce data noise and obtain clean data for subsequent analysis. These sequencing reads were then mapped to reference sequence by software package the SOAP aligner/soap2. 2.4 Differentially expressed genes (DEGs) and function enrichments After calculating the expression level of each gene, the edgeR was applied to analyze differential expression. The false discovery rate (FDR) was used to determine the threshold for p-values in multiple tests. During the analysis, a threshold value of FDR ≤0.01 and an absolute value of the log2 FC (Fold Change) ≥2 were used to judge the significance of the differences in gene expression. The DEGs were then used for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. 2.5 Quantitative real-time PCR (qRT-PCR) validations To verify RNA-seq data, qRT-PCR analysis was performed on several randomly genes selected from all DEGs using the primers listed in Table1. Total RNA was isolated using Trizol reagent according to the manufacturer's protocol and used for cDNA synthesis with reverse transcriptase. The kit used for the cDNA synthesis was NEB #7530 kit (New England Biolabs, USA). A 7500 Fast Real-time PCR System (Applied Biosystem,

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Foster, USA) was used to perform thermal cycling and record fluorescence changes. 2xTaq PCR Master Mix (Thermo Fisher Scientific, Guangzhou, China), ROX, primers and double-distilled water were used for the reaction system. PCR reaction was predenaturated at 95℃ for 2 min. Then 40 cycles of denaturation at 95℃for 5 s and annealing at 60℃ for 40 s were carried out. Fluorescence was measured at 60℃. The quantification of each transcript was repeated using total RNA as the starting materials and each qPCR was performed in triplicate. 3. Results 3.1 Effect of acid stress on C. sakazakii growth The ability of C. sakazakii CICC 21544 to tolerate acidic conditions was analyzed in TSB broth acidified with HCl and citric acid. The lowest tolerable pH values of C. sakazakii with HCl and citric acid were 4.0 and 4.2, respectively. The ability of C. sakazakii to grow under acidic conditions strongly depends on the type of acid and the pH value (Fig. 1). By comparing the growth curves of the two graphs, it is not difficult to find that the growth of C. sakazakii in hydrochloric acid and citric acid is significantly different even at the same pH. Different acid stresses delayed the growth cycles of strain to differing degrees. Compared with hydrochloric acid stress, the strain subjected to citric acid stress obviously need longer time to adapt to acidic environment and resume growth. Moreover, the growth rate under citric acid stress was slower (Fig. 1). 3.2 Data processing and DEGs analysis

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In the following analyses, the control group was abbreviated as CK. The experiment groups treated with hydrochloric acid and citric acid were abbreviated as HCl and CA, respectively. The Q30 quality scores of these three transcriptomes were more than 98% and the GC contents were more than 55%. We successfully annotated 3055 known genes, and no new gene was found. These data indicated that the sequencing quality was good enough for further analysis. DEGs produced from the collection of mapped genes were screened with the criteria of |log2FC|≥2 and FDR ≤0.01. In the comparison with CK, 216 genes were identified differentially expressed in HCl group, of which 138 were up-regulated and 78 were down-regulated (Fig. 2A). In the comparison to CK, 627 DEGs were found in CA group, among which 153 were up-regulated and 474 were down-regulated (Fig. 2B). The Venn diagram revealed that 109 and 520 genes were found specifically altered in HCl and CA groups, respectively. The expression of 107 genes were found significantly altered both in HCl and CA group compared to the CK (Fig. 2C). 3.3 GO and KEGG analyses of DEGs GO and KEGG analyses were applied to determine the function of identified differentially expressed genes. DEGs in the biological process category were mainly associated with cellular process, metabolic process, and single-organism process; Most DEGs were identified in the molecular functional categories with catalytic and binding activities; DEGs within the cell component category were mainly enriched in cell and

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cell part. In KEGG analysis, the DEGs in CK vs HCl were matched to 16 KEGG pathways. The most significantly changed pathways included signal transduction, cell mobility and amino acid metabolism. For example, bacterial chemotaxis is the most concentrated pathway in bacterial motility. The DEGs in CK vs CA were matched to 17 different KEGG pathways, mainly involved in carbohydrate metabolism, membrane transport and amino acid metabolism. Membrane transport were mainly enriched in three pathways: phosphotransferase system (PTS), ABC transporter and bacterial secretion system. 3.4 Validation of DEGs using qRT-PCR In this study, several DEGs were selected randomly to validate results of RNA-seq. As can be seen from Fig. 3, qRT-PCR data and the RNA-seq data are in good agreement (R2=0.9433). In brief, the qRT-PCR data showed similar patterns to the results obtained from RNA-seq, although the values of fold change were different due to different references. 4. Discussion With more and more reports of foodborne infection events associated with acidic foods, the mechanism of survival of Enterobacteriaceae at low pH has attracted increased attention. According to previous reports, 85 out of 107 genes were identified as important genes associated with acid

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stress response (Table 2). Combining the identified DEGs with functional analysis such as KEGG and GO annotations (Fig. 4), we analyzed the underlying mechanism under acid stress in C. sakazakii from the following aspects (Fig. 5). 4.1 Intracellular proton reduction When cells are in an acidic environment, the cytoplasmic membrane integrity and proton motive force are destroyed, resulting in excessive intracellular proton and inhibited growth of bacteria. Therefore, the stress response system is activated. Cells can reduce intracellular protons in two ways to avoid fatal acid environmental damage. 4.1.1 Protons consumption through metabolic reactions The expression of genes arcA, OTC and arcC involved in the pathway of arginine metabolism were up-regulated drastically by 13.67, 3.57 and 14.45 log2 FC in HCl group, respectively. Arginine metabolism via arginine deiminase pathway is ubiquitous in various bacteria and provides protection for the survival and growth of bacteria in acidic environments (Xiong et al., 2015; Xu et al., 2016; Younho et al., 2012). This pathway converts arginine into ammonia, CO2 and ornithine, accompanied by ATP production. It consumes protons by binding to ammonia to form ammonium ions, and then increases the pH to enhance its acid stress resistance. Based on these data, we came to the conclusion that C. sakazakii consumes protons mainly through arginine deiminase (AD) system. In consistence, transcriptional levels of these genes increased even more in

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CA group. The reason why arginine deiminase system is the preferred acid-resistant system may be that it not only consumes protons but also produces energy (Burne, Parsons, & Marquis, 1989). In our results, the 2,3-butanediol pathway is another important AR system and it was speculated to play an acid-resistant role by altering metabolism from producing acids to forming neutral compounds. This pathway consumes one proton at each step and maintains the intracellular NAD+/NADH balance (Blomqvist et al., 1993). Gene butA which encodes acetoin reductase is reported to increase expression at pH 6 (Barriuso-Iglesias, Schluesener, Barreiro, Poetsch, & Martin, 2008). Another gene in the 2,3-butanediol pathway, ilvB was up-regulated by 3.38 and 8.54 log2(FC), in HCl and CA groups, respectively, and its amplitude of up-regulation was similar to gene butA. The glycine cleavage system catalyzes the decarboxylation of glycine to consume protons and produce carbon dioxide, ammonia and methylene tetrahydrofolate. In our study, genes gcvPTH were up-regulated to varying degrees, in which gcvH was up-regulated by 2.86 and 2.07 log2 (FC) in HCl and CA groups, respectively. This system is also important for the adaptability of bacteria under adverse environments (Okamura-Ikeda, Ohmura, Fujiwara, & Motokawa, 1993; Yadav & Sundd, 2018). In addition to the above several systems, the increased expression of gene speC (ornithine decarboxylase), bsdC (phenolic acid decarboxylase) and dmsB (dimethylsulfoxide reductase) indicates that some enzymes consume protons through decarboxylation or reduction during acid stress.

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4.1.2 Protons were pumped out The change of cytoplasmic membrane composition is one of the main mechanisms for bacteria to adapt to environmental stress. Cyclopropane fatty acids (CFA) synthesized by cyclopropane fatty acyl phospholipid synthase (encoded by gene cfa) are the major component of membrane phospholipids among many bacteria (Charoenwong, Andrews, & Mackey, 2011). In HCl group, gene cfa was significantly up-regulated by 3.61 log2 (FC), and the increased expression in CA group was approximately twice as much as that in HCl group. It has been showed that the increase of CFA level in the cell membrane could decrease the permeability of membrane to protons, so as to resist the proton inflow at low external pH. On the other hand, the ability of cells to pump protons was also improved (Shabala & Ross, 2008). Under the experimental conditions of this study, C. sakazakii mainly underwent anaerobic respiration. The C4 dicarboxylic acid transporters encoded by gene dcuA and dcuB are critical for the transport of C4 dicarboxylates. The up-regulated expression levels of these two genes were both about 2-3 log2 (FC) in our study. The transport of C4 dicarboxylates is accompanied by proton pumping (Zhang et al., 2017; Zientz, Six, & Unden, 1996). 4.2 Protect cells from damage Many environmental stresses, including acids, cause oxidative damage to cells by producing hydroxyl radicals and accumulating reactive oxygen

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species (Hu et al., 2018). Therefore, cells must respond to oxidative damages to survive in adversity. Consistent with the above conclusion, the expression of gene soxS was dramatically increased about 16 log2 (FC) in both groups. SoxS is a transcriptional regulator of the AraC family that activates the expression of many regulatory genes that protect cells from oxidative stress, such as genes encoding superoxide scavenging enzymes and DNA repair enzymes (Nakayama & Zhang-Akiyama, 2017). MdaB, the gene encoding NADPH quinone reductase, is another important gene that protects cells from oxidative stress (Hong, Wang, & Maier, 2008). In addition to maintaining intracellular water balance, glycerol can stabilize proteins and prevent oxidative damage by avoiding the production of hydroxyl radicals and scavenging reactive oxygen species. Glycerol 3-phosphate, a direct precursor of phospholipid biosynthesis, would lead to an imbalance in membrane phospholipid levels if consumed excessively (Flower, 2001). According to our results, the increase of gene glpF and glpK expression indicated that glycerol and glycerol-3-phosphate may play a positive protective role under acid stress. Strikingly, gene glpA was also significantly up-regulated. We speculated that the reversible enzyme encoded by this gene mainly converts DHAP (dihydroxyacetone phosphate) to glycerol 3-phosphate under acid stress to increase the synthesis of membrane phospholipids. On the other hand, studies have found that this enzyme participates in redox shuttle and plays a proton pump role in the electronic respiratory chain (Yeh, Chinte, & Du, 2008). In addition to oxidative damage, cells are also vulnerable to viruses under environmental stress. CRISPR/Cas system is an adaptive bacterial

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immune system targeted at phages and plasmids (Hochstrasser et al., 2014). In our study, up-regulated expression of two cas genes was observed. In addition to immune function, this system can also regulate and control gene expression level temporarily without changing gene sequence itself (Bozic, Repac, & Djordjevic, 2019). 4.3 Metabolic regulation of high efficiency and energy conservation genes under adversity According to our results, several genes related to phosphotransferase system (PTS) such as chbC, fruB, malX and manX were up-regulated to various degrees under acid stress. In order to survive in harsh environments, bacteria have developed many economical ways of resource absorption and energy utilization, such as PTS system (Tchieu, Norris, Edwards, & Jr, 2001). The uptake and phosphorylation of sugar substrates catalyzed by phosphoenolpyruvate-dependent PTS is the primary mechanism of carbohydrate accumulation in bacteria (Behrens, Mitchell, & Bahl, 2001). PTS is also a common signal transduction system which allows bacteria to sense changes in the external environment, regulating gene expression and adaptive response of cells to the environmental conditions (Xu et al., 2019a). Apart from adopting energy-efficient energy absorption methods, many metabolic pathways requiring energy consumption are down-regulated in order to survive, and the expression of related genes is correspondingly down-regulated. For example, genes such as nrdA and rutCDG involved in the pathway of pyrimidine metabolism were down-regulated. The gene iucABCD involved in the lysine degradation pathway was also down-

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regulated. Strikingly, the metabolism from putrescine to succinate not only consumes energy, but also produces protons and H2O2, which are harmful to cells (Kurihara, Kato, Asada, Kumagai, & Suzuki, 2010). Consistently, genes involved in putrescine metabolism, puuACDEPR and sad, are also down-regulated. 4.4 Different regulation mechanisms under the stress of HCl and CA Interestingly, it could be seen from our results that 24 genes of C.sakazakii exhibited completely opposite expression patterns under the stresses of HCl and CA. These genes were enriched in the chemotaxis and motility pathways of bacteria. The fact that many genes are involved in chemotaxis and motility suggests that both are the result of survival of the fittest in natural environment. Chemotaxis and motility can provide bacteria with the ability to adapt to various external environmental conditions (Xu et al., 2019b). Bacterial chemotaxis refers to the tendency of bacteria with move ability to favor advantageous environment and to avoid harmful conditions. This behavior is generally achieved by sensing environmental signals and adjusting the direction of flagellum rotation (Wong-Ng, Celani, & Vergassola, 2018). The perception of external signals is accomplished by methyl-accepting chemotaxis proteins (MCPs) and Aer sensor (Samanta, Widom, Borbat, Freed, & Crane, 2016). Eight MCPs with significant changes in expression were detected in this study. Chemotaxis is closely related to virulence and it has been revealed that gene mcp, aer, cheB and cheV act importantly in the adhesion regulation of Vibrio alginolyticus. The absence

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of these genes can lead to defects in adhesion, chemotaxis and flagellum assembly (Huang et al., 2017). The mcp mutant of C. sakazakii has defects in the invasion and adhesion to epithelial cells, and reduced toxicity (Choi et al., 2015). HCl exists mainly in the form of ions and poisons bacteria by destroying the cell membranes and intracellular enzymes. After sensing the ionic stress, C. sakazakii escaped from such an environment by up-regulating chemotaxis and flagellar genes. Citric acid is an intermediate metabolite of tricarboxylic acid cycle, which is a normal product of cell metabolism, and the bacteria do not chemotactically respond to it. Organic acids can deceive bacteria in a similar way, allowing them to easily enter cells and then dissociate to cause damage. This is consistent with the conclusion that organic acids have stronger inhibitory effect on bacteria (Alvarez-Ordonez et al., 2014). It has demonstrated that genes associated with flagellar formation and chemotaxis were significantly down-regulated when C. sakazakii was exposed to an amino acid deficient environment (Chen et al., 2018). This may imply that flagellation and chemotaxis are not necessary for C. sakazakii under severe stresses, such as an extreme lack of energy sources. 4.5 other mechanisms In addition to the measures mentioned above, C. sakazakii has made other adjustments to help itself better adapt to this environment. These include up-regulation of genes that contribute to bacterial growth and adaptability and down-regulation of genes that are not conducive to growth or

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unnecessary. 5. Conclusion Here we systematically analyzed the acid tolerant mechanism of Cronobacter sakazakii CICC 21544 by using high throughput transcriptome sequencing technology. 85 of the 107 DEGs identified were functionally associated with acid tolerance response. In order to reduce excessive intracellular protons, C. sakazakii pumps them out through trans-membrane proteins or consumes them through metabolic reactions. For oxidative damage caused by acid stress, C. sakazakii scavenged reactive oxygen species and hydroxyl radicals accumulated in cells by up-regulating the antioxidant genes. Bacteria survive by reducing energy consumption and maintaining the necessary processes as an energy-saving strategy. As for genes related to chemotaxis and motility, C. sakazakii exhibited opposite response mechanisms under organic and inorganic acidic conditions. This may provide a new perspective for organic acids to better inactivate pathogens. Acknowledgements This work was supported by the National Key Research and Development Program of China (2018YFC1602201), Science and Technology Program Foundation of Guangzhou, China (201904010077) and Natural Science Fund of Zhejiang (No.LY16H260004). We thank Guangzhou Gene Denovo Biotechnology Co., Ltd., China, for technical assistance.

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Fig captions Fig. 1. Growth curves of C. sakazakii CICC 21544 in the laboratory medium acidified with different acidic substances. (A) Tryptic Soy Broth [TSB] acidified with 1M hydrochloric acid at different levels in the range pH 4.0-4.5. (B) TSB acidified with 1M citric acid at different levels in the range pH 4.0-4.5. TSB in neutral pH was set as control. All experiments were performed in triplicate. Fig. 2. Global comparison of transcriptional profiles and differentially expressed genes under organic and inorganic acids. CK is the abbreviation of control group. HCl and CA are the abbreviation of hydrochloric acid and citric acid treatment groups, respectively. (A) Global transcript profiles of C. sakazakii in hydrochloric acid group; (B) Global transcript profiles of C. sakazakii in citric acid group; and (C) Venn diagram shows a comparison of C. sakazakii CICC 21544 acid resistance genes under different acid stress.

24

Fig. 3.qRT-PCR validations. The X-axis represents the log2 fold change of RNA-seq, the y-axis represents the log2 fold change of qRT-PCR, and the R2 represents the R-square of the regression line. Fig. 4. Transcript profiles of genes enhancing ATR in C. sakazakii CICC 21544. Fig. 5. The underlying stress mechanism of ATR in C. sakazakii CICC 21544.

25

Graphical abstract

26

Highlights 

Proton reduction, cell protection, energy-saving are main mechanisms to acid stress



Arginine deaminase pathway and 2,3-butanediol pathway consume protons



Che, mcp , flg up-regulated in inorganic acid while down-regulated in organic acid

27

Fig. 1

TSB

HCl4.0

HCl4.2

HCl4.5

TSB

B 1.4

1.3

CA4.0

CA4.2

CA4.5

1.3

OD600nm

OD600nm

A 1.4 1.2 1.1 1.0

1.2 1.1 1.0

0.9

0.9

0.8

0.8

0.7

0.7

0.6

0.6

0.5

0.5

0.4

0.4

0.3

0.3

0.2

0.2

0.1

0.1

0.0 0

2

4

6

T/h

0.0

T/h 8 10 12 14 16 18 20 22 24

0

28

2

4

6

8

10 12 14 16 18 20 22 24

Fig.2

A

B

C

29

Fig. 3

30

Fig. 4

31

Fig. 5

32

Table 1 Primer pairs used for qRT-PCR validation. Gene name

Gene annotation

Primer pair

Reference

gltB

glutamate synthase (NADPH) large chain

This study

butA

(S,S)-butanediol dehydrogenase / acetoin reductase

ompC

Acid induced outer membrane protein

cfa

Cyclopropane fatty acyl phospholipid synthase

glpK

glycerol kinase

puuA

Gamma-glutamyl-putrescine synthetase

rutG

putative pyrimidine permease RutG

asnA

aspartate--ammonia ligase

cheA

chemotaxis family, sensor kinase CheA

cheZ

Chemotaxis regulator CheZ

fliC

flagellar biosynthesis protein FliC

F,5′-CCGCCGCACCACGACATC- 3′ R,5′-ACGCCCGGCTCAGACACCA- 3′ F,5′-GCGCAGGGCAGGGGATTG- 3′ R,5′-GCGCTTTACGGGTCTGCTCTACTG- 3′ F,5′- CCGATACCGATAGCGCCGTA - 3′ R,5′- GCGGACATCCATGACAGACA - 3′ F,5′-GCCCGAAAAACTACGCCACCTAT- 3′ R,5′-CGCCCCGAAGTTATGCCAGTC- 3′ F,5′-CTCCCGCGCCGTTGTGCT- 3′ R,5′-CCGTTTCGCGCTGGTTGGTAAT- 3′ F,5′-CGCCGAGATCCTGCCCTAACC- 3′ R,5′-GCCCGCGAAGTGAATGCCTATC- 3′ F,5′-CGGGCTGGCGACGATGCT- 3′ R,5′-CGCCGCCGCCACAAAGAC- 3′ F,5′-CTGCCGGACGCCATTCATTTT- 3′ R,5′-GTCGGCGTGGTCCAGTCATCATA- 3′ F,5′-AGGGCCAGGGCACGACGAT- 3′ R,5′-GCGGCTGCAGCGACTCCAT- 3′ F,5′-GCCGCTGGGACGAGTGGTT- 3′ R,5′-AGAAGCTGGGCGTTGGTGAAG- 3′ F,5′-CGTATCGCTGGTGGTGCTAA- 3′ R,5′-CAGCGCCAACCTGAATTTTC- 3′

33

This study (Kothary, Gopinath et al., 2017) This study This study This study This study This study This study This study (Choi, Kim et al., 2015)

Table. 2 Differentially expressed genes in CK vs HCl and CK vs CA under different acid stresses. name

tion 78 arcA 11 OTC 26 arcC 52 ilvB 66 butA 37 gcvH 81 speC 12 bsdC 07 dmsB 74 cfa 91 dcuA 92 dcuB amage 31 soxS 23 mdaB 40 glpF 64 glpK 11 glpA 25 casD 23 casA on strategy 61 chbC 68 fruB 90 malX 93 manX 25 nrdA 21 rutC 23 rutD 16 rutG 97 iucD

Fold change log2FC CK vs HCl CK vs CA

P-value CK vs HCl

CK vs CA

FDR CK vs HCl

13.67 3.57 14.45 3.38 3.34 2.86 4.05 2.96 2.48 3.61 2.12 2.00

20.81 9.47 21.34 8.54 9.04 2.07 8.79 3.36 3.47 6.67 3.52 3.22

15.01 3.63 2.23 2.43 2.86 2.82 3.67

Description CK vs CA

2.39E-10 7.49E-23 7.54E-12 8.16E-55 1.25E-48 0.00 1.99E-08 0.001318 2.45E-07 1.54E-13 1.25E-13 2.79E-07

0.00 0.00 0.00 0.00 0.00 2.83E-22 1.24E-28 2.27E-05 4.68E-21 8.27E-16 1.50E-66 5.87E-29

1.32E-09 6.18E-22 4.47E-11 1.25E-53 1.75E-47 0.00 9.64E-08 0.00383 1.09E-06 9.58E-13 7.87E-13 1.24E-06

0.00 0.00 0.00 0.00 0.00 5.44E-22 3.05E-28 5.30E-05 2.04E-20 1.25E-16 1.30E-65 3.01E-28

Arginine deiminase ornithine carbamoyltransferase carbamate kinase acetolactate synthase (S,S)-butanediol dehydrogenase / acetoin reduct glycine cleavage system protein H ornithine decarboxylase SpeF phenolic acid decarboxylase subunit C dimethylsulfoxide reductase, chain B Cyclopropane-fatty-acyl-phospholipid synthase C4-dicarboxylate ABC transporter anaerobic C4-dicarboxylate transporter

16.63 4.35 5.18 3.25 5.79 2.08 3.78

1.93E-06 9.45E-54 6.73E-87 1.56E-12 1.08E-10 4.43E-09 1.11E-85

1.41E-21 7.76E-11 0.00 7.95e-32 6.15E-14 4.82E-05 1.56E-11

7.92E-06 1.43E-52 1.47E-85 4.47E-12 6.07E-10 2.25E-08 2.37E-84

6.19E-21 9.51E-11 0.00 2.13e-32 8.17E-13 0.000110 1.85E-11

AraC family transcriptional regulator, mar-sox-ro NADPH quinone reductase MdaB glycerol uptake facilitator protein glycerol kinase glycerol-3-phosphate dehydrogenase CRISPR system Cascade subunit CasD CRISPR system Cascade subunit CasA

4.57 2.54 12.02 2.02 -2.77 -15.25 -2.97 -3.75 -6.06

2.79 6.01 13.74 4.44 -4.43 -15.25 -15.15 -5.68 -7.40

4.15E-24 2.27E-05 0.000490 3.70E-46 1.84E-11 7.59E-09 4.56E-10 3.07E-06 5.44E-73

2.02E-06 6.95E-10 6.72E-14 0.00 2.04E-23 1.20E-10 2.39E-19 9.53E-10 5.15E-93

3.55E-23 8.46E-05 0.001518 4.92E-45 1.07E-10 3.82E-08 2.47E-09 1.23E-05 1.02E-71

5.00E-06 7.52E-99 2.41E-13 0.00 9.25E-23 3.76E-10 1.00E-18 2.85E-09 5.42E-92

PTS cellobiose transporter subunit IIC bifunctional PTS fructose transporter subunit IIA PTS system, maltose/glucose-specific IIB compon PTS mannose transporter subunit EIIAB ribonucleotide-diphosphate reductase aminoacrylate peracid reductase aminoacrylate hydrolase putative pyrimidine permease RutG lysine 6-monooxygenase

96

iucB

-5.27

-15.41

2.33E-20

1.97E-27

1.81E-19

9.72E-27

acetyl CoA:N6-hydroxylysine acetyl transferase

94

iucA

-4.92

-9.76

4.23E-11

7.60E-16

1.16E-11

1.11E-15

aerobactin synthase IucA

95

iucC

-4.91

-7.43

1.21E-22

6.47E-32

9.89E-22

3.57E-31

aerobactin synthase IucC

70

puuA

-2.16

-6.83

4.14E-15

1.17E-42

2.78E-14

7.67E-42

Gamma-glutamyl-putrescine synthetase

1

72 puuC 73 puuD 23 puuE 52 puuP 56 puuR 24 sad motility 76 aer 07 cheA 12 cheB 75 cheR 15 cheV 08 cheW 13 cheY 14 cheZ 75 mcp mcp mcp 06 mcp mcp 06 mcp 06 mcp 06 mcp 96 flgK 97 flgL 98 flgM 99 flgN 06 fliC 25 fliZ 56 motA 57 motB

-3.14 -2.29 -2.80 -2.21 -2.65 -2.11

-7.06 -7.05 -21.32 -7.20 -3.00 -3.94

3.52E-26 4.29E-27 0.00 2.96E-10 2.35E-29 5.13E-31

1.66E-49 1.55E-73 0.00 9.90E-28 3.26E-46 8.69E-83

3.12E-25 3.91E-26 0.00 1.62E-09 2.25E-28 5.09E-30

1.19E-48 1.43E-72 0.00 4.95E-27 2.24E-45 8.49E-82

4-(gamma-glutamylamino)butanal dehydrogena gamma-glutamyl-gamma-aminobutyrate hydrola Gamma-aminobutyrate:alpha-ketoglutarate ami Putrescine importer PuuP DNA-binding transcriptional repressor PuuR succinate-semialdehyde dehydrogenase

2.32 2.75 4.04 3.70 3.01 3.22 2.87 2.79 3.27 2.73 2.22 5.06 3.75 2.55 2.86 3.55 2.92 2.42 2.10 2.11 4.20 3.09 2.73 2.30

-3.29 -3.24 -2.90 -3.77 -12.33 -2.37 -2.36 -2.12 -5.21 -3.92 -4.95 -12.18 -4.22 -3.82 -2.21 -11.33 -2.73 -2.55 -2.74 -2.56 -4.56 -3.82 -3.58 -4.71

6.84E-14 0.00 1.98E-24 1.63E-16 8.55E-14 8.35E-27 3.10E-13 4.58E-17 7.18E-35 6.00E-14 1.75E-10 8.18E-12 0.00 2.33E-31 3.27E-23 1.38E-22 0.00 6.73E-46 1.92E-31 0 0 4.83E-21 2.51E-13 9.28E-16

5.72E-06 1.58E-12 4.23E-17 4.38E-20 0.00098 2.81E-32 8.22E-21 1.24E-26 1.21E-07 4.08E-45 1.93E-06 3.07E-05 1.45E-83 1.68E-11 0.00055 0.00098 9.18E-90 4.96E-14 1.55E-15 5.56E-16 0 1.23E-45 6.98E-38 1.73E-99

4.35E-13 0.00 9.50E-24 6.05E-16 5.40E-13 4.44E-27 9.83E-12 1.77E-17 7.56E-34 1.96E-14 9.71E-10 2.32E-12 0.00 2.33E-30 2.73E-22 1.12E-21 0.00 8.86E-45 1.15E-30 0 0 2.08E-20 8.11E-13 3.29E-16

1.39E-05 1.96E-11 1.67E-16 1.87E-19 0.001975 1.56E-31 3.56E-20 6.07E-26 3.22E-07 2.75E-44 4.79E-06 7.06E-05 1.42E-82 5.51E-11 0.001135 0.001975 9.36E-89 1.79E-13 2.25E-15 8.29E-16 0 8.39E-45 4.17E-37 1.86E-98

aerotaxis receptor chemotaxis family, sensor kinase CheA chemotaxis-specific methylesterase chemotaxis methyltransferase CheR chemotaxis protein CheV purine-binding chemotaxis protein chemotaxis regulatory protein CheY chemotaxis regulator CheZ methyl-accepting chemotaxis protein, aspartate methyl-accepting chemotaxis protein methyl-accepting chemotaxis protein methyl-accepting chemotaxis protein chemoreceptor methyl-accepting chemotaxis protein methyl-accepting chemotaxis protein methyl-accepting chemotaxis protein flagellar hook-associated protein FlgK flagellar hook-filament junction protein FlgL Negative regulator of flagellin synthesis flagella synthesis chaperone protein FlgN flagellar biosynthesis protein FliC flagella biosynthesis protein FliZ flagellar motor protein MotA flagellar motor protein MotB

82 49

fruK metE

2.41 2.29

5.77 6.43

7.08E-07 1.87E-13

3.96E-13 0.00

3.02E-06 1.16E-12

5.22E-13 0.00

1-phosphofructokinase 5-methyltetrahydropteroyltriglutamate--homocy methyltransferase

64 75 07 62 04 26 54 02 47

guaC ompC rafA nirB cspA cydB yiaY cysG cysW

2.39 2.50 2.14 2.22 -3.95 -12.40 3.65 -4.85 -3.85

2.36 4.67 2.63 7.06 -2.70 -12.40 4.51 -2.49 -2.04

0.000114 1.68E-26 2.64E-15 1.75E-10 2.51E-07 0.001957 3.07E-06 2.09E-43 8.98E-10

2.54E-05 0.00 1.66E-31 0.00 2.57E-07 0.00049 1.28E-13 2.08E-33 1.77E-07

0.000391 8.46E-257 1.79E-14 9.71E-10 1.12E-06 0.005547 1.23E-05 2.68E-42 4.77E-09

5.92E-05 0.00 9.09E-31 0.00 6.71E-07 0.001021 4.53E-13 1.17E-32 4.66E-07

guanosine 5'-monophosphate（GMP） oxidore outer membrane pore protein C alpha-galactosidase nitrite reductase large subunit cold-shock protein cytochrome oxidase subunit II alcohol dehydrogenase siroheme synthase sulfate/thiosulfate transporter permease subuni

2

52 63 61 59 11 14 13 88 14 14

entB entE exbB exbD fepA fhuA fhuC fhuE foxA iutA

-2.81 -3.82 -2.19 -2.91 -5.35 -2.11 -2.75 -4.53 -3.87 -3.23

-3.09 -14.79 -3.86 -3.31 -3.95 -4.41 -2.44 -12.43 -5.32 -3.19

7.86E-11 2.34E-18 8.56E-93 3.06E-54 1.64E-21 9.92E-12 5.56E-07 5.78E-06 6.05E-41 2.79E-57

9.56E-17 1.59E-29 2.35E-24 2.28E-85 8.76E-26 0.00 1.64E-08 3.03E-08 1.29E-67 7.50E-79

4.46E-10 1.73E-17 1.99E-91 4.67E-53 1.31E-20 3.04E-12 2.42E-06 2.26E-05 7.38E-40 4.51E-56

3.71E-16 8.26E-29 4.90E-28 2.24E-84 4.18E-25 0.00 4.65E-08 8.50E-08 1.12E-66 7.14E-78

isochorismatase 2,3-dihydroxybenzoate-AMP ligase biopolymer transporter ExbB Biopolymer transport protein exbD ferric enterobactin receptor ferrichrome porin FhuA iron-hydroxamate transporter ATP-binding prote TonB-dependent siderophore receptor TonB-dependent siderophore receptor TonB-dependent siderophore receptor

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asnA asnB

-4.17 -3.19

-4.18 -2.35

3.06E-16 0.00

1.05E-23 0.00

1.10E-16 0.00

2.12E-23 0.00

aspartate--ammonia ligase asparagine synthase B

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Author contributions: A.L.Z. and Y.F.C. conceived and designed the study. A.L.Z., Y.F.C. and W.J.T. performed the experiments. D.G.Z. provided the strains. A.L.Z. and Y.F.C. wrote the paper. A.L.Z., Y.FC. , S.F.H. and Y.G.Y. reviewed and edited the manuscript. All authors read and approved the manuscript.

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This manuscript has neither been published in nor under consideration by another journal. All authors have approved the manuscript and agree with its submission to Food Research International. Further, this submission has been approved by the institution where the study was conducted. All the authors have no conflict of interest. Correspondence concerning the manuscript should be to the author Xing-long Xiao.

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