1

Global proteomic and mutagenic analyses reveal ethanol adaptation strategies in 1

Salmonella enterica serovar Enteritidis 2

Running title: Proteome of S. Enteritidis during ethanol adaptation 3

Shoukui He a,b

, Xiaojie Qin a, Catherine W. Y. Wong

b, Chunlei Shi

a, Siyun Wang

b, *, 4

Xianming Shi a,

* 5

6

a MOST-USDA Joint Research Center for Food Safety, School of Agriculture and 7

Biology, State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 8

Shanghai 200240, China 9

b Food, Nutrition and Health, Faculty of Land and Food Systems, The University of 10

British Columbia, Vancouver, BC V6T 1Z4, Canada 11

12

* Corresponding authors: 13

Dr. Xianming Shi 14

Phone & Fax: 86-21-3420-6616 15

Email: xmshi@sjtu.edu.cn 16

17

Dr. Siyun Wang 18

Phone: +1(604)827-1734 19

Email: siyun.wang@ubc.ca 20

21

AEM Accepted Manuscript Posted Online 2 August 2019Appl. Environ. Microbiol. doi:10.1128/AEM.01107-19Copyright © 2019 American Society for Microbiology. All Rights Reserved.

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ABSTRACT 22

Salmonella enterica serovar Enteritidis (S. Enteritidis) is able to adapt to 23

sublethal concentrations of ethanol, which subsequently induce the tolerance of this 24

pathogen to normally lethal ethanol challenges. This work aimed to elucidate the 25

underlying ethanol adaptation mechanisms of S. Enteritidis by proteomic and 26

mutagenic analyses. The global proteomic response of S. Enteritidis to ethanol 27

adaptation (5% ethanol for 1 h) was determined by iTRAQ and it was found that a 28

total of 138 proteins were differentially expressed in ethanol-adapted cells compared 29

to those in non-adapted cells. Fifty-six upregulated proteins were principally 30

associated with purine metabolism and transporters for glycine betaine, phosphate, 31

D-alanine, thiamine and heme; whereas 82 downregulated proteins were mainly 32

involved in enterobactin biosynthesis and uptake, ribosome, flagellar assembly as well 33

as virulence. Moreover, mutagenic analysis further revealed the functions of two 34

highly upregulated proteins belonging to purine metabolism (HiuH, 35

5-hydroxyisourate hydrolase) and glycine betaine transport (ProX, glycine 36

betaine-binding periplasmic protein) pathways. Deletion of either hiuH or proX 37

resulted in the development of stronger ethanol tolerance response, suggesting their 38

negative regulatory roles in ethanol adaptation. Collectively, this work suggested that 39

S. Enteritidis employs multiple strategies to coordinate ethanol adaptation. 40

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IMPORTANCE 45

Stress adaptation in foodborne pathogens has been recognized as a food safety 46

concern since it may compromise currently-employed microbial intervention 47

strategies. While adaptation to sublethal levels of ethanol is able to induce ethanol 48

tolerance in foodborne pathogens, the molecular mechanism underlying this 49

phenomenon is poorly characterized. Hence, global proteomic analysis and mutagenic 50

analysis were conducted in the current work to understand the strategies employed by 51

Salmonella enterica serovar Enteritidis to respond to ethanol adaptation. It was 52

revealed that coordinated regulation of multiple pathways involving metabolism, 53

ABC transporter, regulator, enterobactin biosynthesis and uptake, ribosome, flagella 54

and virulence was responsible for the development of ethanol adaptation response in 55

this pathogen. Such knowledge will undoubtedly contribute to the development and 56

implementation of more effective food safety interventions. 57

58

KEYWORDS: iTRAQ; Salmonella; Stress adaptation; Ethanol; Survival mechanism 59

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INTRODUCTION 61

Ethanol adaptation in foodborne pathogens has been a subject of great interest in 62

food safety in the last two decades. A number of pathogenic bacteria (e.g., Listeria 63

monocytogenes, Bacillus cereus, Vibrio parahaemolyticus and Cronobacter sakazakii) 64

are able to adapt to sublethal concentrations of ethanol (1–4). Ethanol adaptation can 65

enhance the tolerance of these pathogens to homologous and heterologous stressing 66

agents commonly applied during food processing and storage, thus increasing 67

microbial food safety risks (5–7). In fact, there is an increasing number of 68

stress-adapted pathogenic bacteria involved in foodborne outbreaks (8). In this 69

context, it is of paramount importance to uncover ethanol adaptation mechanisms in 70

understudied foodborne pathogens such as Salmonella enterica. 71

To date, the strategies employed by pathogenic bacteria to respond to ethanol 72

adaptation are poorly characterized, especially at the molecular level. Chiang et al. 73

(2008) found that ethanol adaptation increased the ratio of unsaturated to saturated 74

fatty acids, indicating an enhancement in cell membrane fluidity (6). Moreover, 75

two-dimensional gel electrophoresis (2-DE) analysis revealed that the expression of 76

eight proteins were enhanced 1.11- to 1.94-fold while the expression of seven proteins 77

was reduced 0.22- to 0.64-fold by ethanol adaptation (9). Unfortunately, further 78

identification and functional analysis of these differentially-expressed proteins have 79

not yet been reported. Furthermore, traditional gel-based methods such as 2-DE suffer 80

from their lack of proteome coverage, sensitivity and reproducibility (10). A novel 81

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approach, isobaric tags for relative and absolute quantification (iTRAQ), can 82

overcome these shortcomings. The iTRAQ has been extensively utilized to 83

characterize bacterial stress response mechanisms at the proteomics level in recent 84

years (11–14). Maserati et al. (2018) reported that global proteomic analysis by 85

iTRAQ contributed to a better understanding of the regulatory systems involved in the 86

response of Salmonella enterica serovar Typhimurium to low aw, desiccation and heat 87

(15). Additionally, quantitative proteomics revealed the important role of YbgC in the 88

survival of Salmonella enterica serovar Enteritidis (S. Enteritidis) in egg white (16). It 89

is therefore expected that this technology will be helpful to provide an insight into the 90

molecular and cellular bases of ethanol adaptation in foodborne pathogens. 91

Ethanol adaptation in S. Enteritidis was evaluated in our previous study and it 92

was demonstrated that this bacterium acquired tolerance to normally lethal ethanol 93

challenges upon adaptation to sublethal concentrations (2.5-10%) of ethanol, which 94

was defined as the ethanol tolerance response (17). The current work was carried out 95

to unravel ethanol adaptation mechanisms in S. Enteritidis by iTRAQ and mutagenic 96

analyses. 97

98

RESULTS AND DISCUSSION 99

Global changes in the proteome of S. Enteritidis during ethanol adaptation 100

Exposure to 5% ethanol for 1 h has been identified as an optimal adaptation 101

condition that induced the highest magnitude of ethanol tolerance response in S. 102

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Enteritidis (17). This adaptive response was reconfirmed in the current work as 103

ethanol-adapted cells exhibited a significantly (p < 0.05) higher survival rate than 104

non-adapted cells under normally lethal ethanol challenge conditions (15% ethanol for 105

1 h) (Fig. 1). Proteomic response of S. Enteritidis to the aforementioned sublethal 106

treatment (5% ethanol for 1 h) was thus determined by iTRAQ analysis to provide an 107

insight into ethanol adaptation mechanisms. A total of 2,174 proteins were detected 108

and quantified in two independent trials. A significant correlation (p < 0.0001, 109

correlation coefficient > 0.67) between protein expression levels in the two biological 110

replicates for non-adapted and ethanol-adapted groups was observed (supplemental 111

Fig. S1), confirming the repeatability of the iTRAQ experiment. 112

A considerable cut-off criterion (p < 0.05 and iTRAQ ratios > 1.3 or < 0.77) was 113

then employed for protein quantification in the current work. The same iTRAQ ratio 114

cut-off was used by Allan et al. (2016) to determine whether a protein was 115

differentially expressed in Streptococcus pneumoniae in response to nitric oxide (18). 116

It should be noted that differential proteins with moderate iTRAQ ratios may also be 117

important to bacterial stress response. For example, YbgC was upregulated by 1.20- 118

and 1.46-fold after the exposure of S. Enteritidis to 50% and 80% egg white as 119

identified by the iTRAQ experiments; mutagenic analysis further revealed that YbgC 120

was indeed a key protein contributing to S. Enteritidis survival in egg white (16). 121

Therefore, all significantly differentially expressed proteins, including those with 122

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moderate iTRAQ ratios, will be utilized to uncover ethanol adaptation mechanisms in 123

S. Enteritidis in the current study. 124

Based on the aforementioned criterion, a total of 138 differentially expressed 125

proteins (56 upregulated and 82 downregulated) were screened (supplementary Data 126

S1). These proteins were assigned to functional groups by KEGG pathway analysis 127

for a better understanding of their cellular functions. The major clustered functional 128

categories belonged to metabolism, ABC transporter, regulator, enterobactin 129

biosynthesis and uptake, ribosome, flagellar assembly and virulence (Table 1). 130

Moreover, approximately 20% proteins were poorly characterized with an unknown 131

function or with a general function based on predictions only (supplemental Table S1). 132

A proposed model highlighting the major proteomic changes was presented in Fig. 2, 133

which indicated complex regulatory networks governing ethanol adaptation of S. 134

Enteritidis. 135

Metabolism 136

S. Enteritidis altered the expression of a considerable proportion of 137

metabolism-related proteins in the current study (Table 1), reflecting a coordinated 138

regulation of metabolic processes in response to ethanol adaptation. These 139

differentially-expressed proteins belonged to metabolic pathways for carbohydrate, 140

terpenoid and polyketide, energy, amino acid, glycan, cofactor and vitamin, lipid and 141

nucleotide. Some proteins involved in CoA biosynthesis (CoaD), pentose phosphate 142

pathway (STM2340), oxidative phosphorylation (NuoM and NuoN) as well as purine 143

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(HiuH and YaiE), galactose (GatY), glyoxylate (Gcl), histidine (HisIE) and arginine 144

(AstA) metabolism were enhanced 1.34- to 1.98-fold. These diverse metabolic 145

upregulations suggested the nutritional requirements of S. Enteritidis for ethanol 146

adaptation. 147

The relationship between amino acid biosynthesis and microbial ethanol 148

tolerance has been reported before. Transcriptome analysis revealed that biosynthetic 149

pathways for amino acids (e.g., histidine, tryptophan and branched-chain amino acids) 150

were commonly upregulated in ethanol-tolerant strains of Escherichia coli obtained 151

by parallel evolution (19). Furthermore, Hirasawa et al. (2007) found that 152

overexpression of tryptophan biosynthesis genes or supplementation of tryptophan to 153

the culture medium conferred ethanol tolerance to Saccharomyces cerevisiae (20). In 154

the current study, it was noted that several proteins (e.g., HisIE, CysM and STM1557) 155

related to amino acid metabolism were differentially expressed. In particular, histidine 156

biosynthesis bifunctional protein HisIE was elevated by 1.34-fold in ethanol-adapted 157

S. Enteritidis (Table 1). Therefore, amino acid biosynthesis seems to be involved in 158

ethanol adaptation of S. Enteritidis. 159

ABC transporters 160

A large number of differentially expressed proteins were related to ABC 161

transporters in the current study (Table 1). Briefly, proteins responsible for transport 162

of glycine betaine (ProX and ProV), phosphate (PstC and PstS), D-alanine (DalS), 163

thiamine (TbpA) and heme (CcmC) were upregulated; while those for manganese 164

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(SitB), cationic peptide (SapF) and siderophore (FepB and FepC) were downregulated. 165

The differential expression of such a sizable fraction of ABC transporters certainly 166

highlights their importance in ethanol adaptation of S. Enteritidis. There were only 167

two transporters, ProVWX and PstSCAB, with more than one upregulated protein. 168

ProVWX, one of the three osmoprotectant systems in S. enterica, utilizes ATP 169

hydrolysis to drive transport of compatible solutes (21). The pore, ATPase and 170

substrate binding proteins in this system are called ProW, ProV and ProX, 171

respectively. The contribution of compatible solutes (e.g., glycine betaine) transported 172

by ProVWX to bacterial survival under NaCl stress has been outlined (22, 23). In the 173

current study, the expression of ProX and ProV was enhanced 1.65- and 1.42-fold, 174

respectively (Table 1). Nevertheless, ethanol-adapted S. Enteritidis did not mount 175

cross protection against NaCl (17), reflecting that regulatory pathways mediating 176

osmotic stress tolerance may be different to those involved in ethanol stress response. 177

Bacteria have developed intricate strategies to sense and respond to changes in 178

environmental phosphate, thus maintaining intracellular phosphate pools which are 179

essential for their survival (24). The Pho regulon mediates the response of S. enterica 180

and E. coli to phosphate starvation conditions. In this regulon, the PstSCAB 181

transporter senses phosphate concentrations and communicates with the 182

two-component system PhoRB via PhoU (25). The genes belonging to this signal 183

transduction pathway in E. coli are only expressed when external phosphate is limited 184

(24). In the current study, PstS (a phosphate-binding protein), PstC (a phosphate 185

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transport system permease protein) and PhoU (a phosphate-specific transport system 186

accessory protein) were upregulated following ethanol adaptation (Table 1; 187

supplementary Data S1). It was therefore indicative that a phosphate limitation 188

response was triggered by the sublethal ethanol treatment. Similarly, the expression of 189

genes encoding the PstSCAB transporter was enhanced in response to acid and 190

oxidative stresses in S. enterica (25, 26). Overall, maintaining cellular phosphate 191

homeostasis may be essential for S. Enteritidis to mount an adaptive response. 192

Regulators 193

Regulators are indispensable for S. enterica to mount appropriate responses to 194

food processing and storage-related stresses (26–28). Altogether, six regulators (Crl, 195

Fis, RssB, PurR, MetR and CspA) in S. Enteritidis showed differential expression in 196

the current study. Crl and RssB were upregulated by 1.40- and 1.33-fold, respectively, 197

while Fis was downregulated by 1.92-fold (Table 1). Interestingly, all these three 198

proteins are involved in the regulation of the sigma factor RpoS in S. enterica. Crl is 199

an unconventional transcription factor known to enhance RpoS activity by a direct 200

interaction, thus controlling the expression of RpoS-regulated genes (29, 30). The 201

RssB response regulator plays a central role in RpoS degradation by delivering it to 202

the ClpXP protease (31, 32); mutation in rssB (mviA) led to a higher level of RpoS 203

and stronger acid tolerance in S. Typhimurium (33). Fis acts as a regulator which 204

mediates the transcriptional induction of RpoS (34). In fact, RpoS abundance is 205

regulated at many levels, including protein activity, protein turnover, transcription and 206

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translation (35). Although RpoS was not detected by iTRAQ in the current study, a 207

significant increase in rpoS mRNA level was observed upon ethanol adaptation (36). 208

The importance of RpoS to the survival of S. enterica under food processing and 209

storage-related stresses has been well documented (27, 28, 37). Therefore, it is 210

reasonable to speculate that Fis, RssB and Crl play a role in ethanol adaptation of S. 211

Enteritidis considering their regulatory effect on RpoS. 212

PurR is a transcriptional repressor of purine nucleotide biosynthesis in S. 213

enterica (38). In the current study, ethanol adaptation led to a repression of PurR, 214

along with the induction of HiuH and YaiE involved in purine metabolism (Table 1). 215

Cho et al. (2011) provided an evidence for the involvement of PurR in bacterial stress 216

response; deletion of purR decreased the expression of acid tolerance genes (e.g., 217

hdeA, hdeB and hdeD) in E. coli K-12 MG1655 (39). In this sense, downregulation of 218

PurR in the current work correlated well with our previous finding that ethanol 219

adaptation failed to induce cross protection against hydrochloric, citric, lactic, 220

ascorbic and acetic acids in S. Enteritidis (36). 221

MetR is a transcription factor of the LysR family, which regulates the expression 222

of methionine biosynthesis genes (e.g., metE, metF and metH) in S. enterica (40). 223

MetR and two other proteins (STM1557 and CysM) involved in methionine and 224

cysteine metabolism showed downregulation in the current study (Table 1). 225

Furthermore, the above-mentioned six proteins displayed a close interaction by 226

STRING analysis (supplemental Fig. S2). These results indicate the repression of 227

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methionine biosynthesis pathway by ethanol adaptation. In fact, methionine 228

biosynthesis is generally sensitive to environmental signals such as heat shock and 229

oxidative stress (41). 230

CspA, the major and best characterized cold shock protein, acts as a global 231

regulator by binding to mRNA or single-stranded DNA. It can influence the 232

transcriptional and translational properties of bacterial cells (42). For instance, 233

Rennella et al. (2017) highlighted the RNA binding and chaperone activity of CspA in 234

E. coli (43). In S. Typhimurium, CspA targeted about 25% of the RNA encoded by 235

the genome. These targets were responsible for stress response, motility, virulence, 236

metabolic process, cellular transport, transcription regulation and metal binding (44). 237

Further mutational analysis provided evidences that cold shock proteins were 238

involved in ethanol, pH and NaCl stress response of Clostridium botulinum (45). In 239

the current study, ethanol adaptation reduced the expression of CspA by 2.13-fold 240

(Table 1). Meanwhile, our previous study showed that cross protection against -20 °C 241

occurred in S. Enteritidis following ethanol adaptation (17). Hence, the role of CspA 242

in ethanol adaptation and its induced cross protection effect against freezing 243

temperature in S. Enteritidis can be anticipated. 244

Ribosome 245

The expression of ribosome-related proteins was decreased in ethanol-adapted 246

cells of S. Enteritidis in the current study. As shown in Table 1, GTPases (Der and 247

Obg) and ATP-dependent RNA helicases (DeaD, RhlE and DbpA), which are 248

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involved in ribosome maturation at least in E. coli (46), were repressed. The 249

ribosome-binding factor (RbfA) and tRNA methyltransferase (TrmD) were also 250

downregulated. In a similar vein, lower expression levels were observed for 30S 251

(RpsN and RpsI) and 50S (RpmH and RpmD) ribosomal proteins. The number of 252

ribosomal units determines the rate of protein synthesis, which is strictly related to the 253

rate of cellular growth (47). This means that the amount of ribosome-related proteins 254

plays an important role in bacterial growth rate. In our previous study, sublethal 255

concentrations of ethanol (2.5-10%) used for ethanol adaptation inhibited the growth 256

of S. Enteritidis (17). This inhibitory effect can be explained by the repression of 257

ribosome-related proteins under ethanol adaptation conditions. 258

Enterobactin biosynthesis and uptake 259

Enterobactin is a major siderophore produced by S. enterica under iron 260

restriction conditions to solubilize exogenous iron, thereby making this metal 261

available for bacterial cells (48). In the current study, ethanol adaptation led to a 262

repression of proteins responsible for enterobactin biosynthesis (EntA, EntB, EntC, 263

EntF and EntH; 1.38- to 1.69-fold) and uptake (CirA, FepA, FepB and FepC; 1.32- to 264

1.78-fold) (Table 1). In fact, there is increasing evidence implicating the role of 265

enterobactin in bacterial stress response. For example, enterobactin biosynthesis and 266

uptake were induced following exposure of S. Enteritidis to egg white to facilitate iron 267

acquisition, thus providing a survival advantage to this bacterium (16, 49). Peralta et 268

al. (2016) found that enterobactin protected E. coli against oxidative stress and this 269

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effect was independent of its capacity to scavenge iron (50). Moreover, the growth of 270

E. coli ⊿tolC mutant was impaired by the accumulation of periplasmic enterobactin 271

(51). Therefore, blocking enterobactin synthesis and uptake pathways could be an 272

adaptation strategy of S. Enteritidis under sublethal ethanol stress in the current study. 273

Flagella 274

As shown in Table 1, two proteins (FliH, a flagellar assembly protein; FlgF, a 275

flagellar basal body rod protein) related to flagellar assembly were repressed during 276

the course of ethanol adaptation. Similarly, flgF in S. Typhimurium was 277

downregulated in response to oxidative stress, which might serve as an energy 278

conservation strategy (25). Moreover, the expression of both fliH and flgF was 279

reduced when an acid tolerance response was stimulated in S. Typhimurium; further 280

functional analysis revealed that mutation of flgD encoding a scaffolding protein 281

required for flagellar hook formation led to the absence of an acid adaptation 282

phenotype (26). Hence, the results above enforce the knowledge of flagella-related 283

proteins playing a crucial role in the stress response of S. enterica. 284

Salmonella pathogenicity island (SPI) 285

During food processing and storage, foodborne pathogens encounter many of the 286

same stresses as they experience during host infection. Therefore, many stress 287

tolerance-related genes are also likely involved in bacterial survival within the host 288

and stress adaptation can thus alter the virulence potential of foodborne pathogens 289

(52). In the current study, four SPI-related proteins (PrgI, PrgK, MisL and InvC) were 290

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downregulated by 1.39- to 1.85-fold after ethanol adaptation (Table 1). SPIs are 291

highly conserved across the genus and essential for virulence (26). The prgI and prgK 292

genes encode secretion apparatus proteins of SPI-1 (53). The misL gene encodes an 293

outer membrane autotransporter in SPI-3 (54). The invasion gene invC is a key 294

component of type III secretion system (55). Ryan et al. (2015) found that several 295

virulence factors in S. Typhimurium were differentially regulated during acid 296

adaptation, including invACE in SPI-1 and ssaCGJNQRV in SPI-2 (26). Furthermore, 297

heat shock led to a repression of SPI-1 genes (e.g., prgK and prgH) and an induction 298

of SPI-2 and SPI-5 genes in S. Typhimurium, accompanied with a greater adhesion to 299

Caco-2 cells (56). There is still a lack of knowledge on the virulence of 300

ethanol-adapted S. Enteritidis that can be further addressed in future studies. 301

Validation of iTRAQ results at the mRNA level 302

The iTRAQ data were verified by reverse transcription quantitative real-time 303

PCR (RT-qPCR) to determine the transcriptional profile of ten differentially regulated 304

proteins. Six proteins (ProV, SecE, STM2506, YlaC, HiuH and ProX) were 305

upregulated and four (EntA, FepA, SitB and CspA) were downregulated. As shown in 306

Fig. 3, nine of the ten proteins and their corresponding mRNAs displayed a similar 307

expression pattern, and the only exception was ProV. This finding provided evidence 308

for the reliability of data derived from the aforementioned proteomic analysis. 309

Functional analysis of HiuH and ProX in ethanol adaptation of S. Enteritidis 310

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In the current study, we hypothesized that highly-upregulated proteins revealed 311

by iTRAQ are important to ethanol adaptation of S. Enteritidis. Therefore, two 312

proteins (HiuH involved in nucleotide metabolism and ProX associated with ABC 313

transporter) that showed enhanced expression in both iTRAQ and RT-qPCR tests 314

were selected for mutagenic analysis. We constructed S. Enteritidis mutants in which 315

hiuH or proX was deleted and compared their ability to develop ethanol tolerance 316

response with that of the wild type strain. No significant (p > 0.05) difference was 317

found in the growth curve of wild type, ⊿hiuH and ⊿proX strains in Luria-Bertani 318

(LB) broth (supplemental Fig. S3). Nevertheless, ⊿hiuH and ⊿proX mutants mounted 319

a significantly (p < 0.05) higher ethanol tolerance response compared with that of the 320

wild type strain (Fig. 4). Furthermore, ethanol tolerance response was restored in 321

complementing strains (Fig. 4), thereby confirming the negative regulatory role of 322

these two proteins in ethanol adaptation of S. Enteritidis. 323

The 5-hydroxyisourate (5-HIU) hydrolase HiuH is involved in bacterial purine 324

metabolism (57). This pathway requires four enzymatic steps that convert xanthine to 325

uric acid, uric acid to 5-HIU, 5-HIU to OHCU 326

(2-oxo-4-hydroxy-4-carboxy-5-ureidoimidazoline) and OHCU to allantoin, 327

respectively (58). HiuH catalyzes the third step of this reaction to metabolize 5-HIU 328

to OHCU (59). Hennebry et al. (2012) found that mutation in hiuH (yedX) did not 329

affect the response of S. Typhimurium to oxidative stress, reduced nutrient provision 330

and temperature alteration (58). In the current study, it was demonstrated that the 331

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deficiency of hiuH contributed to the development of ethanol tolerance response in S. 332

Enteritidis. Although the mechanism for this negative regulation is unclear, these 333

findings suggest that the purine metabolism pathway is involved in ethanol adaptation 334

of S. Enteritidis. 335

Deletion of proX also led to a significantly (p < 0.05) higher magnitude of 336

ethanol tolerance response in the current study. Similarly, the tolerance of E. coli to 337

n-hexane and cyclohexane was improved by the disruption of proX (60). These 338

observations provided evidence for the involvement of the ProVWX uptake system in 339

bacterial organic solvent tolerance. In ProVWX system, ProX recognizes a 340

compatible solute and delivers it to a protein complex consisting of ProV and ProW. 341

The ProVWX transporter permits the uptake of various compatible solutes (e.g., 342

glycine betaine, ectoine, taurine, proline and structural analogues glycine betaine) 343

involved in bacterial stress response (61). It was therefore speculated that the 344

disruption of the proX gene improved ethanol tolerance response of S. Enteritidis by 345

acting on the intracellular concentration of these solutes. Taken together, mutational 346

analysis supports our hypothesis that highly upregulated proteins, such as HiuH and 347

ProX, play a role in ethanol adaptation of S. Enteritidis. 348

349

CONCLUSIONS 350

Proteomic characterization revealed that complex regulatory pathways associated 351

with metabolism, ABC transporter, regulator, enterobactin biosynthesis and uptake, 352

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ribosome, flagellar assembly and virulence were at play during ethanol adaptation of 353

S. Enteritidis. Moreover, mutagenic and complementation analyses demonstrated a 354

negative regulatory role of ProX and HiuH in ethanol adaptation. Collectively, our 355

work provides important insights into ethanol adaptation mechanisms of S. Enteritidis 356

as well as a framework for further investigation on this subject. For example, 357

functional analysis of more proteins belonging to different pathways will deepen our 358

understanding of ethanol adaptation in S. Enteritidis. It would also be interesting to 359

address the effect of ethanol adaptation on virulence properties of S. Enteritidis in 360

future studies. 361

362

MATERIALS AND METHODS 363

Bacterial strains and storage conditions 364

The S. Enteritidis strain ATCC 13076, obtained from the American Type Culture 365

Collection, was used in the current study. The bacterial strain was maintained in LB 366

broth supplemented with 25% glycerol at -80 °C, and streaked onto LB agar, followed 367

by incubation at 37 °C for 24 h prior to use. For each experiment, a single colony was 368

inoculated in 5 ml LB broth and incubated overnight at 37 °C. A 500-μl aliquot of the 369

active culture was inoculated into 50 ml LB broth and incubated at 37 °C/200 rpm for 370

5 h to reach the late exponential phase (17). 371

Ethanol adaptation assays 372

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The ethanol adaptation assay was carried out as previously described (17). 373

Briefly, the late exponential-phase cultures (5 ml) of S. Enteritidis were centrifuged, 374

washed with PBS (phosphate buffered saline, pH 7.4) and resuspended in 50 ml fresh 375

LB broth (control) or in LB broth containing 5% (v/v) ethanol. These samples were 376

incubated at 25 °C with shaking (170 rpm) for 1 h to prepare non-adapted and 377

ethanol-adapted cultures for iTRAQ test, respectively. Moreover, these two cultures 378

were subjected to ethanol tolerance assessment according to our previous method 379

(17). 380

Protein extraction, quantification and digestion 381

Non-adapted and ethanol-adapted cells of S. Enteritidis were washed twice with 382

PBS, resuspended in SDT buffer (1 mM DTT, 4% SDS, 150 mM Tris-HCl, pH 8.0), 383

boiled for 5 min and ultrasonicated for another 5 min. The lysates were centrifuged at 384

14,000 g for 10 min to remove cellular debris (16). The resulting supernatants were 385

transferred to new tubes and stored at -80 °C for subsequent use. Bicinchoninic acid 386

(BCA) Protein Assay Reagent (Promega, Madison, WI) was then utilized to 387

determine the protein concentration. 388

Protein digestion was performed according to FASP (filter-aided sample 389

preparation) protocol (62). Briefly, 200 μg protein from each sample was mixed with 390

30 μl SDT buffer and was washed three times by ultrafiltration (Pall units, 10 kDa) 391

with 200 μl UA buffer (8 M urea, 150 mM Tris-HCl pH 8.0). Proteins were then 392

alkylated with 50 mM iodoacetamide in the dark for 30 min, washed three times with 393

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100 μl UA buffer and then twice with 100 μl DS buffer (50 mM triethylammonium 394

bicarbonate, pH 8.5). Finally, proteins were digested overnight with 2 μg trypsin 395

(Promega, Madison, WI) in 40 μl DS buffer at 37 °C. The resulting peptides were 396

collected as a filtrate in clean tubes by centrifugation at 14,000 g for 10 min. The 397

peptide content was estimated by UV light spectral density at 280 nm using an 398

extinction coefficient of 1.1 of 0.1% solution that was calculated on the basis of the 399

frequency of tryptophan and tyrosine in vertebrate proteins. 400

iTRAQ labeling and SCX fractionation 401

The 8 multiplex iTRAQ labelings were carried out according to the 402

manufacturer’s instructions (Applied Biosystems, Foster City, CA). iTRAQ reagents 403

113 and 114 were employed to label the peptides from non-adapted S. Enteritidis, 404

whereas the reagents 117 and 118 were utilized to label the peptides from 405

ethanol-adapted S. Enteritidis. Other four labels (115, 116, 119, 121) were used in 406

other experiments. Samples were combined and vacuum dried after labeling. The 407

iTRAQ-labeled peptides were dissolved in 2 ml buffer A (10 mM KH2PO4 in 25% 408

acetonitrile, pH 3.0) and fractionated using an AKTA Purifier system (GE Healthcare, 409

Sweden) and a PolySulfoethyl column (4.6 100 mm, 5 µm, PolyLC Columbia, 410

MD). The gradient elution was conducted with 0% to 10% buffer B (500 mM KCl, 10 411

mM KH2PO4 in 25% acetonitrile, pH 3.0) for 32 min, 10% to 20% buffer B for 10 412

min, 20% to 45% buffer B for 5 min and 45% to 100% buffer B for 13 min. The 413

tryptic peptides were separated at a flow rate of 1,000 μl/min and monitored by 414

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absorbance at 214 nm. The fractions were collected every minute, combined into 15 415

pools, desalted using C18 Cartridges (Empore SPE Sigma, St. Louis, MO) and 416

concentrated by vacuum centrifugation. 417

LC-ESI-MS/MS analysis 418

The labeled peptides were analyzed on a Q Exactive mass spectrometer coupled 419

to an Easy-nLC liquid chromatography system (Proxeon Biosystems, Thermo Fisher, 420

Fairlawn, NJ) and equipped with a C18 trap column (5 μm, 100 μm × 20 mm) and a 421

C18 analytical column (3 μm, 75 μm × 100 mm). An aliquot of 10 μl sample was 422

loaded along with RP-C18 5 μm resin in buffer A (0.1% formic acid). Separation was 423

achieved using a linear gradient of buffer B (84% acetonitrile in 0.1% formic acid) 424

controlled by IntelliFlow technology at a flow rate of 250 nl/min. A data-dependent 425

top 10 method was utilized to acquire MS data, dynamically selecting the most 426

abundant precursor ions from the survey scan (300-1800 m/z) for HCD 427

(higher-energy collisional dissociation) fragmentation. The predictive Automatic Gain 428

Control (pAGC) system was employed with the instrument using dynamic exclusion 429

duration of 60 s to determine the target value. Survey scans were obtained at m/z 200 430

at a resolution of 70,000 and resolution for HCD spectra was set to 17,500 at m/z 200. 431

Normalized collision energy was 30 eV and the underfill ratio was defined as 0.1%. 432

The instrument was run along with the peptide recognition mode enabled. 433

Data analysis 434

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MS/MS spectra were searched against the S. Enteritidis uniprot database (37,314 435

sequences downloaded on June 22, 2016) and the decoy database using Mascot 2.2 436

(Matrix Science, London, UK) embedded in Proteome Discoverer 1.4 (Thermo 437

Electron, San Jose, CA). The following parameters were used for protein 438

identification: enzyme, trypsin; MS/MS tolerance, 0.1 Da; missed cleavage, 2; 439

variable modification, Oxidation (M); fixed modification, Carbamidomethyl (C); 440

iTRAQ8plex(K), iTRAQ8plex(N-term); false discovery rate (FDR), ≤ 0.01. 441

Proteins with iTRAQ ratios > 1.3 (increased) or < 0.77 (decreased) and p < 0.05 442

were considered to be differentially expressed. The KEGG (Kyoto Encyclopedia of 443

Genes and Genomes) pathway enrichment analysis 444

(http://www.genome.jp/kegg/pathway.html) was employed to determine the metabolic 445

pathway for all differentially expressed proteins. 446

Gene expression analysis 447

Differentially expressed proteins in iTRAQ test were validated at the mRNA 448

level by RT-qPCR. A total of ten differentially regulated proteins were selected to 449

determine their corresponding transcription levels. RNA extraction and RT-qPCR 450

analysis were carried out on non-adapted and ethanol-adapted S. Enteritidis cells as 451

previously described using primers listed in Table 2 (36). Alterations of gene 452

expression in ethanol-adapted cells compared to non-adapted counterparts were 453

calculated by the 2−ΔΔCt

method. The 16S rRNA gene was employed as a nonregulated 454

control for data normalization. 455

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Generation of hiuH and proX deletion mutants and complementing strains 456

In-frame deletions of hiuH and proX were performed according to 457

previously-described homologous recombination knockout procedures using primers 458

in Table 3 (63). Plasmids and strains used were listed in Table 4. The fragments of 459

homologous arms were obtained from S. Enteritidis genomic DNA by overlap 460

extension PCR. This product was cloned into the pMD19-T vector (TaKaRa, Dalian, 461

China) to generate pMD19⊿hiuH and pMD19⊿proX, respectively. The correct 462

construction was confirmed by DNA sequencing. Both pMD19⊿hiuH and 463

pMD19⊿proX were digested with Sac I and Xba I, and then ligated into pRE112 (a 464

suicide vector carrying a sucrose-sensitive gene and a chloramphenicol-resistance 465

gene). The resulting pRE⊿hiuH and pRE⊿proX were introduced into E. coli 466

SM10λpir by CaCl2 transformation. These two plasmids were then extracted from E. 467

coli cells and transformed into the wild type S. Enteritidis ATCC 13076 by 468

electroporation (2400 V, 4.2 ms) to accomplish a single crossover. The single 469

crossover strains were grown in LB broth supplemented with 8% sucrose to 470

accomplish a second crossover. Colonies that were resistant to sucrose and sensitive 471

to chloramphenicol were selected. The resulting mutants, S. Enteritidis ⊿hiuH and S. 472

Enteritidis ⊿proX, were confirmed by PCR analysis and DNA sequencing. 473

To generate complemented strains, the constructed plasmids pRE⊿hiuH-C and 474

pRE⊿proX-C were transferred into the corresponding mutant strains by 475

electroporation at 2400 V for 4.2 ms. A double selection was then carried out as 476

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described above. The complementation of these two genes was confirmed by PCR 477

and DNA sequencing. 478

Determination of the role of hiuH and proX in ethanol adaptation 479

The role of hiuH and proX in ethanol adaptation of S. Enteritidis was assessed by 480

comparing the capacity of their deletion mutants (⊿hiuH and ⊿proX) and 481

complemented strains (⊿hiuH-C and ⊿proX-C) to develop ethanol tolerance response 482

with that of the wild type (WT). Ethanol tolerance response, defined as the induced 483

tolerance to normally lethal ethanol challenge conditions following adaptation to mild 484

ethanol stress, was determined as previously detailed (17). The wild type, deletion 485

mutants and complemented strains of S. Enteritidis were adapted in 5% ethanol for 1 486

h as described above. Ethanol-adapted cells (100 μl) were then inoculated into 10 ml 487

LB broth containing 15% ethanol. The viable bacterial population was determined 488

after incubation at 25 °C/170 rpm for 4 h by plating the appropriate dilutions onto LB 489

agar. The survival rate was then calculated by dividing the initial population 490

(corresponding to 100%) with the surviving population. 491

Statistical analysis 492

Gene expression levels and survival rates were subjected to a one-way ANOVA 493

analysis by SAS version 8.0 (SAS Institute Inc., Cary, NC). Duncan’s test was then 494

employed to detect the statistical significance at the level of p < 0.05. 495

ACKNOWLEDGEMENTS 496

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This work was supported by the grant from National Key R&D program of 497

China (2016YFE0106100). The first author Mr. Shoukui He received a scholarship 498

(File No. 201706230177) from China Scholarship Council for his study at The 499

University of British Columbia. Authors would like to thank Dr. Gahee Ban for her 500

critical reading of this manuscript, and Dr. Daniel Ryan for his helpful suggestions on 501

proteomic data analysis. 502

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Figure captions 700

Figure 1 Ethanol adaptation (5% ethanol for 1 h) induces tolerance to a normally 701

lethal ethanol treatment (15% ethanol for 1 h) in S. Enteritidis. The survival rate was 702

calculated by dividing the surviving population by the initial population 703

(corresponding to 100%). Data are presented as mean ± standard deviation. Different 704

lowercase letters indicate significant differences (p < 0.05). 705

Figure 2 A proposed model for major cellular changes occurring during ethanol 706

adaptation of S. Enteritidis. The star symbol (★) indicates that the function of a 707

protein belonging to this pathway has been validated by mutagenic analysis in the 708

current study. 709

Figure 3 Comparison between protein and mRNA levels of ten differentially 710

regulated proteins revealed by iTRAQ and RT-qPCR. Stars (*) signify that a gene in S. 711

Enteritidis was significantly (p < 0.05) differentially expressed in response to 712

sublethal ethanol adaptation (5% ethanol for 1 h). 713

Figure 4 Ethanol tolerance response in the wild type (WT), deletion mutants (⊿hiuH 714

and ⊿proX) and complemented strains (⊿hiuH-C and ⊿proX-C) of S. Enteritidis. 715

Ethanol-adapted cells (5% ethanol for 1 h) were further exposed to 15% ethanol for 4 716

h. The survival rate, calculated by dividing the initial population (corresponding to 717

100%) with the surviving population, was then employed to assess the development 718

of ethanol tolerance response. A survival rate of 50% indicates that the population of 719

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S. Enteritidis cells was reduced by half. Data are presented as mean ± standard 720

deviation. Different lowercase letters indicate significant differences (p < 0.05). 721

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Figure 1 722

723

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Figure 2 724

725 on Decem

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Figure 3 726

727

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Figure 4 728

729

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Table 1 Representative functional groups for differentially expressed proteins during ethanol adaptation of S. Enteritidis 730

731

732

733

734

735

736

737

738

739

740

741

742

743

744

745

746

747

748

749

750

751

752

753

754

755

756

757

758

759

760

761

762

Accession Description Gene name Ratio

Metabolism

S4IEX7 5-hydroxyisourate hydrolase hiuH 1.98

B5QTE0 UPF0345 protein YaiE yaiE 1.36

S4K9X6 Histidine biosynthesis bifunctional protein HisIE hisI 1.34

B5QWI9 Arginine N-succinyltransferase astA 1.81

S4HY70 Cysteine synthase cysM 0.59

S4JEB3 Aminotransferase, class I/II STM1557 0.69

S4JAI7 Ketose-bisphosphate aldolase gatY 1.52

S4I2H1 Glyoxylate carboligase gcl 1.43

S4IDM5 Transketolase protein STM2340 1.40

S4HV82 PTS system fructose-specific EIIBBC component fruA 1.30

B5R1U0 Ribulokinase araB 0.72

S4I914 Succinate dehydrogenase hydrophobic membrane anchor subunit sdhD 0.73

S4I998 PTS system, glucitol/sorbitol-specific, IIBC component srlE 0.49

B5R5F8 Phosphopantetheine adenylyltransferase coaD 1.36

T2Q4S9 Thioesterase family protein yciA 0.61

S4IJ46 Penicillin-binding protein mrdA 0.73

S4JPU1 NDH-1 subunit M nuoM 1.37

B5R2Z7 NADH-quinone oxidoreductase subunit N nuoN 1.38

S4HPP4 Polyprenyl synthetase ispA 0.69

ABC transporter

S4I520 Glycine betaine-binding periplasmic protein proX 1.65

S4JBQ6 Glycine betaine/L-proline transport ATP-binding protein ProV proV 1.42

S4IF67 Phosphate transport system permease protein pstC 1.56

S4JMC0 Phosphate-binding protein PstS pstS 1.76

S4IDQ2 Thiamine/thiamine pyrophosphate ABC transporter tbpA 1.35

S4I2Z4 Heme exporter protein ccmC 1.36

S4IRJ2 ABC transporter, substrate-binding protein, family 3 dalS 1.31

S4IFD6 Peptide transport system ATP-binding protein SapF sapF 0.68

S4HWX8 Manganese transport system ATP-binding protein MntA sitB 0.71

Regulator

B5R4S3 Sigma factor-binding protein Crl crl 1.40

B5R1C8 DNA-binding protein Fis fis 0.52

S4HTK4 Regulator of RpoS rssB 1.33

B5QV29 HTH-type transcriptional repressor PurR purR 0.75

S4IGU5 HTH-type transcriptional regulator MetR metR 0.68

P0A9Y5 Cold shock protein CspA cspA 0.47

Ribosome

B5QUQ1 50S ribosomal protein L34 rpmH 0.70

B5R1F9 50S ribosomal protein L30 rpmD 0.72

S4KBH8 30S ribosomal protein S14 rpsN 0.74

B5R0L7 30S ribosomal protein S9 rpsI 0.75

S4IBG4 ATP-dependent RNA helicase RhlE rhlE 0.66

S4I8H3 ATP-dependent RNA helicase DeaD deaD 0.70

S4KIE0 ATP-dependent RNA helicase DbpA dbpA 0.74

B5R578 GTPase Der der 0.73

B5R0H4 GTPase Obg obg 0.74

B5QZV7 Ribosome-binding factor A rbfA 0.71

B5QUG2 tRNA (guanine-N(1)-)-methyltransferase trmD 0.72

Enterobactin biosynthesis and uptake

S4J0D7 2,3-dihydroxybenzoate-2,3-dehydrogenase entA 0.59

S4ITD9 Isochorismatase entB 0.71

S4K7S9 Isochorismate synthase entC 0.67

S4J0C5 Enterobactin synthetase component F entF 0.73

B5QVK0 Proofreading thioesterase EntH entH 0.72

S4HRN3 Colicin I receptor cirA 0.56

S4IJA9 Ferrienterobactin receptor fepA 0.60

S4IJB9 Ferrienterobactin-binding periplasmic protein fepB 0.76

S4K7S4 Achromobactin ABC transporter, ATP-binding protein fepC 0.70

Flagella

S4JS57 Flagellar basal body protein flgF 0.63

S4IZ57 Flagellar assembly protein FliH fliH 0.75

Salmonella pathogenicity island

T2Q228 Outer membrane autotransporter barrel domain protein misL 0.54

S4IDP5 Type III secretion apparatus lipoprotein, YscJ/HrcJ family prgK 0.68

S4I9H1 Invasion protein InvC invC 0.69

S4JKT7 Type III secretion apparatus needle protein prgI 0.72

Note: Some proteins were classified in multiple functional groups, but information for such proteins was only given in one major category in Table 1. Namely,

EntABCFH and FepBC in enterobactin biosynthesis and uptake pathways also belong to the metabolism and ABC-transporter categories, respectively.

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Table 2 Primers used for RT-qPCR analysis 763

Gene Forward primer sequence (5′ to 3′) Reverse primer sequence (5′ to 3′)

proV CTCGGGTAAATCCACAA TTATCCAGCACGGTCAT

secE CAATCGTCGGCAACTAC TACCAGGCGAACCAGA

STM2506 CGCATGACCCGTATCGT CGGCGTGGTGACAGAAA

ylaC AGCGAAACTATTGATGAC CCGTTGTAACAGACCC

hiuH CAGCAAACAGGCAAAC TAATAACAGCGGCACA

proX GGCATTACCGTCCAAC CGACTTCACTCGGCTTA

entA TTTGCGGTCAATGTGGG GCTGTTCGGCATCTTCG

fepA CGTATCCACCATCACCG ACTCGCTACCGCCTTTT

sitB TGGTAGGCGTAAATGGT CCCTGGCAAGAAACAC

cspA TTCGGCTTTATTACTCCTG CTTTCTGACCTTCGTCCA

16S rRNA CAGAAGAAGCACCGGCTAAC GACTCAAGCCTGCCAGTTTC

764

765

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Table 3 Primers used for the construction and complementation of S. Enteritidis 766

deletion mutants 767

Primer Sequence (5′ to 3′)

hiuH-F1 CTCTAGAGCCGTCAGGCAAATAA (Xba I)

hiuH-R1 AGGCTCTAAAGCTTCACTCCTTTACGGTAT

hiuH-F2 GGAGTGAAGCTTTAGAGCCTATCCCATTAG

hiuH-R2 GCGAGCTCAAGCGGGATAACCACC (Sac I)

proX-F1 CTCTAGAAGGTGCCTGCCGACTT (Xba I)

proX-R1 AAAAACGATCCGTTGTTCCTTTAATTATGG

proX-F2 AGGAACAACGGATCGTTTTTTATGCCGGAT

proX-R2 GCGAGCTCTGCTAAGCGACTGACTGC (Sac I)

768

769

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Table 4 Strains and plasmids used for the construction and complementation of S. 770

Enteritidis deletion mutants 771

Strain or plasmid Description Source/reference

S. Enteritidis ATCC 13076 Wild type strain American Type Culture

Collection

⊿hiuH hiuH deletion mutant of S. Enteritidis ATCC 13076 This study

⊿hiuH-C Complementary strain for hiuH deletion mutant This study

⊿proX proX deletion mutant of S. Enteritidis ATCC 13076 This study

⊿proX-C Complementary strain for proX deletion mutant This study

E. coli DH5α Host for cloning Laboratory stock

E. coli SM10 (λpir) thi thr-1 leu6 proA2 his-4 arg E2 lacY1 galK2,

ara14xyl5 supE44, λpir Laboratory stock

pMD19-T Cloning vector, Ampr TaKaRa, Japan

pRE112 pGP704 suicide plasmid, pir dependent, oriT, oriV,

sacB, Cmr

Laboratory stock

pRE112-⊿hiuH pRE112 containing a 686 bp hiuH-deletion PCR

product

This study

pRE112-⊿hiuH-C pRE112 containing a wild-type copy hiuH and its two

flanks sequence; used to complement strain ⊿hiuH This study

pRE112-⊿proX pRE112 containing a 905 bp proX-deletion PCR

product This study

pRE112-⊿proX-C pRE112 containing a wild-type copy proX and its two

flanks sequence; used to complement strain ⊿proX This study

772

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