Proteomic Analysis Shows That Individual Listeria monocytogenes Strains Use Different Strategies in Response to Gastric Stress

Abstract

Ingestion of contaminated dairy products, in particular soft cheese, is one of the major routes of infection by the human pathogen Listeria monocytogenes. During cheese processing, this foodborne pathogen is exposed to sublethal acid and osmotic stress conditions, which may induce tolerance responses and influence subsequent survival in the gastric tract. The aim of the current study was to evaluate the impact on a L. monocytogenes cheese isolate (serotype 4b) and two cheese dairy isolates (T8, serotype 4b, isolated from vat; and A9, serotype 1/2b or 3b, isolated from shelf stand) of exposure to sublethal conditions of pH and salt (5.5 and 3.5% [w/v] NaCl) in a cheese-simulated medium and further challenge with gastric stress. The bacterial cells exposed to pH 7.0 and no added salt were considered non-adapted. Via two-dimensional gel electrophoresis (2-DE), the proteomes of cheese-simulated medium and gastric challenged Listeria cells were compared. All L. monocytogenes isolates were able to survive the high acidity of gastric fluid (pH 2.5), and no significant differences were observed between adapted and non-adapted cells. However, the analysis of the intracellular proteome profiles revealed a significant intra-strain variation in the protein arsenal used to respond to the adaptation in the cheese-based medium and to the gastric stress. In cheese-based medium, the three strains produced different stress proteins. All three strains showed a higher abundance of carbohydrate proteins, but there was no overlap between them. Exposure to the gastric fluid induced the production of a group of proteins in T8 adapted and non-adapted cells that had not been detected previously in the cheese-based proteome. No such response was shown by A9 and C882 strains. Taken together, this study evidences the proteome tools used by adapted and non-adapted cells to cope with the hostile microenvironment of the stomach.

Introduction

L isteria monocytogenes is a human pathogen of great concern to the food industry and to health organizations. It is the causative agent of listeriosis, a life-threatening disease affecting mainly the elderly, immunocompromised individuals, and fetuses, with high mortality rates (20–30%) (Ryan et al., 2010; Swaminathan and Gerner-Smidt, 2007). The majority of listeriosis outbreaks have been associated with the consumption of dairy products, with soft cheeses one of the major vehicles (Swaminathan and Gerner-Smidt, 2007). L. monocytogenes can be introduced into food processing facilities and food products by cross-contamination with environmental sources, and it can persist within factories for long periods, due to its ability to survive adverse conditions, such as refrigeration temperatures, low pH values, and high salt concentrations (Adrião et al., 2008; Danielsson-Tham et al., 2004; Hill et al., 2002). Following ingestion, to successfully establish its infection cycle, the pathogen needs to overcome a series of host barriers, in particular, the highly acidic gastric secretions. The exposure of L. monocytogenes to sub-lethal stresses usually found in a food matrix, such as low pH and or salt, may increase resistance to downstream stressors encountered in the gastrointestinal system. The survival of Listeria through the passage of a simulated gastric system has been investigated (Barmpalia-Davis et al., 2008; Jiang et al., 2010; Ramalheira et al., 2010; Barbosa et al., 2012). However, these studies were done using standard broth as pre-exposure condition before gastric challenge. Until now, the number of studies that used food or food-simulated media as pre-exposure condition has been very limited (Barmpalia-Davis et al., 2009; Skandamis et al., 2008). It is recognized, however, that there is a need for information about the impact of food matrices on the physiological capacity of L. monocytogenes to respond to the challenges, both by adaptation to the intrinsic food conditions (e.g., pH and salt) and to host conditions such as the acid conditions of gastric fluid (Soni et al., 2011a).

The present study evaluated the effect of exposure of L. monocytogenes cells to a cheese-simulated medium on the ability of Listeria to overcome the low pH of gastric fluid. For this, two L. monocytogenes cheese dairy isolates and a cheese isolate were exposed to sub-lethal conditions of pH and salt in a cheese-simulated medium, and their ability to survive the gastric challenge was evaluated. The listerial physiological responses under the cheese-simulated medium and gastric fluid challenges were evaluated by two-dimensional electrophoresis (2-DE).

Materials and Methods

Bacterial strains

L. monocytogenes A9, T8, and C882 were used in this study. The A9 strain (serotype 1/2b or 3b isolated from a dairy shelf stand) and T8 (serotype 4b isolated from a dairy vat) are cheese dairy isolates (Adrião et al., 2008; Chambel et al., 2007; Perni et al., 2007), and C882 (serotype 4b) is a cow's milk cheese isolate (Faleiro et al., 2003). Listeria cells were stored at −80°C in tryptic soy broth (TSB) supplemented with 25% (v/v) glycerol and, when necessary, were recovered in TSB and maintained on tryptic soy agar (TSA) at 4°C. Prior to each experiment, the cells were transferred to fresh TSA plates and incubated at 30°C for 24 h.

Adaptation to cheese-simulated medium

Adaptation of the L. monocytogenes strains to sub-lethal conditions was done by exposure of the bacterial cells to pH 5.5 and 3.5% (w/v) NaCl using a cheese-simulated medium (Kagkli et al., 2006) with the following composition per liter: amicase 15.0 g, sodium lactate 38.0 mL, yeast extract 3.0 g, CaCl₂ 0.1 g, MgSO₄ 1.02 g, KH₂PO₄ 6.8 g, methionine 6 g, and lactose 2.1 g. The medium was modified and supplemented with additional 0.2% (w/v) glucose, which is the minimal amount required for Listeria growth (Trivett and Meyer, 1971). The selected adaptation conditions are usually found in cheese and induce tolerance responses (Adrião et al., 2008; Faleiro et al., 2003). The bacterial cells were exposed to the cheese medium (CM) for 2 h. Prior to the CM inoculation, the Listeria cells were grown in TSB at 30°C overnight and collected by centrifugation (1575×g, 10 min, 4°C) and transferred to either CM at pH 5.5 and 3.5% (w/v) NaCl (adapted cells) or to CM at pH 7.0 with no NaCl added (non-adapted cells). The incubation was done at 20°C with agitation (60 rpm) for 2 h. The incubation temperature of 20°C was selected as it is the usual room temperature of a cheese-processing environment. The experiments were done in triplicate, and the viability was determined in triplicate according to Miles and Misra (1938) in Brain Heart Infusion agar (BHIa).

Survival in simulated gastric system

The in vitro gastric system simulating digestive process of the mouth and stomach was performed as previously described by Versantvoort et al. (2005), and all the components of the saliva and gastric fluid were purchased from Sigma-Aldrich (Madrid, Spain) or WWR (Lisbon, Portugal). After cheese-simulated medium exposure, adapted and non-adapted cells were collected by centrifugation (3124×g, 5 min, 4°C), and the resulting pellet was resuspended in 9 mL of synthetic saliva and incubated for 5 min at 37°C under low agitation (30 rpm). After this time interval, 12 mL of the synthetic gastric fluid (pH 2.5) was added to the previous saliva suspension. The bacterial cells were gastric challenged for 2 h at 37°C with slight agitation (30 rpm). The viability was determined with BHIa, according to Miles and Misra (1938). The viability was determined in triplicate, and three biological replicates were tested.

Protein extraction and quantification

The protein extraction was done according to Folio et al. (2004). The adapted and non-adapted cells collected from the CM medium and the gastric fluids were collected by centrifugation at 1575×g for 10 min at 4°C. The pellet was washed four times with washing buffer (100 mM Tris, pH 7.0, and 100 mM EDTA) containing 0.1 mL of 100×protease inhibitor (GE Healthcare). The resulting pellet was resuspended in 500 μL of lysis buffer (25 mM Tris, pH 7.0, 50 mM EDTA, 1% [v/v] DTT), and the cells were disrupted by sonication (Soniprep 150, Sanyo) on ice for 15 min. To eliminate nucleic acids contaminants, 1 μL of DNase (1 U/μL; Promega) and 5 μL of RNase (10 mg/mL; Promega) were added. Unbroken cells and cell debris were removed by centrifugation (3000×g for 10 min at 4°C). Protein was precipitated with ice-cold acetone and collected by centrifugation (18000×g during 30 min at 4°C). Samples were air-dried, and proteins were solubilized by addition of 400 μL of solubilization buffer (7 M urea, 2 M thiourea, 4% [w/v] CHAPS, 40 mM DTT, 0.8% [v/v] Pharmalyte). The protein content was determined by the method of Bradford (1976) using bovine serum albumin as the standard. Protein samples were stored at −80°C and resuspended in rehydration buffer (GE Healthcare) prior to electrophoresis.

2-DE

The protein profile of adapted and non-adapted cells in the CM medium and in the gastric fluid was determined by 2-DE, as previously described (Pinto et al., 2012). 500 μg of protein was resuspended in rehydration solution (2 M thiourea, 6 M urea, 4% [w/v] CHAPS, 0.5% [v/v] IPG buffer, 0.5% [v/v] Destreak Reagent, 0.002% [w/v] bromophenol blue). The protein samples were separated in the first dimension using an 18-cm, pH 4–7 Immobiline Dry Strip (GE Healthcare). Protein separation in the second dimension was performed in 12.5% (w/v) SDS–polyacrylamide gels. Three biological replicates were analyzed, and the gels were run in triplicate. The determination of the protein profiles was done using Image Scanner II (GE Healthcare), in combination with computational image analysis done by using Image Master 2D Platinum software, version 6.0 (GE Healthcare). The statistical analysis was performed using the Student's t-test (significance level 0.05 and 0.01). Mean normalized spot volume, standard deviation (SD), and coefficient of variance (CV) were determined for each spot.

Protein identification

The identification of protein spots was done at the University of Leicester Proteomics Facility (PNACL, University of Leicester). Protein spots showing ≥2-fold change in abundance were manually excised from the gel, and in-gel trypsin digestion was carried out upon each (Speicher et al., 2000). Destaining was done by using 200 mM ammonium bicarbonate/20% acetonitrile, followed by reduction (10 mM dithiothreitol; Melford Laboratories Ltd.), alkylation (100 mM iodoacetamide), and enzymatic digestion (sequencing grade modified porcine trypsin; Promega) using an automated digest robot (Multiprobe II Plus EX; Perkin Elmer). After overnight digestion, each sample was acidified using formic acid (final concentration 0.1% [v/v]), and analyzed by MALDI-ToF mass spectrometry. MALDI-ToF analysis was done as follows. Peptide mass fingerprinting was carried out using a Voyager DE-STR MALDI-ToF mass spectrometer (Applied Biosystems) in positive ion reflectron mode. Calibrated mass spectra were searched using Mascot (version 2.2.04, Matrix Science Ltd.) (Perkins et al., 1999) against the UniProtKB/Swissprot database (The Uniprot Consortium, 2010). The peptide tolerance was set to 50 ppm. Fixed modifications were set as carbamidomethyl cysteine, and variable modifications were set as oxidized methionine. The enzyme was set to Trypsin/P, and up to one missed cleavages was allowed. Identifications were considered if they were within the p<0.05 confidence limit.

Statistical analysis

The significant differences between the survival of adapted and non-adapted cultures were determined using the independent t-test through the SPSS 12.0 program (SPSSS Inc., Chicago, IL).

Results

Survival of adapted and non-adapted cells in gastric fluid

Prior to the gastric challenge, the L. monocytogenes cells were exposed to sublethal conditions of low pH and salt (pH 5.5 and 3.5% [w/v] NaCl) in a cheese-simulated medium (CM), conditions that isolates of L. monocytogenes from cheese and cheese-processing environment can survive, and which induces tolerance responses (Adrião et al., 2008; Faleiro et al., 2003). The gastric challenge was started by exposing L. monocytogenes cells to artificial saliva for 5 min. The three L. monocytogenes strains had a 100% survival after 5 min in contact with the artificial saliva (data not shown), and when challenged with the gastric fluid, all three strains were able to survive the acidic condition with no reduction in the viability, and no significant differences between the survival of adapted and non-adapted cells was observed (see Supplementary Table S1; Supplementary Data are available online at www.liebertpub.com/fpd). These results were surprising, as these strains had shown a different acid tolerance response (ATR) in a defined medium when lactic acid was used to achieve the tested sub-lethal and lethal pH values (Adrião et al., 2008). In defined medium, the cheese-processing environmental strain T8 showed an acid-resistant profile in contrast to A9, which showed a typical ATR profile that was also observed in the cheese isolate, C882 (Faleiro et al., 2003). To clarify, if the mechanisms of gastric survival between the adapted and non-adapted cells were similar, a proteomic approach was used for (1) adapted and non-adapted L. monocytogenes in the cheese-simulated medium and (2) gastric challenge adapted and non-adapted cells.

Proteome response to adaptation in a cheese-simulated medium

The protein pattern of adapted cells and non-adapted cells of the three L. monocytogenes strains (T8, A9, and C882) in the CM medium is shown in Figure 1A–F, and the identified protein spots are summarized in Table 1 and in supplementary Table S2. The identified proteins overproduced by T8 adapted cells were distributed through six categories, and three proteins related to stress response were identified, namely the 60-kDa chaperonin (GroEL), ATP synthase F1, β subunit, and the glutamate decarboxylase (see Fig. 2A). Seven proteins underproduced by T8 adapted cells were identified, and one of them was a cold-shock protein (Table 1 and Supplementary Table S2). A different group of overproduced proteins was observed in A9 and C882 strains (Table 1). The overproduced proteins by A9 adapted cells were distributed in six categories, the categories with the highest number of proteins being for carbohydrate metabolism and protein synthesis (Table 1 and Fig. 2B). The C882 adapted cells also overproduced carbohydrate metabolism proteins, but there was no overlap with proteins of this category produced by T8 or A9 (Table 1 and Fig. 2C). In contrast to the T8, A9 and C882 strains only overproduced one protein involved in stress response. A9 overproduced non-heme iron binding ferritin, whereas C882 strain overproduced a 33-kDa chaperonin that belongs to the Heat Shock Protein family (HSP33) (Table 1 and Fig. 2A–C). The lower abundance of a cold shock protein was observed in adapted T8 and C882 cells.

FIG. 1.

Two-dimensional gel electrophoresis (2-DE) maps of intracellular proteomes of Listeria monocytogenes in cheese-based medium. Adapted T8 cells (A), non-adapted cells T8 cells (B), adapted A9 cells (C), non-adapted A9 cells (D), adapted C882 cells (E), and non-adapted C882 cells (F). The more abundant proteins are shown by the ○ symbol, and the less abundant proteins by the symbol. The identified proteins are listed in Table 1.

FIG. 2.

Distribution according to function of those proteins with increased synthesis by Listeria monocytogenes isolates T8 (A), A9 (B), and C882 (C) in adaptation to cheese-based medium: stress response (); carbohydrate metabolism (); vitamin synthesis (); protein synthesis (); nucleotide biosynthesis (); and other functions (). In each protein functional category is indicated the percentage value in relation to the total number of proteins identified.

Table 1.

Proteins Differentially Produced by Listeria monocytogenes Strains T8, A9, and C882 in Cheese-Simulated Medium

Functional category or description	Spot ID	UniProt ID	Gene/locus	Protein name	Fold change ^a
Proteins overproduced by T8 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Stress response	75	Q71XU6	groL/ LMOf2365_2099	60-kDa chaperonin	2.0
Stress response	78	Q4EPJ2	atpD-2/LMOf6854_2591	ATP synthase F1, beta subunit	2.0
Stress response	276	Q4EJM6	gadB/ LMOh7858_2506	Glutamate decarboxylase beta	4.5
Purine and nucleoside metabolism	61	PUR5_LISMF	purM/LMOf2365_1792	Phosphoribosylformylglycinamidine cyclo-ligase	2.0
Purine and nucleoside metabolism	85	Q4EPI4	upp/LMOf6854_2599	Uracil phosphoribosyltransferase	2.0
Purine and nucleoside metabolism	249	C1KW64	purH/Lm4b_01779	Bifunctional purine biosynthesis protein purH	2.0
Carbohydrate metabolism	77	Q71WX1	eno/LMOf2365_2428	Enolase	2.0
Carbohydrate metabolism	90	Q4EK17	manL/LMOh7858_0120	PTS system, mannose-specific, IIAB component	2.0
Vitamin metabolism	211	Q4ESQ4	pdxS/LMOf6854_2162	Pyridoxal biosynthesis lyase pdxS	2.0
Oxidation-reduction reactions	153	Q71X36	LMOf2365_2363	Pyridine nucleotide-disulfide oxidoreductase family protein	2.0
Oxidation-reduction reactions	173	Q4EKC3	gabD/LMOh7858_0975	Succinate-semialdehyde dehydrogenase	2.5
Protein metabolism and chemotaxis	166	C8JY54	LMIG_02608	Chemotaxis protein CheV	2.0
Protein metabolism and chemotaxis	201	Q721K6	LMOf2365_0980	Putative peptidase	2.5
Proteins underproduced by T8 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Stress response	1	Q71ZV8	LMOf2365_1381	Cold-shock domain family protein	−14.4
Protein synthesis	16	Q71WE6	rplC/LMOf2365_2605	50S ribosomal protein L3	−2.1
Protein synthesis	138	Q720E1	codY/LMOf2365_1298	GTP-sensing transcriptional pleiotropic repressor codY	−2.0
Carbohydrate metabolism	202^b	Q71ZM2	ppaC/LMOf2365_1467	Probable manganese-dependent inorganic pyrophosphatase	−2.0
Carbohydrate metabolism	255	Q71Y98	pfl-2/LMOf2365_1946	Formate acetyltransferase	−3.8
Amino acid metabolism	301	Q720C2	glnA/LMOf2365_1317	Glutamine synthetase	−4.8
Proteins overproduced by A9 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Protein synthesis	1	C1KY13	rplL / Lm4b_02342	Putative ABC-transporter ATP binding protein	8.6
Protein synthesis	7	C1KZG8	rplE/ Lm4b_02587	50S ribosomal protein L5	4.5
Protein synthesis	36	C1KVP7	aroA/ Lm4b_01592	3-Deoxy-d-arabino-heptulosonate 7-Phosphate synthase	5.6
Carbohydrate metabolism	40	Q4EI17	pdhA/LMOh7858_1120	Pyruvate dehydrogenase complex	5.8
Carbohydrate metabolism	44	C1KXN2	psuG /Lm4b_02304	Pseudouridine-5′-phosphate glycosidase	9.8
Carbohydrate metabolism	62	C8JUD2	LMIG_01532	Glyceraldehyde-3-phosphate dehydrogenase	3.0
Carbohydrate metabolism	14	C1L2K0	glpD/ Lm4b_01302	Putative glycerol 3-phosphate dehydrogenase	2.4
Carbohydrate metabolism	96	C1L0F8	Lm4b_02797	Putative d-3-phosphoglycerate dehydrogenase	8.0
Stress response	21	C1L1L4	fri/ Lm4b_00962	Non-heme iron binding ferritin	2.7
Amino acid metabolism	89	C1KVR6	daaA/ Lm4b_01630	d-Amino acid aminotransferase	6.8
Coenzymes metabolism	42	D3KMM6	LMFG_01525	Naphthoate synthase	2.0
Not yet assigned	91	C1L1Q3	Lm4b_01002	Putative glucanase and peptidase	2.0
Proteins underproduced by A9 adapted cells (pH 5.5 and 3.5% [w/v] NaCl] in comparison to non-adapted cells (pH 7.0, no NaCl added)
Carbohydrate metabolism	5	C1KVT1	Lm4b_01645	Putative alcohol-acetaldeyde dehydrogenase	−3.0
Carbohydrate metabolism	30	C1KYX2	fbaA/Lm4b_00378	Putative fructose-1,6-biphosphate aldolase	−2.0
Motility	28	Q6LAU6	flaA	Flagellin	−5.5
Amino acid metabolism	24	Q4ELL5	thiD-2/LMOh7858_0725	Phosphomethylpyrimidine kinase	−2.0
Isoprenoid biosynthesis	64	Q4EIM4	mvaA/LMOh7858_1510	Hydroxymethylglutaryl-CoA synthase	−2.0
Proteins overproduced by C882 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Carbohydrate metabolism	46	GPMA_LISMF	gpmA/LMOf2365_2238	2,3-Bisphosphoglycerate-dependent phosphoglycerate mutase	2.3
Carbohydrate metabolism	68	Q4EK17	manL/LMOh7858_0120	PTS system, mannose-specific, IIAB component	3.1
Carbohydrate metabolism	151	GPMI_LISMF	gpmI/LMOf2365_2529	2,3-Bisphosphoglycerate-independent phosphoglycerate mutase	4.1
Stress response	100	Q724J1	hslo/LMOf2365_0233	33-kDa chaperonin	4.0
Nucleotide synthesis	169	Q4EFZ5	purB/LMOh7858_1898	Adenylosuccinate lyase	4.0
Nucleotide synthesis	173	PUR9_LISMF	purH/LMOf2365_1790	Bifunctional purine biosynthesis protein purH	2.4
Nucleotide synthesis	184	C8K6Y8	LMJG_02766	CTP synthetase	3.2
Oxidation–reduction reactions	119	Q4EHW9	LMOh7858_2558	Putative uncharacterized protein	7.6
Oxidation–reduction reactions	170	Q71X14	sufD/LMOf2365_2385	FeS assembly protein sufD	4.9
Proteins underproduced by C882 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Virulence factor	1	C7A0B1	actA/lmo0204	Actin assembly-inducing protein (fragment)	−2.0
Carbohydrate metabolism	5	Q4ER91	ptsH/LMOf6854_1051	Phosphocarrier HPr	−2.2
Stress response	195	D3KND4	LMFG_01795	Cold-shock–like protein CsplA	−139.4
Unknown function	197	Q4EE92	LMOh7858_1343	Putative uncharacterized protein	−25.4

Fold changes in protein abundance (overproduced) are indicated as the ratio between the normalized spot volume from adapted cells (pH 5.5 and 3.5% [w/v] NaCl) and non-adapted cells (pH 7.0 and no NaCl added; Vadapt/Vnon-adapt). The inverse negative value (-Vnon-adapt/Vadapt) is indicated for underproduced proteins.

Two spots (202 and 254) were identified.

Differential protein abundance is indicated as fold change (minimum twofold, p<0.05).

The molecular function and biological process of the identified proteins were annotated according to the database Universal Protein Resource (Uniprot) (www.pir.uniprot.org/).

The proteome response to gastric challenge

The proteome pattern of adapted and non-adapted cells is shown in Figure 3A–F. A different protein profile is seen for each of the three L. monocytogenes strains (Fig. 4). Adapted cells of L. monocytogenes T8 overproduced 33 proteins in comparison to non-adapted cells. Twenty proteins were identified and are listed in Table 2 and Supplementary Table S3. T8 adapted and non-adapted cells during the exposure to the gastric challenge produced nine proteins that had not been detected previously in the bacteria exposed to the CM medium (Fig. 3A and B and Table 2). These nine proteins were distributed in five categories: stress response, hydrolysis activity, deoxyribonucleoside diphosphate metabolism, proteolysis and peptide metabolism, and carbohydrate metabolism. The A9 and C882 strains did not produce proteins strictly linked to the gastric challenge. The proteins overproduced by T8 adapted cells after the gastric challenge were distributed in four categories: stress response, vitamin biosynthesis, carbohydrate metabolism, and fatty acid biosynthesis (Fig. 4A). The higher abundance of pyridoxal biosynthesis lyase PdxS was observed in T8 and C882 adapted cells in contrast to A9, which underproduced this protein. The higher abundance of PdxS by T8 was also observed during adaptation in cheese-simulated medium. The lower abundance of a cold-shock protein (CspLA) was seen in T8 and C882 adapted cells.

FIG. 3.

Two-dimensional gel electrophoresis (2-DE) maps of intracellular proteomes of Listeria monocytogenes exposed to gastric fluid. Adapted T8 cells (A), non-adapted cells T8 cells (B), adapted A9 cells (C), non-adapted A9 cells (D), adapted C882 cells (E), and non-adapted C882 cells (F). The most abundant proteins are shown by the ○ symbol; less abundant proteins by the symbol, and the proteins only expressed by T8 in simulated gastric fluid are shown by the symbol □. The identified proteins are listed in Table 2.

FIG. 4.

Distribution according to function of those proteins with increased synthesis by Listeria monocytogenes isolates T8 (A), A9 (B), and C882 (C) exposed to gastric juice: stress response (); carbohydrate metabolism (); vitamin synthesis (); amino acid metabolism (); protein synthesis (); and other functions (). In each protein functional category is indicated the percentage value in relation to the total number of proteins identified.

Table 2.

Proteins Differentially Produced by Listeria monocytogenes Strains T8, A9, and C882 Exposed to Gastric Fluid

Functional category or description ^a	Spot ID	UniProt ID	Gene/locus	Protein name	Fold change ^b
Proteins overproduced by T8 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Stress response	419	CSPB_LISMO	cspLB/ lmo2016	Cold-shock–like protein CspLB	2.0
Vitamin biosynthesis	112	Q4EL53	pdxS/ LMOh7858_2231	Pyridoxal biosynthesis lyase pdxS	2.0
Carbohydrate metabolism	29	Q4EEP4	tpiA-2/ MOh7858_2606	Triosephosphate isomerase	2.0
Carbohydrate metabolism	260	Q4EEB5	LMOh7858_1367	Aldose epimerase family protein	2.0
Carbohydrate metabolism	287	Q4ETJ7	LMOf6854_2814	Dihydroxyacetone kinase, Dak1 subunit, putative	3.0
Carbohydrate metabolism	391	Q71WX1	eno/ LMOf2365_2428	Enolase	2.4
Fatty acid biosynthesis	387	Q4EFW5	fabH/ LMOh7858_2336	β-Ketoacyl-ACP synthase III	2.9
Proteins underproduced by T8 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Stress response	2	CSPA_LISMO	cspLA/ lmo1364	Cold-shock–like protein CspLA	−2.6
Cell wall regulation	297^c	Q721J2	dltA/ LMOf2365_0994	d-Alanine-poly(phosphoribitol) ligase subunit 1	−4.1
GTP binding and GTPase activity	311	Q4EI06	typA/LMOh7858_1131	GTP-binding protein TypA	−3.2
Proteins produced by adapted and non-adapted cells of L. monocytogenes T8 during exposure to the gastric juice ^d
Stress response	430	Q8Y648	lmo1852	Lmo1852 (similar to mercuric ion binding proteins)	NA
Hydrolase activity	436	C1KYL2	Lm4b_00300	Putative uncharacterized protein	NA
Hydrolase activity	437	Q4EGP0	LMOh7858_1686	UPF0173 metal-dependent hydrolase	NA
Deoxyribonucleoside diphosphate metabolism	438	Q71XL2	nrdB/LMOf2365_2186	Ribonucleoside-diphosphate reductase, beta subunit	NA
Proteolysis and peptide metabolism	440	Q71YN8	pepT/LMOf2365_1805	Peptidase T	NA
Proteolysis and peptide metabolism	441	Q720U2	clp1/LMOf2365_1146	ATP-dependent Clp protease proteolytic subunit	NA
Carbohydrate metabolism	434	Q71WX1	eno/ LMOf2365_2428	Enolase	NA
Carbohydrate metabolism	442	Q4EM05	LMOh7858_0303	Glycosyl hydrolase, family 1	NA
Carbohydrate metabolism	443	Q71ZU4	Gnd/LMOf2365_1395	6-Phosphogluconate dehydrogenase, decarboxylating	NA
Proteins overproduced by A9 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Nucleotide metabolism	8^e	C1L094	guaB/Lm4b_0273	Inosine-5′-monophosphate dehydrogenase	2.3
Amino acid metabolism	31	Q4EHG5	cysK/LMOh7858_0243	Cystein synthase	2.3
Amino acid metabolism	33	Q4EDR2	LMOh7858_1723	Glutamyl-aminopeptidase, putative	3.5
Stress response	11	SODM_LISMO	sodA/lin1478	Superoxide dismutase	2.0
Protein synthesis	48	C8K2C4	LMJG_01152	30S ribosomal protein S1	2.4
Carbohydrate metabolism	40	C8KAU4	LMMG_00024	Pyruvate dehydrogenase complex	2.6
Carbohydrate metabolism	44	C1KXN2	psuG/Lm4b_02304	Pseudouridine-5′-phosphate glycosidase	2.0
Carbohydrate metabolism	45	C8KAU5	LMMG_00025	Pyruvate dehydrogenase complex E1 component beta subunit	4.0
Carbohydrate metabolism	70	Q4EI14	galE/LMOh7858_2626	UDP-glucose 4-epimerase	23.4
Not yet assigned	63	C8K3K1	LMJG_01579	Putative uncharacterized protein	3.8
Proteins underproduced by A9 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Protein synthesis	6	C1KZK8	rpsG/Lm4b_02627	30S ribosomal protein S7	−58.6
Protein synthesis	7	D2P7X8	rplF/LM5923_0243	50S ribosomal protein L6	−14.3
Protein synthesis	39	C1KZK6	tuf/Lm4b_02625	Elongation factor Tu	−26.1
Protein synthesis	16	C1KZI0	rplC/Lm4b_02599	50S ribosomal protein L3	−5.6
Peptidase activity	12	C1KXL1	Lmb4_02283	Putative intracellular protease	−7.0
DNA binding	4	C1KWN4	hup/Lm4b_01951	Putative non-specific DNA-binding	−17.4
Carbohydrate metabolism	29	C1KY96	tpi/Lm4b_02426	Triosephosphate isomerase	−2.0
Vitamin biosynthesis	112	C1KX53	pdxS/Lm4b_02122	Pyridoxal biosynthesis lyase pdxS	−8.3
Proteins overproduced by C882 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0, no NaCl added)
Hydrolyzes	23	C8JQX9	LMIG_00907	Intracellular protease	2.0
Amino acid synthesis	47	Q71X34	LMOf2365_2365	Putative uncharacterized protein	2.0
Stress response	53	C1KZM7	Lm4b_02646	Conserved hypothetical protein, UspA	2.4
Amino acid metabolism	76	C1KX53	pdxS/Lm4b_02122	Pyridoxal biosynthesis lyase pdxS	3.6
Protein synthesis	65	Q71YV8	map/LMOf2365_1733	Methionine aminopeptidase	2.0
Protein synthesis	140	C8KDF3	fusA/LMMG_02489	Elongation factor G	3.2
Carbohydrate metabolism	151	Q71WX0	gpmI/LMOf2365_2429	2,3-Bisphosphoglycerate-independent phosphoglycerate mutase	2.0
Carbohydrate metabolism	205	C8JYE9	LMIG_01097	Bifunctional acetaldehyde-CoA/alcohol dehydrogenase	3.4
Proteins underproduced by C882 adapted cells (pH 5.5 and 3.5% [w/v] NaCl) in comparison to non-adapted cells (pH 7.0 no NaCl added)
Stress response	4	Q4EEZ7	groES/LMOh7858_2198	10-kDa chaperonin	−2.1
Stress response	6	P0A355	cspLA/lmo1364	Cold-shock–like protein cspLA	−3.1
Carbohydrate metabolism	92	C1KX63	Lm4b_02132	Putative mannose-6 phosphate isomerase	−14.3
Carbohydrate metabolism	122	C8JRB8	glmM/LMIG_00768	Phosphoglucosamine mutase	−4.5
Not yet assigned	197	Q4EE92	LMOh7858_1343	Putative uncharacterized protein	−2.1

The molecular function and biological process of the identified proteins were annotated according to the database Universal Protein Resource (Uniprot) (www.pir.uniprot.org/).

Fold changes in protein abundance (overproduced) are indicated as the ratio between the normalized spot volume from adapted cells (pH 5.5 and 3.5% [w/v] NaCl) and non-adapted cells (pH 7.0 and no NaCl added) (Vadapt/Vnon-adapt). For underproduced proteins is indicated the inverse negative value (-Vnon-adapt/Vadapt).

Two spots (297 and 299) were identified.

The indicated protein spots were not observed when T8 cells were exposed to the cheese-simulated medium.

Two spots (8 and 9) were identified.

Differential protein abundance is indicated as fold change (minimum twofold, p<0.05).

NA, not applied.

The proteome pattern of A9 strain is shown in Figure 3C and D. Twenty proteins were identified and are listed in Table 2. The proteins overproduced by A9 adapted cells after gastric challenge were distributed among six categories, with the highest number of proteins being the carbohydrate metabolism category (Fig. 4B).

The gastric proteome of C882 (Fig. 3E and F) showed 74 proteins overproduced by adapted cells in comparison to non-adapted cells. Twelve proteins were identified and are listed in Table 2.

Discussion

The assembly of the proteome response to adaptation to sublethal pH and salt in the cheese-simulated medium by the three L. monocytogenes strains was unique for each strain. The highest number of stress proteins was found in the T8 adapted cells. In previous studies, it has been shown that T8 was innately acid resistant but mounted an osmotolerance response (Adrião et al., 2008; Melo et al., 2013, submitted). Therefore, it seems reasonable to advance the hypothesis that T8 responds to moderate osmolarity (3.5% [w/v] NaCl) in the CM medium with the assistance of the 60-kDa chaperonin (GroEL), ATP synthase F1, β subunit, and the glutamate decarboxylase beta. GroEL has been associated to cold, osmotic, and acid stress responses in L. monocytogenes (Loepfe et al., 2010; Phan-Thanh and Mahouin, 1999; Schmid et al., 2009), whereas F₁F₀ –ATPase and the glutamate decarboxylase, which is part of the glutamate decarboxylase system (GAD), have been associated with the acid tolerance response (Cotter et al., 2000, 2001, 2005; Karatzas et al., 2010). The glutamate decarboxylase converts extracellular glutamate to γ-aminobutyrate (GABA) by consuming an intracellular proton and increasing the internal cellular pH. T8 also showed higher abundance of another protein that seems to be essential to the metabolism of GABA, succinate–semialdehyde dehydrogenase (SSDH). This enzyme converts GABA to succinate (Cotter et al., 2005) and a mutant defective in SSDH is sensitive to low pH possibly due to the inability to metabolize the intracellular GABA to a non-toxic metabolite, succinic acid (Abram et al., 2008a). The higher abundance of SSDH was previously shown in the T8 strain when it was exposed to the same sub-lethal conditions in a defined medium (Melo et al., 2013, submitted). The higher abundance of SSDH by T8 in two different exposures to salt conditions validates its role and it seems reasonable to advance the hypothesis that T8 responds to the moderate osmolarity (3.5% [w/v] NaCl) in the CM medium with an accumulation of GABA that then is converted to succinate by SSDH (Abram et al., 2008a,b; Belitsky and Sonenshein, 2002). It appears that accumulation of GABA not only assists acid tolerance but also osmotolerance. In contrast to T8, only one stress protein was identified in the A9 and C882 strains. In A9 the non-heme iron binding ferritin was identified and in C882 the 33-kDa chaperonin. In L. monocytogenes the non-heme iron-binding ferritin is considered a major cold shock protein (Hebraud and Guzzo, 2000). It seems that its higher abundance can be associated with a multitude of stress conditions since iron storage or the oxidation state of the cell can be disturbed by different stresses and appropriately high levels of ferritin can neutralize the potential damage.

The 33-kDa chaperonin belongs to HSP33. This group of proteins protects both thermally unfolded and oxidatively damaged proteins from irreversible aggregation. It also appears that HSP33 assists in the repair of acid damage, but so far the participation of this protein in L. monocytogenes response to stress conditions (including oxidative, acid, osmotic, and thermal) has not been reported. The activity of this chaperonin is turned on by oxidative stress (Jakob et al., 1999). It is recognized that oxidative and acid stress may be linked, as the production of ROS species may be a consequence of cellular acid damage (Mols and Abee, 2011).

An intriguing result was the lower abundance of cold shock proteins by T8 and C882 adapted cells, as the adaptation was done at the sub-optimal temperature of 20°C. The cold shock proteins have been associated with protection against cold, osmotic and oxidative stress (Schmid et al., 2009). The reason that T8 and C882 strains, at a relatively low temperature and sub-lethal conditions of pH and salt, decrease the production of this type of protein is unknown.

According to our proteomic data, adapted C882 cells underproduced an important virulence factor, the actin polymerase protein (ActA), which is vital to the infectious process of L. monocytogenes (Domann et al., 1992). Another surprising observation was the lower abundance of flagellin by adapted A9 cells. In L. monocytogenes, flagellin expression is regulated by temperature, and the flaA gene is maximally transcribed at 20–25°C and repressed at 37°C (Dons et al., 1992); it seems that L. monocytogenes represses flagellin expression as a strategy of escaping host immunity (Way et al., 2004). So far it has not been reported that flagellin responds to acid or osmotic stress. However, previous studies with Salmonella enterica serovar Typhi showed that flagellin expression decreases under acid and osmotic stress (Xu et al., 2008).

During adaptation, the three L. monocytogenes strains showed differences in abundance of proteins linked with energy requirement. A9 had the highest number of increased proteins involved in carbohydrate metabolism, and an interesting finding was the higher abundance of the pseudouridine-5'-phosphate glycosidase, which was previously associated with the acid adaptation of A9 in a defined medium (Melo et al., 2013, submitted) suggesting a crucial role in the assembly of adaptation responses by this L. monocytogenes strain.

The ability of Listeria to develop acid tolerance responses can be a significant factor in determining the pathogen's survival in the human gastric system (Werbrouck et al., 2009). Despite the fact that survival to gastric fluid has been demonstrated to be strain dependent (Barmpalia-Davis et al., 2008), the three L. monocytogenes strains tested in our study revealed a strong resistance profile to the highly acidic environment. Using a dynamic gastric model Barmpalia-Davis et al. (2008) also reported the ability of several L. monocytogenes strains to survive the severe acid stress conditions of gastric fluids. However our strains survived significantly better when compared to other food and clinical isolates tested by Ramalheira et al. (2010) and to the Portuguese cheese isolates tested by Barbosa et al. (2012), using a gastric system simulation adjusted to pH 2.5. The role of the food matrix on the development of resistance of L. monocytogenes to gastric fluid has been reported (Barmpalia-Davis et al., 2009; Peterson et al., 2007), suggesting that some food components or food properties may cause protective effects against acid injury. It is possible that the exposure of our L. monocytogenes isolates to the cheese-based medium has contributed to their survival during the exposure to the low pH of the gastric fluid.

The proteome analysis of the L. monocytogenes strains exposed to the gastric fluid revealed a different arsenal of proteins used by each strain. The most intriguing strain was T8, which both adapted and non-adapted cells produced a group of proteins in response to the gastric fluid exposure that were not previously observed in the proteome of the cells exposed to the CM medium. Only one of these proteins is a stress response protein, namely Lmo 1852, which is similar to mercuric ion binding protein. Given the absence of mercury in gastric fluid, it suggests an additional although unexplained function for this protein.

The adapted cells of the three L. monocytogenes strains responded to the gastric fluid with the production of different stress response proteins; T8 overproduced a cold- shock–like protein CspLB, A9 overproduced the superoxide dismutase (SOD), and C882 overproduced a conserved hypothetical protein that belongs to the Universal Stress Proteins (UspA). The lower abundance of the cold-shock–like protein CspLA by T8 and C882 adapted cells during the gastric challenge was observed, which was also found during adaptation in the cheese-based medium. However, adapted T8 cells overproduced the cold shock protein CspLB, suggesting a role for these types of proteins in gastric stress response. Besides their recognized role in cold, osmotic, and oxidative stress protection in Listeria, Csp proteins have been associated with host invasion (Loepfe et al., 2010; Schmid et al., 2009). The higher abundance of SOD by adapted A9 cells suggests that during gastric fluid exposure the bacterial cells experience a secondary oxidative stress, resulting from the exposure to the low pH. In contrast, C882 responds with the UspA protein, which has been reported to be important for acid and oxidative stress response in L. monocytogenes (Gomes et al., 2011).

Our proteomic data show that from the collection of previously identified proteins involved in acid and osmotic stress (Soni et al., 2011b) our L. monocytogenes isolates did not show a similar profile, either under the exposure to the sublethal conditions or to the gastric challenge, by the contrary a unique profile was found. These findings reveal the complexity of the stress response of this important foodborne pathogen.

Conclusion

In conclusion, this study shows the individuality of various strains of L. monocytogenes in mounting stress responses in a food-simulated medium. In the present study, three strains rely on different protein repertoires to adapt to a sublethal pH and salt concentration, such as those found in cheese. A similar ability of adapted and non-adapted cells to overcome the gastric barrier was observed, but this similar ability was reached by different means; a distinct set of proteins was used to combat the gastric challenge. The diversity of protein synthesis responses by L. monocytogenes strains makes us aware of the difficulties in finding means of control for this foodborne pathogen and the risks encountered when either an acidic or neutral food is ingested.

Footnotes

Acknowledgments

We are grateful for the technical assistance of Nicola Burke and Shane Hussey. This work was partially financed by Fundação para a Ciência e Tecnologia (PTDC/AGRI-ALI/2006 and IBB/CBME, LA, FEDER/POCI). J.M. is thankful to Fundação para a Ciência e Tecnologia for funding (PhD grant PROTEC SFRH/BD/494037/2009). The authors are grateful to Andrew R. Bottrill and Shairbanu Ashra from the University of Leicester Proteomics Facility for the protein identification work.

Disclosure Statement

No competing financial interests exist.

References

Abram

, Starr

, Karatzas

KAG

, Matlawska-Wasowska

, Boyd

, Wiedmann

, Boor

, Connally

, O'Byrne

. Identification of components of the sigma B regulon in Listeria monocytogenes that contribute to acid and salt tolerance. Appl Environ Microbiol, 2008a. 74:6848–6858.

Abram

, Wan-Lin

, Wiedmann

, Boor

, Coote

, Botting

, Karatzas

KAG

, O'Byrne

. Proteomic analyses of a Listeria monocytogenes mutant lacking σ^B identify new components of the σ^B regulon and highlight a role for σ^B in the utilization of glycerol. Appl Environ Microbiol, 2008b. 74:594–604.

Adrião

, Vieira

, Fernandes

, Barbosa

, Sol

, Tenreiro

, Chambel

, Barata

, Zilhao

, Shama

, Perni

, Jordan

, Andrew

, Faleiro

. Marked intra-strain variation in response of Listeria monocytogenes dairy isolates to acid or salt stress and the effect of acid or salt adaptation on adherence to abiotic surfaces. Int J Food Microbiol, 2008; 123:142–150.

Barbosa

, Borges

, Magalhães

, Ferreira

, Santos

, Silva

, Almeida

, Gibbs

, Teixeira

. Behaviour of Listeria monocytogenes isolates through gastro-intestinal tract passage simulation, before and after two sub-lethal stresses. Food Microbiol, 2012; 30:24–28.

Barmpalia-Davis

, Geornaras

, Kendall

, Sofos

. Differences in survival among thirteen Listeria monocytogenes strains in a dynamic model of the stomach and small intestine. Appl Environ Microbiol, 2008; 74:5563–5567.

Barmpalia-Davis

, Geornaras

, Kendall

, Sofos

. Effect of fat content on survival of Listeria monocytogenes during simulated digestion of inoculated beef frankfurters stored at 7°C. Food Microbiol, 2009; 26:483–490.

Bradford

. A rapid and sensitive method for the quantification of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem, 1976; 72:248–254.

Belitsky

, Sonenshein

. GabR, a member of a novel protein family, regulates the utilization of γ-aminobutyrate in Bacillus subtilis. Mol Microbiol, 2002; 45:569–583.

Chambel

, Sol

, Fernandes

, Barbosa

, Zilhao

, Barata

, Jordan

, Perni

, Shama

, Adriao

, Faleiro

, Requena

, Pelaez

, Andrew

, Tenreiro

. Occurrence and persistence of Listeria spp. in the environment of ewe and cow's milk cheese dairies in Portugal unveiled by an integrated analysis of identification, typing and spatial-temporal mapping along production cycle. Int J Food Microbiol, 2007; 116:52–63.

10.

Cotter

, Gahan

, Hill

. Analysis of the role of the Listeria monocytogenes F0F1-ATPase operon in the acid tolerance response. Int J Food Microbiol, 2000; 60:137–146.

11.

Cotter

, Gahan

CGM

, Hill

. A glutamate decarboxylase system protects Listeria monocytogenes in gastric fluid. Mol Microbiol, 2001; 40:465–475.

12.

Cotter

, Ryan

, Gahan

CGM

, Hill

. Presence of GadD1 glutamate decarboxylase in selected Listeria monocytogenes strains is associated with an ability to grow at low pH. Appl Environ Microbiol, 2005; 71:2832–2839.

13.

Danielsson-Tham

, Eriksson

, Helmersson

, Leffler

, Lüdtke

, Steen

, Sørgjerd

, Tham

. Causes behind a human cheese-borne outbreak of gastrointestinal listeriosis. Foodborne Pathog Dis, 2004; 1:153–159.

14.

Domann

, Wehland

, Rohde

, Pistor

, Hartl

, Goebel

, Leimeister-Wachter

, Wuenscher

, Chakraborty

. A novel bacterial gene in Listeria monocytogenes required for host cell microfilament interaction with homology to the proline-rich region of vinculin. EMBO J, 1992; 11:1981–1990.

15.

Dons

, Rasmussen

, Olsen

. Cloning and characterization of a gene encoding flagellin of Listeria monocytogenes. Mol Microbiol, 1992; 6:2919–2929.

16.

Faleiro

, Andrew

, Power

. Stress response of Listeria monocytogenes isolated from cheese and other foods. Int J Food Microbiol, 2003; 84:207–221.

17.

Folio

, Chavant

, Chafsey

, Belkorchia

, Chambon

, Hébraud

. Two-dimensional electrophoresis database of Listeria monocytogenes EGDe proteome and proteomic analysis of mid-log and stationary growth phase cells. Proteom, 2004; 4:3187–3201.

18.

Gomes

, Izar

, Pazan

, Mohamed

, Mraheil

, Mukherjee

, Billion

, Aharonowitz

, Chakraborty

, Hain

. Universal stress proteins are important for oxidative and acid stress resistance and growth of Listeria monocytogenes EGD-e in vitro and in vivo. PLoS One, 2011; 6:e24965.

19.

Hébraud

, Guzzo

. The main cold shock protein of Listeria monocytogenes belongs to the family of ferritin-like proteins. FEMS Microbiol Lett, 2000; 190:29–34.

20.

Hill

, Cotter

, Sleator

, Gahan

CGM

. Bacterial stress response in Listeria monocytogenes: Jumping the hurdles imposed by minimal processing. Int Dairy J, 2002; 12:273–283.

21.

Jakob

, Muse

, Eser

, Bardwell

JCA

. Chaperone activity with a redox switch. Cell, 1999; 96:341–352.

22.

Jiang

, Olesen

, Andersen

, Fang

, Jespersen

. Survival of Listeria monocytogenes in simulated gastrointestinal system and transcriptional profiling of stress- and adhesion-related genes. Foodborne Pathog Dis, 2010; 7:267–274.

23.

Kagkli

, Tâche

, Cogan

, Hill

, Casaregola

, Bonnarme

. Kluyveromyces lactis and Sacharomyces cerevisiae, two potent deacidifying and volatile-sulphur-aroma-producing microorganisms of the cheese ecosystem. Appl Microb Biotechnol, 2006; 73:434–442.

24.

Karatzas

KAG

, Brennan

, Heavin

, Morrissey

, O'Byrne

. Intracellular accumulation of high levels of γ-aminobutyrate by Listeria monocytogenes 10403S in response to low pH: Uncoupling of γ-aminobutyrate synthesis from efflux in a chemically defined medium. Appl Environ Microbiol, 2010; 76:3529–3537.

25.

Loepfe

, Raimann

, Stephan

, Tasara

. Reduced host cell invasiveness and oxidative stress tolerance in double and triple csp gene family deletion mutants of Listeria monocytogenes. Foodborne Dis Pathog, 2010; 7:775–783.

26.

Miles

, Misra

, Irwin

. The estimation of the bactericidal power of the blood. J Hyg, 1938; 38:732–749.

27.

Mols

, Abee

. Primary and secondary oxidative stress in Bacillus cereus. Environ Microbiol, 2011; 13:1387–1394.

28.

Phan-Thanh

, Mahouin

. A proteomic approach to study the acid response in Listeria monocytogenes. Electrophoresis, 1999; 20:2214–2224.

29.

Perkins

, Pappin

DJC

, Creasy

, Cottrell

. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis, 1999; 20:3551–3567.

30.

Perni

, Aldsworth

, Jordan

, Fernandes

, Barbosa

, Sol

, Tenreiro

, Chambel

, Zilhão

, Barata

, Adrião

, Faleiro

, Andrew

, Shama

. The resistance to detachment of dairy strains of Listeria monocytogenes from stainless steel by shear stress is related to the fluid dynamics characteristics of the location of isolation. Int J Food Microbiol, 2007; 116:384–390.

31.

Peterson

, Faith

, Czuprinsky

. Resistance of Listeria monocytogenes F2365 cells to synthetic gastric fluid is greater following growth on ready-to-eat delli turkey meat than in Brain Heart Infusion Broth. J Food Prot, 2007; 70:2589–2595.

32.

Pinto

, Marques

, Andrew

, Faleiro

. Over-production of P60 proteins, glycolitic and stress response proteins characterizes the autolytic profile of Listeria monocytogenes. Adv Microbiol, 2012; 2:181–200.

33.

Ramalheira

, Almeida

, Azeredo

, Brandão

TRS

, Almeida

, Silva

, Teixeira

. Survival of food isolates of Listeria monocytogenes through simulated gastrointestinal tract conditions. Foodborne Pathog Dis, 2010; 7:121–128.

34.

Ryan

, Begley

, Hill

, Gahan

CGM

. A five-gene stress survival islet (SSI-1) that contributes to the growth of Listeria monocytogenes in suboptimal conditions. J Appl Microbiol, 2010; 109:984–995.

35.

Schmid

, Klumpp

, Raimann

, Loessner

, Stephan

, Tasara

. Role of cold shock proteins in growth of Listeria monocytogenes under cold and osmotic stress conditions. Appl Environ Microbiol, 2009; 75:1621–1627.

36.

Skandamis

, Yoon

, Stopforth

, Kendall

, Sofos

. Heat and acid tolerance of Listeria monocytogenes after exposure to single and multiple sublethal stresses. Food Microbiol, 2008; 25:294–303.

37.

Soni

, Nannapaneni

, Tasara

. The contribution of transcriptomic and proteomic analysis in elucidating stress adaptation responses of Listeria monocytogenes. Foodborne Pathog Dis, 2011a. 8:843–852.

38.

Soni

, Nannapaneni

, Tasara

. An overview of stress proteomes in Listeria monocytogenes. Agric Food Anal Bacteriol, 2011b. 1:66–85.

39.

Speicher

, Kolbas

, Harper

, Speicher

. Systematic analysis of peptide recoveries from in-gel digestions for protein identifications in proteome studies. J Biomol Tech, 2000; 11:74–86.

40.

Swaminathan

, Gerner-Smidt

. The epidemiology of human listeriosis. Microb Infect, 2007; 9:1236–1243.

41.

The Uniprot Consortium. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res, 2010; 38:D142–D148.

42.

Trivett

, Meyer

. Citrate cycle and related metabolism of Listeria monocytogenes. J Bacteriol, 1971; 107:770–779.

43.

Versantvoort

CHM

, Oomen

, Kamp

, Rompelberg

CJM

, Sips

AJAM

. Applicability of an in vitro digestion model in assessing the bioacessibility of mycotoxins from food. Food Chem Toxicol, 2005; 43:31–40.

44.

Way

, Thompson

, Lopes

, Hajjar

, Kollmann

, Freitag

, Wilson

. Characterization of flagellin expression and its role in Listeria monocytogenes infection and immunity. Cell Microbiol, 2004; 6:235–242.

45.

Werbrouck

, Vermeulen

, Van Coillie

, Winy Messens

, Herman

, Devlieghere

, Uyttendaele

. Infuence of acid stress on survival, expression of virulence genes and invasion capacity into Caco-2 cells of Listeria monocytogenes strains of different origins. Int J Food Microbiol, 2009; 134:140–146.

46.

, Zhang

, Sheng

, Xu

, Huang

. Transcriptional expression of fljB:z66, a flagellin gene located on a novel linear plasmid of Salmonella enterica serovar Typhi under environmental stresses. New Microbiol, 2008; 31:241–247.

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