Abstract

   Enterohemorrhagic Escherichia coli (EHEC) O157:H7 is a human pathogen
   responsible for diarrhea, hemorrhagic colitis and hemolytic uremic
   syndrome (HUS). To promote a comprehensive insight into the molecular
   basis of EHEC O157:H7 physiology and pathogenesis, the combined
   proteome of EHEC O157:H7 strains, Clade 8 and Clade 6 isolated from
   cattle in Argentina, and the standard EDL933 (clade 3) strain has been
   analyzed. From shotgun proteomic analysis a total of 2,644
   non-redundant proteins of EHEC O157:H7 were identified, which
   correspond approximately 47% of the predicted proteome of this
   pathogen. Normalized spectrum abundance factor analysis was performed
   to estimate the protein abundance. According this analysis, 50 proteins
   were detected as the most abundant of EHEC O157:H7 proteome. COG
   analysis showed that the majority of the most abundant proteins are
   associated with translation processes. A KEGG enrichment analysis
   revealed that Glycolysis / Gluconeogenesis was the most significant
   pathway. On the other hand, the less abundant detected proteins are
   those related to DNA processes, cell respiration and prophage. Among
   the proteins that composed the Type III Secretion System, the most
   abundant protein was EspA. Altogether, the results show a subset of
   important proteins that contribute to physiology and pathogenicity of
   EHEC O157:H7.

Introduction

   Enterohemorrhagic Escherichia coli (EHEC) O157:H7 is a zoonotic
   pathogen belonging to Shiga toxin-producing E. coli (STEC) and
   responsible for different diseases as diarrhea, hemorrhagic colitis and
   hemolytic uremic syndrome (HUS). HUS is distributed worldwide and
   considered to be a public health problem in several countries
   [[44]1,[45]2]. Unfortunately, Argentina is the country with the highest
   incidence of HUS in the world, with approximately 14 cases per 100,000
   in children under 5 and a report of 500 cases per year [[46]3,[47]4].
   Cattle are the main reservoir of EHEC. Several studies have shown that
   most cases related to infection in human may be attributed to the high
   consumption of foods of bovine origin and especially ground beef is the
   main source of contamination [[48]5].

   Great efforts had been made to characterize strains of E. coli O157:H7
   isolated from Argentinian cattle [[49]6]. Using the analysis of simple
   nucleotide polymorphisms, we have classified 16 strains of STEC O157:H7
   in clade 6 and 8, which are the most virulent clades [[50]6]. In vitro
   and in vivo experimental results showed that the strains Rafaela II
   (clade 8) and 7.1 Anguil (clade 6) have a high virulence potential when
   compared with other strains and the standard strain EHEC O157:H7 EDL933
   [[51]7]. These results enabled us to characterize the high prevalence
   of strains clade 6 and 8 in the Argentinian cattle. Importantly, these
   two clades might contribute to a high incidence of HUS in Argentina.

   The availability of whole genome sequences of different EHEC strains
   has enabled genome-wide comparisons to identify factors that might be
   correlated to physiology and virulence of this pathogen [[52]8]. In
   addition, the implementation of system biology approaches, such as
   prediction of protein-protein network, has contributed substantially in
   the understanding of the pathogen and interactions with its host
   [[53]9].

   Information about the functions and activities of the individual
   proteins and pathways that control these systems is essential to
   understand complex processes occurring in living cells. Large scale
   quantitative proteomics is a powerful approach used to understand
   global proteomic dynamics in a cell, tissue or organism, and has been
   widely used to study protein profiles in the field of microbiology
   [[54]10]. Furthermore, the study of the abundance of proteins in
   different conditions or during different stages of growth or disease
   can provide important information about the activities of individual
   protein components or protein networks and pathways. The rapid growth
   of proteomic and genomic methods and tools has managed to reveal the
   basic protein inventory of a few hundred different organisms.
   Quantitative proteomic approaches have been applied to determine the
   absolute or relative abundance of proteins. This information gives
   insights about the biological function and properties of the cell as
   well as how cells respond to environmental or metabolic changes or
   stresses [[55]11, [56]12]. Quantitative proteomics analysis can
   contribute to the generation of datasets that are critical for our
   understanding of global proteins expression and modifications
   underlying the molecular mechanism of biological processes and disease
   states.

   In a previous study, we reported the use of isobaric tags for
   comparative quantitation (TMT) method to identify the differentially
   expressed proteins among three EHEC O157:H7 isolates: Rafaela II (Clade
   8), Anguil 7.1 (Clade 6) and EDL933 (Clade 3) [[57]7]. The proteome
   differences observed among these strains are related mainly to proteins
   involved in both virulence and cellular metabolism; which might reflect
   the virulence potential of each strain [[58]7]. The aim of the present
   study was to promote a more comprehensive insight into the molecular
   basis of EHEC O157:H7 physiology. For this purpose, we applied
   high-throughput proteomics to combine the proteome of three EHEC
   O157:H7 isolates: Rafaela II, Anguil 7.1 and EDL933 and normalized
   spectrum abundance factor (NSAF) approach [[59]13] to quantify the EHEC
   O157:H7 proteome.

Material and methods

Bacterial strain and growth conditions

   The EHEC O157:H7 strains Rafaela II (clade 8) and 7.1 Anguil (clade 6)
   isolated from cattle in Argentina and EDL933 (clade 3) strain recovered
   from a patient in USA were routinely maintained in Luria-Bertani broth
   (LB, Difco Laboratories, USA) or in LB 1.5% bacteriological agar
   plates, at 37°C. For the proteomic studies, bacterial strains were
   cultured as previously described by Amigo et al. [[60]7]. Overnight
   cultures of the different EHEC O157:H7 strains growth in LB were
   inoculated (1:50) in Dulbecco’s modified Eagle’s medium (DMEM)-F12
   nutrient until reach the mid-exponential growth phase (OD[600 nm] =
   0.6) under a 5% CO[2] atmosphere at 37°C.

Protein extraction and preparation of whole bacterial lysates for LC-MS/MS

   After bacterial growth, protein extractions were performed according to
   Amigo et al. [[61]7]. Three biological replicates of each culture were
   centrifuged at 5000 x g for 20 min at 4°C. The cell pellets were
   resuspended in ice-cold lysis buffer (50 mM Tris-HCl, pH 7.5, 25 mM
   NaCl, 5 mM DTT and 1 mM PMSF) and disrupted by three cycles in liquid
   N[2] and subsequently placed in boiling water. The resulting lysates
   were centrifuged at 30,000 × g for 10 min and precipitated with 5
   volumes of ice-cold acetone at -20°C overnight. Next, the protein
   pellets were resuspended in buffer containing 8 M urea, 2 M
   thiocarbamide and 200 mM tetraethylammonium bromide at pH 8.5. The
   protein concentration was determined by the Bradford assay using BSA
   curve as a standard. Subsequently, the samples were reduced with
   tris-(2-carboxyethyl)-phosphine (200 mM), alkylated with iodoacetamide
   (375 mM) and enzymatically digested with sequencing grade trypsin.
   Finally, the samples were labeled with TMT Reagents 6-plex Kit
   according to the manufacturer's instructions.

Liquid chromatography and mass spectrometry

   The proteomic analyses were performed using High pH Reverse Phase
   Fractionation and Nano LC-MS/MS Analysis by Orbitrap Fusion. Firstly,
   the labeled peptides were pooled together and desalted using Sep-Pak
   SPE (Waters) to remove salt ions. The hpRP chromatography was performed
   with Dionex UltiMate 3000 model on an Xterra MS C18 column (3.5 um, 2.1
   × 150 mm, Waters). The sample were dissolved in buffer A (20 mM
   ammonium formate, pH 9.5) and then eluted with a gradient of 10 to 45%
   buffer B (80% acetonitrile (ACN)/20% 20 mM NH[4]HCO[2]) for 30 min,
   followed by 45% to 90% buffer B for 10 min, and a 5-min hold at 90%
   buffer B. Forty-eight fractions collected at 1 min intervals were
   merged into 12 fractions. The nano LC MS/MS analysis was carried out
   using a Orbitrap Fusion tribrid (Thermo-Fisher Scientific, San Jose,
   CA) mass spectrometer with an UltiMate 3000 RSLC nano system
   (Thermo-Dionex, Sunnyvale, CA). The fraction was injected onto a PepMap
   C18 trapping column (5 μm, 200 μm × 1 cm, Dionex) and separated on a
   PepMap C18 RP nano column (3 μm, 75 μm × 15 cm, Dionex). For all the
   analysis, the mass spectrometer was operated in positive ion mode, MS
   spectra were acquired across 350–1550 m/z scan mass range, at a
   resolution of 12,0000 in the Orbitrap with the max injection time of 50
   ms. Tandem mass spectra were recorded in high sensitivity mode
   (resolution >30000) and made by HCD at normalized collision energy of
   40. Each cycle of data-dependent acquisition (DDA) mode selected the
   top10 most intense peaks for fragmentation. The data were acquired with
   Xcalibur 2.1 software (Thermo-Fisher Scientific).

Database searching, protein identification and abundance estimation

   Tandem mass spectra were extracted and charge state deconvolution and
   deisotoping were not performed. All MS/MS samples were analyzed using
   Mascot (Matrix Science, London, UK; version 2.4.1). Mascot was set up
   to search the EDL933_NCBI_20141031.fasta; TW14539_exclusive_20150310
   database (unknown version, 6341 entries) assuming the digestion enzyme
   trypsin. Mascot was searched with a fragment ion mass tolerance of
   0.020 Da and a parent ion tolerance of 8.0 PPM. Carbamidomethyl of
   cysteine and TMT-6plex of lysine and the n-terminus were specified in
   Mascot as fixed modifications. Deamidated of asparagine and glutamine
   and oxidation of methionine were specified in Mascot as variable
   modifications. Scaffold (version Scaffold_4.8.8, Proteome Software
   Inc., Portland, OR) was used to validate MS/MS based peptide and
   protein identifications. Peptide identifications were accepted if they
   could achieve an FDR less than 1.0% by the Scaffold Local FDR algorithm
   and contained at least 1 identified peptide. Label free quantification
   value was calculated by Normalized spectrum abundance factor (NSAF)
   algorithm [[62]14].

Bioinformatics analysis

   Functional annotations were assigned by the COG database [[63]15].
   Metabolic pathways were determined by analyzing proteins with the Kyoto
   Encyclopedia of Genes pathways and Genomes (KEGG) [[64]16].

Results and discussion

Global proteomic analysis and functional classification of Escherichia coli
(EHEC) O157:H7 proteome

   In this study we have promoted insights into EHEC O157:H7 proteome from
   a dataset generated with strains E. coli O157:H7 Rafaela II, Anguil 7.1
   and EDL933. The strains were grown in D-MEM media and then, proteins
   from total bacterial lysates were extracted and digested in solution.
   The resulting peptides were analyzed by 2D-LC MS/MS. From this
   proteomic analysis, we detected 2,644 non-redundant EHEC O157:H7
   proteins ([65]S1 Table). When comparing this result with in silico data
   of EHEC O157:H7 genome, approximately 47% of the predicted proteome of
   this pathogen was identified ([66]Fig 1A). To determine the abundance
   of the identified proteins, the NSAF approach [[67]13] was used. This
   approach determines to significance of the expression changes based on
   individual protein intensities (Zybailov et al., 2006) ([68]S1 Table).

Fig 1. Characterization of EHEC O157:H7 proteome and correlation with in
silico data.

   [69]Fig 1
   [70]Open in a new tab

   (A) Correlation of the proteomic results with in silico data of EHEC
   O157:H7 genome. (B) Dynamic range based on the emPAI value of the
   proteins identified by LC-MS analysis; pink, most abundant proteins;
   green, less abundant proteins and red, proteins related to EHEC O157:H7
   and that are present in the LEE pathogenicity island.

   According this analysis a dynamic range of protein abundance was
   generated ([71]Fig 1B). Fifty proteins were identified as most abundant
   in EHEC O157:H7 proteome ([72]Table 1). Of the total of proteins
   identified, 25 proteins are encoded by genes that are present in the
   pO157 plasmid; however, these proteins did not show a high abundance
   level ([73]S1 Table)

Table 1. List of the most abundant proteins of EHEC O157:H7 proteome.

   Accession Number Description COG NSAF Value
   [74]AIG70661.1 30S ribosomal protein S4 J 2,87E-03
   [75]AIG70668.1 30S ribosomal protein S5 J 3,79E-03
   [76]AIG71453.1 50S ribosomal protein L1 J 3,33E-03
   [77]AIG70674.1 50S ribosomal protein L24 J 4,79E-03
   [78]AIG70685.1 50S ribosomal protein L3 J 2,94E-03
   [79]AIG71455.1 50S ribosomal protein L7/L12 J 8,47E-03
   [80]AIG67859.1 Acyl carrier protein I 1,17E-02
   [81]AIG66879.1 Alkyl hydroperoxide reductase protein C V 3,59E-03
   [82]AIG71201.1 ATP synthase beta chain C 2,81E-03
   [83]AIG70015.1 Carbon storage regulator T 3,09E-03
   [84]AIG70905.1 Chaperone HdeA O 6,78E-03
   [85]AIG66221.1 Chaperone protein DnaK O 3,95E-03
   [86]AIG68966.1 Cold shock protein CspA K 8,38E-03
   [87]AIG66898.1 Cold shock protein CspA K 2,98E-03
   [88]AIG69737.1 Cysteine synthase E 3,27E-03
   [89]AIG69094.1 Cystine ABC transporter, periplasmic cystine-binding
   protein FliY ET 2,87E-03
   [90]AIG66325.1 Dihydrolipoamide acetyltransferase component of pyruvate
   dehydrogenase complex C 2,77E-03
   [91]AIG70946.1 Dipeptide-binding ABC transporter, E 6,27E-03
   [92]AIG68128.1 DNA-binding protein H-NS L 6,10E-03
   [93]AIG71470.1 DNA-binding protein HU-alpha L 5,03E-03
   [94]AIG66716.1 DNA-binding protein HU-beta L 3,63E-03
   [95]AIG69372.1 DNA-damage-inducible protein I L 3,46E-03
   [96]AIG71732.1 Endoribonuclease L-PSP V 3,64E-03
   [97]AIG70112.1 Enolase G 8,50E-03
   [98]AIG71085.1 EspA protein J 4,18E-03
   [99]AIG69098.1 Flagellar biosynthesis protein FliC N 5,31E-03
   [100]AIG68335.1 Glutamate decarboxylase E 4,16E-03
   [101]AIG71015.1 Glutaredoxin 3 (Grx3) O 3,56E-03
   [102]AIG71630.1 Chaperone GroEL O 7,71E-03
   [103]AIG71629.1 Chaperone GroES O 6,56E-03
   [104]AIG71712.1 Inorganic pyrophosphatase CP 3,12E-03
   [105]AIG67993.1 Isocitrate dehydrogenase [NADP] C 3,89E-03
   [106]AIG67038.1 Molybdenum ABC transporter, ModA P 2,76E-03
   [107]AIG68915.1 NAD-dependent glyceraldehyde-3-phosphate dehydrogenase
   G 1,14E-02
   [108]AIG68347.1 Osmotically inducible protein C V 3,53E-03
   [109]AIG70283.1 Phosphoglycerate kinase G 6,15E-03
   [110]AIG67029.1 Phosphoglycerate mutase G 6,11E-03
   [111]AIG69739.1 Phosphotransferase system, phosphocarrier protein HPr
   TG 9,84E-03
   [112]AIG69741.1 PTS system, glucose-specific IIA component G 3,25E-03
   [113]AIG70329.1 putative Fe(2+)-trafficking protein YggX PO 3,43E-03
   [114]AIG69875.1 Serine hydroxymethyltransferase E 3,74E-03
   [115]AIG67276.1 Tellurium resistance protein TerD T 3,27E-03
   [116]AIG67277.1 Tellurium resistance protein TerE T 3,09E-03
   [117]AIG68542.1 Thiol peroxidase, Tpx-type O 4,93E-03
   [118]AIG71240.1 Thioredoxin O 5,00E-03
   [119]AIG66382.1 Translation elongation factor Ts J 3,81E-03
   [120]AIG70690.1 Translation elongation factor Tu J 8,57E-03
   [121]AIG71387.1 Triosephosphate isomerase G 3,71E-03
   [122]AIG68383.1 Unknown Function S 4,62E-03
   [123]AIG71521.1 UPF0337 protein yjbJ S 2,93E-03
   [124]Open in a new tab

   We subsequently performed functional annotation of the identified
   proteins using gene ontology [[125]15]. Cluster of orthologous group
   (COG) analysis grouped the identified proteins into four important
   functional groups: (i) metabolism, (ii) information storage and
   processing, (iii) cellular processes and signaling, and (iv) poorly
   characterized ([126]Fig 2A). Although most of the identified proteins
   are related to cellular metabolism, the most abundant proteins are
   involved in the translation process, followed by energy metabolism and
   posttranslational modification, protein turnover and chaperones, which
   shows an intense metabolic activity mainly in the protein synthesis
   ([127]Fig 2B). On the other hand, most of the less abundant proteins
   are involved in replication, recombination and repair ([128]Fig 2B).

Fig 2. Functional analysis of the EHEC O157:H7 proteome.

   [129]Fig 2
   [130]Open in a new tab

   (A) Proteins classified by COG functional categories (B) Categorization
   of the proteins identified into biological processes. [C] Energy
   production and conversion; [E] Amino acid transport and metabolism; [D]
   Cell cycle control, cell division, chromosome partitioning; [G]
   Carbohydrate transport and metabolism; [I] Lipid transport and
   metabolism; [J] Translation, ribosomal structure and biogenesis; [K]
   Transcription; [L] Replication, recombination and repair; [M] Cell
   wall/membrane/envelope biogenesis; [N] Cell motility; [O]
   Posttranslational modification, protein turnover, chaperones; [P]
   Inorganic ion transport and metabolism; [R] General function prediction
   only; [S] Function unknown; [T] Signal transduction mechanisms; [U]
   Intracellular trafficking, secretion, and vesicular transport; [V]
   Defense mechanisms; [X] Mobilome: prophages, transposons. (C) KEGG
   pathway enrichment analysis, the colors are based on the protein
   abundance; blue, most abundant and green, less abundant.

   Pieper et al. [[131]17] and Ishihama et al. [[132]18] also conducted
   proteomic studies on E. coli K-12 and EHEC O157:H7 strain 86–24,
   respectively, to determine the absolute abundance of proteins. Thirteen
   proteins of the most abundant proteins in our study were also found as
   the most abundant proteins in E. coli K-12 ([133]Table 2). Those
   proteins are related to carbohydrate metabolism, transcription,
   translation, posttranslational modification and signal transduction
   mechanisms [[134]18]. On the other hand, only 11 proteins of the most
   abundant group ([135]Table 2) were the most abundant ones in the data
   obtained from quantitative proteome of EHEC O157:H7 strain 86–24
   [[136]17]. Some of those proteins (e. g. TerD, TerE, EspA and
   DNA-damage-inducible protein I) are absent from E. coli K-12.
   Interestingly, when comparing our results with those of Pieper et al.
   [[137]17] and Ishihama et al. [[138]18], the E. coli proteome was
   evaluated in different grown condition. Despite the different growth
   conditions, glyceraldehyde-3-phosphate dehydrogenase, translation
   elongation factor Tu, DNA-binding protein H-NS, alkyl
   hydroperoxidereductase protein C, GroEL chaperone and 50S ribosomal
   protein L7/L12 were detected as the most abundant proteins as well
   ([139]Table 2). These results suggest a set of proteins that may play
   an important role in the biology of E. coli.

Table 2. List of the most abundant proteins detected in E. coli K-12 and EHEC
86–24.

   Access Number Gene name Description Detection
         E. coli K-12 EHEC 86–24
   gi|667692306 gapA Glyceraldehyde-3-phosphate dehydrogenase M M
   gi|667694081 tuf Translation elongation factor Tu M M
   gi|667691519 hns DNA-binding protein H-NS M M
   gi|667690270 ahpC Alkyl hydroperoxidereductase protein C M M
   gi|667694846 rplL 50S ribosomal protein L7/L12 (P1/P2) M M
   gi|667695021 groEL Heat shock protein 60 family chaperone GroEL M M
   gi|667694059 rpsE 30S ribosomal protein S5 M
   gi|667691933 tpx Thiol peroxidase, Tpx-type M
   gi|667691384 icdA Isocitrate dehydrogenase [NADP] M
   gi|667695020 groES Heat shock protein 60 family co-chaperone GroES M
   gi|667694592 atpD ATP synthase beta chain M
   gi|667693130 ptsH Phosphotransferase system, phosphocarrier protein HPr
   M
   gi|667693674 pgk Phosphoglycerate kinase M
   gi|667689773 tsf Translation elongation factor Ts M
   gi|667694844 rplA 50S ribosomal protein L1 M
   gi|667693132 crr PTS system, glucose-specific IIA component M
   gi|667694065 rplX LSU ribosomal protein L24p (L26e) M
   gi|667694076 rplC LSU ribosomal protein L3p (L3e) M
   [140]Open in a new tab

   All proteins were detected in the proteomic study of E. coli K-12
   (Ishihama et al. [[141]18]) and EHEC 86–24 (Pieper et al. [[142]17]). M
   = proteins detected at high levels

   We also detected shiga-toxin subunits such as StxA, StxB, Stx2a and
   Stx2cb; these proteins, however, were not among the most abundant
   proteins ([143]Fig 1). Pieper et al. [[144]17] also obtained similar
   results in EHEC 86–24 proteome. This low abundance can be associated
   with environmental or nutritional conditions that contribute to the
   bacterial lysis and consequently to the production of the toxin
   [[145]17, [146]19, [147]20].

Metabolic network analysis

   To identify the most relevant biological pathways of the identified
   proteins, we performed a KEGG enrichment analysis. This analysis
   provides a comprehensive understanding about pathways that might
   contribute to cellular physiology [[148]16]. When we evaluated the most
   abundant proteins, we identified 10 pathways that were considered
   significant (p < 0.05), among them the Glycolysis / Gluconeogenesis was
   the most significant ([149]Fig 2C). On the other hand, among the less
   abundant proteins were proteins related to ABC transport. Different
   studies have reported that glycolysis / gluconeogenesis pathway might
   influence in the colonization process of EHEC in the gastrointestinal
   tract of both mouse and bovine [[150]21, [151]22]. Although glycolysis
   substrates inhibit the expression of genes that are localized in locus
   of enterocyte effacement (LEE), this pathway plays an important role in
   the initial colonization and maintenance of EHEC in the mouse
   intestine. In addition, gluconeogenesis not only induces LEE gene
   expression, but contributes also to the later stages of EHEC
   colonization in mouse [[152]21, [153]23].

   In our proteomic analysis, 23 proteins that composed the Glycolysis /
   Gluconeogenesis pathway of E. coli were identified ([154]Fig 3).
   NAD-dependent glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was the
   second most abundant protein of EHEC O157:H7 proteome ([155]Table 1).
   This important cytoplasmic protein of the Glycolysis pathway is also
   described as a moonlight protein, owing to the distinct functions
   performed by this enzyme in different cellular localization [[156]24].
   Some studies showed that GAPDH secreted by EHEC and enteropathogenic E.
   coli (EPEC) strains can bind to fibrinogen and epithelial cell, which
   could contribute to the pathogenesis of this bacterium mainly through
   cell adhesion [[157]25, [158]26]. Another protein that is also
   described as a moonlight protein and was detected among the most
   abundant proteins of the EHEC proteome is enolase ([159]Table 1)
   [[160]27]. This glycolytic enzyme that plays an important role in the
   carbon metabolism also acts in the RNA degradosome process, mainly in
   the RNA processing and gene regulation. In E. coli, enolase-RNase E/
   degradosome complex regulates bacterial morphology under anaerobic
   condition by inducing a filamentous form, which is observed by some
   pathogenic E. coli strains under oxygen limiting conditions [[161]27].

Fig 3. Overview of the glycolysis / gluconeogenesis pathway of EHEC O157:H7.

   [162]Fig 3
   [163]Open in a new tab

   Enzymes of the Glycolysis / Gluconeogenesis metabolism that were
   identified at the proteome level. Blue, proteins detected in our
   proteomic analysis; Green, proteins not identified in our study and
   Red, proteins detected as most abundant.

   Although, the lipid metabolism not has been detected among the KEEG
   pathway with significant p-value, the acyl carrier protein (ACP) was
   detected as the more abundant protein of EHEC O157:H7 proteome. Studies
   showed that E. coli contain in its genome only a copy of acpP gene,
   which codify to an ACP, this protein plays key role in the fatty acid
   biosynthesis and is also required for the growth of E. coli (Rawlings
   and Cronan, 1992; De Lay and Cronan, 1996). During the fatty acid
   biosynthesis, ACP is post translationally modified by
   4’-phosphopantetheinyl (4’-PP). The acyl intermediates generated are
   bound to the 4’-PP thiol through a thioester linkage, which allows ACP
   to transport intermediaries among the fatty acid synthetic enzymes
   [[164]28, [165]29].

Information storage and processing

   Most proteins described as the most abundant are involved in
   translation processes. Similar results had been observed in E. coli
   K-12 [[166]17]. In addition, according to the KEGG enrichment analysis,
   the ribosome was strongly enriched ([167]Fig 2C). We identified
   proteins involved in structural elements of the ribosome as well as
   related to initiation, elongation and terminations steps, which are
   required to the translation process [[168]30]. These results show an
   intense metabolic activity of EHEC mainly in protein synthesis. Among
   these proteins, the translation elongation factor Tu was identified
   (EF-Tu) ([169]Table 1). EF-Tu could play a role in the resistance
   process of this bacterium in the gastrointestinal tract [[170]31], as
   well as against cellular damage generated by the bile salt sodium
   deoxycholate [[171]32]. Unlike E. coli K-12 [[172]17], the proteins
   involved in transcription process in EHEC were identified as most
   abundant. CspA was identified to be among the most abundant proteins as
   well. This RNA chaperone is described as the major cold shock protein
   of E. coli. CspA binds to RNA molecules and destabilizes stem loop
   structures to prevent and resolve misfolding of RNA [[173]33].

Cellular processes and signaling

   Flagella are filamentous structures that contribute to pathogenesis of
   pathogenic E. coli, mainly in motility, adhesion and biofilm production
   [[174]34]. Generally, this organelle is constituted by basal body, hook
   and a filament that is composed by flagelin or flagellar antigen FliC,
   which belongs to the H-antigens group [[175]35, [176]36]. FliC was
   detected as highly abundant ([177]Table 1). In addition, a study
   performed in EPEC showed that FliC might be involved in the
   inflammatory response during the EPEC infection, due to the capacity of
   flagelin to induce interleukin-8 (IL-8) release in T84 cells [[178]36].

   During infection, E. coli is subject to different environmental
   conditions, for example, temperature changes that occur both in
   external ambient and within host. In our proteomic analysis, DnaK,
   GroEL and GroES were detected among the most abundant proteins
   ([179]Table 1). Studies have shown that these proteins contribute to
   the resistance process of EHEC under elevated temperature [[180]37,
   [181]38]. In addition, Kudva et al. [[182]39] demonstrated that DnaK
   and GroEL were induced when EHEC was grown in bovine rumen fluid, thus
   showing the contribution of these proteins in the adaptation of EHEC to
   the bovine rumen.

   Other type of stress commonly found by EHEC during the infection
   process is oxidative stress, which is generated by reactive oxygen
   species (ROS) such as superoxide anion (O[2]^-) hydrogen peroxide
   (H[2]O[2]) and the hydroxyl radical (OH^·) produced mainly by host
   immune response [[183]40]. Thus, to adapt and survive under this stress
   condition, this bacterium presents different anti-oxidant systems. We
   detected two members of peroxiredoxins (Prxs) family: periplasmic thiol
   peroxidase (Tpx) and alkyl hydroperoxide reductase C (AhpC) system
   ([184]Table 1). These two antioxidant systems play an important role in
   the scavengers of H[2]O[2] and organic hydroperoxides [[185]41,
   [186]42]. Glutaredoxin 3 (Grx3) was also among the most abundant
   proteins ([187]Table 1). Grx3 is associated with Glutaredoxin (Grx)
   system, whose function is to reduce disulfide bond in target proteins
   to control the intracellular redox environment [[188]43]. In addition,
   Smirnova et al. [[189]44] showed that glutaredoxin proteins might be
   involved in the resistance of E. coli to antibiotics as ampicillin.
   Altogether, these different systems promote an efficient pathway of
   antioxidant defense in EHEC that contributes to the pathogenesis of
   this bacterium.

   The ter operon related to tellurite resistance is widely spread in
   several Gram positive and Gram negative pathogenic species [[190]45,
   [191]46]. In EDL933, this operon is composed by six genes (terZABCDE).
   Among the proteins expressed by that operon, only TerC was absent from
   our proteomic analysis. Interestingly, TerD and TerE proteins were
   among the most abundant proteins of EHEC O157:H7 proteome ([192]Table
   1). A study performed with Uropathogenic E. coli (UPEC) isolates showed
   that the introduction of the ter gene cluster contributes to improve
   bacterial fitness inside macrophages [[193]47]. On the other hand, Yin
   et al. [[194]48] demonstrated that ter genes contribute to adherence of
   EHEC O157:H7 to epithelial cells. However, the true role of these genes
   in the EHEC pathogenesis remains unclear. Although tellurium is absent
   from the EHEC niche, interestingly, proteomic studies have detected
   tellurium resistance proteins in EHEC O157 proteome in different media
   and growth conditions such as D-MEM [[195]49], minimal medium
   [[196]50], CHROMagar STEC [[197]51], bovine fluid rumen [[198]39] and
   under conditions that stimulate the quorum sensing pathway [[199]52].
   Despite the several studies in this area, more efforts are necessary to
   unveil the true role of the tellurium resistance proteins in EHEC
   pathogenesis.

Locus of Enterocyte Effacement (LEE)

   The LEE is a pathogenicity island of 35.6 kb that is organized into
   five polycistronic operons (LEE1 to LEE5) and is an additional
   bicistronic operon of glr regulatory proteins [[200]53]. LEE is related
   to intimate adherence of EHEC to cell host and is required for
   attaching and effacing (A/E) lesions, followed by the translocation of
   effector proteins that contribute mainly to host modulation of the
   immune system [[201]54]. In addition, LEE contains the genes that
   encode the Type III secretion system (T3SS) as well as some effectors
   molecules that are exported by this system. The T3SS is responsible for
   the translocation of effectors from within the host cell, whose are
   directly involved in the EHEC pathogenesis, mainly in the host
   modulation of the immune system [[202]54]. In this study the EHEC
   strains were grown in D-MEM, a medium known to induce expression of
   genes encoding T3SS [[203]55]. We identified 24 LEE-encoded proteins
   ([204]Fig 1C, [205]S1 Table). Among these proteins, the most abundant
   were EspA (filamentous structure of the T3SS), Tir (translocated
   intimin receptor), EspB (pore formation and effector activity) and EspD
   (outer membrane adhesin) ([206]Fig 1C).

   Interestingly, these proteins play an important role in the E. coli
   O157 adhesion [[207]56, [208]57]. On the other hand, EspA, EspB, Tir
   and Intimin are potential vaccine candidates against EHEC infection
   [[209]58, [210]59]. EspA, which was detected as the most abundant
   protein of LEE, forms a channel that connect the bacterial cytoplasm
   with the host cell; this exportation conduct allows the translocation
   of effectors from within the host cell [[211]60]. EspB together with
   EspD are responsible for the formation of the translocation pore and
   for the effector translocation of Tir. In addition, EspB can inhibit
   the interaction between myosin and actin, which promotes loss of
   microvilli and consequently contributes to the induction of diarrhea
   [[212]61]. The interaction between Tir and Intimin contributes directly
   to EHEC O157:H7 persistence during the infection process [[213]62,
   [214]63]. Furthermore, Tir and Intimin are involved in the modulation
   of host immunity. Tir might inhibit tumor necrosis factor
   receptor-associated factor 6 (TRAF-6)-mediated by NF-κB activation
   [[215]64]. Instead, intimin can induce a T-helper cell type 1 response
   as well as to stimulate the proliferation of spleen CD4+ T lymphocytes
   and cells from lymphoid tissues [[216]65, [217]66].

Conclusion

   In this work, we applied the quantitative proteomic (TMT)-based and
   emPAI analyses to estimate the quantification of EHEC O157:H7 proteome
   of combined proteomes of two EHEC O157:H7 isolates from Argentinian
   cattle and of the standard strainEDL933. These comprehensive proteomic
   analyses generated a quantitative dataset of EHEC proteome composed of
   a subset of proteins involved in different biological processes. All
   these proteins together might form a network of factors that play an
   important role in the pathogenesis and physiology of this pathogen.
   Altogether, the results presented in this study provide insights into
   the functional genome of EHEC O157:H7 at the protein level and could
   contribute to the understating of the factors associated with the
   biology of this pathogen.

Supporting information

   S1 Table. Total list of proteins identified and quantified by NSAF
   approach.

   (XLSX)
   [218]Click here for additional data file.^ (250.8KB, xlsx)

Acknowledgments