Top-down proteomics reveals a unique protein S-thiolation switch in Salmonella Typhimurium in response to infection-like conditions.

Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Toward this end, we used single-dimension ultra-high-pressure liquid chromatography mass spectrometry to investigate the comprehensive "intact" proteome of the Gram-negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1,665 proteoforms generated by posttranslational modifications (PTMs), representing the largest microbial top-down dataset reported to date. We confirmed many previously recognized aspects of Salmonella biology and bacterial PTMs, and our analysis also revealed several additional biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions. This finding of a S-glutathionylation-to-S-cysteinylation switch in a condition-specific manner was corroborated by bottom-up proteomics data and further by changes in corresponding biosynthetic pathways under infection-like conditions and during actual infection of host cells. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling, and represents a report of S-cysteinylation in Gram-negative bacteria. Additionally, the functional relevance of these PTMs was supported by protein structure and gene deletion analyses. The demonstrated utility of our simple proteome-wide intact protein level measurement strategy for gaining biological insight should promote broader adoption and applications of top-down proteomics approaches.

Global analysis of Salmonella alternative sigma factor E on protein translation.

The alternative sigma factor E (σ(E)) is critical for response to extracytoplasmic stress in Salmonella. Extensive studies have been conducted on σ(E)-regulated gene expression, particularly at the transcriptional level. Increasing evidence suggests however that σ(E) may indirectly participate in post-transcriptional regulation. In this study, we conducted sample-matched global proteomic and transcriptomic analyses to determine the level of regulation mediated by σ(E) in Salmonella. Samples were analyzed from wild-type and isogenic rpoE mutant Salmonella cultivated in three different conditions: nutrient-rich and conditions that mimic early and late intracellular infection. We found that 30% of the observed proteome was regulated by σ(E) combining all three conditions. In different growth conditions, σ(E) affected the expression of a broad spectrum of Salmonella proteins required for miscellaneous functions. Those involved in transport and binding, protein synthesis, and stress response were particularly highlighted. By comparing transcriptomic and proteomic data, we identified genes post-transcriptionally regulated by σ(E) and found that post-transcriptional regulation was responsible for a majority of changes observed in the σ(E)-regulated proteome. Further, comparison of transcriptomic and proteomic data from hfq mutant of Salmonella demonstrated that σ(E)-mediated post-transcriptional regulation was partially dependent on the RNA-binding protein Hfq.

Comparative phosphoproteomics reveals components of host cell invasion and post-transcriptional regulation during Francisella infection.

Francisella tularensis is a facultative intracellular bacterium that causes the deadly disease tularemia. Most evidence suggests that Francisella is not well recognized by the innate immune system that normally leads to cytokine expression and cell death. In previous work, we identified new bacterial factors that were hyper-cytotoxic to macrophages. Four of the identified hyper-cytotoxic strains (lpcC, manB, manC, and kdtA) had an impaired lipopolysaccharide (LPS) synthesis and produced an exposed lipid A lacking the O-antigen. These mutants were not only hyper-cytotoxic but also were phagocytosed at much higher rates compared with the wild type parent strain. To elucidate the cellular signaling underlying this enhanced phagocytosis and cell death, we performed a large-scale comparative phosphoproteomic analysis of cells infected with wild-type and delta-lpcC F. novicida. Our data suggest that not only actin but also intermediate filaments and microtubules are important for F. novicida entry into the host cells. In addition, we observed differential phosphorylation of tristetraprolin, a key component of the mRNA-degrading machinery that controls the expression of a variety of genes including many cytokines. Infection with the delta-lpcC mutant induced the hyper-phosphorylation and inhibition of tristetraprolin, leading to the production of cytokines such as IL-1beta and TNF-alpha that may kill the host cells by triggering apoptosis. Together, our data provide new insights for Francisella invasion and a post-transcriptional mechanism that prevents the expression of host immune response factors that control infection by this pathogen.

Studying Salmonellae and Yersiniae host-pathogen interactions using integrated 'omics and modeling.

Salmonella and Yersinia are two distantly related genera containing species with wide host-range specificity and pathogenic capacity. The metabolic complexity of these organisms facilitates robust lifestyles both outside of and within animal hosts. Using a pathogen-centric systems biology approach, we are combining a multi-omics (transcriptomics, proteomics, metabolomics) strategy to define properties of these pathogens under a variety of conditions including those that mimic the environments encountered during pathogenesis. These high-dimensional omics datasets are being integrated in selected ways to improve genome annotations, discover novel virulence-related factors, and model growth under infectious states. We will review the evolving technological approaches toward understanding complex microbial life through multi-omic measurements and integration, while highlighting some of our most recent successes in this area.

New sub-family of lysozyme-like proteins shows no catalytic activity: crystallographic and biochemical study of STM3605 protein from Salmonella Typhimurium.

Phage viruses that infect prokaryotes integrate their genome into the host chromosome; thus, microbial genomes typically contain genetic remnants of both recent and ancient phage infections. Often phage genes occur in clusters of atypical G+C content that reflect integration of the foreign DNA. However, some phage genes occur in isolation without other phage gene neighbors, probably resulting from horizontal gene transfer. In these cases, the phage gene product is unlikely to function as a component of a mature phage particle, and instead may have been co-opted by the host for its own benefit. The product of one such gene from Salmonella enterica serovar Typhimurium, STM3605, encodes a protein with modest sequence similarity to phage-like lysozyme (N-acetylmuramidase) but appears to lack essential catalytic residues that are strictly conserved in all lysozymes. Close homologs in other bacteria share this characteristic. The structure of the STM3605 protein was characterized by X-ray crystallography, and functional assays showed that it is a stable, folded protein whose structure closely resembles lysozyme. However, this protein is unlikely to hydrolyze peptidoglycan. Instead, STM3605 is presumed to have evolved an alternative function because it shows some lytic activity and partitions to micelles.

RNA type III secretion signals that require Hfq.

Salmonella virulence is largely mediated by two type III secretion systems (T3SS) that deliver effector proteins from the bacterium to a host cell; however, the secretion signal is poorly defined. Effector N termini are thought to contain the signal, but they lack homology, possess no identifiable motif, and adopt intrinsically disordered structures. Alternative studies suggest that RNA-encoded signals may also be recognized and that they can be located in the 5' untranslated leader sequence. We began our study by establishing the minimum sequence required for reporter translocation. Untranslated leader sequences predicted from 42 different Salmonella effector proteins were fused to the adenylate cyclase reporter (CyaA'), and each of them was tested for protein injection into J774 macrophages. RNA sequences derived from five effectors, gtgA, cigR, gogB, sseL, and steD, were sufficient for CyaA' translocation into host cells. To determine the mechanism of signal recognition, we identified proteins that bound specifically to the gtgA RNA. One of the unique proteins identified was Hfq. Hfq had no effect upon the translocation of full-length CigR and SteD, but injection of intact GtgA, GogB, and SseL was abolished in an hfq mutant, confirming the importance of Hfq. Our results demonstrated that the Salmonella pathogenicity island 2 (SPI-2) T3SS assembled into a functional apparatus independently of Hfq. Since particular effectors required Hfq for translocation, Hfq-RNA complexes may participate in signal recognition.

Quantitative PCR-based competitive index for high-throughput screening of Salmonella virulence factors.

Salmonella enterica serovar Typhimurium is an intracellular pathogen and a main cause of food-borne illness. In this study, a quantitative PCR (qPCR)-based competitive index (CI) method was developed to simultaneously compare the growth of multiple Salmonella strains. This method was applied to a mixture of 17 Salmonella mutants lacking regulator genes, and their survival ratios were compared based on expression of natural resistance-associated macrophage protein 1 (Nramp1). Nramp1, as a major host innate immune component, controls the intracellular replication of pathogens. Deletion strains containing unique DNA barcodes in place of regulator genes were mixed with the parental control, and the bacteria were inoculated into congenic mice differing only at Nramp1. Most of the deletion strains were outcompeted by wild-type bacteria in either mouse strain, and the lack of Nramp1 didn't increase the tested strain/parent control replication ratios. When the same collection of mutants was tested in congenic mouse-derived primary macrophages, a major Nramp1-expressing cell type, six strains (ΔhimD, ΔphoP/phoQ, ΔrpoE, ΔrpoS, ΔompR/envZ, and Δhfq strains) grew better in Nramp1(-/-) than in Nramp1(+/+) macrophages, suggesting that these six regulators may play roles in overcoming Nramp1-mediated bactericidal activity in primary macrophages. The discrepancy in survival of macrophages and that of mice suggests either that there are differences in macrophage populations or that other cell types expressing Nramp1 control Salmonella proliferation in the host. The method described allows competitive infection analysis to be carried out on complex mixtures of bacteria and provides high reproducibility from independent biological replicates.

Discovery of Salmonella virulence factors translocated via outer membrane vesicles to murine macrophages.

Salmonella enterica serovar Typhimurium, an intracellular pathogen and leading cause of food-borne illness, encodes a plethora of virulence effectors. Salmonella virulence factors are translocated into host cells and manipulate host cellular activities, providing a more hospitable environment for bacterial proliferation. In this study, we report a new set of virulence factors that is translocated into the host cytoplasm via bacterial outer membrane vesicles (OMV). PagK (or PagK1), PagJ, and STM2585A (or PagK2) are small proteins composed of ∼70 amino acids and have high sequence homology to each other (>85% identity). Salmonella lacking all three homologues was attenuated for virulence in a mouse infection model, suggesting at least partial functional redundancy among the homologues. While each homologue was translocated into the macrophage cytoplasm, their translocation was independent of all three Salmonella gene-encoded type III secretion systems (T3SSs)-Salmonella pathogenicity island 1 (SPI-1) T3SS, SPI-2 T3SS, and the flagellar system. Selected methods, including direct microscopy, demonstrated that the PagK-homologous proteins were secreted through OMV, which were enriched with lipopolysaccharide (LPS) and outer membrane proteins. Vesicles produced by intracellular bacteria also contained lysosome-associated membrane protein 1 (LAMP1), suggesting the possibility of OMV convergence with host cellular components during intracellular trafficking. This study identified novel Salmonella virulence factors secreted via OMV and demonstrated that OMV can function as a vehicle to transfer virulence determinants to the cytoplasm of the infected host cell.

Computational prediction of type III and IV secreted effectors in gram-negative bacteria.

In this review, we provide an overview of the methods employed in four recent studies that described novel methods for computational prediction of secreted effectors from type III and IV secretion systems in Gram-negative bacteria. We present the results of these studies in terms of performance at accurately predicting secreted effectors and similarities found between secretion signals that may reflect biologically relevant features for recognition. We discuss the Web-based tools for secreted effector prediction described in these studies and announce the availability of our tool, the SIEVE server (http://www.sysbep.org/sieve). Finally, we assess the accuracies of the three type III effector prediction methods on a small set of proteins not known prior to the development of these tools that we recently discovered and validated using both experimental and computational approaches. Our comparison shows that all methods use similar approaches and, in general, arrive at similar conclusions. We discuss the possibility of an order-dependent motif in the secretion signal, which was a point of disagreement in the studies. Our results show that there may be classes of effectors in which the signal has a loosely defined motif and others in which secretion is dependent only on compositional biases. Computational prediction of secreted effectors from protein sequences represents an important step toward better understanding the interaction between pathogens and hosts.

Discovery of novel secreted virulence factors from Salmonella enterica serovar Typhimurium by proteomic analysis of culture supernatants.

Salmonella enterica serovar Typhimurium is a leading cause of acute gastroenteritis throughout the world. This pathogen has two type III secretion systems (TTSS) encoded in Salmonella pathogenicity islands 1 and 2 (SPI-1 and SPI-2) that deliver virulence factors (effectors) to the host cell cytoplasm and are required for virulence. While many effectors have been identified and at least partially characterized, the full repertoire of effectors has not been catalogued. In this proteomic study, we identified effector proteins secreted into defined minimal medium designed to induce expression of the SPI-2 TTSS and its effectors. We compared the secretomes of the parent strain to those of strains missing essential (ssaK::cat) or regulatory (ΔssaL) components of the SPI-2 TTSS. We identified 20 known SPI-2 effectors. Excluding the translocon components SseBCD, all SPI-2 effectors were biased for identification in the ΔssaL mutant, substantiating the regulatory role of SsaL in TTS. To identify novel effector proteins, we coupled our secretome data with a machine learning algorithm (SIEVE, SVM-based identification and evaluation of virulence effectors) and selected 12 candidate proteins for further characterization. Using CyaA' reporter fusions, we identified six novel type III effectors and two additional proteins that were secreted into J774 macrophages independently of a TTSS. To assess their roles in virulence, we constructed nonpolar deletions and performed a competitive index analysis from intraperitoneally infected 129/SvJ mice. Six mutants were significantly attenuated for spleen colonization. Our results also suggest that non-type III secretion mechanisms are required for full Salmonella virulence.

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium.

BACKGROUND: Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function. RESULTS: We experimentally annotated the bacterial pathogen Salmonella Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in Salmonella and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in Salmonella pathogenesis. We also characterized post-translational features in the Salmonella genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our in vivo proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function. CONCLUSION: This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of Salmonella as a resource for systems analysis.

Accurate prediction of secreted substrates and identification of a conserved putative secretion signal for type III secretion systems.

The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates--effector proteins--are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.

Coordinated regulation of virulence during systemic infection of Salmonella enterica serovar Typhimurium.

To cause a systemic infection, Salmonella must respond to many environmental cues during mouse infection and express specific subsets of genes in a temporal and spatial manner, but the regulatory pathways are poorly established. To unravel how micro-environmental signals are processed and integrated into coordinated action, we constructed in-frame non-polar deletions of 83 regulators inferred to play a role in Salmonella enteriditis Typhimurium (STM) virulence and tested them in three virulence assays (intraperitoneal [i.p.], and intragastric [i.g.] infection in BALB/c mice, and persistence in 129X1/SvJ mice). Overall, 35 regulators were identified whose absence attenuated virulence in at least one assay, and of those, 14 regulators were required for systemic mouse infection, the most stringent virulence assay. As a first step towards understanding the interplay between a pathogen and its host from a systems biology standpoint, we focused on these 14 genes. Transcriptional profiles were obtained for deletions of each of these 14 regulators grown under four different environmental conditions. These results, as well as publicly available transcriptional profiles, were analyzed using both network inference and cluster analysis algorithms. The analysis predicts a regulatory network in which all 14 regulators control the same set of genes necessary for Salmonella to cause systemic infection. We tested the regulatory model by expressing a subset of the regulators in trans and monitoring transcription of 7 known virulence factors located within Salmonella pathogenicity island 2 (SPI-2). These experiments validated the regulatory model and showed that the response regulator SsrB and the MarR type regulator, SlyA, are the terminal regulators in a cascade that integrates multiple signals. Furthermore, experiments to demonstrate epistatic relationships showed that SsrB can replace SlyA and, in some cases, SlyA can replace SsrB for expression of SPI-2 encoded virulence factors.

A statistical framework for protein quantitation in bottom-up MS-based proteomics.

MOTIVATION: Quantitative mass spectrometry-based proteomics requires protein-level estimates and associated confidence measures. Challenges include the presence of low quality or incorrectly identified peptides and informative missingness. Furthermore, models are required for rolling peptide-level information up to the protein level. RESULTS: We present a statistical model that carefully accounts for informative missingness in peak intensities and allows unbiased, model-based, protein-level estimation and inference. The model is applicable to both label-based and label-free quantitation experiments. We also provide automated, model-based, algorithms for filtering of proteins and peptides as well as imputation of missing values. Two LC/MS datasets are used to illustrate the methods. In simulation studies, our methods are shown to achieve substantially more discoveries than standard alternatives. AVAILABILITY: The software has been made available in the open-source proteomics platform DAnTE (http://omics.pnl.gov/software/).

Proteomic investigation of the time course responses of RAW 264.7 macrophages to infection with Salmonella enterica.

To investigate the extent to which macrophages respond to Salmonella infection, we infected RAW 264.7 macrophages with Salmonella enterica serotype Typhimurium and analyzed macrophage proteins at various time points following infection by using a global proteomic approach. A total of 1,006 macrophage and 115 Salmonella proteins were identified with high confidence. Most of the Salmonella proteins were observed in the late stage of the infection time course, which is consistent with the fact that the bacterial cells proliferate inside RAW 264.7 macrophages. The peptide abundances of most of the identified macrophage proteins remained relatively constant over the time course of infection. Compared to those of the control, the peptide abundances of 244 macrophage proteins (i.e., 24% of the total identified macrophage proteins) changed significantly after infection. The functions of these Salmonella-affected macrophage proteins were diverse, including production of antibacterial nitric oxide (i.e., inducible nitric oxide synthase), production of prostaglandin H(2) (i.e., cyclooxygenase 2), and regulation of intracellular traffic (e.g., sorting nexin 5 [SNX5], SNX6, and SNX9). Diverse functions of the Salmonella-affected macrophage proteins demonstrate a global macrophage response to Salmonella infection. Western blot analysis not only confirmed the proteomic results for a selected set of proteins but also revealed that (i) the protein abundance of mitochondrial superoxide dismutase increased following macrophage infection, indicating an infection-induced oxidative stress in mitochondria, and (ii) in contrast to infection of macrophages by wild-type Salmonella, infection by the sopB deletion mutant had no negative impact on the abundance of SNX6, suggesting a role for SopB in regulating the abundance of SNX6.

Analysis of cells targeted by Salmonella type III secretion in vivo.

The type III secretion systems (TTSS) encoded in Salmonella pathogenicity island-1 and -2 (SPI-1 and -2) are virulence factors required for specific phases of Salmonella infection in animal hosts. However, the host cell types targeted by the TTSS have not been determined. To investigate this, we have constructed translational fusions between the beta-lactamase reporter and a broad array of TTSS effectors secreted via SPI-1, SPI-2, or both. Secretion of the fusion protein to a host cell was determined by cleavage of a specific fluorescent substrate. In cultured cells, secretion of all six effectors could be observed. However, two to four days following i.p. infection of mice, only effectors secreted by SPI-2 were detected in spleen cells. The cells targeted were identified via staining with nine different cell surface markers followed by FACS analysis as well as by conventional cytological methods. The targeted cells include B and T lymphocytes, neutrophils, monocytes, and dendritic cells, but not mature macrophages. To further investigate replication in these various cell types, Salmonella derivatives were constructed that express a red fluorescent protein. Bacteria could be seen in each of the cell types above; however, most viable bacteria were present in neutrophils. We find that Salmonella is capable of targeting most phagocytic and non-phagocytic cells in the spleen but has a surprisingly high preference for neutrophils. These findings suggest that Salmonella specifically target splenic neutrophils presumably to attenuate their microbicidal functions, thereby promoting intracellular survival and replication in the mouse.

Iron transport in Francisella in the absence of a recognizable TonB protein still requires energy generated by the proton motive force.

The mechanism of iron transport in Francisella is still a puzzle since none of the sequenced Francisella strains appears to encode a TonB protein, the energy transducer of the proton motive force necessary to act on the bacterial outer membrane siderophore receptor to allow the internalization of iron. In this work we demonstrate using kinetic experiments of radioactive Fe(3+) utilization, that iron uptake in Francisella novicida, although with no recognizable TonB protein, is indeed dependent on energy generated by the proton motive force. Moreover, mutants of a predicted outer membrane receptor still transport iron and are sensitive to the iron dependent antimicrobial compound streptonigrin. Our studies suggest that alternative pathways to internalize iron might exist in Francisella.

Gene set analyses for interpreting microarray experiments on prokaryotic organisms.

BACKGROUND: Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use biologically defined sets of genes in interpretation, instead of examining results gene-by-gene. Despite a serious limitation, a method based on Fisher's exact test remains one of the few plausible options for gene set analysis when an experiment has few replicates, as is typically the case for prokaryotes. RESULTS: We extend five methods of gene set analysis from use on experiments with multiple replicates, for use on experiments with few replicates. We then use simulated and real data to compare these methods with each other and with the Fisher's exact test (FET) method. As a result of the simulation we find that a method named MAXMEAN-NR, maintains the nominal rate of false positive findings (type I error rate) while offering good statistical power and robustness to a variety of gene set distributions for set sizes of at least 10. Other methods (ABSSUM-NR or SUM-NR) are shown to be powerful for set sizes less than 10. Analysis of three sets of experimental data shows similar results. Furthermore, the MAXMEAN-NR method is shown to be able to detect biologically relevant sets as significant, when other methods (including FET) cannot. We also find that the popular GSEA-NR method performs poorly when compared to MAXMEAN-NR. CONCLUSION: MAXMEAN-NR is a method of gene set analysis for experiments with few replicates, as is common for prokaryotes. Results of simulation and real data analysis suggest that the MAXMEAN-NR method offers increased robustness and biological relevance of findings as compared to FET and other methods, while maintaining the nominal type I error rate.

ChIP-Seq Analysis of the σE Regulon of Salmonella enterica Serovar Typhimurium Reveals New Genes Implicated in Heat Shock and Oxidative Stress Response.

The alternative sigma factor σE functions to maintain bacterial homeostasis and membrane integrity in response to extracytoplasmic stress by regulating thousands of genes both directly and indirectly. The transcriptional regulatory network governed by σE in Salmonella and E. coli has been examined using microarray, however a genome-wide analysis of σE-binding sites in Salmonella has not yet been reported. We infected macrophages with Salmonella Typhimurium over a select time course. Using chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq), 31 σE-binding sites were identified. Seventeen sites were new, which included outer membrane proteins, a quorum-sensing protein, a cell division factor, and a signal transduction modulator. The consensus sequence identified for σE in vivo binding was similar to the one previously reported, except for a conserved G and A between the -35 and -10 regions. One third of the σE-binding sites did not contain the consensus sequence, suggesting there may be alternative mechanisms by which σE modulates transcription. By dissecting direct and indirect modes of σE-mediated regulation, we found that σE activates gene expression through recognition of both canonical and reversed consensus sequence. New σE regulated genes (greA, luxS, ompA and ompX) are shown to be involved in heat shock and oxidative stress responses.

Analysis of the Salmonella regulatory network suggests involvement of SsrB and H-NS in σ(E)-regulated SPI-2 gene expression.

The extracytoplasmic functioning sigma factor σ(E) is known to play an essential role for Salmonella enterica serovar Typhimurium to survive and proliferate in macrophages and mice. However, its regulatory network is not well-characterized, especially during infection. Here we used microarray to identify genes regulated by σ(E) in Salmonella grown in three conditions: a nutrient-rich condition and two others that mimic early and late intracellular infection. We found that in each condition σ(E) regulated different sets of genes, and notably, several global regulators. When comparing nutrient-rich and infection-like conditions, large changes were observed in the expression of genes involved in Salmonella pathogenesis island (SPI)-1 type-three secretion system (TTSS), SPI-2 TTSS, protein synthesis, and stress responses. In total, the expression of 58% of Salmonella genes was affected by σ(E) in at least one of the three conditions. An important finding is that σ(E) up-regulates SPI-2 genes, which are essential for Salmonella intracellular survival, by up-regulating SPI-2 activator ssrB expression at the early stage of infection and down-regulating SPI-2 repressor hns expression at a later stage. Moreover, σ(E) is capable of countering the silencing of H-NS, releasing the expression of SPI-2 genes. This connection between σ(E) and SPI-2 genes, combined with the global regulatory effect of σ(E), may account for the lethality of rpoE-deficient Salmonella in murine infection.