Limits...
Technologies and approaches to elucidate and model the virulence program of salmonella.

McDermott JE, Yoon H, Nakayasu ES, Metz TO, Hyduke DR, Kidwai AS, Palsson BO, Adkins JN, Heffron F - Front Microbiol (2011)

Bottom Line: Salmonella is a primary cause of enteric diseases in a variety of animals.Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration.Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory Richland, WA, USA.

ABSTRACT
Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches used to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

No MeSH data available.


Related in: MedlinePlus

Regulatory network of selected transcription factors essential for virulence. Regulators essential in systemic infection were deleted and microarray expression data under SPI-2 inducing conditions were used to construct a regulatory network. The figure shown represents a selected subset of all the regulators examined (see Yoon et al., 2009 for the complete network). The nodes indicate regulators, with the red node indicating the SPI-2 genes. Edges indicate activation (red) or repression (blue). Predictions made by this model were validated experimentally (Yoon et al., 2009).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3108385&req=5

Figure 2: Regulatory network of selected transcription factors essential for virulence. Regulators essential in systemic infection were deleted and microarray expression data under SPI-2 inducing conditions were used to construct a regulatory network. The figure shown represents a selected subset of all the regulators examined (see Yoon et al., 2009 for the complete network). The nodes indicate regulators, with the red node indicating the SPI-2 genes. Edges indicate activation (red) or repression (blue). Predictions made by this model were validated experimentally (Yoon et al., 2009).

Mentions: Changes in gene expression are attributed to the DNA-binding activity of regulators responding to environmental stimuli. Transcriptional regulation is often a complex process composed of multiple regulatory factors and thus systems biology approaches are necessary to integrate the activities of multiple regulators. With the development of the microarray where thousands of sequences are spotted on a chip and the expression of numerous genes is simultaneously compared, the inference of regulatory networks could be accomplished in a high-throughput manner (Faith et al., 2007; Bonneau, 2008). Furthermore, related approaches including ChIP–microarray (ChIP–chip) and ChIP-sequencing (ChIP-seq) methods, discussed below, have accelerated defining the transcriptional regulatory network (Macquarrie et al., 2011). We have used a transcriptomic approach to decipher the regulatory network governed by virulence regulators during Salmonella systemic infection. Regulators sensing the multiple environmental cues execute defense programs and coordinately tune the expression of genes involved in virulence. By deleting Salmonella regulators across the chromosome and its virulence-related plasmid, we defined 20 regulators that were required for Salmonella systemic infection in mice (avirulent strains in i.p. infection in Table 1). These virulence regulators were varied, including two-component regulators (PhoP/PhoQ, SsrA/SsrB, and OmpR/EnvZ), alternative sigma factors (RpoE, RpoS, and FliA), post-transcriptional/post-translational regulators (SmpB, CsrA, Hfq, and RseA), a response regulator for which the signal sensor is unknown (Hnr), a bending protein essential for some types of recombination (IHF), and an assortment of other transcriptional/putative transcriptional regulators (SlyA, Crp, FruR, RelA/SpoT, STM1547, STM3121, SpvR, and RcsA). We chose 14 Salmonella regulators whose absence caused severe survival defect in mice (see strains in bold in Table 1) and determined the global transcriptional changes by each virulence regulator in intracellular-mimicking conditions. Collective transcriptomic data revealed an interaction network among virulence regulators and furthermore suggested a group of genes that were coordinately controlled by virulence regulators and are likely to be important for Salmonella virulence (Yoon et al., 2009). We show a simplified version of the inferred regulatory network that was obtained in this study in Figure 2. This network shows that the primary regulator responsible for SPI-2 virulence expression, SsrB, integrates signals from many regulators and two-component regulatory systems. Interestingly, this network showed that SlyA is directly upstream of SsrB, but that it also seemed to be directly regulating SPI-2 expression. Both these predictions were validated in the study, elaborating the role that SlyA plays in virulence in Salmonella.


Technologies and approaches to elucidate and model the virulence program of salmonella.

McDermott JE, Yoon H, Nakayasu ES, Metz TO, Hyduke DR, Kidwai AS, Palsson BO, Adkins JN, Heffron F - Front Microbiol (2011)

Regulatory network of selected transcription factors essential for virulence. Regulators essential in systemic infection were deleted and microarray expression data under SPI-2 inducing conditions were used to construct a regulatory network. The figure shown represents a selected subset of all the regulators examined (see Yoon et al., 2009 for the complete network). The nodes indicate regulators, with the red node indicating the SPI-2 genes. Edges indicate activation (red) or repression (blue). Predictions made by this model were validated experimentally (Yoon et al., 2009).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3108385&req=5

Figure 2: Regulatory network of selected transcription factors essential for virulence. Regulators essential in systemic infection were deleted and microarray expression data under SPI-2 inducing conditions were used to construct a regulatory network. The figure shown represents a selected subset of all the regulators examined (see Yoon et al., 2009 for the complete network). The nodes indicate regulators, with the red node indicating the SPI-2 genes. Edges indicate activation (red) or repression (blue). Predictions made by this model were validated experimentally (Yoon et al., 2009).
Mentions: Changes in gene expression are attributed to the DNA-binding activity of regulators responding to environmental stimuli. Transcriptional regulation is often a complex process composed of multiple regulatory factors and thus systems biology approaches are necessary to integrate the activities of multiple regulators. With the development of the microarray where thousands of sequences are spotted on a chip and the expression of numerous genes is simultaneously compared, the inference of regulatory networks could be accomplished in a high-throughput manner (Faith et al., 2007; Bonneau, 2008). Furthermore, related approaches including ChIP–microarray (ChIP–chip) and ChIP-sequencing (ChIP-seq) methods, discussed below, have accelerated defining the transcriptional regulatory network (Macquarrie et al., 2011). We have used a transcriptomic approach to decipher the regulatory network governed by virulence regulators during Salmonella systemic infection. Regulators sensing the multiple environmental cues execute defense programs and coordinately tune the expression of genes involved in virulence. By deleting Salmonella regulators across the chromosome and its virulence-related plasmid, we defined 20 regulators that were required for Salmonella systemic infection in mice (avirulent strains in i.p. infection in Table 1). These virulence regulators were varied, including two-component regulators (PhoP/PhoQ, SsrA/SsrB, and OmpR/EnvZ), alternative sigma factors (RpoE, RpoS, and FliA), post-transcriptional/post-translational regulators (SmpB, CsrA, Hfq, and RseA), a response regulator for which the signal sensor is unknown (Hnr), a bending protein essential for some types of recombination (IHF), and an assortment of other transcriptional/putative transcriptional regulators (SlyA, Crp, FruR, RelA/SpoT, STM1547, STM3121, SpvR, and RcsA). We chose 14 Salmonella regulators whose absence caused severe survival defect in mice (see strains in bold in Table 1) and determined the global transcriptional changes by each virulence regulator in intracellular-mimicking conditions. Collective transcriptomic data revealed an interaction network among virulence regulators and furthermore suggested a group of genes that were coordinately controlled by virulence regulators and are likely to be important for Salmonella virulence (Yoon et al., 2009). We show a simplified version of the inferred regulatory network that was obtained in this study in Figure 2. This network shows that the primary regulator responsible for SPI-2 virulence expression, SsrB, integrates signals from many regulators and two-component regulatory systems. Interestingly, this network showed that SlyA is directly upstream of SsrB, but that it also seemed to be directly regulating SPI-2 expression. Both these predictions were validated in the study, elaborating the role that SlyA plays in virulence in Salmonella.

Bottom Line: Salmonella is a primary cause of enteric diseases in a variety of animals.Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration.Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology and Bioinformatics Group, Pacific Northwest National Laboratory Richland, WA, USA.

ABSTRACT
Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches used to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated large amounts of data and necessitated the development of computational approaches for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird's eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.

No MeSH data available.


Related in: MedlinePlus