Dataset Information

Signal transduction through CsrRS confers an invasive phenotype in group A Streptococcus.

ABSTRACT: The CsrRS (or CovRS) two component system controls expression of up to 15% of the genome of group A Streptococcus (GAS). While some studies have suggested that the sensor histidine kinase CsrS responds to membrane perturbations as a result of various environmental stresses, other data have implicated the human antimicrobial peptide LL-37 and extracellular Mg(2+) as specific signals. We now report that Mg(2+) and LL-37 have opposite effects on expression of multiple genes that are activated or repressed by the transcriptional regulator CsrR. Using a GAS isolate representative of the recently emerged and widely disseminated M1T1 clone implicated in severe invasive disease, we found marked up-regulation by CsrRS of multiple virulence factors including pyrogenic exotoxin A, DNase Sda1, streptolysin O, and the hyaluronic acid capsular polysaccharide, among others. Topology and surface protein labeling studies indicated that CsrS is associated with the bacterial cell membrane and has a surface-exposed extracellular domain accessible to environmental ligands. Replacement of a cluster of three acidic amino acids with uncharged residues in the extracellular domain of CsrS abrogated LL-37 signaling and conferred a hyporesponsive phenotype consistent with tonic activation of CsrS autokinase activity, an effect that could be overridden by mutation of the CsrS active site histidine. Both loss- and gain-of-function mutations of a conserved site in the receiver domain of CsrR established an essential role for lysine 102 in CsrS-to-CsrR signal transduction. These results provide strong evidence that Mg(2+) and LL-37 are specific signals that function by altering CsrS autokinase activity and downstream phosphotransfer to CsrR to modulate its activity as a transcriptional regulator. The representation of multiple antiphagocytic and cytotoxic factors in the CsrRS regulon together with results of in vitro phagocytic killing assays support the hypothesis that CsrRS mediates conversion of GAS from a colonizing to an invasive phenotype in response to signaling by host LL-37.

SUBMITTER: Tran-Winkler HJ

PROVIDER: S-EPMC3203184 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Signal transduction through CsrRS confers an invasive phenotype in group A Streptococcus.

Tran-Winkler Hien J HJ Love John F JF Gryllos Ioannis I Wessels Michael R MR

PLoS pathogens 20111027 10

The CsrRS (or CovRS) two component system controls expression of up to 15% of the genome of group A Streptococcus (GAS). While some studies have suggested that the sensor histidine kinase CsrS responds to membrane perturbations as a result of various environmental stresses, other data have implicated the human antimicrobial peptide LL-37 and extracellular Mg(2+) as specific signals. We now report that Mg(2+) and LL-37 have opposite effects on expression of multiple genes that are activated or re ...[more]

PMID: 22046138

Similar Datasets

Project description:BackgroundThe statistical study of biological networks has led to important novel biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes.ResultsBased on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis and provide examples of de-novo discoveries of gene modules with known roles in apoptosis, immune-mediated tumour suppression, cell-cycle and tumour invasion. Importantly, we also identify a novel gene module within the insulin growth factor signalling pathway, alteration of which may predispose the tumour to metastasize.ConclusionsThese results demonstrate that a metastatic cancer phenotype is characterised by an increase in the randomness of the local information flux patterns. Measures of local randomness in integrated protein interaction mRNA expression networks may therefore be useful for identifying genes and signalling pathways disrupted in one phenotype relative to another. Further exploration of the statistical properties of such integrated cancer expression and protein interaction networks will be a fruitful endeavour.

Dataset Information

Signal transduction through CsrRS confers an invasive phenotype in group A Streptococcus.

Publications

Signal transduction through CsrRS confers an invasive phenotype in group A Streptococcus.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets