Dataset Information

In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD.

ABSTRACT: A wide variety of Salmonella enterica serovars cause intestinal and systemic infections to humans and animals. Salmonella Patogenicity Island 1 (SPI-1) is a chromosomal region containing 39 genes that have crucial virulence roles. The AraC-like transcriptional regulator HilD, encoded in SPI-1, positively controls the expression of the SPI-1 genes, as well as of several other virulence genes located outside SPI-1. In this study, we applied a clustering method to the global gene expression data of S. enterica serovar Typhimurium from the COLOMBOS database; thus genes that show an expression pattern similar to that of SPI-1 genes were selected. This analysis revealed nine novel genes that are co-expressed with SPI-1, which are located in different chromosomal regions. Expression analyses and protein-DNA interaction assays showed regulation by HilD for six of these genes: gtgE, phoH, sinR, SL1263 (lpxR) and SL4247 were regulated directly, whereas SL1896 was regulated indirectly. Interestingly, phoH is an ancestral gene conserved in most of bacteria, whereas the other genes show characteristics of genes acquired by Salmonella. A role in virulence has been previously demonstrated for gtgE, lpxR and sinR. Our results further expand the regulon of HilD and thus identify novel possible Salmonella virulence genes.

SUBMITTER: Martinez-Flores I

PROVIDER: S-EPMC5122947 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD.

Martínez-Flores Irma I Pérez-Morales Deyanira D Sánchez-Pérez Mishael M Paredes Claudia C CC Collado-Vides Julio J Salgado Heladia H Bustamante Víctor H VH

Scientific reports 20161125

A wide variety of Salmonella enterica serovars cause intestinal and systemic infections to humans and animals. Salmonella Patogenicity Island 1 (SPI-1) is a chromosomal region containing 39 genes that have crucial virulence roles. The AraC-like transcriptional regulator HilD, encoded in SPI-1, positively controls the expression of the SPI-1 genes, as well as of several other virulence genes located outside SPI-1. In this study, we applied a clustering method to the global gene expression data of ...[more]

PMID: 27886269

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Project description:MotivationA growing number of studies have explored the process of pre-implantation embryonic development of multiple mammalian species. However, the conservation and variation among different species in their developmental programming are poorly defined due to the lack of effective computational methods for detecting co-regularized genes that are conserved across species. The most sophisticated method to date for identifying conserved co-regulated genes is a two-step approach. This approach first identifies gene clusters for each species by a cluster analysis of gene expression data, and subsequently computes the overlaps of clusters identified from different species to reveal common subgroups. This approach is ineffective to deal with the noise in the expression data introduced by the complicated procedures in quantifying gene expression. Furthermore, due to the sequential nature of the approach, the gene clusters identified in the first step may have little overlap among different species in the second step, thus difficult to detect conserved co-regulated genes.ResultsWe propose a cross-species bi-clustering approach which first denoises the gene expression data of each species into a data matrix. The rows of the data matrices of different species represent the same set of genes that are characterized by their expression patterns over the developmental stages of each species as columns. A novel bi-clustering method is then developed to cluster genes into subgroups by a joint sparse rank-one factorization of all the data matrices. This method decomposes a data matrix into a product of a column vector and a row vector where the column vector is a consistent indicator across the matrices (species) to identify the same gene cluster and the row vector specifies for each species the developmental stages that the clustered genes co-regulate. Efficient optimization algorithm has been developed with convergence analysis. This approach was first validated on synthetic data and compared to the two-step method and several recent joint clustering methods. We then applied this approach to two real world datasets of gene expression during the pre-implantation embryonic development of the human and mouse. Co-regulated genes consistent between the human and mouse were identified, offering insights into conserved functions, as well as similarities and differences in genome activation timing between the human and mouse embryos.Availability and implementationThe R package containing the implementation of the proposed method in C ++ is available at: https://github.com/JavonSun/mvbc.git and also at the R platform https://www.r-project.org/Contactjinbo@engr.uconn.edu.

Dataset Information

In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD.

Publications

In silico clustering of Salmonella global gene expression data reveals novel genes co-regulated with the SPI-1 virulence genes through HilD.

Similar Datasets

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