11 research outputs found
Comparative genomics profiling of clinical isolates of Aeromonas salmonicida using DNA microarrays
BACKGROUND: Aeromonas salmonicida has been isolated from numerous fish species and shows wide variation in virulence and pathogenicity. As part of a larger research program to identify virulence genes and candidates for vaccine development, a DNA microarray was constructed using a subset of 2024 genes from the draft genome sequence of A. salmonicida subsp. salmonicida strain A449. The microarray included genes encoding known virulence-associated factors in A. salmonicida and homologs of virulence genes of other pathogens. We used microarray-based comparative genomic hybridizations (M-CGH) to compare selected A. salmonicida sub-species and other Aeromonas species from different hosts and geographic locations. RESULTS: Results showed variable carriage of virulence-associated genes and generally increased variation in gene content across sub-species and species boundaries. The greatest variation was observed among genes associated with plasmids and transposons. There was little correlation between geographic region and degree of variation for all isolates tested. CONCLUSION: We have used the M-CGH technique to identify subsets of conserved genes from amongst this set of A. salmonicida virulence genes for further investigation as potential vaccine candidates. Unlike other bacterial characterization methods that use a small number of gene or DNA-based functions, M-CGH examines thousands of genes and/or whole genomes and thus is a more comprehensive analytical tool for veterinary or even human health research
Genome-wide expression analyses of Campylobacter jejuni NCTC11168 reveals coordinate regulation of motility and virulence by flhA.
We examined two variants of the genome-sequenced strain, Campylobacter jejuni NCTC11168, which show marked differences in their virulence properties including colonization of poultry, invasion of Caco-2 cells, and motility. Transcript profiles obtained from whole genome DNA microarrays and proteome analyses demonstrated that these differences are reflected in late flagellar structural components and in virulence factors including those involved in flagellar glycosylation and cytolethal distending toxin production. We identified putative sigma(28) and sigma(54) promoters for many of the affected genes and found that greater differences in expression were observed for sigma(28)-controlled genes. Inactivation of the gene encoding sigma(28), fliA, resulted in an unexpected increase in transcripts with sigma(54) promoters, as well as decreased transcription of sigma(28)-regulated genes. This was unlike the transcription profile observed for the attenuated C. jejuni variant, suggesting that the reduced virulence of this organism was not entirely due to impaired function of sigma(28). However, inactivation of flhA, an important component of the flagellar export apparatus, resulted in expression patterns similar to that of the attenuated variant. These findings indicate that the flagellar regulatory system plays an important role in campylobacter pathogenesis and that flhA is a key element involved in the coordinate regulation of late flagellar genes and of virulence factors in C. jejuni
Large-Scale Comparative Genomics Meta-Analysis of Campylobacter jejuni Isolates Reveals Low Level of Genome Plasticity
We have used comparative genomic hybridization (CGH) on a full-genome Campylobacter jejuni microarray to examine genome-wide gene conservation patterns among 51 strains isolated from food and clinical sources. These data have been integrated with data from three previous C. jejuni CGH studies to perform a meta-analysis that included 97 strains from the four separate data sets. Although many genes were found to be divergent across multiple strains (n = 350), many genes (n = 249) were uniquely variable in single strains. Thus, the strains in each data set comprise strains with a unique genetic diversity not found in the strains in the other data sets. Despite the large increase in the collective number of variable C. jejuni genes (n = 599) found in the meta-analysis data set, nearly half of these (n = 276) mapped to previously defined variable loci, and it therefore appears that large regions of the C. jejuni genome are genetically stable. A detailed analysis of the microarray data revealed that divergent genes could be differentiated on the basis of the amplitudes of their differential microarray signals. Of 599 variable genes, 122 could be classified as highly divergent on the basis of CGH data. Nearly all highly divergent genes (117 of 122) had divergent neighbors and showed high levels of intraspecies variability. The approach outlined here has enabled us to distinguish global trends of gene conservation in C. jejuni and has enabled us to define this group of genes as a robust set of variable markers that can become the cornerstone of a new generation of genotyping methods that use genome-wide C. jejuni gene variability data
Comparative genomics profiling of clinical isolates of using DNA microarrays-0
<p><b>Copyright information:</b></p><p>Taken from "Comparative genomics profiling of clinical isolates of using DNA microarrays"</p><p>BMC Genomics 2006;7():43-43.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1434746.</p><p>Copyright © 2006 Nash et al; licensee BioMed Central Ltd.</p>istance and average linkage clustering (n = 1,000 bootstrap iterations). Isolates in bold are atypical isolates that cluster with other known subspecies. The bootstrap values which lead to their cluster assignment are also in bold. All ATCC type strains are denoted "ATCC", and unless otherwise noted, all other isolates are subsp. . (A) Sample clustering based on all genes on the AsalChip1 microarray. (B) Sample clustering based on genes not assigned to the plasmid or transposon functional categories (i.e. "chromosomal" genes)
Comparative genomics profiling of clinical isolates of using DNA microarrays-2
<p><b>Copyright information:</b></p><p>Taken from "Comparative genomics profiling of clinical isolates of using DNA microarrays"</p><p>BMC Genomics 2006;7():43-43.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1434746.</p><p>Copyright © 2006 Nash et al; licensee BioMed Central Ltd.</p>rol strain (higher copy number than in strain A449). Green indicates genes with lower signal intensity for the tester than the control (divergent in sequence or missing or at lower copy number). Gene order reflects results of hierarchical clustering of genes performed as described in Materials and Methods. The strains are ordered as in Figure 1, and unless otherwise noted, all other isolates are subsp. . Asm – subsp. , Asa – subsp. , Ass – subsp. . (A) All genes from the plasmid functional category. The blue bars (both light and dark) indicate genes found on plasmid 5, and the dark blue bars correspond to predicted TTSS genes. (B) All genes from the transposon functional category. The orange bars indicate genes with strong sequence similarity to known transposases
Comparative genomics profiling of clinical isolates of using DNA microarrays-4
<p><b>Copyright information:</b></p><p>Taken from "Comparative genomics profiling of clinical isolates of using DNA microarrays"</p><p>BMC Genomics 2006;7():43-43.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1434746.</p><p>Copyright © 2006 Nash et al; licensee BioMed Central Ltd.</p>n size. The amplicons were "binned" in 50 bp increments (to 1900 bp) then in 200 bp increments (from 2000 to 3000 bp). There were only 4 amplicons of size over 3000 bp
Comparative genomics profiling of clinical isolates of using DNA microarrays-1
<p><b>Copyright information:</b></p><p>Taken from "Comparative genomics profiling of clinical isolates of using DNA microarrays"</p><p>BMC Genomics 2006;7():43-43.</p><p>Published online 7 Mar 2006</p><p>PMCID:PMC1434746.</p><p>Copyright © 2006 Nash et al; licensee BioMed Central Ltd.</p>indicates genes with higher signal intensity for the tester than the control strain (higher copy number than strain A449). Green indicates genes with lower signal intensity for the tester than the control (divergent in sequence or missing or lower copy number). Gene order reflects results of hierarchical clustering of genes performed as described in Materials and Methods. The strains are ordered as in Figure 1, and unless otherwise noted, all other isolates are subsp. . Asm – subsp. , Asa – subsp. , Ass – subsp. . (A) All genes which are divergent in at least one of the sixteen isolates. Blue bars indicate genes associated with the plasmid category and orange bars indicate genes associated with the transposon category as described in Material and Methods. (B) Subset of genes which are divergent (Log Ratio< -1) in the fourteen strains and were not assigned to the plasmid or transposon functional categories. Genes predicted to code for OMPs (purple) and for flagella/pili proteins (grey) are indicated