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Reduced set of virulence genes allows high accuracy prediction of bacterial pathogenicity in humans.

Iraola G, Vazquez G, Spangenberg L, Naya H - PLoS ONE (2012)

Bottom Line: An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens.A reduced subset of highly informative genes (120) is presented and applied to an external validation set.Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions.

View Article: PubMed Central - PubMed

Affiliation: Unidad de Bioinformática, Institut Pasteur Montevideo, Montevideo, Uruguay.

ABSTRACT
Although there have been great advances in understanding bacterial pathogenesis, there is still a lack of integrative information about what makes a bacterium a human pathogen. The advent of high-throughput sequencing technologies has dramatically increased the amount of completed bacterial genomes, for both known human pathogenic and non-pathogenic strains; this information is now available to investigate genetic features that determine pathogenic phenotypes in bacteria. In this work we determined presence/absence patterns of 814 different virulence-related genes among more than 600 finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: Actinobacteria, Gammaproteobacteria, Firmicutes, etc.). An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens. A reduced subset of highly informative genes (120) is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at http : ==bacfier:googlecode:com=files=Bacfier v1 0:zip), that displays not only the prediction (pathogen/non-pathogen) and an associated probability for pathogenicity, but also the presence/absence vector for the analyzed genes, so it is possible to decipher the subset of virulence genes responsible for the classification on the analyzed genome. Furthermore, we discuss the biological relevance for bacterial pathogenesis of the core set of genes, corresponding to eight functional categories, all with evident and documented association with the phenotypes of interest. Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions.

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Related in: MedlinePlus

Phylogenetic relations of bacterial groups used in this work.Chart sizes are proportional to the number of genomes present in each taxonomic group. The precentage of pathogenic organisms is shown in red and green is used for non-pathogenic.
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pone-0042144-g001: Phylogenetic relations of bacterial groups used in this work.Chart sizes are proportional to the number of genomes present in each taxonomic group. The precentage of pathogenic organisms is shown in red and green is used for non-pathogenic.

Mentions: All finished and annotated genomes of human pathogenic and non-pathogenic bacteria were used to perform a presence/absence analysis over groups of orthologous genes belonging to functional categories (toxins, two-component systems, ABC transporters, motility, flagellar assembly, LPS biosynthesis, secretion systems and chemotaxis), in order to determine which ones are strongly related to pathogenicity in different bacterial taxonomic groups (Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Bacteroidetes/Chlorobi, Chlamydiae/Verrucomicrobia, Deltaproteobacteria, Epsilonproteobacteria, Firmicutes, Gammaproteobacteria, Spirochaetes, etc.). Figure 1 shows phylogenetic relations and the proportion of pathogenic and non-pathogenic organisms in studied taxa.


Reduced set of virulence genes allows high accuracy prediction of bacterial pathogenicity in humans.

Iraola G, Vazquez G, Spangenberg L, Naya H - PLoS ONE (2012)

Phylogenetic relations of bacterial groups used in this work.Chart sizes are proportional to the number of genomes present in each taxonomic group. The precentage of pathogenic organisms is shown in red and green is used for non-pathogenic.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3412846&req=5

pone-0042144-g001: Phylogenetic relations of bacterial groups used in this work.Chart sizes are proportional to the number of genomes present in each taxonomic group. The precentage of pathogenic organisms is shown in red and green is used for non-pathogenic.
Mentions: All finished and annotated genomes of human pathogenic and non-pathogenic bacteria were used to perform a presence/absence analysis over groups of orthologous genes belonging to functional categories (toxins, two-component systems, ABC transporters, motility, flagellar assembly, LPS biosynthesis, secretion systems and chemotaxis), in order to determine which ones are strongly related to pathogenicity in different bacterial taxonomic groups (Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Bacteroidetes/Chlorobi, Chlamydiae/Verrucomicrobia, Deltaproteobacteria, Epsilonproteobacteria, Firmicutes, Gammaproteobacteria, Spirochaetes, etc.). Figure 1 shows phylogenetic relations and the proportion of pathogenic and non-pathogenic organisms in studied taxa.

Bottom Line: An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens.A reduced subset of highly informative genes (120) is presented and applied to an external validation set.Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions.

View Article: PubMed Central - PubMed

Affiliation: Unidad de Bioinformática, Institut Pasteur Montevideo, Montevideo, Uruguay.

ABSTRACT
Although there have been great advances in understanding bacterial pathogenesis, there is still a lack of integrative information about what makes a bacterium a human pathogen. The advent of high-throughput sequencing technologies has dramatically increased the amount of completed bacterial genomes, for both known human pathogenic and non-pathogenic strains; this information is now available to investigate genetic features that determine pathogenic phenotypes in bacteria. In this work we determined presence/absence patterns of 814 different virulence-related genes among more than 600 finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: Actinobacteria, Gammaproteobacteria, Firmicutes, etc.). An accuracy of 95% using a cross-fold validation scheme with in-fold feature selection is obtained when classifying human pathogens and non-pathogens. A reduced subset of highly informative genes (120) is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at http : ==bacfier:googlecode:com=files=Bacfier v1 0:zip), that displays not only the prediction (pathogen/non-pathogen) and an associated probability for pathogenicity, but also the presence/absence vector for the analyzed genes, so it is possible to decipher the subset of virulence genes responsible for the classification on the analyzed genome. Furthermore, we discuss the biological relevance for bacterial pathogenesis of the core set of genes, corresponding to eight functional categories, all with evident and documented association with the phenotypes of interest. Also, we analyze which functional categories of virulence genes were more distinctive for pathogenicity in each taxonomic group, which seems to be a completely new kind of information and could lead to important evolutionary conclusions.

Show MeSH
Related in: MedlinePlus