phylen

Phylen is an R package that performs automatic phylogenetic reconstruction given a set of Hidden Markov Models (HMMs). Genomes are screened against these HMMs, genes found in all genomes ("core genes") are aligned individually, those alignments are concatenated into a single supergene alignment, and a phylogenetic reconstruction is performed and returned as an object of class "phylo" so it can be further analysed using ape/phangorn framework in R. Functions to download well curated HMMs from clade-specific orthologous sets from the EggNOG database are provided although any custom set of HMMs can be used as well

Phylogenetic distribution of virulence genes.

<p>Each functional category of virulence-related genes is represented as a vertical bar. Positive values denote association of a particular functional category with pathogenic species of a certain taxonomic group, while negative values with non-pathogenic species. Taxons are grouped according to phylogenetic relationships. In graph legend: ABC: ABC transporters, TCS&CH: two-component systems and chemotaxis, MOT&FLA: motility and flagellar assembly, TOX: toxins, SS: secretion systems, LPS: LPS biosynthesis.</p

Phylogenetic relations of bacterial groups used in this work.

<p>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.</p

Frequency distribution of ABC transporter genes in <i>Alphaproteobacteria</i> and <i>Gammaproteobacteria</i>.

<p>For each gene, abcisse value is the number of pathogenic strains inside a certain taxonomic group in which it is present, divided by the total number of pathogenic strains inside the taxonomic group. The ordinate value is the same but for the non-pathogenic strains inside the group. White circles show that genes coding for ABC transporters are more frequent in pathogenic species of <i>Gammaproteobacteria</i> than in non-pathogenic species of this group. The opposite pattern is observed for <i>Alphaproteobacteria</i> in black circles.</p

Reduced Set of Virulence Genes Allows High Accuracy Prediction of Bacterial Pathogenicity in Humans

<div><p>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 different virulence-related genes among more than finished bacterial genomes from both human pathogenic and non-pathogenic strains, belonging to different taxonomic groups (i.e: <em>Actinobacteria</em>, <em>Gammaproteobacteria</em>, <em>Firmicutes</em>, 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 () is presented and applied to an external validation set. The statistical model was implemented in the BacFier v1.0 software (freely available at ), 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.</p> </div

Additional file 2: Table S1. of Whole genome sequencing of the monomorphic pathogen Mycobacterium bovis reveals local differentiation of cattle clinical isolates

M. bovis strains isolated from a bovine host in Uruguay. (ODS 26 kb

Additional file 1: Figure S1. of Whole genome sequencing of the monomorphic pathogen Mycobacterium bovis reveals local differentiation of cattle clinical isolates

Sequencing and genome annotation statistics for the 23 Uruguayan strains of M. bovis. (PDF 115 kb

Additional file 7: Figure S4a. of Whole genome sequencing of the monomorphic pathogen Mycobacterium bovis reveals local differentiation of cattle clinical isolates

Validation of in silico RD typing with PCR on 21 of the Uruguayan M. bovis strains. Figure S4b. Alignment of the sequenced reads of strain MbURU-003 against the assembled genome of the same strain. Selected pair of reads in red exemplify one of the reads that flanks both sides of a region of difference (RDbov145a) that is absent in this strain. (PDF 1643 kb

Le Courrier

16 décembre 18211821/12/16 (A0,N342)

Additional file 12: Figure S5. of Whole genome sequencing of the monomorphic pathogen Mycobacterium bovis reveals local differentiation of cattle clinical isolates

Bar plots displaying the number of genes affected per strain that are associated to the GO terms carbohydrate metabolic process and peptidoglycan-based cell wall biogenesis. (PDF 1342 kb