PMC:3317825 / 5782-8844 JSONTXT

{"project":"2_test","denotations":[{"id":"22272658-9254694-10678861","span":{"begin":312,"end":314},"obj":"9254694"},{"id":"22272658-10592175-10678862","span":{"begin":808,"end":810},"obj":"10592175"},{"id":"22272658-11125040-10678863","span":{"begin":811,"end":813},"obj":"11125040"},{"id":"22272658-10592173-10678864","span":{"begin":833,"end":835},"obj":"10592173"},{"id":"22272658-16214803-10678865","span":{"begin":844,"end":846},"obj":"16214803"},{"id":"22272658-10802651-10678866","span":{"begin":937,"end":939},"obj":"10802651"},{"id":"22272658-19815525-10678867","span":{"begin":1529,"end":1530},"obj":"19815525"},{"id":"22272658-18952797-10678868","span":{"begin":1531,"end":1533},"obj":"18952797"}],"text":"Gene content analysis\nProtein-coding sequences were retrieved from chromosomes and plasmids of the 29 strains of bacteria (Table 1 and Additional file 1 Table S1). A group of homologous proteins (protein family) was built by all-against-all protein sequence comparison of the 29 strains' proteomes using BLASTP [37], followed by Markov clustering (MCL) with an inflation factor of 1.2 [38]. Homologous proteins were identified by BLASTP on the criteria of an E-value cutoff of 1e-5, and minimum aligned sequence length coverage of 50% of a query sequence. This approach yielded 5014 protein families containing 74122 individual proteins from the 29 strains (see Additional file 1, Table S2). We assigned functions to each protein family by using multiple databases: the Clusters of Orthologous Groups (COG) [39,40], JCVI [41], KEGG [42], SEED [43], Virulence Factors Database (VFDB) [44], MvirDB [45], Pfam [46], and Gene Ontology (GO) [47] database. We searched protein sequences against the Pfam library of hidden Markov models (HMMs) using HMMER http://hmmer.janelia.org/, and converted Pfam accession numbers to GO terms using the 'pfam2go' mapping http://www.geneontology.org/external2go/pfam2go. We performed TBLASTN searches (on the criteria of an E-value cutoff of 1e-5, and minimum aligned sequence length coverage of 50% of a query sequence) of each of the 29 strains' proteomes against whole nucleotide sequences of all the other strains to avoid artefacts caused by differences in protein-coding sequence prediction [8,48]. The resulting gene content (binary data for presence or absence of each protein family) is shown in Additional file 1, Table S2.\nHierarchical clustering (UPGMA) of the 29 strains was performed using a distance between two genomes based on gene content (binary data for presence or absence of each protein family) measured by one minus the Jaccard coefficient (Jaccard distance). To identify taxon-specific genes, we calculated Cramer's V to screen protein families showing biased distributions between comparative groups. Cramer's V is a measure of the degree of correlation in contingency tables. Cramer's V values close to 0 indicate weak associations between variables, while those close to 1 indicate strong associations. We used the most stringent threshold (i.e. Cramer's V of 1) to identify S. aureus and S. simiae unique proteins or protein families. To examine over- or underrepresented functional categories in the 16 S. aureus strains relative to the single S. simiae strain, a 2 × 2 contingency table was constructed for each functional category from the COG, JCVI, KEGG, SEED, VFDB, and GO databases: (a) the number of S. aureus protein families in this category; (b) the number of S. aureus protein families not in this category; (c) the number of S. simiae protein families in this category; and (d) the number of S. simiae protein families not in this category. The odds ratio (= ad/bc) was used to rank the relative over-representation (\u003e 1) or under-representation (\u003c 1) of each of the functional categories."}