A combination of gene loss and acquisition through horizontal gene transfer (HGT) is thought to drive Streptococcus thermophilus adaptation to its niche, i.e. milk. In this study, we describe an in silico analysis combining a stochastic data mining method, analysis of homologous gene distribution and the identification of features frequently associated with horizontally transferred genes to assess the proportion of the S. thermophilus genome that could originate from HGT. Our mining approach pointed out that about 17.7% of S. thermophilus genes (362 CDSs of 1,915) showed a composition bias; these genes were called 'atypical'. For 22% of them, their functional annotation strongly support their acquisition through HGT and consisted mainly in genes encoding mobile genetic recombinases, exopolysaccharide (EPS) biosynthesis enzymes or resistance mechanisms to bacteriophages. The distribution of the atypical genes in the Firmicutes phylum as well as in S. thermophilus species was sporadic and supported the HGT prediction for more than a half (52%, 189). Among them, 46 were found specific to S. thermophilus. Finally, by combining our method, gene annotation and sequence specific features, new genome islands were suggested in the S. thermophilus genome.