Co-evolution of genomic islands and their bacterial hosts revealed through phylogenetic analyses of 17 groups of homologous genomic islands

Genetic and phenotypic assessments for the safety of probiotic Bacillus clausii 088AE

In this study, we report on whole genome sequence analysis of clinically documented, commercial probiotic Bacillus clausii 088AE and genome features contributing to probiotic properties. The whole genome sequence of B. clausii 088AE generated a single scaffold of 4,598,457 bp with 44.74 mol% G + C. This assembled genome sequence annotated by the RAST resulted in 4371 coding genes, 75 tRNAs, and 22 rRNAs. Gene ontology classification indicated 39.5% proteins with molecular function, 44.24% cellular component, and 16.25% proteins involved in biological processes. In taxonomic analysis, B. clausii 088AE shared 99% identity with B. clausii DSM 8716. The gene sequences related to safety and genome stability such as antibiotic resistance (840), virulence factors (706), biogenic amines (1), enterotoxin (0), emetic toxin (0), lanthipeptides (4), prophage (4) and clustered regularly interspaced short palindromic repeats (CRISPR) sequences (11), were identified and evaluated for safety and functions. The absence of functional prophage sequences and the presence of CRISPR indicated an advantage in genome stability. Moreover, the presence of genome features contributing to probiotic characteristics such as acid, and bile salt tolerance, adhesion to the gut mucosa, and environmental resistance ensure the strains survivability when consumed as a probiotic. In conclusion, the absence of risks associated with sequences/genes in the B. clausii 088AE genome and the presence of essential probiotic traits confirm the strain to be safe for use as a probiotic.

Combination of whole genome sequencing and supervised machine learning provides unambiguous identification of eae-positive Shiga toxin-producing Escherichia coli

Introduction

The objective of this study was to develop, using a genome wide machine learning approach, an unambiguous model to predict the presence of highly pathogenic STEC in E. coli reads assemblies derived from complex samples containing potentially multiple E. coli strains. Our approach has taken into account the high genomic plasticity of E. coli and utilized the stratification of STEC and E. coli pathogroups classification based on the serotype and virulence factors to identify specific combinations of biomarkers for improved characterization of eae-positive STEC (also named EHEC for enterohemorrhagic E.coli) which are associated with bloody diarrhea and hemolytic uremic syndrome (HUS) in human.

Methods

The Machine Learning (ML) approach was used in this study on a large curated dataset composed of 1,493 E. coli genome sequences and 1,178 Coding Sequences (CDS). Feature selection has been performed using eight classification algorithms, resulting in a reduction of the number of CDS to six. From this reduced dataset, the eight ML models were trained with hyper-parameter tuning and cross-validation steps.

Results and discussion

It is remarkable that only using these six genes, EHEC can be clearly identified from E. coli read assemblies obtained from in silico mixtures and complex samples such as milk metagenomes. These various combinations of discriminative biomarkers can be implemented as novel marker genes for the unambiguous EHEC characterization from different E. coli strains mixtures as well as from raw milk metagenomes.

The Tetracycline Resistance Gene, tet(W) in Bifidobacterium animalis subsp. lactis Follows Phylogeny and Differs From tet(W) in Other Species

The tetracycline resistance gene tet(W) encodes a ribosomal protection protein that confers a low level of tetracycline resistance in the probiotic bacterium Bifidobacterium animalis subsp. lactis. With the aim of assessing its phylogenetic origin and potential mobility, we have performed phylogenetic and in silico genome analysis of tet(W) and its flanking genes. tet(W) was found in 41 out of 44 examined B. animalis subsp. lactis strains. In 38 strains, tet(W) was flanked by an IS5-like element and an open reading frame encoding a hypothetical protein, which exhibited a similar GC content (51–53%). These genes were positioned in the same genomic context within the examined genomes. Phylogenetically, the B. animalis subsp. lactis tet(W) cluster in a clade separate from tet(W) of other species and genera. This is not the case for tet(W) encoded by other bifidobacteria and other species where tet(W) is often found in association with transferable elements or in different genomic regions. An IS5-like element identical to the one flanking the B. animalis subsp. lactis tet(W) has been found in a human gut related bacterium, but it was not associated with any tet(W) genes. This suggests that the IS5-like element is not associated with genetic mobility. tet(W) and the IS5 element have previously been shown to be co-transcribed, indicating that co-localization may be associated with tet(W) expression. Here, we present a method where phylogenetic and in silico genome analysis can be used to determine whether antibiotic resistance genes should be considered innate (intrinsic) or acquired. We find that B. animalis subsp. lactis encoded tet(W) is part of the ancient resistome and thereby possess a negligible risk of transfer.