- Volume 3, Issue 8, 2017

The genus Lactobacillus is a diverse group with a combined species count of over 200. They are the largest group within the lactic acid bacteria and one of the most important bacterial groups involved in food microbiology and human nutrition because of their fermentative and probiotic properties. Lactobacillus salivarius, a species commonly isolated from the gastrointestinal tract of humans and animals, has been described as having potential probiotic properties and results of previous studies have revealed considerable functional diversity existing on both the chromosomes and plasmids. Our study consists of comparative genomic analyses of the functional and phylogenomic diversity of 42 genomes of strains of L . salivarius using bioinformatic techniques. The main aim of the study was to describe intra-species diversity and to determine how this diversity is spread across the replicons. We found that multiple phylogenomic and non-phylogenomic methods used for reconstructing trees all converge on similar tree topologies, showing that different metrics largely agree on the evolutionary history of the species. The greatest genomic variation lies on the small plasmids, followed by the repA-type circular megaplasmid, with the chromosome varying least of all. Additionally, the presence of extra linear and circular megaplasmids is noted in several strains, while small plasmids are not always present. Glycosyl hydrolases, bacteriocins and proteases vary considerably on all replicons while two exopolysaccharide clusters and several clustered regularly interspaced short palindromic repeats-associated systems show a lot of variation on the chromosome. Overall, despite its reputation as a mammalian gastrointestinal tract specialist, the intra-specific variation of L. salivarius reveals potential strain-dependant effects on human health.

This study aimed to assess the feasibility of using the Oxford Nanopore Technologies (ONT) MinION long-read sequencer in reconstructing fully closed plasmid sequences from eight Enterobacteriaceae isolates of six different species with plasmid populations of varying complexity. Species represented were Escherichia coli, Klebsiella pneumoniae, Citrobacter freundii, Enterobacter cloacae, Serratia marcescens and Klebsiella oxytoca, with plasmid populations ranging from 1–11 plasmids with sizes of 2–330 kb. Isolates were sequenced using Illumina (short-read) and ONT’s MinION (long-read) platforms, and compared with fully resolved PacBio (long-read) sequence assemblies for the same isolates. We compared the performance of different assembly approaches including SPAdes, plasmidSPAdes, hybridSPAdes, Canu, Canu+Pilon (canuPilon) and npScarf in recovering the plasmid structures of these isolates by comparing with the gold-standard PacBio reference sequences. Overall, canuPilon provided consistently good quality assemblies both in terms of assembly statistics (N50, number of contigs) and assembly accuracy [presence of single nucleotide polymorphisms (SNPs)/indels with respect to the reference sequence]. For plasmid reconstruction, Canu recovered 70 % of the plasmids in complete contigs, and combining three assembly approaches (Canu or canuPilon, hybridSPAdes and plasmidSPAdes) resulted in a total 78 % recovery rate for all the plasmids. The analysis demonstrated the potential of using MinION sequencing technology to resolve important plasmid structures in Enterobacteriaceae species independent of and in conjunction with Illumina sequencing data. A consensus assembly derived from several assembly approaches could present significant benefit in accurately resolving the greatest number of plasmid structures.

Multi-locus sequence typing (MLST) is a widely used method for categorizing bacteria. Increasingly, MLST is being performed using next-generation sequencing (NGS) data by reference laboratories and for clinical diagnostics. Many software applications have been developed to calculate sequence types from NGS data; however, there has been no comprehensive review to date on these methods. We have compared eight of these applications against real and simulated data, and present results on: (1) the accuracy of each method against traditional typing methods, (2) the performance on real outbreak datasets, (3) the impact of contamination and varying depth of coverage, and (4) the computational resource requirements.