Improving Phylogeny Reconstruction at the Strain Level Using Peptidome Datasets

Strain-level epidemiology of microbial communities and the human microbiome

The biological importance and varied metabolic capabilities of specific microbial strains have long been established in the scientific community. Strains have, in the past, been largely defined and characterized based on microbial isolates. However, the emergence of new technologies and techniques has enabled assessments of their ecology and phenotypes within microbial communities and the human microbiome. While it is now more obvious how pathogenic strain variants are detrimental to human health, the consequences of subtle genetic variation in the microbiome have only recently been exposed. Here, we review the operational definitions of strains (e.g., genetic and structural variants) as they can now be identified from microbial communities using different high-throughput, often culture-independent techniques. We summarize the distribution and diversity of strains across the human body and their emerging links to health maintenance, disease risk and progression, and biochemical responses to perturbations, such as diet or drugs. We list methods for identifying, quantifying, and tracking strains, utilizing high-throughput sequencing along with other molecular and “culturomics” technologies. Finally, we discuss implications of population studies in bridging experimental gaps and leading to a better understanding of the health effects of strains in the human microbiome.

Diversity of Bacillus cereus sensu lato mobilome

BACKGROUND

Bacillus cereus sensu lato s.l.) is a group of bacteria displaying close phylogenetic relationships but a high ecological diversity. The three most studied species are Bacillus anthracis, Bacillus cereus sensu stricto and Bacillus thuringiensis. While some species are pathogenic to mammals or associated with food poisoning, Bacillus thuringiensis is a well-known entomopathogenic bacterium used as biopesticide worldwide. B. cereus s.l. also contains a large variety of mobile genetic elements (MGEs).

RESULTS

In this study, we detail the occurrence and plasmid vs. chromosome distribution of several MGEs in 102 complete and annotated genomes of B. cereus s.l. These MGEs include 16 Insertion Sequence (IS) families, the Tn3 family, 18 different Bacillus cereus repeats (BCRs) and 30 known group II introns.

CONCLUSIONS

Our analysis not only shows the diversity of these MGEs among strains of the same species and between different species within the B. cereus s.l. group, but also highlights the potential impact of these elements on the plasticity of the plasmid pool, and the TEs (Transposable Elements) - species relationship within B. cereus s.l.

P4P: a peptidome-based strain-level genome comparison web tool

Peptidome similarity analysis enables researchers to gain insights into differential peptide profiles, providing a robust tool to discriminate strain-specific peptides, true intra-species differences among biological replicates or even microorganism-phenotype variations. However, no in silico peptide fingerprinting software existed to facilitate such phylogeny inference. Hence, we developed the Peptidomes for Phylogenies (P4P) web tool, which enables the survey of similarities between microbial proteomes and simplifies the process of obtaining new biological insights into their phylogeny. P4P can be used to analyze different peptide datasets, i.e. bacteria, viruses, eukaryotic species or even metaproteomes. Also, it is able to work with whole proteome datasets and experimental mass-to-charge lists originated from mass spectrometers. The ultimate aim is to generate a valid and manageable list of peptides that have phylogenetic signal and are potentially sample-specific. Sample-to-sample comparison is based on a consensus peak set matrix, which can be further submitted to phylogenetic analysis. P4P holds great potential for improving phylogenetic analyses in challenging taxonomic groups, biomarker identification or epidemiologic studies. Notably, P4P can be of interest for applications handling large proteomic datasets, which it is able to reduce to small matrices while maintaining high phylogenetic resolution. The web server is available at http://sing-group.org/p4p.