A user's guide to the bioinformatic analysis of shotgun metagenomic sequence data for bacterial pathogen detection.

Metagenomics, i.e., shotgun sequencing of the total microbial community DNA from a sample, has become a mature technique but its application to pathogen detection in clinical, environmental, and food samples is far from common or standardized. In this review, we summarize ongoing developments in metagenomic sequence analysis that facilitate its wider application to pathogen detection. We examine theoretical frameworks for estimating the limit of detection for a particular level of sequencing effort, current approaches for achieving species and strain analytical resolution, and discuss some relevant modern tools for these tasks. While these recent advances are significant and establish metagenomics as a powerful tool to provide insights not easily attained by culture-based approaches, metagenomics is unlikely to emerge as a widespread, routine monitoring tool in the near future due to its inherently high detection limits, cost, and inability to easily distinguish between viable and non-viable cells. Instead, metagenomics seems best poised for applications involving special circumstances otherwise challenging for culture-based and molecular (e.g., PCR-based) approaches such as the de novo detection of novel pathogens, cases of co-infection by more than one pathogen, and situations where it is important to assess the genomic composition of the pathogenic population(s) and/or its impact on the indigenous microbiome.

MetaPop: a pipeline for macro- and microdiversity analyses and visualization of microbial and viral metagenome-derived populations.

BACKGROUND: Microbes and their viruses are hidden engines driving Earth's ecosystems from the oceans and soils to humans and bioreactors. Though gene marker approaches can now be complemented by genome-resolved studies of inter-(macrodiversity) and intra-(microdiversity) population variation, analytical tools to do so remain scattered or under-developed. RESULTS: Here, we introduce MetaPop, an open-source bioinformatic pipeline that provides a single interface to analyze and visualize microbial and viral community metagenomes at both the macro- and microdiversity levels. Macrodiversity estimates include population abundances and α- and ß-diversity. Microdiversity calculations include identification of single nucleotide polymorphisms, novel codon-constrained linkage of SNPs, nucleotide diversity (π and θ), and selective pressures (pN/pS and Tajima's D) within and fixation indices (FST) between populations. MetaPop will also identify genes with distinct codon usage. Following rigorous validation, we applied MetaPop to the gut viromes of autistic children that underwent fecal microbiota transfers and their neurotypical peers. The macrodiversity results confirmed our prior findings for viral populations (microbial shotgun metagenomes were not available) that diversity did not significantly differ between autistic and neurotypical children. However, by also quantifying microdiversity, MetaPop revealed lower average viral nucleotide diversity (π) in autistic children. Analysis of the percentage of genomes detected under positive selection was also lower among autistic children, suggesting that higher viral π in neurotypical children may be beneficial because it allows populations to better "bet hedge" in changing environments. Further, comparisons of microdiversity pre- and post-FMT in autistic children revealed that the delivery FMT method (oral versus rectal) may influence viral activity and engraftment of microdiverse viral populations, with children who received their FMT rectally having higher microdiversity post-FMT. Overall, these results show that analyses at the macro level alone can miss important biological differences. CONCLUSIONS: These findings suggest that standardized population and genetic variation analyses will be invaluable for maximizing biological inference, and MetaPop provides a convenient tool package to explore the dual impact of macro- and microdiversity across microbial communities. Video abstract.

RecruitPlotEasy: An Advanced Read Recruitment Plot Tool for Assessing Metagenomic Population Abundance and Genetic Diversity.

Mapping of short metagenomic (or metatranscriptomic) read data to reference isolate or single-cell genomes or metagenome-assembled genomes (MAGs) to assess microbial population relative abundance and/or structure represents an essential task of many studies across environmental and clinical settings. The filtering for the quality of the read match and assessment of read mapping results are frequently performed without visual aids or with the assistance of visualizations produced through ad-hoc, in-house approaches. Here, we introduce RecruitPlotEasy, a fully automated, user-friendly pipeline for these purposes that integrates statistical approaches to quantify intra-population sequence and gene-content diversity and identify co-occurring relative populations in the sample. Hence, RecruitPlotEasy should also greatly facilitate population genetics studies. RecruitPlotEasy is implemented in Python and R languages and is freely available open source software under the Artistic License 2.0 from https://github.com/KGerhardt/RecruitPlotEasy.