Ahsanuddin, S. | Search bioRxiv

bioRxiv2019

Global Genetic Cartography of Urban Metagenomes andAnti-Microbial Resistance

We have created a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities across 3 years. This is the first systematic, worldwide study cataloging the urban microbial ecosystem. We identify taxonomically-defined microorganisms collected across three years. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics AMR markers, and novel genetic elements, including 10,928 viral, 1302 bacteria, and 2 archaea novel species. We identify 4,424 species of urban microorganisms and a consistent "core" of 31 species found in nearly all samples that is largely distinct from any human commensal microbiome. Profiles of AMR genes show geographic variation in type and density. Together, these results constitute a high-resolution, global metagenomic atlas, which enables the discovery of new genetic components, highlights potential forensic applications, and provides an essential first draft of the global AMR burden of the worlds cities.

microbiology↗

bioRxiv2017

Comprehensive Benchmarking and Ensemble Approaches for Metagenomic Classifiers

BackgroundOne of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest (n=35) to date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of eleven metagenomics classifiers. We also assess the effects of filtering and combining tools to reduce the number of false positives.\n\nResultsTools were characterized on the basis of their ability to (1) identify taxa at the genus, species, and strain levels, (2) quantify relative abundance measures of taxa, and (3) classify individual reads to the species level. Strikingly, the number of species identified by the eleven tools can differ by over three orders of magnitude on the same datasets. However, various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Indeed, leveraging tools with different heuristics is beneficial for improved precision. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species and where customized tools may be required.\n\nConclusionsThe results of this study provide positive controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision and recall. We show that proper experimental design and analysis parameters, including depth of sequencing, choice of classifier or classifiers, database size, and filtering, can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

genomics↗