An introduction to the analysis of shotgun metagenomic data

Abstract

Environmental DNA sequencing has revealed the expansive biodiversity of microorganisms and clarified the relationship between host-associated microbial communities and host phenotype. Shotgun metagenomic DNA sequencing is a relatively new and powerful environmental sequencing approach that provides insight into community biodiversity and function. But, the analysis of metagenomic sequences is complicated due to the complex structure of the data. Fortunately, new tools and data resources have been developed to circumvent these complexities and allow researchers to determine which microbes are present in the community and what they might be doing. This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use. Specifically, it documents how metagenomes can be analyzed to quantify community structure and diversity, assemble novel genomes, identify new taxa and genes, and determine which metabolic pathways are encoded in the community. It also discusses several methods that can be used compare metagenomes to identify taxa and functions that differentiate communities.

Automated and accurate estimation of gene family abundance from shotgun metagenomes

“…These include stand-alone software such as MEGAN [6], HUMAnN [7], RAMMCAP [8], SmashCommunity [9], and MOCAT [10], as well as cloud-based tools like CloVR [11], and web portals like MG-RAST [12], MicrobesOnline [13], and the IMG/M annotation server [14](S1 Table). Generally, these methods operate by comparing metagenomic sequence reads to a reference database of functionally annotated protein families and use homology inference to annotate each read [5]. Despite the wide use of this general strategy, surprisingly little is known about how the analytical parameters selected during these procedures (e.g., read translation, homology classification thresholds, reference database) impact the accuracy of the resulting estimates of gene family abundance.…”

“…High-throughput amplicon sequencing of taxonomically informative loci (e.g., small-subunit rRNA genes) has shed light on the tremendous diversity and distribution of microbial communities in nature [1] and revealed patterns and processes related to the assembly [2], diversification [3], and scaling [4] of these communities. Shotgun sequencing of total DNA from microbial communities (i.e., metagenomics) is gaining popularity, as it provides insight into the genomic composition of microbes as they exist in nature and enables inference of the community's biological functional potential [5]. By annotating metagenomic sequences with the gene families from which they derive, the community's biological functional potential can be profiled.…”

Microbiotes et métagénomique

“…On conçoit aisément que l'analyse de données fragmentaires issues d'un mélange de nombreuses espèces de génomes est une gageure. Une méthodologie s'est ainsi progressivement dégagée au fur et à mesure du développement de nouveaux outils informatiques [21] (Figure 1). Les microbiotes environnementaux furent les premiers à être étudiés [22], mais l'anthropocentrisme aidant, les résultats au plus fort impact et les plus nombreux concernent les métagénomes humains [23].…”

Contemporary molecular tools in microbial ecology and their application to advancing biotechnology

“…With the advent of the faster, higher-throughput, and cheaper NGS technologies, metagenomic shotgun sequencing has become very handy and routinely produces large metagenomic datasets (Simon and Daniel 2009, Hentschel, Piel et al 2012, Di Bella, Bao et al 2013, Ferreira, Siam et al 2014, Sharpton 2014. In the shotgun sequencing approach, already applied earlier to cultured microbes and human genomes, metagenomic DNA is randomly sheared and sequenced in short reads.…”