Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics.

Juan Jovel,Naomi Hotte,Gane K.-S Wong,Weiwei Wang,Jordan Patterson,Karen L Madsen,Dina Kao,Troy Mitchel,Troy Perry,Sandra O'Keefe,Andrew L Mason

doi:10.3389/fmicb.2016.00459

Juan Jovel, Naomi Hotte + Show 9 more

Open Access

https://doi.org/10.3389/fmicb.2016.00459

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Abstract

The advent of next generation sequencing (NGS) has enabled investigations of the gut microbiome with unprecedented resolution and throughput. This has stimulated the development of sophisticated bioinformatics tools to analyze the massive amounts of data generated. Researchers therefore need a clear understanding of the key concepts required for the design, execution and interpretation of NGS experiments on microbiomes. We conducted a literature review and used our own data to determine which approaches work best. The two main approaches for analyzing the microbiome, 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses. Several methods for taxonomic classification of bacterial sequences are discussed. We present simulations to assess the number of sequences that are required to perform reliable appraisals of bacterial community structure. To the extent that fluctuations in the diversity of gut bacterial populations correlate with health and disease, we emphasize various techniques for the analysis of bacterial communities within samples (α-diversity) and between samples (β-diversity). Finally, we demonstrate techniques to infer the metabolic capabilities of a bacteria community from these 16S and shotgun data.

Highlights

Irrespective of the method used for clustering, we found a consistent over-representation of sequences in the Clostridium and Lactobacillus genera
It is expected that taxonomic classification performed with each method will be to some extent divergent, as the resolution of the sequences used for taxonomic assignments is distinct and variable depending on which region of the genome is captured in shotgun surveys, which variable region of the 16S ribosomal RNA (rRNA) gene is used, and which composition of species is present in the community under analysis
To illustrate some ideas and techniques related to beta diversity, we sequenced a set of 16S libraries that constitute three well-defined clusters of samples: three stool samples from mice fed with Chow, high fat or low fat diet; the three mock libraries described in Figure 1; and six ileum samples from two patients affected by Crohn’s disease (CD)

Summary

Introduction

High-throughput comparative metagenomics enabled by development of next-generation sequencing (NGS) platforms (Mardis, 2008; Novais and Thorstenson, 2011) has led to an outburst of research endeavors that have rapidly advanced our understanding of the composition and function of bacterial populations in very diverse environments (Ley et al, 2006; Garrett et al, 2010; Caporaso et al, 2011; Bolhuis et al, 2014; Huttenhower et al, 2014a; Norman et al, 2014; Yoon et al, 2015). Using gut microbiome datasets specially designed to illustrate the strengths and weaknesses of 16S or shotgun libraries, we describe several methods for performing taxonomical classification of bacterial sequences, assessment of bacterial diversity within and between samples, and inference of the metabolic capabilities associated with the bacterial microbiome.

Results

Conclusion