Comparing bacterial communities inferred from 16S rRNA gene sequencing and shotgun metagenomics.

Neethu Shah, Haixu Tang, Thomas G Doak, Yuzhen Ye
Author Information
  1. Neethu Shah: School Of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. neetshah@indiana.edu

Abstract

16S rRNA gene sequencing has been widely used for probing the species structure of a variety of environmental bacterial communities. Alternatively, 16S rRNA gene fragments can be retrieved from shotgun metagenomic sequences (metagenomes) and used for species profiling. Both approaches have their limitations-16S rRNA sequencing may be biased because of unequal amplification of species' 16S rRNA genes, whereas shotgun metagenomic sequencing may not be deep enough to detect the 16S rRNA genes of rare species in a community. However, previous studies showed that these two approaches give largely similar species profiles for a few bacterial communities. To investigate this problem in greater detail, we conducted a systematic comparison of these two approaches. We developed PHYLOSHOP, a pipeline that predicts 16S rRNA gene fragments in metagenomes, reports the taxonomic assignment of these fragments, and visualizes their taxonomy distribution. Using PHYLOSHOP, we analyzed 33 metagenomic datasets of human-associated bacterial communities, and compared the bacterial community structures derived from these metagenomic datasets with the community structure derived from 16S rRNA gene sequencing (71 datasets). Based on several statistical tests (including a statistical test proposed here that takes into consideration differences in sample size), we observed that these two approaches give significantly different community structures for nearly all the bacterial communities collected from different locations on and in human body, and that these differences cannot be be explained by differences in sample size and are likely to be attributed by experimental method.

Grants

  1. 1R01HG004908-02/NHGRI NIH HHS

MeSH Term

Bacteria
Computational Biology
Databases, Nucleic Acid
Genes, Bacterial
Genes, rRNA
Humans
Metagenome
Metagenomics
Phylogeny
RNA, Bacterial
RNA, Ribosomal, 16S
Sequence Analysis, RNA
Software

Chemicals

RNA, Bacterial
RNA, Ribosomal, 16S

Word Cloud

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