TY - JOUR

T1 - Joint Analysis of Long and Short Reads Enables Accurate Estimates of Microbiome Complexity

AU - Bankevich, Anton

AU - Pevzner, Pavel A.

PY - 2018/8/22

Y1 - 2018/8/22

N2 - Reduced microbiome diversity has been linked to several diseases. However, estimating the diversity of bacterial communities—the number and the total length of distinct genomes within a metagenome—remains an open problem in microbial ecology. Here, we describe an algorithm for estimating the microbial diversity in a metagenomic sample based on a joint analysis of short and long reads. Unlike previous approaches, the algorithm does not make any assumptions on the distribution of the frequencies of genomes within a metagenome (as in parametric methods) and does not require a large database that covers the total diversity (as in non-parametric methods). We estimate that genomes comprising a human gut metagenome have total length varying from 1.3 to 3.5 billion nucleotides, with genomes responsible for 50% of total abundance having total length varying from only 25 to 61 million nucleotides. In contrast, genomes comprising an aquifer sediment metagenome have more than two orders of magnitude larger total length (≈840 billion nucleotides). We present a method for estimating the diversity of metagenomic samples that combines short and long sequencing reads. We show that our method is capable of capturing rare species and apply it to analyze diversity of the human gut and aquifer sediment metagenomes.

AB - Reduced microbiome diversity has been linked to several diseases. However, estimating the diversity of bacterial communities—the number and the total length of distinct genomes within a metagenome—remains an open problem in microbial ecology. Here, we describe an algorithm for estimating the microbial diversity in a metagenomic sample based on a joint analysis of short and long reads. Unlike previous approaches, the algorithm does not make any assumptions on the distribution of the frequencies of genomes within a metagenome (as in parametric methods) and does not require a large database that covers the total diversity (as in non-parametric methods). We estimate that genomes comprising a human gut metagenome have total length varying from 1.3 to 3.5 billion nucleotides, with genomes responsible for 50% of total abundance having total length varying from only 25 to 61 million nucleotides. In contrast, genomes comprising an aquifer sediment metagenome have more than two orders of magnitude larger total length (≈840 billion nucleotides). We present a method for estimating the diversity of metagenomic samples that combines short and long sequencing reads. We show that our method is capable of capturing rare species and apply it to analyze diversity of the human gut and aquifer sediment metagenomes.

KW - metagenomics

KW - microbal diversity

KW - rare species

KW - BACTERIAL DIVERSITY

KW - COVERAGE

KW - DNA

KW - GUT MICROBIOTA

KW - RARE BIOSPHERE

KW - ABUNDANCE

UR - http://www.scopus.com/inward/record.url?scp=85053854176&partnerID=8YFLogxK

U2 - 10.1016/j.cels.2018.06.009

DO - 10.1016/j.cels.2018.06.009

M3 - Article

AN - SCOPUS:85053854176

VL - 7

SP - 192-200.e3

JO - Cell Systems

JF - Cell Systems

SN - 2405-4712

IS - 2

ER -