imGLAD: accurate detection and quantification of target organisms in metagenomes

PeerJ

article

Juan C. Castro¹  Luis M. Rodriguez-R¹  William T. Harvey²  Michael R. Weigand³  Janet K. Hatt³  Michelle Q. Carter⁵  Konstantinos T. Konstantinidis¹ 

[1] Center for Bioinformatics and Computational Genomics, Georgia Institute of Technology;School of Biological Sciences, Georgia Institute of Technology;School of Civil and Environmental Engineering, Georgia Institute of Technology;Division of Bacterial Diseases, Center for Disease Control and Prevention;Produce Safety and Microbiology, USDA-ARS Western Regional Research Center, US Department of Agriculture

关键词: Genomes;    Metagenomics;    Limit of detection;   

DOI  :  10.7717/peerj.5882

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Accurate detection of target microbial species in metagenomic datasets from environmental samples remains limited because the limit of detection of current methods is typically inaccessible and the frequency of false-positives, resulting from inadequate identification of regions of the genome that are either too highly conserved to be diagnostic (e.g., rRNA genes) or prone to frequent horizontal genetic exchange (e.g., mobile elements) remains unknown. To overcome these limitations, we introduce imGLAD, which aims to detect (target) genomic sequences in metagenomic datasets. imGLAD achieves high accuracy because it uses the sequence-discrete population concept for discriminating between metagenomic reads originating from the target organism compared to reads from co-occurring close relatives, masks regions of the genome that are not informative using the MyTaxa engine, and models both the sequencing breadth and depth to determine relative abundance and limit of detection. We validated imGLAD by analyzing metagenomic datasets derived from spinach leaves inoculated with the enteric pathogen Escherichia coli O157:H7 and showed that its limit of detection can be comparable to that of PCR-based approaches for these samples (∼1 cell/gram).

【 授权许可】

CC BY