Using populations of human and microbial genomes for organism detection in metagenomes.
Identifying causative disease agents in human patients from shotgun metagenomic sequencing (SMS) presents a powerful tool to apply when other targeted diagnostics fail. Numerous technical challenges remain, however, before SMS can move beyond the role of research tool. Accurately separating the known and unknown organism content remains difficult, particularly when SMS is applied as a last resort. The true amount of human DNA that remains in a sample after screening against the human reference genome and filtering nonbiological components left from library preparation has previously been underreported. In this study, we create the most comprehensive collection of microbial and reference-free human genetic variation available in a database optimized for efficient metagenomic search by extracting sequences from GenBank and the 1000 Genomes Project. The results reveal new human sequences found in individual Human Microbiome Project (HMP) samples. Individual samples contain up to 95% human sequence, and 4% of the individual HMP samples contain 10% or more human reads. Left unidentified, human reads can complicate and slow down further analysis and lead to inaccurately labeled microbial taxa and ultimately lead to privacy concerns as more human genome data is collected.
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, California 94550, USA;
Sasha K
SK
Ames
Global Security Computer Applications Division, Lawrence Livermore National Laboratory, Livermore, California 94550, USA;
Shea N
SN
Gardner
Instituto de Física Corpuscular, CSIC-UVEG, E-46980 Valencia, Spain.
Jose Manuel
JM
Marti
Global Security Computer Applications Division, Lawrence Livermore National Laboratory, Livermore, California 94550, USA;
Tom R
TR
Slezak
Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, California 94550, USA;
Maya B
MB
Gokhale
Global Security Computer Applications Division, Lawrence Livermore National Laboratory, Livermore, California 94550, USA;
Jonathan E
JE
Allen
D019295:Computational Biology / Q000379:methods; D030561:Databases, Nucleic Acid; D064349:Genome, Microbial; D006801:Humans; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota; D012372:ROC Curve