ConStrains identifies microbial strains in metagenomic datasets.
An important fraction of microbial diversity is harbored in strain individuality, so identification of conspecific bacterial strains is imperative for improved understanding of microbial community functions. Limitations in bioinformatics and sequencing technologies have to date precluded strain identification owing to difficulties in phasing short reads to faithfully recover the original strain-level genotypes, which have highly similar sequences. We present ConStrains, an open-source algorithm that identifies conspecific strains from metagenomic sequence data and reconstructs the phylogeny of these strains in microbial communities. The algorithm uses single-nucleotide polymorphism (SNP) patterns in a set of universal genes to infer within-species structures that represent strains. Applying ConStrains to simulated and host-derived datasets provides insights into microbial community dynamics.
Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, USA.|Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.|Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Chengwei
C
Luo
Department of Chemistry and Biochemistry, University of Colorado at Boulder, Boulder, Colorado, USA.|Howard Hughes Medical Institute, Boulder, Colorado, USA.
Rob
http://orcid.org/0000-0002-0975-9019
R
Knight
Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.|Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
Heli
H
Siljander
Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.|Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.|Folkhälsan Research Center, Helsinki, Finland.|Department of Pediatrics, Tampere University Hospital, Tampere, Finland.
Mikael
http://orcid.org/0000-0003-0474-0033
M
Knip
Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, USA.|Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.|Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.|Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Ramnik J
RJ
Xavier
Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, Massachusetts, USA.
Dirk
D
Gevers
D000465:Algorithms; D001419:Bacteria / Q000145:classification / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods; D030541:Databases, Genetic; D066264:Datasets as Topic; D016680:Genome, Bacterial / Q000235:genetics*; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D013045:Species Specificity