Dataset Information

Strain/species identification in metagenomes using genome-specific markers.

ABSTRACT: Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ?0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing.

SUBMITTER: Tu Q

PROVIDER: S-EPMC4005670 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Strain/species identification in metagenomes using genome-specific markers.

Tu Qichao Q He Zhili Z Zhou Jizhong J

Nucleic acids research 20140212 8

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagen ...[more]

PMID: 24523352

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Project description:BackgroundThe identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets.DescriptionA pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001) any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively), or if BLAST, using the best hit as the query (reverse BLAST), does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences) are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification) system web site (updated semi-annually) at http://pir.georgetown.edu/cupid.ConclusionCUPID provides a set of proteins specific to a genus, species or a strain, and identifies the most closely related organism.

Dataset Information

Strain/species identification in metagenomes using genome-specific markers.

Publications

Strain/species identification in metagenomes using genome-specific markers.

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