Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequence Typing (MLST) are still widely used and provide a wealth of strain-level information that is currently not exploited by metagenomic methods. We introduce MetaMLST, a software tool that reconstructs the MLST loci of microorganisms present in microbial communities from metagenomic data. Tested on synthetic and spiked-in real metagenomes, the pipeline was able to reconstruct the MLST sequences with >98.5% accuracy at coverages as low as 1X. On real samples, the pipeline showed higher sensitivity than assembly-based approaches and it proved successful in identifying strains in epidemic outbreaks as well as in intestinal, skin and gastrointestinal microbiome samples.

Zolfo, M.; Tett, A.; Jousson, O.; Donati, C.; Segata, N. (2017). MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples. NUCLEIC ACIDS RESEARCH, 45 (2): e7. doi: 10.1093/nar/gkw837 handle: http://hdl.handle.net/10449/35720

MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples

Donati, Claudio;
2017-01-01

Abstract

Metagenomic characterization of microbial communities has the potential to become a tool to identify pathogens in human samples. However, software tools able to extract strain-level typing information from metagenomic data are needed. Low-throughput molecular typing schema such as Multilocus Sequence Typing (MLST) are still widely used and provide a wealth of strain-level information that is currently not exploited by metagenomic methods. We introduce MetaMLST, a software tool that reconstructs the MLST loci of microorganisms present in microbial communities from metagenomic data. Tested on synthetic and spiked-in real metagenomes, the pipeline was able to reconstruct the MLST sequences with >98.5% accuracy at coverages as low as 1X. On real samples, the pipeline showed higher sensitivity than assembly-based approaches and it proved successful in identifying strains in epidemic outbreaks as well as in intestinal, skin and gastrointestinal microbiome samples.
Metagenomics
Population genetics
Microbiology
Settore BIO/19 - MICROBIOLOGIA GENERALE
2017
Zolfo, M.; Tett, A.; Jousson, O.; Donati, C.; Segata, N. (2017). MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples. NUCLEIC ACIDS RESEARCH, 45 (2): e7. doi: 10.1093/nar/gkw837 handle: http://hdl.handle.net/10449/35720
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10449/35720
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