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MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
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 Sequenc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314789/ https://www.ncbi.nlm.nih.gov/pubmed/27651451 http://dx.doi.org/10.1093/nar/gkw837 |
Sumario: | 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 1×. 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. |
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