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.
MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples / Zolfo, Moreno; Tett, Adrian James; Jousson, Olivier; Donati, Claudio; Segata, Nicola. - In: NUCLEIC ACIDS RESEARCH. - ISSN 0305-1048. - 2016:1(2017), p. gkw837. [10.1093/nar/gkw837]
MetaMLST: multi-locus strain-level bacterial typing from metagenomic samples
Zolfo, Moreno;Tett, Adrian James;Jousson, Olivier;Segata, Nicola
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 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.File | Dimensione | Formato | |
---|---|---|---|
2017Zolfo_NuclAcidsRes.pdf
accesso aperto
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Creative commons
Dimensione
4.7 MB
Formato
Adobe PDF
|
4.7 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione