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Resolving the Complexity of Human Skin Metagenomes Using Single-Molecule Sequencing

Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communiti...

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Detalles Bibliográficos
Autores principales: Tsai, Yu-Chih, Conlan, Sean, Deming, Clayton, Segre, Julia A., Kong, Heidi H., Korlach, Jonas, Oh, Julia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society of Microbiology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752602/
https://www.ncbi.nlm.nih.gov/pubmed/26861018
http://dx.doi.org/10.1128/mBio.01948-15
Descripción
Sumario:Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communities. However, the resultant “genomes” are typically fragmented and incomplete due to the limited ability of short-read sequence data to assemble complex or low-coverage regions. Here, we use single-molecule, real-time (SMRT) sequencing to reconstruct a high-quality, closed genome of a previously uncharacterized Corynebacterium simulans and its companion bacteriophage from a skin metagenomic sample. Considerable improvement in assembly quality occurs in hybrid approaches incorporating short-read data, with even relatively small amounts of long-read data being sufficient to improve metagenome reconstruction. Using short-read data to evaluate strain variation of this C. simulans in its skin community at single-nucleotide resolution, we observed a dominant C. simulans strain with moderate allelic heterozygosity throughout the population. We demonstrate the utility of SMRT sequencing and hybrid approaches in metagenome quantitation, reconstruction, and annotation.