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Microbial abundance, activity and population genomic profiling with mOTUs2

Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces est...

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Detalles Bibliográficos
Autores principales: Milanese, Alessio, Mende, Daniel R, Paoli, Lucas, Salazar, Guillem, Ruscheweyh, Hans-Joachim, Cuenca, Miguelangel, Hingamp, Pascal, Alves, Renato, Costea, Paul I, Coelho, Luis Pedro, Schmidt, Thomas S. B., Almeida, Alexandre, Mitchell, Alex L, Finn, Robert D., Huerta-Cepas, Jaime, Bork, Peer, Zeller, Georg, Sunagawa, Shinichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399450/
https://www.ncbi.nlm.nih.gov/pubmed/30833550
http://dx.doi.org/10.1038/s41467-019-08844-4
Descripción
Sumario:Metagenomic sequencing has greatly improved our ability to profile the composition of environmental and host-associated microbial communities. However, the dependency of most methods on reference genomes, which are currently unavailable for a substantial fraction of microbial species, introduces estimation biases. We present an updated and functionally extended tool based on universal (i.e., reference-independent), phylogenetic marker gene (MG)-based operational taxonomic units (mOTUs) enabling the profiling of >7700 microbial species. As more than 30% of them could not previously be quantified at this taxonomic resolution, relative abundance estimates based on mOTUs are more accurate compared to other methods. As a new feature, we show that mOTUs, which are based on essential housekeeping genes, are demonstrably well-suited for quantification of basal transcriptional activity of community members. Furthermore, single nucleotide variation profiles estimated using mOTUs reflect those from whole genomes, which allows for comparing microbial strain populations (e.g., across different human body sites).