Microbial abundance, activity and population genomic profiling with mOTUs2

Alessio Milanese, Daniel R Mende, Lucas Paoli, Guillem Salazar, Hans-Joachim Ruscheweyh, Miguelangel Cuenca, Pascal Hingamp, Renato Alves, Paul I Costea, Luis Pedro Coelho, Thomas S. B. Schmidt, Alexandre Almeida, Alex L Mitchell, Robert D. Finn, Jaime Huerta-Cepas, Peer Bork, Georg Zeller () and Shinichi Sunagawa ()
Additional contact information
Alessio Milanese: European Molecular Biology Laboratory
Daniel R Mende: University of Hawaiʻi at Mānoa
Lucas Paoli: ETH Zürich
Guillem Salazar: ETH Zürich
Hans-Joachim Ruscheweyh: ETH Zürich
Miguelangel Cuenca: ETH Zürich
Pascal Hingamp: Aix Marseille Univ, Université de Toulon, CNRS, IRD, MIO UM 110
Renato Alves: European Molecular Biology Laboratory
Paul I Costea: European Molecular Biology Laboratory
Luis Pedro Coelho: European Molecular Biology Laboratory
Thomas S. B. Schmidt: European Molecular Biology Laboratory
Alexandre Almeida: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus
Alex L Mitchell: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus
Robert D. Finn: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus
Jaime Huerta-Cepas: European Molecular Biology Laboratory
Peer Bork: European Molecular Biology Laboratory
Georg Zeller: European Molecular Biology Laboratory
Shinichi Sunagawa: ETH Zürich

Nature Communications, 2019, vol. 10, issue 1, 1-11

Abstract: Abstract 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).

Date: 2019
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DOI: 10.1038/s41467-019-08844-4

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