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Light into the darkness: Unifying the known and unknown coding sequence space in microbiome analyses

View ORCID ProfileChiara Vanni, View ORCID ProfileMatthew Schechter, Silvia Acinas, Albert Barberán, Pier Luigi Buttigieg, Emilio O. Casamayor, Tom O. Delmont, Carlos M. Duarte, View ORCID ProfileA. Murat Eren, Rob Finn, Alex Mitchell, View ORCID ProfilePablo Sanchez, View ORCID ProfileKimmo Siren, View ORCID ProfileMartin Steinegger, Frank Oliver Glöckner, View ORCID ProfileAntonio Fernandez-Guerra
doi: https://doi.org/10.1101/2020.06.30.180448
Chiara Vanni
1Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359, Bremen, Germany
2Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany
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Matthew Schechter
1Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359, Bremen, Germany
3Department of Medicine, University of Chicago, Chicago, IL 60637, USA
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Silvia Acinas
4Department of Marine Biology and Oceanography, Institut de Ciènces del Mar, CSIC, Barcelona, Spain
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Albert Barberán
5Department of Environmental Science, University of Arizona, Tucson, 85721 AZ, USA
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Pier Luigi Buttigieg
6Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
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Emilio O. Casamayor
7Center for Advanced Studies of Blanes CEAB-CSIC, Spanish Council for Research, Blanes, Spain
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Tom O. Delmont
8Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057 Evry, France
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Carlos M. Duarte
9Red Sea Research Centre (RSRC) and Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
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A. Murat Eren
3Department of Medicine, University of Chicago, Chicago, IL 60637, USA
10Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, MA 02543, USA
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Rob Finn
11European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Alex Mitchell
11European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Pablo Sanchez
4Department of Marine Biology and Oceanography, Institut de Ciènces del Mar, CSIC, Barcelona, Spain
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Kimmo Siren
12Section for Evolutionary Genomics, The GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
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Martin Steinegger
13School of Biological Sciences, Seoul National University, Seoul, 08826, South Korea
14Institute of Molecular Biology and Genetics, Seoul National University, Seoul, 08826, South Korea
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Frank Oliver Glöckner
15Life Sciences and Chemistry, Campus Ring 1, 28759 Bremen, Germany
16Computing Center, Helmholtz Center for Polar and Marine Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
17University of Bremen, MARUM, Bibliothekstraße 1, 28359 Bremen
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Antonio Fernandez-Guerra
1Microbial Genomics and Bioinformatics Research Group, Max Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359, Bremen, Germany
18Lundbeck GeoGenetics Centre, The Globe Institute, University of Copenhagen, 1350 Copenhagen, Denmark
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  • For correspondence: antonio.fernandez-guerra@sund.ku.dk
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Abstract

Bridging the gap between the known and the unknown coding sequence space is one of the biggest challenges in molecular biology today. This challenge is especially extreme in microbiome analyses where between 40% to 60% of the coding sequences detected are of unknown function, and ignoring this fraction limits our understanding of microbial systems. Discarding the uncharacterized fraction is not an option anymore. Here, we present an in-depth exploration of the microbial unknown fraction through the lenses of a conceptual framework and a computational workflow we developed to unify the microbial known and unknown coding sequence space. Our approach partitions the coding sequence space in gene clusters and contextualizes them with genomic and environmental information. We analyzed 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes putting into perspective the extent of the unknown fraction, its diversity, and its relevance in a genomic and environmental context. With the identification of a target gene of unknown function for antibiotic resistance, we demonstrate how a contextualized unknown coding sequence space provides a robust framework for the generation of hypotheses that can be used to augment experimental data.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://dark.metagenomics.eu/

  • https://doi.org/10.6084/m9.figshare.12459056

  • https://github.com/functional-dark-side/agnostos-wf

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Light into the darkness: Unifying the known and unknown coding sequence space in microbiome analyses
Chiara Vanni, Matthew Schechter, Silvia Acinas, Albert Barberán, Pier Luigi Buttigieg, Emilio O. Casamayor, Tom O. Delmont, Carlos M. Duarte, A. Murat Eren, Rob Finn, Alex Mitchell, Pablo Sanchez, Kimmo Siren, Martin Steinegger, Frank Oliver Glöckner, Antonio Fernandez-Guerra
bioRxiv 2020.06.30.180448; doi: https://doi.org/10.1101/2020.06.30.180448
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Light into the darkness: Unifying the known and unknown coding sequence space in microbiome analyses
Chiara Vanni, Matthew Schechter, Silvia Acinas, Albert Barberán, Pier Luigi Buttigieg, Emilio O. Casamayor, Tom O. Delmont, Carlos M. Duarte, A. Murat Eren, Rob Finn, Alex Mitchell, Pablo Sanchez, Kimmo Siren, Martin Steinegger, Frank Oliver Glöckner, Antonio Fernandez-Guerra
bioRxiv 2020.06.30.180448; doi: https://doi.org/10.1101/2020.06.30.180448

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