TY - JOUR
T1 - Unifying the known and unknown microbial coding sequence space.
AU - Vanni, Chiara
AU - Schechter, Matthew S.
AU - Acinas, Silvia G
AU - Barberán, Albert
AU - Buttigieg, Pier Luigi
AU - Casamayor, Emilio O
AU - Delmont, Tom O
AU - Duarte, Carlos M.
AU - Eren, A. Murat
AU - Finn, Robert D
AU - Kottmann, Renzo
AU - Mitchell, Alex
AU - Sanchez, Pablo
AU - Siren, Kimmo
AU - Steinegger, Martin
AU - Gloeckner, Frank Oliver
AU - Fernandez-Guerra, Antonio
N1 - KAUST Repository Item: Exported on 2022-04-05
Acknowledgements: The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2014-2-0085), the BMBF-funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI)(031A537B, 031A533A, 031A538A, 031A533B, 031A535A, 031A537C, 031A534A, 031A532B), the University of Oxford Advanced Research Computing (http://dx.doi.org/10.5281/zenodo.22558) and the MARBITS bioinformatics core at ICM-CSIC. CV was supported by the Max Planck Society. AFG received funding from the European Union’s Horizon 2020 research and innovation program Blue Growth: Unlocking the potential of Seas and Oceans under grant agreement no. 634486 (project acronym INMARE). AM was supported by the Biotechnology and Biological Sciences Research Council [BB/M011755/1, BB/R015228/1] and RDF by the European Molecular Biology Laboratory core funds. EOC was supported by project INTERACTOMA RTI2018-101205-B-I00 from the Spanish Agency of Science MICIU/AEI. SGA and PS received additional funding by the project MAGGY(CTM2017-87736-R) from the Spanish Ministry of Economy and Competitiveness. The Malaspina 2010 Expedition was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) through the Consolider-Ingenio program (ref. CSD2008-00077). The authors thank Johannes Söding and Alex Bateman for helpful discussions.
PY - 2022/3/31
Y1 - 2022/3/31
N2 - Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for $\textit{Cand}$. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.
AB - Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for $\textit{Cand}$. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.
UR - http://hdl.handle.net/10754/676115
UR - https://elifesciences.org/articles/67667
U2 - 10.7554/elife.67667
DO - 10.7554/elife.67667
M3 - Article
C2 - 35356891
SN - 2050-084X
VL - 11
JO - eLife
JF - eLife
ER -