Unraveling the functional dark matter through global metagenomics
Unraveling the functional dark matter through global metagenomics
Date
2023-10-11
Authors
Pavlopoulos, Georgios A.
Baltoumas, Fotis A.
Liu, Sirui
Selvitopi, Oguz
Pedro Camargo, Antonio
Nayfach, Stephen
Azad, Ariful
Roux, Simon
Call, Lee
Ivanova, Natalia N.
Chen, I. Min
Paez-Espino, David
Karatzas, Evangelos
Novel Metagenome Protein Families Consortium
Iliopoulos, Ioannis
Konstantinidis, Konstantinos T.
Tiedje, James M.
Pett-Ridge, Jennifer
Baker, David
Visel, Axel
Ouzounis, Christos A.
Ovchinnikov, Sergey
Buluc, Aydin
Kyrpides, Nikos C.
Baltoumas, Fotis A.
Liu, Sirui
Selvitopi, Oguz
Pedro Camargo, Antonio
Nayfach, Stephen
Azad, Ariful
Roux, Simon
Call, Lee
Ivanova, Natalia N.
Chen, I. Min
Paez-Espino, David
Karatzas, Evangelos
Novel Metagenome Protein Families Consortium
Iliopoulos, Ioannis
Konstantinidis, Konstantinos T.
Tiedje, James M.
Pett-Ridge, Jennifer
Baker, David
Visel, Axel
Ouzounis, Christos A.
Ovchinnikov, Sergey
Buluc, Aydin
Kyrpides, Nikos C.
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DOI
10.1038/s41586-023-06583-7
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Abstract
Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.
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© The Author(s), 2023. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Pavlopoulos, G. A., Baltoumas, F. A., Liu, S., Selvitopi, O., Camargo, A. P., Nayfach, S., Azad, A., Roux, S., Call, L., Ivanova, N. N., Chen, I. M., Paez-Espino, D., Karatzas, E., Novel Metagenome Protein Families Consortium, Iliopoulos, I., Konstantinidis, K., Tiedje, J. M., Pett-Ridge, J., Baker, D., Visel, A., Ouzounis, C. A., Ovchinnikov, S., Buluç, A., & Kyrpides, N. C. (2023). Unraveling the functional dark matter through global metagenomics. Nature, 622(7983), 594–602, https://doi.org/10.1038/s41586-023-06583-7.
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Pavlopoulos, G. A., Baltoumas, F. A., Liu, S., Selvitopi, O., Camargo, A. P., Nayfach, S., Azad, A., Roux, S., Call, L., Ivanova, N. N., Chen, I. M., Paez-Espino, D., Karatzas, E., Novel Metagenome Protein Families Consortium, Iliopoulos, I., Konstantinidis, K., Tiedje, J. M., Pett-Ridge, J., Baker, D., Visel, A., Ouzounis, C. A., Ovchinnikov, S., Buluç, A., & Kyrpides, N. C. (2023). Unraveling the functional dark matter through global metagenomics. Nature, 622(7983), 594–602.