Unraveling the functional dark matter through global metagenomics

Authors

Georgios A. Pavlopoulos, Institute for Fundamental Biomedical Research
Fotis A. Baltoumas, Institute for Fundamental Biomedical Research
Sirui Liu, Harvard University
Oguz Selvitopi, Lawrence Berkeley National Laboratory
Antonio Pedro Camargo, Lawrence Berkeley National Laboratory
Stephen Nayfach, Lawrence Berkeley National Laboratory
Ariful Azad, Indiana University - Bloomington
Simon Roux, Lawrence Berkeley National Laboratory
Lee Call, Lawrence Berkeley National Laboratory
Natalia N. Ivanova, Lawrence Berkeley National Laboratory
Min I. Chen, Lawrence Berkeley National Laboratory
David Paez-Espino, Lawrence Berkeley National Laboratory
Evangelos Karatzas, Institute for Fundamental Biomedical Research
Nathan Ahlgren, Clark UniversityFollow

Document Type

Article

Abstract

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities^1,2. 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. © 2023, The Author(s).

This article has 132 individual authors. We have listed the first 14. For the full list, see the full-text article.

Publication Title

Nature

Publication Date

10-19-2023

Volume

622

Issue

7983

First Page

594

Last Page

602

ISSN

0028-0836

DOI

10.1038/s41586-023-06583-7

Keywords

cluster analysis, metagenome, metagenomics, proteins

Repository Citation

Pavlopoulos, Georgios A.; Baltoumas, Fotis A.; Liu, Sirui; Selvitopi, Oguz; Camargo, Antonio Pedro; Nayfach, Stephen; Azad, Ariful; Roux, Simon; Call, Lee; Ivanova, Natalia N.; Chen, Min I.; Paez-Espino, David; Karatzas, Evangelos; and Ahlgren, Nathan, "Unraveling the functional dark matter through global metagenomics" (2023). Biology. 13.
https://commons.clarku.edu/faculty_biology/13

Copyright Conditions

Published source must be acknowledged with citation:
Pavlopoulos, Georgios A., et al. "Unraveling the functional dark matter through global metagenomics." Nature (2023): 1-9.