Cargando…

Quantifying the taxonomic bias in enzymology

The ongoing biotechnological revolution is rooted in our knowledge of enzymes. However, metagenomics is showing how little we know about Earth's enzyme repertoire. Deep sequencing has revolutionized our view of the tree of life. The genomes of newly‐discovered organisms are replete with novel s...

Descripción completa

Detalles Bibliográficos
Autores principales: Vickers, Chelsea J., Fraga, Dean, Patrick, Wayne M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980516/
https://www.ncbi.nlm.nih.gov/pubmed/33583070
http://dx.doi.org/10.1002/pro.4041
_version_ 1783667444623081472
author Vickers, Chelsea J.
Fraga, Dean
Patrick, Wayne M.
author_facet Vickers, Chelsea J.
Fraga, Dean
Patrick, Wayne M.
author_sort Vickers, Chelsea J.
collection PubMed
description The ongoing biotechnological revolution is rooted in our knowledge of enzymes. However, metagenomics is showing how little we know about Earth's enzyme repertoire. Deep sequencing has revolutionized our view of the tree of life. The genomes of newly‐discovered organisms are replete with novel sequences, emphasizing the trove of enzyme structures and functions waiting to be explored by biochemists. Here, we sought to draw attention to the vastness of the “enzymatic dark matter” within the tree of life by placing enzymological knowledge in the context of phylogeny. We used kinetic parameters from the BRaunschweig ENzyme DAtabase (BRENDA) as our proxy for enzymological knowledge. Mapping 12,677 BRENDA entries onto the phylogenetic tree revealed that 55% of these data were from eukaryotes, even though they are the least diverse part of the tree. At the next taxonomic level, only four of 18 archaeal phyla and 24 of 111 bacterial phyla are represented in the BRENDA dataset. One phylum, the Proteobacteria, accounts for over half of all bacterial entries. Similarly, the supergroup Amorphea, which includes animals and fungi, contains over half the data on eukaryotes. Many major taxonomic groups are notable for their complete absence from BRENDA, including the ultra‐diverse bacterial Candidate Phyla Radiation. At the species level, five mammals (including human) contribute 15% of BRENDA entries. The taxonomic bias in enzymology is strong, but in the era of gene synthesis we now have the tools to address it. Doing so promises to enrich our biochemical understanding of life and uncover powerful new biocatalysts.
format Online
Article
Text
id pubmed-7980516
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley & Sons, Inc.
record_format MEDLINE/PubMed
spelling pubmed-79805162021-07-02 Quantifying the taxonomic bias in enzymology Vickers, Chelsea J. Fraga, Dean Patrick, Wayne M. Protein Sci For the Record The ongoing biotechnological revolution is rooted in our knowledge of enzymes. However, metagenomics is showing how little we know about Earth's enzyme repertoire. Deep sequencing has revolutionized our view of the tree of life. The genomes of newly‐discovered organisms are replete with novel sequences, emphasizing the trove of enzyme structures and functions waiting to be explored by biochemists. Here, we sought to draw attention to the vastness of the “enzymatic dark matter” within the tree of life by placing enzymological knowledge in the context of phylogeny. We used kinetic parameters from the BRaunschweig ENzyme DAtabase (BRENDA) as our proxy for enzymological knowledge. Mapping 12,677 BRENDA entries onto the phylogenetic tree revealed that 55% of these data were from eukaryotes, even though they are the least diverse part of the tree. At the next taxonomic level, only four of 18 archaeal phyla and 24 of 111 bacterial phyla are represented in the BRENDA dataset. One phylum, the Proteobacteria, accounts for over half of all bacterial entries. Similarly, the supergroup Amorphea, which includes animals and fungi, contains over half the data on eukaryotes. Many major taxonomic groups are notable for their complete absence from BRENDA, including the ultra‐diverse bacterial Candidate Phyla Radiation. At the species level, five mammals (including human) contribute 15% of BRENDA entries. The taxonomic bias in enzymology is strong, but in the era of gene synthesis we now have the tools to address it. Doing so promises to enrich our biochemical understanding of life and uncover powerful new biocatalysts. John Wiley & Sons, Inc. 2021-02-25 2021-04 /pmc/articles/PMC7980516/ /pubmed/33583070 http://dx.doi.org/10.1002/pro.4041 Text en © 2021 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle For the Record
Vickers, Chelsea J.
Fraga, Dean
Patrick, Wayne M.
Quantifying the taxonomic bias in enzymology
title Quantifying the taxonomic bias in enzymology
title_full Quantifying the taxonomic bias in enzymology
title_fullStr Quantifying the taxonomic bias in enzymology
title_full_unstemmed Quantifying the taxonomic bias in enzymology
title_short Quantifying the taxonomic bias in enzymology
title_sort quantifying the taxonomic bias in enzymology
topic For the Record
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980516/
https://www.ncbi.nlm.nih.gov/pubmed/33583070
http://dx.doi.org/10.1002/pro.4041
work_keys_str_mv AT vickerschelseaj quantifyingthetaxonomicbiasinenzymology
AT fragadean quantifyingthetaxonomicbiasinenzymology
AT patrickwaynem quantifyingthetaxonomicbiasinenzymology