Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution
Protein domains sometime combine to form multidomain proteins and are acquired or lost in lineages of organisms. These processes are ubiquitous in modern metabolism. To sort out evolutionary patterns of domain recruitment, we developed an algorithm that derives the most plausible ancestry of an enzy...
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Online Access: | https://doi.org/10.2390/biecoll-jib-2013-214 |
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doaj-4c9fc6a6437e4996a9ff0c27b9f519892021-09-06T19:40:56ZengDe GruyterJournal of Integrative Bioinformatics1613-45162013-03-0110111810.2390/biecoll-jib-2013-214Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic EvolutionKim Hee Shin0Mittenthal Jay E.1Caetano-Anollés Gustavo2Evolutionary Bioinformatics Laboratory, Department of Crop Sciences, United States of AmericaDepartment of Cell and Developmental Biology, University of Illinois, Urbana, IL, 61801, http://manet.illinois.edu, United States of AmericaEvolutionary Bioinformatics Laboratory, Department of Crop Sciences, United States of AmericaProtein domains sometime combine to form multidomain proteins and are acquired or lost in lineages of organisms. These processes are ubiquitous in modern metabolism. To sort out evolutionary patterns of domain recruitment, we developed an algorithm that derives the most plausible ancestry of an enzyme from structural and evolutionary annotations in the MANET database. We applied this algorithm to the analysis of 1,163 enzymes with structural assignments. We then counted the number of enzymes along a time series and analyzed enzyme distribution in organisms belonging to superkingdoms Archaea, Bacteria, and Eukarya. The generated timelines described the evolution of modern metabolic networks and showed an early build-up of metabolic activities associated with metabolism of nucleotides, cofactors, and vitamins, followed by enzymes involved in carbohydrate and amino acid metabolism. More importantly, we find that existing domain structures were pervasively co-opted to perform more modern enzymatic tasks, either singly or in combination with other domains. This occurred differentially in lineages of the superkingdoms as the world diversified and organisms adapted to various environments. Our results highlight the important role of recruitment and domain organization in metabolic evolution.https://doi.org/10.2390/biecoll-jib-2013-214 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kim Hee Shin Mittenthal Jay E. Caetano-Anollés Gustavo |
spellingShingle |
Kim Hee Shin Mittenthal Jay E. Caetano-Anollés Gustavo Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution Journal of Integrative Bioinformatics |
author_facet |
Kim Hee Shin Mittenthal Jay E. Caetano-Anollés Gustavo |
author_sort |
Kim Hee Shin |
title |
Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution |
title_short |
Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution |
title_full |
Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution |
title_fullStr |
Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution |
title_full_unstemmed |
Widespread Recruitment of Ancient Domain Structures in Modern Enzymes during Metabolic Evolution |
title_sort |
widespread recruitment of ancient domain structures in modern enzymes during metabolic evolution |
publisher |
De Gruyter |
series |
Journal of Integrative Bioinformatics |
issn |
1613-4516 |
publishDate |
2013-03-01 |
description |
Protein domains sometime combine to form multidomain proteins and are acquired or lost in lineages of organisms. These processes are ubiquitous in modern metabolism. To sort out evolutionary patterns of domain recruitment, we developed an algorithm that derives the most plausible ancestry of an enzyme from structural and evolutionary annotations in the MANET database. We applied this algorithm to the analysis of 1,163 enzymes with structural assignments. We then counted the number of enzymes along a time series and analyzed enzyme distribution in organisms belonging to superkingdoms Archaea, Bacteria, and Eukarya. The generated timelines described the evolution of modern metabolic networks and showed an early build-up of metabolic activities associated with metabolism of nucleotides, cofactors, and vitamins, followed by enzymes involved in carbohydrate and amino acid metabolism. More importantly, we find that existing domain structures were pervasively co-opted to perform more modern enzymatic tasks, either singly or in combination with other domains. This occurred differentially in lineages of the superkingdoms as the world diversified and organisms adapted to various environments. Our results highlight the important role of recruitment and domain organization in metabolic evolution. |
url |
https://doi.org/10.2390/biecoll-jib-2013-214 |
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