Evolution of substrate specificity in a retained enzyme driven by gene loss
- Evolution of Metabolic Diversity Laboratory, Mexico
- Argonne National Laboratory, United States
- University of Texas Health Science Cent, United States
- Weizmann Institute of Science, Israel
- University of California, Berkeley, United States
- Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico
- Centro de Investigación en Matemáticas, Mexico
- University of Texas Health Science Center, United States
Abstract
The connection between gene loss and the functional adaptation of retained proteins is still poorly understood. We apply phylogenomics and metabolic modeling to detect bacterial species that are evolving by gene loss, with the finding that Actinomycetaceae genomes from human cavities are undergoing sizable reductions, including loss of L-histidine and L-tryptophan biosynthesis. We observe that the dual-substrate phosphoribosyl isomerase A or priA gene, at which these pathways converge, appears to coevolve with the occurrence of trp and his genes. Characterization of a dozen PriA homologs shows that these enzymes adapt from bifunctionality in the largest genomes, to a monofunctional, yet not necessarily specialized, inefficient form in genomes undergoing reduction. These functional changes are accomplished via mutations, which result from relaxation of purifying selection, in residues structurally mapped after sequence and X-ray structural analyses. Our results show how gene loss can drive the evolution of substrate specificity from retained enzymes.
Data availability
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The Whole Genome Shotgun (WGS) A. oris MG-1 projectPublicly available at the NCBI Nucleotide (accession no: MAUB00000000).
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Actinomyces oris strain:MG-1 Genome sequencing and assemblyPublicly available at the NCBI BioProject (accession no: PRJNA327886.
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Actinomycetaceae Phylogenomics: Comparative Analysis of ModelsPublicly available, subject to registering an account, at KBase (accession no: ws.17193.obj.1).
Article and author information
Author details
Francisco Barona-Gómez
Funding
Consejo Nacional de Ciencia y Tecnología (132376,179290)
- Ana Lilia Juárez-Vázquez
- Ernesto A Verduzco-Castro
- Julián Santoyo-Flores
- Mauricio Carrillo-Tripp
National Institutes of Health (GM094585)
- Karolina Michalska
- Gyorgy Babnigg
- Michael Endres
- Andrzej Joachimiak
US Department of Energy (DE-AC02-06CH11357)
- Andrzej Joachimiak
- Christopher S Henry
National Science Foundation (1611952)
- Janaka E Edirisinghe
- Christopher S Henry
National Institute of Dental and Craniofacial Research (DE017382)
- Chenggang Wu
- Hung Ton-That
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
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Evolution of substrate specificity in a retained enzyme driven by gene loss
eLife 6:e22679.
https://doi.org/10.7554/eLife.22679
Further reading
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- Biochemistry and Chemical Biology
- Microbiology and Infectious Disease
Teichoic acids (TA) are linear phospho-saccharidic polymers and important constituents of the cell envelope of Gram-positive bacteria, either bound to the peptidoglycan as wall teichoic acids (WTA) or to the membrane as lipoteichoic acids (LTA). The composition of TA varies greatly but the presence of both WTA and LTA is highly conserved, hinting at an underlying fundamental function that is distinct from their specific roles in diverse organisms. We report the observation of a periplasmic space in Streptococcus pneumoniae by cryo-electron microscopy of vitreous sections. The thickness and appearance of this region change upon deletion of genes involved in the attachment of TA, supporting their role in the maintenance of a periplasmic space in Gram-positive bacteria as a possible universal function. Consequences of these mutations were further examined by super-resolved microscopy, following metabolic labeling and fluorophore coupling by click chemistry. This novel labeling method also enabled in-gel analysis of cell fractions. With this approach, we were able to titrate the actual amount of TA per cell and to determine the ratio of WTA to LTA. In addition, we followed the change of TA length during growth phases, and discovered that a mutant devoid of LTA accumulates the membrane-bound polymerized TA precursor.
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- Biochemistry and Chemical Biology
- Computational and Systems Biology
Protein–protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model’s accuracy. We extended our analysis to include interactions between three representative nuage components—Vas, Squ, and Tej—and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.
