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Barkman TJ. Applications of ancestral sequence reconstruction for understanding the evolution of plant specialized metabolism. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230348. [PMID: 39343033 PMCID: PMC11439504 DOI: 10.1098/rstb.2023.0348] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/10/2024] [Accepted: 04/15/2024] [Indexed: 10/01/2024] Open
Abstract
Studies of enzymes in modern-day plants have documented the diversity of metabolic activities retained by species today but only provide limited insight into how those properties evolved. Ancestral sequence reconstruction (ASR) is an approach that provides statistical estimates of ancient plant enzyme sequences which can then be resurrected to test hypotheses about the evolution of catalytic activities and pathway assembly. Here, I review the insights that have been obtained using ASR to study plant metabolism and highlight important methodological aspects. Overall, studies of resurrected plant enzymes show that (i) exaptation is widespread such that even low or undetectable levels of ancestral activity with a substrate can later become the apparent primary activity of descendant enzymes, (ii) intramolecular epistasis may or may not limit evolutionary paths towards catalytic or substrate preference switches, and (iii) ancient pathway flux often differs from modern-day metabolic networks. These and other insights gained from ASR would not have been possible using only modern-day sequences. Future ASR studies characterizing entire ancestral metabolic networks as well as those that link ancient structures with enzymatic properties should continue to provide novel insights into how the chemical diversity of plants evolved. This article is part of the theme issue 'The evolution of plant metabolism'.
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Affiliation(s)
- Todd J. Barkman
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI49008, USA
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Catania EM, Dubs NM, Soumen S, Barkman TJ. The Mutational Road not Taken: Using Ancestral Sequence Resurrection to Evaluate the Evolution of Plant Enzyme Substrate Preferences. Genome Biol Evol 2024; 16:evae016. [PMID: 38290535 PMCID: PMC10853004 DOI: 10.1093/gbe/evae016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 01/19/2024] [Indexed: 02/01/2024] Open
Abstract
We investigated the flowering plant salicylic acid methyl transferase (SAMT) enzyme lineage to understand the evolution of substrate preference change. Previous studies indicated that a single amino acid replacement to the SAMT active site (H150M) was sufficient to change ancestral enzyme substrate preference from benzoic acid to the structurally similar substrate, salicylic acid (SA). Yet, subsequent studies have shown that the H150M function-changing replacement did not likely occur during the historical episode of enzymatic divergence studied. Therefore, we reinvestigated the origin of SA methylation preference here and additionally assessed the extent to which epistasis may act to limit mutational paths. We found that the SAMT lineage of enzymes acquired preference to methylate SA from an ancestor that preferred to methylate benzoic acid as previously reported. In contrast, we found that a different amino acid replacement, Y267Q, was sufficient to change substrate preference with others providing small positive-magnitude epistatic improvements. We show that the kinetic basis for the ancestral enzymatic change in substate preference by Y267Q appears to be due to both a reduced specificity constant, kcat/KM, for benzoic acid and an improvement in KM for SA. Therefore, this lineage of enzymes appears to have had multiple mutational paths available to achieve the same evolutionary divergence. While the reasons remain unclear for why one path was taken, and the other was not, the mutational distance between ancestral and descendant codons may be a factor.
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Affiliation(s)
- Emily M Catania
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI 49008, USA
| | - Nicole M Dubs
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI 49008, USA
| | - Shejal Soumen
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI 49008, USA
| | - Todd J Barkman
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI 49008, USA
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Li X, Karpac J. A distinct Acyl-CoA binding protein (ACBP6) shapes tissue plasticity during nutrient adaptation in Drosophila. Nat Commun 2023; 14:7599. [PMID: 37989752 PMCID: PMC10663470 DOI: 10.1038/s41467-023-43362-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 11/08/2023] [Indexed: 11/23/2023] Open
Abstract
Nutrient availability is a major selective force in the evolution of metazoa, and thus plasticity in tissue function and morphology is shaped by adaptive responses to nutrient changes. Utilizing Drosophila, we reveal that distinct calibration of acyl-CoA metabolism, mediated by Acbp6 (Acyl-CoA binding-protein 6), is critical for nutrient-dependent tissue plasticity. Drosophila Acbp6, which arose by evolutionary duplication and binds acyl-CoA to tune acetyl-CoA metabolism, is required for intestinal resizing after nutrient deprivation through activating intestinal stem cell proliferation from quiescence. Disruption of acyl-CoA metabolism by Acbp6 attenuation drives aberrant 'switching' of metabolic networks in intestinal enterocytes during nutrient adaptation, impairing acetyl-CoA metabolism and acetylation amid intestinal resizing. We also identified STAT92e, whose function is influenced by acetyl-CoA levels, as a key regulator of acyl-CoA and nutrient-dependent changes in stem cell activation. These findings define a regulatory mechanism, shaped by acyl-CoA metabolism, that adjusts proliferative homeostasis to coordinately regulate tissue plasticity during nutrient adaptation.
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Affiliation(s)
- Xiaotong Li
- Department of Cell Biology and Genetics, Texas A&M University, School of Medicine, Bryan, TX, USA
| | - Jason Karpac
- Department of Cell Biology and Genetics, Texas A&M University, School of Medicine, Bryan, TX, USA.
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Lu M, Feau N, Vidakovic DO, Ukrainetz N, Wong B, Aitken SN, Hamelin RC, Yeaman S. Comparative Gene Expression Analysis Reveals Mechanism of Pinus contorta Response to the Fungal Pathogen Dothistroma septosporum. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2021; 34:397-409. [PMID: 33258711 DOI: 10.1094/mpmi-10-20-0282-r] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Many conifers have distributions that span wide ranges in both biotic and abiotic conditions, but the basis of response to biotic stress has received much less attention than response to abiotic stress. In this study, we investigated the gene expression response of lodgepole pine (Pinus contorta) to attack by the fungal pathogen Dothistroma septosporum, which causes Dothistroma needle blight, a disease that has caused severe climate-related outbreaks in northwestern British Columbia. We inoculated tolerant and susceptible pines with two D. septosporum isolates and analyzed the differentially expressed genes (DEGs), differential exon usage, and coexpressed gene modules using RNA-sequencing data. We found a rapid and strong transcriptomic response in tolerant lodgepole pine samples inoculated with one D. septosporum isolate, and a late and weak response in susceptible samples inoculated with another isolate. We mapped 43 of the DEG- or gene module-identified genes to the reference plant-pathogen interaction pathway deposited in the Kyoto Encyclopedia of Genes and Genomes database. These genes are present in PAMP-triggered and effector-triggered immunity pathways. Genes comprising pathways and gene modules had signatures of strong selective constraint, while the highly expressed genes in tolerant samples appear to have been favored by selection to counterattack the pathogen. We identified candidate resistance genes that may respond to D. septosporum effectors. Taken together, our results show that gene expression response to D. septosporum infection in lodgepole pine varies both among tree genotypes and pathogen strains and involves both known candidate genes and a number of genes with previously unknown functions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Mengmeng Lu
- Department of Biological Sciences, University of Calgary, 507 Campus Drive NW, Calgary, Canada
| | - Nicolas Feau
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Dragana Obreht Vidakovic
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Nicholas Ukrainetz
- Forest Improvement and Research Management Branch, Ministry of Forests, Lands and Natural Resource Operations & Rural Development, 18793-32nd Ave., Surrey, Canada
| | - Barbara Wong
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Pavillon Charles-Eugène-Marchand 1030, avenue de la Médecine, Québec, Canada
| | - Sally N Aitken
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
| | - Richard C Hamelin
- Department of Forest and Conservation Sciences, University of British Columbia, 3041-2424 Main Mall, Vancouver, Canada
- Institut de Biologie Intégrative et des Systèmes, Université Laval, Pavillon Charles-Eugène-Marchand 1030, avenue de la Médecine, Québec, Canada
| | - Sam Yeaman
- Department of Biological Sciences, University of Calgary, 507 Campus Drive NW, Calgary, Canada
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O'Donnell AJ, Huang R, Barboline JJ, Barkman TJ. Convergent Biochemical Pathways for Xanthine Alkaloid Production in Plants Evolved from Ancestral Enzymes with Different Catalytic Properties. Mol Biol Evol 2021; 38:2704-2714. [PMID: 33662138 PMCID: PMC8233510 DOI: 10.1093/molbev/msab059] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Convergent evolution is widespread but the extent to which common ancestral conditions are necessary to facilitate the independent acquisition of similar traits remains unclear. In order to better understand how ancestral biosynthetic catalytic capabilities might lead to convergent evolution of similar modern-day biochemical pathways, we resurrected ancient enzymes of the caffeine synthase (CS) methyltransferases that are responsible for theobromine and caffeine production in flowering plants. Ancestral CS enzymes of Theobroma, Paullinia, and Camellia exhibited similar substrate preferences but these resulted in the formation of different sets of products. From these ancestral enzymes, descendants with similar substrate preference and product formation independently evolved after gene duplication events in Theobroma and Paullinia. Thus, it appears that the convergent modern-day pathways likely originated from ancestral pathways with different inferred flux. Subsequently, the modern-day enzymes originated independently via gene duplication and their convergent catalytic characteristics evolved to partition the multiple ancestral activities by different mutations that occurred in homologous regions of the ancestral proteins. These results show that even when modern-day pathways and recruited genes are similar, the antecedent conditions may be distinctive such that different evolutionary steps are required to generate convergence.
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Affiliation(s)
- Andrew J O'Donnell
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI, USA
| | - Ruiqi Huang
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI, USA
| | - Jessica J Barboline
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI, USA
| | - Todd J Barkman
- Department of Biological Sciences, Western Michigan University, Kalamazoo, MI, USA
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Selberg AGA, Gaucher EA, Liberles DA. Ancestral Sequence Reconstruction: From Chemical Paleogenetics to Maximum Likelihood Algorithms and Beyond. J Mol Evol 2021; 89:157-164. [PMID: 33486547 PMCID: PMC7828096 DOI: 10.1007/s00239-021-09993-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 01/04/2021] [Indexed: 12/13/2022]
Abstract
As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.
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Affiliation(s)
- Avery G A Selberg
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA
| | - Eric A Gaucher
- Department of Biology, Georgia State University, Atlanta, GA, 30303, USA
| | - David A Liberles
- Department of Biology and Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA, 19122, USA.
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