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Wang JJT, Steenwyk JL, Brem RB. Natural trait variation across Saccharomycotina species. FEMS Yeast Res 2024; 24:foae002. [PMID: 38218591 PMCID: PMC10833146 DOI: 10.1093/femsyr/foae002] [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: 06/27/2023] [Revised: 10/13/2023] [Accepted: 01/12/2024] [Indexed: 01/15/2024] Open
Abstract
Among molecular biologists, the group of fungi called Saccharomycotina is famous for its yeasts. These yeasts in turn are famous for what they have in common-genetic, biochemical, and cell-biological characteristics that serve as models for plants and animals. But behind the apparent homogeneity of Saccharomycotina species lie a wealth of differences. In this review, we discuss traits that vary across the Saccharomycotina subphylum. We describe cases of bright pigmentation; a zoo of cell shapes; metabolic specialties; and species with unique rules of gene regulation. We discuss the genetics of this diversity and why it matters, including insights into basic evolutionary principles with relevance across Eukarya.
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Affiliation(s)
- Johnson J -T Wang
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Jacob L Steenwyk
- Howard Hughes Medical Institute and Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Rachel B Brem
- Department of Plant and Microbial Biology, University of California, Berkeley, Berkeley, CA 94720, USA
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2
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Contributions of Adaptive Laboratory Evolution towards the Enhancement of the Biotechnological Potential of Non-Conventional Yeast Species. J Fungi (Basel) 2023; 9:jof9020186. [PMID: 36836301 PMCID: PMC9964053 DOI: 10.3390/jof9020186] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 01/19/2023] [Accepted: 01/29/2023] [Indexed: 02/04/2023] Open
Abstract
Changes in biological properties over several generations, induced by controlling short-term evolutionary processes in the laboratory through selective pressure, and whole-genome re-sequencing, help determine the genetic basis of microorganism's adaptive laboratory evolution (ALE). Due to the versatility of this technique and the imminent urgency for alternatives to petroleum-based strategies, ALE has been actively conducted for several yeasts, primarily using the conventional species Saccharomyces cerevisiae, but also non-conventional yeasts. As a hot topic at the moment since genetically modified organisms are a debatable subject and a global consensus on their employment has not yet been attained, a panoply of new studies employing ALE approaches have emerged and many different applications have been exploited in this context. In the present review, we gathered, for the first time, relevant studies showing the ALE of non-conventional yeast species towards their biotechnological improvement, cataloging them according to the aim of the study, and comparing them considering the species used, the outcome of the experiment, and the employed methodology. This review sheds light on the applicability of ALE as a powerful tool to enhance species features and improve their performance in biotechnology, with emphasis on the non-conventional yeast species, as an alternative or in combination with genome editing approaches.
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Lu H, Li F, Yuan L, Domenzain I, Yu R, Wang H, Li G, Chen Y, Ji B, Kerkhoven EJ, Nielsen J. Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection. Mol Syst Biol 2021; 17:e10427. [PMID: 34676984 PMCID: PMC8532513 DOI: 10.15252/msb.202110427] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 10/02/2021] [Accepted: 10/04/2021] [Indexed: 12/24/2022] Open
Abstract
Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.
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Affiliation(s)
- Hongzhong Lu
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Feiran Li
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Le Yuan
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Iván Domenzain
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Rosemary Yu
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Hao Wang
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- National Bioinformatics Infrastructure SwedenScience for Life LaboratoryChalmers University of TechnologyGothenburgSweden
| | - Gang Li
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Yu Chen
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Boyang Ji
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- The Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkLyngbyDenmark
| | - Eduard J Kerkhoven
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
| | - Jens Nielsen
- Department of Biology and Biological EngineeringChalmers University of TechnologyGothenburgSweden
- The Novo Nordisk Foundation Center for BiosustainabilityTechnical University of DenmarkLyngbyDenmark
- BioInnovation InstituteCopenhagen NDenmark
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Victorino da Silva Amatto I, Gonsales da Rosa-Garzon N, Antônio de Oliveira Simões F, Santiago F, Pereira da Silva Leite N, Raspante Martins J, Cabral H. Enzyme engineering and its industrial applications. Biotechnol Appl Biochem 2021; 69:389-409. [PMID: 33555054 DOI: 10.1002/bab.2117] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/18/2021] [Indexed: 01/03/2023]
Abstract
Recently, there has been an increase in the demand for enzymes with modified activity, specificity, and stability. Enzyme engineering is an important tool to meet the demand for enzymes adjusted to different industrial processes. Knowledge of the structure and function of enzymes guides the choice of the best strategy for engineering enzymes. Each enzyme engineering strategy, such as rational design, directed evolution, and semi-rational design, has specific applications, as well as limitations, which must be considered when choosing a suitable strategy. Engineered enzymes can be optimized for different industrial applications by choosing the appropriate strategy. This review features engineered enzymes that have been applied in food, animal feed, pharmaceuticals, medical applications, bioremediation, biofuels, and detergents.
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Affiliation(s)
- Isabela Victorino da Silva Amatto
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Biosciences and Biotechnology Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Nathalia Gonsales da Rosa-Garzon
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Flávio Antônio de Oliveira Simões
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Pharmaceutical Sciences Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Fernanda Santiago
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Biosciences and Biotechnology Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Nathália Pereira da Silva Leite
- Pharmaceutical Sciences Program, Faculty of Philosophy, Sciences and Letters at Ribeirão Preto, XUniversity of São Paulo, Ribeirão Preto, SP, Brazil
| | - Júlia Raspante Martins
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Biosciences and Biotechnology Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Hamilton Cabral
- Department of Pharmaceutical Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Biosciences and Biotechnology Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil.,Pharmaceutical Sciences Program, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
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Tiukova IA, Pettersson ME, Hoeppner MP, Olsen RA, Käller M, Nielsen J, Dainat J, Lantz H, Söderberg J, Passoth V. Chromosomal genome assembly of the ethanol production strain CBS 11270 indicates a highly dynamic genome structure in the yeast species Brettanomyces bruxellensis. PLoS One 2019; 14:e0215077. [PMID: 31042716 PMCID: PMC6493715 DOI: 10.1371/journal.pone.0215077] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Accepted: 03/26/2019] [Indexed: 12/30/2022] Open
Abstract
Here, we present the genome of the industrial ethanol production strain Brettanomyces bruxellensis CBS 11270. The nuclear genome was found to be diploid, containing four chromosomes with sizes of ranging from 2.2 to 4.0 Mbp. A 75 Kbp mitochondrial genome was also identified. Comparing the homologous chromosomes, we detected that 0.32% of nucleotides were polymorphic, i.e. formed single nucleotide polymorphisms (SNPs), 40.6% of them were found in coding regions (i.e. 0.13% of all nucleotides formed SNPs and were in coding regions). In addition, 8,538 indels were found. The total number of protein coding genes was 4897, of them, 4,284 were annotated on chromosomes; and the mitochondrial genome contained 18 protein coding genes. Additionally, 595 genes, which were annotated, were on contigs not associated with chromosomes. A number of genes was duplicated, most of them as tandem repeats, including a six-gene cluster located on chromosome 3. There were also examples of interchromosomal gene duplications, including a duplication of a six-gene cluster, which was found on both chromosomes 1 and 4. Gene copy number analysis suggested loss of heterozygosity for 372 genes. This may reflect adaptation to relatively harsh but constant conditions of continuous fermentation. Analysis of gene topology showed that most of these losses occurred in clusters of more than one gene, the largest cluster comprising 33 genes. Comparative analysis against the wine isolate CBS 2499 revealed 88,534 SNPs and 8,133 indels. Moreover, when the scaffolds of the CBS 2499 genome assembly were aligned against the chromosomes of CBS 11270, many of them aligned completely, some have chunks aligned to different chromosomes, and some were in fact rearranged. Our findings indicate a highly dynamic genome within the species B. bruxellensis and a tendency towards reduction of gene number in long-term continuous cultivation.
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Affiliation(s)
- Ievgeniia A. Tiukova
- Chalmers University of Technology, Department of Biology and Biological Engineering, Systems and Synthetic Biology, Göteborg, Sweden
- Swedish University of Agricultural Sciences, Department of Molecular Sciences, Uppsala, Sweden
| | - Mats E. Pettersson
- Uppsala University, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
| | - Marc P. Hoeppner
- Uppsala University, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
- National Bioinformatics Infrastructure Sweden (NBIS), Uppsala, Sweden
- Christian-Albrechts-University of Kiel, Institute of Clinical Molecular Biology, Kiel, Germany
| | - Remi-Andre Olsen
- Science for Life Laboratory, Division of Gene Technology, School of Biotechnology, Royal Institute of Technology (KTH), Solna, Sweden
| | - Max Käller
- Royal Institute of Technology, Biotechnology and Health, School of Engineering Sciences in Chemistry, SciLifeLab, Stockholm, Sweden
- Stockholm University, Department of Biochemistry and Biophysics, SciLifeLab, Stockholm, Sweden
| | - Jens Nielsen
- Chalmers University of Technology, Department of Biology and Biological Engineering, Systems and Synthetic Biology, Göteborg, Sweden
| | - Jacques Dainat
- Uppsala University, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
- National Bioinformatics Infrastructure Sweden (NBIS), Uppsala, Sweden
| | - Henrik Lantz
- Uppsala University, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
- National Bioinformatics Infrastructure Sweden (NBIS), Uppsala, Sweden
| | - Jonas Söderberg
- Uppsala University, Department of Cell and Molecular Biology, Molecular Evolution, Uppsala, Sweden
| | - Volkmar Passoth
- Swedish University of Agricultural Sciences, Department of Molecular Sciences, Uppsala, Sweden
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