Author, as appears in the article.: Ghiaci, Payam; Jouhten, Paula; Martyushenko, Nikolay; Roca-Mesa, Helena; Vazquez, Jennifer; Konstantinidis, Dimitrios; Stenberg, Simon; Andrejev, Sergej; Grkovska, Kristina; Mas, Albert; Beltran, Gemma; Almaas, Eivind; Patil, Kiran R; Warringer, Jonas
Department: Bioquímica i Biotecnologia
URV's Author/s: Beltran Casellas, Gemma / Mas Baron, Alberto
Keywords: Adaptation Aneuploidy Beneficial mutations Clonal evolution Diminishing returns Directed molecular evolution Dynamics Epistasis Evolutionary engineering Experimental evolution Fermentatio Fermentation Kudriavzevi Metabolism Phenotype Population Saccharomyces cerevisiae Saccharomyces-cerevisiae Strain Wine Yeast
Abstract: Adaptive Laboratory Evolution (ALE) of microorganisms can improve the efficiency of sustainable industrial processes important to the global economy. However, stochasticity and genetic background effects often lead to suboptimal outcomes during laboratory evolution. Here we report an ALE platform to circumvent these shortcomings through parallelized clonal evolution at an unprecedented scale. Using this platform, we evolved 10(4) yeast populations in parallel from many strains for eight desired wine fermentation-related traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum leading to improved wine yeasts unencumbered by unwanted side effects. At the genomic level, evolutionary gains in metabolic characteristics often coincided with distinct chromosome amplifications and the emergence of side-effect syndromes that were characteristic of each selection niche. Several high-performing ALE strains exhibited desired wine fermentation kinetics when tested in larger liquid cultures, supporting their suitability for application. More broadly, our high-throughput ALE platform opens opportunities for rapid optimization of microbes which otherwise could take many years to accomplish.
Thematic Areas: Agricultural and biological sciences (all) Agricultural and biological sciences (miscellaneous) Applied mathematics Biochemistry & molecular biology Biochemistry, genetics and molecular biology (all) Biochemistry, genetics and molecular biology (miscellaneous) Biotecnología Ciências biológicas ii Computational theory and mathematics General agricultural and biological sciences General biochemistry,genetics and molecular biology General immunology and microbiology General medicine Immunology and microbiology (all) Immunology and microbiology (miscellaneous) Informati Information systems Medicine (miscellaneous)
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: albert.mas@urv.cat gemma.beltran@urv.cat
Author identifier: 0000-0002-0763-1679 0000-0002-7071-205X
Record's date: 2025-01-28
Paper version: info:eu-repo/semantics/publishedVersion
Paper original source: Molecular Systems Biology. 20 (10): 1109-1133
APA: Ghiaci, Payam; Jouhten, Paula; Martyushenko, Nikolay; Roca-Mesa, Helena; Vazquez, Jennifer; Konstantinidis, Dimitrios; Stenberg, Simon; Andrejev, Serg (2024). Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes. Molecular Systems Biology, 20(10), 1109-1133. DOI: 10.1038/s44320-024-00059-0
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Entity: Universitat Rovira i Virgili
Journal publication year: 2024
Publication Type: Journal Publications
Repositori URV