Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes

Payam Ghiaci, Paula Jouhten, Nikolay Martyushenko, Helena Roca-Mesa, Jennifer Vázquez, Dimitrios Konstantinidis, Simon Stenberg, Sergej Andrejev, Kristina Grkovska, Albert Mas, Gemma Beltran, Eivind Almaas*, Kiran R. Patil*, Jonas Warringer*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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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 104 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.

Original languageEnglish
Pages (from-to)1109-1133
Number of pages25
JournalMOLECULAR SYSTEMS BIOLOGY
Volume20
Issue number10
Early online date22 Aug 2024
DOIs
Publication statusPublished - 3 Oct 2024
MoE publication typeA1 Journal article-refereed

Keywords

  • Evolutionary Engineering
  • Experimental Evolution
  • Fermentation
  • Metabolism
  • Yeast

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