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Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation

BACKGROUND: Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shiftin...

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Autores principales: Wehrs, Maren, Thompson, Mitchell G., Banerjee, Deepanwita, Prahl, Jan-Philip, Morella, Norma M., Barcelos, Carolina A., Moon, Jadie, Costello, Zak, Keasling, Jay D., Shih, Patrick M., Tanjore, Deepti, Mukhopadhyay, Aindrila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437010/
https://www.ncbi.nlm.nih.gov/pubmed/32811554
http://dx.doi.org/10.1186/s12934-020-01423-z
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author Wehrs, Maren
Thompson, Mitchell G.
Banerjee, Deepanwita
Prahl, Jan-Philip
Morella, Norma M.
Barcelos, Carolina A.
Moon, Jadie
Costello, Zak
Keasling, Jay D.
Shih, Patrick M.
Tanjore, Deepti
Mukhopadhyay, Aindrila
author_facet Wehrs, Maren
Thompson, Mitchell G.
Banerjee, Deepanwita
Prahl, Jan-Philip
Morella, Norma M.
Barcelos, Carolina A.
Moon, Jadie
Costello, Zak
Keasling, Jay D.
Shih, Patrick M.
Tanjore, Deepti
Mukhopadhyay, Aindrila
author_sort Wehrs, Maren
collection PubMed
description BACKGROUND: Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance. RESULTS: We find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses. CONCLUSIONS: Our results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions.
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spelling pubmed-74370102020-08-20 Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation Wehrs, Maren Thompson, Mitchell G. Banerjee, Deepanwita Prahl, Jan-Philip Morella, Norma M. Barcelos, Carolina A. Moon, Jadie Costello, Zak Keasling, Jay D. Shih, Patrick M. Tanjore, Deepti Mukhopadhyay, Aindrila Microb Cell Fact Research BACKGROUND: Despite the latest advancements in metabolic engineering for genome editing and characterization of host performance, the successful development of robust cell factories used for industrial bioprocesses and accurate prediction of the behavior of microbial systems, especially when shifting from laboratory-scale to industrial conditions, remains challenging. To increase the probability of success of a scale-up process, data obtained from thoroughly performed studies mirroring cellular responses to typical large-scale stimuli may be used to derive crucial information to better understand potential implications of large-scale cultivation on strain performance. This study assesses the feasibility to employ a barcoded yeast deletion library to assess genome-wide strain fitness across a simulated industrial fermentation regime and aims to understand the genetic basis of changes in strain physiology during industrial fermentation, and the corresponding roles these genes play in strain performance. RESULTS: We find that mutant population diversity is maintained through multiple seed trains, enabling large scale fermentation selective pressures to act upon the community. We identify specific deletion mutants that were enriched in all processes tested in this study, independent of the cultivation conditions, which include MCK1, RIM11, MRK1, and YGK3 that all encode homologues of mammalian glycogen synthase kinase 3 (GSK-3). Ecological analysis of beta diversity between all samples revealed significant population divergence over time and showed feed specific consequences of population structure. Further, we show that significant changes in the population diversity during fed-batch cultivations reflect the presence of significant stresses. Our observations indicate that, for this yeast deletion collection, the selection of the feeding scheme which affects the accumulation of the fermentative by-product ethanol impacts the diversity of the mutant pool to a higher degree as compared to the pH of the culture broth. The mutants that were lost during the time of most extreme population selection suggest that specific biological processes may be required to cope with these specific stresses. CONCLUSIONS: Our results demonstrate the feasibility of Bar-seq to assess fermentation associated stresses in yeast populations under industrial conditions and to understand critical stages of a scale-up process where variability emerges, and selection pressure gets imposed. Overall our work highlights a promising avenue to identify genetic loci and biological stress responses required for fitness under industrial conditions. BioMed Central 2020-08-18 /pmc/articles/PMC7437010/ /pubmed/32811554 http://dx.doi.org/10.1186/s12934-020-01423-z Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wehrs, Maren
Thompson, Mitchell G.
Banerjee, Deepanwita
Prahl, Jan-Philip
Morella, Norma M.
Barcelos, Carolina A.
Moon, Jadie
Costello, Zak
Keasling, Jay D.
Shih, Patrick M.
Tanjore, Deepti
Mukhopadhyay, Aindrila
Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title_full Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title_fullStr Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title_full_unstemmed Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title_short Investigation of Bar-seq as a method to study population dynamics of Saccharomyces cerevisiae deletion library during bioreactor cultivation
title_sort investigation of bar-seq as a method to study population dynamics of saccharomyces cerevisiae deletion library during bioreactor cultivation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437010/
https://www.ncbi.nlm.nih.gov/pubmed/32811554
http://dx.doi.org/10.1186/s12934-020-01423-z
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