Cargando…

Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum

BACKGROUND: Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the pro...

Descripción completa

Detalles Bibliográficos
Autores principales: Halle, Lars, Hollmann, Niels, Tenhaef, Niklas, Mbengi, Lea, Glitz, Christiane, Wiechert, Wolfgang, Polen, Tino, Baumgart, Meike, Bott, Michael, Noack, Stephan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483779/
https://www.ncbi.nlm.nih.gov/pubmed/37679814
http://dx.doi.org/10.1186/s12934-023-02180-5
_version_ 1785102456354504704
author Halle, Lars
Hollmann, Niels
Tenhaef, Niklas
Mbengi, Lea
Glitz, Christiane
Wiechert, Wolfgang
Polen, Tino
Baumgart, Meike
Bott, Michael
Noack, Stephan
author_facet Halle, Lars
Hollmann, Niels
Tenhaef, Niklas
Mbengi, Lea
Glitz, Christiane
Wiechert, Wolfgang
Polen, Tino
Baumgart, Meike
Bott, Michael
Noack, Stephan
author_sort Halle, Lars
collection PubMed
description BACKGROUND: Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation. RESULTS: Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmol(EtOH) g(CDW)(−1) h(−1) and a growth rate of 0.15 ± 0.01 h(−1) in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements. CONCLUSIONS: The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12934-023-02180-5.
format Online
Article
Text
id pubmed-10483779
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-104837792023-09-08 Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum Halle, Lars Hollmann, Niels Tenhaef, Niklas Mbengi, Lea Glitz, Christiane Wiechert, Wolfgang Polen, Tino Baumgart, Meike Bott, Michael Noack, Stephan Microb Cell Fact Research BACKGROUND: Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation. RESULTS: Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmol(EtOH) g(CDW)(−1) h(−1) and a growth rate of 0.15 ± 0.01 h(−1) in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements. CONCLUSIONS: The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12934-023-02180-5. BioMed Central 2023-09-07 /pmc/articles/PMC10483779/ /pubmed/37679814 http://dx.doi.org/10.1186/s12934-023-02180-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Halle, Lars
Hollmann, Niels
Tenhaef, Niklas
Mbengi, Lea
Glitz, Christiane
Wiechert, Wolfgang
Polen, Tino
Baumgart, Meike
Bott, Michael
Noack, Stephan
Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title_full Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title_fullStr Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title_full_unstemmed Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title_short Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum
title_sort robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by corynebacterium glutamicum
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483779/
https://www.ncbi.nlm.nih.gov/pubmed/37679814
http://dx.doi.org/10.1186/s12934-023-02180-5
work_keys_str_mv AT hallelars roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT hollmannniels roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT tenhaefniklas roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT mbengilea roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT glitzchristiane roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT wiechertwolfgang roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT polentino roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT baumgartmeike roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT bottmichael roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum
AT noackstephan roboticworkflowsforautomatedlongtermadaptivelaboratoryevolutionimprovingethanolutilizationbycorynebacteriumglutamicum