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ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways
The ability to fine tune gene expression has created the field of metabolic pathway optimization and balancing where a variety of factors affecting flux balance are carefully modulated to improve product titers, yields, and productivity. Using a library of isopropyl β-D-1-thiogalactopyranoside (IPTG...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4650668/ https://www.ncbi.nlm.nih.gov/pubmed/26062452 http://dx.doi.org/10.1038/srep11301 |
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author | Jones, J. Andrew Vernacchio, Victoria R. Lachance, Daniel M. Lebovich, Matthew Fu, Li Shirke, Abhijit N. Schultz, Victor L. Cress, Brady Linhardt, Robert J. Koffas, Mattheos A. G. |
author_facet | Jones, J. Andrew Vernacchio, Victoria R. Lachance, Daniel M. Lebovich, Matthew Fu, Li Shirke, Abhijit N. Schultz, Victor L. Cress, Brady Linhardt, Robert J. Koffas, Mattheos A. G. |
author_sort | Jones, J. Andrew |
collection | PubMed |
description | The ability to fine tune gene expression has created the field of metabolic pathway optimization and balancing where a variety of factors affecting flux balance are carefully modulated to improve product titers, yields, and productivity. Using a library of isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible mutant T7 promoters of varied strength a combinatorial method was developed for transcriptional balancing of the violacein pathway. Violacein biosynthesis involves a complex five-gene pathway that is an excellent model for exploratory metabolic engineering efforts into pathway regulation and control due to many colorful intermediates and side products allowing for easy analysis and strain comparison. Upon screening approximately 4% of the total initial library, several high-titer mutants were discovered that resulted in up to a 63-fold improvement over the control strain. With further fermentation optimization, titers were improved to 1829 ± 46 mg/L; a 2.6-fold improvement in titer and a 30-fold improvement in productivity from previous literature reports. |
format | Online Article Text |
id | pubmed-4650668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46506682015-11-24 ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways Jones, J. Andrew Vernacchio, Victoria R. Lachance, Daniel M. Lebovich, Matthew Fu, Li Shirke, Abhijit N. Schultz, Victor L. Cress, Brady Linhardt, Robert J. Koffas, Mattheos A. G. Sci Rep Article The ability to fine tune gene expression has created the field of metabolic pathway optimization and balancing where a variety of factors affecting flux balance are carefully modulated to improve product titers, yields, and productivity. Using a library of isopropyl β-D-1-thiogalactopyranoside (IPTG)-inducible mutant T7 promoters of varied strength a combinatorial method was developed for transcriptional balancing of the violacein pathway. Violacein biosynthesis involves a complex five-gene pathway that is an excellent model for exploratory metabolic engineering efforts into pathway regulation and control due to many colorful intermediates and side products allowing for easy analysis and strain comparison. Upon screening approximately 4% of the total initial library, several high-titer mutants were discovered that resulted in up to a 63-fold improvement over the control strain. With further fermentation optimization, titers were improved to 1829 ± 46 mg/L; a 2.6-fold improvement in titer and a 30-fold improvement in productivity from previous literature reports. Nature Publishing Group 2015-06-11 /pmc/articles/PMC4650668/ /pubmed/26062452 http://dx.doi.org/10.1038/srep11301 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Jones, J. Andrew Vernacchio, Victoria R. Lachance, Daniel M. Lebovich, Matthew Fu, Li Shirke, Abhijit N. Schultz, Victor L. Cress, Brady Linhardt, Robert J. Koffas, Mattheos A. G. ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title | ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title_full | ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title_fullStr | ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title_full_unstemmed | ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title_short | ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways |
title_sort | epathoptimize: a combinatorial approach for transcriptional balancing of metabolic pathways |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4650668/ https://www.ncbi.nlm.nih.gov/pubmed/26062452 http://dx.doi.org/10.1038/srep11301 |
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