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Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae

Heme is an oxygen carrier and a cofactor of both industrial enzymes and food additives. The intracellular level of free heme is low, which limits the synthesis of heme proteins. Therefore, increasing heme synthesis allows an increased production of heme proteins. Using the genome-scale metabolic mod...

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Autores principales: Ishchuk, Olena P., Domenzain, Iván, Sánchez, Benjamín J., Muñiz-Paredes, Facundo, Martínez, José L., Nielsen, Jens, Petranovic, Dina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335255/
https://www.ncbi.nlm.nih.gov/pubmed/35858410
http://dx.doi.org/10.1073/pnas.2108245119
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author Ishchuk, Olena P.
Domenzain, Iván
Sánchez, Benjamín J.
Muñiz-Paredes, Facundo
Martínez, José L.
Nielsen, Jens
Petranovic, Dina
author_facet Ishchuk, Olena P.
Domenzain, Iván
Sánchez, Benjamín J.
Muñiz-Paredes, Facundo
Martínez, José L.
Nielsen, Jens
Petranovic, Dina
author_sort Ishchuk, Olena P.
collection PubMed
description Heme is an oxygen carrier and a cofactor of both industrial enzymes and food additives. The intracellular level of free heme is low, which limits the synthesis of heme proteins. Therefore, increasing heme synthesis allows an increased production of heme proteins. Using the genome-scale metabolic model (GEM) Yeast8 for the yeast Saccharomyces cerevisiae, we identified fluxes potentially important to heme synthesis. With this model, in silico simulations highlighted 84 gene targets for balancing biomass and increasing heme production. Of those identified, 76 genes were individually deleted or overexpressed in experiments. Empirically, 40 genes individually increased heme production (up to threefold). Heme was increased by modifying target genes, which not only included the genes involved in heme biosynthesis, but also those involved in glycolysis, pyruvate, Fe-S clusters, glycine, and succinyl-coenzyme A (CoA) metabolism. Next, we developed an algorithmic method for predicting an optimal combination of these genes by using the enzyme-constrained extension of the Yeast8 model, ecYeast8. The computationally identified combination for enhanced heme production was evaluated using the heme ligand-binding biosensor (Heme-LBB). The positive targets were combined using CRISPR-Cas9 in the yeast strain (IMX581-HEM15-HEM14-HEM3-Δshm1-HEM2-Δhmx1-FET4-Δgcv2-HEM1-Δgcv1-HEM13), which produces 70-fold-higher levels of intracellular heme.
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spelling pubmed-93352552022-07-30 Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae Ishchuk, Olena P. Domenzain, Iván Sánchez, Benjamín J. Muñiz-Paredes, Facundo Martínez, José L. Nielsen, Jens Petranovic, Dina Proc Natl Acad Sci U S A Biological Sciences Heme is an oxygen carrier and a cofactor of both industrial enzymes and food additives. The intracellular level of free heme is low, which limits the synthesis of heme proteins. Therefore, increasing heme synthesis allows an increased production of heme proteins. Using the genome-scale metabolic model (GEM) Yeast8 for the yeast Saccharomyces cerevisiae, we identified fluxes potentially important to heme synthesis. With this model, in silico simulations highlighted 84 gene targets for balancing biomass and increasing heme production. Of those identified, 76 genes were individually deleted or overexpressed in experiments. Empirically, 40 genes individually increased heme production (up to threefold). Heme was increased by modifying target genes, which not only included the genes involved in heme biosynthesis, but also those involved in glycolysis, pyruvate, Fe-S clusters, glycine, and succinyl-coenzyme A (CoA) metabolism. Next, we developed an algorithmic method for predicting an optimal combination of these genes by using the enzyme-constrained extension of the Yeast8 model, ecYeast8. The computationally identified combination for enhanced heme production was evaluated using the heme ligand-binding biosensor (Heme-LBB). The positive targets were combined using CRISPR-Cas9 in the yeast strain (IMX581-HEM15-HEM14-HEM3-Δshm1-HEM2-Δhmx1-FET4-Δgcv2-HEM1-Δgcv1-HEM13), which produces 70-fold-higher levels of intracellular heme. National Academy of Sciences 2022-07-18 2022-07-26 /pmc/articles/PMC9335255/ /pubmed/35858410 http://dx.doi.org/10.1073/pnas.2108245119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Ishchuk, Olena P.
Domenzain, Iván
Sánchez, Benjamín J.
Muñiz-Paredes, Facundo
Martínez, José L.
Nielsen, Jens
Petranovic, Dina
Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title_full Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title_fullStr Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title_full_unstemmed Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title_short Genome-scale modeling drives 70-fold improvement of intracellular heme production in Saccharomyces cerevisiae
title_sort genome-scale modeling drives 70-fold improvement of intracellular heme production in saccharomyces cerevisiae
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335255/
https://www.ncbi.nlm.nih.gov/pubmed/35858410
http://dx.doi.org/10.1073/pnas.2108245119
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