ΔΔ<i>G</i> Method for Elucidating Key Control Reactions from Relative Quantification Metabolome Data: Comparative Analysis of Yeast Glycolysis

This study introduces the ΔΔ<i>G</i> method, a novel approach to analyzing metabolic regulation using relative quantification metabolome data. The method calculates shifts in the Gibbs free energy change (Δ<i>G</i>) in two different metabolic states. Subsequently, key reactions controlling the metabolic flux can be identified by comparing the ΔΔ<i>G</i> values to the reaction rates. Two case studies demonstrated the applicability of this method. First, a metabolome data set was obtained from the wild-type and single-gene-deletion mutant strains of <i>Saccharomyces cerevisiae</i>. The ΔΔ<i>G</i> values of the glycolytic reactions were calculated between those of the wild-type and each mutant strain. A positive correlation was observed between the ΔΔ<i>G</i> values of phosphofructokinase (PFK) and the approximate glycolytic flux levels. These results suggested that PFK regulates glycolytic flux. Moreover, a comparison between <i>S. cerevisiae</i> (Crabtree-positive yeast) and <i>Kluyveromyces marxianus</i> (Crabtree-negative yeast) revealed that <i>S. cerevisiae</i> primarily regulates glycolysis through PFK, whereas <i>K. marxianus</i> employs a more distributed control. The ΔΔ<i>G</i> method provides insights into metabolic regulation that are not apparent from metabolite profiles alone and is applicable to various biological systems, particularly for analyzing glycolysis. Furthermore, the simplicity of this method makes it a valuable tool for metabolic engineering and medical research.

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Publication Details

Journal
Analytical Chemistry
Published
2025-03-22
DOI
https://doi.org/10.1021/acs.analchem.4c04480
Citations
1
Primary Topic
Microbial Metabolic Engineering and Bioproduction
Type
article
Field-Weighted Citation Impact
0.81

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article

ΔΔG Method for Elucidating Key Control Reactions from Relative Quantification Metabolome Data: Comparative Analysis of Yeast Glycolysis

Nobuyuki Okahashi, Akiko Kamiyama, Taisuke Seike, Fumio Matsuda et al.
1 citations
Analytical Chemistry
Microbial Metabolic Engineering and Bioproduction
0.81
article

ΔΔG Method for Elucidating Key Control Reactions from Relative Quantification Metabolome Data: Comparative Analysis of Yeast Glycolysis

Nobuyuki Okahashi, Akiko Kamiyama, Taisuke Seike, Fumio Matsuda, Kazuki Yamasaki
article en
1 citations

Abstract

This study introduces the ΔΔ<i>G</i> method, a novel approach to analyzing metabolic regulation using relative quantification metabolome data. The method calculates shifts in the Gibbs free energy change (Δ<i>G</i>) in two different metabolic states. Subsequently, key reactions controlling the metabolic flux can be identified by comparing the ΔΔ<i>G</i> values to the reaction rates. Two case studies demonstrated the applicability of this method. First, a metabolome data set was obtained from the wild-type and single-gene-deletion mutant strains of <i>Saccharomyces cerevisiae</i>. The ΔΔ<i>G</i> values of the glycolytic reactions were calculated between those of the wild-type and each mutant strain. A positive correlation was observed between the ΔΔ<i>G</i> values of phosphofructokinase (PFK) and the approximate glycolytic flux levels. These results suggested that PFK regulates glycolytic flux. Moreover, a comparison between <i>S. cerevisiae</i> (Crabtree-positive yeast) and <i>Kluyveromyces marxianus</i> (Crabtree-negative yeast) revealed that <i>S. cerevisiae</i> primarily regulates glycolysis through PFK, whereas <i>K. marxianus</i> employs a more distributed control. The ΔΔ<i>G</i> method provides insights into metabolic regulation that are not apparent from metabolite profiles alone and is applicable to various biological systems, particularly for analyzing glycolysis. Furthermore, the simplicity of this method makes it a valuable tool for metabolic engineering and medical research.

Analytical ChemistryVol. 97(12)
Shimadzu (Japan) (JP), The University of Osaka (JP)
Japan Society for the Promotion of Science, Japan Science and Technology Agency
Affordable and clean energy
Openalex Percentile: Top 30%
Microbial Metabolic Engineering and Bioproduction
0.81
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