Flux balance analysis for ethylene formation in genetically engineered Saccharomyces cerevisiae

ABSTRACT Flux balance analysis and phenotypic data were used to provide clues to the relationships between the activities of gene products and the phenotypes resulting from the deletion of genes involved in respiratory function in Saccharomyces cerevisiae. The effect of partial or complete respiratory deficiency on the ethanol production and growth characteristics of hap4Δ/hap4Δ, mig1Δ/mig1Δ, qdr3Δ/qdr3Δ, pdr3Δ/pdr3Δ, qcr7Δ/qcr7Δ, cyt1Δ/cyt1Δ, and rip1Δ/rip1Δ mutants grown in microaerated chemostats was investigated. The study provided additional evidence for the importance of the selection of a physiologically relevant objective function, and it may improve quantitative predictions of exchange fluxes, as well as qualitative estimations of changes in intracellular fluxes. Ethanol production was successfully predicted by flux balance analysis in the case of the qdr3Δ/qdr3Δ mutant, with maximization of ethanol production as the objective function, suggesting an additional role for Qdr3p in respiration. The absence of similar changes in estimated intracellular fluxes in the qcr7Δ/qcr7Δ mutant compared to the rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants indicated that the effect of the deletion of this subunit of complex III was somehow compensated for. Analysis of predicted flux distributions indicated self-organization of intracellular fluxes to avoid NAD+/NADH imbalance in rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants, but not the qcr7Δ/qcr7Δ mutant. The flux through the glycerol efflux channel, Fps1p, was estimated to be zero in all strains under the investigated conditions. This indicates that previous strategies for improving ethanol production, such as the overexpression of the glutamate synthase gene GLT1 in a GDH1 deletion background or deletion of the glycerol efflux channel gene FPS1 and overexpression of GLT1, are unnecessary in a respiration-deficient background.

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Dynamic flux balance analysis of biomass and lipid production by Antarctic thraustochytrid Oblongichytrium sp. RT2316‐13

Biotechnology and Bioengineering ◽

10.1002/bit.27463 ◽

2020 ◽

Vol 117 (10) ◽

pp. 3006-3017 ◽

Cited By ~ 3

Author(s):

Carolina Shene ◽

Paris Paredes ◽

Liset Flores ◽

Allison Leyton ◽

Juan A. Asenjo ◽

...

Keyword(s):

Flux Balance Analysis ◽

Lipid Production ◽

Dynamic Flux Balance Analysis ◽

Flux Balance ◽

Balance Analysis

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Understanding the host-microbe interactions using metabolic modeling

Microbiome ◽

10.1186/s40168-020-00955-1 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Jack Jansma ◽

Sahar El Aidy

Keyword(s):

Human Health ◽

Flux Balance Analysis ◽

Bacterial Species ◽

Flux Balance ◽

Interaction Field ◽

In Silico Simulation ◽

Balance Analysis ◽

Microbe Interactions ◽

Host Microbe Interactions ◽

Genome Scale

AbstractThe human gut harbors an enormous number of symbiotic microbes, which is vital for human health. However, interactions within the complex microbiota community and between the microbiota and its host are challenging to elucidate, limiting development in the treatment for a variety of diseases associated with microbiota dysbiosis. Using in silico simulation methods based on flux balance analysis, those interactions can be better investigated. Flux balance analysis uses an annotated genome-scale reconstruction of a metabolic network to determine the distribution of metabolic fluxes that represent the complete metabolism of a bacterium in a certain metabolic environment such as the gut. Simulation of a set of bacterial species in a shared metabolic environment can enable the study of the effect of numerous perturbations, such as dietary changes or addition of a probiotic species in a personalized manner. This review aims to introduce to experimental biologists the possible applications of flux balance analysis in the host-microbiota interaction field and discusses its potential use to improve human health.

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Why does yeast ferment? A flux balance analysis study

Biochemical Society Transactions ◽

10.1042/bst0381225 ◽

2010 ◽

Vol 38 (5) ◽

pp. 1225-1229 ◽

Cited By ~ 23

Author(s):

Evangelos Simeonidis ◽

Ettore Murabito ◽

Kieran Smallbone ◽

Hans V. Westerhoff

Keyword(s):

Flux Balance Analysis ◽

Energy Cost ◽

Yeast Fermentation ◽

Minimal Amount ◽

Aerobic Growth ◽

Analysis Study ◽

Flux Balance ◽

Balance Analysis ◽

Genome Scale ◽

Excess Glucose

Advances in biological techniques have led to the availability of genome-scale metabolic reconstructions for yeast. The size and complexity of such networks impose limits on what types of analyses one can perform. Constraint-based modelling overcomes some of these restrictions by using physicochemical constraints to describe the potential behaviour of an organism. FBA (flux balance analysis) highlights flux patterns through a network that serves to achieve a particular objective and requires a minimal amount of data to make quantitative inferences about network behaviour. Even though FBA is a powerful tool for system predictions, its general formulation sometimes results in unrealistic flux patterns. A typical example is fermentation in yeast: ethanol is produced during aerobic growth in excess glucose, but this pattern is not present in a typical FBA solution. In the present paper, we examine the issue of yeast fermentation against respiration during growth. We have studied a number of hypotheses from the modelling perspective, and novel formulations of the FBA approach have been tested. By making the observation that more respiration requires the synthesis of more mitochondria, an energy cost related to mitochondrial synthesis is added to the FBA formulation. Results, although still approximate, are closer to experimental observations than earlier FBA analyses, at least on the issue of fermentation.

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