Comparative Metabolic Network Flux Analysis to Identify Differences in Cellular Metabolism

McGarrity, Sarah; Karvelsson, Sigurður Trausti; Sigurjónsson, Ólafur E.; Rolfsson, Óttar

doi:10.1007/978-1-0716-0159-4_11

Cited by 4 publications

(2 citation statements)

References 94 publications

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“…This was followed by random sampling to study the metabolic fluxes with respect to evolution and oxidative stress induction. We then identified the up- and down-regulated reactions (E_LRS5 vs. LRS5 and their corresponding steady states) at cut-off = 1 and FDR <0.05, based on the statistically significant overrepresented genes from the flux enrichment analysis ( McGarrity et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Nowrouzi,

Torres-Montero,

Kerkhoven

et al. 2024

Metabolic Engineering Communications

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Section: Resultsmentioning

confidence: 99%

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Nowrouzi,

Torres-Montero,

Kerkhoven

et al. 2024

Metabolic Engineering Communications

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“…Here, we discuss some fundamental technical principles and applicative aspects of flux analysis by means of labeled substrates. The following references are available for extremely detailed information about theoretical, technical, and data analysis aspects/issues of MFA 105–113 …”

Section: Flux Analysismentioning

confidence: 99%

Investigating metabolism by mass spectrometry: From steady state to dynamic view

et al. 2020

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Metabolism is the set of life‐sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so‐called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady‐state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

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RewiringSaccharomyces cerevisiaemetabolism for optimised Taxol® precursors production

Nowrouzi,

Torres-Montero,

Kerkhoven

et al. 2023

Preprint

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Saccharomyces cerevisiae has been recognised as a convenient host for the production of early precursors to the Taxol anticancer drug. Recent studies have highlighted the harmful impact of oxidative stress as a result of the activity of Taxol first cytochrome P450-reductase enzymes (Taxus spp. CYP725A4-POR). Here, we evolved a new oxidative stress-tolerant yeast strain on galactose, which led to a three-fold higher titre of the CYP725A4 enzyme substrate, taxadiene. We comprehensively analysed the performance of the evolved and parent strain in galactose-limited chemostat cultures before and during oxidative stress induction. Integrating the transcriptomics and metabolite profiling data in an enzyme-constrained genome scale model enabled a more accurate prediction of changes that occurred to biological pathways as a response to/consequence of evolution and oxidative stress. The analyses showed a better performance of the evolved strain with improved respiration and reduced overflow metabolites production. The strain was robust to re-introduction of the oxidative stress, potentially due to the cross-protection mechanism, which contributed to likely better heme, flavin and NADPH availability for an optimal expression of CYP725A4 and POR in yeast. The increased level of taxadiene production has potentially occurred due to the antioxidant properties of taxadiene or as a mechanism to overcome the toxicity of geranylgeranyl diphosphate, the precursor to taxadiene synthase.

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Comparative Metabolic Network Flux Analysis to Identify Differences in Cellular Metabolism

Cited by 4 publications

References 94 publications

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Rewiring Saccharomyces cerevisiae metabolism for optimised Taxol® precursors production

Investigating metabolism by mass spectrometry: From steady state to dynamic view

RewiringSaccharomyces cerevisiaemetabolism for optimised Taxol® precursors production

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