Relative flux trade-offs and optimization of metabolic network functionalities

Hashemi, Seirana; Razaghi-Moghadam, Zahra; Laitinen, Roosa A. E.; Nikoloski, Zoran

doi:10.1016/j.csbj.2022.07.038

Cited by 2 publications

(3 citation statements)

References 37 publications

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“…An example of an absolute trade‐off is that involving cell growth and lipid accumulation in microalgae (Mulgund, 2022). However, in the case when the acquisition of the common resource changes, i.e.,

var ()(, T) \neq 0

, the two traits can exhibit negative as well as positive phenotypic correlations, characterizing a relative trade‐off (Hashemi et al, 2022; Figure 1b). A typical example of a relative trade‐off arises in allocation of total carbon assimilated by photosynthesis in microalgae and plants, which can be considered as the common resource,

T

, that varies with the environment; this common resource is then partitioned between growth, respiration and nonstructural components.…”

Section: The Y‐model Explains Resource Acquisition–allocation Trade‐offsmentioning

confidence: 99%

“…More specifically, the approach extends the Y‐model by identifying non‐negative linear combinations of steady‐state reaction rates that amount to the rate of a reaction of fixed flux. This approach has been further extended to enumerate all relative trade‐offs between steady‐state reaction rates that amount to biomass growth (Hashemi et al, 2022). For instance, for the metabolic network in Figure 4a, it must hold at steady state that

\frac{normald c_{2}}{normald t} = v_{1} + v_{6} - v_{2} = 0

, indicating that the presence of a relative trade‐off between reactions

r_{1}

and

r_{6}

or an absolute trade‐off if the flux of reaction

r_{2}

is robust (Figure 4b).…”

Section: Molecular Mechanisms Of Metabolic Trade‐offs At Different Sc...mentioning

confidence: 99%

“…We note that the identification of the trade‐offs with the two constraint‐based approaches allows insights in the space of alternative flux distributions and relationships of more than two fluxes in this space. In addition, due to the specification of trade‐offs as non‐negative linear combinations of fluxes that amount to an objective (e.g., biomass growth), these approaches have also pointed out a relationship between inherent trade‐offs and metabolic engineering strategies aimed at increasing the objective (Hashemi et al, 2022). This follows from the observation that an increase in the flux for any of the reactions in a relative trade‐off must increase the flux of the reaction that determines the trade‐off (Figure 4b).…”

Section: Molecular Mechanisms Of Metabolic Trade‐offs At Different Sc...mentioning

confidence: 99%

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Models and molecular mechanisms for trade‐offs in the context of metabolism

2023

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Accumulating evidence for trade‐offs involving metabolic traits has demonstrated their importance in the evolution of organisms. Metabolic models with different levels of complexity have already been considered when investigating mechanisms that explain various metabolic trade‐offs. Here we provide a systematic review of modelling approaches that have been used to study and explain trade‐offs between: (i) the kinetic properties of individual enzymes, (ii) rates of metabolic reactions, (iii) the rate and yield of metabolic pathways and networks, (iv) different metabolic objectives in single organisms and in metabolic communities, and (v) metabolic concentrations. In providing insights into the mechanisms underlying these five types of metabolic trade‐offs obtained from constraint‐based metabolic modelling, we emphasize the relationship of metabolic trade‐offs to the classical black box Y‐model that provides a conceptual explanation for resource acquisition–allocation trade‐offs. In addition, we identify several pressing concerns and offer a perspective for future research in the identification and manipulation of metabolic trade‐offs by relying on the toolbox provided by constraint‐based metabolic modelling for single organisms and microbial communities.

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var ()(, T) \neq 0

T

, that varies with the environment; this common resource is then partitioned between growth, respiration and nonstructural components.…”

Section: The Y‐model Explains Resource Acquisition–allocation Trade‐offsmentioning

confidence: 99%

\frac{normald c_{2}}{normald t} = v_{1} + v_{6} - v_{2} = 0

, indicating that the presence of a relative trade‐off between reactions

r_{1}

and

r_{6}

or an absolute trade‐off if the flux of reaction

r_{2}

is robust (Figure 4b).…”

Section: Molecular Mechanisms Of Metabolic Trade‐offs At Different Sc...mentioning

confidence: 99%

Section: Molecular Mechanisms Of Metabolic Trade‐offs At Different Sc...mentioning

confidence: 99%

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Models and molecular mechanisms for trade‐offs in the context of metabolism

2023

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Can Rice Growth Substrate Substitute Rapeseed Growth Substrate in Rapeseed Blanket Seedling Technology? Lesson from Reactive Oxygen Species Production and Scavenging Analysis

Yi,

Ren,

Zhang

et al. 2024

Antioxidants

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Rapeseed (Brassica napus L.) seedlings suffering from inappropriate growth substrate stress will present poor seedling quality. However, the regulatory mechanism for the production and scavenging of reactive oxygen species (ROS) caused by this type of stress remains unclear. In the current study, a split plot experiment design was implemented with two crop growth substrates—a rice growth substrate (RIS) and rapeseed growth substrate (RAS)—as the main plot and two genotypes—a hybrid and an open-pollinated variety (Zheyouza 1510 and Zheyou 51, respectively)—as the sub-plot. The seedling quality was assessed, and the ROS production/scavenging capacity was evaluated. Enzymatic and non-enzymatic systems, including ascorbic acid and glutathione metabolism, and RNA-seq data were analyzed under the two growth substrate treatments. The results revealed that rapeseed seedling quality decreased under RIS, with the plant height, maximum leaf length and width, and aboveground dry matter being reduced by 187.7%, 64.6%, 73.2%, and 63.8% on average, respectively, as compared to RAS. The main type of ROS accumulated in rapeseed plants was hydrogen peroxide, which was 47.8% and 14.1% higher under RIS than under RAS in the two genotypes, respectively. The scavenging of hydrogen peroxide in Zheyouza 1510 was the result of a combination of enzymatic systems, with significantly higher peroxidase (POD) and catalase (CAT) activity as well as glutathione metabolism, with significantly higher reduced glutathione (GSH) content, under RAS, while higher oxidized glutathione (GSSH) was observed under RIS. However, the scavenging of hydrogen peroxide in Zheyou 51 was the result of a combination of elevated oxidized ascorbic acid (DHA) under RIS and higher GSH content under RAS. The identified gene expression levels were in accordance with the observed enzyme expression levels. The results suggest that the cost of substituting RAS with RIS is a reduction in rapeseed seedling quality contributing to excessive ROS production and a reduction in ROS scavenging capacity.

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Relative flux trade-offs and optimization of metabolic network functionalities

Cited by 2 publications

References 37 publications

Models and molecular mechanisms for trade‐offs in the context of metabolism

Models and molecular mechanisms for trade‐offs in the context of metabolism

Can Rice Growth Substrate Substitute Rapeseed Growth Substrate in Rapeseed Blanket Seedling Technology? Lesson from Reactive Oxygen Species Production and Scavenging Analysis

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