Metabolites have to diffuse within the sub-cellular compartments they occupy to specific locations where enzymes are, so reactions could occur. Conventional flux balance analysis (FBA), a method based on linear programming that is commonly used to model metabolism, implicitly assumes that all enzymatic reactions are not diffusion-limited though that may not always be the case. In this work, we have developed a spatial method that implements FBA on a grid-based system, to enable the exploration of diffusion effects on metabolism. Specifically, the method discretises a living cell into a two-dimensional grid, represents the metabolic reactions in each grid element as well as the diffusion of metabolites to and from neighbouring elements, and simulates the system as a single linear programming problem. We varied the number of rows and columns in the grid to simulate different cell shapes, and the method was able to capture diffusion effects at different shapes. We then used the method to simulate heterogeneous enzyme distribution, which suggested a theoretical effect on variability at the population level. We propose the use of this method, and its future extensions, to explore how spatiotemporal organisation of sub-cellular compartments and the molecules within could affect cell behaviour.
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http://dx.doi.org/10.1007/s11538-024-01264-6 | DOI Listing |
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State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
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Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden.
Although the separate effects of water and nitrogen (N) limitations on forest growth are well known, the question of how to predict their combined effects remains a challenge for modeling of climate change impacts on forests. Here, we address this challenge by developing a new eco-physiological model that accounts for plasticity in stomatal conductance and leaf N concentration. Based on optimality principle, our model determines stomatal conductance and leaf N concentration by balancing carbon uptake maximization, hydraulic risk and cost of maintaining photosynthetic capacity.
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Laboratory of Ecophysiology and Molecular Evolution, Brazilian National Institute for Research of the Amazon (INPA), Manaus, Brazil.
The tambaqui (Colossoma macropomum, G. Cuvier 1818) thrives both in the ion-poor waters of the Amazon and in commercial aquaculture. In both, environmental conditions can be harsh due to low ion levels, occasional high salt challenges (in aquaculture), low pH, extreme PO levels (hypoxia and hyperoxia), high PCO levels (hypercapnia), high ammonia levels (in aquaculture), and high and low temperatures.
View Article and Find Full Text PDFSynth Syst Biotechnol
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Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
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