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Using Caenorhabditis elegans to Screen for Tissue-Specific Chaperone Interactions
Published on: June 7, 2020
Epistatic interactions among metabolic genes depend upon environmental conditions
Chintan Jagdishchandra Joshi1, Ashok Prasad
1Department of Chemical and Biological Engineering, Fort Collins, Colorado 80523, USA.
Abstract:
When the effect of the state of one gene is dependent on the state of another gene in more than an additive or a neutral way, the phenomenon is termed epistasis. In particular, positive epistasis signifies that the impact of the double deletion is less severe than the neutral combination, while negative epistasis signifies that the double deletion is more severe. Epistatic interactions between genes affect the fitness landscape of an organism in its environment and are believed to be important for the evolution of sex and the evolution of recombination. Here we use large-scale computational metabolic models of microorganisms to study epistasis computationally using Flux Balance Analysis (FBA). We study what the effects of the environment are on epistatic interactions between metabolic genes in three different microorganisms: the model bacterium E. coli, the cyanobacteria Synechocystis PCC6803 and the model green algae, C. reinhardtii. Prior studies have shown that under standard laboratory conditions epistatic interactions between metabolic genes are dominated by positive epistasis. We show here that epistatic interactions depend strongly upon environmental conditions, i.e. the source of carbon, the carbon/oxygen ratio, and for photosynthetic organisms, the intensity of light. By a comparative analysis of flux distributions under different conditions, we show that whether epistatic interactions are positive or negative depends upon the topology of the carbon flow between the reactions affected by the pair of genes being considered. Thus complex metabolic networks can show epistasis even without explicit interactions between genes, and the direction and the scale of epistasis are dependent on network flows. Our results suggest that the path of evolutionary adaptation in fluctuating environments is likely to be very history dependent because of the strong effect of the environment on epistasis.
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