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Comparing Metabolic Pathway Fluxes of Ground-Bound and Space-Flown Mice Using Single-cell RNA-sequen

Updated: Sep 29, 2022

Shubha Vasisht (1), Yuanchao Zhang (1), Deanne Taylor (1,2) 1. Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia 2. Perelman School of Medicine, University of Pennsylvania

Background: Space biology research has many applications to terrestrial as well as space-related questions about environmental stressors effects on cellular metabolism. Flux balance analysis (FBA) is a type of analysis of the flow of metabolites through a metabolic network and can use gene expression from single-cell RNA analysis to determine regulated reactions and pathways as well as their capacity through optimization of their fluxes. Constraint-based models using FBA can be utilized to simulate metabolic fluxes of cells and tissues to optimize on the gene-transcribed metabolites found in gene expression data. Methods: Combining a constraint-based, context-specific model (CORDA) with the mouse metabolic model, iMM1415, we identified flux differences in certain regulatory metabolic pathways between cell types present in the heart and the brain of the mice that were on the ground versus in spaceflight. Through this model, we were able to simulate key pathways by using an optimization of NAD+ to determine the capacity of this selected metabolic pathway network. Using Van Der Waerden tests to compare the groups, we determined statistically significant pathways. Results: We found that the heart had more significant pathways, with a P-value < 0.01 (n = 53), than the brain (n = 18); there was a higher difference in the expression of genes and metabolic flux in the heart compared to in the brain. Specifically, trabecular muscle-related cells in the heart were identified as the most metabolically active while cells related to choroid plexus and injury responses in the brain were identified as the most metabolically active. Conclusions: Our next steps are to model additional spatial transcriptomics and multi-omics data sets as well as add related pathways in the metabolic network of the model as more reactions may be affected by oxidative stress, microgravity, and space radiation to accurately simulate the metabolism of the mouse.

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