We present our workflow for the reconstruction a genome-scale metabolic model (GSMM) of T. muris (iTMU798) using COBRApy (Python). C. elegans GSMMs (WormJam and iCEL1314) were used as templates. The reconstruction process consists of 5 main steps and manual curation.
The notebook DraftModelReconstruction.ipynb utilizes WormJam as a reference model and creates a preliminary model by mapping C. elegans - T. muris orthologs obtained from BioMart. The notebook MetaboliteNameCorrectionChEBIPubChem.ipynb organizes metabolite information in the draft model using ChEBI & PubChem databases. SearchRHEA.ipynb is responsible for searching additional reactions in RHEA using EC numbers from the T. muris genome sourced from UniProt.
Subsequently, a manual refinement process takes place, which includes organizing the biomass according to iCEL1314 and incorporating subsystems from KEGG. To identify blocked reactions (BlockedReactionIdentification.ipynb) and dead-end metabolites (DeadEndMetaboliteIdentification.ipynb) for gap-filling, FVA (Flux Variability Analysis) is employed. The final outcome of this iterative curation process is the creation of iTMU798.
Identification of essential genes and comparison of iTMU798 with iCEL1314, Worm1 & iDC625 (Analysis)
The notebook ModelContentComparison.ipynb performs a comparative analysis between iTMU798 and the most recent genome-scale metabolic models (GSMMs) of C. elegans (iCEL1314 & Worm1) and Brugia malayi (iDC625). Additionally, the notebook GeneEssentiality_and_Comparison.ipynb is employed to predict essential genes in iTMU798 and compare them with essential genes present in both C. elegans models and the OGEE (Online Gene Essentiality) database.
In the notebook ExpressionData.ipynb, the expression data from larvae and adult worms (from WormBase ParaSite & Duque-Correa, M.A. et al, 2022) are integrated with the relevant essential genes predicted by iTMU798. MetabolomeChart.ipynb undertakes a comparison between the metabolites found in iTMU798 and the identified metabolites from two separate studies (Wangchuk, P. et al, 2019 & Yeshi, K. et al, 2020)
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