mSystems, Journal Year: 2024, Volume and Issue: 10(1)

Published: Dec. 19, 2024

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, application of CS modeling non-conventional microbes still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, RIPTiDe, Python-based tools within BioUML platform, streamlines interrogation metabolic frameworks via Jupyter Notebook. The approach was tested using -omics collected Methylotuvimicrobium alcaliphilum 20Z R , prominent microbial chassis methane capturing valorization. We optimized previously reconstructed whole network by adjusting flux distribution gene expression data. outputs automatically were comparable manually i IA409 models Ca-growth conditions. questions reversibility phosphoketolase pathway suggests higher primary oxidation pathways. also highlighted unresolved carbon partitioning assimilatory catabolic pathways at formaldehyde-formate node. Only very few genes only one enzyme with predicted function in C1 metabolism, homolog formaldehyde ( fae1-2 ), showed significant change La-growth CS-GSM predictions agreed measurements under assumption Fae1-2 part tetrahydrofolate-linked pathway. roles tungsten (W)-dependent formate dehydrogenase fdhAB ) fae homologs fae3 investigated mutagenesis. phenotype f dhAB mutant followed prediction. Furthermore, more reduction biomass yield observed during growth La-supplemented media, confirming through formate. M. mutants lacking did not display any defects methanol-dependent growth. contrary fae1, failed restore formaldehyde-activating complementation tests. Overall, presented suggest developed computational workflow supports validation networks non-model microbes. IMPORTANCE various types routine genotype phenotype. An context whole-genome-based becomes powerful tool facilitates study describes context-specific (CS) methane-utilizing bacterium, . attractive platform production biofuels, chemicals, pharmaceuticals, bio-sorbents atmospheric methane. demonstrate this pipeline can help reconstruct are similar curated networks. able highlight overlooked pathways, thus advancing knowledge systems promoting their development toward biotechnological environmental implementations.

Language: Английский