Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

• Published in: mSystems 2024-12, p.e0110524
• Main Authors: Kulyashov, M A, Hamilton, R, Afshin, Y, Kolmykov, S K, Sokolova, T S, Khlebodarova, T M, Kalyuzhnaya, M G, Akberdin, I R
• Format: Article
• Language: English
• Subjects: Computational Biology; Research Article
• ISSN: 2379-5077; 2379-5077
• DOI: 10.1128/msystems.01105-24

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, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for 20Z , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( ) and homologs ( and ) were investigated via mutagenesis. The phenotype of the f mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. 20Z mutants lacking did not display any significant defects in methane or methanol-dependent growth. However, contrary to the homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. The interrogation of various types of data is a routine strategy to explore the relationshi