Genome-scale community modeling for deciphering the inter-microbial metabolic interactions in fungus-farming termite gut microbiome

• Published in: Computers in biology and medicine 2023-03, Vol.154, p.106600-106600, Article 106600
• Main Authors: Kundu, Pritam, Ghosh, Amit
• Format: Article
• Language: English
• Subjects: Agriculture; Amino acids; Animals; Biochemical Phenomena; Biomass; Biosynthesis; Carbohydrates; Combinatorial analysis; Community metabolic model; Computer applications; Degradation; Digestive system; Distribution patterns; Farming; Fluctuations; Flux variability analysis; Fungi; Fungi - genetics; Fungus gardens; Gastrointestinal Microbiome - genetics; Genome-scale metabolic model; Genomes; Homeostasis; Inflammatory bowel disease; Intestinal microflora; Isoptera - genetics; Isoptera - metabolism; Isoptera - microbiology; Lignocellulose; Mathematical models; Metabolic assistance; Metabolic flux; Metabolism; Metabolites; Microbial activity; Microbial Interactions; Microbiomes; Microbiota; Microcosms; Microorganisms; Mutualism; Next-generation sequencing; Nucleotides; Nutrition; Pairwise growth support index; Parameters; Polymers; Termite gut microbiome; Termites
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2023.106600

Specialized microbial communities in the fungus-farming termite gut and fungal comb microbiome help maintain host nutrition through interactive biochemical activities of complex carbohydrate degradation. Numerous research studies have been focused on identifying the microbial species in the termite gut and fungal comb microbiota, but the community-wide metabolic interaction patterns remain obscure. The inter-microbial metabolic interactions in the community environment are essential for executing biochemical processes like complex carbohydrate degradation and maintaining the host’s physicochemical homeostasis. Recent progress in high-throughput sequencing techniques and mathematical modeling provides suitable platforms for constructing multispecies genome-scale community metabolic models that can render sound knowledge about microbial metabolic interaction patterns. Here, we have implemented the genome-scale metabolic modeling strategy to map the relationship between genes, proteins, and reactions of 12 key bacterial species from fungal cultivating termite gut and fungal comb microbiota. The resulting individual genome-scale metabolic models (GEMs) have been analyzed using flux balance analysis (FBA) to optimize the metabolic flux distribution pattern. Further, these individual GEMs have been integrated into genome-scale community metabolic models where a heuristics-based computational procedure has been employed to track the inter-microbial metabolic interactions. Two separate genome-scale community metabolic models were reconstructed for the O. badius gut and fungal comb microbiome. Analysis of the community models showed up to ∼167% increased flux range in lignocellulose degradation, amino acid biosynthesis, and nucleotide metabolism pathways. The inter-microbial metabolic exchange of amino acids, SCFAs, and small sugars was also upregulated in the multispecies community for maximum biomass formation. The flux variability analysis (FVA) has also been performed to calculate the feasible flux range of metabolic reactions. Furthermore, based on the calculated metabolic flux values, newly defined parameters, i.e., pairwise metabolic assistance (PMA) and community metabolic assistance (CMA) showed that the microbial species are getting up to 15% higher metabolic benefits in the multispecies community compared to pairwise growth. Assessment of the inter-microbial metabolic interaction patterns through pairwise growth support index (PGSI) indicated an increase