IMSc Webinar

Modeling metabolic synergisms in termite gut microbiota for lignocellulose bioconversion

Pritam Kundu

IIT Kharagpur

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The microbial communities in the wood-feeding termite gut microenvironments degrade complex lignocellulosic material through collaborative metabolic activities. In order to formulate defined lignocellulolytic microbial consortia with these biochemically synergistic communities, a system-level understanding of the inter-microbial metabolic interaction patterns is required. Therefore, mathematical modeling techniques have been implemented to understand these inter-microbial metabolic communications at the system level. Initially, the metabolic activities and metagenomic abundance of microbial species identified from the wood-feeding higher termite (Nasutitermes corniger) and fungus-farming termite
(Odontotermes badius) gut microbiota have been leveraged in an in silico framework to estimate the inter-microbial metabolic influences. The resulting inter-species influence network aids in quantifying the overall metabolic impact that a microbial species imparts or receives within the microbiota. Further, the in silico assessment of the metabolic influence pattern showed that competition, parasitism, and mutualism were the major modes of metabolic interactions between microbial entities in the gut environment. Assessment of the topological parameters of the influence network helps identify key microbial species that play crucial roles in maintaining community integrity for lignocellulose bioconversion.

In the next phase, the genome-scale community modeling technique was implemented to map the growth and metabolic compatibility among crucial microbial species identified from the influence network. Reconstruction of genome-scale community metabolic models (GCMs) of termite gut microbes and in silico flux analysis help track the inter-microbial metabolic interactions in the community environment. The analysis of GCMs revealed a significant increase in the inter-microbial exchange of amino acids, SCFAs, and small sugars, demonstrating how microbes support each other's growth and metabolism in pairwise and multispecies communities. The pairwise metabolic assistance (PMA) and pairwise growth support index (PGSI) parameters were introduced to quantify the growth and biochemical synergisms among bacterial pairs. The assessment of the flux-based parameters, i.e., PMA and PGSI, identifies the positively interacting microbial species, showing metabolic mutualisms for executing the complex process of lignocellulose bioconversion. The knowledge of microbial metabolic assistance and interaction patterns derived from the computational work has been tested by developing synergistic co-culture systems with termite gut bacterial isolates. The degree of bacterial enzymatic synergisms in the lignocellulosic substrates showed good coherences with the model-predicted PMA in the bacterial communities. The computational pipelines and flux-based parameters established in this study can be further extended to map the biochemical signature, inter-microbial cross-talk, and critical functional landscape in various microbial ecosystems. This modeling approach will facilitate the deliberate manipulation of microbial community dynamics to aid novel experimental strategies in bioengineering applications and microbiome-based therapeutics.