(347f) An in silico study of the Metabolic Transactions in the Rumen Microbiome and the Metabolic Shifts Inflicted By Virome Interactions | AIChE

(347f) An in silico study of the Metabolic Transactions in the Rumen Microbiome and the Metabolic Shifts Inflicted By Virome Interactions

Authors 

Islam, M. M. - Presenter, University of Nebraska-Lincoln
Fernando, S. C., University of Nebraska-Lincoln
Saha, R., University of Nebraska-Lincoln
The complex microbial ecosystem of the cattle rumen has a significant impact on host energy utilization, health and the environment. However, little is known about the interactions between the functional entities within the system, which dictates the community structure and functional dynamics and host physiology. In addition to the complex syntrophic, mutualistic, and competitive interactions within the rumen microbiome, viruses have been shown to impact microbial populations through a myriad of processes, including cell lysis and reprogramming of host metabolism via Auxiliary Metabolic Genes (AMGs). Although advancements in high-throughput sequencing are providing access to the vast diversity and functions of this complex ecosystem, our understanding of factors that shape the rumen microbial communities is in its infancy, and little is known about the processes shaping the distribution of rumen viruses or the modulation of microbe-driven processes in the rumen. With a gradual increase in computational capability and the abundance of in silico genome-scale metabolic reconstruction tools, metabolic networks combined with constraint-based modeling provides opportunities to study microbe-microbe and phage-microbe interactions.

In this work, we developed a representative rumen community metabolic model with representative organisms from the three major functional guilds in the rumen ecosystem (i.e.,Firmicutes, Bacteroidetes, and Archaea), namely Ruminococcus flavefaciens, Prevotella ruminicola, and Methanobrevibacter gottschalkii, respectively. These organisms are responsible for fiber digestion, starch and protein digestion, and methane production in the rumen. We reconstructed the draft models by using the current knowledgebases1and performed extensive manual curation, including chemical and charge-balancing, eliminating thermodynamically infeasible cycles, and ensuring network connectivity. The curated models of and R. flavefaciens(467 genes, 1033 metabolites, 1015 reactions), P. ruminicola(546 genes, 1069 metabolites, 1088 reactions), and M. gottschalkii (319 genes, 900 metabolites, 847 reactions)were integrated into a community model using a multi-level optimization framework 2,3. To enrich our understanding of the inter-species interactions in the ecosystem, we employed a detailed and comprehensive heuristic procedure that utilized existing GapFind-GapFill tools 4and a subsequent series of knowledgebase-driven validations. We predicted 22 novel inter-species metabolic interactions involving the transfer of fatty acids, vitamins, coenzymes, amino acids, and sugars among the community members. We validated our predictions involving amino acids and fatty acids transactions with published meta-transcriptomic and meta-metabolomic analyses of the rumen microbiome and the ruminal fluid, respectively 5,6. In addition, we bridged the network gaps in the pentose phosphate pathway, amino acid synthesis and utilization, nucleotide synthesis and degradation, purine metabolism, glycerophospholipid metabolism, and starch metabolism in the metabolic models of these organisms.

To understand the functional role of the virome on the microbial ecosystem, we used local alignment search and identified metabolic functions of the viruses associated with the community members that drive nucleotide synthesis, reducing power generation, reprogramming of the bacterial carbon metabolism, and viral replication. The identified functions of viral AMGs were incorporated into the model as additional metabolic functions. The addition of viral functionalities resulted in significant changes in bacterial metabolism, including relaxing metabolic bottleneck in the models, complementing microbe-microbe interactions, utilizing nutrients more efficiently and energy harvest by the host. Overall, these findings support the hypothesis that viral AMGs play a crucial role in enhancing host fitness and robustness. We also studied the effect of using different community-level objective functions (i.e.,growth, short-chain fatty acids production, plant feed utilization, greenhouse gas release, and small sugar molecule production) on the metabolic capacity of the community members. We found that the flux ranges of the microbial species are robust irrespective of the choice of a community objective. These novel findings of the interactions between the phages and their hosts reveal a highly sophisticated metabolic interplay among the microbial hosts and the associated viruses that can potentially affect the health, nutrition, and pathophysiology of the ruminant animal.

References:

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