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Link, K. G.

Publications and source records attributed to Link, K. G..

2 recordsLinked to original sources

Sensitivity analysis of a mechanistic model of rumen fermentation and methane production by rumen microbiota in the presence of Asparagopsis taxiformis

Ruminant animals rely on microbes for the conversion of complex plant material into host accessible metabolites. During this anaerobic conversion of plant biomass, termed enteric fermentation, methanogenic archaea convert hydrogen into the potent greenhouse gas methane (CH4). The search for methane mitigation strategies to combat climate change has identified the red seaweed Asparagopsis taxiformis as a promising feed additive that, when added to a regular cattle diet, reduced enteric CH4 by over 80%. A more complete understanding of microbial interactions during enteric fermentation is needed for ongoing improvement to mitigation methods. Mathematical models that permit in silico simulation of enteric fermentation allow for the identification of key parameters that drive rumen methane production. Here we built upon an existing rumen fermentation model and calibrated it using a preliminary classification of functional microbial groups and gas emission data from a previously published in vitro rumen fermentation experiment, but many microbes remained functionally unclassified. The model was then used to conduct an in silico experiment to explore how the partition of functionally unclassified microbes into functional groups affects methane output. These in silico experiments identified that model methane production is more sensitive to microbial variation in the presence of A. taxiformis versus without. The use of local and global sensitivity analysis approaches revealed other rumen parameters to also be drivers of enteric methane production. In the presence of A. taxiformis, parameters modulating methane production include bromoform concentration, methanogen abundance, total microbial concentration, a parameter effecting the inhibition of methanogen growth rate by the action of bromoform, and the maximum specific utilization rate of hydrogen. Without A. taxiformis, feed composition parameters, the hydrolysis rate constant of cell wall carbohydrates, and a parameter affecting the yield factors during sugar utilization were found to be most significant. For possible methane reduction without A. taxiformis, we propose an adjustment in feed composition parameters that reduces predicted methane by 25.6%.

systems biology↗

A mathematical model of flow-mediated coagulation identifies factor V as a modifier of thrombin generation in hemophilia A

Hemophilia A is a bleeding disorder categorized as severe, mild, and moderate deficiencies in factor VIII (FVIII). Within these categories the variance in bleeding severity is significant and the origins unknown. The number of parameters that could modify bleeding are so numerous that experimental approaches are not feasible for considering all possible combinations. Consequently, we turn to a mathematical model of coagulation under flow to act as a screening tool to identify parameters that are most likely to enhance thrombin generation. We performed global sensitivity analysis on 110,000 simulations that varied coagulation factor levels by 50-150% of their normal values in humans while holding FVIII levels at 1%. These simulations identified low factor V (FV) levels as the strongest candidate, with additional enhancement when combined with high prothrombin levels. This prediction was confirmed in two experimental models: Partial FV inhibition boosted fibrin deposition in flow assays performed at 100 1/s on collagen-tissue factor surfaces using whole blood from individuals with mild and moderate FVIII deficiencies. Low FV (~50%) or partial FV inhibition also augmented thrombin generation in FVIII-inhibited or FVIII-deficient plasma in calibrated automated thrombography. These effects were amplified by high prothrombin levels in both experimental models. Our mathematical model suggests a mechanism in which FV and FVIII compete to bind to factor Xa to initiate thrombin generation in low FV, FVIII-deficient blood. This unexpected result was made possible by a mechanistic mathematical model, providing an example of the potential of such models in making predictions in complex biological networks.

systems biology↗