Model-based exploration of the impact of glucose metabolism on the estrous cycle dynamics in dairy cows

Author:

Omari Mohamed,Lange Alexander,Plöntzke Julia,Röblitz SusannaORCID

Abstract

Abstract Background Nutrition plays a crucial role in regulating reproductive hormones and follicular development in cattle. This is visible particularly during the time of negative energy balance at the onset of milk production after calving. Here, elongated periods of anovulation have been observed, resulting from alterations in luteinizing hormone concentrations, likely caused by lower glucose and insulin concentrations in the blood. The mechanisms that result in a reduced fertility are not completely understood, although a close relationship to the glucose-insulin metabolism is widely supported. Results Following this idea, we developed a mathematical model of the hormonal network combining reproductive hormones and hormones that are coupled to the glucose compartments within the body of the cow. The model is built on ordinary differential equations and relies on previously introduced models on the bovine estrous cycle and the glucose-insulin dynamics. Necessary modifications and coupling mechanisms are thoroughly discussed. Depending on the composition and the amount of feed, in particular the glucose content in the dry matter, the model quantifies reproductive hormones and follicular development over time. Simulation results for different nutritional regimes in lactating and non-lactating dairy cows are examined and compared with experimental studies. The simulations describe realistically the effects of nutritional glucose supply on the ovulatory cycle of dairy cattle. Conclusions The mathematical model enables the user to explore the relationship between nutrition and reproduction by running simulations and performing parameter studies. Regarding its applicability, this work is an early attempt towards developing in silico feeding strategies and may eventually help to refine and reduce animal experiments. Reviewers This article was reviewed by John McNamara and Tin Pang (nominated by Martin Lercher).

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Immunology

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