Metabolic Models of Ruminant Metabolism: Recent Improvements and Current Status

Valine and nonessential amino acids affect bidirectional transport rates of leucine and isoleucine in bovine mammary epithelial cells

A more complete understanding of the mechanisms controlling AA transport in mammary glands of dairy cattle will help identify solutions to increase nitrogen feeding efficiency on farms. It was hypothesized that Ala, Gln, and Gly (NEAAG), which are actively transported into cells and exchanged for all branched-chain AA (BCAA), may stimulate transport of BCAA, and that Val may antagonize transport of the other BCAA due to transporter competition. Thus, we evaluated the effects of varying concentrations of NEAAG and Val on transport and metabolism of the BCAA Ala, Met, Phe, and Thr by bovine mammary epithelial cells. Primary cultures of bovine mammary epithelial cells were assigned to treatments of low (70% of mean in vivo plasma concentrations of lactating dairy cows) and high (200%) concentrations of Val and NEAAG (LVal and LNEAAG, HVal and HNEAAG, respectively) in a 2 × 2 factorial design. Cells were preloaded with treatment media containing [15N]-labeled AA for 24 h. The [15N]-labeled media were replaced with treatment media containing [13C]-labeled AA. Media and cells were harvested from plates at 0, 0.5, 1, 5, 15, 30, 60, and 240 min after application of the [13C]-labeled AA and assessed for [15N]- and [13C]-AA label concentrations. The data were used to derive transport, transamination, irreversible loss, and protein-synthesis fluxes. All Val fluxes, except synthesis of rapidly exchanging tissue protein, increased with the HVal treatment. Interestingly, the rapidly exchanging tissue protein, transamination, and irreversible-loss rate constants decreased with HVal, indicating that the significant flux increases were primarily driven by mass action with the cells resisting the flux increases by downregulating activity. However, the decreases could also reflect saturation of processes that would drive down the mass-action rate constants. This is supported by decreases in the same rate constants for Ile and Leu with HVal. This could be due to either competition for shared transamination and oxidation reactions or a reduction in enzymatic activity. Also, NEAAG did not affect Val fluxes, but influx and efflux rate constants increased for both Val and Leu with HNEAAG, indicating an activating substrate effect. Overall, AA transport rates generally responded concordantly with extracellular concentrations, indicating the transporters are not substrate-saturated within the in vivo range. However, BCAA transamination and oxidation enzymes may be approaching saturation within in vivo ranges. In addition, System L transport activity appeared to be stimulated by as much as 75% with high intracellular concentrations of Ala, Gln, and Gly. High concentrations of Val antagonized transport activity of Ile and Leu by 68% and 15%, respectively, indicating competitive inhibition, but this was only observable at HNEAAG concentrations. The exchange transporters of System L transport 8 of the essential AA that make up approximately 40% of milk protein, so better understanding this transporter is an important step for increased efficiency.

A revised representation of ruminal pH and digestive reparameterization of the Molly cow model

Ruminal pH is a critical factor to regulate nutrient degradation and fermentation. However, it has been poorly predicted in the Molly cow model, and recent improvements in the representation of nitrogen cycling across the rumen wall altered some of the modeled responses to feed nutrients, resulting in some model bias. The objectives of this study were to further improve the representation of pH and to refit parameters related to ruminal metabolism and nutrient digestion in the model to resolve this bias, and to use the improved model to estimate nitrogen and energy fluxes with varying rumen-degradable protein (RDP; 40 vs. 60%) and ruminally degraded starch (RDSt; 50 vs. 75%). A meta data set containing 284 peer reviewed studies with 1,223 treatment means was used to derive parameter estimates for ruminal metabolism and nutrient digestions. Refitting the parameters significantly improved the accuracy and precision of the model predictions for ruminal nutrient outflow [acid detergent fiber (ADF), neutral detergent fiber (NDF), total N, microbial N, nonammonia N, and nonammonia nonmicrobial N], ammonia and blood urea concentrations, and fecal nutrient outflow (protein, ADF, and NDF). The prediction error for body weight was decreased from 19.3 to 6.2% with decreased mean bias (from 76.0 to 11.5%) and slope bias (from 17.2 to 7.7%), primarily due to improved representations of ruminal dry matter and liquid pool size. Adding ammonia concentration as a driver to the pH equation increased the precision of predicted ruminal pH and, thereby, the precision of predicted volatile fatty acid (VFA) concentrations, due to improved representation of pH regulation of VFA production rates. Although minor mean and slope bias were observed for ruminal pH and VFA concentrations, the concordance correlation coefficients indicated that much of the observed variation in these variables remains unexplained. Overall, the biological functions of nutrient degradation and digestion appear to be represented without bias. Simulated results indicated that decreasing RDP and RDSt proportions in an isonitrogenous and isocaloric diet can slightly improve N efficiency, and increasing RDSt proportions can increase energy efficiency.

Fiftieth Anniversary of the California Net Energy System Symposium: What are the energy coefficients for cows?

The same model structure used to describe energy metabolism in the growing animal is often used to model energy metabolism in the cow. Energy requirements of the cow are modeled as the summation of energy required for maintenance and recovered energy, where recovered energy is the summation of energy for the conceptus, milk, and tissue energy. Energetic requirements of the cow fluctuate throughout the production cycle depending on whether they are pregnant, lactating, or both. The current model requires energy cost to be associated with either net energy of maintenance or the partial efficiencies of conceptus growth, milk production, and tissue energy change. Mathematically, they are not independent. Incorrectly estimating one will result in an erroneous estimate in the other. Most of the current models in production agriculture allocate energy use into maintenance, and synthesis of tissues making it difficult to assign energy utilization by tissues that provide support functions to pregnancy, lactation, and weight fluctuation. The consequence is the assignment of partial efficiencies that reflect whole animal efficiencies rather than tissue efficiencies. Historically, these models have been predictive of energy metabolism, but caution should be used when inferring the energetic efficiency at the tissue level. Alternative modeling approaches more thoroughly describe tissue energy metabolism and have been used to estimate whole animal metabolism. These models resolve the problems associated with developing coefficients that lack biological meaning but are more complex. There is a critical need for independent data sets to test new components of the model for cows.

Lipolysis in early lactation is associated with an increase in phosphorylation of adenosine monophosphate-activated protein kinase (AMPK)α1 in adipose tissue of dairy cows

Adenosine monophosphate-activated protein kinase (AMPK)α1 is activated in the context of triacylglycerol hydrolysis in adipose tissue in monogastric animals. This study describes AMPKα1 protein expression and the occurrence of its phosphorylated form (pAMPKα1) in different adipose tissue depots as influenced by time and postpartum diet in dairy cows. Biopsy samples were obtained from subcutaneous (SCAT) and retroperitoneal (RPAT) adipose tissues of 20 Holstein cows 21 d prepartum (ap) and 1 and 21 d postpartum (pp). After d 1 pp, cows were randomly assigned to 2 groups (n=10) and fed different amounts of concentrate until the third biopsy sampling at 21 d pp. Protein expression of AMPK and the extent of its phosphorylation in adipose tissue were measured by semiquantitative Western blotting. Results were not influenced by postpartum feeding. Therefore, both groups were pooled and data analyzed together. Expression of AMPKα1 in SCAT showed a decrease over time, resulting in lower expression at 1d pp compared with 21 d ap. Expression in RPAT was maintained over time. Phosphorylation increased in SCAT, showing a greater extent of phosphorylation at d 21 pp compared with 21 d ap. In RPAT, this could be seen as a trend. The proportion of pAMPKα1 to AMPKα1 significantly increased over time in both tissues. In the first adipose tissue sampling (21 d ap), AMPKα1 protein expression and extent of phosphorylation were significantly higher in RPAT than in SCAT. Lipolysis in early lactation of dairy cows was associated with an increase in phosphorylation of AMPKα1 and ratio of pAMPKα1 to AMPKα1 in bovine adipose tissues. This indicates that AMPKα1 may be involved in the regulation of energy metabolism of bovine adipose tissues.

A Redefinition of the Representation of Mammary Cells and Enzyme Activities in a Lactating Dairy Cow Model

The Molly model predicts various aspects of digestion and metabolism in the cow, including nutrient partitioning between milk and body stores. It has been observed previously that the model underpredicts milk component yield responses to nutrition and consequently overpredicts body energy store responses. In Molly, mammary enzyme activity is represented as an aggregate of mammary cell numbers and activity per cell with minimal endocrine regulation. Work by others suggests that mammary cells can cycle between active and quiescent states in response to various stimuli. Simple models of milk production have demonstrated the utility of this representation when using the model to simulate variable milking and nutrient restriction. It was hypothesized that replacing the current representation of mammary cells and enzyme activity in Molly with a representation of active and quiescent cells and improving the representation of endocrine control of cell activity would improve predictions of milk component yield. The static representation of cell numbers was replaced with a representation of cell growth during gestation and early lactation periods and first-order cell death. Enzyme capacity for fat and protein synthesis was assumed to be proportional to cell numbers. Enzyme capacity for lactose synthesis was represented with the same equation form as for cell numbers. Data used for parameter estimation were collected as part of an extended lactation trial. Cows with North American or New Zealand genotypes were fed 0, 3, or 6 kg of concentrate dry matter daily during a 600-d lactation. The original model had root mean square prediction errors of 17.7, 22.3, and 19.8% for lactose, protein, and fat yield, respectively, as compared with values of 8.3, 9.4, and 11.7% for the revised model, respectively. The original model predicted body weight with an error of 19.7% vs. 5.7% for the revised model. Based on these observations, it was concluded that representing mammary synthetic capacity as a function of active cell numbers and revisions to endocrine control of cell activity was meritorious.