Comparison of Net Portal Absorption with Predicted Flow of Digestible Amino Acids: Scope for Improving Current Models?

Ability of three dairy feed evaluation systems to predict postruminal outflows of nitrogenous compounds in dairy cows: A meta-analysis

Adequate prediction of postruminal outflow of protein fractions is the starting point for the determination of metabolizable protein supply in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict outflows (g/d) of nonammonia nitrogren (NAN), microbial N (MiN), and nonammonia nonmicrobial N (NANMN). Predictions of rumen degradabilities (% of nutrient) of protein (RDP), NDF, and starch were also evaluated. The data set included 1,294 treatment means from 312 digesta flow studies. The 3 feed evaluation systems were compared using the concordance correlation coefficient (CCC), the ratio of root mean square prediction error (RMSPE) on standard deviation of observed values (RSR), and the slope between observed and predicted values. Mean and linear biases were deemed biologically relevant and are discussed if higher than a threshold of 5% of the mean of observed values. The comparisons were done on observed values adjusted or not for the study effect; the adjustment had a small effect on the mean bias but the linear bias reflected a response to a dietary change rather than absolute predictions. For the absolute predictions of NAN and MiN, CNCPS had the best-fit statistics (8% greater CCC; 6% lower RMSPE) without any bias; NRC and NASEM underpredicted NAN and MiN, and NASEM had an additional linear bias indicating that the underprediction of MiN increased at increased predictions. For NANMN, fit statistics were similar among the 3 feed evaluation systems with no mean bias; however, the linear bias with NRC and CNCPS indicated underprediction at low predictions and overprediction at elevated predictions. On average, the CCC were smaller and RSR ratios were greater for MiN versus NAN indicating increased prediction errors for MiN. For NAN responses to a dietary change, CNCPS also had the best predictions, although the mean bias with NASEM was not biologically relevant and the 3 feed evaluation systems did not present a linear bias. However, CNCPS, but not the 2 other feed evaluation systems, presented a linear bias for MiN, with responses being overpredicted at increased predictions. For NANMN, responses were overpredicted at increased predictions for the 3 feed evaluation systems, but to a lesser extent with NASEM. The site of sampling had an effect on the mean bias of MiN and NANMN in the 3 feed evaluation systems. The mean bias of MiN was higher in omasal than duodenal studies in the 3 feed evaluation systems (from 55 to 61 g/d) and this mean bias was twice as large when 15N labeling was used as a microbial marker compared with purines. Such a difference was not observed for duodenal studies. The reasons underlying these systematic differences are not clear as the type of measurements used in the current meta-analysis does not allow to delineate if one site or one microbial marker is yielding the "true" postruminal N outflows. Rumen degradabilities of protein was underpredicted with CNCPS, and RDP responses to a dietary change was underpredicted by the 3 feed evaluation systems with increased RDP predictions. Rumen degradability of NDF was underpredicted and had poor fit statistics for NASEM compared with CNCPS. Fit statistics were similar between CNCPS and NASEM for rumen degradability of starch, but with an underprediction of the response with NASEM and absolute values being overpredicted with CNCPS. Multivariate regression analyses showed that diet characteristics were correlated with prediction errors of N outflows in each feed evaluation system. Globally, compared with NAN and NANMN, residuals of MiN were correlated with several moderators in the 3 feed evaluation systems reflecting the complexity to measure and model this outflow. In addition, residuals of NANMN were correlated positively with RDP suggesting an overestimation of this parameter. In conclusion, although progress is still to be made to improve equations predicting postruminal N outflows, the current feed evaluation systems provide sufficient precision and accuracy to predict postruminal outflows of N fractions.

Ruminal tissue uptake of amino acids in Holstein cows when supply of nutrients within the rumen differs

Characterisation of amino acid (AA) use by the ruminal vein-drained viscera (RDV) has not been assessed in vivo in dairy cattle, and thus, the extent of ruminal AA use from arterial and postabsorptive blood supplies is unclear. Understanding the complete use of AA by the splanchnic bed may lead to alternative feeding programmes that maximise animal N efficiency. The objective of this work was to determine how different nutritional manipulations affect RDV net appearance and apparent affinity for arterial AA in lactating dairy cattle. Data from two arterio-venous (A-V) difference studies, that used a common set of multicatheterised lactating Holstein cows, assigned to different nutritional treatments, were used to assess ruminal metabolism. Study 1 consisted of three dietary treatments at calving [an alfalfa-glucogenic diet, a glucogenic diet (GLCG), or a ketogenic diet (KETO)] to investigate the effects of dietary nutrients and increasing intake postpartum on RDV metabolism of AA at -14, +4, +15, and +29 days relative to calving (DRTC). Study 2 consisted of two dietary levels of CP (17 or 13%) and three ruminal buffers (ammonia, butyrate, and control) to investigate the level of dietary CP and ruminal fermentation products on RDV metabolism of AA. Blood was collected at 9, 20, and 30 min after buffer administration. Regardless of dietary nutrients or fermentation products present in ruminal fluid, net RDV uptake was positive for most AA, excepting Asp, Cys, Glu, and Ser, which were consistently negative. The general positive net uptakes indicate that any AA potentially absorbed from the rumen were not adequate to meet apparent needs. Ruminal plasma flow and net RDV uptake of Trp, Ala, Gly, and Pro increased linearly with increased DRTC. Feeding KETO or GLCG diets increased ruminal plasma flow, and net RDV uptake of Thr and Gly. Feeding high CP diets increased ruminal uptake of Leu, Phe, and Val. The increased AA uptakes were partially driven by increased plasma flow, however, tissue affinity as reflected in clearance rates also increased or tended to for Met, Trp, Ala, Gly, Pro, and Tyr suggesting that changes in RDV uptake were regulated and not due solely to mass action. In conclusion, splanchnic tissue bed responses to dietary and washed rumen conditions were in part driven by changes in RDV nutrient demand and metabolic activity. The adaptive responses alter the fraction of absorbed AA utilised for non-productive purposes and thus the efficiency of conversion of those AA to product.

Histidine optimal supply in dairy cows through determination of a threshold efficiency

Two His deletion studies were conducted to examine the mechanisms used by dairy cows to support milk true protein yield (MTPY) when His supply is altered. The potential mechanisms involved in how the efficiency of utilization of His varied included reduced catabolism, more efficient mammary usage, and use of His labile pools. For the first study, 5 multicatheterized cows were used in a 4 × 4 Latin square plus 1 cow with 14-d periods. Treatments were abomasal infusion of increasing doses of His (0, 7.6, 15.2, and 20.8 g/d) in addition to a mixture of AA (595 g/d; casein profile excluding His). Cows were fed the same protein-deficient diet throughout the study. The MTPY increased linearly with a quadratic tendency with increasing doses of His. Muscle concentrations of carnosine, a His-based dipeptide, tended to increase in a quadratic manner with increasing His supply, suggesting that the 0- and 7.6-g doses were insufficient to cover His requirement. Liver catabolism of His decreased as His supply decreased. Mammary fractional removal of His was considerably greater at low His supply, but the ratio of His mammary net uptake to milk output was not affected by the rate of His infusion, averaging 1.02. The mechanisms to face a reduced His supply included reduced His hepatic catabolism, more efficient His mammary use of lowered arterial supply, and, to a lesser extent, use of His labile pools. Two independent estimates of His efficiency were calculated, one based on the sum of exported proteins (measured MTPY plus estimated metabolic fecal protein and scurf; i.e., the anabolic component, Eff_MTPY) and the other based on liver removal (i.e., the catabolic component). These 2 estimates followed the same pattern of response to His supply, decreasing with increasing His supply. The Eff_MTPY at which MTPY peaked was 0.785. For the second study, 6 cows were used in a 6 × 6 Latin square with 7-d periods. Two greater doses of His (30.4 and 38.0 g/d) were added; otherwise, the nutritional design was similar to the first study. In this second study, the indicator AA oxidation technique was used instead of the multiorgan approach, with labeled Leu as the indicator of His utilization. The MTPY peaked and Leu oxidation reached the nadir at an average Eff_MTPY of 0.763. Combined across both studies, the data indicate that optimal usage of His would occur at a threshold Eff_MTPY of 0.77. The agreement between experimental approaches across both studies indicates that the biological optimal supply of His expressed in grams per day could be calculated as the sum of exported proteins divided by this Eff_MTPY plus estimated endogenous urinary excretion.

Amino Acid Metabolism in Dairy Cows and their Regulation in Milk Synthesis

Background:

Reducing dietary Crude Protein (CP) and supplementing with certain Amino Acids (AAs) has been known as a potential solution to improve Nitrogen (N) efficiency in dairy production. Thus understanding how AAs are utilized in various sites along the gut is critical.

Objective:

AA flow from the intestine to Portal-drained Viscera (PDV) and liver then to the mammary gland was elaborated in this article. Recoveries in individual AA in PDV and liver seem to share similar AA pattern with input: output ratio in mammary gland, which subdivides essential AA (EAA) into two groups, Lysine (Lys) and Branchedchain AA (BCAA) in group 1, input: output ratio > 1; Methionine (Met), Histidine (His), Phenylalanine (Phe) etc. in group 2, input: output ratio close to 1. AAs in the mammary gland are either utilized for milk protein synthesis or retained as body tissue, or catabolized. The fractional removal of AAs and the number and activity of AA transporters together contribute to the ability of AAs going through mammary cells. Mammalian Target of Rapamycin (mTOR) pathway is closely related to milk protein synthesis and provides alternatives for AA regulation of milk protein synthesis, which connects AA with lactose synthesis via α-lactalbumin (gene: LALBA) and links with milk fat synthesis via Sterol Regulatory Element-binding Transcription Protein 1 (SREBP1) and Peroxisome Proliferatoractivated Receptor (PPAR).

Conclusion:

Overall, AA flow across various tissues reveals AA metabolism and utilization in dairy cows on one hand. While the function of AA in the biosynthesis of milk protein, fat and lactose at both transcriptional and posttranscriptional level from another angle provides the possibility for us to regulate them for higher efficiency.

Estimation of correction factors to determine the true amino acid concentration of protein after a 24-hour hydrolysis

Although it has been acknowledged for a long time that a single period of hydrolysis, normally 21 to 24 h, is not the optimal time for most of the AA, a single period is routinely used due to time and cost constraints. As models to balance dairy rations for proteins are evolving toward balancing for AA, it becomes critical to improve the predictions of AA supply from digested proteins. Our objective was to develop correction factors that could systematically be applied to AA concentrations obtained after a 24-h hydrolysis of proteins to account for incomplete recovery and therefore determine their true AA composition. Thirteen substrates were selected to represent different types of proteins commonly used to estimate the supply of AA in ration formulation models: feed ingredients (grass silage, corn silage, soybean meal, canola meal, high-protein corn dried distillers grains, and wheat dried distillers grains plus solubles), 16-h rumen residues (soybean meal and canola meal), digesta (duodenal digesta and feces), and rumen microorganisms (fluid-associated bacteria, particle-associated bacteria and protozoa). Each protein was hydrolyzed in 6 N HCl for multiple hydrolysis times: 13 (2, 4, 8, 12, 18, 21, 24, 30, 48, 72, 96, 120, and 168 h) for feed ingredients, rumen residues, and digesta, and 9 (2, 4, 8, 18, 24, 30, 48, 96, and 168 h) for rumen microorganisms; all analyses were conducted in triplicate. Using nonlinear regression, the AA composition in the protein before the hydrolysis (A0) was derived for each AA in each protein. Two ratios were calculated as potential correction factors: A0/24-h concentration (A0/24h) and the maximal concentration/24-h concentration (max/24h). Both ratios were tested to determine if the type of proteins was affecting them. The ratios A0/24h were not affected by the type of proteins, whereas the ratios max/24h were also not affected by the type of proteins except for 3 nonessential AA (Ala, Glu, and Gly). In an attempt to propose correction factors, our results were combined with results from the literature reporting ratios A0/24h, ratios max/24h, or the ratio of the AA composition calculated from gene structure/24 h. The correction factors proposed for individual AA varied from 1.02 (Asp) to 1.12 (Thr). For the essential AA, the highest ratios were obtained, as expected, for the branched-chain AA and Thr. Formulation programs balancing dairy rations for essential AA would need to acknowledge the incomplete recovery of AA when obtained from 24-h hydrolysis and include correction factors, specific for each AA, but the same across different types of proteins, to correctly estimate the true AA supply to dairy cows.

A 100-Year Review: Protein and amino acid nutrition in dairy cows

Considerable progress has been made in understanding the protein and amino acid (AA) nutrition of dairy cows. The chemistry of feed crude protein (CP) appears to be well understood, as is the mechanism of ruminal protein degradation by rumen bacteria and protozoa. It has been shown that ammonia released from AA degradation in the rumen is used for bacterial protein formation and that urea can be a useful N supplement when lower protein diets are fed. It is now well documented that adequate rumen ammonia levels must be maintained for maximal synthesis of microbial protein and that a deficiency of rumen-degradable protein can decrease microbial protein synthesis, fiber digestibility, and feed intake. Rumen-synthesized microbial protein accounts for most of the CP flowing to the small intestine and is considered a high-quality protein for dairy cows because of apparent high digestibility and good AA composition. Much attention has been given to evaluating different methods to quantify ruminal protein degradation and escape and for measuring ruminal outflows of microbial protein and rumen-undegraded feed protein. The methods and accompanying results are used to determine the nutritional value of protein supplements and to develop nutritional models and evaluate their predictive ability. Lysine, methionine, and histidine have been identified most often as the most-limiting amino acids, with rumen-protected forms of lysine and methionine available for ration supplementation. Guidelines for protein feeding have evolved from simple feeding standards for dietary CP to more complex nutrition models that are designed to predict supplies and requirements for rumen ammonia and peptides and intestinally absorbable AA. The industry awaits more robust and mechanistic models for predicting supplies and requirements of rumen-available N and absorbed AA. Such models will be useful in allowing for feeding lower protein diets and increased efficiency of microbial protein synthesis.

The Cornell Net Carbohydrate and Protein System: Updates to the model and evaluation of version 6.5

New laboratory and animal sampling methods and data have been generated over the last 10 yr that had the potential to improve the predictions for energy, protein, and AA supply and requirements in the Cornell Net Carbohydrate and Protein System (CNCPS). The objectives of this study were to describe updates to the CNCPS and evaluate model performance against both literature and on-farm data. The changes to the feed library were significant and are reported in a separate manuscript. Degradation rates of protein and carbohydrate fractions were adjusted according to new fractionation schemes, and corresponding changes to equations used to calculate rumen outflows and postrumen digestion were presented. In response to the feed-library changes and an increased supply of essential AA because of updated contents of AA, a combined efficiency of use was adopted in place of separate calculations for maintenance and lactation to better represent the biology of the cow. Four different data sets were developed to evaluate Lys and Met requirements, rumen N balance, and milk yield predictions. In total 99 peer-reviewed studies with 389 treatments and 15 regional farms with 50 different diets were included. The broken-line model with plateau was used to identify the concentration of Lys and Met that maximizes milk protein yield and content. Results suggested concentrations of 7.00 and 2.60% of metabolizable protein (MP) for Lys and Met, respectively, for maximal protein yield and 6.77 and 2.85% of MP for Lys and Met, respectively, for maximal protein content. Updated AA concentrations were numerically higher for Lys and 11 to 18% higher for Met compared with CNCPS v6.0, and this is attributed to the increased content of Met and Lys in feeds that were previously incorrectly analyzed and described. The prediction of postruminal flows of N and milk yield were evaluated using the correlation coefficient from the BLUP (R(2)BLUP) procedure or model predictions (R(2)MDP) and the concordance correlation coefficient. The accuracy and precision of rumen-degradable N and undegradable N and bacterial N flows were improved with reduced bias. The CNCPS v6.5 predicted accurate and precise milk yield according to the first-limiting nutrient (MP or metabolizable energy) with a R(2)BLUP=0.97, R(2)MDP=0.78, and concordance correlation coefficient=0.83. Furthermore, MP-allowable milk was predicted with greater precision than metabolizable energy-allowable milk (R(2)MDP=0.82 and 0.76, respectively, for MP and metabolizable energy). Results suggest a significant improvement of the model, especially under conditions of MP limitation.

Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows

The objective of this analysis was to compare the rumen submodel predictions of 4 commonly used dairy ration programs to observed values of duodenal flows of crude protein (CP), protein fractions, and essential AA (EAA). The literature was searched and 40 studies, including 154 diets, were used to compare observed values with those predicted by AminoCow (AC), Agricultural Modeling and Training Systems (AMTS), Cornell-Penn-Miner (CPM), and National Research Council 2001 (NRC) models. The models were evaluated based on their ability to predict the mean, their root mean square prediction error (RMSPE), error bias, and adequacy of regression equations for each protein fraction. The models predicted the mean duodenal CP flow within 5%, with more than 90% of the variation due to random disturbance. The models also predicted within 5% the mean microbial CP flow except CPM, which overestimated it by 27%. Only NRC, however, predicted mean rumen-undegraded protein (RUP) flows within 5%, whereas AC and AMTS underpredicted it by 8 to 9% and CPM by 24%. Regarding duodenal flows of individual AA, across all diets, CPM predicted substantially greater (>10%) mean flows of Arg, His, Ile, Met, and Lys; AMTS predicted greater flow for Arg and Met, whereas AC and NRC estimations were, on average, within 10% of observed values. Overpredictions by the CPM model were mainly related to mean bias, whereas the NRC model had the highest proportion of bias in random disturbance for flows of EAA. Models tended to predict mean flows of EAA more accurately on corn silage and alfalfa diets than on grass-based diets, more accurately on corn grain-based diets than on non-corn-based diets, and finally more accurately in the mid range of diet types. The 4 models were accurate at predicting mean dry matter intake. The AC, AMTS, and NRC models were all sufficiently accurate to be used for balancing EAA in dairy rations under field conditions.