Relationships between gastrointestinal permeability, heat stress, and milk production in lactating dairy cows.

Heat stress (HS) is a global issue that decreases farm profits and compromises animal welfare. To distinguish between the direct and indirect effects of HS, 16 multiparous Holstein cows approximately 100 DIM were assigned to one of 2 treatments: pair fed to match HS cow intake, housed in thermoneutral conditions (PFTN, n = 8) or cyclical HS (n = 8). All cows were subjected to 2 experimental periods. Period 1 consisted of a 4 d thermoneutral period with ad libitum intake. During period 2 (P2), the HS cows were housed in cyclical HS conditions with a temperature-humidity index (THI) ranging from 76 to 80 and the PFTN cows were exposed to a constant THI of 64 for 4 d. Dry matter intake of the PFTN cows was intake matched to the HS cows. Milk yield, milk composition, rectal temperature, and respiration rate were recorded twice daily, blood was collected daily via a jugular catheter, and cows were fed twice daily. On d 3 of each period, Cr-EDTA and sucralose were orally administered and recovered via 24 h total urine collection to assess gastrointestinal permeability. All data were analyzed using the GLIMMIX procedure in SAS. The daily data collected in P1 was averaged and used as a covariate if deemed significant in the model. Heat stress decreased voluntary feed intake by 35% and increased rectal temperature and respiration rate (38.4°C vs. 39.4°C and 40 vs. 71 respirations/min, respectively). Heat stress reduced DMI by 35%, which accounted for 66% of the decrease in milk yield. The yields, and not concentrations, of milk protein, fat, and other solids were lower in the HS cows on d 4 of P2. Milk urea nitrogen was higher and plasma urea nitrogen tended to be higher on d 3 and d 4 of HS. Glucose was 7% lower in the HS cows and insulin was 71% higher in the HS cows than the PFTN cows on d 4 of P2. No difference in lipopolysaccharide-binding protein was observed. Heat stress cows produced 7 L/d more urine than PFTN cows. No differences were detected in the urine concentration or percentage of the oral dose recovered for Cr-EDTA or sucralose. In conclusion, HS was responsible for 34% of the reduction of milk yield. The elevated MUN and the tendency for elevated plasma urea nitrogen indicate a whole-body shift in nitrogen metabolism. No differences in gastrointestinal permeability or lipopolysaccharide-binding protein were observed. These results indicate that, under the conditions of this experiment, activation of the immune system by gut-derived lipopolysaccharide was not responsible for the decreased milk yield observed during HS.

A meta-analysis of the relationship between milk protein production and absorbed amino acids and digested energy in dairy cattle.

Milk protein production is the largest draw on AA supplies for lactating dairy cattle. Prior NRC predictions of milk protein production have been absorbed protein (MP)-based and utilized a first-limiting nutrient concept to integrate the effects of energy and protein, which yielded poor accuracy and precision (root mean squared error (RMSE) > 21%). Using a meta-data set gathered, various alternative equation forms considering MP, absorbed total essential AA (EAA), absorbed individual EAA, and digested energy (DE) supplies as additive drivers of production were evaluated, and all were found to be superior in statistical performance to the first limitation approach (RMSE = 14-15%). Inclusion of DE intake and a quadratic term for MP or absorbed EAA supplies were found to be necessary to achieve intercept estimates (non-productive protein use) that were similar to the factorial estimates of NASEM. The partial linear slope for MP was found to be 0.409, which is consistent with the observed slope bias of -0.34g/g when a slope of 0.67 was used for MP efficiency in a first-limiting nutrient system. Replacement of MP with the supplies of individual absorbed EAA expressed in g/d and a common quadratic across the EAA resulted in unbiased predictions with improved statistical performance as compared with MP-based models. Based on Akaike's Information Criterion (AIC) and biological consistency, the best equations included absorbed His, Ile, Lys, Met, Thr, the non-essential AA, and individual DE intakes from fatty acids, neutral detergent fiber, residual organic matter, and starch. Several also contained a term for absorbed Leu. These equations generally had RMSE of 14.3% and a concordance correlations (CCC) of 0.76. Based on the common quadratic and individual linear terms, milk protein response plateaus were predicted at approximately 320 g/d of absorbed His, Ile, and Lys; 395 g/d of absorbed Thr; 550 g/d of absorbed Met; and 70 g/d of absorbed Leu. Therefore, responses to each except Leu are almost linear throughout the normal in vivo range. De-aggregation of the quadratic term and parsing to individual absorbed EAA resulted in non-biological estimates for several EAA indicating over-parameterization. Expression of the EAA as g/100 g of total absorbed EAA or as ratios of DE intake and using linear and quadratic terms for each EAA resulted in similar statistical performance, but the solutions had identifiability problems and several non-biological parameter estimates. The use of ratios also introduced nonlinearity in the independent variables which violates linear regression assumptions. Further screening of the global model using absorbed EAA expressed as g/d with a common quadratic using an all-models approach, and exhaustive cross-evaluation indicated the parameter estimates for body weight, all 4 DE terms, His, Ile, Lys, Met, and the common quadratic term were stable, while estimates for Leu and Thr were known with less certainty. Use of independent and additive terms and a quadratic expression in the equation results in variable efficiencies of conversion. The additivity also provides partial substitution among the nutrients. Both of these prevent establishment of fixed nutrient requirements in support of milk protein production.

Ability of three dairy feed evaluation systems to predict postruminal outflows of amino acids in dairy cows: A meta-analysis.

Adequate prediction of postruminal outflows of essential AA (EAA) is the starting point of balancing rations for EAA 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 version 6.5.5 [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict EAA outflows (Trp was not tested). The data set included a total of 354 treatment means from 70 duodenal and 24 omasal studies. To avoid Type I error, mean and linear biases were considered of concern if statistically significant and representing >5.0% of the observed mean. Analyses were conducted on raw observed values and on observations adjusted for the random effect of study. The analysis on raw data indicates the ability of the feed evaluation system to predict absolute values whereas the analysis on adjusted values indicates its ability to predict responses of EAA outflows to dietary changes. For the prediction of absolute values (based on raw data), NRC underpredicted outflows of all EAA, from 5.3% to 8.6% of the observed mean (%obs.mean) except for Leu, Lys, and Val; NASEM overpredicted Lys (10.8%obs.mean); and CNCPS overpredicted Arg, His, Lys, Met, and Val (5.2 to 26.0%obs.mean). No EAA had a linear bias of concern with NASEM, followed by NRC for His (6.8%obs.mean), and CNCPS for all EAA (5.6 to 12.2%obs.mean) except Leu, Phe, and Thr. In contrast, for the prediction of responses to dietary changes (based on adjusted data), NRC had 2 EAA presenting a linear bias of concern, followed by NASEM and CNCPS with 4 and 6 EAA, respectively. Predictions of His showed a linear bias of concern (5.3 to 9.6%obs.mean) with the 3 feed evaluation systems. Measured chemistry of crude protein and EAA were reported for 1 or more feed ingredients of the ration in 36% of the studies, and resulted in decreased linear biases in the 3 feed evaluation systems. The difference in mean biases of Met outflows was systematically positive when comparing omasal versus duodenal studies. Predictions of Met outflows with NRC had a higher concordance correlation coefficient in duodenal (used to develop NRC equations) versus omasal studies, whereas the opposite was observed with CNCPS, the latter showing the lowest mean bias for Met in omasal sampling studies. The 30% difference in Met mean biases between sampling sites appeared related to a similar difference found for observed Met versus nonammonia nitrogen outflows between duodenal and omasal studies, which is independent of predictions. In conclusion, NRC and NASEM yielded accurate predictions of EAA outflows, with a small superiority of NASEM to predict absolute values, and slight superiority of NRC to predict the responses to dietary changes. In comparison, CNCPS may present mean and linear biases of concern for many EAA. Moreover, it remains to determine which sampling site is more representative of the true supply of EAA to the cows.

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.

Effects of rumen-encapsulated methionine and lysine supplementation and low dietary protein on nitrogen efficiency and lactation performance of dairy cows.

Low crude protein (CP) diets might be fed to dairy cows without affecting productivity if the balance of absorbed AA were improved, which would decrease the environmental effect of dairy farms. The aim of this study was to investigate the effects of supplementing ruminally protected Lys (RPL) and Met (RPM) at 2 levels of dietary CP on nutrient intake, milk production, milk composition, milk N efficiency (MNE), and plasma concentrations of AA in lactating Holstein cows and to evaluate these effects against the predictions of the new NASEM (2021) model. Fifteen multiparous cows were used in a replicated 3 × 3 Latin square design with 21-d periods. The 3 treatments were (1) a high-protein (HP) basal diet containing 16.4% CP (metabolizable protein [MP] balance of -130 g/d; 95% of target values), (2) a medium-protein diet containing 15% CP plus RPL (60 g/cow per day) and RPM (25 g/cow per day; MPLM; MP balance of -314 g/d; 87% of target values), and (3) a low-protein diet containing 13.6% CP plus RPL (60 g/cow per day) and RPM (25 g/cow per day; LPLM; MP balance of -479 g/d; 80% of target values). Dry matter intake was less for cows fed MPLM and LPLM diets compared with those fed the HP diet. Compared with the HP diet, the intake of CP, neutral detergent fiber, acid detergent fiber, and organic matter, but not starch, was lower for cows fed MPLM and LPLM diets. Milk production and composition were not affected by MPLM or LPLM diets relative to the HP diet. Milk urea N concentrations were reduced for the MPLM and LPLM diets compared with the HP diet, indicating that providing a low-protein diet supplemented with rumen-protected AA led to greater N efficiency. There was no significant effect of treatment on plasma AA concentrations except for proline, which significantly increased for the MPLM treatment compared with the other 2 treatments. Overall, the results supported the concept that milk performance might be maintained when feeding lactating dairy cows with low CP diets if the absorbed AA balance is maintained through RPL and RPM feeding. Further investigations are needed to evaluate responses over a longer time period with consideration of all AA rather than on the more aggregated MP and the ratio between Lys and Met.

Graduate Student Literature Review: System, plant, and animal factors controlling dietary pasture inclusion and their impact on ration formulation for dairy cows.

Diet formulation in a pasture-based dairy system is a challenge as the quality and quantity of available pasture, which generally constitutes the base diet, is constantly changing. The objective of this paper is to cover a more in-depth review of the nutritional characteristics of pasture-based diets, identifying potential system, plant, and animal factors that condition pasture dietary inclusion in dairy cows. In practice, there is a wide diversity of pasture-based systems with predominant to minimal use of pasture requiring a more specific classification that potentially considers the amount and time of access to pasture, access to housing, length of grazing season, seasonality of calving, and level and method of supplementation. There are important differences in the nutritional quality between pasture species and even cultivars. However, under management practices that promote maintenance of pasture in a vegetative state as well as controlling the availability of pasture, it is possible to achieve high dry matter intakes (∼2.9%-3.4% of live weight) of pasture with moderate to high diet energy density, protein supply, and digestibility. The amount of pasture to include in the diet will depend on several factors, such as the type of production system, the cost of supplementary feeds, and the farmer's objectives, but inclusions of ∼40% to 50% of the diet seem to potentially reduce costs while apparently not limiting voluntary feed intake. Considering that there seems to be a continuum of intermediate management systems, a better understanding of the factors inherent to the feed ingredients used, as well as the use of nutrients by cows, and potential interactions between animal × system should be addressed in greater depth. This requires a meta-analysis approach, but given the diversity of the pasture-based system in practice, the existing information is highly fragmented. A clear definition of "subsystems" is necessary to direct the future research and development of mechanistic 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.

Effects of dietary starch and ruminally undegraded protein on glucogenic precursors in lactating dairy cows.

Gluconeogenesis is a large contributor to the blood supply of glucose carbons. The impact of varying dietary starch and ruminally degraded protein (RDP) on glucose entry, and the contributions of propionate and lactate to total plasma glucose entry were evaluated. Six cannulated, lactating, Holstein cows were fed one of four treatment diets arranged as a 2 × 2 factorial within a 4 × 4 partially replicated Latin Square design: (1) 8% RDP (LRDP) and 16% starch (LSt), (2) LRDP and 30% starch (HSt), (3) 11% RDP (HRDP) and LSt, or (4) HRDP and HSt. On d 12 of each period, 2-[13C]-sodium propionate (0.15 g/h) was ruminally infused for 4 h; on d 13, 1,2-[13C2]-glucose (0.2 g/h) was infused into the jugular vein for 1 h followed by 1-[13C]-lactate (0.1 g/h) for 1 h. Blood samples were serially collected starting prior to the infusions, and analyzed for plasma glucose, propionate, and lactate isotopic ratios. A one-compartment, glucose carbon model with inputs from lactate, propionate, and other glucogenic precursors (Oth, primarily absorbed glucose plus amino acids) was fitted to the isotope ratio data to derive glucose entry rates and conversion of the precursors to glucose. Milk protein production additively increased when HSt and HRDP were fed (P = 0.05 and P = 0.02, respectively). Plasma glucose and propionate concentrations increased with HSt (P = 0.04 and P = 0.01, respectively) and LRDP (P = 0.02 and P < 0.01, respectively). Total glucose and Oth entry increased (P = 0.03 and P = 0.03, respectively) with HSt, indicating greater glucose absorption from the small intestine or conversion of amino acids to glucose in the liver. However, neither entry rate was affected by RDP. The lack of an RDP effect suggests the increase in microbial outflow in response to RDP did not significantly alter glucose precursor supplies. Entry rates of propionate and lactate carbon to glucose carbon were not affected by treatment suggesting that neither starch nor RDP significantly affected fermentation or lactate production. Derivation of absolute entry rates and contributions to glucose using isotopic tracers is complicated by single carbon removals in the pentose phosphate (PPP), tri-carboxylic acid (TCA), and gluconeogenic pathways, and label randomization with the PPP and TCA pathways. Multiple tracers must be used to avoid assumptions regarding the proportional entries. These results provide insights on glucose supply and contributors, and draw attention to significant label cycling when utilizing isotope techniques.

Review: How the efficiency of utilization of essential amino acids can be applied in dairy cow nutrition.

How the efficiency of utilization of essential amino acids (EffUEAA) can be applied in dairy cow nutrition is presented in this review. The concept of EffUEAA proposed by the National Academies of Sciences, Engineering and Medicine (NASEM, 2021) is first detailed. It represents the proportion of the metabolisable essential amino acids (mEAA) supply used to support protein secretions and accretions (scurf, metabolic fecal, milk and growth). For these processes, the efficiency of each individual EAA is variable, and considered to vary similarly for all the protein secretions and accretions. The anabolic process of gestation is ascribed to a constant efficiency (33%), whereas the efficiency of endogenous urinary loss (EndoUri) is set at 100%. Therefore, the NASEM model EffUEAA was calculated as the sum of EAA in the true protein of secretions and accretions divided by the available EAA (mEAA - EndoUri - gestation net true protein/0.33). In this paper, the reliability of this mathematical calculation was tested through an example where the experimental efficiency of His was calculated assuming that liver removal represents catabolism. The NASEM model and experimental efficiencies were in the same range and varied in similar manner. Assuming that the NASEM model EffUEAA reflects EAA metabolism in the dairy cow, its different applications were examined. In NASEM, target efficiencies were determined for each EAA: 75, 71, 73, 72, 73, 60, 64, 86 and 74% for His, Ile, Leu, Lys, Met, Phe, Thr, Trp, and Val, respectively. From these, recommendations for mEAA supply can be calculated as: [(secretions + accretions)/(target EffUEAA × 0.01) + EndoUri + gestation/0.33], assuming energy supply is adequate. In addition to NASEM propositions, equations to predict EffUEAA with precision and accuracy are detailed, using the ratio of (mEAA-EndoUri) to digestible energy intake, in a quadratic model that includes days in milk. Moreover, milk true protein yield predictions from predicted EffUEAA or efficiency of utilization of metabolisable protein are better than those from the multivariate equation of NASEM (2021) and superior to those predicted with a fixed efficiency. Finally, either the NASEM model or the predicted EffUEAA can be used to assess the responsiveness of a ration to supplementation with a single EAA. If the EffUEAA of the EAA to supplement is higher than the target EffUEAA, while the EffUEAA of the other EAA are lower than the target value, this suggests a potential improvement in milk true protein yield to supplementation with this EAA.

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.

Effects of acetate, propionate, and pH on volatile fatty acid thermodynamics in continuous cultures of ruminal contents.

To investigate the effects of acetate, propionate, and pH on thermodynamics of volatile fatty acids (VFA) in the rumen, a dual-flow continuous culture study was conducted to quantify production of major VFA, interconversions among the VFA, and H2 and CH4 emissions in a 4 × 4 Latin square design. The 4 treatments were (1) control: pH buffered to an average of 6.75; (2) control plus 20 mmol/d of infused acetate (InfAc); (3) control plus 7 mmol/d of infused propionate (InfPr); and (4) a 0.5-unit decline in pH elicited by adjustment of the buffer (LowpH). All fermentors were fed 40 g of a pelleted diet containing whole alfalfa pellets and concentrate mix pellets (50:50) once daily. After 7 d of treatment, sequential, continuous infusions of [2-13C] sodium acetate (3.5 mmol/d), [U-13C] sodium propionate (2.9 mmol/d), and [1-13C] sodium butyrate (0.22 mmol/d) were carried out from 12 h before feeding for 36 h. Filtered liquid effluent (4 mL) was sampled at 0, 2, 4, 6, 8, 12, 16, and 22 h after feeding, and assessed for VFA concentrations, with another filtered sample (20 mL) used to quantify aqueous concentrations of CH4 and H2. Headspace CH4 and H2 gases were monitored continuously. Ruminal microbes were isolated from the mixed effluent samples, and the microbial community structure was analyzed using the 16S rRNA amplicon sequencing technique. The digestibility of neutral detergent fiber, acid detergent fiber, and starch and microbial C sequestrated from VFA were not affected by treatments. The LowpH treatment increased net propionate production and decreased H2 and CH4 headspace emissions, primarily due to shifts in metabolic pathways of VFA formation, likely due to the observed changes in bacterial community structure. Significant interconversions occurred between acetate and butyrate, whereas interconversions of other VFA with propionate were relatively small. The InfAc and InfPr treatments increased net acetate and propionate production, respectively; however, interconversions among VFA were not affected by pH, acetate, or propionate treatments, suggesting that thermodynamics might not be a primary influencer of metabolic pathways used for VFA formation.

Models to predict milk fat concentration and yield of lactating dairy cows: A meta-analysis.

Few models have attempted to predict total milk fat because of its high variation among and within herds. The objective of this meta-analysis was to develop models to predict milk fat concentration and yield of lactating dairy cows. Data from 158 studies consisting of 658 treatments from 2,843 animals were used. Data from several feed databases were used to calculate dietary nutrients when dietary nutrient composition was not reported. Digested intake (DI, g/d) of each fatty acid (FA; C12:0, C14:0, C16:0, C16:1, C18:0, C18:1 cis, C18:1 trans C18:2, C18:3) and absorbed amounts (g/d) of each AA (Arg, His, Ile, Leu, Lys, Met, Phe, Thr, Trp, Val) were calculated and used as candidate variables in the models. A multi-model inference method was used to fit a large set of mixed models with study as the random effect, and the best models were selected based on Akaike's information criterion corrected for sample size and evaluated further. Observed milk fat concentration (MFC) ranged from 2.26 to 4.78%, and milk fat yield (MFY) ranged from 0.488 to 1.787 kg/d among studies. Dietary levels of forage, starch, and total FA (dry matter basis) averaged 50.8 ± 10.3% (mean ± standard deviation), 27.5 ± 7.0%, and 3.4 ± 1.3%, respectively. The MFC was positively correlated with dietary forage (0.294) and negatively associated with dietary starch (-0.286). The DI of C18:2 (g/d) was more negatively correlated with MFC (-0.313) than that of the other FA. The best variables for predicting MFC were days in milk, FA-free dry matter intake, forage, starch, DI of C18:2, DI of C18:3, and absorbed Met, His, and Trp. The best predictor variables for MFY were FA-free dry matter intake, days in milk, absorbed Met and Ile, and intakes of digested C16:0 and C18:3. This model had a root mean square error of 14.1% and concordance correlation coefficient of 0.81. Surprisingly, DI of C18:3 was positively related to milk fat, and this relationship was consistently observed among models. The models developed can be used as a practical tool for predicting milk fat of dairy cows, while recognizing that additional factors are likely to also affect fat yield.

Comparison of Molly and Karoline models to predict methane production in growing and dairy cattle.

Numerous empirical and mechanistic models predicting methane (CH4) production are available. The aim of this work was to evaluate the Molly cow model and the Nordic cow model Karoline in predicting CH4 production in cattle using a data set consisting of 267 treatment means from 55 respiration chamber studies. The dietary and animal characteristics used for the model evaluation represent the range of diets fed to dairy and growing cattle. Feedlot diets and diets containing additives mitigating CH4 production were not included in the data set. The relationships between observed and predicted CH4 (pCH4) were assessed by regression analysis using fixed and mixed model analysis. Residual analysis was conducted to evaluate which dietary factors were related to prediction errors. The fixed model analysis showed that the Molly predictions were related to the observed data (± standard error) as CH4 (g/d) = 0.94 (±0.022) × pCH4 (g/d) + 31 (±6.9) [root mean squared prediction error (RMSPE) = 45.0 g/d (14.9% of observed mean), concordance correlation coefficient (CCC) = 0.925]. The corresponding equation for the Karoline model was CH4 (g/d) = CH4 (g/d) = 0.98 (±0.019) × pCH4 (g/d) + 7.0 (±6.0) [RMSPE = 35.0 g/d (11.6%), CCC = 0.953]. Proportions of mean squared prediction error attributable to mean and linear bias and random error were 10.6, 2.2, and 87.2% for the Molly model, and 1.3, 0.3, and 98.6% for the Karoline model, respectively. Mean and linear bias were significant for the Molly model but not for the Karoline model. With the mixed model regression analysis RMSPE adjusted for random study effects were 10.9 and 7.9% for the Molly model and the Karoline model, respectively. The residuals of CH4 predictions were more strongly related to factors associated with CH4 production (feeding level, digestibility, fat concentrations) with the Molly model compared with the Karoline model. Especially large mean (underprediction) and linear bias (overprediction of low digestibility diets relative to high digestibility diets) contributed to the prediction error of CH4 yield with the Molly model. It was concluded that both models could be used for prediction of CH4 production in cattle, but Karoline was more accurate and precise based on smaller RMSPE, mean bias, and slope bias, and greater CCC. The importance of accurate input data of key variables affecting diet digestibility is emphasized.

Physiological responses of Holstein calves to heat stress and dietary supplementation with a postbiotic from Aspergillus oryzae.

Increased ambient temperature causes heat stress in mammals, which affects physiological and molecular functions. We have recently reported that the dietary administration of a postbiotic from Aspergillus oryzae (AO) improves tolerance to heat stress in fruit flies and cattle. Furthermore, heat-induced gut dysfunction and systemic inflammation have been ameliorated in part by nutritional interventions. The objective of this study was to characterize the phenotypic response of growing calves to heat stress compared to thermoneutral ad libitum fed and thermoneutral feed-restricted counterparts and examining the physiologic alterations associated with the administration of the AO postbiotic to heat-stressed calves with emphasis on intestinal permeability. In this report, we expand previous work by first demonstrating that heat stress reduced partial energetic efficiency of growth in control (45%) but not in AO-fed calves (62%) compared to thermoneutral animals (66%). While heat stress increased 20% the permeability of the intestine, AO postbiotic and thermoneutral treatments did not affect this variable. In addition, AO postbiotic reduced fecal water content relative to thermoneutral and heat stress treatments. Heat stress increased plasma concentrations of serum amyloid A, haptoglobin and lipocalin-2, and administration of AO postbiotic did not ameliorate this effect. In summary, our findings indicated that heat stress led to reduced nutrient-use efficiency and increased systemic inflammation. Results suggest that the AO postbiotic improved energy-use efficiency, water absorption, and the intestinal permeability in heat stress-mediated increase in gut permeability but did not reduce heat stress-mediated rise in markers of systemic inflammation.

Importance of considering body weight change in response to dietary protein deficiency in lactating dairy cows.

Our objective was to quantify the contribution of body weight (BW) change to the overall response of lactating dairy cows to a shortage of dietary protein. Lactating Holstein cows (n = 166; 92 primiparous, 74 multiparous) with initial milk yield of 41 ± 10 kg/d were fed high and low-protein diets in 7 blocks. Blocks were repeated in the same crossover design with periods of 28 to 35 d. Production of 69 of the 166 cows (42 primiparous, 27 multiparous) was also measured in late lactation. Low-protein diets were 14% crude protein (CP) in peak lactation and 13% CP in late lactation and were formulated to contain adequate rumen-degradable protein to maintain rumen function but inadequate rumen undegradable protein for the average cow in this study. High-protein diets were 18% CP in peak lactation and 16% CP in late lactation and contained extra expeller soybean meal to meet metabolizable protein requirements. Body weight changes were used to predict body energy and protein changes, which were added to milk components to calculate total captured energy and protein. Fixed effects of diet, parity, treatment sequence nested in each block, treatment period nested in block, interaction of diet and parity, and the random effects of block and cow nested within block were included in the model to compare cow responses to diets within each lactation stage. In peak lactation, reducing protein from 18 to 14% resulted in estimated daily losses of 2.9 Mcal of milk energy, 2.2 Mcal of body energy, 127 g of milk protein, and 16 g of body protein. Therefore, BW loss accounted for 43% of the decrease in captured energy and 11% of the decrease in captured protein when cows were fed deficient protein. In late lactation, BW loss accounted for 51% of the decrease in captured energy and 14% of the decrease in captured protein when cows were fed deficient protein. We suggest that BW change should be considered when assessing cow responses to changes in dietary protein.

Evaluation of Molly model predictions of ruminal fermentation, nutrient digestion, and performance by dairy cows consuming ryegrass-based diets.

Several studies have been conducted to improve grazing management and supplementation in pasture-based systems. However, it is necessary to develop tools that integrate the available information linking the representation of biological processes with animal performance for use in decision making. The objective of this study was to evaluate the precision and accuracy of the Molly cow model predictions of ruminal fermentation, nutrient digestion, and animal performance by cows consuming pasture-based diets to identify model strengths and weaknesses, and to derive new digestive parameters when relevant. Model modifications for adipose tissue, protein synthesis in lean body mass and viscera representation were included. Data used for model evaluations were collected from 25 publications containing 115 treatment means sourced from studies conducted with lactating dairy cattle. The inclusion criteria were that diets contained ≥45% perennial ryegrass (Lolium perenne L.), and that dry matter intake, dietary ingredient composition, and nutrient digestion observations were reported. Animal performance and N excretion variables were also included if they were reported. Model performance was assessed before and after model reparameterization of selected digestive parameters, global sensitivity analysis was conducted after reparameterization, and a 5-fold cross evaluation was performed. Although rumen fermentation predictions were not significantly improved, rumen volatile fatty acids absorption rates were recalculated, which improved the concordance correlation coefficient (CCC) for rumen propionate and ammonia concentration predictions but decreased CCC for acetate predictions. Similar degradation rates of crude protein were observed for grass and total mixed ration diets, but rumen-undegradable protein predictions seemed to be affected by the solubility of the protein source as was the intestinal digestibility coefficient. Ruminal fiber degradation was greater after reparameterization, driven primarily by hemicellulose degradation. Predictions of ruminal and fecal outflow of neutral detergent fiber and acid detergent fiber, as well as total fecal output predictions, improved significantly after reparameterization. Blood urea N and urinary N excretion predictions resulted in similar accuracy using both sets of model parameters, whereas fecal N excretion predictions were significantly improved after reparameterization. Body weight and body condition score predictions were greatly improved after model modifications and reparameterization. Before reparameterization, yield predictions for daily milk, milk fat, milk protein, and milk lactose were greatly overestimated (mean bias of 61.0, 58.7, 73.7, and 64.6% of mean squared error, respectively). Although this problem was partially addressed by model modifications and reparameterization (mean bias of 3.2, 1.1, 1.7, and 0.4% of mean squared error, respectively), CCC values were still small. The ability of the model to predict grass digestion and animal performance in dairy cows consuming pasture-based diets was improved, demonstrating the applicability of this model to these productive systems. However, the failure to predict grass digestion based on standard model inputs without reparameterization indicates there are still fundamental challenges in characterizing feeds for this model.

Effects of varying extracellular amino acid concentrations on bidirectional amino acid transport and intracellular fluxes in mammary epithelial cells.

Understanding the regulation of cellular AA uptake as protein supply changes is critical for predicting milk component yields because intracellular supplies partly regulate protein synthesis. Our objective was to evaluate cellular uptake and kinetic behavior of individual AA when cells are presented with varying extracellular AA supplies. Bovine primary mammary epithelial cells were grown to confluency and transferred to medium with an AA profile and concentration similar to that of plasma from dairy cows for 24 h. Treatments were 4 AA concentrations, 0.36, 2.30, 4.28, and 6.24 mM, which represented 16, 100, 186, and 271% of typical plasma AA concentrations, respectively, in lactating dairy cows. Twenty-four plates of cells (89.4 × 19.2 mm) were assigned to each treatment. Cells were first subjected to treatment medium enriched with 15N-labeled AA for 24 h and then incubated with treatment medium enriched with 13C-labeled AA for 0, 15, 60, 300, 900, 1,800, and 3,600 s. Intracellular free AA, intracellular protein-bound AA, and extracellular medium free AA were analyzed for concentrations and isotopic enrichment using gas chromatography-mass spectrometry. A dynamic, 12-pool model was fitted to the data for 14 AA to derive unidirectional uptake and efflux, protein turnover, transamination, oxidation, and synthesis. The derived concentration for half the maximal uptake (km) indicated no saturation of AA uptake at typical in vivo concentrations for 11 of the 14 AA. Arginine, Pro, and Val appeared to exhibit saturation kinetics. Net uptake of all essential AA except Phe was positive across treatments. Most nonessential AA exhibited negative net uptake values. Efflux of AA was quite high, with several AA exhibiting greater than 100% efflux of the respective influx. Intracellular pool turnover was rapid for most AA (e.g., 2 min for Arg), demonstrating plasticity in matching needs for protein translation to supplies. Intracellular AA concentrations increased linearly in response to treatment for most AA, whereas 9 AA exhibited quadratic responses. Amino acid uptake is responsive to varying extracellular supplies to maintain homeostasis. No saturation of uptake was evident for most AA, indicating that transporter capacity is likely not a limitation for most AA except possibly Arg, Val, and Pro in mammary epithelial cells.

Predicting ruminally undegraded and microbial protein flows from the rumen.

The objectives of the present work were (1) to identify the cause of the linear bias in predictions of rumen-undegradable protein (RUP) content of feeds, and devise methods to remove the bias from prediction equations, and (2) to further explore the impact of rumen-degradable protein (RDP) on microbial N (MiN) outflow from the rumen. The kinetic model used by NRC (2001), which is based on protein fractionation and rates of degradation (Kd) and passage (Kp), displays considerable slope bias (-0.30 kg/kg), indicating parameter or structural problems. Regressing Kp by feed class and a static adjustment factor for the in situ-derived Kd on observed RUP flows completely resolved the slope bias problem, and the model performed significantly better than models using unadjusted Kd and marker-based Kp. The Kd adjustment was 3.82%/h, which represents approximately a 50% increase in rates of degradation over the in situ values, indicating that in situ analyses severely underestimate true rates of protein degradation. The Kp for concentrate-derived protein was 5.83%/h, which was slightly less than the marker-predicted rate of 6.69%/h. However, the derived forage protein rate was 0.49%/h, which was considerably less than the marker-based rate of 5.07%/h. Compartmental analysis of data from a single study corroborated the regression analysis, indicating that a 25% reduction in the overall passage rate and an 87% increase in the rate of degradation were required to align ruminal N pool sizes and the extent of protein degradation with the observed data. Therefore, one must conclude that both the in situ-derived degradation rates and the marker-based particle passage rates are biased relative to protein passage and cannot be used directly to predict RUP outflow from the rumen. The effects of RDP supply on microbial nitrogen (MiN) flow were apparent when intakes of individual nutrients were offered but not when DM intake and individual nutrient concentrations were offered, due to collinearity problems. Microbial N flow from the rumen was found to be linearly related to ruminally degraded starch, ruminally degraded neutral detergent fiber (NDF), RDP, and forage NDF intakes; and quadratically related to residual OM intake. More complicated models containing 2- and 3-way interactions among nutrients were also supported by the data. Independent MiN responses to RDP, ruminally degraded starch, and ruminally degraded NDF aligned with the expected responses to each of those nutrients. Nonlinear representations of MiN were found to be inferior to the linear models. Despite using unbiased predictions of RUP and MiN as drivers of AA flows, predictions of Arg, His, Ile, and Lys flow exhibited linear slope bias relative to the observed data, indicating that representations of the AA composition of the proteins may be biased or the observed data are biased. This is an improvement over the NRC (2001) predictions, where bias adjustments were required for all of the essential AA. Despite the bias for 4 AA flows, the revised prediction system was a substantial improvement over the prior work.

Milk urea nitrogen variation explained by differences in urea transport into the gastrointestinal tract in lactating dairy cows.

Milk urea nitrogen (MUN) and blood urea nitrogen are correlated with nitrogen balance and nitrogen excretion; however, there is also a genetic component to MUN concentrations that could be associated with differences in urea transport. It was hypothesized that a portion of the variation in MUN concentrations among cows is caused by variation in gastrointestinal and kidney urea clearance rates. Eight lactating cows with varying MUN concentrations while fed a common diet were infused with [15N15N]urea to determine urea N entry rate (UER), gastrointestinal entry rate, returned to ornithine cycle, urea N used for anabolism, urea N excretion in feces and urine. Urea clearance rates by the kidneys and gastrointestinal tract were calculated from isotopic enrichment of urea excretion in urine and gut entry rate, respectively, and plasma urea N concentrations (PUN). Over the course of the experiment, animals weighed an average of 506 ± 62 kg and produced 26.3 ± 4.39 kg of milk/d, with MUN concentrations ranging from 11.6 to 17.3 mg/dL (average of 14.9 ± 2.1 mg/dL). Plasma urea N was positively correlated with UER, urea N excretion in urine, and urea N used for anabolism. Plasma urea N and MUN were negatively correlated with gut clearance rates and ratio of gastrointestinal entry rate to UER. This relationship supports the hypothesis that differences in gut urea transport activity among animals causes variation in PUN and MUN concentrations, and that cows with high PUN and MUN are less efficient at recycling PUN to the gastrointestinal tract and thus may be more susceptible to ruminal N deficiencies when fed low RDP diets. Such biological variation in urea metabolism necessitates an adequate safety margin when setting regulations for maximal MUN levels as an indicator of herd N efficiency.