Effect of energy and protein supplementation on phosphorus utilization in lactating dairy cows

Two experiments were undertaken in which grass silage was used in conjunction with a series of different concentrate types designed to examine the effect of carbohydrate source, protein level and degradability on total dietary phosphorus (P) utilization with emphasis on P pollution. Twelve Holstein-Friesian dairy cows in early to mid-lactation were used in an incomplete changeover design with four periods consisting of 4 weeks each. Phosphorus intake ranged from 54 to 80 g/day and faecal P represented the principal route by which ingested P was disposed of by cows, with insignificant amounts being voided in urine. A positive linear relationship between faecal P and P intake was established. In Experiment 1, P utilization was affected by dietary carbohydrate type, with an associated output of 3.3 g faecal P/g milk P produced for all treatments except those utilizing low degradable starch and low protein supplements, where a mean value of 2.8 g faecal P/g milk P was observed. In Experiment 2, where two protein levels and three protein degradabilities were examined, the efficiency of P utilization for milk P production was not affected by either level or degradability of crude protein (CP) but a significant reduction in faecal P excretion due to lower protein and P intake was observed. In general, P utilization in Experiment 2 was substantially improved compared to the Experiment 1, with an associated output of 1.8 g faecal P/g milk P produced. The improved utilization of P in Experiment 2 could be due to lower P content of the diets offered and higher dry matter (DM) intake. For dairy cows weighing 600 kg, consuming 17-18 kg DM/day and producing about 25 kg milk, P excretion in faeces and hence P pollution to the environment might be minimized without compromising lactational performance by formulating diets to supply about 68 g P/day, which is close to recent published recommended requirements for P.

Energy and protein interactions and their effect on nitrogen excretion in dairy cows

The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.

Whole crop cereals 2. Prediction of apparent digestibility and energy value from in vitro digestion techniques and near infrared reflectance spectroscopy and of chemical composition by near infrared reflectance spectroscopy

Samples of whole crop wheat (WCW, n = 134) and whole crop barley (WCB, n = 16) were collected from commercial farms in the UK over a 2-year period (2003/2004 and 2004/2005). Near infrared reflectance spectroscopy (NIRS) was compared with laboratory and in vitro digestibility measures to predict digestible organic matter in the dry matter (DOMD) and metabolisable energy (ME) contents measured in vivo using sheep. Spectral models using the mean spectra of two scans were compared with those using individual spectra (duplicate spectra). Overall NIRS accurately predicted the concentration of chemical components in whole crop cereals apart from crude protein. ammonia-nitrogen, water-soluble carbohydrates, fermentation acids and solubility values. In addition. the spectral models had higher prediction power for in vivo DOMD and ME than chemical components or in vitro digestion methods. Overall there Was a benefit from the use of duplicate spectra rather than mean spectra and this was especially so for predicting in vivo DOMD and ME where the sample population size was smaller. The spectral models derived deal equally well with WCW and WCB and Would he of considerable practical value allowing rapid determination of nutritive value of these forages before their use in diets of productive animals. (C) 2008 Elsevier B.V. All rights reserved.

Comparison of energy evaluation systems and a mechanistic model for milk production by dairy cattle offered fresh grass-based diets

Grass-based diets are of increasing social-economic importance in dairy cattle farming, but their low supply of glucogenic nutrients may limit the production of milk. Current evaluation systems that assess the energy supply and requirements are based on metabolisable energy (ME) or net energy (NE). These systems do not consider the characteristics of the energy delivering nutrients. In contrast, mechanistic models take into account the site of digestion, the type of nutrient absorbed and the type of nutrient required for production of milk constituents, and may therefore give a better prediction of supply and requirement of nutrients. The objective of the present study is to compare the ability of three energy evaluation systems, viz. the Dutch NE system, the agricultural and food research council (AFRC) ME system, and the feed into milk (FIM) ME system, and of a mechanistic model based on Dijkstra et al. [Simulation of digestion in cattle fed sugar cane: prediction of nutrient supply for milk production with locally available supplements. J. Agric. Sci., Cambridge 127, 247-60] and Mills et al. [A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation and application. J. Anim. Sci. 79, 1584-97] to predict the feed value of grass-based diets for milk production. The dataset for evaluation consists of 41 treatments of grass-based diets (at least 0.75 g ryegrass/g diet on DM basis). For each model, the predicted energy or nutrient supply, based on observed intake, was compared with predicted requirement based on observed performance. Assessment of the error of energy or nutrient supply relative to requirement is made by calculation of mean square prediction error (MSPE) and by concordance correlation coefficient (CCC). All energy evaluation systems predicted energy requirement to be lower (6-11%) than energy supply. The root MSPE (expressed as a proportion of the supply) was lowest for the mechanistic model (0.061), followed by the Dutch NE system (0.082), FIM ME system (0.097) and AFRCME system(0.118). For the energy evaluation systems, the error due to overall bias of prediction dominated the MSPE, whereas for the mechanistic model, proportionally 0.76 of MSPE was due to random variation. CCC analysis confirmed the higher accuracy and precision of the mechanistic model compared with energy evaluation systems. The error of prediction was positively related to grass protein content for the Dutch NE system, and was also positively related to grass DMI level for all models. In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle. The mechanistic model predicted glucogenic nutrients to limit performance of dairy cattle on grass-based diets, and proved to be more accurate and precise than the energy systems. The mechanistic model could be improved by allowing glucose maintenance and utilization requirements parameters to be variable. (C) 2007 Elsevier B.V. All rights reserved.

Whole crop cereals 1. Effect of method of harvest and preservation on chemical composition, apparent digestibility and energy value

A total of 133 samples (53 fermented unprocessed, 19 fermented processed. 62 urea-treated processed) of whole crop wheat (WCW) and 16 samples (five fermented unprocessed, six fermented processed, five urea-treated processed) of whole crop barley (WCB) were collected from commercial farms over two consecutive years (2003/2004 and 2004/2005). Disruption of the maize grains to increase starch availability was achieved at the point of harvest by processors fitted to the forage harvesters. All samples were subjected to laboratory analysis whilst 50 of the samples (24 front Year 1, 26 front Year 2 all WCW except four WCB in Year 2) were subjected to in vivo digestibility and energy value measurements using mature wether sheep. Urea-treated WCW had higher (P<0.05) pH, and dry matter (DM) and crude protein contents and lower concentrations of fermentation products than fermented WCW. Starch was generally lower in fermented, unprocessed WCW and no effect of crop maturity at harvest (as indicated by DM content) on starch concentrations was seen. Urea-treated WCW had higher (P<0.05) in vivo digestible organic matter contents in the DM (DOMD) in Year 1 although this was not recorded in Year 2. There was a close relationship between the digestibility values of organic matter and gross energy thus aiding the use of DOMD to predict metabolisable energy (ME) content. A wide range of ME values was observed (WCW. 8.7-11.8 MJ/kg DM; WCB 7.9-11.2 MJ/kg DM) with the overall ME/DOMD ratio (ME = 0.0156 DOMD) in line With Studies in other forages. There was no evidence that a separate ME/DOMD relationship was needed for WCB which is helpful for practical application. This ratio and other parameters were affected by year of harvest (P<0.05) highlighting the influence of environmental and Other undefined factors. The variability in the composition and nutritive value of WCW and WCB highlights the need for reliable and accurate evaluation methods to be available to assess the Value of these forages before they are included in diets for dairy cows. (C) 2008 Elsevier B.V. All rights reserved.

Evaluation of NRC, UC Davis and ADAS approaches to estimate the metabolizable energy values of feeds at maintenance energy intake from equations utilizing chemical assays and in vitro determinations

Feed samples received by commercial analytical laboratories are often undefined or mixed varieties of forages, originate from various agronomic or geographical areas of the world, are mixtures (e.g., total mixed rations) and are often described incompletely or not at all. Six unified single equation approaches to predict the metabolizable energy (ME) value of feeds determined in sheep fed at maintenance ME intake were evaluated utilizing 78 individual feeds representing 17 different forages, grains, protein meals and by-product feedstuffs. The predictive approaches evaluated were two each from National Research Council [National Research Council (NRC), Nutrient Requirements of Dairy Cattle, seventh revised ed. National Academy Press, Washington, DC, USA, 2001], University of California at Davis (UC Davis) and ADAS (Stratford, UK). Slopes and intercepts for the two ADAS approaches that utilized in vitro digestibility of organic matter and either measured gross energy (GE), or a prediction of GE from component assays, and one UC Davis approach, based upon in vitro gas production and some component assays, differed from both unity and zero, respectively, while this was not the case for the two NRC and one UC Davis approach. However, within these latter three approaches, the goodness of fit (r(2)) increased from the NRC approach utilizing lignin (0.61) to the NRC approach utilizing 48 h in vitro digestion of neutral detergent fibre (NDF:0.72) and to the UC Davis approach utilizing a 30 h in vitro digestion of NDF (0.84). The reason for the difference between the precision of the NRC procedures was the failure of assayed lignin values to accurately predict 48 h in vitro digestion of NDF. However, differences among the six predictive approaches in the number of supporting assays, and their costs, as well as that the NRC approach is actually three related equations requiring categorical description of feeds (making them unsuitable for mixed feeds) while the ADAS and UC Davis approaches are single equations, suggests that the procedure of choice will vary dependent Upon local conditions, specific objectives and the feedstuffs to be evaluated. In contrast to the evaluation of the procedures among feedstuffs, no procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo, suggesting that the quest for an accurate and precise ME predictive approach among and within feeds, may remain to be identified. (C) 2004 Elsevier B.V. All rights reserved.

Limit-feeding a high-energy diet to meet energy requirements in the dry period alters plasma metabolite concentrations but does not affect intake or milk production in early lactation

Limit-feeding dry cows a high-energy diet may enable adequate energy intake to be sustained as parturition approaches, thus reducing the extent of negative energy balance after parturition. Our objective was to evaluate the effect of dry period feeding strategy on plasma concentrations of hormones and metabolites that reflect energy status. Multiparous Holstein cows (n = 18) were dried off 45 d before expected parturition, paired by expected calving date, parity, and previous lactation milk yield, and randomly assigned to 1 of 2 dry-period diets formulated to meet nutrient requirements at ad libitum or limited intakes. All cows were fed the same diet for ad libitum intake after parturition. Prepartum dry matter intake (DMI) for limit-fed cows was 9.4 kg/d vs. 13.7 kg/d for cows fed ad libitum. During the dry period, limit-fed cows consumed enough feed to meet calculated energy requirements, and ad libitum-fed cows were in positive calculated net energy for lactation (NEL) balance (0.02 vs. 6.37 Mcal/d, respectively). After parturition, milk yield, milk protein concentration, DMI, body condition score, and body weight were not affected by the prepartum treatments. Cows limit fed during the dry period had a less-negative calculated energy balance during wk 1 postpartum. Milk fat concentration and yield were greater for the ad libitum treatment during wk 1 but were lower in wk 2 and 3 postpartum. Plasma insulin and glucose concentrations decreased after calving. Plasma insulin concentration was greater in ad libitum-fed cows on d -2 relative to calving, but did not differ by dietary treatment at other times. Plasma glucose concentrations were lower before and after parturition for cows limit-fed during the dry period. Plasma nonesterified fatty acid concentrations peaked after parturition on d 1 and 4 for the limit-fed and ad libitum treatments, respectively, and were greater for limit-fed cows on d -18, -9, -5, and -2. Plasma tumor necrosis factor-alpha concentrations did not differ by treatment in either the pre- or postpartum period, but tended to decrease after parturition. Apart from a reduction in body energy loss in the first week after calving, limit feeding a higher NEL diet during the dry period had little effect on intake and milk production during the first month of lactation.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

Glycogen phosphorylase inhibitors: a free energy perturbation analysis of glucopyranose spirohydantoin analogues

GP catalyzes the phosphorylation of glycogen to Glc-1-P. Because of its fundamental role in the metabolism of glycogen, GP has been the target for a systematic structure-assisted design of inhibitory compounds, which could be of value in the therapeutic treatment of type 2 diabetes mellitus. The most potent catalytic-site inhibitor of GP identified to date is spirohydantoin of glucopyranose (hydan). In this work, we employ MD free energy simulations to calculate the relative binding affinities for GP of hydan and two spirohydantoin analogues, methyl-hydan and n-hydan, in which a hydrogen atom is replaced by a methyl- or amino group, respectively. The results are compared with the experimental relative affinities of these ligands, estimated by kinetic measurements of the ligand inhibition constants. The calculated binding affinity for methyl-hydan (relative to hydan) is 3.75 +/- 1.4 kcal/mol, in excellent agreement with the experimental value (3.6 +/- 0.2 kcal/mol). For n-hydan, the calculated value is 1.0 +/- 1.1 kcal/mol, somewhat smaller than the experimental result (2.3 +/- 0.1 kcal/mol). A free energy decomposition analysis shows that hydan makes optimum interactions with protein residues and specific water molecules in the catalytic site. In the other two ligands, structural perturbations of the active site by the additional methyl- or amino group reduce the corresponding binding affinities. The computed binding free energies are sensitive to the preference of a specific water molecule for two well-defined positions in the catalytic site. The behavior of this water is analyzed in detail, and the free energy profile for the translocation of the water between the two positions is evaluated. The results provide insights into the role of water molecules in modulating ligand binding affinities. A comparison of the interactions between a set of ligands and their surrounding groups in X-ray structures is often used in the interpretation of binding free energy differences and in guiding the design of new ligands. For the systems in this work, such an approach fails to estimate the order of relative binding strengths, in contrast to the rigorous free energy treatment.

Structure and biogenesis of the capsular F1 antigen from Yersinia pestis: Preserved folding energy drives fiber formation

Most gram-negative pathogens express fibrous adhesive virulence organelles that mediate targeting to the sites of infection. The F1 capsular antigen from the plague pathogen Yersinia pestis consists of linear fibers of a single subunit (Caf1) and serves as a prototype for nonpilus organelles assembled via the chaperone/usher pathway. Genetic data together with high-resolution X-ray structures corresponding to snapshots of the assembly process reveal the structural basis of fiber formation. Comparison of chaperone bound Caf1 subunit with the subunit in the fiber reveals a novel type of conformational change involving the entire hydrophobic core of the protein. The observed conformational change suggests that the chaperone traps a high-energy folding intermediate of Caf1. A model is proposed in which release of the subunit allows folding to be completed, driving fiber formation.

Evaluation of milk urea nitrogen as a diagnostic of protein feeding

An evaluation of milk urea nitrogen (MUN) as a diagnostic of protein feeding in dairy cows was performed using mean treatment data (n = 306) from 50 production trials conducted in Finland (n = 48) and Sweden (n = 2). Data were used to assess the effects of diet composition and certain animal characteristics on MUN and to derive relationships between MUN and the efficiency of N utilization for milk production and urinary N excretion. Relationships were developed using regression analysis based on either models of fixed factors or using mixed models that account for between-experiment variations. Dietary crude protein (CP) content was the best single predictor of MUN and accounted for proportionately 0.778 of total variance [ MUN (mg/dL) = -14.2 + 0.17 x dietary CP content (g/kg dry matter)]. The proportion of variation explained by this relationship increased to 0.952 when a mixed model including the random effects of study was used, but both the intercept and slope remained unchanged. Use of rumen degradable CP concentration in excess of predicted requirements, or the ratio of dietary CP to metabolizable energy as single predictors, did not explain more of the variation in MUN (R-2 = 0.767 or 0.778, respectively) than dietary CP content. Inclusion of other dietary factors with dietary CP content in bivariate models resulted in only marginally better predictions of MUN (R-2 = 0.785 to 0.804). Closer relationships existed between MUN and dietary factors when nutrients (CP to metabolizable energy) were expressed as concentrations in the diet, rather than absolute intakes. Furthermore, both MUN and MUN secretion (g/d) provided more accurate predictions of urinary N excretion (R-2 = 0.787 and 0.835, respectively) than measurements of the efficiency of N utilization for milk production (R-2 = 0.769). It is concluded that dietary CP content is the most important nutritional factor influencing MUN, and that measurements of MUN can be utilized as a diagnostic of protein feeding in the dairy cow and used to predict urinary N excretion.

Computational chemistry for elucidating protein function: energetics and dynamics of myoglobin-ligand systems

State-of-the-art computational methodologies are used to investigate the energetics and dynamics of photodissociated CO and NO in myoglobin (Mb···CO and Mb···NO). This includes the combination of molecular dynamics, ab initio MD, free energy sampling, and effective dynamics methods to compare the results with studies using X-ray crystallography and ultrafast spectroscopy metho ds. It is shown that modern simulation techniques along with careful description of the intermolecular interactions can give quantitative agreement with experiments on complex molecular systems. Based on this agreement predictions for as yet uncharacterized species can be made.

Effects of ammonia treatment and undegradable protein supplementation on nutrient digestion of sheep fed on wheat straw based diets.

A study was conducted to investigate the effects of wheat straw ammonisation and supplementation with a rumen undegradable protein (UDP) source on nutrient digestion and nitrogen balance by lambs while diets were supplemented with kibbled carob pods as energy source. Ammonisation increased the crude protein content of wheat straw by nearly 100% and decreased the contents of neutral detergent fibre and acid detergent fibre by 7% and 1.7% respectively. Treating the straw with ammonia resulted in significant (P<0.01) increase in nitrogen (N) intake and intakes of organic matter (OM) and dry matter (DM) tended toward significance (P<0.1). The UDP source had no effect (P>0.05) on DM and OM intakes but resulted in an increase (P<0.05) of N intakes. Both, ammonization and UDP supplementation increased (P<0.01) the DM, OM and N digestibility. In conclusion, the results of this study suggest that ammonisation and UDP supplementation is a practical dietary manipulation option to improve the nutritional status of ruminants fed on roughage-based diets.

Supranutritional selenium induces alterations in molecular targets related to energy metabolism in skeletal muscle and visceral adipose tissue of pigs

While selenium (Se) is an essential micronutrient for humans, epidemiological studies have raised concern that supranutritional Se intake may increase the risk to develop Type 2 diabetes mellitus (T2DM). We aimed to determine the impact of Se at a dose and source frequently ingested by humans on markers of insulin sensitivity and signalling. Male pigs were fed either a Se-adequate (0.17 mg Se/kg) or a Se-supranutritional (0.50 mg Se/kg; high-Se) diet. After 16 weeks of intervention, fasting plasma insulin and cholesterol levels were non-significantly increased in the high-Se pigs, whereas fasting glucose concentrations did not differ between the two groups. In skeletal muscle of high-Se pigs, glutathione peroxidase activity was increased, gene expression of forkhead box O1 transcription factor and peroxisomal proliferator-activated receptor- coactivator 1 were increased and gene expression of the glycolytic enzyme pyruvate kinase was decreased. In visceral adipose tissue of high-Se pigs, mRNA levels of sterol regulatory element-binding transcription factor 1 were increased, and the phosphorylation of Akt, AMP-activated kinase and mitogen-activated protein kinases was affected. In conclusion, dietary Se oversupply may affect expression and activity of proteins involved in energy metabolism in major insulin target tissues, though this is probably not sufficient to induce diabetes.