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.

Spatial patterns of gluten protein and polymer distribution in wheat grain

The starchy endosperm is the major storage tissue in the mature wheat grain and exhibits quantitative and qualitative gradients in composition, with the outermost cell layers being rich in protein, mainly gliadins, and the inner cells being low in protein but enriched in high-molecular-weight (HMW) subunits of glutenin. We have used sequential pearling to produce flour fractions enriched in particular cell layers to determine the protein gradients in four different cultivars grown at two nitrogen levels. The results show that the steepness of the protein gradient is determined by both genetic and nutritional factors, with three high-protein breadmaking cultivars being more responsive to the N treatment than a low-protein cultivar suitable for livestock feed. Nitrogen also affected the relative abundances of the three main classes of wheat prolamins: the sulfur-poor ω-gliadins showed the greatest response to nitrogen and increased evenly across the grain; the HMW subunits also increased in response to nitrogen but proportionally more in the outer layers of the starchy endosperm than near the core, while the sulfur-rich prolamins showed the opposite trend.

Predicting the profile of nutrients available for absorption: from nutrient requirement to animal response and environmental impact

Current feed evaluation systems for dairy cattle aim to match nutrient requirements with nutrient intake at pre-defined production levels. These systems were not developed to address, and are not suitable to predict, the responses to dietary changes in terms of production level and product composition, excretion of nutrients to the environment, and nutrition related disorders. The change from a requirement to a response system to meet the needs of various stakeholders requires prediction of the profile of absorbed nutrients and its subsequent utilisation for various purposes. This contribution examines the challenges to predicting the profile of nutrients available for absorption in dairy cattle and provides guidelines for further improved prediction with regard to animal production responses and environmental pollution. The profile of nutrients available for absorption comprises volatile fatty acids, long-chain fatty acids, amino acids and glucose. Thus the importance of processes in the reticulo-rumen is obvious. Much research into rumen fermentation is aimed at determination of substrate degradation rates. Quantitative knowledge on rates of passage of nutrients out of the rumen is rather limited compared with that on degradation rates, and thus should be an important theme in future research. Current systems largely ignore microbial metabolic variation, and extant mechanistic models of rumen fermentation give only limited attention to explicit representation of microbial metabolic activity. Recent molecular techniques indicate that knowledge on the presence and activity of various microbial species is far from complete. Such techniques may give a wealth of information, but to include such findings in systems predicting the nutrient profile requires close collaboration between molecular scientists and mathematical modellers on interpreting and evaluating quantitative data. Protozoal metabolism is of particular interest here given the paucity of quantitative data. Empirical models lack the biological basis necessary to evaluate mitigation strategies to reduce excretion of waste, including nitrogen, phosphorus and methane. Such models may have little predictive value when comparing various feeding strategies. Examples include the Intergovernmental Panel on Climate Change (IPCC) Tier II models to quantify methane emissions and current protein evaluation systems to evaluate low protein diets to reduce nitrogen losses to the environment. Nutrient based mechanistic models can address such issues. Since environmental issues generally attract more funding from governmental offices, further development of nutrient based models may well take place within an environmental framework.

Short Communication: effects of 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester on milk production and composition of lactating Holstein dairy cows

Sixteen multiparous Holstein cows were used to determine the effects of 2-hydroxy-4-(methylthio) butanoic acid isopropyl ester (HMBi: 0 vs. 1.26 g/kg of total ration dry matter (DM) and dietary crude protein (CP) concentration [14.7% (low) vs. 16.9% (standard), DM basis] on milk yield and composition using a replicated 4 x 4 Latin square design experiment with 4-wk periods. Cows were fed ad libitum a total mixed ration with a 1: 1 forage-to-concentrate ratio (DM basis), and diets provided an estimated 6.71 and 1.86% lysine and methionine, respectively, in metabolizable protein for the low-protein diet and 6.74 and 1.82% in the standard protein diet. Dry matter intake, milk yield, and composition were measured during wk 4 of each period. There were no effects on DM intake, which averaged 24.7 kg/d. There was an interaction between dietary CP and HMBi for milk yield and 3.5% fat-corrected milk (FCM). Feeding HMBi decreased milk and FCM yield when fed with the low-CP diet but did not affect milk or FCM yield when fed with the standard CP diet. Feeding HMBi increased milk protein concentration regardless of diet CP concentration and increased milk protein yield when added to the standard CP diet but not the low-CP diet. The positive effect of HMBi on milk protein yield was only observed at the standard level of dietary CP, suggesting other factors limited the response to HMBi when dietary protein supply was restricted.

Quantitative plant proteomics

Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.

Extractability and characteristics of proteins deriving from wheat DDGS

Wheat Distillers’ Dried Grains with Solubles (DDGS) and in-process samples were used for protein extraction. Prolamins were the predominant protein components in the samples. The absence of extractable α- and γ-gliadins in DDGS indicated protein aggregation during the drum drying processing stage. Prolamin extraction was performed using 70% (v/v) ethanol or alkaline-ethanol solution in the presence of reducing agent. DDGS extracts had relatively low protein contents (14-44.9%, w/w), regardless of the condition applied. The wet solids were the most suitable raw material for protein extraction, with recovery yields of ~ 55% (w/w) and protein content of ~58% (w/w) in 70% (v/v) ethanol. Protein extracts from wet solids were significantly rich in glutamic acid and proline. Mass balance calculations demonstrated the high carbohydrate content (~ 50%, w/w) of solid residues. Overall, the feasibility of utilising in-process samples of DDGS for protein extraction with commercial potential was demonstrated.

Induction of heme oxygenase 1 by moderately oxidized low-density lipoproteins in human vascular smooth muscle cells: role of mitogen-activated protein kinases and Nrf2

Oxidized low-density lipoproteins (LDL) play a central role in atherogenesis and induce expression of the antioxidant stress protein heme oxygenase 1 (HO-1). In the present study we investigated induction of HO-1 and adaptive increases in reduced glutathione (GSH) in human aortic smooth muscle cells (SMC) in response to moderately oxidized LDL (moxLDL, 100 mu g protein/ml, 24 h), a species containing high levels of lipid hydroperoxides. Expression and activity of HO-1 and GSH levels were elevated to a greater extent by moxLDL than highly oxidized LDL but unaffected by native or acetylated LDL. Inhibitors of protein kinase C (PKC) or mitogen-activated protein kinases (MAPK) p38(MAPK) and MEK or c-jun-NH2-terminal kinase (JNK) significantly attenuated induction of HO-1. Phosphorylation of p38(MAPK), extracellular signal-regulated kinase (ERK1/2), or JNK and nuclear translocation of the transcription factor Nrf2 were enhanced following acute exposure of SMC to rnoxLDL (100 mu g proteiri/ml, 1-2 h). Pretreatment of SMC with the antioxidant vitamin C (100 mu M, 24 h) attenuated the induction of HO-1 by moxLDL. Native and oxidized LDL did not alter basal levels of intracellular ATP, mitochondrial dehydrogenase activity, or expression of the lectin-like oxidized LDL receptor (LOX-1) in SMC. These findings demonstrate for the first time that activation of PKC, p38(MAPK), JNK, ERK1/2, and Nrf2 by oxidized LDL in human SMC leads to HO-1 induction, constituting an adaptive response against oxidative injury that can be ameliorated by vitamin C. (C) 2005 Elsevier Inc. All rights reserved.

Automatic prediction of functional site regions in low-resolution protein structures

World-wide structural genomics initiatives are rapidly accumulating structures for which limited functional information is available. Additionally, state-of-the art structural prediction programs are now capable of generating at least low resolution structural models of target proteins. Accurate detection and classification of functional sites within both solved and modelled protein structures therefore represents an important challenge. We present a fully automatic site detection method, FuncSite, that uses neural network classifiers to predict the location and type of functionally important sites in protein structures. The method is designed primarily to require only backbone residue positions without the need for specific side-chain atoms to be present. In order to highlight effective site detection in low resolution structural models FuncSite was used to screen model proteins generated using mGenTHREADER on a set of newly released structures. We found effective metal site detection even for moderate quality protein models illustrating the robustness of the method.

Mechanisms and dynamics of protein clustering on a solid surface

A methodology for discovering the mechanisms and dynamics of protein clustering on solid surfaces is presented. In situ atomic force microscopy images are quantitatively compared to Monte Carlo simulations using cluster statistics to differentiate various models. We study lysozyme adsorption on mica as a model system and find that all surface-supported clusters are mobile, not just the monomers, with diffusion constant inversely related to cluster size. The surface monomer diffusion constant is measured to be D1∼9×10-16  cm2 s-1, such a low value being difficult to measure using other techniques.

Combinatorial peptide ligand libraries and plant proteomics: a winning strategy at a price

The mechanism of action and properties of a solid-phase ligand library made of hexapeptides (combinatorial peptide ligand libraries or CPLL), for capturing the "hidden proteome", i.e. the low- and very low-abundance proteins constituting the vast majority of species in any proteome, as applied to plant tissues, are reviewed here. Plant tissues are notoriously recalcitrant to protein extraction and to proteome analysis. Firstly, rigid plant cell walls need to be mechanically disrupted to release the cell content and, in addition to their poor protein yield, plant tissues are rich in proteases and oxidative enzymes, contain phenolic compounds, starches, oils, pigments and secondary metabolites that massively contaminate protein extracts. In addition, complex matrices of polysaccharides, including large amount of anionic pectins, are present. All these species compete with the binding of proteins to the CPLL beads, impeding proper capture and identification / detection of low-abundance species. When properly pre-treated, plant tissue extracts are amenable to capture by the CPLL beads revealing thus many new species among them low-abundance proteins. Examples are given on the treatment of leaf proteins, of corn seed extracts and of exudate proteins (latex from Hevea brasiliensis). In all cases, the detection of unique gene products via CPLL capture is at least twice that of control, untreated sample.

A functional proteomic method for the enrichment of peripheral membrane proteins reveals the collagen binding protein Hsp47 is exposed on the surface of activated human platelets

Platelets are small blood cells vital for hemostasis. Following vascular damage, platelets adhere to collagens and activate, forming a thrombus that plugs the wound and prevents blood loss. Stimulation of the platelet collagen receptor glycoprotein VI (GPVI) allows recruitment of proteins to receptor-proximal signaling complexes on the inner-leaflet of the plasma membrane. These proteins are often present at low concentrations; therefore, signaling-complex characterization using mass spectrometry is limited due to high sample complexity. We describe a method that facilitates detection of signaling proteins concentrated on membranes. Peripheral membrane proteins (reversibly associated with membranes) were eluted from human platelets with alkaline sodium carbonate. Liquid-phase isoelectric focusing and gel electrophoresis were used to identify proteins that changed in levels on membranes from GPVI-stimulated platelets. Immunoblot analysis verified protein recruitment to platelet membranes and subsequent protein phosphorylation was preserved. Hsp47, a collagen binding protein, was among the proteins identified and found to be exposed on the surface of GPVI-activated platelets. Inhibition of Hsp47 abolished platelet aggregation in response to collagen, while only partially reducing aggregation in response to other platelet agonists. We propose that Hsp47 may therefore play a role in hemostasis and thrombosis.

Evidence for an inhibitory role of bone morphogenetic protein(s) in the follicular-luteal transition in cattle

Bone morphogenetic proteins (BMPs) and their receptors are expressed in ovarian theca cells (TC) and granulosa cells (GC) and BMPs have been implicated in the regulation of several aspects of follicle development including thecal androgen production and granulosal oestrogen production. Their potential involvement in luteal function has received less attention. in this study, we first compared relative abundance of mRNA transcripts for BMPs, activin-beta A and BMP/activin receptors in bovine corpus luteum (CL) and follicular theca and granulosa layers before undertaking functional in vitro experiments to test the effect of selected ligands (BMP6 and activin A) on luteinizing bovine TC and GC. Relative to P-actin transcript abundance, CL tissue contained more BMP4 and -6 mRNA than granulosa, more BMP2 mRNA than theca but much less activin-beta A mRNA than both granulosa and theca. Transcripts for all seven BMP/activin receptors were readily detected in each tissue and two transcripts (BMPRII, ActRIIA) were more abundant in CL than either theca or granulosa, consistent with tissue responsiveness. In vitro luteinization of TC and GC from antral follicles (4-6 mm) was achieved by culturing with 5% serum for 6 days. Treatment with BMP6 (0, 2, 10, and 50 ng/ml) and activin A (0, 2, 10 and 50 ng/ml) under these conditions dose-dependently suppressed forskolin-induced progesterone (P-4) secretion from both cell types without affecting cell number. BMP6 reduced forskolin-stimulated upregulation of STAR mRNA and raised 'basal' CYP17A1 mRNA level in theca-lutein cells without affecting expression of CYP11A1 or hydroxy-Delta-5-steroid dehydrogenase, 3 beta- and steroid Delta-isomerase 1 (HSD3B1). In granulosa-lutein cells, STAR transcript abundance was not affected by BMP6, whereas forskolin-induced expression of CYP11A1, HSD3B1, CYP19A1 and oxytocin transcripts was reduced. In both cell types, follistatin attenuated the suppressive effect of activin A and BMP6 on forskolin-induced P4 secretion but had no effect alone. Granulosa-lutein cells secreted low levels of endogenous activin A (similar to 1 ng/ml); BMP6 reduced this, while raising follistatin secretion thus decreasing activin A:follistatin ratio. Collectively, these findings support inhibitory roles for BMP/activin signalling in luteinization and steroidogenesis in both TC and GC.

A novel method for production of lipid hydroperoxide- or oxysterol-rich low-density lipoprotein

LDL oxidation may be important in atherosclerosis. Extensive oxidation of LDL by copper induces increased uptake by macrophages, but results in decomposition of hydroperoxides, making it more difficult to investigate the effects of hydroperoxides in oxidised LDL on cell function. We describe here a simple method of oxidising LDL by dialysis against copper ions at 4 degrees C, which inhibits the decomposition of hydroperoxides, and allows the production of LDL rich in hydroperoxides (626 +/- 98 nmol/mg LDL protein) but low in oxysterols (3 +/- 1 nmol 7-ketocholesterol/mg LDL protein), whilst allowing sufficient modification (2.6 +/- 0.5 relative electrophoretic mobility) for rapid uptake by macrophages (5.49 +/- 0.75 mu g I-125-labelled hydroperoxide-rich LDL vs. 0.46 +/- 0.04 mu g protein/mg cell protein in 18 h for native LDL). By dialysing under the same conditions, but at 37 degrees C, the hydroperoxides are decomposed extensively and the LDL becomes rich in oxysterols. This novel method of oxidising LDL with high yield to either a hydroperoxide- or oxysterol-rich form by simply altering the temperature of dialysis may provide a useful tool for determining the effects of these different oxidation products on cell function. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

Assembly rules for protein networks derived from phylogenetic-statistical analysis of whole genomes

Background: We report an analysis of a protein network of functionally linked proteins, identified from a phylogenetic statistical analysis of complete eukaryotic genomes. Phylogenetic methods identify pairs of proteins that co-evolve on a phylogenetic tree, and have been shown to have a high probability of correctly identifying known functional links. Results: The eukaryotic correlated evolution network we derive displays the familiar power law scaling of connectivity. We introduce the use of explicit phylogenetic methods to reconstruct the ancestral presence or absence of proteins at the interior nodes of a phylogeny of eukaryote species. We find that the connectivity distribution of proteins at the point they arise on the tree and join the network follows a power law, as does the connectivity distribution of proteins at the time they are lost from the network. Proteins resident in the network acquire connections over time, but we find no evidence that 'preferential attachment' - the phenomenon of newly acquired connections in the network being more likely to be made to proteins with large numbers of connections - influences the network structure. We derive a 'variable rate of attachment' model in which proteins vary in their propensity to form network interactions independently of how many connections they have or of the total number of connections in the network, and show how this model can produce apparent power-law scaling without preferential attachment. Conclusion: A few simple rules can explain the topological structure and evolutionary changes to protein-interaction networks: most change is concentrated in satellite proteins of low connectivity and small phenotypic effect, and proteins differ in their propensity to form attachments. Given these rules of assembly, power law scaled networks naturally emerge from simple principles of selection, yielding protein interaction networks that retain a high-degree of robustness on short time scales and evolvability on longer evolutionary time scales.