A model to predict the ATP equivalents of macronutrients absorbed from food

Teaching the principles of least-cost poultry feed formulation utilizing the Solver function within a computer software workbook

A Microsoft Excel workbook, User-Friendly Feed Formulation with Data from Australia (UffdAu.xlsm), has been developed for teaching feed formulation techniques to tertiary level, university students. It runs under both Microsoft Windows and Apple iOS operating systems. The example ingredient composition matrix is based on the Australian Feed Ingredient Database to illustrate the biological and econometric principles of least-cost feed formulation. The nutrient data are based roughly on recent primary breeder company recommendations. The workbook is easily adapted to appropriate ingredients, nutrients, and prices most relevant to the students, wherever it is used. The workbook uses the linear routines of Excel's Solver add-in under the Data heading in the header Ribbon. There is a worksheet illustrating how to adapt non-linear responses such as exogenous enzymes to typical linear models using a step function. Additional worksheets illustrate how proximate analysis can be interpreted in modern analytical chemistry terms and, how various feed energy measures are related to feed composition. UffdAu.xlsm is available free of charge from the Poultry Hub Australia website (https://www.poultryhub.org).

Net energy value of canola meal, field pea, and wheat millrun fed to growing-finishing pigs

Two experiments were conducted to (1) determine net energy (NE) values of soybean meal (SBM), Napus canola meal (NCM), Juncea canola meal (JCM), field pea, and wheat millrun (WM) using indirect calorimetry, and (2) compare the determined NE values with the calculated NE values of the same feedstuffs based on a prediction equation. In experiment 1, six ileal-cannulated barrows (31 kg) were fed five diets in 5 × 6 Youden square to give six replicates per diet. Diets were cornstarch-based diets containing SBM, NCM, JCM, field pea, or WM. The SBM was included as a reference. In experiment 2, six ileal-cannulated barrows (70 kg) were fed a N-free diet for determining energy digestibility and NE values of test feedstuffs fed in experiment 1 by difference method. The NE values of test feedstuffs were also calculated from the digestible energy (DE) values and analyzed macronutrient content of the test feedstuffs. On dry matter (DM) basis, SBM, NCM, JCM, field pea, and WM contained 51%, 41%, 42%, 28%, and 18% crude protein; 1.52%, 2.95%, 2.36%, 1.33%, and 3.12% ether extract; 2.93%, 0.14%, 1.44%, 36.7%, and 28.7% starch; and 5.30%, 21.0%, 13.4%, 9.49%, and 16.1% acid detergent fiber, respectively. The determined NE value for SBM (2.29 Mcal/kg) did not differ from that of NCM (1.72 Mcal/kg DM) or JCM (2.14 Mcal/kg DM). The NCM and JCM did not differ in NE value. Also, the determined NE value did not differ between field pea (2.00 Mcal/kg) and WM (2.55 Mcal/kg). The calculated NE values for SBM (2.18 Mcal/kg DM), NCM (1.73 Mcal/kg DM), and JCM (1.86 Mcal/kg DM) did not differ from the corresponding determined NE values of the same feedstuffs. However, the calculated NE value for field pea (2.51 Mcal/kg DM) was greater (P = 0.004) than the determined NE value of field pea, whereas the calculated NE value for WM (2.27 Mcal/kg DM) tended to be lower (P = 0.054) than the determined NE value of WM. In conclusion, the NE value for SBM and canola meals can be predicted based on the DE value and the macronutrient composition of the same feedstuffs. However, the NE value for field pea and WM may not be predicted precisely based on the DE value and the macronutrient composition of the same feedstuffs.

Growth performance, nutrient digestibility, and fecal microbial composition of weaned pigs fed multi-enzyme supplemented diets

A study determined the effects of supplementing corn-based diets for weaned pigs with multi-enzymes on growth performance, apparent total tract digestibility (ATTD) of nutrients, fecal score, and fecal microbial composition. A total of 132 pigs (initial body weight = 7.23 kg) that had been weaned at 21 d of age and fed a drug-free nursery diet for 7 d were housed in 33 pens of 4 barrows or gilts, blocked by body weight and gender, and fed 3 experimental diets at 11 pens per diet. The diets were corn-based diet without or with multi-enzyme A or B. Multi-enzyme A supplied 4,000 U of xylanase, 150 U of β-glucanase, 3,500 U of protease, and 1,500 U of amylase per kilogram of diet. Multi-enzyme B was the same as multi-enzyme A except that it supplied amylase at 150 U/kg, and that its source of amylase was different from that of multi-enzyme A. All diets contained phytase at 1,000 U/kg. The diets were fed for 35 d in 2 phases; phase 1 for the first 14 d and phase 2 for the last 21 d of the trial. Fecal score was determined daily during the first 7 d of the trial. Fecal samples were collected from rectum of 1 pig per pen on days 2, 7, 14, and 35 of the trial for determining bacterial composition. Also, fresh fecal samples were collected from each pen on days 41 and 42 to determine ATTD of nutrients. Multi-enzyme B increased (P < 0.05) average daily gain (ADG) for phases 1 and 2. For the overall study period, multi-enzyme B increased (P < 0.05) ADG from 262 to 313 g, and average daily feed intake (ADFI) from 419 to 504 g. Multi-enzyme A increased (P < 0.05) overall ADG from 262 to 290 g, but did not affect ADFI. Multi-enzyme A or B did not affect ATTD of gross energy, but increased (P < 0.05) the ATTD of ether extract from 30% to 36% or 37%, respectively. Multi-enzyme A did not affect fecal score; however, multi-enzyme B tended to decrease (P = 0.09) fecal score, implying that it tended to decrease diarrhea. Firmicutes were the most abundant phylum of fecal bacteria (its relative abundance ranged from 58% to 72%). Bacteroidetes and Actinobacteria were the 2nd and 3rd most abundant phyla of fecal bacteria. Neither multi-enzyme affected fecal bacterial composition. In conclusion, the addition of multi-enzyme A or B to phytase-supplemented corn-based diet for weaned pigs can improve their growth performance and fat digestibility. However, multi-enzyme B was more effective than multi-enzyme A in terms of improving the growth performance of weaned pigs fed corn-based diet.

Integrating Extracellular Flux Measurements and Genome-Scale Modeling Reveals Differences between Brown and White Adipocytes

White adipocytes are specialized for energy storage, whereas brown adipocytes are specialized for energy expenditure. Explicating this difference can help identify therapeutic targets for obesity. A common tool to assess metabolic differences between such cells is the Seahorse Extracellular Flux (XF) Analyzer, which measures oxygen consumption and media acidification in the presence of different substrates and perturbagens. Here, we integrate the Analyzer's metabolic profile from human white and brown adipocytes with a genome-scale metabolic model to predict flux differences across the metabolic map. Predictions matched experimental data for the metabolite 4-aminobutyrate, the protein ABAT, and the fluxes for glucose, glutamine, and palmitate. We also uncovered a difference in how adipocytes dispose of nitrogenous waste, with brown adipocytes secreting less ammonia and more urea than white adipocytes. Thus, the method and software we developed allow for broader metabolic phenotyping and provide a distinct approach to uncovering metabolic differences.

An overview of energy and protein utilisation during growth in simple-stomached animals

The biological processes underlying the partitioning of amino acids and energy during animal growth are well understood qualitatively. However, if a deeper mechanistic understanding is to be achieved, such as to allow generalised predictions of growth outcomes, these biological processes need to be described quantitatively, along with critical control points. Concepts and rules can be formulated at mechanistic and semi-mechanistic levels, and often reflecting causation, to allow nutrient intake and partitioning to be described in a quantitative manner for different animal and environmental conditions. An overview is given of amino acid and energy partitioning during growth in monogastric animals, in terms of causation and quantitatively based descriptors. Current knowledge is far from complete, and areas requiring new insights and a more in-depth understanding of causative mechanisms include voluntary food-intake control, dynamics of nutrient uptake, temporary post-prandial nutrient storage, relationships among nutrient intakes, protein turnover and maintenance-energy requirement, colonic amino acid uptake in poultry, bioavailability of amino acids other than lysine, diet effects on gut endogenous amino acid loss, inevitable amino acid catabolism, preferential amino acid catabolism, and diet, age and genotype effects on body protein synthesis and degradation.

Whey-reduced weight gain is associated with a temporary growth reduction in young mice fed a high-fat diet

Whey protein consumption reportedly alleviates parameters of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey) in young mice fed a high-fat diet. We hypothesized that whey as the sole protein source reduced early weight gain associated with retarded growth and decreased concentration of insulin-like growth factor-1. Moreover, we hypothesized that these changes were explained by increased nitrogen loss via elevated urea production and/or increased energy expenditure. Male 5-week-old C57BL/6 mice were fed high-fat diets with the protein source being either whey, casein or a combination of both for 5 weeks. After 1, 3 or 5 weeks, respectively, the mice were subjected to a meal challenge with measurements of blood and urinary urea before and 1 and 3 h after eating a weighed meal of their respective diets. In a subset of mice, energy expenditure was measured by indirect calorimetry during the first week of dietary intervention. Observed exclusively during the first week of intervention, whey significantly reduced body length (P<.01) and weight gain (P<.001) correlating positively with plasma concentrations of insulin-like growth factor-1. The combination diet displayed intermediate results indicating an interactive effect. Urea production, urea cycle activity, food intake and energy expenditure were unaffected by protein source. In conclusion, whey decreased growth-related parameters exclusively during the first week of dietary intervention. The early effect of whey could not be explained by food intake, energy expenditure, urea production or urea cycle activity but was correlated with plasma levels of insulin-like growth factor-1.

Whey protein reduces early life weight gain in mice fed a high-fat diet

An increasing number of studies indicate that dairy products, including whey protein, alleviate several disorders of the metabolic syndrome. Here, we investigated the effects of whey protein isolate (whey) in mice fed a high-fat diet hypothesising that the metabolic effects of whey would be associated with changes in the gut microbiota composition. Five-week-old male C57BL/6 mice were fed a high-fat diet ad libitum for 14 weeks with the protein source being either whey or casein. Faeces were collected at week 0, 7, and 13 and the fecal microbiota was analysed by denaturing gradient gel electrophoresis analyses of PCR-derived 16S rRNA gene (V3-region) amplicons. At the end of the study, plasma samples were collected and assayed for glucose, insulin and lipids. Whey significantly reduced body weight gain during the first four weeks of the study compared with casein (P<0.001–0.05). Hereafter weight gain was similar resulting in a 15% lower final body weight in the whey group relative to casein (34.0±1.0 g vs. 40.2±1.3 g, P<0.001). Food intake was unaffected by protein source throughout the study period. Fasting insulin was lower in the whey group (P<0.01) and glucose clearance was improved after an oral glucose challenge (P<0.05). Plasma cholesterol was lowered by whey compared to casein (P<0.001). The composition of the fecal microbiota differed between high- and low-fat groups at 13 weeks (P<0.05) whereas no difference was seen between whey and casein. In conclusion, whey initially reduced weight gain in young C57BL/6 mice fed a high-fat diet compared to casein. Although the effect on weight gain ceased, whey alleviated glucose intolerance, improved insulin sensitivity and reduced plasma cholesterol. These findings could not be explained by changes in food intake or gut microbiota composition. Further studies are needed to clarify the mechanisms behind the metabolic effects of whey.