scholarly journals Natural 15N abundance in specific amino acids indicates associations between transamination rates and residual feed intake in beef cattle

2020 ◽  
Vol 98 (6) ◽  
Author(s):  
Gonzalo Cantalapiedra-Hijar ◽  
Pablo Guarnido ◽  
Anne-Marie Schiphorst ◽  
Richard J Robins ◽  
Gilles Renand ◽  
...  
Keyword(s):  
Amino Acids ◽  
Beef Cattle ◽  
Feed Intake ◽  
Genetic Selection ◽  
Residual Feed Intake ◽  
Future Research ◽  
Metabolic Reaction ◽  
Natural 15N Abundance ◽  
Δ 15N ◽  
15N Abundance

Abstract Improving the ability of animals to convert feed resources into food for humans is needed for more sustainable livestock systems. Genetic selection for animals eating less while maintaining their performance (i.e., low residual feed intake [RFI]) appears a smart strategy but its effectiveness relies on high-throughput animal phenotyping. Here, we explored plasma nitrogen (N) isotope ratios in an attempt to identify easily superior young bulls in terms of RFI. For this, 48 Charolais young bulls fed two contrasting diets (corn vs. grass silage diets) were selected from a larger population as extreme RFI animals (24 low-RFI vs. 24 high-RFI) and their plasma analyzed for natural 15N abundance (δ15N) in the whole protein (bulk protein) and in the individual protein-bound amino acids (PbAA). For the first time, we showed that the δ 15N in plasma bulk protein differed (P = 0.007) between efficient (low-RFI) and inefficient (high-RFI) cattle regardless of diet. Furthermore, most analyzed PbAA followed the same trend as the bulk protein, with lower (P < 0.05) δ 15N values in more efficient (low-RFI) compared with less efficient (high-RFI) cattle, again regardless of diet. The only three exceptions were Phe, Met, and Lys (P > 0.05) for which the first metabolic reaction before being catabolized does not involve transamination, a pathway known naturally to enrich AAs in 15N. The contrasted isotopic signatures across RFI groups only in those PbAA undergoing transamination are interpreted as differences in transamination rates and N-use efficiency between low- and high-RFI phenotypes. Natural isotopic N signatures in bulk proteins and specific PbAA can be proposed as biomarkers of RFI in growing beef cattle fed different diets. However, the current study cannot delineate whether this effect only occurs post-absorption or to some extent also in the rumen. Our data support the conclusion that most efficient cattle in terms of RFI upregulate N conservation mechanisms compared with less efficient cattle and justify future research on this topic.

scholarly journals Exploring Biological Impacts of Prenatal Nutrition and Selection for Residual Feed Intake on Beef Cattle Using Omics Technologies: A Review

2021 ◽  
Vol 12 ◽  
Author(s):  
Aidin Foroutan ◽  
David S. Wishart ◽  
Carolyn Fitzsimmons
Keyword(s):  
Beef Cattle ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Growth And Development ◽  
Genetic Selection ◽  
Residual Feed Intake ◽  
Reproductive Capacity ◽  
Phenotypic Traits ◽  
Prenatal Nutrition ◽  
Selection For

Approximately 70% of the cost of beef production is impacted by dietary intake. Maximizing production efficiency of beef cattle requires not only genetic selection to maximize feed efficiency (i.e., residual feed intake (RFI)), but also adequate nutrition throughout all stages of growth and development to maximize efficiency of growth and reproductive capacity, even during gestation. RFI as a measure of feed efficiency in cattle has been recently accepted and used in the beef industry, but the effect of selection for RFI upon the dynamics of gestation has not been extensively studied, especially in the context of fluctuating energy supply to the dam and fetus. Nutrient restriction during gestation has been shown to negatively affect postnatal growth and development as well as fertility of beef cattle offspring. This, when combined with the genetic potential for RFI, may significantly affect energy partitioning in the offspring and subsequently important performance traits. In this review, we discuss: 1) the importance of RFI as a measure of feed efficiency and how it can affect other economic traits in beef cattle; 2) the influence of prenatal nutrition on physiological phenotypes in calves; 3) the benefits of investigating the interaction of genetic selection for RFI and prenatal nutrition; 4) how metabolomics, transcriptomics, and epigenomics have been employed to investigate the underlying biology associated with prenatal nutrition, RFI, or their interactions in beef cattle; and 5) how the integration of omics information is adding a level of deeper understanding of the genetic architecture of phenotypic traits in cattle.

scholarly journals RAPID COMMUNICATION: Residual feed intake in beef cattle is associated with differences in protein turnover and nutrient transporters in ruminal epithelium

2019 ◽  
Vol 97 (5) ◽  
pp. 2181-2187
Author(s):  
Ahmed A Elolimy ◽  
Emad Abdel-Hamied ◽  
Liangyu Hu ◽  
Joshua C McCann ◽  
Daniel W Shike ◽  
...  
Keyword(s):  
Amino Acid ◽  
Beef Cattle ◽  
Protein Degradation ◽  
Insulin Signaling ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Protein Turnover ◽  
Residual Feed Intake ◽  
Ubiquitin Proteasome ◽  
Ruminal Epithelium

Abstract Residual feed intake (RFI) is a widely used measure of feed efficiency in cattle. Although the precise biologic mechanisms associated with improved feed efficiency are not well-known, most-efficient steers (i.e., with low RFI coefficient) downregulate abundance of proteins controlling protein degradation in skeletal muscle. Whether cellular mechanisms controlling protein turnover in ruminal tissue differ by RFI classification is unknown. The aim was to investigate associations between RFI and signaling through the mechanistic target of rapamycin (MTOR) and ubiquitin-proteasome pathways in ruminal epithelium. One hundred and forty-nine Red Angus cattle were allocated to 3 contemporary groups according to sex and herd origin. Animals were offered a finishing diet for 70 d to calculate the RFI coefficient for each. Within each group, the 2 most-efficient (n = 6) and least-efficient animals (n = 6) were selected. Compared with least-efficient animals, the most-efficient animals consumed less feed (P < 0.05; 18.36 vs. 23.39 kg/d DMI). At day 70, plasma samples were collected for insulin concentration analysis. Ruminal epithelium was collected immediately after slaughter to determine abundance and phosphorylation status of 29 proteins associated with MTOR, ubiquitin-proteasome, insulin signaling, and glucose and amino acid transport. Among the proteins involved in cellular protein synthesis, most-efficient animals had lower (P ≤ 0.05) abundance of MTOR, p-MTOR, RPS6KB1, EIF2A, EEF2K, AKT1, and RPS6KB1, whereas MAPK3 tended (P = 0.07) to be lower. In contrast, abundance of p-EEF2K, p-EEF2K:EEF2K, and p-EIF2A:EIF2A in most-efficient animals was greater (P ≤ 0.05). Among proteins catalyzing steps required for protein degradation, the abundance of UBA1, NEDD4, and STUB1 was lower (P ≤ 0.05) and MDM2 tended (P = 0.06) to be lower in most-efficient cattle. Plasma insulin and ruminal epithelium insulin signaling proteins did not differ (P > 0.05) between RFI groups. However, abundance of the insulin-responsive glucose transporter SLC2A4 and the amino acid transporters SLC1A3 and SLC1A5 also was lower (P ≤ 0.05) in most-efficient cattle. Overall, the data indicate that differences in signaling mechanisms controlling protein turnover and nutrient transport in ruminal epithelium are components of feed efficiency in beef cattle.

338 Nitrogen Use Efficiency Is Proportionally More Improved When Young Bulls Are Ranked on Residual Body Gain Rather Than on Residual Feed Intake

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 187-188
Author(s):  
Pablo Guarnido Lopez ◽  
Isabelle Ortigues Marty ◽  
Cantalapiedra-Hijar Gonzalo
Keyword(s):  
Nitrogen Use Efficiency ◽  
Feed Intake ◽  
Linear Models ◽  
Residual Feed Intake ◽  
Residual Body ◽  
Nitrogen Use ◽  
N Metabolism ◽  
Use Efficiency ◽  
Δ 15N ◽  
Positive Correlations

Abstract Animals with superior feed efficiency (FE) may also have an improved nitrogen use efficiency (NUE), which would be beneficial to economic profitability while reducing environmental impacts. When genetically selecting animals on FE, it is preferable to use residual traits [e.g. residual feed intake (RFI) or residual body gain (RG)] rather than ratios because of their predictable genetic outcomes. We studied the relationship of RFI and RG with NUE, estimated from the validated 15N abundance in plasma, across two contrasted diets based on corn or grass silages. We evaluated FE of 588 (half by diet) Charolais bulls (545 ± 57 kg BW) from 12 experimental cohorts (different farms and periods) over 200 days. Before the end of the FE test, plasma was sampled and analyzed for δ 15N. NUE was related to FE through simple-linear models with variables previously corrected for the cohort and diet effects. The models’ slopes were standardized according to FE deviation in order to compare the response of NUE to FE between indices. Higher NUE was related to higher FE (P < 0.001), showing positive correlations with RG (r=-0.40) and negative with RFI (r=0.29). However, the standardized slope of NUE to RG was significantly higher (+28%; P < 0.05) than that of NUE to RFI. This stronger NUE relation to RG compared to RFI could reflect a higher potential of RG animals to deposit N as compared to a more conservational N metabolism in RFI individuals. Regarding diets, and despite the correction of NUE and FE for this effect, the slopes of NUE to FE were numerically (P > 0.05) higher (-16% and +36%; for RG and RFI) in corn-based diets, which agrees with superior NUE observed in corn-vs-grass diets. Results suggested that superior RG animals may present proportionally higher NUE than superior RFI animals, with even better results in corn-vs-grass diets.

scholarly journals Improving estimates of weight gain and residual feed intake by adjusting for the amount of feed eaten before weighing

2001 ◽  
Vol 41 (7) ◽  
pp. 1057 ◽  
Author(s):  
D. L. Robinson ◽  
V. H. Oddy
Keyword(s):  
Weight Gain ◽  
Feed Intake ◽  
Measurement Errors ◽  
Genetic Selection ◽  
Residual Feed Intake ◽  
Quadratic Growth ◽  
Partial Regression Coefficient ◽  
Gain Error ◽  
Downward Bias ◽  
Over Time

In Australia, a trait under consideration for genetic selection to improve feed efficiency is residual feed intake (RFI), which is defined as the amount of feed eaten by an animal less what would be expected from the animal’s growth rate and body weight. Accurate estimates of RFI therefore require accurate estimates of weight gain. Results presented here on steers finished in a feedlot to liveweights of 540 or 600 kg show that, when feed intake is being measured, weight gain can be estimated more accurately using the amount of feed eaten in the previous 3–5 days (as an adjustment for gut fill) than if feed eaten in the 80 h before weighing is ignored. This is demonstrated by a much lower residual mean square from modelling the weight of each animal as a quadratic growth curve over time if terms are included for feed eaten on the current and previous 3–5 days. An analysis of measurement errors associated with fitting the equation used to calculate RFI: Feed intake = constant + βw x mean metabolic weight + βg x weight gain + error (i.e. RFI) (1) indicates that the relatively high measurement errors associated with weight gain but comparatively low measurement errors associated with metabolic weight will result in upward biases in the partial regression coefficient βw and downward biases in βg. For example, in a 105-day feed intake test of 44 steers (mean start/end weights 440/600 kg), the estimate of βg was 1.26 based on weight gain estimated by a simple linear regression of each animal’s weight over time (LIN), compared with 2.20 using weight gain estimated from the difference between first and last weight of each animal adjusted for the amount of feed eaten on the current and previous 5 days (DIFFadj). From a shorter test, based on weight gains from day 15 to 50 in the automatic feeder pens, the estimate of βg was 0.40 using LIN and 1.67 using DIFFadj. These results illustrate the potential magnitude of the downward bias in βg if inaccurate estimates of weight gain are used to fit equation 1. The higher estimates for βg obtained using DIFFadj may still have some downward bias but are closer to the theoretical values published by SCA (1990) for the amount of metabolisable energy required for weight gain. Adjusting for the amount of feed eaten before weighing therefore increased the accuracy of estimated weight gain and reduced the biases in βg and βw, so providing better and more stable estimates of residual feed intake.

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