Article pubs.acs.org/JAFC
Cite This: J. Agric. Food Chem. 2017, 65, 9817-9827
Exploration of Biological Markers of Feed Efficiency in Young Bulls Sarah J. Meale,*,† Diego P. Morgavi,† Isabelle Cassar-Malek,† Donato Andueza,† Isabelle Ortigues-Marty,† Richard J. Robins,‡ Anne-Marie Schiphorst,‡ Sophie Laverroux,† Benoit Graulet,† Hamid Boudra,† and Gonzalo Cantalapiedra-Hijar*,† †
Université Clermont Auvergne, INRA, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genès-Champanelle, France Elucidation of Biosynthesis by Isotopic Spectrometry Group, CEISAM, CNRS−University of Nantes UMR6230, B.P. 92208, F-44322 Nantes, France
‡
S Supporting Information *
ABSTRACT: The efficiency with which ruminants convert feed to desirable products is difficult to measure under normal commercial settings. We explored the use of potential biological markers from easily obtainable samples, that is, blood, hair, and feces, to characterize potential causes of divergent efficiency when considered as residual feed intake (RFI) or feed conversion efficiency (FCE). A total of 54 Charolais bulls, 20 in period 1 and 34 in period 2, were examined for individual dry matter intake (DMI) and growth. Bulls were offered a diet of 70:30 wrapped grass silage to concentrate for 99 d. At the conclusion of the test period, blood samples were collected for the determination of vitamins B2 and B6, and plasma used for the determination of metabolites, natural isotopic 15N abundance (15N NIA, expressed as δ15N ‰) and fractionation (Δ15Nplasma proteins‑diet and Δ13Cplasma proteins‑diet) and near-infrared spectroscopy (NIRS). Feces were analyzed by NIRS. Bulls were slaughtered at 15−17 months of age and carcass characteristics determined. Bulls were ranked according to RFI with extremes (SD ± 0.5; n = 31) classified as either efficient (Neg-RFI) or inefficient (Pos-RFI). Extreme bulls were then classified for FCE (high vs low FCE), changing the groups. Pos-RFI bulls consumed 14% more feed than Neg-RFI bulls for the same level of weight gain. Low FCE bulls tended to eat more, but had lower weight gains than high FCE bulls. No differences were detected in carcass conformation, fat scores, hot carcass weight, or dressing percentage. Yet, heart and bladder weights were heavier in Pos-RFI, and rumen weight tended to be heavier in Pos-RFI bulls. RFI did not affect bulk 15N or 13C fractionation. A negative correlation was observed between FCE and Δ15Nplasma proteins‑diet. Inefficient bulls (Pos-RFI) had higher δ15N in glycine compared to Neg-RFI bulls. Similarly, metabolomic analysis showed a tendency for concentrations of glycine and sarcosine to be elevated in Pos-RFI bulls, whereas aspartic acid and carnosine tended to be elevated, and serine tended to be lower in High FCE. Among vitamins, only flavin adenine dinucleotide concentration was higher in the blood of bulls with High FCE. These results suggest that the two feed efficiency metrics differ in the underlying mechanisms of metabolism, where RFI is driven by differences in the energetic requirements of visceral organs and the extent of AA catabolism. KEYWORDS: nitrogen fractionation, energetic efficiency, amino acid catabolism, metabolomics, vitamin B
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INTRODUCTION Ruminants, by nature of their specialized digestive system, possess the unique ability to convert fibrous feeds, such as forages, into high protein products. The efficiency of this conversion is variable between individual animals,1 providing an opportunity to select for increased feed efficiency. Conventionally, measures of ruminant production efficiency were defined as the amount of product produced per kilogram of feed ingested, termed feed conversion efficiency (FCE). However, the selection based on greater FCE can also lead to an undesirable selection for a larger animal size and delayed maturity due to its strong correlation with average daily weight gain,2 indirectly leading to higher maintenance requirements and larger input costs for the maintenance of the herd. An alternative measure of feed efficiency is residual feed intake (RFI), defined as the difference between the observed and the expected intake based on the animals’ nutritional maintenance and production requirements. RFI is genetically independent of the growth rate and size of the animal.3 Animals with divergent RFI vary in the way they acquire, metabolize, and/or distribute energy:4 two main biological processes have © 2017 American Chemical Society
been proposed as the primary contributors to the variation in RFIfirst, the metabolism, including processes of protein renewal, tissue metabolism in relation to body composition, thermoregulation, and stress, and second, digestion, including feed ingestion and associated energy costs.5 A major limitation to measuring feed efficiency in nonexperimental settings is the need for strict measurement of individual intake and weight gain over a period of at least 70 d.6 The difficulty is compounded in grazing animals where an accurate measurement of intake is unmanageable. Consequently, biological markers have been explored as proxies for feed efficiency. However, the majority of studies have focused on high concentrate diets and led to variable results. Due to the conflicting demand for grain consumption between livestock and the increasing human population, it is plausible that the diets of livestock will be increasingly comprised of forages, Received: Revised: Accepted: Published: 9817
July 28, 2017 October 23, 2017 October 23, 2017 October 23, 2017 DOI: 10.1021/acs.jafc.7b03503 J. Agric. Food Chem. 2017, 65, 9817−9827
Article
Journal of Agricultural and Food Chemistry despite an associated reduction in feed efficiency, when compared to livestock fed grain diets.7 The need to explore potential biomarkers of efficiency is therefore crucial, especially in animals fed high-forage diets. In order to seek effective proxies for feed efficiency, we explored the potential of biomarkers from less invasive samples (blood, hair, and feces) as indicators of feed efficiency, with the central focus on RFI and its differences to FCE, in growing Charolais bulls fed high forage diets. Specific parameters were selected based on previously observed relationships with components or determinants of feed efficiency (digestion, metabolism, growth, and body composition).
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Table 1. Animal Performance during a 14-week Feed Efficiency Test (n = 54) parameter no. of animals body weight, kg start midtest end age, d start end DMI, kg/d grass silage concentrate total energy-corrected ADG, kg/d FCE, kg/kg average min max RFI, kg DM average min max extreme negative RFI, kg DM/da no. of animals average min max extreme positive RFI, kg DM/d no. of animals average min max low FCE, kg gain/kg DMIb no. of animals average min max high FCE, kg gain/kg DMI no. of animals average min max
MATERIALS AND METHODS
The experiment was conducted at the animal facilities of INRA UE1414 Herbipôle Unit (Saint-Genès Champanelle, France). All animal procedures were approved by the French Ministry of Education and Research (APAFIS no. 2930-2015111814299194) and carried out in accordance with European guidelines and regulations for experimentation with animals. Animals, Diets, and Experimental Design. A total of 54 growing-fattening Charolais bulls, comprising 20 in year 1 (period 1) and 34 in year 2 (period 2), were examined for feed efficiency. The experimental period commenced when bulls were 275 ± 9 and 283 ± 9 d of age for period 1 and 2, respectively, and lasted for 99 d (Table 1). Animals were housed indoors in free stalls. Individual intake was measured through the use of electronic collars and gates (Dairy gate, I.F.E.I, Villeroy, France). Bulls were fed a diet consisting of 70:30 wrapped grass silage to concentrate with amounts adjusted daily to ensure ≥100 g/kg refusals. Water was available ad libitum. In period 2, due to the climatic conditions during the grass growing season, the energy and nitrogen content of grass silage was much lower than that of the previous period. Concentrate was therefore reformulated in period 2 to provide comparable metabolizable protein (PDIE, in the INRA feeding system)8 to the net energy ratio. Ingredients were sampled three times per week throughout the efficiency test. Feeds were ashed at 550 °C for 6 h for organic matter (OM) determination, and nitrogen was determined by the Kjeldahl procedure;9 neutral detergent fiber (NDF) and acid detergent fiber (ADF) were determined according to Van Soest et al.,10 and starch in the concentrate was determined by spectrophotometry after enzymatic analysis.11 Dry matter and OM digestibilities were estimated through enzymatic digestion with pepsin-cellulase.12 In vitro nitrogen degradation of concentrate was assessed by enzymatic hydrolysis for 1 h by a protease extracted from Streptomyces griseus in a boratephosphate buffer at pH 8.13 The chemical composition of ingredients and whole diets are presented in Supplementary Table 1. Production Measurements and Calculation of Feed Efficiency Traits. Body weight (BW, kg) was determined every 14 d at 1400 h (6 h after meal distribution) during the feed efficiency test. Average daily gain (ADG) for each animal was determined as the coefficient of the linear regression of BW on time (d) using the GLM procedure of SAS 9.1 (SAS Institute Inc., Cary, NC, USA). Midtest metabolic BW (MBW) was estimated from the intercept and slope of the regression equation and was represented as BW0.75 50 d before the end of the test in both period 1 and 2. Residual feed intake (RFI) was calculated for each animal as the difference between actual dry matter intake (DMI) and expected DMI. The expected DMI was determined for each animal using a multiple regression model, regressing observed DMI on calculated MBW and ADG, with the period included as a blocking factor. The base model used was:
period 1
period 2
20
34
366 ± 22 451 ± 20 541 ± 20
299 ± 33 377 ± 32 461 ± 32
275 ± 9 374 ± 9
283 ± 10 382 ± 10
5.70 2.74 8.43 8.81 1.78
± ± ± ± ±
0.43 0.16 0.52 0.53 0.14
0.20 ± 0.02 0.17 0.24
5.55 2.55 8.11 8.11 1.64
± ± ± ± ±
0.68 0.15 0.68 0.68 0.16
0.20 ± 0.02 0.17 0.25
0.00 ± 0.49 −1.16 0.91 4
11 −0.56 ± 0.27 −1.16 −0.27
5
11 0.53 ± 0.21 0.25 0.91
5
11 0.180 ± 0.003 0.17 0.19
4
11 0.214 ± 0.002 0.2 0.24
Bulls with RFI > ±0.5 SD from the mean were considered as extremes (n = 31) and designated as either Pos-RFI or Neg-RFI. b Bulls considered to have extreme RFI were ranked based on their FCE and designated as either high or low FCE bulls. a
equivalent to that measured in the diet from period 2) to increase across-period comparability.14 The effect of period was not significant in the model and was then removed. The model R2 coefficient produced from this equation accounted for 50% (P < 0.001) of the variation in observed DMI. Bulls were ranked according to RFI, and animals with RFI ± 0.5 SD (1 SD separated the two groups) were classified as either extreme positive or negative RFI (Pos-RFI vs NegRFI). This classification resulted in 31 bulls being selected (Table 2) for further analysis of feed efficiency biomarkers. The 31 bulls identified as having extreme RFI were further ranked according to their feed conversion efficiency index (FCE), calculated as kg ADG/kg DMI, and designated as either High FCE or Low FCE (Table 2) when their values were ≥ or < the median, respectively, to provide direct comparisons between the two feed efficiency measurements.
Yj = β0 + τi + β1MBWj + β2 ADGj + ej where Yj is the observed DMI of the jth animal, β0 is the regression intercept, τi is the fixed effect of the ith period, β1 is the regression coefficient for MBW, β2 is the regression coefficient for ADG, and ej is the random error associated with the jth animal. The observed DMI was adjusted to a common energy content (1.52 Mcal NE/kg DM; 9818
DOI: 10.1021/acs.jafc.7b03503 J. Agric. Food Chem. 2017, 65, 9817−9827
Article
Journal of Agricultural and Food Chemistry
Table 2. Performance of Selected Young Charolais Bulls with Extremely Divergent Feed Efficiencies (n = 31; RFI > ±0.5 SD from the Mean) P-value
efficiency classification body weight, kg start midtest end age, d start end DMIb, kg/d ADG, kg/d FCE, kg gain/kg DMI a
Pos-RFI
Neg-RFI
Low FCE
322 402 485
326 407 494
335 410 490
280 378 8.86 1.64 0.184
281 380 7.85 1.67 0.212
280 379 8.65 1.55 0.180
P-value
SEM
perioda
RFI
period
FCE
314 399 489
8 8 9
