Urinary excretion of purine derivatives, microbial protein synthesis, nitrogen use, and ruminal fermentation in sheep and goats fed diets of different quality

Metabolizable Protein: 1. Predicting Equations to Estimate Microbial Crude Protein Synthesis in Small Ruminants

Microbial crude protein (MCP) produced in rumen could be estimated by a variety of protocols of experimental sampling and analysis. However, a model to estimate this value is necessary when protein requirements are calculated for small ruminants. This model could be useful to calculate rumen degradable protein (RDP) requirements from metabolizable protein (MP). Then, our objective was to investigate if there is a difference in MCP efficiency between sheep and goats, and to fit equations to predict ruminal MCP production from dietary energy intake. The database consisted of 19 studies with goats (n = 176) and sheep (n = 316), and the variables MCP synthesis (g/day), total digestible nutrients (TDN), and organic matter (OM) intakes (g/day), and OM digestibility (g/kg DM) were registered for both species. The database was used for two different purposes, where 70% of the values were sorted to fit equations, and 30% for validation. A meta-analytical procedure was carried out using the MIXED procedure of SAS, specie was considered as the fixed dummy effect, and the intercept and slope nested in the study were considered random effects. No effect of specie was observed for the estimation of MCP from TDN, digestible Organic Matter (dOM), or metabolizable energy (ME) intakes (P > 0.05), considering an equation with or without an intercept. Therefore, single models including both species at the same fitting were validated. The following equations MCP (g/day) = 12.7311 + 59.2956 × TDN intake (AIC = 3,004.6); MCP (g/day) = 15.7764 + 62.2612 × dOM intake (AIC = 2,755.1); and MCP (g/day) = 12.7311 + 15.3000 × ME intake (AIC = 3,007.3) presented lower values for the mean square error of prediction (MSEP) and its decomposition, and similar values for the concordance correlation coefficient (CCC) and for the residual mean square error (RMSE) when compared with equations fitted without an intercept. The intercept and slope pooled test was significant for equations without an intercept (P < 0.05), indicating that observed and predicted data differed. In contrast, predicted and observed data for complete equations were similar (P > 0.05).

A comparative study on the excretion of urinary metabolites in goats and sheep to evaluate spot sampling applied to protein nutrition trials

The main objective of this study was to establish a protocol to validate urine spot samples to estimate N excretion and microbial synthesis in goat and sheep; and to study factors that affect daily creatinine and purine derivatives (PD) urinary excretion. Also a performance trial was carried out to compare goat and sheep slaughtered after different feedlot periods. Twelve Boer goats (20.6 kg ± 3.4 initial BW) and 12 Dorper sheep (18.4 kg ± 2.3 initial BW), all 4-mo-old, males, were used. Eight animals (4 goats and 4 sheep) were randomly allocated to be slaughtered at 28, 56, and 84 d in feedlot. The experiment was conducted in a completely randomized design in a 2 × 3 factorial scheme, in which the factors were both species and the 3 feedlot periods. Diet consisted of 50% sorghum silage and 50% concentrate on a DM basis. Nutrient intake was higher (P < 0.01) for sheep than goats. Apparent digestibility of nutrients was similar (P > 0.05) in both species. Sheep had greater (P < 0.01) ADG and final BW than goats. Fat deposition and fat:muscle ratio was higher (P < 0.01) in sheep carcasses. Sheep had higher N urinary (P = 0.02) excretion and N retention (g/d; P < 0.01) than goats. Urinary N excretion increased linearly (P < 0.01) in response to feedlot period. However, feedlot did not affect (P = 0.20) N retention, but linearly reduced the relationship between N retained and ingested (P = 0.04) or apparently digested (P < 0.01). Microbial efficiency (P > 0.05) did not differ between species. Creatinine excretion (C mg/d; P < 0.01) was higher in sheep than goats. Purine derivatives (Ŷ) were related closely with OM intake (Ŷ = 0.013±0.0007X; r2 = 94). A difference (P < 0.01) was found between the allometric model for creatinine excretion (Ŷ) and muscle weight (X) for both species, and the following equations were obtained: Ŷ = 89.04(±31.44)X0.9797(±0.16) for goats and Ŷ = 109.8(±47.50)X0.8002(±0.20) for sheep. Creatinine concentration was greater during nocturnal than diurnal periods, with lower diurnal fluctuations. Sampling time did not affect (P = 0.27) the PD:C ratio. The urea (U):C ratio was higher (P < 0.01) in sheep than goats, and was also higher (P < 0.01) during diurnal than nocturnal sampling periods. Our results suggest that it is necessary to take 2 and 3 spot urine samples after feeding to estimate N compounds excretions in goats and sheep, respectively.

Comparison of automated ribosomal intergenic spacer analysis (ARISA) and denaturing gradient gel electrophoresis (DGGE) techniques for analysing the influence of diet on ruminal bacterial diversity

The objective of this study was to compare the automated ribosomal intergenic spacer analysis (ARISA) and the denaturing gradient gel electrophoresis (DGGE) techniques for analysing the effects of diet on diversity in bacterial pellets isolated from the liquid (liquid-associated bacteria (LAB)) and solid (solid-associated bacteria (SAB)) phase of the rumen. The four experimental diets contained forage to concentrate ratios of 70:30 or 30:70 and had either alfalfa hay or grass hay as forage. Four rumen-fistulated animals (two sheep and two goats) received the diets in a Latin square design. Bacterial pellets (LAB and SAB) were isolated at 2 h post-feeding for DNA extraction and analysed by ARISA and DGGE. The number of peaks in individual samples ranged from 48 to 99 for LAB and from 41 to 95 for SAB with ARISA, and values of DGGE-bands ranged from 27 to 50 for LAB and from 18 to 45 for SAB. The LAB samples from high concentrate-fed animals tended (p < 0.10) to show greater peak numbers and Shannon index values than those isolated from high forage-fed animals with ARISA, but no differences were identified with DGGE. The SAB samples from high concentrate-fed animals had lower (p < 0.05) peak numbers and Shannon index values than those from animals fed high-forage diets with ARISA, but only a trend was noticed for these parameters with DGGE (p < 0.10). The ARISA detected that animals fed alfalfa hay diets showed lower (p < 0.05) SAB diversity than those fed grass hay diets, but no differences were observed with DGGE. No effect of forage type on LAB diversity was detected by any technique. In this study, ARISA detected some changes in ruminal bacterial communities that were not detected by DGGE, and therefore ARISA was considered more appropriate for assessing bacterial diversity of ruminal bacterial pellets. The results highlight the impact of the fingerprinting technique used to draw conclusions on dietary factors affecting bacterial diversity in ruminal bacterial pellets.