Effects of taurine on rumen fermentation, nutrient digestion, rumen bacterial community and metabolomics and nitrogen metabolism in beef steers.

BACKGROUND: The objectives of this study were to investigate the effects of taurine on rumen fermentation, rumen bacterial community and metabolomics, nitrogen metabolism and plasma biochemical parameters in beef steers. Six castrated Simmental steers (liveweight 402 ± 34 kg) and three levels of taurine (0, 20, 40 g d-1 ) were assigned in a replicated 3 × 3 Latin square design. Each experimental period included 15 days for adaptation and 5 days for sampling. RESULTS: Supplementing taurine did not affect the ruminal pH or concentrations of ammonia nitrogen and volatile fatty acids (P > 0.10), but linearly increased the ruminal concentrations of taurine (P < 0.001) and microbial crude protein (P = 0.041). Supplementing taurine linearly increased the neutral detergent fiber digestibility (P = 0.018), and tended to linearly increase dry matter digestibility (P = 0.095), tended to increase the fecal nitrogen excretion (P = 0.065) and increased the urinary taurine excretion (P < 0.001). Supplementing taurine quadratically increased the plasma concentration of triglycerides (P = 0.017), tended to linearly decrease growth hormone (P = 0.074), but did not affect other plasma parameters (P > 0.10). Supplementing taurine modified the rumen bacterial community and increased the ruminal concentration of taurine metabolite 2-hydroxyethoxysulfonic acid (P < 0.001). CONCLUSION: It was concluded that taurine improved ruminal microbial crude protein synthesis and increased fiber digestibility through modifying rumen bacterial community. It is necessary to clarify the ruminal hydrolysis of taurine in steers. © 2023 Society of Chemical Industry.

Effects of acetate, propionate, and pH on volatile fatty acid thermodynamics in continuous cultures of ruminal contents.

To investigate the effects of acetate, propionate, and pH on thermodynamics of volatile fatty acids (VFA) in the rumen, a dual-flow continuous culture study was conducted to quantify production of major VFA, interconversions among the VFA, and H2 and CH4 emissions in a 4 × 4 Latin square design. The 4 treatments were (1) control: pH buffered to an average of 6.75; (2) control plus 20 mmol/d of infused acetate (InfAc); (3) control plus 7 mmol/d of infused propionate (InfPr); and (4) a 0.5-unit decline in pH elicited by adjustment of the buffer (LowpH). All fermentors were fed 40 g of a pelleted diet containing whole alfalfa pellets and concentrate mix pellets (50:50) once daily. After 7 d of treatment, sequential, continuous infusions of [2-13C] sodium acetate (3.5 mmol/d), [U-13C] sodium propionate (2.9 mmol/d), and [1-13C] sodium butyrate (0.22 mmol/d) were carried out from 12 h before feeding for 36 h. Filtered liquid effluent (4 mL) was sampled at 0, 2, 4, 6, 8, 12, 16, and 22 h after feeding, and assessed for VFA concentrations, with another filtered sample (20 mL) used to quantify aqueous concentrations of CH4 and H2. Headspace CH4 and H2 gases were monitored continuously. Ruminal microbes were isolated from the mixed effluent samples, and the microbial community structure was analyzed using the 16S rRNA amplicon sequencing technique. The digestibility of neutral detergent fiber, acid detergent fiber, and starch and microbial C sequestrated from VFA were not affected by treatments. The LowpH treatment increased net propionate production and decreased H2 and CH4 headspace emissions, primarily due to shifts in metabolic pathways of VFA formation, likely due to the observed changes in bacterial community structure. Significant interconversions occurred between acetate and butyrate, whereas interconversions of other VFA with propionate were relatively small. The InfAc and InfPr treatments increased net acetate and propionate production, respectively; however, interconversions among VFA were not affected by pH, acetate, or propionate treatments, suggesting that thermodynamics might not be a primary influencer of metabolic pathways used for VFA formation.

Thiocyanate increases the nitrous oxide formation process through modifying the soil bacterial community.

BACKGROUND: Nitrous oxide (N2 O) is a potent greenhouse gas depleting the stratospheric ozone. Previous studies reported that the thiocyanate (TC) excretion in the urine of cattle fed rapeseed meals containing glucosinolates was positively correlated with the N2 O-nitrogen (N) emissions. The objectives of the experiment were to verify the effects and the mechanism of TC on the N2 O-N emissions from the soil applied with artificial urine using static incubation technique. Four levels of TC, that is 0.00, 0.26, 0.78 and 2.33 mmol L-1 were composited in artificial urine as experimental treatments. Soil inorganic N and bacterial community were analyzed to elucidate the effects of TC on the N2 O-N emissions of artificial urine. RESULTS: Adding TC increased the N2 O-N fluxes, the N2 O-N to N application ratio, and the estimated N2 O-N emissions from the soil applied with artificial urine both linearly and quadratically. The estimated N2 O-N emission (Y, in µmol) was increased with the TC adding level (X, in µmol) in a quadratic manner: Y = 52.57 + 4.47 X - 0.123 X 2 (R 2  = 0.70). Adding TC did not affect the soil bacterial diversity and richness, but increased the relative abundances of Nitrosomonas (both for nitrification and denitrification) and Hyphomicrobium, Lysobacter and Terrimonas (for denitrification), and tended to increase the relative abundances of denitrification and dissimilatory nitrate reduction to ammonium. CONCLUSION: TC increased the N2 O-N emissions of the soil applied with artificial urine possibly through enhancing the denitrification of nitrifiers in the soil. Field experiments are necessary to verify the laboratory results. © 2021 Society of Chemical Industry.

Metatranscriptomic analyses reveal ruminal pH regulates fiber degradation and fermentation by shifting the microbial community and gene expression of carbohydrate-active enzymes.

BACKGROUND: Volatile fatty acids (VFA) generated from ruminal fermentation by microorganisms provide up to 75% of total metabolizable energy in ruminants. Ruminal pH is an important factor affecting the profile and production of VFA by shifting the microbial community. However, how ruminal pH affects the microbial community and its relationship with expression of genes encoding carbohydrate-active enzyme (CAZyme) for fiber degradation and fermentation are not well investigated. To fill in this knowledge gap, six cannulated Holstein heifers were subjected to a continuous 10-day intraruminal infusion of distilled water or a dilute blend of hydrochloric and phosphoric acids to achieve a pH reduction of 0.5 units in a cross-over design. RNA-seq based transcriptome profiling was performed using total RNA extracted from ruminal liquid and solid fractions collected on day 9 of each period, respectively. RESULTS: Metatranscriptomic analyses identified 19 bacterial phyla with 156 genera, 3 archaeal genera, 11 protozoal genera, and 97 CAZyme transcripts in sampled ruminal contents. Within these, 4 bacteria phyla (Proteobacteria, Firmicutes, Bacteroidetes, and Spirochaetes), 2 archaeal genera (Candidatus methanomethylophilus and Methanobrevibacter), and 5 protozoal genera (Entodinium, Polyplastron, Isotricha, Eudiplodinium, and Eremoplastron) were considered as the core active microbes, and genes encoding for cellulase, endo-1,4-beta- xylanase, amylase, and alpha-N-arabinofuranosidase were the most abundant CAZyme transcripts distributed in the rumen. Rumen microbiota is not equally distributed throughout the liquid and solid phases of rumen contents, and ruminal pH significantly affect microbial ecosystem, especially for the liquid fraction. In total, 21 bacterial genera, 4 protozoal genera, and 6 genes encoding CAZyme were regulated by ruminal pH. Metabolic pathways participated in glycolysis, pyruvate fermentation to acetate, lactate, and propanoate were downregulated by low pH in the liquid fraction. CONCLUSIONS: The ruminal microbiome changed the expression of transcripts for biochemical pathways of fiber degradation and VFA production in response to reduced pH, and at least a portion of the shifts in transcripts was associated with altered microbial community structure.

A revised representation of ruminal pH and digestive reparameterization of the Molly cow model.

Ruminal pH is a critical factor to regulate nutrient degradation and fermentation. However, it has been poorly predicted in the Molly cow model, and recent improvements in the representation of nitrogen cycling across the rumen wall altered some of the modeled responses to feed nutrients, resulting in some model bias. The objectives of this study were to further improve the representation of pH and to refit parameters related to ruminal metabolism and nutrient digestion in the model to resolve this bias, and to use the improved model to estimate nitrogen and energy fluxes with varying rumen-degradable protein (RDP; 40 vs. 60%) and ruminally degraded starch (RDSt; 50 vs. 75%). A meta data set containing 284 peer reviewed studies with 1,223 treatment means was used to derive parameter estimates for ruminal metabolism and nutrient digestions. Refitting the parameters significantly improved the accuracy and precision of the model predictions for ruminal nutrient outflow [acid detergent fiber (ADF), neutral detergent fiber (NDF), total N, microbial N, nonammonia N, and nonammonia nonmicrobial N], ammonia and blood urea concentrations, and fecal nutrient outflow (protein, ADF, and NDF). The prediction error for body weight was decreased from 19.3 to 6.2% with decreased mean bias (from 76.0 to 11.5%) and slope bias (from 17.2 to 7.7%), primarily due to improved representations of ruminal dry matter and liquid pool size. Adding ammonia concentration as a driver to the pH equation increased the precision of predicted ruminal pH and, thereby, the precision of predicted volatile fatty acid (VFA) concentrations, due to improved representation of pH regulation of VFA production rates. Although minor mean and slope bias were observed for ruminal pH and VFA concentrations, the concordance correlation coefficients indicated that much of the observed variation in these variables remains unexplained. Overall, the biological functions of nutrient degradation and digestion appear to be represented without bias. Simulated results indicated that decreasing RDP and RDSt proportions in an isonitrogenous and isocaloric diet can slightly improve N efficiency, and increasing RDSt proportions can increase energy efficiency.

Fate of pirlimycin and antibiotic resistance genes in dairy manure slurries in response to temperature and pH adjustment.

Quantifying the fate of antibiotics and antibiotic resistance genes (ARGs) in response to physicochemical factors during storage of manure slurries will aid in efforts to reduce the spread of resistance when manure is land-applied. The objectives of this study were to determine the effects of temperature (10, 35, and 55 °C) and initial pH (5, 7, 9, and 12) on the removal of pirlimycin and prevalence of ARGs during storage of dairy manure slurries. We collected and homogenized feces and urine from five lactating dairy cows treated with pirlimycin and prepared slurries by mixing manure and sterile water. Aliquots (200 mL) of slurry were transferred and incubated in 400 mL glass beakers under different temperatures (10, 35, and 55 °C) or initial pH (5, 7, 9, and 12). Pirlimycin concentration and abundances of 16S rRNA, mefA, tet(W), and cfxA as indicators of total bacteria and ARGs corresponding to macrolide, tetracycline, and ß-lactam resistance, respectively, were analyzed during manure incubation. The thermophilic environment (55 °C) increased the deconjugation and removal of pirlimycin, while the acidic shock at pH 5 increased deconjugation but inhibited removal of pirlimycin, suggesting that the chemical stability of pirlimycin could be affected by temperature and pH. The thermophilic environment decreased mefA relative abundance on day 7 and 28 (P = 0.02 and 0.04), which indicates that the bacteria that encoded mefA gene were not thermotolerant. Although mefA relative abundance was greater at the pH 9 shock than the rest of pH treatments on day 7 (P = 0.04), no significant pH effect was observed on day 28. The tet(W) abundance under initial pH 12 shock was less than other pH shocks on day 28 (P = 0.01), while no temperature effect was observed on day 28. There was no significant temperature and initial pH effect on cfxA abundance at any time point during incubation, implying that the bacteria that carrying cfxA gene are relatively insensitive to these environmental factors. Overall, directly raising temperature and pH can facilitate pirlimycin removal and decrease mefA and tet(W) relative abundances during storage of manure slurries.

Short communication: Increasing temperature and pH can facilitate reductions of cephapirin and antibiotic resistance genes in dairy manure slurries.

Quantifying antibiotics and antibiotic resistance genes (ARG) in manure exposed to various temperature and pH treatments could guide the development of cost-effective manure handling methods to minimize the spread of antibiotic resistance following land application of manure. This study aimed to investigate the effect of various temperatures and initial pH shocks on the persistence of a cephalosporin antibiotic and ARG in dairy manure slurries. Feces and urine were collected from 5 healthy dairy cows administered with cephapirin (cephalosporin antibiotic) at dry-off via intramammary infusion and were mixed with sterile water to generate manure slurries. In a 28-d incubation study, dairy manure slurries either were continuously exposed to 1 of 3 temperatures (10, 35, and 55°C) or received various initial pH (5, 7, 9, and 12) shocks. Cephapirin was detected in the initial samples and on d 1 following all treatments, but it was undetectable thereafter. This indicates that cephapirin can be rapidly degraded irrespective of temperature and pH treatments. However, degradation was greater on d 1 with the mesophilic (35°C) and thermophilic (55°C) environments compared with the psychrophilic environment (10°C). Increasing pH beyond neutral also accelerated degradation as cephapirin concentrations were lower on d 1 after initial alkaline adjustments (pH 9 and 12) than after neutral and acidic adjustments (pH 7 and 5). No significant effect of temperature or initial pH was observed on abundances of a ß-lactam ARG, cfxA, and a tetracycline ARG, tet(W), implying that bacteria that encoded cfxA or tet(W) genes were not sensitive to temperature or pH in dairy manure slurries. However, abundances of a macrolide ARG, mefA, were decreased in the psychrophilic and thermophilic environments and also following exposure to a strong alkaline shock (pH 12). Our results suggest that increasing temperature or pH during storage of dairy manure slurries could be used together with other on-farm practices that are tailored to reduce the transfer of ARG from manure to the environment following land application.

Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.

The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as input variables; and (2) to compare accuracy and precision of ANN model predictions with that of a multiple linear regression model (MLR). Data were collected from 229 published papers with 938 treatment means. The data set was randomly split into a training data set containing 70% of the observations and a test data set with the remaining observations. A series of ANN with a range of 1 to 9 artificial neurons in 1 hidden layer were examined, and the best one was selected to compare with the best-fitted MLR model. The performance of model predictions was evaluated by root mean square errors (RMSE) and concordance correlation coefficients (CCC) using cross-evaluations with 100 iterations. When using the ANN to predict ruminal pH and concentrations of ammonia, total VFA, acetate, propionate, and butyrate, the RMSE were 4.2, 41.4, 20.9, 22.3, 32.9, and 29.7% of observed means, respectively. The RMSE for the MLR were 4.2, 37.8, 18.3, 19.9, 29.8, and 26.6% of the observed means. The CCC for ruminal pH, ruminal concentrations of ammonia, total VFA, acetate, propionate, and butyrate were 0.57, 0.49, 0.45, 0.40, 0.52, and 0.40, using the ANN, and 0.37, 0.48, 0.40, 0.29, 0.43, and 0.35, using the MLR. Evaluations of the MLR and the ANN indicated that these 2 model forms exhibited similar prediction errors, with 4.2, 39.6, 19.6, 21.1, 31.3, and 28.1% of observed means for pH, ammonia, total VFA, acetate, propionate, and butyrate. Although the ANN increased the precision of predictions related to ruminal metabolism, it failed to improve the accuracy compared with the linear regression model.

A revised representation of urea and ammonia nitrogen recycling and use in the Molly cow model.

Accurately predicting nitrogen (N) digestion, absorption, and metabolism will allow formulation of diets that more closely match true animal needs from a broad range of feeds, thereby allowing efficiency of N utilization and profit to be maximized. The objectives of this study were to advance representations of N recycling between blood and the gut and urinary N excretion in the Molly cow model. The current work includes enhancements (1) representing ammonia passage to the small intestine; (2) deriving parameters defining urea synthesis and ruminal urea entry rates; (3) adding representations of intestinal urea entry, microbial protein synthesis in the hindgut, and fecal urea-N excretion; and (4) altering existing urinary N excretion equations to scale with body weight and adding purine derivatives as a component of urinary N excretion. After the modifications, prediction errors for ruminal outflows of total N, microbial N, and nonammonia, nonmicrobial N were 29.8, 32.3, and 26.2% of the respective observed mean values. Prediction errors of each were approximately 7 percentage units lower than the corresponding values before model modifications and fitting due primarily to decreased slope bias. The revised model predicted ruminal ammonia and blood urea concentrations with substantially decreased overall error and reductions in slope and mean bias. Prediction errors for gut urea-N entry were decreased from 70.5 to 26.7%, which was also a substantial improvement. Adding purine derivatives to urinary N predictions improved the accuracy of predictions of urinary N output. However, urinary urea-N excretion remains poorly predicted with 69.0% prediction errors, due mostly to overestimated urea-N entry rates. Adding representations of undigested microbial nucleic acids, microbial protein synthesized in the hindgut, and urea-N excretion in feces decreased prediction errors for fecal N excretion from 21.1 to 17.1%. The revised model predicts that urea-N entry into blood accounts for approximately 64% of dietary N intake, of which 64% is recycled to the gut lumen. Between 48 and 67% of the urea recycled to the gut flows into the rumen largely depending on diet, which accounts for 29 to 54% of total ruminal ammonia production, and 65 to 76% of this ammonia-N is captured in microbial protein, which represents 17% of N intake. Based on model simulations, feeding a diet with moderately low crude protein and high rumen-undegradable protein could increase apparent ruminal N efficiency by 20%.

An evaluation of Molly cow model predictions of ruminal metabolism and nutrient digestion for dairy and beef diets.

Model evaluation, as a critical process of model advancement, is necessary to identify adequacy and consistency of model predictions. The objectives of this study were (1) to evaluate the accuracy of Molly cow model predictions of ruminal metabolism and nutrient digestion when simulating dairy and beef cattle diets; and (2) to identify deficiencies in representations of the biology that could be used to direct further model improvements. A total of 229 studies (n = 938 treatments) including dairy and beef cattle data, published from 1972 through 2016, were collected from the literature. Root mean squared errors (RMSE) and concordance correlation coefficients (CCC) were calculated to assess model accuracy and precision. Ruminal pH was very poorly represented in the model with a RMSE of 4.6% and a CCC of 0.0. Although volatile fatty acid concentrations had negligible mean (2.5% of mean squared error) and slope (6.8% of mean squared error) bias, the CCC was 0.28, implying that further modifications with respect to volatile fatty acid production and absorption are required to improve model precision. The RMSE was greater than 50% for ruminal ammonia and blood urea-N concentrations with high proportions of error as slope bias, indicating that mechanisms driving ruminal urea N recycling are not properly simulated in the model. Only slight mean and slope bias were exhibited for ruminal outflow of neutral detergent fiber, starch, lipid, total N, and nonammonia N, and for fecal output of protein, neutral detergent fiber, lipid, and starch, indicating the mechanisms encoded in the model relative to ruminal and total-tract nutrient digestion are properly represented. All variables related to ruminal metabolism and nutrient digestion were more precisely predicted for dairy cattle than for beef cattle. This difference in precision was mostly related to the model's inability to simulate low forage diets included in the beef studies. Overall, ruminal pH was poorly simulated and contributed to problems in ruminal nutrient degradation and volatile fatty acid production predictions. Residual analyses suggested ruminal ammonia concentrations need to be considered in the ruminal pH equation, and therefore the inaccuracies in predicting ruminal urea N recycling must also be addressed. These modifications to model structure will likely improve model performance across a wider array of dietary inputs and cattle type.