ABSTRACT
Supplemental dietary rumen available fats show promise as enteric methane (eCH4) mitigators for lactating dairy cows. However, concerns include variability in eCH4 response and possible negative effects on dairy cow performance. Successful implementation of this mitigation option requires better prediction of responses specifically to rumen available FA as well as understanding the modulating effects of other dietary and animal characteristics. Using meta-analytic and meta-regression techniques, 35 published studies with diet definition were used to assess changes in eCH4 emissions and lactation performance associated with supplemental fat, specific supplemental rumen available FA types, and other dietary characteristics. Enteric CH4 (g/d) was reduced by 3.77% per percentage unit of supplemental rumen available EE (RAEE). Supplemental rumen available PUFA (C18:2 and C18:3) and UFA (C18:1, C18:2, C18:3) mitigated eCH4 (g/d) emissions in dairy cows by 6.88 and 4.65% per percentage unit increase, respectively. The anti-methanogenic effects of PUFA, MUFA and MCFA increased with correspondingly greater basal dietary levels of each FA type. Higher rumen-degradable starch (RDS; > 18% DM) in the basal diet promoted greater reductions in eCH4 yield (eCH4/DMI, g/kg) with supplemental rumen available PUFA and UFA. Both milk fat percentage and yield (kg/d) were reduced with rumen available fat supplementation with a reduction of 7.8% and 6.0%, respectively, relative to control diets. Our results highlight the importance of determining basal levels of the rumen available FA before providing supplemental rumen available FA as an option for enteric eCH4 mitigation. Dairy nutritionists can use estimates generated from this analysis to predict changes in eCH4 emissions and dairy cow performance associated with dietary supplementation of rumen available EE and specific rumen available FA types for the purpose of eCH4 mitigation.
ABSTRACT
The objective of this meta-analysis was to develop and evaluate models for predicting nitrogen (N) excretion in feces, urine, and manure in beef cattle in South America. The study incorporated a total of 1,116 individual observations of N excretion in feces and 939 individual observations of N excretion in feces and in urine (g/d), representing a diverse range of diets, animal genotypes, and management conditions in South America. The dataset also included data on dry matter intake (DMI; kg/d) and nitrogen intake (NI; g/d), concentrations of dietary components, as well as average daily gain (ADG; g/d) and average body weight (BW; kg). Models were derived using linear mixed-effects regression with a random intercept for the study. Fecal N excretion was positively associated with DMI, NI, nonfibrous carbohydrates, average BW, and ADG and negatively associated with EE and CP concentration in the diet. The univariate model predicting fecal N excretion based on DMI (model 1) performed slightly better than the univariate model, which used NI as a predictor variable (model 2) with a root mean square error (RMSE) of 38.0 vs. 39.2%, the RMSE-observations SD ratio (RSR) of 0.81 vs. 0.84, and concordance correlation coefficient (CCC) of 0.53 vs. 0.50, respectively. Models predicting urinary N excretion were less accurate than those derived to predict fecal N excretion, with an average RMSE of 43.7% vs. 37.0%, respectively. Urinary and manure N excretion were positively associated with DMI, NI, CP, average BW, and ADG and negatively associated with neutral detergent fiber concentration in the diet. As opposed to fecal N excretion, the univariate model predicting urinary N excretion using NI (model 10) performed slightly better than the univariate model using DMI (model 9) as predictor variable with an RMSE of 36.0% vs. 39.7%, RSR 0.85 vs. 0.93, and CCC of 0.43 vs. 0.29, respectively. The models developed in this study are applicable for predicting N excretion in beef cattle across a broad spectrum of dietary compositions and animal genotypes in South America. The univariate model using DMI as a predictor is recommended for fecal N prediction, while the univariate model using NI is recommended for predicting urinary and manure N excretion because the use of more complex models resulted in little to no benefits. However, it may be more useful to consider more complex models that incorporate nutrient intakes and diet composition for decision-making when N excretion is a factor to be considered. Three extant equations evaluated in this study have the potential to be used in tropical conditions typical of South America to predict fecal N excretion with good precision and accuracy. However, none of the extant equations are recommended for predicting urine or manure N excretion because of their high RMSE, and low precision and accuracy.
ABSTRACT
Ovarian follicular GCs are strongly implicated in the growth, development, and atresia of ovarian follicles. The Wnt/ß-catenin and Notch signaling pathways participate in GC proliferation, differentiation, apoptosis, and steroid hormone production during follicular development. However, the crosstalk between Wnt and Notch signaling in GCs remains unclear. This study investigated this crosstalk and the roles of these pathways in apoptosis, cell cycle progression, cell proliferation, and steroid hormone secretion in bovine follicular GCs. The interaction between ß-catenin and Notch2 in GCs was assessed by overexpressing CTNNB1, which encodes ß-catenin. The results showed that inhibiting the Notch pathway by Notch2 silencing in GCs arrested the cell cycle, promoted apoptosis, reduced progesterone (P4) production, and inhibited the Wnt2-mediated Wnt/ß-catenin pathway in GCs. IWR-1 inhibited Wnt2/ß-catenin and Notch signaling, reduced GC proliferation, stimulated apoptosis, induced G1 cell cycle arrest, and reduced P4 production. CTNNB1 overexpression had the opposite effect and increased 17ß-estradiol (E2) production and Notch2 protein expression. Co-immunoprecipitation assays revealed that Notch2 interacted with ß-catenin. These results elucidate the crosstalk between the Wnt/ß-catenin and Notch pathways and the role of these pathways in bovine follicular GC development.
ABSTRACT
At the end of the 1950s, studies began to create high-yield cultivars with the aim of increasing the supply of basic foods in the world, this action was called "green evolution". It was associated with the increase in the use of inputs to increase production levels, leading agriculture to a possible increase in environmental impacts and "harmful habits" of management. To characterize the historical damage of this action, it is necessary to use methods that generate universal results, capable of representing the world. Then, we use Life cycle assessment (LCA) to estimate the historical evolution of the environmental impacts of the two main feedstock for feed in the world, soybeans, and corn, from 1961 to 2021. To better understand the variation in their impacts, we consider the change in agricultural management when we use as a functional unit the amount of area needed to produce 1 kg of grain. Although emissions and impacts from agriculture, by area, have increased each decade, when considering productivity through the area/production ratio, we note that a number of emissions were avoided, along with impacts in all categories evaluated. Therefore, the development and use of technologies that modify the area/production ratio can contribute to avoiding environmental impacts.
Subject(s)
Animal Feed , Environment , Animals , Retrospective Studies , Animal Feed/analysis , Agriculture/methods , TechnologyABSTRACT
Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.
ABSTRACT
In bovine follicular development, the proliferation of bovine granulosa cells affects follicular selection, atresia, and cystic follicle formation. When cystic follicles appear on the ovaries, granulosa cells stop proliferating, resulting in the reduction of granulosa cells layer. In our previous study, the whole transcriptome sequencing revealed that Bone morphogenetic protein receptor 2 (BMPR2) was differentially expressed between cystic and normal follicular granulosa cells. We speculated that long noncoding RNA may act as competing endogenous RNA targeting microRNAs and then regulating the expression of BMPR2 and the function of granulosa cells, thereby affecting follicular development and cyst formation. In this study, the results elucidated that long noncoding RNA S100PBP (NONBTAT011846.2) directly bound miR-2285bc, which targeted in the BMPR2 3'-UTR. miR-2285bc suppresses granulosa cells proliferation by downregulating BMPR2 expression. Furthermore, long noncoding RNA S100PBP was silenced by small interfering RNA, and long noncoding RNA S100PBP regulated BMPR2 expression by sponging miR-2285bc investigated through cross-verification. When small interfering RNA of long noncoding RNA S100PBP was transfected into granulosa cells, the results revealed similar molecular changes as those transfected with miR-2285bc mimics. Silencing long noncoding RNA S100PBP or overexpressing miR-2285bc altered the expressions of some follicular development-related genes, which could be related to follicular cyst occurrence. In conclusion, our findings support that long noncoding RNA S100PBP regulates the expression of BMPR2 through sponge miR-2285bc, promotes the proliferation of granulosa cells, inhibits their apoptosis, and increases the synthesis and secretion of follicular steroid hormones, thus promoting the development of bovine follicles.
Subject(s)
Bone Morphogenetic Protein Receptors, Type II , Cell Proliferation , Granulosa Cells , MicroRNAs , RNA, Long Noncoding , Animals , Female , Granulosa Cells/metabolism , Cattle , RNA, Long Noncoding/genetics , RNA, Long Noncoding/metabolism , MicroRNAs/genetics , MicroRNAs/metabolism , Bone Morphogenetic Protein Receptors, Type II/genetics , Bone Morphogenetic Protein Receptors, Type II/metabolism , Gene Expression RegulationABSTRACT
Methane (CH4) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH4. To address this limitation, we developed novel CH4 prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH4 production (g CH4/animal·d, ANIM-B models) and CH4 yield (g CH4/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin's concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH4 prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH4 emissions from sheep, providing valuable insights for future research and mitigation strategies.
Subject(s)
Methane , Rumen , Sheep , Animals , Female , Bayes Theorem , Ruminants , Diet/veterinary , Bacteria/genetics , Animal Feed/analysis , LactationABSTRACT
BACKGROUND: The red macroalgae Asparagopsis is an effective methanogenesis inhibitor due to the presence of halogenated methane (CH4) analogues, primarily bromoform (CHBr3). This study aimed to investigate the degradation process of CHBr3 from A. taxiformis in the rumen and whether this process is diet-dependent. An in vitro batch culture system was used according to a 2 × 2 factorial design, assessing two A. taxiformis inclusion rates [0 (CTL) and 2% DM diet (AT)] and two diets [high-concentrate (HC) and high-forage diet (HF)]. Incubations lasted for 72 h and samples of headspace and fermentation liquid were taken at 0, 0.5, 1, 3, 6, 8, 12, 16, 24, 48 and 72 h to assess the pattern of degradation of CHBr3 into dibromomethane (CH2Br2) and fermentation parameters. Additionally, an in vitro experiment with pure cultures of seven methanogens strains (Methanobrevibacter smithii, Methanobrevibacter ruminantium, Methanosphaera stadtmanae, Methanosarcina barkeri, Methanobrevibacter millerae, Methanothermobacter wolfei and Methanobacterium mobile) was conducted to test the effects of increasing concentrations of CHBr3 (0.4, 2, 10 and 50 µmol/L). RESULTS: The addition of AT significantly decreased CH4 production (P = 0.002) and the acetate:propionate ratio (P = 0.003) during a 72-h incubation. The concentrations of CHBr3 showed a rapid decrease with nearly 90% degraded within the first 3 h of incubation. On the contrary, CH2Br2 concentration quickly increased during the first 6 h and then gradually decreased towards the end of the incubation. Neither CHBr3 degradation nor CH2Br2 synthesis were affected by the type of diet used as substrate, suggesting that the fermentation rate is not a driving factor involved in CHBr3 degradation. The in vitro culture of methanogens showed a dose-response effect of CHBr3 by inhibiting the growth of M. smithii, M. ruminantium, M. stadtmanae, M. barkeri, M. millerae, M. wolfei, and M. mobile. CONCLUSIONS: The present work demonstrated that CHBr3 from A. taxiformis is quickly degraded to CH2Br2 in the rumen and that the fermentation rate promoted by different diets is not a driving factor involved in CHBr3 degradation.
ABSTRACT
Bacterial infections of the reproductive system of dairy cows lead to inflammation, and lipopolysaccharide (LPS) of the cell wall of Gram-negative bacteria is the main pathogenic component of inflammation. LPS inhibits follicular growth and development and alters the expression of follicular granulosa cells (GCs) genes in the ovary, leading to their functional disorders. Naphthoquinones have anti-inflammatory effects. In this experiment, 2-methoxy-1,4-naphthoquinone (MNQ), an extract of Impatiens balsamina L, and its derivative D21 were used to eliminate the inflammatory response of GCs exposed to LPS in vitro and to restore functional disorders in GCs. The anti-inflammatory effects of the two compounds were compared and their mechanism of action was investigated. The cytotoxicity of MNQ and its derivative D21 on follicular GCs was determined by MTT method. The relative expression of inflammatory factors and steroid synthesis-related genes were determined by qRT-PCR. The protective effects of MNQ and D21 on cellular inflammatory damage were observed by TEM. ELISA were performed to detect the levels of estradiol (E2) and progesterone (P4) in the culture supernatant. The expression of differential genes was analyzed by RNA-seq, and GO and KEGG enrichment analysis of differential genes were performed to investigate the mechanism of anti-inflammatory effect of D21. The results showed that the maximum no-cytotoxic concentrations of MNQ and D21 acting on GCs for 12 h were 4 µM and 64 µM, respectively. LPS concentration of 10 µg/mL had little effect on the survival of follicular GCs, but the relative expressions of IL-6, IL-1ß and TNF-α were significantly higher (P < 0.05). The results of qRT-PCR, ELISA and TEM observations showed that the anti-inflammatory effect of D21 was stronger than that of MNQ. RNA-seq analysis revealed a total of 341 differential genes between the LPS vs CK group (Control group) and the D21+L vs LPS group, which were mainly enriched in signaling pathways such as steroid biosynthesis. Nine genes in this signaling pathway were analyzed, and the RNA-seq and qRT-PCR results were found to be basically consistent. In this study, we confirmed that derivative D21 has stronger in vitro anti-inflammatory effects and better efficacy in protecting bovine follicular GCs from inflammatory damage than MNQ and acts through the steroid biosynthesis signaling pathway.
Subject(s)
Cattle Diseases , Naphthoquinones , Female , Animals , Cattle , Lipopolysaccharides/toxicity , Naphthoquinones/pharmacology , Progesterone/metabolism , Signal Transduction , Inflammation/chemically induced , Inflammation/veterinary , Anti-Inflammatory Agents/pharmacology , Cattle Diseases/chemically inducedABSTRACT
Estimating daily enteric hydrogen (H2) and methane (CH4) emitted from dairy cattle using spot sampling techniques requires accurate sampling schemes. These sampling schemes determine the number of daily samplings and their intervals. This simulation study assessed the accuracy of daily H2 and CH4 emissions from dairy cattle using various sampling schemes for gas collection. Gas emission data were available from a crossover experiment with 28 cows fed twice daily at 80% to 95% of the ad libitum intake, and an experiment that used a repeated randomized block design with 16 cows twice daily fed ad libitum. Gases were sampled every 12 to 15 min for 3 consecutive days in climate respiration chambers. Feed was fed in 2 equal portions per day in both experiments. Per individual cow-period combination, generalized additive models were fitted to all diurnal H2 and CH4 emission profiles. Per profile, the models were fitted using the generalized cross-validation, REML, REML while assuming correlated residuals, and REML while assuming heteroscedastic residuals. The areas under the curve (AUC) of these 4 fits were numerically integrated over 24 h to compute the daily production and compared with the mean of all data points, which was considered the reference. Next, the best of the 4 fits was used to evaluate 9 different sampling schemes. This evaluation determined the average predicted values sampled at 0.5, 1, and 2 h intervals starting at 0 h from morning feeding, at 1 and 2 h intervals starting at 0.5 h from morning feeding, at 6 and 8 h intervals starting at 2 h from morning feeding, and at 2 unequally spaced intervals with 2 or 3 samples per day. Sampling every 0.5 h was needed to obtain daily H2 productions not different from the selected AUC for the restricted feeding experiment, whereas less frequent sampling had predictions varying from 47% to 233% of the AUC. For the ad libitum feeding experiment, sampling schemes had H2 productions from 85% to 155% of the corresponding AUC. For the restricted feeding experiment, daily CH4 production needed samplings every 2 h or shorter, or 1 h or shorter, depending on sampling time after feeding, whereas sampling scheme did not affect CH4 production for the twice daily ad libitum feeding experiment. In conclusion, sampling scheme had a major impact on predicted daily H2 production, particularly with restricted feeding, whereas daily CH4 production was less severely affected by sampling scheme.
Subject(s)
Lactation , Milk , Female , Cattle , Animals , Milk/chemistry , Diet/veterinary , Hydrogen , MethaneABSTRACT
Livestock production contributes to greenhouse gas (GHG) emissions. However, there is a considerable variability in the carbon footprint associated with livestock production. Site specific estimates of GHG emissions are needed to accurately focus GHG emission reduction efforts. A holistic approach must be taken to assess the environmental impact of livestock production using appropriate geographical scale. The objective of this study was to determine baseline GHG emissions from dairy production in South Dakota using a life cycle assessment (LCA) approach. A cradle-to-farm gate LCA was used to estimate the GHG emissions to produce 1 kg of fat and protein corrected milk (FPCM) in South Dakota. The system boundary was divided into feed production, farm management, enteric methane, and manure management as these activities are the main contributors to the overall GHG emissions. The production of 1 kg FPCM in South Dakota dairies was estimated to emit 1.23 kg CO2 equivalents. The major contributors were enteric methane (46%) and manure management (32.7%). Feed production and farm management made up 14.1 and 7.2%, respectively. The estimate is similar to the national average but slightly higher than the California dairy system. The source of corn used in the dairies influences the footprint. For example, South Dakota corn had fewer GHG emissions than grain produced and transported in from Iowa. Therefore, locally and more sustainably sourced feed input will contribute to further reducing the environmental impacts. Improvements in efficiency of milk production through better genetics, nutrition animal welfare and feed production are expected to further reduce the carbon footprint of South Dakota dairies. Furthermore, anaerobic digesters will reduce emissions from manure sources.
Subject(s)
Carbon Footprint , Greenhouse Gases , Animals , Manure/analysis , South Dakota , Dairying , Greenhouse Gases/analysis , Milk/chemistry , Methane/analysis , Greenhouse EffectABSTRACT
Inflammation of the reproductive tract in dairy cows lead to functional disorders of follicular granulosa cells (GCs) in mammalian ovaries resulting in infertility and serious losses to the livestock industry. Lipopolysaccharide (LPS) can induce an inflammatory response in follicular granulosa cells in vitro. The aim of this study was to investigate the cellular regulatory mechanism of MNQ (2-methoxy-1,4-naphthoquinone) on eliminating the inflammatory response and restoring normal functions for bovine ovarian follicular GCs cultured in vitro exposed to LPS. The cytotoxicity of MNQ and LPS on GCs were detected by MTT method to determine the safe concentration. The relative expression of inflammatory factors and steroid synthesis-related genes were detected by qRT-PCR. The concentration of steroid hormones in the culture broth were detected by ELISA. Differential gene expressions were analyzed by RNA-seq. There were no toxic effects on GCs at MNQ and LPS concentrations of less than 3 µM and 10 µg/mL, respectively and treated in 12 h. The relative expressions of IL-6, IL-1ß and TNF-α were significantly higher in the LPS group compared with the CK group when GCs cultured in vitro were treated with the above concentrations and times (P < 0.05), but significantly lower in the MNQ+LPS group compared with the LPS group (P < 0.05). The levels of E2 and P4 in the culture solution were significantly reduced in the LPS group compared to the CK group (P < 0.05), and restored in the MNQ+LPS group. The relative expressions of CYP19A1, CYP11A1, 3ß-HSD, and STAR were significantly decreased in the LPS group compared with the CK group (P < 0.05), while the MNQ+LPS group also recovered to some extent. There were 407 differential genes shared by LPS vs CK and MNQ+LPS vs LPS by RNA-seq analysis, which were mainly enriched in steroid biosynthesis and TNF signaling pathway. We screened 10 genes for analysis and found consistent results for RNA-seq and qRT-PCR. In this study, we confirmed the protective effect of MNQ, an extract from Impatiens balsamina L, on LPS-induced inflammatory responses in bovine follicular granulosa cells in vitro as well as functional damage, and acted through steroid biosynthesis and TNF signaling pathways.
Subject(s)
Estradiol , Lipopolysaccharides , Female , Cattle , Animals , Lipopolysaccharides/pharmacology , Estradiol/metabolism , Granulosa Cells/metabolism , Steroids/metabolism , Cytochrome P-450 CYP1A1/metabolism , Mammals/metabolismABSTRACT
Bone morphogenetic protein and activin membrane-bound inhibitor (BAMBI) regulates mammalian ovarian follicle growth and maturation; however, its effect on luteinized granulosa cells (LGCs) in sheep ovarian follicles remains unknown. Here we explored the regulatory role of LGC functions and steroid hormone synthesis by BAMBI. Multiple sequence alignment revealed that the sheep BAMBI gene sequence was relatively conserved. Sheep LGCs were strongly positive for BAMBI. LGC proliferation increased when BAMBI was silenced and decreased when BAMBI was overexpressed. After BAMBI overexpression, the expression of CASP3, CASP8, CASP9, and BAX significantly increased, whereas that of BCL2 and the ratio of BCL2/BAX expression decreased. The opposite was observed after BAMBI silencing. CDKN1A, CCND1, and CCND2 were downregulated with BAMBI overexpression and upregulated with BAMBI silencing. Expression of steroid hormone-related genes (CYP11A1, STAR, and 3BHSD), except CYP19A1, significantly increased after BAMBI overexpression. Moreover, estrogen and progesterone secretion increased after BAMBI overexpression and decreased after BAMBI interference. The effect of the exogenous addition of bone morphogenetic protein 2 (BMP2) on GCs was similar to that of BAMBI overexpression. In conclusion, BAMBI can regulate the proliferation and steroid hormone synthesis of sheep LGCs, and BMP2 can affect LGCs as an activator of BAMBI. These findings provide a basis for further research on the physiological role of BAMBI.
Subject(s)
Granulosa Cells , Steroids , Female , Animals , Sheep , bcl-2-Associated X Protein/metabolism , Cells, Cultured , Granulosa Cells/metabolism , Steroids/metabolism , Progesterone/metabolism , Cell Proliferation , MammalsABSTRACT
Ruminants, particularly dairy and beef cattle, contribute to climate change through mostly enteric methane emissions. Several mitigating options have been proposed, including the feed additive 3-nitrooxypropanol (3-NOP). The objectives of this study were to explain the variability in the mitigating effect of 3-NOP and to investigate the interaction between diet composition and 3-NOP dose, using meta-analytical approaches. Data from 13 articles (14 experiments) met the selection criteria for inclusion in the meta-analysis, and 48 treatment means were used for the analysis. Mean differences were calculated as 3-NOP treatment mean minus control treatment mean and then expressed as a percentage of the control mean. Three types of models were developed: (1) one including 3-NOP dose, overall mean, and individual covariate; (2) a combination of neutral detergent fiber (NDF), 3-NOP dose, and overall mean; and (3) one selected model from all combinations of up to 5 covariates, which were compared using a leave-one-out cross validation method. Models including only 3-NOP dose resulted in a significant reduction of 32.7%, 30.9%, and 32.6% for CH4 production (g/d), yield (g/kg dry matter intake), and intensity (g/kg energy-corrected milk), respectively, at an average 3-NOP dose of 70.5 mg/kg dry matter (DM). The greater the NDF content in the diet, the lower the reduction efficiency for a given 3-NOP dose. For 10 g/kg DM increase in NDF content from its mean (329 g of NDF/kg of DM) the 3-NOP effect on CH4 production was impaired by 0.633%, the 3-NOP effect on CH4 yield by 0.647%, and the 3-NOP effect on CH4 intensity by 0.723%. The analysis based on leave-one-out cross validation showed an increase in NDF and crude fat content reduces efficacy of 3-NOP and an increase in 3-NOP dose increases efficacy. A 1% (10 g/kg) DM decrease in dietary NDF content from its mean may increase the efficacy of 3-NOP in reducing CH4 production by 0.915%. A 1% (10 g/kg DM) decrease in dietary crude fat content from its mean enhances the efficacy of 3-NOP on CH4 production by 3.080% at a given dose and NDF level. For CH4 yield, next to 3-NOP dose, dietary NDF content and dietary crude fat content were included in the selected model, but also dietary starch content with an opposite direction to NDF and crude fat. The effect of 3-NOP dose on CH4 intensity was similar to its effect on CH4 production, whereas the effect of dietary NDF content was slightly lower. Expanding the previously published models with the newly available data published from trials since then improved model performance, hence demonstrating the value of regularly updating meta-analyses if a wider range of data becomes available.
Subject(s)
Lactation , Milk , Female , Cattle , Animals , Milk/chemistry , Diet/veterinary , Ruminants , Dietary Fiber/analysis , Dietary Fats/analysis , Methane , Animal Feed/analysis , Rumen/chemistryABSTRACT
On-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended practices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the predictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (â¼ 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % ≥ DFC ≥ 54 %), and low-forage (50 % ≥ DFC) diets. Feed intake and average daily gain (ADG) were the main predictors of CH4 emission (g d-1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg-1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Simple and multiple regression models including ADG were accurate and a feasible option to predict CH4 emission when data on feed intake are not available. Methane yield was not well predicted by any extant equation in contrast to the newly-developed models. The present study delivered new models that may be alternatives for the IPCC Tier 2 equations to improve CH4 prediction for beef cattle in inventories of LAC countries based either on more or less readily available data.
Subject(s)
Animal Feed , Methane , Animals , Cattle , Animal Feed/analysis , Latin America , Diet/veterinary , EatingABSTRACT
Cross-talk between competitive endogenous RNAs (ceRNAs) may play a critical role in revealing potential mechanism of bovine follicular cysts. Ovarian cyst has always been an intractable scientific problem and has led to considerable economic losses to bovine breeding industry. However, its pathogenesis and molecular mechanisms are still not well understood. Here, this study aimed to investigate the role of non-coding RNAs (ncRNAs) and the ceRNA networks in bovine follicular cyst. Whole transcriptome sequencing of bovine follicular granulosa cells (GCs) was conducted to obtain the expression profiles of mRNAs, lncRNAs and miRNAs. The results for the identified expressions of 8,003 mRNAs, 579 lncRNAs and 205 miRNAs were often altered between cystic and normal follicular GCs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed on these differentially expressed mRNAs. Furthermore, the ceRNA network combining mRNAs, miRNAs, and lncRNAs using several bioinformatics methods based on co-expression analysis between the differentially expressed RNAs was conducted. Finally, the lncRNA NONBTAT027373.1-miR-664b-HSD17B7 pathway was verified by dual-luciferase reporting assay and RNA binding protein immunoprecipitation (RIP) assay. LncRNA NONBTAT027373.1 sponged miR-664b in GCs and prevented miR-664b from binding to the HSD17B7 3'-UTR. These results indicated that genes and lncRNAs related to steroid hormone synthesis and energy metabolism could play important roles in the formation of bovine cystic follicles through the ceRNA mechanism and represent candidate targets for further research. This can be used as a practical guideline for promoting healthy and highly efficient development in the bovine industry.
ABSTRACT
Ruminant livestock are an important source of anthropogenic methane (CH4). Decreasing the emissions of enteric CH4 from ruminant production is strategic to limit the global temperature increase to 1.5°C by 2050. Research in the area of enteric CH4 mitigation has grown exponentially in the last 2 decades, with various strategies for enteric CH4 abatement being investigated: production intensification, dietary manipulation (including supplementation and processing of concentrates and lipids, and management of forage and pastures), rumen manipulation (supplementation of ionophores, 3-nitrooxypropanol, macroalgae, alternative electron acceptors, and phytochemicals), and selection of low-CH4-producing animals. Other enteric CH4 mitigation strategies are at earlier stages of research but rapidly developing. Herein, we discuss and analyze the current status of available enteric CH4 mitigation strategies with an emphasis on opportunities and barriers to their implementation in confined and partial grazing production systems, and in extensive and fully grazing production systems. For each enteric CH4 mitigation strategy, we discuss its effectiveness to decrease total CH4 emissions and emissions on a per animal product basis, safety issues, impacts on the emissions of other greenhouse gases, as well as other economic, regulatory, and societal aspects that are key to implementation. Most research has been conducted with confined animals, and considerably more research is needed to develop, adapt, and evaluate antimethanogenic strategies for grazing systems. In general, few options are currently available for extensive production systems without feed supplementation. Continuous research and development are needed to develop enteric CH4 mitigation strategies that are locally applicable. Information is needed to calculate carbon footprints of interventions on a regional basis to evaluate the impact of mitigation strategies on net greenhouse gas emissions. Economically affordable enteric CH4 mitigation solutions are urgently needed. Successful implementation of safe and effective antimethanogenic strategies will also require delivery mechanisms and adequate technical support for producers, as well as consumer involvement and acceptance. The most appropriate metrics should be used in quantifying the overall climate outcomes associated with mitigation of enteric CH4 emissions. A holistic approach is required, and buy-in is needed at all levels of the supply chain.
Subject(s)
Greenhouse Gases , Methane , Animals , Methane/analysis , Biodiversity , Temperature , RuminantsSubject(s)
Chickens , Methionine , Animals , Dietary Supplements , Meta-Analysis as Topic , RacemethionineABSTRACT
The contribution of greenhouse gas (GHG) emissions from ruminant production systems varies between countries and between regions within individual countries. The appropriate quantification of GHG emissions, specifically methane (CH4), has raised questions about the correct reporting of GHG inventories and, perhaps more importantly, how best to mitigate CH4 emissions. This review documents existing methods and methodologies to measure and estimate CH4 emissions from ruminant animals and the manure produced therein over various scales and conditions. Measurements of CH4 have frequently been conducted in research settings using classical methodologies developed for bioenergetic purposes, such as gas exchange techniques (respiration chambers, headboxes). While very precise, these techniques are limited to research settings as they are expensive, labor-intensive, and applicable only to a few animals. Head-stalls, such as the GreenFeed system, have been used to measure expired CH4 for individual animals housed alone or in groups in confinement or grazing. This technique requires frequent animal visitation over the diurnal measurement period and an adequate number of collection days. The tracer gas technique can be used to measure CH4 from individual animals housed outdoors, as there is a need to ensure low background concentrations. Micrometeorological techniques (e.g., open-path lasers) can measure CH4 emissions over larger areas and many animals, but limitations exist, including the need to measure over more extended periods. Measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the variable that contributes the greatest to measurement uncertainty. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources (enteric and manure). In contrast, top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point. While these two estimation approaches rarely agree, they help identify knowledge gaps and research requirements in practice.
There is a need to accurately and precisely quantify greenhouse gas (GHG) emissions, specifically methane (CH4), to ensure correct reporting of GHG inventories and, perhaps more importantly, determine how to best mitigate CH4 emissions. The objective of this study was to review existing methods and methodologies to quantify and estimate CH4 emissions from ruminants. Historically, most techniques were developed for specific purposes that may limit their widespread use on commercial farms and for inventory purposes and typically required frequent calibration and equipment maintenance. Whole animal and head respiration chambers, spot sampling techniques, and tracer gas methods can be used to measure enteric CH4 from individual animals, but each technique has its own inherent limitations. The measurement of CH4 emissions from manure depends on the type of storage, animal housing, CH4 concentration inside and outside the boundaries of the area of interest, and ventilation rate, which is likely the most complex variable creating many uncertainties. For large-scale areas, aircraft, drones, and satellites have been used in association with the tracer flux method, inverse modeling, imagery, and LiDAR (Light Detection and Ranging), but research is lagging in validating these methods. Bottom-up approaches to estimating CH4 emissions rely on empirical or mechanistic modeling to quantify the contribution of individual sources. Top-down approaches estimate the amount of CH4 in the atmosphere using spatial and temporal models to account for transportation from an emitter to an observation point.
Subject(s)
Greenhouse Gases , Methane , Animals , Eating , Manure/analysis , Methane/analysis , RuminantsABSTRACT
Mitigation of enteric methane (CH4) presents a feasible approach to curbing agriculture's contribution to climate change. One intervention for reduction is dietary reformulation, which manipulates the composition of feedstuffs in ruminant diets to redirect fermentation processes toward low CH4 emissions. Examples include reducing the relative proportion of forages to concentrates, determining the rate of digestibility and passage rate from the rumen, and dietary lipid inclusion. Feed additives present another intervention for CH4 abatement and are classified based on their mode of action. Through inhibition of key enzymes, 3-nitrooxypropanol (3-NOP) and halogenated compounds directly target the methanogenesis pathway. Rumen environment modifiers, including nitrates, essential oils, and tannins, act on the conditions that affect methanogens and remove the accessibility of fermentation products needed for CH4 formation. Low CH4-emitting animals can also be directly or indirectly selected through breeding interventions, and genome-wide association studies are expected to provide efficient selection decisions. Overall, dietary reformulation and feed additive inclusion provide immediate and reversible effects, while selective breeding produces lasting, cumulative CH4 emission reductions.