The polysaccharide isolated from alfalfa was considered to be a kind of macromolecule with some biological activities; however, its molecular structure and effects on immune cells are still unclear. The objectives of this study were to explore the extraction and purifying methods of alfalfa (Medicago sativa L.) polysaccharide (APS) and decipher its composition and molecular characteristics, as well as its activation to lymphocytes. The crude polysaccharides isolated from alfalfa by water extraction and alcohol precipitation methods were purified by semipermeable membrane dialysis. Five batches of alfalfa samples were obtained from five farms (one composite sample per farm) and three replicates were conducted for each sample in determination. The results from ion chromatography (IC) analysis showed that the APS was composed of fucose, arabinose, galactose, glucose, xylose, mannose, galactose, galacturonic acid (GalA), and glucuronic acid (GlcA) with a molar ratio of 2.6:8.0:4.7:21.3:3.2:1.0:74.2:14.9. The weight-average molecular weight (Mw), number-average molecular weight (Mn), and Z-average molecular weight (Mz) of APS were calculated to be 3.30 × 10⁶, 4.06 × 10⁵, and 1.43 × 10⁸ g/mol, respectively, according to the analysis by gel permeation chromatography-refractive index-multiangle laser light scattering (GPC-RI-MALS). The findings of electron ionization mass spectrometry (EI-MS) suggest that APS consists of seven linkage residues, namely 1,5-Araf, galactose (T-D-Glc), glucose (T-D-Gal), 1,4-Gal-Ac, 1,4-Glc, 1,6-Gal, and 1,3,4-GalA, with molar proportions of 10.30%, 4.02%, 10.28%, 52.29%, 17.02%, 3.52%, and 2.57%, respectively. Additionally, APS markedly increased B-cell proliferation and IgM secretion in a dose- and time-dependent manner but not the proliferation and cytokine (IL-2, -4, and IFN-γ) expression of T cells. Taken together, the present results suggest that APS are macromolecular polymers with a molar mass (indicated by Mw) of 3.3 × 10⁶ g/mol and may be a potential candidate as an immunopotentiating pharmaceutical agent or functional food.

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, andSpirochaetes), 2 archaeal genera (Candidatus methanomethylophilusandMethanobrevibacter), and 5 protozoal genera (Entodinium,Polyplastron,Isotricha,Eudiplodinium, andEremoplastron) 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.

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.

● Microbial fermentation in the rumen is a main source of methane emissions. ● Nutritional strategies can effectively mitigate methane emissions by manipulating biochemical reactions in the methanogenesis pathways. ● Mitigation practices must be evaluated in an integrated animal production system instead of as isolated components. Within the agricultural sector, animal production contributes to 14.5% of global anthropogenic greenhouse gas emissions and produces around 37% of global CH₄ emissions, mainly due to ruminal fermentation in ruminants. Over 90% of CH₄ is synthesized by methanogens in the rumen during carbohydrate fermentation. According to different substrates, methanogenesis pathways can be divided into four categories: (1) hydrogenotrophic pathway; (2) acetoclastic pathway; (3) methyl dismutation pathway; and (4) methyl-reducing pathway. Based on the principle of biochemical reactions in the methanogenesis pathways, this paper reviews the latest publications on CH₄ decreases in ruminants and described three nutritional strategies in terms of dietary nutrient manipulation (feeding management, feed composition, forage quality and lipids), microbial manipulation (ionophore, defaunation, methanogen inhibitors and probiotics), and chemical manipulation (nitrate, organic acids, plant secondary metabolites and phlorotannins, or halides in seaweeds). For each mitigation strategy, the review discusses effectiveness for decreasing CH₄ emissions, application prescription, and feed safety based on results from in vitro and in vivo studies. This review summarizes different nutritional strategies to mitigate CH₄ emissions and proposed comprehensive approaches for future feeding interventions and applications in the livestock industry.

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.