Effect of Chitosan on Ruminal Fermentation and Microbial Communities, Methane Emissions, and Productive Performance of Dairy Cattle.
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SUBMITTER: Rey J
PROVIDER: S-EPMC10525946 | biostudies-literature | 2023 Sep
REPOSITORIES: biostudies-literature
Publications
Effect of Chitosan on Ruminal Fermentation and Microbial Communities, Methane Emissions, and Productive Performance of Dairy Cattle.
Rey Jagoba J Díaz de Otálora Xabier X Atxaerandio Raquel R Mandaluniz Nerea N García-Rodríguez Aser A González-Recio Oscar O López-García Adrián A Ruiz Roberto R Goiri Idoia I
Animals : an open access journal from MDPI 20230908 18
This study aimed to expand the knowledge about the activity and mode of action of CHI on methanogenesis and rumen microbial populations in vivo. A total of 16 lactating dairy cows were distributed in two groups, one of them receiving 135 mg CHI/kg body weight daily. The effect on productive performance, milk composition, fermentation efficiency, methane emissions, microbial protein synthesis, and ruminal microbial communities was determined. Supplementation with CHI did not affect rumen microbia ...[more]
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Project description:The aim of this study was to investigate the effects of 3-nitrooxypropanol (3-NOP) and chloroform on methane (CH4) and H2 production, ruminal metabolites and microbial community structure in cattle fed a tropical forage diet. Eight rumen-fistulated steers were fed a roughage hay diet (Rhodes grass; Chloris gayana) for 31 days (control period). Four animals received the antimethanogenic compound chloroform (1.6 g chloroform-cyclodextrin/100 kg live weight (LW)) while the other four received 3-NOP (2.5 g 3-NOP/animal/day) for 21 days. Methane decrease compared with control period was similar for both treatments (30-38%) with no differences for expelled H2 between controls and treatments. Daily weight gain (DWG) was significantly increased when animals were treated with 3-NOP compared with chloroform and control. Regarding the ruminal fermentation parameters increases in ammonia, acetate and branched chain fatty acids were observed with both compounds compared with the controls. Also, methylamines, alcohols and dimethyl sulfone (DMSO2) concentrations were significantly increased with the treatments compared with control, being greater with 3-NOP. The rumen microbial analyses revealed a similar profile for both treatments, with a shift in operational taxonomic units (OTUs) assigned to the Prevotellaceae and Campylobacteraceae family. Moreover, major archaeal OTUs associated with Methanobrevibacter and Methanosphaera were significantly affected to varying extents based on the inhibitory treatments compared to the control. The abundance of the Methanobrevibacter spp. was decreased by 3-NOP and chloroform, while the Methanomassiliicoccaceae family was inhibited only by 3-NOP. The results suggest that despite the specific mode of action of 3-NOP on methanogens, inhibition of methanogenesis by both compounds resulted in similar responses in metabolism and microbial community structure in the rumen. We hypothesized that these changes were driven by the redirection of metabolic hydrogen ([H]) by both treatments. Therefore results from previous publications using chloroform as an inhibitor of methanogenesis may be useful in predicting ruminal microbiota and fermentation responses to 3-NOP.
| S-EPMC6090035 | biostudies-literature
Project description:Greenhouse gas emissions, such as enteric methane (CH4) from ruminant livestock, have been linked to global warming. Thus, easily applicable CH4 management strategies, including the inclusion of dietary additives, should be in place. The objectives of the current study were to: (i) compile a database of animal records that supplemented monensin and investigate the effect of monensin on CH4 emissions; (ii) identify the principal dietary, animal, and lactation performance input variables that predict enteric CH4 production (g/d) and yield (g/kg of dry matter intake DMI); (iii) develop empirical models that predict CH4 production and yield in dairy cattle; and (iv) evaluate the newly developed models and published models in the literature. A significant reduction in CH4 production and yield of 5.4% and 4.0%, respectively, was found with a monensin supplementation of ≤24 mg/kg DM. However, no robust models were developed from the monensin database because of inadequate observations under the current paper's inclusion/exclusion criteria. Thus, further long-term in vivo studies of monensin supplementation at ≤24 mg/kg DMI in dairy cattle on CH4 emissions specifically beyond 21 days of feeding are reported to ensure the monensin effects on the enteric CH4 are needed. In order to explore CH4 predictions independent of monensin, additional studies were added to the database. Subsequently, dairy cattle CH4 production prediction models were developed using a database generated from 18 in vivo studies, which included 61 treatment means from the combined data of lactating and non-lactating cows (COM) with a subset of 48 treatment means for lactating cows (LAC database). A leave-one-out cross-validation of the derived models showed that a DMI-only predictor model had a similar root mean square prediction error as a percentage of the mean observed value (RMSPE, %) on the COM and LAC database of 14.7 and 14.1%, respectively, and it was the key predictor of CH4 production. All databases observed an improvement in prediction abilities in CH4 production with DMI in the models along with dietary forage proportion inclusion and the quadratic term of dietary forage proportion. For the COM database, the CH4 yield was best predicted by the dietary forage proportion only, while the LAC database was for dietary forage proportion, milk fat, and protein yields. The best newly developed models showed improved predictions of CH4 emission compared to other published equations. Our results indicate that the inclusion of dietary composition along with DMI can provide an improved CH4 production prediction in dairy cattle.
| S-EPMC10135289 | biostudies-literature
Project description:IntroductionBiochar has gained significant attention as a possible anti-methanogenic supplement for ruminants due to its potential to reduce methane (CH₄) emissions from enteric fermentation. However, its effects on rumen methanogenesis have been inconsistent and, in some cases, contradictory. These variations are likely influenced by factors such as the type of biochar used, its source material, and how it is administered, including the form in which it is provided and the dosage needed to achieve desired outcomes. This study aimed to examine the effects of two fit-for-purpose biochars on rumen fermentation, CH4 emissions, and the rumen microbiome of cattle-fed roughage-based diets. Two experiments were conducted to assess the potential of biochar in mitigating CH4 emissions.Experiment 1This was a controlled pen trial conducted over 56 days, involving 12 steers that were fed Rhodes grass hay ad libitum. The animals were assigned to one of four treatment groups: control (no biochar, only molasses), low dose (50 g biochar/animal/day), mid dose (100 g biochar/animal/day), or high dose (200 g biochar/animal/day). Two types of biochar, Biochar 1 and Biochar 2, were administered with molasses (200 mL per animal/day). Methane emissions were measured using open-circuit respiration chambers, and rumen fluid samples were collected for analysis of the rumen microbial community and fermentation metabolite.Experiment 2In this trial, 45 heifers were selected and grazed together in a single paddock for 60 days to assess the effects of biochar on productivity and CH4 emissions under grazing conditions. The animals were allocated to one of three treatment groups (15 animals per group): control (no biochar, only molasses), Biochar 1, or Biochar 2. Each group was administered biochar at an estimated single dose of 100 g per animal/day mixed with molasses. Methane emissions were measured using GreenFeed systems in the field to monitor CH₄ production from individual animals.ResultsIn the controlled pen trial (Experiment 1), biochar supplementation resulted in a reduction of CH₄ emissions by 8.8-12.9% without any negative effects on rumen fermentation or dry matter intake (DMI). Minor changes were observed in the rumen bacterial community, particularly in the Christensenellaceae and Prevotellaceae families. However, in the grazing trial (Experiment 2), no significant differences in CH₄ emissions or productivity were detected with biochar supplementation.ConclusionWhile the results from controlled feeding conditions suggest that biochar has the potential to reduce enteric CH₄ emissions, the lack of significant findings under grazing conditions highlights the need for further research. Future studies should focus on identifying biochar types, doses, and delivery methods that are effective in reducing CH₄ emissions in grazing systems without compromising cattle productivity.
| S-EPMC11611548 | biostudies-literature
Project description:Measuring dairy cattle methane (CH4) emissions using traditional recording technologies is complicated and expensive. Prediction models, which estimate CH4 emissions based on proxy information, provide an accessible alternative. This review covers the different modeling approaches taken in the prediction of dairy cattle CH4 emissions and highlights their individual strengths and limitations. Following the guidelines set out by the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA); Scopus, EBSCO, Web of Science, PubMed and PubAg were each queried for papers with titles that contained search terms related to a population of "Bovine," exposure of "Statistical Analysis or Machine Learning," and outcome of "Methane Emissions". The search was executed in December 2022 with no publication date range set. Eligible papers were those that investigated the prediction of CH4 emissions in dairy cattle via statistical or machine learning (ML) methods and were available in English. 299 papers were returned from the initial search, 55 of which, were eligible for inclusion in the discussion. Data from the 55 papers was synthesized by the CH4 emission prediction approach explored, including mechanistic modeling, empirical modeling, and machine learning. Mechanistic models were found to be highly accurate, yet they require difficult-to-obtain input data, which, if imprecise, can produce misleading results. Empirical models remain more versatile by comparison, yet suffer greatly when applied outside of their original developmental range. The prediction of CH4 emissions on commercial dairy farms can utilize any approach, however, the traits they use must be procurable in a commercial farm setting. Milk fatty acids (MFA) appear to be the most popular commercially accessible trait under investigation, however, MFA-based models have produced ambivalent results and should be consolidated before robust accuracies can be achieved. ML models provide a novel methodology for the prediction of dairy cattle CH4 emissions through a diverse range of advanced algorithms, and can facilitate the combination of heterogenous data types via hybridization or stacking techniques. In addition to this, they also offer the ability to improve dataset complexity through imputation strategies. These opportunities allow ML models to address the limitations faced by traditional prediction approaches, as well as enhance prediction on commercial farms.
| S-EPMC11367560 | biostudies-literature
Project description:This study was developed with the goal of exploring the impact of capsaicin on ruminal fermentation and ruminal bacteria in beef cattle affected by high-grain diet-induced subacute ruminal acidosis (SARA). In total, 18 healthy Simmental crossbred cattle were randomized into three separate groups (n = 6/group): (1) control diet (CON; forage-to-concentrate ratio = 80:20); (2) high-grain diet (SARA; forage-to-concentrate ratio = 20:80); and (3) high-grain diet supplemented with capsaicin (CAP; 250 mg/cattle/day). The study was conducted over a 60-day period. The results showed that the SARA model was successfully induced in the SARA group with a high-grain diet. Relative to the SARA group, the addition of capsaicin elevated the ruminal pH from 5.40 to 6.36 (p < 0.01), and decreased the total volatile fatty acids (VFAs) from 133.95 to 82.86 mmol/L (p < 0.01), aligning closely with the levels observed in the CON group. The addition of capsaicin increased the alpha diversity of ruminal bacteria relative to the SARA group, as evidenced by a lower Simpson index (p < 0.05), together with increases in the Ace, Chao, and Shannon indices (p < 0.05). Bacteroidota and Firmicutes were the most common phyla across all treatment groups, while Prevotella was the predominant genera. The unique bacterial genera (LDA scores > 4) identified within the SARA group comprised Succinivibrionaceae_UCG-001, Succinivibrio, NK4A214_group, Lachnospiraceae_NK3A20_group, and Ruminococcus, which may serve as potential biomarkers for the diagnosis of SARA. The unique genera associated with the CON group included Rikenellaceae_RC9_gut_group, Prevotellaceae_UCG-003, and U29-B03, while those for the CAP group included Succiniclasticum and Prevotellaceae_UCG-004. In summary, these results suggest that dietary capsaicin supplementation can limit the adverse effects of SARA through the modulation of bacterial communities within the rumen, thus altering ruminal fermentation in beef cattle.
| S-EPMC11767826 | biostudies-literature
Project description:Four multiparous dairy cows were used in a 4 × 4 Latin square to examine how starch level and oil mixture impact dry matter (DM) intake and digestibility, milk yield and composition, rumen fermentation, ruminal methane (CH4) emissions, and microbial diversity. Experimental treatments comprised high (HS) or low (LS) levels of starch containing 0 or 30 g of a mixture of sunflower and fish oils (2:1 w/w) per kg diet DM (LSO and HSO, respectively). Intake of DM did not differ between cows fed LS and HS diets while oil supplementation reduced DM intake. Dietary treatments did not affect milk and energy corrected milk yields. There was a tendency to have a lower milk fat concentration due to HSO compared with other treatments. Both high starch level and oil supplementation increased digestibility of gross energy. Cows receiving HS diets had higher levels of total rumen VFA while acetate was lower than LS without any differences in rumen pH, or ruminal CH4 emissions. Although dietary oil supplementation had no impact on rumen fermentation, decreased CH4 emissions (g/day and g/kg milk) were observed with a concomitant increase in Anoplodinium-Diplodinium sp. and Epidinium sp. but a decrease in Christensenellaceae, Ruminococcus sp., Methanobrevibacter ruminantium and Mbb. gottschalkii clades.
| S-EPMC8147431 | biostudies-literature
Project description:BackgroundHouse fly larvae (Musca domestica L.) require a live microbial community to successfully develop. Cattle manure is rich in organic matter and microorganisms, comprising a suitable substrate for larvae who feed on both the decomposing manure and the prokaryotic and eukaryotic microbes therein. Microbial communities change as manure ages, and when fly larvae are present changes attributable to larval grazing also occur. Here, we used high throughput sequencing of 16S and 18S rRNA genes to characterize microbial communities in dairy cattle manure and evaluated the changes in those communities over time by comparing the communities in fresh manure to aged manure with or without house fly larvae.ResultsBacteria, archaea and protist community compositions significantly differed across manure types (e.g. fresh, aged, larval-grazed). Irrespective of manure type, microbial communities were dominated by the following phyla: Euryarchaeota (Archaea); Proteobacteria, Firmicutes and Bacteroidetes (Bacteria); Ciliophora, Metamonanda, Ochrophyta, Apicomplexa, Discoba, Lobosa and Cercozoa (Protists). Larval grazing significantly reduced the abundances of Bacteroidetes, Ciliophora, Cercozoa and increased the abundances of Apicomplexa and Discoba. Manure aging alone significantly altered the abundance bacteria (Acinetobacter, Clostridium, Petrimonas, Succinovibro), protists (Buxtonella, Enteromonas) and archaea (Methanosphaera and Methanomassiliicoccus). Larval grazing also altered the abundance of several bacterial genera (Pseudomonas, Bacteroides, Flavobacterium, Taibaiella, Sphingopyxis, Sphingobacterium), protists (Oxytricha, Cercomonas, Colpodella, Parabodo) and archaea (Methanobrevibacter and Methanocorpusculum). Overall, larval grazing significantly reduced bacterial and archaeal diversities but increased protist diversity. Moreover, total carbon (TC) and nitrogen (TN) decreased in larval grazed manure, and both TC and TN were highly correlated with several of bacterial, archaeal and protist communities.ConclusionsHouse fly larval grazing altered the abundance and diversity of bacterial, archaeal and protist communities differently than manure aging alone. Fly larvae likely alter community composition by directly feeding on and eliminating microbes and by competing with predatory microbes for available nutrients and microbial prey. Our results lend insight into the role house fly larvae play in shaping manure microbial communities and help identify microbes that house fly larvae utilize as food sources in manure. Information extrapolated from this study can be used to develop manure management strategies to interfere with house fly development and reduce house fly populations.
| S-EPMC8672618 | biostudies-literature
Project description:Our previous research revealed the advantages of separate feeding (SF) systems compared to total mixed ration (TMR) in terms of ruminal methane (CH4) production. The purpose of this experiment was to confirm the advantage of SF as a nutritional strategy for CH4 mitigation, and to determine the effects of different feeding systems (TMR and SF) on the rumen microbiome and associated metagenome of two different breeds and on CH4 emissions. We randomly allocated four Holstein (305 ± 29 kg) and four Hanwoo steers (292 ± 24 kg) to two groups; the steers were fed a commercial concentrate with tall fescue (75:25) as TMR or SF, in a crossover design (two successive 22-day periods). Neither feeding systems nor cattle breeds had an effect on the total tract digestibility of nutrients. The TMR feeding system and Hanwoo steers generated significantly more CH4 (P < 0.05) and had a higher yield [g/d and g/kg dry matter intake (DMI)] compared to the SF system and Holstein steers. A larger rumen acetate:propionate ratio was observed for the TMR than the SF diet (P < 0.05), and for Hanwoo than Holstein steers (P < 0.001), clearly reflecting a shift in the ruminal H2 sink toward CH4 production. The linear discriminant analysis (LDA) effect size (LEfSe) revealed a greater abundance (α < 0.05 and LDA > 2.0) of operational taxonomic units (OTUs) related to methanogenesis for Hanwoo steers compared to Holstein steers. Kendall's correlation analysis revealed wide variation of microbial co-occurrence patterns between feeding systems, indicating differential H2 thermodynamics in the rumen. A metagenome analysis of rumen microbes revealed the presence of 430 differentially expressed genes, among which 17 and 27 genes exhibited positive and negative associations with CH4 production, respectively (P < 0.001). A strong interaction between feeding system and breed was observed for microbial and metagenomic abundance. Overall, these results suggest that the TMR feeding system produces more CH4, and that Hanwoo cattle are higher CH4 emitters than SF diet and Holstein cattle, respectively. Interestingly, host-associated microbial interactions differed within each breed depending on the feeding system, which indicated that breed-specific feeding systems should be taken into account for farm management.
| S-EPMC8329423 | biostudies-literature
Project description:BackgroundAs the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics.ResultsComparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%.ConclusionsThe results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows. Video Abstract.
| S-EPMC8849036 | biostudies-literature
Project description:Mitigating the effects of global warming has become the main challenge for humanity in recent decades. Livestock farming contributes to greenhouse gas emissions, with an important output of methane from enteric fermentation processes, mostly in ruminants. Because ruminal microbiota is directly involved in digestive fermentation processes and methane biosynthesis, understanding the ecological relationships between rumen microorganisms and their active metabolic pathways is essential for reducing emissions. This study analysed whole rumen metagenome using long reads and considering its compositional nature in order to disentangle the role of rumen microbes in methane emissions. The β-diversity analyses suggested a subtle association between methane production and overall microbiota composition (0.01 < R2 < 0.02). Differential abundance analysis identified 36 genera and 279 KEGGs as significantly associated with methane production (Padj < 0.05). Those genera associated with high methane production were Eukaryota from Alveolata and Fungi clades, while Bacteria were associated with low methane emissions. The genus-level association network showed 2 clusters grouping Eukaryota and Bacteria, respectively. Regarding microbial gene functions, 41 KEGGs were found to be differentially abundant between low- and high-emission animals and were mainly involved in metabolic pathways. No KEGGs included in the methane metabolism pathway (ko00680) were detected as associated with high methane emissions. The KEGG network showed 3 clusters grouping KEGGs associated with high emissions, low emissions, and not differentially abundant in either. A deeper analysis of the differentially abundant KEGGs revealed that genes related with anaerobic respiration through nitrate degradation were more abundant in low-emission animals. Methane emissions are largely associated with the relative abundance of ciliates and fungi. The role of nitrate electron acceptors can be particularly important because this respiration mechanism directly competes with methanogenesis. Whole metagenome sequencing is necessary to jointly consider the relative abundance of Bacteria, Archaea, and Eukaryota in the statistical analyses. Nutritional and genetic strategies to reduce CH4 emissions should focus on reducing the relative abundance of Alveolata and Fungi in the rumen. This experiment has generated the largest ONT ruminal metagenomic dataset currently available.
| S-EPMC8848325 | biostudies-literature