Effects of grain feeding on microbiota in the digestive tract of cattle

Khafipour, Ehsan; Li, S.; Tun, Hein Min; Derakhshani, Hooman; Moossavi, Shirin; Plaizier, J.C.

doi:10.2527/af.2016-0018

Cited by 112 publications

(123 citation statements)

References 42 publications

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“…These metabolites were also reported to be affecting the digestive efficiency in chickens 37 . Previous studies have shown an increase in the concentration of xanthine by increased FI 38,39 . The degradation of rumen fluid into xanthine, hypoxanthine, and uracil by the action of bacterial nucleic acids (DNA, RNA) was reported previously 40 .…”

Section: Discussionmentioning

confidence: 85%

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Carmelo

Banerjee

Diniz

et al. 2020

Sci Rep

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Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for fe could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying fe and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish fe prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased fe.With the expanding human population and requirement for nutrient-rich food, there is an increasing demand for improvement of meat production, but simultaneously, to decrease the input costs in terms of feed 1 . Thus, feed efficiency (FE) is the most important trait in commercial pig farming 2 as increasing the amount of meat produced per feed is beneficial both economically and environmentally. Thereby, improving FE is beneficial for producers and increases the sustainability of pork meat production. Fortunately, FE is a highly heritable trait in Danish pigs (ranging from 0.34 in Duroc to 0.40 in Landrace), thus suitable for the genetic selection of pigs with high breeding values in breeding programs aimed at improving this economically important phenotype 3 .Since FE cannot be measured directly, feed conversion ratio (FCR) and residual feed intake (RFI) have been used to evaluate the animal efficiency 4 . FCR determines the ratio of feed intake (FI) to output and found to correlate with growth rate and body weight 3,5 . RFI calculates the difference between the actual and expected FI 6 predicted based on production traits such as average daily gain (ADG) 7 . ADG is also considered important in commercial pig production as pigs with higher ADG can achieve a target market weight within a shorter period than those with lower ADG, thereby saving feeding costs 8 . Thus, selection for RFI has proved to be effective in improving the FE in pigs 3,9,10 . Selection for FCR will results in co-selection for other traits, such as body composition and ADG. In contrast, RFI selects for increased metabolic efficiency without the same side effects [11][12][13] . RFI and FCR are well c...

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Section: Discussionmentioning

confidence: 85%

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Carmelo

Banerjee

Diniz

et al. 2020

Sci Rep

View full text Add to dashboard Cite

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“…However, one cow among three cows at farm 2 had Succinivibrionaceae at <1.0%, which was similar to the mean proportion of Succinivibrionaceae in the rumen fluid at farm 1. Thus, although Succinivibrionaceae has been known to correlate with grain feeding (Khafipour et al., ), the taxa may show a large cow‐to‐cow variation in rumen fluid.…”

Section: Discussionmentioning

confidence: 99%

“…although Succinivibrionaceae has been known to correlate with grain feeding (Khafipour et al, 2016), the taxa may show a large cow-tocow variation in rumen fluid.…”

Section: Discussionmentioning

confidence: 99%

Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems

Nguyen

Tran

et al. 2019

Animal Science Journal

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Microbiota of the gut, milk, and cowshed environment were examined at two dairy farms managed by automatic milking systems (AMS). Feed, rumen fluid, feces, milk, bedding, water, and airborne dust were collected and the microbiota on each was assessed by Illumina MiSeq sequencing. The most abundant taxa in feed, rumen fluid, feces, bedding, and water were Lactobacillaceae, Prevotellaceae, Ruminococcaceae, Ruminococcaceae, and Lactobacillaceae, respectively, at both farms. Aerococcaceae was the most abundant taxon in milk and airborne dust microbiota at farm 1, and Staphylococcaceae and Lactobacillaceae were the most abundant taxa in milk and airborne dust microbiota at farm 2. The three most prevalent taxa (Aerococcaceae, Staphylococcaceae, and Ruminococcaceae at farm 1 and Staphylococcaceae, Lactobacillaceae, and Ruminococcaceae at farm 2) were shared between milk and airborne dust microbiota. Indeed, SourceTracker indicated that milk microbiota was related with airborne dust microbiota. Meanwhile, hierarchical clustering and canonical analysis of principal coordinates demonstrated that the milk microbiota was associated with the bedding microbiota but clearly separated from feed, rumen fluid, feces, and water microbiota. Although our findings were derived from only two case studies, the importance of cowshed management for milk quality control and mastitis prevention was emphasized at farms managed by AMS.

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“…Health of the rumen is partly associated with proper richness, diversity and stability of the ruminal microbiome (Khafipour et al, 2016). In this study, although the average Chao1 estimate of richness tended to increase postpartum, other alpha-diversity parameters of ruminal microbiota did not change during the transition period.…”

Section: Discussionmentioning

confidence: 99%

Linking Peripartal Dynamics of Ruminal Microbiota to Dietary Changes and Production Parameters

et al. 2017

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During the peripartal period, proper acclimatization of rumen microorganisms to variations in nutritional management can facilitate the transition into lactation. This study characterized the temporal shifts in the composition and functional properties of ruminal microbiota during the periparturient period in dairy cows subjected to a typical two-tiered feeding management approach. Ruminal digesta samples from eight multiparous fistulated Holstein cows were collected on days −14, −7, 10, 20, and 28 relative to parturition. High-throughput Illumina sequencing of the V4 region of the bacterial 16S rRNA gene revealed distinct clustering patterns between pre- and postpartal ruminal microbiota. During the prepartal period, when the voluntary dry matter intake was lower, we observed strikingly lower inter-animal variations in the composition of the ruminal microbiota. Genera Ruminococcus and Butyrivibrio, which are considered major fibrolytic rumen dwellers, were overrepresented in the prepartal rumen ecosystem. In contrast, increased postpartal voluntary DMI was associated with enrichment of bacterial genera mainly consisting of proteolytic, amylolytic, and lactate-producer species (including Prevotella, Streptococcus, and Lactobacillus). These, together with the postpartal enrichment of energy metabolism pathways, suggested a degree of acclimatization of the ruminal microbiota to harvest energy from the carbohydrate-dense lactation diet. In addition, correlations between ruminal microbiota and parameters such as milk yield and milk composition underscored the metabolic contribution of this microbial community to the cow's performance and production.

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Effects of grain feeding on microbiota in the digestive tract of cattle

Cited by 112 publications

References 42 publications

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Rumen fluid, feces, milk, water, feed, airborne dust, and bedding microbiota in dairy farms managed by automatic milking systems

Linking Peripartal Dynamics of Ruminal Microbiota to Dietary Changes and Production Parameters

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