Changes in the rumen and colon microbiota and effects of live yeast dietary supplementation during the transition from the dry period to lactation of dairy cows

Bach, À.; López-García, Adrián; González-Recio, Óscar; Elcoso, G.; Fàbregas, F.; Chaucheyras‐Durand, Frédérique; Castex, Mathieu

doi:10.3168/jds.2018-16105

Cited by 79 publications

(78 citation statements)

References 63 publications

(70 reference statements)

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“…Succinivibrionaceae_UCG-002 and Ruminobacter are two genera in the family Succinivibrionaceae , and this family was thought to be sensitive to changes in individual, diet and environment [31,32]. In this study, positive correlations were observed between Succinivibrionaceae_UCG-002 and temperature and between Ruminobacter and temperature, which is in agreement with Bach et al (2019) who found a negative association between Ruminobacter and DMI [33], because DMI decreased with an increase in temperature at similar humidity [34]. However, it is strange that no associations were found between any genus and humidity, perhaps the humidity level in the current study was not enough to highlight the differences, but further studies are required to prove this hypothesis.…”

Section: Discussionsupporting

confidence: 90%

Temporal Dynamics in Rumen Bacterial Community Composition of Finishing Steers during an Adaptation Period of Three Months

Qiu

Gao

et al. 2019

Microorganisms

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The objective of this study was to explore whether collecting rumen samples of finishing steers at monthly intervals differed, and whether this difference or similarity varied with diets. For these purposes, 12 Chinese Holstein steers were equally divided into two groups. The dietary treatments were either standard energy and standard protein (C) or low energy and low protein (L). Rumen samples were obtained on day 30, day 60 and day 90 from both dietary treatments and were analyzed by using 16S rRNA gene sequencing. The results showed that monthly intervals had no effect on the richness and evenness of the rumen bacterial community in the two diets. However, taxonomic difference analysis (relative abundance >0.5%) revealed that the relative abundance of three phyla (Proteobacteria, Fibrobacteres and Cyanobacteria) and six genera (Rikenellaceae_RC9_gut_group, Ruminococcaceae_NK4A214_group, Fibrobacter, Eubacterium_coprostanoligenes_group, Ruminococcaceae_UCG-010 and Ruminobacter) were significantly different between monthly sampling intervals, and the difference was prominent between sampling in the first month and the subsequent two months. Moreover, the differences in abundances of phyla and genera between monthly sampling intervals were affected by diets. Analysis of similarity (ANOSIM) showed no significant differences between monthly sampling intervals in the C diet. However, ANOSIM results revealed that significant differences between the first month and second month and between the first month and third month were present in the L diet. These results indicated that temporal dynamics in rumen bacterial community composition did occur even after an adaptation period of three months. This study tracked the changes in rumen bacterial populations of finishing cattle after a shift in diet with the passage of time. This study may provide insight into bacterial adaptation time to dietary transition in finishing steers.

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Section: Discussionsupporting

confidence: 90%

Temporal Dynamics in Rumen Bacterial Community Composition of Finishing Steers during an Adaptation Period of Three Months

Qiu

Gao

et al. 2019

Microorganisms

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“…Other members of the Ruminococcaceae family were found to decline across fermentation samples for Experiment 1 and from the neat rumen fluid to the first sampling point of Experiment 2, but they did recover somewhat by the end of the experiment. Similar to Prevotella, the Ruminococcaceae have been shown to have high functional diversity (Bach et al, 2019), which may explain their reduced abundance within the model. A decline of species from the Prevotella and Ruminococcus genera have been observed previously in an in vitro rumen model (Weimer et al, 2011).…”

Section: A)mentioning

confidence: 98%

Cross Inoculation of Rumen Fluid to Improve Dry Matter Disappearance and Its Effect on Bacterial Composition Using an in vitro Batch Culture Model

et al. 2020

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Environmental pressures of ruminant production could be reduced by improving digestive efficiency. Previous in vivo attempts to manipulate the rumen microbial community have largely been unsuccessful probably due to the influencing effect of the host. Using an in vitro consecutive batch culture technique, the aim of this study was to determine whether manipulation was possible once the bacterial community was uncoupled from the host. Two cross inoculation experiments were performed. Rumen fluid was collected at time of slaughter from 11 Holstein-Friesian steers from the same herd for Experiment 1, and in Experiment 2 were collected from 11 Charolais cross steers sired by the same bull and raised on a forage only diet on the same farm from birth. The two fluids that differed most in their in vitro dry matter disappearance (IVDMD; "Good," "Bad") were selected for their respective experiment. The fluids were also mixed (1:1, "Mix") and used to inoculate the model. In Experiment 1, the mixed rumen fluid resulted in an IVDMD midway between that of the two rumen fluids from which it was made for the first 24 h batch culture (34, 29, 20 g per 100 g DM for the Good, Mix, and Bad, respectively, P < 0.001) which was reflected in fermentation parameters recorded. No effect of cross inoculation was seen for Experiment 2, where the Mix performed most similarly to the Bad. In both experiments, IVDMD increased with consecutive culturing as the microbial population adapted to the in vitro conditions and differences between the fluids were lost. The improved performance with each consecutive batch culture was associated with reduced bacterial diversity. Increases in the genus Pseudobutyrivibrio were identified, which may be, at least in part, responsible for the improved digestive efficiency observed, whilst Prevotella declined by 50% over the study period. It is likely that along with host factors, there are individual factors within each community that prevent other microbes from establishing. Whilst we were unable to manipulate the bacterial community, uncoupling the microbiota from the host resulted in changes in the community, becoming less diverse with time, likely due to environmental heterogeneity, and more efficient at digesting DM.

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“…Prevotella spp. -which belongs to Bacteroidetes-has been associated to feed efficiency (Jewell, McCormick, Odt, Weimer, & Suen, 2015; Bach et al, 2019), although most of these results were not consistent due to the low taxonomic resolution of 16S rRNA gene sequencing. Species among this genus are involved in central rumen processes such as pectin and xyloglucan degradation and acetate production (Seshadri et al, 2018), which have a high impact on the nutrition of ruminants.…”

Section: Discussionmentioning

confidence: 98%

“…Classical approaches for modulating the microbiome include management practices and food additives, genetic selection is the principal strategy to obtain animals with improved phenotypic traits (Tapio, Snelling, Strozzi, & Wallace, 2017). It has been suggested that the microbial composition in ruminants could be used as a predictor of complex traits (Gonzalez-Recio, Zubiria, García-Rodríguez, Hurtado, & Atxaerandio, 2018), as there are signs of host genetic control over the microbiome composition in cows, which could lead to animal breeding programs that select animals with a favorable microbiome for a high feed efficiency phenotype (Sasson et al, 2017). Thus, selecting animals with less methane production could lead to a decrease in the overall impact of livestock in our environment.…”

Section: Discussionmentioning

confidence: 99%

Long reads from Nanopore sequencing as a tool for animal microbiome studies

Delgado

Serrano

Gonzalez

et al. 2019

Preprint

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19In the era of bioinformatics and metagenomics, the study of the ruminal microbiome has gained considerable 20 relevance in the field of animal breeding, since the composition of the rumen microbiota significantly impacts 21 production and the environment. Illumina sequencing is considered the gold standard for the analysis of 22 microbiomes, but it is limited by obtaining only short DNA sequences to analyze. As an alternative, Oxford 23 Nanopore Technologies (ONT) has developed a new sequencing technique based on nanopores that can be 24 carried out in the MinION, a portable device with a low initial cost which long DNA readings can be obtained 25 with. The aim of this study was to compare the performance of both types of sequencing applied to samples of 26 ruminal content using a similar pipeline. The ONT sequencing provided similar results to the Illumina 27 sequencing, although it was able to classify a greater number of readings at the species level, possibly due to 28 the increase in the read size. The results also suggest that, due to the size of the reads, it would be possible to 29 obtain the same amount of information in a smaller number of hours. However, detection of archaeal and 30 eukaryotic species is still difficult to accomplish due to their low abundance in the rumen compared to 31 bacteria, suggesting different pipelines and strategies are needed to obtain a whole representation of the less 32 abundant species in the rumen microbiota.33 34 35 36 Background 37 38 The bovine rumen has been studied for years in an attempt to reveal functions and microorganisms associated 39 with nutritional features such as feed efficiency to use them in animal breeding programs for cattle (Knapp, 40 Laur, Vadas, Weiss, & Tricarico, 2014). Lately, methane emissions from ruminants are among the main 41 concerns in animal husbandry, given their contribution to global warming. Microbial cultures were essential 42 for the first descriptions of the rumen content but they are usually hard to achieve (Creevey, Kelly, 43 Henderson, & Leahy, 2014). Thanks to the Next Generation Sequencing (NGS) techniques it is now possible 44 to detect different microbial taxa in rumen samples avoiding culture (Seshadri et al., 2018). This has allowed 45 analyzing metagenomic samples in an easier way and to detect non-culturable microbes that broaden the 46 knowledge of complex microbial communities as well as allow quantifying the relative abundances of each 47 65 profiles in municipal sewage, obtaining similar results as Illumina, although it was still necessary to improve 66 the throughput of the sequencing runs. ONT has also been used to detected arbovirus in mosquitos (Batovska, 67 Lynch, Rodoni, Sawbridge, & Cogan, 2017) obtaining comparable results to Illumina sequencing, despite the 68 poorer quality of the reads was poorer. Other studies focus on the applicability of ONT for real-time viral 69 pathogen detection (Greninger et al., 2015) in human blood as it shows similar results to Illumina but provides 70 faster results, which ...

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Changes in the rumen and colon microbiota and effects of live yeast dietary supplementation during the transition from the dry period to lactation of dairy cows

Cited by 79 publications

References 63 publications

Temporal Dynamics in Rumen Bacterial Community Composition of Finishing Steers during an Adaptation Period of Three Months

Temporal Dynamics in Rumen Bacterial Community Composition of Finishing Steers during an Adaptation Period of Three Months

Cross Inoculation of Rumen Fluid to Improve Dry Matter Disappearance and Its Effect on Bacterial Composition Using an in vitro Batch Culture Model

Long reads from Nanopore sequencing as a tool for animal microbiome studies

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