Heritable Bovine Rumen Bacteria Are Phylogenetically Related and Correlated with the Cow’s Capacity To Harvest Energy from Its Feed

Sasson, Goor; Ben-Shabat, Sheerli Kruger; Seroussi, Eyal; Doron‐Faigenboim, Adi; Shterzer, Naama; Yaacoby, Shamay; Miller, Margret E. Berg; White, Bryan A.; Halperin, Eran; Mizrahi, Itzhak

doi:10.1128/mbio.00703-17

Cited by 134 publications

(134 citation statements)

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“…In an agricultural setting, rumen microbial community (RMC) profiles have been associated with environmentally and economically important traits, such as methane emissions [3,4] and feed efficiency [5,6]. The bacteria, protozoa and fungi of the RMC breaks down ingested feed to produce volatile or short chain fatty acids, which are a source of energy for the host.…”

Section: Introductionmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

et al. 2020

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Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (referencebased and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

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Section: Introductionmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

et al. 2020

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“…In an agricultural setting, rumen microbial community (RMC) profiles have been associated with environmentally and economically important traits, such as methane emissions (3, 4) and feed efficiency (5, 6). The RMC breaks down ingested feed to produce volatile or short chain fatty acids, which are a source of energy for the host.…”

Section: Introductionmentioning

confidence: 99%

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Hess

Rowe

Stijn

et al. 2019

Preprint

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AbstractMicrobial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62±0.06, heritability 0.31±0.29, and genetic and phenotypic correlation with methane emissions of 0.88±0.25 and 0.64±0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0±5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8±1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

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“…Ruminants have a complex and dynamic ecosystem composed of the rumen microbiota, which interacts with each other and has a symbiotic relationship with the host, contributes to the fermentation of the ingested plant materials, and provides energy for host from the breakdown of plant cell walls [1]. The effects of diet, age, environment, and host on the rumen microbial population have received much attention due to the accessibility offered by high-throughput sequencing [2][3][4]. With increasing age, the rumen microbes gradually play a more important role in the nutrient metabolism of ruminants.…”

Section: Introductionmentioning

confidence: 99%

Maturation of the Goat Rumen Microbiota Involves Three Stages of Microbial Colonization

Zhang

Guo

et al. 2019

Animals

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With increasing age, the rumen microbiota of new-born ruminants become central in the translation of fibrous feed substances into essential nutrients. However, the colonization process of the microbial community (especially fungal community) remains poorly understood in ruminants at pre-weaning stages. In this study, the rumen bacterial and fungal colonization processes were investigated in goats at eight stages using amplicon sequencing. For bacteria, we found 36 common core genera at D0, D3, D14, D28, and D56, including mainly Bacillus, Alloprevotella, Bacteroides, Prevotella_1, Lactococcus, and Ruminococcaceae_NK4A214. Firmicutes was the dominant phylum among the total microbiota in newborn goat kids (prior to nursing), while Bacillus, Lactococcus, and Pseudomonas were predominant genera. Interestingly, the proportion of Bacillus was as high as 55% in newborn animals. After milk nursing, the predominant phylum changed to Bacteroidetes, while the proportion of Bacillus and Lactobacillus was very low. CowPi was used to predict the functional gene pathways and we found increases in the abundance of genes associated with amino acid related enzymes, DNA repair and recombination proteins, aminoacyl tRNA biosynthesis, and peptidases after D3. With regard to fungi, we found that there were 51 common genera at day 0 (D0), D3, D14, D28, and D56, including mainly Cryptococcus, Aspergillus, and Caecomyces. Aspergillus occupied approximately 47% at day 0, but then it decreased from day 3 to day 14. This study indicates that the core microbes of rumen emerged shortly after birth, but the abundance was very different from the core genus of the adult rumen. In addition, we also report a detailed scheme of the bacterial and fungal colonization process in rumens and propose three distinct stages during the rumen colonization process in pre-weaning goats, which will offer a reference for the development of milk substitutes for small ruminants.

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Heritable Bovine Rumen Bacteria Are Phylogenetically Related and Correlated with the Cow’s Capacity To Harvest Energy from Its Feed

Cited by 134 publications

References 45 publications

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

Maturation of the Goat Rumen Microbiota Involves Three Stages of Microbial Colonization

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