Multi-Omics Study of The Salivary Modulation of The Rumen Microbiome

Ruminants are able to produce large quantities of saliva which enter into the rumen. Although previous research has indicated that salivary immunoglobulins can partially modulate the rumen microbial activity, the role of the salivary components other than ions on the rumen microbial ecosystem has not been thoroughly investigated in ruminants. A total of 16 semi-continuous in vitro cultures were used to incubate rumen fluid from 4 donor goats inoculated with autoclaved saliva (AUT) as negative control, saliva from the same rumen fluid donor (OWN) as positive control, and either GOAT or SHEEP saliva as experimental interventions. Fermentation was monitored throughout the 7 days of incubation and the prokaryotic communities and metabolome were analysed at day 7 of incubation. Characterization of the salivas used prior to incubation showed a high degree of individual variability in terms of the salivary metabolites and proteins, including immunoglobulins. The prokaryotic community composition in AUT incubators was the most divergent across treatments, suggesting a modulatory effect of active salivary components, which were not affected in the other treatments (OWN, GOAT and SHEEP). The differences across treatments in microbial diversity were mostly caused by a greater abundance of Proteobacteria and Rikenellacea and lower of Prevotellaceae, a key rumen bacterium with greater abundance in GOAT and SHEEP treatments. These results suggest that specific salivary components contribute to host-associated role in selecting the rumen commensal microbiota and its activity.

The rumen liquid metatranscriptome of post-weaned dairy calves differed by pre-weaning ruminal administration of differentially-enriched, rumen-derived inocula

Background Targeted modification of the dairy calf ruminal microbiome has been attempted through rumen fluid inoculation to alter productive phenotypes later in life. However, sustainable effects of the early life interventions have not been well studied, particularly on the metabolically active rumen microbiota and its functions. This study investigated the sustained effects of adult-derived rumen fluid inoculations in pre-weaning dairy calves on the active ruminal microbiome of post-weaned dairy calves analyzed via RNA-sequencing. Results Two different adult-derived microbial inocula (bacterial- or protozoal-enriched rumen fluid; BE or PE, respectively) were administered in pre-weaned calves (3–6 weeks) followed by analyzing active rumen microbiome of post-weaned calves (9 weeks). The shared bacterial community at the genus level of 16S amplicon-seq and RNA-seq datasets was significantly different (P = 0.024), 21 out of 31 shared major bacterial genera differed in their relative abundance between the two analytic pipelines. No significant differences were found in any of the prokaryotic alpha- and beta-diversity measurements (P > 0.05), except the archaeota that differed for BE based on the Bray–Curtis dissimilarity matrix (P = 0.009). Even though the relative abundances of potentially transferred microbial and functional features from the inocula were minor, differentially abundant prokaryotic genera significantly correlated to various fermentation and animal measurements including butyrate proportion, body weight, and papillae length and counts. The overall microbial functions were affected quantitatively by BE and qualitatively by PE (P < 0.05), and this might be supported by the individual KEGG module and CAZymes profile differences. Exclusive networks between major active microbial (bacterial and archaeal genera) and functional features (KEGG modules) were determined which were differed by microbial inoculations. Conclusions This study demonstrated that actively transcribed microbial and functional features showed reliable connections with different fermentations and animal development responses through adult rumen fluid inoculations compared to our previous 16S amplicon sequencing results. Exclusive microbial and functional networks of the active rumen microbiome of dairy calves created by BE and PE might also be responsible for the different ruminal and animal characteristics. Further understanding of the other parts of the gastrointestinal tract (e.g., abomasum, omasum, and small intestine) using metatranscriptomics will be necessary to elucidate undetermined biological factors affected by microbial inoculations.

Strategies for Reducing Ruminant Methane Emissions

The paper studies the effect of additional administration of ultrafine particles on the cattle rumen microbiome composition. The in vitro method was used using the ANKOM Daisy II incubator according to a specialized method. Microflora analysis was performed using MiSeq (Illumina, USA) by a new generation sequencing method with a MiSeq reagent kit. After a detailed analysis of the structure and composition of the microbial community in the contents of the rumen sampled for different diets, it was found that no significant differences were observed in the bacterial communities, with the exception of a slight shift in the Bacteroidetes/Firmicutes ratio. However, we observed numerical differences in the abundance of some representatives, namely, with additional inclusion of Fe and Cr2O3, decrease in the abundance of the methane-forming species Methanobrevibacter, Methanobacterium, Methanosphaera, and Methnaomicrobium was noted regarding the control.

Ruminal Microbiome Manipulation to Improve Fermentation Efficiency in Ruminants

The rumen is an integrated dynamic microbial ecosystem composed of enormous populations of bacteria, protozoa, fungi, archaea, and bacteriophages. These microbes ferment feed organic matter consumed by ruminants to produce beneficial products such as microbial biomass and short-chain fatty acids, which form the major metabolic fuels for ruminants. The fermentation process also involves inefficient end product formation for both host animals and the environment, such as ammonia, methane, and carbon dioxide production. In typical conditions of ruminal fermentation, microbiota does not produce an optimal mixture of enzymes to maximize plant cell wall degradation or synthesize maximum microbial protein. Well-functioning rumen can be achieved through microbial manipulation by alteration of rumen microbiome composition to enhance specific beneficial fermentation pathways while minimizing or altering inefficient fermentation pathways. Therefore, manipulating ruminal fermentation is useful to improve feed conversion efficiency, animal productivity, and product quality. Understanding rumen microbial diversity and dynamics is crucial to maximize animal production efficiency and mitigate the emission of greenhouse gases from ruminants. This chapter discusses genetic and nongenetic rumen manipulation methods to achieve better rumen microbial fermentation including improvement of fibrolytic activity, inhibition of methanogenesis, prevention of acidosis, and balancing rumen ammonia concentration for optimal microbial protein synthesis.

Characterizing the Alteration in Rumen Microbiome and Carbohydrate-Active Enzymes Profile with Forage of Muskoxen Rumen through Comparative Metatranscriptomics

Muskox (Ovibos moschatus), as the biggest herbivore in the High Arctic, has been enduring the austere arctic nutritional conditions and has evolved to ingest and digest scarce and high lignified forages to support the growth and reproduce, implying probably harbor a distinct microbial reservoir for the deconstruction of plant biomass. Therefore, metagenomics approach was applied to characterize the rumen microbial community and understand the alteration in rumen microbiome of muskoxen fed either triticale straw or brome hay. The difference in the structure of microbial communities including bacteria, archaea, fungi, and protozoa between the two forages was observed at the taxonomic level of genus. Further, although the highly abundant phylotypes in muskoxen rumen fed either triticale straw or brome hay were almost the same, the selective enrichment different phylotypes for fiber degrading, soluble substrates fermenting, electron and hydrogen scavenging through methanogenesis, acetogenesis, propionogenesis, and sulfur-reducing was also noticed. Specifically, triticale straw with higher content of fiber, cellulose selectively enriched more lignocellulolytic taxa and electron transferring taxa, while brome hay with higher nitrogen content selectively enriched more families and genera for degradable substrates-digesting. Intriguingly, the carbohydrate-active enzyme profile suggested an over representation and diversity of putative glycoside hydrolases (GHs) in the animals fed on triticale straw. The majority of the cellulases belonged to fiver GH families (i.e., GH5, GH6, GH9, GH45, and GH48) and were primarily synthesized by Ruminococcus, Piromyces, Neocallimastix, and Fibrobacter. Abundance of major genes coding for hemicellulose digestion was higher than cellulose mainly including GH8, GH10, GH16, GH26, and GH30, and these enzymes were produced by members of the genera Fibrobacter, Ruminococcus, and Clostridium. Oligosaccharides were mainly of the GH1, GH2, GH3, and GH31 types and were associated with the genera Prevotella and Piromyces. Our results strengthen metatranscriptomic evidence in support of the understanding of the microbial community and plant polysaccharide response to changes in the feed type and host animal. The study also establishes these specific microbial consortia procured from triticale straw group can be used further for efficient plant biomass hydrolysis.

Co‑cultivation of the anaerobic fungus Caecomyces churrovis with Methanobacterium bryantii enhances transcription of carbohydrate binding modules, dockerins, and pyruvate formate lyases on specific substrates

Anaerobic fungi and methanogenic archaea are two classes of microorganisms found in the rumen microbiome that metabolically interact during lignocellulose breakdown. Here, stable synthetic co-cultures of the anaerobic fungus Caecomyces churrovis and the methanogen Methanobacterium bryantii (not native to the rumen) were formed, demonstrating that microbes from different environments can be paired based on metabolic ties. Transcriptional and metabolic changes induced by methanogen co-culture were evaluated in C. churrovis across a variety of substrates to identify mechanisms that impact biomass breakdown and sugar uptake. A high-quality genome of C. churrovis was obtained and annotated, which is the first sequenced genome of a non-rhizoid-forming anaerobic fungus. C. churrovis possess an abundance of CAZymes and carbohydrate binding modules and, in agreement with previous studies of early-diverging fungal lineages, N6-methyldeoxyadenine (6mA) was associated with transcriptionally active genes. Co-culture with the methanogen increased overall transcription of CAZymes, carbohydrate binding modules, and dockerin domains in co-cultures grown on both lignocellulose and cellulose and caused upregulation of genes coding associated enzymatic machinery including carbohydrate binding modules in family 18 and dockerin domains across multiple growth substrates relative to C. churrovis monoculture. Two other fungal strains grown on a reed canary grass substrate in co-culture with the same methanogen also exhibited high log2-fold change values for upregulation of genes encoding carbohydrate binding modules in families 1 and 18. Transcriptional upregulation indicated that co-culture of the C. churrovis strain with a methanogen may enhance pyruvate formate lyase (PFL) function for growth on xylan and fructose and production of bottleneck enzymes in sugar utilization pathways, further supporting the hypothesis that co-culture with a methanogen may enhance certain fungal metabolic functions. Upregulation of CBM18 may play a role in fungal–methanogen physical associations and fungal cell wall development and remodeling.

Accelerated discovery of novel glycoside hydrolases using targeted functional profiling and selective pressure on the rumen microbiome

Background Carbohydrate-active enzymes (CAZymes) form the most widespread and structurally diverse set of enzymes involved in the breakdown, biosynthesis, or modification of lignocellulose that can be found in living organisms. However, the structural diversity of CAZymes has rendered the targeted discovery of novel enzymes extremely challenging, as these proteins catalyze many different chemical reactions and are sourced by a vast array of microbes. Consequently, many uncharacterized members of CAZyme families of interest have been overlooked by current methodologies (e.g., metagenomic screening) used to discover lignocellulolytic enzymes. Results In the present study, we combined phenotype-based selective pressure on the rumen microbiota with targeted functional profiling to guide the discovery of unknown CAZymes. In this study, we found 61 families of glycoside hydrolases (GH) (out of 182 CAZymes) from protein sequences deposited in the CAZy database—currently associated with more than 20,324 microbial genomes. Phenotype-based selective pressure on the rumen microbiome showed that lignocellulolytic bacteria (e.g., Fibrobacter succinogenes, Butyrivibrio proteoclasticus) and three GH families (e.g., GH11, GH13, GH45) exhibited an increased relative abundance in the rumen of feed efficient cattle when compared to their inefficient counterparts. These results paved the way for the application of targeted functional profiling to screen members of the GH11 and GH45 families against a de novo protein reference database comprised of 1184 uncharacterized enzymes, which led to the identification of 18 putative xylanases (GH11) and three putative endoglucanases (GH45). The biochemical proof of the xylanolytic activity of the newly discovered enzyme validated the computational simulations and demonstrated the stability of the most abundant xylanase. Conclusions These findings contribute to the discovery of novel enzymes for the breakdown, biosynthesis, or modification of lignocellulose and demonstrate that the rumen microbiome is a source of promising enzyme candidates for the biotechnology industry. The combined approaches conceptualized in this study can be adapted to any microbial environment, provided that the targeted microbiome is easy to manipulate and facilitates enrichment for the microbes of interest.

Analyzing Large Microbiome Datasets Using Machine Learning and Big Data

Metagenomics promises to provide new valuable insights into the role of microbiomes in eukaryotic hosts such as humans. Due to the decreasing costs for sequencing, public and private repositories for human metagenomic datasets are growing fast. Metagenomic datasets can contain terabytes of raw data, which is a challenge for data processing but also an opportunity for advanced machine learning methods like deep learning that require large datasets. However, in contrast to classical machine learning algorithms, the use of deep learning in metagenomics is still an exception. Regardless of the algorithms used, they are usually not applied to raw data but require several preprocessing steps. Performing this preprocessing and the actual analysis in an automated, reproducible, and scalable way is another challenge. This and other challenges can be addressed by adjusting known big data methods and architectures to the needs of microbiome analysis and DNA sequence processing. A conceptual architecture for the use of machine learning and big data on metagenomic data sets was recently presented and initially validated to analyze the rumen microbiome. The same architecture can be used for clinical purposes as is discussed in this paper.

The rumen microbiome inhibits methane formation through dietary choline supplementation

Enteric fermentation from ruminants is a primary source of anthropogenic methane emission. This study aims to add another approach for methane mitigation by manipulation of the rumen microbiome. Effects of choline supplementation on methane formation were quantified in vitro using the Rumen Simulation Technique. Supplementing 200 mM of choline chloride or choline bicarbonate reduced methane emissions by 97–100% after 15 days. Associated with the reduction of methane formation, metabolomics analysis revealed high post-treatment concentrations of ethanol, which likely served as a major hydrogen sink. Metagenome sequencing showed that the methanogen community was almost entirely lost, and choline-utilizing bacteria that can produce either lactate, ethanol or formate as hydrogen sinks were enriched. The taxa most strongly associated with methane mitigation were Megasphaera elsdenii and Denitrobacterium detoxificans, both capable of consuming lactate, which is an intermediate product and hydrogen sink. Accordingly, choline metabolism promoted the capability of bacteria to utilize alternative hydrogen sinks leading to a decline of hydrogen as a substrate for methane formation. However, fermentation of fibre and total organic matter could not be fully maintained with choline supplementation, while amino acid deamination and ethanolamine catabolism produced excessive ammonia, which would reduce feed efficiency and adversely affect live animal performance.