Characterization of variations within the rumen metaproteome of Holstein dairy cattle relative to morning feed offering

Harnessing meta-omics to unveil and mitigate methane emissions in ruminants: Integrative approaches and future directions

Methane emissions from enteric fermentation present a dual challenge globally: they not only contribute significantly to atmospheric greenhouse gases but also represent a considerable energy loss for ruminant animals. Utilizing high-throughput omics technologies to analyze rumen microbiome samples (meta-omics, i.e., metagenomics, metatranscriptomics, metaproteomics, metabolomics) holds vast potential for uncovering the intricate interplay between diet, microbiota, and methane emissions in these animals. The primary obstacle is the effective integration of diverse meta-omic approaches and their broader application across different ruminant species. Genetic variability significantly impacts methane production in ruminants, suggesting that genomic selection could be a viable strategy to reduce emissions. While substantial research has been conducted on the microbiological aspects of methane production, there remains a critical need to delineate the specific genetic interactions between the host and its microbiome. Advancements in meta-omics technologies are poised to shed light on these interactions, enhancing our understanding of the genetic factors that govern methane output. This review explores the potential of meta-omics to accelerate genetic advancements that could lead to reduced methane emissions in ruminants. By employing a systems biology approach, the integration of various omics technologies allows for the identification of key genomic regions and genetic markers linked to methane production. These markers can then be leveraged in selective breeding programs to cultivate traits associated with lower emissions. Moreover, the review addresses current challenges in applying genomic selection for this purpose and discusses how omics technologies can overcome these obstacles. The systematic integration and analysis of diverse biological data provide deeper insights into the genetic underpinnings and overall biology of methane production traits in ruminants. Ultimately, this comprehensive approach not only aids in reducing the environmental impact of agriculture but also contributes to the sustainability and efficiency of livestock management.

Deciphering functional groups of rumen microbiome and their underlying potentially causal relationships in shaping host traits

Over the years, microbiome research has achieved tremendous advancements driven by culture-independent meta-omics approaches. Despite extensive research, our understanding of the functional roles and causal effects of the microbiome on phenotypes remains limited. In this study, we focused on the rumen metaproteome, combining it with metatranscriptome and metabolome data to accurately identify the active functional distributions of rumen microorganisms and specific functional groups that influence feed efficiency. By integrating host genetics data, we established the potentially causal relationships between microbes-proteins/metabolites-phenotype, and identified specific patterns in which functional groups of rumen microorganisms influence host feed efficiency. We found a causal link between Selenomonas bovis and rumen carbohydrate metabolism, potentially mediated by bacterial chemotaxis and a two-component regulatory system, impacting feed utilization efficiency of dairy cows. Our study on the nutrient utilization functional groups in the rumen of high-feed-efficiency dairy cows, along with the identification of key microbiota functional proteins and their potentially causal relationships, will help move from correlation to causation in rumen microbiome research. This will ultimately enable precise regulation of the rumen microbiota for optimized ruminant production.

TMT-based quantitative proteomics reveals the nutritional and stress resistance functions of anaerobic fungi in yak rumen during passage at different time intervals

OBJECTIVES

Anaerobic fungi are critical for nutrient digestion in the yak rumen. Although studies have reported the effects of passage at different time intervals on the community structure of yak rumen anaerobic fungi, it is unknown whether passage culture at different time intervals affects the microbial proteins of rumen anaerobic fungi and their functions.

METHODS

Mycelium was obtained using the anaerobic continuous batch culture (CBC) of yak rumen fluid at intervals of 3 d, 5 d and 7 d. Quantitative analysis of fungal proteins and functional analysis was performed using tandem mass tagging (TMT) and bioinformatics.

RESULTS

A total of 56 differential proteins (DPs) were found in 5 d vs. 3 d and 7 d vs. 3 d. Gene ontology (GO) enrichment indicated that the up-regulated proteins were mainly involved in biological regulation, cellular process, metabolic process, macromolecular complex, membrane, cell part, organelle, binding, catalytic activity and transporter activity. The downregulated proteins were mainly enriched in metabolic process, cell part, binding and catalytic activity. Furthermore, the downregulated proteins in 7 d vs. 3 d were related to membrane and organelle. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results indicated that DPs were enriched in 14 pathways in 5 d vs. 3 d and 7 d vs. 3 d, mainly including terpenoid backbone biosynthesis, alaine, aspartate and glutamate metabolism, arginine biosynthesis, hypotaurine, cyanoamino acid, glutathione, β-alanine, pyrimidine, purine, galactose and propanate metabolism, steroid biosynthesis, ribosome biogenesis in eukaryotes and aminoacyl tRNA biosynthesis. The DPs were enriched in only 2 pathways in 5 d vs 3 d, lysine biosynthesis and cysteine and methionine metabolism. N-glycan biosynthesis and retinol metabolism are only found in the metabolism of DPs in 7 d vs 3 d.

CONCLUSIONS

Yak rumen anaerobic fungal proteins are involved in nutrition and stress tolerance during passage at different time intervals.

Use of milk proteins as biomarkers of changes in the rumen metaproteome of Holstein cows fed low-fiber, high-starch diets

Dietary levels of undegraded neutral detergent fiber (uNDF240) and rumen-fermentable starch (RFS) can affect the rumen microbiome and milk composition. The objective of the study is to investigate the use of milk proteins as biomarkers of rumen microbial activity through a comparative evaluation of the rumen microbial and milk protein profiles produced by Holstein cows fed diets with varying contents of physically effective uNDF240 (peuNDF240) and RFS. Eight ruminally cannulated lactating Holstein cows were included in a larger study as part of a 4 × 4 Latin square design with 4 28-d periods to assess 4 diets varying in peuNDF240 and RFS content. For this experiment, cows received one of 2 dietary treatments: (1) low-peuNDF240, high-RFS (LNHR) diet or (2) high-peuNDF240, low-RFS (HNLR) diet. Within each period, rumen fluid samples were collected from each cow on d 26 (1400 h) and d 27 (0600 h and 1000 h), and milk samples were collected from each cow on d 25 (2030 h), d 26 (0430 h, 1230 h, and 2030 h), and d 27 (0430 h and 1230 h). Microbial proteins were isolated from each rumen fluid sample. For milk samples, milk proteins were fractionated, and the whey fraction was subsequently isolated. Isolated proteins within each rumen fluid or milk sample were isobarically labeled and analyzed by liquid chromatography-tandem mass spectrometry. Product ion spectra acquired from rumen fluid samples were searched using SEQUEST against 71 composite databases. In contrast, product ion spectra acquired from milk samples were searched against the Bos taurus database. Data were analyzed using the PROC MIXED procedure in SAS 9.4 to assess the effect of diet and time of sampling. To increase stringency, the false discovery rate-adjusted P-value (PFDR) was also calculated to account for multiple comparisons. Using the mixed procedure, a total of 129 rumen microbial proteins were quantified across 24 searched microbial species. Of these, the abundance of 14 proteins across 9 microbial species was affected due to diet and diet × time interaction, including 7 proteins associated with energetics pathways. Among the 159 quantified milk proteins, the abundance of 21 proteins was affected due to the diet and diet × time interaction. The abundance of 19 of these milk proteins was affected due to diet × time interactions. Of these, 16 proteins had the disparity across diets at the 0430 h sampling time, including proteins involved in host defense, nutrient synthesis, and transportation, suggesting that biological shifts resulting from diet-induced rumen changes are not diurnally uniform across milkings. The concentration of lipoprotein lipase (LPL) was statistically higher in the milk from the cows fed with the LNHR diet, which was numerically confirmed with an ELISA. Further, as determined by ELISA, the LPL concentration was significantly higher in the milk from the cows fed with the LNHR diet at 0430 h sampling point, suggesting that LPL concentration may indicate dietary carbohydrate-induced ruminal changes. The results of this study suggest that diet-induced rumen changes can be reflected in milk in a diurnal pattern, further highlighting the need to consider sampling time points for using milk proteins as a representative biomarker of rumen microbial activity.

Influence of dietary carbohydrate profile on the dairy cow rumen meta-proteome

Diet starch and fiber contents influence the rumen microbial profile and its fermentation products, yet no information exists about the effects of these dietary carbohydrate fractions on the metabolic activity of these microbes. The objective of this experiment was to evaluate the effects of dietary carbohydrate profile changes on the rumen meta-proteome profile. Eight cannulated Holstein cows were assigned to the study as part of a 4 × 4 Latin square design with a 2 × 2 factorial treatment arrangement including four 28-d periods. Cows received 1 of 4 dietary treatments on a dry matter (DM) basis. Diets included different concentrations of rumen fermentable starch (RFS) and physically effective undigested NDF (peuNDF240) content in the diet: (1) low peuNDF240, low RFS (LNLS); (2) high peuNDF240, low RFS (HNLS); (3) low peuNDF240, high RFS (LNHS); and (4) high peuNDF240, high RFS (HNHS). Rumen fluid samples were collected from each cow on the last 2 d of each period at 3 time points (0600, 1000, and 1400 h). The microbial protein fraction was isolated, isobarically labeled, and analyzed using liquid chromatography combined with tandem mass spectrometry techniques. Product ion spectra were searched using the SEQUEST search on Proteome Discoverer 2.4 (Thermo Scientific) against 71 curated microbe-specific databases. Data were analyzed using PROC MIXED procedure in SAS 9.4 (SAS Institute Inc.). A total of 138 proteins were characterized across 26 of the searched microbial species. In total, 46 proteins were affected by treatments across 17 of the searched microbial species. Of these 46 proteins, 28 were affected by RFS content across 13 microbial species, with 20 proteins having higher abundance with higher dietary RFS and 8 proteins having higher abundance with lower dietary RFS. The majority of these proteins have roles in energetics, carbon metabolism, and protein synthesis. Examples include pyruvate, phosphate dikinase (Ruminococcus albus SY3), 30S ribosomal protein S11 (Clostridium aminophilum), and methyl-coenzyme M reductase subunit α (Methanobrevibacter ruminantium strain 35063), which had higher abundances with higher dietary RFS. Conversely, glutamate dehydrogenase (Butyrivibrio fibrisolvens) and 50S ribosomal protein L5 (Pseudobutyrivibrio ruminis) and L15 (Ruminococcus bromii) had lower abundances with higher dietary RFS content. Among the remaining 18 proteins unaffected by RFS content alone, 5 proteins were affected by peuNDF240 content, and 13 were affected by peuNDF240 × RFS interactions. Our results suggest that the RFS content of the diet may have a greater influence on rumen microbial protein abundances than dietary peuNDF240 content or peuNDF240 × RFS interactions. This research highlights that dietary carbohydrate profile changes can influence rumen microbial protein abundances. Further research is needed to fully characterize the effects of diet on the rumen meta-proteome and manipulate the various roles of rumen microbes. This will aid in designing the strategies to maximize the efficiency of nutrient use in the rumen.

Metaproteome plasticity sheds light on the ecology of the rumen microbiome and its connection to host traits

The arsenal of genes that microbes express reflect the way in which they sense their environment. We have previously reported that the rumen microbiome composition and its coding capacity are different in animals having distinct feed efficiency states, even when fed an identical diet. Here, we reveal that many microbial populations belonging to the bacteria and archaea domains show divergent proteome production in function of the feed efficiency state. Thus, proteomic data serve as a strong indicator of host feed efficiency state phenotype, overpowering predictions based on genomic and taxonomic information. We highlight protein production of specific phylogenies associated with each of the feed efficiency states. We also find remarkable plasticity of the proteome both in the individual population and at the community level, driven by niche partitioning and competition. These mechanisms result in protein production patterns that exhibit functional redundancy and checkerboard distribution that are tightly linked to the host feed efficiency phenotype. By linking microbial protein production and the ecological mechanisms that act within the microbiome feed efficiency states, our present work reveals a layer of complexity that bears immense importance to the current global challenges of food security and sustainability.

Rumen Metaproteomics Highlight the Unique Contributions of Microbe-Derived Extracellular and Intracellular Proteins for In Vitro Ruminal Fermentation

Rumen microorganisms can be used in in vitro anaerobic fermentation to encourage the sustainable exploitation of agricultural wastes. However, the understanding of active microbiota under in vitro ruminal fermentation conditions is still insufficient. To investigate how rumen microbes actively participate in the fermentation process in vitro, we resolved the metaproteome generated from ruminal fermentation broth after seven days of in vitro incubation. Herein, the sample-specific database for metaproteomic analysis was constructed according to the metagenomic data of in vitro ruminal fermentation. Based on the sample-specific database, we found in the metaproteome that Bacteroidetes and Firmicutes_A were the most active in protein expression, and over 50% of these proteins were assigned to gene categories involved in energy conversion and basic structures. On the other hand, a variety of bacteria-derived extracellular proteins, which contained carbohydrate-active enzyme domains, were found in the extracellular proteome of fermentation broth. Additionally, the bacterial intracellular/surface moonlighting proteins (ISMPs) and proteins of outer membrane vesicles were detected in the extracellular proteome, and these ISMPs were involved in maintaining microbial population size through potential adherence to substrates. The metaproteomic characterizations of microbial intracellular/extracellular proteins provide new insights into the ability of the rumen microbiome to maintain in vitro ruminal fermentation.

Concepts and Consequences of a Core Gut Microbiota for Animal Growth and Development

Animal microbiomes are occasionally considered as an extension of host anatomy, physiology, and even their genomic architecture. Their compositions encompass variable and constant portions when examined across multiple hosts. The latter, termed the core microbiome, is viewed as more accommodated to its host environment and suggested to benefit host fitness. Nevertheless, discrepancies in its definitions, characteristics, and importance to its hosts exist across studies. We survey studies that characterize the core microbiome, detail its current definitions and available methods to identify it, and emphasize the crucial need to upgrade and standardize the methodologies among studies. We highlight ruminants as a case study and discuss the link between the core microbiome and host physiology and genetics, as well as potential factors that shape it. We conclude with main directives of action to better understand the host-core microbiome axis and acquire the necessary insights into its controlled modulation. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Rumen metaproteomics: Closer to linking rumen microbial function to animal productivity traits

The rumen microbiome constitutes a dense and complex mixture of anaerobic bacteria, archaea, protozoa, virus and fungi. Collectively, rumen microbial populations interact closely in order to degrade and ferment complex plant material into nutrients for host metabolism, a process which also produces other by-products, such as methane gas. Our understanding of the rumen microbiome and its functions are of both scientific and industrial interest, as the metabolic functions are connected to animal health and nutrition, but at the same time contribute significantly to global greenhouse gas emissions. While many of the major microbial members of the rumen microbiome are acknowledged, advances in modern culture-independent meta-omic techniques, such as metaproteomics, enable deep exploration into active microbial populations involved in essential rumen metabolic functions. Meaningful and accurate metaproteomic analyses are highly dependent on representative samples, precise protein extraction and fractionation, as well as a comprehensive and high-quality protein sequence database that enables precise protein identification and quantification. This review focuses on the application of rumen metaproteomics, and its potential towards understanding the complex rumen microbiome and its metabolic functions. We present and discuss current methods in sample handling, protein extraction and data analysis for rumen metaproteomics, and finally emphasize the potential of (meta)genome-integrated metaproteomics for accurate reconstruction of active microbial populations in the rumen.