Mechanistic insights into the digestion of complex dietary fibre by the rumen microbiota using combinatorial high-resolution glycomics and transcriptomic analyses

Current models in bacterial hemicellulase-encoding gene regulation

The discovery and characterization of bacterial carbohydrate-active enzymes is a fundamental component of biotechnology innovation, particularly for renewable fuels and chemicals; however, these studies have increasingly transitioned to exploring the complex regulation required for recalcitrant polysaccharide utilization. This pivot is largely due to the current need to engineer and optimize enzymes for maximal degradation in industrial or biomedical applications. Given the structural simplicity of a single cellulose polymer, and the relatively few enzyme classes required for complete bioconversion, the regulation of cellulases in bacteria has been thoroughly discussed in the literature. However, the diversity of hemicelluloses found in plant biomass and the multitude of carbohydrate-active enzymes required for their deconstruction has resulted in a less comprehensive understanding of bacterial hemicellulase-encoding gene regulation. Here we review the mechanisms of this process and common themes found in the transcriptomic response during plant biomass utilization. By comparing regulatory systems from both Gram-negative and Gram-positive bacteria, as well as drawing parallels to cellulase regulation, our goals are to highlight the shared and distinct features of bacterial hemicellulase-encoding gene regulation and provide a set of guiding questions to improve our understanding of bacterial lignocellulose utilization. KEY POINTS: • Canonical regulatory mechanisms for bacterial hemicellulase-encoding gene expression include hybrid two-component systems (HTCS), extracytoplasmic function (ECF)-σ/anti-σ systems, and carbon catabolite repression (CCR). • Current transcriptomic approaches are increasingly being used to identify hemicellulase-encoding gene regulatory patterns coupled with computational predictions for transcriptional regulators. • Future work should emphasize genetic approaches to improve systems biology tools available for model bacterial systems and emerging microbes with biotechnology potential. Specifically, optimization of Gram-positive systems will require integration of degradative and fermentative capabilities, while optimization of Gram-negative systems will require bolstering the potency of lignocellulolytic capabilities.

Methylation-GC-MS/FID-Based Glycosidic Linkage Analysis of Unfractionated Polysaccharides in Red Seaweeds

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more responses in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Understanding the gut microbiota by considering human evolution: a story of fire, cereals, cooking, molecular ingenuity, and functional cooperation

SUMMARYThe microbial community inhabiting the human colon, referred to as the gut microbiota, is mostly composed of bacterial species that, through extensive metabolic networking, degrade and ferment components of food and human secretions. The taxonomic composition of the microbiota has been extensively investigated in metagenomic studies that have also revealed details of molecular processes by which common components of the human diet are metabolized by specific members of the microbiota. Most studies of the gut microbiota aim to detect deviations in microbiota composition in patients relative to controls in the hope of showing that some diseases and conditions are due to or exacerbated by alterations to the gut microbiota. The aim of this review is to consider the gut microbiota in relation to the evolution of Homo sapiens which was heavily influenced by the consumption of a nutrient-dense non-arboreal diet, limited gut storage capacity, and acquisition of skills relating to mastering fire, cooking, and cultivation of cereal crops. The review delves into the past to gain an appreciation of what is important in the present. A holistic view of "healthy" microbiota function is proposed based on the evolutionary pathway shared by humans and gut microbes.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Revealing the developmental characterization of rumen microbiome and its host in newly received cattle during receiving period contributes to formulating precise nutritional strategies

BACKGROUND

Minimizing mortality losses due to multiple stress and obtaining maximum performance are the production goals for newly received cattle. In recent years, vaccination and metaphylaxis treatment significantly decreased the mortality rate of newly received cattle, while the growth block induced by treatment is still obvious. Assessment of blood metabolites and behavior monitoring offer potential for early identification of morbid animals. Moreover, the ruminal microorganisms' homeostasis is a guarantee of beef steers' growth and health. The most critical period for newly received cattle is the first-month post-transport. Therefore, analyzing rumen metagenomics, rumen metabolomics, host metabolomics, and their interaction during receiving period (1 day before transport and at days 1/4, 16, and 30 after transport) is key to revealing the mechanism of growth retardation, and then to formulating management and nutritional practices for newly received cattle.

RESULTS

The levels of serum hormones (COR and ACTH), and pro-inflammatory factors (IL-1β, TNF-α, and IL-6) were highest at day 16, and lowest at day 30 after arrival. Meanwhile, the antioxidant capacity (SOD, GSH-Px, and T-AOC) was significantly decreased at day 16 and increased at day 30 after arrival. Metagenomics analysis revealed that rumen microbes, bacteria, archaea, and eukaryota had different trends among the four different time points. At day 16 post-transport, cattle had a higher abundance of ruminal bacteria and archaea than those before transport, but the eukaryote abundance was highest at day 30 post-transport. Before transport, most bacteria were mainly involved in polysaccharides digestion. At day 4 post-transport, the most significantly enriched KEGG pathways were nucleotide metabolism (pyrimidine metabolism and purine metabolism). At day 16 post-transport, the energy metabolism (glycolysis/gluconeogenesis, pyruvate metabolism) and ruminal contents of MCP and VFAs were significantly increased, but at the same time, energy loss induced by methane yields (Methanobrevibacter) together with pathogenic bacteria (Saccharopolyspora rectivirgula) were also significantly increased. At this time, the most upregulated ruminal L-ornithine produces more catabolite polyamines, which cause oxidative stress to rumen microbes and their host; the most downregulated ruminal 2',3'-cAMP provided favorable growth conditions for pathogenic bacteria, and the downregulated ruminal vitamin B6 metabolism and serum PC/LysoPC disrupt immune function and inflammation reaction. At day 30 post-transport, the ruminal L-ornithine and its catabolites (mainly spermidine and 1,3-propanediamine) were decreased, and the serum PC/LysoPC and 2',3'-cNMPs pools were increased. This is also consistent with the changes in redox, inflammation, and immune status of the host.

CONCLUSIONS

This study provides new ideas for regulating the health and performance of newly received cattle during the receiving period. The key point is to manage the newly received cattle about day 16 post-transport, specifically to inhibit the production of methane and polyamines, and the reproduction of harmful bacteria in the rumen, therefore improving the immunity and performance of newly received cattle. Video Abstract.

β-glucans: a potential source for maintaining gut microbiota and the immune system

The human gastrointestinal (GI) tract holds a complex and dynamic population of microbial communities, which exerts a marked influence on the host physiology during homeostasis and disease conditions. Diet is considered one of the main factors in structuring the gut microbiota across a lifespan. Intestinal microbial communities play a vital role in sustaining immune and metabolic homeostasis as well as protecting against pathogens. The negatively altered gut bacterial composition has related to many inflammatory diseases and infections. β-glucans are a heterogeneous assemblage of glucose polymers with a typical structure comprising a leading chain of β-(1,4) and/or β-(1,3)-glucopyranosyl units with various branches and lengths as a side chain. β-glucans bind to specific receptors on immune cells and initiate immune responses. However, β-glucans from different sources differ in their structures, conformation, physical properties, and binding affinity to receptors. How these properties modulate biological functions in terms of molecular mechanisms is not known in many examples. This review provides a critical understanding of the structures of β-glucans and their functions for modulating the gut microbiota and immune system.

Changes in the Metagenome-Encoded CAZymes of the Rumen Microbiome Are Linked to Feed-Induced Reductions in Methane Emission From Holstein Cows

Enteric methane (CH4) emission from cattle is strongly linked to the feeding regime and the rumen microbial community structure. Here, we report that feed-induced CH4-reducing effects correlate with specific alterations in the profile of the microbiome-encoded carbohydrate-active enzymes predicted from the rumen fluid metagenome. Rumen microbiome samples were obtained by mouth-tube sampling from 12 lactating Holstein cows after 3-4 weeks of feeding with three different concentrate-to-forage-ratio diets, i.e., standard, high, and extremely high levels of concentrate (4 cows per group; constant dry matter intake in the three groups). Increased inclusion of concentrate involved increased starch levels in the diet at the expense of fiber. The extreme diet resulted in 48% reduction of the CH4 emission per kg dry matter intake compared to the standard diet. From metagenome sequencing of the rumen fluid samples from each cow, 561 different microbial strains (bins) could be derived from analysis of 260 billion DNA base pairs. In the cows fed, the extreme diet, the relative abundance of the majority of the bins, was significantly altered compared to the other groups. Fibrobacterota and Verrucomicrobiota were less abundant in the Extreme group. Surprisingly, no significant abundance changes were observed among Archaea and Bacteroidota, although abundance changes of individual bins of these phyla were found. For each of the 561 bins, the functions of the metagenome-encoded carbohydrate-active enzymes were predicted by bioinformatics using conserved unique peptide pattern (CUPP) analysis. By linking each of the predicted molecular functions of the enzymes to their substrates, changes were found in the predicted abundance of the different enzyme types. Notably, the decreased CH4 emission of the extreme diet group was concurrent with a profound decrease in the xylan-active enzymes, targeting the xylan backbone β-1,4-linkages, acetyl-, feruloyl-, and methyl-glucuronoyl substitutions in xylan. This work provides a first enzyme-conversion-based characterization of how extreme feeding, i.e., lowered forage, can drive rumen microbiome changes that support decreased CH4 emission via a changed carbohydrate-active enzyme profile. The data, furthermore, provide a metagenome-wide catalog of enzymes, underpinning the microbial conversion of different feed fibers (the enzymes attacking specific carbohydrate linkages) in the rumen of Holstein cows.