Background: The horse plays crucial roles across the globe, including in horseracing, as a working and companion animal and as a food animal. The horse hindgut microbiome makes a key contribution in turning a high fibre diet into body mass and horsepower. However, despite its importance, the horse hindgut microbiome remains largely undefined. Here, we applied culture-independent shotgun metagenomics to thoroughbred equine faecal samples to deliver novel insights into this complex microbial community. Results: We performed metagenomic sequencing on five equine faecal samples to construct 123 high- or medium-quality metagenome-assembled genomes from Bacteria and Archaea. In addition, we recovered nearly 200 bacteriophage genomes. We document surprising taxonomic diversity, encompassing dozens of novel or unnamed bacterial genera and species, to which we have assigned new Candidatus names. Many of these genera are conserved across a range of mammalian gut microbiomes. Conclusions: Our metagenomic analyses provide new insights into the bacterial, archaeal and bacteriophage components of the horse gut microbiome. The resulting datasets provide a key resource for future high-resolution taxonomic and functional studies on the equine gut microbiome.

Background: Anthelmintic treatment is a risk factor for intestinal disease in the horse, known as colic. However the mechanisms involved in the onset of disease post anthelmintic treatment are unknown. The interaction between anthelmintic drugs and the gut microbiota may be associated with this observed increase in risk of colic. Little is known about the interaction between gut microbiota and anthelmintics and how treatment may alter microbiome function. The objectives of this study were: To characterise (1) faecal microbiota, (2) feed fermentation kinetics in vitro and (3) metabolic profiles following moxidectin administration to horses with very low (0 epg) adult strongyle burdens. Hypothesis: Moxidectin will not alter (1) faecal microbiota, (2) feed fermentation in vitro, or, (3) host metabolome.Results: Moxidectin increased the relative abundance ofDeferribacterspp. andSpirochaetesspp.observed after 160 h in moxidectin treated horses. Reduced in vitro fibre fermentation was observed 16 h following moxidectin administration in vivo (P = 0.001), along with lower pH in the in vitro fermentations from the moxidectin treated group. Metabolic profiles from urine samples did not differ between the treatment groups. However metabolic profiles from in vitro fermentations differed between moxidectin and control groups 16 h after treatment (R² = 0.69, Q²Y = 0.48), and within the moxidectin group between 16 h and 160 h post moxidectin treatment (R² = 0.79, Q²Y = 0.77). Metabolic profiles from in vitro fermentations and fermentation kinetics both indicated altered carbohydrate metabolism following in vivo treatment with moxidectin.Conclusions: These data suggest that in horses with low parasite burdens moxidectin had a small but measurable effect on both the community structure and the function of the gut microbiome.

Everyday actions such as eating, tooth brushing or applying cosmetics inherently modulate our microbiome. Advances in sequencing technologies now facilitate detailed microbial profiling, driving intentional microbiome-targeted product development. Inspired by an academic-industry workshop held in January 2024, this review explores the oral, skin and gut microbiomes, focussing on the potential long-term implications of perturbations. Key challenges in microbiome safety assessment include confounding factors (ecological variability, host influences and external conditions like geography and diet) and biases from experimental measurements and bioinformatics analyses. The taxonomic composition of the microbiome has been associated with both health and disease, and perturbations like regular disruption of the dental biofilm are essential for preventing caries and inflammatory gum disease. However, further research is required to understand the potential long-term impacts of microbiome disturbances, particularly in vulnerable populations including infants. We propose that emerging technologies, such as omics technologies to characterize microbiome functions rather than taxa, leveraging artificial intelligence to interpret clinical study data and in vitro models to characterize and measure host–microbiome interaction endpoints, could all enhance the risk assessments. The workshop emphasized the importance of detailed documentation, transparency and openness in computational models to reduce uncertainties. Harmonisation of methods could help bridge regulatory gaps and streamline safety assessments but should remain flexible enough to allow innovation and technological advancements. Continued scientific collaboration and public engagement are critical for long-term microbiome monitoring, which is essential to advancing safety assessments of microbiome perturbations.

Host-microbiota interactions are important in shaping immune responses that have the potential to influence the outcome of pathogen infection. However, most studies have focused on the gut microbiota and its possible association with disease outcome, while the role of the nasal microbiota and respiratory pathogen infection has been less well studied. Here we examined changes in the composition of the nasal microbiota of pigs following experimental infection with porcine reproductive and respiratory syndrome virus 2 (PRRSV-2), swine influenza A H3N2 virus (H3N2) or both viruses. DNA extracted from nasal swabs were subjected to 16S rRNA sequencing to study the composition of the nasal microbiota. Bacterial richness fluctuated in all groups, with a slight reduction in pigs singly infected with PRRSV-2 and H3N2 during the first 5 days of infection compared to uninfected controls. In contrast, nasal bacterial richness remained relatively stable after PRRSV-2/H3N2 co-infection. PRRSV-2 and H3N2, alone or in combination differentially altered the abundance and distribution of bacterial families. Single and co-infection with PRRSV-2 or H3N2 was associated with the expansion of the Neisseriaceae family. A positive correlation between H3N2 viral load and the relative abundance of the Neisseriaceae was observed. However, further mechanistic studies are required to understand the significance of the changes in specific bacterial families following these viral infections.

The equine gut model that we have developed and describe has the potential to facilitate the exploration of how the equine gut microbiota is affected by diet, disease, and medication. It is a convenient, cost-effective, and welfare-friendly alternative to in vivo research models.