S ARS-CoV-2 originated in horseshoe bats and probably reached humans through an unidentified intermediary host (1). The virus is aerosolized and highly transmissible among humans; new variants have arisen and spread in successive waves across the world since late 2019. Since a report of SARS-CoV-2 infection in a dog in March 2020 (2), an ever-increasing range of species has been shown to be susceptible to infection, including household cats, dogs, ferrets, and hamsters (3-10).Companion animals have closest contact with humans, creating ample opportunity for exposure. Experimental infections have suggested that most companion animals are infected only transiently, as indicated by PCR positivity or virus isolation (11,12). Conversely, detection of antibodies by ELISA or neutralizing antibody assay suggests infection rates of 0.2%-43.9% related to factors such as the likelihood and frequency of interaction with infected humans (13-16). Infections in animals are typically subclinical or associated with transient respiratory or gastrointestinal disease (17,18). In rare cases, death has been attributed to SARS-CoV-2 infection; however, defining the contribution of SARS-CoV-2 to death in animals with underlying conditions such as cancer, bacterial pneumonia, or obesity is challenging. On the other hand, minks are highly susceptible to infection and pneumonia, and mortality rates of 35%-55% caused by SARS-CoV-2 infection were reported from outbreaks among farmed mink in Utah ( 19). Captive minks also contracted viruses with a unique amino acid substitution in the spike (S) protein that were subsequently retransmitted to humans and to community cats and dogs, around mink farms in the Netherlands (5,20). Similarly, infected pet Syrian hamsters may also retransmit SARS-CoV-2 to humans (21). More than 30% of free-ranging white-tailed deer tested in Ohio were SARS-CoV-2 positive by PCR, and a similarly high proportion of white-tailed deer in Texas and other North America locations had neutralizing antibodies (22,23). Experimentally, white-tailed deer transmitted SARS-CoV-2 to other deer vertically and horizontally by direct contact (24). It has not yet been determined if infected deer experience illness or have increased illness and death rates or if transmission is sustained among wild deer populations. However, such high

Diarrhea is the leading cause of morbidity, mortality and antimicrobial drug use in calves during the first month of age. Alteration in the bacterial communities of the gastrointestinal tract occurs during diarrhea. Diarrheic calves often develop anion gap (AG) acidosis associated with increased concentrations of unmeasured anions including D- and L-lactate. However, studies investigating the association between gut microbiota alterations and the development of acid-base disorders in diarrheic calves are lacking. We investigated the fecal bacterial alterations of calves with diarrhea and its association with changes in blood pH, and AG. Blood and fecal samples from healthy and diarrheic veal calves were taken 7 days after arrival to the farm. The fecal microbiota of healthy and diarrheic calves was assessed by sequencing of 16S ribosomal RNA gene amplicons. Blood gas analysis was completed using an i-Stat analyzer. In healthy calves, higher richness, evenness, and diversity were observed compared to diarrheic calves. Phocaeicola, Bacteroides, Prevotella, Faecalibacterium, Butyricicoccus, Ruminococcaceae and Lachnospiraceae were enriched in healthy compared with diarrheic calves. Enterococcus, Ligilactobacillus, Lactobacilus, Gallibacterium Streptococcus, and Escherichia/Shigella were enriched in diarrheic calves. In diarrheic calves, an increased abundance of lactate-producing bacteria including Lactobacillus, Streptococcus, Veillonella, Ligilactobacillus and Olsenella was detected. Diarrheic calves had a lower pH and bicarbonate concentration and a higher AG concentration than healthy calves. Together, these results indicate that calf diarrhea is associated with a shift from obligated to facultative anaerobes and expansion of lactate-producing bacteria which are related to acidemia, low bicarbonate and increase AG. Our results highlight the importance of the gastrointestinal microbiota on the clinicopathological changes observed in diarrheic calves.

Background The association of microbiota with clinical outcomes and the taxa associated with colitis in horses remains generally unknown. Objectives Describe the fecal microbiota of horses with colitis and investigate the association of the fecal microbiota with the development of laminitis and survival. Animals Thirty‐six healthy and 55 colitis horses subdivided into laminitis (n = 15) and non‐laminitis (n = 39, 1 horse with chronic laminitis was removed from this comparison) and survivors (n = 27) and nonsurvivors (n = 28). Methods Unmatched case‐control study. The Illumina MiSeq platform targeting the V4 region of the 16S ribosomal RNA gene was used to assess the microbiota. Results The community membership (Jaccard index) and structure (Yue and Clayton index) were different (analysis of molecular variance [AMOVA]; P < .001) between healthy and colitis horses. The linear discriminant analysis effect size (LEfSe; linear discriminant analysis [LDA] >3; P < .05) and random forest analyses found Enterobacteriaceae, Lactobacillus, Streptococcus, and Enterococcus enriched in colitis horses, whereas Treponema, Faecalibacterium, Ruminococcaceae, and Lachnospiraceae were enriched in healthy horses. The community membership and structure of colitis horses with or without laminitis was (AMOVA; P > .05). Enterobacteriaceae, Streptococcus, and Lactobacillus were enriched in horses with laminitis (LDA > 3; P < .05). The community membership (AMOVA; P = .008) of surviving and nonsurviving horses was different. Nonsurviving horses had an enrichment of Enterobacteriaceae, Pseudomonas, Streptococcus, and Enterococcus (LDA >3; P < .05). Conclusion and Clinical Importance Differences in the microbiota of horses with colitis that survive or do not survive are minor and, similarly, the microbiota differences in horses with colitis that do or do not develop laminitis are minor.

Exercise is a physiological stress resulting in reactive oxygen species and inflammatory mediators, the accumulation of which are thought to contribute to degenerative articular diseases. The horse is of particular interest in this regard as equine athletes are frequently exposed to repetitive bouts of high-intensity exercise. The purpose of this study was to provide a detailed description of the response of articular and systemic oxidative and inflammatory biomarkers following high-intensity, exhaustive exercise in horses. A group of horses (Ex) underwent repeated bouts of high-intensity exercise, at a target heart rate of 180 beats/min, until voluntary exhaustion. Baseline plasma and synovial fluid (SF) samples were taken 24 h before exercise and then at 0.5, 1, 2, 4, 8, and 24 h following exercise cessation. This time course was repeated in a group of nonexercised control horses (Co). Plasma and SF samples were analyzed for prostaglandin E (PGE), nitric oxide (NO), total antioxidant status (TAS), and glycosaminoglycans (GAG). The Ex group had significantly higher plasma NO at 0.5, 1, and 2 h; and higher plasma PGE at 0.5 and 1 h compared with Co. SF PGE and GAG were also higher in Ex horses at 8 h compared with Co. It is concluded that high-intensity exercise in horses results in a rapid increase in systemic oxidative and inflammatory markers from 0.5 to 2 h after exercise, which is followed by local articular inflammation and cartilage turnover at 8 h postexercise. NEW & NOTEWORTHY In horses, the influence of exercise systemically and within the articular space remains unclear and requires further detailed characterization. In this study, we identify that an acute bout of high-intensity exercise in horses induces systemic inflammation and oxidative stress within 30 min of exercise cessation, which lasts for ~2 h. Articular inflammation and cartilage turnover were also be observed within the equine carpal joint 8 h following exercise completion.

Sample storage conditions are an important factor in fecal microbiota analyses in general. The objective of this study was to investigate the effect of sample storage at room temperature on the equine fecal microbiota composition. Fecal samples were collected from 11 healthy horses. Each sample was divided into 7 sealed aliquots. One aliquot was immediately frozen at −80 °C; the remaining aliquots were stored at room temperature (21 to 22 °C) with one transferred to the freezer at each of the following time points: 6, 12, 24, 48, 72 and 96 h. The Illumina MiSeq sequencer was used for high-throughput sequencing of the V4 region of the 16S rRNA gene. Fibrobacteraceae (Fibrobacter) and Ruminococcaceae (Ruminococcus) were enriched in samples from 0 h and 6 h, whereas taxa from the families Bacillaceae, Planococcaceae, Enterobacteriaceae and Moraxellaceae were enriched in samples stored at room temperature for 24 h or greater. Samples frozen within the first 12 h after collection shared similar community membership. The community structure was similar for samples collected at 0 h and 6 h, but it was significantly different between samples frozen at 0 h and 12 h or greater. In conclusion, storage of equine fecal samples at ambient temperature for up to 6 h before freezing following sample collection had minimal effect on the microbial composition. Longer-term storage at ambient temperature resulted in alterations in alpha-diversity, community membership and structure and the enrichment of different taxa when compared to fecal samples immediately frozen at −80 °C.

Sensitivity of gastrointestinal (GI) tissue to contractile stimuli influences several parameters such as GI transit, nutrient absorption and faecal water content. Smooth muscle, which lines the GI tract, is responsible for the motility and contractile patterns which mix and propel the contents through the various GI compartments. Multiple serious medical complications are related to aberrant GI transit in horses including equine grass sickness (Hudson, Mayhew, & Pearson, 2001) and post-operative ileus (Cohen, Lester, Chris Sanchez, Merritt, & Roussel, 2004). The severity of these conditions highlights the importance of GI motility and proper smooth muscle functioning. Multiple factors including feed ingredients, particle size (Frape,

Obesity is associated with inflammatory disorders in humans, including degenerative joint disease. While obesity is endemic in horses, its relationship to equine degenerative joint disease has not been explored. The current study sought to describe relationships between: body weight (BW), body condition score (BCS), lameness grade (AAEP), total body fat mass (kg; FM) and fat per cent (FP) [multifrequency bioelectrical impedance analysis (mfBIA)], age, gender, activity level (AL), synovial fluid (SF) and plasma (PL) PGE and glycosaminoglycan (GAG) in horses. During this field investigation, the BCS (of nine) of 54 horses at multiple farms in southern Ontario, Canada, was determined. Horses were categorized as thin (BCS=3/9; n = 6), moderate (BCS=4 or 5/9; n = 18), overweight (BCS=6 or 7/9; n = 19) or obese (BCS=8 or 9/9; n = 11). Total fat mass (kg) and body fat% was measured using mfBIA, lameness was assessed (AAEP lameness scale) and synovial fluid was collected via aseptic arthrocentesis from the left intercarpal joint for assessment of inflammatory biomarkers (PGE , GAG). Means were compared with a one-way ANOVA; correlation coefficients were calculated using a Spearman Rank Order Correlation to reveal correlations between variables. BCS was positively correlated with BW, FM, FP, AL and PL-PGE . BW was also significantly positively correlated with PL-PGE . It is concluded that BCS is significantly correlated with PL-PGE , due in part to the combined effect of AL and body condition. Net inflammatory effects of body fat on risk for joint disease require further study.

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