NSAID Enteropathy: Novel Aspects of Pathophysiology, Diagnosis, and Treatment

Although non-steroidal anti-inflammatory drugs (NSAIDs) are among the most frequently used classes of medications in the world, they are well-known to induce an enteropathy that is associated with high morbidity and mortality in upwards of 70% of users. The diagnosis of NSAID enteropathy is difficult. Furthermore, the underlying mechanisms by which NSAIDs induce enteropathy remain ill-defined although microbiota-host interactions appear to play an important role. Importantly, in addition to difficulty in diagnosing this disease, there are also no effective treatment strategies. Therefore, the purpose of this research was to determine if the microbiota-derived metabolite indole, could attenuate severity of NSAID enteropathy. A second goal was to determine if the transcriptome of exfoliated intestinal epithelial cells (IECs) found in the stool could be reflective of NSAID enteropathy, thereby allowing a non-invasive approach to studying how the mucosal transcriptome is altered by NSAIDs and potentially discriminating between healthy and diseased animals. We utilized a mouse model of NSAID enteropathy, whereby mice were assigned to 1 of 4 groups: 1) NSAID; 2) indole; 3) NSAID + indole; and, 4) untreated controls. Disease severity was determined by a number of assays including: fecal calprotectin, microscopic pathology, neutrophil infiltration, and RNA-seq of the ileal mucosa. Diversity and composition of the fecal microbiota was determined by 16S rRNA sequencing. Non-invasive examination of the mucosal transcriptome was determined by isolation and sequencing of polyA+ RNA from the stool followed by novel computational approaches to assess the inter-relatedness of exfoliated and tissue-level transcriptomes. Results from these assays revealed that indole did in fact attenuate disease severity and this improvement appeared to be related to composition of the microbiota. In addition, approximately 96% of all genes that were mapped from the exfoliated cell RNA were also present in the tissue-level RNA and the pathways represented by these genes and their directional changes were similar in both the small intestinal mucosa and exfoliated IEC transcriptome. These findings demonstrate that the exfoliated cell transcriptome correlates to the tissue-level transcriptome and can be used to gain longitudinal information related to NSAID-induced alterations of the mucosal transcriptome and to discriminate between diseased and healthy animals

Comparison of the microbiome, metabolome, and lipidome of obese and non-obese horses.

Metabolic diseases such as obesity and type 2 diabetes in humans have been linked to alterations in the gastrointestinal microbiota and metabolome. Knowledge of these associations has improved our understanding of the pathophysiology of these diseases and guided development of diagnostic biomarkers and therapeutic interventions. The cellular and molecular pathophysiology of equine metabolic syndrome (EMS) and obesity in horses, however, remain ill-defined. Thus, the objectives of this study were to characterize the fecal microbiome, fecal metabolome, and circulating lipidome in obese and non-obese horses. The fecal microbiota, fecal metabolome, and serum lipidome were evaluated in obese (case) horses (n = 20) and non-obese (control) horses (n = 20) matched by farm of origin (n = 7). Significant differences in metabolites of the mitochondrial tricarboxylic acid cycle and circulating free fatty acids were identified in the obese horses compared to the non-obese horses. These results indicate that the host and bacterial metabolism should be considered important in obese horses. Further studies to determine whether these associations are causal and the mechanistic basis of the association are warranted because they might reveal diagnostic biomarkers and therapeutic interventions to mitigate obesity, EMS, and sequelae including laminitis

Differential effects of selective and non-selective cyclooxygenase inhibitors on fecal microbiota in adult horses.

Non-steroidal anti-inflammatory drugs (NSAIDs) are routinely used in both veterinary and human medicine. Gastrointestinal injury is a frequent adverse event associated with NSAID use and evidence suggests that NSAIDs induce gastrointestinal microbial imbalance (i.e., dysbiosis) in both animals and people. It is unknown, however, whether cyclooxygenase (COX)-2-selective NSAIDs induce dysbiosis, or if this phenomenon occurs in horses administered any class of NSAIDs. Therefore, our objectives were to determine whether the composition and diversity of the fecal microbiota of adult horses were altered by NSAID use, and whether these effects differed between non-selective and COX-2-selective NSAIDs. Twenty-five adult horses were randomly assigned to 1 of 3 groups: control (n = 5); phenylbutazone (n = 10); or, firocoxib (n = 10). Treatments were administered for 10 days. Fecal samples were collected every 5 days for 25 days. DNA was extracted from feces and the 16S rRNA gene amplified and sequenced to determine the composition of the microbiota and the inferred metagenome. While the fecal microbiota profile of the control group remained stable over time, the phenylbutazone and firocoxib groups had decreased diversity, and alteration of their microbiota profiles was most pronounced at day 10. Similarly, there were clear alterations of the inferred metagenome at day 10 compared to all other days, indicating that use of both non-selective and selective COX inhibitors resulted in temporary alterations of the fecal microbiota and inferred metagenome. Dysbiosis associated with NSAID administration is clinically relevant because dysbiosis has been associated with several important diseases of horses including abdominal pain (colic), colitis, enteric infections, and laminitis

Effect of gallium maltolate on a model of chronic, infected equine distal limb wounds.

Distal limb wounds are common injuries sustained by horses and their healing is fraught with complications due to equine anatomy, prevalence of infection, and challenges associated with wound management. Gallium is a semi-metallic element that has been shown to possess antimicrobial properties and aid in wound healing in various preclinical models. The effects of Gallium have not been studied in equine wound healing. Therefore, the objective of this study was to compare healing rates between gallium-treated and untreated wounds of equine distal limbs and to demonstrate the antimicrobial effects of gallium on wounds inoculated with S. aureus. Using an established model of equine wound healing we demonstrated beneficial effects of 0.5% topical gallium maltolate on equine wound healing. Specifically we documented reduced healing times, reduced bioburden, and reduced formation of exuberant granulation tissue in wounds treated with gallium maltolate as compared with untreated wounds. Gallium appeared to exert its beneficial effects via its well-described antimicrobial actions as well as by altering the expression of specific genes known to be involved in wound healing of horses and other animals. Specifically, gallium maltolate appeared to increase expression of transforming growth factor-β in both infected and un-infected wounds. Further work is needed to document the effects of gallium on naturally occurring equine wounds and to compare the effects of gallium with other wound treatment options. These data, however, suggest that gallium may be an attractive and novel means of improving equine distal limb wound healing

Composition and Diversity of the Fecal Microbiome and Inferred Fecal Metagenome Does Not Predict Subsequent Pneumonia Caused by <i>Rhodococcus equi</i> in Foals

<div><p>In equids, susceptibility to disease caused by <i>Rhodococcus equi</i> occurs almost exclusively in foals. This distribution might be attributable to the age-dependent maturation of immunity following birth undergone by mammalian neonates that renders them especially susceptible to infectious diseases. Expansion and diversification of the neonatal microbiome contribute to development of immunity in the gut. Moreover, diminished diversity of the gastrointestinal microbiome has been associated with risk of infections and immune dysregulation. We thus hypothesized that varying composition or reduced diversity of the intestinal microbiome of neonatal foals would contribute to increased susceptibility of their developing <i>R</i>. <i>equi</i> pneumonia. The composition and diversity indices of the fecal microbiota at 3 and 5 weeks of age were compared among 3 groups of foals: 1) foals that <u><i>subsequently</i></u> developed <i>R</i>. <i>equi</i> pneumonia after sampling; 2) foals that <u><i>subsequently</i></u> developed ultrasonographic evidence of pulmonary abscess formation or consolidation but <u><i>not</i></u> clinical signs (subclinical group); and, 3) foals that developed neither clinical signs nor ultrasonographic evidence of pulmonary abscess formation or consolidation. No significant differences were found among groups at either sampling time, indicating absence of evidence of an influence of composition or diversity of the fecal microbiome, or predicted fecal metagenome, on susceptibility to subsequent <i>R</i>. <i>equi</i> pneumonia. A marked and significant difference identified between a relatively short interval of time appeared to reflect ongoing adaptation to transition from a milk diet to a diet including available forage (including hay) and access to concentrate fed to the mare.</p></div

Non-invasive evaluation of the equine gastrointestinal mucosal transcriptome.

Evaluating the health and function of the gastrointestinal tract can be challenging in all species, but is especially difficult in horses due to their size and length of the gastrointestinal (GI) tract. Isolation of mRNA of cells exfoliated from the GI mucosa into feces (i.e., the exfoliome) offers a novel means of non-invasively examining the gene expression profile of the GI mucosa. This approach has been utilized in people with colorectal cancer. Moreover, we have utilized this approach in a murine model of GI inflammation and demonstrated that the exfoliome reflects the tissue transcriptome. The ability of the equine exfoliome to provide non-invasive information regarding the health and function of the GI tract is not known. The objective of this study was to characterize the gene expression profile found in exfoliated intestinal epithelial cells from normal horses and compare the exfoliome data with the tissue mucosal transcriptome. Mucosal samples were collected from standardized locations along the GI tract (i.e. ileum, cecum, right dorsal colon, and rectum) from four healthy horses immediately following euthanasia. Voided feces were also collected. RNA isolation, library preparation, and RNA sequencing was performed on fecal and intestinal mucosal samples. Comparison of gene expression profiles from the tissue and exfoliome revealed correlation of gene expression. Moreover, the exfoliome contained reads representing the diverse array of cell types found in the GI mucosa suggesting the equine exfoliome serves as a non-invasive means of examining the global gene expression pattern of the equine GI tract

Data filtering and even sampling depth suggest adequate coverage for subsequent analysis.

<p>A) Bar charts of estimated goods coverage at an even sampling depth of 10,800 reads/sample at time 1 (dotted pattern) and time 2 (checkerboard pattern). Error bars represent the standard deviation. B) Alpha rarefaction curves for all samples showing numbers of observed species at each sampling depth on the y-axis and sequences/sample on the x-axis up to a sampling depth of 10,800 sequences/sample. C) Bar charts of estimated goods coverage at an even sampling depth of 3,000,000 predicted KEGG orthologies/sample at time 1 (dotted pattern) and time 2 (checkerboard pattern). Error bars represent the standard deviation. D) Alpha rarefaction curves for all samples showing numbers of observed species (KEGG orthologies) at each sampling depth on the y-axis and sequences/sample on the x-axis up to a sampling depth of 3,000,000 sequences/sample.</p

No differences in the fecal microbiota among the health groups at time 2.

<p>A) Scatter dot plot of Shannon diversity index for all health groups; healthy (dots), subclinical (squares), and clinical (triangles) at time 2. Horizontal lines represent the mean for each group and error bars represent the standard deviation. There were no statistical differences among the groups. B) Scatter dot plot of Simpson diversity index for all health groups; healthy (dots), subclinical (squares), and clinical (triangles) at time 2. Horizontal lines represent the mean for each group and error bars represent the standard deviation. There were no statistical differences among the groups. C) Alpha rarefication curves for each of the health groups; healthy (red), clinical (blue), subclinical (orange) at time 2 showing numbers of observed species at each sampling depth on the y-axis and sequences/sample on the x-axis up to 10,800 sequences/sample. Error bars represent standard deviations of each group at the specified sampling depth. D) Principal coordinate analysis of unweighted Unifrac distance metric for all heath groups; healthy (red), clinical (blue), subclinical (orange) at time 2. There were no differences among the groups.</p

The composition of the predicted metagenome changes between time 1 and time 2.

<p>(A) Principal coordinate analysis of the Bray Curtis dissimilarity metric of the predicted metagenome for time 1 (red) and time 2 (blue). There was obvious visual clustering of the predicted metagenome at time 1 and time 2. B) Pie chart showing the predicted functional pathways that were significantly (Mann Whitney U test FDR P value < 0.05) decreased >2 fold between time 1 and time 2. The figure legend accompanying the figure explains which pathways are represented by which colors. C) Pie chart showing the predicted functional pathways that were significantly (Mann Whitney U test FDR P value < 0.05) increased >2 fold between time 1 and time 2. The figure legend accompanying the figure explains which pathways are represented by which colors.</p