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Tandem mass tag-based proteomic analysis in saliva of horses with acute abdominal disease

ABSTRACT: The objective of the study was to analyze the changes in proteomics that occur in saliva in acute abdominal disease (AAD) by proteomics in order to identify new proteins that could allow gaining knowledge about the physiopathological changes that can occur in this fluid and identify possible new biomarkers of acute abdominal disease. Samples from two groups of horses were analyzed by TMT proteomic analysis: - Diseased horses (n=7; 4 stallions and 3 mares; mean age = 8 years (range 1-18); Andalusians (n=5) and crossbred (n=2)). Presence of AAD was diagnosed based on history, physical examination (abdominal auscultation, rectal examination and nasogastric intubation) and additional diagnostic tests incl. complete blood count (CBC), serum biochemistry profile, abdominal ultrasound and or abdominocentesis. Final diagnoses were impaction of ascending colon (n=3), right dorsal colon displacement (n=2) and spasmodic colon (n=2). - Healthy horses (n=6, 3 geldings, 2 stallions and 1 mare; mean age = 12 years (range 4-15); Andalusians (n=4) and crossbred (n=2)). Horses were found healthy based on history, clinical examination, CBC and serum biochemistry profile. These procedures were approved by the ethical committee of the University of Murcia (CEEA 288/2017).

INSTRUMENT(S): Q Exactive Plus

ORGANISM(S): Equus Caballus (horse)

TISSUE(S): Saliva

DISEASE(S): Abdominal Pain

SUBMITTER: Anita Horvatic

LAB HEAD: Peter David Eckersall

PROVIDER: PXD025241 | Pride | 2021-05-24

REPOSITORIES: Pride

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Source:

			Action	DRS
	20181019_Damian_horse_six1.mgf	Mgf
	20181019_Damian_horse_six1.raw	Raw
	20181019_Damian_horse_six2.mgf	Mgf
	20181019_Damian_horse_six2.raw	Raw
	20181019_Damian_horse_six3.mgf	Mgf

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Project description:Horses receiving antimicrobials may develop diarrhea due to changes in the gastrointestinal microbiome and metabolome. This matched, case-controlled study compared the fecal microbiome and metabolome in hospitalized horses on antibiotics that developed diarrhea (AAD), hospitalized horses on antibiotics that did not develop diarrhea (ABX) and a healthy, non-hospitalized control population (CON). Naturally-voided fecal samples were collected from AAD horses (n=17) the day that diarrhea developed and matched to ABX (n=15) and CON (n=31) horses for diet, antimicrobial agent and duration of antimicrobial therapy (< 5 days or > 5 days). Illumina sequencing of 16S rRNA genes on fecal DNA was performed. Alpha and beta diversity metrics were generated using QIIME 2.0. A Kruskal-Wallis with Dunn’s post-test and ANOSIM testing was used for statistical analysis. Microbiome composition in AAD was significantly different from CON (ANOSIM, R= 0.568, p=0.001) and ABX (ANOSIM, R=0.121, p=0.0012). Fecal samples were lyophilized and extracted using a solvent-based method. Untargeted metabolomics using gas chromatography-mass spectrometry platforms was performed. Metabolomic data was analyzed using Metaboanalyst 4.0 and Graphpad Prism v 7. Principal component analysis plots (PCA) were used to visualize the distribution of metabolites between groups. Heat maps were used to identify the relative concentrations amongst the most abundant 25 metabolites. A one-way ANOVA was used to compare differences in metabolites amongst the three groups of horses. Only named metabolites were included in the analysis. The microbiome of AAD and ABX horses had significantly decreased richness and evenness than CON horses (p<0.05). Actinobacteria (q=0.0192) and Bacteroidetes (q=0.0005) were different between AAD and CON. Verrucomicrobia was markedly decreased in AAD compared to ABX and CON horses (q=0.0005). Horses with AAD have a dysbiosis compared to CON horses, and show minor differences in bacterial community composition to ABX horses. Metabolite profiles of horses with AAD clustered separately from those with AAD or CON. Ten metabolites were found to be significantly different between groups (P<0.05) and are listed according to their metabolic pathway: amino acid metabolism (R-equol, L-tyrosine, kynurenic acid, xanthurenic acid, 5-hydroxyindole-3-acetic acid ) lipid metabolism (docosahexaenoic acid ethyl ester), biosynthesis of secondary metabolites (daidzein, isoquinoline) and two metabolites with unidentified pathways (1,3-divinyl-2-imidazolidinone, N-acetyltyramine).

Dataset Information

Tandem mass tag-based proteomic analysis in saliva of horses with acute abdominal disease

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