Summary of Study ST001823
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001152. The data can be accessed directly via it's Project DOI: 10.21228/M8ST22 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
Study ID | ST001823 |
Study Title | Alterations in the fecal microbiome and metabolome of horses with antimicrobial-associated diarrhea compared to antibiotic-treated and non-treated healthy case controls |
Study Summary | 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). |
Institute | Texas A&M University |
Last Name | Arnold |
First Name | Carolyn |
Address | 4475 TAMU College of Veterinary Medicine and Biomedical Sciences College Station, Texas 77843-4475 |
carnold@cvm.tamu.edu | |
Phone | 979-412-3145 |
Submit Date | 2021-03-10 |
Analysis Type Detail | LC-MS |
Release Date | 2021-09-10 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
Project ID: | PR001152 |
Project DOI: | doi: 10.21228/M8ST22 |
Project Title: | Alterations in the fecal microbiome and metabolome of horses with antimicrobial-associated diarrhea compared to antibiotic-treated and non-treated healthy case controls |
Project Summary: | 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). |
Institute: | Texas A&M University |
Department: | Department of Large Animal Clinical Sciences |
Last Name: | Arnold |
First Name: | Carolyn |
Address: | 4475 TAMU College of Veterinary Medicine and Biomedical Sciences College Station, Texas 77843-4475 |
Email: | carnold@cvm.tamu.edu |
Phone: | 979-412-3145 |
Subject:
Subject ID: | SU001900 |
Subject Type: | Mammal |
Subject Species: | Equus caballus |
Taxonomy ID: | 9796 |
Factors:
Subject type: Mammal; Subject species: Equus caballus (Factor headings shown in green)
mb_sample_id | local_sample_id | Group |
---|---|---|
SA169171 | 51 | AAD |
SA169172 | 27 | AAD |
SA169173 | 55 | AAD |
SA169174 | 31 | AAD |
SA169175 | 18 | AAD |
SA169176 | 35 | AAD |
SA169177 | 43 | AAD |
SA169178 | 47 | AAD |
SA169179 | 39 | AAD |
SA169180 | 17 | AAD |
SA169181 | 1 | AAD |
SA169182 | 22 | AAD |
SA169183 | 59 | AAD |
SA169184 | 9 | AAD |
SA169185 | 13 | AAD |
SA169186 | 5 | AAD |
SA169187 | 32 | ABX |
SA169188 | 44 | ABX |
SA169189 | 14 | ABX |
SA169190 | 6 | ABX |
SA169191 | 36 | ABX |
SA169192 | 40 | ABX |
SA169193 | 28 | ABX |
SA169194 | 48 | ABX |
SA169195 | 2 | ABX |
SA169196 | 52 | ABX |
SA169197 | 60 | ABX |
SA169198 | 24 | ABX |
SA169199 | 10 | ABX |
SA169200 | 56 | ABX |
SA169201 | 19 | ABX |
SA169202 | 63 | CON |
SA169203 | 58 | CON |
SA169204 | 57 | CON |
SA169205 | 46 | CON |
SA169206 | 45 | CON |
SA169207 | 61 | CON |
SA169208 | 53 | CON |
SA169209 | 54 | CON |
SA169210 | 62 | CON |
SA169211 | 50 | CON |
SA169212 | 49 | CON |
SA169213 | 33 | CON |
SA169214 | 12 | CON |
SA169215 | 15 | CON |
SA169216 | 16 | CON |
SA169217 | 11 | CON |
SA169218 | 8 | CON |
SA169219 | 3 | CON |
SA169220 | 4 | CON |
SA169221 | 7 | CON |
SA169222 | 20 | CON |
SA169223 | 21 | CON |
SA169224 | 37 | CON |
SA169225 | 38 | CON |
SA169226 | 41 | CON |
SA169227 | 34 | CON |
SA169228 | 30 | CON |
SA169229 | 25 | CON |
SA169230 | 26 | CON |
SA169231 | 29 | CON |
SA169232 | 42 | CON |
Showing results 1 to 62 of 62 |
Collection:
Collection ID: | CO001893 |
Collection Summary: | Fecal samples were collected from horses that were matched for diet and antimicrobial agent (including dose, route and duration of therapy). |
Collection Protocol Filename: | Collection_protocol.docx |
Sample Type: | Feces |
Storage Conditions: | -80℃ |
Treatment:
Treatment ID: | TR001913 |
Treatment Summary: | Horses were prescribed antimicrobials as prophylaxis before elective surgery (excluding surgery of the gastrointestinal tract including colic) or to treat a suspected or confirmed infection. |
Sample Preparation:
Sampleprep ID: | SP001906 |
Sampleprep Summary: | Five-hundred mg of feces was aliquoted into a 2ml tube, lyophilized overnight and vortexed with a 5mm stainless steel bead (Quiagen, Germantown, MD ) for 5 minutes. Samples were then extracted using a methanol:chloroform:water-based extraction method. Briefly 800 uL ice cold methanol:chloroform (1:1, v:v) was added to samples in a bead-based lysis tube (Bertin, Rockville, MD). Samples were homogenized for 30 seconds on a Precyllys 24 (Bertin, Rockville, MD) at a speed of 6000. The supernatant was collected and samples were homogenized a second time with 800 uL ice methanol:chloroform. 600 uL ice cold water was added to the combined extract, vortexed and centrifuged to separate the phases. The upper aqueous layer was passed through a 0.2 um nylon filter (Merck Millipore, Burlington, MA). 500 uL of the filtered aqueous phase was then passed through a 3 kDa cutoff column (Thermo Scientific, Waltham, MA) and the flow through was collected for analysis. |
Combined analysis:
Analysis ID | AN002959 |
---|---|
Analysis type | MS |
Chromatography type | Reversed phase |
Chromatography system | Thermo Xcalibur |
Column | Phenomenex Synergi Fusion (150mm x 2mm,4um) |
MS Type | ESI |
MS instrument type | Orbitrap |
MS instrument name | Thermo Q Exactive Plus Orbitrap |
Ion Mode | POSITIVE |
Units | peak intensity |
Chromatography:
Chromatography ID: | CH002192 |
Chromatography Summary: | Samples were maintained at 4 °C before injection. The injection volume was 10 µL. Chromatographic separation was achieved on a Synergi Fusion 4µm, 150 mm x 2 mm reverse phase column (Phenomenex, Torrance, CA) maintained at 30 °C using a solvent gradient method. Solvent A was water (0.1% formic acid). Solvent B was methanol (0.1% formic acid). The gradient method used was 0-5 min (10% B to 40% B), 5-7 min (40% B to 95% B), 7-9 min (95% B), 9-9.1 min (95% B to 10% B), 9.1-13 min (10% B). The flow rate was 0.4 mL min-1. |
Instrument Name: | Thermo Xcalibur |
Column Name: | Phenomenex Synergi Fusion (150mm x 2mm,4um) |
Column Temperature: | 30 |
Flow Gradient: | 0-5 min (10% B to 40% B), 5-7 min (40% B to 95% B), 7-9 min (95% B), 9-9.1 min (95% B to 10% B), 9.1-13 min (10% B). |
Flow Rate: | 0.4 mL/min |
Solvent A: | 100% water; 0.1% formic acid |
Solvent B: | 100% methanol; 0.1% formic acid |
Chromatography Type: | Reversed phase |
MS:
MS ID: | MS002749 |
Analysis ID: | AN002959 |
Instrument Name: | Thermo Q Exactive Plus Orbitrap |
Instrument Type: | Orbitrap |
MS Type: | ESI |
MS Comments: | Sample acquisition was performed Xcalibur (Thermo Scientific). |
Ion Mode: | POSITIVE |
Analysis Protocol File: | MS_protocol.docx |