Summary of study ST001000

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 PR000677. The data can be accessed directly via it's Project DOI: 10.21228/M8XH5B This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001000
Study TitleGut microbiome structure and metabolic activity in inflammatory bowel disease
Study SummaryThe inflammatory bowel diseases (IBD), which include Crohn’s disease (CD) and ulcerative colitis (UC), are multifactorial, chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome -- the molecular interface between host and microbiota -- are less-well understood. To address this gap, we performed untargeted LC-MS metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n=155) and validation (n=65) cohorts of CD, UC, and non-IBD control subjects. Metabolomic and metagenomic profiles were broadly correlated with fecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant (DA) in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While >50% of DA metabolite features were uncharacterized, many could be assigned putative roles through metabolomic “guilt-by-association” (covariation with known metabolites). DA species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between DA species and well-characterized DA metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets.
Institute
Broad Institute of MIT and Harvard
DepartmentMetabolomics Platform
Last NameAvila-Pacheco
First NameJulian
Address415 Main Street
Emailjravilap@broadinstitute.org
Phone617-714-8264
Submit Date2018-07-09
Num Groups3
Total Subjects220
Raw Data AvailableYes
Raw Data File Type(s).raw
Analysis Type DetailLC-MS
Release Date2019-04-17
Release Version1
Julian Avila-Pacheco Julian Avila-Pacheco
https://dx.doi.org/10.21228/M8XH5B
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Project:

Project ID:PR000677
Project DOI:doi: 10.21228/M8XH5B
Project Title:Gut microbiome structure and metabolic activity in inflammatory bowel disease
Project Summary:The inflammatory bowel diseases (IBD), which include Crohn’s disease (CD) and ulcerative colitis (UC), are multifactorial, chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome -- the molecular interface between host and microbiota -- are less-well understood. To address this gap, we performed untargeted LC-MS metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n=155) and validation (n=65) cohorts of CD, UC, and non-IBD control subjects. Metabolomic and metagenomic profiles were broadly correlated with fecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant (DA) in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While >50% of DA metabolite features were uncharacterized, many could be assigned putative roles through metabolomic “guilt-by-association” (covariation with known metabolites). DA species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between DA species and well-characterized DA metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets.
Institute:Broad Institute of MIT and Harvard
Department:Metabolomics Platform
Last Name:Avila-Pacheco
First Name:Julian
Address:415 Main Street, Cambridge MA
Email:jravilap@broadinstitute.org
Phone:617-714-8264
Contributors:Eric A. Franzosa, Alexandra Sirota-Madi, Julian Avila-Pacheco, Nadine Fornelos, Henry J. Haiser, Stefan Reinker, Tommi Vatanen, A. Brantley Hall, Himel Mallick, Lauren J. McIver, Jenny S. Sauk, Robin G. Wilson, Betsy W. Stevens, Justin M. Scott, Kerry Pierce, Amy A. Deik, Kevin Bullock, Floris Imhann, Jeffrey Porter, Alexandra Zhernakova, Jingyuan Fu,7, Rinse K. Weersma, Cisca Wijmenga, Clary B. Clish, Hera Vlamakis, Curtis Huttenhower, Ramnik J. Xavier

Subject:

Subject ID:SU001207
Subject Type:Human
Subject Species:Homo sapiens
Taxonomy ID:9606

Factors:

Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Diagnosis
SA0792808374CD
SA0792818361CD
SA0792828336CD
SA0792838802CD
SA0792848377CD
SA0792858406CD
SA0792868452CD
SA0792878841CD
SA0792888807CD
SA0792898806CD
SA0792908800CD
SA0792918843CD
SA0792928753CD
SA0792937122CD
SA0792948758CD
SA0792958095CD
SA0792968749CD
SA0792978226CD
SA0792988783CD
SA0792998264CD
SA0793008746CD
SA0793017989CD
SA0793028675CD
SA0793038534CD
SA0793048523CD
SA0793058592CD
SA0793068892CD
SA0793078537CD
SA0793088550CD
SA0793098577CD
SA0793108573CD
SA0793118565CD
SA0793128564CD
SA0793138624CD
SA0793148878CD
SA0793158475CD
SA0793168467CD
SA0793178466CD
SA0793187971CD
SA0793198847CD
SA0793208483CD
SA0793218629CD
SA0793228496CD
SA0793238485CD
SA0793248462CD
SA0793257948CD
SA0793267744CD
SA079327UMCGIBD00027CD
SA0793287658CD
SA0793297547CD
SA0793307759CD
SA079331UMCGIBD00238CD
SA079332UMCGIBD00254CD
SA0793337843CD
SA0793347791CD
SA079335UMCGIBD00233CD
SA079336UMCGIBD00064CD
SA0793377486CD
SA0793387184CD
SA0793397153CD
SA0793407150CD
SA0793417147CD
SA0793427238CD
SA0793437406CD
SA0793447445CD
SA0793457421CD
SA0793467408CD
SA079347UMCGIBD00458CD
SA079348UMCGIBD00106CD
SA079349UMCGIBD00030CD
SA079350UMCGIBD00032CD
SA079351UMCGIBD00145CD
SA079352UMCGIBD00072CD
SA0793537938CD
SA0793548591CD
SA0793557947CD
SA0793567941CD
SA0793578794CD
SA079358UMCGIBD00485CD
SA079359UMCGIBD00508CD
SA079360UMCGIBD00112CD
SA079361UMCGIBD00077CD
SA079362UMCGIBD00041CD
SA079363UMCGIBD00442CD
SA079364UMCGIBD00126CD
SA0793657875CD
SA079366UMCGIBD00082CD
SA079367UMCGIBD00141CD
SA0793688784Control
SA0793698788Control
SA0793708789Control
SA079371LLDeep_0028Control
SA079372LLDeep_0033Control
SA079373LLDeep_0030Control
SA079374LLDeep_0029Control
SA079375LLDeep_0027Control
SA079376LLDeep_0034Control
SA079377LLDeep_0037Control
SA079378LLDeep_0052Control
SA079379LLDeep_0047Control
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Collection:

Collection ID:CO001201
Collection Summary:PRISM subject stool samples were collected at the MGH gastroenterology clinic and stored at -80°C prior to DNA extraction. For the Netherlands validation cohort subjects enrolled collected stool at home and then froze it within 15 min in a conventional freezer. A research nurse visited all participants at home to collect home-frozen stool samples, which were then transported and stored at -80°C. The stool samples were kept frozen at -80°C prior to DNA extraction or metabolomic profiling.
Sample Type:Stool
Storage Conditions:Described in summary

Treatment:

Treatment ID:TR001222
Treatment Summary:NA

Sample Preparation:

Sampleprep ID:SP001215
Sampleprep Summary:Stool samples (weight range 50-5­167.8 mg) were homogenized in 4 µL of water per milligram stool sample weight using a bead mill (TissueLyser II; Qiagen) and the aqueous homogenates were aliquoted for metabolite profiling analyses.

Combined analysis:

Analysis ID AN001878 AN001879 AN001880 AN001881
Analysis type MS MS MS MS
Chromatography type HILIC HILIC Reversed phase Reversed phase
Chromatography system Shimadzu Nexera X2 Shimadzu Nexera X2 Shimadzu Nexera X2 Shimadzu Nexera X2
Column Waters 150 x 2 mm Atlantis HILIC column Phenomenex Luna NH2 (150 x 2.1mm, 3um) Waters 150 x 2 mm ACQUITY T3 column Waters Acquity BEH C8 (100 x 2.1mm, 1.7um)
MS Type ESI ESI ESI ESI
MS instrument type Orbitrap Orbitrap Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap Thermo Exactive Plus Orbitrap
Ion Mode POSITIVE NEGATIVE NEGATIVE POSITIVE
Units abundance abundance abundance abundance

Chromatography:

Chromatography ID:CH001359
Instrument Name:Shimadzu Nexera X2
Column Name:Waters 150 x 2 mm Atlantis HILIC column
Chromatography Type:HILIC
  
Chromatography ID:CH001360
Instrument Name:Shimadzu Nexera X2
Column Name:Phenomenex Luna NH2 (150 x 2.1mm, 3um)
Chromatography Type:HILIC
  
Chromatography ID:CH001361
Instrument Name:Shimadzu Nexera X2
Column Name:Waters 150 x 2 mm ACQUITY T3 column
Chromatography Type:Reversed phase
  
Chromatography ID:CH001362
Instrument Name:Shimadzu Nexera X2
Column Name:Waters Acquity BEH C8 (100 x 2.1mm, 1.7um)
Chromatography Type:Reversed phase

MS:

MS ID:MS001734
Analysis ID:AN001878
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4
Ion Mode:POSITIVE
  
MS ID:MS001735
Analysis ID:AN001879
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4
Ion Mode:NEGATIVE
  
MS ID:MS001736
Analysis ID:AN001880
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4
Ion Mode:NEGATIVE
  
MS ID:MS001737
Analysis ID:AN001881
Instrument Name:Thermo Exactive Plus Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Detailed acquisition and data processing methods available in Fransoza et al. (2019) DOI 10.1038/s41564-018-0306-4
Ion Mode:POSITIVE
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