Summary of Study ST002424

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 PR001560. The data can be accessed directly via it's Project DOI: 10.21228/M8242N 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.

Perform statistical analysis  |  Show all samples  |  Show named metabolites  |  Download named metabolite data  |  Perform analysis on untargeted data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST002424
Study TitleIntegrated gut microbiome and lipidomic analyses in animal models of Wilson disease reveal a role of intestine ATP7B in copper-related metabolic dysregulation (Part 2)
Study SummaryAlthough the main pathogenic mechanism of Wilson disease (WD) is related to copper accumulation in the liver and brain, there is limited knowledge about the role of ATP7B copper transporter in extra-hepatic organs, including the intestine, and how it could affect metabolic manifestations of the disease. The aims of the present study were to profile and correlate the gut microbiota and lipidome in mouse models of WD, and to study the metabolic effects of intestine-specific ATP7B deficiency in a newly generated mouse model. Animal models of WD presented reduced gut microbiota diversity compared to mice with normal copper metabolism. Comparative prediction analysis of the functional metagenome showed the involvement of several pathways including amino acid, carbohydrate, and lipid metabolisms. Lipidomic profiles showed dysregulated tri- and diglyceride, phospholipid, and sphingolipid metabolism. When challenged with a high-fat diet, Atp7bΔIEC mice confirmed profound deregulation of fatty acid desaturation and sphingolipid metabolism pathways as well as altered APOB48 distribution in intestinal epithelial cells. Gut microbiome and lipidomic analyses reveal integrated metabolic changes underlying the systemic manifestations of WD. Intestine-specific ATP7B deficit affects both intestine and systemic response to high-fat challenge. WD is as systemic disease and organ-specific ATP7B variants can explain the varied phenotypic presentations.
Institute
University of California, Davis
DepartmentInternal Medicine
LaboratoryMedici's Lab
Last NameSarode
First NameGaurav Vilas
Address451 E. Health Sciences Dr. Genome and Biomedical Sciences Facility Room 6404A Davis, CA 95616
Emailgsarode@ucdavis.edu
Phone5307526715
Submit Date2022-12-22
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2023-06-20
Release Version1
Gaurav Vilas Sarode Gaurav Vilas Sarode
https://dx.doi.org/10.21228/M8242N
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Combined analysis:

Analysis ID AN003947
Analysis type MS
Chromatography type Reversed phase
Chromatography system Agilent 6530
Column Waters ACQUITY UPLC CSH C18 (100 x 2.1mm,1.7um)
MS Type ESI
MS instrument type QTOF
MS instrument name Agilent 6530 QTOF
Ion Mode POSITIVE
Units Peak Height

MS:

MS ID:MS003683
Analysis ID:AN003947
Instrument Name:Agilent 6530 QTOF
Instrument Type:QTOF
MS Type:ESI
MS Comments:Data are analyzed in a four-stage process.First, raw data are processed in an untargeted (qualitative) manner by Agilent’s software MassHunterQual to find peaks in up to 300 chromatograms. Peak features are then imported intoMassProfilerProfessional for peak alignments to seek which peaks are present in multiplechromatograms, using exclusion criteria by the minimumpercentage of chromatograms in which these peaks arepositively detected. We usually use 30% as minimumcriterion. In a tedious manual process, these peaks arethen collated and constrained into a MassHunterquantification method on the accurate mass precursorion level, using the MS/MS information and theLipidBlast library to identify lipids with manualconfirmation of adduct ions and spectral scoringaccuracy. MassHunter enables back-filling ofquantifications for peaks that were missed in theprimary peak finding process, hence yielding data setswithout missing values. The procedure is given in thepanel to the left as workflow diagram
Ion Mode:POSITIVE
  logo