Summary of Study ST003054
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 PR001903. The data can be accessed directly via it's Project DOI: 10.21228/M8R14K 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.
Study ID | ST003054 |
Study Title | Integrated metabolomics and proteomics of symptomatic and early pre-symptomatic states of colitis |
Study Summary | Colitis has a multifactorial pathogenesis with a strong cross-talk among microbiota, hypoxia and tissue metabolism. Here, we aimed to characterize the molecular signature of the disease in symptomatic and pre-symptomatic stages of the inflammatory process at the tissue and fecal level. The study is based on two different murine models for colitis. High-resolution Magic Angle Spinning NMR on cryopreserved “intact” colon tissues and LC-MS/MS on colon tissue extracts were used to derive untargeted metabolomics and proteomics information, respectively. Solution NMR was used to derive metabolomic profiles of fecal extracts. By combining metabolomic and proteomic analyses of the tissues, we found increased anaerobic glycolysis, accompanied by altered citric acid cycle and oxidative phosphorylation in inflamed colons; these changes associate with inflammation-induced hypoxia taking place in colon tissues. Pre-symptomatic states can be discriminated from healthy samples before macroscopic inflammation is observed. Different colitis states are characterized by significantly different metabolomic profiles of fecal extracts, attributable to both the dysbiosis characteristic of colitis, as well as the dysregulated tissue metabolism. Strong and distinctive fecal metabolomic signatures can be detected before onset of symptoms. Therefore, untargeted metabolomics of tissues and fecal extracts provides a comprehensive picture of the changes accompanying the disease onset already at pre-clinical stages, highlighting the diagnostic potential of global metabolomics for inflammatory diseases. |
Institute | University of Florence |
Last Name | Ghini |
First Name | Veronica |
Address | via Luigi Sacconi, 6, Sesto Fiorentino, Firenze, 50019, Italy |
ghini@cerm.unifi.it | |
Phone | +390554574266 |
Submit Date | 2024-01-23 |
Num Groups | 5 |
Total Subjects | 50 |
Raw Data Available | Yes |
Raw Data File Type(s) | fid |
Analysis Type Detail | NMR |
Release Date | 2024-02-28 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
NMR:
NMR ID: | NM000274 |
Analysis ID: | AN005008 |
Instrument Name: | Bruker 600 MHz |
Instrument Type: | FT-NMR |
NMR Experiment Type: | 1D-1H |
Spectrometer Frequency: | 600 MHz |
NMR Probe: | HR-MAS TXI 1H/13C/15N probe |
NMR Solvent: | H2O |
NMR Tube Size: | 4 mm rotor for HR-MAS probe |
Pulse Sequence: | CPMG |
Water Suppression: | water peak suppression-presaturation |
Temperature: | 277 K |
Number Of Scans: | 64 |
Dummy Scans: | 4 |
Acquisition Time: | 1.36s |
Spectral Width: | 12 KHz |
Num Data Points Acquired: | 32 k |
Line Broadening: | 1 |
Baseline Correction Method: | automatic |
Chemical Shift Ref Std: | doublet at 5.24 ppm |
Binned Increment: | 0.02 ppm |
Binned Data Excluded Range: | 4.5-5.5 ppm |