Summary of Study ST004153

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 PR002615. The data can be accessed directly via it's Project DOI: 10.21228/M8N25C 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	ST004153
Study Title	Multi-omics Study of Small Intestine Adaptation After Total Colectomy in a Rat model
Study Summary	The study focuses on investigating the effects of Total Colectomy (TC) surgery (experimental treatment) on intestinal metabolites in a Rat model, using a sham operation as the control treatment. Fecal samples were collected at multiple time points to track metabolic changes associated with the treatments: Experimental Group (TC Surgery): Subjects underwent TC surgery, with fecal samples collected at three key time points: Preoperatively (baseline, before surgery), 1 week postoperatively, 16 weeks postoperatively; Control Group (Sham Operation): Subjects underwent a sham operation (to control for surgical intervention effects), with fecal samples collected at corresponding time points: Preoperatively (baseline, before the sham procedure), 1 week postoperatively, 16 weeks postoperatively. Broad metabolite coverage: Encompasses multiple classes of substances such as lipids (e.g., bile acids, glycerophospholipids), amino acids (e.g., glutamine, proline), and nucleosides (e.g., uridine), involving key pathways like energy metabolism and signal transduction. Good QC stability: Most metabolites (e.g., glutamine) in quality control samples show stable signals with relative standard deviations < 10%, indicating reliable experimental reproducibility. Significant inter-group differences: Bile acids (e.g., glycocholic acid) are significantly elevated in the post16TC group, suggesting changes in hepatic metabolism or bile circulation. Amino acids (e.g., isoleucine) are reduced in the post1SO group, possibly related to increased energy utilization. Lipids (e.g., lysophosphatidylcholine) show obvious differences between SO and TC subgroups, reflecting membrane remodeling or signal differences. Clear pathway associations: Enriched in bile acid synthesis, amino acid metabolism, and lipid oxidation pathways, suggesting that the treatment affects lipid digestion and redox balance. High-confidence identification: Most metabolites have high matching scores (57-58) and small mass errors (< 2 ppm), ensuring reliable identification. Meanwhile, some uncharacterized features require further research.
Institute	Shanghai Jiao Tong University
Last Name	Quan
First Name	Yingjun
Address	1111XianXia Road,Shanghai
Email	qyj4347@hotmail.com
Phone	021-5203-9999
Submit Date	2025-08-10
Raw Data Available	Yes
Raw Data File Type(s)	mzML, raw(Waters)
Analysis Type Detail	LC-MS
Release Date	2025-09-22
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR002615
Project DOI:	doi: 10.21228/M8N25C
Project Title:	Multi-omics Study of Small Intestine Adaptation After Total Colectomy
Project Summary:	To precisely identify the changes in intestinal metabolites after Total Colectomy (TC) surgery, broad-spectrum untargeted metabolomics analysis was performed to analyze fecal metabolites.
Institute:	Shanghai Jiao Tong University
Last Name:	Quan
First Name:	Yingjun
Address:	1111XianXia Road,Shanghai
Email:	qyj4347@hotmail.com
Phone:	021-520- 9999

Subject:

Subject ID:	SU004304
Subject Type:	Mammal
Subject Species:	Rattus norvegicus
Taxonomy ID:	10116

Factors:

Subject type: Mammal; Subject species: Rattus norvegicus (Factor headings shown in green)

mb_sample_id	local_sample_id	Sample source	Treatment	Time_point	Injection order
SA480595	post16SO1	Feces	Sham_operation	16 weeks post	46
SA480596	post16SO2	Feces	Sham_operation	16 weeks post	47
SA480597	post16SO3	Feces	Sham_operation	16 weeks post	48
SA480598	post16SO7	Feces	Sham_operation	16 weeks post	49
SA480599	post16SO9	Feces	Sham_operation	16 weeks post	50
SA480600	post16SO11	Feces	Sham_operation	16 weeks post	51
SA480601	post16SO12	Feces	Sham_operation	16 weeks post	52
SA480602	post16SO13	Feces	Sham_operation	16 weeks post	53
SA480603	post16SO15	Feces	Sham_operation	16 weeks post	54
SA480586	post1SO1	Feces	Sham_operation	1 week post	28
SA480587	post1SO2	Feces	Sham_operation	1 week post	29
SA480588	post1SO3	Feces	Sham_operation	1 week post	30
SA480589	post1SO7	Feces	Sham_operation	1 week post	31
SA480590	post1SO9	Feces	Sham_operation	1 week post	32
SA480591	post1SO11	Feces	Sham_operation	1 week post	33
SA480592	post1SO12	Feces	Sham_operation	1 week post	34
SA480593	post1SO13	Feces	Sham_operation	1 week post	35
SA480594	post1SO15	Feces	Sham_operation	1 week post	36
SA480604	preSO1	Feces	Sham_operation	Preoperative	10
SA480605	preSO2	Feces	Sham_operation	Preoperative	11
SA480606	preSO3	Feces	Sham_operation	Preoperative	12
SA480607	preSO6	Feces	Sham_operation	Preoperative	13
SA480608	preSO7	Feces	Sham_operation	Preoperative	14
SA480609	preSO9	Feces	Sham_operation	Preoperative	15
SA480610	preSO11	Feces	Sham_operation	Preoperative	16
SA480611	preSO13	Feces	Sham_operation	Preoperative	17
SA480612	preSO15	Feces	Sham_operation	Preoperative	18
SA480622	post16TC1	Feces	TC_surgery	16 weeks post	37
SA480623	post16TC2	Feces	TC_surgery	16 weeks post	38
SA480624	post16TC3	Feces	TC_surgery	16 weeks post	39
SA480625	post16TC7	Feces	TC_surgery	16 weeks post	40
SA480626	post16TC9	Feces	TC_surgery	16 weeks post	41
SA480627	post16TC11	Feces	TC_surgery	16 weeks post	42
SA480628	post16TC12	Feces	TC_surgery	16 weeks post	43
SA480629	post16TC13	Feces	TC_surgery	16 weeks post	44
SA480630	post16TC15	Feces	TC_surgery	16 weeks post	45
SA480613	post1TC1	Feces	TC_surgery	1 week post	19
SA480614	post1TC2	Feces	TC_surgery	1 week post	20
SA480615	post1TC3	Feces	TC_surgery	1 week post	21
SA480616	post1TC7	Feces	TC_surgery	1 week post	22
SA480617	post1TC9	Feces	TC_surgery	1 week post	23
SA480618	post1TC11	Feces	TC_surgery	1 week post	24
SA480619	post1TC12	Feces	TC_surgery	1 week post	25
SA480620	post1TC13	Feces	TC_surgery	1 week post	26
SA480621	post1TC15	Feces	TC_surgery	1 week post	27
SA480631	preTC1	Feces	TC_surgery	Preoperative	1
SA480632	preTC2	Feces	TC_surgery	Preoperative	2
SA480633	preTC3	Feces	TC_surgery	Preoperative	3
SA480634	preTC7	Feces	TC_surgery	Preoperative	4
SA480635	preTC9	Feces	TC_surgery	Preoperative	5
SA480636	preTC11	Feces	TC_surgery	Preoperative	6
SA480637	preTC12	Feces	TC_surgery	Preoperative	7
SA480638	preTC13	Feces	TC_surgery	Preoperative	8
SA480639	preTC15	Feces	TC_surgery	Preoperative	9

Showing results 1 to 54 of 54

Showing results 1 to 54 of 54

Collection:

Collection ID:	CO004297
Collection Summary:	Fecal samples were collected from participants using sterile containers. Immediately after collection, samples were stored at -80°C to preserve metabolic integrity until further processing. No additional sample preparation steps are included here, as details are provided in the sample preparation summary.
Sample Type:	Feces

Treatment:

Treatment ID:	TR004313
Treatment Summary:	The study focuses on investigating the effects of TC surgery (experimental treatment) on intestinal metabolites, using a sham operation as the control treatment. Fecal samples were collected at multiple time points to track metabolic changes associated with the treatments: Experimental Group (TC Surgery): Subjects underwent TC surgery, with fecal samples collected at three key time points: Preoperatively (baseline, before surgery). 1 week postoperatively. 16 weeks postoperatively. Control Group (Sham Operation): Subjects underwent a sham operation (to control for surgical intervention effects), with fecal samples collected at corresponding time points: Preoperatively (baseline, before the sham procedure). 1 week postoperatively. 16 weeks postoperatively. Both groups were analyzed using broad-spectrum untargeted metabolomics to compare differences in fecal metabolite profiles, aiming to isolate the specific metabolic impacts of TC surgery versus the control condition.

Treatment ID:

TR004313

Treatment Summary:

The study focuses on investigating the effects of TC surgery (experimental treatment) on intestinal metabolites, using a sham operation as the control treatment. Fecal samples were collected at multiple time points to track metabolic changes associated with the treatments: Experimental Group (TC Surgery): Subjects underwent TC surgery, with fecal samples collected at three key time points: Preoperatively (baseline, before surgery). 1 week postoperatively. 16 weeks postoperatively. Control Group (Sham Operation): Subjects underwent a sham operation (to control for surgical intervention effects), with fecal samples collected at corresponding time points: Preoperatively (baseline, before the sham procedure). 1 week postoperatively. 16 weeks postoperatively. Both groups were analyzed using broad-spectrum untargeted metabolomics to compare differences in fecal metabolite profiles, aiming to isolate the specific metabolic impacts of TC surgery versus the control condition.

Sample Preparation:

Sampleprep ID:	SP004310
Sampleprep Summary:	Sample Preparation Summary Fecal samples were processed using a standardized protocol to extract metabolites for broad-spectrum untargeted metabolomics analysis, as follows: Sample Handling: Frozen-dried fecal samples (20 mg) were used as the starting material to ensure consistency and minimize metabolite degradation. Extraction Process: Each 20 mg aliquot of dried feces was mixed with 400 μL of 70% methanol-water solution, which contained 0.1 mg/mL L-2-Chlorophenylalanine as an internal standard to normalize extraction efficiency. The mixture was vigorously vortexed for 3 minutes to ensure thorough homogenization of the sample with the extraction solvent. To enhance metabolite release, the homogenized mixture was sonicated in an ice bath for 10 minutes (ice bath conditions prevent heat-induced metabolite degradation). Separation of Supernatant: After sonication, the mixture was centrifuged at 12,000 rpm and 4°C for 10 minutes to separate solid debris from the extracted metabolites. The resulting supernatant (containing soluble metabolites) was carefully collected for subsequent LC-ESI-MS/MS analysis. This protocol ensures efficient extraction of a broad range of metabolites while preserving their stability, providing high-quality samples for downstream metabolic profiling.

Sampleprep ID:

SP004310

Sampleprep Summary:

Sample Preparation Summary Fecal samples were processed using a standardized protocol to extract metabolites for broad-spectrum untargeted metabolomics analysis, as follows: Sample Handling: Frozen-dried fecal samples (20 mg) were used as the starting material to ensure consistency and minimize metabolite degradation. Extraction Process: Each 20 mg aliquot of dried feces was mixed with 400 μL of 70% methanol-water solution, which contained 0.1 mg/mL L-2-Chlorophenylalanine as an internal standard to normalize extraction efficiency. The mixture was vigorously vortexed for 3 minutes to ensure thorough homogenization of the sample with the extraction solvent. To enhance metabolite release, the homogenized mixture was sonicated in an ice bath for 10 minutes (ice bath conditions prevent heat-induced metabolite degradation). Separation of Supernatant: After sonication, the mixture was centrifuged at 12,000 rpm and 4°C for 10 minutes to separate solid debris from the extracted metabolites. The resulting supernatant (containing soluble metabolites) was carefully collected for subsequent LC-ESI-MS/MS analysis. This protocol ensures efficient extraction of a broad range of metabolites while preserving their stability, providing high-quality samples for downstream metabolic profiling.

Combined analysis:

Analysis ID	AN006894	AN006895
Chromatography ID	CH005235	CH005236
MS ID	MS006591	MS006592
Analysis type	MS	MS
Chromatography type	Reversed phase	Reversed phase
Chromatography system	ExionLC AD UHPLC System	Waters Acquity I-Class
Column	Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um)	Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um)
MS Type	ESI	ESI
MS instrument type	QTOF	QTOF
MS instrument name	Water-VION IMS QTOF	Water-VION IMS QTOF
Ion Mode	POSITIVE	NEGATIVE
Units	Peak area (LC-MS detected ion intensity)	Peak area (LC-MS detected ion intensity)

Chromatography:

Chromatography ID:	CH005235
Instrument Name:	ExionLC AD UHPLC System
Column Name:	Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um)
Column Temperature:	40
Flow Gradient:	0–1 min: 5% B; 1–12 min: 5–95% B; 12–14 min: 95% B; 14–14.1 min: 95–5% B; 14.1–16 min: 5% B
Flow Rate:	0.3 mL/min
Solvent A:	100% water; 0.1% formic acid
Solvent B:	100% acetonitrile; 0.1% formic acid
Chromatography Type:	Reversed phase

Chromatography ID:	CH005236
Instrument Name:	Waters Acquity I-Class
Column Name:	Waters ACQUITY UPLC BEH C18 (100 x 2.1mm,1.7um)
Column Temperature:	45
Flow Gradient:	0min 1% B; 1min 30% B; 2.5min 60% B; 6.5min 90% B; 8.5min 100% B; 10.7min 100% B; 10.8min 1% B; 13min 1% B
Flow Rate:	0.4 mL/min
Solvent A:	100% water; 0.1% formic acid
Solvent B:	40% Acetonitrile/60% methanol; 0.1% formic acid
Chromatography Type:	Reversed phase

MS:

MS ID:	MS006591
Analysis ID:	AN006894
Instrument Name:	Water-VION IMS QTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	MS acquisition Comments: - For Waters-VION IMS QTOF: Data were acquired in both positive and negative ion modes using an ESI source. In positive ion mode: capillary voltage 2.5 kV, cone voltage 40 V, source temperature 115 °C, desolvation temperature 450 °C, desolvation gas flow 900 L/h. In negative ion mode: capillary voltage 2.0 kV, cone voltage 30 V, source temperature 115 °C, desolvation temperature 450 °C, desolvation gas flow 900 L/h. Both modes utilized full scan (m/z 50-1000) combined with MSE mode (low energy scan at 4 eV and high energy scan with collision energy ramp 20-45 eV). Data processing Comments: - For Waters-VION IMS QTOF data: Raw data from both positive and negative ion modes were processed for baseline filtering, peak alignment, and normalization using Progenesis QI V2.3. Further data refinement included filtering (removing peaks with >50% missing values) and replacement of zero values with 1/2 of the minimum detected value in the dataset, resulting in positive and negative mode data matrices. Software/procedures used for feature assignments: - For Waters-VION IMS QTOF data: Feature assignments relied on precise mass-to-charge ratio, retention time, ion mobility data, and secondary fragment information. These were matched against multiple databases including HMDB, Lipidmaps (V2.3), Metlin, EMDB, PMDB, and an in-house database using Progenesis QI V2.3. Compounds with identification scores <36 (out of 60) were excluded from further analysis.
Ion Mode:	POSITIVE

MS ID:	MS006592
Analysis ID:	AN006895
Instrument Name:	Water-VION IMS QTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	MS acquisition Comments: - For Waters-VION IMS QTOF: Data were acquired in both positive and negative ion modes using an ESI source. In positive ion mode: capillary voltage 2.5 kV, cone voltage 40 V, source temperature 115 °C, desolvation temperature 450 °C, desolvation gas flow 900 L/h. In negative ion mode: capillary voltage 2.0 kV, cone voltage 30 V, source temperature 115 °C, desolvation temperature 450 °C, desolvation gas flow 900 L/h. Both modes utilized full scan (m/z 50-1000) combined with MSE mode (low energy scan at 4 eV and high energy scan with collision energy ramp 20-45 eV). Data processing Comments: - For Waters-VION IMS QTOF data: Raw data from both positive and negative ion modes were processed for baseline filtering, peak alignment, and normalization using Progenesis QI V2.3. Further data refinement included filtering (removing peaks with >50% missing values) and replacement of zero values with 1/2 of the minimum detected value in the dataset, resulting in positive and negative mode data matrices. Software/procedures used for feature assignments: - For Waters-VION IMS QTOF data: Feature assignments relied on precise mass-to-charge ratio, retention time, ion mobility data, and secondary fragment information. These were matched against multiple databases including HMDB, Lipidmaps (V2.3), Metlin, EMDB, PMDB, and an in-house database using Progenesis QI V2.3. Compounds with identification scores <36 (out of 60) were excluded from further analysis.
Ion Mode:	NEGATIVE