Summary of Study ST002180
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 PR001338. The data can be accessed directly via it's Project DOI: 10.21228/M8RX2S 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 | ST002180 |
| Study Title | Global, distinctive and personal changes in molecular and microbial profiles induced by specific fibers in humans (Targeted) |
| Study Summary | Dietary fibers act through the microbiome and improve cardiovascular health, metabolic disorders and cancer prevention. To understand health benefits of dietary fiber supplementation we investigated two popular purified fibers, arabinoxylan (AX) and long-chain inulin (LCI), and a mixture of five fibers. We present multi-omic signatures of metabolomics, lipidomics, proteomics, metagenomics, a cytokine panel and clinical measurements on healthy and insulin resistant participants. Each fiber is associated with fiber-dependent biochemical and microbial responses. AX consumption associates with a significant reduction in LDL and an increase in bile acids, contributing to its observed cholesterol reduction. LCI is associated with an increase in Bifidobacterium. However, at the highest LCI dose there is increased inflammation and elevation in the liver enzyme alanine aminotransferase. This study yields insights into the effects of fiber supplementation, it provides insights into mechanisms behind fiber induced cholesterol reduction, and it shows effects of individual, purified fibers on the microbiome. |
| Institute | Stanford University |
| Last Name | Lancaster |
| First Name | Samuel |
| Address | 240 Pasteur Dr, BMI bldg 4400, Stanford California, 94305 |
| slancast@stanford.edu | |
| Phone | 6126004033 |
| Submit Date | 2022-03-18 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzML |
| Analysis Type Detail | LC-MS |
| Release Date | 2022-07-15 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN003570 | AN003571 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Flow induction analysis | Flow induction analysis |
| Chromatography system | Shimazdu LC-30AD | Shimazdu LC-30AD |
| Column | none | none |
| MS Type | ESI | ESI |
| MS instrument type | QTRAP | QTRAP |
| MS instrument name | ABI Sciex 5500 QTrap | ABI Sciex 5500 QTrap |
| Ion Mode | UNSPECIFIED | UNSPECIFIED |
| Units | nmol/g | nmol/g |
MS:
| MS ID: | MS003327 |
| Analysis ID: | AN003570 |
| Instrument Name: | ABI Sciex 5500 QTrap |
| Instrument Type: | QTRAP |
| MS Type: | ESI |
| MS Comments: | The Lipidyzer (SCIEX), a QTRAP system with SelexION ion mobility, was used for targeted profiling as described previously (Contrepois et al., 2018). In brief, flow injection analysis was performed with a LC-30AD (Shimazdu) operating at 8 μL/min (50 μL injection volume) using a running solution that consisted of 10 mM ammonium acetate in dichloromethane:MeOH (50:50). DMS separates lipids based on the principle that each lipid class has a different head group dipole moment and thus mobility in the DMS aperture (Schneider et al., 2010). The lipid molecular species were identified and quantified using multiple reaction monitoring (MRM) and positive/negative switching. Two acquisition methods were employed covering 10 lipid classes across positive and negative mode. Method 1 had SelexION voltages turned on while Method 2 had SelexION voltages turned off. Method 1 employed an isocratic flow of 8 μL/min for 7.9 min, followed by a 2 minute wash at 30 μL/min. Method 2 employed an isocratic flow of 8 μL/min for 6 minutes, followed by 2 minute wash at 30 μL/min. Each lipid was acquired throughout 20 cycles. Lipid classes targeted in positive mode: SM, DAG, CE, CER, and TAG. Lipid classes targeted in negative mode: LPE, LPC, PC, PE, and FFA. Lipids were quantified using the LWM software, which compares endogenous lipids to the known concentrations of structurally most similar spiked-in lipid standards and reports all detected lipids in nmol/g. Data analysis. Data were downloaded from the Lipidyzer LWM and merged and processed in R. In brief, Excel files (LWM output) were read with the “loadWorkbook” package. From all samples, lipid concentrations determined in a blank control (sample processed in parallel without the addition of cells) were subtracted to correct for background signals. The data set was further filtered accepting only lipid species that detected in at least 25% of all samples. Missing values were imputed by drawing from a random distribution. |
| Ion Mode: | UNSPECIFIED |
| MS ID: | MS003328 |
| Analysis ID: | AN003571 |
| Instrument Name: | ABI Sciex 5500 QTrap |
| Instrument Type: | QTRAP |
| MS Type: | ESI |
| MS Comments: | The Lipidyzer (SCIEX), a QTRAP system with SelexION ion mobility, was used for targeted profiling as described previously (Contrepois et al., 2018). In brief, flow injection analysis was performed with a LC-30AD (Shimazdu) operating at 8 μL/min (50 μL injection volume) using a running solution that consisted of 10 mM ammonium acetate in dichloromethane:MeOH (50:50). DMS separates lipids based on the principle that each lipid class has a different head group dipole moment and thus mobility in the DMS aperture (Schneider et al., 2010). The lipid molecular species were identified and quantified using multiple reaction monitoring (MRM) and positive/negative switching. Two acquisition methods were employed covering 10 lipid classes across positive and negative mode. Method 1 had SelexION voltages turned on while Method 2 had SelexION voltages turned off. Method 1 employed an isocratic flow of 8 μL/min for 7.9 min, followed by a 2 minute wash at 30 μL/min. Method 2 employed an isocratic flow of 8 μL/min for 6 minutes, followed by 2 minute wash at 30 μL/min. Each lipid was acquired throughout 20 cycles. Lipid classes targeted in positive mode: SM, DAG, CE, CER, and TAG. Lipid classes targeted in negative mode: LPE, LPC, PC, PE, and FFA. Lipids were quantified using the LWM software, which compares endogenous lipids to the known concentrations of structurally most similar spiked-in lipid standards and reports all detected lipids in nmol/g. Data analysis. Data were downloaded from the Lipidyzer LWM and merged and processed in R. In brief, Excel files (LWM output) were read with the “loadWorkbook” package. From all samples, lipid concentrations determined in a blank control (sample processed in parallel without the addition of cells) were subtracted to correct for background signals. The data set was further filtered accepting only lipid species that detected in at least 25% of all samples. Missing values were imputed by drawing from a random distribution. |
| Ion Mode: | UNSPECIFIED |
