Summary of Study ST002553
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 PR001645. The data can be accessed directly via it's Project DOI: 10.21228/M82M7C 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 | ST002553 |
| Study Title | Exploring the Impact of Oral Arabic Gum Consumption on Sphingolipid Metabolism and human metabolites in Chronic Kidney Disease: A Mass Spectrometry Analysis |
| Study Type | LC/MS/MS |
| Study Summary | Globally, the incidence of chronic kidney disease is increasing, raising serious concerns about its impact on public health. It also poses significant difficulty in finding novel early diagnostics, understanding biochemical pathways, monitoring patients, and prognosis. Any metabolite found in a biofluid, or tissue may act as a driver, signal, or both in the emergence or spread of the disease. As a result, metabolomics is a very useful strategy in this therapeutic setting. Broad metabolite coverage is essential since it strives to offer a representative image of a biological system. An untargeted metabolomics-based method was used in this cross-sectional study to identify metabolomic changes and their relationship to pathways in the Arabic gum patient group and control participants. Plasma samples were collected from 88 participants who met the inclusion criteria, of whom 43 control patients were treated with a placebo and 45 intervention patients were treated with Arabic gum. Highly sensitive ultra-high-performance liquid chromatography with electrospray ionization and quadrupole time-of-flight mass spectrometry was used to analyze the plasma samples (UHPLC-ESI-QTOF-MS). We investigated the effect of Arabic gum on individual metabolites using a two-tailed independent student t-test. The results showed that 31 out of 92 identified metabolites were found to be statistically significant (p < 0.05). L-Leucine and 5'-Methylthioadenosine were the significantly increased metabolites in the Arabic gum group. Conversely, triethylamine, D-limonene, 4-methylphenylacetic acid, and sphingosine levels were significantly lower in the Arabic gum group compared to the control. Arabic gum primarily affected multiple metabolic pathways, including glycine and serine, arginine and proline, valine, leucine, and isoleucine degradation, phenylalanine and tyrosine, urea cycle, and sphingolipid. The results from this study provide insights into the potential diagnostic significance of different metabolites in chronic kidney disease and their impact on specific metabolic pathways. However, further research involving larger cohorts is necessary to validate the observed metabolite changes following Arabic gum intake and their diagnostic value for chronic kidney disease. |
| Institute | Sharjah Institute for Medical Research |
| Department | Sharjah Institute for Medical Research |
| Laboratory | Biomarker Discovery Group |
| Last Name | Facility |
| First Name | Core |
| Address | M32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates |
| tims-tof@sharjah.ac.ae | |
| Phone | +971 6 5057656 |
| Submit Date | 2023-04-09 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | d |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-10-10 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN004204 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Bruker timsTOF |
| Column | Bruker Intensity Solo 2 C18 (100 mm × 2.1 mm , 1.8 μm) |
| MS Type | ESI |
| MS instrument type | QTOF |
| MS instrument name | Bruker timsTOF |
| Ion Mode | POSITIVE |
| Units | AU |
MS:
| MS ID: | MS003951 |
| Analysis ID: | AN004204 |
| Instrument Name: | Bruker timsTOF |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | The LC-MS/MS analysis was performed using an ultra-high-performance liquid chromatography system (UHPLC) (Bruker Daltonik GmbH, Bremen, Germany) connected to a quadrupole time-of-flight mass spectrometer (QTOF). An electrospray ionization (ESI) source, a solvent delivery systems pump (HPG 1300), an autosampler, and a thermostat column compartment were all included in the system. The computer operating system was Windows 10 Enterprise 2016 LTSB. Bruker Compass HyStar 5.0 SR1 Patch1 (5.0.37.1), Compass 4.1 for otofSeries, and otof Control Version 6.2 software were used for data management. Mobile phases A (water with 0.1% formic acid) and B (acetonitrile with 0.1% formic acid) were employed. The gradient program was: 0–2 min, 99% A: 1% B; 2–17 min, 99–1% A: 1–99% B; 17–20 min, 99% B: 1% A. The flow rate. Subsequently, 20–20.1 min 99% B to 99% A; 20.1–28.5 min, 99% A: 1% B at 0.35 mL/min flow rate; 28.5–30 min; 99% A: 1% B at 0.25 mL/min. A 10 μL aliquot of the sample was injected, and the separation was performed on a Hamilton® Intensity Solo 2 C18 column (100 mm × 2.1 mm × 1.8 μm) at a column oven temperature set at 35 °C. For each injection, the ESI source circumstances were as follows: The capillary voltage was adjusted to 4500 V; the drying gas flow rate was 10.0 L/min at a temperature of 220 °C; and the nebulizer pressure was 2.2 bar. The collision energy stepping for the MS2 acquisition varied between 100 and 250% fixed at 20 eV and an end plate offset of 500 V. [35]. For the external calibration step, sodium formate was utilized as a calibrant. For the calibrant sodium formate, the auto MS scan segment of the acquisition lasted from 0 to 0.3 minutes, and the auto MS/MS segment, which included fragmentation, lasted from 0.3 to 30 minutes. The acquisition in both segments was performed using the positive mode at 12 Hz. The automatic in-run mass scan range was from 20 to 1300 m/z, the width of the precursor ion was ±0.5, the number of precursors was 3, the cycle time was 0.5 s, and the threshold was 400 cts. Active exclusion was excluded after 3 spectra and released after 0.2 min. The data was processed using MetaboScape® 4.0 software (Bruker Daltonics, Billerica, MA, USA) (37). The following were the T-ReX 2D/3D workflow bucketing parameters for the processed data: intensity threshold of 1000; peak length of 7 spectra; and using peak area for quantifying the feature. Mass spectra were calibrated in 0-0.3 minutes using features from at least 48 to 187 samples. However, the auto MS/MS scan was carried out using the average method. The retention time and mass ranges for the scan were 0.3 to 25 minutes and 50 to 1000 m/z, respectively. By using LC-QTOF to analyze every sample in duplicate, 88 samples from both groups undergoing examination were combined to create a data set with 3487 characteristics. Based on the mapping of the MS/MS spectra and retention time in the HMBD 4.0, an annotated database created to meet the demands of the metabolomics community, metabolites were identified. A total of 102 distinct metabolites were selected after MetaboScape® filtration (Supplementary Table S1). The peak intensities of each metabolite were used to quantify the data matrix. Only significant compounds recorded in the HMDB 4.0 with p < 0.05 were included in the metabolite datasets. The online website HMDB (https://hmdb.ca/metabolites/HMDB0059911) was used to filter the human metabolites or Arabic gum metabolites. Following HMDB filtration, 92 unique metabolites remained (Supplementary Table S2). The software MetaboAnalyst 5.0 (Mcgill University, Montreal, QC, Canada), a comprehensive platform for metabolomics data analysis, was used to import the metabolite datasets after exporting them as a CSV file [36]. To help classify the samples, the most discriminating features in the studied group were chosen using the sPLS-DA method in MetaboAnalyst. The rate of false positives was reduced, and multiple hypothesis testing was corrected using the false discovery rate (FDR) approach. The Arabic gum group's significantly altered metabolites were found using a two-tailed independent students t-test in comparison to the control group. As a result, a volcano plot was created to display the statistical significance and fold change for cellular metabolite dysregulation. The threshold for significance was p<0.05. Functional Enrichments were constructed using metaboanalyst (https://www.metaboanalyst.ca). |
| Ion Mode: | POSITIVE |
