Summary of Study ST001326
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 PR000903. The data can be accessed directly via it's Project DOI: 10.21228/M8ZQ3Z 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 | ST001326 |
| Study Title | Untargeted lipidome changes in Chlamydomonas reinhardtii treated with small molecules containing adamantane structures |
| Study Summary | A study to investigate the effect of small molecule lipid inducing compounds that leads to hyper accumulation of lipids in N replete cells of Chlamydomonas reinhardtii. These compounds were identified through a high throughput screening designed for that purpose. During that screening, we screened 43,783 compounds and identified 367 primary hits. These 367 hits were further retested using a 8-point dilution series (from 0.25 to 30 uM) and verified the activity of 250 compounds that induce the hyper lipid accumulating phenotype in algae. Once the hit compounds were identified and confirmed, we then performed extensive chemoinformatics analysis to look for common scaffolds and identified several common substructures. We then selected 15 top performing compounds from 5 diverse structural groups and tested biochemical parameters such as growth, lipid accumulating capacity, effect on photosynthetic rates, respiration rates, oxygen consumption rates, analysis of different lipid species to quantify and identify fatty acid species using GC-MS. To understand the global changes in the lipidome, 2 structurally similar compounds were selected and compared with cells grown without compounds as control for untargeted lipidome analysis. |
| Institute | University of Nebraska-Lincoln |
| Department | Department of Biochemistry |
| Last Name | Wase |
| First Name | Nishikant |
| Address | Department of Biochemistry, 1901 VINE STREET |
| nishikant.wase@gmail.com | |
| Phone | 4023109931 |
| Submit Date | 2020-03-09 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzXML |
| Analysis Type Detail | LC-MS |
| Release Date | 2020-04-03 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN002208 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Agilent 1200 Series HPLC |
| Column | ACE 5 C8-300 (100 x 2.1mm) |
| MS Type | ESI |
| MS instrument type | FT-ICR |
| MS instrument name | Bruker Solarix FT-ICR-MS |
| Ion Mode | POSITIVE |
| Units | intesity |
MS:
| MS ID: | MS002054 |
| Analysis ID: | AN002208 |
| Instrument Name: | Bruker Solarix FT-ICR-MS |
| Instrument Type: | FT-ICR |
| MS Type: | ESI |
| MS Comments: | Accurate MS analysis was performed on Bruker 7.05 T Solarix FT-ICR. Mass spectra were acquired in the positive ionization mode from m/z 150.58 to 2500 at a resolving power of 49,000. Capillary voltage was 4500 V with the end plate offset voltage set to -500 V. Drying temperature was set to 180 °C and with a drying gas flow rate of 4 L/min and nebulizer gas flow set to 1.0 bar. Immediately prior to acquisition the instrument was calibrated in the positive ESI mode using NaTFA clusters. Raw MS spectra were converted to mzXML format using CompassXport v. 3.0.6 and processed by Mzmine v 2.2.4. Feature detection was done on the centrioded data using a noise level of 1.0E06 intensity. Once the masses were detected then FTMS shoulder peak filtering was performed using Lorentzian extended algorithm and chromatograms were build using a min time span of 0.1 min, minimum height of 1.0E06 intensity and m/z tolerance was set at 10 ppm. Peak smoothing was performed using Savitzky-Golay algorithm with a filter width of 3. Chromatograms were deconvulated using Savitzky-Golay algorithm using minimum peak height set at 1.0E06 intensity. Finally all the peak lists were aligned using Join aligner method using mz tolerance of 10 ppm, RT tolerance of 0.5 min. The aligned peak list rows were filtered using duplicated peak list filter to obtain 3448 peaks. The missing peak data was recovered using the Gap filling method using the intensity tolerance of 0.1, mz tolerance of 10 ppm and RT tolerance of 0.5 min. RT correction was allowed at this stage. These peaks were identified using Lipid Search module within the mzMine 2. Potential lipids were annotated according to there accurate mass on MS1 level with following setting. Minimum number of carbon set to 28 and max to 60, max number of double bonds set to 10, m/z tolerance was set to 0.001 Da. Then search was performed with two ionization mode [M+H]+ and [M+NH4]+ to obtain identification on 353 peaks. Peak areas along with identification, m/z, retention time were exported out and brought into R environment for univariate and multivariate analysis. |
| Ion Mode: | POSITIVE |
