Summary of Study ST001221
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 PR000819. The data can be accessed directly via it's Project DOI: 10.21228/M8TD5C 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 | ST001221 |
| Study Title | Effects of selenate exposure on the bumble bee metabolome |
| Study Summary | We exposed worker bumble bees to sodium selenate or control through diet. We then used LCMS untargeted metabolomics on pools of 3 bees each. |
| Institute | University of California, Riverside |
| Last Name | Rothman |
| First Name | Jason |
| Address | 900 University Ave., Riverside, CA, 91766, USA |
| jroth002@ucr.edu | |
| Phone | 9518275817 |
| Submit Date | 2019-07-17 |
| Raw Data File Type(s) | raw(Waters) |
| Analysis Type Detail | GC-MS |
| Release Date | 2020-03-03 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN002034 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Waters Acquity I-Class |
| Column | Waters Acquity CSH Phenyl-Hexyl (100 x 2.1mm,1.7um) |
| MS Type | ESI |
| MS instrument type | QTOF |
| MS instrument name | Waters Synapt G2 Si QTOF |
| Ion Mode | POSITIVE |
| Units | Peak Area |
MS:
| MS ID: | MS001886 |
| Analysis ID: | AN002034 |
| Instrument Name: | Waters Synapt G2 Si QTOF |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | We operated the MS in positive ion mode (50 to 1200 m/z) with a 100 ms scan time and acquired MS/MS data at 1 MS/MS scan per MS scan. We set source and desolvation temperatures to 150° C and 600° C, respectively. We set the desolvation gas flow to 1100 L/hr and cone gas flow to 150 L/h, with all gases being nitrogen except the collision gas, which was argon, and set capillary voltage to 1 kV. We generated a quality control sample by pooling equal aliquots of each sample and analyzed this pool every 3-4 injections to monitor system stability and performance. We analyzed samples in random order and used a leucine enkephalin infusion for mass correction. We processed the metabolite data (peak picking, alignment, deconvolution, integration, normalization, and spectral matching) with Progenesis Qi software (Nonlinear Dynamics, Durham, NC). We normalized the resulting data to total ion abundance and removed features with a coefficient of variation greater than 20% or an average abundance less than 200 in the quality control injections as in Barupal et al. 2018 and Dunn et al. 2011 (Barupal et al., 2018; Dunn et al., 2011). To aid in the identification of features belonging to the same metabolite, we assigned features a cluster ID using RAMClust (Broeckling, Afsar, Neumann, Ben-Hur, & Prenni, 2014). Next, we used a slightly modified version of the metabolomics standard initiative guidelines to assign annotation level confidence (Schymanski et al., 2014; Sumner et al., 2007): Annotation level 1 indicates an MS and MS/MS match or MS and retention time match to an in-house database generated with authentic standards. Level 2a indicates an MS and MS/MS match to an external database. Level 2b indicates an MS and MS/MS match to the LipidBlast database (Kind et al., 2013) or an MS match and diagnostic evidence (i.e. the dominant presence of an m/z 85 fragment ion for acylcarnitines). We searched against several mass spectral metabolite databases including Metlin, Massbank of North America (Blaženović et al., 2019; Kind et al., 2013), and an in-house database in the UC Riverside Metabolomics Core Facility. |
| Ion Mode: | POSITIVE |
