Summary of Study ST002349
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 PR001509. The data can be accessed directly via it's Project DOI: 10.21228/M8N71K 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 | ST002349 |
| Study Title | Biomolecular condensates create phospholipid-enriched microenvironments (Part 1) |
| Study Type | Metabolomes of in vitro synthesized condensates |
| Study Summary | Proteins and RNA are able to phase separate from the aqueous cellular environment to form sub-cellular compartments called condensates. This process results in a protein-RNA mixture that is chemically distinct from the surrounding aqueous phase. Here we use mass spectrometry to characterize the metabolomes of condensates. To test this, we prepared mixtures of phase-separated proteins and cellular metabolites and identified metabolites enriched in the condensate phase. These proteins included SARS-CoV-2 nucleocapsid, as well as low complexity domains of MED1 and HNRNPA1. |
| Institute | Cornell University |
| Department | Department of Pharmacology |
| Laboratory | Dr. Samie Jaffrey |
| Last Name | Dumelie |
| First Name | Jason |
| Address | 1300 York Ave, LC-524, New York City, NY |
| jdumes98@gmail.com | |
| Phone | 6465690174 |
| Submit Date | 2022-11-04 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzdata.xml |
| Analysis Type Detail | Other |
| Release Date | 2023-03-01 |
| Release Version | 2 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN004095 | AN004096 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | Normal phase | Normal phase |
| Chromatography system | Agilent Model 1290 Infinity II liquid chromatography system | Agilent Model 1290 Infinity II liquid chromatography system |
| Column | Cogent Diamond Hydride (150 × 2.1 mm, 4um) | Cogent Diamond Hydride (150 × 2.1 mm, 4um) |
| MS Type | Other | Other |
| MS instrument type | QTOF | QTOF |
| MS instrument name | Agilent 6550 QTOF | Agilent 6550 QTOF |
| Ion Mode | POSITIVE | NEGATIVE |
| Units | Ion counts | Ion counts |
MS:
| MS ID: | MS003842 |
| Analysis ID: | AN004095 |
| Instrument Name: | Agilent 6550 QTOF |
| Instrument Type: | QTOF |
| MS Type: | Other |
| MS Comments: | LC/MS-based targeted and untargeted metabolite profiling. For targeted analysis, raw LC/MS data was extracted by MassProfinder 8.0 (Agilent Technologies) using an in-house annotated personal metabolite database that contains 863 metabolites (Agilent Technologies). Additionally, molecular feature extraction (MFE) was performed for untargeted metabolite profiling using MassProfinder 8.0 (Agilent Technologies). The untargeted molecular features were imported into MassProfiler Professional 15.1 (MPP, Agilent Technologies) and searched against Metlin personal metabolite database (PCDL database 8.0), Human Metabolome Database (HMDB) and an in-house phospholipid database for tentative metabolite ID assignments, based on monoisotopic neutral mass (< 5 ppm mass accuracy) matches. Furthermore, a molecular formula generator (MFG) algorithm in MPP was used to generate and score empirical molecular formulae, based on a weighted consideration of monoisotopic mass accuracy, isotope abundance ratios, and spacing between isotope peaks. A tentative compound ID was assigned when PCDL database and MFG scores concurred for a given candidate molecule. Tentatively assigned molecules were reextracted using Profinder 8.0 for confirmation of untargeted results. For phospholipids, assignment of IDs was based on the defined pattern of neutral loss and head group fragment ions. Metabolites from targeted and untargeted extraction were combined for further statistical analysis among groups of input, aqueous and condensate fractions. Metabolites were removed from our analysis if they had a low ion count or high variation in input samples. Measurements of metabolite ion counts in input samples should be replicates across experiments. As such, differences in metabolite ion counts reflect experimental variability. To determine appropriate cut-offs, we examined the relationship between metabolite ion counts and their variation across input sample technical replicates. Metabolites with a median of < 1000 ion counts/sample tended to have high variation across samples. As a result, these metabolites were removed. Metabolites were also removed with > 2.5 standard deviation in log2(ion counts) since the input measurements for these metabolites were particularly unreliable relative to what was observed for other metabolites. |
| Ion Mode: | POSITIVE |
| MS ID: | MS003843 |
| Analysis ID: | AN004096 |
| Instrument Name: | Agilent 6550 QTOF |
| Instrument Type: | QTOF |
| MS Type: | Other |
| MS Comments: | LC/MS-based targeted and untargeted metabolite profiling. For targeted analysis, raw LC/MS data was extracted by MassProfinder 8.0 (Agilent Technologies) using an in-house annotated personal metabolite database that contains 863 metabolites (Agilent Technologies). Additionally, molecular feature extraction (MFE) was performed for untargeted metabolite profiling using MassProfinder 8.0 (Agilent Technologies). The untargeted molecular features were imported into MassProfiler Professional 15.1 (MPP, Agilent Technologies) and searched against Metlin personal metabolite database (PCDL database 8.0), Human Metabolome Database (HMDB) and an in-house phospholipid database for tentative metabolite ID assignments, based on monoisotopic neutral mass (< 5 ppm mass accuracy) matches. Furthermore, a molecular formula generator (MFG) algorithm in MPP was used to generate and score empirical molecular formulae, based on a weighted consideration of monoisotopic mass accuracy, isotope abundance ratios, and spacing between isotope peaks. A tentative compound ID was assigned when PCDL database and MFG scores concurred for a given candidate molecule. Tentatively assigned molecules were reextracted using Profinder 8.0 for confirmation of untargeted results. For phospholipids, assignment of IDs was based on the defined pattern of neutral loss and head group fragment ions. Metabolites from targeted and untargeted extraction were combined for further statistical analysis among groups of input, aqueous and condensate fractions. Metabolites were removed from our analysis if they had a low ion count or high variation in input samples. Measurements of metabolite ion counts in input samples should be replicates across experiments. As such, differences in metabolite ion counts reflect experimental variability. To determine appropriate cut-offs, we examined the relationship between metabolite ion counts and their variation across input sample technical replicates. Metabolites with a median of < 1000 ion counts/sample tended to have high variation across samples. As a result, these metabolites were removed. Metabolites were also removed with > 2.5 standard deviation in log2(ion counts) since the input measurements for these metabolites were particularly unreliable relative to what was observed for other metabolites. |
| Ion Mode: | NEGATIVE |
