Dataset Information

Youn_et_al_RNAbodies_SAINT3090_MSPLIT_DDA (PAIRED with MSV000081414)

ABSTRACT: This set of submissions contains the mass spectrometry files acquired using Data-Dependent Acquisition mode (DDA), which were paired with Data-Independent Acquisition mode (DIA) files (MSV000081414) for the manuscript by Ji-Young Youn et al. that describes the high-density proximity mapping of RNA bodies. These DDA files were used to generate spectral library in MSPLIT analysis of both DDA and DIA files. The paired SAINT 3090 set entails APMS experiments of stress granule baits treated or untreated briefly with sodium arsenite and these were were performed from Flp-In T-REx HEK293 cells and MS files were acquired on AbSciex Triple TOF 6600 instrument in data-independent acquisition mode.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Anne-Claude Gingras

PROVIDER: MSV000081947 | MassIVE | Wed Jan 17 13:29:00 GMT 2018

REPOSITORIES: MassIVE

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Publications

High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.

Youn Ji-Young JY Dunham Wade H WH Hong Seo Jung SJ Knight James D R JDR Bashkurov Mikhail M Chen Ginny I GI Bagci Halil H Rathod Bhavisha B MacLeod Graham G Eng Simon W M SWM Angers Stéphane S Morris Quaid Q Fabian Marc M Côté Jean-François JF Gingras Anne-Claude AC

Molecular cell 20180125 3

mRNA processing, transport, translation, and ultimately degradation involve a series of dedicated protein complexes that often assemble into large membraneless structures such as stress granules (SGs) and processing bodies (PBs). Here, systematic in vivo proximity-dependent biotinylation (BioID) analysis of 119 human proteins associated with different aspects of mRNA biology uncovers 7424 unique proximity interactions with 1,792 proteins. Classical bait-prey analysis reveals connections of hundr ...[more]

PMID: 29395067

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Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.

Dataset Information

Youn_et_al_RNAbodies_SAINT3090_MSPLIT_DDA (PAIRED with MSV000081414)

Publications

High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.

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