PXD065289

PXD065289 is an original dataset announced via ProteomeXchange.

Title	Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome Coverage
Description	We built and characterised a mass spectrometer capable of performing CID (both beam type and resonant type), UVPD, EID and ECD in an automated fashion during an LCMS type experiment. We exploited this ability to generate large datasets through multienzyme deep proteomics experiments for characterisation of these activation techniques. As a further step, motivated by the complexity generated by these dissociation techniques, we developed a single Prosit deep learning model for fragment ion intensity prediction covering all of these techniques. The generated model has been made publicly available and has been utilised in FragPipe within its MSBooster module. Rescoring allowed both data-dependent acquisition (DDA) and data-independent acquisition (DIA) to achieve on average more than 10% increase in protein identifications across all dissociation techniques and enzymatic digestions. We demonstrate that these alternative fragmentation approaches can now be used within standard data analysis pipelines and can produce data competitive to CID in terms of eficiency, but in the cases of EID and UVPD with far richer and more comprehensive spectra.
HostingRepository	PRIDE
AnnounceDate	2026-03-14
AnnouncementXML	Submission_2026-03-13_21:46:16.833.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Cemil Can Saylan
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606; scientific name: Escherichia coli; NCBI TaxID: NEWT:562; scientific name: Arabidopsis thaliana (Mouse-ear cress); NCBI TaxID: NEWT:3702;
ModificationList	No PTMs are included in the dataset
Instrument	Orbitrap Exploris 480

Revision	Datetime	Status	ChangeLog Entry
0	2025-06-21 09:27:10	ID requested
⏵ 1	2026-03-13 21:46:17	announced

10.1038/S41592-026-03042-9;

submitter keyword: ECD, EID, UVPD

Mathias Wilhelm
contact affiliation	Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
contact email	mathias.wilhelm@tum.de
lab head
Cemil Can Saylan
contact affiliation	Computational Mass Spectrometry, Technical University of Munich, D-85354 Freising, Germany
contact email	cemilcan.saylan@tum.de
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/03/PXD065289

PRIDE project URI

• PRIDE
  1. PXD065289
     1. Label: PRIDE project
     2. Name: Integrating Alternative Fragmentation Techniques into Standard LC-MS Workflows Using a Single Deep Learning Model Enhances Proteome Coverage