PXD023977-1

PXD023977 is an original dataset announced via ProteomeXchange.

Title	Boosting MS1-only proteomics with machine learning allows 2000 protein identifications in single-shot human proteome analyses using 5-minute HPLC gradients
Description	Proteome-wide analyses rely on tandem mass spectrometry and extensive separation of proteolytic mixtures imposing considerable instrumental time consumption that is one of the main obstacles in a broader acceptance of proteomics in biomedical and clinical research. Recently, we presented a fast proteomic method termed DirectMS1 based on ultra-short LC gradients, as well as MS1-only mass spectra acquisition and data processing. The method allows significant squeezing of the proteome-wide analysis time to a few minutes at the depth of quantitative proteome coverage of 1000 proteins at 1% FDR. In this work, to further increase the capabilities of the DirectMS1 method, we explored the opportunities presented by the recent progress in the machine learning area and applied the LightGBM tree-based learning algorithm into the scoring of peptide-feature matches when processing MS1 spectra. Further, we integrated the peptide feature identification algorithm of DirectMS1 with the recently introduced peptide retention time prediction utility, DeepLC. Additional approaches to improve performance of the DirectMS1 method are discussed and demonstrated, such as FAIMS coupled to the Orbitrap mass analyzer. As a result of all improvements to DirectMS1, we succeeded in identifying more than 2000 proteins at 1% FDR from the HeLa cell line in a 5 minute gradient LC-FAIMS/MS1 analysis.
HostingRepository	PRIDE
AnnounceDate	2021-03-18
AnnouncementXML	Submission_2021-03-18_01:54:36.069.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Mark Ivanov
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	iodoacetamide derivatized residue
Instrument	Orbitrap Fusion Lumos

Revision	Datetime	Status	ChangeLog Entry
0	2021-02-03 09:01:59	ID requested
⏵ 1	2021-03-18 01:54:36	announced
2	2024-10-22 05:20:13	announced	2024-10-22: Updated project metadata.

Ivanov MV, Bubis JA, Gorshkov V, Abdrakhimov DA, Kjeldsen F, Gorshkov MV, Boosting MS1-only Proteomics with Machine Learning Allows 2000 Protein Identifications in Single-Shot Human Proteome Analysis Using 5 min HPLC Gradient. J Proteome Res, 20(4):1864-1873(2021) [pubmed]

submitter keyword: Mass Spectrometry, Protein Identification, MS1-only, Fusion Lumos, FAIMS, HeLa

Mikhail Vladimirovich Gorshkov
contact affiliation	V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, 119334 Moscow, Russia
contact email	mike.gorshkov@gmail.com
lab head
Mark Ivanov
contact affiliation	INEP CP RAS
contact email	markmipt@gmail.com
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/2021/03/PXD023977

PRIDE project URI

• PRIDE
  1. PXD023977
     1. Label: PRIDE project
     2. Name: Boosting MS1-only proteomics with machine learning allows 2000 protein identifications in single-shot human proteome analyses using 5-minute HPLC gradients