PXD035637

PXD035637 is an original dataset announced via ProteomeXchange.

Title	Sampling the proteome by emerging single-molecule and mass-spectrometry based methods
Description	Mammalian cells have about 25,000-fold more protein molecules than mRNA molecules. This larger number of molecules and the associated larger dynamic range have major implications in the application of proteomics technologies. We examine these implications for both liquid chromatography-tandem mass-spectrometry (LC-MS/MS) and single-molecule counting and provide estimates on how many molecules are routinely measured in proteomics experiments by LC-MS/MS. We review strategies that have been helpful for counting billions of protein molecules by LC-MS/MS and suggest that these strategies can benefit single-molecule methods, especially in mitigating the challenges of the wide dynamic range of the proteome. We also examine the theoretical possibilities for scaling up single-molecule and mass-spectrometry proteomics approaches to quantifying the billions of protein molecules that make up the proteomes of our cells.
HostingRepository	PanoramaPublic
AnnounceDate	2023-03-30
AnnouncementXML	Submission_2023-03-30_19:32:29.360.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Supported dataset by repository
PrimarySubmitter	Danielle Faivre
SpeciesList	scientific name: Homo sapiens; NCBI TaxID: 9606;
ModificationList	Carbamidomethyl
Instrument	Orbitrap Eclipse

Revision	Datetime	Status	ChangeLog Entry
0	2022-07-29 18:04:58	ID requested
1	2022-08-01 14:35:00	announced
⏵ 2	2023-03-30 19:32:30	announced	: Added PubMed Id

MacCoss MJ, Alfaro JA, Faivre DA, Wu CC, Wanunu M, Slavov N, Sampling the proteome by emerging single-molecule and mass spectrometry methods. Nat Methods, 20(3):339-346(2023) [pubmed]

submitter keyword: data independent acquisition, plasma, extracellular vesicles, bioinformatics

Michael MacCoss
contact affiliation	University of Washington
contact email	maccoss@uw.edu
lab head
Danielle Faivre
contact affiliation	University of Washington
contact email	dfaivre@uw.edu
dataset submitter

Panorama Public dataset URI