Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics.


Journal

Analytical chemistry
ISSN: 1520-6882
Titre abrégé: Anal Chem
Pays: United States
ID NLM: 0370536

Informations de publication

Date de publication:
13 Jan 2023
Historique:
entrez: 13 1 2023
pubmed: 14 1 2023
medline: 14 1 2023
Statut: aheadofprint

Résumé

There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Herein, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.

Identifiants

pubmed: 36637389
doi: 10.1021/acs.analchem.2c03739
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NCI NIH HHS
ID : R01 CA272377
Pays : United States
Organisme : NIDCD NIH HHS
ID : R21 DC019753
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL148860
Pays : United States
Organisme : NCI NIH HHS
ID : UG3 CA275697
Pays : United States

Auteurs

Junho Park (J)

Department of Pharmacology, School of Medicine, CHA University, Seongnam-si, Gyeonggi-do, Seongnam 13488, Republic of Korea.

Fengchao Yu (F)

Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109-1382, United States.

James M Fulcher (JM)

Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Sarah M Williams (SM)

Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Kristin Engbrecht (K)

Nuclear, Chemistry, and Biology Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Ronald J Moore (RJ)

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Geremy C Clair (GC)

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Vladislav Petyuk (V)

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Alexey I Nesvizhskii (AI)

Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109-1382, United States.
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109-1382, United States.

Ying Zhu (Y)

Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Classifications MeSH