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PXD067278

PXD067278 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleFinding the optimal degassing condition for linear polyacrylamide coated capillaries used in capillary zone electrophoresis-mass spectrometry-based top-down proteomics
DescriptionLPA-coated capillaries are widely used; however, the quality of the coating—which directly affects separation performance and analyte identification—can vary significantly depending on the individual performing the procedure. A critical factor in achieving consistent coating quality is the degassing step, which involves removing dissolved oxygen from the LPA solution using nitrogen. In this study, we systematically evaluated four different degassing conditions for preparing polyacrylamide-coated capillaries for CZE-MS top-down proteomic analysis. To prevent oxygen exposure during the coating process, we degassed the solution by flowing nitrogen through a 15 cm-long capillary. The key variable across degassing conditions was whether the acrylamide and APS coating solution was stirred, and the inner diameter of the 15-cm-long capillary used for degassing. Among all designed degassing conditions, the protocol involving no stirring during degassing and using a 75 μm inner diameter capillary to degas (“75_unstirred”) consistently yielded the best performance. Across 210 runs—spanning over 200 hours on a Q-TOF and more than 10 hours on an Orbitrap 480—the 75_unstirred capillary demonstrated lower migration time RSD (<2.6%), narrower peak widths, and a higher number of theoretical plates for standard protein mixture separation. For complex proteomes such as E. coli lysates, this degassing condition exhibited enhanced resolution, signal stability, and excellent run-to-run reproducibility, with minimal migration time variation (RSD<1.5%) and relatively high signal-to-noise ratios. In a run used to identify proteins from a HeLa cell lysate, this capillary enabled the identification of 305 proteoforms. Our results highlight the critical role of degassing conditions—a 75 μm i.d. capillary for degassing and no stirring—in producing reproducible polyacrylamide-coated capillaries. The 75_unstirred protocol, which involves degassing the coating solution without agitation under 30 psi for 10 minutes by nitrogen flowing through a 75 μm i.d., 15 cm in length capillary, provides a simple and effective method for consistent capillary coating. We tested this degassing method through our CE-MS summer school 2025 students. With 10 LPA capillaries made by 9 students, the reproducible separation performance was obtained by CZE-MS separation of 4 standard protein mixture, which further prove the 75_unstirred method is reliable, user-friendly and efficient.
HostingRepositoryPRIDE
AnnounceDate2026-05-14
AnnouncementXMLSubmission_2026-05-14_06:59:31.848.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterLiangliang Sun
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606;
ModificationListNo PTMs are included in the dataset
InstrumentOrbitrap Exploris 480
Dataset History
RevisionDatetimeStatusChangeLog Entry
02025-08-12 12:56:32ID requested
12026-05-14 06:59:32announced
Publication List
Yue Y, Fang F, Gao G, Sadeghi SA, Col, ó, n Rosado JA, Tabatabaeian Nimavard R, Falamarzi Askarani M, Thorp L, Dashtaki MR, Zhu G, Sun L, Advancing the Reproducibility and Repeatability of Capillary Zone Electrophoresis-Mass Spectrometry-Based Top-Down Proteomics by an Improved Capillary Coating Procedure. J Proteome Res, 25(5):2452-2461(2026) [pubmed]
10.1021/acs.jproteome.5c01194;
Keyword List
submitter keyword: degass, polyacrylamide-coated capillary, top-down proteomics, reproducibility,capillary zone electrophoresis
Contact List
Liangliang Sun
contact affiliationDepartment of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
contact emaillsun@chemistry.msu.edu
lab head
Liangliang Sun
contact affiliationMichigan State University
contact emaillsun@chemistry.msu.edu
dataset submitter
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