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PXD023315-1

PXD023315 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleProteomic Analysis of Xinjiang Black Bee's Royal Jelly Using the Osboren Classification Method
DescriptionRoyal jelly has long been recognized as health food, with a high content of proteins. These proteins play important roles in honeybee caste and human health, but the proteomic analysis of those low-abundance proteins in royal jelly is always a challenge. Herein, we used the Osboren classification method to separate the royal jelly proteins of Xinjiang black bees, a sub-species of Apis mellifera mellifera, into various fractions. The globulin, ethanol-soluble protein and glutelin fractions were further separated by SDS-PAGE, and proteomic analysis was carried out by LC-MS/MS and searching against the NCBI database. A total of 63 proteins with definitive names were identified, in which 41 proteins were identified for the first time in royal jelly. The Osboren classification method combined with one-dimensional gel electrophoresis based proteomic analysis allows the identification of low-abundance proteins, and greatly extends the knowledge about the components and functions of royal jelly proteins.
HostingRepositoryPRIDE
AnnounceDate2024-08-09
AnnouncementXMLSubmission_2024-08-09_02:55:53.052.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterLong Chen
SpeciesList scientific name: Apis mellifera (Honeybee); NCBI TaxID: 7460;
ModificationListNo PTMs are included in the dataset
InstrumentQ Exactive
Dataset History
RevisionDatetimeStatusChangeLog Entry
02020-12-25 03:23:42ID requested
12024-08-09 02:55:53announced
22024-10-22 06:53:38announced2024-10-22: Updated project metadata.
Publication List
10.1016/j.jprot.2024.105266;
Keyword List
submitter keyword: oyal jelly
proteome
Osboren classification
low-abundance protein
Contact List
Long Chen
contact affiliationCollege of Life Science & Technology Beijing University of Chemical Technology Beijing, 10029, China
contact emailchenlong@mail.buct.edu.cn
lab head
Long Chen
contact affiliationBeijing University of Chemical Technology
contact emailchenlong@mail.buct.edu.cn
dataset submitter
Full Dataset Link List
Dataset FTP location
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