PXD026783

PXD026783 is an original dataset announced via ProteomeXchange.

Title	Differential retinal protein expression in primary and secondary retinal ganglion cell degeneration identified by integrated SWATH and target-based proteomics
Description	To investigate the retinal proteins associated with primary and secondary retinal ganglion cell (RGC) degeneration and explore their molecular pathways, SWATH label-free and target-based mass spectrometry was employed to identify the proteomes in various retinal locations in response to localized optic nerve injury. Unilateral partial optic nerve transection (pONT) was performed on adult Wistar rats and their retinas were harvested at 2 weeks later. To confirm the separation of primary and secondary RGC degeneration, immunohistochemistry of RNA binding protein with multiple splicing (RBPMS) and glial fibrillary acidic protein (GFAP) was performed on retinal whole-mounts. Retinal proteomes in the temporal and nasal quadrants were evaluated with high resolution hybrid quadrupole time-of-flight mass spectrometry (QTOF-MS), and SWATH-based acquisition, and their expression was compared to the corresponding retinal quadrant in contralateral control eyes and further validated by multiple reaction monitoring mass spectrometry (MRM-MS). A total of 3641 proteins (p<0.05, FDR<1%) were quantified by SWATH-MS. Bioinformatics data analysis showed that there were 35 up-regulated and 24 down-regulated proteins in the temporal quadrant while 19 and 5 proteins were up-regulated and down-regulated, respectively, in the nasal quadrant respectively (n=4, p<0.05; fold change ≥1.4 fold or ≤0.7). Six proteins were regulated in both the temporal and the nasal quadrants including CLU, GFAP, GNG5, IRF2BPL, L1CAM and CPLX1. Linear regression analysis indicated a strong association between the data obtained by SWATH-MS and MRM-MS (temporal, R2=0.97; nasal, R2=0.96). Gene ontology analysis reveals statistically significant changes in the biological processes and cellular components of primary RGC degeneration. The majority of the significant changes in structural, signaling, and cell death proteins were associated with loss of RGCs in the area of primary RGC degeneration. The combined use of SWATH-MS and MRM-MS methods detects and quantifies regional changes of retinal protein expressions after localized injury. Future investigation with this integrated approach will significantly increase understanding of diverse processes of progressive RGC degeneration from a proteomic prospective.
HostingRepository	PRIDE
AnnounceDate	2024-10-22
AnnouncementXML	Submission_2024-10-22_05:25:17.624.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Chuen Lam
SpeciesList	scientific name: Rattus norvegicus (Rat); NCBI TaxID: 10116;
ModificationList	acetylated residue
Instrument	QTRAP 6500+; TripleTOF 6600

Revision	Datetime	Status	ChangeLog Entry
0	2021-06-18 03:50:13	ID requested
1	2021-09-07 04:11:43	announced
⏵ 2	2024-10-22 05:25:18	announced	2024-10-22: Updated project metadata.

Kwong JMK, Caprioli J, Sze YH, Yu FJ, Li KK, To CH, Lam TC, Differential Retinal Protein Expression in Primary and Secondary Retinal Ganglion Cell Degeneration Identified by Integrated SWATH and Target-Based Proteomics. Int J Mol Sci, 22(16):(2021) [pubmed]

10.3390/ijms22168592;

submitter keyword: ganglion cell, mass spectrometry,neurodegeneration, optic nerve, protein

Thomas Chuen Lam
contact affiliation	Associate Professor, Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong SAR
contact email	thomas.c.lam@polyu.edu.hk
lab head
Chuen Lam
contact affiliation	The Hong Kong Polytechnic University/School of optometry
contact email	cclam@polyu.edu.hk
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD026783
     1. Label: PRIDE project
     2. Name: Differential retinal protein expression in primary and secondary retinal ganglion cell degeneration identified by integrated SWATH and target-based proteomics