The effects of p53 gene inactivation on mutant proteome expression in a human melanoma cell model.
Cancer
Protein mass spectrometry
Proteogenomics
Proteomics
p53
Journal
Biochimica et biophysica acta. General subjects
ISSN: 1872-8006
Titre abrégé: Biochim Biophys Acta Gen Subj
Pays: Netherlands
ID NLM: 101731726
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
28
04
2020
revised:
02
08
2020
accepted:
24
08
2020
pubmed:
1
9
2020
medline:
5
1
2021
entrez:
1
9
2020
Statut:
ppublish
Résumé
The identification of mutated proteins in human cancer cells-termed proteogenomics, requires several technologically independent research methodologies including DNA variant identification, RNA sequencing, and mass spectrometry. Any one of these methodologies are not optimized for identifying potential mutated proteins and any one output fails to cover completely a specific landscape. An isogenic melanoma cell with a p53-null genotype was created by CRISPR/CAS9 system to determine how p53 gene inactivation affects mutant proteome expression. A mutant peptide reference database was developed by comparing two distinct DNA and RNA variant detection platforms using these isogenic cells. Chemically fractionated tryptic peptides from lysates were processed using a TripleTOF 5600+ mass spectrometer and their spectra were identified against this mutant reference database. Approximately 190 mutated peptides were enriched in wt-p53 cells, 187 mutant peptides were enriched in p53-null cells, with an overlap of 147 mutated peptides. STRING analysis highlighted that the wt-p53 cell line was enriched for mutant protein pathways such as CDC5L and POLR1B, whilst the p53-null cell line was enriched for mutated proteins comprising EGF/YES, Ubiquitination, and RPL26/5 nodes. Our study produces a well annotated p53-dependent and p53-independent mutant proteome of a common melanoma cell line model. Coupled to the application of an integrated DNA and RNA variant detection platform (CLCbio) and software for identification of proteins (ProteinPilot), this pipeline can be used to detect high confident mutant proteins in cells. This pipeline forms a blueprint for identifying mutated proteins in diseased cell systems.
Sections du résumé
BACKGROUND
The identification of mutated proteins in human cancer cells-termed proteogenomics, requires several technologically independent research methodologies including DNA variant identification, RNA sequencing, and mass spectrometry. Any one of these methodologies are not optimized for identifying potential mutated proteins and any one output fails to cover completely a specific landscape.
METHODS
An isogenic melanoma cell with a p53-null genotype was created by CRISPR/CAS9 system to determine how p53 gene inactivation affects mutant proteome expression. A mutant peptide reference database was developed by comparing two distinct DNA and RNA variant detection platforms using these isogenic cells. Chemically fractionated tryptic peptides from lysates were processed using a TripleTOF 5600+ mass spectrometer and their spectra were identified against this mutant reference database.
RESULTS
Approximately 190 mutated peptides were enriched in wt-p53 cells, 187 mutant peptides were enriched in p53-null cells, with an overlap of 147 mutated peptides. STRING analysis highlighted that the wt-p53 cell line was enriched for mutant protein pathways such as CDC5L and POLR1B, whilst the p53-null cell line was enriched for mutated proteins comprising EGF/YES, Ubiquitination, and RPL26/5 nodes.
CONCLUSION
Our study produces a well annotated p53-dependent and p53-independent mutant proteome of a common melanoma cell line model. Coupled to the application of an integrated DNA and RNA variant detection platform (CLCbio) and software for identification of proteins (ProteinPilot), this pipeline can be used to detect high confident mutant proteins in cells.
GENERAL SIGNIFICANCE
This pipeline forms a blueprint for identifying mutated proteins in diseased cell systems.
Identifiants
pubmed: 32866596
pii: S0304-4165(20)30234-8
doi: 10.1016/j.bbagen.2020.129722
pii:
doi:
Substances chimiques
Proteome
0
Tumor Suppressor Protein p53
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
129722Subventions
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/C511599/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 094417/Z/10/Z
Pays : United Kingdom
Informations de copyright
Copyright © 2020. Published by Elsevier B.V.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.