Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining
Amr Elguoshy1,2,3, Yoshitoshi Hirao1, Bo Xu1
1Biofluid and Biomarker Center, Niigata University , Niigata 950-2181, Japan.
Researchers developed a pipeline to identify and validate missing human proteins using transcriptomics and proteomics data. This approach successfully identified 402 missing and 19 uncertain proteins, validating 41 missing proteins with high confidence.
Area of Science:
- Proteomics
- Genomics
- Human Proteome Project
Background:
- The Chromosome-Centric Human Proteome Project (C-HPP) aims to complete the human proteome.
- Significant numbers of missing (2579) and uncertain (572) proteins remain in neXtProt (2017-1).
- Low abundance and limited unique tryptic peptides are key challenges in detecting missing proteins.
Purpose of the Study:
- To develop and implement a pipeline for analyzing, identifying, and validating human missing and uncertain proteins.
- To investigate the expression patterns and challenges associated with missing proteins.
- To leverage open-access transcriptomics and proteomics databases for protein discovery.
Main Methods:
- Analysis of RNA expression patterns in the Human Protein Atlas.
- Utilizing open-access mass spectrometry (MS)-based proteomics databases (PA, GPM).
- Searching for predicted unique tryptic peptides and validating with native spectra against SRMAtlas synthetic counterparts.
Main Results:
- 28% of missing proteins showed no RNA expression; 21% were tissue-enriched.
- 95% of missing proteins had low RNA expression (0-10 TPM), indicating low abundance challenges.
- Identified 402 missing and 19 uncertain proteins with ≥2 unique peptides; validated 41 missing proteins using ≥2 proteotypic peptides.
Conclusions:
- The developed pipeline is effective for identifying and validating missing and uncertain proteins.
- Low abundance and limited unique peptides are significant hurdles for missing protein detection.
- Targeting tissue-enriched proteins and exploring uncommon tissues are crucial strategies for future proteomic studies.
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