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Mass-spectrometry-based draft of the human proteome
Mathias Wilhelm1, Judith Schlegl2, Hannes Hahne3
11] Chair of Proteomics and Bioanalytics, Technische Universität München, Emil-Erlenmeyer Forum 5, 85354 Freising, Germany [2] SAP AG, Dietmar-Hopp-Allee 16, 69190 Walldorf, Germany [3].
Nature
|May 30, 2014
Summary
This study presents a mass spectrometry-based human proteome draft and ProteomicsDB, a database for analyzing large proteomic datasets. It offers insights into organ-specific proteins, translated long intergenic non-coding RNAs, and drug sensitivity predictions.
Area of Science:
- Proteomics
- Bioinformatics
- Genomics
Background:
- Proteomes contain vital biological information, including protein abundance, expression patterns, and modifications, inaccessible through genomics or transcriptomics.
- Understanding the human proteome is crucial for advancing biological insights and developing new technologies.
Purpose of the Study:
- To create a mass-spectrometry-based draft of the human proteome.
- To develop ProteomicsDB, a public, high-performance database for real-time analysis of large-scale proteomic data.
- To identify organ-specific proteins, translated long intergenic non-coding RNAs (lincRNAs), and proteins associated with drug sensitivity.
Main Methods:
- Mass spectrometry-based proteomics to generate a draft of the human proteome.
- Development of ProteomicsDB, an in-memory database for handling terabytes of proteomic data.
- Integration of proteomic data with messenger RNA expression profiles and drug-sensitivity data.
Main Results:
- A comprehensive draft of the human proteome was established.
- ProteomicsDB was created, enabling real-time analysis of large proteomic datasets.
- Identification of organ-specific proteins, numerous translated lincRNAs, and proteins predicting drug resistance or sensitivity.
- Analysis revealed conserved control of protein abundance across human tissues.
Conclusions:
- The human proteome draft and ProteomicsDB provide valuable resources for biological research.
- These resources facilitate the navigation of proteomes, offer biological insights, and support the advancement of proteomic technologies.
- The findings have implications for understanding gene expression, protein complex stoichiometry, and personalized medicine through drug-sensitivity prediction.
