Towards Complete Proteome Coverage and Identification of the Entire Protein Coding Potential of the Model Pathogen Bartonella henselae
EMSL Project ID
39923
Abstract
Complete proteome discovery projects provide unique information not amenable by genomics technologies, including genes missed in the genome annotation, protein modifications, the true expression level of proteins, and the composition of protein complexes and interaction networks. Importantly, such projects provide catalogs of experimentally observed proteotypic peptides (PTPs), i.e. peptides that unambiguously identify one protein and that are observable by mass spectrometry techniques. The targeted analysis of these PTPs, which are comparable to gene-specific oligonucleotides, can provide quantitative proteomics insights into basic molecular processes on a dynamic and time-resolved level.The recent development of targeted proteome discovery strategies and the ability to predict PTPs without prior experimental knowledge have indicated that the description of complete proteomes is now finally within reach. An ideal model system to further improve targeted proteomics strategies and to complete a proteome within a manageable time frame would be a prokaryote of moderate complexity.
We expect that our proposal which aims to i) describe a complete proteome and assess the entire protein coding potential of the genome, ii) develop an improved strategy to reach high proteome coverage at minimal levels of redundancy, and iii) study important pathways and protein complexes for host pathogen interaction could have an impact on the scientific research community in several areas:
(1) It could demonstrate that a complete proteome coverage can be achieved for a moderately complex prokaryotic proteome within a reasonable time frame, in particular by using improved strategies that integrate directed shotgun proteomics and scoring predicted PTPs with the sensitive MRM technology.
(2) It could provide an estimate of how many genes are missed by standard genome annotation approaches.
(3) The high quality proteomics datasets allow to assess the detection limits of state of the art proteomics and RNA-Seq transcriptomics technologies and the biases of different experimental approaches.
(4) The top down approach on very high accuracy mass spectrometers should provide a global view of the repertoire of post-translational modifications used in a prokaryote.
(5) The optimized ADE feedback loop strategy could enable other researchers to achieve high proteome coverage with a minimal amount of effort. The experimental approaches to increase coverage of short, basic, low abundant and membrane proteins will likely be of general interest.
(6) Based on an extremely dense proteome catalog and our already existing prototype of an improved, generic PTP predictor, highly relevant projects such as the monitoring of signaling pathways and the assembly and stoichiometry of important membrane-spanning protein complexes that govern host pathogen interaction could be studied on a dynamic, time-resolved level, thereby gaining insights into biological systems that cannot be obtained by genomics or transcriptomics approaches.
For a complete proteome discovery project, we critically rely on access to the latest high accuracy mass spectrometers available at the EMSL in order to minimize the false discovery rate that otherwise would lead to many spurious identifications. We look forward to benefit from the profound expertise of the EMSL research staff, which have expressed an explicit interest in a collaborative approach on this project.
Project Details
Project type
Large-Scale EMSL Research
Start Date
2010-10-06
End Date
2013-09-30
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members
Related Publications
Omasits U, M Quebatte, DJ Stekhoven, C Fortes, B Roschitzki, MD Robinson, C Dehio, and CH Ahrens. 2013. "Directed Shotgun Proteomics Guided by Saturated RNA-seq Identifies a Complete Expressed Prokaryotic Proteome." Genome Research 23(11):1916-1927. doi:10.1101/gr.151035.112
Stekhoven DJ, U Omasits, M Quebatte, C Dehio, and CH Ahrens. 2014. "Proteome-Wide Identification of Predominant Subcellular Protein Localizations in a Bacterial Model Organism." Journal of Proteomics 99:123-137. doi:10.1016/j.jprot.2014.01.015