NCRR National Research Resource Center in Mass Spectrometry, Biomolecular Mass Spectrometry and Proteomics
- Current Research Portfolio
- Protein Prospector and Software Development
- Training and Dissemination
- Other Biomedical Technology Resource Centers
A major theme of research within the Resource is development of strategies and technology for characterizing the interplay between multiple protein posttranslational modifications(PTMs). Most modifications are currently studied in isolation, but it is well known that there is cross-talk between different PTMs[1, 2, 3, 4, 5], so by analysis of only one modification at a time the full regulatory process cannot be revealed. In addition, most analysis protocols involve characterization of modifications after digestion of proteins into small peptides. This approach loses connectivity between multiple modifications on the same protein species. Thus we pursue development of high mass accuracy and resolution strategies to analyze peptides that are much larger than those obtained from tryptic digestions.
Spectrum of acylated histone H4 peptide .
The biological paradigm where understanding the relationship between multiple modifications is best recognized as being important is the epigenetic regulation of gene expression through the modification of histones [3, 6]. As the sequence of the histones bound to all DNA is identical, regulation is achieved through dynamic modulation of combinations of either activating or repressing post-translational marks. These combinations of co-occuring modifications have been referred to as a histone code, and deconvolving these regulatory messages ideally requires strategies that can characterize intact histone proteins. The Resource is developing strategies employing electron capture dissociation (ECD) and electron transfer dissociation (ETD) to fragment intact proteins on a chromatographic time-scale. This work involves development of improved chromatographic separation strategies, optimization of the latest mass spectrometric instrumentation, and production of bioinformatic tools that can rapidly and efficiently summarize the acquired data.
The Resource has major efforts in developing strategies for the analysis of O–GlcNAcylation[7, 8] and phosphorylation[9, 10, 11]. These modifications interplay with each other in the regulation of many biological processes [12, 13, 14, 15], and O–GlcNAcylation has been implicated in diseases including diabetes, cancer and Alzheimer, so there is a major effort within the Resource to characterize cross-talk between these two types of modification. This requires development of analysis approaches that allow thorough study of both modification types from the same sample through sequential enrichment of each modification type. As noted above the use of enzymes that produce large fragments is also being employed to increase the frequency of multiple modifications being present on a single peptide, to confirm their co-existence on the same protein species. This work is made more comprehensive by the availability of complementary fragmentation approaches of CID and ETD on the same instrument.
Assigning a biological role to a post-translational modification can be challenging when there are large numbers of proteins in a sample and multiple pathways are being activated. Hence, the Resource is helping develop a number of strategies that allow more targeted understanding of modifications. These include methods that allow identification of specific targets of kinase inhibitors, identification of phosphorylation targets of specific kinases[18, 19], or identification of post-translational modifications that are regulated by activation of a specific receptor tyrosine kinase. There are also projects investigating post-translational proteolytic processing to form new protein N–termini, which have major implications in processes such as apoptosis and inflammation, necrosis, and may have application in biomarker discovery. The human genome encodes more proteolytic enzymes than protein kinases, so many important biological events are expected to be revealed with this effort.
Many of these approaches are reliant on obtaining quantitative measurements and the Resource has been involved in development and application of a number of isotopic labeling approaches for quantification[10, 22, 23]. A major present frustration of several of these strategies is the incomplete overlap in components quantified between different experiments, so the Resource is developing targeted approaches that allow sensitive quantification of the same components in each comparative experiment.
The resource has over fifty active collaborative projects. Some of these involve application of existing technology to important biological and biomedical questions. Others are technically more challenging and require the development of new techniques, reagents or software in order to solve pressing problems. Several of these are successful long-term collaborative efforts with high-profile researchers such as Frank McCormick, Michael Fainzilber, Lennart Mucke, Ralf Schoepfer, Kevan Shokat and James Wells.
For all these research projects a key component is the availability of robust and powerful bioinformatics software to manage, interpret and summarize results. The Resource develops arguably the most powerful and diverse suite of proteomic analysis tools available in Protein Prospector. Peptide and protein identification from tandem mass spectrometry data is the cornerstone of most current proteomic research and Protein Prospector has been demonstrated to be one of the most sensitive and effective search engines for interpretation of data produced from a wide range of different instruments. The recent widespread emergence of ECD and ETD fragmentation approaches for proteomic research presents new challenges for searching software, but Protein Prospector has been shown to be one of the most effective at analysis of this type of data.
The ability to compare or combine results from multiple datasets is an important part of proteomic research, but this functionality is not available in most search engines. However, Protein Prospector uses a database structure for storing previous search results that allows comparison or merging of unlimited numbers of different data analyses. This has particular application in studies where CID and ETD analysis of the same sample may have been performed and a combined results summary is desired.
Relative quantification of components can be determined using isotopic labeling or label-free strategies. Protein Prospector supports both these measurement strategies, and is the only freely available software that combines database searching and stable isotope quantification analysis in one package.
Chemical cross-linking strategies are powerful for characterizing protein structure, binding partners and interaction surfaces. However, analysis of this type of data is complicated. The Resource is developing improved searching strategies within Protein Prospector that allow identification of cross-linked peptides in the background of complex peptide mixtures.
All these features of Protein Prospector are freely available through a public website maintained by the Resource. This website is used for over a million searches every year, demonstrating its importance to the research community. Researchers are also able to contact us through the website to request new features, and these suggestions are evaluated and those seen as being of wide use to other researchers are implemented.
Training in proteomic analysis strategies and dissemination of technologies developed within the facility are significant parts of the work of the Resource. In support of this aspect of the Resource's mission, the facility is continuously working with and mentoring postdoctoral scholars and graduate students. Currently the facility's research staff includes six postdoctoral scholars and three graduate students. Additionally, one graduate-level course is taught by the Resource (Chem204). It is open to other researchers, and a number of post-doctoral scholars and PIs from both within UCSF and from other local research institutions attend. The Resource also hosts a biennial International Symposium on Mass Spectrometry in the Health and Life Sciences, which attracts world-class researchers from both mass spectrometry and biological backgrounds and is a major avenue for fertilization of cross-disciplinary research.
The Resource publishes extensively in peer-reviewed journals (available on the website) and also presents its research at a range of international conferences and forums. Through this website it also makes available protocols (In-Gel Digestion, Phosphorylated Peptide Enrichment Using TiO2, and Lectin Weak Affinity Chromatography) and software tools (ProteinProspector and available software) used in the Resource.
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 Mahrus, S., J.C. Trinidad, D.T. Barkan, A. Sali, A.L. Burlingame, and J.A. Wells, Global sequencing of proteolytic cleavage sites in apoptosis by specific labeling of protein N termini. Cell, 2008. 134(5): p. 866-76. [Pubmed]
 Hansen, K.C., G. Schmitt-Ulms, R.J. Chalkley, J. Hirsch, M.A. Baldwin, and A.L. Burlingame, Mass Spectrometric Analysis of Protein Mixtures at Low Levels Using Cleavable 13C-Isotope-coded Affinity Tag and Multidimensional Chromatography. Mol Cell Proteomics, 2003. 2(5): p. 299-314. [Pubmed]
 Hirsch, J., K.C. Hansen, A. Sapru, J.A. Frank, R.J. Chalkley, X. Fang, J.C. Trinidad, P. Baker, A.L. Burlingame, and M.A. Matthay, Impact of low and high tidal volumes on the rat alveolar epithelial type II cell proteome. Am J Respir Crit Care Med, 2007. 175(10): p. 1006-13. [Pubmed]
 Chalkley, R.J., P.R. Baker, K.F. Medzihradszky, A.J. Lynn, and A.L. Burlingame, In-depth Analysis of Tandem Mass Spectrometry Data from Disparate Instrument Types. Mol Cell Proteomics, 2008. 7(12): p. 2386-98. [Pubmed]
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 Chalkley, R.J., P.R. Baker, L. Huang, K.C. Hansen, N.P. Allen, M. Rexach, and A.L. Burlingame, Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-of-flight mass spectrometer: II. New developments in Protein Prospector allow for reliable and comprehensive automatic analysis of large datasets. Mol Cell Proteomics, 2005. 4(8): p. 1194-1204. [Pubmed]
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