Washington Proteomics and Bioinformatics Core
The overall goals of the Proteomics and Bioinformatics Core are to provide the powerful tools of modern mass spectrometry and complex data set analysis to Diabetes Research Center investigators to permit structural identification and quantitation of proteins involved in diabetes and its complications in support of both basic as well as translational and clinical studies.
To accomplish these goals the Proteomics and Bioinformatics Core provides the following to Diabetes Research Center affiliate investigators:
- Mass spectrometric (MS) analyses for Diabetes Research Center investigators, such as quantifying target analytes and obtaining spectra for structural identification of proteins. Technologies include electrospray ionization tandem mass spectrometry (ESI-MS/MS).
- Targeted quantitative assays of specific protein analytes relevant to diabetes in support of clinical and translational studies.
- Development of new MS methods for structural identification or quantification of biomolecules involved in the pathogenesis of diabetes and its complications, risk factors, or treatment.
- Training in principles of MS and LCMS and data analysis and interpretation.
- Bioinformatics support for analyzing and interpreting proteomic data sets and for integrating them with Gene Ontology, protein-protein interaction databases, and pathway analysis.
- Computational and bioinformatics support and training for transcriptomics (e.g., RNA-seq) and metabolomics data, including differential feature analysis, functional enrichment and pathway analysis, as well as gene product interaction network analysis.
- A central facility for data storage, dissemination, and sharing.
Proteins of interest are identified by a variety of factors, including changes in relative abundance or alterations in apparent pI (which suggests a post-translational modification, such as phosphorylation). Proteins are immunostained and isolated, digested enzymatically, and identified by LC tandem mass spectrometric analysis (LC-ESI-MS/MS).
The shotgun proteomics analysis is available to the Diabetes Research Center affiliate investigators to provide in-depth global protein identification of simple as well as complex protein samples (protein complexes, cell lysates, cell secretome, biofluids, etc). wherein shotgun proteomics enzymatic digests of proteins are separated by liquid chromatography (LC) and subjected to electrospray ionization (ESI) and data-dependent MS/MS analysis. The peptides are identified by searching against a protein database.
Spectral counting and peptide ion intensity are alternative, label-free methods for quantifying relative protein abundance and will also be made available to the Diabetes Research Center affiliate investigator. Spectral counting sums all of the MS/MS spectra observed for peptides derived from a single protein. Because abundant proteins are more likely to be identified during data-dependent MS/MS scanning, spectral counting has the potential to quantify protein levels. Spectral counting is a useful statistic for assessing relative protein abundance in biological samples.
Data Independent Analysis
Limitations of Data Dependent Analysis (DDA) traditionally used for shotgun proteomics are the stochastic selection of peptides for MS/MS analysis and the fact that spectral counting provides imprecise results at low concentrations. In contrast, targeted methods like Parallel Reaction Monitoring require an a-priori list of target proteins and corresponding peptides to be included in the target list and , if the list of target proteins is not known, then a separate LC-MS/MS analysis for the PRM acquisition is required in addition to the DDA analysis. To alleviate these limitations, Data-Independent Analysis (also referred to as SWATH) has been developed where the MS/MS spectra are sequentially acquired on swaths of m/z range (e.g. each 5 m/z wide) covering the full mass range, without prior selection of precursors. The data analysis benefits from high resolution spectra (mass accuracy 1-5 ppm) of the precursor and fragment ions and allows deconvolution of the individual precursor MS/MS spectra from coelution profiles of the precursors and fragments. DIA provides both qualitative as well as quantitative information in a single LC-MS/MS analysis, providing meaningful data, particularly for samples with limited availability. QPFC has adapted this technology and it is now available for Diabetes Research Center affiliates.
Identifying Differential Protein Expression
Parallel reaction monitoring (PRM)
For highly sensitive quantitative analysis, targeted methods still outperform even the DIA. To facilitate the rapid transition from shotgun proteomics to quantitative assessment of differential protein expression of specific proteins, the Quantitative and Functional Proteomics Core employs PRM, wherein a single precursor peptide ion (from selected peptides of a target protein, i.e. identified in shotgun proteomics analysis) is monitored to provide selective and specific quantification without need for time-consuming method development. This tandem MS technique greatly reduces chemical noise, markedly improving the signal-to-noise ratio and thereby sensitivity. Furthermore, the instrument’s duty cycle is almost entirely used to monitor the specific peptide ions, further increasing sensitivity.
Data analysis is facilitated by the Skyline software suite, which is used to visualize spectra and build scheduled PRM methods directly by predicting the retention time of previously uncharacterized peptides and process data from DIA analysis. A state-of-the-art peak-finding algorithm in Skyline then provides rapid and reliable analysis of the acquired PRM and DIA data. Skyline also contains a powerful set of tools that can determine which peak within a complex mixture is formed from a peptide of interest. To do this, Skyline uses the predicted retention time and a new scoring algorithm to compare the rank order of product ion intensities from co-varying transitions with a product ion spectrum stored in a spectrum library. The software provides full support for using standard peptide and stable isotope-labeled peptide internal standards.
Computer Cluster, Data Storage and Integration
The Core has made available to the Diabetes Research Center affiliate investigators use of a 4-multicore-node computer cluster (102 CPU), which is used to run the Comet and Xtandem search engines required for database searching. A user-friendly relational database system, Labkey Server (Labkey, Seattle), is used to store and analyze data and facilitate bioinformatics analysis and encapsulates user authentication and project management features as well as daily backups. It also allows investigators secure access the Core’s proteomic data.
Clinical Protein Assays
Clinical quality protein assays are provided to Affiliate Investigators. These assays include the clinical assays run for routine patient care (typically run on automated clinical analyzers), novel quantitative targeted LC-MS/MS assays that are run in a CLIA environment, and validated research immunoassays (most commonly in a 96-well plate ELISA format). Quality control is monitored continuously to provide the most accurate results possible. Method development and validation of assays not currently on the menu is available, contact Core Directors for more information.
Other “omics" platforms
n addition to the described proteomics data analysis, the Core has expertise in analyzing gene expression data (microarray, RNA-seq) and metabolomics data (targeted and untargeted). These services include differential feature identification, pathway and functional enrichment analysis, cluster analysis and PCA, data visualization, as well as gene product interaction network analysis. These bioinformatics methods can complement the proposed proteomics experiments and potentially be integrated across ”omics” platforms. Furthermore, training of interested staff, students, and faculty in these approaches is offered.
For the proteomics analysis the Core utilizes instruments its own instruments as well as instruments accessible at the UW School of Medicine Proteomics Resource, a central walk-up facility located at SLU, which provides UW investigators access to the state-of-the-art instrumentation.
- Waters QTOF Premier with nanoelectrospray ionization and an Waters nanoAcquity UPLC for protein analysis
- Two differential ion mobility analyzer (TSI) for analysis of particle concentration and protein size and concentration measurements.
- Thermo Q Exactive Plus
- Waters TQS triple quadrupole system
- Beckman Coulter DxI immunochemistry analyzer
- Beckman Coulter AU5812 immunoturbidometric analyzer
- IDS iSYS immunoassay system
- Thermo Exploris480
- Thermo Fusion Lumos tribrid instrument
- Thermo LTQ Fusion tribrid quadrupole-orbitrap-ion trap instrument with ETD
- Thermo Q Exactive Plus
- Thermo TSQ Altis
- Thermo TSQ Vantage
All mass spectrometers are fitted with Waters nanoACQUITY UPLC systems.