The Proteomics Section of the Systems Technologies Core (STC) is led by Dr. Taufika Islam Williams. Dr. Islam Williams is the Proteomics Navigator for the CHHE and all requests for consultation, support and services must go through the STC portal https://labs.ncsu.edu/link/SelectLab/STC for CHHE Project Requests. Please watch this short video on how to access and use the STC portal.
All CHHE Full Members are eligible for the CHHE’s STC Voucher Program. Under this program, CHHE provides 50% of the costs up to $15K/Full member for $30K STC services (link listed above).
Proteins are the vehicles of change in living organisms and proteomics is the large-scale determination of geneand cellular function at the protein level. As with many –OMIC fields, proteomics developed as significant technological advances led to the better characterization of all cellular molecules including the complete sequencing of several genomes. These advances further confirmed previous observations that the expressed phenotype is often more complicated than deciphering the genotype. For example, it is known that RNA levels are often a poor proxy for protein abundances. In addition, protein function is dependent on post translational modifications (PTMs) that can regulate protein activity and binding partners. This dynamic information is not available from transcriptome data, but is essential for understanding disease mechanisms and cellular homeostasis. To date, the most powerful method for protein identification is undoubtedly mass spectrometry owing to its high sensitivity, high dynamic range, and capability to achieve absolute molecular specificity.
The Aims of the Proteomic Section are:
Specific Aim 1: Provide expertise, guidance, and consultation on experimental design for innovative -omics technologies involving discovery and targeted proteomics.
Dr. Islam Williams will provide CHHE members with expertise in experimental design, sample collection, preparation, and analysis for successful implementation of proteomics research. The Proteomics Section enhances the ability of scientists working in the field of EHS to identify and capitalize on emerging opportunities in systems biology and the growing area of toxicoproteomics. Toxicoproteomics, a subfield of both proteomics and toxicogenomics, uses both global and targeted protein methodologies to identify and characterize critical proteins/complexes/pathways/receptors that are affected by, or respond to, chemical and environmental exposures. The Proteomics Section increases the impact of CHHE members’ research by: 1) correlating genome/epigenome studies with protein expression patterns; 2) discovering novel biomarkers of exposure in biological fluids; and 3) evaluating the impacts of exposure on key biological processes by characterizing protein expression, interaction, and modification using both in vitro cellular and in vivo animal models of exposure. Drs. Bereman and Islam Williams provide expertise in the types of proteomic experiments needed to meet the goals of each research project.
Specific Aim 2: Perform targeted and global -OMICS analyses with state-of-the-art instrumentation and resources via a highly trained and qualified team.
In general, the Proteomics Section employ the widely used and powerful bottom-up strategy for protein identification and quantification (relative and absolute). Briefly, protein samples are extracted from tissues, biological cells, or biological fluid and then prepared by protein denaturation, reduction of disulfide bonds, alkylation of free cysteines, and enzymatic digestion. Peptides are then purified via solid phase extraction and analyzed by LC MS/MS. Specific applications to explore include discovery and targeted proteomic studies. Examples of each include:
Applications in Discovery Proteomics
- Biomarkers for environmental exposures in biological fluids
- Determination of protein binding partners
- Global protein identification and relative quantification (e., shotgun proteomics)
- Protein identification from excised gel bands
Applications in Targeted Proteomics
- Relative quantification of peptide biomarkers of interest
- Protein specific PTM analysis (g., phosphorylation)
- Verification of siRNA knockdown experiments
- Absolute quantification using protein cleavage isotope dilution mass spectrometry (PC-IDMS)
Specific Aim 3: Perform and provide a seamless link to CHHE’s Environmental Data Science Group for training on analyses, advanced pathway mapping, data visualization and data storage.
Software, Data Analysis and Data Storage: METRIC provides access to multiple software packages for analyzing proteomics data, including: SAS JMP Pro v11.0 (for Design of Experiments), Mascot v2.5 (40 processor license), Proteome Discoverer 2.2, Scaffold 4.8, Biopharma 2.0, MaxQuant and Perseus, X-Caliber. Each software suite operates on an independent high-performance computer with a minimum of 4 cores. Data can also be transferred to Bioinformatics Research Center- and CHHE-supported servers and analyzed by CHHE Environmental Data Science Group (EDSG) which brings together five bioinformaticians/biostatisticians. The EDSG conducts informatics analyses of large data sets from in silico, in vitro, in vivo, and population studies to address important problems in EHS. Bioinformatic support is provided cost-free to CHHE Full members (see Bioinformatic Support section of IHSFC).
Ingenuity Pathway Analysis (IPA)
An IPA software license is purchased yearly by CHHE for access by all members and cores. IPA has broad adoption by the life science research community and is cited in thousands of articles for the analysis, integration, and interpretation of data derived from -omics experiments, such as RNA-seq, small RNA-seq, microarrays including miRNA and SNP, metabolomics, and proteomics. Mummichug in MetaboAnalyast and KEGG pathway analysis in Compound Discoverer are also used.
Visualization is vital to the analysis of large datasets and multi-omic integration. In partnership with the EDSG (see Data Visualization section of IHSFC) members are directed to personnel and software to generate appropriate data graphics.