Faculty Bibliography

BACKGROUND: Proteomics research is enabled with the high-throughput technologies, but our ability to identify expressed proteome is limited in small samples. The coverage and consistency of proteome expression are critical problems in proteomics. Here, we propose pathway analysis and combination of microproteomics and transcriptomics analyses to improve mass-spectrometry protein identification from small size samples. RESULTS: Multiple proteomics runs using MCF-7 cell line detected 4,957 expressed proteins. About 80% of expressed proteins were present in MCF-7 transcripts data; highly expressed transcripts are more likely to have expressed proteins. Approximately 1,000 proteins were detected in each run of the small sample proteomics. These proteins were mapped to gene symbols and compared with gene sets representing canonical pathways, more than 4,000 genes were extracted from the enriched gene sets. The identified canonical pathways were largely overlapping between individual runs. Of identified pathways 182 were shared between three individual small sample runs. CONCLUSIONS: Current technologies enable us to directly detect 10% of expressed proteomes from small sample comprising as few as 50 cells. We used knowledge-based approaches to elucidate the missing proteome that can be verified by targeted proteomics. This knowledge-based approach includes pathway analysis and combination of gene expression and protein expression data for target prioritization. Genes present in both the enriched gene sets (canonical pathways collection) and in small sample proteomics data correspond to approximately 50% of expressed proteomes in larger sample proteomics data. In addition, 90% of targets from canonical pathways were estimated to be expressed. The comparison of proteomics and transcriptomics data, suggests that highly expressed transcripts have high probability of protein expression. However, approximately 10% of expressed proteins could not be matched with the expressed transcripts.

Recommendations and outlines for standardization in biobanking processes are presented by a research team with long-term experience in clinical studies. These processes have important bearing on the use of samples in developing assays. These measurements are useful to document states of health and disease that are beneficial for academic research, commercial healthcare, drug development industry and government regulating agencies. There is a need for increasing awareness within proteomic and genomic communities regarding the basic concepts of collecting, storing and utilizing clinical samples. Quality control and sample suitability for analysis need to be documented and validated to ensure data integrity and establish contexts for interpretation of results. Standardized methods in proteomics and genomics are required to be practiced throughout the community allowing datasets to be comparable and shared for analysis. For example, sample processing of thousands of clinical samples, performed in 384 high-density sample tube systems in a fully automated workflow, preserves sample content and is presented showing validation criteria. Large studies will be accompanied by biological and molecular information with corresponding clinical records from patients and healthy donors. These developments position biobanks of human patient samples as an increasingly recognized major asset in disease research, future drug development and within patient care. BIOLOGICAL SIGNIFICANCE: The current manuscript is of major relevance to the proteomic and genomic fields, as it outlines the standardization aspects of biobanking and the requirements that are needed to run future clinical studies that will benefit the patients where OMICS science will play a major role. A global view of the field is given where best practice and conventional acceptances are presented along with ongoing large-scale biobanking projects. The authors represent broadly stakeholders that cover the academic, pharma, biotech and healthcare fields with extensive experience and deliveries. This contribution will be a milestone paper to the proteomic and genomic scientists to present data in the future that will have impact to the life science area. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.

AIMS: Cell function requires formation of molecular clusters localized to discrete subdomains. The composition of these interactomes, and their spatial organization, cannot be discerned by conventional microscopy given the resolution constraints imposed by the diffraction limit of light ( approximately 200-300 nm). Our aims were (i) Implement single-molecule imaging and analysis tools to resolve the nano-scale architecture of cardiac myocytes. (ii) Using these tools, to map two molecules classically defined as components 'of the desmosome' and 'of the gap junction', and defined their spatial organization. METHODS AND RESULTS: We built a set-up on a conventional inverted microscope using commercially available optics. Laser illumination, reducing, and oxygen scavenging conditions were used to manipulate the blinking behaviour of individual fluorescent reporters. Movies of blinking fluorophores were reconstructed to generate subdiffraction images at approximately 20 nm resolution. With this method, we characterized clusters of connexin43 (Cx43) and of 'the desmosomal protein' plakophilin-2 (PKP2). In about half of Cx43 clusters, we observed overlay of Cx43 and PKP2 at the Cx43 plaque edge. SiRNA-mediated loss of Ankyrin-G expression yielded larger Cx43 clusters, of less regular shape, and larger Cx43-PKP2 subdomains. The Cx43-PKP2 subdomain was validated by a proximity ligation assay (PLA) and by Monte-Carlo simulations indicating an attraction between PKP2 and Cx43. CONCLUSIONS: (i) Super-resolution fluorescence microscopy, complemented with Monte-Carlo simulations and PLAs, allows the study of the nanoscale organization of an interactome in cardiomyocytes. (ii) PKP2 and Cx43 share a common hub that permits direct physical interaction. Its relevance to excitability, electrical coupling, and arrhythmogenic right ventricular cardiomyopathy, is discussed.

Selected Reaction Monitoring (SRM) is a method of choice for accurate quantitation of low-abundance proteins in complex backgrounds. This strategy is, however, sensitive to interference from other components in the sample that have the same precursor and fragment masses as the monitored transitions. We present here an approach to detect interference by using the expected relative intensity of SRM transitions. We also designed an algorithm to automatically detect the linear range of calibration curves. These approaches were applied to the experimental data of Clinical Proteomic Tumor Analysis Consortium (CPTAC) Verification Work Group Study 7 and show that the corrected measurements provide more accurate quantitation than the uncorrected data.

Antibodies can protect from Plasmodium falciparum (Pf) infection and clinical malaria disease. However, in the absence of constant reexposure, serum immunoglobulin (Ig) levels rapidly decline and full protection from clinical symptoms is lost, suggesting that B cell memory is functionally impaired. We show at the single cell level that natural Pf infection induces the development of classical memory B cells (CM) and atypical memory B cells (AtM) that produce broadly neutralizing antibodies against blood stage Pf parasites. CM and AtM contribute to anti-Pf serum IgG production, but only AtM show signs of active antibody secretion. AtM and CM were also different in their IgG gene repertoire, suggesting that they develop from different precursors. The findings provide direct evidence that natural Pf infection leads to the development of protective memory B cell antibody responses and suggest that constant immune activation rather than impaired memory function leads to the accumulation of AtM in malaria. Understanding the memory B cell response to natural Pf infection may be key to the development of a malaria vaccine that induces long-lived protection.

We report progress assembling the parts list for chromosome 17 and illustrate the various processes that we have developed to integrate available data from diverse genomic and proteomic knowledge bases. As primary resources, we have used GPMDB, neXtProt, PeptideAtlas, Human Protein Atlas (HPA), and GeneCards. All sites share the common resource of Ensembl for the genome modeling information. We have defined the chromosome 17 parts list with the following information: 1169 protein-coding genes, the numbers of proteins confidently identified by various experimental approaches as documented in GPMDB, neXtProt, PeptideAtlas, and HPA, examples of typical data sets obtained by RNASeq and proteomic studies of epithelial derived tumor cell lines (disease proteome) and a normal proteome (peripheral mononuclear cells), reported evidence of post-translational modifications, and examples of alternative splice variants (ASVs). We have constructed a list of the 59 "missing" proteins as well as 201 proteins that have inconclusive mass spectrometric (MS) identifications. In this report we have defined a process to establish a baseline for the incorporation of new evidence on protein identification and characterization as well as related information from transcriptome analyses. This initial list of "missing" proteins that will guide the selection of appropriate samples for discovery studies as well as antibody reagents. Also we have illustrated the significant diversity of protein variants (including post-translational modifications, PTMs) using regions on chromosome 17 that contain important oncogenes. We emphasize the need for mandated deposition of proteomics data in public databases, the further development of improved PTM, ASV, and single nucleotide variant (SNV) databases, and the construction of Web sites that can integrate and regularly update such information. In addition, we describe the distribution of both clustered and scattered sets of protein families on the chromosome. Since chromosome 17 is rich in cancer-associated genes, we have focused the clustering of cancer-associated genes in such genomic regions and have used the ERBB2 amplicon as an example of the value of a proteogenomic approach in which one integrates transcriptomic with proteomic information and captures evidence of coexpression through coordinated regulation.

A first research development progress report of the Chromosome 19 Consortium with members from Sweden, Norway, Spain, United States, China and India, a part of the Chromosome-centric Human Proteome Project (C-HPP) global initiative, is presented ( http://www.c-hpp.org ). From the chromosome 19 peptide-targeted library constituting 6159 peptides, a pilot study was conducted using a subset with 125 isotope-labeled peptides. We applied an annotation strategy with triple quadrupole, ESI-Qtrap, and MALDI mass spectrometry platforms, comparing the quality of data within and in between these instrumental set-ups. LC-MS conditions were outlined by multiplex assay developments, followed by MRM assay developments. SRM was applied to biobank samples, quantifying kallikrein 3 (prostate specific antigen) in plasma from prostate cancer patients. The antibody production has been initiated for more than 1200 genes from the entire chromosome 19, and the progress developments are presented. We developed a dedicated transcript microarray to serve as the mRNA identifier by screening cancer cell lines. NAPPA protein arrays were built to align with the transcript data with the Chromosome 19 NAPPA chip, dedicated to 90 proteins, as the first development delivery. We have introduced an IT-infrastructure utilizing a LIMS system that serves as the key interface for the research teams to share and explore data generated within the project. The cross-site data repository will form the basis for sample processing, including biological samples as well as patient samples from national Biobanks.

ATP-sensitive K(+) (K(ATP) ) channels are expressed ubiquitously, but have diverse roles in various organs and cells. Their diversity can partly be explained by distinct tissue-specific compositions of four copies of the pore-forming inward rectifier potassium channel subunits (Kir6.1 and/or Kir6.2) and four regulatory sulfonylurea receptor subunits (SUR1 and/or SUR2). Channel function and/or subcellular localization also can be modified by the proteins with which they transiently or permanently interact to generate even more diversity. We performed a quantitative proteomic analysis of K(ATP) channel complexes in the heart, endothelium, insulin-secreting min6 cells (pancreatic beta-cell like), and the hypothalamus to identify proteins with which they interact in different tissues. Glycolysis is an overrepresented pathway in identified proteins of the heart, min6 cells, and the endothelium. Proteins with other energy metabolic functions were identified in the hypothalamic samples. These data suggest that the metabolo-electrical coupling conferred by K(ATP) channels is conferred partly by proteins with which they interact. A large number of identified cytoskeletal and trafficking proteins suggests endocytic recycling may help control K(ATP) channel surface density and/or subcellular localization. Overall, our data demonstrate that K(ATP) channels in different tissues may assemble with proteins having common functions, but that tissue-specific complex organization also occurs.

Mass Spectrometry (MS) is becoming a preferred method to identify class I and class II peptides presented on major histocompability complexes (MHC) on antigen presenting cells (APC). We describe a combined computational and MS approach to identify exogenous MHC II peptides presented on mouse spleen dendritic cells (DCs). This approach enables rapid, effective screening of a large number of possible peptides by a computer-assisted strategy that utilizes the extraordinary human ability for pattern recognition. To test the efficacy of the approach, a mixture of epitope peptide mimics (mimetopes) from HIV gag p24 sequence were added exogenously to Fms-like tyrosine kinase 3 ligand (Flt3L)-mobilized splenic DCs. We identified the exogenously added peptide, VDRFYKTLRAEQASQ, and a second peptide, DRFYKLTRAEQASQ, derived from the original exogenously added 15-mer peptide. Furthermore, we demonstrated that our strategy works efficiently with HIV gag p24 protein when delivered, as vaccine protein, to Flt3L expanded mouse splenic DCs in vitro through the DEC-205 receptor. We found that the same MHC II-bound HIV gag p24 peptides, VDRFYKTLRAEQASQ and DRFYKLTRAEQASQ, were naturally processed from anti-DEC-205 HIV gag p24 protein and presented on DCs. The two identified VDRFYKTLRAEQASQ and DRFYKLTRAEQASQ MHC II-bound HIV gag p24 peptides elicited CD4(+) T-cell mediated responses in vitro. Their presentation by DCs to antigen-specific T cells was inhibited by chloroquine (CQ), indicating that optimal presentation of these exogenously added peptides required uptake and vesicular trafficking in mature DCs. These results support the application of our strategy to identify and characterize peptide epitopes derived from vaccine proteins processed by DCs and thus has the potential to greatly accelerate DC-based vaccine development.