Sandra L. McCutchen-Maloney

Proteomic Characterization of Yersinia pestis Virulence

The Yersinia pestis proteome was studied as a function of temperature and calcium by two-dimensional differential gel electrophoresis. Over 4,100 individual protein spots were detected, of which hundreds were differentially expressed. A total of 43 differentially expressed protein spots, representing 24 unique proteins, were identified by mass spectrometry. Differences in expression were observed for several virulence-associated factors, including catalase-peroxidase (KatY), murine toxin (Ymt), plasminogen activator (Pla), and F1 capsule antigen (Caf1), as well as several putative virulence factors and membrane-bound and metabolic proteins. Differentially expressed proteins not previously reported to contribute to virulence are candidates for more detailed mechanistic studies, representing potential new virulence determinants.

Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder™

MOTIVATION The DeCyder software (GE Healthcare) is the current state-of-the-art commercial product for the analysis of two-dimensional difference gel electrophoresis (2D DIGE) experiments. Analyses complementing DeCyder are suggested by incorporating recent advances from the microarray data analysis literature. A case study on the effect of smallpox vaccination is used to compare the results obtained from DeCyder with the results obtained by applying moderated t-tests adjusted for multiple comparisons to DeCyder output data that was additionally normalized. RESULTS Application of the more stringent statistical tests applied to the normalized 2D DIGE data decreased the number of potentially differentially expressed proteins from the number obtained from DeCyder and increased the confidence in detecting differential expression in human clinical studies.

Host–pathogen interactions: a proteomic view

Host–pathogen interactions reflect the balance of host defenses and pathogen virulence mechanisms. Advances in proteomic technologies now afford opportunities to compare protein content between complex biologic systems ranging from cells to animals and clinical samples. Thus, it is now possible to characterize host–pathogen interactions from a global proteomic view. Most reports to date focus on cataloging protein content of pathogens and identifying virulence-associated proteins or proteomic alterations in host response. A more in-depth understanding of host–pathogen interactions has the potential to improve our mechanistic understanding of pathogenicity and virulence, thereby defining novel therapeutic and vaccine targets. In addition, proteomic characterization of the host response can provide pathogen-specific host biomarkers for rapid pathogen detection and characterization, as well as for early and specific detection of infectious diseases. A review of host–pathogen interactions focusing on proteomic analyses of both pathogen and host will be presented. Relevant genomic studies and host model systems will be also be discussed.

Statistical Analysis of Variation in the Human Plasma Proteome

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling was used to remove dye and gel variability. Mixed-effects modeling was then used to quantitate the sources of proteomic variation. The subject-to-subject variation represented the largest variance component, while the time-within-subject variation was comparable to the experimental variation found in a previous technical variability study where one human plasma sample was processed eight times in parallel and each was then analyzed by 2-D DIGE in triplicate. Here, 21 protein spots had larger than 50% CV, suggesting that these proteins may not be appropriate as biomarkers and should be carefully scrutinized in future studies. Seventy-eight protein spots showing differential protein levels between different individuals or individual collections were identified by mass spectrometry and further characterized using hierarchical clustering. The results present a first step toward understanding the complexity of longitudinal and individual variation in the human plasma proteome, and provide a baseline for improved biomarker discovery.

Serum Protein Profile Alterations in Hemodialysis Patients

Background: Serum protein profiling patterns can reflect the pathological state of a patient and therefore may be useful for clinical diagnostics. Here, we present results from a pilot study of proteomic expression patterns in hemodialysis patients designed to evaluate the range of serum proteomic alterations in this population. Methods: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was used to analyze serum obtained from patients on periodic hemodialysis treatment and healthy controls. Serum samples from patients and controls were first fractionated into six eluants on a strong anion exchange column, followed by application to four array chemistries representing cation exchange, anion exchange, metal affinity and hydrophobic surfaces. A total of 144 SELDI-TOF-MS spectra were obtained from each serum sample. Results: The overall profiles of the patient and control samples were consistent and reproducible. However, 30 well-defined protein differences were observed; 15 proteins were elevated and 15 were decreased in patients compared to controls. Serum from 1 patient exhibited novel protein peaks suggesting possible additional changes due to a secondary disease process. Conclusion: SELDI-TOF-MS demonstrated consistent serum protein profile differences between patients and controls. Similarity in protein profiles among dialysis patients suggests that patient physiological responses to end-stage renal disease and/or dialysis therapy have a major effect on serum protein profiles.

Domain Mapping of the DNA Binding, Endonuclease, and ERCC1 Binding Properties of the Human DNA Repair Protein XPF†

During nucleotide excision repair, one of the two incisions necessary for removal of a broad spectrum of DNA adducts is made by the human XPF/ERCC1 protein complex. To characterize the biochemical function of XPF, we have expressed and purified the independent 104 kDa recombinant XPF protein from E. coli and determined that it is an endonuclease and can bind DNA in the absence of the ERCC1 subunit. Endonuclease activity was also identified in a stable 70 kDa proteolysis fragment of XPF obtained during protein expression, indicating an N-terminal catalytic domain. Sequence homology and secondary structure predictions indicated a second functional domain at the C-terminus of XPF. To investigate the significance of the two predicted domains, a series of XPF deletion fragments spanning the entire protein were designed and examined for DNA binding, endonuclease activity, and ERCC1 subunit binding. Our results indicate that the N-terminal 378 amino acids of XPF are capable of binding and hydrolyzing DNA, while the C-terminal 214 residues are capable of binding specifically to ERCC1. We propose that the N-terminal domain of XPF contributes to the junction-specific endonuclease activity observed during DNA repair and recombination events. In addition, evidence presented here suggests that the C-terminal domain of XPF is responsible for XPF/ERCC1 complex formation. A working model for the XPF protein is presented illustrating the function of XPF in the nucleotide excision pathway and depicting the two functional domains interacting with DNA and ERCC1.

Cluster analysis of host cytokine responses to biodefense pathogens in a whole blood ex vivo exposure model (WEEM)

BackgroundRapid detection and therapeutic intervention for infectious and emerging diseases is a major scientific goal in biodefense and public health. Toward this end, cytokine profiles in human blood were investigated using a human whole blood ex vivo exposure model, called WEEM.ResultsSamples of whole blood from healthy volunteers were incubated with seven pathogens including Yersinia pseudotuberculosis, Yersinia enterocolitica, Bacillus anthracis, and multiple strains of Yersinia pestis, and multiplexed protein expression profiling was conducted on supernatants of these cultures with an antibody array to detect 30 cytokines simultaneously. Levels of 8 cytokines, IL-1α, IL-1β, IL-6, IL-8, IL-10, IP-10, MCP-1 and TNFα, were significantly up-regulated in plasma after bacterial exposures of 4 hours. Statistical clustering was applied to group the pathogens based on the host response protein expression profiles. The nearest phylogenetic neighbors clustered more closely than the more distant pathogens, and all seven pathogens were clearly differentiated from the unexposed control. In addition, the Y. pestis and Yersinia near neighbors were differentiated from the B. anthracis strains.ConclusionsCluster analysis, based on host response cytokine profiles, indicates that distinct patterns of immunomodulatory proteins are induced by the different pathogen exposures and these patterns may enable further development into biomarkers for diagnosing pathogen exposure.