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

BACKGROUND: Rapid 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. RESULTS: Samples 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-1ß, 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. CONCLUSIONS: Cluster 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.

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.

Polynucleotide phosphorylase independently controls virulence factor expression levels and export in Yersinia spp.

Previously, it was shown that optimal functioning of the Yersinia type III secretion system (T3SS) in cell culture infection assays requires the exoribonuclease polynucleotide phosphorylase (PNPase) and that normal T3SS activity could be restored in the Deltapnp strains by expressing just the approximately 70-aa S1 RNA-binding domain of PNPase. Here, it is shown that the Yersinia Deltapnp strain is less virulent in the mouse compared with the isogenic wild-type strain. To begin to understand what could be limiting T3SS activity in the absence of PNPase, T3SS-encoding transcripts and proteins in the YersiniaDeltapnp strains were analyzed. Surprisingly, it was found that the Deltapnp Yersinia strains possessed enhanced levels of T3SS-encoding transcripts and proteins compared with the wild-type strains. We then found that an S1 variant containing a disruption in its RNA-binding subdomain was inactive in terms of restoring normal T3SS activity. However, T3SS expression levels did not differ between Deltapnp strains expressing active and inactive S1 proteins, further showing that T3SS activity and expression levels, at least as related to PNPase and its S1 domain, are not linked. The results suggest that PNPase affects the expression and activity of the T3SS by distinct mechanisms and that the S1-dependent effect on T3SS activity involves an RNA intermediate.

Biomarker candidate identification in Yersinia pestis using organism-wide semiquantitative proteomics.

The accurate mass and time tag mass spectrometry method and clustering analysis were used to compare the abundance change of 992 Yersinia pestis proteins under four contrasting growth conditions (26 and 37 degrees C, with or without Ca2+) that mimicked growth states in either a flea vector or mammalian host. Eighty-nine proteins were observed to have similar abundance change profiles to 29 known virulence associated proteins, providing identification of additional biomarker candidates. Eighty-seven hypothetical proteins, which clustered into 5 distinct clusters of like-protein abundance change, were identified as unique biomarkers related specifically to growth condition.

Statistical analysis of the experimental variation in the proteomic characterization of human plasma by two-dimensional difference gel electrophoresis.

The complexity of human plasma presents a number of challenges to the efficient and reproducible proteomic analysis of differential expression in response to disease. Before individual variation and disease-specific protein biomarkers can be identified from human plasma, the experimental variability inherent in the protein separation and detection techniques must be quantified. We report on the variation found in two-dimensional difference gel electrophoresis (2-D DIGE) analysis of human plasma. Eight aliquots of a human plasma sample were subjected to top-6 highest abundant protein depletion and were subsequently analyzed in triplicate for a total of 24 DIGE samples on 12 gels. Spot-wise standard deviation estimates indicated that fold changes greater than 2 can be detected with a manageable number of replicates in simple ANOVA experiments with human plasma. Mixed-effects statistical modeling quantified the effect of the dyes, and segregated the spot-wise variance into components of sample preparation, gel-to-gel differences, and random error. The gel-to-gel component was found to be the largest source of variation, followed by the sample preparation step. An improved protocol for the depletion of the top-6 high-abundance proteins is suggested, which, along with the use of statistical modeling and future improvements in gel quality and image processing, can further reduce the variation and increase the efficiency of 2-D DIGE proteomic analysis of human plasma.

An integrated proteomic workflow for two-dimensional differential gel electrophoresis and robotic spot picking.

New technologies have advanced the field of proteomics, and a number of companies have developed innovative platforms to drive this research. However, significant challenges are often encountered when trying to integrate complementary technologies from multiple manufacturers. We have developed a software and hardware solution to integrate the Ettan two-dimensional difference gel electrophoresis (2-D DIGE) system (GE Healthcare) with the Investigator ProPic spot picking robot (Genomic Solutions). We have analyzed protein sample preparations from bacterial and mammalian sources to demonstrate a new workflow with increased throughput for gel-based proteomics.

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.

Subcellular proteomic analysis of host-pathogen interactions using human monocytes exposed to Yersinia pestis and Yersinia pseudotuberculosis.

Yersinia pestis, the etiological agent of plague, is of concern to human health both from an infectious disease and a biodefense perspective. While Y. pestis and Yersinia pseudotuberculosis share more than 90% DNA homology, they have significantly different clinical manifestations. Plague is often fatal if untreated, yet Y. pseudotuberculosis causes severe intestinal distress but is rarely fatal. A better understanding of host response to these closely related pathogens may help explain the different mechanisms of virulence and pathogenesis that result in such different clinical outcomes. The aim of this study was to characterize host protein expression changes in human monocyte U937 cells after exposure to Y. pestis and Y. pseudotuberculosis. In order to gain global proteomic coverage of host response, proteins from cytoplasmic, nuclear and membrane fractions of host cells were studied by two-dimensional differential gel electrophoresis and relative protein expression differences were quantitated. Differentially expressed proteins, with at least 1.5-fold expression changes and p values of 0.01 or less, were identified by mass spectrometry including matrix-assisted laser desorption/ionization-MS or liquid chromatography tandem mass spectrometry. With these criteria, differential expression was detected in 16 human proteins after Y. pestis exposure and 13 human proteins after Y. pseudotuberculosis exposure, of which only two of the differentially expressed proteins identified were shared between the two exposures. Proteins identified in this study are reported to be involved in a wide spectrum of cellular functions and host defense mechanisms including apoptosis, cytoskeletal rearrangement, protein synthesis and degradation, DNA replication and transcription, metabolism, protein folding, and cell signaling. Notably, the differential expression patterns observed can distinguish the two pathogen exposures from each other and from unexposed host cells. The functions of the differentially expressed proteins identified provide insight on the different virulence and pathogenic mechanisms of Y. pestis and Y. pseudotuberculosis.

Proteomic analysis of human serum by two-dimensional differential gel electrophoresis after depletion of high-abundant proteins.

Two-dimensional differential gel electrophoresis (2-D DIGE) was used to analyze human serum following the removal of albumin and five other high-abundant serum proteins. After protein removal, serum was analyzed by SDS-PAGE as a preliminary screen, and significant differences between four high-abundant protein removal methods were observed. Antibody-based albumin removal and high-abundant protein removal methods were found to be efficient and specific. To further characterize serum after protein removal, 2-D DIGE was employed, enabling multiplexed analysis of serum through the use of three fluorescent protein dyes. Comparison between crude serum and serum after removal of high-abundant proteins clearly illustrates an increase in the number of lower abundant protein spots observed. Approximately 850 protein spots were detected in crude serum whereas over 1500 protein spots were exposed following removal of six high-abundant proteins, representing a 76% increase in protein spot detection. Several proteins that showed a 2-fold increase in intensity after depletion of high-abundant proteins, as well as proteins that were depleted during abundant protein removal methods, were further characterized by mass spectrometry. This series of experiments demonstrates that high-abundant protein removal, combined with 2-D DIGE, is a practical approach for enriching and characterizing lower abundant proteins in human serum. Consequently, this methodology offers advances in proteomic characterization, and therefore, in the identification of biomarkers from human serum.

Real-time characterization of virulence factor expression in Yersinia pestis using a GFP reporter system.

A real-time reporter system was developed to monitor the thermal induction of virulence factors in Yersinia pestis, the etiological agent of plague. The reporter system consists of a plasmid in Y. pestis in which the expression of green fluorescent protein (GFP) is under the control of the promoters for six virulence factors, yopE, sycE, yopK, yopT, yscN, and lcrE yopN, which are all components of the Type III secretion virulence mechanism of Y. pestis. Induction of the expression of these genes in vivo was determined by the increase in fluorescence intensity of GFP in real time, in 96-well format. Different basal levels of expression at 26 degrees C were observed for the Y. pestis promoters. Expressed as percentages of the level measured for the lac promoter (positive control), the basal expression levels before temperature shift were: yopE (15%), sycE (15%), yopK (13%), yopT (4%), lcrE (3.3%), and yscN (0.8%). Following the shift in temperature from 26 to 37 degrees C, the rates of expression of these genes increased with the yopE reporter showing the strongest degree of induction. The rates of induction of the other virulence factors after the temperature, expressed as percentages of yopE induction, were: yopK (57%), sycE (9%), yscN (3%), lcrE (3%), and yopT (2%). The thermal induction of each of these promoter fusions was repressed by calcium, and the ratios of the initial rates of thermal induction without calcium supplementation compared to the rate with calcium supplementation were: yopE (11-fold), yscN (7-fold), yopK (6-fold), lcrE (3-fold), yopT (2-fold), and sycE (1-fold). This work demonstrates a novel approach to quantify gene induction and provides a method to rapidly determine the effects of external stimuli on expression of Y. pestis virulence factors in real time, in living cells, as a means to characterize virulence determinants.

Proteomic characterization of host response to Yersinia pestis and near neighbors.

Host-pathogen interactions result in protein expression changes within both the host and the pathogen. Here, results from proteomic characterization of host response following exposure to Yersinia pestis, the causative agent of plague, and to two near neighbors, Yersinia pseudotuberculosis and Yersinia enterocolitica, are reported. Human monocyte-like cells were chosen as a model for macrophage immune response to pathogen exposure. Two-dimensional electrophoresis followed by mass spectrometry was used to identify host proteins with differential expression following exposure to these three closely related Yersinia species. This comparative proteomic characterization of host response clearly shows that host protein expression patterns are distinct for the different pathogen exposures, and contributes to further understanding of Y. pestis virulence and host defense mechanisms. This work also lays the foundation for future studies aimed at defining biomarkers for presymptomatic detection of plague.

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.

Protein identification by liquid chromatography-mass spectrometry using retention time prediction.

Liquid chromatography has been coupled with mass spectrometry to improve the dynamic range and to reduce the complexity of sample introduced to the mass spectrometer at any given time. The chromatographic separation also provides information on the analytes, such as peptides in enzymatic digests of proteins; information that can be used when identifying the proteins by peptide mass fingerprinting. This paper discusses a recently introduced method based on retention time prediction to extract information from chromatographic separations and the applications of this method to protein identification in organisms with small and large genomes.

A rapid method to capture and screen for transcription factors by SELDI mass spectrometry.

A novel method to screen for transcription factors binding to promoter DNA sequences has been developed using DNA chip surfaces and mass spectrometry. This technique was demonstrated with Escherichia coli lac repressor, LacI. The consensus promoter binding sequence for LacI and a scrambled version of the same DNA sequence were prepared on two affinity chip surfaces. Total E. coli protein lysate was applied to the two surfaces. A 38.2 kDa protein, as detected by SELDI-MS, was captured on the chip surface containing the binding sequence for LacI but not on the surface containing the scrambled sequence. The protein was identified following one-step, small-scale affinity capture and peptide mapping. Subsequent database searches identified the 38.2 kDa protein as the lac repressor of E. coli. We discuss application of DNA chip affinity capture to characterize transcription factors and to screen for differences in cellular regulatory networks.

Characterization of transcription factors by mass spectrometry and the role of SELDI-MS.

Over the last decade, much progress has been made in the field of biological mass spectrometry, with numerous advances in technology, resolution, and affinity capture. The field of genomics has also been transformed by the sequencing and characterization of entire genomes. Some of the next challenges lie in understanding the relationship between the genome and the proteome, the protein complement of the genome, and in characterizing the regulatory processes involved in progressing from gene to functional protein. In this new age of proteomics, development of mass spectrometry methods to characterize transcription factors promises to add greatly to our understanding of regulatory networks that govern expression. However, at this time, regulatory networks of transcription factors are mostly uncharted territory. In this review, we summarize the latest advances in characterization of transcription factors by mass spectrometry including affinity capture, identification of complexes of DNA-binding proteins, structural characterization, determination of protein-DNA and protein-protein interactions, assessment of modification sites and metal binding, studies of functional activity, and the latest chip technologies that use SELDI-MS that allow the rapid capture and identification of transcription factors.