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Biomedical subjects

J Patrick Fitch

Publications and source records attributed to J Patrick Fitch.

10 recordsLinked to original sources
PubMed2005

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.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2005

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.

Bacterial Proteins↗
PubMed2004

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.

Adenosine Triphosphatases↗
PubMed2004

Linear fuzzy gene network models obtained from microarray data by exhaustive search.

BACKGROUND: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling. RESULTS: We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes. CONCLUSION: Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems.

Artificial Intelligence↗
PubMed2004

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.

Bacterial Proteins↗
PubMed2004

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.

Adult↗
PubMed2003

Technology challenges in responding to biological or chemical attacks in the civilian sector.

Increasingly sophisticated technologies are needed for counterterrorism responses to biological and chemical warfare agents. Recently developed detection and identification systems are characterized by increased sensitivity, greater automation, and fewer false alarms. Attempts are also under way to reduce the cost and complexity of field-deployable systems. A broad range of decontamination reagents for equipment and personnel is emerging, but decontamination of large buildings, inaccessible spaces, and sensitive equipment remains problematic.

Automation↗
PubMed2002

A quantitative model of human DNA base excision repair. I. Mechanistic insights.

Base excision repair (BER) is a multistep process involving the sequential activity of several proteins that cope with spontaneous and environmentally induced mutagenic and cytotoxic DNA damage. Quantitative kinetic data on single proteins of BER have been used here to develop a mathematical model of the BER pathway. This model was then employed to evaluate mechanistic issues and to determine the sensitivity of pathway throughput to altered enzyme kinetics. Notably, the model predicts considerably less pathway throughput than observed in experimental in vitro assays. This finding, in combination with the effects of pathway cooperativity on model throughput, supports the hypothesis of cooperation during abasic site repair and between the apurinic/apyrimidinic (AP) endonuclease, Ape1, and the 8-oxoguanine DNA glycosylase, Ogg1. The quantitative model also predicts that for 8-oxoguanine and hydrolytic AP site damage, short-patch Polbeta-mediated BER dominates, with minimal switching to the long-patch subpathway. Sensitivity analysis of the model indicates that the Polbeta-catalyzed reactions have the most control over pathway throughput, although other BER reactions contribute to pathway efficiency as well. The studies within represent a first step in a developing effort to create a predictive model for BER cellular capacity.

DNA Repair↗
PubMed2002

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.

Bacterial Proteins↗