REGULATION OF TOXIN SYNTHESIS BY CLOSTRIDIUM DIFFICILE

Clostridium difficile is the leading definable cause of nosocomial diarrhea worldwide due to its virulence, multi-drug resistance, spore-forming ability, and environmental persistence. The incidence of C. difficile infection (CDI) has been increasing exponentially in the last decade. Virulent strains of C. difficile produce either toxin A and/or toxin B, which are essential for the pathogenesis of this bacterium. Current methods for diagnosing CDI are mostly qualitative tests that detect the bacterium, the toxins, or the toxin genes. These methods do not differentiate virulent C. difficile strains that produce active toxins from non-virulent strains that do not produce toxins or produce inactive toxins. Based on the knowledge that C. difficile toxins A and B cleave a substrate that is stereochemically similar to the native substrate of the toxins, uridine diphosphoglucose, a quantitative, cost-efficient assay, the Cdifftox activity assay, was developed to measure C. difficile toxin activity. The concept behind the activity assay was modified to develop a novel, rapid, sensitive, and specific assay for C. difficile toxins in the form of a selective and differential agar plate culture medium, the Cdifftox Plate assay (CDPA). This assay combines in a single step the specific identification of C. difficile strains and the detection of active toxin(s). The CDPA was determined to be extremely accurate (99.8% effective) at detecting toxin-producing strains based on the analysis of 528 C. difficile isolates selected from 50 tissue culture cytotoxicity assay-positive clinical stool samples. This new assay advances and improves the culture methodology in that only C. difficile strains will grow on this medium and virulent strains producing active toxins can be differentiated from non-virulent strains. This new method reduces the time and effort required to isolate and confirm toxin-producing C. difficile strains and provides a clinical isolate for antibiotic susceptibility testing and strain typing. The Cdifftox activity assay was used to screen for inhibitors of toxin activity. Physiological levels of the common human conjugated bile salt, taurocholate, was found to inhibit toxin A and B in vitro activities. When co-incubated ex vivo with purified toxin B, taurocholate protected Caco-2 colonic epithelial cells from the damaging effects of the toxin. Furthermore, using a caspase-3 detection assay, taurocholate reduced the extent of toxin B-induced Caco-2 cell apoptosis. These results suggest that bile salts can be effective in protecting the gut epithelium from C. difficile toxin damage, thus, the delivery of physiologic amounts of taurocholate to the colon, where it is normally in low concentration, could be useful in CDI treatment. These findings may help to explain why bile rich small intestine is spared damage in CDI, while the bile salt poor colon is vulnerable in CDI. Toxin synthesis in C. difficile occurs during the stationary phase, but little is known about the regulation of these toxins. It was hypothesized that C. difficile toxin synthesis is regulated by a quorum sensing mechanism. Two lines of evidence supported this hypothesis. First, a small (KDa), diffusible, heat-stable toxin-inducing activity accumulates in the medium of high-density C. difficile cells. This conditioned medium when incubated with low-density log-phase cells causes them to produce toxin early (2-4 hrs instead of 12-16 hrs) and at elevated levels when compared with cells grown in fresh medium. These data suggested that C. difficile cells extracellularly release an inducing molecule during growth that is able to activate toxin synthesis prematurely and demonstrates for the first time that toxin synthesis in C. difficile is regulated by quorum signaling. Second, this toxin-inducing activity was partially purified from high-density stationary-phase culture supernatant fluid by HPLC and confirmed to induce early toxin synthesis, even in C. difficile virulent strains that over-produce the toxins. Mass spectrometry analysis of the purified toxin-inducing fraction from HPLC revealed a cyclic compound with a mass of 655.8 Da. It is anticipated that identification of this toxin-inducing compound will advance our understanding of the mechanism involved in the quorum-dependent regulation of C. difficile toxin synthesis. This finding should lead to the development of even more sensitive tests to diagnose CDI and may lead to the discovery of promising novel therapeutic targets that could be harnessed for the treatment C. difficile infections.

Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression

The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material.

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Development of combined micro -preparation, separation, and mass spectrometry methods and application in the microdialysis study of neuropeptide metabolism

Two sets of mass spectrometry-based methods were developed specifically for the in vivo study of extracellular neuropeptide biochemistry. First, an integrated micro-concentration/desalting/matrix-addition device was constructed for matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) to achieve attomole sensitivity for microdialysis samples. Second, capillary electrophoresis (CE) was incorporated into the above micro-liquid chromatography (LC) and MALDI MS system to provide two-dimensional separation and identification (i.e. electrophoretic mobility and molecular mass) for the analysis of complex mixtures. The latter technique includes two parts of instrumentation: (1) the coupling of a preconcentration LC column to the inlet of a CE capillary, and (2) the utilization of a matrix-precoated membrane target for continuous CE effluent deposition and for automatic MALDI MS analysis (imaging) of the CE track.^ Initial in vivo data reveals a carboxypeptidase A (CPA) activity in rat brain involved in extracellular neurotensin metabolism. Benzylsuccinic acid, a CPA inhibitor, inhibited neurotensin metabolite NT1-12 formation by 70%, while inhibitors of other major extracellular peptide metabolizing enzymes increased NT1-12 formation. CPA activity has not been observed in previous in vitro experiments. Next, the validity of the methodology was demonstrated in the detection and structural elucidation of an endogenous neuropeptide, (L)VV-hemorphin-7, in rat brain upon ATP stimulation. Finally, the combined micro-LC/CE/MALDI MS was used in the in vivo metabolic study of peptide E, a mu-selective opioid peptide with 25 amino acid residues. Profiles of 88 metabolites were obtained, their identity being determined by their mass-to-charge ratio and electrophoretic mobility. The results indicate that there are several primary cleavage sites in vivo for peptide E in the release of its enkephalin-containing fragments. ^