Biophysical and computational investigations into G-quadruplex structural polymorphism and interaction with small molecules.

In the cell, guanine-rich nucleic acids can self-assemble into unique four stranded tertiary structures known as G-quadruplexes. G-quadruplex formation in the telomere leads inhibits telomerase, an enzyme activated in cancer cells to maintain the telomere and allowing for cancer cells to achieve immortality. G-quadruplex formation in the promoters and 5’-untranslated regions regulates the expression of many oncogenes. Furthermore, G-quadruplex formation during cellular replication promotes genomic instability, a characteristic which enables tumor development. Because of their implication in cancer, G-quadruplex structures have emerged as attractive drug targets for anti-tumor therapeutics. In the current dissertation work, we present three experimental approaches to investigate G-quadruplex structures, biophysical properties, small molecule interaction, and the thermodynamics of G-quadruplex formation. Current approaches to study G-quadruplex structures often employ sequence modifications or changes to the experimental condition, as a way of resolving the structural polymorphism associated with many G-quadruplex-forming sequences, to select for a single conformation for high-resolution structural studies. Our strategy for resolving G-quadruplex structural polymorphism is superior in that the experimental approaches do not result in drastic perturbation of the system. In the first approach, we employed size exclusion chromatography to separate a mixture of G-quadruplex structures formed from a G-quadruplex-forming sequence. We demonstrated that it is possible to isolate distinct species of G-quadruplex structures for further biophysical studies. In the second approach, we employed hydrodynamic bead modeling to study the structural polymorphism of a G-quadruplex-forming sequence. We showed that properties calculated from models agreed with experimentally determined values and could be used to predict the folding of G-quadruplex-forming oligonucleotides whose high-resolution structures are ambiguous or not available. In our third approach, we presented a virtual screening platform that was successful in identifying a new Gquadruplex-interacting small molecule. The results of the virtual screen were validated with extensive biophysical testing. Our target for the virtual screen was a G-quadruplex structure generated in silico, which represents one approach to receptor-based drug discovery when high-resolution structures of the binding site are not available. Taken together, our three approaches represent a new paradigm for drug discovery from guaninerich sequence to anti-cancer drugs

Exploring hypotheses of the actions of TGF-beta 1 in epidermal wound healing using a 3D computational multiscale model of the human epidermis

In vivo and in vitro studies give a paradoxical picture of the actions of the key regulatory factor TGF-beta 1 in epidermal wound healing with it stimulating migration of keratinocytes but also inhibiting their proliferation. To try to reconcile these into an easily visualized 3D model of wound healing amenable for experimentation by cell biologists, a multiscale model of the formation of a 3D skin epithelium was established with TGF-beta 1 literature-derived rule sets and equations embedded within it. At the cellular level, an agent-based bottom-up model that focuses on individual interacting units ( keratinocytes) was used. This was based on literature-derived rules governing keratinocyte behavior and keratinocyte/ECM interactions. The selection of these rule sets is described in detail in this paper. The agent-based model was then linked with a subcellular model of TGF-beta 1 production and its action on keratinocytes simulated with a complex pathway simulator. This multiscale model can be run at a cellular level only or at a combined cellular/subcellular level. It was then initially challenged ( by wounding) to investigate the behavior of keratinocytes in wound healing at the cellular level. To investigate the possible actions of TGF-beta 1, several hypotheses were then explored by deliberately manipulating some of these rule sets at subcellular levels. This exercise readily eliminated some hypotheses and identified a sequence of spatial-temporal actions of TGF-beta 1 for normal successful wound healing in an easy-to-follow 3D model. We suggest this multiscale model offers a valuable, easy-to-visualize aid to our understanding of the actions of this key regulator in wound healing, and provides a model that can now be used to explore pathologies of wound healing

In silico transitions to multicellularity

The emergence of multicellularity and developmental programs are among the major problems of evolutionary biology. Traditionally, research in this area has been based on the combination of data analysis and experimental work on one hand and theoretical approximations on the other. A third possibility is provided by computer simulation models, which allow to both simulate reality and explore alternative possibilities. These in silico models offer a powerful window to the possible and the actual by means of modeling how virtual cells and groups of cells can evolve complex interactions beyond a set of isolated entities. Here we present several examples of such models, each one illustrating the potential for artificial modeling of the transition to multicellularity.Comment: 21 pages, 10 figures. Book chapter of Evolutionary transitions to multicellular life (Springer

Virtual cardiac monolayers for electrical wave propagation

The complex structure of cardiac tissue is considered to be one of the main determinants of an arrhythmogenic substrate. This study is aimed at developing the first mathematical model to describe the formation of cardiac tissue, using a joint in silico-in vitro approach. First, we performed experiments under various conditions to carefully characterise the morphology of cardiac tissue in a culture of neonatal rat ventricular cells. We considered two cell types, namely, cardiomyocytes and fibroblasts. Next, we proposed a mathematical model, based on the Glazier-Graner-Hogeweg model, which is widely used in tissue growth studies. The resultant tissue morphology was coupled to the detailed electrophysiological Korhonen-Majumder model for neonatal rat ventricular cardiomyocytes, in order to study wave propagation. The simulated waves had the same anisotropy ratio and wavefront complexity as those in the experiment. Thus, we conclude that our approach allows us to reproduce the morphological and physiological properties of cardiac tissue

Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping

This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates the probability of cells being occupied by walls of buildings, is obtained by a mobile robot equipped with an omnidirectional camera, GPS and a laser range finder. This semantic information is used for local and global segmentation of an aerial image. The result is a map where the semantic information has been extended beyond the range of the robot sensors and predicts where the mobile robot can find buildings and potentially driveable ground

Differences in reactivation of tuberculosis induced from anti-tnf treatments are based on bioavailability in granulomatous tissue

The immune response to Mycobacterium tuberculosis (Mtb) infection is complex. Experimental evidence has revealed that tumor necrosis factor (TNF) plays a major role in host defense against Mtb in both active and latent phases of infection. TNF-neutralizing drugs used to treat inflammatory disorders have been reported to increase the risk of tuberculosis (TB), in accordance with animal studies. The present study takes a computational approach toward characterizing the role of TNF in protection against the tubercle bacillus in both active and latent infection. We extend our previous mathematical models to investigate the roles and production of soluble (sTNF) and transmembrane TNF (tmTNF). We analyze effects of anti-TNF therapy in virtual clinical trials (VCTs) by simulating two of the most commonly used therapies, anti-TNF antibody and TNF receptor fusion, predicting mechanisms that explain observed differences in TB reactivation rates. The major findings from this study are that bioavailability of TNF following anti-TNF therapy is the primary factor for causing reactivation of latent infection and that sTNF-even at very low levels-is essential for control of infection. Using a mathematical model, it is possible to distinguish mechanisms of action of the anti-TNF treatments and gain insights into the role of TNF in TB control and pathology. Our study suggests that a TNF-modulating agent could be developed that could balance the requirement for reduction of inflammation with the necessity to maintain resistance to infection and microbial diseases. Alternatively, the dose and timing of anti-TNF therapy could be modified. Anti-TNF therapy will likely lead to numerous incidents of primary TB if used in areas where exposure is likely. © 2007 Marino et al