Physics
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Item Jamming effects in glasses and biopolymers(2014) Kang, Hongsuk; Thirumalai, Devarajan; Chemical Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, jamming effects in highly packed systems are studied in two specific materials: glasses and biopolymers in cellular environments. Suspensions consisting of highly charged colloids, which are well-known glass-forming systems, are investigated using molecular dynamics simulations in order to test Random First Order Transition (RFOT) theory. I found that there is a critical volume fraction at which ergodic-to-nonergodic transitions for three dynamic observables take place in accordance with RFOT. Based on numerical observations, it is also proposed that the dynamic heterogeneity can be attributed to the violation of law of large numbers. In addition, the bond orientational order of colloidal suspensions and soft-spheres is discussed in the context of liquid-glass transitions. The response of biopolymers to a crowded environment is another interesting issue because 20-40% volume of a cell is occupied by various cellular components such as ribosomes and proteins in vivo. In this work, using low-friction langevin dynamics simulations with explicit crowding particles, I examined the conformational change of biopolymers in the presence of crowders of various sizes and shapes. The simulation results reveal that cylindrical crowders induce much greater compaction of the polymers than spherical ones at low volume fractions and the stronger crowding effects disappear at higher volume fractions due to local nematic ordering of cylindrical particles. The reduction in the size of polymer is even more dramatic in a mixture of spherical and cylindrical shapes because of cooperative crowding effects explained by the phase separation of spheres and rodlike particles. Finally, the crowding effects of cellular components on bacterial chromosomes are estimated using a mixture of spherical crowders with the composition found in bacterial cytoplasms.Item USING SINGLE MOLECULE TECHNIQUES TO DETERMINE THE MECHANISM OF DNA TOPOLOGY SIMPLIFICATION BY TYPE IIA TOPOISOMERASES(2011) Hardin, Ashley Harris; Thirumalai, Devarajan; Neuman, Keir C; Chemical Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Type IIA topoisomerases are essential, universally conserved proteins that modify DNA topology by passing one segment of duplex DNA (the transfer, or T-segment) through a transient double strand break in a second segment of DNA (the gate, or G-segment) in an ATP-dependent reaction. Type IIA topoisomerases decatenate, unknot, and relax supercoiling in DNA to levels below equilibrium, resulting in global topology simplification. The mechanism underlying non-equilibrium topology simplification remains speculative, though several plausible models have been proposed. This thesis tests two of these, the bend angle and kinetic proofreading models, using single-molecule techniques. The bend angle model postulates that non-equilibrium topology simplification scales with the bend angle imposed on the G-segment DNA by a type IIA topoisomerase. To test this model, we used atomic force microscopy and single molecule Förster resonance energy transfer to measure the extent of bending imposed on DNA by three type IIA topoisomerases that span the range of topology simplification activity. We found that all proteins bent DNA, but the imposed bends are similar and cannot account for the differences among the enzymes. These data do not support the bend angle model and suggest that DNA bending is not the sole determinant of non-equilibrium topology simplification. Based on the assumption that the rates of collision between DNA segments is higher in knotted, linked, and supercoiled DNA than in topologically free or relaxed DNA, the kinetic proofreading model proposes that two successive binding events between a G-segment bound topoisomerase and a putative T-segment are required to initiate strand passage. As a result of the two step process, the overall rate of strand passage should scale with the square of the collision probability of two DNA segments. To test this model, we used magnetic tweezers to manipulate a paramagnetic bead tethered to the surface by two DNA molecules. By rotating the bead, we varied the proximity, and thus collision rate, of the two molecules to determine the relationship between collision probability and rate of strand passage. Our data indicate that the strand passage rate scales linearly with the collision probability, which is inconsistent with the kinetic proofreading model.Item Patterns and Complexity in Biological Systems: A Study of Sequence Structure and Ontology-based Networks(2010) Glass, Kimberly; Girvan, Michelle; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Biological information can be explored at many different levels, with the most basic information encoded in patterns within the DNA sequence. Through molecular level processes, these patterns are capable of controlling the states of genes, resulting in a complex network of interactions between genes. Key features of biological systems can be determined by evaluating properties of this gene regulatory network. More specifically, a network-based approach helps us to understand how the collective behavior of genes corresponds to patterns in genetic function. We combine Chromatin-Immunoprecipitation microarray (ChIP-chip) data with genomic sequence data to determine how DNA sequence works to recruit various proteins. We quantify this information using a value termed "nmer-association.'' "Nmer-association'' measures how strongly individual DNA sequences are associated with a protein in a given ChIP-chip experiment. We also develop the "split-motif'' algorithm to study the underlying structural properties of DNA sequence independent of wet-lab data. The "split-motif'' algorithm finds pairs of DNA motifs which preferentially localize relative to one another. These pairs are primarily composed of known transcription factor binding sites and their co-occurrence is indicative of higher-order structure. This kind of structure has largely been missed in standard motif-finding algorithms despite emerging evidence of the importance of complex regulation. In both simple and complex regulation, two genes that are connected in a regulatory fashion are likely to have shared functions. The Gene Ontology (GO) provides biologists with a controlled terminology with which to describe how genes are associated with function and how those functional terms are related to each other. We introduce a method for processing functional information in GO to produce a gene network. We find that the edges in this network are correlated with known regulatory interactions and that the strength of the functional relationship between two genes can be used as an indicator of how informationally important that link is in the regulatory network. We also investigate the network structure of gene-term annotations found in GO and use these associations to establish an alternate natural way to group the functional terms. These groups of terms are drastically different from the hierarchical structure established by the Gene Ontology and provide an alternative framework with which to describe and predict the functions of experimentally identified groups of genes.