Biological Nanowires: Integration of the silver(I) base pair into DNA with nanotechnological and synthetic biological applications

Modern computing and mobile device technologies are now based on semiconductor technology with nanoscale components, i.e., nanoelectronics, and are used in an increasing variety of consumer, scientific, and space-based applications. This rise to global prevalence has been accompanied by a similarly precipitous rise in fabrication cost, toxicity, and technicality; and the vast majority of modern nanotechnology cannot be repaired in whole or in part. In combination with looming scaling limits, it is clear that there is a critical need for fabrication technologies that rely upon clean, inexpensive, and portable means; and the ideal nanoelectronics manufacturing facility would harness micro- and nanoscale fabrication and self-assembly techniques. The field of molecular electronics has promised for the past two decades to fill fundamental gaps in modern, silicon-based, micro- and nanoelectronics; yet molecular electronic devices, in turn, have suffered from problems of size, dispersion and reproducibility. In parallel, advances in DNA nanotechnology over the past several decades have allowed for the design and assembly of nanoscale architectures with single-molecule precision, and indeed have been used as a basis for heteromaterial scaffolds, mechanically-active delivery mechanisms, and network assembly. The field has, however, suffered for lack of meaningful modularity in function: few designs to date interact with their surroundings in more than a mechanical manner. As a material, DNA offers the promise of nanometer resolution, self-assembly, linear shape, and connectivity into branched architectures; while its biological origin offers information storage, enzyme-compatibility and the promise of biologically-inspired fabrication through synthetic biological means. Recent advances in DNA chemistry have isolated and characterized an orthogonal DNA base pair using standard nucleobases: by bridging the gap between mismatched cytosine nucleotides, silver(I) ions can be selectively incorporated into the DNA helix with atomic resolution. The goal of this thesis is to explore how this approach to “metallize” DNA can be combined with structural DNA nanotechnology as a step toward creating electronically-functional DNA networks. This work begins with a survey of applications for such a transformative technology, including nanoelectronic component fabrication for low-resource and space-based applications. We then investigate the assembly of linear Ag+-functionalized DNA species using biochemical and structural analyses to gain an understanding of the kinetics, yield, morphology, and behavior of this orthogonal DNA base pair. After establishing a protocol for high yield assembly in the presence of varying Ag+ functionalization, we investigate these linear DNA species using electrical means. First a method of coupling orthogonal DNA to single-walled carbon nanotubes (SWCNTs) is explored for self-assembly into nanopatterned transistor devices. Then we carry out scanning tunneling microscope (STM) break junction experiments on short polycytosine, polycationic DNA duplexes and find increased molecular conductance of at least an order of magnitude relative to the most conductive DNA analog. With an understanding of linear species from both a biochemical and nanoelectronic perspective, we investigate the assembly of nonlinear Ag+-functionalized DNA species. Using rational design principles gathered from the analysis of linear species, a de novo mathematical framework for understanding generalized DNA networks is developed. This provides the basis for a computational model built in Matlab that is able to design DNA networks and nanostructures using arbitrary base parity. In this way, DNA nanostructures are able to be designed using the dC:Ag+:dC base pair, as well as any similar nucleobase or DNA-inspired system (dT:Hg2+:dT, rA:rU, G4, XNA, LNA, PNA, etc.). With this foundation, three general classes of DNA tiles are designed with embedded nanowire elements: single crossover Holliday junction (HJ) tiles, T-junction (TJ) units, and double crossover (DX) tile pairs and structures. A library of orthogonal chemistry DNA nanotechnology is described, and future applications to nanomaterials and circuit architectures are discussed

Deriving Protein Structures Efficiently by Integrating Experimental Data into Biomolecular Simulations

Proteine sind molekulare Nanomaschinen in biologischen Zellen. Sie sind wesentliche Bausteine aller bekannten Lebensformen, von Einzellern bis hin zu Menschen, und erfüllen vielfältige Funktionen, wie beispielsweise den Sauerstofftransport im Blut oder als Bestandteil von Haaren. Störungen ihrer physiologischen Funktion können jedoch schwere degenerative Krankheiten wie Alzheimer und Parkinson verursachen. Die Entwicklung wirksamer Therapien für solche Proteinfehlfaltungserkrankungen erfordert ein tiefgreifendes Verständnis der molekularen Struktur und Dynamik von Proteinen. Da Proteine aufgrund ihrer lichtmikroskopisch nicht mehr auflösbaren Größe nur indirekt beobachtet werden können, sind experimentelle Strukturdaten meist uneindeutig. Dieses Problem lässt sich in silico mittels physikalischer Modellierung biomolekularer Dynamik lösen. In diesem Feld haben sich datengestützte Molekulardynamiksimulationen als neues Paradigma für das Zusammenfügen der einzelnen Datenbausteine zu einem schlüssigen Gesamtbild der enkodierten Proteinstruktur etabliert. Die Strukturdaten werden dabei als integraler Bestandteil in ein physikbasiertes Modell eingebunden. In dieser Arbeit untersuche ich, wie sogenannte strukturbasierte Modelle verwendet werden können, um mehrdeutige Strukturdaten zu komplementieren und die enthaltenen Informationen zu extrahieren. Diese Modelle liefern eine effiziente Beschreibung der aus der evolutionär optimierten nativen Struktur eines Proteins resultierenden Dynamik. Mithilfe meiner systematischen Simulationsmethode XSBM können biologische Kleinwinkelröntgenstreudaten mit möglichst geringem Rechenaufwand als physikalische Proteinstrukturen interpretiert werden. Die Funktionalität solcher datengestützten Methoden hängt stark von den verwendeten Simulationsparametern ab. Eine große Herausforderung besteht darin, experimentelle Informationen und theoretisches Wissen in geeigneter Weise relativ zueinander zu gewichten. In dieser Arbeit zeige ich, wie die entsprechenden Simulationsparameterräume mit Computational-Intelligence-Verfahren effizient erkundet und funktionale Parameter ausgewählt werden können, um die Leistungsfähigkeit komplexer physikbasierter Simulationstechniken zu optimieren. Ich präsentiere FLAPS, eine datengetriebene metaheuristische Optimierungsmethode zur vollautomatischen, reproduzierbaren Parametersuche für biomolekulare Simulationen. FLAPS ist ein adaptiver partikelschwarmbasierter Algorithmus inspiriert vom Verhalten natürlicher Vogel- und Fischschwärme, der das Problem der relativen Gewichtung verschiedener Kriterien in der multivariaten Optimierung generell lösen kann. Neben massiven Fortschritten in der Verwendung von künstlichen Intelligenzen zur Proteinstrukturvorhersage ermöglichen leistungsoptimierte datengestützte Simulationen detaillierte Einblicke in die komplexe Beziehung von biomolekularer Struktur, Dynamik und Funktion. Solche computergestützten Methoden können Zusammenhänge zwischen den einzelnen Puzzleteilen experimenteller Strukturinformationen herstellen und so unser Verständnis von Proteinen als den Grundbausteinen des Lebens vertiefen

Bioinformatics, Thermodynamics and Kinetics Analysis of an All Alpha Helical Protein with a Gree-Key Topology

Computational and experimental studies focusing on the role of conserved residues for folding and stability is an active and promising area of research. To further expand our understanding we present the results of a bioinformatics analysis of the death domain superfamily. The death domain superfamily fold consists of six α-helices arranged in a Greek-key topology, which is shared by the all β-sheet immunoglobulin and mixed α/β-plait superfamilies. Our sequence and structural studies have identified a group of conserved hydrophobic residues and corresponding long-range interactions, which we propose are important in the formation and stabilization of the hydrophobic core and native topology. Equilibrium unfolding and refolding studies of a model superfamily member, the Fas-associated death domain protein indicate that this process is cooperative, two-state and reversible. Stopped-flow fluorescence studies reveal that the folding is rapid and biphasic with the majority of the hydrophobic core forming in the first phase. Site-directed mutagenesis studies indicate that conserved Trp112, Trp148, Leu115 and Val121 are important to structure, native state stability and folding. We also present the results of experiments aimed at characterizing the formation of secondary structure. Stopped-flow far-UV CD spectroscopy revealed that the folding process was monophasic and the rate is 23.4 s-1. To gain atomic resolution a combination of quenched-flow methods, hydrogen deuterium exchange (HX) and NMR spectroscopy was implemented. Twenty-two amide hydrogens in the backbone of the helices and two in the backbone of the loops were monitored and the folding of all six helices was determined to be monophasic with rates between 19 s-1 and 22 s-1. These results indicate that the formation of secondary structure is largely cooperative and concomitant with the hydrophobic collapse. Additional insights are gained by calculating the exchange rates of twenty-three residues from equilibrium FIX experiments. The majority of protected amide protons are found on helices 2, 4, and 5 which make up core structural elements of the Greek-key topology. These results appear to be the earliest conservation analysis and biophysical characterization conducted on the Fas-associated death domain and folding kinetics using quenched-flow combined with NMR spectroscopy on an all a-helical Greek-key protein

The Application of Multi-dimensional Fluorescence Imaging to Microfluidic Systems

This thesis describes the application of multidimensional fluorescence imaging to microfluidic systems. The work focuses on time- and polarisation-resolved fluorescence microscopy to extract information from microchannel environments. The methods are applied to polymerase chain reaction (PCR) and a DNA repair enzyme, uracil DNA glycosylase (UDG). The fluorescence lifetimes Rhodamine B are calibrated over a thermal gradient using time correlated single photon counting. The dye is then introduced in solution into a novel microfluidic PCR device. Fluorescence lifetime imaging microscopy (FLIM) is then performed, and using the calibration curve, the temperature distributions are accurately determined. The device is subsequently optimised for efficient DNA amplification. A line-scanning FLIM microscope is used to characterise a rapid microfluidic mixer via a fluorescence quenching experiment. Fluorescein and sodium iodide are mixed in a continuous flow format and imaged in 3-D. The spatial distributions of the fluorescence lifetimes are converted to the concentrations of sodium iodide to quantify mixing. Computational fluid dynamic (CFD) simulations are validated by comparison to the quantitative concentrations obtained experimentally. The binding reaction between UDG and a hexachlorofluorescein (HEX) labelled DNA strand is characterised spectrally. As well as an increase in fluorescence polarisation anisotropy, a 700 ps increase in the fluorescence lifetime is measured. Confocal microscopy shows the same spectral properties when the reaction is performed in both simple and rapid microfluidic mixers. In the latter experiment, a concentration series allows the determination of kinetics, which agree with conventional stopped-flow data. A two-colour two-photon (2c2p) FLIM microscope is developed and applied to the UDG-DNA system. An oligonucleotide containing 2-aminopurine, a reporter of DNA base flipping, and HEX is mixed with UDG in a microfluidic Y-mixer. The 2c2p excitation allows FLIM of both fluorophores and hence detection of binding and base flipping. Comparison to CFD with known kinetic rate constants confirms the experimental observations

Protein folding, metal ions and conformational states: the case of a di-cluster ferredoxin

Dissertation presented to obtain the PhD degree in Biochemistry at the Instituto de Tecnologia Química e Biológica, Universidade Nova de LisboaMetal ions are present in over thirty percent of known proteins. Apart from a well established function in catalysis and electron transfer, metals and metal centres are also important structural elements which may as well play a key role in modulating protein folding and stability. In this respect, cofactors can act not only as local structural stabilizing elements in the native state, contributing to the maintenance of a given specific structural fold, but may also function as potential nucleation points during the protein folding process...Fundação para a Ciência e Tecnologia is acknowledged for financial support, by awarding a PhD Grant SFRH/BD/18653/2004. This work has been funded by the projects POCTI/QUI/37521; POCTI/QUI/45758 and PTDC/QUI/70101 all to Cláudio M. Gomes

AccuSyn: Using Simulated Annealing to Declutter Genome Visualizations

We apply Simulated Annealing, a well-known metaheuristic for obtaining near-optimal solutions to optimization problems, to discover conserved synteny relations (similar features) in genomes. The analysis of synteny gives biologists insights into the evolutionary history of species and the functional relationships between genes. However, as even simple organisms have huge numbers of genomic features, syntenic plots initially present an enormous clutter of connections, making the structure difficult to understand. We address this problem by using Simulated Annealing to minimize link crossings. Our interactive web-based synteny browser, AccuSyn, visualizes syntenic relations with circular plots of chromosomes and draws links between similar blocks of genes. It also brings together a huge amount of genomic data by integrating an adjacent view and additional tracks, to visualize the details of the blocks and accompanying genomic data, respectively. Our work shows multiple ways to manually declutter a synteny plot and then thoroughly explains how we integrated Simulated Annealing, along with human interventions as a human-in-the-loop approach, to achieve an accurate representation of conserved synteny relations for any genome. The goal of AccuSyn was to make a fairly complete tool combining ideas from four major areas: genetics, information visualization, heuristic search, and human-in-the-loop. Our results contribute to a better understanding of synteny plots and show the potential that decluttering algorithms have for syntenic analysis, adding more clues for evolutionary development. At this writing, AccuSyn is already actively used in the research being done at the University of Saskatchewan and has already produced a visualization of the recently-sequenced Wheat genome

Engineering DNA-Based Self-Assembly Systems to Produce Nanostructures and Chemical Patterns

While commonly known as a material that stores biological information essential for life, few realize that deoxyribonucleic acid (DNA) is also a wonderful building (i.e., physical structures) and computing material. The field of DNA nanotechnology aims to use DNA primarily to build and control matter on the nanoscale. In 2006, a technique known as DNA origami was developed, which allows for the formation of about any shape on the nanoscale. Such DNA origami have been used in many applications: nanodevices, nanotubes, nanoreactors. However, the small surface area of the origami often limits its usefulness. One promising method for building large (micron-sized) DNA origami structures is to self-assemble multiple origami components into well-defined structures. To date, however, such structures suffer low yields, long reaction times and require experimental optimization with no guiding principles. One primary reason is that a governing theory and experimental measurements behind such a self-assembly process are lacking. In this work, we develop coarse-grained computational simulations to describe and understand the self-assembly of finite-sized, multicomponent complexes (e.g., nine different DNA-origami components that form a square grid complex). To help inform the model, we experimentally investigate how various interface architectures between two self-assembling DNA origami components affect the reaction kinetics and thermodynamics. We further develop the accuracy of our simulations by incorporating these measurements and other thermodynamic measurements from our group and implement a computational algorithm that optimizes the interaction strengths between self-assembling components for reaction efficiency (i.e., speed and yield of the complex). With these experimentally-informed simulations, we suggest design improvements and provide yield predictions to an experimentally demonstrated tetrameric complex. Finally, with the overarching idea of using DNA-based components to self-assemble to produce ordered structures and patterns, we build a reaction-diffusion system whose reactions are programmed using DNA strand displacement and diffusion which occurs in a hydrogel, wherein patterns develop, and liquid reservoirs, which are used to supply the high energy components. With this reaction-diffusion system we create stable (i.e., unchanging in space and time) one and two-dimensional patterns of DNA molecules with millimeter-scale features

Derivative-free hybrid methods in global optimization and their applications

In recent years large-scale global optimization (GO) problems have drawn considerable attention. These problems have many applications, in particular in data mining and biochemistry. Numerical methods for GO are often very time consuming and could not be applied for high-dimensional non-convex and / or non-smooth optimization problems. The thesis explores reasons why we need to develop and study new algorithms for solving large-scale GO problems .... The thesis presents several derivative-free hybrid methods for large scale GO problems. These methods do not guarantee the calculation of a global solution; however, results of numerical experiments presented in this thesis demonstrate that they, as a rule, calculate a solution which is a global one or close to it. Their applications to data mining problems and the protein folding problem are demonstrated.Doctor of Philosoph

Antenna near-field wave studies in magnetized plasmas as part of the optimization of auxiliary heating in fusion devicesAntenna near-field wave studies in magnetized plasmas as part of the optimization of auxiliary heating in fusion devices

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