<p>This study is focused on designing and characterizing protein-based building blocks in order to construct self-assembled nano-structured biomaterials. In detail, this research aims to: (1) investigate a new class of proteins that possess nanospring behaviors at a single-molecule level, and utilize these proteins along with currently characterized elastomeric proteins as building blocks for nano-structured biomaterials; (2) develop a new method to accurately measure intermolecular interactions of self-assembling two or more arbitrary (poly)peptides, and select some of them which have appropriate tensile strength for crosslinking the proteins to construct elastomeric biomaterials; (3) construct well-defined protein building blocks which are composed of elastomeric proteins terminated with self-oligomerizing crosslinkers, and characterize self-assembled structures created by the building blocks to determine whether the elasticity of proteins at single-molecule level can be maintained.</p><p>Primary experimental methods of this research are (1) atomic force microscope (AFM) based single-molecule force spectroscopy (SMFS) that allows us to manipulate single molecules and to obtain their mechanical properties such as elasticity, unfolding and refolding properties, and force-induced conformational changes, (2) AFM imaging that permits us to identify topology of single molecules and supramolecular structures, and (3) protein engineering that allows us to genetically connect elastomeric proteins and self-assembling linkers together to construct well-defined protein building blocks.</p><p>Nanospring behavior of á-helical repeat proteins: We revealed that á-helical repeat proteins, composed of tightly packed á-helical repeats that form spiral-shaped protein structures, unfold and refold in near equilibrium, while they are stretched and relaxed during AFM based SMFS measurements. In addition to minimal energy dissipation by the equilibrium process, we also found that these proteins can yield high stretch ratios (>10 times) due to their packed initial forms. Therefore, we, for the first time, recognized a new class of polypeptides with nanospring behaviors. </p><p>Protein-based force probes for gauging molecular interactions: We developed protein-based force probes for simple, robust and general AFM assays to accurately measure intermolecular forces between self-oligomerization of two or more arbitrary polypeptides that potentially can serve as molecular crosslinkers. For demonstration, we genetically connected the force probe to the Strep-tag II and mixed it with its molecular self-assembling partner, the Strep-Tactin. Clearly characterized force fingerprints by the force probe allowed identification of molecular interactions of the single Strep-tag II and Strep-Tactin complex when the complex is stretched by AFM. We found a single energy barrier exists between Strep-tag II and Strep-Tactin in our given loading rates. Based upon our demonstration, the use of the force probe can be expanded to investigate the strength of interactions within many protein complexes composed of homo- and hetero-dimers, and even higher oligomeric forms. Obtained information can be used to choose potential self-assembling crosslinkers which can connect elastomeric proteins with appropriate strength in higher-order structures. </p><p>Self-assembled nano-structured biomaterials with well-defined protein-based building blocks: We constructed well-defined protein building blocks with tailored mechanical properties for self-assembled nano-structured materials. We engineered protein constructs composed of tandem repeats of either a I27-SNase dimer or a I27 domain alone and terminated them with a monomeric streptavidin which is known to form extremely stable tetramers naturally. By using molecular biology and AFM imaging techniques, we found that these protein building blocks transformed into stable tetrameric complexes. By using AFM based SMFS, we measured, to our knowledge for the first time, the mechanical strength of the streptavidin tetramer at a single-molecule level and captured its mechanical anisotropy. Using streptavidin tetramers as crosslinkers offers a unique opportunity to create well-defined protein based self-assembled materials that preserve the molecular properties of their building blocks.</p> / Dissertation

Fluorescence correlation spectroscopy has become a standard technique for modern biophysics and single molecule spectroscopy research. Here is presented a novel widefield extension of the established single-point technique. Flow in microfluidic devices was used as a model system for microscopic motion and through widefield fluorescence correlation spectroscopy flow profiles were mapped in three dimensions. The technique presented is shown to be more tolerant to low signal strength, allowing image data with signal-to-noise values as low as 1.4 to produce accurate flow maps as well as utilizing dye-labeled single antibodies as flow tracers. With proper instrumentation flows along the axial direction can also be measured. Widefield fluorescence correlation spectroscopy has also been utilized to produce super-resolution confocal microscopic images relying on the single-molecule microsecond blinking dynamics of fluorescent silver clusters. A method for fluorescence modulation signal extraction as well as synthesis of several novel noble metal fluorophores is also presented.

Within the last years, e.g. by investigating the fluorescence of single molecules in biological cells, remarkable progress has been made in cell biology extending conventional ensemble techniques concerning temporal / spatial resolution and the detection of particle subpopulations [82]. In addition to employing single fluorophores as &amp;quot;molecular beacons&amp;quot; to determine the position of biomolecules, single molecule fluorescence studies allow to access the photophysical dynamics of genetically encoded fluorescent proteins itself. However, in order to gain statistically consistent results, e.g. on the mobility behavior or the photophysical properties, the fluorescence image sequences have to be analyzed in a preferentially automated and calibrated (non-biased) way. In this thesis, a single molecule fluorescence optical setup was developed and calibrated and experimental biological in-vitro systems were adapted to the needs of single molecule imaging. Based on the fluorescence image sequences obtained, an automated analysis algorithm was developed, characterized and its limits for reliable quantitative data analysis were determined. For lipid marker molecules diffusing in an artifcial lipid membrane, the optimum way of the single molecule trajectory analysis of the image sequences was explored. Furthermore, effects of all relevant artifacts (specifically low signal-to-noise ratio, finite acquisition time and high spot density, in combination with photobleaching) on the recovered diffusion coefficients were carefully studied. The performance of the method was demonstrated in two series of experiments. In one series, the diffusion of a fluorescent lipid probe in artificial lipid bilayer membranes of giant unilamellar vesicles was investigated. In another series of experiments, the photoconversion and photobleaching behavior of the fluorescent protein Kaede-GFP was characterized and protein subpopulations were identified.

We use time-lapse AFM to visualize collagen fibrils self-assembly. A solution of acid-solubilized collagen was injected into the AFM fluid cell and fibril formation was observed in vitro. Single fibrils continuously grew and fused with each other until the supporting surface was completely covered by a nanoscopically well-defined collagen matrix. Laterally, the fibrils grew in steps of ~4 nm suggesting a two-step mechanism. In a first step, collagen molecules associated together. In the second step, these molecules rearranged into a structure called a microfibril. High-resolution AFM topographs revealed substructural details of the D-band architecture. These substructures correlated well with those revealed from positively stained collagen fibers imaged by transmission electron microscopy. Secondly, a covalent assembly approach to prepare membrane protein for AFM imaging that avoids crystallization was proposed. High-resolution AFM topographs can reveal structural details of single membrane proteins but, as a prerequisite, the proteins must be adsorbed to atomically flat mica and densely packed in a membrane to restrict their lateral mobility. Atomically flat gold, engineered proteins, and chemically modified lipids were combined to rapidly assemble immobile and fully oriented samples. The resulting AFM topographs of single membrane proteins were used to create averaged structures with a resolution approaching that of 2D crystals. Finally, the contribution of specific amino acid residues to the stability of membrane proteins was studied. Two structurally similar proteins sharing only 30% sequence identity were compared. Single-molecule atomic force microscopy and spectroscopy was used to detect molecular interactions stabilizing halorhodopsin (HR) and bacteriorhodopsin (BR). Their unfolding pathways and polypeptide regions that established stable segments were compared. Both proteins unfolded exactly via the same intermediates. This 3 Molecular Assemblies observed by AFM observation implies that these stabilizing regions result from comprehensive contacts of all amino acids within them and that different amino acid compositions can establish structurally indistinguishable energetic barriers. However, one additional unfolding barrier located in a short segment of helix E was detected for HR. This barrier correlated with a Pi-bulk interaction, which locally disrupts helix E and divides into two stable segments.

This thesis explores stochastic modeling and Bayesian inference strategies in the context of the following three problems: 1) Modeling the complex interactions between and within molecules; 2) Extracting information from stepwise signals that are commonly found in biophysical experiments; 3) Improving the computational efficiency of a non-parametric Bayesian inference algorithm. Chapter 1 studies the data from a recent single-molecule biophysical experiment on enzyme kinetics. Using a stochastic network model, we analyze the autocorrelation of experimental fluorescence intensity and the autocorrelation of enzymatic reaction times. This chapter shows that the stochastic network model is capable of explaining the experimental data in depth and further explains why the enzyme molecules behave fundamentally differently from what the classical model predicts. The modern knowledge on the molecular kinetics is often learned through the information extracted from stepwise signals in experiments utilizing fluorescence spectroscopy. Chapter 2 proposes a new Bayesian method to estimate the change-points in stepwise signals. This approach utilizes marginal likelihood as the tool of inference. This chapter illustrates the impact of the choice of prior on the estimator and provides guidelines for setting the prior. Based on the results of simulation study, this method outperforms several existing change-points estimators under certain settings. Furthermore, DNA array CGH data and single molecule data are analyzed with this approach. Chapter 3 focuses on the optional Polya tree, a newly established non-parametric Bayesian approach (Wong and Li 2010). While the existing study shows that the optional Polya tree is promising in analyzing high dimensional data, its applications are hindered by the high computational costs. A heuristic algorithm is proposed in this chapter, with an attempt to speed up the optional Polya tree inference. This study demonstrates that the new algorithm can reduce the running time significantly with a negligible loss of precision. / Statistics

Eukaryotic genomes are packaged as chromatin, which restricts access to the DNA by critical processes such as DNA replication, repair, and transcription. As a result, eukaryotic cells rely on ATP-dependent chromatin remodeling enzymes (remodelers) to alter the position, structure, and composition of nucleosomes. Understanding the mechanism and regulation of remodeling requires detailed information about transient intermediates of the remodeling process--a challenge ideally suited for single-molecule approaches. In particular, we use single-molecule fluorescence resonance energy transfer (smFRET) to measure nanometer-scale distance changes between strategically placed donor and acceptor dyes to monitor nucleosome translocation in real-time. The mechanism(s) by which remodelers use the free energy of ATP hydrolysis to disrupt histone-DNA contacts and reposition nucleosomes are not well understood. Using smFRET, we show that remodeling by ISWI enzymes begins with a 7 base-pair (bp) step followed by subsequent 3 bp steps toward the exit-side of the nucleosome. These multi-bp steps are actually compound steps composed of 1 bp elementary steps. We discover that DNA movement on the entry side lags behind exit side translocation, which is contrary to previously proposed models. Based on our results, we propose a new integrated mechanism for nucleosome translocation by ISWI enzymes. In the physiological context, remodelers are highly regulated. We study the regulation of human ACF, a prototypical ISWI complex, by critical features of the nucleosomal substrate. First, we dissect how the nucleosome translocation cycle is affected by the linker DNA length and histone H4 tail. Next, we introduce mutations/deletions into conserved enzyme domains to determine the mechanism by which linker length information sensed by the Acfl accessory subunit is allosterically transmitted to the Snf2h catalytic subunit. Interestingly, we find that Acfl modulates the activity of Snf2h indirectly by interacting with the H4 tail in a linker-length dependent fashion. While the majority of our experiments focus on observing changes in nucleosome position, we also develop strategies for site-specific labeling of ISWI enzymes and demonstrate their use in the study of dynamic enzyme-substrate interactions and enzyme conformational changes.

Rare-event phenomena are ubiquitous in nature. We propose a new strategy, kappa-dynamics, to model rare event dynamics. In this methodology we only assume that the important rare-event dynamics obey first-order kinetics. Exact rates are not required in the calculation and the reaction path is determined on the fly. kappa-dynamics is highly parallelizable and can be implemented on computer clusters and distributed machines. Theoretical derivations and several examples of atomic scale dynamics are presented. With single-molecule (SM) techniques, the individual molecular process can be resolved without being averaged over the ensemble. However, factors such as apparatus stability, background level, and data quality will limit the amount of information being collected. We found that the correlation function calculated from the finite-size SM rotational diffusion trajectory will deviate from its true value. Therefore, care must be taken not to interpret the difference as the evidence of new dynamics occurred in the system. We also proposed an algorithm of single fluorophore orientation reconstruction which converts three measured intensities {I₀,I₄₅,I₉₀} to the dipole orientation. Fluctuations in the detected signals caused by the shot noise result in a different prediction from the true orientation. This difference should not be interpreted as the evidence of the nonisotropic rotational motion. Catalytic reactions are also governed by the rare-events. Studying the dynamics of catalytic processes is an important subject since the more we learn, the more we can improve current catalysts. Fuel cells have become a promising energy source in the past decade. The key to make a high performance cell while keeping the price low is the choice of a suitable catalyst at the electrodes. Density functional theory calculations are carried out to study the role of geometric relaxation in the oxygen-reduction reaction for nanoparticle of various transition metals. Our calculations of Pt nanoparticles show that the structural deformation induced by atomic oxygen binding can energetically stabilize the oxidized states and thus reduces the catalytic activity. The catalytic performance can be improved by making alloys with less deformable metals. / text

No description available.

Single-walled carbon nanotubes are naturally-forming nanostructures that have attracted considerable recent research interest due to their unique opto-electronic properties and comparative ease of fabrication. Two-thirds of nanotube species are semiconductors due to symmetry conditions imposed by their pseudo-one-dimensional tubular structure, and exhibit band-gap photoluminescence when isolated from their environment. Despite their elegant structural simplicity, fundamental properties of carbon nanotubes, such as their intrinsic quantum efficiency, non-linear excitonic recombination mechanisms, and the role of environmental effects, continue to be disputed in the literature. The design of an apparatus capable of observing nanotube photoluminescence is presented, along with conclusive proof of the observation of a single (9,8)-chirality nanotube in the form of spectral, spatial, and polarization-dependent measurements. The dependance of the excitation and emission spectra of a single nanotube on the excitation intensity is explored and the emission spectra found to be described by a Gaussian peak function, in contrast to previously-reported results. The unexpected ability to cause redshifts in the emission spectrum via the ambient humidity is discovered, which has consequences on experimental best practices. Photoluminescence quantum efficiencies are measured to be 4±2% and 13±6% for two different nanotubes. This is at the high end of the range for comparable literature results, and supports the validity of a recent literature value for the effective atomic absorption coefficient for carbon, AC=1.6×10^−3nm^2, which is ten times greater than previous literature values. Pulsed power dependence studies show that the PL emission undergoes ‘hard’ saturation at an excitation intensity of 0.5×10^12photons/pulse/cm2, which is at least 100 times lower than previous reports and provides insight into non-linear decay dynamics. A novel theoretical model is developed to explain this saturation process, which yields an absorption co-efficient of AC=1.2±0.3×10^−3nm^2 as a fit parameter. Time-resolved photoluminescence dynamics are explored using femtosecond excitation correlation spectroscopy. Results suggest that the one-body decay processes are bi-exponential, with time constants of 31±4ps and 313±61ps, but also highlight the limitations of this technique in observing the expected very rapid (~1 ps) two-body Auger recombination process. / Thesis (Master, Physics, Engineering Physics and Astronomy) -- Queen's University, 2008-09-26 16:23:40.81

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