Matching Items (8)
Nanosphere lithography is a high throughput procedure that has important implications
for facile, low cost scaling of nanostructures. However, current benchtop experiments have
limitations based on the placement of molecular species that exhibit greater than singlemolecular binding. In addition, reliance upon bottom-up self-assembly of close-packed
nanospheres makes it problematic to resolve images using low-cost light microscopes due to the
spacing limitations smaller in magnitude than light wavelength. One method that is created to
resolve this issue is iterative size reduction (ISR), where repetitive ‘iterative’ processes are
employed in order to increase the precision at which single molecules bind to a given substrate.
ISR enables inherent separation of nanospheres and therefore any subsequent single molecule
binding platforms. In addition, ISR targets and encourages single-molecule binding by
systematically reducing binding site size. Results obtained pursuing iteratively reduced
nanostructures showed that many factors are needed to be taken into consideration, including
functionalization of nanosphere particles, zeta potential, and protonation-buffer reactions.
Modalities used for observation of nanoscale patterning and single-molecule binding included
atomic force microscopy (AFM) and ONI super-resolution and fluorescence microscopy. ISR
was also used in conjunction with zero mode waveguides, which are nanoapertures enabling realtime single molecule observation at zeptoliter volumes. Although current limitations and
obstacles still exist with reproducibility and scalability of ISR, it nonetheless exhibits limitless
potential and flexibility in nanotechnology applications.
Proteins are the machines of living systems that carry out a diverse set of essential biochemical functions. Furthermore, the diversity of their functions has grown overtime via molecular evolution. This thesis aims to explore fundamental questions in protein science regarding the mechanisms of protein evolution particularly addressing how substitutions in sequence modulate function through structure and structural dynamics. In the work presented here, the first goal is to develop a set of tools which connect the sequence-structure relationship which are implemented in two major projects of protein structural refinement and protein structural design. Both of these two works highlight the importance of capturing important pairwise interactions within a given protein system.The second major goal of this work is to understand how sequence and structural dynamics give rise to protein function, and, importantly, how Nature can utilize allostery to evolve towards a new function. Here I employ several in-house and novel computational tools to shed light onto the mechanisms of allostery, and, particularly dynamic allostery in the absence of structural rearrangements. This analysis is applied to several different protein systems including Pin1, LacI, CoV-1 and CoV-2 and TEM-1. I show that the dynamics of protein systems may be altered fundamentally by distal perturbations such as ligand binding or point mutations. These peturbations lead to change in local interactions which cascade within the 3-D network of interaction of a protein and give rise to flexibility changes of distal sites, particularly those of functional/active residues positions thereby altering the protein function.
This networking picture of the protein is further explored through asymmetric dynamic coupling which shows to be a marker of allosteric interactions between distal residue pairs. Within the networking picture, the concept of sequence context dependence upon mutation becomes critical in understanding the functional outcome of these mutations. Here I design a computational tool, EpiScore, which is able to capture these effects and correlate them to measured experimental epistasis in two protein systems, dihydrofolate reductase (DHFR) and TEM-1. Ultimately, the work provided in this thesis shows that both allostery and epistasis may be considered, and accurately modeled, as intrinsic properties of anisotropic networks.
A form of nanoscale steganography exists described as DNA origami cryptography which is a technique of secure information encryption through scaffold, staple, and varying docking strand self- assembling mixtures. The all-DNA steganography based origami was imaged through high-speed DNA-PAINT super-resolution imaging which uses periodic docking sequences to eliminate the need for protein binding. The purpose of this research was to improve upon the DNA origami cryptography protocol by encrypting information in 2D Rothemund Rectangular DNA Origami (RRO) and 3D cuboctahedron DNA origami as a platform of self-assembling DNA nanostructures to increase the routing possibilities of the scaffold. The initial focus of the work was increasing the incorporation efficiency of all individual docking spots for full 20nm grid RRO pattern readout. Due to this procedural optimization was pursued by altering annealing cycle length, centrifugal spin rates for purification, and lengthening docking strands vs. imager poly T linkers. A 14nm grid was explored as an intermediate prior to the 10nm grid for comparison of optimized experimental procedure for a higher density encryption pattern option. Imager concentration was discovered to be a vital determining factor in effectively resolving the 10nm grids due to high concentrations of imager strands inducing simultaneous blinking of adjacent docking strands to be more likely causing the 10nm grids to not be resolved. A 2 redundancy and 3 redundancy encryption scheme was developed for the 10nm grid RRO to be encrypted with. Further experimentation was completed to resolve full 10nm DNA-origami grids and encrypt with the message ”ASU”. The message was successfully encrypted and resolved through the high density 10nm grid with 2 and 3 redundancy patterns. A cuboctahedron 3D origami was explored with DNA-PAINT techniques as well resulting in successful resolution of the z-axis through variation of biotin linker length and calibration file. Positive results for short message ”0407” encryption of the cuboctahedron were achieved. Data encryption in DNA origami is further being explored and could be an optimal solution for higher density data storage with greater longevity of media.
With climate change threatening to increase the frequency of global pandemics, the need for quick and adaptable responses to novel viruses will become paramount. DNA nanotechnology offers a highly customizable, biocompatible approach to combating novel outbreaks. For any DNA nanotechnology-based therapeutic to have future success in vivo, the structure must be able to withstand serological conditions for an extended time period. In this study, the stability of a wireframe DNA snub cube with attached nbGFP used to bind a nonessential viral epitope on Pseudorabies virus is evaluated in vitro both with and without one of two modifications designed to enhance stability: 1) the use of trivalent spermidine cations during thermal annealing of the nanostructure, and 2) the introduction of a polylysine-polyethylene glycol coating to the conjugated nanostructure. The design, synthesis, and purification of the multivalent inhibitor were also evaluated and optimized. Without modification, the snub cube nanostructure was stable for up to 8 hours in culture media supplemented with 10% FBS. The spermidine-annealed nanostructures demonstrated lesser degrees of stability and greater degradation than the unmodified structures, whereas the polylysine-coated structures demonstrated equivalent stability at lower valencies and enhanced stability at the highest valency of the snub cube inhibitor. These results support the potential for the polylysine-polyethylene glycol coating as a potential method for enhancing the stability of the snub cube for future in vivo applications.
Biopolymers perform the majority of essential functions necessary for life. From a small amount of components emerges considerable complexity in both structure and function. The separated timescales of dynamic processes and intricate intra- and inter-molecular interactions of these molecules necessitate the development and utilization of computational approaches for biopolymer study and nanotechnology applications. Biopolymer nanotechnology exploits the natural chemistry of biopolymers to perform novel functions at the nanoscale. Molecular dynamics is the numerical simulation of chemical entities according to the physical laws of motion and statistical mechanics. The number of atoms in biopolymers require coarse-grained methods to fully sample the dynamics of the system with reasonable resources. Accordingly, a coarse-grained molecular dynamics model for the characterization of hybrid nucleic acid-protein nanotechnology was developed. Proteins are represented as an anisotropic network model (ANM) which show good agreement with experimentally derived protein dynamics for a small computational cost. The model was subsequently applied to hybrid DNA-protein cages systems and exhibited excellent agreement with experimental results. Ongoing development efforts look to apply network models to oxDNA origami to create multiscale models for DNA origami. The network approximation will allow for detailed simulation of DNA origami association, of concern to DNA crystal and lattice formation. Identification and design of target-specific binders (aptamers) has received considerable attention on account of their diagnostic and therapeutic potential. Generated in selection cycles from extensive random libraries, biopolymer aptamers are of particular interest due to their potential non-immunogenic properties. Machine learning leverages the use of powerful statistical principles to train a model to transform an input into a desired output. Parameters of the model are iteratively adjusted according to the gradient of the cost function. An unsupervised and generative machine learning model was applied to Thrombin aptamer sequence data. From the model, sequence characteristics necessary for binding were identified and new aptamers capable of binding Thrombin were sampled and verified experimentally. Future work on the development and utilization of an unsupervised and interpretable machine learning model for unaligned sequence data is also discussed.
Two distinct aspects of synthetic biology were investigated: the development of viral structures for new methods of studying self-assembly and nanomanufacturing, and the designs of genetic controls systems based on controlling the secondary structure of nucleic acids. Viral structures have been demonstrated as building blocks for molecular self-assembly of diverse structures, but the ease with which viral genomes can be modified to create specific structures depends on the mechanisms by which the viral coat proteins self-assemble. The experiments conducted demonstrate how the mechanisms that guide bacteriophage lambda’s self-assembly make it a useful and flexible platform for further research into biologically enabled self-assembly. While the viral platform investigations focus on the creation of new structures, the genetic control systems research focuses on new methods for signal interpretation in biological systems. Regulators of genetic activity that operate based on the secondary structure formation of ribonucleic acid (RNA), also known as riboswitches, are genetically compact devices for controlling protein translation. The toehold switch ribodevice can be modified to enable multiplexed logical operations with RNA inputs, requiring no additional protein transcription factors to regulate activity, but they cannot receive chemical inputs. RNA sequences generated to bind to specific chemicals, known as aptamers, can be used in riboswitches to confer genetic activity upon binding their target chemical. But attempts to use aptamers for logical operations and genetic circuits are difficult to generalize due to differences in sequence and binding strength. The experiments conducted demonstrate a ribodevice structure in which aptamers can be used semi-interchangeably to translate chemical inputs into the toehold switch paradigm, marrying the programmability and orthogonality of toehold switches with the broad sensing potential of aptamer-based ribodevices.
The propulsion matrix provides a compact description of the locomotion of a single flagella molecular motor in a low Reynolds number environment. The locomotion properties of individual flagellar motors are central to bacterial behavior, including chemotaxis, pathogenesis, and biofilm formation. However, because conventional hydrodynamic measurement approaches require applied forces, torques, or fluid flows, it is not possible to directly measure the propulsion matrix for an individual microscale helical filament. Here, the limitations inherent to conventional measurement approaches are overcome using a combination of theoretical, experimental, and computational advancements. First, the relationship between the elements of the propulsion matrix with translational and rotational Brownian motion is derived using the fluctuation-dissipation theorem. Next, a volumetric fluorescent imaging using high resolution oblique plane microscopy with sufficient spatio-temporal resolution is conducted to resolve both translation and rotation of individual helical filaments isolated from E.coli's flagellar motor. Finally, a computational framework is developed to track individual helical filaments across six degrees of freedom, extract diffusion coefficients, and quantify the temporal correlation between translation and rotation. This study computed the maximum propulsion efficiency to be around 1.7%. Direct measurement of propulsion efficiency generally agrees with the ensemble and large-scale measurements previously performed using conventional hydrodynamic measurements. The findings suggest that the approach described here can be extended to more complex in-vitro experiments that evaluate microscale molecular motors. For example, evaluating sperm motility without inducing chemotaxis or utilizing a microfluidic setup.
Scientists are entrusted with developing novel molecular strategies for effective prophylactic and therapeutic interventions. Antivirals are indispensable tools that can be targeted at viral domains directly or at cellular domains indirectly to obstruct viral infections and reduce pathogenicity. Despite their transformative potential in healthcare, to date, antivirals have been clinically approved to treat only 10 out of the greater than 200 known pathogenic human viruses. Additionally, as obligate intracellular parasites, many virus functions are intimately coupled with host cellular processes. As such, the development of a clinically relevant antiviral is challenged by the limited number of clear targets per virus and necessitates an extensive insight into these molecular processes. Compounding this challenge, many viral pathogens have evolved to evade effective antivirals. Therefore, a means to develop virus- or strain-specific antivirals without detailed insight into each idiosyncratic biochemical mechanism may aid in the development of antivirals against a larger swath of pathogens. Such an approach will tremendously benefit from having the specific molecular recognition of viral species as the lowest barrier. Here, I modify a nanobody (anti-green fluorescent protein) that specifically recognizes non-essential epitopes (glycoprotein M-pHluorin chimera) presented on the extra virion surface of a virus (Pseudorabies virus strain 486). The nanobody switches from having no inhibitory properties (tested up to 50 μM) to ∼3 nM IC50 in in vitro infectivity assays using porcine kidney (PK15) cells. The nanobody modifications use highly reliable bioconjugation to a three-dimensional wireframe deoxyribonucleic acid (DNA) origami scaffold. Mechanistic studies suggest that inhibition is mediated by the DNA origami scaffold bound to the virus particle, which obstructs the internalization of the viruses into cells, and that inhibition is enhanced by avidity resulting from multivalent virus and scaffold interactions. The assembled nanostructures demonstrate negligible cytotoxicity (<10 nM) and sufficient stability, further supporting their therapeutic potential. If translatable to other viral species and epitopes, this approach may open a new strategy that leverages existing infrastructures – monoclonal antibody development, phage display, and in vitro evolution - for rapidly developing novel antivirals in vivo.