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- All Subjects: Biomedical Engineering
Description
Volumetric cell imaging using 3D optical Computed Tomography (cell CT) is advantageous for identification and characterization of cancer cells. Many diseases arise from genomic changes, some of which are manifest at the cellular level in cytostructural and protein expression (functional) features which can be resolved, captured and quantified in 3D far more sensitively and specifically than in traditional 2D microscopy. Live single cells were rotated about an axis perpendicular to the optical axis to facilitate data acquisition for functional live cell CT imaging. The goal of this thesis research was to optimize and characterize the microvortex rotation chip. Initial efforts concentrated on optimizing the microfabrication process in terms of time (6-8 hours v/s 12-16 hours), yield (100% v/s 40-60%) and ease of repeatability. This was done using a tilted exposure lithography technique, as opposed to the backside diffuser photolithography (BDPL) method used previously (Myers 2012) (Chang and Yoon 2004). The fabrication parameters for the earlier BDPL technique were also optimized so as to improve its reliability. A new, PDMS to PDMS demolding process (soft lithography) was implemented, greatly improving flexibility in terms of demolding and improving the yield to 100%, up from 20-40%. A new pump and flow sensor assembly was specified, tested, procured and set up, allowing for both pressure-control and flow-control (feedback-control) modes; all the while retaining the best features of a previous, purpose-built pump assembly. Pilot experiments were performed to obtain the flow rate regime required for cell rotation. These experiments also allowed for the determination of optimal trapezoidal neck widths (opening to the main flow channel) to be used for cell rotation characterization. The optimal optical trap forces were experimentally estimated in order to minimize the required optical power incident on the cell. Finally, the relationships between (main channel) flow rates and cell rotation rates were quantified for different trapezoidal chamber dimensions, and at predetermined constant values of laser trapping strengths, allowing for parametric characterization of the system.
ContributorsShetty, Rishabh M (Author) / Meldrum, Deirdre R (Thesis advisor) / Johnson, Roger H (Committee member) / Tillery, Stephen H (Committee member) / Arizona State University (Publisher)
Created2013
Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
Approximately 1% of the world population suffers from epilepsy. Continuous long-term electroencephalographic (EEG) monitoring is the gold-standard for recording epileptic seizures and assisting in the diagnosis and treatment of patients with epilepsy. However, this process still requires that seizures are visually detected and marked by experienced and trained electroencephalographers. The motivation for the development of an automated seizure detection algorithm in this research was to assist physicians in such a laborious, time consuming and expensive task. Seizures in the EEG vary in duration (seconds to minutes), morphology and severity (clinical to subclinical, occurrence rate) within the same patient and across patients. The task of seizure detection is also made difficult due to the presence of movement and other recording artifacts. An early approach towards the development of automated seizure detection algorithms utilizing both EEG changes and clinical manifestations resulted to a sensitivity of 70-80% and 1 false detection per hour. Approaches based on artificial neural networks have improved the detection performance at the cost of algorithm's training. Measures of nonlinear dynamics, such as Lyapunov exponents, have been applied successfully to seizure prediction. Within the framework of this MS research, a seizure detection algorithm based on measures of linear and nonlinear dynamics, i.e., the adaptive short-term maximum Lyapunov exponent (ASTLmax) and the adaptive Teager energy (ATE) was developed and tested. The algorithm was tested on long-term (0.5-11.7 days) continuous EEG recordings from five patients (3 with intracranial and 2 with scalp EEG) and a total of 56 seizures, producing a mean sensitivity of 93% and mean specificity of 0.048 false positives per hour. The developed seizure detection algorithm is data-adaptive, training-free and patient-independent. It is expected that this algorithm will assist physicians in reducing the time spent on detecting seizures, lead to faster and more accurate diagnosis, better evaluation of treatment, and possibly to better treatments if it is incorporated on-line and real-time with advanced neuromodulation therapies for epilepsy.
ContributorsVenkataraman, Vinay (Author) / Jassemidis, Leonidas (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2012
Description
Development of post-traumatic epilepsy (PTE) after traumatic brain injury (TBI) is a major health concern (5% - 50% of TBI cases). A significant problem in TBI management is the inability to predict which patients will develop PTE. Such prediction, followed by timely treatment, could be highly beneficial to TBI patients. Six male Sprague-Dawley rats were subjected to a controlled cortical impact (CCI). A 6mm piston was pneumatically driven 3mm into the right parietal cortex with velocity of 5.5m/s. The rats were subsequently implanted with 6 intracranial electroencephalographic (EEG) electrodes. Long-term (14-week) continuous EEG recordings were conducted. Using linear (coherence) and non-linear (Lyapunov exponents) measures of EEG dynamics in conjunction with measures of network connectivity, we studied the evolution over time of the functional connectivity between brain sites in order to identify early precursors of development of epilepsy. Four of the six TBI rats developed PTE 6 to 10 weeks after the initial insult to the brain. Analysis of the continuous EEG from these rats showed a gradual increase of the connectivity between critical brain sites in terms of their EEG dynamics, starting at least 2 weeks prior to their first spontaneous seizure. In contrast, for the rats that did not develop epilepsy, connectivity levels did not change, or decreased during the whole course of the experiment across pairs of brain sites. Consistent behavior of functional connectivity changes between brain sites and the "focus" (site of impact) over time was demonstrated for coherence in three out of the four epileptic and in both non-epileptic rats, while for STLmax in all four epileptic and in both non-epileptic rats. This study provided us with the opportunity to quantitatively investigate several aspects of epileptogenesis following traumatic brain injury. Our results strongly support a network pathology that worsens with time. It is conceivable that the observed changes in spatiotemporal dynamics after an initial brain insult, and long before the development of epilepsy, could constitute a basis for predictors of epileptogenesis in TBI patients.
ContributorsTobin, Edward (Author) / Iasemidis, Leonidas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
Description
Non-invasive visualization of the trigeminal nerve through advanced MR sequences and methods like tractography is important for studying anatomical and microstructural changes due to pathology like trigeminal neuralgia (TN), facial dystonia, multiple sclerosis, and for surgical pre-planning. The use of specific anatomical markers from CT, MPRAGE and cranial nerve imaging (CRANI) sequences, enabled successful tractography of patient-specific trajectory of the frontal, nasociliary, infraorbital, and mandibular nerve branches extending beyond the cisternal brain stem region and leading to the face. Performance of MPRAGE sequence together with the advanced T2-weighted CRANI sequence with and without a gadolinium contrast agent, was studied to characterize identification efficiency in smaller nerve structures in the extremities. A large FOV nerve visualization exam inclusive of the anatomy of all trigeminal nerve distal branches can be obtained within an acquisition time of 20 minutes using pre-contrast CRANI and MPRAGE. Post-processing with MPR and MIP images improved nerve visualization.Transcranial electrical stimulation techniques (TES) have been used for the treatment of multiple neurodegenerative diseases. These techniques involve placing electrodes on the scalp with multiple peripheral branches of the trigeminal nerve crossing directly under that may be stimulated. This was studied through hybrid computational realistic axon models. These models also facilitated studying the effects of electrode drift during experiments on the recruitment of peripheral nerves. An optimal point of lowest threshold was found while displacing the nerve horizontally i.e., the activation thresholds of both myelinated and unmyelinated axons increased when the electrodes were displaced medially and decreased to a certain extend when the electrodes were displaced laterally, after which further lateral displacement led to increase of thresholds. Inclusion of unmyelinated axons in the modeling provided the capability of finding maximum stimulation amplitude below which side effects like pain sensation may be avoided. In the case of F3 – F4 electrode montage the maximum amplitude was 2.39 mA and in case of RS – LS montage the maximum amplitude was 2.44 mA. Such modeling studies may be useful for personalization of TES devices for finding optimal positioning of electrodes with respect to target and stimulation amplitude range that minimizes side effects.
ContributorsSahu, Sulagna (Author) / Sadleir, Rosalind (Thesis advisor) / Tillery, Stephen H (Committee member) / Crook, Sharon (Committee member) / Beeman, Scott (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2023
Detect and analyze the 3-D head movement patterns in marmoset monkeys using wireless tracking system
Description
Head movement is a natural orienting behavior for sensing environmental events around us. Head movement is particularly important for identifying through the sense of hearing the location of an out-of-sight, rear-approaching target to avoid danger or threat. This research aims to design a portable device for detecting the head movement patterns of common marmoset monkeys in laboratory environments. Marmoset is a new-world primate species and has become increasingly popular for neuroscience research. Understanding the unique patterns of their head movements will improve its values as a new primate model for uncovering the neurobiology of natural orienting behavior. Due to their relatively small head size (5 cm in diameter) and body weight (300-500 g), the device has to meet several unique design requirements with respect to accuracy and workability. A head-mount wireless tracking system was implemented based on inertial sensors that are capable of detecting motion in the Yaw, Pitch and Roll axes. The sensors were connected to the encoding station, which transmits wirelessly the 3-axis movement data to the decoding station at the sampling rate of ~175 Hz. The decoding station relays this information to the computer for real-time display and analysis. Different tracking systems, based on the accelerometer and Inertial Measurement Unit is implemented to track the head movement pattern of the marmoset head. Using these systems, translational and rotational information of head movement are collected, and the data analysis focuses on the rotational head movement in body-constrained marmosets. Three stimulus conditions were tested: 1) Alert, 2) Idle 3) Sound only. The head movement patterns were examined when the house light was turned on and off for each stimulus. Angular velocity, angular displacement and angular acceleration were analyzed in all three axes.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.
Fast and large head turns were observed in the Yaw axis in response to the alert stimuli and not much in the idle and sound-only stimulus conditions. Contrasting changes in speed and range of head movement were found between light-on and light-off situations. The mean peak angular displacement was 95 degrees (light on) and 55 (light off) and the mean peak angular velocity was 650 degrees/ second (light on) and 400 degrees/second (light off), respectively, in response to the alert stimuli. These results suggest that the marmoset monkeys may engage in different modes of orienting behaviors with respect to the availability of visual cues and thus the necessity of head movement. This study provides a useful tool for future studies in understanding the interplay among visual, auditory and vestibular systems during nature behavior.
ContributorsPandey, Swarnima (Author) / Zhou, Yi (Thesis advisor) / Tillery, Stephen H (Thesis advisor) / Buneo, Christpher A (Committee member) / Arizona State University (Publisher)
Created2015
Description
From time immemorial, epilepsy has persisted to be one of the greatest impediments to human life for those stricken by it. As the fourth most common neurological disorder, epilepsy causes paroxysmal electrical discharges in the brain that manifest as seizures. Seizures have the effect of debilitating patients on a physical and psychological level. Although not lethal by themselves, they can bring about total disruption in consciousness which can, in hazardous conditions, lead to fatality. Roughly 1\% of the world population suffer from epilepsy and another 30 to 50 new cases per 100,000 increase the number of affected annually. Controlling seizures in epileptic patients has therefore become a great medical and, in recent years, engineering challenge.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
In this study, the conditions of human seizures are recreated in an animal model of temporal lobe epilepsy. The rodents used in this study are chemically induced to become chronically epileptic. Their Electroencephalogram (EEG) data is then recorded and analyzed to detect and predict seizures; with the ultimate goal being the control and complete suppression of seizures.
Two methods, the maximum Lyapunov exponent and the Generalized Partial Directed Coherence (GPDC), are applied on EEG data to extract meaningful information. Their effectiveness have been reported in the literature for the purpose of prediction of seizures and seizure focus localization. This study integrates these measures, through some modifications, to robustly detect seizures and separately find precursors to them and in consequence provide stimulation to the epileptic brain of rats in order to suppress seizures. Additionally open-loop stimulation with biphasic currents of various pairs of sites in differing lengths of time have helped us create control efficacy maps. While GPDC tells us about the possible location of the focus, control efficacy maps tells us how effective stimulating a certain pair of sites will be.
The results from computations performed on the data are presented and the feasibility of the control problem is discussed. The results show a new reliable means of seizure detection even in the presence of artifacts in the data. The seizure precursors provide a means of prediction, in the order of tens of minutes, prior to seizures. Closed loop stimulation experiments based on these precursors and control efficacy maps on the epileptic animals show a maximum reduction of seizure frequency by 24.26\% in one animal and reduction of length of seizures by 51.77\% in another. Thus, through this study it was shown that the implementation of the methods can ameliorate seizures in an epileptic patient. It is expected that the new knowledge and experimental techniques will provide a guide for future research in an effort to ultimately eliminate seizures in epileptic patients.
ContributorsShafique, Md Ashfaque Bin (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Muthuswamy, Jitendran (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2016
Description
Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or slowed. An estimated 5.4 million Americans live with AD, and this number is expected to triple by year 2050 as the baby boomers age. The cost of care for AD in the US is about $200 billion each year. Unfortunately, in addition to the lack of an effective treatment or AD, there is also a lack of an effective diagnosis, particularly an early diagnosis which would enable treatment to begin before significant neuronal damage has occurred.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.
Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
ContributorsTian, Huilai (Author) / Sierks, Michael R (Thesis advisor) / Dai, Lenore (Committee member) / Tillery, Stephen H (Committee member) / Nielsen, David R (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2014
Description
Electromagnetic fields (EMFs) generated by biologically active neural tissue are critical in the diagnosis and treatment of neurological diseases. Biological EMFs are characterized by electromagnetic properties such as electrical conductivity, permittivity and magnetic susceptibility. The electrical conductivity of active tissue has been shown to serve as a biomarker for the direct detection of neural activity, and the diagnosis, staging and prognosis of disease states such as cancer. Magnetic resonance electrical impedance tomography (MREIT) was developed to map the cross-sectional conductivity distribution of electrically conductive objects using externally applied electrical currents. Simulation and in vitro studies of invertebrate neural tissue complexes demonstrated the correlation of membrane conductivity variations with neural activation levels using the MREIT technique, therefore laying the foundation for functional MREIT (fMREIT) to detect neural activity, and future in vivo fMREIT studies.
The development of fMREIT for the direct detection of neural activity using conductivity contrast in in vivo settings has been the focus of the research work presented here. An in vivo animal model was developed to detect neural activity initiated changes in neuronal membrane conductivities under external electrical current stimulation. Neural activity was induced in somatosensory areas I (SAI) and II (SAII) by applying electrical currents between the second and fourth digits of the rodent forepaw. The in vivo animal model involved the use of forepaw stimulation to evoke somatosensory neural activations along with hippocampal fMREIT imaging currents contemporaneously applied under magnetic field strengths of 7 Tesla. Three distinct types of fMREIT current waveforms were applied as imaging currents under two inhalants – air and carbogen. Active regions in the somatosensory cortex showed significant apparent conductivity changes as variations in fMREIT phase (φ_d and ∇^2 φ_d) signals represented by fMREIT activation maps (F-tests, p <0.05). Consistent changes in the standard deviation of φ_d and ∇^2 φ_d in cortical voxels contralateral to forepaw stimulation were observed across imaging sessions. These preliminary findings show that fMREIT may have the potential to detect conductivity changes correlated with neural activity.
The development of fMREIT for the direct detection of neural activity using conductivity contrast in in vivo settings has been the focus of the research work presented here. An in vivo animal model was developed to detect neural activity initiated changes in neuronal membrane conductivities under external electrical current stimulation. Neural activity was induced in somatosensory areas I (SAI) and II (SAII) by applying electrical currents between the second and fourth digits of the rodent forepaw. The in vivo animal model involved the use of forepaw stimulation to evoke somatosensory neural activations along with hippocampal fMREIT imaging currents contemporaneously applied under magnetic field strengths of 7 Tesla. Three distinct types of fMREIT current waveforms were applied as imaging currents under two inhalants – air and carbogen. Active regions in the somatosensory cortex showed significant apparent conductivity changes as variations in fMREIT phase (φ_d and ∇^2 φ_d) signals represented by fMREIT activation maps (F-tests, p <0.05). Consistent changes in the standard deviation of φ_d and ∇^2 φ_d in cortical voxels contralateral to forepaw stimulation were observed across imaging sessions. These preliminary findings show that fMREIT may have the potential to detect conductivity changes correlated with neural activity.
ContributorsAshok Kumar, Neeta (Author) / Sadleir, Rosalind J (Thesis advisor) / Greger, Bradley (Committee member) / Muthuswamy, Jitendran (Committee member) / Tillery, Stephen H (Committee member) / Sohn, SungMin (Committee member) / Arizona State University (Publisher)
Created2020
Description
One of the single-most insightful, and visionary talks of the 20th century, “There’s plenty of room at the bottom,” by Dr. Richard Feynman, represented a first foray into the micro- and nano-worlds of biology and chemistry with the intention of direct manipulation of their individual components. Even so, for decades there has existed a gulf between the bottom-up molecular worlds of biology and chemistry, and the top-down world of nanofabrication. Creating single molecule nanoarrays at the limit of diffraction could incentivize a paradigm shift for experimental assays. However, such arrays have been nearly impossible to fabricate since current nanofabrication tools lack the resolution required for precise single-molecule spatial manipulation. What if there existed a molecule which could act as a bridge between these top-down and bottom-up worlds?
At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.
The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
At ~100-nm, a DNA origami macromolecule represents one such bridge, acting as a breadboard for the decoration of single molecules with 3-5 nm resolution. It relies on the programmed self-assembly of a long, scaffold strand into arbitrary 2D or 3D structures guided via approximately two hundred, short, staple strands. Once synthesized, this nanostructure falls in the spatial manipulation regime of a nanofabrication tool such as electron-beam lithography (EBL), facilitating its high efficiency immobilization in predetermined binding sites on an experimentally relevant substrate. This placement technology, however, is expensive and requires specialized training, thereby limiting accessibility.
The work described here introduces a method for bench-top, cleanroom/lithography-free, DNA origami placement in meso-to-macro-scale grids using tunable colloidal nanosphere masks, and organosilane-based surface chemistry modification. Bench-top DNA origami placement is the first demonstration of its kind which facilitates precision placement of single molecules with high efficiency in diffraction-limited sites at a cost of $1/chip. The comprehensive characterization of this technique, and its application as a robust platform for high-throughput biophysics and digital counting of biomarkers through enzyme-free amplification are elucidated here. Furthermore, this technique can serve as a template for the bottom-up fabrication of invaluable biophysical tools such as zero mode waveguides, making them significantly cheaper and more accessible to the scientific community. This platform has the potential to democratize high-throughput single molecule experiments in laboratories worldwide.
ContributorsShetty, Rishabh Manoj (Author) / Hariadi, Rizal F (Thesis advisor) / Gopinath, Ashwin (Committee member) / Varsani, Arvind (Committee member) / Nikkhah, Mehdi (Committee member) / Tillery, Stephen H (Committee member) / Hu, Ye (Committee member) / Arizona State University (Publisher)
Created2019