Matching Items (22)
Description
After a decade of efforts, accurate and affordable DNA sequencing continues to remain an important goal in current research landscape. This thesis starts with a brief overview of the recent updates in the field of DNA sequencing technologies followed by description of the nanofluidics route to single molecule DNA detection. Chapter 2 presents discusses carbon nanotube(CNT) based nanofluidics. The fabrication and DNA sensing measurements of CNT forest membrane devices are presented. Chapter 3 gives the background for functionalization and recognition aspects of reader molecules. Chapter 4 marks the transition to solid state nanopore nanofluidics. The fabrication of Imidazole functionalized nanopores is discussed. The Single Molecule detection results of DNA from Palladium nanopore devices are presented next. Combining chemical recognition to nanopore technology, it has been possible to prolong the duration of single molecule events from the order of a few micro seconds to upto a few milliseconds. Overall, the work presented in this thesis promises longer single molecule detection time in a nanofludic set up and paves way for novel nanopore- tunnel junction devices that combine recognition chemistry, tunneling device and nanopore approach.
ContributorsKrishnakumar, Padmini (Author) / Lindsay, Stuart (Thesis advisor) / He, Jin (Committee member) / Vaiana, Sara (Committee member) / Schmidt, Kevin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Single molecule DNA Sequencing technology has been a hot research topic in the recent decades because it holds the promise to sequence a human genome in a fast and affordable way, which will eventually make personalized medicine possible. Single molecule differentiation and DNA translocation control are the two main challenges in all single molecule DNA sequencing methods. In this thesis, I will first introduce DNA sequencing technology development and its application, and then explain the performance and limitation of prior art in detail. Following that, I will show a single molecule DNA base differentiation result obtained in recognition tunneling experiments. Furthermore, I will explain the assembly of a nanofluidic platform for single strand DNA translocation, which holds the promised to be integrated into a single molecule DNA sequencing instrument for DNA translocation control. Taken together, my dissertation research demonstrated the potential of using recognition tunneling techniques to serve as a general readout system for single molecule DNA sequencing application.
ContributorsLiu, Hao (Author) / Lindsay, Stuart M (Committee member) / Yan, Hao (Committee member) / Levitus, Marcia (Committee member) / Arizona State University (Publisher)
Created2013
Description
An understanding of diet habits is crucial in implementing proper management strategies for wildlife. Diet analysis, however, remains a challenge for ruminant species. Microhistological analysis, the method most often employed in herbivore diet studies, is tedious and time consuming. In addition, it requires considerable training and an extensive reference plant collection. The development of DNA barcoding (species identification using a standardized DNA sequence) and the availability of recent DNA sequencing techniques offer new possibilities in diet analysis for ungulates. Using fecal material collected from controlled feeding trials on pygmy goats, (Capra hicus), novel DNA barcoding technology using the P6-loop of the chloroplast trnL (UAA) intron was compared with the traditional microhistological technique. At its current stage of technological development, this study demonstrated that DNA barcoding did not enhance the ability to detect plant species in herbivore diets. A higher mean species composition was reported with microhistological analysis (79%) as compared to DNA barcoding (50%). Microhistological analysis consistently reported a higher species presence by forage class. For affect positive species identification, microhistology estimated an average of 89% correct detection in control diets, while DNA barcoding estimated 50% correct detection of species. It was hypothesized that a number of factors, including variation in chloroplast content in feed species and the effect of rumen bacteria on degradation of DNA, influenced the ability to detect plant species in herbivore diets and concluded that while DNA barcoding opens up new possibilities in the study of plant-herbivore interactions, further studies are needed to standardize techniques and for DNA bar-coding in this context.
ContributorsMurphree, Julie Joan (Author) / Miller, William H. (Thesis advisor) / Steele, Kelly (Committee member) / Salywon, Andrew (Committee member) / Arizona State University (Publisher)
Created2012
Description
Single molecule identification is one essential application area of nanotechnology. The application areas including DNA sequencing, peptide sequencing, early disease detection and other industrial applications such as quantitative and quantitative analysis of impurities, etc. The recognition tunneling technique we have developed shows that after functionalization of the probe and substrate of a conventional Scanning Tunneling Microscope with recognition molecules ("tethered molecule-pair" configuration), analyte molecules trapped in the gap that is formed by probe and substrate will bond with the reagent molecules. The stochastic bond formation/breakage fluctuations give insight into the nature of the intermolecular bonding at a single molecule-pair level. The distinct time domain and frequency domain features of tunneling signals were extracted from raw signals of analytes such as amino acids and their enantiomers. The Support Vector Machine (a machine-learning method) was used to do classification and predication based on the signal features generated by analytes, giving over 90% accuracy of separation of up to seven analytes. This opens up a new interface between chemistry and electronics with immediate implications for rapid Peptide/DNA sequencing and molecule identification at single molecule level.
ContributorsZhao, Yanan, 1986- (Author) / Lindsay, Stuart (Thesis advisor) / Nemanich, Robert (Committee member) / Qing, Quan (Committee member) / Ros, Robert (Committee member) / Zhang, Peiming (Committee member) / Arizona State University (Publisher)
Created2014
Description
Single molecules in a tunnel junction can now be interrogated reliably using chemically-functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode ("tethered molecule-pair" configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Importantly, at large tunnel gaps, there exists a regime for many molecules in which the tunneling is influenced more by the chemical identity of the molecules than by variability in the molecule-metal contact. Functionalizing a pair of electrodes with recognition reagents (the "free analyte" configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules.
ContributorsChang, Shuai (Author) / Lindsay, Stuart (Thesis advisor) / Ros, Robert (Committee member) / Zhang, Peiming (Committee member) / Tao, Nongjian (Committee member) / Shumway, John (Committee member) / Arizona State University (Publisher)
Created2012
Description
No two cancers are alike. Cancer is a dynamic and heterogeneous disease, such heterogeneity arise among patients with the same cancer type, among cancer cells within the same individual’s tumor and even among cells within the same sub-clone over time. The recent application of next-generation sequencing and precision medicine techniques is the driving force to uncover the complexity of cancer and the best clinical practice. The core concept of precision medicine is to move away from crowd-based, best-for-most treatment and take individual variability into account when optimizing the prevention and treatment strategies. Next-generation sequencing is the method to sift through the entire 3 billion letters of each patient’s DNA genetic code in a massively parallel fashion.
The deluge of next-generation sequencing data nowadays has shifted the bottleneck of cancer research from multiple “-omics” data collection to integrative analysis and data interpretation. In this dissertation, I attempt to address two distinct, but dependent, challenges. The first is to design specific computational algorithms and tools that can process and extract useful information from the raw data in an efficient, robust, and reproducible manner. The second challenge is to develop high-level computational methods and data frameworks for integrating and interpreting these data. Specifically, Chapter 2 presents a tool called Snipea (SNv Integration, Prioritization, Ensemble, and Annotation) to further identify, prioritize and annotate somatic SNVs (Single Nucleotide Variant) called from multiple variant callers. Chapter 3 describes a novel alignment-based algorithm to accurately and losslessly classify sequencing reads from xenograft models. Chapter 4 describes a direct and biologically motivated framework and associated methods for identification of putative aberrations causing survival difference in GBM patients by integrating whole-genome sequencing, exome sequencing, RNA-Sequencing, methylation array and clinical data. Lastly, chapter 5 explores longitudinal and intratumor heterogeneity studies to reveal the temporal and spatial context of tumor evolution. The long-term goal is to help patients with cancer, particularly those who are in front of us today. Genome-based analysis of the patient tumor can identify genomic alterations unique to each patient’s tumor that are candidate therapeutic targets to decrease therapy resistance and improve clinical outcome.
The deluge of next-generation sequencing data nowadays has shifted the bottleneck of cancer research from multiple “-omics” data collection to integrative analysis and data interpretation. In this dissertation, I attempt to address two distinct, but dependent, challenges. The first is to design specific computational algorithms and tools that can process and extract useful information from the raw data in an efficient, robust, and reproducible manner. The second challenge is to develop high-level computational methods and data frameworks for integrating and interpreting these data. Specifically, Chapter 2 presents a tool called Snipea (SNv Integration, Prioritization, Ensemble, and Annotation) to further identify, prioritize and annotate somatic SNVs (Single Nucleotide Variant) called from multiple variant callers. Chapter 3 describes a novel alignment-based algorithm to accurately and losslessly classify sequencing reads from xenograft models. Chapter 4 describes a direct and biologically motivated framework and associated methods for identification of putative aberrations causing survival difference in GBM patients by integrating whole-genome sequencing, exome sequencing, RNA-Sequencing, methylation array and clinical data. Lastly, chapter 5 explores longitudinal and intratumor heterogeneity studies to reveal the temporal and spatial context of tumor evolution. The long-term goal is to help patients with cancer, particularly those who are in front of us today. Genome-based analysis of the patient tumor can identify genomic alterations unique to each patient’s tumor that are candidate therapeutic targets to decrease therapy resistance and improve clinical outcome.
ContributorsPeng, Sen (Author) / Dinu, Valentin (Thesis advisor) / Scotch, Matthew (Committee member) / Wallstrom, Garrick (Committee member) / Arizona State University (Publisher)
Created2015
Description
There are many biological questions that require single-cell analysis of gene sequences, including analysis of clonally distributed dimeric immunoreceptors on lymphocytes (T cells and B cells) and/or the accumulation of driver/accessory mutations in polyclonal tumors. Lysis of bulk cell populations results in mixing of gene sequences, making it impossible to know which pairs of gene sequences originated from any particular cell and obfuscating analysis of rare sequences within large populations. Although current single-cell sorting technologies can be used to address some of these questions, such approaches are expensive, require specialized equipment, and lack the necessary high-throughput capacity for comprehensive analysis. Water-in-oil emulsion approaches for single cell sorting have been developed but droplet-based single-cell lysis and analysis have proven inefficient and yield high rates of false pairings. Ideally, molecular approaches for linking gene sequences from individual cells could be coupled with next-generation high-throughput sequencing to overcome these obstacles, but conventional approaches for linking gene sequences, such as by transfection with bridging oligonucleotides, result in activation of cellular nucleases that destroy the template, precluding this strategy. Recent advances in the synthesis and fabrication of modular deoxyribonucleic acid (DNA) origami nanostructures have resulted in new possibilities for addressing many current and long-standing scientific and technical challenges in biology and medicine. One exciting application of DNA nanotechnology is the intracellular capture, barcode linkage, and subsequent sequence analysis of multiple messenger RNA (mRNA) targets from individual cells within heterogeneous cell populations. DNA nanostructures can be transfected into individual cells to capture and protect mRNA for specific expressed genes, and incorporation of origami-specific bowtie-barcodes into the origami nanostructure facilitates pairing and analysis of mRNA from individual cells by high-throughput next-generation sequencing. This approach is highly modular and can be adapted to virtually any two (and possibly more) gene target sequences, and therefore has a wide range of potential applications for analysis of diverse cell populations such as understanding the relationship between different immune cell populations, development of novel immunotherapeutic antibodies, or improving the diagnosis or treatment for a wide variety of cancers.
ContributorsSchoettle, Louis (Author) / Blattman, Joseph N (Thesis advisor) / Yan, Hao (Committee member) / Chang, Yung (Committee member) / Lindsay, Stuart (Committee member) / Arizona State University (Publisher)
Created2017
Description
DNA, RNA and Protein are three pivotal biomolecules in human and other organisms, playing decisive roles in functionality, appearance, diseases development and other physiological phenomena. Hence, sequencing of these biomolecules acquires the prime interest in the scientific community. Single molecular identification of their building blocks can be done by a technique called Recognition Tunneling (RT) based on Scanning Tunneling Microscope (STM). A single layer of specially designed recognition molecule is attached to the STM electrodes, which trap the targeted molecules (DNA nucleoside monophosphates, RNA nucleoside monophosphates or amino acids) inside the STM nanogap. Depending on their different binding interactions with the recognition molecules, the analyte molecules generate stochastic signal trains accommodating their “electronic fingerprints”. Signal features are used to detect the molecules using a machine learning algorithm and different molecules can be identified with significantly high accuracy. This, in turn, paves the way for rapid, economical nanopore sequencing platform, overcoming the drawbacks of Next Generation Sequencing (NGS) techniques.
To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day.
In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition, Pyrene reader showed higher DNA base-calling accuracy compare to Imidazole reader, the workhorse in our previous projects. In my other projects, various amino acids and RNA nucleoside monophosphates were also classified with significantly high accuracy using RT. Twenty naturally occurring amino acids and various RNA nucleosides (four canonical and two modified) were successfully identified. Thus, we envision nanopore sequencing biomolecules using Recognition Tunneling (RT) that should provide comprehensive betterment over current technologies in terms of time, chemical and instrumental cost and capability of de novo sequencing.
To read DNA nucleotides with high accuracy in an STM tunnel junction a series of nitrogen-based heterocycles were designed and examined to check their capabilities to interact with naturally occurring DNA nucleotides by hydrogen bonding in the tunnel junction. These recognition molecules are Benzimidazole, Imidazole, Triazole and Pyrrole. Benzimidazole proved to be best among them showing DNA nucleotide classification accuracy close to 99%. Also, Imidazole reader can read an abasic monophosphate (AP), a product from depurination or depyrimidination that occurs 10,000 times per human cell per day.
In another study, I have investigated a new universal reader, 1-(2-mercaptoethyl)pyrene (Pyrene reader) based on stacking interactions, which should be more specific to the canonical DNA nucleosides. In addition, Pyrene reader showed higher DNA base-calling accuracy compare to Imidazole reader, the workhorse in our previous projects. In my other projects, various amino acids and RNA nucleoside monophosphates were also classified with significantly high accuracy using RT. Twenty naturally occurring amino acids and various RNA nucleosides (four canonical and two modified) were successfully identified. Thus, we envision nanopore sequencing biomolecules using Recognition Tunneling (RT) that should provide comprehensive betterment over current technologies in terms of time, chemical and instrumental cost and capability of de novo sequencing.
ContributorsSen, Suman (Author) / Lindsay, Stuart (Thesis advisor) / Zhang, Peiming (Thesis advisor) / Gould, Ian R. (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2016
Description
This thesis describes several approaches to next generation DNA sequencing via tunneling current method based on a Scanning Tunneling Microscope system. In chapters 5 and 6, preliminary results have shown that DNA bases could be identified by their characteristic tunneling signals. Measurements taken in aqueous buffered solution showed that single base resolution could be achieved with economic setups. In chapter 7, it is illustrated that some ongoing measurements are indicating the sequence readout by making linear scan on a piece of short DNA oligomer. However, to overcome the difficulties of controlling DNA especially ssDNA movement, it is much better to have the tunneling measurement incorporated onto a robust nanopore device to realize sequential reading of the DNA sequence while it is being translocated.
ContributorsHuang, Shuo (Author) / Lindsay, Stuart (Thesis advisor) / Sankey, Otto (Committee member) / Tao, Nongjian (Committee member) / Drucker, Jeff (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2011
Description
Rosalind Elsie Franklin worked with X-ray crystallography at King's College London, UK, and she helped determine the helical structure of DNA in the early 1950s. Franklin's research helped establish molecular genetics, a field that investigates how heredity works on the molecular level. The discovery of the structure of DNA also made future research possible into the molecular basis of embryonic development, genetic disorders, and gene manipulation.
ContributorsO'Connell, Lindsey (Author) / Drago, Mary (Editor) / Arizona State University. School of Life Sciences. Center for Biology and Society. Embryo Project Encyclopedia. (Publisher) / Arizona Board of Regents (Publisher)
Created2013-11-17