Aptamers are biomolecular ligands composed of nucleic acids. They can be selected to bind specifically to a range of target molecules and subsequently exploited in a fashion analogous to more traditional biomolecules such as antibodies. In this study a method for selecting new aptamers which specifically bind whole live bacterial cells is described. A non-pathogenic strain of Escherichia coli K12 was used to develop the method. A DNA library containing 100 bases long random nucleotide sequences was produced and the aptamer selection process was repeated nine times. An enzyme-linked technique was first used to detect bound aptamers thereafter fluorimetry and fluorescence microscopy methods were used for the detection. The aptamers were cloned and sequenced and the cloned aptamers produced with fluorescent labels. The E. coli K12-binding aptamers were used to demonstrate the detection of the bacterial cells in a complex food matrix, namely probiotic yogurt, by using fluorescence based detection method. The aptamer selection method with some modifications was also used to select aptamers with specificity for the food pathogens E. coli O157, Listeria monocytogenes, L. innocua, S. typhimurium and S. enteritidis. The aptamers against E. coli O157 and S. typhimurium were cloned and the sequences and the binding properties of these aptamers were analysed. The use of E. coli K12 as a target organism and the aptamer sequences presented in this study, have not previously been published in scientific literature. This is also the first report where the aptamers have been used in detection of live bacterial cells in yogurt.

The timely identification of pathogens responsible for disease outbreaks is crucial for implementing effective control measures and minimizing the spread of infectious diseases. Conventional methods of identification are limited to specific pathogen species because they require prior knowledge and pure cultures of the pathogen. Therefore, these methods cannot detect new pathogens responsible for newly emerging diseases. Computational methods that rely on sequencing data have the potential to overcome these limitations. However, the diverse phenotypes among microbial species and strains within the same species pose a challenge in accurately identifying the specific pathogen responsible for the disease. This dissertation highlights the importance of strain-level detection for the identification and characterization of pathogens by employing computational methods that rely on genomic and metagenomic sequencing data. To realize that computational goal, a comparison of different tools, currently used for metagenome classification, was done to illustrate effective detection of bacterial pathogens. To develop computational methods for characterization, genomes of the plant pathogen Ralstonia solanacearum were studied to understand the basis of virulence at cool temperatures. Finally, a new tool was developed that combines accurate detection and characterization at the strain level, through the use of taxonomic databases constructed using genome similarity thresholds. This dissertation work is a contribution to the development of improved approaches to detect and contain disease outbreaks in plants with possible applications in human and animal diseases as well. / Doctor of Philosophy / Detecting and identifying pathogens is crucial for controlling disease outbreaks in humans, animals, and plants. However, currently used methods are limited to identifying only those pathogens that can be grown in a lab. An ideal method for pathogen detection should be broadly applicable to many pathogens. A newer technique called metagenome sequencing allows us to identify known as well as unknown pathogens, including the ones that cannot be grown in a lab. This makes it possible to detect new pathogens from newly emerging diseases. Computational tools that accurately analyze the sequencing data are needed. This dissertation highlights the importance of accurately identifying specific strains of pathogens using computational techniques based on genomic and metagenomic sequencing data. As a result, different tools were evaluated for classifying metagenomes for the successful detection of bacterial pathogens. For the characterization of specific traits responsible for causing disease, genomes of Ralstonia solanacearum, a plant pathogen, were studied to understand how some strains remain harmful at lower temperatures. The dissertation also introduces a novel metagenomic classification tool that combines accurate detection and characterization of pathogen strains by using genome similarity thresholds to create taxonomic databases. This approach improves our ability to identify and understand pathogens at a more specific level. Overall, this research aims to enhance our ability to identify and understand pathogens, allowing for more effective measures to control and prevent disease outbreaks.

Detection of cellular messenger RNA is a useful diagnostic strategy for the detection of patho-gens. A rapid and sensitive method for on-site detection of specific pathogens would be of great use in a number of fields. For example, a simple and inexpensive method for the detection of harmful biological agents in train stations and airports is useful for national security. Rapid detection of pathogenic E. coli strains in food production would also be of great benefit in ensuring the safety and quality of our food supply. Here we present a method for the rapid de-tection of cellular mRNA. This system is based on the 3’-labeling approach in which targeted RNA is simultaneously extended and labeled with the use of biotin labeled-dNTPs and DNA po-lymerase on an immobilized nucleic acid probe. The biotin is subsequently converted to an enzymatic label, which produces a detectable chemiluminescent reaction in the presence of substrate. Detection time of this system is short (approximately 20 minutes) because there is no need for amplification by PCR, transcription, or fluorophore labeling. This novel methodology has been successfully demonstrated by selective detection of lac Z mRNA in a total RNA sample from E. coli.

This work introduces technology for rapid pathogen detection using handheld optical immunoassay and wire-guided droplet PCR systems. There have been a number of cases of foodborne or waterborne illness among humans that are caused by pathogens such as Escherichia coli O157:H7, Salmonella typhimurium, Influenza A H1N1, and the norovirus. The current practices to detect such pathogenic agents are: cell/viral culturing, immunoassays, or polymerase chain reactions (PCRs). These methods are essentially laboratory-based methods that are not at all real-time and thus unavailable for early-monitoring of such pathogens. They are also very difficult to be implemented in field, preventing early detection opportunities. This dissertation is divided into three papers that present methodologies towards the expeditious detections of infectious pathogens and the miniaturization of these detection systems towards field-deployable and point-of-care applications. Specifically, the work presented focuses on two methodologies: (1) light scatter detection using immunoagglutination assays with optimized Mie light scatter parameters in a real biological matrix consisting of plant tissue, and (2) wire-guided droplet manipulations for rapid and improved sample analysis, preparation, and PCR thermocycling. Both of these methods carry a collective objective towards providing high impact technologies for addressing the issues of food-related outbreaks and overall public safety. In the first paper, the direct and sensitive detection of foodborne pathogens from fresh produce samples was accomplished using a handheld lab-on-a-chip device, requiring little to no sample processing and enrichment steps for a near-real-time detection and truly field-deployable device. The detection of Escherichia coli K12 and O157:H7 in iceberg lettuce was achieved utilizing optimized Mie light scatter parameters with a latex particle immunoagglutination assay. The system exhibited good sensitivity, with a limit of detection of 10 CFU mL⁻¹ and an assay time of <6 min. Minimal pretreatment with no detrimental effects on assay sensitivity and reproducibility was accomplished with a simple and cost-effective KimWipes filter and disposable syringe. Mie simulations were used to determine the optimal parameters (particle size d, wavelength λ, and scatter angle θ) for the assay that maximize light scatter intensity of agglutinated latex microparticles and minimize light scatter intensity of the tissue fragments of iceberg lettuce, which were experimentally validated. This introduces a powerful method for detecting foodborne pathogens in fresh produce and other potential sample matrices. The integration of a multi-channel microfluidic chip allowed for differential detection of the agglutinated particles in the presence of the antigen, revealing a true field-deployable detection system with decreased assay time and improved robustness over comparable benchtop systems. In the second paper, we demonstrate a novel method of wire-guided droplet manipulations towards very quick RT-PCR. Because typical RT-PCR assays take about 1–2 h for thermocycling, there is a growing need to further speed up the thermocycling to less than 30 min. Additionally, the PCR assay system should be made portable as a point- of-care detection tool. Rapid movements of droplets (immersed in oil) over three different temperature zones make very quick PCR possible, as heating/cooling will be made by convective heat transfer, whose heat transfer coefficients are much higher than that of conduction, the latter of which is used in most conventional PCR systems. A 30-cycle PCR of a 160 bp gene sequence amplified from 2009 H1N1 influenza A (human origin) was successfully demonstrates in 6 min and 50 sec for a very large 10 μL droplet (with additional 4 min for reverse transcription). The proposed system has a potential to become a rapid, portable, point-of-care tool for detecting influenza A. In the third paper, a wire-guided CNC apparatus was used to perform droplet centrifugation, DNA extraction, and VQ-PCR thermocycling on a single superhydrophobic surface measuring 25 mm by 55 mm and a multi-chambered PCB heater. This methodology exhibited no limitations on the complexity and configuration of procedures that it can perform, making it versatile and far-reaching in its applications. The only modification required for adding or implementing changes for a new protocol is through simple pre-defined programming. The highly adaptive and flexible system was used to execute easily pre-programmed droplet movements and manipulations for the rapid detection of Escherichia coli from PCR detection. Serial dilutions were performed to simulate a diluted field sample with a high level of accuracy. Centrifugation of the diluted sample containing E. coli demonstrated a novel approach to sample pre-treatment. Furthermore, the extraction of DNA from the sample droplet containing E. coli was also performed on the same superhydrophobic surface as the previous 2 steps, requiring less than 10 min. Following extraction, the genetic material was amplified using wire-guided droplet PCR thermocycling, successfully completing 30 cycles of Peptidase D (a long 1500 bp sequence) in 10 min. The droplet centrifugation process was determined to greatly improve the positive band intensity over the non-centrifuged sample. Thus, this work demonstrates the adaptability of the system to replace many common laboratory tasks on a single platform (through re-programmability), in rapid succession (using droplets), and with a high level of accuracy and automation.

This research demonstrates technology for detection of pathogens and environmental monitoring using a handheld optofluidic immunosensor and CFD simulation. The current methods such as ELISA and PCR require few hours for identification which means it is unavailable for early-monitoring. The use of a near-real-time, handheld biosensor device in a real animal/human environment is the key to monitoring the spread of dangerous pathogens. A 3-D computational fluid dynamics (CFD) simulation is needed to track the pathogens within an environment.This dissertation has four papers that demonstrate technologies for the detection and monitoring of pathogens and the miniaturization of these detection systems for in field applications with a handheld immunosensor and CFD simulation.In the first paper, an environmental prediction model was developed for optimal ventilation in a mushroom house by using sensible heat balance and 3-D CFD method. It is shown that the models can be used for farmers to predict the environmental conditions over different locations in a mushroom house.In the second paper, a field lab-on-a-chip system was constructed to detect mouse immunoglobulin G and Escherichia coli by using light scattering detection of particle immunoagglutination. Antibody-conjugated particles were able to be stored in a 4°C refrigerator for at least 4 weeks and to be lyophilized as a powder form for the storage in room temperature.In the third paper, rapid monitoring of the spreads of porcine reproductive and respiratory syndrome virus (PRRSV) was attempted using samples collected from nasal swabs of pigs and air samplers within an experimental swine building. An optofluidic device containing liquid-core waveguides was used to detect. It is shown that the developed optofluidic device and 3-D CFD model can serve as a good model for monitoring the spread of airborne viruses within animal and human environments.In the fourth paper, a handheld optofluidic immunosensor was developed for rapid detection of H1N1/2009 virus inside a 1:10 scale mock classroom. Both miniature spectrometer and cell phone camera were used as detector. A 3-D computational fluid dynamics (CFD) model was developed to track the transport/distribution of H1N1/2009 viruses, and corresponded very well with immunosensor readings.

This dissertation is composed of two projects dedicated to the development of techniques and technologies for improving the quality of life for patients in both clinical and resource-limited settings. The purpose of the first project was to design a rapid diagnostic device to screen whole blood samples for the presence of infectious agents. Point-of-care (PoC) technologies are becoming increasingly important for the detection of infectious agents in resource-limited settings (RSLs) where state-of-the-art blood screening practices are not feasible for implementation. For this project, a rapid diagnostic device was developed to directly detect pathogen content within freshly drawn whole blood samples using a ligand-binding assay format. The assay is completely self-contained within a hermetically sealed device to minimize operational complexity and ensure operator safety. The diagnostic device is capable of processing complex sample matrices by selectively capturing, concentrating, and labeling infectious agents upon functionalized surfaces. Following sample processing, the assay is optically interrogated with a fluorescence-based reader to provide rapid feedback regarding sample purity. Designs of the rapid diagnostic platform evolved over several prototype generations corresponding to project milestones emphasizing ergonomic performance, military specification testing for environmental resilience, and manufacture to yield production-grade devices for future diagnostic performance data collection. The goal of the regenerative therapy-based portion of this research was to develop a novel technique for the selective enrichment of cells demonstrating enhanced regenerative capacity in tissue-extracted cell samples. Adherent cell cultures of stromal vascular fractions (SVFs) extracted from adipose tissues were exposed to nutrient deficient conditions' eliciting a bimodal cellular response between two dissimilar cell culture subpopulations. The regenerative capacity of these two distinct subpopulations was evaluated by assessing their characteristic morphology, metabolic activity, and ability to undergo multilineage differentiation. The SVF subpopulation which demonstrated sensitivity to the nutrient deficient conditions expressed typical morphological expression of adherent cell cultures, elevated metabolic activity, and the ability to differentiate along adipogenic, chondrogenic, and osteogenic lineages. The SVF subpopulation which demonstrated resistance to the nutrient deficient conditions, however, expressed atypical morphologies, impaired metabolic activity, and did not survive culture with differentiation growth media. Based on the data, the 'treatment-sensitive' SVF subpopulation demonstrated a greater regenerative capacity than the‘treatment-resistant' subpopulation. Furthermore, the treatment-resistant subpopulation of the SVF may be representative of the damaged, senescent, and otherwise less-functional cells that comprise a significant portion of tissue-extracted cell samples and pose a significant risk to therapeutic efficacy and reproducibility. Ultimately, this expedient and inexpensive bioprocessing technique may serve to improve cell-based regenerative therapies by eliminating undesirable cells from culture.

Doctor of Philosophy / Department of Chemistry / Jun Li / Reduction in electrode size down to nanometers dramatically enhances the detection sensitivity and temporal resolution. Here we explore nanoelectrode arrays (NEAs) and nanoparticles in building high performance biosensors. Vertically aligned carbon nanofibers (VACNFs) of diameter ~100 nm were grown on a Si substrate using plasma enhanced chemical vapor deposition. SiO[subscript]2 embedded CNF NEAs were then fabricated using techniques like chemical vapor deposition, mechanical polishing, and reactive ion etching, with CNF tips exposed at the final step. The effect of the interior structure of CNFs on electron transfer rate (ETR) was investigated by covalently attaching ferrocene molecules to the exposed end of CNFs. Anomalous differences in the ETR were observed between DC voltammetry (DCV) and AC voltammetry (ACV). The findings from this study are currently being extended to develop an electrochemical biosensor for the detection of cancerous protease (legumain). Preliminary results with standard macro glassy carbon electrodes show a significant decrease in ACV signal, which is encouraging. In another study, NEA was employed to capture and detect pathogenic bacteria using AC dielectrophoresis (DEP) and electrochemical impedance spectroscopy (EIS). A nano-DEP device was fabricated using photolithography processes to define a micro patterned exposed active region on NEA and a microfluidic channel on macro-indium tin oxide electrode. Enhanced electric field gradient at the exposed CNF tips was achieved due to the nanometer size of the electrodes, because of which each individual exposed tip can act as a potential DEP trap to capture the pathogen. Significant decrease in the absolute impedance at the NEA was also observed by EIS experiments. In a final study, we modified gold nanoparticles (GNPs) with luminol to develop chemiluminescence (CL) based blood biosensor. Modified GNPs were characterized by UV-Vis, IR spectroscopy and TEM. We have applied this CL method for the detection of highly diluted blood samples, in both intact and lysed forms, which releases Fe[superscipt]3[superscript]+ containing hemoglobin to catalyze the luminol CL. Particularly, the lysed blood sample can be detected even after 10[superscript]8 dilution (corresponding to ~0.18 cells/well). This method can be readily developed as a portable biosensing technique for rapid and ultrasensitive point-of-care applications.

L’étude, la détection et l’identification de pathogènes est une problématique majeure pour la sécurité alimentaire et la médecine. Cependant, les pathogènes bactériens présents à de faibles concentrations nécessitent souvent une période de plus de 36h pour être identifiés par les méthodes standards. Ce délai est extrêmement contraignant pour des domaines où la rapidité du diagnostic est un facteur clé. Il y a donc une forte demande pour le développement d’outils pour mieux comprendre le comportement bactérien et ainsi développer des techniques de détection plus rapides et plus performantes.Les systèmes d’imagerie SPR sont largement utilisés pour l’analyse d’interactions moléculaires, car ils permettent une mesure en parallèle, en temps réel et sans marquage, tout en étant faciles d’utilisation et compatibles avec des milieux complexes. Cette technique a montré son efficacité pour l'étude et la détection de bactéries en utilisant les interactions moléculaires avec les anticorps, mais les délais de détection restent pénalisants.Dans ce contexte, un nouveau système d’imagerie permettant l’étude et la détection spécifique de pathogènes bactériens performant est développé en mettant à profit les avancées récentes en imagerie SPR optimisée en résolution. Notre système permet d'améliorer les temps de détection de pathogènes en milieux modèles grâce à sa capacité à détecter des bactéries individuelles. Il peut également être utilisé pour l'étude de l'interaction entre bactéries et surfaces spécifiques. Des premiers tests montrent que notre instrument est capable de caractériser le comportement bactérien de plusieurs souches bactériennes en interaction avec des surfaces fonctionnalisées par des espèces chimiques différentes / The study, detection and identification of pathogens is a major issue for food safety and medicine. However, bacterial pathogens present at low concentrations often require a period of more than 36 hours to be identified by standard methods. This delay is extremely constraining for areas where rapid diagnosis is a key factor. There is therefore a strong demand for the development of tools to better understand bacterial behavior and thus develop faster and more efficient detection techniques.SPR imaging systems are widely used for the analysis of molecular interactions, as they allow parallel, real-time and unlabeled measurement, while being easy to use and compatible with complex media. This technique has proven effective in the study and detection of bacteria using molecular interactions with antibodies, but detection times remain penalizing.In this context, a new imaging system allowing the study and specific detection of high-performance bacterial pathogens is being developed, taking advantage of recent advances in SPR imaging optimized in resolution. Our system improves pathogen detection times in model environments through its ability to detect individual bacteria. It can also be used to study the interaction between bacteria and specific surfaces. Initial tests show that our instrument is capable of characterizing the bacterial behaviour of several bacterial strains in interaction with surfaces functionalized by different chemical species.

With the ability to produce reads with hundreds of kilobases in length, long-read sequencing technology is emerging as a powerful tool to decode complex genetic sequences that are previously inaccessible for short reads. Though the sequencing chemistry and base calling algorithm are being actively developed, the accuracy of the current long-read sequencing is still considerably low, thus limiting its applications. In this dissertation, I present three long read based DNA sequencing methods to overcome the limitation of read accuracy, contribute to a better understanding of Cas9 editing outcomes and mitochondrial DNA heterogeneity, and pave the way for real-time pathogen detection and mutation surveillance. The development of IDMseq enables the single-base-resolution haplotype-resolved quantitative characterization of diverse types of rare variants. IDMseq provides the first quantitative evidence of persistent nonrandom large structural variants following repair of double-strand breaks induced by CRISPR-Cas9 in human ESCs. The development of iMiGseq represents the first mitochondrial DNA sequencing method that provides ultra-sensitive variant detection, complete haplotyping, and unbiased evaluation of heteroplasmy levels, all at the individual mitochondrial DNA molecule level. iMiGseq uncovers unappreciated levels of heteroplasmic variants in single healthy human oocytes well below the current 1% detection limit, of which numerous variants are deleterious and associated with late-onset mitochondrial disease and cancer. It could comprehensively characterize and haplotype single-nucleotide and structural variants of mitochondrial DNA and their genetic linkage in NARP/Leigh syndrome patient-derived cells. The development of NIRVANA deals with the COVID-19 pandemic. NIRVANA can simultaneously detect SARS-CoV-2 and three co-infecting respiratory viruses, and monitor mutations for up to 96 samples in real time. It provides a promising solution for rapid field-deployable detection and mutation surveillance of pandemic viruses. Taken all together, IDMseq, iMiGseq and NIRVANA utilize the advantage of long reads, overcome the limitation of low accuracy, and facilitate the application of long-read sequencing technologies in multidisciplinary fields.

Protecting drinking water supplies from pathogens such as Cryptosporidium parvum is a major concern for water treatment plants worldwide. The sensitivity and specificity of current detection methods are largely determined by the effectiveness of the concentration and separation methods used. In this study, disposable microfluidic micromixers were fabricated to effectively isolate Cryptosporidium parvum Oocysts from water samples, while allowing direct observation of Oocysts captured in the device using high quality immunofluorescence microscopy. In parallel, quantitative analysis of the capture yield was carried out by analyzing the waste from the microfluidics outlet with an Imaging Flow Cytometer. At the optimal flow rate, capture efficiencies higher than 95% were achieved in spiked samples, suggesting that scaled microfluidic isolation and detection of Cryptosporidium parvum will provide a faster and more efficient detection method for Cryptosporidium compared to other available laboratory-scale technologies.