Qingshan Wei

In this proposal, we aim to study and develop a transformative plant wearable sensor that can be deployed on-plant for continuous monitoring of biotic and abiotic stresses of plants and their microenvironment to inform plant health status and early detection of plant diseases. This multifunctional plant wearable sensor will include an array of ligand-functionalzied chemiresistive sensors to profile plant leaf VOCs and nanowire-based flexible sensors to monitor microclimate in parallel. The sensors will be prepared on a light-transparent, gas-permeable, and stretach substrate for long-term wearibility on live plants. In addition, a signal transmitter will be developed for wireless data acquistion and transmission. The system will be thourughly tested on tomato plants in the greenhouse for stress monitoring and disease detection.

The overarching goal of this project is to systematically study and optimize two microneedle-based platforms for rapid DNA extraction and genotyping from plant leaves and seeds, respectively. DNA genotyping is an indispensable tool to identify specific traits and select progeny in plant breeding. However, the current seed genotyping method is a complicated multistep process, involving seed chipping, DNA extraction, and assaying. On the other side, leaf genotyping is relatively simpler, but it depends on manual punctuation of leaf tissues and actual breeding of new crop species before analysis, which increases both time and test cost significantly. To address these immediate needs, our team will investigate a novel plant DNA extraction and genotyping system that is robust, simple, and scalable for single-nucleotide polymorphism (SNP) analysis for both plant leaves and seeds. Two DNA extraction platforms, namely the polymeric microneedle array (PMA) and metallic microneedle (MM), will be developed and optimized for leaf and seed DNA isolation, respectively. The extraction system will be integrated with a multiplexed genotyping assay such as padlock-based rolling circle amplification (RCA) for rapid detection of specific trait loci markers. The potential for on-needle detection of SNPs and automation of the entire process will also be explored.

This CAREER proposal seeks to study the fundamental properties of CRISPR Cas proteins for nucleic acid detection through collateral nonspecific cleavage (or trans-cleavage). Systematic characterization, optimization, and control of the enzyme activity and kinetics of Cas proteins will convert genome-editing CRISPR-Cas platform into next-generation, rapid, and ultrasensitive biosensors. However, the detailed mechanism and properties of trans-cleavage are still not fully understood yet. Moreover, many existing CRISPR biosensors require pre-amplification steps to achieve high detection sensitivity, which significantly hinders their point-of-care (POC) applications. Our recent data (see Section RO1) suggest that trans-cleavage kinetics of Cas proteins in a one-pot reaction is different from the literature reports of pre-assembled and activated Cas-crRNA complex. Therefore, a revised enzymatic model is needed to accurately describe the enzymatic properties of CRISPR biosensor. As such, the overarching goal of this work is to understand and control the unique characteristics of CRISPR trans-nuclease and use the knowledge gained to design a chip-based, preamplification-free digital CRISPR (dCRISPR) sensor chip. The sensor chip will be coupled with a newly designed smartphone scope, EpiView, to form a cost-effective, smartphone-based testing platform for POC measurement of viral load of the human immunodeficiency virus (HIV) from finger prick blood.

Breast cancer (BC) is a major global health concern. It is the most common cancer among women and leading cause of cancer death for women worldwide. Limited-resource settings (LRS) account for about half of the cases and majority of deaths from BC, and rates are increasing. The reason for poor outcomes in LRS relative to abundant-resource settings (ARS) is related to higher incidence of late-stage presentation resulting from the lack of healthcare infrastructure to support diagnostic pathology services for BC. Breast pathology is the cornerstone of appropriate BC management, and the quality of pathology services directly correlates to the quality of care and patient outcomes. Unfortunately, access to adequate breast pathology services can be limited or even nonexistent in LRS. The objective of proposal is to develop a low-cost, mobile platform that provides cellular and molecular breast pathology of BC. This proposal is significant as it directly address the unmet need for sustainable approaches toward complete breast pathology in LRS and has the potential for transformative impact by improving survival of BC patients in LRS worldwide.

Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world and in the US. Climate change is exacerbating weather events that affect crop production and food access for vulnerable areas. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover and evolution of new pathogen genetic lineages. Prediction of plant disease pandemics is unreliable due to the lack of real-time detection, surveillance and data analytics to inform decisions and prevent spread. In order to tackle these grand challenges, a new set of predictive tools are needed. In the PIPP Phase I project, our multidisciplinary team will develop a pandemic prediction system called ����������������Plant Aid Database (PAdb)��������������� that links pathogen transmission biology, disease detection by in-situ and remote sensing, genomics of emerging pathogen strains and real-time spatial and temporal data analytics and predictive simulations to prevent pandemics. We plan to validate the PAdb using several model pathogens including novel and host resistance breaking strains of lineages of two Phytophthora species, Phytophthora infestans and P. ramorum and the cucurbit downy mildew pathogen Pseudoperonspora cubensis Adoption of new technologies and mitigation interventions to stop pandemics require acceptance by society. In our work, we will also characterize how human attitudes and social behavior impact disease transmission and adoption of surveillance and sensor technologies by engaging a broad group of stakeholders including growers, extension specialist, the USDA APHIS, Department of Homeland Security and the National Plant Diagnostic Network in a Biosecurity Preparedness workshop. This convergence science team will develop tools that help mitigate future plant disease pandemics using predictive intelligence. The tools and data can help stakeholders prevent spread from initial source populations before pandemics occur and are broadly applicable to animal and human pandemic research.

Project is in support of PSI. We have developed faster and more reliable in-field detection methods for plant pathogens that will greatly reduce plant disease by reducing time from occurrence to detection and thus time to mitigation. Two new innovations in sensor technology have been developed including a smart-phone field-compatible molecular assay that uses a loop-mediated isothermal amplification (LAMP) sensor and a volatile-based sensor that will speed identification of plant pathogens in the field. In this project renewal, we will continue deploy and field test work a volatile organic compound (VOC) sensor and microneedle patch-supported LAMP sensors to differentiate two regulatory Phytophthora species of concern, P. ramorum and P. kernoviae. Phytophthora ramorum and P. kernoviae cause disease on nursery plants such as rhododendron, lilac and kalmia and important forestry tree species including oak and beech among others. Phytophthora kernoviae has not yet been found in the US. We will test the sensors in field tests and deploy them with inexpensive cartridges to run on a smartphone reader. We will also complete the modeling of historic late blight disease occurrence data using a near-real time mapping platform and the process based spatially explicit discrete time PoPS (Pest or Pathogen Spread) Forecasting Platform to develop predictive maps of pathogen risk of spread at regular intervals. The system will improve the response time of USDA APHIS PPQ and National Plant Diagnostic Network (NPDN) personnel to respond to emerging Phytophthora threats and improve economic return of growers as they use the digital diagnostic tools to prevent the spread of important Phytophthora diseases.

Emerging plant disease and pest outbreaks reduce food security, national security, human health, and the environment, with serious economic implications for North Carolina growers. These outbreaks may accelerate in coming decades due to shifts in the geographic distributions of pests, pathogens and vectors in response to climate change and commerce. Data-driven agbioscience tools can help growers solve pest and disease problems in the field more quickly but there is an urgent need to harness game-changing technologies. Computing devices are now embedded in our personal lives with sensors, wireless technology, and connectivity in the ����������������Internet of Things��������������� (IoT) but these technologies have yet to be scaled to agriculture. Our interdisciplinary team will build transformative sensor technology to identify plant pathogens, link local pathogen data and weather data, bioinformatics tools (pathogen genotypes), and use data driven analytics to map outbreaks, estimate pest and pathogen risk and economic damage, in order to coordinate response to emerging diseases, and contain threats. Sensor-supported early and accurate detection of pathogens before an outbreak becomes wide-spread in growing crops will significantly reduce pesticide use and increase crop yields.

Bed bug resurgence: The common bed bug, Cimex lectularius, continues to undergo a dramatic resurgence in the U.S. and globally. Although virtually eliminated from developed nations some 60������������������70 years ago, the prevalence of bed bug infestations has risen sharply in the last two decades with numerous infestations now reported in all 50 U.S. states. Unlike infestations in the early part of the 20th century, which were limited to places with high turnover, infestations are now common in urban, suburban and military settings, including homes, apartment buildings, hotels/motels, hospitals, nursing homes, dormitories, office buildings, thrift stores, social service and emergency care centers, prisons, movie theaters, modes of transport, and of course ������������������ military bases in the U.S. and abroad. The high incidence of high levels of insecticide resistance in bed bug populations and the lack of safe and effective chemical and non-insecticidal methods to control bed bug infestations suggest that continuing escalation of this serious pest problem is inevitable. Bed bug biology: Cimex lectularius is a blood-sucking insect that feeds at night. Adult females and males ingest 4������������������8 ���������l of blood at one feeding, increasing their body mass >250%. An adult female can produce up to 540 eggs in her lifetime. In a laboratory setting (27���������C, 50������������������60 % RH), adults take a blood-meal from an artificial membrane-based system as soon as 3 days after their last meal. There are five nymphal instars, and each stage requires a blood-meal before molting to the next stage. When feeding, the bugs fully engorge in 5������������������10 min and may probe the skin several times before feeding begins. Once feeding is terminated, bed bugs return to their refuges, which they usually share with other bed bugs as a mixed aggregation of various life stages. Bed bug control: Bed bugs feed only on liquids, namely, blood from warm-blooded hosts. Therefore, to date, all insecticide applications have relied on applying the insecticide as residuals on surfaces (e.g., baseboards, headboards, mattresses) and relying on bed bugs walking over the insecticide. This approach, aside from issues with insecticide resistance, is inherently inefficient. Large surface areas are covered with vast amounts of insecticides, while only a few nanograms are needed to kill bed bugs. Thus, the bioavailability ratio is at least a million to one, resulting in waste of insecticide, contamination of residential surfaces, and negative effects on human and pet health. Baiting ������������������ transformative approach: At night, when host activity is minimal, bed bugs leave their harborages in search of a host and a blood-meal. The manner in which bed bugs find a host is largely unknown. Recently we showed that in close proximity to hosts they detect and orient toward heat produced by the host (Journal of Experimental Biology 219: 3773������������������3780. doi: 10.1242/jeb.143487). Host odors, human sweat and body secretions, and CO2 also play a role in attracting bed bugs to their hosts. We have conceptualized and obtained data on several components of a baiting system against bed bugs. This system consists of two approaches: (1) a xenointoxication approach, whereby a host is used to deliver a systemic insecticide to the bed bug, and (2) an artificial bait that includes a heated element surrounded by a liquid bait medium that contains an insecticide. The liquid bait is housed within a membrane that allows bed bugs to feed. Our Overall Goal is to develop, validate and demonstrate components of a baiting system and integrate them into prototypes for lab and field experiments. Provide proof of technological feasibility, general military utility, cost reduction potential, greater efficacy, and availability for transition to a useable product. To optimize the baiting system, we propose the following Objectives: 1. Identify chemical attractants for an artificial baiting system. How do bed bugs find an acceptable host? 2. Develop an artificial baiting system, consisting of attractants (host odors, CO2, and heat), feeding

This project aims to develop a microfluidic filtering and imaging device for rapid sterility testing in biomanufacturing of biologics such as nucleic acid products and proteins. Current sterility testing is costly and time-consuming, requires a large sample volume, and is not amenable to in-line/continuous processes. In this project, a miniaturized testing chip that can perform pathogen separation, labeling and imaging will be developed to enable rapid sterility testing.

The goal of this project is to develop a low-cost, rapid VOC sensor for the detection of volatile emissions from fruits and vegetables. The initial target of the project will be onion. If successful, the technology can be potentially applied to watermelon, and other fruits and vegetables.