Performing Department
(N/A)
Non Technical Summary
Pesticides are among the most ubiquitous and persistent contaminants, and human epidemiological studies have found associations between pesticide exposure and a number of adverse health conditions. We will develop a nanobody-based biosensor strain along with a on-line biosensor platform that uses a microfluidic device to detect and quantify the pesticide chlorpyrifos in real time.Objective 1: To identify and characterize the binding kinetics of nanobodies for chlorpyrifos. We will identify nanobodies that bind chlorpyrifos molecules and characterize their capture potential when surface displayed in an E. coli strain. We will work with a set of nanobodies that are enriched for specificity to the target, and we will clone them into our E. coli nanobody display vector, and screen and characterize them within our multiplexed microfluidic platform.Objective 2: To develop a prototype for continuous and batch chlorpyrifos sensing. We will develop an assay for measuring agglutination on a microfluidic-scale from many individual strain banks. We will optimize an agglutination assay using the surface-displayed nanobody strains, and then transduce the agglutination signal using a customized computational algorithm. Finally, we will optimize a sensor device to facilitate this assay and maximize the cellular signal so that we can quantify the amount of contaminant present in the water.Importantly, this project serves as a seed project, as once we have demonstrated proof of principle with the development of a sensor for chlorpyrifos detection, we will have a pipeline to rapidly develop sensors for many other emerging contaminants of concern.?
Animal Health Component
50%
Research Effort Categories
Basic
(N/A)
Applied
50%
Developmental
50%
Goals / Objectives
The main objective of this SBIR project is to develop a continuous water sensor that can detect and quantify the concentration of pesticides in real-time. The project will aim to integrate nanobody technology with an existing customizable biosensor platform (the Qube) that uses engineered microbial sensor strains paired with microfluidic technology to continuously monitor water for common contaminants and other agriculturally relevant targets (e.g. nitrate). In previous work, we have developed this platform to quickly and accurately measure the concentration of heavy metals and nutrients in water continuously for over a month without requiring subjective interpretation, extensive calibration, or regular oversight. A simple monthly cartridge and media swap enables the sensor to run indefinitely, reporting the toxin concentrations to a mobile friendly portal. The work proposed here will develop a novel nanobody-based approach to expand the func- tionality of this sensor platform, which will enable the detection of almost any type of contaminant that can be recognized by a nanobody. That is, while the project leverages an existing water sampling platform along with a computational backbone for analyzing cellular responses in real-time, the development of an innovative approach to nanobody-based biosensor strain development will be transformative and broadly impactful. We will begin by developing the capability to detect chlorpyrifos as proof of principal in Phase I, with a plan expand to other pesticides and emerging contaminants as well as perform field validations of the platform with relevant end-users in Phase II.
Project Methods
We propose to develop a biosensor platform that continuously monitors water for chlorpyrifos using surface-displayed nanobodies to produce an agglutination response in engineered microbial sensor strains. There are two primary Objectives needed to demonstrate technical feasibility prior to bringing this technology to market. While we have demonstrated the ability to develop and screen target-specific nanobodies and to use surface-displayed nanobodies to trigger agglutination, there is a significant challenge in both developing a new type of sensor strain that can sensitively and specifically bind chlorpyrifos as well as the challenge of developing an assay to continuously monitor agglutination within our imaging platform. Here we will briefly describe these key technical challenges and how we plan to address them as part of this Phase I project.Technical Objective 1: Identify and characterize nanobodies specific to chlorpyrifos. We will begin by working with a local nanobody company, Abcore, to isolate a set of nanobodies that are enriched for specificity to chlorpyrifos (Task 1). We will then bring these nanobodies to our facility, clone them into our E. coli nanobody display vector, and screen and characterize them within our multiplexed microfluidic platform. This is a process we have validated in previous work and will likely result in a reduced set of highly specific nanobodies (Task 2). A key risk here is the uncertainty that specific or strong binding candidates will emerge from llama immunization. While nanobodies for chlorpyrifos have not been developed in the past, traditional antibodies have been created, suggesting that analogous nanobodies can be developed. Furthermore, our personal successes with fentanyl and the successes of other groups for a wide range of small molecule environmental contaminants points to the likeliness of identifying chlorpyrifos specific nanobodies. Lastly, in the case that immunization only returns weakly binding nanobodies, the directed evolution described in Task 2 will further assist in the discovery of stronger candidates.Technical Objective 2: Develop a sensor platform that employs an agglutination-based assay to continuously monitor for specific contaminants. We will begin by developing and optimizing an agglutination assay using our reduced set of surface-displayed nanobody strains (Task 3). We will carefully characterize the degree and speed of agglutination in batch over a wide range of parameters, in order to develop a robust assay for determining the concentration of chlorpyrifos. Finally, we will adapt this agglutination assay to operate as a continuous sensor in our imaging platform (Task 4). We will build upon previous results to transduce the agglutination signal to a fluorescence response, and we will optimize a sensor device to facilitate this assay and maximize signal. The main risk here is the inherent noisiness of biological systems, which may make quantitative measurements of chlorpyrifos beyond simple present or not-present readouts difficult. However, these are challenges we have faced and overcome by leveraging our experience with sensor design, strain engineering, and computation analysis. By optimizing device geometries, including appropriate biological controls, and tuning data analysis pipelines, we are confident in our ability to quantitatively measure chlorpyrifos via agglutination.Ultimately, we aim to demonstrate technical feasibility for the continuous monitoring of a specific pesticide. While there are inherent risks, we have a carefully crafted work plan and are building upon a foundation of successful sensor and assay development.