The lack of reliable and widely-available SARS-CoV-2 antibody testing has left many unanswered questions. For example, although it is known that SARS-CoV-2 specific antibodies appear within two weeks of someone becoming infected with the virus. However several factors are unknown, including a) the viral loads that generate antibody responses; b) how long SARS-CoV-2 antibodies last; or c) the amount of antibody needed for protection. The creation of low-cost, high-accuracy platforms for SARS-CoV-2 antibody analysis could therefore play a crucial role in tracking the spread of COVID-19, informing epidemiological responses, and supporting the development of diagnostics, treatments, and vaccines. This project will develop a low-cost alternative for rapidly measuring SARS-CoV-2 antibody binding. These systems could be used to measure SARS-CoV-2 antibody titers in patient samples and allow researchers to better model the spread and understand the disease course of COVID-19. The development of this customizable antibody detection platform will also make it easier to respond to future novel pandemics. In addition, the platform has substantial potential as a general research tool, as it could be used to detect a variety of antigen-antibody interactions. Broader impacts: The proposed system will provide a scalable, low-cost alternative to the ELISA that could be used to measure SARS-CoV-2-specific antibody titers in patient samples and facilitate efforts to model the spread and understand the etiology of COVID-19. Immediate broader impacts of the project also include i) unique opportunities for Ph.D. and undergraduate students to participate in use-inspired science and engineering, ii) engagement with diverse public audiences to communicate key ideas about the science of COVID-19 antibody testing, and iii) graphic materials about the science of COVID-19 antibody testing for use in public-facing events and sharing via social media that will be freely available under Creative Commons licenses.
This project will develop a cell-free transcription and translation (TXTL) platform for measuring SARS-CoV-2 antigen-antibody binding with the quantitative precision of ELISA, and the easy customizability and scalability of a system that is entirely genetically-encoded. Recent work developed a programmable CRISPR-Cas transcriptional activation (CRISPRa) system for E. coli and TXTL that uses modified guide RNAs (gRNAs) to recruit a transcriptional activator. Here, the goal is to engineer CRISPRa as a platform for quantifying antigen-antibody binding by making CRISPRa activity conditional to the presence of IgG antibodies in a sample. It is straightforward to couple CRISPRa activity to visible outputs, and the system developed here could provide a scalable, low-cost alternative to ELISAs that permits the quantification of antibody titers using only DNA and TXTL master mix as reagents. Even more, because of the inherent multiplexing capabilities of CRISPRa, it will be possible to develop new diagnostics that produce a signal only upon detection of multiple antigens, resulting in lower false-positive rates. Intellectual merit: Developing scalable approaches to rapidly quantify antigen-antibody binding is a long-standing scientific and engineering challenge. By developing rules to couple antigen-antibody binding to CRISPRa-directed reporter gene expression, this project will create assays for measuring SARS-CoV-2 antigen-antibody binding using DNA-programmed cell-free platforms that are easy to customize and could be readily re-configured as point-of-care diagnostics. While there are a number of CRISPR-based tools that are being adapted to detect viral nucleic acids, the proposed system is comparatively unique as a sensor for protein antibody detection.
This EAGER award is made by the Systems and Synthetic Biology Program in the Division of Molecular and Cellular Biosciences, using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
