Developing, Characterizing, and Modeling CRISPR-Based Point-of-Use Pathogen Diagnostics

Recent years have
seen intense interest in the development of point-of-care
nucleic acid diagnostic technologies to address the scaling limitations
of laboratory-based approaches. Chief among these are combinations
of isothermal amplification approaches with CRISPR-based detection
and readouts of target products. Here, we contribute to the growing
body of rapid, programmable point-of-care pathogen tests by developing
and optimizing a one-pot NASBA-Cas13a nucleic acid detection assay.
This test uses the isothermal amplification technique NASBA to amplify
target viral nucleic acids, followed by the Cas13a-based detection
of amplified sequences. We first demonstrate an in-house formulation
of NASBA that enables the optimization of individual NASBA components.
We then present design rules for NASBA primer sets and LbuCas13a guide
RNAs for the fast and sensitive detection of SARS-CoV-2 viral RNA
fragments, resulting in 20–200 aM sensitivity. Finally, we
explore the combination of high-throughput assay condition screening
with mechanistic ordinary differential equation modeling of the reaction
scheme to gain a deeper understanding of the NASBA-Cas13a system.
This work presents a framework for developing a mechanistic understanding
of reaction performance and optimization that uses both experiments
and modeling, which we anticipate will be useful in developing future
nucleic acid detection technologies.