# One-pot CRISPR-based point of care platform for rapid, specific and sensitive detection of HPV 16 without pre-amplification

## TL;DR

This paper introduces a one-pot CRISPR-based diagnostic method for detecting HPV 16 with high specificity and sensitivity, eliminating the need for pre-amplification.

## Contribution

The novel CASTSA platform combines CRISPR-Cas12a and qPCR in a single reaction for rapid, specific pathogen subtyping.

## Key findings

- CASTSA achieved a limit of detection of 18 copies/reaction for HPV 16.
- The method successfully discriminated HPV 16 from other subtypes like HPV 18, 33, 45, and 52.
- CASTSA was validated using clinical samples and an electrochemical sensor platform.

## Abstract

Accurate detection of gene subtypes with high sequence similarity is critical for pathogen diagnosis. Current CRISPR-based PCR diagnostics methods may provide improved specificity but rely on pre-amplification in a separate reaction, due to Cas protein thermal instability, increasing cross contamination. Here, we developed CRISPR-based terminal-specific amplification (CASTSA), a one-pot platform which makes use of the CRISPR-Cas12a specific recognition and cleavage, generating a single strand digested product with specific 5’ termini, to serve as the template for qPCR amplification. Our assay simplifies sample preparation by eliminating the need pre-amplification, whilst simultaneously fully exploiting the high specificity of the CRISPR system and high sensitivity of PCR. CASTSA was validated in vitro and with clinical samples collected from individuals with Human Papillomavirus (HPV), demonstrating high specificity for HPV 16, whilst discriminating HPV 18, 33, 45, and 52 sub-types, using a laser-induced graphene (LIG)-based electrochemical sensor platform. The technique achieved a limit of detection of 18 copies/reaction and offers a robust and reproducible, one-pot solution for pathogen subtyping, providing excellent specificity, so advancing nucleic acid detection with an assay that is easier to implement when compared with standard clinical diagnostic workflows.