Establishment and application of Recombinase-aided amplification combined with LbCas12a  for the rapid detection of Karenia brevis

Abstract

Species of the Karenia genus are widely distributed in global waters and frequently cause harmful algal blooms (HABs), posing significant threats to coastal ecosystems, aquaculture, and human safety. Among them, Karenia brevis is one of the most extensively studied species due to its production of brevetoxins, which are highly toxic to marine life and can adversely impact public health. In this study, we developed a rapid detection method that combines Recombinase-aided amplification (RAA) with CRISPR/LbCas12a, aimed at the precise identification of K. brevis. Specific RAA primers and crRNAs were designed based on the highly variable regions of the internal transcribed spacer (ITS) sequence of K. brevis. After screening multiple RAA primer pairs and crRNAs, the optimal combination was identified, ensuring both high efficiency and specificity of the detection system. For field application, two detection modes were employed: fluorescence-based (FQ) and lateral flow dipstick (LFD), along with a simple and rapid DNA extraction method. Sensitivity tests demonstrated that the detection limit of this method was 5.9 × 10³ copies/µL for plasmid DNA and 1 cell/mL for live cells. Environmental water samples collected during a HAB event in Lianjiang, Fujian Province, in May 2024, tested negative for K. brevis using the RAA-CRISPR/LbCas12a system. However, two other Karenia species—Karenia mikimotoi and Karenia longicanalis—were identified through ITS fragment amplification, cloning sequencing and phylogenetic analysis. In spiked experiments where K. brevis was introduced into natural water samples, the RAA-CRISPR/LbCas12a system accurately detected its presence. Overall, the RAA-CRISPR/LbCas12a detection system demonstrated excellent sensitivity, specificity and operational simplicity, making it a promising tool for rapid field detection of K. brevis and potentially suitable for broader applications in HAB monitoring.