RPA-primed droplet-partitioned CRISPR/Cas12a assay for low-copy detection of Candida albicans in vaginal specimens
Candida albicans is a major cause of vulvovaginal candidiasis, and sensitive detection of low-abundance fungal DNA remains challenging in clinical specimens. In this study, we developed a two-stage assay combining rapid recombinase polymerase amplification (RPA) with droplet-partitioned CRISPR/Cas12a fluorescence detection. Target DNA was first amplified by RPA for 10 min and subsequently analyzed in vortex-generated polydisperse droplets without microfluidic chip fabrication. Using predefined NTC-based analytical criteria, the operational LoDs were 10 copies/μL for the bulk RPA-Cas12a assay and 1 copy/μL for the droplet-partitioned format under the tested conditions. No cross-reactivity was observed with the tested non-target organisms, including additional clinically relevant non- albicans Candida species. In a preliminary evaluation of 28 residual vaginal swab specimens, the assay showed complete concordance with a routine composite clinical reference using an exploratory cohort-derived droplet-count cutoff. Because the comparator was not species-specific for C. albicans , these findings represent preliminary concordance rather than definitive diagnostic accuracy. The complete workflow was performed within approximately 1 h using basic laboratory equipment. These findings demonstrate that droplet partitioning can improve the low-copy analytical readout of RPA-Cas12a detection and provide a practical approach for qualitative identification of C. albicans DNA in vaginal specimens.
Authors
- Wenfei Xu (ORCID: https://orcid.org/0000-0003-4257-0100)
- Jie Peng (ORCID: https://orcid.org/0000-0002-2786-6221)
- Fang Liu
- Juan Xie
- Ju Long
- Xu-Hui Li
Institutions
- Jiaxing University (CN)
- Women's Hospital, School of Medicine, Zhejiang University (CN)
- Shanghai Ocean University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Frontiers in Cellular and Infection Microbiology
- Published
- 2026-10-28
- DOI
- https://doi.org/10.3389/fcimb.2026.1960866
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00