Ultrasensitive single-point mutation detection via digital counting of individual dCas9-DNA complexes

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Title
Ultrasensitive single-point mutation detection via digital counting of individual dCas9-DNA complexes
Author(s)
S Kim; Wi-Jae Lee; H K Lee; S Ji; J K Hur; S H Lee; H R Koh
Bibliographic Citation
Sensors and Actuators B-Chemical, vol. 444, pp. 138466-138466
Publication Year
2025
Abstract
Single-point DNA mutations represent the majority of oncogenic mutations and contribute significantly to genetic variations. Thus, ultrasensitive methods to detect a very low fraction of single-point mutations are critical for the early diagnosis of mutation-associated genetic diseases. Here, we developed a highly sensitive approach for detecting single-point mutations by counting individual nuclease-dead Cas9 (dCas9) complexes bound to DNA at the single-molecule level. The clustered regularly interspaced short palindromic repeats (CRISPR)/dCas9 system, composed of dCas9 protein and guide RNA (gRNA), specifically recognizes DNA sequences complementary to the gRNA and bearing an appropriate protospacer adjacent motif (PAM) adjacent to the target site. By combining the PAM-dependent binding specificity with single-molecule counting, we successfully discriminated single-point mutations in clinically relevant genes, including EGFR (c.2573?T?>?G) and KRAS (c.34?G>T and c.35?G>A). Kinetic and thermodynamic analyses revealed that the discrimination mechanism was primarily driven by the faster association rate of the dCas9-gRNA complex to target DNA with a canonical PAM. Furthermore, we quantitatively measured the mutant allele fraction across the entire range of mutation rates and achieved discrimination of mutations present at levels as low as 0.5?%. These results suggest that digital single-molecule counting of dCas9 complexes may serve as a promising approach for early and sensitive detection of single-point mutations.
Keyword
CRISPR/dCas9Single-point DNA mutationSinge-molecule countingPAM-dependent binding
ISSN
0925-4005
Publisher
Elsevier
Full Text Link
http://dx.doi.org/10.1016/j.snb.2025.138466
Type
Article
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1. Journal Articles > Journal Articles
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