Systematic Position Mapping of Split CRISPR‐Cas12a Activators Enables Highly Sensitive miRNA Detection and Cancer Cell Stratification

Amplification-free Cas12a diagnostics with split crRNA enable rapid and programmable target recognition, yet insufficient understanding of DNA activator architecture prevents predictable control over trans-cleavage activity and sensitivity. Here we systematically map over 200 split DNA activator configurations by introducing nicks at every position across both strands. The mapping reveals that target strand nicks suppress activity with position-dependent severity, while non-target strand nicks enhance activity. Guided by these rules, we engineer an optimized split activator pair that achieves attomolar microRNA detection (LOD: 112 aM), ∼480-fold higher sensitivity than intact activators. The enhanced sensitivity supports multiplexed live-cell profiling of five miRNAs for machine learning-based cancer cell stratification, and is further generalized to non-nucleic acid targets, including APE1 enzyme (0.0073 U/L) and HClO (2.37 pM) through position-informed cleavable sites. This work provides a generalizable methodology for engineering CRISPR-Cas12a performance across diagnostic and biosensing applications.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-07-23
DOI
https://doi.org/10.1002/advs.76576
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systematic Position Mapping of Split CRISPR‐Cas12a Activators Enables Highly Sensitive miRNA Detection and Cancer Cell Stratification

Ma My, Junqiu Zhai, Yuning Lu, Tiangang Luan et al.
Advanced Science
CRISPR and Genetic Engineering
article

Systematic Position Mapping of Split CRISPR‐Cas12a Activators Enables Highly Sensitive miRNA Detection and Cancer Cell Stratification

Ma My, Junqiu Zhai, Yuning Lu, Tiangang Luan, Xinyu Luan, Jiajun Ke, Zijian Mo, Zhe Li, Xiaoyan Tang
article en

Abstract

Amplification-free Cas12a diagnostics with split crRNA enable rapid and programmable target recognition, yet insufficient understanding of DNA activator architecture prevents predictable control over trans-cleavage activity and sensitivity. Here we systematically map over 200 split DNA activator configurations by introducing nicks at every position across both strands. The mapping reveals that target strand nicks suppress activity with position-dependent severity, while non-target strand nicks enhance activity. Guided by these rules, we engineer an optimized split activator pair that achieves attomolar microRNA detection (LOD: 112 aM), ∼480-fold higher sensitivity than intact activators. The enhanced sensitivity supports multiplexed live-cell profiling of five miRNAs for machine learning-based cancer cell stratification, and is further generalized to non-nucleic acid targets, including APE1 enzyme (0.0073 U/L) and HClO (2.37 pM) through position-informed cleavable sites. This work provides a generalizable methodology for engineering CRISPR-Cas12a performance across diagnostic and biosensing applications.

Advanced Science
Guangzhou University of Chinese Medicine (CN), Sun Yat-sen University (CN), Wuyi University (CN), Wuyi University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
CRISPR and Genetic Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Systematic Position Mapping of Split CRISPR‐Cas12a Activators Enables Highly Sensitive miRNA Detection and Cancer Cell Stratification — Ma My, Junqiu Zhai, et al. · Advanced Science (2026) | TGRS Research Map | TGRS