A one-pot CRISPR/Cas12b assay for extraction-free and visual detection of Haemophilus influenzae

Haemophilus influenzae is a major respiratory pathogen, particularly in pediatric populations, and its rapid and accurate detection is critical for early diagnosis and targeted treatment. Traditional diagnostic methods, such as bacterial culture and PCR, are often time-consuming and require specialized equipment. In this study, we developed the Hi-ExCad assay, a one-pot, extraction-free CRISPR/Cas12b-based system for the rapid, simple, and accurate detection of H. influenzae. The assay integrates loop-mediated isothermal amplification and CRISPR/Cas12b detection in a single reaction, enabling direct detection from clinical sputum samples without the need for nucleic acid extraction. The Hi-ExCad assay demonstrated high specificity, correctly identifying H. influenzae in clinical samples, with a limit of detection of 1 pg of genomic DNA. The assay also exhibited excellent performance in real-time detection and visual result interpretation under blue light, making it highly suitable for point-of-care testing and resource-limited settings. These findings suggest that the Hi-ExCad assay provides a rapid, reliable, and user-friendly method for the detection of H. influenzae, with significant potential for clinical application.

Authors

Institutions

Publication Details

Journal
BMC Microbiology
Published
2026-04-06
DOI
https://doi.org/10.1186/s12866-026-04907-x
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

A one-pot CRISPR/Cas12b assay for extraction-free and visual detection of Haemophilus influenzae

Min Yuan, Linghui Yuan, Bin Du, Xiaotong Qiu et al.
BMC Microbiology
CRISPR and Genetic Engineering
article

A one-pot CRISPR/Cas12b assay for extraction-free and visual detection of Haemophilus influenzae

Min Yuan, Linghui Yuan, Bin Du, Xiaotong Qiu, Xiao Ma, Yanan Li, Zhenjun Li, Xueping Liu
article en

Abstract

Haemophilus influenzae is a major respiratory pathogen, particularly in pediatric populations, and its rapid and accurate detection is critical for early diagnosis and targeted treatment. Traditional diagnostic methods, such as bacterial culture and PCR, are often time-consuming and require specialized equipment. In this study, we developed the Hi-ExCad assay, a one-pot, extraction-free CRISPR/Cas12b-based system for the rapid, simple, and accurate detection of H. influenzae. The assay integrates loop-mediated isothermal amplification and CRISPR/Cas12b detection in a single reaction, enabling direct detection from clinical sputum samples without the need for nucleic acid extraction. The Hi-ExCad assay demonstrated high specificity, correctly identifying H. influenzae in clinical samples, with a limit of detection of 1 pg of genomic DNA. The assay also exhibited excellent performance in real-time detection and visual result interpretation under blue light, making it highly suitable for point-of-care testing and resource-limited settings. These findings suggest that the Hi-ExCad assay provides a rapid, reliable, and user-friendly method for the detection of H. influenzae, with significant potential for clinical application.

BMC Microbiology
Shanxi Medical University (CN), Capital Medical University (CN), National Institute for Communicable Disease Control and Prevention (CN), Beijing Friendship Hospital (CN), Shanxi Academy of Medical Sciences (CN)
Chinese Center for Disease Control and Prevention, National Key Research and Development Program of China
Openalex Percentile: Top 8%
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.