Development and evaluation of a hybrid capture-based NGS panel for comprehensive detection of respiratory pathogens

Infectious diseases caused by diverse pathogens-including viruses, bacteria, and fungi-pose a significant diagnostic challenge, especially when conventional assays fail to identify the causative agents. Next-generation sequencing (NGS), particularly hybrid-capture-based NGS, offers a culture-independent approach for comprehensive pathogen detection directly from clinical samples. In this study, we developed a hybrid-capture-based NGS panel targeting 85 respiratory pathogens (62 viruses, 23 bacteria/fungi) and evaluated its analytical and clinical performance. Analytical validation using 50 pathogens demonstrated high sensitivity, with 10× genome coverage ≥ 96% in 32 of 36 viral targets and ≥ 95% in all 14 bacterial/fungal targets. The panel maintained ≥ 80% genome coverage at Ct values up to 34. Clinical assessment of 561 respiratory specimens identified 25 pathogen species, achieving ≥ 90% genome coverage in 57.5% of virus-positive and 83.6% of bacteria-positive samples. Notably, additional pathogens were detected in high Ct value undetected by RT-PCR, and 35 cases of viral-viral and viral-bacterial co-infections were identified. This approach improves the detection performance for respiratory infections of unknown etiology and serves as a practical platform for the detection of emerging pathogens and public health preparedness. This technology has significant potential for applications in infectious disease surveillance and development of vaccines and therapeutics.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-11-26
DOI
https://doi.org/10.1038/s41598-025-26421-2
Primary Topic
Respiratory viral infections research
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Development and evaluation of a hybrid capture-based NGS panel for comprehensive detection of respiratory pathogens

Daehwan Lee, Jeong-Ah Kim, Hee Soo Lee, Chaeyoung Lee et al.
Scientific Reports
Respiratory viral infections research
article

Development and evaluation of a hybrid capture-based NGS panel for comprehensive detection of respiratory pathogens

Daehwan Lee, Jeong-Ah Kim, Hee Soo Lee, Chaeyoung Lee, Eun‐Jin Kim, Il‐Hwan Kim, Jeong‐Min Kim, Jae‐Hwan Jeong
article en

Abstract

Infectious diseases caused by diverse pathogens-including viruses, bacteria, and fungi-pose a significant diagnostic challenge, especially when conventional assays fail to identify the causative agents. Next-generation sequencing (NGS), particularly hybrid-capture-based NGS, offers a culture-independent approach for comprehensive pathogen detection directly from clinical samples. In this study, we developed a hybrid-capture-based NGS panel targeting 85 respiratory pathogens (62 viruses, 23 bacteria/fungi) and evaluated its analytical and clinical performance. Analytical validation using 50 pathogens demonstrated high sensitivity, with 10× genome coverage ≥ 96% in 32 of 36 viral targets and ≥ 95% in all 14 bacterial/fungal targets. The panel maintained ≥ 80% genome coverage at Ct values up to 34. Clinical assessment of 561 respiratory specimens identified 25 pathogen species, achieving ≥ 90% genome coverage in 57.5% of virus-positive and 83.6% of bacteria-positive samples. Notably, additional pathogens were detected in high Ct value undetected by RT-PCR, and 35 cases of viral-viral and viral-bacterial co-infections were identified. This approach improves the detection performance for respiratory infections of unknown etiology and serves as a practical platform for the detection of emerging pathogens and public health preparedness. This technology has significant potential for applications in infectious disease surveillance and development of vaccines and therapeutics.

Scientific ReportsVol. 15(1)
Korea Disease Control and Prevention Agency (KR), Bristol-Myers Squibb (Switzerland) (CH)
Korea Disease Control and Prevention Agency
Openalex Percentile: Top 52%
Respiratory viral infections research
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.