High-throughput screening for central nervous system infection-associated pathogens using TaqMan array cards, metagenomic next-generation sequencing, and targeted next-generation sequencing: a retrospective study
Abstract
BackgroundCentral nervous system (CNS) infections feature diverse pathogens and ambiguous clinical manifestations, which complicate rapid and accurate etiological diagnosis. This study aimed to characterize the pathogen spectrum in cerebrospinal fluid (CSF) specimens from patients with clinically suspected CNS infections and to evaluate the detection performance of metagenomic next-generation sequencing (mNGS) and targeted next-generation sequencing (tNGS) for pathogen identification in CSF.MethodsThis study employed three relatively independent workflows, namely TaqMan Array Cards (TAC) screening, Illumina-based unbiased mNGS, and Oxford Nanopore Technologies (ONT)-based tNGS, for the identification of CNS pathogens.ResultsIn this retrospective study, 316 clinical CSF specimens were examined. The overall pathogen-positive rate of TAC-qPCR strategy was 24.68%, and polymicrobial positive samples accounted for 4.11% of all samples. We further compared the pathogen detection performance of mNGS and tNGS using 48 representative CSF samples (25 qPCR-positive, 23 qPCR-negative). The sensitivities of mNGS and tNGS for identifying CNS pathogens among qPCR-positive CSF samples were 68.57 and 65.71%, respectively, indicating comparable overall sensitivity; however, mNGS achieved higher specificity (82.35%) than tNGS (72.73%). Unbiased mNGS enables the identification of pathogens not covered by the qPCR panel; for instance, Human parvovirus B19 was detected by mNGS in several samples and further confirmed by qPCR. By contrast, benefiting from targeted amplification, tNGS yielded approximately 692-fold higher pathogen RPM and only 9.2% host reads (versus 89.0% in mNGS), as well as a substantially shortened sample-to-answer turnaround time (10 h versus 30 h). However, tNGS carried a risk of false positives caused by elevated signals from environmental contaminant bacteria. Our combined TAC-qPCR, Illumina-mNGS and Nanopore-tNGS testing identified a broad spectrum of CNS pathogens covering the major viral, fungal and bacterial etiological agents of central nervous system infections.ConclusionThe TAC strategy enables high-throughput preliminary pathogen screening of large sample cohorts, while the unbiased mNGS workflow allows identification of rare or unexpected pathogens outside predefined panels, and tNGS achieves robust target enrichment and a greatly shortened testing turnaround time. Therefore, the optimal sequencing approach should be selected on a case-by-case basis according to clinical demands and suspected pathogens.
Related
- Cerebrospinal fluid metagenomic next-generation sequencing for culture-negative anaerobic central nervous system infection involving Prevotella oris: attribution challenges in low-biomass specimens
- Metagenomic next-generation sequencing of aqueous humor guides targeted therapy for Staphylococcus epidermidis endophthalmitis in chronic ocular graft-versus-host disease: a case report
- Metagenomic next-generation sequencing improves pathogen detection in culture-negative infections: a diagnostic performance study
- Analysis of structural modifications and metagenomic sequencing during the ensiling of Caragana korshinskii provides insights into how extrusion pretreatment promotes lignocellulose degradation
- Benchmarking Microbiome Methods for Improved Metagenomic Sequencing of Lower Respiratory Tract Samples
BibTeX
@article{jia2026highthroughput,
title = {{High-throughput screening for central nervous system infection-associated pathogens using TaqMan array cards, metagenomic next-generation sequencing, and targeted next-generation sequencing: a retrospective study}},
author = {Xiaofang Jia and Lyuyin Hu and Min Wu and Jun Chen and Di Tian and Zhigang Yi and Yun Ling and Yinzhong Shen and Xiaonan Zhang},
journal = {Frontiers in Microbiology},
year = {2026},
month = nov,
doi = {10.3389/fmicb.2026.2001491},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2026.2001491},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - High-throughput screening for central nervous system infection-associated pathogens using TaqMan array cards, metagenomic next-generation sequencing, and targeted next-generation sequencing: a retrospective study
AU - Xiaofang Jia
AU - Lyuyin Hu
AU - Min Wu
AU - Jun Chen
AU - Di Tian
AU - Zhigang Yi
AU - Yun Ling
AU - Yinzhong Shen
AU - Xiaonan Zhang
PY - 2026
DA - 2026/11/04
JO - Frontiers in Microbiology
DO - 10.3389/fmicb.2026.2001491
UR - https://www.frontiersin.org/articles/10.3389/fmicb.2026.2001491
AB - BackgroundCentral nervous system (CNS) infections feature diverse pathogens and ambiguous clinical manifestations, which complicate rapid and accurate etiological diagnosis. This study aimed to characterize the pathogen spectrum in cerebrospinal fluid (CSF) specimens from patients with clinically suspected CNS infections and to evaluate the detection performance of metagenomic next-generation sequencing (mNGS) and targeted next-generation sequencing (tNGS) for pathogen identification in CSF.MethodsThis study employed three relatively independent workflows, namely TaqMan Array Cards (TAC) screening, Illumina-based unbiased mNGS, and Oxford Nanopore Technologies (ONT)-based tNGS, for the identification of CNS pathogens.ResultsIn this retrospective study, 316 clinical CSF specimens were examined. The overall pathogen-positive rate of TAC-qPCR strategy was 24.68%, and polymicrobial positive samples accounted for 4.11% of all samples. We further compared the pathogen detection performance of mNGS and tNGS using 48 representative CSF samples (25 qPCR-positive, 23 qPCR-negative). The sensitivities of mNGS and tNGS for identifying CNS pathogens among qPCR-positive CSF samples were 68.57 and 65.71%, respectively, indicating comparable overall sensitivity; however, mNGS achieved higher specificity (82.35%) than tNGS (72.73%). Unbiased mNGS enables the identification of pathogens not covered by the qPCR panel; for instance, Human parvovirus B19 was detected by mNGS in several samples and further confirmed by qPCR. By contrast, benefiting from targeted amplification, tNGS yielded approximately 692-fold higher pathogen RPM and only 9.2% host reads (versus 89.0% in mNGS), as well as a substantially shortened sample-to-answer turnaround time (10 h versus 30 h). However, tNGS carried a risk of false positives caused by elevated signals from environmental contaminant bacteria. Our combined TAC-qPCR, Illumina-mNGS and Nanopore-tNGS testing identified a broad spectrum of CNS pathogens covering the major viral, fungal and bacterial etiological agents of central nervous system infections.ConclusionThe TAC strategy enables high-throughput preliminary pathogen screening of large sample cohorts, while the unbiased mNGS workflow allows identification of rare or unexpected pathogens outside predefined panels, and tNGS achieves robust target enrichment and a greatly shortened testing turnaround time. Therefore, the optimal sequencing approach should be selected on a case-by-case basis according to clinical demands and suspected pathogens.
SN - 1664-302X
ER -