Pathogen Detection in Spinal Infections: Next-Generation Sequencing Versus Conventional Microbiological Methods

Abstract

Objective and

Background

Early and accurate diagnosis of spinal infections, including spinal tuberculosis, is pivotal for effective treatment but remains challenging. This study aims to assess the diagnostic yield of metagenomic next-generation sequencing (mNGS) compared with that of conventional microbiological tests (CMTs) in identifying pathogens associated with spinal pathologies, with a special focus on infections leading to surgical interventions.

Methods

We enrolled 85 patients who underwent spinal surgery, comprising 63 patients with clinically diagnosed spinal infections, including patients with spinal tuberculosis, and 22 patients with noninfectious spinal conditions. The procedures involved irrigation and debridement for persistent wound drainage, with subsequent DNA extraction from plasma and joint fluid for mNGS and CMT analysis.

Results

Significantly increased C-reactive protein (CRP) levels were observed in patients with infections. The mNGS approach showed greater diagnostic sensitivity (92.06%) for detecting pathogens, including Mycobacterium tuberculosis, than did CMTs (36.51%). Despite its low specificity, mNGS had considerable negative predictive value (70.59%), underscoring its utility in ruling out infections.

Conclusions

The mNGS offers superior sensitivity over CMTs in the diagnosis of a variety of spinal infections, notably

spinal tuberculosis. This study highlights the potential of mNGS in enhancing the diagnosis of complex spinal infections, thereby informing targeted treatment strategies.

Keywords

Metagenomic next-generation sequencing / Conventional microbiological tests / Spinal infections / Sensitivity / Specificity / Predictive value / D-dimers

© The Author(s), under exclusive licence to Huazhong University of Science and Technology 2025

Acknowledgements We would like to express our gratitude to Wuhan KadWise Clinical Laboratory Co., Ltd. for their technical support regarding next-generation sequencing (NGS).

Author's Contributions Khan Akhtar Ali was responsible for writing the abstract, introduction, discussion, results, and collecting data. Xiao-he Ling collected data, performed statistical analysis, and wrote the results. Fang Gao was responsible for data collection and review. Ze-an Xia and Huang Hui has reviewed and made corrections. The corresponding authors are Prof. Dr. Heng Zeng and Wei-hua Hu.

Funding This study was supported by the Hubei Provincial Natural Science Foundation of China (No. 2023AFB646); Knowledge Innovation Program of Wuhan (No. 2023020201010155); Educational Research Program of Huazhong University of Science and Technology (No. 2022135).

Data availability None.

Declarations

Conflict of Interests The authors declare no conflict of interest.

Ethical Approval and Consent to Participate The Ethical Committee of Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology has approved the study and registered under registration number TJ-IRB202406071. All procedures were carried out in conformity with relevant guidelines and regulations. All subjects and/or their legal guardian(s) provided their informed consent.

Informed Consent Additional informed consent was obtained from all individual participants for whom identifying information is included in this article.

Consent for Publication Not applicable.

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Funding

Hubei Provincial Natural Science Foundation of China ((2023AFB646))

Innovation Program of Wuhan Basic Research((No. 2023020201010155))

Educational Research Program of Huazhong University of Science and Technology((2022135))

RIGHTS & PERMISSIONS

The Author(s), under exclusive licence to Huazhong University of Science and Technology