Retrospective clinical and microbiologic analysis of metagenomic next-generation sequencing in the microbiological diagnosis of cutaneous infectious granulomas

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Abstract

Background: Cutaneous infectious granulomas (CIG) are localized and chronic skin infection caused by a variety of pathogens such as protozoans, bacteria, worms, viruses and fungi. The diagnosis of CIG is difficult because microbiological examination shows low sensitivity and the histomorphological findings of CIG caused by different pathogens are commonly difficult to be distinguished. Objective: The objective of this study is to explore the application of mNGS in tissue sample testing for CIG cases, and to compare mNGS with traditional microbiological methods by evaluating sensitivity and specificity. Methods: We conducted a retrospective study at the Department of Dermatology of Sun Yat-sen Memorial Hospital, Sun Yat-sen University from January 1st, 2020, to May 31st, 2024. Specimens from CIG patients with a clinical presentation of cutaneous infection that was supported by histological examination were retrospectively enrolled. Specimens were delivered to be tested for microbiological examinations and mNGS. Results: Our data show that mNGS detected Non-tuberculosis mycobacteria, Mycobacterium tuberculosis, fungi and bacteria in CIG. Compared to culture, mNGS showed a higher positive rate (80.77% vs. 57.7%) with high sensitivity rate (100%) and negative predictive value (100%). In addition, mNGS can detect more pathogens in one sample and can be used to detect variable samples including the samples of paraffin-embedded tissue with shorter detective time. Of the 21 patients who showed clinical improvement within a 30-day follow-up, eighteen had their treatments adjusted, including fifteen who continued treatment based on the results of mNGS. Conclusions: mNGS could provide a potentially rapid and effective alternative detection method for diagnosis of cutaneous infectious granulomas and mNGS results may affect the clinical prognosis resulting from enabling the patients to initiate timely treatment.

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Liu, H., Ran, Q., Ma, J., Zhang, J., Tan, N., Xi, L., … Lu, S. (2024). Retrospective clinical and microbiologic analysis of metagenomic next-generation sequencing in the microbiological diagnosis of cutaneous infectious granulomas. Annals of Clinical Microbiology and Antimicrobials, 23(1). https://doi.org/10.1186/s12941-024-00744-w

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