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Unbiased pathogen detection via metagenomics NGS in a cohort of 623 FFPE tissue samples.

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NIAID Data Ecosystem2026-05-10 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP172495
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Objectives: Pathogen detection in formalin-fixed paraffin-embedded (FFPE) tissue remains challenging. We implemented metagenomic next-generation sequencing (mNGS) in our routine diagnostic workflow to evaluate its feasibility, diagnostic yield, and pathogen spectrum in real-world infectious pathology cases. Methods: Between November 2021 and April 2025, we analyzed 623 FFPE tissue samples using a low-depth mNGS workflow on the Thermo Fisher Ion Torrent platform with a CLC Genomics Workbench bioinformatics pipeline. Our assay was designed to detect DNA pathogens. When possible, results were validated by orthogonal methods including species-specific PCRs, 16S/ITS PCR, and immunohistochemistry on tissue sections. Results: Among 623 samples analyzed, at least one potentially pathogenic and plausible microorganism was identified in 229 samples (36.8%), while 334 (53.6%) were negative and 60 (9.6%) were uninterpretable due to quality control failures or suspected contamination. Of the 229 positive samples, 145 (63.3%) involved bacteria, 37 (16.2%) viruses, 28 (12.2%) fungi, and 9 (3.9%) parasites; mixed infections with more than one pathogen were detected in 10 (4.4%) samples. The most frequently identified bacterial family was Mycobacteriaceae (n=27), including Mycobacterium xenopi (n=8), which is not routinely covered by syndromic multiplex PCR panels. Notable viral and fungal detections included a novel human circovirus and Coccidioides spp. Despite variable sample quality and DNA input, mNGS yielded reliable results in a wide range of tissue types. Conclusions: Metagenomic NGS is a feasible, valuable addition to routine infectious pathology diagnostics, particularly in complex or inconclusive cases. The assay improved the diagnostic yield compared to conventional PCR, expanded the range of detectable pathogens, and proved robust even in low-quality FFPE samples. These results support broader adoption of mNGS in tissue-based pathogen diagnostics.
创建时间:
2026-03-02
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