Abstract
Fusobacterium nucleatum (Fn) is increasingly recognized as a cancer-associated bacterium, yet reliable quantification in human specimens is challenging due to low bacterial burden and abundant host DNA. We analyzed 145 Fusobacterium genomes to design primers targeting conserved regions of the fadA adhesin gene and developed a duplex quantitative real-time PCR (qPCR) assay for simultaneous detection of fadA and a human PGT as an internal control. Analytical sensitivity, specificity, precision, and reproducibility were evaluated using serially diluted Fn DNA, spike-in experiments with human DNA, and cross-platform/operator validation. Clinical performance was assessed in colorectal cancer patient tissues, including fresh tissue (n = 24) and formalin-fixed paraffin-embedded (FFPE) samples (n = 22), using 16S rRNA-based methods as references. The assay successfully detected all four major Fn subspecies (nucleatum, animalis, polymorphum, and vincentii). The limit of detection was ≤0.1 pg, with no interference between duplex targets. Spike-in experiments demonstrated consistent target detection in human-DNA-rich samples, with strong linearity (R2 = 0.998) across dilutions. High precision (coefficient of variations < 5%) was observed across intra-day, inter-day, inter-instrument, and inter-operator evaluations. In fresh tissues, the assay yielded 86% sensitivity, 94% specificity, and 92% accuracy. Using the FFPE samples, the assay achieved 91% sensitivity and 100% specificity, confirming robust classification in both clinical samples. This duplex qPCR assay enables broad detection of Fn with high analytical performance in both fresh and FFPE tissues. Its simplicity, reproducibility, and compatibility with pathology workflows support deployment in multi-center studies and downstream applications in diagnostic studies and prognostic modeling.
| Original language | English |
|---|---|
| Article number | 11319 |
| Journal | International journal of molecular sciences |
| Volume | 26 |
| Issue number | 23 |
| DOIs | |
| Publication status | Published - 2025 Dec |
Bibliographical note
Publisher Copyright:© 2025 by the authors.
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This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Catalysis
- Molecular Biology
- Computer Science Applications
- Spectroscopy
- Physical and Theoretical Chemistry
- Organic Chemistry
- Inorganic Chemistry
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