ArticleFrontiers in cellular and infection microbiology2026
Optimized protocol for profiling mucosa-associated microbiota from formalin-fixed paraffin-embedded gut tissues from treatment-naïve pediatric patients with Crohn's disease.
Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Formalin-fixed, paraffin-embedded (FFPE) tissues are yet underutilized resources for microbiome studies. Data on the mucosa-associated microbiota (MAM) of patients with Crohn's disease (CD) are scarce, due to several methodological limitations. In this study, we aimed to develop and validate a new optimized amplicon-based workflow to profile MAM from FFPE gut biopsies of pediatric CD patients. Methods: We examined 68 FFPE samples, including 34 biopsies from treatment-naïve patients with CD and 34 from healthy controls (HC). V3-V7 regions of the 16S rRNA gene were amplified and sequenced on the Oxford Nanopore platform. Two protocols were tested: Protocol 1 (P1), consisting of a single PCR amplification and purification step, and Protocol 2 (P2), including two sequential PCR amplifications with purification after each round. The second amplification and purification steps were introduced to increase sequencing yield and improve microbiota detection. Results: P2 consistently outperformed P1, yielding significantly higher DNA concentration and purity, reducing human DNA contamination and sustaining pore performance. P2 also generated more microbial reads and recovered a richer, more taxonomically diverse community, including increased detection of species with low abundance. More taxa were enriched in P2 across all levels, enhancing species-level resolution. P2 enabled comprehensive detection of pathogenic genera, such as Conclusions: The optimized workflow with a two-step strategy improved sequencing performance and enhanced microbiota detection in FFPE tissues. This approach enabled successful profiling of MAM, providing a novel method for retrospective characterization of the microbiome from archival tissues and providing a scalable platform for clinical biomarker discovery.
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