Optimized protocol for profiling mucosa-associated microbiota from formalin-fixed paraffin-embedded gut tissues from

Noora Al-Ali1, Haifa Al-Awadhi2, Maya Hassane1

  • 1Department of Medical Microbiology and Immunology, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates.

Abstract

Insights

A new two-step PCR method enhances microbiome analysis in FFPE tissues, improving detection of mucosa-associated microbiota in pediatric Crohn's disease patients.

Area of Science:

  • Microbiome research
  • Molecular biology
  • Genomics

Background:

  • Formalin-fixed, paraffin-embedded (FFPE) tissues are valuable but underutilized for microbiome studies.
  • Data on mucosa-associated microbiota (MAM) in Crohn's disease (CD) are limited due to methodological challenges.

Purpose of the Study:

  • To develop and validate an optimized amplicon-based workflow for profiling MAM from pediatric CD patient FFPE gut biopsies.
  • To improve the detection and characterization of the gut microbiome in archival tissue samples.

Main Methods:

  • Compared two protocols (single vs. two-step PCR) for 16S rRNA gene amplification and sequencing on the Oxford Nanopore platform.
  • Analyzed 68 FFPE gut biopsy samples from pediatric CD patients and healthy controls.
  • Optimized protocol involved two sequential PCR amplifications with purification steps to enhance yield and purity.

Main Results:

  • The two-step protocol (P2) significantly outperformed the single-step protocol (P1).
  • P2 yielded higher DNA concentration, reduced human DNA contamination, and improved pore performance.
  • P2 detected a richer, more diverse microbial community, including low-abundance species and pathogenic genera like *Escherichia* and *Klebsiella*.

Conclusions:

  • The optimized two-step workflow enhances sequencing performance and microbiota detection in FFPE tissues.
  • This method enables retrospective microbiome characterization from archival samples.
  • The approach offers a scalable platform for clinical biomarker discovery in diseases like CD.

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