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Updated: Feb 3, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

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Standard Detection Protocol: PCR and RFLP Analyses Based on 16S rRNA Gene

Assunta Bertaccini1, Samanta Paltrinieri2, Nicoletta Contaldo2

  • 1Phytobacteriology Laboratory, DISTAL, Alma Mater Studiorum, University of Bologna, Bologna, Italy. assunta.bertaccini@unibo.it.

Methods in Molecular Biology (Clifton, N.J.)
|October 27, 2018
PubMed

Insights

This study details a PCR and restriction fragment length polymorphism method for phytoplasma detection and identification. It accurately identifies known and unknown phytoplasmas at the 16S rRNA group and subgroup levels.

Area of Science:

  • Plant pathology
  • Molecular biology
  • Microbial genetics

Background:

  • Phytoplasmas are plant-pathogenic bacteria lacking cell walls.
  • Accurate detection and identification are crucial for disease management.
  • Current methods rely on molecular techniques for differentiation.

Purpose of the Study:

  • To describe a PCR-based protocol for phytoplasma detection.
  • To enable differentiation of phytoplasmas at 16S rRNA (16Sr) group and subgroup levels.
  • To validate the method for both in vitro amplicons and in silico sequence analysis.

Main Methods:

  • Polymerase Chain Reaction (PCR) amplification of the 16S rRNA gene.
  • Restriction Fragment Length Polymorphism (RFLP) analysis of PCR products.
  • In silico analysis of 16S rRNA gene sequences.

Main Results:

  • The PCR-RFLP method successfully detected and differentiated phytoplasmas.
  • The protocol allowed for classification at the 16Sr group and subgroup levels.
  • Both direct analysis of amplicons and in silico analysis yielded consistent results.

Conclusions:

  • PCR-RFLP is a reliable method for phytoplasma identification.
  • This protocol aids in the characterization of known and potentially novel phytoplasmas.
  • The method is applicable to both experimental and computational analyses.
Keywords:
DetectionIdentificationPhytoplasmaRibosomal groupRibosomal subgroupSequencing

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