Comparison between two bioinformatics approaches for 16S metabarcoding analysis in the identification of bacterial microbiota of attine ants and associated soil

• Grant number: 24/21504-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: May 01, 2025
• End date: April 30, 2026
• Field of knowledge: Biological Sciences - Genetics - Molecular Genetics and Genetics of Microorganisms
• Principal Investigator: Milene Ferro
• Grantee: Letícia de Melo El Kadre
• Host Institution: Instituto de Biociências (IB). Universidade Estadual Paulista (UNESP). Campus de Rio Claro. Rio Claro , SP, Brazil

Abstract

The 16S rRNA gene, used in metabarcoding sequencing analyses, is considered a universal molecular marker for identifying and analyzing bacterial communities. Unlike traditional cultivation techniques, this method allows for a more comprehensive analysis since not all microorganisms are cultivable in the laboratory and cultivation is often limited by the specificity of culture media, which could result in an underestimation of the real diversity of species present. Leaf-cutting ants, represented in this project by Atta sexdens, exemplify a symbiotic relationship with fungi cultivated in underground gardens, serving as a clear example of mutualism. In this system, the ants provide substrate and nutrients, such as cut leaves, for the fungi growth, while the fungi serve as the main source of food for the ants. This mutualistic interaction not only sustains both species, but also shapes the structure and dynamics of the anthill, reflecting adaptive coevolution and ecological specialization. Additionally, the microbial diversity associated with leaf-cutting ants plays an essential role in the health and functioning of the anthill, participating directly in maintaining the structure between the ants and the fungi that is cultivated. In light of this, this project aims to compare the bioinformatics tools Kraken2 and DADA2 in terms of the diversity and taxonomic classification obtained from 16S metabarcoding data for Atta sexdens ants and soil near the anthill. The objective is to evaluate the results of bioinformatics analyses of metabarcoding libraries using the DADA2 pipeline and compare them with the diversity and taxonomic classification detected by Kraken2. Thus, through the analyses carried out by both tools, possible differences and similarities will be evaluated and verified in terms of the diversity and taxonomic classification found using the different tools in different samples.