Aplicación de la tecnología de metabarcoding 16S rRNA para el análisis de la rizosfera de mora (Rubus glaucus) en cultivos de la provincia de Tungurahua

Abstract

This study focuses on characterizing the diversity and abundance of the microbiota associated with the blackberry rhizosphere, as well as predicting the metabolism of the taxa found. Utilizing next-generation sequencing (NGS) technology and analysis of the hypervariable regions V3-V4 of the 16S rRNA gene, a wide range of bacterial taxa predominantly Proteobacteria, Firmicutes, and Actinobacteria were identified. Alpha and beta diversity analyses revealed high microbial diversity in most of the sampled locations, with significant variations between sampling points, indicating the influence of local environmental factors. Additionally, functional predictions of metabolic profiles were performed using advanced bioinformatics tools such as PICRUSt2 and EzBioCloud, highlighting the contribution of these microbial communities to the biogeochemical cycles of nitrogen, carbon, and sulfur. The results underscore the importance of rhizospheric microbiota in soil health and the growth of R. glaucus and suggest its potential for use in biocontrol and biofertilization strategies. This study not only provides a deeper understanding of microbial ecology in blackberry crops but also offers a foundation for future research and practical applications in sustainable agricultural management in the Tungurahua region.