Bacteriome diversity in leaf and root of the resurrection species Selaginella convoluta and S. sellowii in the Brazilian Cerrado

Abstract Plants have developed adaptive strategies to combat dehydration, including forming associations with microbes, which help plants cope with drought by altering hormone levels, enhancing antioxidants, or improving water uptake. Selaginella species, the resurrection plants, can endure desiccation and revive with rehydration. Here, we investigated the bacteriome of leaves and roots of S. convoluta and S. sellowii inhabiting rocky outcrops. We analyzed 16 S rRNA bacterial sequences from 38 leaves samples and 36 from roots. Actinobacteriota , Chloroflexi , Proteobacteria , and Acidobacteriota were the dominant phyla, with Methylobacteriaceae , Pseudonocardiaceae , and Sphingomonadaceae being the most prevalent bacterial families. The roots and leaves exhibited an increased relative abundance of the phyla Actinobacteriota and Proteobacteria , whereas Chloroflexi and Acidobacteriota were also common in the roots. The families identified in the leaves are commonly associated with soil, likely reflecting the plant structure and their close contact with the ground; root samples displayed higher diversity indices than leaves. The functional diversity analysis showed no significant differences between the species’ roots, though some samples displayed increased photoautotrophic reactions. Selaginella selowii exhibited enhanced aerobic ammonia oxidation, photoautotrophy, and denitrification, while S. convoluta showed increased methanol oxidation and methylotrophy, with Methylopila as the main contributor. The identified bacterial families were beneficial for nutrient acquisition, growth, and fungal regulation at the root interface, contributing to plant health in nutrient-poor, shallow, and acidic soils characteristic of the Brazilian Cerrado. This study highlights the importance of understanding plant–microbiome interactions in harsh environments, such as the Cerrado biome, using Selaginella as a model for drought tolerance.