Soil-borne microbiome: linking diversity to function

Soil microorganisms are sensitive to environment disturbances, and such alterations have consequences on microbial diversity and functions. Our hypothesis is that alpha diversity of microbial communities and functional diversity decrease from undisturbed to disturbed soils, with consequences for functional redundancy in the soil ecosystem. To test this hypothesis, we used soil DNA shotgun metagenomics approach to assess the soil microbiome in a chronosequence of land-use from a native tropical forest, followed by deforestation and cultivation of soybean croplands and pasture in different seasons. Agriculture and pasture soils were among the most diverse and presented higher functional redundancy, which is important to maintain the ecosystem functioning after the forest conversion. On the other hand, the ecosystem equilibrium in forest is maintained based on a lower alpha diversity but higher abundance of microorganisms. Our results indicate that land-use change alters the structure and composition of microbial communities; however, ecosystem functionality is overcome by different strategies based on the abundance and diversity of the communities.

Taxonomical and functional microbial community selection in soybean rhizosphere

This study addressed the selection of the rhizospheric microbial community from the bulk soil reservoir under agricultural management of soybean in Amazon forest soils. We used a shotgun metagenomics approach to investigate the taxonomic and functional diversities of microbial communities in the bulk soil and in the rhizosphere of soybean plants and tested the validity of neutral and niche theories to explain the rhizosphere community assembly processes. Our results showed a clear selection at both taxonomic and functional levels operating in the assembly of the soybean rhizosphere community. The taxonomic analysis revealed that the rhizosphere community is a subset of the bulk soil community. Species abundance in rhizosphere fits the log-normal distribution model, which is an indicator of the occurrence of niche-based processes. In addition, the data indicate that the rhizosphere community is selected based on functional cores related to the metabolisms of nitrogen, iron, phosphorus and potassium, which are related to benefits to the plant, such as growth promotion and nutrition. The network analysis including bacterial groups and functions was less complex in rhizosphere, suggesting the specialization of some specific metabolic pathways. We conclude that the assembly of the microbial community in the rhizosphere is based on niche-based processes as a result of the selection power of the plant and other environmental factors.

Acidobacterial community responses to agricultural management of soybean in Amazon forest soils

This study focused on the impact of land-use changes and agricultural management of soybean in Amazon forest soils on the abundance and composition of the acidobacterial community. Quantitative real-time PCR (q-PCR) assays and pyrosequencing of 16S rRNA gene were applied to study the acidobacterial community in bulk soil samples from soybean croplands and adjacent native forests, and mesocosm soil samples from soybean rhizosphere. Based on qPCR measurements, Acidobacteria accounted for 23% in forest soils, 18% in cropland soils, and 14% in soybean rhizosphere of the total bacterial signals. From the 16S rRNA gene sequences of Bacteria domain, the phylum Acidobacteria represented 28% of the sequences from forest soils, 16% from cropland soils, and 17% from soybean rhizosphere. Acidobacteria subgroups 1-8, 10, 11, 13, 17, 18, 22, and 25 were detected with subgroup 1 as dominant among them. Subgroups 4, 6, and 7 were significantly higher in cropland soils than in forest soils, which subgroups responded to decrease in soil aluminum. Subgroups 6 and 7 responded to high content of soil Ca, Mg, Mn, and B. These results showed a differential response of the Acidobacteria subgroups to abiotic soil factors, and open the possibilities to explore acidobacterial subgroups as early-warning bioindicators of agricultural soil management effects in the Amazon area.