Cultivable bacteria isolated from apple trees cultivated under different crop systems: Diversity and antagonistic activity against Colletotrichum gloeosporioides.

This study evaluated the diversity of cultivable plant growth-promoting (PGP) bacteria associated with apple trees cultivated under different crop management systems and their antagonistic ability against Colletotrichum gloeosporioides. Samples of roots and rhizospheric soil from apple trees cultivated in organic and conventional orchards in southern Brazil were collected, together with soil samples from an area never used for agriculture (native field). Bacteria were identified at the genus level by PCR-RFLP and partial sequencing of the 16S rRNA, and were evaluated for some PGP abilities. The most abundant bacterial genera identified were Enterobacter (27.7%), Pseudomonas (18.7%), Burkholderia (13.7%), and Rahnella (12.3%). Sixty-nine isolates presented some antagonist activity against C. gloeosporioides. In a greenhouse experiment, five days after exposure to C. gloeosporioides, an average of 30% of the leaf area of plants inoculated with isolate 89 (identified as Burkholderia sp.) were infected, whereas 60 to 73% of the leaf area of untreated plants was affected by fungal attack. Our results allowed us to infer how anthropogenic activity is affecting the bacterial communities in soil associated with apple tree crop systems, and to obtain an isolate that was able to delay the emergence of an important disease for this culture.

A model to explain plant growth promotion traits: a multivariate analysis of 2,211 bacterial isolates.

Plant growth-promoting bacteria can greatly assist sustainable farming by improving plant health and biomass while reducing fertilizer use. The plant-microorganism-environment interaction is an open and complex system, and despite the active research in the area, patterns in root ecology are elusive. Here, we simultaneously analyzed the plant growth-promoting bacteria datasets from seven independent studies that shared a methodology for bioprospection and phenotype screening. The soil richness of the isolate's origin was classified by a Principal Component Analysis. A Categorical Principal Component Analysis was used to classify the soil richness according to isolate's indolic compound production, siderophores production and phosphate solubilization abilities, and bacterial genera composition. Multiple patterns and relationships were found and verified with nonparametric hypothesis testing. Including niche colonization in the analysis, we proposed a model to explain the expression of bacterial plant growth-promoting traits according to the soil nutritional status. Our model shows that plants favor interaction with growth hormone producers under rich nutrient conditions but favor nutrient solubilizers under poor conditions. We also performed several comparisons among the different genera, highlighting interesting ecological interactions and limitations. Our model could be used to direct plant growth-promoting bacteria bioprospection and metagenomic sampling.