Deciphering Genomes: Genetic Signatures of Plant-Associated Micromonospora

Abstract

Understanding plant-microbe interactions with the possibility to modulate the plant's microbiome is essential to design new strategies for a more productive and sustainable agriculture and to maintain natural ecosystems. Therefore, a key question is how to design bacterial consortia that will yield the desired host phenotype. This work was designed to identify the potential genomic features involved in the interaction between Micromonospora and known host plants. Seventy-four Micromonospora genomes representing diverse environments were used to generate a database of all potentially plant-related genes using a novel bioinformatic pipeline that combined screening for microbial-plant related features and comparison with available plant host proteomes. The strains were recovered in three clusters, highly correlated with several environments: plant-associated, soil/rhizosphere, and marine/mangrove. Irrespective of their isolation source, most strains shared genes coding for commonly screened plant growth promotion features, while differences in plant colonization related traits were observed. When Arabidopsis thaliana plants were inoculated with representative Micromonospora strains selected from the three environments, significant differences were in found in the corresponding plant phenotypes. Our results indicate that the identified genomic signatures help select those strains with the highest probability to successfully colonize the plant and contribute to its wellbeing. These results also suggest that plant growth promotion markers alone are not good indicators for the selection of beneficial bacteria to improve crop production and the recovery of ecosystems.

Keywords: Micromonospora; PGP; actinobacteria; endophyte; genome; microbe-plant interaction.

FIGURE 1

Bioinformatic workflow for database construction. Symbols: cylinders, databases; circles, pipeline processes; rhomboids, annotations; squares, input data; balloons, partial results.

FIGURE 2

Principal component analysis (PCA) of putative plant-related genes according to COG categories with strains recovered in groups G1, G2, and G3, respectively (for Group composition, see Section “Results”). The bar graph represents the contribution (%) of each COG category to dimensions 1 and 2 of the PCA.

FIGURE 3

Up-to-date bacterial core gene phylogenomic tree reconstructed with 92 bacterial core genes. Gene support indices are given at nodes as filled purple circles.

FIGURE 4

Differential KEGG annotations between Cluster 1 (Plant associated), Cluster 2 (Soil/rhizosphere), and Cluster 3 (Mangrove/marine). Annotations are grouped in their corresponding KEGG categories (first and last columns).

FIGURE 5

Arabidopsis thaliana plants after 4 weeks of growth and inoculated with strains from Cluster 1 (MED15, PSN01, and PSH03), Cluster 2 (M. aurantiaca DSM 43813^T, M. chaiyaphumensis DSM 45246^T, and M. chalcea DSM 43026^T), and Cluster 3 (M. pattaloongensis JCM 12833^T, M. palomenae DSM 102131^T, and M. olivasterospora DSM 43868^T).

FIGURE 6

(A) Accumulated Z-scores of the growth parameters measured in A. thaliana after 4 weeks of growth and inoculated with Micromonospora strains selected from clusters C1, C2, and C3. (B) PCA distribution of the strains based on the plant growth parameters measured. Symbols: green circles, C1 (plant-associated); red triangles, C22 (soil/rhizosphere); blue squares, C3 (mangrove/marine sediments).