Bipartite interactions, antibiotic production and biosynthetic potential of the Arabidopsis leaf microbiome.

Plants are colonized by phylogenetically diverse microorganisms that affect plant growth and health. Representative genome-sequenced culture collections of bacterial isolates from model plants, including Arabidopsis thaliana, have recently been established. These resources provide opportunities for systematic interaction screens combined with genome mining to discover uncharacterized natural products. Here, we report on the biosynthetic potential of 224 strains isolated from the A. thaliana phyllosphere. Genome mining identified more than 1,000 predicted natural product biosynthetic gene clusters (BGCs), hundreds of which are unknown compared to the MIBiG database of characterized BGCs. For functional validation, we used a high-throughput screening approach to monitor over 50,000 binary strain combinations. We observed 725 inhibitory interactions, with 26 strains contributing to the majority of these. A combination of imaging mass spectrometry and bioactivity-guided fractionation of the most potent inhibitor, the BGC-rich Brevibacillus sp. Leaf182, revealed three distinct natural product scaffolds that contribute to the observed antibiotic activity. Moreover, a genome mining-based strategy led to the isolation of a trans-acyltransferase polyketide synthase-derived antibiotic, macrobrevin, which displays an unprecedented natural product structure. Our findings demonstrate that the phyllosphere is a valuable environment for the identification of antibiotics and natural products with unusual scaffolds.

Metabolic footprint of epiphytic bacteria on Arabidopsis thaliana leaves.

The phyllosphere, which is defined as the parts of terrestrial plants above the ground, is a large habitat for different microorganisms that show a high extent of adaption to their environment. A number of hypotheses were generated by culture-independent functional genomics studies to explain the competitiveness of specialized bacteria in the phyllosphere. In contrast, in situ data at the metabolome level as a function of bacterial colonization are lacking. Here, we aimed to obtain new insights into the metabolic interplay between host and epiphytes upon colonization of Arabidopsis thaliana leaves in a controlled laboratory setting using environmental metabolomics approaches. Quantitative nuclear magnetic resonance (NMR) and imaging high-resolution mass spectrometry (IMS) methods were used to identify Arabidopsis leaf surface compounds and their possible involvement in the epiphytic lifestyle by relative changes in compound pools. The dominant carbohydrates on the leaf surfaces were sucrose, fructose and glucose. These sugars were significantly and specifically altered after epiphytic leaf colonization by the organoheterotroph Sphingomonas melonis or the phytopathogen Pseudomonas syringae pv. tomato, but only to a minor extent by the methylotroph Methylobacterium extorquens. In addition to carbohydrates, IMS revealed surprising alterations in arginine metabolism and phytoalexin biosynthesis that were dependent on the presence of bacteria, which might reflect the consequences of bacterial activity and the recognition of not only pathogens but also commensals by the plant. These results highlight the power of environmental metabolomics to aid in elucidating the molecular basis underlying plant-epiphyte interactions in situ.

DynaMet: a fully automated pipeline for dynamic LC-MS data.

Dynamic isotope labeling data provides crucial information about the operation of metabolic pathways and are commonly generated via liquid chromatography-mass spectrometry (LC-MS). Metabolome-wide analysis is challenging as it requires grouping of metabolite features over different samples. We developed DynaMet for fully automated investigations of isotope labeling experiments from LC-high-resolution MS raw data. DynaMet enables untargeted extraction of metabolite labeling profiles and provides integrated tools for expressive data visualization. To validate DynaMet we first used time course labeling data of the model strain Bacillus methanolicus from (13)C methanol resulting in complex spectra in multicarbon compounds. Analysis of two biological replicates revealed high robustness and reproducibility of the pipeline. In total, DynaMet extracted 386 features showing dynamic labeling within 10 min. Of these features, 357 could be fitted by implemented kinetic models. Feature identification against KEGG database resulted in 215 matches covering multiple pathways of core metabolism and major biosynthetic routes. Moreover, we performed time course labeling experiment with Escherichia coli on uniformly labeled (13)C glucose resulting in a comparable number of detected features with labeling profiles of high quality. The distinct labeling patterns of common central metabolites generated from both model bacteria can readily be explained by one versus multicarbon compound metabolism. DynaMet is freely available as an extension package for Python based eMZed2, an open source framework built for rapid development of LC-MS data analysis workflows.

Oral insecticidal activity of plant-associated pseudomonads.

Biocontrol pseudomonads are most known to protect plants from fungal diseases and to increase plant yield, while intriguing aspects on insecticidal activity have been discovered only recently. Here, we demonstrate that Fit toxin producing pseudomonads, in contrast to a naturally Fit-deficient strain, exhibit potent oral activity against larvae of Spodoptera littoralis, Heliothis virescens and Plutella xylostella, all major insect pests of agricultural crops. Spraying plant leaves with suspensions containing only 1000 Pseudomonas cells per ml was sufficient to kill 70-80% of Spodoptera and Heliothis larvae. Monitoring survival kinetics and bacterial titres in parallel, we demonstrate that Pseudomonas fluorescens CHA0 and Pseudomonas chlororaphis PCL1391, two bacteria harbouring the Fit gene cluster colonize and kill insects via oral infection. Using Fit mutants of CHA0 and PCL1391, we show that production of the Fit toxin contributes substantially to oral insecticidal activity. Furthermore, the global regulator GacA is required for full insecticidal activity. Our findings demonstrate the lethal oral activity of two root-colonizing pseudomonads so far known as potent antagonists of fungal plant pathogens. This adds insecticidal activity to the existing biocontrol repertoire of these bacteria and opens new perspectives for applications in crop pest control and in research on their ecological behaviour.