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The influence of resource overlap on bacterial reproductive success in the phyllosphere

Schlechter, R. O.; Kear, E. J.; Bernach, M.; Remus, D. M.; Remus-Emsermann, M. N. P.

2022-01-21 microbiology
10.1101/2022.01.20.477054 bioRxiv
Show abstract

The phyllosphere is densely colonised by rich microbial communities, despite sparse and heterogeneously distributed resources. The limitation of resources is expected to drive bacterial competition resulting in exclusion or coexistence based on fitness differences and resource overlap between individual colonisers. We studied the impact of resource competition by determining the effects of different bacterial colonisers on the growth of the model epiphyte Pantoea eucalypti 299R (Pe299R). Resource overlap was predicted based on genome-scale metabolic modelling. By combining results of metabolic modelling and pairwise competitions in the Arabidopsis thaliana phyllosphere and in vitro, we found that ten resources sufficed to explain fitness of Pe299R. An effect of both resource overlap and phylogenetic relationships was found on competition outcomes in vitro as well as in the phyllosphere. However, effects of resource competition were much weaker in the phyllosphere when compared to in vitro experiments. When investigating growth dynamics and reproductive success at the single-cell resolution, resource overlap and phylogenetic relationships are only weakly correlated with epiphytic Pe299R reproductive success, indicating that the leafs spatial heterogeneity mitigates resource competition. Although the correlation is weak, the presence of competitors led to the development of Pe299R subpopulations that experienced different life histories and cell divisions. Surprisingly, in some in planta competitions, Pe299R benefitted from the presence of epiphytes despite high resource overlap to the competitor strain suggesting other factors having stronger effects than resource competition. This study provides fundamental insights into how bacterial communities are shaped in heterogeneous environments and provides a framework to predict competition outcomes.

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