bioRxivMicrobiology
Leaf side determines the relative importance of dispersal versus host filtering in the phyllosphere microbiome
W. Smets, M. K. Chock, C. M. Walsh, C. Q. Vanderburgh, E. Kau, S. E. Lindow, N. Fierer, B. Koskella
Abstract
Leaf surface-associated bacterial communities play a significant role in plant health and have therefore been the focus of increasing interest. Despite this, we currently lack a predictive understanding of how leaf-associated bacterial communities are structured within and across hosts, including how leaf traits shape this variation and how community assembly processes may differ across distinct microbial habitats on a leaf. In this study, we characterize the composition of bacterial phyllosphere communities from the upper and lower leaf surfaces of 66 plants across 24 species grown at a common site using 16S rRNA amplicon sequencing. By comparing leaves that vary in pH and stomatal densities and analyzing the leaf surfaces separately, we were able to test the key factors shaping the phyllosphere across host plant species from diverse geographical origins. We found a surprisingly large shared/core microbiome across species, as well as a strong effect of plant species and native origin in shaping composition. Importantly, we found the lower leaf side, where pH values are generally lower and stomatal densities higher, to have lower taxonomic richness relative to the upper leaf side. While the upper leaf side community appears to be more strongly influenced by dispersal effects, the lower leaf appears to be more strongly influenced by plant host filtering effects, as supported by higher relative abundance of shared core taxa and higher signatures of endemism. This work highlights important differences in community assembly processes across the upper and lower leaf microbiomes and underscores the importance of considering differences among habitats within a host when explaining microbial community assembly and composition.
- organism: plant (other)
- assay: metagenomics
- research focus: ecology & biodiversity
- approach: statistical model
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