Time, More than Genes, Shapes the Poplar Tree Microbiome
Ecological assembly and source tracking models characterize the initial assembly of the poplar microbiome across plant-associated habitats.
Recent work shows that the plant microbiome—the microorganisms in a plant and its immediate environment—influences plant health, survival, and fitness. The initial assembly of the microbiome is particularly important. Assembly refers to the processes that produce the types and numbers of species within the microbiome. This research characterized the initial assembly of the microbiome in several types of poplar trees. The study found that the composition of the microbiome changed dramatically over time. For archaea and bacteria in the microbiome, the passage of time caused the amount of variation to decrease. However, variation among fungi in the microbiome was shaped by several processes. The poplar trees’ genetic makeup proved to be less of a factor than researchers had expected.
The initial assembly of a plant microbiome may help set the microbiome’s future. This can determine the overall future health of the plant. However, while scientists know much about the initial microbiome assembly of grasses and agricultural crops, they know less about the initial microbiome of long-lived trees, such as poplar. Poplar trees may be excellent candidates for biofuels and other applications. If scientists gain a better understanding of the plant’s microbiome, they can make greater use of these trees. For example, the findings of this new research could help scientists use microbes to improve the health and growth of poplar trees.
Recent work shows that the plant microbiome, particularly the initial assembly of this microbiome, influences plant health, survival, and fitness. In this research, scientists characterized the initial assembly of Populus microbial communities across ten genotypes belonging to two poplar species in a common garden. The researchers sequenced the microbiome within leaf and root tissues (leaf and root endosphere), leaf surface, and root surface and immediate surroundings (rhizosphere). They paired molecular analyses with ecological assembly models and source tracking models to describe the assembly of the Populus microbiome during the first growing season.
The scientists found that the composition of the microbiome changed dramatically over time across all plant-associated habitats and host genotypes. For archaea and bacteria, these changes were dominated by strong homogenizing selection (accounting for 29 to 62 percent of pairwise comparisons). However, fungal assembly was generally characterized by multiple ecological assembly processes (a mix of weak selective and dispersal processes). Interestingly, genotype, while a significant moderator of microbiome composition, generally explained less variation than sample date across plant-associated habitats. The researchers defined a set of core genera that accounted for, on average, 36 percent of the microbiome. The relative abundance of this core community was consistent over time. Additionally, using source tracking modeling, they determined that new microbial taxa colonize from both aboveground and belowground sources. Combined with our ecological assembly null models, they found that both selective and dispersal processes explained the differences between exo- (i.e., leaf surface and rhizosphere) and endospheric microbiomes. Taken together, the results suggest that the initial assembly of the Populus microbiome is dependent on time, genotype, and habitat and is moderated by both selective and stochastic factors.
Oak Ridge National Laboratory
BER Program ManagerCatherine Ronning
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Biological Systems Science Division
This research was supported by the Genomic Science program with the Biological and Environmental Research Program of the U.S. Department of Energy Office of Science, as part of the Plant-Microbe Interfaces Scientific Focus Area.
Dove, N. C., et al., Assembly of the Populus microbiome is temporally dynamic and determined by selective and stochastic factors. mSphere. 6(3), e01316-20 (2021). [DOI: 10.1128/mSphere.01316-20]