Resolving metabolic interaction mechanisms in plant microbiomes

Incorporating microbiome analyses can enhance conservation of threatened species and ecosystem functions

Conservation genomics is a rapidly growing subdiscipline of conservation biology that uses genome-wide information to inform management of biodiversity at all levels. Such efforts typically focus on species or systems of conservation interest, but rarely consider associated microbes. At least three major approaches have been used to study how microorganisms broadly contribute to conservation areas: (1) diversity surveys map out microbial species distribution patterns in a variety of hosts, natural environments or regions; (2) functional surveys associate microbial communities with factors of interest, such as host health, symbiotic interactions, environmental characteristics, ecosystem processes, and biological invasions; and (3) manipulative experiments examine the response of changes to microbial communities or determine the functional roles of specific microbes within hosts or communities by adding, removing, or genetically modifying microbes. In practice, multiple approaches are often applied simultaneously. The results from all three conservation genomics approaches can be used to help design practical interventions and improve management actions, some of which we highlight below. However, experimental manipulations allow for more robust causal inferences and should be the ultimate goal of future work. Here we discuss how further integration of microbial research of a host's microbiome and of free living microbes into conservation biology will be an essential advancement for conservation of charismatic organisms and ecosystem functions in light of ongoing global environmental change.

The rhizosphere and root selections intensify fungi-bacteria interaction in abiotic stress-resistant plants

The microbial communities, inhabiting around and in plant roots, are largely influenced by the compartment effect, and in turn, promote the growth and stress resistance of the plant. However, how soil microbes are selected to the rhizosphere, and further into the roots is still not well understood. Here, we profiled the fungal, bacterial communities and their interactions in the bulk soils, rhizosphere soils and roots of eleven stress-resistant plant species after six months of growth. The results showed that the root selection (from the rhizosphere soils to the roots) was stronger than the rhizosphere selection (from the bulk soils to the rhizosphere soils) in: (1) filtering stricter on the fungal (28.5% to 40.1%) and bacterial (48.9% to 68.1%) amplicon sequence variants (ASVs), (2) depleting more shared fungal (290 to 56) and bacterial (691 to 2) ASVs measured by relative abundance, and (3) increasing the significant fungi-bacteria crosskingdom correlations (142 to 110). In addition, the root selection, but not the rhizosphere selection, significantly increased the fungi to bacteria ratios (f:b) of the observed species and shannon diversity index, indicating unbalanced effects to the fungal and bacteria communities exerted by the root selection. Based on the results of network analysis, the unbalanced root selection effects were associated with increased numbers of negative interaction (140 to 99) and crosskingdom interaction (123 to 92), suggesting the root selection intensifies the negative fungi-bacteria interactions in the roots. Our findings provide insights into the complexity of crosskingdom interactions and improve the understanding of microbiome assembly in the rhizosphere and roots.

Metabolic interaction models recapitulate leaf microbiota ecology

Resource allocation affects the structure of microbiomes, including those associated with living hosts. Understanding the degree to which this dependency determines interspecies interactions may advance efforts to control host-microbiome relationships. We combined synthetic community experiments with computational models to predict interaction outcomes between plant-associated bacteria. We mapped the metabolic capabilities of 224 leaf isolates from Arabidopsis thaliana by assessing the growth of each strain on 45 environmentally relevant carbon sources in vitro. We used these data to build curated genome-scale metabolic models for all strains, which we combined to simulate >17,500 interactions. The models recapitulated outcomes observed in planta with >89% accuracy, highlighting the role of carbon utilization and the contributions of niche partitioning and cross-feeding in the assembly of leaf microbiomes.