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Prenni, J.

Publications and source records attributed to Prenni, J..

3 recordsLinked to original sources

Variation in root exudate composition influences soil microbiome membership and function

Root exudation is one of the primary processes that mediate interactions between plant roots, microorganisms, and the soil matrix. Previous research has shown that plant root exudate profiles vary between species and genotypes which can likely support different microbial associations. Here, utilizing distinct sorghum genotypes as a model system, we characterized the chemical heterogeneity between root exudates and the effects of that variability on soil microbial membership and metabolisms. Distinct exudate chemical profiles were quantified and used to formulate synthetic root exudate treatments, a High Organic acid Treatment (HOT) and a High Sugar Treatment (HST). Root exudate treatments were added to laboratory soil reactors and 16S rRNA gene profiling illustrated distinct microbial membership in response to HST or HOT amendments. Alpha and beta diversity metrics were significantly different between treatments, (Shannons, p < 0.0001, mrpp = 0.01, respectively). Exometabolite production was highest in the HST, with increased production of key organic acids, non-proteinogenic amino acids, and three plant growth-promoting phytohormones (benzoic acid, salicylic acid, indole-3-acetic acid), suggesting plant-derived sugars fuel microbial carbon metabolism and contribute to phytohormone production. Linking the metabolic capacity of metagenome-assembled genomes in the HST to the exometabolite patterns, we identified potential plant growth-promoting microorganisms that could produce these phytohormones. Our findings emphasize the tractability of high-resolution multi-omics tools to investigate soil microbiomes, opening the possibility of manipulating native microbial communities to improve specific soil microbial functions and enhance crop production. ImportanceUnderstanding interactions between plant root exudates and the soil microbiome provides an avenue for a more comprehensive appreciation for how plant roots modulate their microbial counterparts to promote an environment favorable to plant fitness. Although these dynamics are appreciated as indispensable, mechanisms controlling specific rhizobiome membership and complexity are not fully understood. In this study, we investigate how variability in root exudation, modeled after differences observed between distinct sorghum genotypes, contributes to altered microbial membership and metabolisms. The results demonstrate how microbial diversity is influenced by root exudates of differing chemical composition and how changes in microbial membership correspond to modifications in carbon utilization and enhance production of plant-relevant metabolites. Our findings suggest carbon substrate preferences among bacteria in semi-arid climate soils and mechanisms for root exudate utilization. These findings provide new information on plant-soil environments useful for the development of efficient and precise microbiota management strategies in agricultural systems.

plant biology↗

Increased signal to noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components.

Environmental variability poses a major challenge to any field study. Researchers attempt to mitigate this challenge through replication. Thus, the ability to detect experimental signals is determined by the degree of replication and the amount of environmental variation, noise, within the experimental system. A major source of noise in field studies comes from the natural heterogeneity of soil properties which create micro-treatments throughout the field. To make matters worse, the variation within different soil properties is often non-randomly distributed across a field. We explore this challenge through a sorghum field trial dataset with accompanying plant, microbiome and soil property data. Diverse sorghum genotypes and two watering regimes were applied in a split-plot design. We describe a process of identifying, estimating, and controlling for the effects of spatially distributed soil properties on plant traits and microbial communities using minimal degrees of freedom. Importantly, this process provides a tool with which sources of environmental variation in field data can be identified and removed, improving our ability to resolve effects of interest and to quantify subtle phenotypes. IMPORTANCEData from field experiments are notoriously noisy. Proper field designs with high replication aid in mitigating this challenge, yet true biological correlations are still often masked by environmental variability. This work identifies soil property composition as a spatially distributed source of variance to three types of characteristics: plant phenotype, microbiome composition, and leaf traits. We show that once identified, spatial principal component regression was able to account for these effects so that more precise estimates of experimental factors were obtained. This generalizable method is applicable to diverse field experiments.

systems biology↗

Early metabolic priming under differing carbon sufficiency conditions influences peach fruit quality development

Crop load management is an important preharvest factor to balance yield, quality, and maturation in peach. However, few studies have addressed how preharvest factors impact metabolism on fruit of equal maturity. An experiment was conducted to understand how carbon competition impacts fruit internal quality and metabolism in Cresthaven peach trees by imposing distinct thinning severities. Fruit quality was evaluated at three developmental stages (S2, S3, S4), while controlling for equal maturity using non-destructive near-infrared spectroscopy. Non-targeted metabolite profiling was used to characterize fruit at each developmental stage from trees that were unthinned (carbon starvation) or thinned (carbon sufficiency). Carbon sufficiency resulted in significantly higher fruit dry matter content and soluble solids concentration at harvest when compared to the carbon starved, underscoring the true impact of carbon manipulation on fruit quality. Significant differences in the fruit metabolome between treatments were observed at S2 when phenotypes were similar, while less differences were observed at S4 when the carbon sufficient fruit exhibited a superior phenotype. This suggests a potential metabolic priming effect on fruit quality when carbon is sufficiently supplied during early fruit growth and development. In particular, elevated levels of catechin may suggest a link between secondary/primary metabolism and fruit quality development. HighlightAn investigation of variable carbon supply conditions in peach fruit reveals that early metabolic priming is associated with quality development

plant biology↗