ABSTRACT
Root hairs are considered important for rhizosphere formation, which affects root system functioning. Through interactions with soil microorganisms mediated by root exudation, root hairs may affect the phenotypes and growth of young plants. We tested this hypothesis by integrating results from two experiments: (1) a factorial greenhouse seedling experiment with Zea mays B73-wt and its root-hairless mutant, B73-rth3, grown in live and autoclaved soil, quantifying 15 phenotypic traits, seven growth rates, and soil microbiomes and (2) a semi-hydroponic system quantifying root exudation of maize genotypes. Possibly as compensation for lacking root hairs, B73-rth3 seedlings allocated more biomass to roots and grew slower than B73-wt seedlings in live soil, whereas B73-wt seedlings grew slowest in autoclaved soil, suggesting root hairs can be costly and their benefits were realized with more complete soil microbial assemblages. There were substantial differences in root exudation between genotypes and in rhizosphere versus non-rhizosphere microbiomes. The microbial taxa enriched in the presence of root hairs generally enhanced growth compared to taxa enriched in their absence. Our findings suggest the root hairs' adaptive value extends to plant-microbe interactions mediated by root exudates, affecting plant phenotypes, and ultimately, growth.
Subject(s)
Microbiota , Soil , Seedlings , Zea mays , Plant Roots , Rhizosphere , Soil MicrobiologyABSTRACT
Plant genotype is recognized to contribute to variations in microbial community structure in the rhizosphere, soil adherent to roots. However, the extent to which the viral community varies has remained poorly understood and has the potential to contribute to variation in soil microbial communities. Here we cultivated replicates of two Zea mays genotypes, parviglumis and B73, in a greenhouse and harvested the rhizobiome (rhizoplane and rhizosphere) to identify the abundance of cells and viruses as well as rhizobiome microbial and viral community using 16S rRNA gene amplicon sequencing and genome resolved metagenomics. Our results demonstrated that viruses exceeded microbial abundance in the rhizobiome of parviglumis and B73 with a significant variation in both the microbial and viral community between the two genotypes. Of the viral contigs identified only 4.5% (n = 7) of total viral contigs were shared between the two genotypes, demonstrating that plants even at the level of genotype can significantly alter the surrounding soil viral community. An auxiliary metabolic gene associated with glycoside hydrolase (GH5) degradation was identified in one viral metagenome-assembled genome (vOTU) identified in the B73 rhizobiome infecting Propionibacteriaceae (Actinobacteriota) further demonstrating the viral contribution in metabolic potential for carbohydrate degradation and carbon cycling in the rhizosphere. This variation demonstrates the potential of plant genotype to contribute to microbial and viral heterogeneity in soil systems and harbors genes capable of contributing to carbon cycling in the rhizosphere.
ABSTRACT
Plants influence the abiotic and biotic environment of the rhizosphere, affecting plant performance through plant-soil feedback (PSF). We compared the strength of nutrient and microbe-mediated PSF and its implications for plant performance in domesticated and wild grasses with a fully crossed greenhouse PSF experiment using four inbred maize genotypes (Zea mays ssp. mays b58, B73-wt, B73-rth3, and HP301), teosinte (Z. mays ssp. parviglumis), and two wild prairie grasses (Andropogon gerardii and Tripsacum dactyloides) to condition soils for three feedback species (maize B73-wt, teosinte, Andropogon gerardii). We found evidence of negative PSF based on growth, phenotypic traits, and foliar nutrient concentrations for maize B73-wt, which grew slower in maize-conditioned soil than prairie grass-conditioned soil. In contrast, teosinte and A. gerardii showed few consistent feedback responses. Both rhizobiome and nutrient-mediated mechanisms were implicated in PSF. Based on 16S rRNA gene amplicon sequencing, the rhizosphere bacterial community composition differed significantly after conditioning by prairie grass and maize plants, and the final soil nutrients were significantly influenced by conditioning, more so than by the feedback plants. These results suggest PSF-mediated soil domestication in agricultural settings can develop quickly and reduce crop productivity mediated by PSF involving changes to both the soil rhizobiomes and nutrient availability.
ABSTRACT
Species concepts have long provided a source of debate among biologists. These lively debates have been important for reaching consensus on how to communicate across scientific disciplines and for advancing innovative strategies to study evolution, population biology, ecology, natural history, and disease epidemiology. Species concepts are also important for evaluating variability and diversity among communities, understanding biogeographical distributions, and identifying causal agents of disease across animal and plant hosts. While there have been many attempts to address the concept of species in the fungi, there are several concepts that have made taxonomic delimitation especially challenging. In this review we discuss these major challenges and describe methodological approaches that show promise for resolving ambiguity in fungal taxonomy by improving discrimination of genetic and functional traits. We highlight the relevance of eco-evolutionary theory used in conjunction with integrative taxonomy approaches to improve the understanding of interactions between environment, ecology, and evolution that give rise to distinct species boundaries. Beyond recent advances in genomic and phenomic methods, bioinformatics tools and modeling approaches enable researchers to test hypothesis and expand our knowledge of fungal biodiversity. Looking to the future, the pairing of integrative taxonomy approaches with multi-locus genomic sequencing and phenomic techniques, such as transcriptomics and proteomics, holds great potential to resolve many unknowns in fungal taxonomic classification.
