Disentangling the genetic basis of rhizosphere microbiome assembly in tomato

Microbiomes play a pivotal role in plant growth and health, but the genetic factors involved in microbiome assembly remain largely elusive. Here, 16S amplicon and metagenomic features of the rhizosphere microbiome were mapped as quantitative traits of a recombinant inbred line population of a cross between wild and domesticated tomato. Gene content analysis of prioritized tomato QTLs suggested a genetic basis for differential recruitment of various rhizobacterial lineages, including a Streptomyces-associated 6.31-Mbp region harboring tomato domestication sweeps and encoding, among others, the iron regulator FIT and the aquaporin SlTIP2.3. Within metagenome-assembled genomes of the rhizobacterial lineages Streptomyces and Cellvibrio, we identified microbial genes involved in metabolism of plant polysaccharides, iron, sulfur, trehalose, and vitamins, whose genetic variation associated with either modern or wild tomato QTLs. Integrating 'microbiomics' and quantitative plant genetics pinpointed putative plant and reciprocal microbial traits underlying microbiome assembly, thereby providing the first step towards plant-microbiome breeding programs.

Biosolid-Amended Soil Enhances Defense Responses in Tomato Based on Metagenomic Profile and Expression of Pathogenesis-Related Genes

Biosolid application is an effective strategy, alternative to synthetic chemicals, for enhancing plant growth and performance and improving soil properties. In previous research, biosolid application has shown promising results with respect to tomato resistance against Fusarium oxysporum f. sp. radicis-lycopersici (Forl). Herein, we aimed at elucidating the effect of biosolid application on the plant–microbiome response mechanisms for tomato resistance against Forl at a molecular level. More specifically, plant–microbiome interactions in the presence of biosolid application and the biocontrol mechanism against Forl in tomato were investigated. We examined whether biosolids application in vitro could act as an inhibitor of growth and sporulation of Forl. The effect of biosolid application on the biocontrol of Forl was investigated based on the enhanced plant resistance, measured as expression of pathogen-response genes, and pathogen suppression in the context of soil microbiome diversity, abundance, and predicted functions. The expression of the pathogen-response genes was variably induced in tomato plants in different time points between 12 and 72 h post inoculation in the biosolid-enriched treatments, in the presence or absence of pathogens, indicating activation of defense responses in the plant. This further suggests that biosolid application resulted in a successful priming of tomato plants inducing resistance mechanisms against Forl. Our results have also demonstrated that biosolid application alters microbial diversity and the predicted soil functioning, along with the relative abundance of specific phyla and classes, as a proxy for disease suppression. Overall, the use of biosolid as a sustainable soil amendment had positive effects not only on plant health and protection, but also on growth of non-pathogenic antagonistic microorganisms against Forl in the tomato rhizosphere and thus, on plant–soil microbiome interactions, toward biocontrol of Forl.

An ancient antimicrobial protein co-opted by a fungal plant pathogen for in planta mycobiome manipulation

Microbes typically secrete a plethora of molecules to promote niche colonization. Soil-dwelling microbes are well-known producers of antimicrobials that are exploited to outcompete microbial coinhabitants. Also, plant pathogenic microbes secrete a diversity of molecules into their environment for niche establishment. Upon plant colonization, microbial pathogens secrete so-called effector proteins that promote disease development. While such effectors are typically considered to exclusively act through direct host manipulation, we recently reported that the soil-borne, fungal, xylem-colonizing vascular wilt pathogen Verticillium dahliae exploits effector proteins with antibacterial properties to promote host colonization through the manipulation of beneficial host microbiota. Since fungal evolution preceded land plant evolution, we now speculate that a subset of the pathogen effectors involved in host microbiota manipulation evolved from ancient antimicrobial proteins of terrestrial fungal ancestors that served in microbial competition prior to the evolution of plant pathogenicity. Here, we show that V. dahliae has co-opted an ancient antimicrobial protein as effector, named VdAMP3, for mycobiome manipulation in planta. We show that VdAMP3 is specifically expressed to ward off fungal niche competitors during resting structure formation in senescing mesophyll tissues. Our findings indicate that effector-mediated microbiome manipulation by plant pathogenic microbes extends beyond bacteria and also concerns eukaryotic members of the plant microbiome. Finally, we demonstrate that fungal pathogens can exploit plant microbiome-manipulating effectors in a life stage–specific manner and that a subset of these effectors has evolved from ancient antimicrobial proteins of fungal ancestors that likely originally functioned in manipulation of terrestrial biota.

Glutamic acid reshapes the plant microbiota to protect plants against pathogens

Background Plants in nature interact with other species, among which are mutualistic microorganisms that affect plant health. The co-existence of microbial symbionts with the host contributes to host fitness in a natural context. In turn, the composition of the plant microbiota responds to the environment and the state of the host, raising the possibility that it can be engineered to benefit the plant. However, technology for engineering the structure of the plant microbiome is not yet available. Results The loss of diversity and reduction in population density of Streptomyces globisporus SP6C4, a core microbe, was observed coincident with the aging of strawberry plants. Here, we show that glutamic acid reshapes the plant microbial community and enriches populations of Streptomyces, a functional core microbe in the strawberry anthosphere. Similarly, in the tomato rhizosphere, treatment with glutamic acid increased the population sizes of Streptomyces as well as those of Bacillaceae and Burkholderiaceae. At the same time, diseases caused by species of Botrytis and Fusarium were significantly reduced in both habitats. We suggest that glutamic acid directly modulates the composition of the microbiome community. Conclusions Much is known about the structure of plant-associated microbial communities, but less is understood about how the community composition and complexity are controlled. Our results demonstrate that the intrinsic level of glutamic acid in planta is associated with the composition of the microbiota, which can be modulated by an external supply of a biostimulant.

Advances in understanding modes of action of microbial bioprotectants

Plant-associated microorganisms are involved in important functions related to growth, performance and health of their hosts. Understanding their modes of action is important for the development and application of microbial bioprotectants and biostimulants. Recent studies have revealed manifold plant-microbe as well as pathogen-microbe interactions, which form the basis of understanding beneficial effects of plant-associated microorganisms. Microbiome research has contributed to our understanding of the modes of action of various plant-associated microorganisms. This chapter summarizes current knowledge about beneficial plant-microbe interactions, discusses recent insights into the functioning of the plant microbiome and beneficial plant-microbe networks. It shows that the use of microorganisms and the exploitation of beneficial plant–microbe interactions offer promising and environmentally-friendly strategies to achieve sustainable agriculture on a global scale.

Multiple Facets of Plant-Microbiome Associations in Unlocking the Communication Paradigm through Extracellular Vesicles. s

: Communication among different species across kingdoms occurs through a chain of regulatory molecules that are transferred around cellular boundaries. These molecules are also crucial for defense, virulence and pathogenesis. In the past, the transport of proteins in long distance communication was observed, but in the present era, the discovery of extracellular vesicles (EVs) has changed our understanding of molecular communication. EVs are not only involved in cell signaling and immunity, but also can transfer information by sRNAs, forming a basis for interactions among a wide variety of organisms. Despite extensive research on EVs in other areas, their role in communication between plants and the plant microbiome has been lacking. EVs are potentially involved in protein trafficking along with transport of lipids and nucleic acids. Interactions between hosts and their microbiomes may also be mediated by EVs, which can be involved in stress responses, immune surveillance and defense, virulence and signaling along with many metabolic activities within plant microbiomes. In this review, we have focused on recent information about the role of EVs and the molecules they transport between hosts and microbes. The connection between biofilms and the generation of EVs is also considered. These findings enhance our knowledge about plant-microbiome interactions in terms of immunity and virulence and challenge the conventional viewpoint of inter-kingdom signaling.

Application of Deep Learning in Plant–Microbiota Association Analysis

Unraveling the association between microbiome and plant phenotype can illustrate the effect of microbiome on host and then guide the agriculture management. Adequate identification of species and appropriate choice of models are two challenges in microbiome data analysis. Computational models of microbiome data could help in association analysis between the microbiome and plant host. The deep learning methods have been widely used to learn the microbiome data due to their powerful strength of handling the complex, sparse, noisy, and high-dimensional data. Here, we review the analytic strategies in the microbiome data analysis and describe the applications of deep learning models for plant–microbiome correlation studies. We also introduce the application cases of different models in plant–microbiome correlation analysis and discuss how to adapt the models on the critical steps in data processing. From the aspect of data processing manner, model structure, and operating principle, most deep learning models are suitable for the plant microbiome data analysis. The ability of feature representation and pattern recognition is the advantage of deep learning methods in modeling and interpretation for association analysis. Based on published computational experiments, the convolutional neural network and graph neural networks could be recommended for plant microbiome analysis.