Month: March 2023

Traditionally, measuring soil quality parameters requires destructive sampling and laboratory analyses that are laborious, slow, or expensive. Similarly, root phenotyping requires time and labor intensive processing and scanning of root tissue to collect data such as root length density and root architecture . Advances in imaging have been able to offset some of these hands on analyses: high resolution RGB imaging can differentiate between soil types facilitating soil type detection, which can improve mapping and hence conservation efforts . New approaches that overcome the limitations of laboratory tests include thermal infrared imaging, which can be used to assess soil moisture distribution and hydraulic properties and inform land surface models . Near infrared spectroscopy has been used for rapid and accurate identification of soil total nitrogen , organic matter , and pH levels in soil that can replace laboratory techniques . Similarly, hyperspectral imaging can be used to accurately provide TN, OM, and organic content information in various soils as well as fungal viability based on pixel spectra specific to browned, damaged, and undamaged tissue types . Because image processing of HSI is more challenging than that of RGB imaging, the two technologies can be used in tandem; for example, to optimize comprehensive analyses of soil and root systems in rhizoboxes . The accuracy of both IR and HSI can be improved by applying extreme learning machine models, which were previously used to increase the accuracy of soil moisture and surface temperature measurements . Because UAVs are scalable and programmable,vertical plant rack we expect that drone usage in phytobiome research will move toward autonomous UAV fleets that can monitor extensive fields with an array of cheaper and more accurate sensors.

We also expect aerial monitoring to be more closely coupled to robotics on the ground that could aid in conducting soil and plant analysis and deployment and maintenance of local sensor networks among various other tasks. Thus far, the development of robotics to measure soil characteristics has primarily focused on applications in environments that are difficult or unsafe to access. For instance, a robot was developed for measuring soil strength over depth, which is normally manually measured using a penetrometer, in unsafe zones . The Mars Phoenix Lander returned in situ measurements of Mars soil temperature, generated a topography map using imaging, and excavated soil samples for downstream testing .Plant microbiome signaling and metabolism rely on exchange of a large diversity of metabolites derived from microorganisms, plants, and the soil environment. Metabolomic methods enable direct characterization of these small molecules from soils and the various biological components. Given the large diversity of compounds that reside intra and extracellularly in these systems, mass spectrometry coupled to chromatography such as liquid chromatography MS and gas chromatography MS have become primary methods for chemical analysis. Both techniques are well suited for identification and quantification of a wide range of molecules found in biological and environmental samples by coupling the physical separation of the compounds using LC with the separation and analysis of ions using MS mass.GC MS typically has higher resolving power and produces richer fragmentation spectra, which makes it particularly well suited for identifying molecules such as small glycans that are often difficult to characterize by LC MS. It is also well suited for volatile molecules and poorly ionizing molecules that are often lost or not detected by LC MS.

LC MS, on the other hand, is better suited for thermally labile compounds and is a technique of choice for analysis of novel compounds. Typically, these approaches are suitable for identification of several hundreds of metabolites based on spectral databases and authentic standards . However, they are currently far from comprehensive, and improving metabolite identification is an important goal of metabolomics research. A number of studies have used MS based metabolomics to examine the chemical exchanges within phytobiomes; for example, the signaling molecules that direct the establishment of bacterial and mycorrhizal pathogens or symbionts with host plants. A number of metabolites have been identified, including sugars, amino acids, organic acids, phenolic compounds, and plant hormones, that are associated with beneficial interactions and are also implicated by single strain and whole community approaches . Exometabolite profiling methods have been used to examine root exudates and their function in recruiting soil bacteria . O’Banion et al. have reviewed the function of the main chemical constituents of plant microbe signaling. Similarly, chemical imaging of solutes in soils has been reviewed . Although MS imaging is a powerful and promising technique , it is extremely difficult to identify organic components from complex environmental samples due to chemical complexity of these samples and the lack of physical separation of compounds prior to ionization. New developments in using ion mobility to separate ions within mass spectrometers have tremendous potential to overcome these limitations and enable direct analysis of metabolites from tissues and environmental samples .It is well known that phytobiomes are affected by plant growth form and life history , plant community composition and habitat of origin, and even host plant species . In fact, there is growing evidence of that intraspecific variability of plant hosts produces variability in phytobiomes . Genetic differences within host species can affect microbe recruitment, community assembly, and, ultimately, the composition of phytobiomes.

As such, the phytobiome can be considered an extended phenotype of the plant that is determined by host genetics, the environment, and their complex interaction. Here, the standard tools of quantitative genetics can be used to study the phytobiome. For example, family experimental designs or kinship based mixed models can be used to partition variation in microbial abundance or composition into genetic and environmental components of variance for an entire assemblage of microbes associated with a particular plant compartment. This approach can provide insight into the host genetic architecture of the plant microbiome and, potentially, help to identify classes of microbes with close affinities for specific genotypes within a population. A number of recent publications have documented genetic variation within plant species for aspects of the microbiome, including providing estimates of heritability for overall microbial community diversity and richness and for the abundance of specific microbial taxa based on counts derived from amplicon sequencing,growing strawberries vertical system for example The majority of such studies have focused on crop plants in agronomic settings and little is known about the heritability of microbes from more natural populations; one exception to this is the outdoor study of Bergelson et al. . We imagine that some of these host genetic effects are related to available habitat for microbial establishment , to resources shared with microbes as root exudates, or from more complex immune responses in the plant. Incorporating host genetics in plant microbiome studies is promising because it will point to mechanisms leading to beneficial or deleterious plant–microbe interactions, as well as leverage the growing resources available in plant genomics. In order to more efficiently develop and deploy improved plant varieties, it is valuable to identify the causal genes or genetic markers underlying agronomic traits and disease resistance . In addition, there is a need to understand the plant genes that influence the composition and function of the microbiome to improve our understanding and in order to maximize plant productivity. Two methods are commonly used to identify genes or markers associated with quantitative traits: quantitative trait locus mapping and genome wide association studies . Both approaches rely on genome wide scans for statistical association between polymorphic genetic markers and quantitative variation in a measured phenotype. In the case of phytobiomes, the phenotype of interest could be a feature of the aggregate microbial community or an estimate of the relative abundance of a specific taxon . A key distinction between these methods is that QTL mapping populations are derived from lines crosses and, therefore, represent experimentally structured populations, whereas GWAS focus on naturally occurring individuals. QTL mapping tends to have more power to detect true associations but reduced ability to localize effects in the genome because of limited recombination in a breeding population. In contrast, GWAS are frequently under powered, given limited sample sizes, but can yield remarkably fine scaled localization due to extensive historical recombination.

It can also be much faster to establish a GWAS population than a QTL population because there is no need to create recombinant progeny through complex breeding designs across multiple generations. However, GWAS requires dense markers and reliable controls for population structure and, at best, yields correlative results rather than causal inference as achieved with QTLs. Because, in QTL studies, fewer alleles and markers are analyzed using a randomized genetic background, statistical analysis can yield causal relationships between alleles and traits . Although both GWAS and QTL analyses establishing relationships between plant genetics and phenotypic traits are common, links between plant genetics and microbiome composition and function have been rare. The earliest studies utilizing this approach focused on plant related microbial diseases , including fungal, oomycete, and bacterial pathogens. More recently, studies utilizing the model plant Arabidopsis thaliana have been published that explore complete microbial communities based on 16S rRNA gene amplicon sequencing. For example, Horton et al. identified host loci that influence fungal and bacterial colonization density on leaves across an A. thaliana population in the field and found that loci encoding defense and cell wall integrity affect bacterial and fungal community variation, whereas loci that influence the reproduction of viruses, trichome branching, and morphogenesis affect bacterial species richness. Similarly, Wallace et al. looked at the leaf microbial communities across maize lines and found that functions related to short chain carbon metabolism, secretion, and nitrotoluene degradation primarily encoded by Methylobacteria spp. are heritable metabolic traits, and that few plant loci were found to be significantly associated. These studies provide an exciting glimpse of the potential importance of host genetic variation in the phytobiome and give a clear path to the identification of candidate genes. Future studies will help to define the groups of microbes with strong host impacts, as well as identify new genetic and metabolic pathways important in plant– microbe interactions. Although aggregate community metrics may be relatively straightforward to generate, they may be difficult to interpret and less meaningful than studies focused on individual microbial species. However, it is also unclear how to best define microbial taxa for counting—what inference can be made from amplicon sequence variants, traditionally defined operational taxonomic units, or gene content abundance derived from enrichment or metagenomic analyses? Finally, genome wide studies carry a heavy multiple testing burden due to dense testing both across genomes and also across multiple taxa or phenotypes. Care will need to be taken to limit false positives and misleading inferences—methods developed for other “omics” based quantitative genetic systems such as expression or metabolic QTL analyses may provide helpful directions as the field matures.In an effort to conduct plant microbiome research across biologically meaningful spatiotemporal scales and with increased control, a range of fabricated ecosystems are being developed. Experimental control and complexity are inversely related in plant microbiome research. At the most extreme, controlled laboratory experiments are often binary , whereas field experiments feature real world complexity that is difficult to replicate year by year. A new generation of experimental platforms of increasing complexity now allows for multi factorial insight, reproducibility, and increased statistical power. The concept of controlled environments for exploring plant ecophysiology dates back to the late 1940s, when Firits Went developed a Phytotron at Caltech , a “Climatron” in St. Louis, MO , and an ecophysiology lab at the Desert Research Institute, University of Nevada, Reno, which is now home to the recently developed EcoCELLs . Went’s work inspired the development of the EcoTron program at Centre National de la Recherche Scientifique, Montpellier, France , and the EcoTron at Imperial College London, United Kingdom . EcoTrons are large, fabricated ecosystems that consist of an above ground dome of approximately 40 m3 and a below ground chamber that contains a lysimeter that can hold 2 to 12 tons of soil . The canopy area is up to 2 m tall and allows work under natural light as well as under controlled or artificial light conditions. Both above and below ground compartments are equipped with arrays of sensors and instrumentation for environmental control. Using the EcoTron, simulations of a wide range of environmental scenarios under realistic conditions can be performed, while measurements important for ecosystem processes such as atmospheric and soil gas composition, temperature, and pH, among others, can be conducted.

Sugars constitute a significant fraction of exudates, and are a main carbon source for microbes. Interestingly, many more sugar uptake than release systems have been described. Sugar Transport Proteins utilize high extracellular proton levels to import sugars, and mutation of STPs leads to higher external sugar levels. Sugars Will Eventually Be Exported Transporters are sugar uniporters, and all root expressed members localize to the vacuole. Due to an alteration of root sugar homeostasis, SWEET mutant plants exhibited higher sugar export from roots compared with wild type plants, and were more susceptible to disease. Intriguingly, no transporters directly exporting sugars into the rhizosphere have been characterized so far, and it is debated whether sugar exudation is a transport driven process at all. Potential evidence for passive sugar efflux was supported by the observation of higher sucrose concentrations around young, permeable root tissue than around older, less permeable root tissue. However, because sugars are synthesized in leaves, they still need to be unloaded either from phloem or from root cells to be exuded into the rhizosphere, a process likely depending on transporters due to the hydrophilic nature of sugars. A further indication of the presence of elusive transporters is the differential sugar exudation in various environments, as shown, for example, for maize grown in potassium , phosphate , or iron deficient conditions.Sugar alcohols are imported by secondary active proteins with broad substrate specificity , whereas the modes of export are enigmatic. Sugar phosphates are involved in intracellular carbohydrate metabolism,hydroponic vertical farming and plastid localized sugar–phosphate co transporters have been reported in several species.

Although sugar phosphates are detected in exudates, neither import nor export mechanisms are currently characterized.Amino acids are recognized by microbial chemoreceptors crucial for the early steps of root colonization, making amino acids an important fraction of exudates. Modulation of amino acid transport could be either a means of communication with microbes, or a response to microbial presence. Amino acid uptake is mediated by several transporter families with broad substrate specificity. Amino acid exudation is affected by several transporters expressed in vascular tissue: mutation of phloem localized UmamiTs resulted in lower amino acid exudation, whereas mutation of xylem localized Glutamine Dumpers caused increased exudation. Although no plasma membrane localized amino acid exporters have been characterized so far, several lines of evidence suggest their presence. First, higher tryptophan exudation from older root zones than younger parts suggests the involvement of transport proteins in exudation, due to the fully formed Casparian strips and thick cell walls in mature root parts interfering with diffusion. Second, concentration differences between amino acids in root exudates and root extracts are not the same for all the amino acids, suggesting the selective transport of at least some amino acids. Third, various transporter families exhibit bidirectional amino acid transport characteristics in heterologous systems , and could be involved in amino acid exudation.Organic acids constitute a large fraction of exudates, and are microbial nutrients. No importers have been characterized so far, but the release of malate and citrate by Aluminium Activated Malate Transporters and Multi drug and Toxic Compound Extrusion families are among the few well understood examples of transporters involved in exudation .

Activity of members of both families is often modulated by metal ions and microbes . Uncharacterized ALMT and MATE family members are primary candidates for exporters of other organic acids due to their similarity to already characterized members, their plasma membrane localization, and their function as proton antiporters.Nucleotides are imported by secondary active transporters, but their exudation remains elusive. It is well established that extracellular ATP has a signaling function, and ABC transporters were proposed to mediate cellular export. Peptide uptake is transporter mediated in heterologous systems, and a role of ABC transporters in peptide exudation has been suggested .Fatty acid transport is necessary for mycorrhizal symbiosis: mycorrhizal fungi depended on their hosts for the synthesis of certain fatty acids, and the current model includes transport of lipids by ABCG proteins in the symbiotic membrane. One ABCG member, STR, was previously shown to be required for mycorrhization. Interestingly, arabidopsis ABCG transporters were similarly shown to export fatty acids for cutin synthesis in above ground tissues . Lipid transport was required not only for symbiotic interactions, but also for pathogen colonization. Fatty acids are detected in root exudates , but the mode of lipid exudation into the rhizosphere has yet to be discovered. A role in lipid exudation could be envisioned for root expressed ABCG members .Secondary metabolites are ubiquitous in root exudates, and ABC transporters are likely candidates for specialized metabolite transport into the rhizosphere. A distinct exudation profile was described for seven ABC mutants, and one mutant line displayed an altered microbial community. Although the causal metabolites could not be identified, the authors noted transport of the same compound by various proteins, and possible broad substrate specificity for some transporters. In a later study, exudates of arabidopsis ABCG37/PDR9 mutant lines were found to be deficient in several phenylpropanoids.

Arabidopsis PDR9 was previously characterized as auxin precursor transporter, which suggests a broad substrate specificity for PDR9. Interestingly, a PDR9 homolog was highly expressed in cluster roots of white lupin devoid of phosphate, illustrating PDR9 involvement in response to various abiotic stresses. These studies illustrate the potential for the discovery of novel transporter functions in the ABC family, an excellent target for future studies investigating root exudation. In addition, MATE proteins transport secondary metabolites into the vacuole,vertical hydroponic garden and plasma membrane localized members could also be involved in secondary metabolite exudation. In summary, more transport proteins involved in metabolite import into roots than in export from roots have been reported so far . The characterization of additional transport families involved in exudation will enable the generation of mutant lines that are devoid of the exudation of specific metabolites. Such lines could be used to investigate the correlation of exudation profiles and microbial communities.Plant derived transporters and exometabolites are intrinsic to plant–mycorrhizal and rhizobial symbioses . We speculate that, although there is paucity of evidence, plants analogously select for a beneficial rhizobiome. Given that plants evolved in the presence of microbes, a subset of which benefits plant growth, we hypothesize that, over millennia, plant exudation via active transport processes evolved with the substrate specificity of plant associated bacteria. In Box 2, we discuss exudates and other steps involved in root microbiome assembly, analogously to the establishment of plant–mycorrhizal and rhizobial symbioses. However, intense future research is needed to reveal the precise mechanisms governing plant microbiome assembly, and the possible beneficial functions of the microbial community. The major mechanisms by which plants are thought to modulate microbial interactions currently include: modulation of their exudate profiles ; root morphology ; and regulation of immune system activities . In turn, mechanisms for successful rhizosphere colonization by soil microbes require that they: are metabolically active ; sense the plant ; move towards the root and successfully compete with other microbes for root niches . In addition, for successful colonization of the rhizoplane or root tissue, microbes must be able to attach to the surface or enter root tissue . Despite apparent parallels between plant microbiomes and the aforementioned symbioses, plant microbiomes have some specific characteristics. First, microbiomes are detected in all environmental conditions, whereas mycorrhizal and rhizobial symbioses are induced in specific circumstances. Second, microbiomes occur on various tissues, whereas rhizobia and mycorrhiza interface with roots only. Third, microbiomes comprise many members, whereas the aforementioned symbioses persist between two predominant partners. Fourth, although most members of the microbiome originate from the environment similar to rhizobia and mycorrhiza, there is evidence that some endophytes may be vertically transmitted via seeds.

Future research should focus on the factors involved in microbiome assembly, the relative contribution of epi and endophytes to microbiomes, and the signaling crosstalk between plants and microbial communities.Rhizobiome assembly and the involvement of the plant in this process are currently enigmatic. Here, we have discussed multiple factors shaping the rhizobiome, including host genotype and development, root morphology, border cells and mucilage, and root exudates. Root exudation is a dynamic process, likely dependent on a plethora or transporters that are mostly uncharacterized. Spatially defined exudation likely results in distinct microbial communities that are observed to be associated with specific root parts. The success of microbial colonization of the rhizosphere depends on several aspects, such as chemotaxis, substrate specificity, competitiveness, and cooperativeness. Furthermore, endophytes likely form biofilms on the root surface, and encounter the plant immune system. Although some factors shaping root microbiomes emerge, many open questions remain .Due to the chemical complexity of soil, exudation is traditionally analyzed in hydroponic culture, an environment distant from the more natural settings of plant microbiome studies. Furthermore, novel technologies enabling high throughput screening of putative transporters against possible substrates are needed to reveal the impact of the respective substrates on the rhizobiome and, in turn, on plant health. An increased understanding of root morphology, exudation, and involved transporters will likely enable the engineering or breeding of plants with altered abilities to interact with specific beneficial microbes or pathogens. This needs to be complemented with an improved understanding of the substrate preferences of plant associated microbes, their interactions, and the mechanisms through which they benefit the plant. A holistic understanding of the functions of a healthy plant rhizobiome would enable the directed design of customized microbial communities. With this, specific plants in a given environment could be tailored to a specific purpose, such as phytoremediation, stress resistance, altered plant development, or increased yield.Interactions between plants and microbes are an integral part of our terrestrial ecosystem. There are several types of plant microbe interactions: competition, commensalism, mutualism, and parasitism. The more common interactions are commensalism or mutualism, where either one or both species benefit from the relationship, respectively . There are several excellent reviews reporting current research on lifestyles and molecular interactions of plant associated bacteria , rhizosphere interactions , plant responses to bacterial quorum sensing signals , endophyte applications , and rhizosphere bacteria responses to transgenic plants . Examination of these interactions helps us to understand natural phenomena that affect our daily lives and could lead to applications resulting in sustainable resources, less impact on the environment, cleanup of pollution and influence on atmospheric gases on a global scale. Advantages of using these interactions for biotechnological applications are many fold. The use of naturally existing plant microbe symbiosis for plant growth and bio control reduces synthetic fertilizer and pesticide treatments leading to cost effectiveness and less impact by nutrients and pesticides on surrounding fauna and flora. The production of useful compounds with pharmaceutical and industrial relevance using plant bacteria symbiosis is energy efficient and diminishes the need to add expensive precursors and catalysts. Remediation through conventional method, such as excavate and treat, is expensive and labor intensive. Conversely, plantmicrobial remediation strategies can be less intrusive and much more economical .Carbon sequestration through plant rhizosphere processes is a potentially sustainable method to lowering atmospheric carbon . This review focuses on recent progress in the fields of plant growth promotion, plant disease control, production of bio active compounds and bio materials, remediation of contaminated sites, and carbon sequestration. The potential of applying these new developments are discussed. Figure 1 summarizes applications resulting from microbe shoot and microbe root interactions and techniques used. Table 1 is a glossary of the techniques mentioned in this review. Plant microbe interactions have been utilized to improve plant growth for the production of food, fiber, bio fuels and key metabolites. The mutualistic interaction can be beneficial in directly providing nutrients to the plant or increasing the availability of compounds such as iron or phosphate. Free living plant growth promoting bacteria also produce compounds that directly affect plant metabolism or modulate phytohormone production or degradation. The phytohormones: auxins, cytokinins, gibberellic acid , abscisic acid and ethylene are signaling molecules essential for growth which mediate a range of developmental processes in plants. Recent studies on each of these areas are presented in the following section. As chemical fertilizers are costly both to the agricultural businesses and the environment, development of biofertilizers is an important and exciting area.