Month: March 2023

The Arabidopsis CLE gene was found to be induced by N deficiency, and over expression of CLE inhibits lateral root elongation but not initiation. The peptide sequence of CLE is homologous to CLV3, which binds to CLV1 and the clv1 mutant showed increased lateral root length under low N conditions. The transcript levels of CLE were increased in the clv1 mutant, suggesting a feedback regulation of CLE by CLV1. Transgenic lines with increased CLE levels in clv1 did not inhibit lateral root growth, indicating that the inhibition of CLE3 on lateral root development requires CLV1. Altogether, the N responsive CLE CLV1 peptide receptor signaling module restricts expansion of the lateral root system in N deficient environments. Although nitrate is a crucial nutrient and signaling molecule, its distribution in soils is heterogeneous. To adapt the prevailing nitrate conditions, plants have evolved a systemic response mechanism. NRT2.1 was the first molecular target identified in long distance signaling reflecting root responses to environmental nitrate conditions. Plants were grown using a 1 mM NO3 − solution, then the root was split into two parts, one subjected to N free treatment and the other one treated with 1 mM NO3 −. Both 15NO3 − influx and the transcript level of NRT2.1 were increased in the NO3 − fed root. Recent findings revealed that the C terminally encoded peptide originated from N starved roots; located in xylem vessels, it sends root derived ascending signals to the shoot before being recognized by a leucine rich repeat receptor kinase, CEP Receptor 1 , and then inducing the expression of CEPD polypeptides. CEPD sent long distance mobile signals translocated to each root and upregulated the expression of NRT2.1. The activity and expression of NRT2.1 in plants were inhibited when supplied with high N. Lepetit’s lab configured a forward genetic approach using a transgenic line expressing the pNRT2.1::LUC construct as a reporter gene. The mutant hni9, showing increased expression of NRT2.1 under high N supply,vertical growing systems was isolated and the mutation was found in IWS1, a component of the RNAPII complexes.

Further investigation revealed that the levels of the H3K27me3 on NRT2.1 chromatin decreased, resulting in the upregulated expression of NRT2.1 in response to high N supply in the iws1 mutants. Thus IWS1 is likely to be involved in the transduction of N systemic signals through controlling the expression of NRT2.1 in plants. Another important player participating in root foraging, TCP20, was identified by Crawford’s lab using the yeast one hybrid system to screen the transcription factors that can bind to the fragment of nitrate enhance DNA. TCP20 was found to be able to bind to the promoters of NIA1, NRT1.1, and NRT2.1. The tcp20 mutants exhibited deficiencies in preferential lateral root growth on heterogeneous media in split root experiments, indicating that TCP20 can regulate the preferential growth of lateral roots in high nitrate zones, thus playing an important role in the systemic signaling pathway. Recently, using an electrophoretic mobility shift assay , the DNA binding sites of TCP20 in a 109 bp NIA1 enhancer fragment were found to be in close proximity to NLP7 and NLP6 binding sites. Yeast two hybrid and bimolecular fluorescence complementation assays showed that NLP7 and NLP6 can interact with TCP20 and both the PB1 domains of NLP6&7 and the glutamine rich domain of TCP20 are necessary for protein–protein interaction. Further work will be needed to elucidate the underlying molecular mechanism explaining the involvement of TCP20 in systemic signaling.Root microbiota associate with every land plant and show community compositions and dynamics that are distinct from the surrounding soil microbial community . Both rhizosphere and root endosphere microbiomes affect plant health and soil health via processes such as mineral and nutrient turnover and pathogen suppression . Attribution of specific processes to distinct microbial players or populations is challenging because soil ecosystems are among the most complex environments on Earth . Soils are made up of a multitude of heterogeneous abiotic and biotic components that interact in a dynamic fashion over a range of spatial and temporal scales .

Soil type, together with climatic characteristics, allows for the development and activity of biological constituents that are specific to a given soil in a particular location and can vary dramatically among soils and locations . Those biological constituents can include plants, insects, bacteria, archaea, and fungi, which all contribute to and feed off of the bio geochemical cycles in a given soil. The resulting complex network of interactions is extremely challenging to disentangle due to technological limitations and insufficient information in biological and chemical reference databases . Furthermore, soils contain a vast diversity of microorganisms, which are heterogeneously distributed and engage in frequent horizontal gene transfer. Despite this, most root microbiome studies present data from single time points or single locations and primarily conduct amplicon sequencing combined with limited information on plant or environment. Although the average values provided by such studies may suggest some interactions or mechanisms, few studies follow up with the comprehensive sampling necessary to definitively understand these mechanisms and interactions. In addition, single point studies are difficult to compare or extrapolate to other environments or plants because measured values can vary dramatically over time . Soil and other environmental characteristics can be important indicators of biogeochemical processes that have occurred in the past or are ongoing. Generally, few root and soil microbiome studies take advantage of the relatively inexpensive techniques to measure soil characteristics. Data on parameters such as pH, volumetric water content, temperature, and salt concentration could allow researchers to draw correlations between microbial activity, plant productivity, and environmental parameters and facilitate opportunities to cross reference studies conducted under comparable conditions.

In the last decade, the root microbiome research community has made tremendous progress in understanding the complexity of soil ecosystems through improvements in experimental methods at both laboratory and field scales.This review summarizes recent technological advancements and the resulting research opportunities categorized by ecosystem component and scale ,outdoor vertical plant stands and ends with an outlook and potential applications for phytobiome research.Microbial colonization of the root and rhizosphere can significantly affect root phenology and metabolism. Roots demonstrate enormous phenotypic plasticity with respect to anatomy, shape, cell type, cellular structure, metabolism, and biochemical composition, and these characteristics contribute tremendously to root exudation variation and, as a result, to microbial community differentiation . These reciprocal interactions between roots and microbes are not well understood but their direct link showcases the fact that, for understanding root microbiomes, a foundational understanding of root biology is required. Although hyperspectral imaging of leaves has been broadly applied to monitor plant health, even simple imaging of intact roots has lagged behind due to the challenges presented by the opaqueness of soil . Ideally, imaging of root architecture, microbes, and chemical composition as well as visualization of fluxes such as carbon flow through plant compartments and into the soil would be conducted at multiple temporal and spatial scales. Most current methods for analyzing root growth either require artificial growing conditions , are severely restricted in the fraction of roots detectable , or are destructive . For example, many root phenotypic datasets have employed coring or “shovelomics”, subsequent root picking and washing, and imaging using light imagers such as the RhizoVision Crown platform . This method provides valuable information about root architecture; however, it is extremely laborious, it is often not feasible to excavate deep roots, it can remain unknown how much of the root system was recovered and scanned, and root excavation often times terminates the experiment for the selected plants. All of these methods are severely limited because they are destructive, low throughput, or artificial. The later point is particularly important because root architecture can be significantly affected by plant genetics, environmental conditions, soil type, and root colonizing bacteria and fungi . Magnetic resonance imaging presents a noninvasive modality that addresses some of the limitations of other root measurement techniques. When coupled with an analysis pipeline in an automated system, MRI can monitor root mass, length, diameter, tip number, growth angles , and spatial distribution in a high throughput manner . Similarly, X ray computed tomography scanning can provide a comprehensive picture of root systems as long as the roots have a diameter larger than the instruments’ resolution . Hence, small plants or young roots are not likely to be resolved well. Another limitation common to both MRI and CT technology is that plants must be grown in pots that fit into the imaging machines and the applicability of MRI and X ray CT in three dimensional imaging of root systems across various pot sizes was recently evaluated . Although both MRI and CT were able to resolve high quality 3D images of root systems in vivo, the reconstructed length and image details differed significantly between the two methods. In small pots, CT outperformed MRI and provided more details thanks to higher resolution whereas, in large pots, MRI was able to display root systems more comprehensively than CT.

Soil features such as minerals and burrows can be resolved with CT, while MRI can measure water content in roots and soil. Both CT and MRI, struggled with roots thinner than 400 mm .Using Synchrotron X ray microtomography, Milien et al. contrasted the 3D images of vascular systems of successful and unsuccessful graft interfaces in vine rootstocks. Others have applied synchrotron X ray microtomography to visualize drought induced embolism in various plant species , to correlate root hair with rhizosphere soil structure formation , and to quantify root induced changes of rhizosphere physical properties . Although synchrotron X ray micro CT can render unprecedented detail into the microanatomy of plants and microorganisms, the focus window is relatively limited and biological samples tend to lose viability as a result of the intense X ray radiation. There are various other imaging methods that have been recently developed or applied to phytobiome research, including super resolution confocal imaging, which can enhance 3D mapping of root and microbial or fungal cells and showcase green fluorescent proteins , and correlative confocal and focused ion beam tool with integrated scanning electron microscope, which allows for extremely fine scaled 3D mapping . When applied individually or in combination, the above mentioned imaging methods will provide opportunities to visualize plant tissue and attached or internally residing bacteria, fungi, and viruses at unprecedented resolution, as well provide information about their physical and chemical context. Because root development is vital for plant health, expansion of root image databases and novel correlations between above and below ground plant features will enhance our understanding of plant response to environmental and biological stimuli.An important goal of the plant microbiome field is to discover beneficial or deleterious effects of microbes. This means that recording and understanding plant phenotypes and linking them to microbiome variation is key. Similarly, plant microbiomes are intimately tied to the background soil; hence, monitoring soil characteristics is important but can be challenging and labor intensive at appropriate temporal or spatial scales.Unmanned aerial vehicles equipped with RGB cameras, infrared cameras, multi spectral and hyperspectral cameras, GPS, navigation systems, programmable controllers, and automated flight planning have emerged as powerful tools for nondestructive, high throughput field phenotyping that can be performed throughout the growth season . This has removed a bottleneck in phenotyping but automated processing of this data still presents various challenges, which are discussed elsewhere . Monitoring of agricultural fields using drones has become popular among researchers to more accurately plan and manage their experimental operations. Drones can produce precise maps of soil characteristics and plant characteristics , as well as determine irrigation needs, nitrogen levels, and pest occurrence . RGB, IR, and hyper as well as multi spectral cameras attached to drones can collect images of the above ground portion in a range of wavelengths. The resulting data can produce, for example, a vegetation index describing the amount of wavelengths of light emitted from a crop and, hence, can trigger irrigation systems or evaluate the sensitivity of crop breeds to soil moisture in a high throughput manner . Image data can also provide information about plant health status over time and in dependence on the field location and, thereby, allows the employment of an early warning and response system to plant disease or stress .

Rhizobiomes are influenced by their spatial orientation towards roots in two ways. First, the radial proximity of microbial communities to roots defines community complexity and composition, as described in recent publications, and as outlined by the two step model ofmicrobial root colonization mentioned above. Second, the lateral position of microbes along a root shapes the community, as exemplified by early studies. Importantly, recent microbiome studies take into consideration the former, but not the latter aspect. In this section, we discuss specific microbial associations with various root regions, and the role of spatially distinct root exudation. Root tips are the first tissues that make contact with bulk soil: root tips are associated with the highest numbers of active bacteria compared with other root tissues, and likely select microbes in an active manner. The root elongation zone is specifically colonized by Bacillus subtilis, which suggests a particular role of this zone in plant–microbe interactions.Their community includes decomposers, which could be involved in the degradation of dead cells shedding from old root parts. Similarly, lateral roots are associated with distinct microbial communities, differing between tips and bases, as well as between different types of lateral root. One trait influencing the differential microbial colonization of root tissues could be the differential exudation profiles of the distinct root parts. This is illustrated in the following example. Clusterroots are densely packed lateral roots formed by some plants growing on extremely nutrient poor soils; these roots exude high amounts of organic acids and,nft vertical farming in some cases, protons, to solubilize phosphate.

The low pH and carboxylate rich rhizosphere of cluster roots is associated with a specialized rhizobiome, dominated by Burkholderia species that metabolize citrate and oxalate. Besides organic acids, mature cluster roots also exude isoflavonoids and fungal cell wall degrading enzymes, leading to a decrease in bacterial abundance, as well as fungal sporulation. Taken together, cluster root exudates not only solubilize phosphate, but also regulate microbes in such a way that they do not interfere with phosphate uptake. Beyond this example, spatial patterns of metabolite exudation are largely unexplored.We hypothesize that such patterns exist in all root systems for the following reasons: spatially distinct organic acid exudation is atrait of all root systems ; spatially distinct exudation was similarly detected for strigolactones, amino acids, and sugars; and root nutrient uptake, which is sometimes coupled with proton transport, can also exhibit spatial patterns . Overall, spatially defined metabolite exudation by distinct root parts is likely an important factor in structuring the rhizobiome. Future studies should aim at characterizing spatially distinct rhizobiomes and their functional traits, and at investigating spatially distinct root exudation.Roottips are not only associated with high numbers of bacteria , but also produce border cells and mucilage , crucial for plant–microbe interactions. Depending on the root meristemorganization,border cells are released into the rhizosphere either as single cells or as border like cells .Residence time in the soil is different for the two types of border cell. Single maize border cells stayed alive in soil for months, likely due to the presence of starch deposits, whereas arabidopsis border like cells survived for only 2 weeks. Border cells have a transcriptional profile distinct from root tip wells, with overall lower primary and higher secondary metabolism. ABCtransporters constitute a large fraction of differentially expressed genes, which is consistent with transport of secondary metabolites. Secondary metabolites are likely central to the role of border cells in defense against pathogens.

Pathogen attack can result not only in higher border cell production and release, but also in higher mucilage production by border cells and root tip cells. Mucilage contains proteins with antimicrobial functions, as well as extracellular DNA involved in defense against fungi and certain bacteria. Importantly, mucilage is also produced under nonpathogenic conditions, serving as a lubricant for the root environment and stabilizing soil particles. Interestingly, mucilage also provides distinct carbon sources for microbes, thus influencing rhizobiome composition. Border cells similarly interact with nonpathogenic microbes : they release flavonoids that attract rhizobia, uncharacterized compounds that induce branching of mycorrhizal hyphae, and arabinogalactans that trigger biofilm formation of specific beneficial bacteria. The full extent of how border cells and mucilage shape root–microbe interactions remains unclear. It is tempting to speculate that the specialized metabolism of the border cells results in a distinct exudation profile of not only proteins and mucilage, but also low molecular weight compounds that could serve as microbial nutrients or as signaling compounds. Further research should focus on the genetic and physiological differences between border cells and border like cells, as well as on the transport proteins involved in exudation of low molecular weight compounds, DNA, and proteins.Plant–microbe interactions are not only defined by plant root morphology and plant derived exudates, but also by microbe–microbe interactions . Thus, we focus further here on microbial communities. Specififcally, we discuss: how plant exudates influence microbial diversity; how plant responsive microbes are identified; how microbes interact and how mycorrhizal fungi influence root–bacteria interactions. The rhizosphere serves as carbon rich niche for the establishment of microbial communities, in contrast to bulk soil, which is rapidly depleted in carbon and other nutrients by heterotrophic microbes.

Given that the ability of microbes to metabolize plant derived exometabolites might determine their success in the microbial community, several studies have investigated whether the diversity of plant exudates correlates with microbial diversity. Some studies found higher plant diversity was associated with higher microbial diversity, and that the addition of a diverse exudate mix to plant monocultures increased microbial diversity. Interestingly, isolates from soils with a diverse plant community consistently exhibited less narrow niches and displayed less resource competition than did isolates from low plant diversity environments. Although on a global scale, environmental factors had a larger impact on microbial diversity than did plant diversity, we can conclude that, on a local scale, high plant diversity likely promotes a diverse microbial community.The large diversity of microbial communities is a current challenge for plant–microbe research, because it is impractical to study questions such as how members of a community interact, and what specific traits a microbial community has. Therefore,indoor vertical farming many studies currently aim at identifying the subset of microbes responsive to plants. Strikingly, only 7% of bulk soil microbes increased in abundance in the rhizosphere compared with bulk soil, which reduces the number of taxa to investigate from thousands to hundreds. Other approaches to identifying plant responsive microbes have focused on transcriptional profiling. Compared with soil abundant microbes, plant associated microbes exhibited distinct transcriptional responses to plant exudates and, intriguingly, displayed distinct phylogenetic clustering. Network analyses further revealed that rhizosphere microbes displayed higher levels of interactions than did bulk soil microbes. These studies illustrate the potential for the identification of a distinct set of plant responsive microbes. The above points highlight how plants influence microbial communities. However, the members of microbial communities also interact with each other. Compellingly, it is still unclear whether microbe–microbe interactions are predominantly positive or negative. Network analyses reported predominantly positive intrakingdom interactions. By contrast, laboratory growth assays identified competition as the major factor in shaping isolate communities, and cooperation could only be detected for 6–10% of the isolates. One major difference between the two experimental approaches is that the former investigates a natural system, whereas the latter is based on the ability to culture microbes. Isolation of microbes introduces a bias, since it can select against cooperators, precluding obligate syntrophs. Further evidence that at least some microbes avoid competition was provided by co cultivation experiments.

Environmental isolates: displayed high substrate specialization; did not necessarily take up the compound with the highest energy; and diverged in substrate use when cultivated for several generations. In addition, some metabolites exuded by microbes could be metabolized by others, suggesting potential cross feeding between community members. The above findings suggest complex interactions of microbes. It remains to be resolved in which situation competition or cooperation dominates communities. However, it is evident that microbial interactions are based on altered gene expression. Microbes responded to competing bacteria or even close relatives by differentially regulating genes involved in metabolite exudation and transport processes, making the study of microbial transporters a compelling topic for future studies. Thus, metabolite uptake, release, and sensing are important factors in shaping microbial communities. Metabolite turnover in soil is influenced not only by plants, but also by functionally diverse bacteria, fungi, and animals. Plant–fungal and plant–animal interactions in the rhizosphere go beyond the scope of this review, and are discussed elsewhere. Here, we provide a few brief examples focusing on the impacts of mycorrhiza on rhizobiomes and exometabolite turnover. Endomycorrhizal fungi receive a significant fraction of the carbon fixed by plants . Interestingly, these fungi also exude sugars, shaping a distinct bacterial community. Likewise, Ectomycorrhiza receive carbon from plants, and form a dynamic bacterial community; they even participate in plant to plant carbon transport. The field of fungal microbiomes is nascent: if and how fungi control exudation, whether fungal microbiomes have beneficial functions, and how plant and fungal microbiomes influence each other are all unknowns. Although many questions remain, these recent findings already suggest that a holistic view of rhizosphere nutrient cycling and signaling exchange via exometabolites requires a whole community approach including all domains of life.Plant exudates shape microbial communities. Overall, plants exude up to 20% of fixed carbon and 15% of nitrogen, which includes an array of simple molecules, such as sugars, organic acids, and secondary metabolites, as well as complex polymers, such as mucilage . Although every plant produces exudates, the amount and composition of root exudates varies. First, exudation is defined by the genotype of the host, as observed in the distinct exudation patterns of 19 arabidopsis accessions. Strikingly, the amount of variation between the accessions depended on the metabolite class investigated. Glucosinolates displayed most, flavonoids medium, and phenylpropanoids low variability. Second, exudation changes with plant developmental stage: with increasing age, arabidopsis sugar exudation decreased, and amino acid and phenolic exudation increased. Third, exudation is modulated by abiotic stresses: the amounts of exuded amino acids, sugars, and organic acids changed in maize grown in phosphate , iron , nitrogen , or potassium deficient conditions. In addition, phosphate deficient arabidopsis plants increased coumarin and oligolignol exudation, heavy metal treated poplar induced organic acid exudation, and zinc deficient wheat increased phytosiderophore exudation. Differential exudation is a plausible mechanism by which plants could modulate their interaction with microbes, as exemplified by the correlation between exudation patterns and rhizobiome variation reported for eight arabidopsis accessions. Differential exudation modulated by transport proteins is discussed below.Plant derived exometabolites need to cross at least one membrane to transit from the cytoplasm of root cells into the rhizosphere. There is considerable discussion as to what degree plants are able to regulate this transport. In general, different modes of transport could be envisioned. First, small, hydrophilic compounds could diffuse from the root into the rhizosphere, driven by the large concentration gradient. Second, channel proteins could facilitate such diffusion. Third, active or secondary active transporters could shuttle compounds across membranes against a concentration gradient. Diffusion of compounds can only be relevant in young root tissue, which is still devoid of Casparian strips or suberized endodermis that both block apoplasmic flow in adult tissues. Transport proteins involved in exudation are mostly elusive. From a conceptual point of view, plasma membrane localized exporters likely have a direct, and vacuolar transporters an indirect effect on exudation. The vacuole is a major storage organelle for many metabolites detected in exudates, such as sugars, organic acids, and secondary metabolites. Alteration of vacuolar transporter levels impacts vacuolar and cytosolic concentrations and, thus, can influence metabolite exudation into the rhizosphere. The few characterized transporters involved in exudation are essential for the transport of specific compounds, and are presented in Table 1. Since only a few transporters involved in exudation have been characterized, we suggest additional families that might be involved in the process. To complete the picture of metabolite exchange between roots and soil, Table 1 additionally contains a few important plasma membrane localized metabolite uptake systems. Below, we discuss the evidence for transport processes involved in the import and exudation of compounds detected in root exudates, such as sugars, organic acids, and secondary metabolites.