Genome-informed trophic classification and functional characterization of virulence proteins from the maize tar spot pathogen Phyllachora maydis.

Phyllachora maydis is an ascomycete foliar fungal pathogen and the causal agent of tar spot in maize. Though P. maydis is considered an economically important foliar pathogens of maize, our general knowledge of the trophic lifestyle and functional role of effector proteins from this fungal pathogen remains limited. Here, we utilized a genome-informed approach to predict the trophic lifestyle of P. maydis and functionally characterized a subset of candidate effectors from this fungal pathogen. Leveraging the most recent P. maydis genome annotation and the CATAStrophy pipeline, we show this fungal pathogen encodes a predicted Carbohydrate-active enzymes (CAZymes) repertoire consistent with that of biotrophs. To investigate fungal pathogenicity, we selected 18 candidate effector proteins that were previously shown to be expressed during primary disease development. We assessed whether these putative effectors share predicted structural similarity with other characterized fungal effectors and determined whether any suppress plant immune responses. Using AlphaFold2 and Foldseek, we showed one candidate effector, PM02_g1115, adopts a predicted protein structure similar to that of an effector from Verticillium dahlia. Furthermore, transient expression of candidate effector-fluorescent protein fusions in Nicotiana benthamiana revealed two putative effectors, PM02_g378 and PM02_g2610, accumulated predominantly in the cytosol, and three candidate effectors, PM02_g1115, PM02_g7882, and PM02_g8240 consistently attenuated chitin-mediated reactive oxygen species production. Collectively, these results presented herein provide insights into the predicted trophic lifestyle and putative functions of effectors from P. maydis and will likely stimulate continued research to elucidate the molecular mechanisms used by P. maydis to induce tar spot.

Uncovering the Infection Strategy of Phyllachora maydis during Maize Colonization: A Comprehensive Analysis.

Tar spot, a disease caused by the ascomycete fungal pathogen Phyllachora maydis, is considered one of the most significant yield-limiting diseases of maize (Zea mays L.) within the United States. P. maydis may also be found in association with other fungi, forming a disease complex which is thought to result in the characteristic fish eye lesions. Understanding how P. maydis colonizes maize leaf cells is essential for developing effective disease control strategies. Here, we used histological approaches to elucidate how P. maydis infects and multiplies within susceptible maize leaves. We collected tar spot-infected maize leaf samples from four different fields in northern Indiana at three different time points during the growing season. Samples were chemically fixed and paraffin-embedded for high-resolution light and scanning electron microscopy. We observed a consistent pattern of disease progression in independent leaf samples collected across different geographical regions. Each stroma contained a central pycnidium that produced asexual spores. Perithecia with sexual spores developed in the stomatal chambers adjacent to the pycnidium, and a cap of spores formed over the stroma. P. maydis reproductive structures formed around but not within the vasculature. We observed P. maydis associated with two additional fungi, one of which is likely a member of the Paraphaeosphaeria genus; the other is an unknown fungi. Our data provide fundamental insights into how this pathogen colonizes and spreads within maize leaves. This knowledge can inform new approaches to managing tar spot, which could help mitigate the significant economic losses caused by this disease.

Image-based plant wilting estimation.

BACKGROUND: Environmental stress due to climate or pathogens is a major threat to modern agriculture. Plant genetic resistance to these stresses is one way to develop more resilient crops, but accurately quantifying plant phenotypic responses can be challenging. Here we develop and test a set of metrics to quantify plant wilting, which can occur in response to abiotic stress such as heat or drought, or in response to biotic stress caused by pathogenic microbes. These metrics can be useful in genomic studies to identify genes and genomic regions underlying plant resistance to a given stress. RESULTS: We use two datasets: one of tomatoes inoculated with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease, and another of soybeans exposed to water stress. For both tomato and soybean, the metrics predict the visual wilting score provided by human experts. Specific to the tomato dataset, we demonstrate that our metrics can capture the genetic difference of bacterium wilt resistance among resistant and susceptible tomato genotypes. In soybean, we show that our metrics can capture the effect of water stress. CONCLUSION: Our proposed RGB image-based wilting metrics can be useful for identifying plant wilting caused by diverse stresses in different plant species.

The NIN-LIKE PROTEIN 7 transcription factor modulates auxin pathways to regulate root cap development in Arabidopsis.

The root cap is a small tissue located at the tip of the root with critical functions for root growth. Present in nearly all vascular plants, the root cap protects the root meristem, influences soil penetration, and perceives and transmits environmental signals that are critical for root branching patterns. To perform these functions, the root cap must remain relatively stable in size and must integrate endogenous developmental pathways with environmental signals, yet the mechanism is not clear. We previously showed that low pH conditions altered root cap development, and these changes are mediated by the NIN LIKE PROTEIN 7 (NLP7) transcription factor, a master regulator of nitrate signaling. Here we show that in Arabidopsis NLP7 integrates nitrate signaling with auxin pathways to regulate root cap development. We found that low nitrate conditions promote aberrant release of root cap cells. Nitrate deficiency impacts auxin pathways in the last layer of the root cap, and this is mediated in part by NLP7. Mutations in NLP7 abolish the auxin minimum in the last layer of the root cap and alter root cap expression of the auxin carriers PIN-LIKES 3 (PILS3) and PIN-FORMED 7 (PIN7) as well as transcription factors that regulate PIN expression. Together, our data reveal NLP7 as a link between endogenous auxin pathways and nitrate signaling in the root cap.

Image-based assessment of plant disease progression identifies new genetic loci for resistance to Ralstonia solanacearum in tomato.

A major challenge in global crop production is mitigating yield loss due to plant diseases. One of the best strategies to control these losses is through breeding for disease resistance. One barrier to the identification of resistance genes is the quantification of disease severity, which is typically based on the determination of a subjective score by a human observer. We hypothesized that image-based, non-destructive measurements of plant morphology over an extended period after pathogen infection would capture subtle quantitative differences between genotypes, and thus enable identification of new disease resistance loci. To test this, we inoculated a genetically diverse biparental mapping population of tomato (Solanum lycopersicum) with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease. We acquired over 40 000 time-series images of disease progression in this population, and developed an image analysis pipeline providing a suite of 10 traits to quantify bacterial wilt disease based on plant shape and size. Quantitative trait locus (QTL) analyses using image-based phenotyping for single and multi-traits identified QTLs that were both unique and shared compared with those identified by human assessment of wilting, and could detect QTLs earlier than human assessment. Expanding the phenotypic space of disease with image-based, non-destructive phenotyping both allowed earlier detection and identified new genetic components of resistance.

Getting to the root of Ralstonia invasion.

Plant diseases caused by soilborne pathogens are a major limiting factor in crop production. Bacterial wilt disease, caused by soilborne bacteria in the Ralstonia solanacearum Species Complex (Ralstonia), results in significant crop loss throughout the world. Ralstonia invades root systems and colonizes plant xylem, changing plant physiology and ultimately causing plant wilting in susceptible varieties. Elucidating how Ralstonia invades and colonizes plants is central to developing strategies for crop protection. Here we review Ralstonia pathogenesis from root detection and attachment, early root colonization, xylem invasion and subsequent wilting. We focus primarily on studies in tomato from the last 5-10 years. Recent work has identified elegant mechanisms Ralstonia uses to adapt to the plant xylem, and has discovered new genes that function in Ralstonia fitness in planta. A picture is emerging of an amazingly versatile pathogen that uses multiple strategies to make its surrounding environment more hospitable and can adapt to new environments.

Tomato deploys defence and growth simultaneously to resist bacterial wilt disease.

Plant disease limits crop production, and host genetic resistance is a major means of control. Plant pathogenic Ralstonia causes bacterial wilt disease and is best controlled with resistant varieties. Tomato wilt resistance is multigenic, yet the mechanisms of resistance remain largely unknown. We combined metaRNAseq analysis and functional experiments to identify core Ralstonia-responsive genes and the corresponding biological mechanisms in wilt-resistant and wilt-susceptible tomatoes. While trade-offs between growth and defence are common in plants, wilt-resistant plants activated both defence responses and growth processes. Measurements of innate immunity and growth, including reactive oxygen species production and root system growth, respectively, validated that resistant plants executed defence-related processes at the same time they increased root growth. In contrast, in wilt-susceptible plants roots senesced and root surface area declined following Ralstonia inoculation. Wilt-resistant plants repressed genes predicted to negatively regulate water stress tolerance, while susceptible plants repressed genes predicted to promote water stress tolerance. Our results suggest that wilt-resistant plants can simultaneously promote growth and defence by investing in resources that act in both processes. Infected susceptible plants activate defences, but fail to grow and so succumb to Ralstonia, likely because they cannot tolerate the water stress induced by vascular wilt.

Candidate Effector Proteins from the Maize Tar Spot Pathogen Phyllachora maydis Localize to Diverse Plant Cell Compartments.

Most fungal pathogens secrete effector proteins into host cells to modulate their immune responses, thereby promoting pathogenesis and fungal growth. One such fungal pathogen is the ascomycete Phyllachora maydis, which causes tar spot disease on leaves of maize (Zea mays). Sequencing of the P. maydis genome revealed 462 putatively secreted proteins, of which 40 contain expected effector-like sequence characteristics. However, the subcellular compartments targeted by P. maydis effector candidate (PmEC) proteins remain unknown, and it will be important to prioritize them for further functional characterization. To test the hypothesis that PmECs target diverse subcellular compartments, cellular locations of super yellow fluorescent protein-tagged PmEC proteins were identified using a Nicotiana benthamiana-based heterologous expression system. Immunoblot analyses showed that most of the PmEC-fluorescent protein fusions accumulated protein in N. benthamiana, indicating that the candidate effectors could be expressed in dicot leaf cells. Laser-scanning confocal microscopy of N. benthamiana epidermal cells revealed that most of the P. maydis putative effectors localized to the nucleus and cytosol. One candidate effector, PmEC01597, localized to multiple subcellular compartments including the nucleus, nucleolus, and plasma membrane, whereas an additional putative effector, PmEC03792, preferentially labelled both the nucleus and nucleolus. Intriguingly, one candidate effector, PmEC04573, consistently localized to the stroma of chloroplasts as well as stroma-containing tubules (stromules). Collectively, these data suggest that effector candidate proteins from P. maydis target diverse cellular organelles and could thus provide valuable insights into their putative functions, as well as host processes potentially manipulated by this fungal pathogen.

A Straightforward High-Throughput Aboveground Phenotyping Platform for Small- to Medium-Sized Plants.

High-throughput phenotyping platforms for growth chamber and greenhouse-grown plants enable nondestructive, automated measurements of plant traits including shape, aboveground architecture, length, and biomass over time. However, to establish these platforms, many of these methods require expensive equipment or phenotyping expertise. Here we present a relatively inexpensive and simple phenotyping method for imaging hundreds of small- to medium-sized growth chamber or greenhouse-grown plants with a digital camera. Using this method, we image hundreds of tomato plants in 1 day.

In vitro functional characterization predicts the impact of bacterial root endophytes on plant growth.

Utilizing beneficial microbes for crop improvement is one strategy to achieve sustainable agriculture. However, identifying microbial isolates that promote crop growth is challenging, in part because using bacterial taxonomy to predict an isolate's effect on plant growth may not be reliable. The overall aim of this work was to determine whether in vitro functional traits of bacteria were predictive of their in planta impact. We isolated 183 bacterial endophytes from field-grown roots of two tomato species, Solanum lycopersicum and S. pimpinellifolium. Sixty isolates were screened for six in vitro functional traits: auxin production, siderophore production, phosphate solubilization, antagonism to a soilborne pathogen, and the presence of two antimicrobial metabolite synthesis genes. Hierarchical clustering of the isolates based on the in vitro functional traits identified several groups of isolates sharing similar traits. We called these groups 'functional groups'. To understand how in vitro functional traits of bacteria relate to their impact on plants, we inoculated three isolates from each of the functional groups on tomato seedlings. Isolates within the same functional group promoted plant growth at similar levels, regardless of their host origin or taxonomy. Together, our results demonstrate the importance of examining root endophyte functions for improving crop production.

Trehalose increases tomato drought tolerance, induces defenses, and increases resistance to bacterial wilt disease.

Ralstonia solanacearum causes bacterial wilt disease, leading to severe crop losses. Xylem sap from R. solanacearum-infected tomato is enriched in the disaccharide trehalose. Water-stressed plants also accumulate trehalose, which increases drought tolerance via abscisic acid (ABA) signaling. Because R. solanacearum-infected plants suffer reduced water flow, we hypothesized that bacterial wilt physiologically mimics drought stress, which trehalose could mitigate. We found that R. solanacearum-infected plants differentially expressed drought-associated genes, including those involved in ABA and trehalose metabolism, and had more ABA in xylem sap. Consistent with this, treating tomato roots with ABA reduced both stomatal conductance and stem colonization by R. solanacearum. Treating roots with trehalose increased xylem sap ABA and reduced plant water use by lowering stomatal conductance and temporarily improving water use efficiency. Trehalose treatment also upregulated expression of salicylic acid (SA)-dependent tomato defense genes; increased xylem sap levels of SA and other antimicrobial compounds; and increased bacterial wilt resistance of SA-insensitive NahG tomato plants. Additionally, trehalose treatment increased xylem concentrations of jasmonic acid and related oxylipins. Finally, trehalose-treated plants were substantially more resistant to bacterial wilt disease. Together, these data show that exogenous trehalose reduced both water stress and bacterial wilt disease and triggered systemic disease resistance, possibly through a Damage Associated Molecular Pattern (DAMP) response pathway. This suite of responses revealed unexpected linkages between plant responses to biotic and abiotic stress and suggested that R. solanacearum-infected plants increase trehalose to improve water use efficiency and increase wilt disease resistance. The pathogen may degrade trehalose to counter these efforts. Together, these results suggest that treating tomatoes with exogenous trehalose could be a practical strategy for bacterial wilt management.

4D Structural root architecture modeling from digital twins by X-Ray Computed Tomography.

BACKGROUND: Breakthrough imaging technologies may challenge the plant phenotyping bottleneck regarding marker-assisted breeding and genetic mapping. In this context, X-Ray CT (computed tomography) technology can accurately obtain the digital twin of root system architecture (RSA) but computational methods to quantify RSA traits and analyze their changes over time are limited. RSA traits extremely affect agricultural productivity. We develop a spatial-temporal root architectural modeling method based on 4D data from X-ray CT. This novel approach is optimized for high-throughput phenotyping considering the cost-effective time to process the data and the accuracy and robustness of the results. Significant root architectural traits, including root elongation rate, number, length, growth angle, height, diameter, branching map, and volume of axial and lateral roots are extracted from the model based on the digital twin. Our pipeline is divided into two major steps: (i) first, we compute the curve-skeleton based on a constrained Laplacian smoothing algorithm. This skeletal structure determines the registration of the roots over time; (ii) subsequently, the RSA is robustly modeled by a cylindrical fitting to spatially quantify several traits. The experiment was carried out at the Ag Alumni Seed Phenotyping Facility (AAPF) from Purdue University in West Lafayette (IN, USA). RESULTS: Roots from three samples of tomato plants at two different times and three samples of corn plants at three different times were scanned. Regarding the first step, the PCA analysis of the skeleton is able to accurately and robustly register temporal roots. From the second step, several traits were computed. Two of them were accurately validated using the root digital twin as a ground truth against the cylindrical model: number of branches (RRMSE better than 9%) and volume, reaching a coefficient of determination (R2) of 0.84 and a P < 0.001. CONCLUSIONS: The experimental results support the viability of the developed methodology, being able to provide scalability to a comprehensive analysis in order to perform high throughput root phenotyping.

Ralstonia solanacearum Effectors Localize to Diverse Organelles in Solanum Hosts.

Phytopathogenic bacteria secrete type III effector (T3E) proteins directly into host plant cells. T3Es can interact with plant proteins and frequently manipulate plant host physiological or developmental processes. The proper subcellular localization of T3Es is critical for their ability to interact with plant targets, and knowledge of T3E localization can be informative for studies of effector function. Here we investigated the subcellular localization of 19 T3Es from the phytopathogenic bacteria Ralstonia pseudosolanacearum and Ralstonia solanacearum. Approximately 45% of effectors in our library localize to both the plant cell periphery and the nucleus, 15% exclusively to the cell periphery, 15% exclusively to the nucleus, and 25% to other organelles, including tonoplasts and peroxisomes. Using tomato hairy roots, we show that T3E localization is similar in both leaves and roots and is not impacted by Solanum species. We find that in silico prediction programs are frequently inaccurate, highlighting the value of in planta localization experiments. Our data suggest that Ralstonia targets a wide diversity of cellular organelles and provides a foundation for developing testable hypotheses about Ralstonia effector function.

Shedding the Last Layer: Mechanisms of Root Cap Cell Release.

The root cap, a small tissue at the tip of the root, protects the root from environmental stress and functions in gravity perception. To perform its functions, the position and size of the root cap remains stable throughout root growth. This occurs due to constant root cap cell turnover, in which the last layer of the root cap is released, and new root cap cells are produced. Cells in the last root cap layer are known as border cells or border-like cells, and have important functions in root protection against bacterial and fungal pathogens. Despite the importance of root cap cell release to root health and plant growth, the mechanisms regulating this phenomenon are not well understood. Recent work identified several factors including transcription factors, auxin, and small peptides with roles in the production and release of root cap cells. Here, we review the involvement of the known players in root cap cell release, compare the release of border-like cells and border cells, and discuss the importance of root cap cell release to root health and survival.

Novel Imaging Modalities Shedding Light on Plant Biology: Start Small and Grow Big.

The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometricand physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale.

A Scanning Electron Microscopy Technique for Viewing Plant-Microbe Interactions at Tissue and Cell-Type Resolution.

Observing pathogen colonization and localization within specific plant tissues is a critical component of plant pathology research. High-resolution imaging, in which the researcher can clearly view the plant pathogen interacting with a specific plant cell, is needed to enhance our understanding of pathogen lifestyle and virulence mechanisms. However, it can be challenging to find the pathogen along the plant surface or in a specific cell type. Because of the time-consuming and expensive nature of high-resolution microscopy, techniques that allow a researcher to find a region of pathogen colonization more quickly at low resolution and subsequently move to a high-resolution microscope for detailed observation are needed. Here we present paraffin scanning electron microscopy (PSEM), a technique in which paraffin-embedded samples are first sectioned to identify a region of interest. Subsequently the same block is recut, deparaffinized, and used in scanning electron microscopy (SEM) to generate high-resolution images of plant-pathogen interactions in specific plant cell types. This method has several additional advantages over traditional SEM techniques, including reduced noise and better image quality. Here we use this technique to show that Fusarium oxysporum f. sp. lycopersici colonization is restricted in resistant Solanum pimpinellifolium and that PSEM works well in additional pathosystems, including maize leaves and Clavibacter michiganensis subsp. nebraskensis and Arabidopsis leaves and Pseudomonas syringae.

A role for the gibberellin pathway in biochar-mediated growth promotion.

Biochar is a carbon negative soil amendment that can promote crop growth. However, the effects of biochar on different plant species and cultivars within a species are not well understood, nor is the underlying basis of biochar-mediated plant growth promotion. This knowledge is critical for optimal use of biochar and for breeding biochar-responsive plants. Here, we investigated the genotype-specific effects of biochar on two cultivars of Solanum lycopersicum (tomato), and two wild relatives of tomato, Solanum pimpinellifolium, and Solanum pennelli, in two types of biochar. Biochar promoted shoot growth in all genotypes independent of biochar type but had genotype-dependent effects on other plant traits. Germination tests, exogenous GA4 application and mutant analysis indicated a role for GA in biochar-mediated plant growth promotion. Together, our results suggest that biochar promotes growth partially through stimulation of the GA pathway.

Further insights into the role of NIN-LIKE PROTEIN 7 (NLP7) in root cap cell release.

The root cap protects the root from environmental stress and senses gravity. Cells of the last layer of the root cap are shed in a developmentally programmed process. We previously showed that the transcription factor NIN-LIKE PROTEIN7 (NLP7) regulates root cap cell release likely through regulation of CELLULASE5 (CEL5). Here we provide a supplement to that work. We hypothesized that the nlp7 mutant has defects in additional root cap functions. We find that neither gravity sensing nor expression of a root cap cell identity marker is altered in nlp7 but that expression of another cellulase, CEL3, is upregulated. We conclude that NLP7 control of root cap cell release is largely independent of gravity sensing and root cap cell identity.

Whole Root Transcriptomic Analysis Suggests a Role for Auxin Pathways in Resistance to Ralstonia solanacearum in Tomato.

The soilborne pathogen Ralstonia solanacearum is the causal agent of bacterial wilt and causes significant crop loss in the Solanaceae family. The pathogen first infects roots, which are a critical source of resistance in tomato (Solanum lycopersicum L.). Roots of both resistant and susceptible plants are colonized by the pathogen, yet rootstocks can provide significant levels of resistance. Currently, mechanisms of this 'root-mediated resistance' remain largely unknown. To identify the molecular basis of this resistance, we analyzed the genome-wide transcriptional response of roots of resistant 'Hawaii 7996' and susceptible 'West Virginia 700' (WV) tomatoes at multiple timepoints after inoculation with R. solanacearum. We found that defense pathways in roots of the resistant Hawaii 7996 are activated earlier and more strongly than roots of susceptible WV. Further, auxin signaling and transport pathways are suppressed in roots of the resistant variety. Functional analysis of an auxin transport mutant in tomato revealed a role for auxin pathways in bacterial wilt. Together, our results suggest that roots mediate resistance to R. solanacearum through genome-wide transcriptomic changes that result in strong activation of defense genes and alteration of auxin pathways.

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences.

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.