Molecular, biochemical and metabolomics analyses reveal constitutive and pathogen-induced defense responses of two sugarcane contrasting genotypes against leaf scald disease.

Leaf scald caused by the bacteria Xanthomonas albilineans is one of the major concerns to sugarcane production. To breed for resistance, mechanisms underlying plant-pathogen interaction need deeper investigations. Herein, we evaluated sugarcane defense responses against X. albilineans using molecular and biochemical approaches to assess pathogen-triggered ROS, phytohormones and metabolomics in two contrasting sugarcane genotypes from 0.5 to 144 h post-inoculation (hpi). In addition, the infection process was monitored using TaqMan-based quantification of X. albilineans and the disease symptoms were evaluated in both genotypes after 15 d post-inoculation (dpi). The susceptible genotype presented a response to the infection at 0.5 hpi, accumulating defense-related metabolites such as phenolics and flavonoids with no significant defense responses thereafter, resulting in typical symptoms of leaf scald at 15 dpi. The resistant genotype did not respond to the infection at 0.5 hpi but constitutively presented higher levels of salicylic acid and of the same metabolites induced by the infection in the susceptible genotype. Moreover, two subsequent pathogen-induced metabolic responses at 12 and 144 hpi were observed only in the resistant genotype in terms of amino acids, quinic acids, coumarins, polyamines, flavonoids, phenolics and phenylpropanoids together with an increase of hydrogen peroxide, ROS-related genes expression, indole-3-acetic-acid and salicylic acid. Multilevel approaches revealed that constitutive chemical composition and metabolic reprogramming hampers the development of leaf scald at 48 and 72 hpi, reducing the disease symptoms in the resistant genotype at 15 dpi. Phenylpropanoid pathway is suggested as a strong candidate marker for breeding sugarcane resistant to leaf scald.

Mechanisms of Isothiocyanate Detoxification in Larvae of Two Belowground Herbivores, Delia radicum and D. floralis (Diptera: Anthomyiidae).

Like aboveground herbivores, belowground herbivores are confronted with multiple plant defense mechanisms including complex chemical cocktails in plant tissue. Roots and shoots of Brassicaceae plants contain the two-component glucosinolate (GSL)-myrosinase defense system. Upon cell damage, for example by herbivore feeding, toxic and pungent isothiocyanates (ITCs) can be formed. Several aboveground-feeding herbivores have developed biochemical adaptation strategies to overcome the GSL-ITC defenses of their host plant. Whether belowground herbivores feeding on Brassica roots possess similar mechanisms has received little attention. Here, we analyze how two related belowground specialist herbivores detoxify the GSL-ITC defenses of their host plants. The larvae of the fly species Delia radicum and D. floralis are common pests and specialized herbivores on the roots of Brassicaceae. We used chemical analyses (HPLC-MS/MS and HPLC-UV) to examine how the GSL-ITC defense system is metabolized by these congeneric larvae. In addition, we screened for candidate genes involved in the detoxification process using RNAseq and qPCR. The chemical analyses yielded glutathione conjugates and amines. This indicates that both species detoxify ITCs using potentially the general mercapturic acid pathway, which is also found in aboveground herbivores, and an ITC-specific hydrolytic pathway previously characterized in microbes. Performance assays confirmed that ITCs negatively affect the survival of both species, in spite of their known specialization to ITC-producing plants and tissues, whereas ITC breakdown products are less toxic. Interestingly, the RNAseq analyses showed that the two congeneric species activate different sets of genes upon ITC exposure, which was supported by qPCR data. Based on our findings, we conclude that these specialist larvae use combinations of general and compound-specific detoxification mechanisms with differing efficacies and substrate preferences. This indicates that combining detoxification mechanisms can be an evolutionarily successful strategy to handle plant defenses in herbivores.

A high-quality functional genome assembly of Delia radicum L. (Diptera: Anthomyiidae) annotated from egg to adult.

Belowground herbivores are overseen and underestimated, even though they can cause significant economic losses in agriculture. The cabbage root fly Delia radicum (Anthomyiidae) is a common pest in Brassica species, including agriculturally important crops, such as oilseed rape. The damage is caused by the larvae, which feed specifically on the taproots of Brassica plants until they pupate. The adults are aboveground-living generalists feeding on pollen and nectar. Female flies are attracted by chemical cues in Brassica plants for oviposition. An assembled and annotated genome can elucidate which genetic mechanisms underlie the adaptation of D. radicum to its host plants and their specific chemical defences, in particular isothiocyanates. Therefore, we assembled, annotated and analysed the D. radicum genome using a combination of different next-generation sequencing and bioinformatic approaches. We assembled a chromosome-level D. radicum genome using PacBio and Hi-C Illumina sequence data. Combining Canu and 3D-DNA genome assembler, we constructed a 1.3 Gbp genome with an N50 of 242 Mbp and 6 pseudo-chromosomes. To annotate the assembled D. radicum genome, we combined homology-, transcriptome- and ab initio-prediction approaches. In total, we annotated 13,618 genes that were predicted by at least two approaches. We analysed egg, larval, pupal and adult transcriptomes in relation to life-stage specific molecular functions. This high-quality annotated genome of D. radicum is a first step to understanding the genetic mechanisms underlying host plant adaptation. As such, it will be an important resource to find novel and sustainable approaches to reduce crop losses to these pests.

IQ67 DOMAIN proteins facilitate preprophase band formation and division-plane orientation.

Spatiotemporal control of cell division is essential for the growth and development of multicellular organisms. In plant cells, proper cell plate insertion during cytokinesis relies on the premitotic establishment of the division plane at the cell cortex. Two plant-specific cytoskeleton arrays, the preprophase band (PPB) and the phragmoplast, play important roles in division-plane orientation and cell plate formation, respectively1. Microtubule organization and dynamics and their communication with membranes at the cortex and cell plate are coordinated by multiple, mostly distinct microtubule-associated proteins2. How division-plane selection and establishment are linked, however, is still unknown. Here, we report members of the Arabidopsis IQ67 DOMAIN (IQD) family3 as microtubule-targeted proteins that localize to the PPB and phragmoplast and additionally reside at the cell plate and a polarized cortical region including the cortical division zone (CDZ). IQDs physically interact with PHRAGMOPLAST ORIENTING KINESIN (POK) proteins4,5 and PLECKSTRIN HOMOLOGY GTPase ACTIVATING (PHGAP) proteins6, which are core components of the CDZ1. The loss of IQD function impairs PPB formation and affects CDZ recruitment of POKs and PHGAPs, resulting in division-plane positioning defects. We propose that IQDs act as cellular scaffolds that facilitate PPB formation and CDZ set-up during symmetric cell division.

User-friendly assessment of pavement cell shape features with PaCeQuant: Novel functions and tools.

Leaf epidermis pavement cells develop complex jigsaw puzzle-like shapes in many plant species, including the model plant Arabidopsis thaliana. Due to their complex morphology, pavement cells have become a popular model system to study shape formation and coordination of growth in the context of mechanically coupled cells at the tissue level. To facilitate robust assessment and analysis of pavement cell shape characteristics in a high-throughput fashion, we have developed PaCeQuant and a collection of supplemental tools. The ImageJ-based MiToBo plugin PaCeQuant supports fully automatic segmentation of cell contours from microscopy images and the extraction of 28 shape features for each detected cell. These features now also include the Largest Empty Circle criterion as a proxy for mechanical stress. In addition, PaCeQuant provides a set of eight features for individual lobes, including the categorization as type I and type II lobes at two- and three-cell junctions, respectively. The segmentation and feature extraction results of PaCeQuant depend on the quality of input images. To allow for corrections in case of local segmentation errors, the LabelImageEditor is provided for user-friendly manual postprocessing of segmentation results. For statistical analysis and visualization, PaCeQuant is supplemented with the R package PaCeQuantAna, which provides statistical analysis functions and supports the generation of publication-ready plots in ready-to-use R workflows. In addition, we recently released the FeatureColorMapper tool which overlays feature values over cell regions for user-friendly visual exploration of selected features in a set of analyzed cells.

Slug Feeding Triggers Dynamic Metabolomic and Transcriptomic Responses Leading to Induced Resistance in Solanum dulcamara.

Induced plant responses to insect herbivores are well studied, but we know very little about responses to gastropod feeding. We aim to identify the temporal dynamics of signaling- and defense-related plant responses after slug feeding in relation to induced resistance. We exposed Solanum dulcamara plants to feeding by the gray field slug (GFS; Deroceras reticulatum) for different periods and tested disks of local and systemic leaves in preference assays. Induced responses were analyzed using metabolomics and transcriptomics. GFS feeding induced local and systemic responses. Slug feeding for 72 h more strongly affected the plant metabolome than 24 h feeding. It increased the levels of a glycoalkaloid (solasonine), phenolamides, anthocyanins, and trypsin protease inhibitors as well as polyphenol oxidase activity. Phytohormone and transcriptome analyses revealed that jasmonic acid, abscisic acid and salicylic acid signaling were activated. GFS feeding upregulated more genes than that it downregulated. The response directly after feeding was more than five times higher than after an additional 24 h without feeding. Our research showed that GFS, like most chewing insects, triggers anti-herbivore defenses by activating defense signaling pathways, resulting in increased resistance to further slug feeding. Slug herbivory may therefore impact other herbivores in the community.

Morphological Analysis of Leaf Epidermis Pavement Cells with PaCeQuant.

Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.

A Mobile Auxin Signal Connects Temperature Sensing in Cotyledons with Growth Responses in Hypocotyls.

Plants have a remarkable capacity to adjust their growth and development to elevated ambient temperatures. Increased elongation growth of roots, hypocotyls, and petioles in warm temperatures are hallmarks of seedling thermomorphogenesis. In the last decade, significant progress has been made to identify the molecular signaling components regulating these growth responses. Increased ambient temperature utilizes diverse components of the light sensing and signal transduction network to trigger growth adjustments. However, it remains unknown whether temperature sensing and responses are universal processes that occur uniformly in all plant organs. Alternatively, temperature sensing may be confined to specific tissues or organs, which would require a systemic signal that mediates responses in distal parts of the plant. Here, we show that Arabidopsis (Arabidopsis thaliana) seedlings show organ-specific transcriptome responses to elevated temperatures and that thermomorphogenesis involves both autonomous and organ-interdependent temperature sensing and signaling. Seedling roots can sense and respond to temperature in a shoot-independent manner, whereas shoot temperature responses require both local and systemic processes. The induction of cell elongation in hypocotyls requires temperature sensing in cotyledons, followed by the generation of a mobile auxin signal. Subsequently, auxin travels to the hypocotyl, where it triggers local brassinosteroid-induced cell elongation in seedling stems, which depends upon a distinct, permissive temperature sensor in the hypocotyl.

Microtubule-associated protein IQ67 DOMAIN5 regulates morphogenesis of leaf pavement cells in Arabidopsis thaliana.

Plant microtubules form a highly dynamic intracellular network with important roles for regulating cell division, cell proliferation, and cell morphology. Their organization and dynamics are co-ordinated by various microtubule-associated proteins (MAPs) that integrate environmental and developmental stimuli to fine-tune and adjust cytoskeletal arrays. IQ67 DOMAIN (IQD) proteins recently emerged as a class of plant-specific MAPs with largely unknown functions. Here, using a reverse genetics approach, we characterize Arabidopsis IQD5 in terms of its expression domains, subcellular localization, and biological functions. We show that IQD5 is expressed mostly in vegetative tissues, where it localizes to cortical microtubule arrays. Our phenotypic analysis of iqd5 loss-of-function lines reveals functions of IQD5 in pavement cell (PC) shape morphogenesis. Histochemical analysis of cell wall composition further suggests reduced rates of cellulose deposition in anticlinal cell walls, which correlate with reduced anisotropic expansion. Lastly, we demonstrate IQD5-dependent recruitment of calmodulin calcium sensors to cortical microtubule arrays and provide first evidence for important roles for calcium in regulation of PC morphogenesis. Our work identifies IQD5 as a novel player in PC shape regulation and, for the first time, links calcium signaling to developmental processes that regulate anisotropic growth in PCs.

Gastropods and Insects Prefer Different Solanum dulcamara Chemotypes.

Solanum dulcamara (Bittersweet nightshade) shows significant intraspecific variation in glycoalkaloid (GA) composition and concentration. We previously showed that constitutive differences in overall GA levels are correlated with feeding preference of the grey field slug (GFS; Deroceras reticulatum). One particularly preferred accession, ZD11, contained low GA levels, but high levels of previously unknown structurally related uronic acid conjugated compounds (UACs). Here we test whether different slug species as well as insect herbivores show similar feeding preferences among six S. dulcamara accessions with different GA chemotypes. In addition, we investigate whether slug feeding can lead to induced changes in the chemical composition and affect later arriving herbivores. A leaf disc assay using greenhouse-grown plants showed that three slug species similarly preferred accessions with low GA levels. Untargeted metabolomic analyses showed that previous slug feeding consistently increased the levels of N-caffeoyl-putrescine and a structurally related metabolite, but not the levels of GAs and UACs. Slug-induced responses only affected slug preference in one accession. A common garden experiment using the same six accessions revealed that ZD11 received the highest natural gastropod feeding damage, but suffered the lowest damage by specialist flea beetles. The latter preferred to feed on accessions with high GA levels. Our study indicates that different selection pressures imposed by generalist gastropods and specialist insects may explain part of the observed chemical diversity in S. dulcamara.

Interactive Responses of Solanum Dulcamara to Drought and Insect Feeding are Herbivore Species-Specific.

In nature, plants are frequently subjected to multiple biotic and abiotic stresses, resulting in a convergence of adaptive responses. We hypothesised that hormonal signalling regulating defences to different herbivores may interact with drought responses, causing distinct resistance phenotypes. To test this, we studied the hormonal and transcriptomic responses of Solanum dulcamara subjected to drought and herbivory by the generalist Spodoptera exigua (beet armyworm; BAW) or the specialist Leptinotarsa decemlineata (Colorado potato beetle; CPB). Bioassays showed that the performance of BAW, but not CPB, decreased on plants under drought compared to controls. While drought did not alter BAW-induced hormonal responses, it enhanced the CPB-induced accumulation of jasmonic acid and salicylic acid (SA), and suppressed ethylene (ET) emission. Microarray analyses showed that under drought, BAW herbivory enhanced several herbivore-induced responses, including cell-wall remodelling and the metabolism of carbohydrates, lipids, and secondary metabolites. In contrast, CPB herbivory enhanced several photosynthesis-related and pathogen responses in drought-stressed plants. This may divert resources away from defence production and increase leaf nutritive value. In conclusion, while BAW suffers from the drought-enhanced defences, CPB may benefit from the effects of enhanced SA and reduced ET signalling. This suggests that the fine-tuned interaction between the plant and its specialist herbivore is sustained under drought.

Current Challenges in Plant Eco-Metabolomics.

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant⁻organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology.

PaCeQuant: A Tool for High-Throughput Quantification of Pavement Cell Shape Characteristics.

Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitative analysis of PC shape characteristics that can easily be applied to study PC development in large data sets.

Ambient temperature and genotype differentially affect developmental and phenotypic plasticity in Arabidopsis thaliana.

BACKGROUND: Global increase in ambient temperatures constitute a significant challenge to wild and cultivated plant species. Forward genetic analyses of individual temperature-responsive traits have resulted in the identification of several signaling and response components. However, a comprehensive knowledge about temperature sensitivity of different developmental stages and the contribution of natural variation is still scarce and fragmented at best. RESULTS: Here, we systematically analyze thermomorphogenesis throughout a complete life cycle in ten natural Arabidopsis thaliana accessions grown under long day conditions in four different temperatures ranging from 16 to 28 °C. We used Q10, GxE, phenotypic divergence and correlation analyses to assess temperature sensitivity and genotype effects of more than 30 morphometric and developmental traits representing five phenotype classes. We found that genotype and temperature differentially affected plant growth and development with variing strengths. Furthermore, overall correlations among phenotypic temperature responses was relatively low which seems to be caused by differential capacities for temperature adaptations of individual accessions. CONCLUSION: Genotype-specific temperature responses may be attractive targets for future forward genetic approaches and accession-specific thermomorphogenesis maps may aid the assessment of functional relevance of known and novel regulatory components.

Unity in defence: honeybee workers exhibit conserved molecular responses to diverse pathogens.

BACKGROUND: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. RESULTS: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. CONCLUSIONS: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions.

Auxin-induced expression divergence between Arabidopsis species may originate within the TIR1/AFB-AUX/IAA-ARF module.

Auxin is an essential regulator of plant growth and development, and auxin signaling components are conserved among land plants. Yet, a remarkable degree of natural variation in physiological and transcriptional auxin responses has been described among Arabidopsis thaliana accessions. As intraspecies comparisons offer only limited genetic variation, we here inspect the variation of auxin responses between A. thaliana and A. lyrata. This approach allowed the identification of conserved auxin response genes including novel genes with potential relevance for auxin biology. Furthermore, promoter divergences were analyzed for putative sources of variation. De novo motif discovery identified novel and variants of known elements with potential relevance for auxin responses, emphasizing the complex, and yet elusive, code of element combinations accounting for the diversity in transcriptional auxin responses. Furthermore, network analysis revealed correlations of interspecies differences in the expression of AUX/IAA gene clusters and classic auxin-related genes. We conclude that variation in general transcriptional and physiological auxin responses may originate substantially from functional or transcriptional variations in the TIR1/AFB, AUX/IAA, and ARF signaling network. In that respect, AUX/IAA gene expression divergence potentially reflects differences in the manner in which different species transduce identical auxin signals into gene expression responses.

Optimized probe masking for comparative transcriptomics of closely related species.

Microarrays are commonly applied to study the transcriptome of specific species. However, many available microarrays are restricted to model organisms, and the design of custom microarrays for other species is often not feasible. Hence, transcriptomics approaches of non-model organisms as well as comparative transcriptomics studies among two or more species often make use of cost-intensive RNAseq studies or, alternatively, by hybridizing transcripts of a query species to a microarray of a closely related species. When analyzing these cross-species microarray expression data, differences in the transcriptome of the query species can cause problems, such as the following: (i) lower hybridization accuracy of probes due to mismatches or deletions, (ii) probes binding multiple transcripts of different genes, and (iii) probes binding transcripts of non-orthologous genes. So far, methods for (i) exist, but these neglect (ii) and (iii). Here, we propose an approach for comparative transcriptomics addressing problems (i) to (iii), which retains only transcript-specific probes binding transcripts of orthologous genes. We apply this approach to an Arabidopsis lyrata expression data set measured on a microarray designed for Arabidopsis thaliana, and compare it to two alternative approaches, a sequence-based approach and a genomic DNA hybridization-based approach. We investigate the number of retained probe sets, and we validate the resulting expression responses by qRT-PCR. We find that the proposed approach combines the benefit of sequence-based stringency and accuracy while allowing the expression analysis of much more genes than the alternative sequence-based approach. As an added benefit, the proposed approach requires probes to detect transcripts of orthologous genes only, which provides a superior base for biological interpretation of the measured expression responses.