Regulation of adaptive growth decisions via phosphorylation of the TRAPPII complex in Arabidopsis

Plants often adapt to adverse or stress conditions via differential growth. The trans-Golgi network (TGN) has been implicated in stress responses, but it is not clear in what capacity it mediates adaptive growth decisions. In this study, we assess the role of the TGN in stress responses by exploring the previously identified interactome of the Transport Protein Particle II (TRAPPII) complex required for TGN structure and function. We identified physical and genetic interactions between AtTRAPPII and shaggy-like kinases (GSK3/AtSKs) and provided in vitro and in vivo evidence that the TRAPPII phosphostatus mediates adaptive responses to abiotic cues. AtSKs are multifunctional kinases that integrate a broad range of signals. Similarly, the AtTRAPPII interactome is vast and considerably enriched in signaling components. An AtSK-TRAPPII interaction would integrate all levels of cellular organization and instruct the TGN, a central and highly discriminate cellular hub, as to how to mobilize and allocate resources to optimize growth and survival under limiting or adverse conditions.

SARS-CoV-2 NSP14 MTase activity is critical for inducing canonical NF-κB activation

Upon SARS-CoV-2 infection, patients with severe forms of COVID-19 often suffer from a dysregulated immune response and hyperinflammation. Aberrant expression of cytokines and chemokines is associated with strong activation of the immunoregulatory transcription factor NF-κB, which can be directly induced by the SARS-CoV-2 protein NSP14. Here, we use NSP14 mutants and generated cells with host factor knockouts (KOs) in the NF-κB signaling pathways to characterize the molecular mechanism of NSP14-induced NF-κB activation. We demonstrate that full-length NSP14 requires methyltransferase (MTase) activity to drive NF-κB induction. NSP14 WT, but not an MTase-defective mutant, is poorly expressed and inherent post-translational instability is mediated by proteasomal degradation. Binding of SARS-CoV-2 NSP10 or addition of the co-factor S-adenosylmethionine (SAM) stabilizes NSP14 and augments its potential to activate NF-κB. Using CRISPR/Cas9-engineered KO cells, we demonstrate that NSP14 stimulation of canonical NF-κB activation relies on NF-κB factor p65/RELA downstream of the NEMO/IKK complex, while c-Rel or non-canonical RelB are not required to induce NF-κB transcriptional activity. However, NSP14 overexpression is unable to induce canonical IκB kinase β (IKKβ)/NF-κB signaling and in co-immunoprecipitation assays we do not detect stable associations between NSP14 and NEMO or p65, suggesting that NSP14 activates NF-κB indirectly through its methyltransferase activity. Taken together, our data provide a framework how NSP14 can augment basal NF-κB activation, which may enhance cytokine expression in SARS-CoV-2 infected cells.

Speos: an ensemble graph representation learning framework to predict core gene candidates for complex diseases

Understanding phenotype-to-genotype relationships is a grand challenge of 21st century biology with translational implications. The recently proposed "omnigenic" model postulates that effects of genetic variation on traits are mediated by core-genes and -proteins whose activities mechanistically influence the phenotype, whereas peripheral genes encode a regulatory network that indirectly affects phenotypes via core gene products. Here, we develop a positive-unlabeled graph representation-learning ensemble-approach based on a nested cross-validation to predict core-like genes for diverse diseases using Mendelian disorder genes for training. Employing mouse knockout phenotypes for external validations, we demonstrate that core-like genes display several key properties of core genes: Mouse knockouts of genes corresponding to our most confident predictions give rise to relevant mouse phenotypes at rates on par with the Mendelian disorder genes, and all candidates exhibit core gene properties like transcriptional deregulation in disease and loss-of-function intolerance. Moreover, as predicted for core genes, our candidates are enriched for drug targets and druggable proteins. In contrast to Mendelian disorder genes the new core-like genes are enriched for druggable yet untargeted gene products, which are therefore attractive targets for drug development. Interpretation of the underlying deep learning model suggests plausible explanations for our core gene predictions in form of molecular mechanisms and physical interactions. Our results demonstrate the potential of graph representation learning for the interpretation of biological complexity and pave the way for studying core gene properties and future drug development.

Regulation of adaptive growth decisions via phosphorylation of the TRAPPII complex in Arabidopsis

Plants often adapt to adverse or stress conditions via differential growth. The trans-Golgi Network (TGN) has been implicated in stress responses, but it is not clear in what capacity it mediates adaptive growth decisions. In this study, we assess the role of the TGN in stress responses by exploring the interactome of the Transport Protein Particle II (TRAPPII) complex, required for TGN structure and function. We identified physical and genetic interactions between TRAPPII and shaggy-like kinases (GSK3/AtSKs). Kinase assays and pharmacological inhibition provided in vitro and in vivo evidence that AtSKs target the TRAPPII-specific subunit AtTRS120/TRAPPC9. GSK3/AtSK phosphorylation sites in AtTRS120/TRAPPC9 were mutated, and the resulting AtTRS120 phosphovariants subjected to a variety of single and multiple stress conditions in planta . The non-phosphorylatable TRS120 mutant exhibited enhanced adaptation to multiple stress conditions and to osmotic stress whereas the phosphomimetic version was less resilient. Higher order inducible trappii atsk mutants had a synthetically enhanced defect in root gravitropism. Our results suggest that the TRAPPII phosphostatus mediates adaptive responses to abiotic cues. AtSKs are multifunctional kinases that integrate a broad range of signals. Similarly, the TRAPPII interactome is vast and considerably enriched in signaling components. An AtSK-TRAPPII interaction would integrate all levels of cellular organization and instruct the TGN, a central and highly discriminate cellular hub, as to how to mobilize and allocate resources to optimize growth and survival under limiting or adverse conditions.

Symbiont-host interactome mapping reveals effector-targeted modulation of hormone networks and activation of growth promotion

Plants have benefited from interactions with symbionts for coping with challenging environments since the colonisation of land. The mechanisms of symbiont-mediated beneficial effects and similarities and differences to pathogen strategies are mostly unknown. Here, we use 106 (effector-) proteins, secreted by the symbiont Serendipita indica (Si) to modulate host physiology, to map interactions with Arabidopsis thaliana host proteins. Using integrative network analysis, we show significant convergence on target-proteins shared with pathogens and exclusive targeting of Arabidopsis proteins in the phytohormone signalling network. Functional in planta screening and phenotyping of Si effectors and interacting proteins reveals previously unknown hormone functions of Arabidopsis proteins and direct beneficial activities mediated by effectors in Arabidopsis. Thus, symbionts and pathogens target a shared molecular microbe-host interface. At the same time Si effectors specifically target the plant hormone network and constitute a powerful resource for elucidating the signalling network function and boosting plant productivity.

A resource of human coronavirus protein-coding sequences in a flexible, multipurpose Gateway Entry clone collection

The COVID-19 pandemic has catalyzed unprecedented scientific data and reagent sharing and collaboration, which enabled understanding the virology of the SARS-CoV-2 virus and vaccine development at record speed. The pandemic, however, has also raised awareness of the danger posed by the family of coronaviruses, of which 7 are known to infect humans and dozens have been identified in reservoir species, such as bats, rodents, or livestock. To facilitate understanding the commonalities and specifics of coronavirus infections and aspects of viral biology that determine their level of lethality to the human host, we have generated a collection of freely available clones encoding nearly all human coronavirus proteins known to date. We hope that this flexible, Gateway-compatible vector collection will encourage further research into the interactions of coronaviruses with their human host, to increase preparedness for future zoonotic viral outbreaks.

A proteome-scale map of the SARS-CoV-2-human contactome

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

Segmentation, tracking and cell cycle analysis of live-cell imaging data with Cell-ACDC

Background

High-throughput live-cell imaging is a powerful tool to study dynamic cellular processes in single cells but creates a bottleneck at the stage of data analysis, due to the large amount of data generated and limitations of analytical pipelines. Recent progress on deep learning dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and tools spanning the complete range of image analysis are still needed.

Results

We present Cell-ACDC, an open-source user-friendly GUI-based framework written in Python, for segmentation, tracking and cell cycle annotations. We included state-of-the-art deep learning models for single-cell segmentation of mammalian and yeast cells alongside cell tracking methods and an intuitive, semi-automated workflow for cell cycle annotation of single cells. Using Cell-ACDC, we found that mTOR activity in hematopoietic stem cells is largely independent of cell volume. By contrast, smaller cells exhibit higher p38 activity, consistent with a role of p38 in regulation of cell size. Additionally, we show that, in S. cerevisiae, histone Htb1 concentrations decrease with replicative age.

Conclusions

Cell-ACDC provides a framework for the application of state-of-the-art deep learning models to the analysis of live cell imaging data without programming knowledge. Furthermore, it allows for visualization and correction of segmentation and tracking errors as well as annotation of cell cycle stages. We embedded several smart algorithms that make the correction and annotation process fast and intuitive. Finally, the open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation, tracking, and downstream image analysis.

Source code: https://github.com/SchmollerLab/Cell_ACDC

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01372-6.

Novel Pseudomonas sp. SCA7 Promotes Plant Growth in Two Plant Families and Induces Systemic Resistance in Arabidopsis thaliana

Pseudomonas sp. SCA7, characterized in this study, was isolated from roots of the bread wheat Triticum aestivum. Sequencing and annotation of the complete SCA7 genome revealed that it represents a potential new Pseudomonas sp. with a remarkable repertoire of plant beneficial functions. In vitro and in planta experiments with the reference dicot plant A. thaliana and the original monocot host T. aestivum were conducted to identify the functional properties of SCA7. The isolate was able to colonize roots, modify root architecture, and promote growth in A. thaliana. Moreover, the isolate increased plant fresh weight in T. aestivum under unchallenged conditions. Gene expression analysis of SCA7-inoculated A. thaliana indicated a role of SCA7 in nutrient uptake and priming of plants. Moreover, confrontational assays of SCA7 with fungal and bacterial plant pathogens revealed growth restriction of the pathogens by SCA7 in direct as well as indirect contact. The latter indicated involvement of microbial volatile organic compounds (mVOCs) in this interaction. Gas chromatography-mass spectrometry (GC-MS) analyses revealed 1-undecene as the major mVOC, and octanal and 1,4-undecadiene as minor abundant compounds in the emission pattern of SCA7. Additionally, SCA7 enhanced resistance of A. thaliana against infection with the plant pathogen Pseudomonas syringae pv. tomato DC3000. In line with these results, SA- and JA/ET-related gene expression in A. thaliana during infection with Pst DC3000 was upregulated upon treatment with SCA7, indicating the ability of SCA7 to induce systemic resistance. The thorough characterization of the novel Pseudomonas sp. SCA7 showed a remarkable genomic and functional potential of plant beneficial traits, rendering it a promising candidate for application as a biocontrol or a biostimulation agent.

Chemokine-like MDL proteins modulate flowering time and innate immunity in plants

Human macrophage migration inhibitory factor (MIF) is an atypical chemokine implicated in intercellular signaling and innate immunity. MIF orthologs (MIF/D-DT-like proteins, MDLs) are present throughout the plant kingdom, but remain experimentally unexplored in these organisms. Here, we provide an in planta characterization and functional analysis of the three-member gene/protein MDL family in Arabidopsis thaliana. Subcellular localization experiments indicated a nucleo-cytoplasmic distribution of MDL1 and MDL2, while MDL3 is localized to peroxisomes. Protein–protein interaction assays revealed the in vivo formation of MDL1, MDL2, and MDL3 homo-oligomers, as well as the formation of MDL1-MDL2 hetero-oligomers. Functionally, Arabidopsismdl mutants exhibited a delayed transition from vegetative to reproductive growth (flowering) under long-day conditions, but not in a short-day environment. In addition, mdl mutants were more resistant to colonization by the bacterial pathogen Pseudomonas syringae pv. maculicola. The latter phenotype was compromised by the additional mutation of SALICYLIC ACID INDUCTION DEFICIENT 2 (SID2), a gene implicated in the defense-induced biosynthesis of the key signaling molecule salicylic acid. However, the enhanced antibacterial immunity was not associated with any constitutive or pathogen-induced alterations in the levels of characteristic phytohormones or defense-associated metabolites. Interestingly, bacterial infection triggered relocalization and accumulation of MDL1 and MDL2 at the peripheral lobes of leaf epidermal cells. Collectively, our data indicate redundant functionality and a complex interplay between the three chemokine-like Arabidopsis MDL proteins in the regulation of both developmental and immune-related processes. These insights expand the comparative cross-kingdom analysis of MIF/MDL signaling in human and plant systems.

ARMADILLO REPEAT ONLY proteins confine Rho GTPase signalling to polar growth sites

Polar growth requires the precise tuning of Rho GTPase signalling at distinct plasma membrane domains. The activity of Rho of plant (ROP) GTPases is regulated by the opposing action of guanine nucleotide-exchange factors (GEFs) and GTPase-activating proteins (GAPs). Whereas plant-specific ROPGEFs have been shown to be embedded in higher-level regulatory mechanisms involving membrane-bound receptor-like kinases, the regulation of GAPs has remained enigmatic. Here, we show that three Arabidopsis ARMADILLO REPEAT ONLY (ARO) proteins are essential for the stabilization of growth sites in root hair cells and trichomes. AROs interact with ROP1 enhancer GAPs (RENGAPs) and bind to the plasma membrane via a conserved polybasic region at the ARO amino terminus. The ectopic spreading of ROP2 in aro2/3/4 mutant root hair cells and the preferential interaction of AROs with active ROPs and anionic phospholipids suggests that AROs recruit RENGAPs into complexes with ROPs to confine ROP signalling to distinct membrane regions.

Publisher Correction: Extensive signal integration by the phytohormone protein network

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

TRIPP Is a Plant-Specific Component of the Arabidopsis TRAPPII Membrane Trafficking Complex with Important Roles in Plant Development

How the membrane trafficking system spatially organizes intracellular activities and intercellular signaling networks in plants is not well understood. Transport Protein Particle (TRAPP) complexes play key roles in the selective delivery of membrane vesicles to various subcellular compartments in yeast and animals but remain to be fully characterized in plants. Here, we investigated TRAPP complexes in Arabidopsis (Arabidopsis thaliana) using immunoprecipitation followed by quantitative mass spectrometry analysis of AtTRS33, a conserved core component of all TRAPP complexes. We identified 14 AtTRS33-interacting proteins, including homologs of all 13 TRAPP components in mammals and a protein that has homologs only in multicellular photosynthetic organisms and is thus named TRAPP-Interacting Plant Protein (TRIPP). TRIPP specifically associates with the TRAPPII complex through binary interactions with two TRAPPII-specific subunits. TRIPP colocalized with a subset of TRS33 compartments and trans-Golgi network markers in a TRS33-dependent manner. Loss-of-function tripp mutants exhibited dwarfism, sterility, partial photomorphogenesis in the dark, reduced polarity of the auxin transporter PIN2, incomplete cross wall formation, and altered localization of a TRAPPII-specific component. Therefore, TRIPP is a plant-specific component of the TRAPPII complex with important functions in trafficking, plant growth, and development.

GROWTH-REGULATING FACTORS Interact with DELLAs and Regulate Growth in Cold Stress

DELLA proteins are repressors of the gibberellin (GA) hormone signaling pathway that act mainly by regulating transcription factor activities in plants. GAs induce DELLA repressor protein degradation and thereby control a number of critical developmental processes as well as responses to stresses such as cold. The strong effect of cold temperatures on many physiological processes has rendered it difficult to assess, based on phenotypic criteria, the role of GA and DELLAs in plant growth during cold stress. Here, we uncover substantial differences in the GA transcriptomes between plants grown at ambient temperature (21°C) and plants exposed to cold stress (4°C) in Arabidopsis (Arabidopsis thaliana). We further identify over 250, to the largest extent previously unknown, DELLA-transcription factor interactions using the yeast two-hybrid system. By integrating both data sets, we reveal that most members of the nine-member GRF (GROWTH REGULATORY FACTOR) transcription factor family are DELLA interactors and, at the same time, that several GRF genes are targets of DELLA-modulated transcription after exposure to cold stress. We find that plants with altered GRF dosage are differentially sensitive to the manipulation of GA and hence DELLA levels, also after cold stress, and identify a subset of cold stress-responsive genes that qualify as targets of this DELLA-GRF regulatory module.

Interactions between Transport Protein Particle (TRAPP) complexes and Rab GTPases in Arabidopsis

Transport Protein Particle II (TRAPPII) is essential for exocytosis, endocytosis, protein sorting and cytokinesis. In spite of a considerable understanding of its biological role, little information is known about Arabidopsis TRAPPII complex topology and molecular function. In this study, independent proteomic approaches initiated with TRAPP components or Rab-A GTPase variants converge on the TRAPPII complex. We show that the Arabidopsis genome encodes the full complement of 13 TRAPPC subunits, including four previously unidentified components. A dimerization model is proposed to account for binary interactions between TRAPPII subunits. Preferential binding to dominant negative (GDP-bound) versus wild-type or constitutively active (GTP-bound) RAB-A2a variants discriminates between TRAPPII and TRAPPIII subunits and shows that Arabidopsis complexes differ from yeast but resemble metazoan TRAPP complexes. Analyzes of Rab-A mutant variants in trappii backgrounds provide genetic evidence that TRAPPII functions upstream of RAB-A2a, allowing us to propose that TRAPPII is likely to behave as a guanine nucleotide exchange factor (GEF) for the RAB-A2a GTPase. GEFs catalyze exchange of GDP for GTP; the GTP-bound, activated, Rab then recruits a diverse local network of Rab effectors to specify membrane identity in subsequent vesicle fusion events. Understanding GEF-Rab interactions will be crucial to unravel the co-ordination of plant membrane traffic.

Systems Biology of Plant-Microbiome Interactions

In natural environments, plants are exposed to diverse microbiota that they interact with in complex ways. While plant-pathogen interactions have been intensely studied to understand defense mechanisms in plants, many microbes and microbial communities can have substantial beneficial effects on their plant host. Such beneficial effects include improved acquisition of nutrients, accelerated growth, resilience against pathogens, and improved resistance against abiotic stress conditions such as heat, drought, and salinity. However, the beneficial effects of bacterial strains or consortia on their host are often cultivar and species specific, posing an obstacle to their general application. Remarkably, many of the signals that trigger plant immune responses are molecularly highly similar and often identical in pathogenic and beneficial microbes. Thus, it is unclear what determines the outcome of a particular microbe-host interaction and which factors enable plants to distinguish beneficials from pathogens. To unravel the complex network of genetic, microbial, and metabolic interactions, including the signaling events mediating microbe-host interactions, comprehensive quantitative systems biology approaches will be needed.

Independent yet overlapping pathways ensure the robustness and responsiveness of trans-Golgi network functions in Arabidopsis

The trans-Golgi-network (TGN) has essential housekeeping functions in secretion, endocytosis and protein sorting, but also more specialized functions in plant development. How the robustness of basal TGN function is ensured while specialized functions are differentially regulated is poorly understood. Here, we investigate two key regulators of TGN structure and function, ECHIDNA and the Transport Protein Particle II (TRAPPII) tethering complex. An analysis of physical, network and genetic interactions suggests that two network communities are implicated in TGN function and that ECHIDNA and TRAPPII belong to distinct yet overlapping pathways. Whereas ECHIDNA and TRAPPII colocalized at the TGN in interphase cells, their localization diverged in dividing cells. Moreover, ECHIDNA and TRAPPII localization patterns were mutually independent. TGN structure, endocytosis and sorting decisions were differentially impacted in echidna and trappii mutants. Our analyses point to a partitioning of specialized TGN functions, with ECHIDNA being required for cell elongation and TRAPPII for cytokinesis. Two independent pathways able to compensate for each other might contribute to the robustness of TGN housekeeping functions and to the responsiveness and fine tuning of its specialized functions.

High-Quality Yeast-2-Hybrid Interaction Network Mapping

In this article, we describe a Y2H interaction mapping protocol for systematically screening medium-to-large collections of open reading frames (ORFs) against each other. The protocol is well suited for analysis of focused networks, for modules of interest, assembling genome-scale interactome maps, and investigating host-microbe interactions. The four-step high-throughput protocol has a demonstrated low false-discovery rate that is essential for producing meaningful network maps. Following the assembly of yeast expression clones from an existing ORFeome collection, we describe in detail the four-step procedure that begins with the primary screen using minipools, followed by secondary verification of primary positives, identification of candidate interaction pairs by sequencing, and a final verification step using fresh inoculants. In addition to this core protocol, aspects of network mapping and quality control will be discussed briefly. © 2018 by John Wiley & Sons, Inc.

The Next Generation of Training for Arabidopsis Researchers: Bioinformatics and Quantitative Biology

Training for experimental plant biologists needs to combine bioinformatics, quantitative approaches, computational biology, and training in the art of collaboration, best achieved through fully integrated curriculum development.

LSU network hubs integrate abiotic and biotic stress responses via interaction with the superoxide dismutase FSD2

In natural environments, plants often experience different stresses simultaneously, and adverse abiotic conditions can weaken the plant immune system. Interactome mapping revealed that the LOW SULPHUR UPREGULATED (LSU) proteins are hubs in an Arabidopsis protein interaction network that are targeted by virulence effectors from evolutionarily diverse pathogens. Here we show that LSU proteins are up-regulated in several abiotic and biotic stress conditions, such as nutrient depletion or salt stress, by both transcriptional and post-translational mechanisms. Interference with LSU expression prevents chloroplastic reactive oxygen species (ROS) production and proper stomatal closure during sulphur stress. We demonstrate that LSU1 interacts with the chloroplastic superoxide dismutase FSD2 and stimulates its enzymatic activity in vivo and in vitro. Pseudomonas syringae virulence effectors interfere with this interaction and preclude re-localization of LSU1 to chloroplasts. We demonstrate that reduced LSU levels cause a moderately enhanced disease susceptibility in plants exposed to abiotic stresses such as nutrient deficiency, high salinity, or heavy metal toxicity, whereas LSU1 overexpression confers significant disease resistance in several of these conditions. Our data suggest that the network hub LSU1 plays an important role in co-ordinating plant immune responses across a spectrum of abiotic stress conditions.