Deciphering cell signaling networks with massively multiplexed biosensor barcoding.

Genetically encoded fluorescent biosensors are powerful tools for monitoring biochemical activities in live cells, but their multiplexing capacity is limited by the available spectral space. We overcome this problem by developing a set of barcoding proteins that can generate over 100 barcodes and are spectrally separable from commonly used biosensors. Mixtures of barcoded cells expressing different biosensors are simultaneously imaged and analyzed by deep learning models to achieve massively multiplexed tracking of signaling events. Importantly, different biosensors in cell mixtures show highly coordinated activities, thus facilitating the delineation of their temporal relationship. Simultaneous tracking of multiple biosensors in the receptor tyrosine kinase signaling network reveals distinct mechanisms of effector adaptation, cell autonomous and non-autonomous effects of KRAS mutations, as well as complex interactions in the network. Biosensor barcoding presents a scalable method to expand multiplexing capabilities for deciphering the complexity of signaling networks and their interactions between cells.

The EGFR phosphatase RPTPγ is a redox-regulated suppressor of promigratory signaling.

Spatially organized reaction dynamics between proto-oncogenic epidermal growth factor receptor (EGFR) and protein tyrosine phosphatases determine EGFR phosphorylation dynamics in response to growth factors and thereby cellular behavior within developing tissues. We show that the reaction dynamics of mutual inhibition between RPTPγ phosphatase and autocatalytic ligandless EGFR phosphorylation enable highly sensitive promigratory EGFR signaling responses to subnanomolar EGF levels, when < 5% receptors are occupied by EGF. EGF thereby triggers an autocatalytic phospho-EGFR reaction by the initial production of small amounts of phospho-EGFR through transient, asymmetric EGF-EGFR2 dimers. Single cell RPTPγ oxidation imaging revealed that phospho-EGFR induces activation of NADPH oxidase, which in turn inhibits RPTPγ-mediated dephosphorylation of EGFR, tilting the autocatalytic RPTPγ/EGFR toggle switch reaction towards ligandless phosphorylated EGFR. Reversibility of this reaction to EGF is maintained by the constitutive phosphatase activity of endoplasmic reticulum-associated TCPTP. This RPTPγ/EGFR reaction at the plasma membrane causes promigratory signaling that is separated from proliferative signaling induced by accumulated, liganded, phosphorylated EGF-EGFR in endosomes. Accordingly, loss of RPTPγ results in constitutive promigratory signaling from phosphorylated EGFR monomers. RPTPγ is thus a suppressor of promigratory oncogenic but not of proliferative EGFR signaling.

Characterization of p38α Signaling Networks in Cancer Cells Using Quantitative Proteomics and Phosphoproteomics.

p38α (encoded by MAPK14) is a protein kinase that regulates cellular responses to almost all types of environmental and intracellular stresses. Upon activation, p38α phosphorylates many substrates both in the cytoplasm and nucleus, allowing this pathway to regulate a wide variety of cellular processes. While the role of p38α in the stress response has been widely investigated, its implication in cell homeostasis is less understood. To investigate the signaling networks regulated by p38α in proliferating cancer cells, we performed quantitative proteomic and phosphoproteomic analyses in breast cancer cells in which this pathway had been either genetically targeted or chemically inhibited. Our study identified with high confidence 35 proteins and 82 phosphoproteins (114 phosphosites) that are modulated by p38α and highlighted the implication of various protein kinases, including MK2 and mTOR, in the p38α-regulated signaling networks. Moreover, functional analyses revealed an important contribution of p38α to the regulation of cell adhesion, DNA replication, and RNA metabolism. Indeed, we provide experimental evidence supporting that p38α facilitates cancer cell adhesion and showed that this p38α function is likely mediated by the modulation of the adaptor protein ArgBP2. Collectively, our results illustrate the complexity of the p38α-regulated signaling networks, provide valuable information on p38α-dependent phosphorylation events in cancer cells, and document a mechanism by which p38α can regulate cell adhesion.

Network modeling predicts personalized gene expression and drug responses in valve myofibroblasts cultured with patient sera.

Aortic valve stenosis (AVS) patients experience pathogenic valve leaflet stiffening due to excessive extracellular matrix (ECM) remodeling. Numerous microenvironmental cues influence pathogenic expression of ECM remodeling genes in tissue-resident valvular myofibroblasts, and the regulation of complex myofibroblast signaling networks depends on patient-specific extracellular factors. Here, we combined a manually curated myofibroblast signaling network with a data-driven transcription factor network to predict patient-specific myofibroblast gene expression signatures and drug responses. Using transcriptomic data from myofibroblasts cultured with AVS patient sera, we produced a large-scale, logic-gated differential equation model in which 11 biochemical and biomechanical signals were transduced via a network of 334 signaling and transcription reactions to accurately predict the expression of 27 fibrosis-related genes. Correlations were found between personalized model-predicted gene expression and AVS patient echocardiography data, suggesting links between fibrosis-related signaling and patient-specific AVS severity. Further, global network perturbation analyses revealed signaling molecules with the most influence over network-wide activity, including endothelin 1 (ET1), interleukin 6 (IL6), and transforming growth factor ß (TGFß), along with downstream mediators c-Jun N-terminal kinase (JNK), signal transducer and activator of transcription (STAT), and reactive oxygen species (ROS). Lastly, we performed virtual drug screening to identify patient-specific drug responses, which were experimentally validated via fibrotic gene expression measurements in valvular interstitial cells cultured with AVS patient sera and treated with or without bosentan-a clinically approved ET1 receptor inhibitor. In sum, our work advances the ability of computational approaches to provide a mechanistic basis for clinical decisions including patient stratification and personalized drug screening.

A flagellar accessory protein links chemotaxis to surface sensing.

Bacteria find suitable locations for colonization by sensing and responding to surfaces. Complex signaling repertoires control surface colonization, and surface contact sensing by the flagellum plays a central role in activating colonization programs. Caulobacter crescentus adheres to surfaces using a polysaccharide adhesin called the holdfast. In C. crescentus, disruption of the flagellum through interactions with a surface or mutation of flagellar genes increases holdfast production. Our group previously identified several C. crescentus genes involved in flagellar surface sensing. One of these, fssF, codes for a protein with homology to the flagellar C-ring protein FliN. We show here that a fluorescently tagged FssF protein localizes to the flagellated pole of the cell and requires all components of the flagellar C-ring for proper localization, supporting the model that FssF associates with the C-ring. Deleting fssF results in a severe motility defect, which we show is due to a disruption of chemotaxis. Epistasis experiments demonstrate that fssF promotes adhesion through a stator-dependent pathway when late-stage flagellar mutants are disrupted. Separately, we find that disruption of chemotaxis through deletion of fssF or other chemotaxis genes results in a hyperadhesion phenotype. Key genes in the surface sensing network (pleD, motB, and dgcB) contribute to both ∆flgH-dependent and ∆fssF-dependent hyperadhesion, but these genes affect adhesion differently in the two hyperadhesive backgrounds. Our results support a model in which the stator subunits of the flagella incorporate both mechanical and chemical signals to regulate adhesion.IMPORTANCEBacterial biofilms pose a threat in clinical and industrial settings. Surface sensing is one of the first steps in biofilm formation. Studying surface sensing can improve our understanding of biofilm formation and develop preventative strategies. In this study, we use the freshwater bacterium Caulobacter crescentus to study surface sensing and the regulation of surface attachment. We characterize a previously unstudied gene, fssF, and find that it localizes to the cell pole in the presence of three proteins that make up a component of the flagellum called the C-ring. Additionally, we find that fssF is required for chemotaxis behavior but dispensable for swimming motility. Lastly, our results indicate that deletion of fssF and other genes required for chemotaxis results in a hyperadhesive phenotype. These results support that surface sensing requires chemotaxis for a robust response to a surface.

Revisiting Neuroblastoma: Nrf2, NF-κB and Phox2B as a Promising Network in Neuroblastoma.

Neuroblastoma is the most common solid extracranial tumor during childhood; it displays extraordinary heterogeneous clinical courses, from spontaneous regression to poor outcome in high-risk patients due to aggressive growth, metastasizing, and treatment resistance. Therefore, the identification and detailed analysis of promising tumorigenic molecular mechanisms are inevitable. This review highlights the abnormal regulation of NF-κB, Nrf2, and Phox2B as well as their interactions among each other in neuroblastoma. NF-κB and Nrf2 play a key role in antioxidant responses, anti-inflammatory regulation and tumor chemoresistance. Recent studies revealed a regulation of NF-κB by means of the Nrf2/antioxidant response element (ARE) system. On the other hand, Phox2B contributes to the differentiation of immature sympathetic nervous system stem cells: this transcription factor regulates the expression of RET, thereby facilitating cell survival and proliferation. As observed in other tumors, we presume striking interactions between NF-κB, Nrf2, and Phox2B, which might constitute an important crosstalk triangle, whose decompensation may trigger a more aggressive phenotype. Consequently, these transcription factors could be a promising target for novel therapeutic approaches and hence, further investigation on their regulation in neuroblastoma shall be reinforced.

Deletion of PTP4A3 phosphatase in high grade serous ovarian cancer cells decreases tumorigenicity and produces marked changes in intracellular signaling pathways and cytokine release.

The oncogenic protein tyrosine phosphatase PTP4A3 is frequently overexpressed in human ovarian cancers and is associated with poor patient prognosis. PTP4A3 is thought to regulate multiple oncogenic signaling pathways, including STAT3, SRC, and ERK. The objective of this study was to generate ovarian cancer cells with genetically depleted PTP4A3; to assess their tumorigenicity; to examine their cellular phenotype; and to uncover changes in their intracellular signaling pathways and cytokine release profiles. Genetic deletion of PTP4A3 using CRISPR/Cas9 enabled the generation of individual clones derived from single cells isolated from the polyclonal knockout population. We observed a >90% depletion of PTP4A3 protein levels by Western blotting in the clonal cell lines compared to the sham transfected wildtype population. The wildtype and polyclonal knockout cell lines shared similar monolayer growth rates, while the isolated clonal populations 2B4, 3C9, and 3C12 exhibited significantly lower monolayer growth characteristics consistent with their lower PTP4A3 levels. The clonal PTP4A3 knockout cell lines also had substantially lower in vitro colony formation efficiencies compared to the wildtype cells and were less tumorigenic in vivo The clonal knockout cells were markedly less responsive to IL-6-stimulated migration in a scratch wound assay compared to the wildtype cells. Antibody microarray assays documented differences in cytokine release and intracellular phosphorylation patterns in the PTP4A3 deleted clones. Bioinformatic network analyses indicated alterations in cellular signaling nodes. These biochemical changes could ultimately form the foundation for pharmacodynamic endpoints useful for emerging anti-PTP4A3 therapeutics. Significance Statement Clones of high grade serous ovarian cancer cells were isolated in which the oncogenic phosphatase PTP4A3 was deleted using CRISPR/Cas9 methodologies. The PTP4A3 null cells exhibited loss of in vitro proliferation, colony formation, and migration, and reduced in vivo tumorigenesis. Marked differences in intracellular protein phosphorylation and cytokine release were seen. The newly developed PTP4A3 knockout cells should provide useful tools to probe the role of PTP4A3 phosphatase in ovarian cancer cell survival, tumorigenicity and cell signaling.

CDK6 activity in a recurring convergent kinase network motif.

In humans, more than 500 kinases phosphorylate ~15% of all proteins in an emerging phosphorylation network. Convergent local interaction motifs, in which ≥two kinases phosphorylate the same substrate, underlie feedback loops and signal amplification events but have not been systematically analyzed. Here, we first report a network-wide computational analysis of convergent kinase-substrate relationships (cKSRs). In experimentally validated phosphorylation sites, we find that cKSRs are common and involve >80% of all human kinases and >24% of all substrates. We show that cKSRs occur over a wide range of stoichiometries, in many instances harnessing co-expressed kinases from family subgroups. We then experimentally demonstrate for the prototypical convergent CDK4/6 kinase pair how multiple inputs phosphorylate the tumor suppressor retinoblastoma protein (RB) and thereby hamper in situ analysis of the individual kinases. We hypothesize that overexpression of one kinase combined with a CDK4/6 inhibitor can dissect convergence. In breast cancer cells expressing high levels of CDK4, we confirm this hypothesis and develop a high-throughput compatible assay that quantifies genetically modified CDK6 variants and inhibitors. Collectively, our work reveals the occurrence, topology, and experimental dissection of convergent interactions toward a deeper understanding of kinase networks and functions.

An Escherichia coli-Based Phosphorylation System for Efficient Screening of Kinase Substrates.

Posttranslational modifications (PTMs), particularly phosphorylation, play a pivotal role in expanding the complexity of the proteome and regulating diverse cellular processes. In this study, we present an efficient Escherichia coli phosphorylation system designed to streamline the evaluation of potential substrates for Arabidopsis thaliana plant kinases, although the technology is amenable to any. The methodology involves the use of IPTG-inducible vectors for co-expressing kinases and substrates, eliminating the need for radioactive isotopes and prior protein purification. We validated the system's efficacy by assessing the phosphorylation of well-established substrates of the plant kinase SnRK1, including the rat ACETYL-COA CARBOXYLASE 1 (ACC1) and FYVE1/FREE1 proteins. The results demonstrated the specificity and reliability of the system in studying kinase-substrate interactions. Furthermore, we applied the system to investigate the phosphorylation cascade involving the A. thaliana MKK3-MPK2 kinase module. The activation of MPK2 by MKK3 was demonstrated to phosphorylate the Myelin Basic Protein (MBP), confirming the system's ability to unravel sequential enzymatic steps in phosphorylation cascades. Overall, this E. coli phosphorylation system offers a rapid, cost-effective, and reliable approach for screening potential kinase substrates, presenting a valuable tool to complement the current portfolio of molecular techniques for advancing our understanding of kinase functions and their roles in cellular signaling pathways.

Gain-of-Function Mutations: An Emerging Advantage for Cancer Biology.

Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in cancer. Elucidating the functional pathways altered by loss-of-function (LOF) or gain-of-function (GOF) mutations will be crucial for prioritizing cancer-causing variants and their resultant therapeutic liabilities. In this review, we highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also summarize advances in experimental and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of mutations. Together, systematic investigations of the function of GOF mutations will provide an important missing piece for cancer biology and precision therapy.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis.

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.

Long non-coding RNA (lncRNA) H19 in human cancer: From proliferation and metastasis to therapy.

Initiation and development of cancer depend on multiple factors that mutations in genes and epigenetic level can be considered as important drivers. Epigenetic factors include a large family of members and understanding their function in cancer has been a hot topic. LncRNAs are RNA molecules with no capacity in synthesis of proteins, and they have regulatory functions in cells. LncRNAs are localized in nucleus and cytoplasm, and their abnormal expression is related to development of tumor. This manuscript emphasizes on the role of lncRNA H19 in various cancers and its association with tumor hallmarks. The function of lncRNA H19 in most tumors is oncogenic and therefore, tumor cells increase its expression for promoting their progression. LncRNA H19 contributes to enhancing growth and cell cycle of cancers and by EMT induction, it is able to elevate metastasis rate. Silencing H19 induces apoptotic cell death and disrupts progression of tumors. LncRNA H19 triggers chemo- and radio-resistance in cancer cells. miRNAs are dually upregulated/down-regulated by lncRNA H19 in increasing tumor progression. Anti-cancer agents reduce lncRNA H19 in impairing tumor progression and increasing therapy sensitivity. A number of downstream targets and molecular pathways for lncRNA H19 have been detected in cancers including miRNAs, RUNX1, STAT3, ß-catenin, Akt2 and FOXM1. Clinical studies have revealed potential of lncRNA H19 as biomarker and its association with poor prognosis. LncRNA H19 can be transferred to cancer cells via exosomes in enhancing their progression.

MAP kinase and mammalian target of rapamycin are main pathways of gallbladder carcinogenesis: results from bioinformatic analysis of next generation sequencing data from a hospital-based cohort (NCT05404347).

BACKGROUND: Gallbladder Cancer (GBC) is one of the most common cancers of the biliary tract and the third commonest gastrointestinal (GI) malignancy worldwide. The disease is characterized by the late presentation and poor outcome despite treatment, and hence, newer therapies and targets need to be identified. METHODS: The current study investigated various functionally enriched pathways in GBC pathogenesis involving the genes identified through Next Generation Sequencing (NGS) in a hospital-based cohort. The Pathway enrichment analysis and Gene Ontology (GO) were carried out after NGS, followed by the construction of the protein-protein interaction (PPI) network to discover associations among the genes. RESULTS: Of the thirty-three patients with GBC who were screened through next-generation sequencing (NGS), 27somatic mutations were identified. These mutations involved a total of 14 genes. The p53 and KRAS were commonly found to be mutated, while mutations in other genes were seen in one case each, the mean number of mutations were 1.2, and maximum mutation in a single case (eight) was seen in one case. The bioinformatics analysis identified MAP kinase, PI3K-AKT, EGF/EGFR, and Focal Adhesion PI3K-AKT-mTOR signaling pathways and cross-talk between these. CONCLUSION: The results suggest that the complex crosstalk between the mTOR, MAPK, and multiple interacting cell signaling cascades can promote GBC progression, and hence, mTOR-MAPK targeted treatment will be an attractive option.

A natural derivative from ethnomedicinal mushroom potentiates apoptosis, autophagy and attenuates cell migration, via fine tuning the Akt signaling in human lung adenocarcinoma cells (A549).

Although comprehensive exertions have been made in late decades for treating advanced lung cancer with inclusive therapies but efficient anti-lung cancer therapeutics are statically inadequate in the clinics. Hence, compelling novel anti-lung cancer drugs are considerably desired. This backdrop enticed us to unveil anticancer efficacy of astrakurkurol, derivative of wild edible mushroom against lung cancer, whose effects have not yet been described. Mechanistic analysis disclosed that sensitizing effect of astrakurkurol is due to cell cycle arrest at G0/G1 phase, increased level of Fas, FADD, decreased ratio of Bax/Bcl-2, and increased cleaved form of caspase 9, 8, and 3. Apart from the induction of apoptosis, it was demonstrated for the first time that astrakurkurol induced an autophagic response as evidenced by the development of acidic vesicular organelles (AVOs) with up-regulation of beclin-1, Atg7, and downregulated p62. Apoptosis and autophagy can be sparked by the same stimuli, which was as evident from the astrakurkurol-induced inactivation of PI3K/AKT signaling. The thorough scanning of the mechanism of crosstalk between apoptosis and autophagy is requisite for prosperous anticancer remedy. Triterpenoid has evidently intensified cytotoxicity, induced apoptosis and autophagy on A549 cells. Besides astrakurkurol could also curb migration and regress the size of tumor in ex ovo xenograft model. All these findings put forth astrakurkurol as a convincing novel anti-cancer agent, for scrutinizing the lung cancer therapies and as a robust contender for future in vitro and in vivo analysis.

Quantitative Systems Pharmacology and Biased Agonism at Opioid Receptors: A Potential Avenue for Improved Analgesics.

Chronic pain is debilitating and represents a significant burden in terms of personal and socio-economic costs. Although opioid analgesics are widely used in chronic pain treatment, many patients report inadequate pain relief or relevant adverse effects, highlighting the need to develop analgesics with improved efficacy/safety. Multiple evidence suggests that G protein-dependent signaling triggers opioid-induced antinociception, whereas arrestin-mediated pathways are credited with modulating different opioid adverse effects, thus spurring extensive research for G protein-biased opioid agonists as analgesic candidates with improved pharmacology. Despite the increasing expectations of functional selectivity, translating G protein-biased opioid agonists into improved therapeutics is far from being fully achieved, due to the complex, multidimensional pharmacology of opioid receptors. The multifaceted network of signaling events and molecular processes underlying therapeutic and adverse effects induced by opioids is more complex than the mere dichotomy between G protein and arrestin and requires more comprehensive, integrated, network-centric approaches to be fully dissected. Quantitative Systems Pharmacology (QSP) models employing multidimensional assays associated with computational tools able to analyze large datasets may provide an intriguing approach to go beyond the greater complexity of opioid receptor pharmacology and the current limitations entailing the development of biased opioid agonists as improved analgesics.

mPR-Specific Actions Influence Maintenance of the Blood-Brain Barrier (BBB).

Cerebral cavernous malformations (CCMs) are characterized by abnormally dilated intracranial microvascular sinusoids that result in increased susceptibility to hemorrhagic stroke. It has been demonstrated that three CCM proteins (CCM1, CCM2, and CCM3) form the CCM signaling complex (CSC) to mediate angiogenic signaling. Disruption of the CSC will result in hemorrhagic CCMs, a consequence of compromised blood-brain barrier (BBB) integrity. Due to their characteristically incomplete penetrance, the majority of CCM mutation carriers (presumed CCM patients) are largely asymptomatic, but when symptoms occur, the disease has typically reached a clinical stage of focal hemorrhage with irreversible brain damage. We recently reported that the CSC couples both classic (nuclear; nPRs) and nonclassic (membrane; mPRs) progesterone (PRG)-receptors-mediated signaling within the CSC-mPRs-PRG (CmP) signaling network in nPR(-) breast cancer cells. In this report, we demonstrate that depletion of any of the three CCM genes or treatment with mPR-specific PRG actions (PRG/mifepristone) results in the disruption of the CmP signaling network, leading to increased permeability in the nPR(-) endothelial cells (ECs) monolayer in vitro. Finally, utilizing our in vivo hemizygous Ccm mutant mice models, we demonstrate that depletion of any of the three CCM genes, in combination with mPR-specific PRG actions, is also capable of leading to defective homeostasis of PRG in vivo and subsequent BBB disruption, allowing us to identify a specific panel of etiological blood biomarkers associated with BBB disruption. To our knowledge, this is the first report detailing the etiology to predict the occurrence of a disrupted BBB, an indication of early hemorrhagic events.

Bayesian Network Structure Learning Method Based on Causal Direction Graph for Protein Signaling Networks.

Constructing the structure of protein signaling networks by Bayesian network technology is a key issue in the field of bioinformatics. The primitive structure learning algorithms of the Bayesian network take no account of the causal relationships between variables, which is unfortunately important in the application of protein signaling networks. In addition, as a combinatorial optimization problem with a large searching space, the computational complexities of the structure learning algorithms are unsurprisingly high. Therefore, in this paper, the causal directions between any two variables are calculated first and stored in a graph matrix as one of the constraints of structure learning. A continuous optimization problem is constructed next by using the fitting losses of the corresponding structure equations as the target, and the directed acyclic prior is used as another constraint at the same time. Finally, a pruning procedure is developed to keep the result of the continuous optimization problem sparse. Experiments show that the proposed method improves the structure of the Bayesian network compared with the existing methods on both the artificial data and the real data, meanwhile, the computational burdens are also reduced significantly.

StrongestPath: a Cytoscape application for protein-protein interaction analysis.

BACKGROUND: StrongestPath is a Cytoscape 3 application that enables the analysis of interactions between two proteins or groups of proteins in a collection of protein-protein interaction (PPI) network or signaling network databases. When there are different levels of confidence over the interactions, the application is able to process them and identify the cascade of interactions with the highest total confidence score. Given a set of proteins, StrongestPath can extract a set of possible interactions between the input proteins, and expand the network by adding new proteins that have the most interactions with highest total confidence to the current network of proteins. The application can also identify any activating or inhibitory regulatory paths between two distinct sets of transcription factors and target genes. This application can be used on the built-in human and mouse PPI or signaling databases, or any user-provided database for some organism. RESULTS: Our results on 12 signaling pathways from the NetPath database demonstrate that the application can be used for indicating proteins which may play significant roles in a pathway by finding the strongest path(s) in the PPI or signaling network. CONCLUSION: Easy access to multiple public large databases, generating output in a short time, addressing some key challenges in one platform, and providing a user-friendly graphical interface make StrongestPath an extremely useful application.

Precision transcriptomics of viral foci reveals the spatial regulation of immune-signaling genes and identifies RBOHD as an important player in the incompatible interaction between potato virus Y and potato.

Whereas the activation of resistance (R) proteins has been intensively studied, the downstream signaling mechanisms leading to the restriction of the pathogen remain mostly unknown. We studied the immunity network response conditioned by the potato Ny-1 gene against potato virus Y. We analyzed the processes in the cell death zone and surrounding tissue on the biochemical and gene expression levels in order to reveal the spatiotemporal regulation of the immune response. We show that the transcriptional response in the cell death zone and surrounding tissue is dependent on salicylic acid (SA). For some genes the spatiotemporal regulation is completely lost in the SA-deficient line, whereas other genes show a different response, indicating multiple connections between hormonal signaling modules. The induction of NADPH oxidase RBOHD expression occurs specifically on the lesion border during the resistance response. In plants with silenced RBOHD, the functionality of the resistance response is perturbed and the spread of the virus is not arrested at the site of infection. RBOHD is required for the spatial accumulation of SA, and conversely RBOHD is under the transcriptional regulation of SA. Using spatially resolved RNA-seq, we also identified spatial regulation of an UDP-glucosyltransferase, another component in feedback activation of SA biosynthesis, thus deciphering a novel aspect of resistance signaling.

A plant effector-triggered immunity signaling sector is inhibited by pattern-triggered immunity.

Since signaling machineries for two modes of plant-induced immunity, pattern-triggered immunity (PTI) and effector-triggered immunity (ETI), extensively overlap, PTI and ETI signaling likely interact. In an Arabidopsis quadruple mutant, in which four major sectors of the signaling network, jasmonate, ethylene, PAD4, and salicylate, are disabled, the hypersensitive response (HR) typical of ETI is abolished when the Pseudomonas syringae effector AvrRpt2 is bacterially delivered but is intact when AvrRpt2 is directly expressed in planta These observations led us to discovery of a network-buffered signaling mechanism that mediates HR signaling and is strongly inhibited by PTI signaling. We named this mechanism the ETI-Mediating and PTI-Inhibited Sector (EMPIS). The signaling kinetics of EMPIS explain apparently different plant genetic requirements for ETI triggered by different effectors without postulating different signaling machineries. The properties of EMPIS suggest that information about efficacy of the early immune response is fed back to the immune signaling network, modulating its activity and limiting the fitness cost of unnecessary immune responses.