Pseudomonas syringae Virulence Regulatory Network construction
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA575032 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pseudomonas syringae, a Gram-negative plant pathogen, infects more than 50 crops with its type III secretion system (T3SS) and causes severe economic losses around the world. Although the mechanisms of virulence-associated regulators of P. syringae T3SS have been studied for decades, the crosstalk and network underlying these regulators are still elusive. Previously, we have individually studied a group of T3SS regulators, including AefR, HrpS, and RhpRS. In the present study, we found 4 new T3SS regulator genes (envZ, ompR, tsiS and phoQ) via transposon-mediated mutagenesis. Two-component systems EnvZ and TsiS natively regulate T3SS. In order to uncover the crosstalk between 16 virulence-associated regulators, (including AefR, AlgU, CvsR, GacA, HrpL, HrpR, HrpS, MgrA, OmpR, PhoP, PilR, PsrA, RhpR, RpoN, TsiR and Vfr) in P. syringae, we mapped an intricate network named PSVnet (Pseudomonas syringae Virulence Regulatory Network) by combining differentially expression genes in RNA-seq and binding loci in ChIP-seq of all regulators.
2021-03-29 | GSE138204 | GEO
Project description:The model Gram-negative plant pathogen Pseudomonas syringae utilizes hundreds of transcription factors (TFs) to manipulate its functional processes, including virulence and metabolic pathways to control its infection to host plants. Although the molecular mechanisms of regulators have been studied for decades, the comprehensive understanding throughout the genome-wide TFs in P. syringae remains uncertain. Here, we set out to investigate the binding characteristics of 170 of all 301 annotated TFs using ChIP-seq. To further explore and delineate the physiological and pathogenic roles of TFs in P. syringae, we integrated both the 118 different position weight matrix (PWM) motifs of 100 TFs analyzed by HT-SELEX previously and more than 26000 direct interactions of 170 TFs here, mapped the hierarchical regulatory network not only between TFs but also within TFs and target genes. We next investigated the co-association statistics across the 26000 interactions and identified the high co_x0002_association scores of bottom TFs in the hierarchical network. The evolution analysis revealed the functional variability of TFs between different pathovars of P. syringae. Topological modularity network of all ChIPed TFs and their targets exhibited the various biological functions. Overall, our work provided the global transcriptional regulatory network of genome-wide TFs in P. syringae, including 35 virulence_x0002_associated and metabolic TFs, which promoted the development of effective treatment and prevention strategies for the related infectious diseases.
2024-06-21 | GSE247395 | GEO
Project description:Construction of a dynamic gene regulatory network required for cellular reprogramming
| PRJNA471847 | ENA
Project description:Bacteria relies on two-component systems (TCSs) to respond to a wide range of stimuli or environmental cues for their survival and virulence. However, the functions and synergistic actions of TCSs in genomic level remains unclear. Here, in model phytopathogen Pseudomonas syringae, by integrating multiomics data, we developed a network-based PSTCSome (Pseudomonas syringae two-component systems regulome) to identify functions and crosstalk among global TCSs under either virulence suppressing (King’s B medium, KB) or activating conditions (minimal medium, MM). Transcriptome profiling identifies 2,099 differentially expressed genes (DEGs) in KB and 1,250 DEGs in MM, while ChIP-seq identifies 1,628 target genes across the whole genome. The multiomics results are applied to perform not only gene ontology (GO) analysis to detect the biological processes that TCSs involved in, but also subnetworks and co-expression analysis of 8 virulence-related pathways to decipher the TCSs regulated pathogenic behaviors. The following phenotypic experiments newly confirmed 8 TCSs that regulates type III secretion system (T3SS) (PSPPH_0253, PSPPH_2606, PSPPH_4416, and PSPPH_4451) and surface attachment (PSPPH_0253, PSPPH_3041, PSPPH_3473, PSPPH_3736, PSPPH_4001). We then compute 259 functional genes in KB and 161 in MM for those cluster TCSs. Analysis of cluster TCSs regulons led to the identification of either novel functions or 2 master regulatory TCSs (RhpS/RhpR and PSPPH_4827/4828) toward virulence. Our results show that TCSs in P. syringae dynamically adjust their regulatory networks by sensing the external environment, and then switch bacteria between pathogenic and non-pathogenic states in a sophisticated way. Furthermore, we present an online platform of PSTCSome to facilitate updating, network visualization and user-customized analyses.
2022-10-04 | GSE148104 | GEO
Project description:Expression profiles of 22 reference Arabidopsis immunity mutants were collected using the Arabidopsis Pathoarray 464_001 (GPL3638) in order to build a network model predicting the Arabidopsis immune signaling network. Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. Here, we demonstrate that use of mRNA profiling to collect and analyze detailed descriptions of changes in the network state resulting from specific network perturbations is a powerful and economical strategy to elucidate regulatory relationships among the components of a complex signaling network. Specifically, we studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with the Pto DC3000 AvrRpt2 and used as detailed descriptions of the network states resulting from specific genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting network model accurately predicted 22 of 23 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; (ii) negative regulatory relationships are common between signaling sectors. One case of a novel negative regulatory relationship, between the early microbe-associated molecular pattern (MAMP)-activated sector and the salicylic acid (SA)-mediated sector, was further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector-switching" network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. Keywords: Responses of reference Arabidopsis immunity mutants to Pseudomonas syringae pv. tomato DC3000 carrying avrRpt2 This experiment consists of two (group00) or three (group01-04) biological replicates of each genotype (total 25 genotypes [3 are multiple mutants, which were removed for the network modeling, but were used for normalization]). For each genotype, two leaves per plant were pooled from three pots to prepare total RNA.
2010-07-22 | E-GEOD-19663 | biostudies-arrayexpress
Project description:The CovR regulatory network drives the evolution of Group B Streptococcus virulence
| PRJNA663852 | ENA
Project description:Pseudomonas syringae pv. aptata is a member of the sugar beet pathobiome and the causative agent of leaf spot disease. Like many pathogenic bacteria, P. syringae relies on the secretion of toxins, which manipulate host-pathogen interactions, to establish and maintain an infection. This study analyzes the secretome of six pathogenic P. syringae pv. aptata strains with different defined virulence capacities in order to identify common and strain-specific features, and correlate the secretome with disease outcome. All strains show a high type III secretion system (T3SS) and type VI secretion system (T6SS) activity under apoplast-like conditions mimicking the infection. Surprisingly, we found that low pathogenic strains show a higher secretion of most T3SS substrates (19 of the 23 detected effectors and accessory harpin proteins), whereas a distinct subgroup of four effectors is exclusively secreted in medium and high pathogenic strains. Similarly, we detected two T6SS secretion patterns: while one set of proteins was highly secreted in all strains, another subset consisting of known T6SS substrates and previously uncharacterized proteins with a highly similar secretion pattern was exclusively secreted in medium and high virulence strains. Taken together, our data shows that P. syringae pathogenicity is correlated with the repertoire and fine-tuning of effector secretion and indicates distinct strategies for establishing virulence of P. syringae pv. aptata in plants.
2023-06-02 | PXD040715 | Pride
Project description:We reconstructed the Virulence Regulatory Network (VRN) of R. solanacearum strain GMI1000 by collecting bibliographical information based on genetic and genomic studies, including three transcriptomic studies. The reconstructed R. solanacearum VRN comprises 712 genes including 29 genes coding for transcription factors and 34 proteins involved in signal transduction. This VRN perceives 86 signals and controls the expression of 606 genes.
2023-11-10 | MODEL1710170000 | BioModels
Project description:Bacteria use a variety of mechanisms, such as two‐component regulatory systems (TCSs), to rapidly sense and respond to distinct conditions and signals in their host organisms. For example, a type III secretion system (T3SS) is the key determinant of the virulence of the model plant pathogen Pseudomonas syringae and contains the TCS RhpRS as a key regulator. However, the signal sensed by RhpRS remains unknown. We found that RhpRS directly senses plant-generated polyphenols and responds by switching off P. syringae T3SS via crosstalk with alternative histidine kinases. Through a chemical screen, we identified three natural polyphenols (tannic acid, 1,2,3,4,6-pentagalloylglucose and epigallocatechin gallate) that induced the expression of the rhpRS operon in a RhpS-dependent manner.
2021-09-20 | GSE160492 | GEO
Project description:The generation of induced Pluripotent Stem Cells (iPSCs) from somatic cells provides an excellent example to study mechanisms of transcription factor-induced global alterations of the genome and the epigenome. Here, we have investigated the early transcriptional events of cellular reprogramming triggered by the co-expression of OSKM (Oct4, Sox2, Klf4 and c-Myc) in Mouse Embryonic Fibroblasts (MEFs) and mouse Hepatocytes (mHeps) and identified a novel gene regulatory network composed of 9 Transcriptional Regulators (TRs), which are directly targeted by OSKM. Functional studies using single and double shRNA knock-downs of any of these TRs caused disruption of the network and dramatic reductions in reprogramming efficiency, demonstrating that this novel gene regulatory network is essential for the induction and establishment of pluripotency. We demonstrate that that the stochastic co-expression of the 9TRs network components occurs in a remarkably small number of cells approximating the percentage of reprogrammed cells as the result of dynamic molecular events. Thus, the early binding patterns of OSKM and the subsequent stochastic co-expression of pivotal TRs in subpopulations of cells steer the reconstruction of a gene regulatory network crucial for the generation of iPSCs. In this study, we show that OSKM trigger the gradual establishment of the stemness phenotype by inducing the stochastic reconstruction of a novel 9TRs gene regulatory network that guides the acquisition to pluripotency.
2019-02-14 | GSE114581 | GEO