Pseudomonas syringae
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA15584 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The independent data acquisition (DIA) approach, which is a proteomic quantitative analysis method, was applied to quantitatively trace coronatine production and proteomic changes in Pseudomonas syringae pv. tomato DC3000 under different FeCl3 culture conditions.Coronatine (COR) is a new type of plant growth regulator that is produced by Pseudomonas syringae pathovars and plays an important role in modulating plant growth, development, and tolerance to multiple stresses.
2020-03-23 | PXD018139 |
Project description:Comparative Genomics of Pseudomonas syringae
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Project description:Pseudomonas syringae pathovars phaseolicola, actinidiae genome sequencing and assembly
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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: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:Pseudomonas syringae pv. actinidiae biovar 6 (Psa6) is a causal agent of kiwifruit bacterial canker and is a unique plant pathogenic bacterium, producing two types of phytotoxins, coronatine and phaseolotoxin. We investigated the expression behavior of virulent genes of Psa6 under various culture conditions.
2020-05-02 | GSE149743 | GEO
Project description:Blue light perception by epiphytic Pseudomonas syringae drives chemoreceptor expression enabling efficient plant infection
2020-10-31 | GSE152188 | GEO
Project description:We used three different strains of Pseudomonas syringae pv tomato DC3000 to investigate systemic responses to infection in Arabidopsis and the development of SAR. Wildtype DC3000, the hrpA mutant and DC3000 carrying the avirulence gene avrRpm1 were syringe infiltrated into 4-week-old plants at a concentration of 10e8 cfu/ml. At least 5 leaves per plant were infiltrated and at least 10 plants were pooled for each sample. Systemic, uninfected tissue was then harvested at 8, 12 and 21h after inoculation. Three independent experiments were carried out to give three biological replicates for each timepoint.
2009-12-10 | GSE19264 | 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:We used three different strains of Pseudomonas syringae pv tomato DC3000 to investigate systemic responses to infection in Arabidopsis and the development of SAR. Wildtype DC3000, the hrpA mutant and DC3000 carrying the avirulence gene avrRpm1 were syringe infiltrated into 4-week-old plants at a concentration of 10e8 cfu/ml. At least 5 leaves per plant were infiltrated and at least 10 plants were pooled for each sample. Systemic, uninfected tissue was then harvested at 8, 12 and 21h after inoculation. Three independent experiments were carried out to give three biological replicates for each timepoint. 27 samples were used in this experiment.
2009-12-09 | E-GEOD-19264 | biostudies-arrayexpress