Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Peer pressure from a Proteus mirabilis self-recognition system controls participation in cooperative swarm motility

ABSTRACT: Peer pressure from a Proteus mirabilis self-recognition system controls participation in cooperative swarm motility

PROVIDER: PRJNA544269 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR9109010.fastq.gz	Fastqsanger.gz
	SRR9109011.fastq.gz	Fastqsanger.gz
	SRR9109012.fastq.gz	Fastqsanger.gz
	SRR9109013.fastq.gz	Fastqsanger.gz
	SRR9109014.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 12

Similar Datasets

Peer pressure from a Proteus mirabilis self-recognition system controls participation in cooperative swarm motility

Project description:A resident of animal intestines, Proteus mirabilis is a major cause of catheter-associated urinary tract infections and can cause recurrent, persistent infections. Swarming, which is a collective behavior that promotes centimeter-scale population migration, is implicated in colonization of bladders and kidneys. A regulatory factor of swarming is kin recognition, which involves the transfer of a self-identity protein from one cell into a physically adjacent neighboring cell. However, how kin recognition regulates swarming was previously unclear. We have now shown a mechanism linking kin recognition, swarm migration, and antibiotics tolerance: cells induce a transient antibiotics-tolerant, persister-like state in adjacent non-identical cells which in turn prevents non-identical cells from continuing to participate in collective swarming. These affected non-identical cells continue to exhibit large-scale gene expression suggesting an active shift into a different expression state. These data provide two key insights for the field. First, kin recognition can be a regulatory mechanism that acts with spatial and temporal precision. Second, induction into an antibiotics-tolerant state, instead of occurring stochastically, can be physically and spatially regulated by neighboring cells. These insights highlight the importance of further developing four-dimensional (time and X-, Y-, Z-axes) model systems for interrogating cell-cell signaling and control in microbial populations.

2019-05-23 | GSE131647 | GEO

Transcriptomic analysis of swarm motility phenotype of Salmonella enterica serovar Typhimurium mutant defective in periplasmic glucan synthesis

Project description:Movement of food-borne pathogens on moist surfaces enables them to migrate towards more favorable niches and facilitate their survival for extended periods of time. Salmonella enterica serovar Typhimurium mutants defective in OPG synthesis are unable to exhibit motility on moist surfaces (swarming) however their mobility in liquid (swim motility) remains unaffected. In order to understand the role of OPG in swarm motility, transcriptomic analysis was performed using cells growing on a moist agar surface. In the opgGH-deletion mutant, lack of OPG significantly altered transcription of 1039 genes out of total 4712 genes (22%). Introduction of a plasmid borne copy of opgGH into the opgGH-deletion mutant restored normal expression of all but 30 genes, indicating a wide-range influence of OPG on gene expression under the swarm motility condition. Major pathways that were differentially-expressed in opgGH mutants were motility, virulence and invasion, and genes related to the secondary messenger molecule, cyclic di-GMP. These observations provide insights and help explain the pleiotropic nature of OPG mutants such as sub-optimal virulence and competitive organ colonization in mice, biofilm formation, and sensitivity towards detergent stress.

2019-08-31 | GSE86311 | GEO

Peer pressure from a Proteus mirabilis self-recognition system controls participation in cooperative swarm motility.

Project description:Colonies of the opportunistic pathogen Proteus mirabilis can distinguish self from non-self: in swarming colonies of two different strains, one strain excludes the other from the expanding colony edge. Predominant models characterize bacterial kin discrimination as immediate antagonism towards non-kin cells, typically through delivery of toxin effector molecules from one cell into its neighbor. Upon effector delivery, receiving cells must either neutralize it by presenting a cognate anti-toxin as would a clonal sibling, or suffer cell death or irreversible growth inhibition as would a non-kin cell. Here we expand this paradigm to explain the non-lethal Ids self-recognition system, which stops access to a social behavior in P. mirabilis by selectively and transiently inducing non-self cells into a growth-arrested lifestyle incompatible with cooperative swarming. This state is characterized by reduced expression of genes associated with protein synthesis, virulence, and motility, and also causes non-self cells to tolerate previously lethal concentrations of antibiotics. We show that temporary activation of the stringent response is necessary for entry into this state, ultimately resulting in the iterative exclusion of non-self cells as a swarm colony migrates outwards. These data clarify the intricate connection between non-lethal recognition and the lifecycle of P. mirabilis swarm colonies.

| S-EPMC6682164 | biostudies-literature

5-aza-2-deoxycytidine treatment of Swarm rat chondrosarcoma cells

Project description:The puropose of this experiment was to identify gene expression changes that result from 5-aza-2-deoxycytidine induced DNA demethylation of Swarm rat chondrosarcoma cells. The gene expression profiles of untreated Swarm rat chondrosarcoma cells were compared to the gene expression profiles of Swarm rat chondrosarcoma cells that were treated for 5 passages with a low dose of 5-aza-2-deoxycytidine (0.1uM). Five chip study. For these experiments, microarray was carried out on untreated (control) Swarm rat chondrosarcoma cells (3 biological replicates), and microarray was also carried out on Swarm rat chondrosarcoma cells treated with 5-aza-2-deoxycytidine (2 biological replicates).

2010-08-06 | E-GEOD-17598 | biostudies-arrayexpress

5-aza-2-deoxycytidine treatment of Swarm rat chondrosarcoma cells

2010-08-06 | GSE17598 | GEO

Swarmer Cell Development of the Bacterium Proteus mirabilis Requires the Conserved Enterobacterial Common Antigen Biosynthesis Gene rffG

Project description:Individual cells of the bacterium Proteus mirabilis can elongate up to 40- fold on surfaces before engaging in a cooperative surface-based motility termed swarming. How cells regulate this dramatic morphological remodeling remains an open question. In this paper, we move forward the understanding of this regulation by demonstrating that P. mirabilis requires the gene rffG for swarmer cell elongation and subsequent swarm motility.

2018-07-04 | GSE116587 | GEO

Transcriptomic analysis of swarm motility phenotype of Salmonella enterica serovar Typhimurium mutant defective in periplasmic glucan synthesis

Project description:Transcriptomic analysis of swarm motility phenotype of Salmonella enterica serovar Typhimurium mutant defective in periplasmic glucan synthesis

| PRJNA341384 | ENA

ddRADseq analysis of a hybrid swarm

Project description:Fine scale description of hybrid classes in a hybrid swarm

| PRJEB24320 | ENA

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

Project description:The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

| S-EPMC4433345 | biostudies-literature

The structure and target identification of the tandem RRM of yeast Npl3 bound to RNA reveal a cooperative sequence-specific recognition and an RNA chaperone role in splicing

Project description:The conserved SR-like protein Npl3 promotes the splicing of diverse pre-mRNAs. However, the RNA sequence(s) recognized by the RNA Recognition Motifs (RRM1 & RRM2) of Npl3 during the splicing reaction remain elusive. Here, we developed a split-iCRAC approach in vivo to determine the consensus sequence bound to each RRM in yeast. High-resolution NMR structures show that RRM2 recognizes a 5´-GNGG-3´ motif leading to an unusual mille-feuille topology. In addition, our data indicate a non-specific interaction of the RS domain with RNA. These structures reveal how RRM1 preferentially interacts with a CC-dinucleotide upstream of this motif, and how the inter-RRM linker and the region C-terminal to RRM2 contributes to cooperative RNA-binding. Structure-guided studies show that Npl3 genetically interacts with U2 snRNP specific factors and we provide evidence that Npl3 melts U2 snRNA stem-loop I, a prerequisite for U2/U6 duplex formation within the catalytic centre of the Bact spliceosomal complex. Our findings provide a mechanistic role for Npl3 during spliceosome active site formation.

2022-12-01 | E-MTAB-11736 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data