Dataset Information

Quantification of high-specificity cyclic diguanylate signaling.

ABSTRACT: Cyclic di-GMP (c-di-GMP) is a second messenger molecule that regulates the transition between sessile and motile lifestyles in bacteria. Bacteria often encode multiple diguanylate cyclase (DGC) and phosphodiesterase (PDE) enzymes that produce and degrade c-di-GMP, respectively. Because of multiple inputs into the c-di-GMP-signaling network, it is unclear whether this system functions via high or low specificity. High-specificity signaling is characterized by individual DGCs or PDEs that are specifically associated with downstream c-di-GMP-mediated responses. In contrast, low-specificity signaling is characterized by DGCs or PDEs that modulate a general signal pool, which, in turn, controls a global c-di-GMP-mediated response. To determine whether c-di-GMP functions via high or low specificity in Vibrio cholerae, we correlated the in vivo c-di-GMP concentration generated by seven DGCs, each expressed at eight different levels, to the c-di-GMP-mediated induction of biofilm formation and transcription. There was no correlation between total intracellular c-di-GMP levels and biofilm formation or gene expression when considering all states. However, individual DGCs showed a significant correlation between c-di-GMP production and c-di-GMP-mediated responses. Moreover, the rate of phenotypic change versus c-di-GMP concentration was significantly different between DGCs, suggesting that bacteria can optimize phenotypic output to c-di-GMP levels via expression or activation of specific DGCs. Our results conclusively demonstrate that c-di-GMP does not function via a simple, low-specificity signaling pathway in V. cholerae.

SUBMITTER: Massie JP

PROVIDER: S-EPMC3411991 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Cyclic dimeric GMP (c-di-GMP) is a universal second messenger in bacteria. A large number of c-di-GMP-related diguanylate cyclases (DGCs), phosphodiesterases (PDEs), and effectors are responsible for the complexity and dynamics of c-di-GMP signaling. Some of these components employ various methods to avoid undesired cross talk to maintain signaling specificity. The synthesis of the antibiotic HSAF (heat-stable antifungal factor) in Lysobacter enzymogenes is regulated by a specific c-di-GMP signaling pathway that includes a PDE, LchP, and a c-di-GMP effector, Clp (also a transcriptional regulator). In the present study, from among 19 DGCs, we identified a diguanylate cyclase, LchD, that participates in this pathway. Subsequent investigation indicates that LchD and LchP physically interact and that the catalytic center of LchD is required for both the formation of the LchD-LchP complex and HSAF production. All the detected phenotypes support that LchD and LchP display local c-di-GMP signaling to regulate HSAF biosynthesis. Although direct evidence is lacking, our investigation, which shows that the interaction between a DGC and a PDE maintains the specificity of c-di-GMP signaling, suggests the possibility of the existence of local c-di-GMP pools in bacteria. IMPORTANCE Cyclic dimeric GMP (c-di-GMP) is a universal second messenger in bacteria. The signaling of c-di-GMP is complex and dynamic, and it is mediated by a large number of components, including c-di-GMP synthases (diguanylate cyclases [DGCs]), c-di-GMP-degrading enzymes (phosphodiesterases [PDEs]), and c-di-GMP effectors. These components deploy various methods to avoid undesired cross talk to maintain signaling specificity. In the present study, we identified a DGC that interacted with a PDE to specifically regulate antibiotic biosynthesis in L. enzymogenes. We provide direct evidence to show that the DGC and PDE form a complex and also indirect evidence to argue that they may balance a local c-di-GMP pool to control antibiotic production. These results represent an important finding regarding the mechanism of a DGC and PDE pair to control the expression of specific c-di-GMP signaling pathways.

Project description:In this work, we used our recently developed method Spec-seq to characterize the binding specificity of Glucocorticoid receptor in vitro. This GR Spec-seq experiment has been run twice separately (Dec 2014 and Mar 2015) with different library compositions. The basic workflow is the same as our previous work for lac repressor published in Genetics 198.3 (2014): 1329-1343. Recombinant human GR protein was used to facilitate in vitro DNA-binding and separation experiments. Bound and Unbound DNA fragments were separated in EMSA gels, purified, barcoded for further Illumina sequencing. An initial experiment was performed using the putative consensus sequence: AGAACA GGG TGTTCT; randomized library 1: AGAACN NSN NGTTCT [diversity =512]; randomized library 2: AGAANN GGG NNNTCT [diversity = 1024]; randomized library 3: AGAACA GGG TGNNNN [diversity =256]; randomized library 4: AGAACA GGGC NNNTCT [diversity = 64]. The initial total library diversity was ~1853 with a library composition of 10% positive control sequence + randomized libraries 1-4 + 5% negative control sequence. A 5th library containing 2304 sequences based on DDNACW KKN KGTTCT, where D="not C", N="any base", W="A or T" and K="G or T" was subsequently prepared and analyzed using similar ratios of control sequences. Binding conditions for EMSA were 100ng FAM-labelled dsDNA+ 0/0.5/1/2/4uM GR DBD protein for each lane, 1X NEB buffer 4. GR DBD was prepared as previously described. The EMSA was performed using a 9% 33:1 acrylamide gel and TB buffer, and was run at 200V for 30mins @ 0 degrees C. The 2uM protein lane used for final sequencing. Bound/unbound fractions resulting from EMSA of these libraries and conditions were used to generate PWMs as described. The GR PWM that was generated through this analysis was used to define relative binding energies using the patser program (35), which can be accessed online at (http://stormo.wustl.edu/consensus/cgi-bin/Server/Interface/patser.cgi ). Derived binding affinities are proportional to the inverse of the natural log of the calculated energies.

Dataset Information

Quantification of high-specificity cyclic diguanylate signaling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets