Dataset Information

A complex interplay between nitric oxide, quorum sensing and a unique secondary metabolite tundrenone constitutes hypoxia response in Methylobacter

ABSTRACT: Methylobacter species, members of the Methylococcales, have recently emerged as some of the globally widespread, cosmopolitan species, appearing to play a key role in consumption of methane in a variety of environments and across gradients of dioxygen tensions. We approached the question of how Methylobacter copes with low dioxygen partial pressures that it encounters in its natural habitats, via laboratory manipulation. Through comparative transcriptomics of cultures grown under high dioxygen partial pressure and cultures starved for dioxygen, we identified a gene cluster encoding a hybrid cluster protein along with sensing and regulatory functions. Through mutant analysis we demonstrated that this gene cluster is involved in both oxidative and nitrosative stress responses and in NO reduction, while being responsive to NO, likely through direct sensing. Through additional transcriptomic analyses, we further uncovered a complex interconnection between the NO-mediated stress response and quorum sensing in turn controlling synthesis of the secondary metabolite tundrenone, these two systems being inversely regulated. Some of the key methylotrophy functions, such as the two alternative methanol dehydrogenases seem to be parts of the stress response regulatory cascade. One intriguing scenario that emerged from our analyses is that the main role of the respiratory denitrification pathway may be in producing the signaling molecule, NO, in response to hypoxia, rather than in serving as an energy-generating pathway. This novel and complex hypoxia stress response system is unique to Methylobacter tundripaludum, and it may play a role in the environmental fitness of these organisms and in their cosmopolitan environmental distribution.

ORGANISM(S): Methylobacter tundripaludum 31/32 Methylobacter tundripaludum 21/22

PROVIDER: GSE138276 | GEO | 2019/10/01

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:This a model from the article: Stress-specific response of the p53-Mdm2 feedback loop Alexander Hunziker, Mogens H Jensen and Sandeep Krishna BMC Systems Biology 2010, Jul 12;4(1):94 20624280, Abstract: ABSTRACT: BACKGROUND: The p53 signalling pathway has hundreds of inputs and outputs. It can trigger cellular senescence, cell-cycle arrest and apoptosis in response to diverse stress conditions, including DNA damage, hypoxia and nutrient deprivation. Signals from all these inputs are channeled through a single node, the transcription factor p53. Yet, the pathway is flexible enough to produce different downstream gene expression patterns in response to different stresses. RESULTS: We construct a mathematical model of the negative feedback loop involving p53 and its inhibitor, Mdm2, at the core of this pathway, and use it to examine the effect of different stresses that trigger p53. In response to DNA damage, hypoxia, etc., the model exhibits a wide variety of specific output behaviour -- steady states with low or high levels of p53 and Mdm2, as well as spiky oscillations with low or high average p53 levels. CONCLUSIONS: We show that even a simple negative feedback loop is capable of exhibiting the kind of flexible stress-specific response observed in the p53 system. Further, our model provides a framework for predicting the differences in p53 response to different stresses and single nucleotide polymorphisms. The parameters of the model corresponds to the resting state, with delta = 11hr-1, gamma = 0.2hr-1, kt = 0.03nM-1hr-1 and kf = 5000nM-1hr-1. To simulate different stress conditions as in figure 2A (also look at the curation figure of this model) of the reference publication, the above parameter should be changed. The parameter values corresponding to different stress conditions are shown in the following table. Stress Condition/Parameter delta gamma kt kf Nutlin 11hr-1 0.2hr-1 0.03nM-1hr-1 500nM-1hr-1 Oncogene 2hr-1 0.2hr-1 0.03nM-1hr-1 5000nM-1hr-1 DNA damage 2hr-1 0.5hr-1 0.03nM-1hr-1 2500nM-1hr-1 Hypoxia 2hr-1 0.2hr-1 0.01nM-1hr-1 5000nM-1hr-1 This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2011 The BioModels.net Team.For more information see the terms of use.To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Dataset Information

A complex interplay between nitric oxide, quorum sensing and a unique secondary metabolite tundrenone constitutes hypoxia response in Methylobacter

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets