The ubiquitous localization of these mitochondrial transcripts in the nucleus suggests that they are new players in the mitochondrial-nuclear communication pathway or retrograde signaling. Down regulation of the ASncmtRNAs seems to be an important step on neoplastic transformation and cancer progression.
SUMMARY
The dynamic nanoscale organization of cell surface receptors plays an important role in signaling. We determine this organization and its relation to activation of VEGF receptor-2 (VEGFR-2), a critical receptor tyrosine kinase in endothelial cells (ECs), by combining single-molecule imaging of endogenous VEGFR-2 in live ECs with multiscale computational analysis. We find that surface VEGFR-2 can be mobile or exhibit restricted mobility and be monomeric or non-monomeric, with a complex interplay between the two. This basal heterogeneity results in heterogeneity in the sequence of steps leading to VEGFR-2 activation by VEGF. Specifically, we find that VEGF can bind to monomeric and non-monomeric VEGFR-2 and that, when binding to monomeric VEGFR-2, its effect on dimerization depends on the mobility of VEGFR-2. Our study highlights the dynamic and heterogeneous nature of cell surface receptor organization and the need for multiscale, single-molecule-based analysis to determine its relationship to receptor activation and signaling.
Within systems biology there is an increasing interest in the stochastic behavior of genetic and biochemical reaction networks. An appropriate stochastic description is provided by the chemical master equation, which represents a continuous time Markov chain (CTMC). In this paper we consider the stochastic properties of a toggle switch, involving a protein compound (E2Fs and Myc) and a miRNA cluster (miR-17-92), known to control the eukaryotic cell cycle and possibly involved in oncogenesis, recently proposed in the literature within a deterministic framework. Due to the inherent stochasticity of biochemical processes and the small number of molecules involved, the stochastic approach should be more correct in describing the real system: we study the agreement between the two approaches by exploring the system parameter space. We address the problem by proposing a simplified version of the model that allows analytical treatment, and by performing numerical simulations for the full model. We observed optimal agreement between the stochastic and the deterministic description of the circuit in a large range of parameters, but some substantial differences arise in at least two cases: (1) when the deterministic system is in the proximity of a transition from a monostable to a bistable configuration, and (2) when bistability (in the deterministic system) is "masked" in the stochastic system by the distribution tails. The approach provides interesting estimates of the optimal number of molecules involved in the toggle switch. Our discussion of the points of strengths, potentiality and weakness of the chemical master equation in systems biology and the differences with respect to deterministic modeling are leveraged in order to provide useful advice for both the bioinformatician and the theoretical scientist.
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