scholarly journals Strategies for Multiplexed Biosensor Imaging to Study Intracellular Signaling Networks

2021 ◽  
pp. 1-20
Author(s):  
Jeremiah Keyes ◽  
Sohum Mehta ◽  
Jin Zhang
Keyword(s):  
Intracellular Signaling ◽  
Signaling Networks

Synaptic Plasticity In Vitro and In Silico: Insights into an Intracellular Signaling Maze

Physiology ◽  
2006 ◽  
Vol 21 (4) ◽  
pp. 289-296 ◽  
Author(s):  
Sriram M. Ajay ◽  
Upinder S. Bhalla
Keyword(s):  
Experimental Data ◽  
Synaptic Plasticity ◽  
Neuronal Activity ◽  
In Silico ◽  
Intracellular Signaling ◽  
Signaling Networks ◽  
Functional Roles ◽  
Current State ◽  
History Of

Synaptic plasticity provides a record of neuronal activity and is a likely basis for memory. The early apparent simplicity of the process of synaptic plasticity has been lost in a flood of experimental data that now implicates some 200 signaling molecules in cellular memory. It is now clear that these signaling networks perform surprisingly sophisticated cellular decisions that weigh factors such as input patterns, location of stimulus, history of activity, and context. Computer models have followed experiments into this maze of molecular detail, often matching closely with their experimental counterparts, but perhaps losing simplicity in the process. Here, we suggest that the merger of models and experiment have begun to restore the earlier simplicity by outlining a few key functional roles for signaling networks in synaptic plasticity. In this review, we discuss the current state of understanding of synaptic plasticity in terms of models and experiments.

Modeling the Nonlinear Dynamics of Intracellular Signaling Networks

BIO-PROTOCOL ◽  
2021 ◽  
Vol 11 (14) ◽  
Author(s):  
Oleksii Rukhlenko ◽  
Boris Kholodenko
Keyword(s):  
Nonlinear Dynamics ◽  
Intracellular Signaling ◽  
Signaling Networks

scholarly journals Subcellular optogenetic activation of Cdc42 controls local and distal signaling to drive immune cell migration

2016 ◽  
Vol 27 (9) ◽  
pp. 1442-1450 ◽  
Author(s):  
Patrick R. O’Neill ◽  
Vani Kalyanaraman ◽  
N. Gautam
Keyword(s):  
Cell Migration ◽  
Intracellular Signaling ◽  
Immune Cell ◽  
Leading Edge ◽  
Signaling Networks ◽  
Membrane Protrusions ◽  
A Cell ◽  
Immune Cell Migration ◽  
Directional Cell Migration ◽  
Rhoa Signaling

Migratory immune cells use intracellular signaling networks to generate and orient spatially polarized responses to extracellular cues. The monomeric G protein Cdc42 is believed to play an important role in controlling the polarized responses, but it has been difficult to determine directly the consequences of localized Cdc42 activation within an immune cell. Here we used subcellular optogenetics to determine how Cdc42 activation at one side of a cell affects both cell behavior and dynamic molecular responses throughout the cell. We found that localized Cdc42 activation is sufficient to generate polarized signaling and directional cell migration. The optically activated region becomes the leading edge of the cell, with Cdc42 activating Rac and generating membrane protrusions driven by the actin cytoskeleton. Cdc42 also exerts long-range effects that cause myosin accumulation at the opposite side of the cell and actomyosin-mediated retraction of the cell rear. This process requires the RhoA-activated kinase ROCK, suggesting that Cdc42 activation at one side of a cell triggers increased RhoA signaling at the opposite side. Our results demonstrate how dynamic, subcellular perturbation of an individual signaling protein can help to determine its role in controlling polarized cellular responses.

scholarly journals Exploring Extreme Signaling Failures in Intracellular Molecular Networks

2021 ◽  
Author(s):  
Mustafa Ozen ◽  
Effat S. Emamian ◽  
Ali Abdi
Keyword(s):  
Intracellular Signaling ◽  
Molecular Mechanisms ◽  
Incorrect Response ◽  
Complex Trait ◽  
Molecular Networks ◽  
Signaling Networks ◽  
Initial Increase ◽  
Network Failure ◽  
Human Disorders ◽  
Cell Signaling Networks

AbstractDeveloping novel methods for the analysis of intracellular signaling networks is essential for understanding interconnected biological processes that underlie complex human disorders. A fundamental goal of this research is to quantify the vulnerability of a signaling network to the dysfunction of one or multiple molecules, when the dysfunction is defined as an incorrect response to the input signals. In this study, we propose an efficient algorithm to identify the extreme signaling failures that can induce the most detrimental impact on the physiological function of a molecular network. The algorithm basically finds the molecules, or groups of molecules, with the maximum vulnerability, i.e., the highest probability of causing the network failure, when they are dysfunctional. We propose another algorithm that efficiently accounts for signaling feedbacks in this analysis. The algorithms are tested on two experimentally verified ERBB and T cell signaling networks. Surprisingly, results reveal that as the number of concurrently dysfunctional molecules increases, the maximum vulnerability values quickly reach to a plateau following an initial increase. This suggests the specificity of vulnerable molecule (s) involved, as a specific number of faulty molecules cause the most detrimental damage to the function of the network. Increasing a random number of simultaneously faulty molecules does not further deteriorate the function of the network. Such a group of specific molecules whose dysfunction causes the extreme signaling failures can better elucidate the molecular mechanisms underlying the pathogenesis of complex trait disorders, and can offer new insights for the development of novel therapeutics.

scholarly journals The World of Cyclic Dinucleotides in Bacterial Behavior

Molecules ◽  
2020 ◽  
Vol 25 (10) ◽  
pp. 2462 ◽  
Author(s):  
Aline Dias da Purificação ◽  
Nathalia Marins de Azevedo ◽  
Gabriel Guarany de Araujo ◽  
Robson Francisco de Souza ◽  
Cristiane Rodrigues Guzzo
Keyword(s):  
Intracellular Signaling ◽  
Three Dimensional ◽  
Structural Data ◽  
Research Topic ◽  
Signaling Networks ◽  
Bacterial Cells ◽  
Signaling Systems ◽  
The World ◽  
Second Messenger Systems ◽  
Cyclic Dinucleotides

The regulation of multiple bacterial phenotypes was found to depend on different cyclic dinucleotides (CDNs) that constitute intracellular signaling second messenger systems. Most notably, c-di-GMP, along with proteins related to its synthesis, sensing, and degradation, was identified as playing a central role in the switching from biofilm to planktonic modes of growth. Recently, this research topic has been under expansion, with the discoveries of new CDNs, novel classes of CDN receptors, and the numerous functions regulated by these molecules. In this review, we comprehensively describe the three main bacterial enzymes involved in the synthesis of c-di-GMP, c-di-AMP, and cGAMP focusing on description of their three-dimensional structures and their structural similarities with other protein families, as well as the essential residues for catalysis. The diversity of CDN receptors is described in detail along with the residues important for the interaction with the ligand. Interestingly, genomic data strongly suggest that there is a tendency for bacterial cells to use both c-di-AMP and c-di-GMP signaling networks simultaneously, raising the question of whether there is crosstalk between different signaling systems. In summary, the large amount of sequence and structural data available allows a broad view of the complexity and the importance of these CDNs in the regulation of different bacterial behaviors. Nevertheless, how cells coordinate the different CDN signaling networks to ensure adaptation to changing environmental conditions is still open for much further exploration.

scholarly journals Querying quantitative logic models (Q2LM) to study intracellular signaling networks and cell-cytokine interactions

2012 ◽  
Vol 7 (3) ◽  
pp. 374-386 ◽  
Author(s):  
Melody K. Morris ◽  
Zachary Shriver ◽  
Ram Sasisekharan ◽  
Douglas A. Lauffenburger
Keyword(s):  
Intracellular Signaling ◽  
Signaling Networks ◽  
Logic Models ◽  
Cytokine Interactions
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