198,962 research outputs found
The macroscopic effects of microscopic heterogeneity
Over the past decade, advances in super-resolution microscopy and
particle-based modeling have driven an intense interest in investigating
spatial heterogeneity at the level of single molecules in cells. Remarkably, it
is becoming clear that spatiotemporal correlations between just a few molecules
can have profound effects on the signaling behavior of the entire cell. While
such correlations are often explicitly imposed by molecular structures such as
rafts, clusters, or scaffolds, they also arise intrinsically, due strictly to
the small numbers of molecules involved, the finite speed of diffusion, and the
effects of macromolecular crowding. In this chapter we review examples of both
explicitly imposed and intrinsic correlations, focusing on the mechanisms by
which microscopic heterogeneity is amplified to macroscopic effect.Comment: 20 pages, 5 figures. To appear in Advances in Chemical Physic
The statistical mechanics of complex signaling networks : nerve growth factor signaling
It is becoming increasingly appreciated that the signal transduction systems
used by eukaryotic cells to achieve a variety of essential responses represent
highly complex networks rather than simple linear pathways. While significant
effort is being made to experimentally measure the rate constants for
individual steps in these signaling networks, many of the parameters required
to describe the behavior of these systems remain unknown, or at best,
estimates. With these goals and caveats in mind, we use methods of statistical
mechanics to extract useful predictions for complex cellular signaling
networks. To establish the usefulness of our approach, we have applied our
methods towards modeling the nerve growth factor (NGF)-induced differentiation
of neuronal cells. Using our approach, we are able to extract predictions that
are highly specific and accurate, thereby enabling us to predict the influence
of specific signaling modules in determining the integrated cellular response
to the two growth factors. We show that extracting biologically relevant
predictions from complex signaling models appears to be possible even in the
absence of measurements of all the individual rate constants. Our methods also
raise some interesting insights into the design and possible evolution of
cellular systems, highlighting an inherent property of these systems wherein
particular ''soft'' combinations of parameters can be varied over wide ranges
without impacting the final output and demonstrating that a few ''stiff''
parameter combinations center around the paramount regulatory steps of the
network. We refer to this property -- which is distinct from robustness -- as
''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption
for GIF), IOP style; supp. info/figs. included as brown_supp.pd
Coupling biochemistry and mechanics in cell adhesion: a model for inhomogeneous stress fiber contraction
Biochemistry and mechanics are closely coupled in cell adhesion. At sites of
cell-matrix adhesion, mechanical force triggers signaling through the
Rho-pathway, which leads to structural reinforcement and increased
contractility in the actin cytoskeleton. The resulting force acts back to the
sites of adhesion, resulting in a positive feedback loop for mature adhesion.
Here we model this biochemical-mechanical feedback loop for the special case
when the actin cytoskeleton is organized in stress fibers, which are
contractile bundles of actin filaments. Activation of myosin II molecular
motors through the Rho-pathway is described by a system of reaction-diffusion
equations, which are coupled into a viscoelastic model for a contractile actin
bundle. We find strong spatial gradients in the activation of contractility and
in the corresponding deformation pattern of the stress fiber, in good agreement
with experimental findings.Comment: Revtex, 35 pages, 13 Postscript figures included, in press with New
Journal of Physics, Special Issue on The Physics of the Cytoskeleto
Phosphorelays provide tunable signal processing capabilities for the cell
Achieving a complete understanding of cellular signal transduction requires deciphering the relation between structural and biochemical features of a signaling system and the shape of the signal-response relationship it embeds. Using explicit analytical expressions and numerical simulations, we present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward, reverse phosphorylation and hydrolysis reactions. This reveals a set of mathematical conditions which, when satisfied, dictate the shape of the signal-response relationship. We find that a specific topology also observed in nature can satisfy these conditions in such a way to allow plasticity among hyperbolic and sigmoidal signal-response relationships. Particularly, the shape of the signal-response relationship of this relay topology can be tuned by altering kinetic rates and total protein levels at different parts of the relay. These findings provide an important step towards predicting response dynamics of phosphorelays, and the nature of subsequent physiological responses that they mediate, solely from topological features and few composite measurements; measuring the ratio of reverse and forward phosphorylation rate constants could be sufficient to determine the shape of the signal-response relationship the relay exhibits. Furthermore, they highlight the potential ways in which selective pressures on signal processing could have played a role in the evolution of the observed structural and biochemical characteristic in phosphorelays
Sequential pattern formation governed by signaling gradients
Rhythmic and sequential segmentation of the embryonic body plan is a vital
developmental patterning process in all vertebrate species. However, a
theoretical framework capturing the emergence of dynamic patterns of gene
expression from the interplay of cell oscillations with tissue elongation and
shortening and with signaling gradients, is still missing. Here we show that a
set of coupled genetic oscillators in an elongating tissue that is regulated by
diffusing and advected signaling molecules can account for segmentation as a
self-organized patterning process. This system can form a finite number of
segments and the dynamics of segmentation and the total number of segments
formed depend strongly on kinetic parameters describing tissue elongation and
signaling molecules. The model accounts for existing experimental perturbations
to signaling gradients, and makes testable predictions about novel
perturbations. The variety of different patterns formed in our model can
account for the variability of segmentation between different animal species.Comment: 12 pages, 5 figure
Context-aware Cluster Based Device-to-Device Communication to Serve Machine Type Communications
Billions of Machine Type Communication (MTC) devices are foreseen to be
deployed in next ten years and therefore potentially open a new market for next
generation wireless network. However, MTC applications have different
characteristics and requirements compared with the services provided by legacy
cellular networks. For instance, an MTC device sporadically requires to
transmit a small data packet containing information generated by sensors. At
the same time, due to the massive deployment of MTC devices, it is inefficient
to charge their batteries manually and thus a long battery life is required for
MTC devices. In this sense, legacy networks designed to serve human-driven
traffics in real time can not support MTC efficiently. In order to improve the
availability and battery life of MTC devices, context-aware device-to-device
(D2D) communication is exploited in this paper. By applying D2D communication,
some MTC users can serve as relays for other MTC users who experience bad
channel conditions. Moreover, signaling schemes are also designed to enable the
collection of context information and support the proposed D2D communication
scheme. Last but not least, a system level simulator is implemented to evaluate
the system performance of the proposed technologies and a large performance
gain is shown by the numerical results
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