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Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions.
Cell-to-cell communication networks have critical roles in coordinating diverse organismal processes, such as tissue development or immune cell response. However, compared with intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far less understood. Major complications include: cells are themselves regulated by complex intracellular signaling networks; individual cells are heterogeneous; and output of any one cell can recursively become an additional input signal to other cells. Here, we make use of a framework that treats intracellular signal transduction networks as "black boxes" with characterized input-to-output response relationships. We study simple cell-to-cell communication circuit motifs and find conditions that generate bimodal responses in time, as well as mechanisms for independently controlling synchronization and delay of cell-population responses. We apply our modeling approach to explain otherwise puzzling data on cytokine secretion onset times in T cells. Our approach can be used to predict communication network structure using experimentally accessible input-to-output measurements and without detailed knowledge of intermediate steps
Learning theories reveal loss of pancreatic electrical connectivity in diabetes as an adaptive response
Cells of almost all solid tissues are connected with gap junctions which
permit the direct transfer of ions and small molecules, integral to regulating
coordinated function in the tissue. The pancreatic islets of Langerhans are
responsible for secreting the hormone insulin in response to glucose
stimulation. Gap junctions are the only electrical contacts between the
beta-cells in the tissue of these excitable islets. It is generally believed
that they are responsible for synchrony of the membrane voltage oscillations
among beta-cells, and thereby pulsatility of insulin secretion. Most attempts
to understand connectivity in islets are often interpreted, bottom-up, in terms
of measurements of gap junctional conductance. This does not, however explain
systematic changes, such as a diminished junctional conductance in type 2
diabetes. We attempt to address this deficit via the model presented here,
which is a learning theory of gap junctional adaptation derived with analogy to
neural systems. Here, gap junctions are modelled as bonds in a beta-cell
network, that are altered according to homeostatic rules of plasticity. Our
analysis reveals that it is nearly impossible to view gap junctions as
homogeneous across a tissue. A modified view that accommodates heterogeneity of
junction strengths in the islet can explain why, for example, a loss of gap
junction conductance in diabetes is necessary for an increase in plasma insulin
levels following hyperglycemia.Comment: 15 pages, 5 figures. To appear in PLoS One (2013
Competition through selective inhibitory synchrony
Models of cortical neuronal circuits commonly depend on inhibitory feedback
to control gain, provide signal normalization, and to selectively amplify
signals using winner-take-all (WTA) dynamics. Such models generally assume that
excitatory and inhibitory neurons are able to interact easily, because their
axons and dendrites are co-localized in the same small volume. However,
quantitative neuroanatomical studies of the dimensions of axonal and dendritic
trees of neurons in the neocortex show that this co-localization assumption is
not valid. In this paper we describe a simple modification to the WTA circuit
design that permits the effects of distributed inhibitory neurons to be coupled
through synchronization, and so allows a single WTA to be distributed widely in
cortical space, well beyond the arborization of any single inhibitory neuron,
and even across different cortical areas. We prove by non-linear contraction
analysis, and demonstrate by simulation that distributed WTA sub-systems
combined by such inhibitory synchrony are inherently stable. We show
analytically that synchronization is substantially faster than winner
selection. This circuit mechanism allows networks of independent WTAs to fully
or partially compete with each other.Comment: in press at Neural computation; 4 figure
Design Principles of Pancreatic Islets: Glucose-dependent Coordination of Hormone Pulses
Pancreatic islets are functional units involved in glucose homeostasis. The
multicellular system comprises three main cell types; and
cells reciprocally decrease and increase blood glucose by producing insulin and
glucagon pulses, while the role of cells is less clear. Although their
spatial organization and the paracrine/autocrine interactions between them have
been extensively studied, the functional implications of the design principles
are still lacking. In this study, we formulated a mathematical model that
integrates the pulsatility of hormone secretion and the interactions and
organization of islet cells and examined the effects of different cellular
compositions and organizations in mouse and human islets. A common feature of
both species was that islet cells produced synchronous hormone pulses under
low- and high- glucose conditions, while they produced asynchronous hormone
pulses under normal glucose conditions. However, the synchronous coordination
of insulin and glucagon pulses at low glucose was more pronounced in human
islets that had more cells. When cells were selectively
removed to mimic diabetic conditions, the anti-synchronicity of insulin and
glucagon pulses was deteriorated at high glucose, but it could be partially
recovered when the re-aggregation of remaining cells was considered. Finally,
the third cell type, cells, which introduced additional complexity in
the multicellular system, prevented the excessive synchronization of hormone
pulses. Our computational study suggests that controllable synchronization is a
design principle of pancreatic islets.Comment: 24 pages, 7 figure
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