114 research outputs found
Blood Vessel Tortuosity Selects against Evolution of Agressive Tumor Cells in Confined Tissue Environments: a Modeling Approach
Cancer is a disease of cellular regulation, often initiated by genetic
mutation within cells, and leading to a heterogeneous cell population within
tissues. In the competition for nutrients and growth space within the tumors
the phenotype of each cell determines its success. Selection in this process is
imposed by both the microenvironment (neighboring cells, extracellular matrix,
and diffusing substances), and the whole of the organism through for example
the blood supply. In this view, the development of tumor cells is in close
interaction with their increasingly changing environment: the more cells can
change, the more their environment will change. Furthermore, instabilities are
also introduced on the organism level: blood supply can be blocked by increased
tissue pressure or the tortuosity of the tumor-neovascular vessels. This
coupling between cell, microenvironment, and organism results in behavior that
is hard to predict. Here we introduce a cell-based computational model to study
the effect of blood flow obstruction on the micro-evolution of cells within a
cancerous tissue. We demonstrate that stages of tumor development emerge
naturally, without the need for sequential mutation of specific genes.
Secondly, we show that instabilities in blood supply can impact the overall
development of tumors and lead to the extinction of the dominant aggressive
phenotype, showing a clear distinction between the fitness at the cell level
and survival of the population. This provides new insights into potential side
effects of recent tumor vasculature renormalization approaches
Vascular networks due to dynamically arrested crystalline ordering of elongated cells
Recent experimental and theoretical studies suggest that crystallization and
glass-like solidification are useful analogies for understanding cell ordering
in confluent biological tissues. It remains unexplored how cellular ordering
contributes to pattern formation during morphogenesis. With a computational
model we show that a system of elongated, cohering biological cells can get
dynamically arrested in a network pattern. Our model provides a new explanation
for the formation of cellular networks in culture systems that exclude
intercellular interaction via chemotaxis or mechanical traction.Comment: 11 pages, 4 figures. Published as: Palm and Merks (2013) Physical
Review E 87, 012725. The present version includes a correction in the
calculation of the nematic order parameter. Erratum submitted to PRE on Jun
5th 2013. The correction does not affect the conclusion
Particle-based simulation of ellipse-shaped particle aggregation as a model for vascular network formation
Computational modelling is helpful for elucidating the cellular mechanisms
driving biological morphogenesis. Previous simulation studies of blood vessel
growth based on the Cellular Potts model (CPM) proposed that elongated,
adhesive or mutually attractive endothelial cells suffice for the formation of
blood vessel sprouts and vascular networks. Because each mathematical
representation of a model introduces potential artifacts, it is important that
model results are reproduced using alternative modelling paradigms. Here, we
present a lattice-free, particle-based simulation of the cell elongation model
of vasculogenesis. The new, particle-based simulations confirm the results
obtained from the previous Cellular Potts simulations. Furthermore, our current
findings suggest that the emergence of order is possible with the application
of a high enough attractive force or, alternatively, a longer attraction
radius. The methodology will be applicable to a range of problems in
morphogenesis and noisy particle aggregation in which cell shape is a key
determining factor.Comment: 9 pages, 11 figures, 2 supplementary videos (on Youtube), submitted
to Computational Particle Mechanics, special issue: Jos\'e-Manuel Garcia
Aznar (Ed.) Particle-based simulations on cell and biomolecular mechanic
Tip cell overtaking occurs as a side effect of sprouting in computational models of angiogenesis
During angiogenesis, endothelial cells compete for the tip position during
angiogenesis: a phenomenon named tip cell overtaking. It is still unclear to
what extent tip cell overtaking is a side effect of sprouting or to what extent
a biological function. To address this question, we studied tip cell overtaking
in two existing cellular Potts models of angiogenic sprouting. In these models
angiogenic sprouting-like behavior emerges from a small set of plausible cell
behaviors and the endothelial cells spontaneously migrate forwards and
backwards within sprouts, suggesting that tip cell overtaking might occur as a
side effect of sprouting. In accordance with experimental observations, in our
simulations the cells' tendency to occupy the tip position can be regulated
when two cell lines with different levels of Vegfr2 expression are contributing
to sprouting (mosaic sprouting assay), where cell behavior is regulated by a
simple VEGF-Dll4-Notch signaling network. Our modeling results suggest that tip
cell overtaking occurs spontaneously due to the stochastic motion of cells
during sprouting. Thus, tip cell overtaking and sprouting dynamics may be
interdependent and should be studied and interpreted in combination.
VEGF-Dll4-Notch can regulate the ability of cells to occupy the tip cell
position, but only when cells in the simulation strongly differ in their levels
of Vegfr2. We propose that VEGF-Dll4-Notch signaling might not regulate which
cell ends up at the tip, but assures that the cell that randomly ends up at the
tip position acquires the tip cell phenotype.Comment: 20 pages, 6 figures, 4 supplementary figure
Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression
Angiogenesis involves the formation of new blood vessels by sprouting or
splitting of existing blood vessels. During sprouting, a highly motile type of
endothelial cell, called the tip cell, migrates from the blood vessels followed
by stalk cells, an endothelial cell type that forms the body of the sprout. To
get more insight into how tip cells contribute to angiogenesis, we extended an
existing computational model of vascular network formation based on the
cellular Potts model with tip and stalk differentiation, without making a
priori assumptions about the differences between tip cells and stalk cells. To
predict potential differences, we looked for parameter values that make tip
cells (a) move to the sprout tip, and (b) change the morphology of the
angiogenic networks. The screening predicted that if tip cells respond less
effectively to an endothelial chemoattractant than stalk cells, they move to
the tips of the sprouts, which impacts the morphology of the networks. A
comparison of this model prediction with genes expressed differentially in tip
and stalk cells revealed that the endothelial chemoattractant Apelin and its
receptor APJ may match the model prediction. To test the model prediction we
inhibited Apelin signaling in our model and in an \emph{in vitro} model of
angiogenic sprouting, and found that in both cases inhibition of Apelin or of
its receptor APJ reduces sprouting. Based on the prediction of the
computational model, we propose that the differential expression of Apelin and
APJ yields a "self-generated" gradient mechanisms that accelerates the
extension of the sprout.Comment: 48 pages, 10 figures, 8 supplementary figures. Accepted for
publication in PLoS ON
Mechanical cell-matrix feedback explains pairwise and collective endothelial cell behavior in vitro
In vitro cultures of endothelial cells are a widely used model system of the
collective behavior of endothelial cells during vasculogenesis and
angiogenesis. When seeded in an extracellular matrix, endothelial cells can
form blood vessel-like structures, including vascular networks and sprouts.
Endothelial morphogenesis depends on a large number of chemical and mechanical
factors, including the compliancy of the extracellular matrix, the available
growth factors, the adhesion of cells to the extracellular matrix, cell-cell
signaling, etc. Although various computational models have been proposed to
explain the role of each of these biochemical and biomechanical effects, the
understanding of the mechanisms underlying in vitro angiogenesis is still
incomplete. Most explanations focus on predicting the whole vascular network or
sprout from the underlying cell behavior, and do not check if the same model
also correctly captures the intermediate scale: the pairwise cell-cell
interactions or single cell responses to ECM mechanics. Here we show, using a
hybrid cellular Potts and finite element computational model, that a single set
of biologically plausible rules describing (a) the contractile forces that
endothelial cells exert on the ECM, (b) the resulting strains in the
extracellular matrix, and (c) the cellular response to the strains, suffices
for reproducing the behavior of individual endothelial cells and the
interactions of endothelial cell pairs in compliant matrices. With the same set
of rules, the model also reproduces network formation from scattered cells, and
sprouting from endothelial spheroids. Combining the present mechanical model
with aspects of previously proposed mechanical and chemical models may lead to
a more complete understanding of in vitro angiogenesis.Comment: 25 pages, 6 figures, accepted for publication in PLoS Computational
Biolog
Deformability and collision-induced reorientation enhance cell topotaxis in dense microenvironments
In vivo, cells navigate through complex environments filled with obstacles.
Recently, the term 'topotaxis' has been introduced for navigation along
topographic cues such as obstacle density gradients. Experimental and
mathematical efforts have analyzed topotaxis of single cells in pillared grids
with pillar density gradients. A previous model based on active Brownian
particles has shown that ABPs perform topotaxis, i.e., drift towards lower
pillar densities, due to decreased effective persistence lengths at high
pillars densities. The ABP model predicted topotactic drifts of up to 1% of the
instantaneous speed, whereas drifts of up to 5% have been observed
experimentally. We hypothesized that the discrepancy between the ABP and the
experimental observations could be in 1) cell deformability, and 2) more
complex cell-pillar interactions. Here, we introduce a more detailed model of
topotaxis, based on the Cellular Potts model. To model persistent cells we use
the Act model, which mimicks actin-polymerization driven motility, and a hybrid
CPM-ABP model. Model parameters were fitted to simulate the experimentally
found motion of D. discoideum on a flat surface. For starved D. discoideum,
both CPM variants predict topotactic drifts closer to the experimental results
than the previous ABP model, due to a larger decrease in persistence length.
Furthermore, the Act model outperformed the hybrid model in terms of topotactic
efficiency, as it shows a larger reduction in effective persistence time in
dense pillar grids. Also pillar adhesion can slow down cells and decrease
topotaxis. For slow and less persistent vegetative D. discoideum cells, both
CPMs predicted a similar small topotactic drift. We conclude that deformable
cell volume results in higher topotactic drift compared to ABPs, and that
feedback of cell-pillar collisions on cell persistence increases drift only in
highly persistent cells
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