Cells as state machines: Cell behavior patterns arise during capillary formation as a function of BDNF and VEGF

Long, Byron L.; Rekhi, Rahul; Abrego, Amada M.; Jung, Jiwon; Qutub, Amina A.

doi:10.1016/j.jtbi.2012.11.030

Cited by 17 publications

(17 citation statements)

References 71 publications

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“…Our approach was inspired by a prior study that used a computational model to identify what cell behavior changed when endothelial cells were treated with certain growth factors [31]. This study used an agent-based, 3D model of angiogenesis in which sprouts extend from a spheroid.…”

Section: Discussionmentioning

confidence: 99%

“…To develop new hypotheses on the role of tip and stalk cell differentiation during angiogenesis, we developed an explorative approach inspired by Long et al [31] who used a genetic algorithm to identify the transition rules between endothelial cell behaviors that could best reproduce in vitro sprouting. Here we use a cell-based, computational model of angiogenesis [12] that is based on the cellular Potts model (CPM) [32,33].…”

Section: Introductionmentioning

confidence: 99%

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Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression

et al. 2016

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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 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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression

et al. 2016

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“…In doing so, the field provides computational tools to characterize behavioral patterns at the cellular level that will be the building blocks of more sophisticated synthetic design. Systems biology approaches are particularly powerful in characterizing cell–cell interactions across scales, such as in capillary patterning and organ development, where the gene circuits approach in synthetic biology has proven limited in capturing adaptation, cellular heterogeneity and spatial hierarchy (Yingling et al, 2005; Qutub et al, 2009; Long et al, 2013). As such, many of the challenges to applying synthetic biology toward controlling mammalian tissue can be addressed in part by methods and techniques that are well-developed in systems bioengineering.…”

Section: Computational Techniques and Advances: Systems Biology Applimentioning

confidence: 99%

“…Existing libraries, such as MASON, Repast, and Swarm, allow for the construction of multi-scale agent-based models atop adaptable frameworks, facilitating their use by synthetic biologists with limited prior exposure to the technique. This methodology has been employed toward modeling brain capillary regeneration (Long et al, 2013), immunological and inflammatory responses (Bailey et al, 2007; Chandran et al, 2009; Pothen et al, 2013), and cancer progression (Wang et al, 2009; Basanta et al, 2012; Wodarz et al, 2012; Walker and Southgate, 2013), among other topics. Within synthetic biology specifically, agent-based models have also simulated tissue development, tissue formation, and microbial chemotaxis (Endler et al, 2009).…”

Section: Computational Techniques and Advances: Systems Biology Applimentioning

confidence: 99%

Systems approaches for synthetic biology: a pathway toward mammalian design

Rekhi

Qutub

2013

Front. Physiol.

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We review methods of understanding cellular interactions through computation in order to guide the synthetic design of mammalian cells for translational applications, such as regenerative medicine and cancer therapies. In doing so, we argue that the challenges of engineering mammalian cells provide a prime opportunity to leverage advances in computational systems biology. We support this claim systematically, by addressing each of the principal challenges to existing synthetic bioengineering approaches—stochasticity, complexity, and scale—with specific methods and paradigms in systems biology. Moreover, we characterize a key set of diverse computational techniques, including agent-based modeling, Bayesian network analysis, graph theory, and Gillespie simulations, with specific utility toward synthetic biology. Lastly, we examine the mammalian applications of synthetic biology for medicine and health, and how computational systems biology can aid in the continued development of these applications.

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“…Computational models offer unique insight into the study of biological systems, enabling us to query unmeasurable, unobservable, or inaccessible metrics pertinent to biomedical science 32–37 . In assembling a model, the investigator is able to explicitly define methods for simulating each aspect of the biological processes they are modeling – either as stochastic or as rule-based.…”

Section: Introductionmentioning

confidence: 99%

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

Walpole

Chappell

et al. 2015

Integr. Biol.

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Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

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Cells as state machines: Cell behavior patterns arise during capillary formation as a function of BDNF and VEGF

Cited by 17 publications

References 71 publications

Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression

Computational Screening of Tip and Stalk Cell Behavior Proposes a Role for Apelin Signaling in Sprout Progression

Systems approaches for synthetic biology: a pathway toward mammalian design

Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks

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