scholarly journals Modelling cell surface dynamics and cell–cell interactions using Cell Studio: a three-dimensional visualization tool based on gaming technology

2019 ◽  
Vol 16 (160) ◽  
pp. 20190264
Author(s):  
Asaf Liberman ◽  
Matan Mussel ◽  
Danny Kario ◽  
David Sprinzak ◽  
Uri Nevo
Keyword(s):  
Numerical Solutions ◽  
Contact Region ◽  
Single Cells ◽  
Cell Signalling ◽  
Three Dimensional ◽  
Predictive Modelling ◽  
Agent Based Model ◽  
Long Distance ◽  
Mean Field Model ◽  
Agent Based

Predictive modelling of complex biological systems and biophysical interactions requires the inclusion of multiple nano- and micro-scale events. In many scenarios, however, numerical solutions alone do not necessarily enhance the understanding of the system. Instead, this work explores the use of an agent-based model with visualization capabilities to elucidate interactions between single cells. We present a model of juxtacrine signalling, using Cell Studio, an agent-based modelling system, based on gaming and three-dimensional visualization tools. The main advantages of the system are its ability to apply any cell geometry and to dynamically visualize the diffusion and interactions of the molecules within the cells in real time. These provide an excellent tool for obtaining insight about different biological scenarios, as the user may view the dynamics of a system and observe its emergent behaviour as it unfolds. The agent-based model was validated against the results of a mean-field model of Notch receptors and ligands in two neighbouring cells. The conversion to an agent-based model is described in detail. To demonstrate the advantages of the model, we further created a filopodium-mediated signalling model. Our model revealed that diffusion and endocytosis alone are insufficient to produce significant signalling in a filopodia scenario. This is due to the bottleneck at the cell–filopodium contact region and the long distance to the end of the filopodium. However, allowing active transport of ligands into filopodia enhances the signalling significantly compared with a face-to-face scenario. We conclude that the agent-based approach can provide insights into mechanisms underlying cell signalling. The open-source model can be found in the Internet hosting service GitHub.

scholarly journals Systematic functional characterization of antisense eRNA of protocadherin α composite enhancer

2021 ◽  
Vol 35 (19-20) ◽  
pp. 1383-1394
Author(s):  
Yuxiao Zhou ◽  
Siyuan Xu ◽  
Mo Zhang ◽  
Qiang Wu
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Functional Characterization ◽  
Three Dimensional ◽  
Elongation Factor ◽  
Locked Nucleic Acid ◽  
Loop Formation ◽  
Long Distance ◽  
Enhancer Region

Enhancers generate bidirectional noncoding enhancer RNAs (eRNAs) that may regulate gene expression. At present, the eRNA function remains enigmatic. Here, we report a 5′ capped antisense eRNA PEARL (Pcdh eRNA associated with R-loop formation) that is transcribed from the protocadherin (Pcdh) α HS5-1 enhancer region. Through loss- and gain-of-function experiments with CRISPR/Cas9 DNA fragment editing, CRISPRi, and CRISPRa, as well as locked nucleic acid strategies, in conjunction with ChIRP, MeDIP, DRIP, QHR-4C, and HiChIP experiments, we found that PEARL regulates Pcdhα gene expression by forming local RNA–DNA duplexes (R-loops) in situ within the HS5-1 enhancer region to promote long-distance chromatin interactions between distal enhancers and target promoters. In particular, increased levels of eRNA PEARL via perturbing transcription elongation factor SPT6 lead to strengthened local three-dimensional chromatin organization within the Pcdh superTAD. These findings have important implications regarding molecular mechanisms by which the HS5-1 enhancer regulates stochastic Pcdhα promoter choice in single cells in the brain.

scholarly journals An Agent-Based Model of Combination Oncolytic Viral Therapy and Anti-PD-1 Immunotherapy Reveals the Importance of Spatial Location When Treating Glioblastoma

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5314
Author(s):  
Kathleen M. Storey ◽  
Trachette L. Jackson
Keyword(s):  
Three Dimensional ◽  
Spatial Location ◽  
Adaptive Strategy ◽  
Treatment Modalities ◽  
Agent Based Model ◽  
Agent Based ◽  
Oncolytic Viral Therapy ◽  
Landscape Characteristics ◽  
Adaptive Immune ◽  
Viral Therapy

Oncolytic viral therapies and immunotherapies are of growing clinical interest due to their selectivity for tumor cells over healthy cells and their immunostimulatory properties. These treatment modalities provide promising alternatives to the standard of care, particularly for cancers with poor prognoses, such as the lethal brain tumor glioblastoma (GBM). However, uncertainty remains regarding optimal dosing strategies, including how the spatial location of viral doses impacts therapeutic efficacy and tumor landscape characteristics that are most conducive to producing an effective immune response. We develop a three-dimensional agent-based model (ABM) of GBM undergoing treatment with a combination of an oncolytic Herpes Simplex Virus and an anti-PD-1 immunotherapy. We use a mechanistic approach to model the interactions between distinct populations of immune cells, incorporating both innate and adaptive immune responses to oncolytic viral therapy and including a mechanism of adaptive immune suppression via the PD-1/PD-L1 checkpoint pathway. We utilize the spatially explicit nature of the ABM to determine optimal viral dosing in both the temporal and spatial contexts. After proposing an adaptive viral dosing strategy that chooses to dose sites at the location of highest tumor cell density, we find that, in most cases, this adaptive strategy produces a more effective treatment outcome than repeatedly dosing in the center of the tumor.

scholarly journals The long-distance flight behavior of Drosophila supports an agent-based model for wind-assisted dispersal in insects

2021 ◽  
Vol 118 (17) ◽  
pp. e2013342118
Author(s):  
Katherine J. Leitch ◽  
Francesca V. Ponce ◽  
William B. Dickson ◽  
Floris van Breugel ◽  
Michael H. Dickinson
Keyword(s):  
Mojave Desert ◽  
Genetic Model ◽  
Release Site ◽  
Flight Behavior ◽  
Agent Based Model ◽  
Critical Question ◽  
Long Distance ◽  
Agent Based ◽  
Dispersal Behavior ◽  
Odor Plumes

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

A three-dimensional multi-agent-based model for the evolution of Chagas’ disease

Biosystems ◽  
2010 ◽  
Vol 100 (3) ◽  
pp. 225-230 ◽  
Author(s):  
Viviane Galvão ◽  
José Garcia Vivas Miranda
Keyword(s):  
Chagas Disease ◽  
Three Dimensional ◽  
Agent Based Model ◽  
Agent Based ◽  
Multi Agent

scholarly journals A computational multiscale agent-based model for simulating spatio-temporal tumour immune response to PD1 and PDL1 inhibition

2017 ◽  
Vol 14 (134) ◽  
pp. 20170320 ◽  
Author(s):  
Chang Gong ◽  
Oleg Milberg ◽  
Bing Wang ◽  
Paolo Vicini ◽  
Rajesh Narwal ◽  
...  
Keyword(s):  
Cancer Cells ◽  
Immune Checkpoint ◽  
Temporal Dynamics ◽  
Checkpoint Inhibitors ◽  
Tumour Progression ◽  
Cytotoxic T Cells ◽  
Three Dimensional ◽  
Agent Based Model ◽  
Agent Based ◽  
Tumour Development

When the immune system responds to tumour development, patterns of immune infiltrates emerge, highlighted by the expression of immune checkpoint-related molecules such as PDL1 on the surface of cancer cells. Such spatial heterogeneity carries information on intrinsic characteristics of the tumour lesion for individual patients, and thus is a potential source for biomarkers for anti-tumour therapeutics. We developed a systems biology multiscale agent-based model to capture the interactions between immune cells and cancer cells, and analysed the emergent global behaviour during tumour development and immunotherapy. Using this model, we are able to reproduce temporal dynamics of cytotoxic T cells and cancer cells during tumour progression, as well as three-dimensional spatial distributions of these cells. By varying the characteristics of the neoantigen profile of individual patients, such as mutational burden and antigen strength, a spectrum of pretreatment spatial patterns of PDL1 expression is generated in our simulations, resembling immuno-architectures obtained via immunohistochemistry from patient biopsies. By correlating these spatial characteristics with in silico treatment results using immune checkpoint inhibitors, the model provides a framework for use to predict treatment/biomarker combinations in different cancer types based on cancer-specific experimental data.

scholarly journals Analytical solution of equivalent SEIR and agent-based model of COVID-19; showing the bounds of contact tracing

2020 ◽  
Author(s):  
Huseyin Tunc ◽  
Fatma Zehra Sari ◽  
Busra Nur Darendeli ◽  
Ramin Nashebi ◽  
Murat Sari ◽  
...  
Keyword(s):  
Growth Rate ◽  
Numerical Solutions ◽  
Transmission Rate ◽  
Contact Tracing ◽  
Analytical Relationship ◽  
Model Parameters ◽  
Agent Based Model ◽  
Agent Based ◽  
Hidden Parameters ◽  
Sensitive Parameters

AbstractMathematical models not only forecast the possible future but also is used to find hidden parameters of the COVID-19 pandemic. Numerical estimates can inform us of both goals. Still, the interdependencies of parameters stay obscure. Many numerical solutions have been proposed so far; however, the analytical relationship between the outbreak growth, decay and equilibrium are much less studied. In this study, we have employed both an equivalent agent-based model and a Susceptible-Exposed-Infected-Recovered (SEIR)-like model to prove that the growth rate can be determined analytically in terms of other model parameters, including contact tracing rate. We identify the most sensitive parameters as undocumented transmission rate and documentation ratio. Unfortunately, these are the parameters we have the least knowledge. We derived an identity that predicts the effectiveness of contact tracing in a country from observable parameters. We underline an unavoidable dilemma: that even in the case of high contact tracing, we cannot bring the outbreak to stalemate without applying substantial quarantine; however, some countries are benefiting from contact tracing. Besides, we have shown that the seemingly same parameters of the SEIR models and agent-based models are not equivalent. We propose a correction to bridge both models.

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