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Using CompuCell3D as a Platform to Construct Multicellular Virtual Tissues to Explore the Interactions between Infection, Host Tissues and Immune Response

James A. Glazier

Dept. of Intelligent Systems Engineering

and Biocomplexity Institute

Indiana University

Bloomington, IN 47408, USA

IMAG MSM WG on Multiscale Modeling and Viral Pandemics

Thursday, June 2, 2022

IU Bloomington: [Dr. Priyom Adhyapok], [Dr. Dragos Amarie], [Dr. Josua Aponte-Serrano], [Dr. Ariel Balter], Dr. Maria Bondesson, [Kira Berithaupt], [Dr. Stephen Burns], [Dr. Sherry Clendenon], [Alin Comanescu], [Dr. Clayton Davis], Dr. Rita de Almeida, [Aaron Dy], Juliano Ferrari-Gianlupi, Dr. Geoffrey Fox, [Dr. Xiao Fu], [Garth Gast], [Dr. Thomas Gast], [Dr. J. Scott Gens], [Samuel R. Heaps], [Randy Heiland], [Dr. Susan Hester], [Dr. Mitja Hmeljak], [Dr. Srividhya Jayaraman], [Dr. James Klaunig], [Dr. Roeland Merks], [Nazanin Mosavian], [Guilherme Oliveira], [Dr. Nikodem Poplawski], Ellen Quardokus, [Ryan Roper], Dr. TJ Sego, [Dr. Abbas Shirinifard], Dr. James Sluka, [Dr. Endre Somogyi], Dr. Maciej Swat, Dr. Gilberto Thomas, Dr. Javier Toledo, Joel Vanin, [Ruei Wu], [Benjamin Zaitlen], [Dr. Ying Zhang]. Indiana University, School of Medicine: Dr. Robert Bacallao, [Dr. Nicholas F. Berbari], [Dr. Kenn Dunn], [Evan V. Greene], [Britney-Shea Herbert], Dr. Tarunendu Mapder, Dr. Sara K. Quinney, Dr. Robert Stratford, [Wei Min Xu]. [University of Houston: Dr. Jan-Ake Gustafsson, Dr. Catharine McCollum]. [EPA: Dr. Thomas Knudsen, Dr. Imran Shah, Dr. John Wambaugh, Dr. Nicole Kleinstreuer]. [University of Notre Dame: Dr. Santiago Schnell]. [KUMC: Dr. Charles Little]. University College London: Ana S. Dias, Irene de Almeida, Dr. Claudio Stern, [University of Dundee: Dr. Mark Chaplain]. [Moffitt Cancer Center: Dr. Heiko Enderling]. [CRG Barcelona: Dr. James Sharpe]. [Cambridge University: Dr. Octavian Voicelescu]. [University of Paris 6: Dr. Francois Graner]. [University of Wisconsin Milwaukee: Dr. Roshan D’Souza]. [UCSF: Dr. Tony Hunt], [Emory University: Dr. Fereydoon Family, Dr. Hans Grossniklaus]. [Georgia State University: Dr. Yi Jiang]. [University of New Mexico, School of Medicine: Heather H. Ward, Angela Wandinger-Ness. Amgen: Michael Boedigheimer, Michael Damore, William G. Richards]. [Otsuka Pharmaceuticals: Sandro Rossetti]. [Mayo Clinic (Rochester, MN): Peter C. Harris]. [Exxon Research: Dr. Michael P. Anderson, Dr. Gary S. Grest]. LifeOmic: Ananth Iyer [Matthew Phillips]. TU Dresden: Dr. Lutz Brusch. University of Melbourne: Jessica Crawshaw, Dr. James M. Osborne. Georgia State University: Dr. Richard Plemper. University of Pittsburgh: Dr. Bard Ermentrout, Dr. Jason Shoemaker, Jordan Weaver. Carlow University: Dr. Ericka Mochan. [University of Tennessee Medical Center: Dr. Amber Smith]. NCSU: Dr. Julio Belmonte. Université de Montréal: Dr. Morgan Craig. Pasadena City College: Trinity Chung

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Running CompuCell3D on nanoHUB

If you want to follow along on nanoHUB and don’t have an account go to www.nanoHUB.org to register (it takes about 2 minutes to do)

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Installing CC3D on Desktop

  • http://www.compucell3d.org/
  • One-button installers for Windows, Macs and LINUX (see binaries)
  • Easy, but does take a few minutes (and you need to give permissions if you get security warnings)

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Multiscale Biomedical Questions

Development: How does a fertilized egg organize into an adult?

Homeostasis: How does an organism maintain itself?

Developmental Diseases: How does failure of homeostasis lead to pathology?

Infectious Diseases: How do pathogens and host interact?

Medicine/Bioengineering: How can we control, repair or create new forms of these processes?

http://www.kvarkadabra.net/images/articles/Regeneracija-organov_1_original.jpg

All of these exhibit complex interplay of physical and biochemical mechanism

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Can We Make Engineer the Immune Response?

  • Almost every engineered system (e.g., airplanes, computers, video games…) is currently designed, built, monitored and diagnosed using mechanistic predictive dynamic computer simulations—biomedicine is not currently engineered
  • To engineer immune response we need to be able to predict how immune states change, so
  • Predicting immune states and designing optimal treatments will be a key technology
  • We call such simulations in the context of biomedicine Virtual Tissues (Digital Twins are a further development of the VT concept)

“Using digital twins in viral infection,” Reinhard Laubenbacher, James P. Sluka, James A. Glazier,

Science 371: 1105-1106, 2021, DOI: 10.1126/science.abf3370

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Many Layers of Interaction between Molecular Scales and Systemic Outcomes

6

Reaction: Source ODE:

A -> NA; Vmax_A*A/(Km_A+A)

NA+GSH -> NAGSH; kNaGsh*NA*GSH

$X1 -> GSH; kGsh*(GSHmax-GSH)

A -> Ac; Vmax_II_A*A/(Km_II_A+A)

Periportal

Pericentral

Whole body

(and population)

Subcell

Organ

Tissue

Cell

Biology (in vivo)

Computation (in silico)

Hepatocyte

Red Blood Cell

Blood�Portion

k=0.05

k=0.0005

k=0.05

k=0.0005

k=0.0005

k=0.0005

k=0.05

k=0.05

k=0.0005

Length Scale

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Virtual Tissues

Virtual Tissues representing individual cells particularly helpful when cells move, change shape or individual cell behaviors are critical: e.g. cancer metastasis, wound healing, neoangiogenesis,…

Spatial Computer Simulations to Explain How Interacting Chemical, Physical and Biological Mechanisms lead to Outcomes

Dynamic Network/

ODE/Gillespie Level

Multi-Cellular/Potts Level

Diffusive Signaling/

PDE Level

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CompuCell3D simulation of vascularized tumor growth

Morpheus simulation of colonic crypt

VirtualLeaf Simulation plant development

Simmune simulation spatial aspects of intra and inter cell signaling

Lammps simulation of red-blood cell morphology

Simulation Software with Explicit Cell Shapes

Modeling epithelial sheets, Satoru Okuda

Modeling tumor growth Kasia Rejniak, Moffitt Center, Tampa

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CompuCell3D VT Simulation Environment

Flexible rapid construction of VT-based toxicological and developmental toxicity models

Supports:

  • PBPK modeling of whole-body toxicant ADME
  • Subcellular (cell by cell) RK and Stochastic Models of gene regulation, metabolism, signaling and damage
  • Multicellular modeling of tissue architecture and cell-cell interactions (including immune cells)
  • Tissue-level modeling of chemical and mechanical gradients and fluid transport

Multicellular Models specified in CC3DML and Python

Subcellular and PBPK Models can be specified in SBML, CellML, Antimony or MaBoSS, CellDesigner,…

Models are compact, easy to extend and share

Open-source Windows/MAC/LINUX: www.compucell3d.org

Cluster and cloud executable, e.g., on AWS or nanoHUB servers

https://nanohub.org/tools/cc3dbase4x

Customized Editor

Twedit++

Simulation Execution, Control Visualization Tool

Player

Desktop Version

nanoHUB Web Version

Jupyter Notebook Version Available Soon

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CompuCell3D Supported Concepts

nutrient

MDE

Objects: Fields, Generalized Cells, Links, Networks

Fields:

Properties: Concentration, Diffusion Constants, Decay Constants

Behaviors: Diffusion, Decay,

Interactions: Reaction, Secretion, Absorption, Advection

Generalized Cells:

Properties: Volume, Polarity, Surface Area, Inertia, Density, Viscosity, Elasticity, Plasticity, Substructure, Adjacency

Behaviors: Motility, Growth, Division, Death

Interactions: Adhesion, Chemotaxis, Differentiation, Secretion, Absorption

Links:

Properties: Length, Target Length, Elastic Modulus, Yield Strain, Target Angles, Bending Moduli

Behaviors: Creation, Destruction, Change of Target Length

Interactions: Exert Forces on Cells, Pulled on By Cells

Dynamic Networks (Specified in SBML, CellML, Antimony, MaBoss):

Properties: Values

Behaviors: ODEs, Stochastic Evolution

Interactions: Activation, Inhibition, Reaction, Decay

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Flexible and It Works…

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Running a Simple Angiogenesis Example on nanoHUB CompuCell3D

  • Go to https://nanohub.org/tools/cc3delongdemo
  • To the Tool
  • While CC3D is launching you will see a blue box

  • Let’s spend a minute or two exploring the simulation

Merks RMH, Perryn ED, Shirinifard A, Glazier JA (2008) Contact-Inhibited Chemotaxis in De Novo and Sprouting Blood-Vessel Growth. PLoS Comput Biol 4: e1000163. https://doi.org/10.1371/journal.pcbi.1000163

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Features and Capabilities of CompuCell3D

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Creating and Running a Simulation in CC3D

  • To introduce launching and running CC3D on desktop or nanoHUB I will quickly show you how to create a simple cell growth simulation

  • CompuCell3D (CC3D) also comes with a number of “Demos,” small simulations that illustrate basic biological principles or modeling or programming concepts

  • CompuCell3D consists of two tools:
    • Player, a GUI for executing simulations

    • Twedit++, a model editor

    • Player and Twedit++ are software which help you to write and run models (think of Microsoft Word) but are not models themselves

  • Feel free to follow along as we go through these steps

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Launching CompuCell3D on nanoHUB

  • On your dashboard under “MY TOOLS” search for CompuCell3D v4 (1,2,3)
  • It’s a good idea to click on the heart, favoriting the tool (4)
  • To launch CC3D:
  • Clicking on “CompuCell3D v4 Main Tool” will take you to the “About” page of the tool, click on “Launch Tool” to launch it (5)
    • Clicking on will also launch CC3D Player (6)
  • While CC3D is launching you will see a blue box

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2

3

1

4

5

6

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Twedit++ Provides User-Supported Model Definition

You will see Player Open

We want to Switch to Twedit++ (If you have Twedit++ open already you can skip this step)

You can launch Twedit++ by hitting the editor icon (1)

Or

pulling down the “File” menu (2) and selecting Start Twedit++ (3)

Or just hit the “Twedit++” Icon in the toolbar

On a desktop installation search and launch Twedit++

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2

3

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Quick troubleshooting of windows not displaying properly on nanoHub

  • nanoHUB has an issue with screen updates which is (unfortunately) external to CC3D. If the window is not displayed properly, drag the bottom right corner a tiny bit and the screen will update (1)

1

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Simulation Wizard allows Rapid Model Structure Specification

In nanoHUB you will see a single window with Twedit++ foregrounded (on a desktop Payer and Twedit++ are separate apps)

Select “CC3D Project” Pulldown (1)

Then Select “New CC3D Project” (2)

1

2

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Launching Simulation Wizard in Twedit++

In nanoHUB you will see a single window with Twedit++ foregrounded (on a desktop Payer and Twedit++ are separate apps)

Select “CC3D Project” Pulldown

Then Select “New CC3D Project”

CompuCell3D Simulation Wizard will open

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Naming a Simulation in Wizard

Type the name of the simulation (only alphanumeric characters or underscores, i.e. no !-? etc). We will call it “CellGrowthSimulation” (1)

Make Sure that the Simulation Directory is a subdirectory of your user-name directory

(If it isn’t hit “Browse” (2) and select your user directory (3) in the pop-up window and hit “Choose” (4))

Hit “Next>” (5)

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2

3

4

5

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Specifying a Simulation Configuration in Wizard

The General Simulation Properties window allows us to change the size and duration of a simulation

We will use the defaults so just hit “Next>” (1)

1

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Specifying Cell Types in Wizard

In the Cell Type Specification Window we will Create two Cell types, “Cell1” and “Cell2”

Type the name “Cell1” into the “Cell Type” Line (1) and hit “Add” (2)

You will see Cell1 in the table of Cell Types

Then type “Cell2” into the “Cell Type” (3) Line and hit “Add” (4)

Then hit “Next>” (5)

3

2

1

4

5

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Selecting Cell Properties/Behaviors in Wizard

The Chemical Fields window allows us to specify chemical species, we won’t use it, so just hit “Next>” (1)

We want our cells to have variable volume, stick to each other and grow and divide, so we select the “Contact” (for adhesion) (2), “VolumeLocalFlex” (3) for variable volume, “Growth” (4) and “Mitosis” (50 boxes (Selecting “Growth” will automatically hide the “VolumeFlex” option)

Make sure you have selected all four boxes, then hit “Next>” (6)

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6

2

4

5

3

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Creating Simulation Specification in Wizard

To create the simulation, hit “Finish” (1)

You will return to the Main Twedit++ window

To view your simulation double click on “CellGrowthSimulation” (2)

1

2

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Saving a Simulation in Twedit++

To save your simulation, you can hit the “Save Project” (1) or “Save All” (2) Icons in the Tool Bar or Pull Down CC3D Project (3) and Select “Save CC3D Project” (4)

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2

3

4

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Running a CC3D Simulation

To run the simulation, you have a few options

Right click on the “CellGrowthSimulation.cc3d” in the left-hand (1) panel and select “Open in Player” (2)

In the Desktop Version you can also hit the “CC3D” icon

Then switch to the Player tab to view the simulation (3)

1

2

3

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Controlling Tabs in nanoHUB

You should see something like this

We will want to resize the tab to see what is going on

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Manipulating CC3D Player in nanoHUB

  • After CC3D Player has launched, it works as a normal computer program, you can resize it (1, 2) or maximize or minimize the window, using
  • You can resize the tool area by dragging on the boundary box (3)
  • You can also shrink the “Model Editor” box (4)

1

2

4

3

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Starting, Stepping, Pausing and Stopping Simulations in CC3D Player

The four buttons in the menu bar control simulation operation

“Run” Puts the simulation into continuous execution (1)

“Step” Single steps the simulation if it is not yet executing or is paused and then pauses, or executes one additional step if the simulation is currently executing (2)

“Pause” Pauses simulation execution allowing restart of the current run (3)

“Stop” terminates simulation execution and does not allow restart of the current run (4)

Don’t hit “Stop” unless you want to restart the simulation

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2

3

4

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Congratulations—You’ve Just Written A CC3D Simulation Cell Growth and Division Simulation

  • Try Stopping and Restarting the Simulation

  • nanoHUB has an issue with screen updates which is (unfortunately) external to CC3D. If the window is not displayed properly, drag the bottom right corner a tiny bit and the screen will update (1)

1

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CC3D Specification Structure

CC3D Simulations have 2 main components:

a CC3DML specification of static aspects for simple and rapid definition

and a

Python specification of dynamic aspects for maximum flexibility and to allow data analysis

CC3DML

Python

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Looking at a Simulation Specification

  • Switch back to Twedit++ by selecting the Twedit++ Tab (1)

  • Double click on the .xml in the left navigation pane (2)

or

  • Click on the .xml tab to view the CC3DML (3)

  • You can scroll using the bar at the right (4)

1

2

3

4

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CC3DML Simulation Specification

  • The first few lines specify the size and duration of the simulation

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CC3DML Simulation Specification

  • The first few lines specify the size and duration of the simulation (we will discuss these in the class)

  • Next we specify the Cell Types we want and say that they have a volume (nothing exists in a CC3D simulation until we assert it – the same goes for anything inside a computer, it only exists if someone says so)

  • Specifications of Cell and Chemical Field Behaviors are made using Plugins

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CC3DML Simulation Specification

  • The first few lines specify the size and duration of the simulation (we will discuss these in the class)

  • Next we specify the Cell Types we want and say that they have a volume (nothing exists in a CC3D simulation until we assert it)

  • Specifications of Cell and Chemical Field Behaviors are made using Plugins

  • Then we say specify that the cells have a Contact Energy with each other which could depend on their type

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CC3DML Simulation Initial Conditions

  • Steppables are routines which act on the whole simulations

  • UniformInitializer draws a rectangular grid of cells

  • You could try changing the Box dimensions to see what happens

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CC3D Python

  • Now switch to looking at the CC3D Python code by double clicking on the CellGrowthSteppables.py tab or double clicking on the line in the navigation pane

  • We will focus on a few highlights

  • CC3D specifications live inside Python Classes

  • Don’t worry, the amount of python you need to know is minimal

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1

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CC3D Python Cell Initialization

The Python code consists of a series of functions that operate on the simulation

The start function acts once at the beginning of a simulation

We see a Python loop (iterator) for cell

acting on all cells in a cell_list (note the self.)

  • In CC3D (and any multicell modeling framework) we must specify the targetVolume of a cell and its compressibility rather than its actual volume (imagine trying to squeeze a bunch of balloons in a box)

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CC3D Python Cell Growth

The step function acts every time step of the simulation

We see a Python loop (iterator) for cell acting on all cells in the cell_list that causes their target volume to grow

(you could play with the growth rate if you wanted to explore)

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CC3D Python Cell Division

If a cell’s volume get too big, we want it to divide

We create an empty list [] to hold the list of cells to divide

Look at all cells, add (append) the big ones to the list

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CC3D Python Cell Division

If a cell’s volume get too big, we want it to divide

We create an empty list to hold the list of cells to divide

Look at all cells, add the big ones to the list

Then iterate over the list of cells to divide and call a cell division function to make the division

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CC3D Python Cell Division

If a cell’s volume get too big, we want it to divide

We create an empty list to hold the list of cells to divide a list

Look at all cells, add the big ones to the list

Then iterate over the list and call a cell division function to make the division

Finally, we need to say what happens when the cells divide (update_attributes function)

Here, the daughter cell inherits half the target volume of the parent

All other attributes of the parent are copied (clone) to the daughter cell except that if the parent cell was of type Cell1, the daughter cell is of type Cell2 and vice versa

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Coupling MultiCellular Models with Network Dynamics

Coupling Multicellular Models to Dynamic Network Models is easy in CC3D

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SBML and CompuCell3D—Cell Cycle

Simple Workflow:

1) Download an SBML Model

e.g. Tyson2001_Cell_Cycle_Regulation

2) Load the SBML model into the cell. Create an auxiliary field to display the CycB concentration in the cell

3) Execute the simulation—model runs independently in each cell

def __init__(self, frequency=1):

SteppableBasePy.__init__(self, frequency)

self.track_cell_level_scalar_attribute(field_name='CycB', attribute_name='lastCycB')

def start(self):

model_file = './Simulation/BIOMD0000000195_url.xml'

self.add_sbml_to_cell_ids(model_file=model_file, model_name='cellcycle', cell_ids=[1], step_size=0.2)

def step(self,mcs):

for cell in self.cellList:

cell.dict['lastCycB'] = CycB

self.timestepSBML()

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Antimony and CompuCell3D—Delta-Notch Patterning

Human intestinal crypt cup. Chen et al. MSB (2017)

Notch, a transmembrane receptor that coordinates a signaling system, regulating cell fates and pattern formation

 

Simple Workflow:

1) Express intracellular model in Antimony in CC3D Model Specification

2) Load the Antimony model into each cell

3) Execute the simulation—model runs independently in each cell

4) Couple Delta and Notch between cells

5) Execute simulation

model_string = '''

// Reactions

J1: -> N; Davg^k/(a + Davg^k) - N;

J2: -> D; v*(1/(1 + b*N^h) - D);

// Species initializations

Davg = 0.4;

D = 0.5;

N = 0.5;

// Variable initializations

k = 2;

a = 0.01;

v = 1;

b = 100;

h = 2;

'''

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Antimony and CompuCell3D—Delta-Notch Patterning

 

Simple Workflow:

1) Express intracellular model in Antimony in CC3D Model Specification

2) Load the Antimony model into each cell, specify frequency of time-stepping

3) Couple Delta and Notch between cells

4) Execute simulation

model_string = '''

// Reactions

J1: -> N; Davg^k/(a + Davg^k) - N;

J2: -> D; v*(1/(1 + b*N^h) - D);

'''

def start(self):

self.add_antimony_to_cell_types(model_string=model_string, model_name='DN’, cell_types=[self.CELLA], step_size=0.2)

for cell in self.cell_list:

cell.sbml.DN['D'] = np.random.uniform(0.9,1.0)

cell.sbml.DN['N'] = np.random.uniform(0.9,1.0)

Def step(self,mcs):

self.timestep_sbml()

def step(self,mcs):

for cell in self.cell_list:

Davg = 0

nn = 0.0

for (neighbor,common_surface_area) in self.get_cell_neighbor_data_list(cell):

if neighbor:

Davg += neighbor.sbml.DN['D']

nn += 1.0

if nn:

cell.sbml.DN['Davg’] = Davg/nn

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MaBoSS + CC3D

  • Networks can be used and tested in dynamic tissue microenvironments with motile, deformable cells and heterogeneous fields
  • MaBoSS simulations can be readily coupled with dynamic cell shape, contact conditions and other MaBoSS simulations

Sample code of MaBoSS in CompuCell3D

True

False

Boolean states

Notch-expressing

Delta-expressing

Non-expressing

Phenotypes

Network coupling cell cycle and delta-notch signaling

Cell

Cell

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CC3D COVID-19 Drug Treatment Explorer�on nanoHUB

Search cc3dcovid19

Select COVID-19 drug Treatment Explorer

Adjust Windows

Hit “Tile” in Windows Pulldown Menu

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CC3D COVID-19 Drug Treatment Explorer

  • Host-pathogen dynamics consist of lots of mechanisms at multiple scales
  • Drug therapies target specific mechanisms to modify infection outcomes that benefit a patient
  • CC3D can simulate agent-based models that consider mechanisms related to susceptible cells in target tissues
  • Available tool online: https://nanohub.org/resources/coviddrugexp
  • Interactive tool to modify therapeutic model mechanisms and simulate emergent behaviors
  • Simulated therapies
    • Viral internalization blocker
    • Viral replication blocker
  • Drug therapy parameters
    • Potency
    • Dosing period
    • Metabolism and elimination rates

Juliano Ferrari Gianlupi, Tarunendu Mapder, T. J. Sego, James P. Sluka, Sara K. Quinney, Morgan Craig, Robert E. Stratford Jr, and James A. Glazier. "Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2." Viruses 14 (2022): 605.

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Basic Tissue Patch Model with Simplified Immune Cells

“A modular framework for multiscale, multicellular, spatiotemporal modeling of acute primary viral infection and immune response in epithelial tissues and its application to drug therapy timing and effectiveness,” T. J. Sego, et al., 21 Dec 2020 PLOS Computational Biology, https://doi.org/10.1371/journal.pcbi.1008451

Uninfected

Infected

Virus releasing

Dead

Epithelial

Immune

Virus

Cytokine

Oxidative Agent

On-line version available at https://nanohub.org/tools/cc3dcovid19

Drugs like Remdesivir inhibit RNA synthesis in viral replication

By Boghog - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=89892581

Active agent is a metabolite of the prodrug

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How Does Spatial Inhomogeneity Affect the Predictions of Pharmacokinetic Models?

  • What are the effects of heterogeneous cell metabolism of the drug on outcomes?
    • A pure population + PK model wouldn’t be able to investigate effects of heterogeneity inside that population, as they would be washed out by the mean behavior
    • Even if there’s stochasticity in population their effects would be washed out by mixing
  • Expect that infection progression will depend on amount of time spent above below the half-maximal inhibitory concentration (IC50)

Scivit, 28 April 2020, https://en.wikipedia.org/wiki/ADME#/media/File:Pharmacokinetics.svg

Relative uptake rates

Relative elimination rates

Ferrari Gianlupi, Juliano, et al. "Multiscale Model of Antiviral Timing, Potency, and Heterogeneity Effects on an Epithelial Tissue Patch Infected by SARS-CoV-2." Viruses 14 (2022): 605.

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Cellular Metabolic Heterogeneity Worsens Outcomes

  • Heterogeneity in drug metabolism by cells worsens outcomes
  • Double dose required to achieve same control

More potent drug

Heterogeneous

Homogeneous

Longer period in between doses

Potency multiplier

100x 50x 33x 25x 20x 16x 14x 12.5x 11x 10x

Potency multiplier

100x 50x 33x 25x 20x 16x 14x 12.5x 11x 10x

  • Changing variability of metabolism moves the boundary between effective and ineffective treatment
  • High heterogeneity makes control challenging
  • If we want to use models effectively in the design of clinical treatments we have to quantify and model spatial heterogeneity, so we should integrate cell-to-cell heterogeneity when we build and apply PBPK models

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Investigating Biological Mechanisms: Cells that Don’t Metabolize the Prodrug into the Antiviral Well Responsible for Most Viral Production

  • Simulations where cells were heterogeneous in either their uptake or elimination rates
  • Cells that don’t metabolize the drug into its active component fast or that eliminate it fast produce the most virus
    • Effectively, we have super spreader cells
  • Change with the uptake rate is steady, on the elimination rate there is a plateau

“Homework”—Edit the Dosing nanoHUB Demo to include this variance

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Strengths of Virtual Tissues

  • Function as ‘variable magnification’ virtual microscope to allow study of processes at variable spatial and temporal resolution
  • Simulations with graded perturbations can infer thresholds for systemic effects when feedback within and between scales can lead to amplification and permanent disruption or compensation and recovery from molecular-scale perturbations
  • Infer hard-to-observe parameters and test mechanistic hypotheses
  • Allows exploration of more combinatorics than experiments and exploration of contrafactual situations
  • Visualize and communicate systems-level outcomes
  • A valuable platform for knowledge integration and reuse and to extract more understanding from existing data
  • Explore contrafactual conditions not possible in experiment
  • Building models codifies and tests biological understanding and reveals critical gaps in understanding and experimental data
  • Exploring new conditions and adding replicas is effectively free once you have the models built

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Mechanica VT Simulation Environment

  • Interactive particle-based modeling and simulation environment
    • Large-scale, long-range mechanical interactions, deformations and flow
    • Simultaneous, multiscale modeling and simulation
    • Large-scale simulations (~100k agents real-time, >1 million batch)
    • Direct simulation initialization from segmented data
  • Framework supports:
    • single-molecule molecular dynamics
    • macromolecular machinery simulation
    • cell-based multicellular tissue modeling
  • Particle-based off-lattice method
  • Multithreaded, dynamic GPU-accelerated (CUDA)
  • Supported on Windows, Mac, Linux
  • Model spec. in C, C++ and Python
  • Github: https://github.com/tjsego/mechanica
  • Available on conda: “conda install -c mechanica mechanica”

Center-model simulation of failed and successful (blue) gastrulation in sea urchin

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Jupyter CC3D

  • Coming soon: CC3D in Jupyter Notebook
  • Multicellular simulation supporting modern research productivity, training, education and outreach
    • Sharable
    • Interactive
    • Self-documenting
    • Publishable
  • Lightweight interface, same capability
    • All Python model specification
    • Development in a browser
    • Interactive, real-time execution and visualization

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Links and Disclosures

  • You can download CompuCell3D software from www.compucell3d.org or run them on line at https://nanohub.org/tools/cc3dcovid19
  • Especially useful for studying the effects of microdosimetry or cell-cell variation in metabolism or uptake

Teach 2022 Virtual Summer Workshop on these Methods August 1-7

2021 Course is available on YouTube: https://youtube.com/playlist?list=PLiEtieOeWbMIitJHcLMrDvKHDOJRVpUbO

Happy to support you apply CC3D in your applications: jaglazier@gmail.com

Support: NIH NIBIB-U24EB028887, NIGMS-R01GM122424, NSF-188553, NSF-186890, NSF-1720625, NIGMS-R01GM076692, NIGMS-R01GM077138, NIBIB/NIGMS/NIEHS-U01-GM111243, Falk Medical Research Trust, IUCRG, EPA, NSF, AMGEN

Disclosure: Dr. Glazier and other investigators listed have filed for international patent protection for the ADPKD and Diabetic Retinopathy therapies under development and have financial interest in Apoptocys Inc. and Virtual Tissues For Health LLC, also owns a small amount of stock in Gilead. D. Stratford is employed by Otsuka Pharmaceutical Co., Ltd.