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From 2012.igem.org

Modeling

Levels of Investigation

• How biofilm responds to shear, flow, temp, surface attachment, etc
• How Silica traps the particle during flow
• How Curli adheres and how OmpA-Silicatein Alpha polymerizes Silica/How the silica crystalizes (introduction of Salicylic Acid)
• How protien expression responds to external and metabolic variation (e.g. introduction of IPTG to system)
• How constructs work with each other/controls systems
• How RBS/ Promoter effects protein expression

Distribution of Modeling

Matlab

• Protein Production
• Feed Forward Loop Control Structure

TinkerCell

• Quorum sensing
• Feed Forward Loop

JMP

• Experimental Design and Characterization Experiments

Comsol/Other

• Waterflow and shear force on final system
• Silica formation

Design

Desired Outcomes of Models

Levels of Abstractions

Biofilter response to Environmental conditions

• Shear
• Flow
• Temperature
• Abiotic Surface (Adhesion)

Formation of Silica Matrix

BioFilm Development

• Model of Bacterial Growth, Death, Breaking Off

Expression of Proteins

• Response to addition of IPTG
• Optimal Production rate/expression of Curli and OmpA-Silicatein Alpha protiens
• Control Systems
• Fine Tuning of Protein Expression with RBS/Promoter combination variants

Platforms

Considerations and Assumption

Parameters

Equations

The growth of the Biofilm can be modeled with modified continuous growth models. Traditional models of population growth make use of basic differential equations to measure the change in population over unit time. At the most fundamental level

Population Change Rate =	dN	= bN-dN
	dt

Where N is the population of individuals, b is the rate of births or immigration, and d is the rate of deaths or emigration.

To understand these dynamics of population in the context of biofilm growth, we treat the bacterial attachment and detachment as a reversible reaction of the form

N Bacteria Attached <	k1	> N Bacteria Detached
	k2

Where k₁ is the rate constant of detachment and k₂ is the rate constant of attachment. Because we have chosen to simplfily the cell attachment and detachment as a reaction, we are able to employ reaction kinects to predict the rate of binding that will dictate the constants to population growth.

Such assumptions allow us to make use of basic principles of reaction kinetics such as a the Law of Mass Action

Assumptions and Simplifications

Outcomes

Parameter	Theoretical Value	Experimental Value	Analysis
Parameter 1	____	____	____
Parameter 2	____	____	____
Parameter 3	____	____	____
Parameter 4	____	____	____