1. The Computable Plant Claire Schulkey Kiri Hamaker California Institute of Technology Dr. Bruce E. Shapiro

2. Overview What are the shoot apical meristem (SAM) and auxin? What are the shoot apical meristem (SAM) and auxin? What is our project? What is our project? How does our project involve the SAM and auxin? How does our project involve the SAM and auxin? How are we going to make an auxin transport model? How are we going to make an auxin transport model?

3. Shoot Apical Meristem (SAM) The SAM is a bunching of plant stem cells at the very tip of a plant stem. The SAM is at a dynamic equilibrium, maintaining a stock of stem cells while allowing other cells to differentiate into specific plant tissues. A SAM and forming leaf primordia http://www.science.siu.edu/landplants/Lycophyta/lycophyta.html

4. Auxin is a signaling hormone in plants believed to influence a variety of a plant’s physiological processes though regulation of gene expression. Indole-3-acetic acid (IAA), the most prevalent auxin in plant growth Image released to public domain by author, and modified by C. Schulkey Auxin

5. Project Overview Create a working model of how auxin is transported throughout a network of cells. Create a working model of how auxin is transported throughout a network of cells. This model represents a 2-D slice of the SAM in the layer with chemical reactions denoted by differential equations with robust initial conditions, formulated by the xCellerator plugin in Mathematica. This model represents a 2-D slice of the SAM in the L1 layer with chemical reactions denoted by differential equations with robust initial conditions, formulated by the xCellerator plugin in Mathematica. Image released to public domain by author, and modified by Kiri Hamaker

6. The Computable Plant A long term project whose encompassing goal is to determine: How genetic makeup and environment affect developmental processes involved in forming tissue and organs in undifferentiated cells. A long term project whose encompassing goal is to determine: How genetic makeup and environment affect developmental processes involved in forming tissue and organs in undifferentiated cells. This project has implications in forefront biomathematics, systems biology, and microbiological imaging and has played a part in key development of revolutionary tools in the field. This project has implications in forefront biomathematics, systems biology, and microbiological imaging and has played a part in key development of revolutionary tools in the field. Image released to public domain by author

7. Tools SBML SBML (Systems Biology Markup Language) (Systems Biology Markup Language) xCellerator xCellerator Mathematica Mathematica

8. SBML Low-level computer- readable format Low-level computer- readable format Created for modeling microbiological pathways Created for modeling microbiological pathways Users employ high-level tools to interface with SBML Users employ high-level tools to interface with SBML In Mathematica, we use a specific form of SBML created by Dr. Shapiro: MathSBML In Mathematica, we use a specific form of SBML created by Dr. Shapiro: MathSBML Sample code taken from basic model definition handbook: Systems Biology Markup Language (SBML) Level 1: Structures and Facilities for Basic Model Definitions, Michael Hucka, Andrew Finney, Herbert Sauro, Hamid Bolouri, http://sbml.org/specifications/sbml-level-1/version-2/html/sbml-level-1.html

9. xCellerator User-friendly Mathematica package User-friendly Mathematica package Accepts inputs into chemical reactions selectable through an organized xCellerator palette Accepts inputs into chemical reactions selectable through an organized xCellerator palette xCellerator translates chemical reactions into sets of ordinary differential equations Mathematica can use xCellerator translates chemical reactions into sets of ordinary differential equations Mathematica can use xCellerator package functions with multiple plugins for employing sets of ODEs to create models as desired, including: xCellerator package functions with multiple plugins for employing sets of ODEs to create models as desired, including: MathSBML – interprets/edits SBML MathSBML – interprets/edits SBML Cellzilla – creates/manipulates cell networks Cellzilla – creates/manipulates cell networks Qhull – supports coordinate modeling in 2D, 3D, and further dimensions Qhull – supports coordinate modeling in 2D, 3D, and further dimensions

10. Mathematica Powerful and flexible mathematical computing software Powerful and flexible mathematical computing software Main framework for computing lists of differential equations generated by xCellerator Main framework for computing lists of differential equations generated by xCellerator

11. Project Stepping Stones 1. Determine the important processes influencing auxin transport and Aux/IAA regulation 2. Create a model for a single cell 3. Expand the single cell model to a network

12. Step 1: Process Selection Auxin Influx/Efflux Proteins Auxin Influx/Efflux Proteins PIN1, AUX1 (EIR1?, AXR4?) PIN1, AUX1 (EIR1?, AXR4?) These auxin transport proteins, with passive diffusion, move auxin into and out of a cell. These auxin transport proteins, with passive diffusion, move auxin into and out of a cell. Proteins and genes involved in Aux/IAA protein pathway Proteins and genes involved in Aux/IAA protein pathway ARF, auxin response factor Active/inactive Aux/IAA gene Proteasomal degredation Charged and uncharged auxin

13. Step 2: Model a single cell Simple Overview

14. Step 2: Model a single cell

15. Step 3: A network of cells (future work) The model can then be expanded to encompass a number of cells to model the flow of auxin in a network. Visual representations of the auxin flow may be created for more complete understanding of the model’s implications. Image taken from wild-type Wuschel activity simulation: Jönsson, Henrik et. al. Modeling the organization of the WUSCHEL expression domain in the shoot apical meristem. Bioinformatics 21(S1):i232-i240 (July 2005).

16. Acknowledgements Dr. Bruce E. Shapiro Dr. Bruce E. Shapiro Biological Network Modeling Center (BNMC) Biological Network Modeling Center (BNMC) The Computable Plant Team The Computable Plant Team SoCalBSI mentors and students SoCalBSI mentors and students Special Thanks to: NIHNSF Los Angeles – Orange County Biotechnology Center