Difference between revisions of "SURF 2019: Modeling and Analysis on Robust Synthetic Consortia with Localized Functions"

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'''[[SURF 2018|2018 SURF]]: project description'''
'''[[SURF 2019|2019 SURF]]: project description'''
* Mentor: Richard M. Murray
* Mentor: Richard M. Murray
* Co-mentor: Xinying (Cindy) Ren
* Co-mentor: Xinying (Cindy) Ren
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*Deterministic and stochastic simulation algorithms
*Deterministic and stochastic simulation algorithms
*Feedback control in synthetic biology, analysis and estimation for dynamical systems
*Feedback control in synthetic biology, analysis and estimation for dynamical systems
'''Prerequisite Skills'''

You need to be familiar with:
You need to be familiar with:

Latest revision as of 01:15, 12 December 2018

2019 SURF: project description

  • Mentor: Richard M. Murray
  • Co-mentor: Xinying (Cindy) Ren


Engineering synthetic microbial consortia is an emerging area in synthetic biology. Multiple cell types can interact via cell-cell communications and perform more complex functions. Cooperation and competition are fundamental intercellular interactions, and can shape population level behaviors in consortia. Intercellular interactions can enhance stability of coexistence of multiple cell types and support robust communities by adapting to environmental disturbances. Designing robust synthetic consortia requires in-depth knowledge in cell internal dynamics, cell-cell communication mechanisms and cell growth, division and gene partition rules.

To realize multiple functions, there exist consortia with certain self-organized spatial structures in nature, such as biofilm and gut microbiome. The spatial structures are essential for localized functions and emergent population level behaviors. Designing synthetic consortia with localized functions need understanding of cell-cell and cell-environment interactions and cell movements caused by motility and division.

Building models and running simulations for synthetic consortia help to predict population levels. Analysis on system dynamics provide conditions for stability and robustness of the system. Combining models for intracellular chemical reactions, intercellular communications and cell growth, we can characterize multiscale dynamics and provide control principles for robust and spatially organized consortia.

Project Goals:

The aim of this SURF project is to provide theoretical insights to biological design using model predictions and analysis. There will be several potential modules and mechanisms to use in circuits design, so the modeling and analysis should include certain biology details. Specific interesting questions to think about:

  • What are the differences of cell population behaviors when using different intracellular regulatory modules (growth gene, self lysis gene, antibiotics resistant genes, etc.)?
  • How do cells switch cell-cell interactions (cooperation <-> competition) to adapt to environmental perturbations?
  • What drives spatial patterning of microbial consortia (heterogeneity in environment, intercellular interactions, etc.)?
  • How to avoid interference between cells that conduct localized functions (orthogonal signaling, growth/death competition, etc.)?

In this SURF project, you will learn:

  • Modeling for synthetic consortia across multiple scales
  • Deterministic and stochastic simulation algorithms
  • Feedback control in synthetic biology, analysis and estimation for dynamical systems

Prerequisite Skills

You need to be familiar with:

  • Synthetic biology and genetic circuit design
  • ODEs and PDEs
  • Probability and stochastic processes
  • Programming in Python (preferred) or Matlab


  1. Del Vecchio, D., & Murray, R. M. (2015). Biomolecular feedback systems. Princeton, NJ: Princeton University Press.
  2. Johns, N. I., Blazejewski, T., Gomes, A. L., & Wang, H. H. (2016). Principles for designing synthetic microbial communities. Current opinion in microbiology, 31, 146-153.
  3. Coyte, K. Z., Schluter, J., & Foster, K. R. (2015). The ecology of the microbiome: networks, competition, and stability. Science, 350(6261), 663-666.
  4. Nadell, C. D., Drescher, K., & Foster, K. R. (2016). Spatial structure, cooperation and competition in biofilms. Nature Reviews Microbiology, 14(9), 589.