SURF 2017: Length and time scales of cell-cell signalling circuits in agar

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2017 SURF project description

  • Mentor: Richard Murray
  • Co-mentor: James Parkin

One of the focuses of the Murray biolab is biological event detectors, specifically modified bacteria that are designed to alert a researcher that a specific condition in their local environment has occurred. As a part of this focus, we are trying to engineer a bacterial strain that detects the order in which a pair of chemical inducers are applied to opposite ends of an agar plate. The detector bacteria, embedded in the agar, will communicate with their neighbors to determine which chemical appeared first, as no individual cell would detect both chemicals.

The engineered bacteria communicate using protein components borrowed from natural quorum sensing systems. Quorum sensing (QS) systems are the communication paradigm of choice for many synthetic biologists because they are portable and reliable [1, 2, 4, 5]. Augmenting E coli with QS-mediated communication requires only two protein components, a signal synthase and a signal-activated transcription factor. Furthermore, QS signalling chemicals (acyl-homoserine lactones, AHL) freely diffuse through the cell walls of Gram-negative bacteria, no transmembrane transport protein required.

The summer project I am proposing is to investigate the characteristic length and time scales observed from various experimental setups and signalling circuits. Students would use previously-characterized genetic components to compose communication circuits in cells, grow them in various semisolid media preparations, expose them to different patterns of chemical inducers, and analyze the resulting patterns of gene expression in the growing bacteria. From these data, students would quantify the experimentally feasible range of pattern lengths and determine how the behavior of a circuit changes as cells approach stationary phase [1, 3, 5]. These results would provide information to help guide future research into self-patterning or spatiotemporal event detectors.

Students may also investigate how modeling can support this line of inquiry. This may involve anything from recreating experiments in simulators developed by other labs to writing their own numerical simulations from scratch. Similarly, analyzing images or videos of the communicating bacteria as they grow may be approached by identifying features by hand or through developing models that consider both spatially heterogeneous cell growth and reaction-diffusion treatment of cell-cell signaling.

Recommended skills:

  • Fluency with basic molecular biology and bacterial culture techniques
  • Experience with scientific programming (MATLAB, R, Python scipy, or similar)
  • Students interested in pursuing modeling or simulation should have significant previous work in numerical simulation software, multivariate calculus, and partial differential equations.

References:

  1. Liu, C. et al. Sequential Establishment of Stripe Patterns in an Expanding Cell Population. Science 334, 238–241 (2011).
  2. Dilanji, G. E., Langebrake, J., Leenheer, P. De & Stephen, J. Quorum activation at a distance : spatiotemporal patterns of gene regulation from diffusion of an autoinducer signal. 1–17 (2012).
  3. Basu, S., Mehreja, R., Thiberge, S., Chen, M.-T. & Weiss, R. Spatiotemporal control of gene expression with pulse-generating networks. Proc. Natl. Acad. Sci. U. S. A. 101, 6355–6360 (2004).
  4. Basu, S., Gerchman, Y., Collins, C. H., Arnold, F. H. & Weiss, R. A synthetic multicellular system for programmed pattern formation. Nature 434, 1130–1134 (2005).
  5. Tsimring, L. et al. A synchronized quorum of genetic clocks. Nature 463, 326–330 (2010).