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Team:ETH Zurich/expresults/diffusion
From 2014.igem.org
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== Diffusion On Chip == | == Diffusion On Chip == | ||
| - | Our project aims for the biological implementation of [https://2014.igem.org/Team:ETH_Zurich/project/background/modeling#Cellular_Automata cellular automata] with [https://2014.igem.org/Team:ETH_Zurich/modeling/xor#XOR_Logic_Gate XOR] logic gates. In order to achieve this, we found a way to create a regular grid of cells with a defined, optimal neighborhood. This means channel length, well size, and medium were optimized and the properties were modelled with Matlab and Comsol whenever feasible. With these [https://2014.igem.org/Team:ETH_Zurich/modeling/diffmodel ''in silico'' results] in mind we used CAD software to design our custom made molds, which where then 3D-printed and used for the production of [https://2014.igem.org/Team:ETH_Zurich/lab/chip#PDMS_Chip_Preparation PDMS chips]. The cells containing one of our genetic circuits were encapsulated in [https://2014.igem.org/Team:ETH_Zurich/lab/bead alginate beads] and loaded on the [https://2014.igem.org/Team:ETH_Zurich/lab/chip millifluidic chip]. This approach allowed us to establish a method for measuring diffusion and cell-to-cell communication. In particular, a step towards the emergence of complex | + | Our project aims for the biological implementation of [https://2014.igem.org/Team:ETH_Zurich/project/background/modeling#Cellular_Automata cellular automata] with [https://2014.igem.org/Team:ETH_Zurich/modeling/xor#XOR_Logic_Gate XOR] logic gates. In order to achieve this, we found a way to create a regular grid of cells with a defined, optimal neighborhood. This means channel length, well size, and medium were optimized and the properties were modelled with Matlab and Comsol whenever feasible. With these [https://2014.igem.org/Team:ETH_Zurich/modeling/diffmodel ''in silico'' results] in mind we used CAD software to design our custom made molds, which where then 3D-printed and used for the production of [https://2014.igem.org/Team:ETH_Zurich/lab/chip#PDMS_Chip_Preparation PDMS chips]. The cells containing one of our genetic circuits were encapsulated in [https://2014.igem.org/Team:ETH_Zurich/lab/bead alginate beads] and loaded on the [https://2014.igem.org/Team:ETH_Zurich/lab/chip millifluidic chip] arranged in a Sierpinski triangle. All other wells were filled with beads containing cells not able to produce GFP as a background reference. This approach allowed us to establish a method for measuring diffusion and cell-to-cell communication. In particular, a step towards the emergence of complex patterns by cell-to-cell communication was made. Also the [https://2014.igem.org/Team:ETH_Zurich/modeling/diffmodel#Pattern_developing Comsol model] regarding pattern formation was confirmed experimentally with our rapid-prototyping approach. The final time-lapse video of the [https://2014.igem.org/Team:ETH_Zurich/project/background/biotools#Quorum_Sensing cell-to-cell communication] experiment is shown below in video 1. |
| - | {|class="wikitable" style="background-color: white; text-align:center; width:auto; margin: auto;" | + | {|class="wikitable" style="background-color: white; text-align:center; width:auto; margin: auto; font-size:10pt;" |
| - | |{{:Team:ETH_Zurich/Templates/Video|width= | + | |colspan="2" style='font-size:10pt';text-align:left|{{:Team:ETH_Zurich/Templates/Video|width=1080px|id=video3|ratio=1920/720|srcMP4=<html>https://static.igem.org/mediawiki/2014/b/b1/ETH_Zurich_2014_signal_propagation_with_simulation.mp4</html>|poster=<html>https://static.igem.org/mediawiki/2014/6/69/ETH_Zurich_2014_signal_propagation_with_simulation_preview.png</html>}} |
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| - | |'''Video 1''' '''Row wise, self-propagating [https://2014.igem.org/Team:ETH_Zurich/project/background | + | |colspan="2" style='font-size:10pt';text-align:left|'''Video 1''' '''Row wise, self-propagating [https://2014.igem.org/Team:ETH_Zurich/project/background#Biotools cell-to-cell communication] of ''E. coli'' cells confined in [https://2014.igem.org/Team:ETH_Zurich/lab/bead alginate beads] (d=3 mm, initially 10<sup>7</sup> cells/bead) on a [https://2014.igem.org/Team:ETH_Zurich/lab/chip custom-made millifluidic PDMS chip].''' |
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| + | |style="width:50%"| All cells contained [https://2014.igem.org/Team:ETH_Zurich/expresults/rr#Riboregulators riboregulated] sfGFP followed by [http://parts.igem.org/Part:BBa_C0161 LuxI (BBa_C0161)] together under the control of the [http://parts.igem.org/Part:BBa_R0062 pLux promoter (BBa_R0062)], and [http://parts.igem.org/Part:BBa_J23100 constitutively (BBa_J23100)] expressed [http://parts.igem.org/Part:BBa_C0062 LuxR (BBa_C0062)]. LuxI catalyzes the production of the autoinducer 3OC6-HSL, which is then diffusing from cell to cell. For initialization, the cells in one bead of the top row were induced with 3OC6-HSL before encapsulation. Imaging was implemented with a [https://2014.igem.org/Team:ETH_Zurich/lab/protocols#Biostep_Dark-Hood_DH-50.E2.84.A2__and_the_Argus-X1.E2.84.A2_software Biostep Dark-Hood DH-50 (Argus X1 software)] fitted with a Canon EOS 500D DSLR camera and a fluorescence filter (545 nm filter). Pictures were usually taken every 2 min at an excitation wavelength of 470 nm with the standard Canon EOS Utility software. Time-lapse movies were created with Adobe After Effects CC software. 1950x faster than real-time, the video shown starts 10 h after the initiation of the experiment (however the time scale shown corresponds to minutes after loading of the chip) | ||
| + | ||Simulation of the propagation of the pattern in the millifluidic chip. [http://www.comsol.com/comsol-multiphysics Comsol Multiphysics Simulation software] was used in order to simulate a detailed diffusion model including quorum sensing steps in colonies and cell growth. Overall GFP concentration in beads has been scaled in order to account for the high background of the experimental setup. Green Fluorescence Protein is produced earlier in the wells, but can be seen only above a certain threshold.<br>Accurate prediction of experimental data by the model has been achieved, with parameters from our own fittings or from the literature. Experimental observation combined with simulation enables to show that a pattern is able to develop in the millifluidic chip in a reasonable time scale. For precise equations and other dynamic results, check the [https://2014.igem.org/Team:ETH_Zurich/modeling/diffmodel Diffusion model] page. | ||
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Latest revision as of 15:41, 12 August 2015
Diffusion On Chip
Our project aims for the biological implementation of cellular automata with XOR logic gates. In order to achieve this, we found a way to create a regular grid of cells with a defined, optimal neighborhood. This means channel length, well size, and medium were optimized and the properties were modelled with Matlab and Comsol whenever feasible. With these in silico results in mind we used CAD software to design our custom made molds, which where then 3D-printed and used for the production of PDMS chips. The cells containing one of our genetic circuits were encapsulated in alginate beads and loaded on the millifluidic chip arranged in a Sierpinski triangle. All other wells were filled with beads containing cells not able to produce GFP as a background reference. This approach allowed us to establish a method for measuring diffusion and cell-to-cell communication. In particular, a step towards the emergence of complex patterns by cell-to-cell communication was made. Also the Comsol model regarding pattern formation was confirmed experimentally with our rapid-prototyping approach. The final time-lapse video of the cell-to-cell communication experiment is shown below in video 1.
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| Video 1 Row wise, self-propagating cell-to-cell communication of E. coli cells confined in alginate beads (d=3 mm, initially 107 cells/bead) on a custom-made millifluidic PDMS chip. | |
| All cells contained riboregulated sfGFP followed by [http://parts.igem.org/Part:BBa_C0161 LuxI (BBa_C0161)] together under the control of the [http://parts.igem.org/Part:BBa_R0062 pLux promoter (BBa_R0062)], and [http://parts.igem.org/Part:BBa_J23100 constitutively (BBa_J23100)] expressed [http://parts.igem.org/Part:BBa_C0062 LuxR (BBa_C0062)]. LuxI catalyzes the production of the autoinducer 3OC6-HSL, which is then diffusing from cell to cell. For initialization, the cells in one bead of the top row were induced with 3OC6-HSL before encapsulation. Imaging was implemented with a Biostep Dark-Hood DH-50 (Argus X1 software) fitted with a Canon EOS 500D DSLR camera and a fluorescence filter (545 nm filter). Pictures were usually taken every 2 min at an excitation wavelength of 470 nm with the standard Canon EOS Utility software. Time-lapse movies were created with Adobe After Effects CC software. 1950x faster than real-time, the video shown starts 10 h after the initiation of the experiment (however the time scale shown corresponds to minutes after loading of the chip) | Simulation of the propagation of the pattern in the millifluidic chip. [http://www.comsol.com/comsol-multiphysics Comsol Multiphysics Simulation software] was used in order to simulate a detailed diffusion model including quorum sensing steps in colonies and cell growth. Overall GFP concentration in beads has been scaled in order to account for the high background of the experimental setup. Green Fluorescence Protein is produced earlier in the wells, but can be seen only above a certain threshold. Accurate prediction of experimental data by the model has been achieved, with parameters from our own fittings or from the literature. Experimental observation combined with simulation enables to show that a pattern is able to develop in the millifluidic chip in a reasonable time scale. For precise equations and other dynamic results, check the Diffusion model page. |
