Difference between revisions of "Team:UCSF/Description"

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"<p class='headerProjectSub'>INTRODUCTION</p><div class='headerBreakSub' style='width:100%'></div></br><p class='content1'><b style='color:#368E8C;font-size:1.5em'>Inspiration</b></br></br>We drew inspiration for this sense and secrete signaling motif by its ubiquity in natural systems <sup>[1]</sup>. By sensing a self-generated signal, cells participate in social and asocial behaviors that allow them to communicate decisions effectively with their neighbors <sup>[13]</sup>. This process is generally stochastic, due to the random local concentration makeups and molecular proximities of cells and signal <sup>[2]</sup>. However, sense and secrete signaling motifs allow for powerful mechanisms to alter community phenotypes. Cellular populations use this signaling molecule to create robust decisions for the whole population such as convergence, divergence, cell differentiation, or other community responses.</br></br>Sense and secrete circuits are found in most bacterial communities through species specific quorum sensing <sup>[12]</sup>. V. fischeri, aquatic bacteria that bioluminesce at certain cell densities, sense and secrete an autoinducer to keep a census of their population. Low signal concentrations are correlated with low cell density and high signal concentrations are correlated with high cell density. However, when confined to a small area, these signal concentrations are dramatically amplified and all bacteria activate a signaling cascade to bioluminesce. This is an example of cellular populations averaging out individual variation through communication.</br></br>Sense and secrete systems are also found in the adaptive immune system, which is comprised of T Cells with varied responses to a specific antigen <sup>[4. 10, 11]</sup>. When a T Cell senses an antigen, it initiates a signaling cascade in which a signaling cytokine, IL2, is secreted and a receptor for IL2 is produced <sup>[11]</sup>. After communicating to neighboring T Cells with IL2, the T Cell population coordinates its efforts to proliferate only the cells best suited to fight off the antigen. Thus, we see varied individual responses leading way to divergent community responses in T Cell populations after communication.</br></br>Community decision making can also be found in bacterial communities, such as B. subtilis <sup>[8]</sup>. These cellular populations are made of genetically identical cells that utilize extracellular signals to differentiate into phenotypically different cells that play specific roles in the survival of the community. B. subtilis utilizes a sense-and-secrete motif, similar to quorum sensing autoinducers, that couple with local environmental factors to assign “jobs” to individual cells in the community, and thus different molecular makeups. By communicating with members of their community, B. subtilis communities are able to amplify individual responses to differentiate cells into multiple distinct cell fates.</br></p></br>");
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"<p class='headerProjectSub'>INTRODUCTION</p><div class='headerBreakSub' style='width:100%'></div></br><p class='content1'><b style='color:#368E8C;font-size:1.5em'>Inspiration</b></br></br>We drew inspiration for this sense and secrete signaling motif by its ubiquity in natural systems <sup>[1]</sup>. By sensing a self-generated signal, cells participate in social and asocial behaviors that allow them to communicate decisions effectively with their neighbors <sup>[13]</sup>. This process is generally stochastic, due to the random local concentration makeups and molecular proximities of cells and signal <sup>[2]</sup>. However, sense and secrete signaling motifs allow for powerful mechanisms to alter community phenotypes. Cellular populations use this signaling molecule to create robust decisions for the whole population such as convergence, divergence, cell differentiation, or other community responses.</br></br>Sense and secrete circuits are found in most bacterial communities through species specific quorum sensing <sup>[12]</sup>. V. fischeri, aquatic bacteria that bioluminesce at certain cell densities, sense and secrete an autoinducer to keep a census of their population. Low signal concentrations are correlated with low cell density and high signal concentrations are correlated with high cell density. However, when confined to a small area, these signal concentrations are dramatically amplified and all bacteria activate a signaling cascade to bioluminesce. This is an example of cellular populations averaging out individual variation through communication.</br></br>Sense and secrete systems are also found in the adaptive immune system, which is comprised of T Cells with varied responses to a specific antigen <sup>[4, 10, 11]</sup>. When a T Cell senses an antigen, it initiates a signaling cascade in which a signaling cytokine, IL2, is secreted and a receptor for IL2 is produced <sup>[11]</sup>. After communicating to neighboring T Cells with IL2, the T Cell population coordinates its efforts to proliferate only the cells best suited to fight off the antigen. Thus, we see varied individual responses leading way to divergent community responses in T Cell populations after communication.</br></br>Community decision making can also be found in bacterial communities, such as B. subtilis <sup>[8]</sup>. These cellular populations are made of genetically identical cells that utilize extracellular signals to differentiate into phenotypically different cells that play specific roles in the survival of the community. B. subtilis utilizes a sense-and-secrete motif, similar to quorum sensing autoinducers, that couple with local environmental factors to assign “jobs” to individual cells in the community, and thus different molecular makeups. By communicating with members of their community, B. subtilis communities are able to amplify individual responses to differentiate cells into multiple distinct cell fates.</br></p></br>");
 
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Revision as of 17:26, 17 September 2015

BACKGROUND

Cells in a population can have varied responses to a stimulus, but are able to coordinate their responses through communication motifs. Chemical signaling to neighbors in a community can allow populations to make more robust and effective decisions as a collective whole.T Cells, for instance, need to know whether or not to proliferate to attack a given antigen. If too many proliferate, an autoimmune disorder is generated. If too little proliferate, the antigen continues to attack the body. By sensing the antigen at varying levels and communicating with the population, each T Cell knows whether or not it should activate and what level to activate at, in order to carry on their function properly.

But, how do these cells communicate and how do they understand their role as part of the collective? How do these genetically identical cells in the same population differentiate themselves from others? What motifs are necessary to elicit a bimodal response, in which high activating cells stay ON and low activating cells stay OFF? Our goal this year is to understand these questions and to take advantage of the natural variation found within cells of the same population in order to amplify that difference and create two divergent responses.

Our genetic circuit will utilize a stimulus that activates a fluorescent readout for individual response (GFP) and the secretion of a communication signal that is sensed and secreted by all members of the community. This community signal will in turn activate a fluorescent readout for community response (RFP).

General Circuit Diagram

SYNTHETIC MODEL

Basic Circuit Button Sense Circuit Button Degradation Circuit Button Hotspots Circuit Button Hotspots Circuit Button Synthetic Circuit Diagram

Click on the part of our circuit you are interested in learning about in the image above.

RETURN TO CIRCUIT

REFERENCES

  1. Balázsi, Gábor, Alexander Van Oudenaarden, and James J. Collins. "Cellular Decision Making and Biological Noise: From Microbes to Mammals." Cell 144.6 (2011): 910-25.
  2. Cotari, Jesse W., Guillaume Voisinne, and Grégoire Altan-Bonnet. "Diversity Training for Signal Transduction: Leveraging Cell-to-cell Variability to Dissect Cellular Signaling, Differentiation and Death." Current Opinion in Biotechnology 24.4 (2013): 760-66.
  3. Diener, Christian, Gabriele Schreiber, Wolfgang Giese, Gabriel Del Rio, Andreas Schröder, and Edda Klipp. "Yeast Mating and Image-Based Quantification of Spatial Pattern Formation." PLoS Comput Biol PLoS Computational Biology 10.6 (2014).
  4. Feinerman, O., J. Veiga, J. R. Dorfman, R. N. Germain, and G. Altan-Bonnet. "Variability and Robustness in T Cell Activation from Regulated Heterogeneity in Protein Levels." Science 321.5892 (2008): 1081-084.
  5. Höfer, Thomas, Oleg Krichevsky, and Grégoire Altan-Bonnet. "Competition for IL-2 between Regulatory and Effector T Cells to Chisel Immune Responses." Front. Immun. Frontiers in Immunology 3 (2012).
  6. Huberman, L. B., and A. W. Murray. "Genetically Engineered Transvestites Reveal Novel Mating Genes in Budding Yeast." Genetics 195.4 (2013): 1277-290.
  7. Jahn, Michael, Annett Mölle, Gerhard Rödel, and Kai Ostermann. "Temporal and Spatial Properties of a Yeast Multi-Cellular Amplification System Based on Signal Molecule Diffusion." Sensors 13.11 (2013): 14511-4522.
  8. López, Daniel, and Roberto Kolter. "Extracellular Signals That Define Distinct and Coexisting Cell Fates in Bacillus Subtilis." FEMS Microbiology Reviews FEMS Microbiol Rev 34.2 (2010): 134-49.
  9. Shiow, Lawrence R., David B. Rosen, Naděžda Brdičková, Ying Xu, Jinping An, Lewis L. Lanier, Jason G. Cyster, and Mehrdad Matloubian. "CD69 Acts Downstream of Interferon-α/β to Inhibit S1P1 and Lymphocyte Egress from Lymphoid Organs." Nature 440.7083 (2006): 540-44.
  10. Tkach, Karen, and Grégoire Altan-Bonnet. "T Cell Responses to Antigen: Hasty Proposals Resolved through Long Engagements." Current Opinion in Immunology 25.1 (2013): 120-25.
  11. Tkach, Karen E., Debashis Barik, Guillaume Voisinne, Nicole Malandro, Matthew M. Hathorn, Jesse W. Cotari, Robert Vogel, Taha Merghoub, Jedd Wolchok, Oleg Krichevsky, and Grégoire Altan-Bonnet. "T Cells Translate Individual, Quantal Activation into Collective, Analog Cytokine Responses via Time-integrated Feedbacks." ELife 3 (2014).
  12. Waters, Christopher M., and Bonnie L. Bassler. "QUORUM SENSING: Cell-to-Cell Communication in Bacteria." Annual Review of Cell and Developmental Biology Annu. Rev. Cell Dev. Biol. 21.1 (2005): 319-46.
  13. Youk, H., and W. A. Lim. "Secreting and Sensing the Same Molecule Allows Cells to Achieve Versatile Social Behaviors." Science 343.6171 (2014): 1242782.

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