The Science of Collective Behaviors
Our inspiration for this project stems from the lack of comprehensive understanding of cellular collective behavior. In synthetic biology, it is particularly important to understand population mechanisms and collective behavior in order to properly replicate and study natural systems in a laboratory setting. From the study of T cell communication in immune responses to correcting for quorum sensing in bacterial cultures, collective behavior is a powerful, inevitable and largely unknown phenomenon in biological systems. Our project aims to create a synthetic cell circuit capable of not only modeling natural collective systems, but quantitatively analyzing such interactions.
As the biological sciences are making a shift from a qualitative science to a quantitative science, our team is making an effort to support this transformation by creating methods for replicable and standardized measurement of biological phenomena. By designing a solely synthetic circuit with modular parts, we are able to fine tune collective responses using various feedback loops and stimuli. Through this modular approach, we hope to expand this cell circuit to be able to replicate/simulate all different kinds of collective responses from autoimmune responses to cell adhesion. In addition, a key design feature of our cell circuit is an autonomous/community-coordinated readout able to be quantitatively measured with flow cytometry. Our cell circuit impacts science at the research level, helping scientists understand natural phenomena and providing a novel measurement tool. A standardized quantitative method of measurement, opposed to qualitative observations, will create a more transparent and un-biased data analysis tool for scientists to use and relay data to the public. We hope that our project will be able to provide novel insights into cellular communities and provide a tool to study various natural systems, with implications reaching into everything from pharmaceuticals to tissue-biology.
Scientist - Community Interactions
Outside of the wetlab, our research-driven approach in this year’s project hopes to combat the growing stigma of science in the public. Through media propaganda and general ignorance of the subject, biotechnology is generally looked upon as “elitist” and “secretive.” In the philosophy of iGEM, the UCSF/UCB team made it a primary goal this year to act as a bridge between the public and scientists to make science more accessible, transparent, and publicly involved.
In addition, our human practices were designed primarily to educate the public about synthetic biology in hopes of dispelling detrimental myths and creating awareness about the helpful applications of science in their daily lives. To do so, we presented a public outreach event at the Exploratorium and educated the public on the topic of “fact and fiction” in synthetic biology. Through a creative spin of superheroes on the matter, our team excited the public with the potential of synthetic biology, while promoting public involvement in science. Following this event, we have adapted our presentation into a curriculum and lesson packet) capable of introducing middle school and high school students to synthetic biology, in hopes of furthering science education. Toward this, our team also met with San Francisco city supervisors (pictured on the right) to discuss our project this year, garnering public support and advocating higher science education at the public school level. Through our project and public interactions this summer, we are optimistic in our approach to move science towards a transparent, exciting, and involved field.
Open Source Science
As part of this year’s West Coast iGEM Meetup, the teams present participated in an ethics forum organized by UCSC (pictured on the right). A panel of faculty members in science, policy, and ethics moderated the discussion and provided perspective to team questions and concerns.
Of particular interest was discussion about the issue of making data freely available to the public. There are many arguments for (e.g. providing tax-payer access to data resulting from their investment, increasing speed of progress and development, reducing barriers) and against (e.g. knowledge could be repurposed for malicious intents or marketed) open access data sharing. This is a complex issue, and there are no right or wrong answers. Ultimately, we came away with a more in- depth understanding of our responsibility as scientists to practice safe science and be cognizant of the downstream developments and implications of our work.
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