Evolable Living Computing: Understanding and Qunatifying Synthetic Biological Systems' Applicability, Performance and Limits

Successful computing systems leverage their underlying technologies to solve problems humans simply cannot. Electronic systems harness the power of radio waves and electrons. Mechanical systems use physical force and physical interactions. Biological systems represent a computing paradigm that can harness evolution, adaptation, replication, self-repair, chemistry, and living organisms. Engineered, living biological systems which make decisions, process "data", record events, adapt to their environment, and communicate to one another will deliver exciting new solutions in bio-therapeutics, bio-materials, bio-energy, and bio-remediation. This project will create a quantitative set of freely available design principles, computational tools, mathematical models, physical biological artifacts, educational resources, and outreach activities. Once available, these resources will allow for novel, living biological solutions to be built more quickly, perform better, be more reliable to manufacture, and cost less to produce. This project is unique in that these resources will be explicitly developed to validate key computational concepts to understand how well these concepts can be applied rigorously and repeatedly to biology. This project decomposes these concepts into three areas: Computing Paradigm (digital, analog, memory, and communication), Computing Activity (specification, design, and verification), and Computing Metric (time, space, quality, and complexity). Once complete, this project will provide the most comprehensive, freely available, and computationally relevant set of building blocks to engineer biological systems to date.

By developing the tools, techniques, and materials outlined in this project, this research will fundamentally change the way biological systems are specified, designed, assembled, and tested. Advanced bio-energy, bio-sensing, bio-therapeutics, and bio-materials all will become increasingly viable commercial technologies that can be made better, cheaper, faster, and more safely as a result of this project. The education of an entire new generation of engineers will occur through workshops, coursework, and community engagement activities. This new generation will have access to these approaches which will influence how biological computation is done and how that process is communicated to the community. This project will bring computational questions and methods to the forefront of biotechnology via an interdisciplinary research team focused not on one-off solutions but on foundational computing principles.

Explicitly five unanswered questions will be addressed in this project: (1) What computational models are available to biology, what are their limits, and how do they perform? (2) What communication mechanisms are available to biology, what are their limits, and how do they perform? (3) What are the theoretical and empirical measures of quality, scale, time, and space in biological computing systems? (4) How generalizable are the concepts and "design rules" which can be learned from studying biological systems? (5) How can the results (data and learnings) from biological specification, design, and verification be authoritatively disseminated to the community as design principles and grand challenges? This project addresses these questions with an interdisciplinary team with expertise in theoretical computer science, electronic design automation, bio-physics/chemistry, control theory, and molecular cell biology.