(4nb) Cell-Free Synthetic Biology: A Novel Platform for Biomanufacturing and Diagnostics

Engineerable biological systems have the potential to be some of our greatest tools against a host of problems, from biological and chemical threats to human health, to food insecurity, and the sustainable production of materials. Understanding the fundamental building blocks of complex biological systems and their interactions lies at the heart of creating biological tools that can function robustly, predictably, and with quantitative precision. In my work, I utilize the tools of cell-free synthetic biology to perform high-throughput characterization of cell-free biological systems with the goal of both understanding their fundamental function and improving their ability to generate novel mechanisms for biological sensing and biological production. These methods reconceptualize how biological systems are engineered for applications in health, materials, and energy. In this manner cell-free synthetic biology functions as a tool to perform fundamental research by applying it to novel questions; as an applied engineering method; and as a field of study in and of itself. My lab will focus on developing new strategies that expand our traditional models of biomanufacturing by taking a data-driven and multiplexed approach to elucidate fundamental principles that allow for scalable cell-free synthetic biology.

Specifically we will focus on three key projects to take a holistic approach to generating the tools and fundamental knowledge to develop cell-free systems as scalable biomanufacturing platforms and research tools: computationally driven design of biosensors, machine learning-enabled materials production, and fundamental explorations of cell-free metabolism towards small molecule production. Scaling these systems to more effectively function as high-throughput tools for biological discovery and biological manufacturing will be pivotal to addressing challenges spanning the gamut from medical and environmental diagnostics to the production of complex molecules. The core competencies of my lab combined with significant interest in scaling novel biomanufacturing platforms and technologies will provide rich avenues for both academic and government collaborations across a variety of disciplines, as well significantly contribute fundamental knowledge to the fields of synthetic biology and bioengineering.

Research Experience:

During my PhD work, as part of the Plant-Microbe Interfaces project at Oak Ridge National Lab, I took on the challenge of developing biological tools for the exploration of metabolic networks outside of the traditional methods of generating genetic systems for organisms of interest. My graduate studies were completed at the University of Tennessee Knoxville and Oak Ridge National Laboratory under the guidance of Dr. Mitchell Doktycz where my work led to several awards including the National Science Foundation’s Graduate Research Fellowship as well as to eight peer-reviewed publications, with several in various stages of the submission process.

Following my graduate work, I became interested in the prospect of further enabling the development of cell-free systems as a scalable platform technology. As part of a joint postdoc with the US Army DEVCOM CBC and Caltech, I was awarded a National Research Council Fellowship to develop scaling methodologies as a member of the Cell-Free Biomanufacturing Institute, a congressionally-funded effort with Northwestern University. Our successes in these efforts have advanced the use of high-throughput characterization techniques for cell-free enabled production of solid-matrix biosensors and small molecules leading to significant progress scaling cell-free systems as production platforms and three submitted manuscripts with four currently in preparation.

My current work continues to expand on the data-driven approaches to high-throughput cell-free synthetic biology that I developed during my NRC fellowship. At Caltech I have been focusing on the use of machine learning-based methods to enable biological discovery; specifically, the use of machine learning and large-language models to effectively develop novel tools for biological sensing and biological catalysis. These efforts have led to a $405,000, and a $750,000 grant from the DoD, with me as principal investigator, for the development of cell and cell-free based tools for genetic code expansion and machine learning methods for biological polymer production, respectively.

Qualifications to Complete this work:

Throughout my career I have successfully collaborated on and completed multiple cross-disciplinary papers and projects that expand on the functions, scale, and methodologies used to generate and utilize cell-free systems. My postdoctoral work at the Department of Defense and Caltech has provided me with substantial experience in securing independent funding, managing the administrative duties of running a laboratory, and mentoring multiple graduate students on independent research projects. These foundations have given me an excellent preparation for integrating into work at university setting. The partnerships and collaborations I have developed throughout the DoD and Caltech, as well as the increased governmental emphasis on investment in novel biosensing and biomanufacturing capabilities, represent significant potential future collaborators and initial funding sources for my research.

Teaching Philosophy:

As an academic, I have always believed that mentoring students is the fundamental cornerstone of our profession. Becoming a faculty member presents an exciting opportunity not just because of the ability to generate new knowledge, but also because of the promise and privilege of sharing it with students.

My approach to teaching is largely inspired by the liberal arts pedagogy I benefited from as an undergraduate. These methods emphasize melding theory and practice in a way that translates well to lab settings even at large research institutions. In my Synthetic Biology International Genetically Engineered Machine (iGEM) course, I served as a mentor and teaching assistant and taught the fundamentals of biochemistry and molecular biology by directly connecting lectures to both the laboratory practicum and the iGEM students’ project. Problem sets were directly inspired by both the lab and lecture materials in order to reinforce the skills students would need not just on the team but in their future careers. I found this approach effectively helped students understand not just the concepts and laboratory skills but also allowed them to develop a perspective for a much larger effort. As result of this pedagogical style, my examinations are largely essay and project based so as to test both a theoretical and practical application of the student’s knowledge.

My experience spans a wide variety of topics including biochemistry, molecular biology, analytical techniques, and metabolic engineering. I am well prepared to teach undergraduate courses as well as serve as an advisor and teacher for graduate students. Given the scope of my current research, I am particularly interested in teaching classes that focus on synthetic biology, enzymology, and the application of computational methods to chemical and biological problems.

As a mentor, I have always tried to focus on understanding the needs of the students under my tutelage. The cornerstone of my approach has always been to make myself readily available to my students and to ensure that they know I am always available for anything from simple questions to rectifying mistakes. I have found that providing feedback on a student’s ability to describe their work, either through talks or written reports, allows me to effectively steer a project and provides them with a more holistic view of the mechanics and purpose of their work.

Selected Publications:

• Brown, D.M., Phillips, D., Garcia, D.C., et al. Semi-automated Production of Cell-Free Biosensors. In Submission. (2024)
• Phillips, D.; Garcia, D.C., Davidson, C., et al. High-throughput toolkit for assembly, analysis, and scale-up of cell-free sensor reactions on paper tickets. In Prep (2024)
• Garcia, D.C.; Davies, J.P., Phillips, D., Miklos, A., Lux, M. High-Throughput Optimization of Paper-Based Cell-Free Biosensors. BiorXiv https://doi.org/10.1101/2024.10.03.616554. (2024)
• Garcia, D.C., Davies, J.P., Lee, M., Lux, M. Cell-Free Optimized Production of Protoporphyrin IX. BiorXiv, https://doi.org/10.1101/2023.12.28.573540. (2023)
• McManus, J.B., Bernhards, C.B., Sharpes, C.E., Garcia, D.C.; Cole, S.D.; Murray, R.M.; Emanuel, P.A.; Lux, M.W. Rapid Characterization of Genetic Parts with Cell-free Systems, Journal of Visualized Experiments, (2021)
• Garcia, D.C., Dinglasan, Jaime L.N., Shrestha, H., Abraham, P.E., Hettich, R.L., Doktycz, M.J; A lysate proteome engineering strategy for enhancing cell-free metabolite production. Metabolic engineering communications. (2020)
• Garcia, D.C., Cheng, X., Land, M, Standaert, R., Morrell-Falvey, J., Doktycz, M. Computationally-Guided Discovery and Experimental Validation of Indole-3-Acetic Acid Synthesis Pathways. ACS Chemical Biology. (2019).
• Cecil, J. H.; Garcia, D. C.; Giannone, R. J.; Michener, J. K. Rapid, Parallel Identification of Catabolism Pathways of Lignin-Derived Aromatic Compounds in Novosphingobium Aromaticivorans. Environ. Microbiol. (2018)
• Garcia, D.C., Mohr, B., Dovgan, J. T., Hurst, G. B., Standaert, R. F., and Doktycz, M. J. Elucidating the potential of crude cell extracts for producing pyruvate from glucose. Synthetic Biology. (2018).
• Rydzak T.M., Garcia, D.C., Stevenson, D., Armador-Noguez, D., Sladek, M., Klingeman, D.M., Holwerda, E., Brown, S.D. & Guss, A.M. Deletion of Type I glutamine synthetase deregulates nitrogen metabolism and increases ethanol production in Clostridium thermocellum. Eng. (2017)

Selected Fellowships, Awards, and Grants:

• Grant: Co-PI with Marilyn Lee: DoD Tri-Service Biotechnology for a Resilient Supply Chain (T-BRSC) ($300K) (2024)
• Grant: Principal Investigator: Chemical Biological Advanced Materials and Manufacturing Science ($750K) (2023)
• Grant: Principal Investigator: DEVCOM CBC Laboratory Independent Research Program ($405K) (2022)
• Fellowship: National Research Council Postdoctoral Fellowship (2020)
• Award: ORNL (Biosciences Division) Distinguished Achievement Award (2020)
• Award: UT Extraordinary Professional Promise Award (2020)
• Fellowship, National Science Foundation Graduate Research Fellowship (2016)

For more details, please visit my website: https://david-c-garcia.github.io or contact me directly at Dgarciac@caltech.edu.