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Scalable Platforms for Computation and Memory in Living Cells Scalable Platforms for Computation and Memory in Living Cells by Fahim Farzadfard Submitted to the Microbiology Graduate Program in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2018 © Massachusetts Institute of Technology 2018. All rights reserved. Author ….……………………………………………………………. Microbiology Graduate Program January 11, 2017 Certified by .…………………………………………………………. Timothy K. Lu Associate Professor of Biological Engineering and of Electrical Engineering and Computer Science Thesis Supervisor Accepted by …………………………………………………………. Kristala Jones Prather Arthur D. Little Professor of Chemical Engineering, Co-Director of the Microbiology Graduate Program 2 Scalable Platforms for Computation and Memory in Living Cells by Fahim Farzadfard Submitted to the Microbiology Graduate Program on January 11, 2018, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract Living cells are biological computers – constantly sensing, processing and responding to biological cues they receive over time and space. Devised by evolution, these biological machines are capable of performing many computing and memory operations, some of which are analogous to and some are distinct from man-made computers. The ability to rationally design and dynamically control genetic programs in living cells in a robust and scalable fashion offers unprecedented capacities to investigate and engineer biological systems and holds a great promise for many biotechnological and biomedical applications. In this thesis, I describe foundational platforms for computation and memory in living cells and demonstrate strategies for investigating biology and engineering robust, scalable, and sophisticated cellular programs. These include platforms for genomically-encoded analog memory (SCRIBE – Chapter 2), efficient and generalizable DNA writers for spatiotemporal recording and genome engineering (HiSCRIBE – Chapter 3), single-nucleotide resolution digital and analog computing and memory (DOMINO – Chapter 4), concurrent, autonomous and high-capacity recording of signaling dynamics and events histories for cell lineage mapping with tunable resolution (ENGRAM – Chapter 5), continuous in vivo evolution and synthetic Lamarckian evolution (DRIVE – Chapter 6), tunable and multifunctional transcriptional factors for gene regulation in eukaryotes (crisprTF – Chapter 7), and an unbiased, high-throughput and combinatorial strategy for perturbing transcriptional networks for genetic screening (PRISM – Chapter 8). I envision the platforms and approaches described herein will enable broad applications for investigating basic biology and engineering cellular programs. Thesis Supervisor: Timothy K. Lu Title: Associate Professor of Biological Engineering and of Electrical Engineering and Computer Science 3 4 Acknowledgments My time in graduate school has been a stimulating and rewarding journey, both personally and intellectually, and I am immensely grateful to all the people who contributed in different ways to writing this thesis. First and foremost, I want to thank my mentor, Prof. Timothy Lu; for creating a multidisciplinary and intellectually-stimulating environment in his lab in which I could thrive and pursue my scientific curiosities, for giving me the freedom to explore my ideas and learn, for guiding me how to identify and critically approach fundamental scientific questions and technological needs, and for his guidance and constant support throughout my PhD. I am grateful to my thesis committee members – Profs. Jim Collins, Michael Laub, David Bartel and Kevin Esvelt – for their mentorship and guidance and for making time in their busy schedules to meet me. Likewise, I am also grateful to Prof. George Church for serving on my thesis defense committee. I am grateful to the MIT Microbiology Graduate Program (in particular, Profs. Alan Grossman, Michael Laub, and Kris Prather) which gave me the opportunity to join the MIT community and shaped my graduate education. I am grateful to my friends and collaborators in the Lu lab for their camaraderie: Jacob Rubens, Robert Citorik, Mark Mimee, Ying-Chou Chen, Isaak Mueller, Ramez Daniel, Samuel Perli, Kevin Yehl, Yasutomi Higashikuni, Giyoung Jung, Zijay Tang, Eleonore Tham, William Chen, Jicong Cao and others. I also would like to thank Ky Lowenhaupt, for her tireless efforts to ensure everything runs smoothly in the lab. I am grateful to my parents, Mohammad and Mansoureh, and my sisters, Fahimeh, Farzaneh, and Farahnaz for their endless love, support, and inspiration throughout different chapters of my life. I am also grateful to my in-laws, for their continuous support. Finally, I am grateful to my wife, friend, and collaborator, Nava, who supported me constantly and unconditionally throughout this journey. Closing this chapter of my life, I feel immensely fortunate and elated knowing I have her by my side in my future journeys. 5 Table of Contents Chapter 1: Introduction ............................................................................................................. 8 Chapter 2: SCRIBE .................................................................................................................. 12 2.1 Abstract ....................................................................................................................... 12 2.2 Introduction ................................................................................................................ 12 2.3 Results ......................................................................................................................... 13 2.4 Discussion .................................................................................................................... 24 2.5 Supplementary Information ........................................................................................ 25 Chapter 3: HiSCRIBE .............................................................................................................. 49 3.1 Abstract ....................................................................................................................... 49 3.2 Introduction ................................................................................................................ 49 3.3 Results ......................................................................................................................... 51 3.4 Discussion .................................................................................................................... 64 3.5 Supplementary Information ........................................................................................ 66 Chapter 4: DOMINO................................................................................................................ 92 4.1 Abstract ....................................................................................................................... 92 4.2 Introduction ................................................................................................................ 92 4.3 Results ......................................................................................................................... 94 4.4 Discussion ................................................................................................................... 110 4.5 Supplementary Information ....................................................................................... 113 Chapter 5: ENGRAM .............................................................................................................. 137 5.1 Abstract ...................................................................................................................... 137 5.2 Introduction ............................................................................................................... 137 5.3 Results ........................................................................................................................ 138 5.4 Discussion ................................................................................................................... 142 5.5 Supplementary Information ....................................................................................... 143 Chapter 6: DRIVE .................................................................................................................. 147 6.1 Abstract ...................................................................................................................... 147 6.2 Introduction ............................................................................................................... 147 6.3 Results ........................................................................................................................ 149 6.4 Discussion ................................................................................................................... 158 6.5 Supplementary Information ....................................................................................... 160 Chapter 7: crisprTF ................................................................................................................ 171 7.1 Abstract ...................................................................................................................... 171 7.2 Introduction ............................................................................................................... 171 7.3 Results .......................................................................................................................
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