Research Collection Doctoral Thesis Directed Evolution of Enzymes using Ultrahigh-Throughput Screening Author(s): Debon, Aaron Publication Date: 2021 Permanent Link: https://doi.org/10.3929/ethz-b-000502194 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library DISS. ETH NO. 27208 DIRECTED EVOLUTION OF ENZYMES USING ULTRAHIGH-THROUGHPUT SCREENING A thesis submitted to attain the degree of DOCTOR OF SCIENCES of ETH ZURICH (Dr. sc. ETH Zurich) presented by AARON DEBON MSc Interdisciplinary Sciences, ETH Zürich born on 15.11.1990 citizen of Einsiedeln, Schwyz accepted on the recommendation of Prof. Dr. Donald Hilvert, examiner Prof. Dr. Andrew deMello, co-examiner 2021 Don’t play the butter notes. - Miles Davis Acknowledgements First, I would like to speak my deepest gratitude to my supervisor Prof. Don Hilvert for taking me in as his PhD student. His enthusiasm for science is a true inspiration and without his support and guidance none of this would have been possible. Additionally, I want to thank him for his excellent sportsmanship in the Schmutzli party. His ability ability not to laugh I will never forget. Along this line, I also want to thank Prof. Peter Kast, not only for being Don’s Schmutzli nemesis, but also for helpful inputs concerning everything microbiology. I’m grateful to Prof. Andrew deMello for refereeing this thesis and also the time I was able to spend working in his lab as a student. Furthermore, I want to thank Anita Meier-Lüssi and Antonella Toth for their help with administrative tasks and Leyla Hernandez for all her work in the lab. I want to thank the people that were mentors to me over the years. Big thanks go out to Sabine Studer for introducing me to the lab and, of course, being my Ying. I thank Anthony Green for his support in science and doubtful computer skills. Richard Obexer was the best microfluidics mentor imaginable, always challenging me to learn. Moritz Pott, without you I would also only be half the dancer I’m now. This thesis was proofread by Tom Edwardson, Oliver Alleman, and Dominic Hoch for which I’m extremely grateful. My time in the Hilvert lab was not only marked by science, but also by the many great friendships that were formed during my time here. I’m deeply grateful to Doug Hansen for being the best host in the west; keep an eye out for these rattle snakes. David Niquille’s repeated attempts to spark my interest in football weren’t successful, but "high/low"-five anyway. I thank Shiksha Mantri for her cooking skills and for inventing coop time. Furthermore, I want to thank Reinhard Zschoche for his timeless sense of style, Takahiro Hayashi for his iii iv excellent jokes, Stephan Tetter for co-spearheading, Mik Levasseur for admiring my forearms, Yusuke Azuma for proving that mornings are overrated, Oliver Allemann for teaching me the importance of speaking french in Paris, Susanne Mailand for never ending a night too early, brew master Christian Stocker, Xavi Garrabou for his various rants, Ines the Queenes Folger, Marcel Grogg for his group hike, and Duncan Macdonald and Anna Camus for sharing a home with me. The F328 lab was always a great working environment. I want to thank ev- eryone who contributed: Naohiro Terasaka for teaching me how to nap, Cathleen Zeymer for starting the snack tray, Richard Bernitzky for bringing new wind to the lab, Eita Sasaki aka the mountain goat, Sophie Basler for always laughing in the right moment, the talent scout Dominic G. Hoch, Sebastian Sjöstöm for his Swedish French press, and Raphi Frey for being an outstanding duet partner and fierce table tennis adversary. Also, they were brave enough to make me decide the music most of the time. The Höngg climbing group deserves special mention. The Austrian aces Madeleine Fellner and Matthias Tinzl, who thought me his language, and also Adrian Guggisberg for many hours spent at Gasi. Thanks to Thomas G. W. Edwardson for being the best person to get sandbagged with. Having great friends helps staying grounded besides the strenuous research life. Therefore, a big thank you to Jan Würschem, Roman Meier, Martin Meier, Sebastian Schenk, and Felix Schumacher for ski holidays and other time spent in the mountains and cities. I would not be writing these lines without the continuing support of my family. Thanks to my sister Mirjam and my mother Luzia. I’m deeply grateful for all the time, nerves, and energy you have invested into me. Thanks for always being there for me. Finally, I want to thank Anna Volokitin for being with me and for her loving support during the writing of this thesis. Abstract Virtually all biologically relevant chemical reactions are catalyzed by enzymes. The latter are sophisticated biocatalysts shaped by billions of years of natural evolution. Enzymes display astounding rate accelerations, specificities and selec- tivities. Some even reach catalytic efficiencies that allow reactions to take place at the speed of diffusion. In general, enzymes are far more efficient catalysts than their human-made small molecule counterparts, all while operating at ambient temperatures and in aqueous solution. Therefore, enzymes are of great interest in biotechnology to enable industrially important and environmentally impactful reactions under milder conditions. However, to render natural enzymes industri- ally useful, significant engineering to modify their function is typically required. With the advent of directed evolution as a robust method of tailoring enzyme function, this goal is now within reach. Several approaches to obtain new biocatalysts have been developed. The most widely used exploits the promiscuous activities of natural enzymes. More recently, computational design has enabled the creation of biocatalysts entirely from scratch. However, activities found from enzyme promiscuity or generated through computational design are generally low compared to naturally occurring enzymatic reactions. In both cases, low starting activities can be optimized by directed evolution, a powerful engineering algorithm that can be applied to tailor enzyme properties, in the absence of prior knowledge about structure or mechanism. Although directed evolution provides a method to explore new enzyme functions, beneficial mutations in the vast space of possible amino acid sequences are extremely rare. As a consequence many iterative cycles of mutation and screening may be needed to achieve the desired function. The success of laboratory evolution is thus often limited by the number of variants that can be screened in a reasonable amount of time. In this thesis, we explore fluorescence- activated droplet sorting (FADS) as an ultra-high throughput method to expedite v vi this process. Screening of enzymatic activity in microfluidic droplets offers a more than 1000-fold increase in throughput compared to regular microtiter plate-based assays. The commonly used means of detecting enzymatic reactivity in picoliter-sized droplets is fluorescence spectroscopy. This limits the utility of droplet sorting, because it usually requires the use of labeled model substrates of little real world interest. In Chapter 2, we describe a strategy that overcomes this limitation. Using an enzymatic cascade reaction to detect hydrogen peroxide, a common by-product of many enzyme-catalyzed reactions, oxidase enzymes can be assayed in ultra-high throughput in a label-free manner. We employed this approach to improve the promiscuous activity of cyclohexylamine oxidase (CHAO) for non- natural substrates. An initial library of CHAO variants containing four million members was created and sorted for oxidation of the non-natural substrates (S)-1- phenylpropylamine and 1,2,3,4-tetrahydroisoquinoline. For both amines, active variants were found that had a 9-fold and a 50-fold improvement in catalytic efficiency, respectively. This result is especially notable, as the respective starting activities of CHAO were 30% and 0.3% of its activity towards the native substrate cyclohexylamine. It demonstrates the large dynamic range in activities that can be handled by this FADS assay. By creating a bespoke mutant library for the hydrophobic active site of CHAO with non-degenerate codons, we targeted 75% of all active site residues simultane- ously. Using our assay we screened the resulting 1.7x106 variants for the oxidation of 1-phenyl-1,2,3,4-tetrahydroisoquinoline (PheTIQ), a bulky chiral active phar- maceutical ingredient for which the wild-type enzyme possesses little activity −1 −1 −1 (kcat=KM = 10 M s , kcat = 0.0095 s ). We discovered a mutant that shows −1 −1 a 960-fold improvement in kcat=KM of 9,400 M s towards the (R)-enantiomer of PheTIQ. Thus, in one step of mutagenesis and screening, we created an en- zyme that has similar activity to CHAO with its native substrate (kcat=KM = 10,630 M−1s−1). The large increase in efficiency is mainly the consequence of a 340-fold improved rate acceleration. Additionally, this variant proved to be highly selective, it exhibits a 4,200-fold preference for the (R)-enantiomer. As a result, (S)-1-phenyl- and (S)-1-ethyl-1,2,3,4-tetrahydroisoquinoline could be syn- vii thesized with e.e. values of 99% and 98%, respectively. Computational modeling and further kinetic characterization of this variant showed that the active site was radically reshaped to completely alter the substrate scope of the enzyme. Overall, the enzyme now preferentially converts (R)-enantiomers of bulky sec- ondary and primary amines, which constitutes a substantial switch in stereo- and substrate preference compared to the wild-type enzyme’s strong selectivity for small (S)-configured primary amines. Besides improving promiscuous enzyme activity, FADS has also been suc- cessfully applied to the optimization of computationally designed catalysts.