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THESE POUR OBTENIR LE GRADE DE DOCTEUR

DE L'UNIVERSITE DE MONTPELLIER

En Biochimie et biologie pour la santé

École doctorale Sciences Chimiques et Biologiques pour la Santé CBS2 N°168 Unité de recherche Centre de Biochimie Structurale de Montpellier

CNRS UMR5048 - UM - INSERM U1054

Présentée par Sarah GUIZIOU

Le 14 septembre 2018

Sous la direction de Jérôme BONNET

Devant le jury composé de

Dr. Yolanda SCHAERLI, Assistant professor, University of Lausanne Dr. Javier MACIA, Professor, Universitat Pompeu Fabra Dr. Pascal HERSEN, Directeur de recherche, Université Paris Diderot Dr. Patrick LEMAIRE, Directeur de recherche, Centre de Recherche de Biochimie Macromoléculaire

Rapporteur

Rapporteur

Examinateur

Président du jury

Engineering framework for scalable recombinase logic operating in living cells.

Acknowledgments

I would like to thank Prof. Yolanda Schaerli and Prof. Javier Macia for having accepted to evaluate my thesis, I thank you in advance for your feedback on this work. I would like to thank also Dr. Pascal Hersen, Dr. Patrick Lemaire, and Prof. Ricard Soléto act as examiners during my defense. I am looking forward to your striking remarks. First of all, I would like to warmly thank my PhD supervisor Jerome Bonnet. Jerome gave me a perfect environment to complete my PhD, in terms of science, working environment and people. I am deeply grateful to have him as a supervisor, for his support, his patience, his excitement for science and his sympathy. Jerome guided me during these four years on how to become a good scientist and a good person. Jerome was the best supervisor I could have ever expected, as he is an amazing scientist and more importantly a great person. I am very grateful to my team colleagues, Hung-Ju Chang, Pauline Mayonove, Peter Voyvodic, Ana Zuniga, Martin Cohen-Gonsaud and Angélique DeVish, which have filled the lab with great energy and good science. It has been great for me to work in this warm and intense scientific atmosphere. I am really thankful to Luca Ciandrini for his great scientific and human support and his calmness at all events. I would like to thank Guillaume Cambray for its helpful scientific critiques and advice. Thank you all for all the friendly times in the lab or around a beer, you all have been of great support: gracias, merci, thanks, grazie, Xiexie. I would like to thank my collaborators at INRA Jouy en Josas, Matthieu Jules and Vincent Sauveplane on the B. subtilis project. It was a pleasure to work with them on this project, and I am thankful for their patience, trust and support. Many thanks also to Nathalie Declerck and Caroline Clertéfor having shared their knowledge on the microscope and on B. subtilis with me. I would like to warmly thank my collaborators at the LIRMM, Michel Leclere, Guillaume Kihli and Federico Ulliana. It was for me a really exciting collaboration, and I am thankful for their excitement for the project, the intense scientific discussion and their patience on our multiple changes of opinion. I am really grateful to Konstantin Todorov who initiated this collaboration, and mainly for his friendship and for having added music to my thesis. I would like to thank Jean-Luc Pons for his patience and help during my linux and programming learning, and thanks also to Laurent Bonnet and Violaine Moreau for the great and warm website that is CALIN. I would like to thank the interns who worked with me: Léa Meneu, ChloéTailhades, So- phie Affalo, Stanley Mitchell, Morgane Terezol and Thomas Meiller-Legrand. They all have contributed to this work, they have been great people to work with and they have taught me patience. A special thanks to the iGEM team 2013. I started to work on recombinase-based logic gates during this summer. Thanks Elodie, Manon, Antoine, Antoine, Quentin, Stick, Yoann, ii Fanny, Isabelle, Hang for this intense project. I would like to warmly thank Gilles Truan who supervised us during the summer, had faith in me during this project and has supported me ever since. I would like to thank Claude Marange who took care of all of us during all our degrees. I am really grateful to have spent these four and a half years at the CBS. It was always a pleasure to come to the lab, thanks to Pierre-Emmanuel Millet who makes this place work as well as it does. Thanks to everyone at the CBS, which has been my second home and family during these years. I am really grateful to have been surrounded by all these skilled, friendly and cheerful colleagues and scientists. I want to especially thank Martin, Angélique, Pauline, Hung-Ju, Peter, Ana, Léa, Aurélie, Michel for being enthusiastic lab neighbors, and for having borne my grumbling. A special thanks to Lucile who guided me through latex and to Ashley who was always open to help me code, write or to have beers. A huge thanks to my office- mates Annika, Pauline, and Anna for the nice and welcoming working atmosphere, it has been wonderful for me to be surrounded by you. I am deeply thankful to have found awesome people at the CBS with whom I have spent many hours outside of the lab deciphering science and the world. Thanks to Ashley, Mélanie, Elise, Luca, Annika, Lucile, Peter, Pauline, ... all of the beer group. A warm thanks to all the previous members of the CBS, and especially to my first compan- ions of my thesis, Tom, Solène and Alice. I would like to give a special thanks to Alexis Courbet, for his friendship, his strong support, and the great philosophical and scientific discussions. Thanks for showing me the path through the PhD. I would like to warmly thank my two PhD student buddies: Pierre and Carola, with whom I shared all my thesis grumbling and who have always been there in the hard times and have pushed me through to the end. Good luck to Pierre for his last month(s) and to Carola for her final years. I have been lucky during all the years of my thesis and all the years before to have been surrounded by faithful friends. I am really grateful to have you guys, thanks Klervi, Melissa, Helo, Elodie, Caro, Zoé, Xavier, Manon, Antoine, Arthur, Helene and to the little

Gauthier.

To finish, I would like to warmly thank my parents, Maurice and Dominique, and my brothers, Léo, Maël, Erwan and Thomas for their unconditional support. A special thanks for welcoming me during my writing retreat, and thanks to Thomas for the gaming breaks. Thanks for your support from the beginning and for having always believed in me. I want to give a special thanks to sci-hub which has been a precious and loyal help during these four years. Thanks also to the birds and the four hens who have kept me company during my writing. Many thanks to the kilograms of bacteria that I have killed during my thesis; thanks for having given your body to science.

Contents

1 Introduction1

1.1Synthetic Biology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.1A brief history of synthetic biology. . . . . . . . . . . . . . . . . . . . . . 2

1.1.2Principles of synthetic biology. . . . . . . . . . . . . . . . . . . . . . . . . 5

1.1.3Technologies underpinning to the development and extension of synthetic

biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.1.4Engineering part libraries and complex devices. . . . . . . . . . . . . . . 9

1.1.5Applications of synthetic biology. . . . . . . . . . . . . . . . . . . . . . . 13

1.2Logic circuits built using biological components.. . . . . . . . . . . . . . . . . . 19

1.2.1Introduction to logic and circuit design strategies. . . . . . . . . . . . . . 20

1.2.2In vitrobiocomputing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

1.2.3Implementing logic circuits in living organisms -in vivobio-computation30

1.2.4A comparison of the different design strategies forin vivoimplementation

of Boolean functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

1.3Recombinases: tools for DNA editing. . . . . . . . . . . . . . . . . . . . . . . . . 40

1.3.1Serine and tyrosine recombinases and their mechanisms. . . . . . . . . . 40

1.3.2Recombinases as a tool for DNA editing. . . . . . . . . . . . . . . . . . . 47

1.3.3Recombinases as a tool for logic implementation. . . . . . . . . . . . . . 49

1.4Thesis objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2 Boolean logic in multicellular consortia using recombinases57

2.1An automated design framework for multicellular recombinase logic. . . . . . . . 58

2.2Implementation of multicellular Boolean logic using recombinase switches. . . . 66

2.2.1Selection of a set of four orthogonal integrases. . . . . . . . . . . . . . . 67

2.2.2Design of a standard logic device architecture. . . . . . . . . . . . . . . . 70

2.2.3Characterization of a set of logic elements. . . . . . . . . . . . . . . . . . 71

2.2.4Construction and characterization of the 14 computational devices for

4-input multicellular Boolean logic

. . . . . . . . . . . . . . . . . . . . . . 75 ivContents

2.2.5Prototyping a multicellular system simulating the implementation of com-

plex Boolean logic functions . . . . . . . . . . . . . . . . . . . . . . . . . . 82

2.2.6Characterization of parts to optimize logic devices. . . . . . . . . . . . . 86

2.2.7Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

2.2.8Materiel and Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

3 Programming history-dependent logic in a multicellular system109

3.1Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

3.2Automated design of history-dependent programs. . . . . . . . . . . . . . . . . . 113

3.2.1Distributing history-dependent gene-expression programs within a multi-

cellular system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

3.2.2A modular scaffold design to implement history-dependent gene expres-

sion programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

3.2.3Automation of history-dependent gene-expression program designs. . . . 116

3.2.4Minimization of history-dependent circuits using Boolean logic devices. . 116

3.3Implementation of history-dependent gene-expression programs in multicellular

consortia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

3.3.1OSiRIS: Optimization by SynthesIs of Recombination Intermediate States121

3.3.2Characterization of a history-dependent program by sequential induction128

3.4Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

3.5Materials and Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135

3.5.1Equations for the determination of number of functions/strains/devices

for history-dependent logic . . . . . . . . . . . . . . . . . . . . . . . . . . 135

3.5.2Automated generation of genetic designs to execute multicellular Boolean

logic and history-dependent gene expression programs . . . . . . . . . . . 135

4 Design of scalable single-cell recombinase logic141

4.1RECOMBINATOR: a framework for combinatorial design of single-cell integrase

logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142

4.1.1Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142

4.1.2Definition of a formal language to permit the generation of a design database144

4.1.3Ontology of synthetic gene circuits. . . . . . . . . . . . . . . . . . . . . . 146

4.1.4Generation of all possible sequences. . . . . . . . . . . . . . . . . . . . . 150

Contentsv

4.1.5A web-interface for exploring on the database. . . . . . . . . . . . . . . . 153

4.1.6Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154

4.2Using the Recombinator database for the systematic design and construction of

all single-cell 3-input logic gates . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

4.2.1P-class and itsin vivocorrespondence. . . . . . . . . . . . . . . . . . . . 156

4.2.2NP-class and itsin vivocorrespondence using DNA inversion. . . . . . . 158

4.2.3Using the Recombinator database to select inversion-based logic devices. 159

4.2.4Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161

5 Discussion163

5.1Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164

5.1.1Distribution of computation in multicellular system. . . . . . . . . . . . 164

5.1.2Minimization of Boolean logic circuit design.. . . . . . . . . . . . . . . . 165

5.1.3Systematic engineering of synthetic biological circuits.. . . . . . . . . . 166

5.2Control and engineering of serine integrase activity.. . . . . . . . . . . . . . . . . 167

5.3The use of integrase coupled with excisionase permits the implementation of

wider types of logic. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

5.4What are the future applications and future challenges of biocomputing?. . . . . 170

Bibliography173

Annex201

A Systematic rules for designing minimized integrase logic circuits.201 A.1Definition of elements and composition rules for the design of single-cell logic devices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 A.2Implementation in Python of a set of factorisation rules using a brute force approach204 A.3Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205

B Supplementary Information - Introduction207

B.1Implementation of computation by regulation of transcription using Zinc Fingers,

TAL effectors, and CRISPR.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 B.2In vivoimplementation of sequential logic systems.. . . . . . . . . . . . . . . . . 208 viContents B.2.1Circuits using rewritable memory devices.. . . . . . . . . . . . . . . . . . 208 B.2.2Irreversible history-dependent circuits.. . . . . . . . . . . . . . . . . . . . 209 C A part toolbox to tune genetic expression inB. subtilis211 D Supplementary Data: An automated design framework for multicellular re- combinase logic. 251
E Supplementary Data of History-dependent programs: Cell History Tracker257

F DNA sequences of parts, primers, fragments.261

F.1DNA sequences of parts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 F.2Primers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 F.3DNA sequences of fragments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273

G Protocols283

H BioArt295

Chapter 1

Introduction

Contents

1.1Synthetic Biology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.1A brief history of synthetic biology. . . . . . . . . . . . . . . . . . . . . . . 2

1.1.2Principles of synthetic biology. . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.1.3Technologies underpinning to the development and extension of synthetic

biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.1.4Engineering part libraries and complex devices. . . . . . . . . . . . . . . . 9

1.1.5Applications of synthetic biology. . . . . . . . . . . . . . . . . . . . . . . . 13

1.2Logic circuits built using biological components.. . . . . . . . . . . . . . 19

1.2.1Introduction to logic and circuit design strategies. . . . . . . . . . . . . . . 20

1.2.2In vitrobiocomputing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

1.2.3Implementing logic circuits in living organisms -in vivobio-computation. 30

1.2.4A comparison of the different design strategies forin vivoimplementation

of Boolean functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

1.3Recombinases: tools for DNA editing. . . . . . . . . . . . . . . . . . . . 40

1.3.1Serine and tyrosine recombinases and their mechanisms. . . . . . . . . . . 40

1.3.2Recombinases as a tool for DNA editing. . . . . . . . . . . . . . . . . . . . 47

1.3.3Recombinases as a tool for logic implementation. . . . . . . . . . . . . . . 49

1.4Thesis objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

2Chapter 1. Introduction

1.1 Synthetic Biology

1.1.1A brief history of synthetic biology

"Toutes les sciences naturelles suivent une évolution analogue, elles débutent par l?observation

et la classification des objets et des phénomènes, puis elles décomposent ceux-ci pour déterminer le mécanisme physique de leur production, elles deviennent alors analytiques ; lorsque le mécanisme d"un phénomène est connu, il devient possible, en dirigeant les forces

physiques, de reproduire ce phénomène ; la science est devenue synthétique. [...] La biologie

doit évoluer comme les autres sciences naturelles et être successivement descriptive, analytique

et synthétique.» "All natural sciences follow an analog evolution, they start from the observation and classification of objects and phenomena, they decompose these to determine the physical mechanism of their production, then they become analytic ; when the mechanism of a phenomenon is known, it becomes possible, by directing the physical forces, to reproduce this phenomenon ; science is becoming synthetic [...] Biology has to evolve as other natural sciences and to be successively descriptive, analytic, and synthetic.»

Stéphane Leduc 1910

"What I cannot create I do not understand.»

Richard Feynman 1988

Since the dawn of civilization, humans have studied and used living organisms that sur- rounded them, but also shaped those life forms via selective breeding to obtain improved sources of food and materials. We also developed workflows for large scale production of refined foods, such as beer or bread with yeast. However, at this time, we did not understand how living organism operate at the molecular level. The term "synthetic biology" was used for the first time by Stéphane Leduc [

Leduc 1910]

Leduc 1912]. Stéphane Leduc was interested in the synthesis of life from inanimate materials. At this time, he envisioned that biology would progress like the other sciences by successively being descriptive, analytical, and finally synthetic. This idea was mainly inspired from Jacques

Loeb and his mechanistic concept of life.

In 1961, in their publication summarizing their study of the lac operon, Jacques Monod and François Jacob envisioned the future ability to assemble new regulatory systems from elementary molecular components [ Monod 1961]. This publication is now considered as the origin of synthetic biology [ Cameron 2014]. It is also contemporary with the discovery of the structure of DNA [ Watson 1953], demonstrated a few years before to be the support of genetic information by Avery and colleagues [ Avery 1944] . By the late fifties, Francis Crick introduced the first definition of the central dogma of molecular biology [

Crick 1958].

1.1. Synthetic Biology3

Between 1960s and 1980s, various molecular biology tools were developed, leading to the field of genetic engineering. These breakthroughs included: (1) the discovery of restriction enzymes in the 1960s (Nobel Prize 1978) [ Arber 1962,Smith 1973]; (2) the application of the restriction enzymes for DNA recombinant technology (Nobel Prize 1980) [

Jackson 1972]; (3) the develop-

ment of oligonucleotides synthesis [ Beaucage 1981,McBride 1983]; and (4) the development of the Polymerase Chain Reaction (PCR) (Nobel Prize 1993) [

Mullis 1986].

In 1978, to congratulate Daniel Nathans, Werner Arber, and Hamilton Smith for the No- bel Prize on DNA restriction enzymes, Szybalaski and Skalka wrote, "The work on restriction nucleases not only permits us easily to construct recombinant DNA molecules and to analyse individual genes, but also has led us into the new era of" synthetic biology" where not only existing genes are described and analyzed but also new gene arrangements can be constructed and evaluated" [ Szybalski 1978]. All these technological developments quickly enabled the pro- duction of proteins of interest using microorganisms, such as recombinant somatostatin and insulin [ Itakura 1977] [Goeddel 1979]. However, genetic engineering was mostly restricted to cloning and recombinant gene expression. Detailed knowledge of biological systems was still limited in part due to the technological limitations of DNA sequencing at the time. In the mid-1990s, the development of high-throughput techniques for DNA sequencing, quan- tifying RNA, protein, lipids, and metabolites, and the increasing capacities of computational tools led to the field of systems biology. Biologists and computer scientists worked in symbiosis to reverse-engineer cellular networks. From this basic research effort emerged a view of cellular networks organized as a hierarchy of discernible and functional modules [

Hartwell 1999].

Stéphane Leduc said: "Biology must evolve like other natural sciences and to be succes- sively descriptive, analytic and synthetic." (1910). As such, the development of systems biology with the view of organisms as composed of modular, regulatory networks laid the foundation for synthetic biology. The construction of new biological systems permits (1) the further un- derstanding of biology and (2) the use of engineered biological systems with novel functions for biotechnological applications, such as manufacturing high-value compounds or addressing unmet healthcare needs. However, the construction of useful synthetic biological system remained "an expensive, unreliable and ad hoc research process" [

Endy 2005]. Engineering biology is indeed a great

challenge due to the large complexity of biological systems. To facilitate the engineering of biology, scientists from various backgrounds were inspired from other engineering fields. They applied well-known engineering principles, such as standardization, decoupling, and abstrac- tion, to simplify the construction of synthetic biological systems. The use of these engineering concepts, together with the development and sharing of common tools and platforms is what clearly differentiates genetic engineering from synthetic biology. The first Synthetic Biology conference, hold at MIT (SB1.0) in 2004, was an important catalyst for the nascent field and helped create its community and culture. Moreover, the

4Chapter 1. Introduction

iGEM competition, a synthetic biology student competition each year gathering teams from the entire world (4 teams in 2004 and 337 teams in 2017) has supported the quick, worldwide expansion of synthetic biology, the training of young synthetic biology researchers, and helped spread public awareness of the field. In order to standardize synthetic biological systems, researchers decomposed them into devices and biological parts. Parts, devices, and systems are supposed to be stored with their precisely and documented characterization in an open-access database such as the Reg- istry of Standard Biological Parts ( http://parts.igem.org/Main_Page). Shared information should support further construction of more complex systems using already optimized and well- characterized parts. This open-access culture is a strong component of synthetic biology inspired from computer science. In the past 15 years, many parts and circuits of increasing size have been engineered, leading

to a large collection of biological parts and a large set of applications in biotechnology and health

(Figure

1.1). However, the complexity of synthetic biological systems did not increase much

as expected in the early 2000s. Parts composition is still unreliable and circuit design is still mainly a trial-and-error process. Moreover, the specifications of standard biological parts are still not common to all and little effort is made on the standardization and distribution of well-functioning parts. Due to intellectual property and commercialization concerns, a part of the community does not intend to distribute its work. Consequently, we are now at a critical point where the community has to choose between thead-hocdevelopment of proof-of-concept and prototype circuits and pushing the standardization and characterization of parts and part composition. The challenge is to provide an open ecosystem that supports academic research, companies development, and public access to the tools of synthetic biology. The following years will be crucial. In my opinion, synthetic biology could be separated in three paths with different, yet com- plementary, often overlapping goals: (1) the development of foundational technology supporting the engineering of biology: new design and engineering principles, standards, and workflows, including the development of standard parts and devices; (2) the application of these tools to answer fundamental questions in basic research; and (3) the application of these devices to solve pressing challenges in biotechnology, health, and the environment. In my thesis, I developed the first aspect. In this introduction to synthetic biology, I will present: (1) the engineering principles that founded the synthetic biology community; (2) the techniques enabling high-throughput con- struction and characterization of biological circuits; (3) the fundamental biological parts and devices which were engineered these past years; and (4) the various applications of synthetic biological circuits.

1.1. Synthetic Biology5

Figure 1.1: A brief history of synthetic biology. Timeline from [Cameron 2014]

1.1.2Principles of synthetic biology

Synthetic biology is based on engineering principles applied to the construction of artificial biological circuits, networks, and systems. Engineering is defined as a branch of science and technology concerned with the design, building, and use of engines, machines, and structures. It has been previously applied to physics (e.g. in aviation) and chemistry. The three founda- tions for engineering biology defined in 2005 by Drew Endy are, similarly to other disciplines, standardization, decoupling, and abstraction [

Endy 2005]. Standardization corresponds to the

definition of standards for biological parts, functions, experimental measurements, system oper- ation, and data-exchange protocols. Decoupling is the decomposition of a complicated problemquotesdbs_dbs25.pdfusesText_31

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