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Taming the Beasts of Antibiotic Resistance in Mycobacterium

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Taming the Beasts of Antibiotic Resistance in Mycobacterium DISS. ETH NO. 26372 RESISTANCEISFUTILE:TAMINGTHEBEASTSOFANTIBIOTICRESISTANCEIN MYCOBACTERIUMTUBERCULOSIS . A thesis submitted to attain the degree of DOCTOR OF SCIENCES of ETH ZURICH (Dr. sc. ETH Zurich) presented by J ULIJAPE¯ CERSKAˇ M.Sc. ETH Zurich, Zurich, Switzerland born on 24.01.1990 citizen of Latvia accepted on the recommendation of Prof. Dr. Tanja Stadler (examiner), Prof. Dr. Sebastien Gagneux (co-examiner), Prof. Dr. François Balloux (co-examiner) 2019 ACKNOWLEDGMENTS These past 5 years have been a journey I never anticipated, but I am extremely happy that I did end up taking it on. It has not been always smooth sailing, but if I had the choice to do it all over again knowing what I know now, I would do it without question. This work has helped me feel like I am in the right place and I belong to something bigger – the vast and glorious scientific community. I am extremely grateful to my supervisor, Tanja Stadler, for guiding me through all these years, I could not have wished for better guidance and support. My time as a student with Tanja has allowed me to work on exciting scientific projects that are relevant to global wellbeing, as well as participate in activities that improve the life of students locally within the department. Thanks to Tanja I could rediscover and nourish my passion for teaching, which will most likely guide my future career choices. I am very grateful to Sebastien Gagneux for kind guidance in collaborative projects and well as for being on my committee. I am also very grateful to François Balloux for agreeing to join the committee for my PhD examination. Many thanks to my collaborators in different projects, and in particular to Denise Kühnert, Conor Meehan, Sebastian Gygli, Andrej Trauner and Mark Tanaka. Your insight and support has been invaluable and the conversations we had were always enlightening and fun. A huge thanks goes out to the wonderful cEvo group members, current and former: Tim, Marc, Venelin, Rachel, Jana, Sarah, Nicola, Jérémie, Sasha, Chi and David. And a special thanks to Veronika, Joëlle and Carsten for sometimes being my antagonists (especially when it comes to teaching), but for being amazing friends to me despite our differences. And yet another thanks to cEvo for rising up to the occasion and working together on the Taming the Beast workshop series – each of these workshops have been unique and exciting in its own way and I am endlessly grateful I could teach in so many of the workshops. A loving thank you to all the friends who have supported me, worried about me and incessantly made fun of me throughout this long journey, and in particular to Alëna, Alina, Jelizaveta, Maria, Irina and Dmitry. I appreciate every one of you and I could not do without your support. Last but not least, a huge thank you goes to my family: my parents and grandparents who brought me up to be who I am, my dearest sister Anna Esther who is my closest friend, and to my partner Jaroslavs who has supported me in my crazy endeavours (and put up with my scientific journey for all these years). I love you! iii CONTENTS 1 introduction1 1.1 Tuberculosis epidemiology 2 1.2 Bayesian phylodynamic inference for epidemiology 4 1.3 Outline 5 2 existing approaches to tb and mdr-tb modelling7 3 transmission fitness costs in mdr-tb 47 4 pyrazinamide resistance fitness costs in mdr-tb in georgia 79 5 transmission time and clustering methods in tb epidemiology 91 6 quantifying the fitness cost of hiv drug resistance 105 7 transmission of hepatitis b and d in an african community 143 8 bayesian analyses made understandable 183 9 discussion and conclusions 189 bibliography 193 v ABSTRACT Tuberculosis (TB) has been declared a global public health emergency more than a quarter of a century ago and while significant progress has been made to reduce the mortality and infection rates, there is still a long way to go to the ultimate goal of eradicating TB. While we have efficient treatment regimens, even the shortest regimen for fully drug-sensitive TB is already 6 months long. This regimen, while effective at treating drug-sensitive cases, provides plenty of room for resistance development due to sheer treatment length. Resistance development is further sped up by the characteristics of the bacterium and of the disease that it causes in humans. In this thesis, I estimated the relative transmission fitness of drug-resistant Mycobacterium tuberculosis strains in relation to drug-sensitive strains using phylodynamics. Phylodynamic analysis has been used in the past 20 years to quantify population dynamic processes studying a plethora of different population types. The methods were used to study population dynamics on drastically different scales: from species dynamics on macroscopic, to virus and other pathogen dynamics on microscopic scales. A lot has been done on estimating epidemiological dynamics of pathogens, however most work has been on fast evolving viruses and not extensively tested on much slower bacterial pathogens, of which Mycobacterium tuberculosis is a prominent example. In Chapter 1 I give a general introduction to the topic at hand and justify the importance of whole genome sequencing of ongoing TB outbreaks. I briefly describe the current knowledge of TB dynamics as well as the gaps in knowledge that we will still need to extensively research to cover. I then introduce Bayesian phylodynamic methods for epidemiological analyses, highlighting in particular the most important characteristics of said analyses for TB epidemiology. In Chapter 2 I cover current approaches to TB modelling, describing a range of models from evolutionary to epidemiological to a combination of both. The chapter shows the diversity of modelling approaches, as well as areas of development for further modelling efforts. In Chapter 3 I describe a proof-of-concept simulation study and an empirical analysis of a multi-drug resistant TB (MDR-TB) dataset. In the simulation study I use an efficient implementation of the multi-type birth-death (MTBD) model in BEAST2 to analyse simulated TB epidemics, showing that even though the simulated dynamics are much more complex than MTBD assumptions, the analyses recover the parameters accurately and precisely. I then analyse an MDR-TB lineage 4 dataset from Kinshasa using the MTBD model, estimating the relative transmission fitness of pyrazinamide-resistant MDR-TB strains. In Chapter 4 I analysed a different dataset, this time of two TB lineages from Georgia, quantifying the transmission fitness costs of pyrazinamide resistance. The two datasets, Kin- shasa and Georgia, show very different estimated transmission fitness costs for pyrazinamide resistance, the former showing the expected transmission fitness cost, while the latter shows signal for no reduction in fitness associated with the studied resistance. This is a worrying result, as the current consensus is that pyrazinamide resistance fitness costs are high and pyrazinamide is one of the few first line drugs used in both drug-sensitive and MDR-TB treatment regimens. Low fitness costs, however, would mean that resistance evolution is very vii viii contents likely to happen on a population wide level. Chapter 5 covers the most commonly used modern TB genotyping techniques and the correlation between different cluster definitions using the genotyping data and the times spanned by the clusters. Chapter 6 describes using the computational approach used in Chapter 3 and Chapter 4 on an HIV dataset to estimate the relative fitness of different drug resistance mutants. Chapter 7 contains a study on the epidemiological dynamics of active and occult cases of Hepatitis B spreading in an African rural community with no access to treatment. Chapter 8 covers the online resource hub set up after running the first “Taming the Beast” workshop in the series. The demand for phylodynamic expertise can not be covered even with the multiple workshops running in different parts of the world, thus we have created a portal containing all the existing tutorials to allow scientists to learn the necessary skills online. Finally, I discuss the work presented in this thesis as well as outlook on further research in the area in Chapter 9. ZUSAMMENFASSUNG Tuberkulose (TB) wurde vor mehr als einem Vierteljahrhundert als international relevante gesundheitliche Notlage deklariert. Obwohl signifikante Fortschritte erzielt wurden, um die Sterbe- und Infektionsraten zu reduzieren, ist es noch ein weiter Weg, das ultimative Ziel, TB auszurotten, zu erreichen. Es gibt einige wirksame Therapien, doch schon die kürzeste Therapie dauert 6 Monate. Diese Therapie ist effektiv, wenn Fälle von arzneimittelsensiblen Tuberkuloseinfektionen behandelt werden, allerdings begünstigt die Länge der Therapie die Entwicklung von resistenten Stämmen während der Behandlung. Die Resistenzentwicklung wird durch die Eigenschaften des Bakteriums und der Krankheit, die es beim Menschen verursacht, weiter beschleunigt. In dieser Doktorarbeit schätze ich die relative Fitness der Übertragung von Antibiotika resis- tenten Mycobacterium tuberculosis Stämmen in Relation zu der Fitness von arzneimittelsensiblen Stämmen mit Hilfe von Phylodynamischen Methoden. Phylodynamische Analysen wurden in den letzten 20 Jahren benutzt, um populationsdynamische Prozesse auf makroskopischer Ebene (wie Speziesevolution) bis hin zur mikroskopischen Welt (wie Viren) zu quantifizieren. Die meisten Untersuchungen betrafen jedoch sich schnell entwickelnde Viren, doch langsamer entwickelnde Bakterien wie das Mycobacterium tuberculosis wurden
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