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Evolutionary dynamics in the virosphere: from HIV-1 to bacteriophage evolution

Druelle, Valentin. Evolutionary dynamics in the virosphere: from HIV-1 to bacteriophage evolution. 2024, Doctoral Thesis, University of Basel, Faculty of Science.

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Official URL: https://edoc.unibas.ch/96360/

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Abstract

Evolution is a fundamental force shaping all life on Earth. Viruses, the most numerous and diverse biological entities on the planet, excel in evolution and thrive in many hosts and environments. The study of their evolutionary dynamics, which are essential to their success, has significant implications for public health. Historical and recent pandemics have shown the considerable impact that viruses can have on society, and understanding their evolution is therefore essential to mitigate their effects, help control disease spread, design better vaccines and antiviral drugs, and create new innovative treatments.
Studies of HIV-1 biology and evolution enabled the creation of life-saving treatments for infected patients. Despite this considerable achievement, we lack a satisfactory explanation of how HIV-1's within-host evolution generates its global diversity. In the first part of this thesis, we sought to explain this discrepancy by investigating the evolutionary dynamics at play on both scales. We showed that between-host evolution can mostly be explained from within-host dynamics if one accounts for the changing immune pressure that the virus faces from one host to the next. The evolution of the virus, constrained by the immune response of the patient, leads to the emergence of many escape mutations that are relevant only in that specific host. When infecting a new host, the different immune pressure causes the reversion of previously acquired mutations to their original state. On longer time scales, we thus observe a slower evolution driven by adaptation to changing environments.
In the second part of this thesis, we study the evolution of another type of virus: the bacteriophages. These viruses infect bacteria and are much more numerous and diverse than human viruses. Bacteriophages hold great promise for a wide range of research fields such as ecology, healthcare and molecular biology. Their viral nature and diversity makes them great candidates to investigate viral evolutionary dynamics. However, phage research is currently limited to a handful of well-characterized bacteriophage models, or to broad metagenomics studies where the phages are rarely isolated and poorly characterized. The former limits the scope of the findings, while the latter cannot provide the detailed characterization that would require experimental intervention. This depth vs. breadth dichotomy hinders our ability to comprehensively study phage evolution, and we sought to bridge this gap in two ways. First by creating a collection of phages, the BASEL phage collection, that is representative of the natural diversity of E.coli phages but where individual phages are also well-characterized. This gives a detailed snapshot of the results of natural phage evolution, which is informative of the evolutionary trade-offs that these phages face. Our second approach to address the dichotomy is to enable phage evolution experiments at scale. To achieve this, we created a high-throughput framework to perform bacteriophage evolution rapidly, reliably and at scale. The central piece of this framework is the continuous culture machine we crafted to perform the bacteriophage evolution experiment: the Aionostat. We present the machine and the results of two experiments to showcase its abilities. In these experiments, we evolved phages to increase their infectivity on a challenging bacterial strain, demonstrating that the Aionostat can drive the evolution of bacteriophages both vertically and through horizontal transfers. Both approaches complement each other and open new avenues for bacteriophage research.
Advisors:Neher, Richard A
Committee Members:van Nimwegen, Erik and Regoes, Roland
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Computational Modeling of Biological Processes (Neher)
UniBasel Contributors:Druelle, Valentin and van Nimwegen, Erik
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:15348
Thesis status:Complete
Number of Pages:x, 112
Language:English
Identification Number:
  • urn: urn:nbn:ch:bel-bau-diss153486
edoc DOI:
Last Modified:27 May 2024 15:20
Deposited On:24 May 2024 13:32

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