Hildegard Uecker

January 12, 2022

Please refer to http://web.evolbio.mpg.de/stochdyn/index.html and contact Hildegard for further information on the projects.

Project 1. Population genetic models for the interplay between CRISPR systems and plasmids in bacteria

 

Co-supervisor: Franz Baumdicker (University of Tübingen) http://www.baumdickergroup.de/, contact: franz.baumdicker@uni-tuebingen.de

The revolutionary CRISPR/Cas technology to edit genomes has its origin in the natural CRISPRCas
defense systems of bacteria and archaea. These systems essentially work by cutting foreign
DNA (e.g. phage DNA) at specific spots. Some types of CRISPR are preferentially encoded on
plasmids, which are extra-chromosomal DNA elements. So-called conjugative plasmids can
horizontally transfer between bacterial cells and thus introduce the CRISPR system into other cells.
CRISPR systems have some remarkable properties that make them particularly interesting for both
theoretical as well as applied investigations. To identify specific foreign DNA, the CRISPR system
contains an array of spacers that align with these targets. This array is itself subject to evolutionary
forces including deletion,and selection. Based on their ability to target specific DNA sequences,
CRISPR systems could help to re-sensitize resistant pathogenic strains to antibiotic treatment --
they could be used to eliminate other plasmids that carry antibiotic resistance genes.

The aim of this project is to develop mathematical models for the eco-evolutionary dynamics of
plasmid-encoded CRISPR systems within the framework of theoretical population genetics and to
explore their potential as a therapeutic intervention against antibiotic resistant bacteria. Possible
questions include: Do plasmids use CRISPR systems to compete with other plasmids? How does
the copy number of resistance plasmids affect the chance of successful elimination through mobile
CRISPR systems? How can we optimize the outcome of a combined antibiotic drug and CRISPRbased
re-sensitizing treatment?

On the mathematical side, the project involves stochastic modeling in combination with
deterministic approaches using branching processes as well as diffusion theory. An optional
computational side of the project can involve simulation-based inference as well as quantitative
analysis of sequenced CRISPR arrays on plasmids. Depending on the interests and profile of the
student, the focus can be more on analytical work or on computer simulations.

Applicants should have a degree preferably in mathematics or physics, or alternatively in computer
science, quantitative biology or another related field. Good quantitative skills are essential.
Experience in mathematical modeling and knowledge of a programming language is an advantage.

Papers of interest:
Santer, M. and Uecker, H. (2020). Evolutionary rescue and drug resistance on multicopy plasmids.
Genetics 215(3): 847-868.
Baumdicker, F., Huebner, A.M.I., and Pfaffelhuber, P. (2018). The independent loss model with
ordered insertions for the evolution of CRISPR spacers. Theor. Popul. Biol. 119, 72–82.

Project 2. Population genetics models of rapid adaptation to environmental change

Severe changes in the environment of a population can lead to maladaptation and ultimately extinction unless evolution is rapid, giving rise to genotypes that are well-adapted to the new conditions and rise in frequency. Such a scenario is termed "evolutionary rescue". Whether populations confronted with environmental change survive or go extinct is a key question in evolutionary biology. Which populations have the greatest chances to survive? How do genetic and environmental factors interact to slow down or to speed up adaptation? The extent of humaninduced environmental change endangering biodiversity makes answering these questions a pressing need. An answer is equally important in medicine and in agriculture where we aim to eradicate the pathogens or pests and to inhibit the evolution of resistance.

Besides laboratory experiments and field studies, mathematical modeling greatly contributes to our understanding of rapid adaptation to environmental change. The aim of this project is to develop mathematical models for the eco-evolutionary dynamics of evolutionary rescue within the framework of theoretical population genetics. The precise project will be developed together with the student according to their interests.

On the mathematical side, the project involves stochastic modeling in combination with deterministic approaches. Depending on the interests and profile of the student, the focus can be more on analytical work or on computer simulations.

Applicants should have a degree in mathematics, physics, biology, computer science or another related field. Good quantitative skills are essential. Experience in mathematical modeling and knowledge of a programming language (Matlab, Python, Java, R, C, C++,...) is an advantage.

Papers of interest:
Santer, M. and Uecker, H. (2020). Evolutionary rescue and drug resistance on multicopy plasmids.
Genetics 215(3): 847-868.
Uecker, H. and Hermisson, J. (2016). The role of recombination in evolutionary rescue. Genetics
202:1-12.

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