Josupeit, Mario (2020). The Fitness Landscape of Translation. Masters thesis, Universität zu Köln.

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In this thesis I examine the fitness effects in the translation step of protein synthesis. The idea for this topic originates from the surprising findings of Zwart et al. in 2018 [35]. Their paper on the TEM-1 �-lactamase gene of the Escherichia coli bacterium states, that synonymous mutations, which are those mutations, that change the nucleic acids, but leave the encoded protein the same, can have a strong fitness effect, with the fitness being the number of offspring per individual. The fitness in an environment with the antibiotic cefotaxime, was measured for all combinations of 4 synonymous mutations in the TEM-1 gene. This fitness is the antibiotic stress resistance IC99.99. The synonymous mutations observed are at the 9th, 17th, 87th and 89th codon of the gene that has a length of 284 codons. The space of all 24 possible combinations of mutations is called a fitness landscape, connecting a point within the mutations landscape to the measured fitness. The fitness landscape of synonymous mutations from Zwart et al. [35] features many neutral mutations, which do not change the fitness, as well as sign epistasis, a feature of the landscape where the effect of a mutation has a different sign on different backgrounds. The key to analyzing and understanding such a landscape, beyond looking at the fitness values themselves, is to examine interactions of mutations in the landscape. This work presents a tool for analyzing these landscapes which could lead to a deeper understanding of the characteristics of synonymous mutations. The goal of this thesis is to formulate a model for interacting mutations and analyze the landscape that inspired this investigation. The road to this goal reaches from the biological basics and the TASEP, a non-equilibrium physics model of translation, via the description of a model proposed by this thesis and comparisons to numerical results and literature, to an analysis of experimental results for a fitness landscape of synonymous mutations. The methods of this thesis reach from analytic approaches to numerical simulations and data analysis.

Item Type: Thesis (Masters thesis)
CreatorsEmailORCIDORCID Put Code
Josupeit, Mariojosupeim@smail.uni-koeln.deUNSPECIFIEDUNSPECIFIED
URN: urn:nbn:de:hbz:38-121155
Date: 7 August 2020
Language: English
Faculty: Faculty of Mathematics and Natural Sciences
Divisions: Faculty of Mathematics and Natural Sciences > Department of Physics > Institut für Biologische Physik
Subjects: Natural sciences and mathematics
Life sciences
Uncontrolled Keywords:
Fitness landscapeEnglish
Date of oral exam: 18 August 2020
NameAcademic Title
Krug, JoachimProf. Dr.
Schadschneider, AndreasProf. Dr.
Refereed: Yes


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