Coupling of genotype-phenotype maps to noise-driven adaptation, showcased in yeast polarity

Research output: ThesisDissertation (TU Delft)

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Abstract

One of the biggest scientific challenges to be tackled this century is how traits of living organisms originate from genes, the so-called genotype-phenotype map, and conversely how traits influence genes through a process called evolution. The solution will yield a large societal impact, with applications in food (e.g., engineering drought-resistant crops), industry (e.g., material production through microorganisms) and health care (e.g., personalized medicine). The complexity of the genotype-phenotype map lies in how it typically spans multiple, interwoven scales (e.g., in size). This dissertation builds on the ambition that ultimately, a solution is found by generalizations of simpler systems. Therefore, we unravel here the map for a tractable example, polarization in budding yeast, and make insightful how evolution can couple to the map.
During polarization, the unicellular organism budding yeast chooses a direction in which it will divide. This involves self-organizing many proteins, in particular Cdc42p, to a single region on its cell membrane. While starting on the molecular scale, the process ultimately affects population traits such as doubling time. To understand the transition in scales in detail, we start bottom-up by experimentally verifying the molecular theory behind polarity success for different genetic backgrounds. The theoretical model treats, amongst others, proteins that activate Cdc42p, which are mechanistically included for the first time. Concretely, we test resulting predictions on sharp lower Cdc42p concentration bounds for viability using, inter alia, growth assays on strains variably producing fluorescent Cdc42p. The experiments confirmed the theory that allows reconstitution of molecular mechanisms underlying polarity establishment.
To advance to population traits, I constructed a tractable growth model, fed by simple rules emerging from the aforementioned theory (only implicitly encompassing the molecular information). Essentially, Cdc42p is stochastically produced, diluted by basic volume expansion, and must exceed a concentration threshold to divide. Despite disregarding many details, quantitative agreement between unintuitive, experimentally validated traits documented in literature and those from model simulations is reached.

The simplicity of the model assumptions also allows new insights in evolution. I elaborate theoretically how lucky cells that by chance produce above average amounts of protein, proliferate better to bias the observed population. Therefore, protein levels promptly adapt non-genetically, also in response to e.g., environmental changes, in a reversible and almost automatic manner. Based on existing experimental data, I predict this noise-based mechanism to notably expand the ease of evolution for essential genes (in yeast for 25%-60% of these). Due to its simple nature, I conjecture that it should be found in many organisms.
In conclusion, we find a successful strategy to tractably analyze the genotype-phenotype map in yeast polarity. The map can be expanded to other functions than polarity, provided that sufficient bio-functional information is available. The analysis also elucidates a new evolutionary coupling to this map. At a step above genes, noisy protein production can freely be utilized for short-term adaptation. Experimentally confirming the presence of this evolutionary mechanism in other model systems, and applying to these the same strategy to predict traits, will generate a completer picture of how traits of living systems are formed and shaped by evolution.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Dogterom, A.M., Supervisor
  • Laan, L., Advisor
Award date13 May 2020
Print ISBNs978-90-8593-437-0
DOIs
Publication statusPublished - 2020

Keywords

  • Self-organization
  • evolution
  • epigenetics
  • yeast polarity
  • genotype-phenotype map

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