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Abstract

Optimality is a cornerstone of biology, as evolutionary forces drive biological systems towards optimal performance. In this work, I develop theoretical models to reveal optimality principles in two biological systems: ligand discrimination by immune receptors and nuclear multiplication by parasites.

In multicellular organisms, antiviral defense is mediated by signaling molecules. They are usually characterized by highly inhomogeneous distributions due to scarcity of producer cells, diffusion and localized degradation. And yet, a molecular hub of antiviral response, the type I interferon receptor (IFNAR), discriminates between ligand types by their affinity regardless of concentration. In the first part of this work, I address the long-standing question of how a single receptor can robustly decode different ligand types. I frame ligand discrimination as an information-theoretic problem and systematically compare the major classes of receptor architectures: allosteric, homodimerizing, and heterodimerizing. As a result, the architecture of IFNAR---namely asymmetric heterodimers---achieve the best discrimination power over the entire physiological range of local ligand concentrations, enabling sensing of ligand presence and type. Here, receptor turnover, which drives the receptor system out of thermodynamic equilibrium, enables buffering against even high concentration fluctuation. Overall, these findings suggest that IFNAR is optimized for detecting and separating the presence of different ligand types in a noisy environment.

The malaria-causing pathogen Plasmodium falciparum is a eukaryotic parasite with a complex life cycle that includes proliferation within red blood cells. During the blood stage, the parasite invades a red blood cell, undergoes several rounds of asynchronous nuclear division, becoming multinucleated, and eventually forms and releases around 20 daughter parasites. Although clinical symptoms of malaria are manifest during this stage, a true understanding of the nuclear multiplication and its asynchrony remains missing. In the second part of this work, I address this topic by modeling the nuclear multiplication with various concepts of theoretical physics. The theoretical models are complemented by live-cell microscopy experiments, tracking nuclei and DNA replication. Our findings suggest that Plasmodium falciparum has evolved optimal resource utilization by exploiting a sequential sharing of replication machinery, a general mechanism for efficient and fast proliferation. This result was achieved by first investigating nuclear multiplication, showing that the number of daughter parasites is regulated by a counter mechanism. Second, we demonstrate that the nuclei are coupled by a shared resource that limits DNA replication and thereby actively generates asynchrony. In order to address the question in what way this asynchrony might be beneficial for the parasite, I introduce a minimal biophysical model for allocation of a shared enzyme to individual nuclei. The model captures parallel and sequential DNA replication mode, the latter being able to describe the observed asynchrony of the parasite. When the shared enzyme is limiting, a sequential replication utilizes resources more efficiently, resulting in faster completion of nuclear multiplication.