Engineering principles of chemotaxis signalling pathways

A vast amount of biological data has been accumulated over the last few decades focusing on properties of single molecules and qualitative changes in cell morphology due to genetic manipulation. However, very little is known about the engineering principles of the underlying biological pathways inside cells, i.e. how complete pathways work, what types of signals they process, how they deal with noise, and what they are optimized for. The chemotaxis pathways are a model for how cells process information about their environments to sense and move towards chemicals. In particular, the chemotaxis pathway in the bacterium E. coli is one of the very few fully characterized signalling pathways in any organism. We have begun to develop the computational tools for understanding how the complete pathway processes the signals by modelling experimental data of the cell's 'output' to a well-defined 'input', e.g. to a change of a chemical in the environment. Much less is known about the chemotaxis pathways in higher single-cell organisms and cells of our immune system. However, it is well established that cells are able to respond to tiny changes of chemicals in their environment. From a theoretical standpoint the distribution of chemoreceptors on the cell surface is crucial for this high sensitivity. These receptor distributions are qualitatively known for various organisms based on new high-resolution imaging techniques. We have begun developing a theory of how accurately chemicals can be measured by cell-surface receptors. We will extend this method to obtain the optimal receptor distribution for the most accurate measurement of chemicals.

Cells sense chemicals in their environment with high accuracy, either by temporally sensing gradients while moving (e.g. bacterium E. coli), or by spatially measuring gradients across the cell diameter (higher single-cell organisms and cells of our immune system). Additionally, cells have often the ability to adapt precisely to persistent changes of such chemicals. Inside the cell, signals are transduced by molecular pathways of interacting protein components. In particular, the molecular components of the chemotaxis pathway in E. coli are well characterized, ranging from membrane-bound chemoreceptors to flagellated rotary motors for swimming. In order to understand the engineering principles of such biological pathways, i.e. how the remarkable signalling properties emerge and how pathways deal with different types of input signals and noise, we need to develop new quantitative approaches. In the proposed work we will model the response of E. coli cells to well-defined changes of chemicals. The response is measured by tethering cells to a glass slide with a single flagellum to observe the motor's clockwise or counter clockwise rotation. Particular attention will be paid to understand the motor output in frequency space, specifically the observed low- and high-pass filters, as well as bandwidth. We would also like to understand how accurately cells can measure concentrations and gradients using cell-surface receptors. Such measurements are inherently noisy since molecules arrive randomly at receptors by diffusion and since rebinding of already measured (previously bound) molecules provides no new information about the abundance of the chemical in the environment. Rebinding strongly depends on the distribution of receptors on the cell surface. Specifically we will derive optimal receptor distributions for both types of measurements.