Cellular responses to spatial information in the microenvironment

Eukaryotic cells live in a highly complex microenvironment in which individual cells are exposed to a wide array of signals that are chemical, physical or spatial in nature. Studying how these cells respond to spatially organized signals is difficult due to the lack of experimental control. Techniques for creating spatial patterns of biological molecules have changed the way scientists study spatial signaling. A great deal of progress has been made and employing these patterns has deepened our understanding of cell biology. However the cellular mechanisms that are responsible for these specific spatial responses are largely unknown. In this thesis I propose and test a new experimental scheme that considers the cellular response to spatial patterns as a function of the pattern spatial information. In the course of developing the scheme, I show that cells respond to patterns with varying spatial information, establish a general method for quantifying spatial information using Shannon's information theory and show that the application of this metric can be used to gain insight into how cells process spatial signals.;First, I demonstrate that Swiss 3T3 cells can detect changes in spatial information in a 2D protein pattern. I show that cells grown on patterns, that vary smoothly between lines and randomness, respond to informational entropy change of only 6.6 bits and that this response is dependent on information density.;Second, I establish a general methodology for quantifying spatial order using information theory. Using information theory to evaluate the Fourier coefficients of an image I create a new metric, k-space information (kSI). kSI is zero for a completely disordered image and varies smoothly to a non zero quantity as order is introduced. The metric can be used to quantify any array and has implications far beyond those presented in this work.;Lastly I apply kSI and mutual information to human umbilical vein endothelial cells (HUVECs) grown on patterns that resemble extracellular matrix fibers. I establish several courses of analysis using kSI and MI.