By Prof. Jan H. Hoh, Johns Hopkins School of Medicine
In multicellular organisms cells have highly specialized functions that depend on signals from their local microenvironment. Understanding the relationship between these signals and the cellular responses requires the ability to quantify them. In many simple cases there are direct ways for doing so, such as measuring the concentration of a ligand or the steepness of a gradient. However, important signals are often compositionally and spatially complex. For example, in a developing nervous system axonal growth is directed by the composition and distribution of molecules in the extracellular environment. Likewise, the migration of cancer cells involves responses to the organization of specific molecules in the surroundings. One powerful approach to understanding how cells process spatial signals is based on using micropatterned substrates to control the distribution of signaling molecules. Here we propose that the Shannon information theory formalism provides a robust and useful way to quantify the organization of proteins in micropatterned systems. To demonstrate the use of informational entropy as a metric we microfluidically patterned of lines of fibronectin with varying information content. Fibroblasts grown on these patterns were sensitive to very small changes in informational entropy (6.6 bits), and the responses depended on the scale of the pattern.