Noise in noise out - single molecule studies of molecular motors

Abstract

Many cellular functions rely on the movements of molecular motors. Single molecule studies of these motors allow investigation into their step-sizes and stall forces. Such studies inevitably involve noise, which is inherent in the biological and imaging systems probing these motors. Having to work with noise in the system, we develop a parameter, called the FIONA Index, which serves as a guide for data quality based on noise per step-size (NPS) and frames per step (FPS). Attempting to bring the noise out of the system, we develop Magnetic Cytoskeleton Affinity (MiCA) purification to remove excess dyes that prevent clear observation of individual motors. We show that with appropriate treatment of noise, complex systems can be assembled to study how multiple motors work together.