Algorithm Advancements for the Measurement of Single Cell Oxygen Consumption Rates

Abstract

Advancements in methods and algorithms for the measurement of oxygen consumption rates of single cells is presented. In this system a low density of randomly seeded eukaryotic cells are sealed in an array of microwells etched in glass (zero to three cells per microwell). The decrease in oxygen concentration inside each microwell in the array is measured yielding the oxygen consumption rates of the cells trapped in the array. While fundamentally simple in concept, the system requires advanced algorithms for data collection and image processing. The data collection technique enabling the oxygen sensors in each microwell has been modified to increase speed and sensor precision. Utilizing internal triggering and an integrate-on-chip mode rather than external triggering and an off-chip accumulation mode improves sensor precision by 45% and increases collection speed by a factor of seven. Furthermore, an optimized sensor locator algorithm has reduced the time to process image data for a single oxygen measurement point five-fold. A new measurement technique involving custom image-processing algorithms has also been developed revealing the microwell volumes to be 0.54 nL on average with a 6% maximum spread from the mean. To demonstrate the utility of the system, we present an experiment that successfully measured the oxygen consumption rates of 1, 2 or 3 cells in nine individual microwells simultaneously.