Abstract
There is a long history of cryobiologists adapting a Coulter counter to measure cellular biophysical parameters including establishing that cells are ideal osmometers, estimating water and solute permeabilities and their activation energies, and measuring isosmotic volume. These techniques have been used in many cell types to facilitate prediction of optimal protocols for CPA addition and removal as well as optimal cooling and warming protocols. While it has advantages over other techniques in some aspects, the Coulter counter technique is also challenging in several scenarios. First, the technique requires large sample volumes and cell counts, and introduces a several second time lag between exposure to anisosmotic media and cell volume detection. In many cell types and at low temperatures, this lag may not critical, but for cells with very high surface area to volume ratios, or cells with very high water permeability, this lag makes accurate biophysical measurement nearly impossible. Moreover, it is experimentally challenging to perform measurements at temperatures other than ambient. Finally, volume measurements are taken from individual cells only once as they pass through an aperture. This yields a “population” permeability estimate, and requires considerable data reduction and advanced parameter estimation techniques to obtain mean biophysical parameter values. Here we describe the design, fabrication and testing of a MEMS Coulter counter specifically designed for dynamic biophysical measurements. In particular, as opposed to several existing MEMS Coulter counters that size static cells, ours has an ultrarapid mixing region in which individual cells are rapidly mixed with desired reagents (e.g. anisosmotic media) and their volumes are measured at ten specific time points. Our new approach allows initial measurement of cell responses in less than 100 ms, provides a much improved estimate of the population variance of water and solute permeability, and facilitates very simple temperature control of the system. We present initial data and analysis of system output.
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