Large particle multiphoton flow cytometry to purify intact embryoid bodies exhibiting enhanced potential for cardiomyocyte differentiation

On Chip Sorting of Stem Cell-Derived β Cell Clusters Using Traveling Surface Acoustic Waves

There is a critical need for sorting complex materials, such as pancreatic islets of Langerhans, exocrine acinar tissues, and embryoid bodies. These materials are cell clusters, which have highly heterogeneous physical properties (such as size, shape, morphology, and deformability). Selecting such materials on the basis of specific properties can improve clinical outcomes and help advance biomedical research. In this work, we focused on sorting one such complex material, human stem cell-derived β cell clusters (SC-β cell clusters), by size. For this purpose, we developed a microfluidic device in which an image detection system was coupled to an actuation mechanism based on traveling surface acoustic waves (TSAWs). SC-β cell clusters of varying size (∼100-500 μm in diameter) were passed through the sorting device. Inside the device, the size of each cluster was estimated from their bright-field images. After size identification, larger clusters, relative to the cutoff size for separation, were selectively actuated using TSAW pulses. As a result of this selective actuation, smaller and larger clusters exited the device from different outlets. At the current sample dilutions, the experimental sorting efficiency ranged between 78% and 90% for a separation cutoff size of 250 μm, yielding sorting throughputs of up to 0.2 SC-β cell clusters/s using our proof-of-concept design. The biocompatibility of this sorting technique was also established, as no difference in SC-β cell cluster viability due to TSAW pulse usage was found. We conclude the proof-of-concept sorting work by discussing a few ways to optimize sorting of SC-β cell clusters for potentially higher sorting efficiency and throughput. This sorting technique can potentially help in achieving a better distribution of islets for clinical islet transplantation (a potential cure for type 1 diabetes). Additionally, the use of this technique for sorting islets can help in characterizing islet biophysical properties by size and selecting suitable islets for improved islet cryopreservation.

Noninvasive sorting of stem cell aggregates based on intrinsic markers

Noninvasive biomarkers hold important potential for the characterization and purification of stem cells because the addition of exogenous labels, probes, or reporters, as well as the disruption of cell-cell and cell-extracellular matrix interactions, can unintentionally but dramatically alter stem cell state. We recently showed that intensity of the intrinsically fluorescent metabolite, nicotinamide adenine dinucleotide (NADH), fluctuates predictably with changes in stem cell viability and differentiation state. Here, we use multiphoton flow cytometry developed in our laboratory to rapidly and noninvasively characterize and purify populations of intact stem cell aggregates based on NADH intensity and assessed the differentiation capacity of sorted populations. We found removal of aggregates with NADH intensity indicative of cell death resulted in a remaining population of aggregates significantly more likely to produce beating cardiomyocytes (26% vs. 8%, P < 0.05). Similarly, we found isolation of stem cell aggregates with NADH intensity indicative of future cardiac differentiation gave rise to more aggregates with beating cardiomyocytes at later time points (50% vs. 28%, P < 0.05). Further, coupling NADH intensity with gating based on size, enhances the enrichment for EBs capable of giving rise to cardiomyocytes (59% vs. 27%, P < 0.05). Thus, we demonstrate that endogenous properties of cell aggregates, such as NADH and size, can serve as gating parameters for large particle sorting devices to purify populations of stem cells or their progeny in a noninvasive manner, leading the way for improved therapeutic applications.