Abstract
The microfluidic-based, label-free image-guided cell sorter offers a low-cost, high information content, and disposable solution that overcomes many limitations in conventional cell sorters. However, flow confinement for most microfluidic devices is generally only one-dimensional using sheath flow. As a result, the equilibrium distribution of cells spreads beyond the focal plane of commonly used Gaussian laser excitation beams, resulting in a large number of blurred images that hinder subsequent cell sorting based on cell image features. To address this issue, we present a Bessel–Gaussian beam image-guided cell sorter with an ultra-long depth of focus, enabling focused images of >85% of passing cells. This system features label-free sorting capabilities based on features extracted from the output temporal waveform of a photomultiplier tube (PMT) detector. For the sorting of polystyrene beads, SKNO1 leukemia cells, and Scenedesmus green algae, our results indicate a sorting purity of 97%, 97%, and 98%, respectively, showing that the temporal waveforms from the PMT outputs have strong correlations with cell image features. These correlations are also confirmed by off-line reconstructed cell images from a temporal–spatial transformation algorithm tailored to the scanning Bessel–Gaussian beam.
Highlights
Characterization, classification, and isolation of cell types among a heterogeneous population based on their stain-free morphological characteristics can yield significant biological insights, especially when coupled with phenotype–genotype correlations
We demonstrate a scanning Bessel beam system with extended focal depth to overcome the above limits and develop innovative approaches to perform image-guided cell sorting in a disposable microfluidic cartridge
When there is no object in the microfluidic channel, the scanning Bessel–Gaussian beam transmits through the slit and the photomultiplier tube (PMT) shows a periodic background signal, caused by any imperfections or dust particles in the cyclo-olefin copolymer (COC) microfluidic chip intersected by the laser beam
Summary
Characterization, classification, and isolation of cell types among a heterogeneous population based on their stain-free morphological characteristics can yield significant biological insights, especially when coupled with phenotype–genotype correlations. Today’s image-guided flow cytometer cell sorters using a tightly focused Gaussian beam from a high numerical aperture (NA) objective face two major challenges: (a) to keep cells of different properties in the flow channel all in focus and (b) to keep all parts of the cells across their thickness along the optical axis in focus. Inability to meet the former requirement gives rise to a large number of out-of-focus cells, resulting in low throughput and biased analysis since some cell subpopulations tend to be in focus more than others. We demonstrate an increased percentage of infocus cell images from 30% to 40% for a Gaussian beam system to >85% by using a Bessel–Gaussian beam, effectively increasing the throughput by about three folds to around 300 cells/s, limited by the response of the on-chip piezoelectric actuator and the presence of cell doublets
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