Label-free image-encoded microfluidic cell sorter with a scanning Bessel beam

Xinyu Chen; Lauren Waller; Jiajie Chen; Rui Tang; Zunming Zhang; Ivan Gagne; Bien Gutierrez; Sung Hwan Cho; Chi-Yang Tseng; Ian Y Lian; Yu-Hwa Lo

doi:10.1063/5.0051354

Label-free image-encoded microfluidic cell sorter with a scanning Bessel beam

APL Photonics. 2021 Jul 1;6(7):076101. doi: 10.1063/5.0051354. Epub 2021 Jul 2.

Authors

Xinyu Chen¹, Lauren Waller², Jiajie Chen³, Rui Tang¹, Zunming Zhang¹, Ivan Gagne⁴, Bien Gutierrez⁴, Sung Hwan Cho⁴, Chi-Yang Tseng⁵, Ian Y Lian⁶, Yu-Hwa Lo¹

Affiliations

¹ Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093, USA.
² Department of Bioengineering, University of California, San Diego, La Jolla, California 92093, USA.
³ College of Physics and Optoelectronics Engineering, Shenzhen University, Shenzhen 518060, China.
⁴ NanoCellect Biomedical, Inc., San Diego, California 92121, USA.
⁵ Department of Materials Science and Engineering, University of California, San Diego, La Jolla, California 92093, USA.
⁶ Department of Biology, Lamar University, Beaumont, Texas 77710, USA.

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.