Computational Hyperspectral Microflow Cytometry

Author:

Yun Hyo Geun1,Cadierno Yoel Alonso2,Kim Tae Won1,Muñoz‐Barrutia Arrate2,Garica‐Gonzalez Daniel3,Choi Sungyoung145ORCID

Affiliation:

1. Department of Electronic Engineering Hanyang University Seoul 04763 Republic of Korea

2. Bioengineering Department Universidad Carlos III De Madrid Avda. de la Universidad 30, Leganés Madrid 28911 Spain

3. Department of Continuum Mechanics and Structural Analysis Universidad Carlos III De Madrid Avda. de la Universidad 30, Leganés Madrid 28911 Spain

4. Department of Biomedical Engineering Hanyang University Seoul 04763 Republic of Korea

5. Hanyang Institute of Bioscience and Biotechnology Hanyang University Seoul 04763 Republic of Korea

Abstract

AbstractMiniaturized flow cytometry has significant potential for portable applications, such as cell‐based diagnostics and the monitoring of therapeutic cell manufacturing, however, the performance of current techniques is often limited by the inability to resolve spectrally‐overlapping fluorescence labels. Here, the study presents a computational hyperspectral microflow cytometer (CHC) that enables accurate discrimination of spectrally‐overlapping fluorophores labeling single cells. CHC employs a dispersive optical element and an optimization algorithm to detect the full fluorescence emission spectrum from flowing cells, with a high spectral resolution of ≈3 nm in the range from 450 to 650 nm. CHC also includes a dedicated microfluidic device that ensures in‐focus imaging through viscoelastic sheathless focusing, thereby enhancing the accuracy and reliability of microflow cytometry analysis. The potential of CHC for analyzing T lymphocyte subpopulations and monitoring changes in cell composition during T cell expansion is demonstrated. Overall, CHC represents a major breakthrough in microflow cytometry and can facilitate its use for immune cell monitoring.

Funder

National Research Foundation of Korea

Publisher

Wiley

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