Label‐Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy. Issue 1 (11th December 2018)

• Record Type: Journal Article
• Authors: Ma, Ning; Kamalakshakurup, Gopakumar; Aghaamoo, Mohammad; Lee, Abraham P.; Digman, Michelle A.
• Other Names: Periasamy Ammasi guestEditor.
• Is Part Of: Cytometry. Volume 95:Issue 1(2019)
• Page Start: 93
• Page End: 100
• Publication Date: 2018-12-11
• Subjects: metabolism -- fluorescence lifetime imaging microscopy -- phasor analysis -- droplet microfluidics -- single cell analysis -- circulating tumor cells -- quiescent stage; Flow cytometry -- Periodicals; Imaging systems in biology -- Periodicals; Imaging systems in medicine -- Periodicals; Diagnostic imaging -- Periodicals; 571.605
• DOI: 10.1002/cyto.a.23673
• Languages: English
• ISSNs: 1552-4922

Abstract

Abstract: Characterization of single cell metabolism is imperative for understanding subcellular functional and biochemical changes associated with healthy tissue development and the progression of numerous diseases. However, single‐cell analysis often requires the use of fluorescent tags and cell lysis followed by genomic profiling to identify the cellular heterogeneity. Identifying individual cells in a noninvasive and label‐free manner is crucial for the detection of energy metabolism which will discriminate cell types and most importantly critical for maintaining cell viability for further analysis. Here, we have developed a robust assay using the droplet microfluidic technology together with the phasor approach to fluorescence lifetime imaging microscopy to study cell heterogeneity within and among the leukemia cell lines (K‐562 and Jurkat). We have extended these techniques to characterize metabolic differences between proliferating and quiescent cells—a critical step toward label‐free single cancer cell dormancy research. The result suggests a droplet‐based noninvasive and label‐free method to distinguish individual cells based on their metabolic states, which could be used as an upstream phenotypic platform to correlate with genomic statistics. © 2018 International Society for Advancement of Cytometry