ArticleCytometry. Part A : the journal of the International Society for Analytical Cytology2019
Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.
Article in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Microfluidic Applications in Prostate Cancer Research.Micromachines · 2024Review
- Unveiling the Potential of Single-Cell Encapsulation in Biomedical Applications: Current Advances and Future Perspectives.Small science · 2024Article
- Optical Detection of Cancer Cells Using Lab-on-a-Chip.Biosensors · 2023Review
- Droplets microfluidics platform-A tool for single cell research.Frontiers in bioengineering and biotechnology · 2023Review
- FLUTE: A Python GUI for interactive phasor analysis of FLIM data.Biological imaging · 2023Article
- Application of Microfluidic Systems for Breast Cancer Research.Micromachines · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
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.
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Registered trials
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