Literature DB >> 29638231

Rapid and label-free identification of single leukemia cells from blood in a high-density microfluidic trapping array by fluorescence lifetime imaging microscopy.

Do-Hyun Lee1, Xuan Li, Ning Ma, Michelle A Digman, Abraham P Lee.   

Abstract

The rapid screening and isolation of single leukemia cells from blood has become critical for early leukemia detection and tumor heterogeneity interrogation. However, due to the size overlap between leukemia cells and the more abundant white blood cells (WBCs), the isolation and identification of leukemia cells individually from peripheral blood is extremely challenging and often requires immunolabeling or cytogenetic assays. Here we present a rapid and label-free single leukemia cell identification platform that combines: (1) high-throughput size-based separation of hemocytes via a single-cell trapping array, and (2) leukemia cell identification through phasor approach and fluorescence lifetime imaging microscopy (phasor-FLIM), to quantify changes between free/bound nicotinamide adenine dinucleotide (NADH) as an indirect measurement of metabolic alteration in living cells. The microfluidic trapping array designed with 1600 highly-packed addressable single-cell traps can simultaneously filter out red blood cells (RBCs) and trap WBCs/leukemia cells, and is compatible with low-magnification imaging and fast-speed fluorescence screening. The trapped single leukemia cells, e.g., THP-1, Jurkat and K562 cells, are distinguished from WBCs in the phasor-FLIM lifetime map, as they exhibit significant shift towards shorter fluorescence lifetime and a higher ratio of free/bound NADH compared to WBCs, because of their glycolysis-dominant metabolism for rapid proliferation. Based on a multiparametric scheme comparing the eight parameter-spectra of the phasor-FLIM signatures, spiked leukemia cells are quantitatively distinguished from normal WBCs with an area-under-the-curve (AUC) value of 1.00. Different leukemia cell lines are also quantitatively distinguished from each other with AUC values higher than 0.95, demonstrating high sensitivity and specificity for single cell analysis. The presented platform is the first to enable high-density size-based single-cell trapping simultaneously with RBC filtering and rapid label-free individual-leukemia-cell screening through non-invasive metabolic imaging. Compared to conventional biomolecular diagnostics techniques, phasor-FLIM based single-cell screening is label-free, cell-friendly, robust, and has the potential to screen blood in clinical volumes through parallelization.

Entities:  

Mesh:

Year:  2018        PMID: 29638231     DOI: 10.1039/c7lc01301a

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  11 in total

1.  Label-Free Metabolic Classification of Single Cells in Droplets Using the Phasor Approach to Fluorescence Lifetime Imaging Microscopy.

Authors:  Ning Ma; Gopakumar Kamalakshakurup; Mohammad Aghaamoo; Abraham P Lee; Michelle A Digman
Journal:  Cytometry A       Date:  2018-12-11       Impact factor: 4.355

2.  A simple microdevice for single cell capture, array, release, and fast staining using oscillatory method.

Authors:  Dantong Cheng; Yang Yu; Chao Han; Mengjia Cao; Guang Yang; Jingquan Liu; Xiang Chen; Zhihai Peng
Journal:  Biomicrofluidics       Date:  2018-05-16       Impact factor: 2.800

3.  An integrated microfluidic platform for size-selective single-cell trapping of monocytes from blood.

Authors:  Do-Hyun Lee; Xuan Li; Alan Jiang; Abraham P Lee
Journal:  Biomicrofluidics       Date:  2018-09-19       Impact factor: 2.800

Review 4.  Chemical Analysis of Single Cells and Organelles.

Authors:  Keke Hu; Tho D K Nguyen; Stefania Rabasco; Pieter E Oomen; Andrew G Ewing
Journal:  Anal Chem       Date:  2020-12-07       Impact factor: 6.986

5.  High-throughput microfluidic single-cell trapping arrays for biomolecular and imaging analysis.

Authors:  Xuan Li; Abraham P Lee
Journal:  Methods Cell Biol       Date:  2018-11-05       Impact factor: 1.441

Review 6.  Microfluidic systems for hydrodynamic trapping of cells and clusters.

Authors:  Qiyue Luan; Celine Macaraniag; Jian Zhou; Ian Papautsky
Journal:  Biomicrofluidics       Date:  2020-05-20       Impact factor: 2.800

7.  A Review of New High-Throughput Methods Designed for Fluorescence Lifetime Sensing From Cells and Tissues.

Authors:  Aric Bitton; Jesus Sambrano; Samantha Valentino; Jessica P Houston
Journal:  Front Phys       Date:  2021-04-26

8.  Live-cell imaging of glucose-induced metabolic coupling of β and α cell metabolism in health and type 2 diabetes.

Authors:  Zhongying Wang; Tatyana Gurlo; Aleksey V Matveyenko; David Elashoff; Peiyu Wang; Madeline Rosenberger; Jason A Junge; Raymond C Stevens; Kate L White; Scott E Fraser; Peter C Butler
Journal:  Commun Biol       Date:  2021-05-19

Review 9.  FLIM as a Promising Tool for Cancer Diagnosis and Treatment Monitoring.

Authors:  Yuzhen Ouyang; Yanping Liu; Zhiming M Wang; Zongwen Liu; Minghua Wu
Journal:  Nanomicro Lett       Date:  2021-06-03

10.  Fluorescence lifetime shifts of NAD(P)H during apoptosis measured by time-resolved flow cytometry.

Authors:  Faisal Alturkistany; Kapil Nichani; Kevin D Houston; Jessica P Houston
Journal:  Cytometry A       Date:  2018-10-19       Impact factor: 4.355

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