Literature DB >> 23201386

Accurate measurement of peripheral blood mononuclear cell concentration using image cytometry to eliminate RBC-induced counting error.

Leo Li-Ying Chan1, Daniel J Laverty, Tim Smith, Parham Nejad, Hillary Hei, Roopali Gandhi, Dmitry Kuksin, Jean Qiu.   

Abstract

Peripheral blood mononuclear cells (PBMCs) have been widely researched in the fields of immunology, infectious disease, oncology, transplantation, hematological malignancy, and vaccine development. Specifically, in immunology research, PBMCs have been utilized to monitor concentration, viability, proliferation, and cytokine production from immune cells, which are critical for both clinical trials and biomedical research. The viability and concentration of isolated PBMCs are traditionally measured by manual counting with trypan blue (TB) using a hemacytometer. One of the common issues of PBMC isolation is red blood cell (RBC) contamination. The RBC contamination can be dependent on the donor sample and/or technical skill level of the operator. RBC contamination in a PBMC sample can introduce error to the measured concentration, which can pass down to future experimental assays performed on these cells. To resolve this issue, RBC lysing protocol can be used to eliminate potential error caused by RBC contamination. In the recent years, a rapid fluorescence-based image cytometry system has been utilized for bright-field and fluorescence imaging analysis of cellular characteristics (Nexcelom Bioscience LLC, Lawrence, MA). The Cellometer image cytometry system has demonstrated the capability of automated concentration and viability detection in disposable counting chambers of unpurified mouse splenocytes and PBMCs stained with acridine orange (AO) and propidium iodide (PI) under fluorescence detection. In this work, we demonstrate the ability of Cellometer image cytometry system to accurately measure PBMC concentration, despite RBC contamination, by comparison of five different total PBMC counting methods: (1) manual counting of trypan blue-stained PBMCs in hemacytometer, (2) manual counting of PBMCs in bright-field images, (3) manual counting of acetic acid lysing of RBCs with TB-stained PBMCs, (4) automated counting of acetic acid lysing of RBCs with PI-stained PBMCs, and (5) AO/PI dual staining method. The results show comparable total PBMC counting among all five methods, which validate the AO/PI staining method for PBMC measurement in the image cytometry method.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23201386     DOI: 10.1016/j.jim.2012.11.010

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


  9 in total

1.  Cytometry in the brain: studying differentiation to diagnostic applications in brain disease and regeneration therapy.

Authors:  H Ulrich; J Bocsi; T Glaser; A Tárnok
Journal:  Cell Prolif       Date:  2014-02       Impact factor: 6.831

2.  A high-throughput AO/PI-based cell concentration and viability detection method using the Celigo image cytometry.

Authors:  Leo Li-Ying Chan; Tim Smith; Kendra A Kumph; Dmitry Kuksin; Sarah Kessel; Olivier Déry; Scott Cribbes; Ning Lai; Jean Qiu
Journal:  Cytotechnology       Date:  2016-08-03       Impact factor: 2.058

3.  Label-free, non-invasive, and repeatable cell viability bioassay using dynamic full-field optical coherence microscopy and supervised machine learning.

Authors:  Soongho Park; Vinay Veluvolu; William S Martin; Thien Nguyen; Jinho Park; Dan L Sackett; Claude Boccara; Amir Gandjbakhche
Journal:  Biomed Opt Express       Date:  2022-05-05       Impact factor: 3.562

4.  Morphological observation and analysis using automated image cytometry for the comparison of trypan blue and fluorescence-based viability detection method.

Authors:  Leo Li-Ying Chan; Dmitry Kuksin; Daniel J Laverty; Stephanie Saldi; Jean Qiu
Journal:  Cytotechnology       Date:  2014-03-19       Impact factor: 2.058

5.  The Potential Use of Peripheral Blood Mononuclear Cells as Biomarkers for Treatment Response and Outcome Prediction in Psychiatry: A Systematic Review.

Authors:  Jobbe Goossens; Manuel Morrens; Violette Coppens
Journal:  Mol Diagn Ther       Date:  2021-05-12       Impact factor: 4.074

6.  Virtual Global Transplant Laboratory Standard Operating Procedures for Blood Collection, PBMC Isolation, and Storage.

Authors:  Lauren E Higdon; Karim Lee; Qizhi Tang; Jonathan S Maltzman
Journal:  Transplant Direct       Date:  2016-08-18

7.  Cell Density Detector Based on Light Beam Focusing.

Authors:  Aoqun Jian; Huiming Li; Yixia Zhang; Qianqian Duan; Qianwu Zhang; Shengbo Sang
Journal:  Micromachines (Basel)       Date:  2018-11-13       Impact factor: 2.891

8.  An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

Authors:  Richa Hanamsagar; Timothy Reizis; Mathew Chamberlain; Robert Marcus; Frank O Nestle; Emanuele de Rinaldis; Virginia Savova
Journal:  Sci Rep       Date:  2020-02-10       Impact factor: 4.379

9.  Observation and quantification of the morphological effect of trypan blue rupturing dead or dying cells.

Authors:  Leo Li-Ying Chan; William L Rice; Jean Qiu
Journal:  PLoS One       Date:  2020-01-24       Impact factor: 3.240

  9 in total

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