Literature DB >> 25952947

An Imaging Flow Cytometry-based approach to analyse the fission yeast cell cycle in fixed cells.

James O Patterson1, Matthew Swaffer1, Andrew Filby2.   

Abstract

Fission yeast (Schizosaccharomyces pombe) is an excellent model organism for studying eukaryotic cell division because many of the underlying principles and key regulators of cell cycle biology are conserved from yeast to humans. As such it can be employed as tool for understanding complex human diseases that arise from dis-regulation in cell cycle controls, including cancers. Conventional Flow Cytometry (CFC) is a high-throughput, multi-parameter, fluorescence-based single cell analysis technology. It is widely used for studying the mammalian cell cycle both in the context of the normal and disease states by measuring changes in DNA content during the transition through G1, S and G2/M using fluorescent DNA-binding dyes. Unfortunately analysis of the fission yeast cell cycle by CFC is not straightforward because, unlike mammalian cells, cytokinesis occurs after S-phase meaning that bi-nucleated G1 cells have the same DNA content as mono-nucleated G2 cells and cannot be distinguished using total integrated fluorescence (pulse area). It has been elegantly shown that the width of the DNA pulse can be used to distinguish G2 cells with a single 2C foci versus G1 cells with two 1C foci, however the accuracy of this measurement is dependent on the orientation of the cell as it traverses the laser beam. To this end we sought to improve the accuracy of the fission yeast cell cycle analysis and have developed an Imaging Flow Cytometry (IFC)-based method that is able to preserve the high throughput, objective analysis afforded by CFC in combination with the spatial and morphometric information provide by microscopy. We have been able to derive an analysis framework for subdividing the yeast cell cycle that is based on intensiometric and morphometric measurements and is thus robust against orientation-based miss-classification. In addition we can employ image-based metrics to define populations of septated/bi-nucleated cells and measure cellular dimensions. To our knowledge, this is the first use of IFC to study fission yeast and we are confident that this will provide a springboard for further IFC-based analysis across all aspects of fission yeast biology.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cell cycle; Fission yeast; Imaging Flow Cytometry

Mesh:

Year:  2015        PMID: 25952947     DOI: 10.1016/j.ymeth.2015.04.026

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  4 in total

Review 1.  Flow Cytometry and Cell Cycle Analysis: An Overview.

Authors:  Aja M Rieger
Journal:  Methods Mol Biol       Date:  2022

2.  An open-source solution for advanced imaging flow cytometry data analysis using machine learning.

Authors:  Holger Hennig; Paul Rees; Thomas Blasi; Lee Kamentsky; Jane Hung; David Dao; Anne E Carpenter; Andrew Filby
Journal:  Methods       Date:  2016-09-02       Impact factor: 3.608

3.  Label-free cell cycle analysis for high-throughput imaging flow cytometry.

Authors:  Thomas Blasi; Holger Hennig; Huw D Summers; Fabian J Theis; Joana Cerveira; James O Patterson; Derek Davies; Andrew Filby; Anne E Carpenter; Paul Rees
Journal:  Nat Commun       Date:  2016-01-07       Impact factor: 14.919

4.  Live cell X-ray imaging of autophagic vacuoles formation and chromatin dynamics in fission yeast.

Authors:  Natalja Strelnikova; Nora Sauter; Manuel Guizar-Sicairos; Michael Göllner; Ana Diaz; Petrina Delivani; Mariola Chacón; Iva M Tolić; Vasily Zaburdaev; Thomas Pfohl
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

  4 in total

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