Literature DB >> 23839904

Frequency determination of rare populations by flow cytometry: a hematopoietic stem cell perspective.

Alexandra Rundberg Nilsson1, David Bryder, Cornelis J H Pronk.   

Abstract

Flow cytometry allows for identification of cellular subsets based on cell intrinsic properties, most often by the use of fluorochrome-conjugated antibodies recognizing distinct cell-surface epitopes that define the cells of interest. Advances in technical instrumentation and the availability of an ever-increasing number of fluorophores, today enables identification of multicolor defined cellular populations to a previously unreachable resolution. However, these possibilities put an increasing demand on preparation, acquisition, and subsequent analysis of the investigated samples. Identification of very rare cellular subsets, such as the bone marrow-residing hematopoietic stem cells (HSCs), causes further complexity to such analysis. Here, we discuss considerations and aspects in multicolor flow cytometry as exemplified by analysis of human and mouse HSCs. We illustrate advantages and drawbacks of polychromatic flow cytometry and propose strategies, such as the use of internal reference populations, for sample analysis.
© 2013 International Society for Advancement of Cytometry.

Entities:  

Keywords:  flow cytometry; frequencies; hematopoietic stem cell; human; murine; rare cell types

Mesh:

Year:  2013        PMID: 23839904     DOI: 10.1002/cyto.a.22324

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  5 in total

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3.  A New Method of Bone Stromal Cell Characterization by Flow Cytometry.

Authors:  Chirayu Patel; Lihong Shi; John F Whitesides; Brittni M Foster; Roberto J Fajardo; Ellen E Quillen; Bethany A Kerr
Journal:  Curr Protoc       Date:  2022-03

4.  Identification of stem cells from large cell populations with topological scoring.

Authors:  Mihaela E Sardiu; Andrew C Box; Jeffrey S Haug; Michael P Washburn
Journal:  Mol Omics       Date:  2020-09-14

5.  HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats.

Authors:  Lukas M Weber; Charlotte Soneson
Journal:  F1000Res       Date:  2019-08-19
  5 in total

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