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    J Immunol Methods. 1998 Aug 1;217(1-2):27-39.

    Bone marrow cellular composition in Listeria monocytogenes infected mice detected using ER-MP12 and ER-MP20 antibodies: a flow cytometric alternative to differential counting.

    Source

    Department of Immunology, Erasmus University, Rotterdam, Netherlands.

    Abstract

    Detailed assessment of bone marrow cellular composition is essential in the evaluation of various experimental in vivo systems, such as expression of transgenes, null mutations and stimulation of host defence in infection. Traditional morphological analysis of mouse bone marrow is laborious, requires specific cytological expertise, and is somewhat subjective. As an alternative, we have examined whether double labelling of bone marrow with the anti-precursor monoclonal antibodies ER-MP12 and ER-MP20 could be used for differential analysis by flow cytometry, as these antibodies define six relatively homogeneous cell populations in mouse bone marrow. Following a sublethal infection of mice with Listeria monocytogenes, we monitored changes in cellular composition of the bone marrow at various time points in three ways: differential morphological count; single-color flow cytometric analysis using markers for the myeloid, erythroid and lymphoid lineages; and double labelling with ER-MP12 and ER-MP20. As expected, the bone marrow composition changed dramatically during infection, leading to an increase of myeloid cells which peaked after 1 week of infection. Data determined by ER-MP12/20 flow cytometric analysis appeared to be in close agreement with both morphology and lineage marker analysis. In addition, ER-MP12/20 analysis provided more detailed information with regards to the presence of early myeloid precursors compared to lineage marker analysis. These data show that flow cytometric analysis of bone marrow using ER-MP12 and ER-MP20 monoclonal antibodies provides a relatively simple, rapid and objective assay when evaluating cellular composition in the bone marrow of the mouse.

    PMID:
    9776572
    [PubMed - indexed for MEDLINE]

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