Literature DB >> 3974624

Use of a human X mouse hybrid cell line to detect aneuploidy induced by environmental chemicals.

R S Athwal, S S Sandhu.   

Abstract

A short-term assay utilizing a human/mouse monochromosomal hybrid cell line R3-5, to detect chemically induced aneuploidy in mammalian cells is described. A single human chromosome transferred into mouse cells was used as a cytogenetic marker to quantitate abnormal chromosome segregation following chemical treatment. The human chromosome present in the mouse cells can be readily identified by differential staining procedures. The frequency of cells containing 0 or 2 human chromosomes in the progeny of chemically treated monochromosomal hybrid cells provided a direct measure of aneuploidy. We tested the sensitivity of the proposed system with 3 model chemicals (colcemid, cyclophosphamide and benomyl) known to induce numerical or structural changes in chromosomes. The frequency of an abnormal segregation of the human chromosome was found to be dose dependent and consistently higher than controls. This system has the capability to detect gain as well as loss of a chromosome resulting from nondisjunction or other mechanisms leading to aneuploidy.

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Year:  1985        PMID: 3974624     DOI: 10.1016/0027-5107(85)90011-9

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  3 in total

1.  Sequence of centromere separation: separation in a quasi-stable mouse-human somatic cell hybrid.

Authors:  B K Vig; R S Athwal
Journal:  Chromosoma       Date:  1989-09       Impact factor: 4.316

2.  A monochromosomal hybrid cell assay for evaluating the genotoxicity of environmental chemicals.

Authors:  S S Sandhu; R D Gudi; R S Athwal
Journal:  Cell Biol Toxicol       Date:  1988-12       Impact factor: 6.691

Review 3.  Monochromosomal Hybrids and Chromosome Transfer: A Functional Approach for Gene Identification.

Authors:  Raj P Kandpal; Arbans K Sandhu; Gurpreet Kaur; Gursurinder P Kaur; Raghbir S Athwal
Journal:  Cancer Genomics Proteomics       Date:  2017 Mar-Apr       Impact factor: 4.069

  3 in total

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