Literature DB >> 15478183

Detection and classification of threat agents via high-content assays of mammalian cells.

Sarah B Tencza1, Michael A Sipe.   

Abstract

One property common to all chemical or biological threat agents is that they damage mammalian cells. A threat detection and classification method based on the effects of compounds on cells has been developed. This method employs high-content screening (HCS), a concept in drug discovery that enables those who practice cell-based assays to generate deeper biological information about the compounds they are testing. A commercial image-based cell screening platform comprising fluorescent reagents, automated image acquisition hardware, image analysis algorithms, data management and informatics was used to develop assays and detection/classification methods for threat agents. These assays measure a cell's response to a compound, which may include activation or inhibition of signal transduction pathways, morphological changes or cytotoxic effects. Data on cell responses to a library of compounds was collected and used as a training set. At the EILATox-Oregon Workshop, cellular responses following exposure to unknown samples were measured by conducting assays of p38 MAP kinase, NF-kappaB, extracellular-signal related kinase (ERK) MAP kinase, cyclic AMP-response element binding protein (CREB), cell permeability, lysosomal mass and nuclear morphology. Although the assays appeared to perform well, only four of the nine toxic samples were detected. However the system was specific, because no false positives were detected. Opportunities for improvement to the system were identified during the course of this enlightening workshop. Some of these improvements were applied in subsequent tests in the Cellomics laboratories, resulting in a higher level of detection. Thus, an HCS approach was shown to have potential in detecting threat agents, but additional work is necessary to make this a comprehensive detection and classification system. Copyright (c) 2004 John Wiley & Sons, Ltd.

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Year:  2004        PMID: 15478183     DOI: 10.1002/jat.1025

Source DB:  PubMed          Journal:  J Appl Toxicol        ISSN: 0260-437X            Impact factor:   3.446


  3 in total

1.  Single cell cytometry of protein function in RNAi treated cells and in native populations.

Authors:  Peter LaPan; Jing Zhang; Jing Pan; Andrew Hill; Steven A Haney
Journal:  BMC Cell Biol       Date:  2008-08-01       Impact factor: 4.241

2.  Toxicity assays in nanodrops combining bioassay and morphometric endpoints.

Authors:  Frédéric Lemaire; Céline A Mandon; Julien Reboud; Alexandre Papine; Jesus Angulo; Hervé Pointu; Chantal Diaz-Latoud; Christian Lajaunie; François Chatelain; André-Patrick Arrigo; Béatrice Schaack
Journal:  PLoS One       Date:  2007-01-17       Impact factor: 3.240

Review 3.  Generating 'omic knowledge': the role of informatics in high content screening.

Authors:  Mark A Collins
Journal:  Comb Chem High Throughput Screen       Date:  2009-11       Impact factor: 1.339

  3 in total

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