Literature DB >> 21078346

Real-time impedance analysis of host cell response to meningococcal infection.

H Slanina1, A König, H Claus, M Frosch, A Schubert-Unkmeir.   

Abstract

Measuring cell proliferation and cell death during bacterial infection involves performing end-point assays that represent the response at a single time point. A new technology from Roche Applied Science and ACEA Biosciences allows continuous monitoring of cells in real-time using specialized cell culture microplates containing micro-electrodes. The xCELLigence system enables continuous measurement and quantification of cell adhesion, proliferation, spreading, cell death and detachment, thus creating a picture of cell function during bacterial infection. Furthermore, lag and log phases can be determined to estimate optimal times to infect cells. In this study we used this system to provide valuable insights into cell function in response to several virulence factors of the meningitis causing pathogen Neisseria meningitidis, including the lipopolysaccharide (LPS), the polysaccharide capsule and the outer membrane protein Opc. We observed that prolonged time of infection with pathogenic Neisseria strains led to morphological changes including cell rounding and loss of cell-cell contact, thus resulting in changed electrical impedance as monitored in real-time. Furthermore, cell function in response to 14 strains of apathogenic Neisseria spp. (N. lactamica and N. mucosa) was analyzed. In contrast, infection with apathogenic N. lactamica isolates did not change electrical impedance monitored for 48 h. Together our data show that this system can be used as a rapid monitoring tool for cellular function in response to bacterial infection and combines high data acquisition rates with ease of handling.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 21078346     DOI: 10.1016/j.mimet.2010.11.004

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  15 in total

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2.  Real-time cell analysis for monitoring cholera toxin-induced human intestinal epithelial cell response.

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10.  Machine learning algorithms for mode-of-action classification in toxicity assessment.

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