Label free detection of pseudorabies virus infection in Vero cells using laser force analysis
The rapid and robust identification of viral infections has broad implications for a number of fields, including medicine, biotechnology and biodefense. Most detection systems rely on specific molecules, such as nucleic acids or proteins, to identify the target(s) of interest. These molecules afford...
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Veröffentlicht in: | Analyst (London) 2014-03, Vol.139 (6), p.1472-1481 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The rapid and robust identification of viral infections has broad implications for a number of fields, including medicine, biotechnology and biodefense. Most detection systems rely on specific molecules, such as nucleic acids or proteins, to identify the target(s) of interest. These molecules afford great specificity, but are often expensive, labor-intensive, labile and limited in scope. Label free detection methods seek to overcome these limitations by instead using detection methods that rely on intrinsic properties as a basis for identifying and separating species of interest and thus do not rely on specific prior knowledge of the target. Optical chromatography, one such technique, uses the balance between optical and fluidic drag forces within a microfluidic channel to determine the optical force on cells or particles. Here we present the application of individual optical force measurements as a means of investigating pseudorabies virus infection in Vero cells. Optical force differences are seen between cells from uninfected and infected populations at a multiplicity of infection as low as 0.001 and as soon as 2 hours post infection, demonstrating the potential of this technique as a means of detecting viral infection. Through the application of a pattern recognition neural network, individual cell size data are combined with optical force as a means of classifying cell populations. Potential applications include the early detection of bloodborne pathogens for the prevention of sepsis and other diseases as well as the detection of biological threat agents. |
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ISSN: | 0003-2654 1364-5528 |
DOI: | 10.1039/c3an01713c |