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Because many aspects of viral infection dynamics and inhibition are governed by stochastic processes, single-cell analysis should provide more information than approaches using population averaging. We have developed a microfluidic device composed of ~6000 wells, with each well containing a microstructure to capture single, infected cells replicating an enterovirus expressing a fluorescent reporter protein. We have used this system to characterize enterovirus inhibitors with distinct mechanisms of action. Single-cell analysis reveals that each class of inhibitor interferes with the viral infection cycle in a manner that can be distinguished by principal component analysis. Single-cell analysis of antiviral candidates not only reveals efficacy but also facilitates clustering of drugs with the same mechanism of action and provides some indication of the ease with which resistance will develop.
Pubmed ID: 31692968
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Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
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