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Automated Analysis of Cryptococcal Macrophage Parasitism Using GFP-Tagged Cryptococci

Voelz, Kerstin and Johnston, Simon A. and Rutherford, Julian C. and May, Robin C. (2010) Automated Analysis of Cryptococcal Macrophage Parasitism Using GFP-Tagged Cryptococci. PLoS ONE, 5 (12). e15968. ISSN 1932-6203

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URL of Published Version: http://dx.doi.org/10.1371/journal.pone.0015968

Identification Number/DOI: doi:10.1371/journal.pone.0015968

The human fungal pathogens Cryptococcus neoformans and C. gattii cause life-threatening infections of the central nervous system. One of the major characteristics of cryptococcal disease is the ability of the pathogen to parasitise upon phagocytic immune effector cells, a phenomenon that correlates strongly with virulence in rodent models of infection. Despite the importance of phagocyte/Cryptococcus interactions to disease progression, current methods for assaying virulence in the acrophage system are both time consuming and low throughput. Here, we introduce the first stable and fully characterised GFP–expressing derivatives of two widely used cryptococcal strains: C. neoformans serotype A type strain H99 and C. gattii serotype B type strain R265. Both strains show unaltered responses to environmental and host stress conditions and no deficiency in virulence in the macrophage model system. In addition, we report the development of a method to effectively and rapidly investigate macrophage parasitism by flow cytometry, a technique that preserves the accuracy of current approaches but offers a four-fold improvement in speed.

Type of Work:Article
Date:31 December 2010 (Publication)
School/Faculty:Colleges (2008 onwards) > College of Life & Environmental Sciences
Department:School of Biosciences
Subjects:QR Microbiology
R Medicine (General)
Institution:University of Birmingham
Copyright Holders:Public Library of Science
ID Code:892
Refereed:YES
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