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Applied and Environmental Microbiology, May 2008, p. 2990-2996, Vol. 74, No. 10
0099-2240/08/$08.00+0 doi:10.1128/AEM.02246-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Department of Civil and Environmental Engineering, University of California, Davis, California 95616,1 Marshfield Clinic Research Foundation, Marshfield, Wisconsin 544492
Received 2 October 2007/ Accepted 13 March 2008
Available filtration methods to concentrate waterborne viruses are either too costly for studies requiring large numbers of samples, limited to small sample volumes, or not very portable for routine field applications. Sodocalcic glass wool filtration is a cost-effective and easy-to-use method to retain viruses, but its efficiency and reliability are not adequately understood. This study evaluated glass wool filter performance to concentrate the four viruses on the U.S. Environmental Protection Agency contaminant candidate list, i.e., coxsackievirus, echovirus, norovirus, and adenovirus, as well as poliovirus. Total virus numbers recovered were measured by quantitative reverse transcription-PCR (qRT-PCR); infectious polioviruses were quantified by integrated cell culture (ICC)-qRT-PCR. Recovery efficiencies averaged 70% for poliovirus, 14% for coxsackievirus B5, 19% for echovirus 18, 21% for adenovirus 41, and 29% for norovirus. Virus strain and water matrix affected recovery, with significant interaction between the two variables. Optimal recovery was obtained at pH 6.5. No evidence was found that water volume, filtration rate, and number of viruses seeded influenced recovery. The method was successful in detecting indigenous viruses in municipal wells in Wisconsin. Long-term continuous filtration retained viruses sufficiently for their detection for up to 16 days after seeding for qRT-PCR and up to 30 days for ICC-qRT-PCR. Glass wool filtration is suitable for large-volume samples (1,000 liters) collected at high filtration rates (4 liters min–1), and its low cost makes it advantageous for studies requiring large numbers of samples.
Published ahead of print on 21 March 2008.
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