Development and validation of a concentration method for the detection of influenza a viruses from large volumes of surface water

Abstract

Contamination of lakes and ponds plays an essential role as a reservoir of avian influenza A virus (AIV) in the environment. A method to concentrate waterborne AIV is a prerequisite for the detection of virus present at low levels in water. The aim of this study was to develop and validate a method for the concentration and detection of infectious AIV from large volumes of surface water samples. Two filtration systems, glass wool and electropositive NanoCeram filter, were studied. The individual effects of filtration-elution and polyethylene glycol (PEG) concentration parameters on the recovery efficiency of the H1N1 strain from 10-liter surface water samples were assessed. An ultimate 1% recovery rate of infectious viruses was achieved with the optimal protocol, corresponding to filtration through glass wool, followed by a viral elution step and then a PEG concentration. This method was validated for the detection of highly pathogenic H5N1 strains from artificially contaminated larger water volumes, from 10 to up to 50 liters, from different sources. The viral recovery efficiencies ranged from 0.01% to 7.89% and from 3.63% to 13.79% with lake water and rainwater, respectively. A theoretical detection threshold of 2.25 × 10(2) TCID(50) (50% tissue culture infectious dose) in the filtered volume was obtained for seeded lake waters by M gene reverse transcriptase PCR (RT-PCR). Moreover, the method was used successfully in field studies for the detection of naturally occurring influenza A viruses in lake water in France.

Fig. 1.

Individual effects of parameters on infectious H1N1 recovery. The mean recovery by factor level (dot) and global mean recovery (dashed line) are represented. BE, beef extract; O/N, overnight.

Fig. 2.

Assessment of theoretical detection thresholds of the concentration method by M (A) and H5 (B) gene-specific RT-PCR detections from seeded lake water. The linear regression model (solid line) was built with experimental Cq values obtained by RT-PCR and plotted against inoculated viral loads in water (circles). For a given viral load, the Cq value has a 0.95 probability to fall below the diagonal dashed line. A positive detection occurs for Cq values lower than or equal to 42 (horizontal dotted line). The detection threshold, corresponding to the viral load for which a positive detection is obtained with a probability of 0.95, is thus found at the intersection of these two lines.