Evaluation of the pooling of swabs for real-time PCR detection of low titre shedding of low pathogenicity avian influenza in turkeys.

The purpose of this study was to determine whether pooling avian influenza (AI)-positive swabs with negative swabs has a detrimental effect on the sensitivity of AI real-time reverse transcription-polymerase chain reactions (rRT-PCRs). Cloacal and buccal swabs were sampled daily from 12 turkeys infected with A/goose/England/07(H2N2). For half the turkeys, each swab was mixed with four swabs from known AI-negative turkeys, and for the other half the swabs were tested individually. Bayesian modelling was used to (i) determine whether pooling the positive swabs compromised the cycle threshold (C(t)) value obtained from the rRT-PCRs, and (ii) estimate the likelihood of detection of an H2N2 infected turkey flock via rRT-PCR for pooled and individually tested swabs (cloacal and buccal) vs. the number of days post-infection of the flock. Results indicated that there was no significant effect of compromising AI rRT-PCR sensitivity by pooling a weak positive swab with negative swabs on the Ct values which were obtained. Pooled sampling was able to widen the detection window compared to individual sampling, for the same number of rRT-PCR tests. This indicates that pooled sampling would be an effective method of reducing the number of tests to be performed to determine flock status during an AI outbreak and for surveillance.

Identification of sensitive and specific avian influenza polymerase chain reaction methods through blind ring trials organized in the European Union.

Many different polymerase chain reaction (PCR) protocols have been used for detection and characterization of avian influenza (AI) virus isolates, mainly in research settings. Blind ring trials were conducted to determine the most sensitive and specific AI PCR protocols from a group of six European Union (EU) laboratories. In part 1 of the ring trial the laboratories used their own methods to test a panel of 10 reconstituted anonymized clinical specimens, and the best methods were selected as recommended protocols for part 2, in which 16 RNA specimens were tested. Both panels contained H5, H7, other AI subtypes, and non-AI avian pathogens. Outcomes included verification of 1) generic AI identification by highly sensitive and specific M-gene real-time PCR, and 2) conventional PCRs that were effective for detection and identification of H5 and H7 viruses. The latter included virus pathotyping by amplicon sequencing. The use of recommended protocols resulted in improved results among all six laboratories in part 2, reflecting increased sensitivity and specificity. This included improved H5/H7 identification and pathotyping observed among all laboratories in part 2. Details of these PCR methods are provided. In summary, this study has contributed to the harmonization of AI PCR protocols in EU laboratories and influenced AI laboratory contingency planning following the first European reports of H5N1 highly pathogenic AI during autumn 2005.