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The Quartz crystal microbalance (QCM) is a very sensitive mass-detecting device which is based on changes in to the vibrational frequency of quartz crystals after adsorption of substances to a modified crystal surface. In this study a QCM-based biosensor was developed for the rapid diagnosis of influenza viruses and its suitability and limitations were compared with currently available diagnostic methods on 67 clinical samples (nasal washes) received during the 2005 Australian winter. The type-specific and conserved viral M1 proteins of both A/PR/8/34 and B/Lee/40 viruses were used to prepare polyclonal antisera for the development of an ELISA. The limits of detection of ELISAs for the detection of purified A/PR/8/34 and B/Lee/40 ƒnviruses were 20ƒÝg/mL ƒnand 14 ƒÝg/mL using polyclonal antibodies, and 30 ƒÝg/mL and 20 ƒÝg/mL for monoclonal antibodies, respectively. The limit for detection of each virus was 104 pfu/mL, irrespective of whether antisera or monoclonal antibodies were used for capture. Non-purified cell culture-grown preparations of either virus could be detected at 103 pfu/mL The QCM utilised the same reagents used in ELISAs. However, a number of parameters were then further optimised to improve the sensitivity of the tests. These included blocking of non-specific binding, examination of the effects of flow-cell compression, the role of pH, flow rate, antibody concentration and the addition of protein A to the crystal surfaces of the biosensor. The lowest virus concentration that could be detected with the QCM was 104 pfu/mL for egg-grown preparations of both A/PR/8/34 and B/Lee/40, which could be detected within 30 min. However, conjugation of 13 nm gold nanoparticles to a second detector antibody resulted in a 10-fold increase in sensitivity and a detection limit of 103 pfu/mL that could be determined within 1 h. The direct detection of the influenza viruses in nasal samples was not possible by QCM because of the significant frequency fluctuation that was probably caused by the viscosity of the samples. Therefore, an additional culture step of 12 h was required, which increased the processing time to 2 days. The QCM/nanoparticle method was shown to be as sensitive as the standard cell culture method, and the QCM method as sensitive as the shell vial method. The QCM and QCM/nanoparticle methods were shown to be 81 and 87% as sensitive and both were 100% as specific as the real-time polymerase chain reaction. However, for use in rapid diagnosis, improvements are required to remove frequency fluctuation resulting from the direct use of nasal samples.

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In systems biology and genomics, epistasis characters the impact that a substitution at a particular location in a genome can have on a substitution at another location. This phenomenon is often implicated in the evolution of drug resistance or to explain why particular ‘disease-causing’ mutations do not have the same outcome in all in- dividuals. Hence, uncovering these mutations and their locations in a genome is a central question in biology. However, epistasis is notoriously difficult to uncover, es- pecially in fast-evolving organisms. Here, we present a novel statistical approach that takes inspiration from a model developed in ecology and that we adapt to analyze genetic data in a typically fast-evolving system: the influenza A virus. We validate the approach using experimentally-validated data: known interactions are recovered. We further evaluate the ability of our approach to detect epistasis during antigenic shifts or at the emergence of drug resistance. We show that in all cases, epistasis is prevalent in influenza A viruses, involving many pairs of sites linked together in chains, a hallmark of historical contingency. Strikingly, interacting sites are sepa- rated by large physical distances, which entail either long-range structural effects or functional tradeoffs, for which we find support with the emergence of drug resistance. Our work paves a new way for the unbiased detection of epistasis in a wide range of organisms by performing whole-genome scans.

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No description available.