Kevin Downard (Presenter)
University of New South Wales
Bio: Kevin Downard conducted his postdoctoral studies and held a subsequent academic position at the Massachusetts Institute of Technology after award of a PhD degree from the University of Adelaide in Australia. For the past 18 years he has held professorial positions in the USA and Australia with his research focused on the development and application of new advanced mass spectrometric and bioinformatic approaches to improve the molecular surveillance and responses to the influenza virus. He has twice received international fellowships from both the Australian Academy of Science and the Japan Society for the Promotion of Science and has received large continuous research funding from the Australian Research Council. He has authored over 100 publications, including 2 books on mass spectrometry, and is the only Australian awarded by the world’s largest mass spectrometry society.
Authorship: Kevin M. Downard, Jason W.H. Wong JWH, Aaron T.L. Lun, Neil D. Fernandes
University of New South Wales, Sydney, Australia
Influenza remains a leading cause of death the world over with between 250,000-500,000 deaths associated with the virus annually. Global surveillance has been overseen by the WHO's Global Influenza Surveillance and Response System (GISRS) for over half a century yet deficiencies with characterizing and responding to outbreaks in a timely and effective manner remain. We have developed more direct and rapid mass spectrometry approaches that can improve the molecular based surveillance of clinical specimens and responses to the virus. Viruses can be typed, subtyped, and their lineage determined through single ion detection and these data sets can be used to assess the evolutionary history of the strain using mass-based phylogenetic trees. This presentation will provide an overview of these approaches highlighting their speed, sensitivity and throughput for clinical applications.
The high rates of morbidity and mortality associated with influenza are due to its high rate of transmission, its rapid rate of evolution, its ability to cross from animal to human populations, as exemplified by the recent 2009 pandemic H1N1 virus, and difficulties with responding to outbreaks in a timely and effective manner. The early detection and laboratory diagnosis of the influenza virus in human populations are important for managing the virus, either in the context of annual seasonal outbreaks or following the emergence of pandemic strains. Current response strategies involve vaccination ahead of the influenza season with inactivated or attenuated strains predicted to be in circulation, and the administration of antiviral drugs post-infection to reduce complications and deaths. These approaches are challenged by the constant need to survey viral strains in the population, using both non-molecular and molecular (currently RT-PCR) approaches, and the proven ability of the virus to develop resistance to antiviral drugs. A new rapid direct proteotyping approach, using high-resolution mass spectrometry, that allows the influenza virus to be typed and subtyped at the molecular level within whole virus digests has recently been reviewed .
Strains of human influenza viruses from primary clinical specimens grown in MDCK cells were harvested after 48-72 hours. The average viral titers, measured by plaque assays, were between 2500-3500 PFU/ml. Viruses were precipitated with polyethylene glycol and proteolytically digested with trypsin. The resulting peptides were analyzed by high-resolution mass spectrometry and unique signature peptides characteristic of type A H1N1 and H3N2 and type B influenza viruses identified. These mass-based datasets were also used to construct phylogenetic trees in order to visualize strain evolution. New bioinformatics approaches and algorithms developed in this laboratory  were employed in these analyses.
A high-resolution MALDI-FT-ICR mass spectrum of a whole virus digest obtained from a seasonal specimen contained 36 peptides. The detection of a HA signature peptide consisting of residues 164 to 171 (m/z 944.5560) enabled the strain to be confidently identified as being of the type A H1N1 subtype . The detection of a total of 18 period-specific signature peptides also enabled the strain to be differentiated from type A H1N1 pandemic strains co-circulating during this period. A type A H3N2 strain was characterized in the same manner . A spectrum for an additional strain contained 25 peptides diagnostic of type B influenza viruses, 13 of which were signature peptides for all type B viruses. The presence of an additional signature peptide at m/z 939.4893, associated with HA residues 273 to 280, unequivocally establishes that the type B virus belongs to the Victoria lineage and can be fit to a mass tree reflecting its evolutionary history .
The identification and characterization of type A and B influenza viruses in human primary clinical specimens at the molecular level using a new proteotyping approach provides a convenient, direct, rapid, and reliable approach. Importantly, the approach is not encumbered by problems associated with viral evolution that affect PCR assays, and multiple proteins (associated with multiple genes) are screened simultaneously. Another advantage of this approach is that it is open to the detection of novel virus strains that can escape detection by RT-PCR-based approaches, and it is also capable of detecting and differentiating other respiratory pathogens such as the parainfluenza virus.
References & Acknowledgements:
 Downard KM (2013) Proteotyping for the Rapid Identification of Pandemic Influenza Virus and other Biopathogens, Chem. Soc. Rev., 42: 8584-8595.
 Schwahn AB, Wong JWH, Downard KM (2010) FluTyper - An Algorithm for Automated Typing and Subtyping of the Influenza Virus from High Resolution Mass Spectral Data, BMC Bioinformatics, 11: 266.
 Fernandes ND, Downard KM (2014) Incorporation of a Proteotyping Approach using Mass Spectrometry for the Surveillance of the Influenza Virus in Cell Culture, J. Clin. Microbio., 52, 725-735.
 Lun ATL, Swaminathan K, Wong JWH, Downard KM (2013) Mass Trees – A New Phylogenetic Approach and Algorithm to Chart Evolutionary History with Mass Spectrometry, Anal. Chem., 85: 5475-5482.
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|Board Member||yes||various professional societies/journals|
IP Royalty: no
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