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Comparative Genomics in the Influenza Research Database. 17 June 2011 Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center. NIAID-sponsored Bioinformatics Resource Centers. www.fludb.org. Query Results. Workbench. Novel Data Features in IRD.
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Comparative Genomics in theInfluenza Research Database 17 June 2011 Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center
Novel Data Features in IRD • CEIRS Surveillance Data • 3D Structures and Data Integration • Sequence Feature Variant Types
3D Structures & Integration • Visualize protein structure in 3D • Display sequence conservation heat map on the structure • Highlight sequence features (epitopes, etc.) • Download highlighted protein structure image
SFVT approach Influenza A_NS1_nuclear-export-signal_137(10) Influenza A_NS1_alpha-helix_171(17) VT-1 I F D R L E T L I L VT-2 I F N R L E T L I L VT-3 I F D R L E T IV L VT-4 L F D Q L E T L VS VT-5 I F D R L E N L T L VT-6 I F N R L E A L I L VT-7 I Y D R L E T L I L VT-8 I F D R L E T L V L VT-9 I F D R L E NIVL VT-10 I F E R L E T L I L VT-11 L F D QM E T L VS • Identify regions of protein/gene with known structural or functional properties – Sequence Features (SF) • an alpha-helical region, the binding site for another protein, an enzyme active site, an immune epitope • Determine the extent of sequence variation for each SF by defining each unique sequence as a Variant Type (VT) • High-level, comprehensive grouping of all virus strains by VT membership for each SF independently
Influenza A Sequence Features as of10JUN2011 >4000SFs total
Flu pandemics of the 20th and 21st centuries initiated by species jump events • 1918 flu pandemic (Spanish flu) • subtype H1N1 (avian origin) • estimated to have claimed between 2.5% to 5.0% of the world’s population (20 > 100 million deaths) • Asian flu (1957 – 1958) • subtype H2N2 (avian origin) • 1 - 1.5 million deaths • Hong Kong flu (1968 – 1969) • subtype H3N2 (avian origin) • between 750,000 and 1 million deaths • 2009 H1N1 • subtype H1N1 (swine origin) • ~ 16,000 deaths as of March 2010
Pandemic stages Adaptive drivers
Basic reproductive number (R0) • Total number of secondary cases per case • Reasonable surrogate of fitness • Characteristics of pandemic viruses: • R0H >1, and • In genetic neighborhood of viruses with R0R>1 and R0H<1 • Adaptive drivers A1 A2 • Reservoir virus • (R0R>1 and R0H<<1) • Stuttering viruses • (R0R>1 and R0H<1) • Pandemic Viruses • (R0H >1)
Adaptive drivers Pepin KM et al. (2010) “Identifying genetics markers of adaptation for surveillance of viral host jump” Nature Reviews Microbiology 8: 802-814.
Stuttering transmission and adaptive drivers • Stuttering transmission can reveal adaptive drivers by evidence of convergent evolution • Odds of finding the same neutral mutation by chance in multiple species jumps is low • Therefore, finding same mutation in multiple independent species jump events is strong evidence for adaptive driver
Genetic convergence during species jump • Virus isolate groups from IRD • Avian H5N1 (PB2) from Southeast Asia* up to 2003 (260 records) – reservoirs of source viruses • Human H5N1 (PB2) from Southeast Asia 2003-present (165 records) – many examples of independent species jumps • Align amino acid sequence and calculate conservation score • Identify highly conserved positions in avian records (≤1/260 variants) (557positions/759) – functionally restricted in reservoir • Select subset in which two or more human isolates contained the same sequence variant – either due to human-human transmission or convergent evolution *China, Hong Kong, Indonesia, Thailand, Viet Nam
Human influenza pandemics are initiated by species jump events followed by sustained human to human transmission (R0H>1) Multiple independent occurrences of the same mutation during stuttering transmission is evidence of convergent evolution of adaptive drivers – hypotheses for experimental testing Surveillance for adaptive drivers in reservoir species could help anticipate the next pandemic Summary N01AI40041
U.T. Southwestern Richard Scheuermann Burke Squires JyothiNoronha Victoria Hunt ShubhadaGodbole Brett Pickett Ayman Al-Rawashdeh MSSM Adolfo Garcia-Sastre Eric Bortz Gina Conenello Peter Palese Vecna Chris Larsen Al Ramsey LANL Catherine Macken Mira Dimitrijevic U.C. Davis Nicole Baumgarth Northrop Grumman Ed Klem Mike Atassi Kevin Biersack Jon Dietrich WenjieHua Wei Jen Sanjeev Kumar Xiaomei Li Zaigang Liu Jason Lucas Michelle Lu Bruce Quesenberry Barbara Rotchford Hongbo Su Bryan Walters JianjunWang Sam Zaremba LiweiZhou Acknowledgments • IRD SWG • Gillian Air, OMRF • Carol Cardona, Univ. Minnesota • Adolfo Garcia-Sastre, Mt Sinai • ElodieGhedin, Univ. Pittsburgh • Martha Nelson, Fogarty • Daniel Perez, Univ. Maryland • Gavin Smith, Duke Singapore • David Spiro, JCVI • Dave Stallknecht, Univ. Georgia • David Topham, Rochester • Richard Webby, St Jude • USDA • David Suarez • Sage Analytica • Robert Taylor • Lone Simonsen • CEIRS Centers