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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
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NIAID-sponsoredBioinformatics Resource Centers
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www.fludb.orgQuery Results
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www.fludb.orgWorkbench
www.fludb.orgNovel Data Features in IRD
• CEIRS Surveillance Data• 3D Structures and Data Integration• Sequence Feature Variant Types
www.fludb.orgCEIRS
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www.fludb.org3D 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
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www.fludb.orgSFVT approach
VT-1 I F D R L E T L I LVT-2 I F N R L E T L I LVT-3 I F D R L E T I V LVT-4 L F D Q L E T L V SVT-5 I F D R L E N L T LVT-6 I F N R L E A L I LVT-7 I Y D R L E T L I LVT-8 I F D R L E T L V LVT-9 I F D R L E N I V LVT-10 I F E R L E T L I LVT-11 L F D Q M E T L V S
Influenza A_NS1_nuclear-export-signal_137(10)
• 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_NS1_alpha-helix_171(17)
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Influenza A Sequence Features as of 10JUN2011
>4000 SFs total
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ADAPTIVE GENETIC DRIVERS OF SPECIES JUMP EVENTS
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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
www.fludb.orgPandemic stages
Adaptive drivers
www.fludb.orgBasic 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
Pandemic Viruses(R0H >1)
Stuttering viruses(R0R>1 and R0H<1)
Reservoir virus(R0R>1 and R0H<<1)
A1 A2
www.fludb.orgAdaptive drivers
Pepin KM et al. (2010) “Identifying genetics markers of adaptation for surveillance of viral host jump” Nature Reviews Microbiology 8: 802-814.
www.fludb.orgStuttering 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
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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
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Strain Search – PB2 avian H5N1 Southeast Asia up to 2003
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www.fludb.orgE627K and species jump
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www.fludb.orgSummary
• 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
N01AI40041
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Acknowledgments
• U.T. Southwestern– Richard Scheuermann– Burke Squires– Jyothi Noronha– Victoria Hunt– Shubhada Godbole– 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– Wenjie Hua– Wei Jen– Sanjeev Kumar– Xiaomei Li– Zaigang Liu– Jason Lucas– Michelle Lu– Bruce Quesenberry– Barbara Rotchford– Hongbo Su– Bryan Walters– Jianjun Wang– Sam Zaremba– Liwei Zhou
• IRD SWG– Gillian Air, OMRF– Carol Cardona, Univ. Minnesota– Adolfo Garcia-Sastre, Mt Sinai– Elodie Ghedin, 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
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