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Data Mining in the Influenza Research Database (IRD) and the Virus Pathogen Resource (ViPR) JCVI-GSCID/NIAID Workshop University of Limpopo 01 June 2011 Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center

Data Mining in the Influenza Research Database (IRD) and the Virus Pathogen Resource ( ViPR )

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Data Mining in the Influenza Research Database (IRD) and the Virus Pathogen Resource ( ViPR ). JCVI-GSCID/NIAID Workshop University of Limpopo 01 June 2011 Richard H. Scheuermann, Ph.D. Department of Pathology U.T. Southwestern Medical Center. www.fludb.org. www.viprbrc.org. - PowerPoint PPT Presentation

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Page 1: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Data Mining in the Influenza Research Database (IRD) and the

Virus Pathogen Resource (ViPR)

JCVI-GSCID/NIAID WorkshopUniversity of Limpopo

01 June 2011

Richard H. Scheuermann, Ph.D.Department of Pathology

U.T. Southwestern Medical Center

Page 2: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

www.fludb.org

Page 3: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 4: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 5: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 6: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 7: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 8: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 9: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 10: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 11: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 12: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 13: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
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www.viprbrc.org

Page 15: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 16: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )
Page 17: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

IDENTIFICATION OF ADAPTIVE DRIVERS OF SPECIES JUMP EVENTS

Page 18: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Public Health Impact of Influenza

• Seasonal flu epidemics occur yearly during the fall/ winter months and result in 3-5 million cases of severe illness worldwide.

• More than 200,000 people are hospitalized each year with seasonal flu-related complications in the U.S.

• Approximately 36,000 deaths occur due to seasonal flu each year in the U.S.

• Populations at highest risk are children under age 2, adults age 65 and older, and groups with other comorbidities.

Source: World Health Organization - http://www.who.int/mediacentre/factsheets/fs211/en/index.html

Page 19: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

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

Page 20: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

2009 Pandemic species jump

Page 21: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Pandemic stages

Adaptive drivers

Page 22: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

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

Pandemic Viruses(R0H >1)

Stuttering viruses(R0R>1 and R0H<1)

Reservoir virus(R0R>1 and R0H<<1)

A1 A2

Page 23: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Fitness barriers

• Constant barriers to fitness – host-specific biochemical pathways/components and innate immunity

• Dynamic barriers to fitness – adaptive immunity and health status

• Variable barriers to fitness – host genetic polymorphisms

• Include transmission barriers and replication barriers

Page 24: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Fit pandemic virus

• Fit as a transmission source in reservoir species• Fit in the transmission process from reservoir species

to human• Fit in human receipt of transmission• Fit in infection establishment in human• Fit in viral replication in human• Fit for human to human transmission as above

Page 25: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Is adaptive immunity relevant?

• In previous pandemics, new virus was largely novel to the adaptive immune system, especially antibody-mediated immunity

• Therefore, in contrast to seasonal antigenic drift, pandemic-related adaptive mutations do not need to target immune epitopes

Page 26: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Adaptive drivers

Pepin KM et al. (2010) “Identifying genetics markers of adaptation for surveillance of viral host jump” Nature Reviews Microbiology 8: 802-814.

Page 27: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

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

Page 28: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

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

Page 29: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Strain Search – PB2 avian H5N1 Southeast Asia up to 2003

Page 30: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

260 PB2 records

Page 31: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Sequence variation analysis

Page 32: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Position order

Page 33: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Order by conservation score

Page 34: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

My Workbench

Page 35: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Select strains with specific sequence alterations

Page 36: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Convergent evolution candidates

d

d

d

Page 37: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Surface exposed

PB2_A/MEXICO/INDRE4487/2009(H1N1)

Conservation scoreAll convergent evolution

candidates 586, 591, 627, 629

Page 38: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Convergent evolution candidates

Page 39: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

E627K

Page 40: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

E627K and species jump

Page 41: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

K660R

Page 42: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

Summary

• 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

Page 43: Data Mining in the  Influenza Research  Database (IRD)  and the  Virus Pathogen  Resource ( ViPR )

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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