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Office of Infectious Diseases

Computational Challenges for Infectious Diseases Michael Shaw, PhD OID/Office of the Director. Office of Infectious Diseases. CDC’s Scientific Agenda for AMD:

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Office of Infectious Diseases

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  1. Computational Challenges for Infectious Diseases Michael Shaw, PhD OID/Office of the Director Office of Infectious Diseases

  2. CDC’s Scientific Agenda for AMD: To use modern laboratory and computing technologies to enhance public health surveillance, response to outbreaks, and the control and prevention of infectious diseases

  3. Pathogen Detection and Characterization Applications. Molecular detection as a replacement for traditional methods such as culture/isolation or visualization of antigens/antibodies: Allows more laboratories to detect pathogens and thus increases the amount of surveillance data. Allows surveillance of more pathogens. Makes true Molecular Epidemiology possible.

  4. Challenge: Hepatitis C virus (HCV) exists in infected host as a large population of genetically related intra-host variants • A single sequence cannot adequately represent the intra-host viral population • It is important to sample numerous intra-host viral variants for many molecular epidemiological applications: • - detection of transmission networks • drug resistance • vaccine escape • disease severity

  5. Detection of HCV transmissions using NGS Clinical Institution HCV cases ? ? Computational tools Detection of epidemiological links Next-Generation Sequencing Surveillance ? ? Not linked ? Most probable source Network of transmissions Transmission cluster Ganova-Raeva, L. et al. Detection of hepatitis C virus transmission using mass spectrometry. Journal of Infectious Diseases. 207(6):999-1006.

  6. Challenge: NGS error correction • Blue dot represents the only • real variant • - Yellow dots are NGS errors Skums, P. Et al. Efficient Error Correction of High-throughput Viral Sequencing. 2011. BMC bioinformatics. 2012, 13(Suppl 10):S6.

  7. Challenge: Risk Assessment of an Emerging Pathogen, Influenza A (H7N9) RBS AS-B Hemagglutinin Structure AS-A AS-D AS-E AS-C Antigenic Site A Red Antigenic Site B Gold Antigenic Site C Magenta Antigenic Site D Cyan Antigenic Site E Green Receptor Binding Site Gray Equivalent sites to H3N2 viruses: Wiley et al. 1981, Nature 289:373 Popovaet al. 2012, PLoS One 7:e421895 Daniels et al. 1983, J Gen Virol 64:1657 Stray et al. 2012, Virol J 9:91

  8. H7N9: Genetic Markers Characteristic of Host Adaptation or Virulence • NA stalk deletion aa 69-73 characteristic of poultry adaptation • M1 protein: N30D and T215A – increased virulence in mice • PB2: • 89V – enhanced polymerase activity and increased virulence in mice • 627K - enhanced polymerase activity and increased virulence in mice (most human isolates; absent in avian or environmental virus sequences) • PB1: • H99Y and I368V – H5 transmissibility in ferrets; not present in all • NS1 • P42S – increased virulence in mice

  9. H7 Receptor binding site Netherlands/219/2003 vs 2013 H7N9 180: A/T / A/ A Minimal impact, if any on the RBS. Assuming receptor binding is similar to published structural data, this should not directly interact with receptor 177: V/G /G /V Point towards the RBS pocket. More hydrophobic in Anhui/1/2013 May reduce α2-3 interactions? 212: T P, conserved in other H7 HAs 125: A/T /A / A Glycosylation site at position 123 in NL219 is not present in 2013 H7N9 217: L/Q /Q /I Equivalent to residue 226 in H3 numbering. Crucial for switching between α2-3 and α2-6 receptor specificity in H2/H3 HAs. 128: S A, conserved in other H7 HAs

  10. Glycans and influenza virus specificity A/New Caledonia/20/1999 (pre2009 H1N1) Seasonal Human Pattern A/Netherlands/219/2003 (H7N7) Avian Receptor-binding Pattern A/Anhui/1/2013 (H7N9) a2-3 Avian-type receptors, found in human lower respiratory tract a2-6 Human-type receptors, found in human upper respiratory tract

  11. Outbreak Response • Detection of etiologic agent • Identification of previously unknown pathogens • SARS and MERS CoV • Distinguish from background of commensals • Increasing reliance on PCR and sequencing • Characterization of etiologic agent • Tissue tropism and host range • Clinical recognition and management • Non human reservoir identification (important for control efforts) • Diagnostics development • Susceptibility to antimicrobial therapeutics • Vaccine development and use

  12. Questions? • Michael Shaw, Office of Infectious Diseases • MShaw1@cdc.gov • Yuri Khudyakov, Division of Viral Hepatitis • YKhudyakov@cdc.gov

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