1 / 22

Virus Evolution Molecular Epidemiology of Viral Infections

Virus Evolution Molecular Epidemiology of Viral Infections. Jen-Ren Wang, Ph. D. 王貞仁 Dept. of Medical Laboratory Science and Biotechnology National Cheng Kung University. Virus evolution. Virus evolution : constant change of a viral population in the face of selection pressures

helena
Download Presentation

Virus Evolution Molecular Epidemiology of Viral Infections

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Virus EvolutionMolecular Epidemiology of Viral Infections Jen-Ren Wang, Ph. D. 王貞仁 Dept. of Medical Laboratory Science and Biotechnology National Cheng Kung University

  2. Virus evolution • Virus evolution:constant change of a viral population in the face of selection pressures • Virus populations display diversity. • The sources of diversity:mutation (genetic drift), recombination, natural selection (adaptation, fitness)

  3. Replicating viruses produce large numbers of mutant genomes • RNA virus:Error rate- 1 in 104 or 105 • DNA virus:lower error rate – 1 in 107 or 108 - error-correcting DNA polymerase - latent infection

  4. RNA viruses and quasispecies • Viruses exist as dynamic distributions of non identical but related replicons. • Polymorphism

  5. Viruses exchange information • Recombination - polymerase changes templates (copy choice) during replication (RNA virus) - nucleic acid segments are broken and rejoined (DNA virus) • Reassortment

  6. Molecular studies are useful in • Epidemiological investigation • Real-time surveillance • Make predictions about future developments

  7. Molecular epidemiology of viral infections • Distinguish between related strains of viruses • Deduce the relationships between viruses from different outbreaks or individual patients • Dissemination and evolution of viruses can be followed locally and globally

  8. Molecular epidemiology of viruses • Determine the sources of imported viruses • Monitor pathways of virus transmission • Monitor the process of control activities • Develop molecular reagents for rapid detection of viral infections

  9. Implications of sequence information • Maintain effective diagnostics, treatment, and prophylaxis • Strain-specific treatment: HIV, HCV, HBV, CMV • HCV:indicator of susceptibility to specific treatments eg. Genotype 1 is resistant to interferon therapy • Detection of mutation that confer antiviral resistance • HIV:monitor emergence of drug resistance • Distinguish between more or less pathogenic strains • Avian influenza :HAPI or LAPI • HCV:differ in the in tendency to cause liver damage • Attenuated vaccine strains

  10. Methods for molecular epidemiological analysis • Oligonucleotide fingerprinting: Rnase T1 Recognize relationship between isolates separate from ancestral infection by no more than 3 to 5 years • Monoclonal antibody characterization of viral epitopes • Nucleic acid analysis Nucleic acid hybridization PCR-RFLP PCR-SSCP PCR-sequencing

  11. Oligonucleotide fingerprint analysis • Restriction enzyme- No • Probe- No • Basis for distinctions- Rnase T1 cleavage sites • Level of resolution- subtypes, quasispecies • Advantages- simple: directly applicable to RNA viruses. Can detect point mutations • Disadvantages- complex electrophoresis procedure

  12. Nucleotide sequencing • Restriction enzyme- No • Probe- No • Basis for distinctions- nucleotide sequence • Level of resolution- single genome (if cloned) • Advantages- wide applicability, can identify single nucleotide mutation • Disadvantages- Technically complex; produces large amounts of data; automated sequencing requires expensive equipment

  13. Influenza viruses • Antigenic drift - Epidemics - increase in incidence of pneumonia and lower respiratory disease - excess rates of hospitalization or mortality • Antigenic shift -Widespread and severe epidemics - Pandemic

  14. Viruses recommended in the influenza vaccines, 1968-

  15. Each year a new flu vaccine is produced, and judging which strains to target is a tricky business. A new study evaluating viral evolution suggests a more systemic approach to predicting next year’s virus.Plotkin et al. PNAS 99:6263-6268, 2002

  16. They found that among the sequences within each of these large clusters, those sequences isolated in China or Hong Kong are found preferentially in the first half of the cluster’s lifetime. These results support the hypothesis that dominant viral swarms tend to originate in Asia and thereafter spread across the globe. Joshua B. Plotkin et.al., PNAS 99:6362-6268, 2002

  17. Predicting evolutionary change in the influenza A virusNeil M. Ferguson and Roy M. AndersonNature Medicine 8:562-563, 2002

  18. Unlike HIV, which is constantly growing in diversity, influenza change constantly but with limited diversity at any point in time-giving an unusual “conifer” tree shape (R. Bush). Ferguson and Anderson. Nature Medicine 8:562, 2002

  19. The thick line running from the lower left to the upper right (open square) is called the trunk and represents the successful H3N2 lineage. Fitch et al. PNAS 94: 7712, 1997

  20. The average life-span of a nontrunk lineage is 1.5 years, although one recent nontrunk lineage persisted for 5 years (*). Bush et al. Science 286: 1921, 1999

  21. Positive selection is defined as a significant excess of nucleotide substitutions that result in amino acid replacements. Bush et al. Science 286: 1921, 1999

  22. Evolution isn’t just something that happened in the past; evolution can be observed in the present, and in some cases, used to predict the future. School boards and science educators need to understand this simple fact: If student don’t learn about evolution, they can’t possibly understand modern biology or medicine.David M. Hillis. Predictive Evolution. Science 286: 1866, 1999.

More Related