Investigations of HIV-1 Env Evolution Evolutionary Bioinformatics Education: A BioQUEST Curriculum Consortium Approach Grand Valley State University August.

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Presentation transcript:

Investigations of HIV-1 Env Evolution Evolutionary Bioinformatics Education: A BioQUEST Curriculum Consortium Approach Grand Valley State University August 9-11, 2006

HIV Life Cycle

HIV Virus

The HIV Genome

HIV env Gene

gp120 V3 region sequence Nucleic Acid Sequence CTAGCAGAAGAAGAGGTAGTAATTAGATCTGCCAATTTCACAGACAATGCTAAAATCATAATAGTACAGC TGAATGCATCTGTAGAAATTAATTGTACAAGGCCCAACAACAATACAAGAAAAGGTATACATATAGGACC AGGGAGAGCATTTTATGCAACAGGAGAAATAATAGGAGATATAAGACAAGCACATTGTAACATTAGTAGA GAAAAATGGAATAATACTTTAAACCAGGTAGTTACAGAATTAAGGGAACAATTTGGGAATAAAACAATAA CCTTTAATCACTCCTCAGGAGGGGACCCAGAAATTGTAATGCACAGTTTTAATTGTGGAGGGGAATTTTT CTATTGTAAT Amino Acid Sequence LAEEEVVIRSANFTDNAKIIIVQLNASVEINCTRPNNNTRKGIHIGPGRAFYATGEIIGDIRQAHCNISR EKWNNTLNQVVTELREQFGNKTITFNHSSGGDPEIVMHSFNCGGEFFYCN

gp 120 Structure

The Markham et al.HIV-1 env Sequence Dataset Richard Markham and his colleagues (1998), published some research on the pattern of HIV evolution and the rate of CD4 T-cell decline in the Proceedings of the National Academy of Sciences. In addition to the journal article they submitted 666 nucleotide sequences to the GenBank database. They studied a 285 base pair region of the env gene. The gene product, membrane protein gp120, binds to the CD4 receptor site on T-lymphocytes and is involved with the entry of the virus into those cells. Markham et al. followed the evolution of this viral gene sequence in 15 subjects by collecting blood samples at six month intervals for up to four years. For each visit all the forms of the gene (clones) were sequenced and CD4 T-cell counts were made. This data set provides a rich resource for looking closely at the patterns of change in HIV over time.

Summary of the data set Subjects: 15 Number of visits: 3-9 Number of clones per visit: 2-18 Total number of sequences available: 666 CD4 cell counts for each visit

Possible Investigations What is the pattern of HIV evolution within an individual? –Do the number of clones over time change in any regular way? –Do certain clones appear to survive (leave descendents) over time while other disappear (go extinct)?

Possible Investigations What is the pattern of HIV evolution within the env sequence? –Are there particular positions in the sequence that are more or less likely to mutate? –Are there different rates of synonymous (silent) and non-synonymous mutations?

User Web Browser Output to User User Input Format Translator, Query Engine and Program Driver Workbench Server Results to User User Instructions and queries Application Programs (May have varying interfaces and be written in different languages) Results Instructions Information Sources (May be of varying formats) Information Queries NCSA Computational Biology Group The NCSA Information Workbench - An Architecture for Web-Based Computing