Alex Cardenas Week 3

Ten Terms

1. Seroconversion - the change of a serologic test from negative to positive, indicating the development of antibodies in response to infection or immunisation. Biology Online September 20 2011
2. CD4 T Cell - A form of T lymphocyte with CD4 receptor on the cell surface that recognizes antigens of a virus-infected cell Biology Online September 20 2011
3. Epitope - that part of an antigenic molecule to which the t-cell receptor responds, a site on a large molecule against which an antibody will be produced and to which it will bind Biology Online September 20 2011
4. Cohort - a group of animals of the same species, identified by a common characteristic, which are studied over a period of time as part of a scientific or medical investigation Biology Online September 20 2011
5. Stratification - The use of chemical and mechanical systems to break dormancy and increase germination. Biology Online September 20 2011
6. Taxon - Any group or rank in a biological classification into which related organisms are classified. Biology Online September 20 2011
7. PCR - polymerase chain reaction; the first practical system for in vitro amplification of dNA and as such one of the most important recent developments in molecular biology. Biology Online September 20 2011
8. Plasma Viral Load - The number of viral particles (usually hIV) in a sample of blood plasma. HIV viral load is increasingly employed as a surrogate marker for disease progression. It is measured by pCR and bDNA tests and is expressed in number of HIV copies or equivalents per millilitre. Biology Online September 20 2011
9. Recombination - The process of forming new allelic combination in offspring by exchanges between genetic materials (as exchange of DNA sequences between DNA molecules). Biology Online September 20 2011
10. HIV 1 - The type species of lentivirus and widely recognised as the aetiologic agent of acquired immunodeficiency syndrome (aids). It is characterised by its cytopathic effect and affinity for the t4-lymphocyte. Biology Online

Outline

Abstract

• Extent of CD$ T cell decline was studied.
• Rates were both higher in nonprogressors than progressors.
• Individuals with rapid or moderates disease progression favored nonsynonomous mutations; nonprogrssors selected against nonsynonymous mutiations.
• Levels to which CD4 T cells fall resulted in differences in mutiations types that was best adapted to host enviornment.
  • High mutation and replication of HIV -1 (1-3) allow rapid changes to enviornment.
• Different virus samples would show uniform genetic makeup with little variants due to neutral mutiations.
  • Organisms with high mutations abaility, have been observed where their enviornmental changes are geared toward them (i.e. – Escherichia coli)
  • Yet, unstable host enviornment could alter genetic composition of virus pool.
  • Could be done by differential display of coreceptors or host cell immune response.
• Indiscriminate but powerful destabilizing force would display variants which were most numerous.
  • If immune response only targeted most abundant viral variant, we could see a decrease in viral load because of less frequent viral stands contributing diversity.
• Studying patterns of HIV -1 evolution diversity, can propose selection forces that influence how virus is adapting to forces and viral evolution.
• PREVIOUS STUDIES examined infected subjects that were characterized by HIV -1 genetic evolution.
  • Non direct examination techniques were used on sequence patterns and analysis was limited in number in subjects.
• CURRENT WORK analysis of HIV -1 evolution in 15 subjects were observed over a 4 year period in intervals.
• Rapid CD4 T cell decline has relation to attaining higher levels of genetic diversity and between moderately or rapidly progressing subjects and nonprogressor, it was observed that there are differing patterns of selection.

Methods

• The study Population
  • 15 participants of injecting drug users.
  • Compared CD4 – T cells 6 months, 2 years, 4 years.
• Sequencing of HIV -1 env Genes

Studies conclude: preponderance of viral DNA – obtained from PBMC that is unactivated.

• • 2 env primers used and 2 nested primers used. Underlined portion are nested primers for cloning purposes.
  • Varying levels of heat and time were applied to cycles. PCR amplifications were cloned into pUC19.
  • Screen for input of viral DNA copy number – done so by limiting dilution single-round PCR.
  • All clones from PCR amp. Came from a viral genome template.
• Generation of Phylogenetic Trees
  • Distance measure, accounts for base composition and transition bias.
  • Subjects data lacking for some visits (note)
  • Different taxa colors – time observed. Independent segregation of clones – trees (except S1&S2)
• Correlation Analysis
  • 15 subjects displayed 76 time points, 1 year later, CD4 T cell count known.
  • Relation to different CD4 T cell counts 1 year later with Xo values in which individuals start at similar CD4 T cell counts can be extracted from CD4 T cell count .
• Determination of dS/dN Ratios
  • Sequence of subjected that was computed, compared to stain.
    • Nonsynonymous / synonymous
    • Number of sites that mutation of each class could occur corrected bias of nonsyn. changes shown through random mutation
    • Jukes-Cantor correction used
  • dS & dN averaged over all strains at certain visit. Skewed distribution was shown median value was used.
• Examination of Source of Greater Initial Visit Diversity in Subjects 9 and 15
  • Subjects 9 and 15 displayed high genetic variation. Affected with 2 different viruses?
  • 3 trees made, clones of first visit from subject 9 and 15. And 150-200 random clones were studied.
    • Viruses segregated independently or monophyletic virus
      • Answer: monophyletic
  • Preseroconverison history reexamined
    • Showed up to 7 months before first visit, subjects showed to be HIV-1 seronegative.
    • Exclusion of recombination events in subject 15 had pi value of 11.4.
    • For a 6-month postseroconversion visit, 11.4 displayed higher values.
• Comparison of the Rather of Change of Divergence and Diversity
  • Each individual – regression line fit of diversity/divergence as a change in time.
  • Random effects models were compared in order to give average slopes for 3 groups.

Results

• CD4 decline varied in 15 subjects (fig 1)
  • Median annual changes in CD4 T cell count from increase 53/year – decrease 593/year.
• 1,702 to 321,443 copies of viral genonme – all subjects from 1 of first 3 visits.
• Nonprogressor group – at early times, had low viral loads vs. progressor groups.
• Analysis of genetic sequence mainly focused around third hypervarialbe (V3) domain.
  • Site of host-virus interaction
  • Can tolerate frequent mutation.
• Genetic diversity at each visit & divergence – parameters that influenced changes in HIV 1 sequences.
• Diversity and divergences increased in time.
  • Rapid progressor group – greater rate of increase.
• When compared with CD4 T cell count, diversity and divergence had negative corollary.
• Subjects most likely to have CD4 T cell decline over next year if their virus showed greater genetic diversity at a visit.
• If ratio = 1, mutation is occurring randomly without selection.
  • Moderate and rapid progressors showed median dS/dN ratio 0.4, selective advantage.
• Trees from 10 to 15 – no predominance of single strain throughout period of time.
• Viruses from visit 5 spread in tree.
  • Visit 6 and 7 viruses extended and carried clones 1 and 9 from visit 5.
  • Shows many different viruses and branching throughout trees at various visits.
• Determination analysis and ratios were calculated in order to put together the phylogenetic tree of viral evolution.