Personal perspective:
an HIV-positive family
http://www.youtube.com/watch?v=EDFiAfJC848
Introduction
• This module uses an inquiry-based approach using
video, mathematical modeling, world mapping, and
bioinformatics to follow the progression and
understanding of HIV-AIDS.
• The problem is designed for undergraduate students in
the life sciences and mathematics.
• Using global health cases, visualization data, and
mathematical models, students working collaboratively
will share what they know about HIV-AIDS.
Introduction (cont.)
• A mathematical model will enable them to
compute the intensity of the HIV-AIDS epidemic,
calculate the half-life of disease progression, and
measure the effects of interventions.
• Based on Markham data (as referenced by Sam
Donovan), students will be able to design
questions to correlate, classify, and compare CD4
counts and various HIV clones as well as build
phylogenetic trees.
What we need to know?
Potential students questions
• Difference
between HIV/AIDS
• What kind of virus
is HIV?
•Education
•Transmission
•Vaccines
Prevention
Cost
• Demographics
What is
HIV?
Treatment
• Effectiveness
• Resistance
HIV through maps
ucatlas.ucsc.edu
HIV infected people versus income
around the world
http://www.who.int/healthinfo/statistics/04.whostat2005map_hivprevalence.jpg
This map summarizes the global distribution
of HIV-1 strains in 2003
www.pbs.org/.../frontline/aids/atlas/clade.html
Deaths due to HIV/AIDS in 2002
http://www.worldmapper.org/display_extra.php?selected=374#
http://www.worldmapper.org/posters/worldmapper_map227_ver5.pdf
http://www.worldmapper.org/posters/worldmapper_map226_ver5.pdf
http://www.worldmapper.org/posters/worldmapper_map225_ver5.pdf
Deaths by STDs Excluding HIV
http://www.worldmapper.org/display_extra.php?selected=375
a Syphilis, Map 375, (87% of deaths).
b Chlamydia, Map 376, (5% of deaths).
c Gonorrhoea, Map 377, (1% of deaths).
d Other STDs, no map, (7% of deaths).
Module Activities
Sequence Data Set
Protein
Markham
Sequences
1998
Nucleic
Acids
Data Analysis
Alignments
Structures
Mathematical
Modeling
Sequences
Trees
Distance matrices
Sequence analysis
Sequence
Biology
Workbench
Consurf
Swiss
Viewer
PDB
General Information on HIV
Biology
HIV Infection and AIDS
• An often asymptomatic infection caused
by the Human Immunodeficiency Virus
(HIV).
• AIDS is the advanced state of the disease
characterized by a series of opportunistic
infections occurring due to an
immunosupressed state.
AIDS Definition (CDC)
• HIV+ and a CD4 count of 200/mm3 or less*
• At least one out of 26 defined opportunistic infections
such as:
– Pneumocystic carinii pneumonia (PCP)
– Kaposi’s Sarcoma
– Systemic Candidiasis
* For people 13 year of age or older
HIV Transmission
• Sexual transmission
– Through the mucosal membranes: vagina, vulva, urethra,
rectum and mouth.
• Blood or blood products
– Diminished risk by blood transfusions.
• Syringes
– Intravenous drug users.
• Vertical transmission from mother to child
– Depends on the delivery method.
HIV is not transmitted through…
• casual contact
• shearing silverware,
towels or clothing.
• saliva
• sweat
• tears
• swiming
pools
• telephones
• toilets
• door knobs
• insect bites
The HIV virus infects and destroys CD4 cells
• T-helper Lymphocytes (CD4 cells)
are essential for the proper
function of the immune system
helping in antibody production
against infectious agents.
• The HIV virus targets CD4
lymphocytes destroying them as
the newly made viruses exit the
cell.
• As the amount of virus (viral load)
increases in a subject, the number
of viable CD4 cells (CD4 count)
decreases.
HIV infection depends on the recognition of
surface molecules on the CD4 cell.
• The first step in HIV infection is
the binding of the CD4 molecule
in the lymphocyte surface with
the viral receptor protein GP120.
• The HIV-CD4 complex then binds
the CCR5 molecule that serves as
a co-receptor for HIV infection.
•The viral GP120 binds to the coreceptor through a specific
protein domain known as the V3
loop.
•Differences in the viral DNA gene
sequence encoding the V3 loop
may affect viral recognition of the
target cell.
• Differences in the viral DNA sequence
accounts for different strains of the HIV
virus. An infected individual often has
several viral strains.
Resources
• Gap minder
– http://www.gapminder.org/videos/ted-talk-2009hans-rosling-hiv-facts/
• Information related to HIV statistics around the world
• World mapper
– http://www.worldmapper.org/
• NCBI
– http://www.nlm.nih.gov
Resources
•
•
•
•
•
•
Clustal W shape/motif/
ConSurf http://consurf.tau.ac.il/
CD4/gp120 3D-model prediction
Work Bench http://seqtool.sdsc.edu/
NCBI BLAST http://ncbi.nlm.nih.gov
Mathematica http://wolfram.com.
Resources
• Markham RB, Wang WC, Weisstein AE, Wang Z, Munoz A, Templeton A,
Margolick J, Vlahov D, Quinn T, Farzadegan H, Yu X-F. 1998. Patterns of
HIV-1 evolution in individuals with differing rates of CD4 T cell decline.
Proc. Natl. Acad. Sci. USA 95: 12568-12573. The original paper presenting
and analyzing the data on which this problem space is based.
• Burks J, Ward L, Hota S, Gunasekaran G. Mathematical Modeling of
HIV/AIDS Epidemic; In Press for publication in NCUR Proceedings
• AVERT: AVERTing HIV and AIDS: http://www.avert.org
• Kuby Immunology, 6th Ed. 2007 W.H. Freeman and Co.
• National Institute of Allergy and Infectious Diseases:
http://www.niaid.nih.gov/DAIDs/dtpdb/graphics/cellbin.gif