Download JournalClub1

Patterns of selection for or against
amino acid change among different
CD4 T-cell count progressor groups
Michael Pina, Salomon Garcia
Journal Club Presentation
BIOL398-01/S10: Bioinformatics Laboratory
March 2, 2010
Outline
•
•
•
•
•
•
Introduction to the Markham et al. paper
Our question about the article
Methods
Results
Conclusion
Focusing on a newer study
CD4 T-cell count associated with
diversity and divergence
• The evolution of the HIV-1 gene was
studied in 15 seroconverting participants
(intravenous drug users)
• They were selected for differences in the
rate of their CD4 T-cell decline
• Rates of diversity and divergence both
showed a pattern of increase among the
progressor groups
Evolution of the HIV-1 virus in
the participants
• Viral evolution among the progressor
groups showed a selection for
nonsynonymous mutants
• Nonprogressors with low viral loads
selected against nonsynonymous
mutations
• For the progressor groups, this may have
resulted in higher reproduction rates of the
virus
HIV-1 variants over the course of
the study
• No single variant was dominant across all
participants
• Evolution away from a variant was
followed by evolution towards a variant
• This may show selection against a
predominant strain or the product of
independent evolutions within different
host environments
The importance of CD4 T-cells
• Differences of CD4 T-cell count reflect not
only the quantity of mutations, but
differences in the mutations that may be
best suited to the host environment
• Higher levels of genetic diversity is most
frequently associated with more rapid CD4
T-cell decline
Taking a closer look at the paper
• We wanted to know how the amino acid
changes are affecting the interaction
between the virus and host environment
• “The overall pattern is one in which viral
strains from nonprogressors showed
possible selection against amino acid
change, while those from progressors
showed selection for such change (or
against the absence of change).”
(Markham et al. 12572)
Our question regarding the paper
• What can the dS-dN value tell us about
the selection for/against amino acid
change?
• Our hypothesis is that subject 10 will show
more nonsynonymous changes and
subject 13 will show more synonymous
changes.
Methods to find an answer
• Subjects 10 and 13 were chosen because of
their quintessential qualities as “rapid
progressor” and “nonprogressor”, respectively
– They have nearly the same amount of data points
collected over a similar time span
• All of their DNA sequences were obtained from
the Bedrock website, in addition to other data
from the study
• The online Biology Workbench tools were used
for a variety of tasks
CD4 T cell trajectory, diversity, and divergence over
time since first seropositive visit (t = 0) in each of the
15 subjects
Statistical calculations
Subject
# clones
S
Theta
Min Diff
Max Diff
10
49
74
16.3
1.14
20.0
13
26
24
6.43
1.14
9.12
Using the Biology Workbench
• CLUSTALW was used for multiple
sequences alignments for all available
sequences of subjects 10 and 13
– Phylogenetic trees were also generated
• CLUSALDIST was used to generate a
distance matrix
Phylogenetic trees for subject 10
and 13
Subject 10
Subject 13
dS-dN values
10
.5
• Converted to log
scale for consistency
among data values
• Negative value
indicates synonymous
mutations
• Positive value
indicates
nonsynonymous
mutations
-
13
n/a
1
-0.118
-0.861
2
0.530
n/a
3
-
-0.333
4
-0.133
1.724
5
-0.447
0.479
6
0.785
7
-
-
8
n/a
-
9
n/a
-
10
n/a
-
11
n/a
-
12
n/a
-
13
n/a
-
An answer to our question
• It was determined that subjects 10 and 13
do indeed differ in their diversity and
divergence as represented visually in their
phylogenetic trees and also in our
statistical calculations
• The dS-dN values are so similar and
limited that it is difficult to say whether or
not progressors show a selection for
amino acid change
A more recent article
• Functional diversity of HIV-1 envelope proteins
expressed by contemporaneous plasma viruses.
(Nora et al.)
• Clones carrying unique mutations in V3 often
displayed low infectivity
• No correlation was observed between viral
infectivity and sensitivity to entry inhibitors (such
as CD4)
• Genetic evidence supports the idea that
purifying selection against deleterious mutations
is occurring in the env region
References
• Markham RB, Wang WC, Weisstein AE, Wang Z, Munoz A,
Templeton A, Margolick J, Vlahov D, Quinn T, Farzadegan H, and
Yu XF. Patterns of HIV-1 evolution in individuals with differing rates
of CD4 T cell decline. Proc Natl Acad Sci U S A 1998 Oct 13; 95(21)
12568-73
• Nora T, Bouchonnet F, Labrosse B, Charpentier C, Mammano F,
Clavel F, and Hance AJ. Functional diversity of HIV-1 envelope
proteins expressed by contemporaneous plasma viruses.
Retrovirology 2008 Feb 29; 5 23. doi:10.1186/1742-4690-5-23
• A special thanks to Dr. Dahlquist for answering our questions along
the way!