STEM Undergraduate
Research Symposium
First Place Winners
May 20, 2014
Sergine Lezeau
Florida Atlantic University
Accelerating HIV eradication by defining the
contribution of patients’ clinical, biological,
and socio-demographical factors on the
size of the HIV reservoir
Sergeine Lezeau
Advisor: Rafick-Pierre Sékaly, Ph.D.
Vaccine and Gene Therapy Institute
What is HIV?
Human Immunodeficiency Virus
Image Credit: Shutterstock
Two strains: Type 1 (HIV-1)
Type 2 (HIV-2)
Image Credit: UNAIDS
HIV Replication
CD4+
HIV
T cell
combination Antiretroviral Therapy
(cART) only targets actively
replicating HIV-infected cells
1
Reservoir
Image Credit: HIV gross german.png
HIV Reservoir
# cells with integrated, nonReservoir-size =
replicating, or latent HIV
Established early during acute HIV infection
Enables HIV infection to persist in treated
patients
2,3
cART cannot eradicate HIV
Circulating virus
START
STOP
Limit of detection
Time
Image Credit: vgtifl.org
Which factors
influence
reservoir-size to
vary in every
patient?
Clinical?
• CD8 count
• Co-infections
• Infection or cART duration
Biological?
• Age
• Race
• Gender
Sociodemographical?
• Ethnicity
• Geographical location
• Socio-economic status
Hypothesis
We proposed that the size of the latent HIV
reservoir correlates with multiple factors that
can affect the function of the immune system in
HIV patients.
Research Strategy
Screening
Visit
Leukapheresis
Procedure
HIV Integrated
DNA PCR Assay
Collected blood
& clinical data
Measured reservoir-size
(HIV Integrated DNA copies/
106 CD4+ T cells)
Collected clinical,
biological, & sociodemographical data
Database
Design
Statistical
Software
HIV Treated Patients
n=336
C = Caucasian
A = African American
H = Hispanic
NH = Non-Hispanic
O = Other (Mixed, Pacific
Islander, Asian)
Location
Fort Pierce, FL
n=42
Montreal, QC
San Francisco, CA
n=132
n=162
Age Range, Mean:
(32-67), 47.18
Gender:
9F, 33M
Race, Ethnicity:
20 C,NH 3 C,H
17 A,NH 1 A,H
1 O,H
Age Range, Mean:
(31-76), 54.98
Gender:
8F, 154M
Race, Ethnicity:
119 C 20 A
10 H 13 O
Age Range, Mean:
(20-68), 46.82
Gender:
26F, 106M
*Race, Ethnicity:
103 C 17 A
1O
* Race/ethnicity data is not
available for 11 patients
Reservoir-size inversely
correlates with CD4 count
Limit of
Detection
Mid
Low
Low
Mid
High
High
p <0.0001
CD4+ T cell count
(cells/μL blood)
1300
1000
500
0
100
500 1000
10000
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size positively
correlates with age
p <0.0001
10000
1000
500
100
Limit of Detection
0
35
60
Age at Blood Draw (years)
Reservoir-size positively correlates
with duration of infection
Limit of
Detection
Low
Mid
Low
Mid
High
High
p 0.0064
Estimated Duration
of Infection (years)
30
20
10
0
0
100
5001000
10000
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Racial groups show significant
differences in reservoir-size
Mean = 957.2
Mean = 299.9
p 0.0003
10000
1000
500
100
Limit of Detection
0
African
American
Males
Caucasian
Males
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Racial groups show significant differences
in reservoir-size for 35-60 year old males
Mean = 877.0
Mean = 265.5
10000
p 0.0007
1000
500
100
Limit of Detection
0
African
American
Males
Caucasian
Males
Summary
Age, race, infection duration, and reservoir-size
are associated with factors that can affect
immune function in HIV patients.
A significant difference in reservoir-size occurs
between HIV+ Caucasian and African American
males.
Future Work
Increase cohort size and data stratification
Demonstrate the correlation between reservoirsize and gender, co-infections, etc.
Identify the factors influencing these correlations
Significance
Increase limited knowledge on reservoir-size
Identify novel indicators for reservoir-size
Implement treatments adapted to HIV patients’
age, race, infection duration, etc.
Acknowledgments
Rafick-Pierre Sékaly, Ph.D.
Rebeka Bordi, Ph.D.
Nicolas Chomont, Ph.D.
Rémi Fromentin, Ph.D.
Jessica Brehm, Ph.D.
Franck Dupuy, Ph.D.
Zhaofeng Jian, M.S.
Anne Gambardella
Jeff Smith
Moti Ramgopal, M.D.
Dawn Brown, R.N.
Steven Deeks, M.D.
Melissa Krone
Evelyn Frazier, Ph.D.
John Nambu, Ph.D.
Ramon Garcia-Areas
Chelsea Bennice
Honors Thesis Students
Donna Chamely, Ph.D.
Tricia Meredith, Ph.D.
Jean-Pierre Routy, M.D.
Jennie Soberon
References
R.P., et al. (2013). “Barriers to a Cure for HIV: New Ways to
Target and Eradicate HIV-1 Reservoirs.” The Lancet.
1 Sekaly,
N., et al. (2010). “HIV Persistence and the Prospect of Longterm Drug-free Remissions for HIV- infected Individuals.” Science 329.
2 Chomont,
3
Chomont, N., et al. (2009). “HIV Reservoir Size and Persistence are
Driven by T Cell Survival and Homeostatic Proliferation.” Nature
Medicine 15:893-900.
Reservoir-size inversely
correlates with CD4 count
Early treatment initiation
limits reservoir-size
© The Author 2013. Published by Oxford University Press on behalf
of the Infectious Diseases Society of America. All rights reserved.
Females show higher CD4
count reconstitution
Reservoir-size inversely correlates
with CD4 count in Immune Responders
CD4+ T cell Count
(cells/μL blood)
Limit of
Detection
Mid
Low
Low
Mid
High
High
p 0.006
1000
500
0
100
500 1000
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size positively correlates
with age in Immune Responders
p 0.0215
10000
1000
500
100
0
Limit of Detection
35
60
Age at Blood Draw (years)
Reservoir-size positively correlates with
duration of infection in Immune Responders
Limit of
Detection
Low
Mid Mid
Low High
High
Estimated Duration
of Infection (years)
p 0.0053
30
20
10
0
0
100
500 1000
10000
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Reservoir-size (HIV Integrated
DNA copies/106 CD4+ T cells)
Racial groups show significant differences
in reservoir-size for male Immune Responders
Mean = 824.1
Mean = 223.9
p 0.0104
10000
1000
500
100
0
Limit of Detection
African
American
Males
Caucasian
Males
Eligibility Criteria
≥18 years old
Confirmatory test of HIV-1 infection
Clinical data history
--CD4/CD8 Counts & Viral Load
Signed consent form
No prior enrollment in HIV vaccine trial
No active autoimmune disease
AIDS Diagnoses and Related Deaths
New HIV Infections (2011)
Image Credit: UNAIDS
Taaha Menda
University of Miami
Taaha Mendha, N. Shamaladevi, Bal L . Lokeshwar
University of Miami Miller School of Medicine
Departments of Urology and Microbiology &
Immunology
What is Cancer?
Definition: uncontrolled cell death
Benign Tumors vs. Malignant Tumors
Prostate Cancer
Treatment
Resistance
Experimental Design
Curcumin
Piperine
Docetaxel
Cytotoxicity of Docetaxel
Cell Viability
(% Control)
100
PC-3
75
50
25
0
0.0
1.0
2.5
Docetaxel, nM
5.0
100
PC-3
75
50
25
0 0.0
2.5 5.0 10.0
Curcumin, M
Cell Viability
(% Control)
Cell Viability
(% Control)
Cytotoxicity of Curcumin and
Piperine
100
75
50
25
0
0
10 20 30
Piperine,M
150
125
C: Curcumin; P: Piperine
100
75
50
25
Treatment, M
0
P1
P5
0
+
P1
P5
C5
C5
+
C5
0
+
P1
P5
C1
C1
+
C1
nt
ro
l
0
Co
Colonies/well
Combinational Cytotoxicity
Time Dependence
Adding Piperine(24hours)
before
Cell Viability
(% Control)
100
PC-3
C 1uM
C 2.5uM
C 5uM
C 10uM
75
50
25
0
0
10
20
30
Piperine,M
40
Cell Viability
(% Control)
Adding Curcumin
(24hours) before
PC-3
100
P10
P20
P30
75
50
25
0
0
5
10
15
Curcumin,M
20
Apoptosis
Apoptosis vs. Necrosis
Tunel
DAPl
MERGE
Control
C10 uM
P10 uM
C10uM
+ P20uM
P20um +
C5uM
Effect of
curcumin and
piperine on the
molecular
events related
to cell death.
TUNEL
positive
apoptotic
bodies were
observed in
curcumin
treated PC-3
cells.
Future Plans
In vivo
Biochemical Pathway
Acknowledgements
Dr. Isaac Skromne, University of Miami
Mr. Daniel Munoz, Ms. Nicole Salazar,
Ms. Lei Zhang
University of Miami College of Arts and
Sciences
Syed Raza
Florida Atlantic University
Syed Raza
Research Advisor : Dr. David Binninger
Affects the thermoregulatory systems:
Excessive metabolic production of heat
Excessive environmental heat or impaired heat
dissipation
http://live-and-learn-always.blogspot.com/2011/04/gasp.html
Drosophila respond to the thermal stress by
entering into spreading depression
1. Reversible coma like state to conserve energy
2.Motor and neuronal systems are shut down
3. Reactive Oxygen Species levels tend to increase
http://www.cookaj.com/category/7490/funny-flies
http://faculty.baruch.cuny.edu/jwahlert/bio1003/fruit_flies.html
ROS are produced by oxygen metabolism
▪ O2
▪ H2O2
▪ OH
Excess ROS can lead to cell structure damage.
ROS affects amino acids
▪ Methionine is the most susceptible to ROS.
http://www.clker.com/clipart-dendritic-cell-1.html
Process can be reverted by Msr enzymes.
http://www.photobiology.info/Buettner.html
MsrA and MsrB:
Protect cellular
proteins from
oxidative damage
Accomplished through deletion
WT31 vs. AB46: Rate of Failure
Percent Failed
150
WT31
AB46
100
50
0
0
10
20
Minute
30
40
WT31 vs. AB46 vs. A90 vs. B54: Rate of Failure
Percent Failed
150
A90
AB46
B54
WT31
100
50
0
0
10
20
Minute
30
40
http://www.pops
ci.com/category/ta
gs/drosophila
Readout: the minute the fly does not move is
recorded.
Micro Hybridization Incubator and DAM
http://www.frontiers
in.org/Journal/10.338
9/fgene.2012.00068/
full
http://www.afab-lab.com/store/index.php?main_page=index&cPath=44
Drosophilla Activity Monitor (DAM)
30 minutes 38.5°C
Accomplished through RNAi- Interference
Msr B shows no significant difference
compared to parental lines
ACT X YW vs. RNAi B X YW vs. RNAi B X ACT: Rate of Failure
ACT X YW
RNAI B X YW
150
RNAI B X ACT
Percent Failed
100
50
0
0
10
20
Time
30
40
Msr B shows no significant difference
in middle aged flies
RNAi B X YW vs. RNAi A X ACTvs. RNAi X YW: Rate of failure
ACT X YW
RNAi B X YW
RNAi B X ACT
150
Percent Failed
100
50
0
0
10
20
Time
30
40
Msr B in old age shows significant
difference with one parental line
ACT X YW vs. RNAi B X YW vs.RNAi B X ACT: Rate of Failure
ACT X YW
RNAi B X YW
RNAi B X ACT
150
Percent Failed
100
50
0
0
10
20
Time
30
40
•
Flies lacking both MsrA and MsrB had a
higher failure rate compared to the wild type
•
Flies lacking MsrB had the highest failure rate
compared to the wild type (whether or not
MsrA present)
•
Knockdown of MsrB in young age(5-24) had
no effect
•
Increase in failure rates began to show in
middle age (35-39)
Experiments involving 60-65 days are ongoing
Knocking down MsrB in specific tissues will help
understand the molecular basis
Specific Tissue
Where it is
expressed
OK6
Motor Neurons
MHC
Muscle
GawB
Muscle
Dr. David Binninger
Dr. Frazier
Dr. Nambu
Ramon Garcia-Areas
Chelsea Bennice
Lindsay Bruce
Lab mates
Honor students
Undergraduate Research Grant
Hyperthermia inducing ROS
http://www.jpma.org.p
k/full_article_text.php?
article_id=4123
MsrB with OK6 in young age flies show
no statistical difference.
OK6 X YW vs. RNAi B X OK6 vs.RNAi B X YW: Rate of Failure
RNAI B X OK6
RNAI B X YW
150
OK6 X YW
Percent Failed
100
50
0
0
10
20
Time
30
40
Specific Tissue
Where it is expressed
w; Act-Gal4/Uas-RNAi-Msr/+ ; +
Ubiquitous
w; MHC-Gal4/Uas-RNAi-Msr/+ ; +
Muscle
w; OK6-Gal4/Uas-RNAi-Msr/+ ; +
Motor Neurons
w; GawB-Gal4/Uas-RNAi-Msr/+ ; +
Muscle
MsrA and MsrB
are expressed
w; UAS-RNAi-MsrB/+ ; +
w; Act5c-Gal4/UAS-RNAi MsrB; +
MsrA is
expressed
w; Act5c-Gal4/+ ; +
w; UAS-RNAi-MsrA/+ ;
+
w; Act5c-Gal4/UAS-RNAi MsrA; +
MsrB is
expressed
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