1. HIV Immune Dysfunction in Innate Cell Populations
Minhthu Nguyen, Harry Wynn-Williams, Lishomwa Ndhlovu
1Department of Tropical Medicine, John A. Burns School of Medicine,
University of Hawaii, Manoa, Honolulu, HI
In 2012, according to Global Report, over 35 million Americans were
infected with the Human Immunodeficiency Virus (HIV) indicating this
disease, despite effective therapy, still continues to have a significant
health burden. HIV IS A POTENT virus due to its’ ability to infect T-cells, a
key element in the body’s immune system. The virus recognizes a
particular type of T-ell that expresses the surface proteins CD4 and CD3.
During the course of HIV infection, the virus effectively depletes the
body’s CD4+ T-cells. Eventually over a 8-10 year period progression to a
full blown Acquired Immunodeficiency Syndrome develops and death
ensues if no treatment is given. While modern antiretroviral drugs are
effective at reducing virus and prolonging life in HIV+ patients, there are
currently no cures for HIV and several non-AIDS related morbidities are
occurring. It appears HIV integrates its own genetic code into the host
CD4 T-cell and remains in a latent state. This makes it difficult for the
body’s immune system to detect the HIV virus and clear it.
Introduction Results Methods
References
1 Kerstin Puellmann1, Alexander W Beham2, Tina Fuchs3, Julia Kzhyshkowska3, Alexei Gratchev3, Rebecca Laird2,
Johannes T Wessels2, Michael Neumaier3, Arnold Ganser1 and Wolfgang E Kaminski3. “Macrophages express a TCRβ-
based variable immunoreceptor” The Journal of Immunology. 134.34 (2009): 182.
http://www.jimmunol.org/cgi/content/meeting_abstract/182/1_MeetingAbstracts/134.34.
2 Lanier LL1, Chang C, Spits H, Phillips JH. “Expression of cytoplasmic CD3 epsilon proteins in activated human adult
natural killer (NK) cells and CD3 gamma, delta, epsilon complexes in fetal NK cells. Implications for the relationship of
NK and T lymphocytes” The Journal of Immunology. 1876.80 (1992): 149(6).
http://www.ncbi.nlm.nih.gov/pubmed/1387664
Objective
Can we effectively isolate highly purified Monocyte populations from
human peripheral blood, free of T-cell contaminants using
multiparameteric flow cytometry cell sorting technology and to
subsequently test for contamination of T-cells in our isolated populations
by quantitative Polymerase chain reaction using T-cell receptor genes
and develop the platform for accurately assessing HIV reservoirs in
Monocytes in treated HIV infected patients?
Analysis of extracted RNA from sorted
populations. 6 genes of interest were used to
detemrine the presence of TCR and/or CD3
genes in our sorted populations. Using the
CD3+ population as a control sample, the
relative expression of CD3 genes and TCR Beta
chain genes was determined using Delta Delta
CT statistical analysis. We see that our
monocyte populations exhibit very little gene
expression of the four CD3 genes however
there is some expression of the two TCR genes.
Similar research amongst other groups
indicates certain monocyte subsets do express
a variable TCR-like receptor1, thus supporting
the evidence of TCR gene expression in our
CD14+16- and CD16+ subsets.
The high expression of CD3 zeta in our
CD19/20/56+ population may be attributed to
the prevalence of CD3 zeta in Natural Killer
(NK) cell populations. While NK cells generally
don’t express CD3 surface proteins, they have
been shown to express CD3 zeta2. The high
presence of both TCR genes in our CD19/20/56
population is most likely due to contamination.
While much research has focused on the role of CD4 T-cells in HIV
infection, there is evidence that another type of immune cell, the
Monocyte, is also prone to HIV infection and can serve as a viral
‘reservoir’ allowing the virus to remain dormant for long periods of time.
Monocytes descend from myeloid progenitor cells and can differentiate
into Macrophages and Dendritic cells, both key players in the body’s
innate defense system. In order to study Monocytes as reservoirs of HIV,
these cells must first be isolated from other cells. In this study we aimed
to develop a protocol for the isolation of our target cell populations.
Hypothesis
If we sort leukocytes based on protein surface expression, then the
expression of the CD3 and TCR (T-cell receptor) gene in the RNA of our
Monocyte populations should be negligible when compared to the RNA of
our T-cell population.
Subjects: Freshly isolated blood was obtained from a buffy coat derived from a healthy
blood donor from Stanford Blood Bank, CA.
Flow Cytometry Cell Sorting Isolation: Cryopreserved PBMC’s from a healthy donor was
rapidly thawed in RPMI 1640 with 2% FBS and washed in PBS buffer. Cells were counted
using Guava staining procedure and resuspended for final concentrations of 106
cells/200uL. For surface staining, conjugated antibodies to CD3, CD11b, CD14, CD16,
CD19, CD20, CD56 and HLA-DR were used. Live/Dead staining was carried out using
RARD dye. Samples were washed and resuspended in FBS 2% to a concentration of
10^6/mL and proceeded to cell sorting. Cell sorting was carried out using a FACSAria cell
sorter with gating strategy as depicted. Leukocyte subsets were cell sorted into 4
populations according to expression of CD3, CD14, CD16, CD19, CD20, CD56 and HLA-DR
to purities ranging from 82-99%. Cells were sorted into FBS 2% and placed on ice prior to
RNA extraction.
RNA Extraction: RNA extraction was performed using Qiagen AllPrep Universal RNA
Extraction Kit. Total RNA was eluted from the columns, quantitated on a Nanodrop
spectrophotometer, and aliquoted for further applications. Prior to qPCR analysis RNA
was frozen in -80°C for long term storage.
SyberGreen qPCR: Applied Biosystems SyberGreen gene expression kit was used along
with ABi StepOne real time PCR thermocycler. RNA was diluted to concentrations
between 100-200 ng/uL and combined with SyberGreen reagents according to ABi
protocol. Results were analyzed with ABi OneStep software using the Delta Delta CT
method.
Figure 1: HIV infection and integration of provirus followed by viral synthesis.
CD19/20/56+
CD3+
CD3+CD19/25/56+
CD16+CD14+16-
CD14+16-
CD16+
Gating Strategy: Cells were sorted according to surface phenotype and then
a purity check was performed post-sort to determined efficacy of gating
strategy. Purities ranged from 82% for the CD14+16- monocyte population
to 99% for the CD3+ population.
RNA Extraction and PCR
Cell Sorting
Figure 2: Gating strategy based on expression of surface proteins on leukocyte populations
Figure 3: Purity check post-sort
82%
93%99%
95%
Taken from Janeway Immunobiology Textbook
Figure 4: Expression levels of CD3 and TCR genes in extracted RNA of sorted cells
Monocytes
T-cells
B-cells/NK cells
Conclusions
Process by which PCR replicates DNA
After sorting leukocytes based on surface protein expression we can see that the
monocyte populations express lower levels of CD3 genes than the CD3+
population.
qPCR analysis indicates the presence of TCR genes in the monocyte populations
which could either a result of contamination or due to a small subset of
monocytes that express a TCR-like receptor. Other studies have indicated similar
findings1.
This method of sorting monocytes will be useful to further our understanding of
the role monocytes play in HIV pathogenesis. Downstream applications including
viral outgrowth assays and microarrays may help us understand how monocytes
act as a reservoir for HIV.
Cells sorted into separate tubes using
surface protein expression