Minh's Poster

1
HIV Immune Dysfunction in Innate Cell Populations Minhthu Nguyen, Harry Wynn-Williams, Lishomwa Ndhlovu 1 Department 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 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 Introduction Results Methods References 1 Kerstin Puellmann 1 , Alexander W Beham 2 , Tina Fuchs 3 , Julia Kzhyshkowska 3 , Alexei Gratchev 3 , Rebecca Laird 2 , Johannes T Wessels 2 , Michael Neumaier 3 , Arnold Ganser 1 and Wolfgang E Kaminski 3. “ 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 LL 1 , 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 receptor 1 , 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 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 10 6 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 Monocyte s 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 findings 1 . 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

Transcript of Minh's Poster

Page 1: Minh's Poster

HIV Immune Dysfunction in Innate Cell PopulationsMinhthu 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

References1 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

ObjectiveCan 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.

HypothesisIf 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