The use of DNA microarrays to determine the effect of histone deacetylase
inhibitors on host response to gene therapy vectors.
Mike Waters
Dr. A. Malcolm Campbell, Dr. Paul Fawcett
Introduction
A new discovery in the field of gene therapeutics resonates throughout the world
of clinical medicine. Gene therapy regimens are currently under investigation as possible
treatments of cancer9, 8, HIV/AIDS8, 10, cardiovascular diseases4, infectious diseases2, and
neurodegenerative disorders1. Clinical progress however has been slowed due to
problems regarding the vehicles of gene transduction into the patient’s genome. Today,
three major transgene vectors are used in gene therapy studies: retroviral vectors,
adenoviral vectors, and non-viral vectors. Of the three, adenoviral vectors pose the most
promise from a pharmacological standpoint because of their efficiency of gene
transduction, ability to transduce genes regardless of mitotic cell status, tissue specificity,
and potential duration of transgene expression6, 7, 8, 9.
However, adenoviral vectors are problematic pharmacological agents due to the
degree in which they elicit an innate immune response in their host3, 5, 7, 8. Induction of
the innate immune response poses two problems for clinical gene therapy treatments.
First, stimulation of the innate immune response leads to local inflammation of the
effected tissue. This inflammation often leads to morbidity of the local tissue and
therefore the transduced host cell, sharply attenuating transgene expression.11 The second
problem associated with the innate immune response is the activation of effector cells.
Pathogen recognition by the innate immune system results in the recruitment of
leukocytes that secrete chemokines to the surrounding tissue; this results in a positive
feedback loop of leukocyte recruitment. If pathogen exposure is prolonged a “chemokine
storm” can result ending in sepsis and likely host death.11
The inflammatory and leukocyte response to viral infection is driven by the
MyD88-dependent and STAT pathways. The first step in host identification of non-self
gene therapy vectors is recognition of pathogen associated molecular patterns (PAMPS)
by cell membrane toll-like receptors (TLRs).12 That recognition activates a signal cascade
mediated by the universal adaptor protein My-D88 that results in the activation of NF-kB,
a protein complex transcription factor that induces the production of interferon-α and
other inflammatory cytokines.14,17
Interferon-α production results in the activation of the STAT pathway. Binding of
inteferons to interferon receptors on the cell membrane induces the phosphorylation and
subsequent heterodimerization of the STAT1 and STAT2 proteins. The heterodimer then
binds to interferon regulatory factor 9 (IRF9) to form interferon stimulated gene factor 3
(ISG3), a transcription factor capable of nuclear translocation. ISG3 then binds to a
responsive element (ISRE) upstream of genes responsible for the establishment of an
antiviral state, resulting in their production.12,13,16
Recently it has been shown that inhibition of a class histone deacetylase enzymes
prevent the establishment of the antiviral state by modulating interferon-α induced
transcription to a basal level.13 Though the exact mechanism of this modulation has not
been determined it has been found that HDAC activity is required to recruit RNA
polymerase II to the promoters of selected ISRE genes.13 Traditionally HDAC inhibitors
have been known as global repressors, however recent literature suggests that the effect
of acetylases and deacetylases as post-translational modifiers needs to be reevaluated on a
gene by gene basis. Therapeutically HDAC inhibitors have been approved by the FDA as
anti-cancer agents, thus we suspect the global nature of HDAC inhibitors modulation of
gene expression does not affect its ability to be used as a pharmacological product. 6, 13, 15
Currently the goal of our laboratory is to determine whether the treatment of a
host cell with an HDAC inhibitor prior to adenoviral infeciton is sufficient to transiently
subdue the expression of genes associated with an antiviral state and therefore obtain
stable transgene expression.
Progress Report
We planned to carry the infections out in ex-vivo cell lines therefore it was
necessary to first determine the multiplicity of infection (MOI) and cell type to use.
Initially we planned on using bone marrow derived macrophage (MAST) or macrophage
like (RAW 24.7) cells. We collaborated with the Valerie Lab to carry out a dose-response
experiment measuring the titer of virus vs. the percentage of cells that obtained stable
transgene (GFP) expression. Interestingly none of the cells during the experiment
obtained stable GFP expression, including the positive controls. We decided to proceed
with parameters established in the literature for adenoviral infection (hepatocytes with
and MOI of 10).
Next we decided to run 2 microarrays (fig.1) comparing levels of RNA expression
at different time points during adenoviral infection in the presence or absence of
trichostatin A (an HDAC inhibitor).
0 Hours
6 Hours -TSA
Control for the up-regulation of innate immune response
genes upon infection
6 Hours + TSA
6 Hours -TSA
Comparison of the expression of the program of genes
involved in innate immune response in the presence of TSA
Fig 1.-depicts the arrays run in our experiement
We succeded in obtaining a “gridable” .tiff image for the array comparing RNA
collected at 6 hours + TSA and 6 hours –TSA. Using the GenePix Pro 5.1 software, the
array was grided and the data was entered into the ramhorn gene array data base for
analysis. In all, 1064 gene expression levels were changed by log2 or greater when treated
with TSA 3 hours before infection with GFP adenovirus. We noticed the repression of
several genes involved in the innate immune response (Fig.2) however repeated trials and
controls are needed for more complete analysis as we did not obtain the same “gridable”
file for the control array (0 hours vs. 6 hours –TSA).
Gene
Fold Repression
TNF
Interacting
Protein
-4.272
Interferon
Tau
-3.822
Interferon
Alpha
-2.05
CBP
-4.891
Interleukin
enhanced binding
domain
-2.031
Fig 2.-depicts the fold repression of several genes involved in the immune response
Goals
During the academic year I plan to make periodic trips to VCU to obtain
microarray data that can be analyzed and grided at Davidson. The first set of microarrays
that I will run will be a repeated trial of the first experiment ( 0 vs. 6- and 6+ vs. 6-).
These arrays have to be run for the purposes of establishing a control and to ensure
reproducibility. The subsequent sets of microarrays I will run will involve either new cell
lines (BMDM, MAST etc.) or new HDAC inhibitors. Availability of new HDAC
inhibitors will play a large role in the experimental parameters of the coming arrays that I
will run. All arrays will be conducted in murine cell lines under the experimental
procedures used in the Fawcett Lab for cell culturing, RNA prep, RNA amplification, dye
coupling and hybridization, scanning and griding. Computationally I will continue to
work with the GenePix Pro 5.1 software in order to be able to enter my data into the VCU
ramhorn database. Also I will be looking into learning about novel analysis software to
interpret the large amount of data produced by a microarray.
During the academic year I will be involved in coursework aimed at furthering
my background in genomics, microbiology, chemistry and biological statistics. During
the fall semester I’m enrolled in (Chemical Equilibrium), (Genomics, Proteomics and
Bioinformatics), and (Biostatistics).
My budget of $1400 dollars will mostly be spent purchasing RNA amplification
kits ($1123). Other costs might include fees for a symposium poster($6-20) or
miscellaneous reagents needed for the other steps in processing a microarray.
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