Joshua D Bernstock1, Yang-ja Lee2, Luca Peruzzotti-Jametti3, Noel Southall4, Kory R Johnson5, Dragan Maric6, Giulio Volpe3, Jennifer Kouznetsova4, Wei Zheng4, Stefano Pluchino3, John M Hallenbeck7. 1. Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD, USA Department of Clinical Neurosciences, Division of Stem Cell Neurobiology, Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK. 2. Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD, USA. 3. Department of Clinical Neurosciences, Division of Stem Cell Neurobiology, Wellcome Trust-Medical Research Council Stem Cell Institute, University of Cambridge, Cambridge, UK. 4. National Center for Advancing Translational Sciences, National Institutes of Health (NCATS/NIH), Bethesda, MD, USA. 5. Bioinformatics Section, Information Technology & Bioinformatics Program, Division of Intramural Research (DIR), (NINDS/NIH), Bethesda, MD, USA. 6. Flow Cytometry Core Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD, USA. 7. Stroke Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NINDS/NIH), Bethesda, MD, USA HallenbJ@ninds.nih.gov.
Abstract
The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Y human neuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevant miRNA(s) in ischemic pathobiology.
The conjugation/de-conjugation of Small Ubiquitin-like Modifier (SUMO) has been shown to be associated with a diverse set of physiologic/pathologic conditions. The clinical significance and ostensible therapeutic utility offered via the selective control of the global SUMOylation process has become readily apparent in ischemic pathophysiology. Herein, we describe the development of a novel quantitative high-throughput screening (qHTS) system designed to identify small molecules capable of increasing SUMOylation via the regulation/inhibition of members of the microRNA (miRNA)-182 family. This assay employs a SHSY5Yhumanneuroblastoma cell line stably transfected with a dual firefly-Renilla luciferase reporter system for identification of specific inhibitors of either miR-182 or miR-183. In this study, we have identified small molecules capable of inducing increased global conjugation of SUMO in both SHSY5Y cells and rat E18-derived primary cortical neurons. The protective effects of a number of the identified compounds were confirmed via an in vitro ischemic model (oxygen/glucose deprivation). Of note, this assay can be easily repurposed to allow high-throughput analyses of the potential drugability of other relevantmiRNA(s) in ischemic pathobiology.
Stroke is one of the most common causes of death and disability worldwide. Due to an
aging population, the burden will markedly increase in the coming decades and will
be particularly pronounced in developing countries.[1] Of strokes that occur in the
United States, 87% are ischemic, 10% are intracerebral hemorrhagic
strokes, whereas 3% are subarachnoid hemorrhages.[1] Based on this distribution, the
majority of research efforts are directed towards the development of
interventions/therapeutics capable of targeting the variety of pathophysiological
alterations that occur in ischemic stroke.The continuing failure of clinical trials targeting single mechanisms of
neuroprotection in ischemic stroke supports the view of ischemic brain damage as a
highly complex multifactorial process, that appears to involve the interplay of many
non-dominant effectors. In order to confront the enormous biocomplexity of such
network dynamics, it is prudent to focus on plurifunctional targets that affect
multiple mechanisms governing homeostasis in states of both natural and acquired
tolerance to brain ischemia.One such candidate that is capable of meeting the aforementioned criteria is that of
global SUMOylation. SUMOylation is a form of post-translation modification that
operates in states of tolerance and acts to preserve homeostasis under stress via a
myriad of beneficial effects in the ischemic network.[2] Briefly, SUMO, like ubiquitin,
is synthesized as an inactive precursor and is processed by SUMO-specific proteases
to yield its mature form.[3] A single heterodimeric E1 enzyme, SAE1/SAE2, serves to
initiate conjugation by adenylating SUMO leading to the formation of a covalent
thioester E1-SUMO intermediate.[3] SUMO is then transferred to the
catalytic cysteine of the sole E2 conjugase, Ubc9, which alone or in concert with a
target specific E3-ligase catalyses the formation of an isopeptide linkage between
the C-terminal glycine residue of SUMO and the epsilon amino group of the substrate
lysine residue.[3] SUMO conjugation is balanced via the deconjugative actions of
the various SUMO-specific proteases (SENPs).[3,4] There are three systemically
distributed SUMO paralogs in mammals: SUMO-2 and SUMO-3, which are 97%
identical and cannot be distinguished by specific antibodies, and SUMO-1 which
shares only ∼50% homology with the other paralogs and therefore has
distinct immunoreactivity.[3] SUMOylation has been documented to play a role in numerous
processes throughout the cell, including signal transduction, gene expression,
chromatin remodeling, and protein translocation.[3,5]Of particular interest in the context of ischemic pathobiology were the changes
(10–30 fold increases) in global SUMOylation levels that have been reported
to occur during hibernation torpor in 13-lined ground squirrels (Ictidomys
tridecemlineatus)[6] which are one of the most
resistant mammals to brain hypoperfusion.[7] During torpor, these animals
significantly reduce their brain blood flow levels to roughly 10% of their
baseline, yet upon arousal show no evidence of cellular damage and/or functional
deficits despite prolonged exposure to perfusion levels characteristic of the
“ischemic core”.[7,8] Further,
in vitro work conducted in both immortalized cell lines
and primary cortical neuronal cultures exposed to periods of oxygen and glucose
deprivation (OGD) confirmed that increases in global SUMOylation are in fact
cytoprotective.[9] We went on to show that transgenic mice that overexpress
Ubc9 do in fact increase global SUMOylation levels and confer a corresponding level
of resistance to brain ischemia.[10,11] In so doing, we established
that the level of global SUMOylation is directly proportional to the level of
cytoprotection in preclinical models of stroke.[10]Additional work has since focused on elucidating the molecular mechanisms that
control the levels of global SUMOylation. The goal of this effort is to develop
methods capable of boosting global SUMOylation to those levels seen in hibernating
animals and to test whether comparable cytoprotection can be reproduced in stroke
models. To this end, we have recently identified a series of microRNAs serving as
regulators of both global SUMOylation and global post-translational modification by
other ubiquitin-like modifiers (ULMs) including NEDD8, ISG15, UFM1 and FUB1 (all of
which were significantly increased in the brains of hibernating ground squirrels
during torpor).[12] This report was the first to link the natural tolerance to
brain ischemia, witnessed in hibernators, to multimodal regulation by miRNAs.
Analyses established that the miR-200 family (miR-200 a,b,c/miR-141/miR-429)
and the miR-182 family (miR-182/miR-183/miR-96) were consistently depressed in the
brain during the torpor phase as compared to active animals.[12] We showed that
the inhibition of the miR-200 family and/or miR-182 family in SHSY5Y cells increased
global protein conjugation by the abovementioned ULMs, and in so doing made these
cells more resistant to OGD-induced cell death.[12] Collectively, such evidence
suggests that augmentation of global SUMOylation may potentially be harnessed and
exploited for the protection of vulnerable ischemic tissue through the manipulation
of miRNA.Herein we describe the development of a novel qHTS assay designed to uncover small
molecules that increase global SUMOylation via inhibition of the miR-182 family. The
validity of the assay was confirmed by immunoblotting. Of note, a select number of
compounds were capable of inducing protection during OGD in both SYSH5Y cells and
E18 primary cortical neurons thereby confirming the functional utility of this
assay.
Materials and methods
Generation of dual-luciferase miRNA target expression constructs
The pmirGLO (Promega (Madison, WI, USA)) and the psiCHECK-1 (Promega) vectors
were designed to quantitatively evaluate miRNA activity via the insertion of
specific target sites into the 3′ untranslated region (UTR) of the
firefly (pmirGLO vector) or Renilla (psiCHECK-1) luciferase gene mRNA. Starting
from these two vectors, we built a dual reporter construct with the miR-182 (or
miR-183) target sequence (Figure 1 and Supplementary Figure 1), so that the presence of mature
miR-182 or miR-183 would lead to a decrease in luciferase (both firefly and
Renilla) signal, enabling the detection of putative miR-182 (or miR-183) levels.
Post-construction, we examined whether these constructs would work as had been
predicted. We transfected SHSY5Y cells transiently with these constructs along
with either negative control miRNA or miR-182 (or miR-183) mimics (miRIDIAN
micro RNA Negative control or Mimics, Thermo Fisher Scientific (Waltham, MA,
USA)) and measured luciferase activities. As shown in Supplementary Figure 2a,
increased miR-182 (or -183) levels induced via the transfection of mimics
significantly depressed both firefly and Renilla luciferase activity. Next we
contrived SHSY5Y stable transfectants of the engineered constructs. The
established stable transfectants responded well to both miR-182 or miR-183
mimics (i.e. the transfection of these mimics caused the depression of both
firefly and Renilla luciferase acitivities in each cell line (Supplementary
Figure 2b)). Of note, the endogenous levels of both miR-182 and miR-183 are
quite low in SHSY5Y cells and thus the basal levels of luciferase activities are
quite high (Supplementary Figure 2a and b). In order to maintain minimal basal
levels of luciferase activities, we transduced these stable cell lines with
lentiviral particles containing miR-182 (or miR-183) shMIMIC microRNAs (Thermo
Fisher Scientific), and in so doing established cell lines that constitutively
expressed these miRNAs via the selective pressure of puromycin. We then examined
whether these stable transfectants (miR-182 or miR-183 target sequence in
pmirGLO/psiCHECK1 plus lentiviral particles containing miR-182 or miR-183
shMIMIC) were usable for high-throughput screens. The final stable reporter cell
line was designed to identify small compounds that inhibit miR-182 (and/or
miR-183) generation or function, thereby resulting in the activation of the
luciferases (both firefly and Renilla). We used a miR-182 (or miR-183) inhibitor
(miRIDIAN microRNA hairpin inhibitor, Thermo Fisher Scientific) as a positive
control and non-specific miRNA (miRIDIAN microRNA Negative Control, Thermo
Fisher Scientific) as a negative control. As shown in Supplementary Figure 2(c),
the basal level of luciferase activities (both firefly and Renilla) are very low
in comparison to negative controls in Supplementary Figure 2(a) and (b) and the
activation by the miR-182 (or miR-183) inhibitors were substantial. Calculated
Z-factors, which represent a well-established quantitative measure of the
quality of an assay, were 0.61 for miR-182/firefly, 0.5 for miR-182/Renilla,
0.47 for miR-183/firefly, and 0.66 for miR-183/Renilla. Being that a Z-factor
between 0.5 and 1.0 corresponds to an excellent assay, our assay system
qualifies as having sufficient sensitivity for high-throughput screening.
Figure
1.
Generation of dual-luciferase miRNA target
expression constructs and their stable transfectants. (a)
Commercially available original vectors, pmirGLO and psiCHECK-1,
which were designed to quantitatively evaluate miRNA activity via
the insertion of miRNA target sites on the 3′ UTR of the
firefly gene (luc2) (pmirGLO) or 3′ UTR of
the Renilla gene (hRluc) (psiCHECK-1). (b)
Insertion of annealed oligonucleotide pairs, which contain the
miR-182 (or miR-183) target sequence with appropriate restriction
sites (PmeI and XbaI for pmirGLO, SgfI and PmeI for psiCHECK-1)
downstream of luc2 in the pmirGLO and downstream of
hRluc in the psiCHECK-1. These vectors were
digested with KpnI and BamHI and the fragments which contained the
reporter units were isolated/ligated. (c) The final construct
consists of a dual reporter system utilizing both firefly and
Renilla luciferase. (d) (1) Using SHSY5Y cells, stable transfectants
of the engineered reporter constructs were created (specific for
either miR-182 [represented] or miR-183). (2) In order to maintain
minimal basal levels of activity of both luciferases, the stable
host cells were transduced with lentiviral particles containing
miR-182 (or miR-183) shMIMIC microRNAs. (3) These stable
transfectants (miR-182 or miR-183 target sequence in
pmirGLO/psiCHECK1 plus lentiviral particles containing miR-182 or
miR-183 shMIMIC) were usable for high-throughput screens. The final
stable reporter cell line was designed to identify small compounds
(e.g. HDAC inhibitor Panobinostat) that inhibit miR-182 (and/or
miR-183) generation or function, thereby resulting in the activation
of the luciferases (both firefly and Renilla).
Generation of dual-luciferase miRNA target
expression constructs and their stable transfectants. (a)
Commercially available original vectors, pmirGLO and psiCHECK-1,
which were designed to quantitatively evaluate miRNA activity via
the insertion of miRNA target sites on the 3′ UTR of the
firefly gene (luc2) (pmirGLO) or 3′ UTR of
the Renilla gene (hRluc) (psiCHECK-1). (b)
Insertion of annealed oligonucleotide pairs, which contain the
miR-182 (or miR-183) target sequence with appropriate restriction
sites (PmeI and XbaI for pmirGLO, SgfI and PmeI for psiCHECK-1)
downstream of luc2 in the pmirGLO and downstream of
hRluc in the psiCHECK-1. These vectors were
digested with KpnI and BamHI and the fragments which contained the
reporter units were isolated/ligated. (c) The final construct
consists of a dual reporter system utilizing both firefly and
Renilla luciferase. (d) (1) Using SHSY5Y cells, stable transfectants
of the engineered reporter constructs were created (specific for
either miR-182 [represented] or miR-183). (2) In order to maintain
minimal basal levels of activity of both luciferases, the stable
host cells were transduced with lentiviral particles containing
miR-182 (or miR-183) shMIMIC microRNAs. (3) These stable
transfectants (miR-182 or miR-183 target sequence in
pmirGLO/psiCHECK1 plus lentiviral particles containing miR-182 or
miR-183 shMIMIC) were usable for high-throughput screens. The final
stable reporter cell line was designed to identify small compounds
(e.g. HDAC inhibitor Panobinostat) that inhibit miR-182 (and/or
miR-183) generation or function, thereby resulting in the activation
of the luciferases (both firefly and Renilla).
Cell culture and transfection/transduction
The humanneuroblastoma cell line SHSY5Y (ATCC (Manassas, VA, USA)) and its
stable derivatives (stable reporter cell lines) were cultured in DMEM
supplemented with 10% FBS, 100 U/mL penicillin and
100 µg/mL streptomycin (pen/strep) at 37℃ with
5% CO2. Cortical neurons were isolated from E18 embryos of
Sprague-Dawley rats in accordance with the policies set forth by the ACUC
(Animal Care and Use Committee) of NINDS and experiments were performed
according to ACUC, NIH, and ARRIVE guidelines (http://www.nc3rs.org/ARRIVE). Cells were plated on
poly-l-lysine coated plates and cultured in Neurobasal media (Gibco
(Waltham, MA, USA)) supplemented with B27 (Gibco), pen/strep as previously
described[9]; cells were used after seven days in culture.
Transfection of SHSY5Y cells was performed using electroporation with
nucleofector (Amaxa (Basel, Switzerland)) for plasmid constructs and
Lipofectamine 2000 (Invitrogen (Waltham, MA, USA)) for miR mimics or inhibitors
per the manufacturers’ instructions. Transductions of shMIMIC Lentiviral
miRNA particles were performed at low multiplicities of infection (MOI) (i.e.
0.3) according to the manufacturer’s (Thermo Fisher Scientific)
instructions in the media devoid of serum and antibiotics.
Assay for firefly and Renilla luciferase activities
We used ‘Dual-Glo Luciferase Assay System (Promega)’ to measure
luciferase (firefly and Renilla) activities according to the
manufacturer’s instructions. Briefly, after cells were transfected with
the miRNA mimics/inhibitors or treated with small molecules, Dual-Glo Luciferase
Assay reagent was added to each well at a volume equal to that of the culture
(i.e. 80 µl in 96-well plate; 4 µl in 1536-well
plate), incubated for 10 min at room temperature and the luminescence
measured (firefly). Then, the Dual-Glo Stop and Glo reagent was added to the
plate (same volume as the first reagent), incubated for another 10 min
at room temperature, and the luminescence measured (Renilla). Luminescence in
96-well plates was measured using a LB 960 Centro (Berthold Technology (Oak
Ridge, TN, USA)), while luminescence in 1536 plates was measured via the ViewLux
plate reader (PerkinElmer (Waltham, MA, USA)).
qHTS assay and viability
For each cell line tested, a total of 2000 cells per well in 4 µL
of media were dispensed using a Multidrop Combi dispenser (Thermo Fisher
Scientific) and a small cassette into barcoded 1536-well flat-bottom white
(Corning (Corning, NY, USA)) collagen-coated plates. After a 24 h
incubation, library compounds and controls were added to assay plates at a
volume of 23 nL/well via a NX-TR pintool station (Wako Scientific Solutions (San
Diego, CA, USA)), and the plates were incubated further (another 24 h).
Firefly and Renilla luminescence outputs were measured sequentially using the
Dual-Glo Luciferase Assay System (Promega) and the ViewLux plate reader
(PerkinElmer). The assay’s performance was stable throughout the screen.
The activity of each compound was normalized to control wells (DMSO alone),
which were included on each plate. Cells treated with DMSO alone were defined as
having 0% activity. Of note, the following libraries were screened: the
library of pharmacologically active compounds (LOPAC),[13] MIPE[14] and the
NIH Chemical Genomics Center (NCGC) Pharmaceutical Collection
(NPC).[15]
Western blot analysis
Whole cell lysates were prepared and subjected to SDS-PAGE as described
previously.[9] The antibodies used in this study were: anti-SUMO-1
(rabbit polyclonal, in house), ant-SUMO-2,3 (rabbit polyclonal, in house),
anti-Ubc9 (rabbit monoclonal, Abcam (Cambridge, UK)) and anti-β-actin
(mouse monoclonal, Sigma (St. Louis, MO, USA)). Intensities of bands were
analysed using Image-J (NIH (Bethesda, MD, USA)). In order to measure SUMO
conjugation levels, the region corresponding to molecular weights above
100 kDa in each lane was cropped and the total intensity was analysed.
The densities were normalized with corresponding actin levels and expressed as
the ratio to control (DMSO alone).
OGD and the assessment of cell death
OGD for SHSY5Y and rat cortical neurons were performed as described
previously.[6,9] We subjected cells with or without drugs to OGD for
15 h (SHSY5Y cells) or 5 h (cortical neurons) followed by the
restoration of oxygen/glucose (ROG) for 6 h (SHSY5Y) or 16 h
(cortical neurons). The duration of OGD and ROG was determined by our previous
studies.[6,9] Cell death was assessed via nuclear staining with Hoechst
33342 and propidium iodide (PI) followed by fluorescence-activated cell sorting
(FACS) analysis.[6,9] Typically, 1 × 105 cells
were analysed. The percentage of total cell death (both apoptotic and necrotic)
was calculated by taking the difference of viable cell populations between
non-OGD and OGD-subjected, and dividing it by the viable cell population of
non-OGD, with the understanding that some of compounds themselves may have an
effect on cell viability without OGD (i.e. toxicity at time
points > 13 h). The compounds were all dissolved
in DMSO and were subsequently diluted to attain a final DMSO concentration of
0.1% in all experiments, and 0.1% DMSO alone, without drug was
used as our OGD/ROG control. We normalized the calculated cell deaths to the
0.1% DMSO control within each experiment. Cell death was also assessed
by measuring LDH release according to the manufacturer’s directions
(Abcam).
Quantification of neuronal apoptosis/death via microscopic histology
Primary cortical neurons were plated at a density of
3 × 105 on poly-l-lysine-coated
Lab-Tek chamber slides (Nalge Nunc International (Waltham, MA, USA)) for the
assessment of neuronal apoptosis/death. After OGD or OGD/ROG, neurons were
fixed/subsequently stained with terminal deoxy-nucleotide transferase dUTP nick
end labeling (TUNEL) and a rabbitanti-β-tubulin (Covance (Princeton,
NJ, USA) MRB-435 P) antibody, followed by an anti-rabbit Alexa Fluor
647-conjugated secondary antibody. Nuclei were counterstained with
4′,6-diamidino-2-phenylindole (DAPI). Briefly, for TUNEL staining
(APO-BrdU™ TUNEL Assay, Thermo Fisher Scientific), 70%
ethanol-fixed cells were incubated in the provided DNA-labelling solution which
contained TdT and BrdUTP for 1 h at 37℃. After incubating the
cells with the staining solution (Alexa Fluor 488 dye-labeled anti-BrdU
antibody) for 30 min at RT, the PI/RNase A staining buffer was applied
for an additional 30 min. TUNEL+ cells were then
manually counted using microphotographs collected at six random regions of
interest (ROIs). Data are expressed as mean
percentage ± standard error (SE) of
TUNEL+ cells over DAPI.
Analysis of dendritic arborizations and spines
Primary cortical neurons were plated at a density of
1.5 × 105 cells in chamber slides for the
assessment of dendritic arborizations and spine density. After OGD or OGD/ROG,
neurons were fixed/stained using a chickenanti-microtubule-associated protein 2
(MAP2) (Abcam ab5392) and a mouseanti-postsynaptic density protein 95 (PSD95)
(Abcam ab2723) primary antibodies, followed by an anti-chicken Alexa Fluor
488-conjugated and an anti-mouseAlexa Fluor 568-conjugated secondary antibody
respectively. Nuclei were counterstained with DAPI. For the initial assessment
of MAP2 immunoreactivity, immunofluorescence stainings were evaluated using a
CCD camera/fluorescence microscope;
n = 6 equally distributed ROIs were
acquired via a 20x objective lens for analysis. Data are expressed as
MAP2+ area (mm2) ± SE over DAPI.
MAP2+/PSD95+ neurons were then
analysed in more detail using a 63x objective lens for the evaluation of
dendritic arborizations and spines. Criteria for inclusion within the analyses
were the following: (i) the neuron had to be well stained; (ii) the neuron had
to be in full view, (i.e. neither obscured/obstructed by overlapping dendrites
from other neurons); and (iii) the neuron had to contain intact dendritic
arborizations (i.e. not display any obvious signs of degeneration).[16] The first
four neurons from each experimental condition that fit the abovementioned
criteria were reconstructed by following the dendrites through the
z-axis, and the length of each dendritic branch was
determined using Sholl and Branch analysis via StereoInvestigator software
(MicroBrightField (Williston, VT, USA)), as has been previously
described.[17] For statistical analysis, we used a standard software
package (GraphPad Prism version 4.0). Histological data were evaluated by
unpaired two-tailed t-tests (for comparisons between two
groups) and by one-way ANOVA followed by Newman–Keuls tests for post hoc
analysis (for comparison amongst ≥ three groups). To test for
differences in dendritic length (Sholl analysis), a two-way ANOVA, followed by
Tukey’s post hoc test, was performed. Values of
p ≤ 0.05 were deemed to be
significant.
Active compound-gene (protein) interaction and stroke enrichment
enquiry
The Ingenuity Pathway Analysis (IPA) tool was used (www.ingenuity.com). Compounds by
name were entered into IPA and all known gene (protein) interactions supported
by IPA returned. These interactions were summarized in IPA via a network view
and enumerated/compared across compounds via a bar plot using Microsoft Excel.
IPA was also used to identify biological pathways and functions enriched with
proteins having interactions with each compound, by compound. Enrichment results
were summarized both by heat map using R (www.cran.r-project.org) and by bar plot using Microsoft Excel.
Lastly, IPA was queried for all proteins having association with stroke. These
stroke-associated proteins were then intersected with proteins having
interaction with each compound by compound and an enrichment
p-value calculated for the intersection via Chi-square test
with Yates correction using GraphPad Prism.
qHTS data analysis
Plate-based qHTS data were normalized and concentration–effect
relationships derived using in-house developed software.[18] The
activity of each compound was normalized to vehicle control wells (DMSO), which
were included on each plate, and reported as an absolute percentage change in
signal relative to these control wells. EC50 values were obtained by data fit
using a residual error minimization algorithm with automatic outlier
determination to a four-parameter Hill equation as the dose–response
model. Concentration–effect relationships (CERs) were categorized by fit
quality (r2), response magnitude, and degree of measured activity.[18]
Results
Quantitative high-throughput screening (qHTS) via a dual luciferase reporter
assay for the identification of inhibitors of miRNA 182/183
The ultimate goal of this work was to develop a system capable of identifying
molecular entities (MEs)/active pharmaceutical ingredients (APIs) capable of
upregulating global SUMOylation through the inhibition of miRNAs 182 and/or 183.
To minimize interference and increase our confidence in hits ascertained during
screening, we designed constructs that contain two different reporters (dual
reporter system), firefly luciferase and Renilla luciferase (Figure 1), which are not
homologous and therefore have unrelated bioluminescent properties. We confirmed
that the presence of mature miR-182 or miR-183 would lead to a decrease in
luciferase (both firefly and Renilla) signal, enabling the detection of putative
miR-182 (or miR-183) levels (Supplementary Figure 2). We then established cell
lines which stably expressed these constructs as described in Figure 1, and used them
for the screening of small molecule libraries in a 1536 well format. From a
total of 4489 compounds screened, 120 compounds were initially identified in the
course of the primary screening process. These 120 compounds were subsequently
selected and re-screened for validation through the use of confirmatory assays.
From the follow-up screening, 21 active compounds (listed in Table 1) were
confirmed based on their activities in both firefly and Renilla luminescence
assays and were taken forward for further study/characterization. We note that
most confirmed compounds do not give equivalent percentage changes in signal in
both channels, perhaps due to a difference in sensitivity in the detection
methodology for these readouts (Figure 2 and Supplementary Figure 3).
Table
1.
Molecular entities – libraries of
origin and regulatory status.
Molecular entity
Library
Status
1
Romidepsin
NPC
Approved drug
2
Panobinostat
NPC
Clinical testing
3
Entinostat
NPC
Clinical testing
4
Belinostat
NPC
Approved drug
5
Pracinostat
NPC
Approved drug
6
Fosmidomycin
NPC
Clinical testing
7
NCGC00185916
NPC
Preclinical testing
8
Licofelone
NPC
Clinical testing
9
Motesanib
NPC
Clinical testing
10
Orotic acid
NPC
Clinical testing
11
JWH-015
LOPAC
Preclinical testing
12
5-Azacitidine
LOPAC
Approved drug
13
AHPN
NPC
Preclinical testing
14
Lenalidomide
NPC
Approved drug
15
Vatalanib
NPC
Clinical testing
16
VX-702;KVK-702
NPC
Clinical testing
17
Dianiline
NPC
Preclinical testing
18
Diazoxide
NPC
Approved drug
19
Telmisartan
NPC
Approved drug
20
JQ1
NPC
Preclinical testing
21
TW-37
NPC
Preclinical testing
Figure
2.
Dose–response curves. (a) The
non-specific response of Dianiline across five concentrations. (b)
The miRNA-182 specific response of Panobinostat. (c) The miRNA-183
specific response of AHPN.
Molecular entities – libraries of
origin and regulatory status.Dose–response curves. (a) The
non-specific response of Dianiline across five concentrations. (b)
The miRNA-182 specific response of Panobinostat. (c) The miRNA-183
specific response of AHPN.
Active compounds identified during the primary screen induced SUMO
conjugation in SHSY5Y cells and rat E18 primary cortical neurons
To determine the effect of the active compounds identified via the primary screen
on the induction of SUMO conjugation, the 21 compounds were tested in orthogonal
cell-based assays with SHSY5Y cells. The compounds were incubated with SHSY5Y
cells for 13.5 h at both a low and high concentration extrapolated from
the concentration–response curves of the confirmatory assay. As shown in
Figure 3,
immunoblotting effectively demonstrated that the majority of the compounds
identified were indeed capable of upregulating SUMO1 and SUMO-2/3 conjugation,
thereby confirming the biologic validity of the positive hits resulting from the
qHTS assay. Further, it was noted that many of the compounds seemed to increase
the levels of the sole SUMO E2 conjugase Ubc9 as well (Figure 3). To examine whether the
upregulation of global SUMO conjugation by these compounds in SHSY5Y cells
(stable derivatives of which we used for the screening) were cell type specific,
or not, we next examined the effect of the compounds on the SUMOylation levels
of primary cortical neurons isolated from rat embryos. Since the lower dose of
the majority of the compounds had a similar effect when compared to the higher
dose in SHSY5Y cells (Figure
3), we explored the lower/physiologically compatible dose in primary
cortical neurons. As shown in Figure 4, most compounds were capable of increasing the levels of
global SUMO conjugation in primary cortical neurons. Interestingly, the levels
of global SUMOylation induced did vary from compound to compound between the
SHSY5Y cell line and the primary cortical neurons (Figures 3 and 4). To exclude the confounding
contributions of compound cytotoxicity, a cell viability assay was performed in
parallel with the SUMO conjugation assay. We found that the increases in global
SUMOylation were unrelated to a cellular stress response or cell death as
compound cytotoxicity was not observed; critically, cells were treated with the
compounds for an equivalent amount of time (Supplementary Figure 4).
Figure
3.
Treatments with small molecules identified by
qHTS increase the levels of SUMO conjugation and the Ubc9 conjugase
in SHSY5Y parent cells. (a) Representative immunoblots of high
molecular weight (>100 kDa) SUMO-1 and SUMO-2,3
conjugates and the Ubc9 protein in the total cell lysates from
SHSY5Y cells treated with various compounds with indicated
concentrations for 13.5 h. (b) Quantitative analyses of the
conjugates and Ubc9 from three independent experiments. High
molecular weight SUMO-1 or SUMO-2,3 conjugates
(>100 kDa) were cropped in each lane and the total
intensity measured. The densities were normalized to corresponding
actin levels and expressed as the ratio to control (DMSO alone).
Data represent the mean+/−standard deviation of three
independent experiments.
**p < 0.01,
*p < 0.05
compared to DMSO control.
Figure
4.
The effect of small molecules identified by
qHTS on SUMO conjugation and Ubc9 levels in E18 rat cortical
neurons. (a) Representative immunoblots of high molecular weight
(>100 kDa) SUMO-1 and SUMO-2,3 conjugates and the
Ubc9 conjugase in the total cell lysates from rat E18 primary
cortical neurons treated with various compounds with the indicated
concentrations for 13.5 h. (b) Quantitative analyses of the
conjugates and Ubc9 from three independent experiments. Data
represent the mean+/−standard deviation of three independent
experiments.
**p < 0.01,
*p < 0.05
compared to DMSO control.
Treatments with small molecules identified by
qHTS increase the levels of SUMO conjugation and the Ubc9 conjugase
in SHSY5Y parent cells. (a) Representative immunoblots of high
molecular weight (>100 kDa) SUMO-1 and SUMO-2,3
conjugates and the Ubc9 protein in the total cell lysates from
SHSY5Y cells treated with various compounds with indicated
concentrations for 13.5 h. (b) Quantitative analyses of the
conjugates and Ubc9 from three independent experiments. High
molecular weight SUMO-1 or SUMO-2,3 conjugates
(>100 kDa) were cropped in each lane and the total
intensity measured. The densities were normalized to corresponding
actin levels and expressed as the ratio to control (DMSO alone).
Data represent the mean+/−standard deviation of three
independent experiments.
**p < 0.01,
*p < 0.05
compared to DMSO control.The effect of small molecules identified by
qHTS on SUMO conjugation and Ubc9 levels in E18 rat cortical
neurons. (a) Representative immunoblots of high molecular weight
(>100 kDa) SUMO-1 and SUMO-2,3 conjugates and the
Ubc9 conjugase in the total cell lysates from rat E18 primary
cortical neurons treated with various compounds with the indicated
concentrations for 13.5 h. (b) Quantitative analyses of the
conjugates and Ubc9 from three independent experiments. Data
represent the mean+/−standard deviation of three independent
experiments.
**p < 0.01,
*p < 0.05
compared to DMSO control.
qHTS identified active compounds are capable of inducing protection against
oxygen/glucose deprivation (OGD)/restoration of oxygen/glucose (ROG)
The ultimate goal of this qHTS was to characterize a novel method capable of
uncovering small molecules that might be used for the treatment of ischemicstroke. The 21 compounds were consequently tested for their putative efficacy in
protecting SHSY5Y cells from OGD followed by ROG
in vitro. Concentrations were chosen based on the
aforementioned qHTS (Supplementary Table 1). As shown in Figure 5(a), most compounds induced
protection from OGD/ROG-induced cell death in SHSY5Y cells, with Panobinostat (a
histone deacetylase [HDAC] inhibitor) and
6-[3-adamantyl-4-hydroxyphenyl]-2-napthalene carboxylic acid (AHPN), a synthetic
retinoid, being the most effective. We then tested the active compounds that
displayed statistically significant effects in E18 primary cortical neurons. We
found that far fewer compounds displayed protective effects against OGD/ROG in
E18 primary cortical neurons as compared to SHSY5Y cells, but again AHPN was
noted to be effective (Figure
5b). Being that AHPN was found to be the most effective compound in
protecting both SHSY5Y and E18 primary cortical neurons from OGD/ROG-induced
cell death, we decided to further characterize its effects on primary cortical
neurons. As previously reported, OGD/ROG treatment causes both
apoptosis/necrosis and these populations can be distinguished via
FACS.[9] As shown in Figure 5(c), 5 h OGD followed by 16 h ROG caused
∼40% cell death (30% apoptosis/10% necrosis) in
untreated cells (i.e. DMSO alone) whilst increasing concentrations of AHPN
during OGD/ROG provided statistically significant decreases in amounts of cell
death. While both apoptosis and necrosis levels were decreased, AHPN was most
effective in decreasing the number of apoptotic cells. Total cell death after
OGD/ROG was also assessed by LDH release (Figure 5d). In addition, we analysed how
AHPN protects primary cortical neurons after 5 h OGD, or 5 h OGD
followed by 16 h ROG via both TUNEL and MAP2/PSD95 staining. We found
that 1 µM AHPN induced a significant reduction in
TUNEL+ neurons (a marker of cell apoptosis/death) when
compared with both control neurons exposed to OGD and OGD/ROG (Figure 6a). Interestingly,
the lowest dose of AHPN (0.2 µM) also displayed a significant
effect on the survival of OGD/ROG neurons (Figure 6a). Critically, both
in vivo ischemia and
in vitro OGD have been shown to induce alterations
of dendrites (i.e. early degeneration[19] and a compensatory
outgrowth[20]). As such, we decided to examine MAP2 immunoreactivity
in the surviving cortical neurons after OGD and OGD/ROG, being that MAP2 is a
cytoskeletal phosphoprotein that provides scaffolding within dendrites,
particularly near spines.[19] Interestingly, we found
that AHPN was capable of preventing a decrease in MAP2 intensity after OGD and
OGD/ROG in a dose-dependent manner (Figure 6b). We then examined the
dendritic arborization of primary cortical neurons and focused our attention on
PSD 95 positive spines (Figure
6c and d). Sholl analysis performed on the neuronal three-dimensional
(3D) reconstructions confirmed that the total dendritic length was different
among groups with a significant decrease in dendritic arborizations occurring
after exposure to OGD and OGD/ROG as compared to non-hypoxic controls.
Interestingly, AHPN at 1 µM was capable of significantly
inhibiting the decrease in neurons subjected to OGD (Figure 6c) while it had no clear effect
on neurons exposed to both OGD/ROG (Figure 6d).
Figure
5.
The effect of small molecules identified by
qHTS on OGD/ROG-induced cell death in SHSY5Y cells and E18 rat
cortical neurons. After OGD/ROG exposure (OGD/ROG:
16 h/5 h for SHSY5Y, 5 h/16 h for
cortical neurons) in the presence or absence of the small molecules
indicated, cell death/survival was assessed via nuclear staining
with Hoechst 33342 and propidium iodide (PI) followed by FACS
analyses. The percentage of total cell death (both apoptotic and
necrotic) was calculated and recorded vs the percentage of
0.1% DMSO control cell death in each experiment. (a) SHSY5Y
cells. (b) Rat cortical neurons. (c) Increasing concentrations of
AHPN displayed statistically significant increases in viability and
decreases in cell death after OGD/ROG as measured by FACS analysis.
Upper panels: representative dot plots without AHPN (left) and with
1 µM AHPN (right) with numbers in each population
(left, apoptotic cells; upper right, necrotic cells; lower right,
viable cells); lower panels: Quantitative analyses of cell survival
(left) and cell death (right). (d) Increasing concentrations of AHPN
displayed statistically significant decreases in cell death as
measured by LDH release. Data represent the
means ± standard deviation of three
independent experiments.
**p < 0.01,
*p < 0.05
compared with OGD/ROG without AHPN by student's
t-test.
Figure
6.
AHPN reduces ischemic neuronal apoptosis and
preserves dendritic/synaptic integrity
in vitro. (a) Representative images of
TUNEL+ (in green) and
β-tubulin+ (in red) neurons and
quantitative analysis. Nuclei are counterstained with DAPI (blue).
Scale bars: 100 µm. Data are
means ± standard error.
*p ≤ 0.05,
compared with OGD and OGD/ROG controls, respectively.
+++p ≤ 0.001,
++p ≤ 0.01,
compared with non-hypoxic CTRL neurons;
**p ≤ 0.01,
*p ≤ 0.05,
compared with OGD or OGD/ROG controls. (b) Representative
microphotographs of primary cortical neurons dendrites stained for
MAP2 (green) and corresponding quantification. Nuclei are
counterstained with DAPI (blue). Scale bars: 100 µm.
Note the dose-dependent increase of MAP2 expression induced by AHPN
in both OGD and OGD/ROG treated neurons.
++p ≤ 0.01
compared with non-hypoxic CTRL neurons;
*p ≤ 0.05, compared
with OGD or OGD/ROG controls. (c,d) Representative reconstructions
and microphotographs of OGD (c) and OGD/ROG (d) primary cortical
neurons treated with AHPN. Dendrites are stained with MAP2 (green),
while spines are stained with PSD95 (red). Nuclei are counterstained
with DAPI (blue). Scale bars: 10 µm. Sholl analysis
of dendritic length with nested concentric spheres centred at the
cell soma and with a gradually increasing radius
(5 µm) showing cumulative dendritic length in the
function of cell soma distance, the integrated total dendritic
length, and the spine density of primary cortical neurons.
+p ≤ 0.05,
compared with non-hypoxic CTRL neurons,
**p ≤ 0.01,
*p ≤ 0.05,
compared with OGD or OGD/ROG controls.
The effect of small molecules identified by
qHTS on OGD/ROG-induced cell death in SHSY5Y cells and E18 rat
cortical neurons. After OGD/ROG exposure (OGD/ROG:
16 h/5 h for SHSY5Y, 5 h/16 h for
cortical neurons) in the presence or absence of the small molecules
indicated, cell death/survival was assessed via nuclear staining
with Hoechst 33342 and propidium iodide (PI) followed by FACS
analyses. The percentage of total cell death (both apoptotic and
necrotic) was calculated and recorded vs the percentage of
0.1% DMSO control cell death in each experiment. (a) SHSY5Y
cells. (b) Rat cortical neurons. (c) Increasing concentrations of
AHPN displayed statistically significant increases in viability and
decreases in cell death after OGD/ROG as measured by FACS analysis.
Upper panels: representative dot plots without AHPN (left) and with
1 µM AHPN (right) with numbers in each population
(left, apoptotic cells; upper right, necrotic cells; lower right,
viable cells); lower panels: Quantitative analyses of cell survival
(left) and cell death (right). (d) Increasing concentrations of AHPN
displayed statistically significant decreases in cell death as
measured by LDH release. Data represent the
means ± standard deviation of three
independent experiments.
**p < 0.01,
*p < 0.05
compared with OGD/ROG without AHPN by student's
t-test.AHPN reduces ischemic neuronal apoptosis and
preserves dendritic/synaptic integrity
in vitro. (a) Representative images of
TUNEL+ (in green) and
β-tubulin+ (in red) neurons and
quantitative analysis. Nuclei are counterstained with DAPI (blue).
Scale bars: 100 µm. Data are
means ± standard error.
*p ≤ 0.05,
compared with OGD and OGD/ROG controls, respectively.
+++p ≤ 0.001,
++p ≤ 0.01,
compared with non-hypoxic CTRL neurons;
**p ≤ 0.01,
*p ≤ 0.05,
compared with OGD or OGD/ROG controls. (b) Representative
microphotographs of primary cortical neurons dendrites stained for
MAP2 (green) and corresponding quantification. Nuclei are
counterstained with DAPI (blue). Scale bars: 100 µm.
Note the dose-dependent increase of MAP2 expression induced by AHPN
in both OGD and OGD/ROG treated neurons.
++p ≤ 0.01
compared with non-hypoxic CTRL neurons;
*p ≤ 0.05, compared
with OGD or OGD/ROG controls. (c,d) Representative reconstructions
and microphotographs of OGD (c) and OGD/ROG (d) primary cortical
neurons treated with AHPN. Dendrites are stained with MAP2 (green),
while spines are stained with PSD95 (red). Nuclei are counterstained
with DAPI (blue). Scale bars: 10 µm. Sholl analysis
of dendritic length with nested concentric spheres centred at the
cell soma and with a gradually increasing radius
(5 µm) showing cumulative dendritic length in the
function of cell soma distance, the integrated total dendritic
length, and the spine density of primary cortical neurons.
+p ≤ 0.05,
compared with non-hypoxic CTRL neurons,
**p ≤ 0.01,
*p ≤ 0.05,
compared with OGD or OGD/ROG controls.
Gene/protein expression and biological pathways perturbed by active
compounds
To explore the potential mechanisms of the active compounds, the Ingenuity
Pathway Analysis (IPA) knowledgebase was used to query all gene (protein)
interactions contained therein having association with the compounds listed in
Figure 7.
Summarization and exploration of these interactions via a network diagram
revealed that certain compounds have a greater number of interactions than
others; suggesting the perturbation potential at the molecular level for these
compounds may too be greater. To enumerate and compare the difference in number
of interactions across compounds, a bar plot was constructed. By this plot, AHPN
has the greatest number of interactions compared to licofelone, a dual COX/LOX
inhibitor, which has the fewest. To further elucidate a compound’s
perturbation potential at the molecular level, IPA was used again to identify
those biological pathways and functions supported in IPA that are significantly
enriched (Fisher's exact test p < 0.05)
for the genes (proteins) associated with each compound. To enumerate and compare
the difference in number of significantly enriched biological pathways and
functions across compounds, bar plots were constructed. From these plots,
compounds having the greatest number of significantly enriched biological
pathways (e.g. AHPN, romidepsin, and entinostat) and functions (e.g. romidepsin,
entinostat, and telmisartan) could be readily identified and argued to have the
greatest perturbation potential at the biological pathway and function levels.
Of particular interest is Supplementary Table 2, which describes the number of
associated genes (proteins) per compound in IPA, the number of genes (proteins)
associated with stroke in IPA, and whether the intersection via Chi-square test
is significant (Yates corrected
p < 0.05) or not. Per the results,
64% of the active compounds (9/14) were found to be significantly
enriched for genes (proteins) associated with stroke.
Figure
7.
Off-target enquiry. The Ingenuity Pathway
Analysis tool (IPA) was used to query all gene (protein)
interactions by compound (www.ingenuity.com).
These interactions were summarized in two ways. First, a network was
constructed across compounds to demonstrate that no exclusive gene
(protein) interactions exist (upper left plot). Second, a bar plot
was constructed to describe that the number of gene (protein)
interactions by compound is unbalanced (lower left plot). To gauge
and compare compound impact on biological pathways and functions,
IPA was used to report enrichment p-values
(Fisher’s exact test) for 562 pathways (upper right plot)
and 3455 functions (lower right plot).
Off-target enquiry. The Ingenuity Pathway
Analysis tool (IPA) was used to query all gene (protein)
interactions by compound (www.ingenuity.com).
These interactions were summarized in two ways. First, a network was
constructed across compounds to demonstrate that no exclusive gene
(protein) interactions exist (upper left plot). Second, a bar plot
was constructed to describe that the number of gene (protein)
interactions by compound is unbalanced (lower left plot). To gauge
and compare compound impact on biological pathways and functions,
IPA was used to report enrichment p-values
(Fisher’s exact test) for 562 pathways (upper right plot)
and 3455 functions (lower right plot).
Discussion
Therapeutic options for ischemic brain injury are limited. As such, the research
presented herein seeks to highlight the development of a novel cell-based qHTS
system designed to streamline the clinical development and translation of previously
approved drugs that may ultimately be repurposed for the treatment of ischemicstroke. In an effort to elucidate targets capable of providing the plurifunctional
cytoprotection needed to overcome the inherent complexities of stroke pathobiology,
mechanisms of tolerance were examined in the hibernating 13-lined ground squirrel.
I. tridecemlineatus has an extraordinary capacity to withstand
prolonged and profound reductions of blood flow and oxygen delivery to brain without
incurring any cellular damage.[7] One of the underlying molecular
means allowing this multifactorial cytoprotection to unfold is that of global
SUMOylation.[6,9]
The identification of miRNAs 182 and 183 (reported functions reviewed by Lee
et al.[12]) as an endogenous mechanism, which in part controls global
SUMOylation, pushed us to identify small molecules capable of regulating this form
of post-translational modification via miRNA as novel targets for development of
stroke therapies.[12]MicroRNAs are key players within gene regulatory networks and modulate multimodal
gene expression by binding to complementary sequences in target mRNAs, and as such
are critically positioned to influence network dynamics/outcomes. One miRNA usually
targets more than one hundred genes[21] with interactome hubs and
downstream signaling components (e.g. transcription factors) typically regulated by
more miRNAs than other nodes within a given network.[22,23] Of note, miRNA binding may
suspend and/or permanently repress the translation of a given mRNA
transcript,[24,25] thereby altering post-transcriptional gene profiles.Drugs that directly modulate a single molecular target have come to be understood as
insufficient for the cytoprotective treatment of ischemic stroke, unless such a
target is itself critically positioned to influence a network.[22] If one seeks
to combat the pathobiology underlying complex and/or polygenic disease processes,
the design of a new generation of efficacious drugs must be developed to modulate
diseased cellular networks.[22,26,27] Accordingly, the rationale for polypharmacology (i.e. the
promiscuous modulation of several molecular targets simultaneously)[26] has
progressively garnered support in both academia and industry. Understanding the
plurifunctional underpinnings of miRNA and its relationship to global SUMOylation,
we sought to develop a screening system capable of identifying MEs capable of
influencing post-ischemic clinical outcomes.Acknowledging that luciferase-dependent assay interference in qHTS cannot be entirely
eliminated, it is nonetheless possible to significantly reduce the probability of
its occurrence through the rational engineering of one’s reporter system and
via the selection of appropriate orthogonal assays to confirm compound activity.
Both of the aforementioned represent the best means of identifying artifactual
activity early in drug discovery processes.[28] Further, many of the compounds
within screening libraries directly perturb the activity of luciferase reporters,
thus skewing data interpretation and complicating candidate selection.[28-31] In order to facilitate the
construction of a functional cell-based qHTS assay capable of accurately identifying
inhibitors of our miRNAs of interest, we constructed stable dual firefly-Renilla
luciferase reporter lines, thereby reducing the number of downstream manipulations
and enhancing concurrently the overall reproducibility of the assay.To minimize interference and increase our confidence in hits during screening, we
designed a construct that contains two different reporters. Of note, firefly
luciferase and Renilla luciferase are not homologous and therefore have unrelated
bioluminescent properties; firefly luciferase uses d-luciferin as
its substrate, while Renilla luciferase makes use of coelenterazine as its
substrate.[32] Our assay rules out false-positives due to compound toxicity,
which can occur in an assay based on a decrease in reporter signal. Moreover, since
compounds identified using this proprietary screening approach may still have
off-target effects, they need to be validated using orthogonal assays following the
primary assay to differentiate between compounds that generate false positives verse
those compounds that are specifically active against the target. As such, we
confirmed our screening with a series of western blots and in so doing demonstrated
the overall reliability of our assay.The final strength of this novel dual reporter assay system is its downstream utility
in exploring the drugability of other miRNAs of clinical interest in a qHTS manner
(i.e. via the insertion of the appropriate target sequences into the
pmirGLO/psiCHECK1 firefly and Renilla 3′ UTRs) expanding upon the elegant
technique originally put forth by Connelly et al.[33]Of the 21 compounds that definitively emerged from the screen and the following
orthogonal assay, we noted that five were HDAC inhibitors: romidepsin, panobinostat,
entinostat, belinostat, and pracinostat. HDAC inhibitors are a class of drugs that
increase the acetylation of histone and non-histone proteins to activate
transcription, enhance gene expression, and modify the function of target
proteins.[34] HDAC inhibitors have been shown in a myriad of basic and
preclinical studies to provide vigorous protection against excitotoxicity, oxidative
and endoplasmic reticulum stress, apoptosis, inflammation, and blood brain barrier
breakdown, all of which are core components of the pathobiology caused by an acute
ischemic brain insult (reviewed in Fessler et al.[34]). Beyond the suppression of
post-stroke injury, HDAC inhibitors have been shown capable of augmenting recovery
through the promotion of angiogenesis, neurogenesis, and stem cell migration,
thereby dramatically increasing both functional and behavioral recovery after
experimental cerebral ischemia.[34] Intriguingly, work has emerged
to link HDAC inhibitors to the regulation of miRNA in ischemia[35] and cancer
models.[36,37] Of particular interest, Blakeslee et al. have provided
a direct link between HDAC inhibition and SUMOylation in both cardiomyocytes and
fibroblasts that may help explain the beneficial effects of HDAC inhibitors in
preclinical models of heart failure.[38] Of note, the protective
influences of the HDAC inhibitors have a foil in the class’ baseline
toxicity, and it has therefore proven difficult to optimize the concentrations that
may ultimately achieve maximal protection from OGD/ROG.[39] Strategies including pulsed
treatment may be employed to mitigate such toxicity moving forward.[40]The compound that had the most pronounced effect in both cell lines (SHSY5Y and
cortical neurons) was AHPN. Disruption of retinoid signaling has been linked to the
pathological hallmarks of a number of neuroinflammatory/neurodegenerative diseases
that share components of ischemic pathobiology.[41,42] As such, both endogenous and
synthetic retinoids (AHPN) have been examined for their ability to modulate
inflammation via interactions with both macrophages and microglia.[41,43,44] Previous
reports have documented AHPN’s ability to act as a chemotherapeutic via an
inhibition of cellular proliferation and/or induction of apoptotic cell
death.[45,46] Despite this, the work by Farso et al. has effectively
demonstrated AHPN’s ability, at low concentrations, to attenuate microglial
activation-associated responses without triggering cell death.[41] Such work
highlights the critical nature of AHPN dose to related biological outcomes and
suggests that more work will be needed to fully elucidate this molecule’s
protective capacity. It is again prudent to note that a number of the other
compounds which proved capable of providing protection against the injurious effects
of OGD/ROG in the primary cortical neurons have been linked previously with
neuroprotection after ischemia; accordingly, orotic acid, diazoxide and telmisartan
have all been shown capable of modulating relevant components of ischemic
pathobiology.[47-49]Of interest, the response of both cell types (SHSY5Y and cortical neurons) to the
drugs differed and the level of protection induced did not directly correlate with
the level of global SUMOylation, as may have been expected. We therefore propose
that the SUMOylation of specific target sets may be a critical component of the
protection afforded against ischemia in addition to global SUMOylation levels as
evidenced by the recent work of Yang et al.[50] Such differences may
ultimately be exploited to further elucidate the dynamics controlling both global
SUMOylation and its influence on neuroprotection during OGD/ROG.Understanding both the burden of disease caused by ischemic stroke and our concurrent
lack of cell protective therapeutic options, we sought to engineer and optimize a
novel mechanism to identify molecules capable of inducing global SUMOylation via the
inhibition of miRNA. Such work has considerable potential, and it is our hope that
it will lead to advanced therapies that may be used to significantly reduce
morbidity/mortality following ischemic brain injury, thereby improving quality of
life for both patients and their families.Future work will seek to optimize doses (of single drugs and combinations) both
in vitro and ultimately
in vivo to further explore the potential clinical
translation of our findings.
Authors: Juan Wang; Tao Pang; Roman Hafko; Julius Benicky; Enrique Sanchez-Lemus; Juan M Saavedra Journal: Neuropharmacology Date: 2013-12-04 Impact factor: 5.250
Authors: Joshua D Bernstock; Daniel Ye; Jayden A Smith; Yang-Ja Lee; Florian A Gessler; Adam Yasgar; Jennifer Kouznetsova; Ajit Jadhav; Zhuoran Wang; Stefano Pluchino; Wei Zheng; Anton Simeonov; John M Hallenbeck; Wei Yang Journal: FASEB J Date: 2018-01-03 Impact factor: 5.191
Authors: Joshua D Bernstock; Daniel G Ye; Allison Griffin; Yang-Ja Lee; John Lynch; Lawrence L Latour; Gregory K Friedman; Dragan Maric; John M Hallenbeck Journal: Front Neurol Date: 2018-01-12 Impact factor: 4.003