Integrated assessment of viral transcription, antigen presentation, and CD8+ T cell function reveal multiple limitations of class I selective HDACi during HIV-1 latency reversal

Abstract

Antiretroviral (ARV) drug regimens suppress HIV-1 replication but are unable to cure infection. This leaves people living with HIV-1 burdened by a lifelong commitment to expensive daily medication. Furthermore, it has become clear that ARV therapy does not fully restore health, leaving individuals at elevated risk for cardiovascular disease, certain types of cancers, and neurocognitive disorders, as well as leaving them exposed to stigma. Efforts are therefore under way to develop therapies capable of curing infection. A key focus of these efforts has been on a class of drugs called histone deacetylase inhibitors (HDACi), which have the potential of exposing hidden reservoirs of HIV-1 to elimination by the immune system. Unfortunately, clinical trial results with HDACi have thus far been disappointing. In the current study, we integrate a number of experimental approaches to build a model that provides insights into the limited activity of HDACi in clinical trials and offers direction for future approaches.

Full text

Integrated Assessment of Viral Transcription, Antigen
Presentation, and CD8
ⴙ
T Cell Function Reveals Multiple
Limitations of Class I-Selective Histone Deacetylase Inhibitors
during HIV-1 Latency Reversal
Talia M. Mota,
a
Chase D. McCann,
a,b
Ali Danesh,
a
Szu-Han Huang,
a
Dean B. Magat,
a
Yanqin Ren,
a
Louise Leyre,
b
Tracy D. Bui,
a
Thomas M. Rohwetter,
c
Colin M. Kovacs,
d
Erika Benko,
d
Lynsay MacLaren,
e
Avery Wimpelberg,
e
Christopher M. Cannon,
e
W. David Hardy,
f
Jeffrey T. Safrit,
g
R. Brad Jones
a,b,c
a
Infectious Diseases Division, Department of Medicine, Weill Cornell Medical College, New York, New York, USA
b
Program in Immunology and Microbial Pathogenesis, Weill Cornell Graduate School of Medical Sciences, New York, New York, USA
c
Department of Microbiology, Immunology, & Tropical Medicine, The George Washington University, Washington, DC, USA
d
Maple Leaf Clinic, Toronto, Ontario, Canada
e
Research Department, Whitman-Walker Health, Washington, DC, USA
f
Division of Infectious Disease, Johns Hopkins University School of Medicine, Washington, DC, USA
g
NantBioScience Inc./NantKwest LLC, Culver City, California, USA
ABSTRACT Clinical trials investigating histone deacetylase inhibitors (HDACi) to re-
verse HIV-1 latency aim to expose reservoirs in antiretroviral (ARV)-treated individu-
als to clearance by immune effectors, yet have not driven measurable reductions in
the frequencies of infected cells. We therefore investigated the effects of the class
I-selective HDACi nanatinostat and romidepsin on various blocks to latency reversal
and elimination, including viral splicing, antigen presentation, and CD8
⫹
T cell func-
tion. In ex vivo CD4
⫹
T cells from ARV-suppressed individuals, both HDACi signifi-
cantly induced viral transcription, but not splicing nor supernatant HIV-1 RNA. In an
HIV-1 latency model using autologous CD8
⫹
T cell clones as biosensors of antigen
presentation, neither HDACi-treated CD4
⫹
T cell condition induced clone degranula-
tion. Both HDACi also impaired the function of primary CD8
⫹
T cells in viral inhibi-
tion assays, with nanatinostat causing less impairment. These findings suggest that
spliced or cell-free HIV-1 RNAs are more indicative of antigen expression than un-
spliced HIV-RNAs and may help to explain the limited abilities of HDACi to generate
CD8
⫹
T cell targets in vivo.
IMPORTANCE Antiretroviral (ARV) drug regimens suppress HIV-1 replication but are
unable to cure infection. This leaves people living with HIV-1 burdened by a lifelong
commitment to expensive daily medication. Furthermore, it has become clear that
ARV therapy does not fully restore health, leaving individuals at elevated risk for car-
diovascular disease, certain types of cancers, and neurocognitive disorders, as well as
leaving them exposed to stigma. Efforts are therefore under way to develop thera-
pies capable of curing infection. A key focus of these efforts has been on a class of
drugs called histone deacetylase inhibitors (HDACi), which have the potential of ex-
posing hidden reservoirs of HIV-1 to elimination by the immune system. Unfortu-
nately, clinical trial results with HDACi have thus far been disappointing. In the cur-
rent study, we integrate a number of experimental approaches to build a model
that provides insights into the limited activity of HDACi in clinical trials and offers di-
rection for future approaches.
KEYWORDS CTL, HDACi, HIV, RNA splicing, epigenetics, latency, reservoir
Citation Mota TM, McCann CD, Danesh A,
Huang S-H, Magat DB, Ren Y, Leyre L, Bui TD,
Rohwetter TM, Kovacs CM, Benko E, MacLaren
L, Wimpelberg A, Cannon CM, Hardy WD, Safrit
JT, Jones RB. 2020. Integrated assessment of
viral transcription, antigen presentation, and
CD8
+
T cell function reveals multiple
limitations of class I-selective histone
deacetylase inhibitors during HIV-1 latency
reversal. J Virol 94:e01845-19. https://doi.org/10
.1128/JVI.01845-19.
Editor Guido Silvestri, Emory University
Copyright © 2020 American Society for
Microbiology. All Rights Reserved.
Address correspondence to R. Brad Jones,
rbjones@med.cornell.edu.
Received 28 October 2019
Accepted 4 February 2020
Accepted manuscript posted online 12
February 2020
Published
VIRUS-CELL INTERACTIONS
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Although antiretroviral therapy (ART) can reduce HIV-1 viral loads to undetectable
levels, there remains no scalable cure for infection. A critical obstacle to overcome
is the persistence of CD4
⫹
T cells containing proviral genomes (1, 2), which are
maintained at different depths of viral latency (3, 4). Efforts to purge this persistent viral
reservoir have been the focus of over a decade of investigation, with substantial efforts
focused on reversing viral latency (5).
The original hypothesis of the “kick and kill” approach to reducing HIV-1 reservoirs was
that small-molecule epigenetic modifiers, i.e., histone deacetylase inhibitors (HDACi), could
be used to induce viral protein expression in latently infected cells, exposing them to
elimination by immune effectors, such as CD8
⫹
cytotoxic T lymphocytes (CTLs). HDACi
orchestrate latency reversal through various mechanisms, primarily through enabling the
acetylation of histones at the promoter region of the viral genome, the 5=long terminal
repeat (LTR) (6, 7). HDACi facilitate changes in the chromatin architecture that enable the
recruitment of host transcription factors to the LTR to promote viral transcription (8–10).
Clinical trials investigating HDACi have demonstrated increases in viral transcription,
while failing to measurably impact the size of the reservoir in peripheral blood (11–17).
To achieve successful latency reversal, many inherent host-conserved blocks that
maintain HIV-1 latency must be reversed, including HDAC suppression of viral tran-
scription (18–23), negative elongation factors that prevent viral RNA elongation (24–
26), and a lack of active HIV-1 regulatory proteins that orchestrate splicing (27–29) and
nuclear export (30, 31) of viral RNAs. HDACi alter the splicing of many host genes and
modify aberrantly spliced transcripts to restore full-length mRNA in inherited disorders
where the defect is an unsolicited splicing event (32–38). Of particular interest, the
removal of HDAC1 at host promoters by short interfering RNA (siRNA) or HDACi is
implicated in inhibiting splicing (32). HDAC1 is associated with the HIV-1 LTR and
removed during HDAC inhibition during latency reversal (6, 8, 9). In this context, with
the provirus considered a gene unit, the full-length unspliced (US) viral genome may be
favorably reactivated from latency using HDACi. This was demonstrated ex vivo (3) and
in vivo, with the potent HDACi romidepsin (RMD) reported to increase US HIV-1 RNA
(16) but failed to increase multiply spliced (MS) HIV-1 RNA (39). Without the accumu-
lation of MS HIV-1 RNAs, which express viral regulatory proteins that drive robust viral
expression, it is not clear that viral genomes would be sufficiently induced to achieve
antigen presentation and thus recognition by CD8
⫹
T cells (40).
While latency reversing agents (LRAs) must potently reactivate proviral genomes,
any adverse effects on CD8
⫹
T cell function must also be considered. HDACi, particu-
larly romidepsin and panobinostat, have been shown to impair multiple functions
of HIV-1- and human T cell leukemia virus type 1 (HTLV-1)-specific CD8
⫹
T cell
responses in vitro, including proliferative capacity and ability to kill HIV-infected CD4
⫹
T cells (41–45). Corresponding effects on CD8
⫹
T cell function in clinical trials with
individuals living with HIV-1 have been mixed. In vivo administration of the HDACi
panobinostat transiently increased the activation of CD8
⫹
T cells (46) and modestly
increased the magnitude and breadth of cytokine-secreting HIV-1-specific CD8
⫹
T cells,
although without influencing the size of the reservoir (47). In contrast, evidence of
transient in vivo suppression of CD8
⫹
T cell responses was observed with romidepsin
(B. Mothe, data presented at the Conference on Retroviruses and Opportunistic Infec-
tions 2017, Seattle, Washington; reviewed in reference 48). Researchers investigating
inflammatory or autoimmune disorders have harnessed this immunosuppressive activ-
ity of HDACi by utilizing pan-HDACi, which enable the acetylation of HDAC6 to impair
CD8
⫹
T cell function, including cytotoxicity (49–53). Additionally, HDAC1, which is
targeted by all HDACi investigated in HIV-1 clinical trials to date, has been implicated
in maintaining the homeostasis of CD8
⫹
T cells and is required to induce the expansion
of and stimulate CD8
⫹
T cells against viral infection (54, 55). The functional importance
of HDAC1 and HDAC6 in their deacetylated states within CD8
⫹
T cells has potential
implications for the suitability of pan-HDACi as systemically delivered LRAs, which
might be mitigated through the use of more-selective HDACi.
Here, we employ a class I-selective HDACi, nanatinostat (VRx-3996; CHR-3996) (56),
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as a potential LRA. Nanatinostat has previously been demonstrated to increase histone
H3 acetylation within peripheral blood mononuclear cells (PBMCs) in vivo (57). Nana-
tinostat is currently being investigated in a phase 1b/2 clinical trial to treat Epstein-Barr
virus-positive lymphoma (VT3996-201, ClinicalTrials.gov) and has previously been eval-
uated in patients with advanced solid tumors (NCT00697879, ClinicalTrials.gov)(57). We
compare nanatinostat to a very well investigated class I-selective HDACi in the HIV-1
field, romidepsin (10, 16, 17, 39, 41), hypothesizing that both HDACi would achieve
similar increases in US HIV-1 RNA but that they may prevent splicing of viral RNAs. We
further postulated that this would affect the ability of HDACi-treated CD4
⫹
T cells
latently infected with HIV-1 to present antigen and thus to be recognized by CD8
⫹
T
cells, and that both HDACi would directly impact CD8
⫹
T cell function. To investigate
these hypotheses, we utilized primary CD4
⫹
T cells from individuals living with HIV-1
suppressed by ART (for at least 3 years) (Table 1) to compare the potencies of both
HDACi to induce viral transcription and splicing. Parallel experiments were performed
using a primary cell latency model, with CD4
⫹
T cells from an infected individual and
autologous HIV-1-specific CD8
⫹
T cell clones as “biosensors,” to investigate whether
HDACi-mediated latency reversal was sufficient to induce antigen presentation and
recognition. We further directly measured any impairment of HDACi on primary bulk
CD8
⫹
T cell antiviral function through viral inhibition assays.
RESULTS
Nanatinostat reactivates latent HIV-1 in J-LAT 10.6 cells. As the first investigation
of nanatinostat’s potential LRA activity, we performed a dose-response experiment on
the J-LAT 10.6 cell line, which is a Jurkat cell line that contains a copy of a full-length
HIV-1 genome with a frameshift mutation in env and which expresses green fluorescent
protein (GFP) in place of the nef gene (58). Based on a study demonstrating 50% lethal
concentration (LC
50
) values of up to 100 nM nanatinostat in multiple cell lines (59), we
opted to test a 2-fold serial dilution of nanatinostat, ranging from 1,000 nM to 62.5 nM.
We observed a dose-dependent response in latency reversal, which was significant
compared to what occurred with the vehicle carrier dimethyl sulfoxide (DMSO; 0.001%
DMSO matched by concentration with 1,000 nM nanatinostat) even at the lowest
concentration tested (62.5 nM) (Fig. 1A). Phorbol 12-myristate 13-acetate plus ionomy-
cin (PMA/I) was included as a positive control and potently increased GFP expression in
this cell line (Fig. 1A). One hundred nanomolar nanatinostat was chosen as the
concentration to use in the remainder of this study based on (i) this titration, (ii) viability
data from primary CD4
⫹
T cells (Fig. 1C to E), and (iii) the fact that 100 nM is a clinically
relevant dose, as previously described (57).
We then tested the full panel of LRAs to be used in our ex vivo reactivation studies
with this cell line. J-LAT 10.6 cells were treated with nanatinostat (100 nM), romidepsin
TABLE 1 Participant characteristics
a
Donors used in Fig. 1 and 2 have unique symbol identifiers next to them.
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(a 40 nM dose was selected given its success in HIV-1 in vitro and ex vivo studies [10]),
and bryostatin (10 nM), using 0.001% DMSO as the negative control and PMA/I (10 nM-
500 nM) as the positive control. At 24 h posttreatment, each LRA had induced statisti-
cally significant increases in the percentages of cells expressing GFP, which is indicative
of HIV-1 expression (Fig. 1B). Of the test LRAs, romidepsin induced the greatest increase
in the frequencies of cells expressing GFP (mean ⫾standard deviation [SD], 57 ⫾
0.4%; P⬍0.0001), followed by nanatinostat (38 ⫾0.6%; P⫽0.0001) and bryostatin
(38 ⫾0.7%; P⬍0.0001). As expected, the most potent reactivation was observed with
the positive control of PMA/I (87 ⫾0.1%; P⬍0.0001).
Effects of nanatinostat on the viability and activation of primary CD4
ⴙ
T cells.
As a precursor to performing ex vivo latency reversal studies, we tested nanatinostat in
two toxicity assays. Based on a study demonstrating LC
50
values of up to 100 nM
nanatinostat in multiple cell lines (59), we opted to test a 2-fold serial dilution of
nanatinostat, ranging from 1,000 nM to 62.5 nM. To measure the effects of nanatinostat
FIG 1 Nanatinostat reverses HIV-1 latency in J-Lat 10.6 cells at concentrations that are minimally toxic to primary ex vivo CD4
⫹
T cells. (A
and B) HIV-1 latency reversal was assessed at 24 h by measuring GFP expression in L-Lat 10.6 cells following a titration of nanatinostat
(N-stat) (A) or the panel of LRAs used in this study (B), with DMSO as the negative control and PMA/I as the positive control. Bryo,
bryostatin. Each dot in panels A and B represents a mean of results from technical replicates, columns represent means, and error bars
represent standard deviations. (C and D) Primary CD4
⫹
T cells from uninfected donors treated with a titration of nanatinostat (C) or from
infected donors treated with the entire LRA panel used in this study plus ARVs (D), were tested for metabolic activity at 72 h using the
MTS assay. (E to G) Primary CD4
⫹
T cells from ARV-treated individuals living with HIV were cultured in the presence of LRAs, including
IL-2 and ARVs, and flow cytometry was used to measure live cells (E), MHC class I expression (F), and CD69 expression (G). FC, fold change;
MFI, mean fluorescent intensity. (H) Representative example from panel G of the changes in CD69 expression, with the percentage of cells
expressing CD69 noted. Paired ttests were used for ⬍6 experiments (A, B, D), and the nonparametric Wilcoxon matched-pair signed-rank
test was used for sample sizes of at least 6 (C, E to G). *,P⬍0.05; **,P⬍0.01; ***,P⬍0.001; ****,P⬍0.0001.
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on primary cell viability, CD4
⫹
T cells isolated from HIV-negative donor PBMCs were
treated with the 2-fold titration of nanatinostat (Fig. 1C)(
n⫽6). The drug was washed
out at 24 h, and the 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-
sulfophenyl)-2H-tetrazolium (MTS) assay was performed at 72 h. This assay can indicate
drugs that are cytotoxic or that induce proliferation as measured by the level of the
MTS tetrazolium compound reduced by metabolically active cells, generating a soluble
formazan dye (60). MTS readouts were normalized to those of DMSO. Each concentra-
tion of nanatinostat was observed to significantly alter the metabolic activity of the
primary CD4
⫹
T cells (Fig. 1C). The observed reductions in metabolic activity were
modest, however, with a ⬍20% reduction observed at the lowest concentrations; the
median changes (interquartile ranges [IQRs]) were a 17% (13 to 22%) reduction at
125 nM and a 12% (7 to 17%) reduction at 62.5 nM (P⫽0.03 for both comparisons). The
positive-control, PMA/I, significantly induced the proliferation of CD4
⫹
T cells (with a
median increase in the formazan dye signal of 452% [IQR, 399 to 508%]; P⫽0.03)
(Fig. 1C).
To more closely represent the upcoming ex vivo experimental conditions with CD4
⫹
T cells from ARV-treated donors, we next used the full panel of LRAs in the presence of
tenofovir, nevirapine, emtricitabine, and T20, with the addition of 10 U interleukin 2
(IL-2) (to promote cell survival), and assessed metabolic activity, viability, and activation
using the MTS assay (n⫽4) (Fig. 1D) and flow cytometry (n⫽8) (Fig. 1E to G). Cell
metabolic activity was significantly reduced after HDACi treatment, whereas both
bryostatin and PMA/I induced significant proliferation (Fig. 1D). We next employed a
LIVE/DEAD fixable-stain assay, where dead cells with compromised membranes are
labeled with dyes and measured by flow cytometry. In comparison with DMSO, both
nanatinostat and romidepsin displayed significant toxicity, which was modest for
nanatinostat treatment (median fold change [FC] [IQR], 0.1 [0.06 to 0.12]; P⫽0.008) and
more apparent for romidepsin (0.3 FC [0.22 to 0.4]; P⫽0.008). Bryostatin and PMA/I did
not significantly alter cell viability, as measured by flow cytometry (Fig. 1E). Given its
importance in antigen presentation, major histocompatibility complex (MHC) class I
expression was also measured. Only bryostatin and PMA/I changed its expression on
CD4
⫹
T cells (mean fluorescence intensity [MFI] median FC [IQR] ⫽1.75 FC [1.6 to 2.3]
[P⫽0.008] for bryostatin and 3.2 FC [2.1 to 3.8] [P⫽0.02] for PMA/I) (Fig. 1F). CD69 was
also measured as a marker of early cell activation (61). Nanatinostat did not induce
CD69 upregulation (Fig. 1G), whereas romidepsin did (9.4 FC from DMSO [3.8 to 29.6];
P⫽0.008), in line with the results of a previous report (44). Bryostatin also increased
CD69 expression (83.3 FC [30 to 207]; P⫽0.008), and the largest increase was observed
with PMA/I (100.1 FC [34 to 233]; P⫽0.008) (Fig. 1G and H). One hundred nanomolar
nanatinostat was chosen as the concentration to use in the remainder of this study
based on (i) the MTS titration (Fig. 1C), (ii) viability data in HIV-1-infected primary CD4
⫹
T cells (Fig. 1D), and (iii) the fact that 100 nM is the clinically relevant dose previously
described (57). Although romidepsin displayed more toxicity than nanatinostat, we
used 40 nM in this study based on previously published data (10, 62).
Nanatinostat and romidepsin stimulate HIV-1 transcription in ex vivo CD4
ⴙ
T
cells from ARV-treated individuals. Next, we assessed the ability of nanatinostat to
increase levels of HIV-1 transcription from CD4
⫹
T cells isolated from the ex vivo PBMCs
of ARV-treated individuals. These cells were treated in the presence of ARVs, and IL-2
(10 U/ml) to maintain viability (63), with nanatinostat (100 nM), romidepsin (40 nM), or
bryostatin (10 nM), using DMSO (0.001%) as the negative control and PMA/I (10 nM-
500 nM) as the positive control. To assess changes in viral RNA, we performed Droplet
Digital PCR (ddPCR). Unspliced (US) HIV-1 RNA was detected by using a primer set that
crosses viral splice donor 1 to represent that a splicing event did not occur at this major
splice donor (64). Pasternak and Berkhout caution that measuring only US RNA may not
be the best surrogate for latency reversal (65); thus, to quantify a multiply spliced (MS)
HIV-1 RNA, primers were designed to capture a splicing event between splice donor 4
and splice acceptor 7, with a probe spanning the splice junction (3). This particular
primer set captures HIV-1 tat and rev RNAs (3).
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Compared to results with DMSO (median number of copies per microgram of US
RNA [range], 55.0 [11.6 to 192.4]), nanatinostat and romidepsin each significantly
increased levels of US RNA (112 [26.8 to 439.2] copies and 328 [20.8 to 689.2] copies,
respectively; P⫽0.004 for both) (Fig. 2A and D) but not of MS RNA (with DMSO, 4.6 [0
to 10.6] copies; with nanatinostat, 5.4 [0 to 41.1] copies; P⫽0.16; with romidepsin, 8.2
[0 to 67] copies; P⫽0.11) (Fig. 2B and E) (note that undetectable is 0 by ddPCR but is
represented as 1 for the purpose of representation on the log-scale graphs; fold change
graphs [Fig. 2D, E, and F] are presented to demonstrate normalized data over DMSO
data, and values are divided by 1 if they are undetectable). The levels of induction of
US RNA did not differ significantly between romidepsin and nanatinostat (P⫽0.32).
Representative examples of raw ddPCR plots are given in Fig. 2G, representing changes
to US HIV-1 RNA. Bryostatin increased the level of US RNA (median, 149.3 [15.2 to 810.8]
copies; P⫽0.03) and induced increases in MS RNA in 7/9 donors (median, 11.8 [0 to
129] copies; P⫽0.02). PMA/I is a strong T cell mitogen used in vitro to potently activate
T cells (66) and serves here as a positive control for HIV-1 reactivation studies, given its
FIG 2 Ex vivo primary CD4
⫹
T cells treated with nanatinostat significantly induce the transcription of unspliced but not multiply
spliced HIV-1 RNAs and do not drive the production of detectable supernatant HIV-1 RNA. Primary CD4
⫹
T cells from
ARV-suppressed individuals living with HIV (n⫽9) were treated with LRAs in the presence of IL-2 and ARVs. (A and D) Changes
in the levels of US transcripts are presented as numbers of copies per microgram of RNA (A) and as a fold changes from values
for cells treated with DMSO (D). (B and E) Changes in the levels of MS transcripts are presented as numbers of copies per
microgram of RNA (B) and as fold changes from values with DMSO (E). (C and F) Supernatant HIV-1 RNA was measured and
is represented as log
10
numbers of copies per milliliter (C) and corresponding fold changes (F). Graphs are displayed as
medians plus IQRs, and conditions were compared pairwise to results with DMSO using the Wilcoxon matched-pair
signed-rank test.*,P⬍0.05; **,P⬍0.01. (G) Representative example of ddPCR data demonstrating increases in US HIV-1 RNAs,
with values depicting the concentration of positive droplets per sample.
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consistency in reversing latency (62). PMA/I induced the highest level of both US
(median, 250 [64.0 to 994.0] copies; P⫽0.004) and MS (median, 54 [16.5 to 121.5]
copies; P⫽0.004) HIV transcripts. PMA/I treatment was the only condition under which
every donor had detectable MS HIV-1 RNA, and the level of spliced transcripts after
PMA/I treatment was significantly higher than with both nanatinostat and romidepsin
(P⫽0.004 and P⫽0.03, respectively) (Fig. 2B and E).
To test whether ex vivo treatment with HDACi was associated with virus production,
we also measured cell-free HIV-1 RNA in the supernatant of the 72-h cultures. Neither
HDACi demonstrated a significant release of supernatant HIV-1 RNA (Fig. 2C and F). Six
of nine donors displayed increases in HIV-1 RNA in the supernatant when their cells
were treated with bryostatin compared to with DMSO (median number [range] of
copies with DMSO, 0 [0 to 2,224] copies; bryostatin, 8,803 [0 to 167,106] copies;
P⫽0.02). PMA/I significantly enabled the detection of HIV-1 RNA in the supernatant
(median, 38,871 [93.4 to 562,462] copies; P⫽0.03) and was the only condition to
stimulate the release of supernatant HIV-1 RNA for every donor. In conclusion, HDACi
that were able to significantly increase the levels of US RNA but not MS RNA were
similarly unable to induce significant increases in supernatant HIV-1 RNA, demonstrat-
ing an inability to completely reverse HIV-1 latency. Although PMA/I is used as a
positive control and is not clinically viable, it significantly increased both intracellular
species of HIV-1 RNA in this ex vivo model and HIV-1 RNA measured in the supernatant,
demonstrating successful latency reversal.
HIV-specific CD8
ⴙ
T cell clones do not recognize antigen in HDACi-reactivated
autologous CD4
ⴙ
T cells in vitro.We next determined whether these LRAs could drive
antigen presentation using CD8
⫹
T cell clones as biosensors with an HIV-1 latency
model (40, 67). CD8
⫹
T cell responses were mapped using an enzyme-linked immu-
nosorbent spot (ELISPOT) assay, and select responses were isolated as Gag- and
Nef-specific CD8
⫹
T cell clones (epitopes IRLRPGGKK [IK9] and RMRRAEPAA [RA9],
respectively) using a gamma interferon (IFN-
␣
) capture assay, followed by limiting
dilution. Clones were checked for specificity by pulsing them with their cognate
peptide in the presence of CD107a antibody, which is a marker for degranulation when
CD8
⫹
T cells contact their cognate peptide, as measured by flow cytometry. On the day
of the biosensor assay, the Gag clone was confirmed to respond specifically to the
peptide IK9 (89.2% CD107a
⫹
)(Fig. 3F, top panels) and the Nef clone to the peptide RA9
(84.9% CD107a
⫹
)(Fig. 3F, bottom panels), indicating that both were ready for use. A
cultured central memory latency model was generated as previously described (sche-
matic in Fig. 3A)(67, 68), using primary CD4
⫹
T cells from the same donor from which
the clones were derived (see Materials and Methods). Prior to LRA stimulation, ARV-
treated superinfected and nonsuperinfected (mock) cells were positively selected for
CD4 expression to remove residual productively infected cells expressing Gag and
downregulating CD4 (Fig. 3B) This population of latently infected CD4
⫹
T cells was
treated with either DMSO, nanatinostat, romidepsin, bryostatin, or PMA/I for 24 h and
then washed, and at 48 h, it was washed 3 more times to remove residual LRAs. These
target cells were then cocultured with either the Gag- or the Nef-specific CD8
⫹
T cell
clone in the presence of CD107a antibody.
As a measure of latency reversal, Gag expression and supernatant HIV-1 RNA were
quantified prior to the 48-h washout and addition of the CD8
⫹
T cell clones (Fig. 3C and
D). Nanatinostat and romidepsin did not change the proportions of CD4
⫹
T cells
expressing Gag, as measured by flow cytometry, and did not increase cell-free HIV-1
RNA. Both bryostatin and PMA/I increased the proportion of CD4
⫹
T cells expressing
Gag (mean FC ⫾SD, 2.3 ⫾0.27; P⬍0.001; and 4.3 ⫾0.85; P⫽0.005, respectively) and
the level of supernatant HIV-1 RNA (mean FC ⫾SD, 1.78 ⫾0.18; P⫽0.004; and
1.77 ⫾0.23; P⫽0.007, respectively), demonstrating latency reversal in this model.
Changes in the proportions of CD4
⫹
T cells expressing Gag were also assessed after
coculture with the CD8
⫹
T cell clones (Fig. 3E). Modest reductions were observed under
conditions of treatment with DMSO, nanatinostat, and romidepsin with the Gag-specific
clones but not the Nef-specific clone, consistent with killing of Gag-expressing cells by
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FIG 3 Gag- and Nef-specific CD8
⫹
T cell clones do not recognize CD4
⫹
T cells treated with nanatinostat in a biosensor assay using a model of HIV-1 latency.
(A) Schematic of the previously described HIV-1 latency model used as target cells throughout this figure (67, 68). (B) Cultures were depleted of downregulating
CD4
⫹
T cells. (C and D) Cells were then reactivated with the indicated LRAs in the continued presence of ARVs for 48 h prior to an 8-h coculture with either
Gag- or Nef-specific CD8
⫹
T cells clones (IK9 or RA9, respectively). Latency reversal was assessed by measuring the percentages of CD4
⫹
T cells expressing Gag
(Continued on next page)
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the former clone. Bryostatin and PMA/I, both of which induced significant Gag expres-
sion in this model, enabled the detection of more dramatic reductions in the propor-
tions of cells expressing Gag by the Gag-specific clone (mean FC ⫾SD, 0.18 ⫾0.05;
P⫽0.001; and 0.14 ⫾0.02; P⫽0.004, respectively). CD107a is a marker for degranula-
tion and is used as the readout of antigen recognition in this biosensor assay. In a
representative example, we demonstrate degranulation by the Gag-specific CD8
⫹
T cell
clone under conditions where reactivated CD4
⫹
T cells expressed antigen (Fig. 3G).
Only bryostatin and PMA/I drove degranulation (0.4% and 8.48%, respectively), with
neither HDACi inducing detectable degranulation. Despite an extensive washout,
downregulation of the CD8
⫹
receptor was observed for the bryostatin and PMA/I
conditions, indicating activation in the presence of residual drug. However, this did not
directly drive degranulation, given that nonsuperinfected CD4
⫹
T cells also demon-
strated this activation but did not show increased frequencies of CD107a
⫹
CD8
⫹
T cells
(Fig. 3G, lower panel). To assess degranulation, statistical comparisons were made
between JRCSF-superinfected and nonsuperinfected (mock-infected) CD4
⫹
T cells for
each LRA condition. To control for possible nonspecific degranulation by direct effects
of LRAs on CD8
⫹
T cells, comparisons were made between superinfected and non-
superinfected (background) target cells. For the Gag-specific clone, there was no
significant difference in degranulation between superinfected and nonsuperinfected
CD4
⫹
T cells treated with DMSO, nanatinostat, or romidepsin, demonstrating that these
LRA conditions did not sufficiently reverse latency to enable detectable antigen pre-
sentation of this epitope (mean difference ⫾standard error [SE] and adjusted Pvalues
with DMSO, 0.07 ⫾0.03; P⫽0.12; with nanatinostat, 0.07 ⫾0.05; P⫽0.12; with RMD,
0.05 ⫾0.02; P⫽0.11) (Fig. 3H). CD4
⫹
T cells treated with bryostatin or PMA/I signifi-
cantly enabled degranulation of the Gag-specific clone, indicating that these LRAs
reversed latency to the point of antigen presentation in this model (bryostatin,
0.30 ⫾0.05; P⫽0.005; PMA/I, 9.7 ⫾0.44; P⬍0.0001) (Fig. 3H). Results were similar for
the Nef-specific clone in that nanatinostat and romidepsin treatment displayed no
differences between JRCSF-infected and nonsuperinfected CD4
⫹
T cells in the degran-
ulation of the CD8
⫹
T cell clones (nanatinostat, 0.28 ⫾0.15; P⫽0.12; RMD, 0.32 ⫾0.13;
P⫽0.10) (Fig. 3I). Bryostatin-treated CD4
⫹
T cells most potently enabled Nef-specific
CD8
⫹
T cell degranulation (5.67 ⫾0.31; P⬍0.0001), and PMA/I treatment also signifi-
cantly drove degranulation of this clone (2.50 ⫾0.23; P⬍0.0001) (Fig. 3I). Taken
together, these data indicate that, in this model of HIV-1 latency, bryostatin and PMA/I
enabled antigen presentation to CD8
⫹
T cell clones against two different HIV-1
products, Gag and Nef, while the HDACi romidepsin and nanatinostat did not. This
pattern of antigen expression also corresponded with the induction of detectable
supernatant HIV-1 RNA, which was observed only for bryostatin and PMA/I. These
results support the idea that LRAs which enable the release of cell-free HIV-1 RNA
render CD4
⫹
T cells recognizable by HIV-specific T cells in this in vitro assay.
Nanatinostat exhibits less toxicity and functional impairment of HIV-specific
CD8
ⴙ
T cells than romidepsin in vitro.We and others have previously observed that
HDACi can impair CD8
⫹
T cell function against HIV-1 (41) and HTLV-1 (42), although this
consideration may change depending on the specific HDACi tested and which classes
of HDACs are targeted. For example, vorinostat has little impact on CD8
⫹
T cell function
at physiological doses (44). To assess any potential impacts of nanatinostat on CD8
⫹
T
cell function, we performed a series of viral inhibition assays. The IL-15 superagonist
FIG 3 Legend (Continued)
(C) and supernatant RNA (D), represented as FCs from values with DMSO. (E) Changes in the proportions of CD4
⫹
T cells expressing Gag once cells were exposed
to CD8
⫹
T cell clones were assessed. (F) A CD8
⫹
T cell clone specificity check was performed with cognate peptide. The flow cytometry results show that this
clone potently degranulates in response to its peptide. (G) A representative example of the Gag-IK9-specific CD8
⫹
T cell clones expressing antigen and
undergoing degranulation in response to CD4
⫹
T cells in which HIV-1 latency had been sufficiently reversed is displayed in the top panel, with mock-
superinfected cells displayed in the bottom panel. (H and I) To assess antigen presentation, we measured the percentages of Gag-specific CD8
⫹
T cell clones
expressing CD107a (H), as well as the Nef-specific clones (I). (C to E) Paired ttests were used to compare the value with each LRA to that with DMSO (C, D)
or the value for the CD8
⫹
T cell clone to that with no clone (E). (H and I) Multiple ttests were performed using the Holm-Sidak method for multiple comparisons
to assess differences between JRCSF-infected cells and mock-infected cells for each LRA. *,P⬍0.05; **,P⬍0.01; ***,P⬍0.001.
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N-803 (400 ng/ml, previously called ALT-803) was selected as a positive control, given
that we have previously demonstrated its ability to enhance HIV-specific T cell function
in vitro (41). As is represented in Fig. 4A, CD4
⫹
T cells were superinfected with HIV-1
JRCSF and then cocultured with autologous bulk CD8
⫹
T cells. Supernatants were
collected on day 3 and day 7 postcoculture to measure viral inhibition by a reduction
in detectable supernatant p24 compared to that of the culture with CD4
⫹
T cells alone.
Cells were also harvested on day 7 to measure changes in the percentages of cells
expressing Gag across the various conditions. The negative control, DMSO, repre-
sents the individual’s antiviral response from their unperturbed population of bulk
CD8
⫹
T cells, as measured by a reduction in HIV-1 Gag-expressing CD4
⫹
T cells that
have been superinfected relative to the level in the no-CD8
⫹
T cell control condi-
tion. To investigate the effect of LRAs on CD8
⫹
T cell function, we measured the
frequencies of CD4
⫹
T cells expressing Gag after 7 days, as well as the proportions
of CD8
⫹
T cells that remained viable. Initially, when CD8
⫹
T cells were cultured for
the 24-h period with LRA prior to coculture with CD4
⫹
T cells, we used the MTS
assay to assess cell toxicity and proliferation and demonstrated that CD8
⫹
T cells
were not significantly affected by HDACi or N-803 relative to effects of DMSO at this
time point (Fig. 4B).
CD8
⫹
T cells treated with either HDACi declined by day 7 of the culture period,
whereas N-803 had no effect on the CD8
⫹
T cells remaining in culture (Fig. 4C).
Additionally, there were more CD4
⫹
T cells remaining in culture after 7 days for CD8
⫹
T cells initially treated with nanatinostat and romidepsin than in cells treated with
N-803 (Fig. 4D). A representative experiment (Fig. 4E) demonstrates the ability of LRA-
or DMSO-treated CD8
⫹
T cells to reduce the percentage of Gag-expressing CD4
⫹
T cells
at the end of the culture period, compared to the condition receiving no CD8
⫹
effectors. Overall, DMSO-treated (control) CD8
⫹
T cells enabled an average 63% reduc-
tion (mean FC ⫾SD, 0.37 ⫾0.25; P⫽0.02) in the percentage of CD4
⫹
T cells expressing
Gag, while N-803-treated CD8
⫹
T cells drove a greater reduction of 86% (mean FC ⫾
SD, 0.14 ⫾0.28; P⫽0.03) (Fig. 4F). Nanatinostat-treated CD8
⫹
T cells also significantly
reduced the percentages of HIV-infected (Gag
⫹
) cells compared to the percentages
with no effectors (mean FC ⫾SD, 0.63 ⫾0.12; P⫽0.02), however, only by an average
of 37%, which was significantly less than the percentage in DMSO-treated CD8
⫹
T cells
(mean FC ⫾SD; 1.8 ⫾1.4; P⫽0.04) (Fig. 4F). Romidepsin-treated CD8
⫹
T cells did not
measurably inhibit viral replication in these assays (mean FC ⫾SD, 0.93 ⫾0.12;
P⫽0.38), and this was also significantly different from viral replication in the popula-
tion of control CD8
⫹
T cells (mean difference ⫾SD, 3.7 ⫾2.7; P⫽0.04) (Fig. 4F). N-803
significantly enhanced the abilities of CD8
⫹
T cells to reduce levels of supernatant p24
on day 3 (mean FC ⫾SD, 0.10 ⫾0.11; P⫽0.007) (Fig. 4G). Thus, both HDACi tested
impaired the abilities of CD8
⫹
T cells to suppress viral replication, while N-803 en-
hanced this activity.
When comparing nanatinostat to romidepsin at their tested doses, we observed
more killing of CD4
⫹
T cells with less toxicity to CD8
⫹
T cells following coculture with
the former (Fig. 4I and J). Nanatinostat treatment was also associated with greater
CD8
⫹
T cell-mediated reductions in the proportions of HIV-infected cells than
romidepsin (32% less; 1.9 ⫾1.4 mean difference; P⫽0.04) (Fig. 4K). We also directly
compared N-803-treated CD8
⫹
T cells to untreated (DMSO) cells and found that
while both conditions did not significantly differ in proportions of CD4
⫹
T cells
versus CD8
⫹
T cells remaining in culture (Fig. 4L and M), N-803-treated CD8
⫹
T cells
exhibited significantly greater suppression of HIV replication (percentages of Gag
⫹
cells at day 7) than untreated (DMSO) CD8
⫹
T cells (mean, 70% less; mean
difference ⫾SD, 1.2 ⫾0.41; P⫽0.009) (Fig. 4N). Thus, whereas both HDACi tested
in this study impaired CD8
⫹
T cell function, this effect was observed to be
substantially less for nanatinostat at concentrations where both agents exhibited
similar effects on HIV-1 transcription (Fig. 2).
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FIG 4 Nanatinostat moderately impaired the abilities of CD8
⫹
T cells to suppress viral replication, while romidepsin abrogated this activity under
the conditions tested. (A) Schematic of viral inhibition assay. (B) LRA-treated CD8
⫹
T cells were assessed for metabolic activity by the MTS assay
(Continued on next page)
Limitations of HDACi during HIV-1 Latency Reversal Journal of Virology
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DISCUSSION
Our results support that, while class I-selective HDACi act as a transcriptional “on
switches” for latent HIV-1, they do not facilitate the production of viral antigens or
particles from primary CD4
⫹
T cells, partially due to a lack of sufficient accumulation of
spliced viral transcripts. The complexity of the HIV-1 proviral genome, with gene
products encoded within overlapping exonic regions, multiple open reading frames,
and nine major genes with distinct functions, which are compressed into a 10-kb
genome, may require more than transcriptional initiation to achieve antigen presen-
tation during latency reversal (3, 27, 64, 69). Cotranscriptional HIV-1 RNA splicing is
tightly coordinated and important early during viral replication (27, 64, 70)(Fig. 5B). MS
RNAs encode the regulatory proteins Tat, Rev, and Nef, which are required for success-
ful viral replication. Tat is particularly important in driving robust viral transcription and
elongation and coordinating viral splicing (71), and the absence of Tat is more essential
than the cellular environment in maintaining viral latency (72). Unspliced transcripts
contain secondary structures termed the Rev response element (RRE), which retain
HIV-1 RNAs in the nucleus. Rev is required to export RRE-containing viral transcripts,
including env and the unspliced genome, to the cytoplasm for translation or packaging
(69, 73, 74). During latency reversal, when HDACi do not provoke a significant accu-
mulation of tat and rev RNA or their encoded proteins, it is unlikely that this condition
results in the production of virions, as evidenced here by a lack of supernatant HIV-1
RNA after HDACi treatment compared to after bryostatin and PMA/I treatment, which
enabled the release of viral RNA (75)(Fig. 5B).
Although changes to MS HIV-1 RNA after HDACi treatment did not reach statistical
significance, some donors were able to increase the levels of MS RNA after HDACi
treatment, yet this did not result in detectable supernatant HIV-1 RNA. This may be due
to further blocks to latency that were not overcome, including the nuclear retention of
spliced viral RNAs (76, 77), issues with 3=processing and polyadenylation (3), or the lack
of cellular factors required for the nuclear export and translation of Tat and Rev, which
are required to drive virion production. Alternatively, should Tat become expressed
during latency reversal, long noncoding RNAs present in mCD4
⫹
T cells may selectively
promote the degradation of Tat protein (78). Tat posttranslational modifications driven
by the acetylation of lysine residues by HDACi may additionally alter the behavior of Tat
in its replication feedback loop, also affecting the ability to form virions (71). The
capacity to reverse latency will also depend on the environment of the host cell. Recent
evidence suggests differential activities of LRAs in their ability to reactivate latency
based on the cellular subset (79, 80). Distinct changes to the activation state of host
factors associated with viral replication, i.e., histone acetylation, NF-
␬
B, and positive
transcription elongation factor b (P-TEFb), differ based on LRA stimulation and the cell
subset treated (80). While this paper investigates total CD4
⫹
T cells, it will be interesting
in the future to investigate the effects of these LRAs on the induction of spliced versus
unspliced transcripts across various T cell subsets or across different tissues (81). In
donors where MS HIV-1 RNA failed to accumulate while US HIV-1 RNA increased after
HDACi treatment, this may have been due to the recently described emerging role of
HDACs and histone modifications in splicing (82). HDACs together with serine-arginine-
rich splicing factors (SRSF), involved in the maintenance of viral latency and viral
FIG 4 Legend (Continued)
and then cocultured with JRCSF-superinfected CD4s at an effector/target ratio of 4:1. (C and D) Cells were collected on day 7 and analyzed by flow
cytometry to quantify numbers of remaining CD8
⫹
T cells (C) and CD4
⫹
T cells (D). (E) Representative flow cytometry plots for each condition with
gating on viable CD4
⫹
T cells and depicting intracellular Gag expression as a measure of infection. Reductions in Gag
⫹
cells relative to the value
for the condition “No CD8s” are indicative of CD8-mediated viral inhibition. (F) Summary data depicting fold changes in frequencies of Gag
⫹
CD4
⫹
T cells on day 7. (G and H) Supernatant p24 levels were measured on day 3 (G) and day 7 (H) as a readout for viral replication. Each dot represents
a different study participant, and FCs are expressed relative to the no-CD8 condition. (I to M) Shown are pairwise comparisons between nanatinostat
and romidepsin (I to K) or between DMSO and N803 (L and M). The comparisons in panels I and L are derived from the data shown in panel D,
the comparisons in panels J and M are from the data in panel C, and the comparisons in panels K and N are from the data in panel F. Experiments
of 5 donors were performed in duplicate; donor results are graphed as means and standard deviations. Paired ttests were used to compare drug
conditions to the condition with the DMSO control (A to C) or no-effector control (E to G). *,P⬍0.05; **,P⬍0.01.
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FIG 5 Latency reversal. (A) During HIV-1 latency and its reversal, we propose that when a series of blocks that maintain latency are
overcome, the “kick” of “kick and kill” may be sufficient to stimulate antigen presentation and/or viral cytopathic affects, as was
achieved by treatment with bryostatin and PMA/I in this study. Transcriptional initiation and RNA elongation. When the LTR of an
integrated provirus is bound by HDACs, the first step in enabling the induction of transcription is through the removal of these
HDACs with host histone acetyl (Ac) transferases or through treatment with HDACi. This alters the chromatin architecture so that
transcription factors, i.e., NF-êB, can interact with the NF-êB binding sites within the HIV-1 LTR to drive transcriptional initiation.
Transcription proceeds with RNA polymerase II (Pol II) to transcribe through the trans-activation response element (TAR) region of
LTR RNA. Elongation can pause here, with the TAR RNA and RNA Pol II associated with negative elongation factors. With Tat
translation and its recruitment of P-TEFb to the TAR RNA, elongation may proceed. (B) Viral splicing and nuclear export. (B1) Tat
drives transcriptional initiation and elongation and also orchestrates viral splicing. Spliced transcripts are then processed into
poly-adenylated mRNA (B2) and exported to the cytoplasm to translate HIV-1 regulatory proteins, including Tat and Rev (B3). Both
localize back into the nucleus, where Tat continues to drive transcription, elongation, and splicing, and once a threshold of Rev is
achieved, a switch into late viral replication induces the accumulation of singly spliced and unspliced transcripts to create accessory
and structural proteins (B4). Singly spliced and unspliced viral transcripts contain the RRE, restricting them to the nucleus. Rev binds
the RRE to facilitate export of the transcripts into the cytoplasm (B4). Virus production and antigen presentation. Once the late viral
gene products are expressed (B5), viral particles are created and will bud from the cell (B6). Cells may die via viral cytotoxicity. As
viral proteins are expressed, some will be cleaved to be processed as antigen and complex with MHC I molecules, which will be
transported to the cell membrane (B7). HIV-1-specific CD8
⫹
T cells can recognize their cognate antigen, stimulating degranulation
and targeted death of the infected CD4
⫹
T cell. Proposed model of latency reversal with HDACi. In this study, HDACi induce
transcription in all donors. Some donors modestly accumulate spliced transcripts, although this does not occur for every donor, nor
does it reach statistical significance compared to results with DMSO. HDACi do not drive the release of viral RNA into ex vivo cultures,
and treated CD4
⫹
T cells do not significantly induce degranulation of CD8
⫹
T cell clones. Additionally, HDACi display toxicity to CD8
⫹
T cells (B8), which impairs their function in vitro. We propose that while HDACi clearly initiate viral transcription, they do not
consistently remove all blocks to viral latency required for clinical potency. Defective proviral genomes, for example, that encode Gag
but lack a sequence containing the RRE may be transcribed and transported to the cytoplasm without blocks that require Rev and
can be translated, processed as antigen, and recognized by CD8
⫹
T cells (B9). We predict that defective genomes may be easier to
reverse from latency with fewer blocks to overcome. We further predict that latently infected cells otherwise experience a burst of
transcriptional initiation from the viral LTR, which eventually goes back into a latent state.
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splicing, respectively, coordinate the interface between chromatin organization and
cotranscriptional alternative splicing (83, 84). The kinetic coupling of HDACs and SRSF
proteins in regulating splicing can be disrupted by the addition of an HDACi. HDAC1,
which is associated with maintaining latency of the viral LTR, is demonstrated to
regulate splicing in its deacetylated state, where the addition of an HDACi can inhibit
splicing (32). SRSF proteins undergo proteasomal degradation if acetylated within their
RNA recognition motif, which may be affected by the addition of an HDACi (85). While
these two potential mechanisms may play a role in the ex vivo experiments carried out
in this study, the environment of the cell subset undergoing latency reversal may affect
the behavior of the HDACi with host cellular factors (86).
Our results identify a key discrepancy between the J-Lat cell line and primary CD4
⫹
T cells, where the products of multiply spliced HIV-1 transcripts were expressed in the
former. The reporter gfp replaces nef in the proviral sequence harbored within J-Lat
cells; GFP expression is therefore encoded by a multiply spliced viral RNA. While our
results with primary CD4
⫹
T cells indicate inhibition of viral RNA splicing by HDACi, the
activation of GFP expression in J-Lat cells by both romidepsin and nanatinostat
demonstrates that appreciable splicing occurred in this context. We interpret this
discrepancy as arising from the multitude of host factor differences between primary
CD4
⫹
T cells and transformed cell lines. Jurkat T cells, the parental cell line of J-Lat cells,
are tetraploid, with thousands of identified deletions, insertions, inversions, and chro-
mosomal translocations, promoting an extensive deviation from normal T cell biology
(87). Other researchers have demonstrated differences in alternative splicing between
primary cells and their representative model immortalized cell lines (88–90). Marked
discrepancies in HIV-1 transcriptional profiles, T cell phenotypic markers, and antiviral
restriction factors were recently reported between latently infected HIV-1 cell lines and
infected primary T cells (4). Thus, in the current study, J-Lat cells served the role of an
initial check for the activities of our LRAs, with the understanding that the activity in
these immortalized cells would not closely mimic the biology that occurs during latency
reversal of primary CD4
⫹
T cells.
A key feature of our study was the use of an HIV-1-specific CD8
⫹
T cell clone
biosensor assay to elucidate whether HDACi-induced transcriptional initiation from the
LTR was sufficient to drive antigen presentation (41, 67). T cells are exquisitely sensitive
and specific and can form an immunological synapse with a target cell presenting as
few as 10 MHC-peptide complexes on the cell surface (40, 67, 91). We hypothesized that
if the observed HDACi-induced increases in US RNA were enough to drive antigen
presentation, even without enabling splicing and the expression of MS proteins, the
HDACi would drive degranulation of the Gag-specific clone (as Gag is expressed by an
US transcript), but not the Nef-specific clone (Nef is expressed by a MS transcript).
However, we observed that neither HDACi triggered the degranulation of either CD8
⫹
T cell clone, while degranulation was observed with bryostatin and PMA/I. These data
are consistent with a requirement for regulatory gene products expressed from MS
transcripts to achieve antigen expression and subsequent presentation to HIV-1-
specific CD8
⫹
T cells, i.e., the nuclear export of US RNA by Rev. Thus, in these
experiments, CD8
⫹
T cell recognition of reactivated cells occurred in agreement with
the release of cell-free HIV-1 RNA as achieved by bryostatin and PMA/I. In contrast,
HDACi treatment, which did not enable detectable cell-free HIV-1 RNA, was not
associated with CD4
⫹
T cell recognition by these clones.
Given that our biosensor assay uses an intact laboratory strain virus, the inability for
HDACi to enable antigen presentation in this study is based on a replication-competent
genome that has entered latency. However, 98% of viral reservoirs in individuals on ART
are typically comprised of defective proviruses that contain APOBEC3G-induced hyper-
mutations, internal deletions, or frameshift nonsense mutations obtained during re-
combination or error-prone reverse transcription, respectively, as well as sequences
containing mutations in splice donor and acceptor sites (92–94). Large internal dele-
tions can encompass the tat and rev open reading frames, including within the env
sequence (92), which may make the nuclear export of unspliced viral RNA possible in
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the absence of Rev. Defective genomes are also capable of transcription and translation
and can be targeted by CD8
⫹
T cells (94). Intact replication-competent proviral ge-
nomes are hardwired to achieve successful viral replication but depend on a well-
defined set of cellular factors that remain scarce or inactivated in latently infected CD4
⫹
T cells (72). In the deepest state of HIV-1 latency, a completely transcriptionally
quiescent intact provirus may be the most difficult to reactivate, as studies have
demonstrated that multiple rounds of strong T cell stimulation may be required to
reverse latency of certain replication-competent genomes (95). Defective genomes may
be easier to reactivate depending on what region of the genome is deleted or mutated,
with fewer potential hurdles to overcome (96)(Fig. 5). In an LRA-induced HIV eradica-
tion assay, we recently demonstrated resistance to killing of CD4
⫹
T cells harboring
replication-competent intact genomes, whereas defective proviral genomes were more
readily reactivated and killed by CD8
⫹
T cells (97). This might be attributed to the
inability of a durably quiescent intact genome to be reactivated with a single round of
LRA stimulation compared to that of a defective provirus with fewer blocks during
reactivation, particularly deletions that remove the RRE from the genome (96). Addi-
tionally, antigen presentation may be affected by the action of the LRA. Unspliced host
RNAs that encode the proteolytic machinery that influence antigen processing and
presentation are retained in the nuclei of unactivated CD4
⫹
T cells, and T cell receptor
(TCR)-dependent or -independent pathways can release these RNAs, changing the
cytosolic compositions of certain HIV-1 epitopes, altering the MHC HIV-1 peptidome
(98). This might affect what peptides are presented and thus recognized by CD8
⫹
T
cells in this study.
In comparing our results to those of clinical studies, we note that Søgaard et al. (16)
observed modest increases in viral load with in vivo romidepsin treatment, suggesting
full reversal of latency. However, they also observed transient yet statistically significant
increases in early and late activation markers in all CD4
⫹
T cell subsets (16). Without
further validation, it remains difficult to differentiate whether the reported virus pro-
duction was driven by the targeted mechanism of chromatin remodeling or whether it
was an outcome of cell activation. Other in vivo studies have not assessed the activation
status of CD4
⫹
T cells after HDACi treatment or demonstrated significant increases in
plasma viral load (11–16). Thus, our ex vivo assessment of unspliced and spliced viral
RNAs builds on the growing literature that includes spliced RNAs as a measurement for
latency reversal (4, 39, 65, 81). Further mechanistic research is warranted to define the
role of splicing during latency reversal and how it pertains to antigen presentation and
recognition by HIV-specific CD8
⫹
T cells.
While studying the action of HDACi in latency reversal, it is also important to
elucidate their effects on CD8
⫹
T cell cytotoxicity (reviewed in reference 48). Romidep-
sin has been implicated in delayed impairment of CD8
⫹
T cell function ex vivo (44), and
we have previously demonstrated that romidepsin can reduce the viability, IFN-
␣
production, and proliferation of CD8
⫹
T cells, while impairing the ability of CTL clones
to kill infected target CD4
⫹
T cells (41). Studies that have subsequently assessed the
impact of romidepsin in vivo on HIV-1-specific CD8
⫹
T cells in clinical trials have yielded
mixed results. Søgaard et al. reported a lack of statistically significant impairment in
HIV-specific CD8
⫹
T cell responses (16), whereas Mothe and colleagues observed a
transient, but significant, 35% decrease in the magnitudes of HIV-1-specific T cell
responses (IFN-
␣
) after romidepsin treatment (B. Mothe et al., presented at the Con-
ference on Retroviruses and Opportunistic Infections 2017, Seattle, WA; abstract 450,
reviewed in reference 48). An important limitation that we perceive in the former study
was that the sample size tested (n⫽5) is unable to yield a significant result with the
Wilcoxon matched-pair signed-rank test that was used (this particular statistical test
requires a minimum sample size of 6 to calculate a Pvalue of ⬍0.05) (99). Thus, we
consider the question of whether or not romidepsin impairs HIV-1-specific T cells in vivo
to be unresolved. While this paper builds upon our previous work by using primary ex
vivo CD8
⫹
T cells rather than CTL clones, we acknowledge limitations of in vitro assays
with regard to the complex in vivo interactions that take place amid the diversity of cell
Limitations of HDACi during HIV-1 Latency Reversal Journal of Virology
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types within peripheral blood versus tissue microenvironments, where reservoir cells
and HIV-1-specific CD8
⫹
T cells reside. However, our results highlight the ongoing
importance of assessing a variety of readouts throughout the process of latency
reversal in vitro and in vivo.
Though the role of the IL-15 superagonist N-803 in the current study is primarily to
serve as a positive control, our data provide further evidence that it directly enhances
the antiviral activity of ex vivo HIV-specific CD8
⫹
T cells. N-803 has also been shown to
exhibit LRA activity in vitro (40) and in vivo in CD8-depleted rhesus macaques (100)as
well as to drive trafficking of simian immunodeficiency virus (SIV)-specific CD8
⫹
T cells
from peripheral blood into the B cell follicles within lymph nodes (101), an important
anatomical viral reservoir (102). Investigators have also demonstrated that N-803 can
reduce SIV loads in monkeys without ART, likely by enhancing CD8
⫹
T cell and/or NK
cell function (101, 103). Thus, our study adds to the body of evidence supporting the
prioritization of N-803 for in vivo studies related to an HIV-1 cure. It would also be of
interest, in future studies, to test combinations of nanatinostat and N-803, both for
potential synergy as LRAs and to determine the net effect on CD8
⫹
T cell-mediated viral
inhibition.
Limitations of this study include using the quantification of viral RNA transcripts
from bulk RNA samples. As with any such PCR assay, we cannot distinguish between a
single RNA being reactivated from multiple proviruses versus many RNA transcripts
being reactivated from a single provirus. The amount of RNA induced per cell may also
differ depending on the LRA used, which might affect the capacity to express antigen.
Another limitation is the particular HIV-1-specific CD8
⫹
T cell responses of the individ-
ual used in our biosensor assay, restricting the variety of presented epitopes that we
were able to study with our CD8
⫹
T cell clones. Different LRAs may also modify the
repertoire of epitopes presented (98). Finally, the lower limit of sensitivity of our CD8
⫹
T cell biosensor assay is unknown, and thus the lack of detectable degranulation should
not be interpreted as an absolute lack of antigen expression but rather the lack of
detection above an unknown threshold. That being said, there are lines of evidence
supporting the idea that this is a highly sensitive way of measuring antigen expression:
(i) as mentioned above, T cells can form an immunological synapse with a target cell
presenting as few as 10 MHC-peptide complexes on the cell surface (40, 67, 91) and (ii)
the numbers of CTL clone cells that can degranulate is proportional to the number of
target cells that express antigen, given that this is driven by direct effector-target cell
interactions. Thus, the observation that ⬃10% of CTL clones degranulate following
coculture with target cells, where only ⬃0.25% of cells have detectable Gag expression
by flow cytometry, is consistent with a high degree of sensitivity. Furthermore, this
assay is unique in that the threshold of detection of latency reversal is directly relevant
to the desired outcome of kick and kill eradication strategies, as both depend upon
triggering CTLs to degranulate.
This study thus provides insights that are relevant both to the interpretation of
outcomes of kick and kill clinical trials that have been conducted to date and to the
design of future studies. We postulate that limitations in accumulating spliced HIV-1
RNA and their encoded regulatory proteins preclude the nuclear export of RRE-
containing US RNA, at least for intact genomes, reducing antigen processing and
presentation in HDACi-treated CD4
⫹
T cells (Fig. 5). Our results also highlight the
importance of considering putative LRAs from the perspective of immune effectors,
both in terms of their abilities to induce bona fide antigen expression and in terms of
their potential to either impair or enhance immune cell function. Potential approaches
that may leverage the ability of class I-selective HDACi to initiate transcription, while
addressing the limitations identified here, include (i) the targeted delivery of these
agents to the exterior of CD4
⫹
T cells or in a triggered release manner (104), thus
avoiding impairment of CD8
⫹
T cells as well as other potential off-target effects, and (ii)
combinations with putative agents which may enhance viral splicing or enhance CD8
⫹
T cell function, such as N-803, or other immunotherapeutics.
Mota et al. Journal of Virology
May 2020 Volume 94 Issue 9 e01845-19 jvi.asm.org 16
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MATERIALS AND METHODS
Ethics statement. Study participants (HIV-infected individuals) were recruited from the Maple Leaf
Medical Clinic in Toronto, Canada, through a protocol approved by the University of Toronto Institutional
Review Board or through Whitman Walker Health in Washington, DC, through a protocol approved by
the George Washington University Institutional Review Board. Secondary use of these study participants
was approved through the Weill Cornell Medicine Institutional Review Boards. All subjects were adults
and gave written informed consent. Clinical data for these participants are given in Table 1.
J-Lat 10.6 experiments. J-Lat 10.6 cells were seeded at 5 ⫻10
4
cells per well in a 96-well plate and
with a 2-fold serial dilution of nanatinostat (1,000 nM to 62.5 nM) or with PMA-ionomycin (10 nM-0.5
␮
M)
as the positive control or DMSO as the negative control, given that all drugs were dissolved in DMSO.
DMSO was added at 0.001%, the highest compound concentration used for the LRAs. Three experiments
were performed in duplicate. A concentration of 100 nM was chosen based on this titration to move
forward with remaining experiments. J-Lat 10.6 cells were seeded as in previous experiments and treated
in duplicate with nanatinostat (100 nM; Viracta), romidepsin (40 nM; Selleck Chemicals), bryostatin
(10 nM; Sigma-Aldrich), PMA-ionomycin (10 nM-500 nM; Sigma-Aldrich), or DMSO. Cells were harvested
at 24 h and analyzed for changes in GFP expression by flow cytometry.
MTS viability assay. To assess cellular viability following treatment with nanatinostat, total CD4
⫹
T
cells were negatively selected from PBMCs using the EasySep human CD4
⫹
T cell isolation kit (Stemcell
Technologies), cultured in duplicate at 1 ⫻10
5
cells per well in a 96-well plate, and either treated with
a 2-fold titration of nanatinostat (1,000 nM to 62.5 nM), left untreated, treated with PMA-ionomycin
(10 nM-500 nM) as the positive control, or treated with DMSO as the negative control. Drugs were
washed at 24 h and cells were harvested at 72 h for the MTS assay, which was performed as per the
manufacturer’s protocol (Abcam). Additional MTS assays were performed with CD4
⫹
T cells from
individuals living with HIV and with the entire LRA panel, including nanatinostat (100 nM; Viracta),
romidepsin (40 nM; Selleck Chemicals), bryostatin (10 nM; Sigma-Aldrich), PMA-ionomycin (10 nM-
500 nM; Sigma-Aldrich), or DMSO, in the presence of ARVs.
Ex vivo studies of CD4
ⴙ
T cells from HIV-1-infected individuals on ART. PBMCs were collected by
leukapheresis from HIV-1-infected individuals on ART. Total CD4
⫹
T cells were negatively selected from
PBMCs using the EasySep human CD4
⫹
T cell isolation kit (Stemcell Technologies). Cells were cultured
at 5 million cells per well in a 24-well plate in RPMI medium supplemented with 10% fetal bovine serum
(FBS), penicillin-streptomycin, L-glutamine, 10 U/ml IL-2, 1
␮
M tenofovir, 1
␮
M nevirapine, 1
␮
M emtric-
itabine, and 10
␮
M T20. Cells were treated with nanatinostat (100 nM; Viracta), romidepsin (40 nM),
bryostatin (10 nM), PMA-ionomycin (10 nM-0.5
␮
M) as the positive control, or DMSO as the negative
control. Drugs were washed out at 24 h, ARV medium was replenished, and cells were harvested at 72 h
for flow cytometry or stored in TRIzol (Life Technologies) for RNA extraction. Cells were stained with Aqua
LIVE/DEAD viability dye (Thermo Fischer Scientific) and anti-CD3, -CD4, -HLA-abc, and -CD69 antibodies
(BioLegend) and analyzed by flow cytometry. RNA was extracted per the manufacturer’s protocol. RNA
for each sample was reverse transcribed into cDNA using random hexamers and Superscript III reverse
transcriptase (RT; Life Technologies).
Quantification of cell-associated HIV-1 RNA by ddPCR. Droplet Digital PCR (ddPCR) was per-
formed using primer/probe sets as previously validated for comparisons of MS and US HIV-1 RNAs (3,
105). We used the tat/rev assay from the work of Yukl et al. (3) to measure MS HIV RNA and chose a primer
set to measure gag RNA that includes splice donor 1 to define an US HIV-1 RNA transcript. Five hundred
nanograms of input cellular RNA per reaction mixture was mixed with ddPCR Supermix for probes (no
dUTPs) (Bio-Rad) and the following primer/probe sets: forward primer 5=-TCTCGACGCAGGACTCG-3=,
reverse primer 5=-TACTGACGCTCTCGCACC-3=, and probe FAM-CTCTCTCCTTCTAGCCTC-MGBNFQ (where
FAM is 6-carboxyfluorescein) for unspliced gag HIV-1 RNA and forward primer 5=-CTTAGGCATCTCCTAT
GGCAGGAA-3=, reverse primer 5=-GGATCTGTCTCTGTCTCTCTCTCCACC-3=, and probe FAM-ACCCGACAG
GCC-MGBNFQ for tat/rev HIV-1 RNA. Droplets were prepared using the Droplet Generator (Bio-Rad)
according to the manufacturer’s instructions. Sealed plates were cycled using the following program:
95°C for 10 min, 45 cycles of 94°C for 30 s and 59°C for 1 min, and 98°C for 10 min, with a 2°C/s ramping
speed. Reactions were analyzed in duplicate using the QX200 Droplet Reader, and numbers of RNA
copies per nanogram of RNA were estimated using QuantaLife ddPCR software. No RT controls were used
for the US RNA condition.
Measuring supernatant HIV-1 RNA in ex vivo cultures. Viral RNA was extracted from 100
␮
lof
culture supernatant using the QIAamp viral RNA minikit (Qiagen) according to the manufacturer’s
recommendations. RNA was eluted in 60
␮
l nuclease-free water and immediately analyzed by quanti-
tative RT PCR (qRT-PCR). HIV-1 RNA copies were quantified using the AgPath-ID one-step RT-PCR kit;
reactions were prepared by mixing 8.5
␮
l of extracted viral RNA with 0.4
␮
M primer iSCA-for (5=-TTTG
GAAAGGACCAGCAAA-3=), 0.4
␮
M primer iSCA-rev (5=-CCTGCCATCTGTTTTCCA-3=), and 0.25
␮
M probe
iSCA (5=-FAM-AAAGGTGAAGGGGCAGTAGTAATACA-TAMRA-3=, where TAMRA is 6-carboxytetramethyl-
rhodamine) in a 25-
␮
l final volume on ice. Samples were analyzed on an ABI Viia7 real-time PCR system
using the following cycling parameters: 45°C for 10 min and 95°C for 10 min, followed by 40 cycles of
95°C for 15 s and 60°C for 1 min. Tenfold serial dilutions of an RNA standard and negative-control wells
were included in each run.
Biosensor assay. An IFN-
␣
ELISPOT assay was used to map HIV-1-specific CD8
⫹
T cell responses
using 270 optimal peptides, and specific responses were cloned as previously described (41). Clones were
checked for specificity by incubating them for 5 h with their cognate peptide in the presence of CD107a
antibody, a marker for degranulation. Meanwhile, a model for HIV-1 latency was used as previously
described (67) as modified from reference 68. Briefly, naive CD4
⫹
T cells were isolated from an individual
Limitations of HDACi during HIV-1 Latency Reversal Journal of Virology
May 2020 Volume 94 Issue 9 e01845-19 jvi.asm.org 17
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living with HIV-1 on suppressive ART and expanded using anti-IL-4 and anti-IL-12 antibodies in the
presence of transforming growth factor
␤
(TGF-
␤
) and anti-CD3 anti-CD28 Dynabeads. Cells were
superinfected with JRCSF on day 7 or not superinfected. On day 13, cells were treated with ART, and 3
days later, productively infected downregulating CD4
⫹
T cells were removed using a CD4
⫹
selection kit
(Thermo Fisher). Cells were treated with LRAs for 24 h and then washed, ARVs were re-added, and
cultures were maintained for 48 h at 37°C and 5% CO
2
. The supernatant was collected to detect cell-free
HIV-1 RNA, and cells were more extensively washed before coculture with the CD8
⫹
T cell clones specific
for Gag (IK9 epitope) or Nef (RA9) in four biological replicates in the presence of CD107a antibody for 8 h.
Recognition of target cells was observed by measuring live CD107a
⫹
CD3
⫹
CD8
⫹
T cells by flow
cytometry.
Viral inhibition assay. To investigate the effects of HDACi on the function of CD8
⫹
T cells, viral
inhibition assays were performed as previously described, with modifications (106). Briefly, CD4
⫹
T cells
from individuals living with HIV-1 were isolated as described above, cultured in RPMI medium supple-
mented with 30 U/ml IL-2, and treated with 1
␮
g/ml each of anti-CD3 (clone OKT3; BioLegend) and
anti-CD28 (clone CD28.2; BioLegend) for 48 h. The following day, autologous CD8
⫹
T cells were
negatively selected using an EasySep human CD8
⫹
T cell isolation kit (Stemcell Technologies) and treated
with nanatinostat (100 nM), romidepsin (40 nM), N-803 (400 ng/ml), or DMSO (0.001%) for 24 h. On day
3, CD4
⫹
T cells were infected with JRCSF at a multiplicity of infection of 0.01 for 3 h at 37°C, and the virus
was washed well. CD8
⫹
T cells were washed well before being cocultured in duplicate with autologous
CD4
⫹
T cells at an effector-to-target ratio of 4:1 in the absence of ARVs to allow for viral replication. The
supernatant was harvested at days 3 and 7 postinfection for p24 ELISAs (NCI, Frederick, MD). Cells were
harvested on day 7, stained with Aqua LIVE/DEAD viability dye (Thermo Fischer Scientific) and anti-CD3,
-CD4, and -CD8 prior to cell permeabilization and intracellular staining with antibodies against HIV-1 Gag
(KC57- RD1; Beckman Coulter), and analyzed by flow cytometry.
Statistical methods. GraphPad PRISM version 7 software was used for statistical analyses.
ACKNOWLEDGMENTS
We thank the participants living with HIV-1 who have donated samples through
leukapheresis. We thank Steven Yukl and Sushama Telwatte for their help with the
HIV-1 RNA ddPCRs. The following reagents were obtained from the NIH AIDS Research
and Reference Reagent Program at no cost: IL-2 and pJRCSF.
This work was supported by the NIH-funded R01 awards AI131798 (R.B.J.) and
AI147845 (R.B.J.). It was also supported in part by the Martin Delaney BELIEVE Collabo-
ratory (NIH grant 1UM1AI26617), which is supported by the following cofunding and
participating institutes and centers: the NIAID, NCI, NICHD, NHLBI, NIDA, NIMH, NIA, FIC,
and OAR.
R.B.J. and T.M.M. conceptualized the study. R.B.J., T.M.M., C.D.M., and S.-H.H. devel-
oped the methodology. R.B.J., T.M.M., C.D.M., A.D., S.-H.H., D.B.M., L.L., T.M.R., and Y.R.
conducted the investigation. R.B.J., E.B., C.C.K., and W.D.H. provided resources. T.M.M.
and R.B.J. wrote the manuscript, which was reviewed by all authors. R.B.J. acquired
funding. R.B.J. supervised the study.
R.B.J. declares that he has received payments for his role on the scientific advisory
board of AbbVie Inc. J.T.S. is an employee of NantKwest, Inc., which assisted in the
provision of N-803 via ImmunityBio. L.M. received an honorarium from Giliad in 2019 for
participation on its HIV Prevention Advisory Board.
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