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Downregulation of miRNA-26a by HIV-1 Enhances CD59 Expression and Packaging Impacting Virus Susceptibility to Antibody-Dependent Complement-Mediated Lysis

A peer-reviewed version of this preprint was published in:
Viruses 2024, 16(7), 1076. https://doi.org/10.3390/v16071076

Submitted:

04 June 2024

Posted:

05 June 2024

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Abstract
MicroRNAs (miRNAs) play important roles in the control of HIV-1 infection. Here, we performed RNAseq profilings of miRNAs and mRNAs expressed in CD4+ T-lymphocytes upon HIV-1 infection. Our results reveal significant alterations of miRNAs and mRNAs expression profiles in infected relative to uninfected cells. One of the miRNAs markedly downregulated in infected cells is miRNA-26a. Among the putative targets of miRNA-26a are CD59 receptor transcripts, which are significantly upregulated in infected CD4+ T-cells. Addition of miRNA-26a mimics to CD4+ T-cells reduces CD59 at both mRNA and surface protein levels, validating CD59 as a miRNA-26a target. Consistent with the reported inhibitory role of CD59 in complement-mediated lysis (CML), knocking-out CD59 in CD4+ T-cells renders both HIV-1 infected cells and progeny virions more prone to antibody-dependent CML (ADCML). Addition of miRNA-26a mimics to infected cells leads to enhanced sensitivity of progeny virions to ADCML, a condition linked to a reduction of CD59 packaging into released virions. Lastly, HIV-1-mediated downregulation of miRNA-26a expression is shown to be dependent on integrated HIV-1 expression but does not involve viral accessory proteins. Overall, these results highlight a novel mechanism by which HIV-1 limits ADCML by upregulating CD59 expression via miRNA-26a downmodulation.
Keywords: 
CD59
;  
HIV-1
;  
complement- mediated lysis
;  
miRNA-26a
;  
innate immunity
;  
viral evasion
Subject: 
Biology and Life Sciences  -   Virology

1. Introduction

The identification of host and viral determinants that govern human immunodeficiency virus type 1 (HIV-1) transmission and infection is critical for the development of effective targeted prevention and therapeutic approaches. Following infection by a transmitter founder (T/F) virus, a humoral response is rapidly established with mostly non-neutralizing antibodies (Abs) being directed against HIV-1 envelope glycoproteins (Env, gp120 and gp41) [1,2,3]. Neutralizing Abs specific for the T/F virus then promptly emerge; however, these autologous neutralizing Abs, which target highly variable regions of the Env, rapidly select virus-escape mutants that in turn induce new Ab specificities [4,5,6]. The ensuing Ab-virus “arms race” leads after years of infection to the induction of broadly neutralizing antibodies (bNAbs) in only 10-25% of chronically-infected individuals, which target highly conserved Env regions and have higher and broader neutralizing potency [7]. While the host humoral response exerts an immune pressure directly on replicating viruses, the binding of Abs to Env epitopes can also lead to activation of the classical complement pathway, a process that results in lysis of infected cells and virions [8].
Complement can be activated by three canonical mechanisms, designated as the classical, alternative and lectin pathways [9]. Ultimately, all three pathways lead to the formation of the membrane attack complex (MAC) as well as the formation of anaphylatoxins, which contribute to inflammation by attracting leukocytes to the site of infection [10]. Among the complement regulatory proteins that are present at the surface of human cells is CD59, a glycosyl-phosphatidylinositol (GPI)-linked cellular receptor, which prevents the polymerization of component 9 (C9) and thus inhibits the formation of MAC [11,12]. Interestingly, HIV-1 has been shown to incorporate CD59 and other complement regulatory proteins, such as CD55, into its viral envelope during the budding process, a condition that confers protection against complement-mediated lysis (CML) [13,14]. While antibody-dependent mediated complement activity directed against HIV-1 virions is detected during acute infection [15,16], it remains unclear whether HIV-1 has evolved to limit this host antiviral response.
MicroRNAs (miRNAs) are small single-stranded non-coding RNA molecules (containing about 22 nucleotides) encoded by plants, mammals, and even viruses. They are involved in post-transcriptional regulation of gene expression and RNA silencing [17]. MiRNAs work by base pairing with complementary sequences in the target mRNA, primarily in the 3′ untranslated region (UTR). As a result, the targeted mRNA is silenced by one or more mechanisms, including mRNA cleavage and mRNA translation blockage by ribosomes [18]. Host miRNAs have been shown to play a key role during HIV-1 infection by regulating cellular factors that govern the susceptibility or the resistance of target cells to viral infection [19]. For instance, upregulation of miRNAs-221/222 inhibits HIV-1 infection by downregulating the virus primary CD4 receptor in lymphocytes as well as in monocyte-derived macrophages (MDMs) [20,21]. More recently, we provided evidence that the p53-regulated miRNA-103 participates in the downmodulation of CCR5 in macrophages [22] as well as during different stages of CD4+ T-cell differentiation [23], thus regulating the process of HIV-1 entry into these cells. MiRNAs can also regulate HIV-1 infection at post-entry steps as shown for miRNA-181, which targets the restriction factor SAMHD1 in monocytes [24]. This is also the case of miRNA-155, which promotes HIV-1 latency by targeting the E3 ubiquitin ligase TRIM32 that activates NF-κB [25].
In the context of HIV-1 infection, a large number of host factor-targeting miRNAs identified so far are upregulated and modulate the permissiveness of target cells to productive infection by downregulating the expression of HIV-1-dependency or restriction factors. In this study, we performed a global transcriptomic analysis of HIV-1 infected primary CD4+ T-cells and compared their miRNA and mRNA profiles with uninfected cells. Our results reveal a significant differential expression of both miRNAs and mRNAs in infected relative to uninfected cells. Among the miRNAs analyzed, we show that miRNA-26a is downregulated in infected cells and further identity the MAC regulatory CD59 receptor as a target of this miRNA, which indeed is found upregulated. Accordingly, we document that enhancing miRNA-26a in HIV-1 infected cells reduces CD59 expression and packaging into virions, a condition that impacts their susceptibility to antibody-dependent complement-mediated lysis (ADCML). These results underscore the role of miRNA-26a in regulating CD59 expression levels in CD4+ T-cells and highlight how the modulation of miRNA-26a may affect HIV-1 susceptibility to ADCML by regulating the extent of CD59 packaging into HIV-1 virions.

2. Methods

3. Results

3.1. HIV-1 Alters the miRNA and mRNA Expression Profiles during Infection of CD4+ T-Cells

In order to identify miRNAs and mRNAs that are modulated upon HIV-1 infection, CD4+ T-lymphocytes were isolated from peripheral blood mononuclear cells (PBMCs) of 3 blood donors and infected for 48h with green fluorescent protein (GFP)-marked HIV-1 (CCR5-tropic NL4.3-ADA-GFP). Infected cells (GFP-positive) were then enriched by flow cytometry sorting (Figure S1) and total RNAs extracted. RNAs from mock-infected CD4+ T-cells (uninfected) were used as control. MiRNA and mRNA expression profiles in uninfected and GFP-positive CD4+ T-lymphocytes were then assessed by next-generation RNAseq (Figure 1). MiRNAs or mRNAs with a log2 fold change (Fc) of >0.585 (Fc= ~1.5) and a computed (using DeSeq2) base mean >100 were deemed upregulated whereas those with a log2Fc <-0.585 were considered downregulated. GFP-positive infected cells displayed a distinct profile of cellular mRNAs as compared to uninfected cells, with 188 upregulated and 34 downregulated genes (Figures 1A and S2). Gene ontology analyses (using g:Profiler, https://biit.cs.ut.ee/gprofiler/gost) of the most differentially-expressed genes (both upregulated and downregulated) revealed a predominance of genes involved in signal transduction, immune system process, immune and defense response, inflammatory response, programmed cell death as well as response to stress and virus (Figure 1B). Interestingly, comparative analyses of the miRNAseq profiles of GFP-positive cells with that of uninfected cells identified 17 upregulated and 20 downregulated miRNAs (Figure 1C), indicating that productive infection of CD4+ T-cells impacted also the cellular miRNA expression profile. Our analyses identified several miRNAs whose expression was previously reported to be modulated upon HIV-1 infection (Figure 1D). For instance, miRNA-181, a miRNA which is known to target the restriction factor SAMHD1, is upregulated in infected cells [24]. Similarly, miRNA-25, a miRNA that we recently found to target peroxisomes components [26] as well as the E3 ubiquitin ligase MARCH1 [27] is similarly increased in infected CD4+ T-cells. In contrast, we found that some miRNAs, such as miRNA-16, were downregulated in GFP-positive CD4+ T-cells (Figure 1D). MiRNA-16 was previously reported to target Pur-⍺, a DNA and RNA binding protein that promotes Tat-induced transactivation [28].

3.2. Analyses of mRNA and miRNA Profiles in Infected CD4+ T-Cells Link CD59 Upregulation to a Decrease of Putative Targeting miRNAs

Among the 34 genes whose mRNA levels were downregulated in GFP-positive compared to uninfected cells, we identified several genes potentially relevant to HIV-1 infection based on the reported literature (Figure 2A). For example, Transactive Response DNA-binding protein (TARDBP/TDP-43) encodes a protein that regulates cell permissivity to HIV-1 infection by acting as a transcriptional repressor of HIV-1 gene expression through histone deacetylase 6 (HDAC6) [29], which is also a negative regulator of the APOBEC3G restriction factor [30] (log2fc = -0.58). NOL12 encodes for a RNA binding protein that plays an important role in repairing DNA damage pathways and maintaining genome integrity, although its effect on HIV-1 infection remains unclear [31] (log2fc = -0.59). On the other hand, among the 188 genes which mRNA levels were upregulated, we also identified cellular genes relevant to HIV-1 infection. For instance, BCL2L11 (or BIM), which encodes for Bcl2, a regulator of pro-apoptotic signaling in HIV-1 infection [32] (log2fc = 0.63); PLD1, which encodes for Phospholipase D1, an enzyme that links T-cell activation signals to increased cell permissivity to HIV-1 infection [33] (log2fc = 0.64), and FOXP3, which encodes for a marker of regulatory CD4+ T-cells [34] (log2fc = 0.85) all displayed an upregulated expression in GFP-positive cells (Figure 2A). Noticeably, CD59, which encodes for a GPI-linked membrane protein receptor that has a key inhibitory role in regulating complement activation [11,12], was also found to show a significant upregulation of its expression in GFP-positive cells (log2fc = 0.88) (Figure 2A). Indeed, CD59 was also found to be among the genes in 9 of the upregulated ontology pathways that we identified (Figures 1B, left panel, and 2B). To assess whether the upregulation of CD59 mRNA was linked to the downregulation of specific miRNAs, we first identified the miRNAs that were the most downregulated in GFP-positive cells (Figure 2C). Online databases-directed analyses (mirDIP, http://ophid.utoronto.ca/mirDIP/), singled-out three potential miRNAs that could target CD59 mRNA (Figure 2C and D): miRNA-21 (log2fc = -1.62), miRNA-26a (log2fc = -1.11) and miRNA-29a (log2fc = -1.84). Further validation of the miRNA-seq data using real-time qPCR revealed that miRNAs-21, -26a and -29a are indeed decreased in HIV-1-infected primary CD4+ T-cells as compared to uninfected cells (~ 6-, 2- and 4-fold less, p=0.0003, p=0,0484, p=0.0020, respectively) (Figure 3A). We also validated the mRNA-seq data and found that CD59 mRNA levels are indeed increased in GFP-positive relative to uninfected primary CD4+ T-cells (FC=2.1-fold, p value = 0.0022) (Figure 3B). Furthermore, flow cytometry analyses indicated that HIV-1 infected CD4+ T-lymphocytes expressed 1.5-2.0 times more CD59 protein at their cell surface as compared to uninfected cells (Figure 3C). Taken together, these results indicate that HIV-1 infection of CD4+ T-cells induces an upregulation of CD59 receptor at the mRNA and cell-surface protein levels and this condition appears to be linked to a downregulation of miRNAs, namely miRNA-21, -26a and 29a, predicted to target CD59.

3.3. CD59 Is a Target of miRNA-26a

To evaluate the impact of these miRNAs on the levels of CD59 mRNA and surface protein expression levels, we nucleofected either miRNA-21, -26a and -29a mimics into primary CD4+ T-cells. Transfection of miRNA-26a mimics significantly decreased CD59 mRNA levels after 48h (~ 2-fold less, p = 0.0065) and CD59 protein surface expression 96h post-nucleofection (approximately 50%, p = 0.0285) when compared to controls (Figure 4A and B). Neither miRNA-21 nor miRNA-29a mimics had a significant effect on CD59 mRNA expression levels. Consistently, we confirmed that miRNA-21 mimics had no effect on CD59 surface expression levels (Figure 4A and B). These results suggest that CD59 expression can be downregulated by miRNA-26a but not by miRNA-21 or -29a in CD4+ T-cells.
An online database (TargetScanHuman, www.targetscan.org) analysis predicted that the 3′UTR of CD59 mRNA could be targeted by miRNA-26a at two potential sites (Figure 4C). To validate whether these sites were targeted by miRNA-26a, we transiently expressed a construct encoding the Firefly Luciferase (F-Luc) gene fused to a 429 base pair fragment of the 3′UTR encompassing the two potential target sites (A+B-WT) in HEK293T cells. These cells were also co-transfected with miRNA-26a or control mimics. F-Luc activity in the cell lysates was significantly reduced in cells transfected with miRNA-26a mimics (~ 2-fold less, p=0.0338) when compared to control (Figure 4D). Furthermore, mutations in the CD59 3′UTR sequences predicted to be targeted by miRNA-26a (Figure 4C, A+B-Mut) prevented the silencing effect on F-Luc (Figure 4D). We also tested in this system two different CD59 3′UTR fragments (A and B) (Figure 4C), each containing one of the two single individual sites targeted by miRNA-26a and found that both sites are functional and independent (Figure 4D). Altogether, these data further validate that miRNA-26a can regulate CD59 expression levels by targeting two specific sites complementary to the miRNA-26a seed sequence located in the 3′UTR of CD59 mRNA.

3.4. CD59 affects the Susceptibility of HIV-1 to Antibody-Dependent Complement-Mediated Lysis

Given the critical inhibitory regulatory function of CD59 in CML and the fact that its expression is upregulated during HIV-1 infection of CD4+ T-lymphocytes, we examined the impact of CD59 expression on the susceptibility of HIV-1-infected cells and released virions to ADCML. To this end, we took advantage of a T lymphoblast CEM-CCR5 cell line [35] as a model for the regulation of CD59 by miRNA-26a. Indeed, upon HIV-1 infection of this cell line, we observed a downregulation of miRNA-26a expression (~ 2-fold less, p=0.0286) and a concomitant upregulation of CD59 mRNA (3.5-fold, p=0.0079) and surface protein levels (Figure S3A). We thus generated two CD59_knock-out (KO) clones of the CEM-CCR5 cell line (CEM-CD59_KO_clone 1 and CEM-CD59_KO_clone 2) using the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 technology as described in Methods. A CEM-CD59_control cell line in which the CRISPR/Cas9 guide sequence was absent was also generated. As shown in Figure S3B, both CEM-CD59_KO clones exhibited a marked reduction of total as well as cell-surface CD59 expression levels as compared to the control cell line. Neither cell proliferation, nor CD4/CCR5 HIV-1 receptor levels, were affected by knocking-out CD59 in the CEM-CCR5 cell line (Figure S3C).
We next assessed the susceptibility of these cell lines to ADCML using PGT121, a bNAb that targets a V3-glycan-dependent epitope on HIV-1 gp120 [36], as a model Ab in this system. Control or CEM-CD59_KO cells infected at comparable infection frequencies were exposed to PGT121 in the presence of normal human serum (NHS), as a source of active complement, or in the presence of heat-inactivated human serum (HIHS) as control. The percentage of dead cells in the GFP-positive cells (based on Zombie NIR fluorescence) was measured by flow cytometry. In the presence of NHS, infected CEM-CD59_KO cells were more susceptible to ADCML as compared to the CEM-CD59_control cells (Figure 5A, upper panels). This increased susceptibility of CEM-CD59_KO cells to ADCML was abolished in conditions using HIHS (Figure 5A, lower panels).
Knowing that CD59 is packaged into HIV-1 virions likely as a mean to protect viral particles from ADCML [13], we characterized the impact of CD59 packaging into released virions on their susceptibility to lysis. Using a virion capture-assay allowing for the detection of CD59-containing virions, we confirmed that infected CEM-CD59_KO cell lines produced virions with significantly reduced CD59 levels, as compared to viral particles produced from their control cell line counterpart (~6.5-fold less, p=0.285 for clone 1; ~5-fold less, p=0.0482 for clone 2) (Figure 5B). These results are consistent with the marked reduction of CD59 expression observed at the cell surface of the CEM-CD59_KO cell lines compared to the CEM-CD59_control (Figure S3B). HIV-1 virions released from CEM-CD59_KO and CEM-CD59_control cells were treated with PGT121 and either NHS or HIHS. RNA released from lysed virions was then digested by RNase treatment, and viral RNA from the remaining complement-mediated lysis-resistant intact virions was extracted and quantified by real-time PCR. As shown in Figure 5C, viruses produced from the CEM-CD59_KO cell lines were much more sensitive to ADCML (NHS conditions) than those produced from the control cell line (5.5-fold for clone 1 and 6.6-fold for clone 2, p=0.0022), confirming that packaging of CD59 into HIV-1 virions protects viruses from ADCML.

3.5. Enhanced Levels of miRNA-26a Promote ADCML of HIV-1 by Reducing CD59 Packaging into Released Virions

To specifically examine the impact of augmenting miRNA-26a levels during HIV-1 infection, we nucleofected primary CD4+ T-cells with miRNA-26a or control mimics and infected them with HIV-1. Figure 6A shows that transfection of miRNA-26a mimics does not interfere with viral replication as virus production was comparable between miRNA-26a and control mimics-treated cells. Using the virion capture-assay described above, we also confirmed that cells treated with miRNA-26a mimics produced approximately 50% less CD59-containing virions than their control-treated counterparts (~2-fold less, p=0.0079), suggesting that downregulation of CD59 expression by miRNA-26a leads to a reduced packaging of the protein into released virions (Figure 6B). Importantly, viruses produced from miRNA-26a mimic-treated cells displayed an enhanced susceptibility to PGT-121-dependent CML (NHS conditions) as compared to the control (3.1-fold, p=0.0022) (Figure 6C). These results suggest that a 50% modulation in CD59 expression and incorporation levels into released virus particles is sufficient to effectively affect their sensitivity to ADCML (Figures 4A-B and 6B). To further validate the result obtained with PGT121, we repeated these experiments using purified Abs from sera of viremic individuals (#163 and #497). We first confirmed that exposure of virus to purified Abs alone did not induce lysis of virions (Figure S4A). Viruses produced by cells treated with miRNA-26a mimics displayed an enhanced susceptibility to ADCML in the presence of Abs from sera #163 (2.1-fold, p=0.0260) or #497 (1.6-fold, p=0.0649) as compared to controls (Figure 6D). The results obtained with Abs from serum #163 were further validated using virus produced during infection of CEM-CD59 KO_clone 1 (Figure S4B); in this context, virus produced displayed a 4.4-fold increased susceptibility to ADCML as compared to control (Figure S4B). Taken together, these results show that CD59 expression and packaging into virions during infection of CD4+ T-cells can be downregulated by miRNA-26a, a condition that affects the susceptibility of released virions to ADCML. Based on these results, we infer that downregulation of miRNA-26a by HIV-1 is likely a mean to render infected cells and released virions more resistant to ADCML through optimal CD59 expression and packaging into virions.

3.6. The Downregulation of miRNA-26a during HIV-1 Infection of CD4+ T-lymphocytes Is Contingent on viral DNA Integration and Expression

We next analyzed the viral determinants that contribute to the downregulation of miRNA-26a expression in CD4+ T-lymphocytes during HIV-1 infection. To define the step of the infection cycle that is important for miRNA-26a expression downregulation, we treated cells with either the HIV-1 reverse transcriptase inhibitor, efavirenz (EFV), or the HIV-1 integrase inhibitor, raltegravir (RAL), prior to their infection with HIV-1. As shown in Figure 7A, we observed a downregulation of miRNA-26a in untreated infected GFP-positive sorted cells. However, treatment of cells with EFV or RAL abolished the downregulation, suggesting that integration of proviral DNA into the genome of target cells is a necessary step for miRNA-26a downregulation. In order to further validate these results, we used a fully replicative dual reporter virus system, which is very similar to a single-cycle dual reporter virus system that we previously described and characterized [23,37]. This fully infectious and replicative reporter virus system (HIV Nef-2A-CRIMZs) enables to distinguish cells harboring transcriptionally-inactive proviruses (ZsGreen positive, this reporter gene being under the control of an Elongation factor 1-alpha promoter) from cells that contain specifically transcriptionally-active integrated proviruses (both ZsGreen positive and E2-Crimson positive, the later reporter gene being under the control of the HIV-1 LTR). Indeed, we show that following treatment of infected cells with TNF-alpha as a virus latency reversing agent, the frequency of infected cells harboring a transcriptionally-inactive provirus (only ZsGreen positive; latent) was reduced and a concomitant increase in the frequency of infected cells with transcriptionally-active integrated provirus (both E2-Crimson/ZsGreen positive; productive) was detected (Figure S5A). Additionally, productively infected cells, which are predicted to express Nef and Vpu, were found to display, as expected, a downregulation of the CD4 receptor, a condition not observed in bystander cells or latently-infected cells (Figure S5B).
Analyses of miRNA expression in the different isolated populations of infected lymphocytes revealed that miRNA-26a expression levels were decreased in productively infected cells (~1.7-fold less, p=0.0015) but not in latently infected cells (Figure 7B). These results suggest that HIV-1 gene expression is necessary for the downregulation of miRNA-26a during infection. Given that HIV-1 accessory proteins, such as Vpu, have been reported to modulate the expression of miRNAs [26,27], we tested if their expression could impact miRNA-26a levels. To this end, CD4+ T- lymphocytes were infected with well-established and -characterized GFP-marked HIV-1 that are isogenic except for the expression of Nef, Vpu, Nef and Vpu, or Vpr [38,39,40]. As shown in Figure 7C, expression levels of miRNA-26 were downregulated in cells infected with the different mutant HIV-1 viruses to comparable extent than in cells infected with WT HIV-1, suggesting that reduction of miRNA-26a expression during HIV-1 infection appears independent of Vpr, Vpu or/and Nef expression. Given the important role of the Vif accessory protein in counteracting the potent restriction mediated by APOBEC3F/G on HIV-1 reverse transcription [41], we evaluated the effect of Vif on miRNA-26a expression in the CEM-SS cell line, which does not express APOBEC3F/G and is permissive to infection by Vif-defective viruses [42]. MiRNA-26a expression was found to be downregulated to the same extent in CEM-SS cells infected with WT virus (~1.8-fold less, p=0.0500) or Vif-deficient virus (~1.8-fold less, p=0.0500), suggesting that the reduction of miRNA-26a expression in HIV-1-infected cells is independent from Vif expression (Figure 7D). Taken together, our results indicate that while downregulation of miRNA26a during HIV-1 infection requires viral gene expression, this regulation does not appear to be dependent on HIV-1 accessory gene expression.

4. Discussion

In this study, we performed RNA-seq of miRNAs and mRNAs in HIV-1 infected CD4+ T-cells and further analyzed their expression profiles relative to uninfected cells (Figure 1). Since the miRNA and mRNA profiling was conducted simultaneously on the same sorted infected (GFP-positive) and mock-infected cells as a baseline reference allowed us to establish potential links between the degree of expression of specific candidate cellular genes and putative targeting miRNAs. We found that the infected cell population displayed important changes in the cellular transcriptomes and miRNA expression profiles in relation to the mock-infected population. Among the 222 cellular genes whose expression was either upregulated (188) or downregulated (34) (Figure S2), we identified through a systematic literature search several candidates that could have either positive or negative effects on HIV-1 replication or persistence (Figure 2A). To assess whether differentially-expressed genes in the infected population could be regulated by miRNAs, we cross-analyzed the most differentially expressed miRNAs and found that three of the most downregulated miRNAs, namely miRNA-29a, -21 and 26a, were predicted to target CD59 transcripts, which indeed were upregulated in infected cells (Figures 2, 3 and S2). CD59 is a cell-surface protein receptor that plays a negative regulatory role in the complement pathway and is incorporated in budding viruses, a condition that protects HIV-1 particles from ADCML [13]. These findings raised the possibility that HIV-1 is downmodulating the expression of these miRNAs to optimize the expression and packaging of CD59 as a mean to limit the activity of the host complement lysis pathway.
MiRNAs have been shown to play a key role not only in regulating target cell susceptibility to HIV-1 infection but also in promoting viral persistence [19]. Of the three miRNAs that were predicted to target CD59, further validation revealed that miRNA-26a was the only one that could target and regulate CD59 expression in CD4+ T-cells (Figure 4). MiRNA-26a is a member of the miRNA-26 family, which includes miRNA-26a and miRNA-26b. This family has previously been described to be involved in the regulation of muscle development [43] and glucose metabolism [44], but surprisingly little is known about its role in immune cell functions or innate immunity. Recently, a study showed that the miRNA-26 family plays a role in the early development and transformation of B lymphocytes, particularly in the differentiation of pre-B cells, although the mechanism behind this phenomenon is not fully elucidated [45].
Our results suggest that miRNA-26a regulates the expression of CD59 in CD4+ T-lymphocytes and its downregulation during HIV-1 infection leads to an upregulation of CD59 mRNA levels and surface protein expression (Figure 3 and Figure 4), conditions that are likely to increase its packaging into released virus particles. Knowing that CD59 incorporation into viral particles protects HIV-1 from CML activity, our results suggest an important role of miRNA-26a in regulating the susceptibility of HIV-1 to CML (Figure 5 and Figure 6). Since packaging of CD59 is not an exclusive property of HIV-1 as it has also been shown in other enveloped viruses [46,47], namely human T lymphotropic virus type 1 (HTLV-1), human cytomegalovirus (HCMV) and hepatitis virus type C (HCV), it would be interesting to assess whether these viruses promote CD59 packaging by downmodulating miRNA-26a during infection.
Our results show that MiRNA-26a expression levels are decreased in CD4+ T- cells upon HIV-1 infection and we provide evidence that this reduction requires the integration of the viral DNA into the genome of target cell as well as the expression of HIV-1 genes (Figure 7). However, expression of accessory proteins Vif, Vpr, Nef and Vpu do not appear to mediate the downregulation of miRNA-26a as viruses deficient for the expression of these viral proteins were still competent for downregulating miRNA-26a expression. These results suggest that other viral proteins such as Tat, Rev, the Env glycoproteins, or the products of the Gag and Gag-pol precursors might potentially be involved. Little is known about the direct regulators of miRNA-26a expression although previous reports have shown a double negative feedback loop between miRNA-26a and the negative transcriptional regulators EZH2 [48] and E2F7 [49].
HIV-1 is protected from CML by the incorporation of several complement regulatory proteins, such as CD46, CD55, and CD59, into viral particles [12]. CD59 controls the formation of the MAC at the terminal stage of the complement activation common to all known activation pathways [11], while CD55 prevents the formation of C3 convertases and C5 [50] and CD46 acts as an inactivator of C3b and C4b [51]. In this study, we provide evidence supporting the notion that HIV-1-mediated enhancement of CD59 cell-surface expression and packaging helps protect virions and infected cells from ADCML. Indeed, we show that knocking-down CD59 by CRISPR-Cas9 in target CD4+ T-cells enhances susceptibility of cells and virions to ADCML. These findings are collectively consistent with results obtained previously using Ab-mediated blockade of CD59 [52,53] as well as evidence that GPl-anchor deficiency, which leads to an absence of CD59 at the cell surface, renders released HIV-1 susceptible to complement attack [54]. Taken together, these results suggest that limiting CD59 expression or targeting its function at the cell surface of infected cells could represent an approach to restore optimal complement activation and increase the efficiency of Ab-mediated responses against HIV-1.
The ability to activate complement in response to HIV-1 infection is Ab-dependent. Indeed, Dufloo et al. showed that polyclonal Abs present in the sera of infected individuals trigger complement activation less effectively than bNAbs [55]. These observations are consistent with our results, which show a much greater ADCML on virions exposed to the bNAb PGT121 as compared to a pool of Abs purified from the sera of viremic individuals, which most likely target diverse epitopes (Figure 6). Furthermore, it is likely that the neutralizing activity of Abs present in the viremic patient sera tested is less significant than that of bNAbs, which development takes place late in the course of infection and only in a limited number of individuals [56]. Given that complement is activated by Ab hexamers assembled on the surface by Fc-Fc interactions [57], it is likely that the orientation of the Fc region as well as Ab density are critical factors for complement activation by a given bNAb. Indeed, Abs targeting the CD4 binding site or the V3 loop can bind up to 3 Fab fragments on an Env trimer, which would promote Fc-Fc interactions [58]. Altogether, these points could explain why a more efficient ADCML of virions was observed using PGT121 as compared to Abs purified from infected individual sera and could also explain the variability detected using Abs from the sera of the two viremic individuals (Figure 6).
In conclusion, our study identifies miRNA-26a as a post-transcriptional negative regulator of CD59 expression in CD4+ T-cells. Our results show that HIV-1 reduces the level of this miRNA during infection likely via the expression of a viral protein whose identity remains to be defined. We also provide evidence that the addition of exogenous miRNA-26a mimics to infected cells reduces the resistance of HIV-1 to ADCML. This miRNA is yet another example of a miRNA of which the modulation of expression allows HIV-1 to escape the host immune response and more specifically ADCML. This mechanism could be targeted to augment the potency of antibody-based preventive or therapeutic strategies against HIV-1.

Supplementary Materials

There are Supplementary figures (Figures S1-S5) and a supplementary Table S1 related to this work: Figure S1. Characterization of the infected cell populations used for the RNA-seq, related to Figure 1. Figure S2. List for genes for which mRNA expression levels are modulated in the GFP-positive population compared to Mock, related to Figure 1. Figure S3. Modulation of miRNA-26a and CD59 expression levels in HIV-1 infected CEM-CCR5 cells and characterization of CEM-CD59_KO cells, related to Figure 5. Figure S4. ADCML assay with antibodies purified from the sera of viremic individuals, related to Figure 6. Figure S5. Characterization of CD4+ T-cell subpopulations following infection with the dual reporter HIV Nef-2A-CRIMZs virus, related to Figure 7. Table S1 – Sequences of miRNAs mimics and oligonucleotides used in this study.

Author Contributions

N.B, R.L and E.A.C designed the study. N.B performed all experiments and C.Y contributed to the generation of plasmid constructs for the MIR-REPORT assays. N.B, R.L and E.A.C analyzed data. T.T.M and O.A provided the replicative dual reporter HIV-1 system. N.B, R.L and E.A.C wrote the manuscript. E.A.C secured funding.

Funding

This study was supported by Canadian Institutes of Health Research (CIHR) grants FDN-154324 and HB2-164064 (Canadian HIV Cure Enterprise-CanCURE 2.0) to E.A.C as well as by the Fonds de Recherche du Québec-Santé (FRQS)-funded Réseau SIDA/Maladies Infectieuses. E.A.C is the recipient of the IRCM-Université de Montréal Chair of Excellence in HIV Research.

Data Availability Statement

The online GEO accession numbers for the reported mRNA-seq and miRNA-seq data are GSE247191 (mRNA-seq) and GSE247194 (miRNA-seq), respectively.

Acknowledgments

The authors wish to thank all the study participants as well as IRCM Clinic staff for coordinating access to blood donors. We also thank Julie Lord and Eric Massicotte for their assistance for flow cytometry analyses, Odile Neyret and the IRCM Molecular Biology and Functional Genomics Core staff for their support with the Illumina technology and cDNA sequencing, and Virginie Calderon for her help with database bioinformatics analyses.The following reagents were obtained through the NIH HIV Reagent Program, Division of AIDS, NIAID, NIH: Monoclonal Anti-HIV-1 gp120 (PGT121) (ARP-12343), contributed by the International AIDS Vaccine Initiative; CEM.NKR CCR5+ cells (ARP-4376) contributed by Dr. Alexandra Trkola; ACH-2 Cells (ARP-349) contributed by Dr. Thomas Folks.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. RNA-seq mRNA and miRNA profiles in infected CD4+ T-cells compared to uninfected cells. (A) Volcano plot representing the differential expression (fc= fold change) of mRNAs in infected (GFP-positive, GFP-pos) CD4+ T-cells as compared to uninfected cells (Mock). The mRNAs with a log2Fc of >0.585 and a DeSeq2 base mean >100 are in red, while those with a log2Fc <-0.585 are in blue. (B) Graphs representing the upregulated (left panel) or downregulated (right panel) biological processes in infected (GFP-pos) as compared to uninfected cells (Mock) as determined by g:Profiler (https://biit.cs.ut.ee/gprofiler/gost). (C) Volcano plot representing the differential expression of miRNAs in infected (GFP-pos) CD4+ T-cells as compared to uninfected cells (Mock). Dots of upregulated miRNAs with a log2Fc of >0.585 and a DeSeq2 base mean >100 are in red, while those downregulated with a log2Fc <-0.585 are in blue. (D) The heatmap depicts the 37 miRNAs specifically dysregulated in the GFP-pos population detected in this study. The scale bar is in log2(Fc). MiRNAs with forms (1) and (2) are identical miRNAs produced by two distinct loci. See also Figures S1-S2.
Figure 1. RNA-seq mRNA and miRNA profiles in infected CD4+ T-cells compared to uninfected cells. (A) Volcano plot representing the differential expression (fc= fold change) of mRNAs in infected (GFP-positive, GFP-pos) CD4+ T-cells as compared to uninfected cells (Mock). The mRNAs with a log2Fc of >0.585 and a DeSeq2 base mean >100 are in red, while those with a log2Fc <-0.585 are in blue. (B) Graphs representing the upregulated (left panel) or downregulated (right panel) biological processes in infected (GFP-pos) as compared to uninfected cells (Mock) as determined by g:Profiler (https://biit.cs.ut.ee/gprofiler/gost). (C) Volcano plot representing the differential expression of miRNAs in infected (GFP-pos) CD4+ T-cells as compared to uninfected cells (Mock). Dots of upregulated miRNAs with a log2Fc of >0.585 and a DeSeq2 base mean >100 are in red, while those downregulated with a log2Fc <-0.585 are in blue. (D) The heatmap depicts the 37 miRNAs specifically dysregulated in the GFP-pos population detected in this study. The scale bar is in log2(Fc). MiRNAs with forms (1) and (2) are identical miRNAs produced by two distinct loci. See also Figures S1-S2.
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Figure 2. CD59 is predicted to be regulated in infected cells by three miRNAs. (A) Example of genes whose expression is dysregulated in infected cells (GFP-pos) compared to uninfected cells (Mock) and that are relevant in the context of HIV-1 infection based on the current literature. The Fc values indicated correspond to the values obtained based on the RNA-seq analysis. (B) Graph representing the upregulated gene ontology pathways (from Figure 1B, left panel) which include CD59. (C) Shown are the 10 most downregulated miRNAs in GFP-pos cells compared to Mock, ranked from most to least decreased. The Fc values indicated correspond to the values based on the RNA-seq analysis. (D) MiRNAs-21, -26a and 29a potentially target many dysregulated genes in GFP-pos cells, including CD59. Cross-referencing of miRNA and transcriptomic RNA data was performed using online databases (mirDIP, http://ophid.utoronto.ca/mirDIP/).
Figure 2. CD59 is predicted to be regulated in infected cells by three miRNAs. (A) Example of genes whose expression is dysregulated in infected cells (GFP-pos) compared to uninfected cells (Mock) and that are relevant in the context of HIV-1 infection based on the current literature. The Fc values indicated correspond to the values obtained based on the RNA-seq analysis. (B) Graph representing the upregulated gene ontology pathways (from Figure 1B, left panel) which include CD59. (C) Shown are the 10 most downregulated miRNAs in GFP-pos cells compared to Mock, ranked from most to least decreased. The Fc values indicated correspond to the values based on the RNA-seq analysis. (D) MiRNAs-21, -26a and 29a potentially target many dysregulated genes in GFP-pos cells, including CD59. Cross-referencing of miRNA and transcriptomic RNA data was performed using online databases (mirDIP, http://ophid.utoronto.ca/mirDIP/).
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Figure 3. Validation of the differential expression of predicted CD59-targeting miRNAs (miRNA-21, miRNA-26a and miRNA-29a) and CD59 upon HIV-1 infection. Expression levels of MiRNA-21, -26a and -29a (A) and CD59 mRNA (B) in uninfected (Mock) and productively infected (GFP-pos) CD4+ T-cells (n = 6) were measured by real-time qPCR. Shown are the mean fold changes compared to uninfected cells (in gray, which is set at 1). Error bars represent standard error of the mean (SEM). Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (C) CD59 cell-surface expression was evaluated by flow cytometry and the mean fluorescent intensity (MFI) was compared between uninfected (Mock) and infected CD4+ T-cells (GFP-positive) obtained from healthy blood donors. Error bars represent SEM (n=3).
Figure 3. Validation of the differential expression of predicted CD59-targeting miRNAs (miRNA-21, miRNA-26a and miRNA-29a) and CD59 upon HIV-1 infection. Expression levels of MiRNA-21, -26a and -29a (A) and CD59 mRNA (B) in uninfected (Mock) and productively infected (GFP-pos) CD4+ T-cells (n = 6) were measured by real-time qPCR. Shown are the mean fold changes compared to uninfected cells (in gray, which is set at 1). Error bars represent standard error of the mean (SEM). Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (C) CD59 cell-surface expression was evaluated by flow cytometry and the mean fluorescent intensity (MFI) was compared between uninfected (Mock) and infected CD4+ T-cells (GFP-positive) obtained from healthy blood donors. Error bars represent SEM (n=3).
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Figure 4. – CD59 mRNA is a target of miRNA-26a. (A) CD59 mRNA levels were measured in miRNA-21, -26a and -29a mimics or control-nucleofected primary CD4+ T-cells by real-time qPCR. Shown is the mean fold change compared to control transfected cells (in gray, which is set at 1) (n = 4). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: **p < 0.01. (B) CD59 surface expression was evaluated in miRNA-21, -26a mimics or control-nucleofected primary CD4+ T-cells by flow cytometry. Shown is the cell surface expression of CD59 from CD4+ T-cells of four blood donors (normalized to CTRL which was set at 100%) with a representative result on the left (MFI are shown). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: *p < 0.05. (C) The MIR-Report system was used to validate whether the CD59 3′UTR was a target of miRNA-26a. MiRNA blue nucleotides represent those predicted to interact with the CD59 3′UTR. WT or mutated (substituted nucleotides in green) fragments of the 3′UTR encompassing the predicted sequences recognized by miRNA-26a were fused to the F-Luciferase (F-Luc) gene. (D) HEK293T cells were transfected with miRNA-26 mimics, the reporter plasmids with the indicated fragment of the WT (in yellow) or mutated (in black) 3′ UTR, and a Renilla-Luciferase (R-Luc) normalizing control. Following cell lysis, relative light units (RLUs) were measured and F-Luc normalized to negative control (in grey, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: *p < 0.05.
Figure 4. – CD59 mRNA is a target of miRNA-26a. (A) CD59 mRNA levels were measured in miRNA-21, -26a and -29a mimics or control-nucleofected primary CD4+ T-cells by real-time qPCR. Shown is the mean fold change compared to control transfected cells (in gray, which is set at 1) (n = 4). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: **p < 0.01. (B) CD59 surface expression was evaluated in miRNA-21, -26a mimics or control-nucleofected primary CD4+ T-cells by flow cytometry. Shown is the cell surface expression of CD59 from CD4+ T-cells of four blood donors (normalized to CTRL which was set at 100%) with a representative result on the left (MFI are shown). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: *p < 0.05. (C) The MIR-Report system was used to validate whether the CD59 3′UTR was a target of miRNA-26a. MiRNA blue nucleotides represent those predicted to interact with the CD59 3′UTR. WT or mutated (substituted nucleotides in green) fragments of the 3′UTR encompassing the predicted sequences recognized by miRNA-26a were fused to the F-Luciferase (F-Luc) gene. (D) HEK293T cells were transfected with miRNA-26 mimics, the reporter plasmids with the indicated fragment of the WT (in yellow) or mutated (in black) 3′ UTR, and a Renilla-Luciferase (R-Luc) normalizing control. Following cell lysis, relative light units (RLUs) were measured and F-Luc normalized to negative control (in grey, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: *p < 0.05.
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Figure 5. Reduction of CD59 expression in HIV-1 infected cells and decreased packaging of CD59 in released virions enhance their susceptibility to ADCML. (A) The level of dead cells in GFP-positive populations was measured by flow cytometry and compared between CEM-CD59_Control or CEM-CD59_KO cells exposed to the indicated conditions (PGT121 + normal human serum (NHS) and PGT121 + heat-inactivated human serum (HIHS)). Shown are data for one representative experiment (n=2). (B) Detection of CD59 incorporation in virions produced from HIV-1-infected CEM-CD59_control or CEM-CD59_KO cells by Ab capture assay. Equal amounts of virus released from each cell line was analyzed. Data shown indicate the mean levels of CD59-containing virus as measured by ELISA for p24 (pg/ml) following lysis of anti-CD59 bead-associated virus (background capture with the isotypic control was subtracted). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: *p < 0.05. (C) Shown are the normalized total HIV-1 copies of PGT121-treated viruses (with either NHS or HIHS) from CEM-CD59_control or CEM-CD59_KO infected cells as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean HIHS condition, which is set at 100%. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. In all conditions, equal amounts of virus released from each cell line was analyzed. See also Figure S3.
Figure 5. Reduction of CD59 expression in HIV-1 infected cells and decreased packaging of CD59 in released virions enhance their susceptibility to ADCML. (A) The level of dead cells in GFP-positive populations was measured by flow cytometry and compared between CEM-CD59_Control or CEM-CD59_KO cells exposed to the indicated conditions (PGT121 + normal human serum (NHS) and PGT121 + heat-inactivated human serum (HIHS)). Shown are data for one representative experiment (n=2). (B) Detection of CD59 incorporation in virions produced from HIV-1-infected CEM-CD59_control or CEM-CD59_KO cells by Ab capture assay. Equal amounts of virus released from each cell line was analyzed. Data shown indicate the mean levels of CD59-containing virus as measured by ELISA for p24 (pg/ml) following lysis of anti-CD59 bead-associated virus (background capture with the isotypic control was subtracted). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: *p < 0.05. (C) Shown are the normalized total HIV-1 copies of PGT121-treated viruses (with either NHS or HIHS) from CEM-CD59_control or CEM-CD59_KO infected cells as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean HIHS condition, which is set at 100%. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. In all conditions, equal amounts of virus released from each cell line was analyzed. See also Figure S3.
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Figure 6. Enhanced expression of miRNA-26a during HIV-1 infection renders released virions more susceptible to ADCML. (A) Primary CD4+ T-cells were nucleofected with miRNA-26a or a miRNA-control mimics for 72h and infected with HIV-1 for 48h (n=3). Data shown indicate the total HIV-1 produced (as RNA copy numbers of HIV-1) from infected cells as measured by real-time qPCR, following reverse transcription of viral RNA. Error bars represent SEM. (B) Detection and quantification of CD59-containing virus particles by Ab-capture assay of virions produced by infected cells transfected with miRNA-26a or negative control mimics. The left panel indicates the mean level of CD59-containing virus as determined by p24 ELISA (pg/ml) after lysis of virus captured with CD59-antibody-conjugated beads (the capture assay background obtained with the isotypic Ab control was subtracted). The right panel indicates the mean level of CD59-containing virus normalized to the value obtained with the control mimic condition (set at 100%). In all conditions, equal amounts of virus were analyzed. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (C) Shown are the normalized total HIV-1 copy numbers of PGT-121-treated viruses from infected cells transfected with either miRNA-26a or negative control mimics, as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean of those obtained with HIHS-treated viruses, which were set at 100%. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (D) Shown are the normalized total HIV-1 copy numbers of Ab-treated viruses from infected cells transfected with miRNA-26a or negative control mimics as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean of those obtained with HIHS-treated viruses, which were set at 100%. Abs were purified from sera of viremic individuals #163 (left panel) or #497 (right panel). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: *p < 0.05, ** p < 0.01. In all conditions, equal amounts of virus were analyzed. See also Figure S4.
Figure 6. Enhanced expression of miRNA-26a during HIV-1 infection renders released virions more susceptible to ADCML. (A) Primary CD4+ T-cells were nucleofected with miRNA-26a or a miRNA-control mimics for 72h and infected with HIV-1 for 48h (n=3). Data shown indicate the total HIV-1 produced (as RNA copy numbers of HIV-1) from infected cells as measured by real-time qPCR, following reverse transcription of viral RNA. Error bars represent SEM. (B) Detection and quantification of CD59-containing virus particles by Ab-capture assay of virions produced by infected cells transfected with miRNA-26a or negative control mimics. The left panel indicates the mean level of CD59-containing virus as determined by p24 ELISA (pg/ml) after lysis of virus captured with CD59-antibody-conjugated beads (the capture assay background obtained with the isotypic Ab control was subtracted). The right panel indicates the mean level of CD59-containing virus normalized to the value obtained with the control mimic condition (set at 100%). In all conditions, equal amounts of virus were analyzed. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (C) Shown are the normalized total HIV-1 copy numbers of PGT-121-treated viruses from infected cells transfected with either miRNA-26a or negative control mimics, as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean of those obtained with HIHS-treated viruses, which were set at 100%. Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (D) Shown are the normalized total HIV-1 copy numbers of Ab-treated viruses from infected cells transfected with miRNA-26a or negative control mimics as measured by real-time qPCR, following reverse transcription of viral RNA. Values are normalized relative to the mean of those obtained with HIHS-treated viruses, which were set at 100%. Abs were purified from sera of viremic individuals #163 (left panel) or #497 (right panel). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: *p < 0.05, ** p < 0.01. In all conditions, equal amounts of virus were analyzed. See also Figure S4.
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Figure 7. Analyses of HIV-1 determinants regulating miRNA-26a expression during infection. (A) Primary CD4+ T-cells were pretreated with efavirenz (EFV – 10μM) or raltegravir (RAL - 20μM), infected with NL4.3-ADA-GFP (WT) and their total RNA was extracted. MiRNA-26a levels in uninfected, infected GFP-positive and EFV- or RAL-treated cells were measured by real-time qPCR (n = 5). Shown are the mean fold changes compared to uninfected cells (gray histogram, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (B) Primary CD4+ T-cells were infected with the dual reporter HIV Nef-2A-CRIMZs viruses, which allows the distinction between cells harboring LTR-directed active transcription (E2-Crimson-positive/ZsGreen-positive) from cells harboring LTR-directed inactive transcription (E2-Crimson-negative and ZsGreen-positive cells). The different cell populations were sorted, and their total RNA was extracted. MiRNA-26a expression levels in uninfected (mock), productively, and latently infected CD4+ T-cells were measured by real-time qPCR (n = 6). Shown are the mean fold changes compared to uninfected cells (in gray, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: **p < 0.01. (C) Primary CD4+ T-cells were infected with the indicated mutant NL4.3-ADA-GFP viruses and their RNA was extracted 48h post-infection. MiRNA-26a expression in uninfected (mock) and infected GFP-positive cells were measured by real-time qPCR (n = 5). Shown are the mean fold changes compared to mock (gray histogram, which is set at 1). Error bars represent SEM. (D) CEM-SS cells were infected with NL4.3-ADA-GFP (WT) or NL4.3-ADA-GFP (ΔVif) and their RNA extracted 48h post-infection. MiRNA-26a expression levels in uninfected (mock) and infected cells were measured by real-time qPCR (n = 3). Shown are the mean fold change compared to mock (in gray, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann Whitney’s test, values: *p < 0.05. See also Figure S5.
Figure 7. Analyses of HIV-1 determinants regulating miRNA-26a expression during infection. (A) Primary CD4+ T-cells were pretreated with efavirenz (EFV – 10μM) or raltegravir (RAL - 20μM), infected with NL4.3-ADA-GFP (WT) and their total RNA was extracted. MiRNA-26a levels in uninfected, infected GFP-positive and EFV- or RAL-treated cells were measured by real-time qPCR (n = 5). Shown are the mean fold changes compared to uninfected cells (gray histogram, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann-Whitney’s test, values: **p < 0.01. (B) Primary CD4+ T-cells were infected with the dual reporter HIV Nef-2A-CRIMZs viruses, which allows the distinction between cells harboring LTR-directed active transcription (E2-Crimson-positive/ZsGreen-positive) from cells harboring LTR-directed inactive transcription (E2-Crimson-negative and ZsGreen-positive cells). The different cell populations were sorted, and their total RNA was extracted. MiRNA-26a expression levels in uninfected (mock), productively, and latently infected CD4+ T-cells were measured by real-time qPCR (n = 6). Shown are the mean fold changes compared to uninfected cells (in gray, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Kruskal Wallis test, values: **p < 0.01. (C) Primary CD4+ T-cells were infected with the indicated mutant NL4.3-ADA-GFP viruses and their RNA was extracted 48h post-infection. MiRNA-26a expression in uninfected (mock) and infected GFP-positive cells were measured by real-time qPCR (n = 5). Shown are the mean fold changes compared to mock (gray histogram, which is set at 1). Error bars represent SEM. (D) CEM-SS cells were infected with NL4.3-ADA-GFP (WT) or NL4.3-ADA-GFP (ΔVif) and their RNA extracted 48h post-infection. MiRNA-26a expression levels in uninfected (mock) and infected cells were measured by real-time qPCR (n = 3). Shown are the mean fold change compared to mock (in gray, which is set at 1). Error bars represent SEM. Statistical significance was determined by the nonparametric Mann Whitney’s test, values: *p < 0.05. See also Figure S5.
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