Induction of tolerogenicity following a molecular dialogue between HTLV-1-infected T cells and dendritic cells

Induction of tolerogenicity following a molecular dialogue between HTLV-1-infected T cells and dendritic cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Induction of tolerogenicity following a molecular dialogue between HTLV-1-infected T cells and dendritic cells Hélène Dutartre, Auriane Carcone, Franck Mortreux, Sandrine Alais, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4413764/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Manipulation of immune cell functions, independently of direct infection of these cells, emerges as a key process in viral pathophysiology. Chronic infection by Human T-cell Leukemia Virus type 1 (HTLV-1) is associated with immune dysfunctions, including misdirected responses of dendritic cells (DCs). Here, we interrogate the ability of HTLV-1-infected T cells to indirectly manipulate human DC functions. We show that upon coculture with chronically infected T cells, monocyte-derived DCs (MDDCs) fail to fully mature. We further show that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs, which differs from a typical maturation program, and which is correlated with a dampened ability of HTLV-1-exposed MDDCs to subsequently respond to restimulation. Induction of this tolerogenic behavior is not strictly dependent on capture of HTLV-1 viral particles by MDDCs, nor on cell-cell contacts between HTLV-1-infected T cells and MDDCs, but is instead the result of a molecular dialogue between HTLV-1-infected T cells and MDDCs upon coculture, illustrating how HTLV-1 might indirectly induce a local tolerogenic immune microenvironment suitable for its own persistence. Biological sciences/Microbiology/Virology/HTLV Biological sciences/Immunology/Infectious diseases/Viral infection Biological sciences/Immunology/Innate immune cells/Dendritic cells Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Chronic infection by the deltaretrovirus Human T-cell Leukemia Virus type 1 (HTLV-1) generally remains asymptomatic, but leads to severe diseases in 5 to 10% of infected individuals 1 , in the form of Adult T-cell Leukemia/Lymphoma (ATL), or Tropical Spastic Paraparesis/HTLV-1 Associated Myelopathy (TSP/HAM). Remarkably, HTLV-1 chronic infection increases the risk of viral, bacterial or parasitic co-infections 2 . In agreement with these clinical observations, immune dysfunctions have been repeatedly reported in asymptomatic HTLV-1 carriers, years before severe diseases were diagnosed, indicating that chronic infection induces systemic effects and impairs the ability of the immune system to respond appropriately to infectious and non-infectious triggers 3 – 7 . Dendritic cells (DCs) are critical mediators of innate and adaptive immune responses during viral infection. Upon efficient viral recognition, DCs undergo a maturation program that renders them capable of inducing specific T-cell responses. The DC maturation process is characterized by a transcriptional program that translates, among others, in the upregulation of several maturation markers at the cell surface ( e.g. CD80, CD86), accompanied by the secretion of pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α), and antiviral cytokines such as type I interferons (IFN-I) 8 . However, inappropriate DC responses can contribute to immunopathology, a process that is exacerbated in chronic viral infections 9 . The role of DCs in HTLV-1 infection has been extensively investigated in terms of viral transmission to CD4 + T cells, both in vitro 10 – 12 and in animal models 13 , 14 . Whether HTLV-1 induces the maturation of DCs has been investigated in vitro , but only using murine bone marrow-derived DCs exposed to cell-free Moloney-pseudotyped chimeric HTLV-1 15 . Given that cell-free HTLV-1 is not detected in HTLV-1 carriers or patients, in vivo DCs are probably mostly exposed to chronically infected cells rather than cell-free virus. Hence, these experimental settings may not fully recapitulate in vivo virus / host interactions. Strikingly, myeloid cells such as monocytes and DCs can harbor infectious HTLV-1 genomes in infected individuals, including in asymptomatic individuals 6 , 16 , and exhibit impaired phenotypes and functions 16 – 18 that may correlate with their proviral load 19 . These observations in humans indicate that HTLV-1 could in fact dampen the responsiveness of infected DCs, which may ultimately contribute to immune dysfunction during chronic infection. Accordingly, DCs derived from ATL patients exhibit maturation defects 17 associated with an inability to induce proliferation of CD4 + T cells 18 . However, because the proportion of DCs infected in vivo is low, the impact of HTLV-1 on DC function might not be solely attributed to HTLV-1-infected DCs, suggesting that HTLV-1 could indirectly modulate the functions of DCs, in the absence of direct infection. In this work, we aimed at determining whether HTLV-1 transformed T cells could indirectly affect human DC functions in vitro . In contrast with previous work using murine cells and cell-free virus, we show that upon coculture with HTLV-1 transformed T cell lines, human monocyte-derived DCs (MDDCs) do not fully mature. We further show that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs, which differs from a typical maturation program, and which is correlated with a dampened responsiveness of HTLV-1-exposed MDDCs to subsequent stimulation. Interestingly, this tolerogenic behavior is induced as the result of a molecular dialogue between HTLV-1-infected T cells and MDDCs upon coculture. This unique mechanism of viral-induced tolerance in DCs illustrates how HTLV-1 might indirectly manipulate innate cells to induce a local immune microenvironment suitable for its own persistence. Results Human MDDCs do not fully mature when exposed to HTLV-1-infected T cells To determine whether chronically infected T cells could directly or indirectly manipulate human DC functions in vitro , we first addressed whether infected T cells were sensed by DCs. We used human monocyte-derived DCs (MDDCs) cultured in vitro with HTLV-1-infected and transformed T cell lines, and assessed MDDCs maturation by flow cytometry after 24h or 48h of coculture, using the MDDC-specific CD11c marker to identify MDDCs in the coculture (see Fig. 1 a for the experimental settings, and Supplementary Fig. 1 for the gating strategy). At these time points, less than 1% of MDDCs have integrated the viral genome and they do not release virions 11 , indicating that they are not productively infected. In contrast to MDDCs exposed to measles virus (MeV), MDDCs exposed to HTLV-1 transformed C91-PL cells, failed to fully upregulate CD86, used in this first experiment as a surrogate of DC maturation (Fig. 1 b, left panel ). Repeated experiments using MDDC samples from independent donors showed that while around 90% of MDDCs upregulated CD86 upon exposure to MeV, regardless of their ability to express MeV (Fig. 1 b, right panel , compare total versus GFP − and GFP + MDDCs), as well as upon stimulation by the TLR-4 agonist LPS (Fig. 1 b, right panel ), the percentage of activated MDDCs after coculture with HTLV-1-transformed C91-PL cells remained low (Fig. 1 b, right panel ). To exclude a cell line-specific effect, and to thoroughly characterize MDDCs maturation status, MDDCs were exposed to several control uninfected T cell lines ( Supplementary Fig. 2a-f ; Jurkat, CEM or Molt-4 T cell lines, green bars), as well as to several HTLV-1-transformed T cell lines ( Supplementary Fig. 2a-f; C91 -PL, MT-2 or Hut102; blue bars), and the regulation of both maturation markers CD86, CD83, CD80, and CD40, ( Supplementary Fig. 2a-d ) and inhibition markers ICOSL and PD-L1 ( Supplementary Fig. 2e-f ) at the cell surface was monitored by flow cytometry. All the HTLV-1-transformed T cell lines induced either no change, or only minor changes, in the expression (percentage of positive cells and normalized mean signal intensity, MFI) of maturation or inhibition markers at the surface of cocultured MDDCs ( Supplementary Fig. 2a-f ). Increasing the duration of coculture to 48h did not impact these observations ( Supplementary Fig. 2a-f ), excluding a delay in maturation. The inefficient upregulation of MDDC maturation markers was also accompanied by a low ability to secrete TNF-α or IFN-I (Fig. 1 c and Supplementary Fig. 2g ), strengthening the notion that HTLV-1-infected T cells do not induce a typical maturation program in MDDCs, and thus might not be efficiently sensed by human DCs, in contrast to observations made with cell-free virus in a mouse model 15 . Since similar observations were made with all HTLV-1-infected T cell lines tested, and with the tested maturation markers and cytokines, only the C91-PL T cell line and CD86 were used in some of the following experiments. Previous work from our laboratory showed that MDDCs efficiently capture HTLV-1 after coculture with HTLV-1-infected T cell lines 11 , suggesting that in our experimental conditions, HTLV-1 capture itself is inefficient in driving MDDC maturation. To formally demonstrate this, we assessed HTLV-1 capture in MDDCs following coculture, by staining the HTLV-1 Gag p19 structural protein. As expected, MDDCs were efficient at capturing HTLV-1 (Fig. 1 d), irrespective of the infected T cell line used in the coculture ( Supplementary Fig. 2h ), with around 30% of capture observed in a representative coculture experiment with C91-PL cells (Fig. 1 d, left ), and reaching up to 80% of capture observed in repeated experiments using independent donors (Fig. 1 d, right ). Maturation was then compared in MDDCs that had not captured HTLV-1 (Gag p19-negative MDDCs, cyan, Fig. 1 e), or had captured HTLV-1 (Gag p19-positive MDDCs, magenta, Fig. 1 e). Although CD86 expression was consistently higher in p19-positive MDDCs (Fig. 1 e, right , compare cyan and magenta bars), the percentage of Gag p19-positive cells remained low compared to fully matured LPS-exposed MDDCs (Fig. 1 e, compare magenta and red bars), highlighting that maturation remained inefficient even in MDDCs that had capture HTLV-1. No significant correlation was detected among repeated experiments between the level of HTLV-1 capture and the efficiency of MDDC maturation ( Supplementary Fig. 2i, p = 0.1412), further confirming that HTLV-1 capture itself is inefficient in driving MDDC maturation. Taken together, these observations, recapitulated in Fig. 1 f, demonstrate that cell-associated HTLV-1 fails to fully mature MDDCs, suggesting that it is poorly sensed by these human innate cells. Exposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs Interestingly, our previous work demonstrated that in contrast to MDDCs, plasmacytoid dendritic cells (pDC) do efficiently sense cell-associated HTLV-1 20 . Inefficient sensing of HTLV-1-infected T cells by MDDCs could be the result of either a stealth behavior of cell-associated virus towards MDDCs, resulting in a bona fid e lack of response specifically in this cell type, or, alternatively, to the active manipulation of MDDC functions by HTLV-1-infected T cells, resulting in a specific response that differs from a typical maturation program. To discriminate between both these scenari, we aimed at determining the complete transcriptomic landscape of MDDCs after exposure to HTLV-1-infected T cells, or to control uninfected T cells, using bulk RNA-seq (Fig. 2 ). After 24h of coculture, MDDCs were magnetically separated from C91-PL or control Jurkat T cells, based on the exclusive expression of CADM1 on T cells ( Supplementary Fig. 3a ). Note that although the levels of CADM1 were higher at the surface of C91-PL cells compared to Jurkat cells ( Supplementary Fig. 3a ), a similar MDDC enrichment yield of around 99% was observed after separation in both conditions, with no significant T cell contamination ( Supplementary Fig. 3b ). LPS-stimulated MDDCs were also included in the RNA-seq analysis, as a reference for fully matured MDDCs. RNA was extracted from each MDDC sample, and submitted to quality control followed by sequencing. First, to show global similarities in gene expression between samples, unsupervised hierarchical clustering and principal component analysis (PCA) were performed on normalized transcript count tables. Analysis of sample clustering along the two first PCs (Fig. 2 a, PC1 and PC2), that explain 81 and 8% of the total variance, respectively, showed that the main source of variance in the dataset was the stimulation by LPS, followed by the infection status of cocultured T cells, while the identity of the MDDC donor contributed only weakly to the global variance. In agreement with flow cytometry data shown in Fig. 1 , this confirmed, at the transcriptional level, the inefficient activation of MDDCs after exposure to HTLV-1-infected T cells, which contrasts with the typical maturation program of fully activated MDDCs. This also indicates that exposure to HTLV-1-infected T cells does induce a detectable, yet subtle, transcriptional response, when compared to exposure to uninfected T cells. To characterize the changes in gene expression in MDDCs induced by exposure to HTLV-1-infected T cells, we used DESeq2 to identify differentially expressed genes (DEGs) between C91-PL- and Jurkat-exposed MDDCs. As a reference for a typical maturation program, we identified DEGs between LPS- and Jurkat-exposed MDDCs. Using a fold-change cut-off of 2, a total number of 474 DEGs were obtained between C91-PL- and Jurkat-exposed MDDCs (padj < 0.05), with 435 genes found significantly upregulated upon HTLV-1 exposure, and 39 genes found significantly downregulated (Fig. 2 b and Supplementary Table 1 ). A heatmap of the 474 DEGs showed clustering between samples, as expected ( Supplementary Fig. 4a ). To gain insight into the processes modulated in MDDCs after exposure to HTLV-1-infected T cells, we performed gene ontology analysis on the set of 435 upregulated genes. Over-represented KEGG pathways were retrieved and filtered to reduce redundancy (see Supplementary Table 2 ), leading to a final list of 7 pathways (Fig. 2 c and Supplementary Tables 2 and 3 ). Strikingly, exposure to HTLV-1-infected T cells was characterized by significant over-representation of upregulated genes involved in lipid biosynthesis and metabolism (Fig. 2 c). Interestingly, genes involved in several pathways linked with response to viral infection were also over-represented, including genes involved in innate immune sensing (sub-pathways: RIG-I or Toll-like receptors and NOD-like receptors), in viral infection (sub-pathways: Influenza A, Measles, Hepatitis C, Hepatitis B, Human Papillomavirus, Herpes simplex virus 1, Coronavirus, HIV, EBV), and in the NF-κB signaling pathway. Taken together, these results confirm that exposure to HTLV-1-infected T cells does induce a transcriptional response in MDDCs, indicating that sensing does occur to some extent, but does not culminate in a typical maturation and anti-viral program. To further determine the extent to which this transcriptional response is distinct from a typical maturation signature, we compared the genes affected by LPS stimulation of Jurkat-exposed MDDC to those affected by MDDC exposure to C91-PL. Among the 474 DEGs, 373 genes were also differentially expressed after LPS stimulation (Fig. 2 d), representing only 5% of all LPS-modulated genes. Among these shared genes, 7 genes annotated as involved in the NF-κB signaling pathway were retrieved, including CCL19, TNFSF13B, TRIM25, BCL2L1 and BCL2A1 ( Supplementary Fig. 4b ). However, the level of up-regulation of these shared NF-κB-related genes was strikingly lower after HTLV-1 exposure compared to LPS stimulation ( Supplementary Fig. 4b ). This observation of a lower magnitude of differential expression (either up- or downregulation) was general to most of the 373 shared DEGs (Fig. 2 e). Of note, the RELA, RELB and NFKB1 genes that were upregulated by LPS stimulation were not upregulated upon C91-PL exposure ( Supplementary Fig. 4c ), possibly contributing to the lower activation of the NF-κB-dependent genes observed above ( Supplementary Fig. 4b ). In addition, among the 377 Interferon-Stimulated Genes (ISG) listed in Supplementary Table 1 , only 121 were retrieved in the set of significantly upregulated genes, and again, their up-regulation was lower to that induced by LPS stimulation ( Supplementary Fig. 4d ). These observations strengthen the notion that while sensing of HTLV-1-infected T cells does occur to some extent, the magnitude of the maturation and antiviral transcriptional response remains very limited, which is consistent with the inefficient maturation of MDDCs observed at the protein level (see Fig. 1 ). Interestingly, among the 474 DEGs, 101 genes were not present in the list of DEGs between LPS- and Jurkat-exposed MDDCs (Fig. 2 d and f ), defining a unique transcriptional signature associated with the exposure to HTLV-1-infected C91PL cells. Due to the limited number of genes included in this specific signature, gene ontology analysis was not feasible. Interestingly however, several genes retrieved in Fig. 2 c as those involved in lipid biosynthesis and metabolism, were also included in this specific signature, such as ELOVL3 (Elongation of Very Long Fatty Acid Elongase 3), FADS1 (Fatty Acid Desaturase 1), and SLC27A6 (Solute Carrier Family 27 Member 6, a member of the fatty acid transport protein family) (Fig. 2 g). Altogether, these transcriptomic analyses demonstrate that exposure to HTLV-1-infected T cells is not completely silent in MDDCs, but rather results in a unique transcriptional response that differs from a typical maturation program. This supports the notion that HTLV-1-infected T cells might actively manipulate MDDC functions to limit their functional response, possibly by rewiring lipid biosynthesis and metabolism. Pre-exposure to HTLV-1-infected T cells dampens the responsiveness of MDDCs to subsequent stimulation We next aimed at investigating whether this unique transcriptional response observed upon exposure to HTLV-1-infected T cells indeed translates into functional defects in MDDCs, beyond their inefficient maturation. To this end, we addressed whether pre-exposure to HTLV-1-infected cells influenced MDDC responsiveness when exposed to a subsequent stimulation. After 24h of coculture with HTLV-1-infected T cell lines, MDDCs were restimulated with strong inducers of MDDCs maturation, in the form of LPS (TLR-4 ligand) or R848 (TLR-7/8 ligand, Fig. 3 a), for another 24h. When compared to MDDCs pre-exposed to uninfected control T cell lines (red bars), MDDCs pre-exposed to HTLV-1-transformed T cells (dark blue bars) upregulated CD86 (as well as other maturation markers) to a significantly lower extent when stimulated by LPS or R848 (Fig. 3 b, Supplementary Fig. 5a-d ). In addition, TNF-α secretion by MDDCs upon LPS stimulation was also significantly reduced by pre-exposure to HTLV-1-transformed T cells (Fig. 3 c, left panel, Supplementary Fig. 5e ), while IFN-I secretion was not affected (Fig. 3 c, right panel, Supplementary Fig. 5e ). These results indicate that pre-exposure to HTLV-1-transformed T cells indeed influences the responsiveness of MDDCs to subsequent stimulation, by specifically dampening their pro-inflammatory response (monitored here through the upregulation of maturation markers and through TNF-α secretion), without hampering their antiviral response (monitored here through IFN-I secretion) (recapitulated in Fig. 3 d). This suggests that HTLV-1 might specifically manipulate the responsiveness of certain signaling pathways in MDDCs, such as the NF-κB pathway upstream of the pro-inflammatory program, while leaving the responsiveness of others unaffected, such as the IRF3 pathway upstream of the antiviral program. Pre-exposure to HTLV-1-transformed T cells alters the transcriptional response of MDDCs to subsequent stimulation To obtain a broader overview of how pre-exposure to HTLV-1-transformed T cells affects the responsiveness of MDDCs, a second bulk RNA-seq analysis was conducted on MDDCs pre-exposed to an HTLV-1-infected T cell line (C91-PL), or to a control uninfected T cell line (Jurkat), and then restimulated by LPS (Fig. 4 ). To address whether viral capture was required for this manipulation of MDDC responsiveness, we also included in the RNA-seq analysis MDDCs cocultured with the HTLV-1-infected C8166 T cell line that does not produce viral particles 21 . As expected, no viral particle was captured by C8166-exposed MDDCs, in contrast to C91-PL-exposed MDDCs ( Supplementary Fig. 6 ). PCA analysis of samples showed that both the donor and the infection status of cocultured T cells were the main sources of variance in the dataset (Fig. 4 a), confirming that pre-exposure to HTLV-1-transformed T cells does alter the transcriptional response of MDDCs to subsequent stimulation. In contrast, the ability to capture HTLV-1 did not contribute to a visible extent to the global variance, suggesting that viral capture might not be required for this alteration. We then retrieved the lists of genes differentially expressed between the different experimental conditions. In agreement with the PCA analysis, 1324 genes were found differentially expressed between LPS-stimulated C91-PL-pre-exposed MDDCs, and LPS-stimulated Jurkat-pre-exposed MDDCs ( Supplementary Table 4 ), with a total of 403 DEGs being downregulated and 921 DEGs being upregulated (Fig. 4 b). Gene ontology analysis was conducted on these sets of downregulated and upregulated genes, respectively (Fig. 4 c, left and right panels, respectively). The set of downregulated genes was characterized by a significant over-representation of genes annotated as being involved in TNF-α or NF-κB signaling and innate immune sensing (Fig. 4 c, left panel, arrows, see Supplemental Table 5 ). Conversely, the set of upregulated genes was characterized by a significant over-representation of genes annotated as being involved in the TGF-β signaling pathway (Fig. 4 c, right panel, arrow, see Supplemental Table 6 ). This confirmed that pre-exposure to HTLV-1-transformed T cell does influence the transcriptional response to LPS stimulation. To further identify the expression patterns of these genes differentially expressed between LPS-stimulated C91-PL-pre-exposed MDDCs, and LPS-stimulated Jurkat-pre-exposed MDDCs, we classified these genes based on their differential expression across conditions (detailed in Supplemental Fig. 7a , see also Supplementary Table 4) as follows: (i) Genes whose responsiveness to LPS (be it repression or induction) is specifically conferred by pre-exposure to infected cells (Fig. 4 d, upper panel). (ii) Genes whose responsiveness to LPS (be it induction or repression) is exacerbated by pre-exposure to infected cells (Fig. 4 d, middle panel). (iii) Genes whose responsiveness to LPS is attenuated or (iv) abolished by pre-exposure to infected cells (Fig. 4 d, lower panel). This classification demonstrates that pre-exposure to HTLV-1-transformed T cells induces both a change in the identity of genes that transcriptionally respond to LPS stimulation, defining a unique LPS-induced transcriptional signature; and a change in the magnitude of the transcriptional response of genes that are normally responsive to LPS. In line with the gene ontology analysis presented in Fig. 4 c, the responsiveness of genes involved in NF-κB signaling, such as MYD88 (Fig. 4 d, lower panel, see graph), or the pro-inflammatory genes CCL2 , IL12B , TNF , CXCL10 and CXCL11 ( Supplementary Fig. 7b , upper panel), was found drastically attenuated by pre-exposure to infected cells (C91-PL or C8166). This could account for the inefficient maturation and production of pro-inflammatory cytokines by HTLV-1-pre-exposed MDDCs after LPS stimulation, which was observed in Fig. 3 . In addition, in line with the gene ontology analysis presented in Fig. 4 c, genes of the TGF-β signaling pathway, including BMP6, BMP7 , and IL13 ( Supplementary Fig. 7b , middle panel), which do not respond to LPS in normal conditions, were found to be responsive to LPS when MDDCs were pre-exposed to HTLV-1-transformed cells, while the responsiveness of TGFB2 , which is repressed upon LPS stimulation in normal conditions, was abolished by pre-exposure to HTLV-1-infected cells (Fig. 4 d, lower panel, see graph). Interestingly, these genes encode cytokines known to participate in the induction of a tolerogenic immune microenvironment, with Treg and T H 2 responses, which are inefficient at controlling viral infection. Finally, pre-exposure to HTLV-1-transformed cells also conferred responsiveness to DDIT4 (Fig. 4 d, upper panel, see graph), a gene reported in other contexts of tolerogenicity 22 . Of note, and in agreement with the efficient induction of IFN-I after LPS stimulation in both Jurkat- or C91PL-pre-exposed MDDCs (see Fig. 3 c), the responsiveness of ISGs such as ISG15, IFI44 and IRF2 was not affected by pre-exposure to HTLV-1-infected cells ( Supplementary Fig. 7b , lower panel). Altogether, this transcriptomic analysis indicated that pre-exposure to HTLV-1-transformed T cells influences the responsiveness of MDDCs to subsequent stimulation, by specifically dampening their pro-inflammatory response at the transcriptional level. In addition, it uncovered the fact that pre-exposure to HTLV-1-transformed T cells allows a unique set of genes to respond to LPS stimulation, triggering a biased, pro-tolerogenic response of MDDCs upon subsequent stimulation. Neither HTLV-1 viral capture, nor cell-cell contact with infected T cells, are strictly required to dampen the responsiveness of MDDCs to subsequent stimulation As stated above, RNA-seq analysis using the C8166 infected cell line suggests that viral capture might not be required to alter the transcriptional response of MDDCs to a secondary stimulation. To confirm this notion at the functional level, we repeated the coculture experiment followed by LPS stimulation, and analyzed MDDC maturation profile by flow cytometry (Fig. 5 a). Despite the lack of viral particle capture by C8166-exposed MDDCs (see Supplementary Fig. 6 ), C8166 pre-exposure still dampened the responsiveness of MDDCs to LPS and R848 stimulation, as monitored through CD86, CD83 or CD80 upregulation, similar to C91-PL pre-exposure (Fig. 5 a and Supplemental Fig. 8a ), confirming that viral capture is not strictly required. Although C8166 do not produce viral particles, they might still engage in cell-cell contacts with MDDCs 23 , which could be the trigger of the dampening of MDDC responsiveness. We addressed this hypothesis by performing the cocultures in transwells, in which MDDCs were physically separated from infected T cells by a permeable membrane (Fig. 5 b). Of note, reduced but detectable levels of viral capture were detected in MDDCs physically separated from C91-PL ( Supplementary Fig. 8b ), most probably because the virus is preferentially associated to the cell surface of infected cells and might be released as large adhesive viral aggregates 24 poorly able to cross the 0.4µm pores of the permeable membrane. The absence of physical contact between MDDCs and infected T cells, either producing (C91-PL) or not producing viral particles (C8166), did not restore a fully efficient maturation after LPS stimulation (Fig. 5 b), indicating that cell-cell contacts are not strictly required to allow HTLV-1-infected T cells to manipulate MDDC responsiveness. Of note however, C8166 cells appeared less efficient than C91PL cells in dampening MDDC responsiveness upon transwell coculture. This could result from additive effects of mechanisms dependent on viral capture on the one hand, and of cell-cell contact on the other hand: indeed, in the presence of cell-cell contacts (Fig. 5 a), the contribution of viral capture might be negligible; while in the absence of cell-cell contacts (Fig. 5 b), such contribution might become relatively more important. Consistently, comparison of MDDC responsiveness in paired experiments of MDDC pre-exposed to infected cells with (coculture) or without (transwell) physical contacts (Fig. 5 c) showed that preventing physical contacts between MDDCs and infected cells resulted in a slightly higher, yet not significantly different, MDDC responsiveness (Fig. 5 c). This indicates that viral capture and/or cell-cell contacts may participate, but are not strictly required to allow HTLV-1-infected T cells to manipulate MDDC responsiveness, and suggests the contribution of a distantly acting set of soluble mediators. A molecular dialogue between HTLV-1-infected T cells and MDDCs induces the release of soluble tolerogenic mediators Since neither viral particles nor cell-cell contacts are strictly required to manipulate MDDC responsiveness, we then tested the conditioning ability of the supernatant of HTLV-1-infected T cells. More specifically, we hypothesized that IL-10 produced by HTLV-infected T cells 25 could be a candidate mediator, as it was reported to have tolerogenic properties 26 . However, except for the supernatant of the MT-2 infected T cell line, IL-10 was not detected in the supernatant of any of the other infected T cell lines ( Supplementary Fig. 9a ). More surprisingly, none of these supernatants were sufficient to manipulate MDDC responsiveness, as MDDCs pre-incubated in these supernatants still efficiently matured upon LPS stimulation ( Supplementary Fig. 9b ). This suggested that MDDC manipulation requires a molecular dialogue between HTLV-1-transformed T cells and MDDCs that would lead to the production of soluble tolerogenic mediators upon coculture. To test this hypothesis, we collected the conditioned medium of MDDCs cocultured with infected T cells for 24h, and used it to culture fresh, naïve MDDCs derived from the same monocyte donor (autologous cells) for 24h, before LPS stimulation for another 24h (see Fig. 6 a for the experimental settings). In contrast to supernatant of infected T cells alone ( Supplementary Fig. 9b ), the supernatant from the co-culture was still able to dampen the responsiveness of MDDCs (Fig. 6 b), although with less potency compared to coculture with infected T cells, as observed by analysis of paired experiments (Fig. 6 c). This is consistent with the tendency observed upon transwell cultures (see Fig. 5 c), and confirms the release of soluble tolerogenic mediators following a molecular dialogue between infected T cells and MDDCs upon coculture, which could cooperate with other mechanisms dependent on viral capture and/or cell-cell contacts. Next, we addressed the kinetics of the molecular dialogue required for the release of these mediators. Conditioned medium of MDDCs cocultured with infected T cells were collected over time, and used to culture fresh autologous MDDCs before the addition of LPS (Fig. 6 d). A lowered responsiveness of MDDCs was only observed with supernatants collected at least 18h after coculture (Fig. 6 e), suggesting that the mediators is produced and released after a transcriptional response. Alternatively, we tested the kinetics required for the mediators to manipulate MDDC responsiveness. Conditioned medium of MDDCs cocultured with infected T cells was collected after 24h, and used to culture fresh autologous MDDCs for a varying duration before the addition of LPS (Fig. 6 f). A lowered responsiveness of MDDCs was only observed when MDDCs were cultured for at least 18h with the conditioned medium before adding the LPS (Fig. 6 g). The manipulation of MDDC responsiveness might thus also rely on a transcriptional control, which is consistent with the unique transcriptional signature induced by exposure to HTLV-1-infected T cells observed by RNA-seq. Altogether, our results (recapitulated in Fig. 6 h) show that upon coculture, a molecular dialogue is initiated between HTLV-1-transformed T cells and MDDCs, which results in the transcriptionally-controlled release of a set of soluble tolerogenic mediators that manipulates MDDC responsiveness, in cooperation with additional mechanisms dependent on viral capture and/or cell-cell contacts. Discussion The remarkable ability of viruses to manipulate intracellular pathways in infected host cells is essential for establishing and maintaining infection. In addition to these direct effects, viruses may also establish a specific microenvironment around infected cells, which may favor viral spread and persistence by influencing the signaling pathways and behavior of neighboring, uninfected cells, including immune cells 27 , 28 . As a by-stander effect, this may alter immune responsiveness to other stimuli. Mechanisms by which viruses influence uninfected cells in their local environment are still poorly understood. In this study, we aimed to decipher how HTLV-1-infected cells indirectly manipulate cocultured DCs. We demonstrate that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in DCs, preventing their maturation and impairing their ability to be subsequently activated. This induction of tolerogenicity is not directly caused by infection of DCs, but instead results from a molecular dialogue between infected T cells and DCs, reminiscent of a viral microenvironment 27 , 28 . Previous work on the interplay between HTLV-1 and DCs has focused on the role of DCs as intermediate target cells for HTLV-1 transmission to T cells 10 – 12 . Several studies investigated whether viral capture by DCs could lead to T cell cis- and/or trans-infection, and whether specific DC subtypes or maturation statuses could impact this proviral function. In particular, in a previous paper, we demonstrated that immature MDDCs do efficiently capture and transmit HTLV-1 to T cells, while mature MDDCs do not efficiently transmit HTLV-1 to T cells, despite high levels of viral capture 11 . While these data indicated that the maturation status of DCs could impact their proviral functions, they did not address whether exposure to HTLV-1 induced a antiviral immune response by DCs. Such a question was investigated in pDCs, which we showed to be efficient at sensing HTLV-1-infected cells after cell-cell contact, and at responding by producing IFN-I 20 . Here, we specifically addressed how MDDCs respond to HTLV-1 exposure. Intriguingly, our results are in stark contrast to those obtained in pDCs, as we show that MDDCs do not respond to HTLV-1-infected T cells by activating a typical maturation and antiviral program, even in the presence of cell-cell contact. The unique transcriptional response observed could be the result of a specific molecular dialogue occurring between HTLV-1-infected T cells and MDDCs, that does not occur with pDCs. Alternatively, this molecular dialogue could also occur with pDCs, but be outperformed by the highly efficient capacity of pDCs to produce IFN-I. Investigating how pDC added to the coculture between HTLV-1-infected T cells and MDDCs could modulate this induction of tolerogenicity, and how this tolerogenic behavior would shape HTLV-1 transmission to uninfected T cells, would give insight into how these distinct behaviors are integrated into the microenvironment system. Of note, our results are also in contrast with data obtained on murine DCs, using cell-free HTLV-1 15 . This underlines the importance of working with human cells when investigating HTLV-1/host interactions. Our data point towards the release of soluble tolerogenic mediators following a molecular dialogue between infected T cells and MDDCs upon coculture, which could cooperate with other mechanisms dependent on viral capture and/or cell-cell contacts. The identity of the soluble mediators initiating the molecular dialogue observed between HTLV-1-infected T cells and MDDCs, as well as produced as a result of this dialogue, is currently under investigation in our laboratory. As we observed that conditioned medium from infected T cells alone did not induce the tolerogenic behavior of MDDCs, but that conditioned medium from infected T cells cocultured with MDDCs did, it raises the hypothesis that HTLV-1-infected T cells sense a soluble factor released by MDDCs, that activates the release of a second soluble factor by infected T cells. This second factor could then launch a specific transcriptomic response in MDDCs that would lead to tolerogenicity. Among potential soluble mediators produced by HTLV-1-infected cells, exosomes emerge as compelling candidates. Their composition could be modified by viral infection, explaining the differences observed in MDDC responses between exposure to uninfected or infected T cells. Also, their production by T cells could be boosted by coculture with MDDCs, explaining the requirement of a molecular dialogue between both cell types. Last, the diameter of exosomes, around 100 nm, is compatible with their diffusion through the pores of the transwell (0.4 µm) used in our experimental settings. Interestingly, several HTLV-1-infected T cell lines, independently of their ability to produce viral particles or not, do produce exosomes containing cytokines, viral proteins and RNA 29 – 31 able to modulate target cells, resulting in an increased susceptibility to infection 23 . We can thus hypothesize that in our experimental settings, these exosomes could modulate DC functions, inducing the unique transcriptional signature that we observe. This would be reminiscent of data obtained on Epstein-Barr Virus (EBV), where infection changes the ability of exosomes purified from gastric cancer cell lines to mature MDDCs, leading to a defect in CD86 upregulation and reduced tumor immunity 32 . Whether HTLV-1 proteins contained in exosomes could contribute to the induction of tolerogenicity remains to be investigated. Viral proteins such as p30, HBZ, and Tax are found in exosomes produced by infected cells 23 , 29 , independently of the production of viral particles by these infected cells. In addition, these viral proteins have the potential to interfere with immune functions. For instance, p30 expressed in MDDCs reduces IFN-I responses upon TLR3/4 stimulation, but not upon TLR7/8 stimulation 33 , suggesting a specific targeting of the TLR3/4 signaling pathway. However, as we found no alteration in the IFN response of LPS restimulated, HTLV-1-pre-exposed MDDCs, a role of p30 can be excluded. In contrast, HBZ is known to inhibit the NF-κB pathway 34 by degrading the transcription factor p65 35 . As we observed the repression of the NF-κB pathway in HTLV-1-pre-exposed MDDCs upon LPS restimulation, we could suggest that exosome-transferred HBZ could contribute to modulating MDDC functions. Interestingly, following the molecular dialogue between infected T cells and MDDCs, we observed the upregulation of genes involved in fatty acid metabolism (such as ELOVL3 , FADS1 , and SLC27A6 ) in MDDCs. As these genes are not found in the typical maturation program of MDDCs, it raises the possibility that upon coculture with HTLV-1-infected T cells, MDDCs produce fatty acids, that may act in a autocrine and paracrine manner to modulate MDDC functions. Of note, fatty acid precursors such as squalene and vitamin D are recognized inducers of tolerogenic DCs 36 , 37 . Polyinsaturated fatty acids have also been shown to block DC activation and functions 38 , and inhibition of fatty acid synthesis has been shown to increase their production of pro-inflammatory cytokines 39 . Whether HTLV-1-exposed MDDCs produce higher levels of fatty acids, and whether these could contribute to their observed tolerogenic behavior, is currently under investigation. Thus, our transcriptomic analysis reveals how viruses could indirectly rewire lipid metabolism in immune cells to modulate the immune microenvironment. Upon restimulation with LPS, HTLV-1-pre-exposed MDDCs undergo a specific transcriptomic response, including an abolished downregulation of TGFB expression, which remains highly expressed, and upregulation of IL13 expression, which could be the basis for their tolerogenic properties. Of note, from the literature, the exact transcriptomic program underlying the tolerogenic behavior of DCs is unclear, as different transcriptomic signatures have been reported 40 – 42 . Nonetheless, a set of common genes has been defined as a gene signature of tolerogenic DCs 22 , including DDIT4 (DNA-damage-inducible transcript 4), which encodes an inhibitor of mTOR signaling 22 . Interestingly, responsiveness of DDIT4 was also specifically conferred by pre-exposure to infected cells. Thus, the transcriptomic program induced in HTLV-1-pre-exposed MDDCs by LPS restimulation partially mirrors the tolerogenic DC signature defined in other contexts. In conclusion, our study demonstrates that exposure to HTLV-1-transformed cells can indirectly distort the functionality of DCs and impair their response to subsequent stimulation. Our in vitro results are consistent with in vivo observations, which report that MDDCs from HTLV-1-infected patients exhibit deficiencies in both basal maturation and responsiveness to TNF-α treatment, as well as defects in the induction of T-cell response 16 , 17 . In addition, PBMCs from HTLV-1-infected patients stimulated with tuberculin produce fewer TNF-α than PBMC isolated from healthy individuals 43 . Finally, the fact that viral production is not necessary to dampen MDDC responsiveness, might reflect the in vivo situation in which HTLV-1 expression is repressed in chronically infected cells 44 . Therefore, it is plausible that defects in the myeloid cell response, particularly in DCs, may represent a mechanism of HTLV-1 pathogenesis in vivo . Thus, this work illustrates how HTLV-1 might induce a local immune microenvironment suitable for its own persistence. Such microenvironnement may additionally contribute to by-stander immune dysfunctions, in asymptomatic HTLV-1 carriers as well as symptomatic HTLV-1-infected patients. Methods Cells lines HTLV-1 infected T-cell lines (C91-PL from Cellosaurus ref CVCL_0197, MT-2 ref CVCL_2631 45 , Hut102 ref CVCL_3526 46 and C8166 ref ECACC 88051601 21 ) and control uninfected T-cell lines (Jurkat from ATCC ref ACC 282, CEM/C1 ref CRL-2265, Molt-4 Cellosaurus ref CVCL_0013) were maintained at a cell density of 0.5.10 6 cells/mL in complete RPMI medium: RPMI1640 GlutaMAX (Gibco; 61870010) supplemented with 10% fetal calf serum (FCS) and penicillin-streptomycin (100 U/mL and 100 µg/mL respectively). The human fibrosarcoma cell line HL116 stably expressing the firefly luciferase reporter gene under the control of the immediate early IFN-I inducible 6–16 promoter (kindly provided by Dr. S. Pelligrini, Institut Pasteur, France 47 ) was maintained under HAT selection (Gibco; 21060017, used at 1X final concentration) in DMEM GlutaMAX pyruvate medium (Gibco; 10569010) supplemented with 10% FCS and penicillin-streptomycin (100 U/mL and 100 µg/mL respectively). All cells were grown at 37°C in 5% CO 2 and tested negative for mycoplasma contamination on a regular basis. None of the cell lines were authenticated. Human primary monocyte-derived dendritic cells (MDDCs) MDDCs were derived from purified monocytes from healthy blood donors as described previously 11 . Briefly, blood samples were collected at Etablissement Français du Sang (EFS) from anonymous healthy blood donors according to the institutional Standard Operating Procedures for blood donation, including a signed informed consent. Blood was diluted in PBS 1X (Gibco) and peripheral blood mononuclear PBMCs were isolated using a density gradient separation using Ficoll-Paque (Fisher Scientific, 11778538). Monocytes were then isolated from PBMCs using a density gradient separation using Percoll Centrifugation Medium (Fisher Scientific, 10607095). Freshly or frozen monocytes were cultured in six-well plates at 3.10 6 cells/mL in complete MDDC medium: RPMI1640 GlutaMAX (Gibco) supplemented with 10% FCS, penicillin-streptomycin (100 U/mL and 100 µg/mL respectively), Hepes buffer (Gibco, 15630080; 10 mM), MEM non-essential amino acids (2,5mM, Gibco, 11140050), sodium pyruvate (Gibco, 11360070; 1 mM), and beta-mercaptoethanol (Gibco, 31350-010; 0.05 mM). MDDC medium was supplemented with IL-4 and GM-CSF (Miltenyi Biotec, 130-093-922 and 130-093-866; 100 ng/mL each) for differentiation. On day 3, the culture medium was refreshed by discarding half of the medium and adding the same volume of new MDDC medium and twice concentrated IL-4 and GM-CSF to all cell cultures. Immature MDDCs were harvested on day 5 or 6. Every experiment was repeated on MDDCs derived from independent blood donors. Reagents and antibodies Toll-like receptor (TLR)-4 agonist (LPS, tlrl-3pelps; 1µg/mL) and TLR-7/8 agonist (R848, tlrl-r848; 3µg/mL) were purchased from Invivogen. MeV IC323-eGFP 48 is a recombinant MeV expressing the gene-encoding eGFP (using the plasmid-encoding MeV IC323-eGFP kindly provided by Yanagi, Kyushu University, Fukuoka, Japan). MeV IC323 recombinant virus was rescued in 293-3-46 cells, as previously described 49 . Production of the viruses was performed at 32°C. All viruses were propagated and titrated in Vero-SLAM/CD150 cells. MDDCs were infected using a multiplicity of infection (MOI) of 1. The following antibodies were used: V450-coupled mouse anti-Human CD11c (BD Biosciences, 560369; 1/100), PE-coupled mouse anti-Human CD86 (Invitrogen, 12-0869-42; 1/100), APC-coupled mouse anti-Human CD83 (Miltenyi Biotec, 130-094-186; 1/50), BV510-coupled mouse anti-Human CD83 (BD Biosciences, 563223; 1/50), APC-H7-coupled mouse anti-Human CD80 (BD Biosciences, 561134; 1/50), BB515-coupled mouse anti-Human PDL1 (BD Biosciences, 564554; 1/25), PE-Cy7-coupled mouse anti-Human ICOSL (BioLegend, 309410; 1/100), Mouse anti-Gagp19 clone TP7 (Zeptometrix, 081107; 1/500), AlexaFluor647-coupled Alpaca anti-Mouse IgG1 (Chromotek, sms1AF647-1-5; 1/500), Biotin-coupled mouse anti-Human CADM1 (MBL Life Sciences, CM004-6; 1/1000), AlexaFluor647-coupled mouse streptavidin (Invitrogen, S31374; 1/500). MDDCs coculture experiment Immature MDDCs (3.10 5 cells) were plated in 48-well plates and cocultured with HTLV-1-infected or control uninfected T-cells (6.10 4 cells) in 300µL complete MDDC medium supplemented with IL-4 and GM-CSF for 24h or 48h. When indicated, transwell 24-well plates with permeable polycarbonate membrane inserts (0.4µm diameter) were used (Fisher Scientific, 10147291). Alternatively, MDDCs were cultured in supernatant collected from either HTLV-1-infected or control uninfected T-cell culture, or from coculture of MDDCs with HTLV-1-infected cells or control uninfected T-cell during 24h (or the indicated duration). After 24h, cells were harvested, or stimulated with LPS or R848 or medium for an additional 24h (or the indicated duration). At the indicated time points, cells and supernatants were collected for phenotyping using flow cytometry and for cytokine quantification, respectively. Flow cytometry analysis To assess surface marker expression, cells were fixed using 4% paraformaldehyde (PFA) diluted from 20% PFA (Electron Microscopy Science, 50-980-493) in PBS 1X, and stained with the indicated surface markers antibodies diluted in PBS 1X-1% Bovine Serum Albumin (BSA) for 20 min at 4°C. To assess viral capture, cells were fixed and permeabilized using the Fix/Perm FoxP3 and Transcription factors kit (Invitrogen, 00-5523-00) according to the manufacturer’s instructions, and stained with mouse anti-Gagp19 antibody followed by the AlexaFluor647-coupled anti-mouse antibody diluted in the PERM buffer supplemented with 7% Normal Goat Serum (NGS) for 25 min at room temperature. Cells were then stained for the indicated surface markers diluted in PBS 1X 1% BSA as described above. Compensation beads (BD Biosciences, 552843) were used to correct signal overlap between the emission spectra of the different fluorophores. Data were acquired using a flow cytometer FACS CantoII (BD Biosciences) and analyzed with FlowJo v10.7 software (BD Life Sciences). The full gating strategy is exemplified in Supplementary Fig. 1 . Cytokine quantification TNF-α and IL-10 were quantified in the collected supernatants using Bio-Plex Pro Human Luminex kit (Bio-Rad) according to the manufacturer’s instructions. Type I interferon quantification HL116 cells were seeded at 2.10 4 cells/well in 96-U-bottom-well plates and incubated for 24h. Supernatant collected from MDDCs culture (100 µL) or serial dilutions of recombinant IFN-α (Tebu-Bio, RPA033Gu02) used for standard curve determination were added for an additional 17h. Cells were then lysed (Promega Passive Lysis Buffer, E1941) and luciferase activity assayed according to the manufacturer’s instruction (Promega Luciferase Assay System, E1501). MDDCs isolation after coculture Cells from MDDC / T-cell lines coculture (1.10 6 MDDCs and 2.10 5 T-cells) were harvested and stained using biotin-coupled anti-CADM1 followed by AlexaFluor647-coupled streptavidin diluted in PBS 1X-1% BSA for 20 min at 4°C. After several washes in PBS, cells were then incubated with anti-AlexaFluor647 MicroBeads (Miltenyi Biotec, 130-091-395) and separated on MACS Separation LD Columns (Miltenyi Biotec, 130-042-901) according to the manufacturer’s instructions. To assess the purity and yield of enrichment of MDDCs after magnetic separation, 6.10 4 cells were collected before and after separation on LD columns, fixed in 4% PFA and stained with CD11c-V450 antibody, before analysis using FACS Canto II. RNA preparation After magnetic separation, MDDCs were lysed and total RNA was extracted using the NucleoSpin RNA Mini kit for RNA purification (Macherey-Nagel, 740955) according to the manufacturer’s instructions. RNA concentration was determined with a NanoDropND1000 spectrophotometer (Thermo Fisher Scientific) and samples were stored at -80°C until shipment for external sequencing. Stranded RNA libraries were prepared after removal of rRNA. High throughput sequencing of 150 bp paired-end reads was performed with an Illumina HiSeq 2500 platform by Novogene Europe (Cambridge, United Kingdom). Each sample had on average 50 million matched pairs of reads. RNA-seq data analysis The quality of sequences was checked using the FastQC tool. The reads were trimmed with PrinSeq 50 to remove low-quality bases and then mapped to the human reference transcriptome (hg19) using Kallisto pseudoalignment 51 . Differential gene analysis was carried out with DESeq2 package 52 . Genes with a basemean > 10 showing an absolute fold change (FC) ≥ 2 with an adjusted p-value < 0.05 (Wald test using Benjamini and Hochberg method) were considered differentially expressed. All DEGs identified in this study are listed in Supplementary Tables 1 and 4. DAVID functional annotation tool using the KEGG pathways database was used for gene ontology analysis 53 , 54 . For clarity, KEGG pathways were filtered and grouped as listed in Supplementary Table 2 to reduce redundancy. To identify the expression pattern responsiveness in LPS-stimulated MDDC pre-exposed to C91-PL, we retrieved the genes by Venn analysis using the following list of DEGs: MDDC/Jurkat restim.w/LPS vs MDDC/Jurkat; MDDC/C91-PL restim.w/LPS vs MDDC/Jurkat restim.w/LPS; MDDC/C91-PL restim.w/LPS vs MDDC/Jurkat. Then, genes were classified as follows (summarized in Supplementary Fig. 7a ): (i) responsiveness confered by pre-exposure to infected cells: genes that are not differentially expressed between mock- and LPS-stimulated Jurkat-pre-exposed MDDCs, but are differentially expressed (either up or down) between mock-stimulated Jurkat-pre-exposed MDDCs and LPS-stimulated C91-PL-pre-exposed MDDCs; (ii) responsiveness exacerbated by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, and further up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs compared, to mock-stimulated Jurkat-pre-exposed MDDCs, and further down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; (iii) responsiveness attenuated by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, but down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, but up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; (iv) responsiveness abolished by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs, but not differentially expressed in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs, but not differentially expressed in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs. Statistical analysis Median fluorescence intensity and percentages of gated cells were determined from flow cytometry analysis with FlowJo software. Data were analyzed using Prism 8 (GraphPad Software). The central tendency represents the mean, and the error bar represents the standard error of the mean (SEM).Statistical analysis was performed as follows: normality of the dataset was tested using Shapiro Wilk test. If the dataset followed a Gaussian distribution, differences among means were tested using Repeated measures one-way ANOVA, or Ordinary one-way ANOVA when the dataset contained missing values. Post-hoc comparisons with the mean of the control condition (exposure to uninfected Jurkat T cells) were assessed with Dunnet's test. Note that for Fig. 1 e, Sidak's test was used to compare the means of the C91-PL-exposed MDDCs depending on their capture status. When normality of the dataset was not met, analysis was performed using Friedman test, or Kruskal Wallis test when the dataset had missing values. Post-hoc comparisons with the mean of the control condition (exposure to uninfected Jurkat T cells) were performed using Dunn's test. For main Figures that are subsets of larger supplementary figures, the indicated p-values are reported from the analysis on the total dataset. When only two groups were compared, statistical analysis was performed using parametric paired t-test (Figs. 5 c and 6 c, Sup Fig. 8b) or its non-parametric equivalent Wilcoxon matched-pairs signed rank test (Fig. 5 c). Note that a parametric unpaired Welch’s t-test was used to analyze Fig. 6 g due to the uneven number of replicates. The potential correlation investigated in Supplementary Fig. 2i was fitted with a simple linear regression model. p-value < 0.05 was considered significant, and statistics are denoted as * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001. Declarations Data Availability The RNA-seq raw data generated in the present study were deposited in GEO under the accession number GSE266976. Acknowledgements We dedicate this work to the memory of Pr. Renaud Mahieux. We thank the Retroviral Oncogenesis team, as well as Dr. Arnaud Moris, Dr. Sylvain Baize, Dr. Anne-Sophie Beignon, Pr. Luc Willems, Dr. Franck Halary, Dr. Claudine Pique, Pr. Mathias Faure and Dr. Delphine Muriaux for helpful discussion and/or critical reading of the manuscript. This work has benefited from the facilities and expertise of the SFR Biosciences Lyon (UMS3444/CNRS, US8/Inserm, ENS de Lyon, UCBL). We acknowledge the contribution of the Etablissement Français du Sang Auvergne - Rhône-Alpes, and we thank Dr. Marlène Dreux (CIRI) and her team for the help with PBMC isolation. We thank Dr. Carine Rey (BIBS, CIRI, Lyon) for her help with RNA-seq data analysis. This work was supported by the “Fondation pour la Recherche Médicale, équipe labellisée” program (grant number DEQ. 20180339200), and by the “Agence Nationale de la Recherche” (grant number ANR-22-CE15-0044). AC and CJ are funded by the ENS de Lyon. FM, SA, and HD are funded by Inserm. CM is funded by CNRS. Author Contributions Conception and design of the work: HD. Acquisition, analysis, or interpretation of data: AC, FM, SA, CM, CJ, HD. Initial draft of the manuscript: AC, HD. Revision of the manuscript: HD, CM, FM and CJ. Approval of manuscript: AC, SA, CM, FM, CJ and HD. Competing Interests statement The authors declare no competing interests. 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Supplementary Files SupFiguresv20240426legendspdf.pdf nreditorialpolicychecklist.pdf nrreportingsummary.pdf SupTable1DEGrelativetoFig2andSupFig4.xlsx Dataset1 SupTable2KEGGpathwaysrelativetoFig2andFig4.xlsx Dataset 2 SupTable3DEGineachKEGGpathwayrelativetoFig2.xlsx Dataset 3 SupTable4DEGrelativetoFig4.xlsx Dataset 4 SupTable5DownDEGineachKEGGpathwayrelativetoFig4.xlsx Dataset 5 SupTable6UpDEGineachKEGGpathwayrelativetoFig4.xlsx Dataset 5 SupTable7SourceData.xlsx Dataset 7 SupTable8SourceDataSup.xlsx Dataset 8 SupplementaryTablesLegends.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4413764","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":305125058,"identity":"47bfbff7-2cca-44b1-a3fe-2f68b2ea47dd","order_by":0,"name":"Hélène Dutartre","email":"data:image/png;base64,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","orcid":"","institution":"INSERM","correspondingAuthor":true,"prefix":"","firstName":"Hélène","middleName":"","lastName":"Dutartre","suffix":""},{"id":305125059,"identity":"2a50fc06-f698-4583-b89f-5a3baedcefb0","order_by":1,"name":"Auriane Carcone","email":"","orcid":"https://orcid.org/0000-0003-0378-6822","institution":"ENS de Lyon","correspondingAuthor":false,"prefix":"","firstName":"Auriane","middleName":"","lastName":"Carcone","suffix":""},{"id":305125060,"identity":"9b1e79d9-4f45-4f12-b286-3f5ad983f545","order_by":2,"name":"Franck Mortreux","email":"","orcid":"https://orcid.org/0000-0002-4840-021X","institution":"INSERM","correspondingAuthor":false,"prefix":"","firstName":"Franck","middleName":"","lastName":"Mortreux","suffix":""},{"id":305125061,"identity":"11bd3382-9b9a-4bdc-9d11-a2b878b6583d","order_by":3,"name":"Sandrine Alais","email":"","orcid":"","institution":"INSERM","correspondingAuthor":false,"prefix":"","firstName":"Sandrine","middleName":"","lastName":"Alais","suffix":""},{"id":305125062,"identity":"de4229b8-d5c9-45df-9299-bdba5b4adba1","order_by":4,"name":"Cyrille Mathieu","email":"","orcid":"https://orcid.org/0000-0002-6682-2029","institution":"CIRI, Centre International de Recherche en Infectiologie, Team Immuno-Biology of Viral Infections, Univ Lyon, Inserm, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, ENS de Lyon","correspondingAuthor":false,"prefix":"","firstName":"Cyrille","middleName":"","lastName":"Mathieu","suffix":""},{"id":305125063,"identity":"df633e8b-1785-437f-badd-12be340f9468","order_by":5,"name":"Chloe Journo","email":"","orcid":"https://orcid.org/0000-0002-0973-0777","institution":"CIRI","correspondingAuthor":false,"prefix":"","firstName":"Chloe","middleName":"","lastName":"Journo","suffix":""}],"badges":[],"createdAt":"2024-05-13 14:10:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4413764/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4413764/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57177883,"identity":"84b54ece-4bc6-49c5-9e27-ae030b1d9e1d","added_by":"auto","created_at":"2024-05-27 03:19:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":374413,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHuman MDDCs do not fully mature when exposed to HTLV-1-infected T cells. a.\u003c/strong\u003e Schematic representation of the experimental setting. From day 0 (d0), monocytes were differentiated into MDDCs by a 5-day culture in the presence of IL-4 and GM-CSF. At day 5 (d5), MDDCs were cocultured with control uninfected or HTLV-1-infected T cell lines for 24h (or 48h, see Supplementary Fig. 2a-f). Alternatively, MDDCs were stimulated with GFP-expressing MeV or LPS (control stimuli) for 24h (or 48h, see Supplementary Fig. 2a-f). Cells and culture supernatants were collected at d6 (or d7, see Supplementary Fig. 2a-f). \u003cstrong\u003eb.\u003c/strong\u003e Flow cytometry analysis at d6 after CD11c and CD86 staining. The percentage of CD86\u003csup\u003e+\u003c/sup\u003e MDDCs (indicated gate) among total CD11c\u003csup\u003e+\u003c/sup\u003e MDDCs was quantified. \u003cstrong\u003eLeft\u003c/strong\u003e: representative experiment. \u003cstrong\u003eRight\u003c/strong\u003e: results from n=3 independent experiments, analyzed with RM one-way ANOVA as described in Supplementary Table 7. \u003cstrong\u003ec.\u003c/strong\u003e Supernatant from the indicated cocultures or from LPS-stimulated MDDCs was collected at d6, and TNF-α (\u003cstrong\u003etop\u003c/strong\u003e) and IFN-I (\u003cstrong\u003ebottom\u003c/strong\u003e) were quantified by Luminex and reporter cell assay, respectively. Results from n=3 or 8 independent experiments, respectively. Presented data are a subset of Supplementary Figure 2g analyzed with RM one-way ANOVA (top) or Kruskal-Wallis test (bottom) as described in Supplementary Table 7\u0026amp;8. \u0026nbsp;\u003cstrong\u003ed. \u003c/strong\u003eViral capture in MDDCs cocultured with Jurkat or C91-PL T cells was assessed at d6 by Gag p19 staining on CD11c\u003csup\u003e+\u003c/sup\u003e MDDCs. The percentage of Gag p19\u003csup\u003e+\u003c/sup\u003e and Gag p19\u003csup\u003e-\u003c/sup\u003e MDDCs among total CD11c\u003csup\u003e+\u003c/sup\u003e MDDCs was determined. \u003cstrong\u003eLeft\u003c/strong\u003e: representative experiment. \u003cstrong\u003eRight\u003c/strong\u003e: results from n=14 independent experiments analyzed with Kruskal-Wallis test as described in Supplementary Table 7\u0026amp;8 as a subset of Supplementary Figure 2h. \u003cstrong\u003ee.\u003c/strong\u003e Flow cytometry analysis after CD11c, Gag p19 and CD86 staining. \u003cstrong\u003eLeft\u003c/strong\u003e: representative experiment. Dashed lines: LPS-exposed MDDCs. Solid black lines: Jurkat-exposed MDDCs, light blue line: Gag p19\u003csup\u003e-\u003c/sup\u003e MDDCs. Magenta lines: Gag p19\u003csup\u003e+\u003c/sup\u003e MDDCs. \u003cstrong\u003eRight\u003c/strong\u003e: the same color code is used to represent results from n=15 independent experiments analyzed with one-way ANOVA as described in Supplementary Table 7. \u003cstrong\u003ef.\u003c/strong\u003e Schematic drawing summarizing the results from Fig. 1 and Supplemental Fig. 2 . The drawing was created using BioRender.com\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/57209a01a6e75c2e7d530a5a.png"},{"id":57177890,"identity":"4f17c17e-70c1-4613-b50a-4a901e4315ef","added_by":"auto","created_at":"2024-05-27 03:19:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":248031,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs\u003c/strong\u003e. MDDCs were cocultured for 24h with control Jurkat cells, or with HTLV-1-infected C91‑PL cells, or with control Jurkat cells in the presence of LPS. Cells were then separated and RNA-seq analysis was performed on MDDCs in 3 independent replicates. \u003cstrong\u003ea.\u003c/strong\u003e Principal component analysis of global similarities in gene expression between samples (DC_ JK: MDDCs after coculture with Jurkat cells, green; DC_JK_LPS: MDDCs after coculture with Jurkat cells in the presence of LPS, red; DC_C91: MDDCs after coculture with C91-PL cells, blue). \u003cstrong\u003eb.\u003c/strong\u003e Volcano plot of DEGs between MDDCs exposed to C91-PL and MDDCs exposed to Jurkat cells. \u003cstrong\u003ec.\u003c/strong\u003e KEGG pathways analysis performed on the 435 upregulated DEGs. Bars represent the fold-enrichments, while dots represent the p-values expressed as log10 for each pathway, or their respective mean for grouped pathways (see Supplemental Table 2). \u0026nbsp;\u003cstrong\u003ed. \u003c/strong\u003eVenn diagram of the DEGs in C91-PL-exposed MDDCs compared to Jurkat-exposed MDDCs (blue circle), and of the LPS-modulated DEGs in Jurkat-exposed MDDCs (red circle). \u003cstrong\u003ee-f.\u003c/strong\u003eHeatmap of the 373 shared (\u003cstrong\u003ee\u003c/strong\u003e) and 101 unique (\u003cstrong\u003ef\u003c/strong\u003e) DEGs. Gene expression was normalized per row. \u003cstrong\u003eg. \u003c/strong\u003eDESeq2 normalized counts for \u003cem\u003eELOVL3\u003c/em\u003e, \u003cem\u003eFADS1\u003c/em\u003e, and \u003cem\u003eSLC27A6\u003c/em\u003e across samples.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/56be73a78c8ca82b79c8a092.png"},{"id":57177882,"identity":"3530c010-f3a3-4c53-88c3-e7dc3f540c36","added_by":"auto","created_at":"2024-05-27 03:19:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":190445,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePre-exposure to HTLV-1-infected T cells dampens the responsiveness of MDDCs to subsequent stimulation. a.\u003c/strong\u003e Schematic representation of the experimental setting. MDDCs were exposed to uninfected (Jurkat, green) or HTLV-1-infected T cells (C91-PL, blue) for 24h, before restimulation with LPS or R848 for an additional 24h. \u003cstrong\u003eb.\u003c/strong\u003e Flow cytometry analysis after CD11c and CD86 staining, in LPS- (\u003cstrong\u003eleft\u003c/strong\u003e) or R848-restimulated MDDCs (\u003cstrong\u003eright\u003c/strong\u003e) pre-exposed to Jurkat (red) or C91-PL (dark blue) cells. Data are represented as the normalized MFI of CD86, with the MFI in restimulated Jurkat-pre-exposed MDDCs set to 100 (n=30 or 10 independent experiments, respectively). Presented data are a subset of Supplementary Figure 5a or 5d, respectively and were analysed with Kruskal-Wallis test or ordinary one-way ANOVA, respectively as described in Supplementary Table 7\u0026amp;8 \u003cstrong\u003ec.\u003c/strong\u003e Supernatant from the indicated cocultures was collected after LPS restimulation, and TNF-α (\u003cstrong\u003eleft\u003c/strong\u003e) and IFN-I (\u003cstrong\u003eright\u003c/strong\u003e) concentrations were quantified for n=3 or 10 independent experiments, respectively. Presented data are a subset of Supplementary Figure 5e and were analysed with RM one-way ANOVA or ordinary one-way ANOVA, respectively as described in Supplementary Table 7\u0026amp;8. \u003cstrong\u003ed.\u003c/strong\u003e Schematic drawing summarizing the results from Fig. 2 and Supplemental Fig. 5. The drawing was created using BioRender.com.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/352705ba721fa5d043611152.png"},{"id":57177888,"identity":"1bf7fc60-b729-456a-b077-bcb862c7e570","added_by":"auto","created_at":"2024-05-27 03:19:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":442266,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePre-exposure to HTLV-1-infected T cells alters the transcriptional response of MDDCs to subsequent stimulation. \u003c/strong\u003eMDDCs were cocultured for 24h with Jurkat cells, or with HTLV-1-infected C91‑PL or C8166 cells, before restimulation with LPS for an additional 24h. Cells were then separated and RNA-seq analysis was performed on MDDCs in 3 independent replicates. \u003cstrong\u003ea.\u003c/strong\u003e Principal component analysis of global similarities in gene expression between samples (DC_JK_LPS: Jurkat-pre-exposed MDDCs after LPS restimulation, red; DC_C91_LPS: C91-PL-pre-exposed MDDCs after LPS restimulation, pink, DC_C81_LPS: C8166-pre-exposed MDDCs after LPS restimulation, purple). \u003cstrong\u003eb.\u003c/strong\u003e Volcano plot of DEGs between C91-PL-pre-exposed MDDCs after LPS restimulation, and Jurkat-pre-exposed MDDCs after LPS restimulation. \u003cstrong\u003ec.\u003c/strong\u003e KEGG pathways analysis performed on the 403 downregulated DEGs (\u003cstrong\u003eleft\u003c/strong\u003e) or on the 921 upregulated DEGs (\u003cstrong\u003eright\u003c/strong\u003e). Bars represent the fold-enrichments, while dots represent the p-values expressed as log10 for each pathway, or their respective mean for grouped pathways. \u003cstrong\u003ed.\u003c/strong\u003e Heatmaps and DESeq2 normalized counts across samples of illustrative genes, showing expression across samples of genes belonging to the “conferred” (\u003cstrong\u003etop\u003c/strong\u003e), “exacerbated” (\u003cstrong\u003emiddle\u003c/strong\u003e) or “attenuated or abolished” (\u003cstrong\u003ebottom\u003c/strong\u003e) responsiveness pattern.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/b404617148dca257a913511a.png"},{"id":57177896,"identity":"95899d7e-8117-43e6-ac46-19410e8b39af","added_by":"auto","created_at":"2024-05-27 03:19:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":253048,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNeither HTLV-1 viral capture, nor cell-cell contact with infected T cells, are strictly required to dampen the responsiveness of MDDCs to subsequent stimulation. a-b.\u003c/strong\u003e MDDCs were cocultured for 24h with Jurkat cells, or with HTLV-1-infected C91‑PL or C8166 cells, in the absence (\u003cstrong\u003ea\u003c/strong\u003e) or presence (\u003cstrong\u003eb\u003c/strong\u003e) of a transwell insert (0.4µm pore diameter), before re-stimulation with LPS for an additional 24h. Flow cytometry analysis after CD11c and CD86 staining. Data are represented as the normalized MFI of CD86, with the MFI in re-stimulated Jurkat-exposed MDDCs set to 100 (\u003cstrong\u003eleft\u003c/strong\u003e), or as the percentage of CD86\u003csup\u003e+\u003c/sup\u003e MDDCs (\u003cstrong\u003eright\u003c/strong\u003e), and summarize n=21 (\u003cstrong\u003ea\u003c/strong\u003e) or n=5 (\u003cstrong\u003eb\u003c/strong\u003e) independent experiments. Red: Jurkat-exposed MDDCs restimulated with LPS; dark blue: C91-PL pre-exposed MDDCs restimulated with LPS; purple: C8166 pre-exposed MDDCs restimulated with LPS. Detailed statistical analysis is presented in Supplementary Table 7. Briefly, the statistical difference between means was tested using RM one-way ANOVA (a, left and b, right) or Friedman test (a, right and b, left), in accordance with the distribution. \u003cstrong\u003ec.\u003c/strong\u003e Paired percentage of CD86\u003csup\u003e+\u003c/sup\u003e MDDCs in standard coculture (as measured in \u003cstrong\u003ea\u003c/strong\u003e),\u003cstrong\u003e \u003c/strong\u003eor with a transwell insert (as measured in \u003cstrong\u003eb\u003c/strong\u003e),\u003cstrong\u003e \u003c/strong\u003ewith HTLV-1-infected C91‑PL (\u003cstrong\u003eleft\u003c/strong\u003e) or C8166 cells (\u003cstrong\u003eright\u003c/strong\u003e). Data summarized n=4 or 5 independent experiments, respectively analysed with paired t-test or its non parametric equivalent Wilcoxon matched-pairs signed rank test as described in Supplementary Table 7. \u003cstrong\u003e\u0026nbsp;d.\u003c/strong\u003e Schematic drawing summarizing the results from Fig. 5 and Supplemental Fig. 8. The drawing was created using BioRender.com.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/f1ccce729babc862fe334e4a.png"},{"id":57177898,"identity":"4c8248ed-28e9-4e79-b8fd-200b4b0790f1","added_by":"auto","created_at":"2024-05-27 03:19:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":270475,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA molecular dialogue between HTLV-1-infected T cells and MDDCs induces the release of soluble tolerogenic mediators. a.\u003c/strong\u003e Schematic representation of the experimental setting. MDDCs were cocultured for 24h with uninfected Jurkat cells, or with HTLV-1-infected C91‑PL or C8166 cells. Conditioned medium was collected and added on naive autologous MDDCs for 24h, before restimulation with LPS for an additional 24h. \u003cstrong\u003eb.\u003c/strong\u003e Flow cytometry analysis after CD11c and CD86 staining. Data are represented as the normalized MFI of CD86, with the MFI in re-stimulated MDDCs cultured in MDDC/Jurkat-conditioned medium set to 100. The color code is the same as in Fig. 5. Data summarize n=5 (C91-PL) or n=3 (C8166) independent experiments analysed with ordinary one-way ANOVA as described in Supplementary Table 7. \u003cstrong\u003ec.\u003c/strong\u003eAnalysis of paired experiments, after standard coculture with C91-PL (\u003cstrong\u003eleft\u003c/strong\u003e) or C8166 cells (\u003cstrong\u003eright\u003c/strong\u003e,\u003cstrong\u003e \u003c/strong\u003eas measured in \u003cstrong\u003eFig. 5a\u003c/strong\u003e), or after culture in conditioned medium from MDDC/C91-PL coculture or from MDDC/C8166 coculture (n=5 or 3 independent experiments, respectively). Data were analysed with Paired t-test as described in Supplementary Table 7. \u003cstrong\u003ed.\u003c/strong\u003e Schematic representation of the experimental setting. MDDCs were cocultured with C91-PL, and conditioned medium was collected at multiple time points of coculture and added on naïve autologous MDDCs for 24h, before re-stimulation with LPS for another 24h. \u003cstrong\u003ee.\u003c/strong\u003e Flow cytometry analysis after CD11c and CD86 staining. Data are represented as the normalized MFI of CD86, with the MFI in LPS-stimulated MDDCs cultured in normal medium set to 100 (n=6 and n=3 independent experiments, for \u0026lt;12h and for 18h and 24h conditions, respectively). Data were analysed with ordinary one-way ANOVA as described in Supplementary Table 7. \u003cstrong\u003ef.\u003c/strong\u003e Schematic representation of the experimental setting. MDDCs were cocultured for 24h with C91-PL. Conditioned medium was collected and added on naive autologous MDDCs for the indicated time, before re-stimulation with LPS for another 24h. \u003cstrong\u003eg.\u003c/strong\u003e Flow cytometry analysis after CD11c and CD86 staining. Data are represented as the normalized MFI of CD86, with the MFI in LPS-stimulated MDDCs cultured in normal medium set to 100 (independent experiments were performed using n=7 for \u0026lt;12h condition, n=3 for 18h condition and n=2 for 24h condition). Statistical analysis of the two first columns was performed with Unpaired Welch’s t-test. \u003cstrong\u003eh.\u003c/strong\u003e Schematic drawing summarizing the results from Fig. 6 and Supplemental Fig. 9. The drawing was created using BioRender.com.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/259353c1935af79d4999a943.png"},{"id":57178995,"identity":"f3c5e162-a05f-4e3a-916e-7bf7ef501a0c","added_by":"auto","created_at":"2024-05-27 03:43:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2821922,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/a65d4833-95b0-4016-9f70-4677edf39b1d.pdf"},{"id":57177885,"identity":"eae1b5a6-b704-463b-ba46-7c0b477d8372","added_by":"auto","created_at":"2024-05-27 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03:19:54","extension":"xlsx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":97184,"visible":true,"origin":"","legend":"\u003cp\u003eDataset 8\u003c/p\u003e","description":"","filename":"SupTable8SourceDataSup.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/97537c5039424116676a51f5.xlsx"},{"id":57177889,"identity":"45e5f79e-7745-49cd-ad92-022eeb90f54e","added_by":"auto","created_at":"2024-05-27 03:19:53","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":14119,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4413764/v1/ab12e19c43946e9714c3e113.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Induction of tolerogenicity following a molecular dialogue between HTLV-1-infected T cells and dendritic cells","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic infection by the deltaretrovirus Human T-cell Leukemia Virus type 1 (HTLV-1) generally remains asymptomatic, but leads to severe diseases in 5 to 10% of infected individuals\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, in the form of Adult T-cell Leukemia/Lymphoma (ATL), or Tropical Spastic Paraparesis/HTLV-1 Associated Myelopathy (TSP/HAM). Remarkably, HTLV-1 chronic infection increases the risk of viral, bacterial or parasitic co-infections\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In agreement with these clinical observations, immune dysfunctions have been repeatedly reported in asymptomatic HTLV-1 carriers, years before severe diseases were diagnosed, indicating that chronic infection induces systemic effects and impairs the ability of the immune system to respond appropriately to infectious and non-infectious triggers\u003csup\u003e\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Dendritic cells (DCs) are critical mediators of innate and adaptive immune responses during viral infection. Upon efficient viral recognition, DCs undergo a maturation program that renders them capable of inducing specific T-cell responses. The DC maturation process is characterized by a transcriptional program that translates, among others, in the upregulation of several maturation markers at the cell surface (\u003cem\u003ee.g.\u003c/em\u003e CD80, CD86), accompanied by the secretion of pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α), and antiviral cytokines such as type I interferons (IFN-I)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, inappropriate DC responses can contribute to immunopathology, a process that is exacerbated in chronic viral infections\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe role of DCs in HTLV-1 infection has been extensively investigated in terms of viral transmission to CD4\u003csup\u003e+\u003c/sup\u003e T cells, both \u003cem\u003ein vitro\u003c/em\u003e\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e and in animal models\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Whether HTLV-1 induces the maturation of DCs has been investigated \u003cem\u003ein vitro\u003c/em\u003e, but only using murine bone marrow-derived DCs exposed to cell-free Moloney-pseudotyped chimeric HTLV-1\u003csup\u003e15\u003c/sup\u003e. Given that cell-free HTLV-1 is not detected in HTLV-1 carriers or patients, \u003cem\u003ein vivo\u003c/em\u003e DCs are probably mostly exposed to chronically infected cells rather than cell-free virus. Hence, these experimental settings may not fully recapitulate \u003cem\u003ein vivo\u003c/em\u003e virus / host interactions.\u003c/p\u003e \u003cp\u003eStrikingly, myeloid cells such as monocytes and DCs can harbor infectious HTLV-1 genomes in infected individuals, including in asymptomatic individuals\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and exhibit impaired phenotypes and functions\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e that may correlate with their proviral load\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. These observations in humans indicate that HTLV-1 could in fact dampen the responsiveness of infected DCs, which may ultimately contribute to immune dysfunction during chronic infection. Accordingly, DCs derived from ATL patients exhibit maturation defects\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e associated with an inability to induce proliferation of CD4\u003csup\u003e+\u003c/sup\u003e T cells\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, because the proportion of DCs infected \u003cem\u003ein vivo\u003c/em\u003e is low, the impact of HTLV-1 on DC function might not be solely attributed to HTLV-1-infected DCs, suggesting that HTLV-1 could indirectly modulate the functions of DCs, in the absence of direct infection. In this work, we aimed at determining whether HTLV-1 transformed T cells could indirectly affect human DC functions \u003cem\u003ein vitro\u003c/em\u003e. In contrast with previous work using murine cells and cell-free virus, we show that upon coculture with HTLV-1 transformed T cell lines, human monocyte-derived DCs (MDDCs) do not fully mature. We further show that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs, which differs from a typical maturation program, and which is correlated with a dampened responsiveness of HTLV-1-exposed MDDCs to subsequent stimulation. Interestingly, this tolerogenic behavior is induced as the result of a molecular dialogue between HTLV-1-infected T cells and MDDCs upon coculture. This unique mechanism of viral-induced tolerance in DCs illustrates how HTLV-1 might indirectly manipulate innate cells to induce a local immune microenvironment suitable for its own persistence.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHuman MDDCs do not fully mature when exposed to HTLV-1-infected T cells\u003c/h2\u003e \u003cp\u003eTo determine whether chronically infected T cells could directly or indirectly manipulate human DC functions \u003cem\u003ein vitro\u003c/em\u003e, we first addressed whether infected T cells were sensed by DCs. We used human monocyte-derived DCs (MDDCs) cultured \u003cem\u003ein vitro\u003c/em\u003e with HTLV-1-infected and transformed T cell lines, and assessed MDDCs maturation by flow cytometry after 24h or 48h of coculture, using the MDDC-specific CD11c marker to identify MDDCs in the coculture (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea for the experimental settings, \u003cb\u003eand Supplementary Fig.\u0026nbsp;1\u003c/b\u003e for the gating strategy). At these time points, less than 1% of MDDCs have integrated the viral genome and they do not release virions\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, indicating that they are not productively infected. In contrast to MDDCs exposed to measles virus (MeV), MDDCs exposed to HTLV-1 transformed C91-PL cells, failed to fully upregulate CD86, used in this first experiment as a surrogate of DC maturation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, \u003cb\u003eleft panel\u003c/b\u003e). Repeated experiments using MDDC samples from independent donors showed that while around 90% of MDDCs upregulated CD86 upon exposure to MeV, regardless of their ability to express MeV (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, \u003cb\u003eright panel\u003c/b\u003e, compare total versus GFP\u003csup\u003e\u0026minus;\u003c/sup\u003e and GFP\u003csup\u003e+\u003c/sup\u003e MDDCs), as well as upon stimulation by the TLR-4 agonist LPS (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, \u003cb\u003eright panel\u003c/b\u003e), the percentage of activated MDDCs after coculture with HTLV-1-transformed C91-PL cells remained low (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, \u003cb\u003eright panel\u003c/b\u003e). To exclude a cell line-specific effect, and to thoroughly characterize MDDCs maturation status, MDDCs were exposed to several control uninfected T cell lines (\u003cb\u003eSupplementary Fig.\u0026nbsp;2a-f\u003c/b\u003e; Jurkat, CEM or Molt-4 T cell lines, green bars), as well as to several HTLV-1-transformed T cell lines (\u003cb\u003eSupplementary Fig.\u0026nbsp;2a-f; C91\u003c/b\u003e-PL, MT-2 or Hut102; blue bars), and the regulation of both maturation markers CD86, CD83, CD80, and CD40, (\u003cb\u003eSupplementary Fig.\u0026nbsp;2a-d\u003c/b\u003e) and inhibition markers ICOSL and PD-L1 (\u003cb\u003eSupplementary Fig.\u0026nbsp;2e-f\u003c/b\u003e) at the cell surface was monitored by flow cytometry. All the HTLV-1-transformed T cell lines induced either no change, or only minor changes, in the expression (percentage of positive cells and normalized mean signal intensity, MFI) of maturation or inhibition markers at the surface of cocultured MDDCs (\u003cb\u003eSupplementary Fig.\u0026nbsp;2a-f\u003c/b\u003e). Increasing the duration of coculture to 48h did not impact these observations (\u003cb\u003eSupplementary Fig.\u0026nbsp;2a-f\u003c/b\u003e), excluding a delay in maturation. The inefficient upregulation of MDDC maturation markers was also accompanied by a low ability to secrete TNF-α or IFN-I (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec and \u003cb\u003eSupplementary Fig.\u0026nbsp;2g\u003c/b\u003e), strengthening the notion that HTLV-1-infected T cells do not induce a typical maturation program in MDDCs, and thus might not be efficiently sensed by human DCs, in contrast to observations made with cell-free virus in a mouse model\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Since similar observations were made with all HTLV-1-infected T cell lines tested, and with the tested maturation markers and cytokines, only the C91-PL T cell line and CD86 were used in some of the following experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePrevious work from our laboratory showed that MDDCs efficiently capture HTLV-1 after coculture with HTLV-1-infected T cell lines\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, suggesting that in our experimental conditions, HTLV-1 capture itself is inefficient in driving MDDC maturation. To formally demonstrate this, we assessed HTLV-1 capture in MDDCs following coculture, by staining the HTLV-1 Gag p19 structural protein. As expected, MDDCs were efficient at capturing HTLV-1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed), irrespective of the infected T cell line used in the coculture (\u003cb\u003eSupplementary Fig.\u0026nbsp;2h\u003c/b\u003e), with around 30% of capture observed in a representative coculture experiment with C91-PL cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed, \u003cb\u003eleft\u003c/b\u003e), and reaching up to 80% of capture observed in repeated experiments using independent donors (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed, \u003cb\u003eright\u003c/b\u003e). Maturation was then compared in MDDCs that had not captured HTLV-1 (Gag p19-negative MDDCs, cyan, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee), or had captured HTLV-1 (Gag p19-positive MDDCs, magenta, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). Although CD86 expression was consistently higher in p19-positive MDDCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, \u003cb\u003eright\u003c/b\u003e, compare cyan and magenta bars), the percentage of Gag p19-positive cells remained low compared to fully matured LPS-exposed MDDCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, compare magenta and red bars), highlighting that maturation remained inefficient even in MDDCs that had capture HTLV-1. No significant correlation was detected among repeated experiments between the level of HTLV-1 capture and the efficiency of MDDC maturation (\u003cb\u003eSupplementary Fig.\u0026nbsp;2i, p\u003c/b\u003e\u0026thinsp;=\u0026thinsp;0.1412), further confirming that HTLV-1 capture itself is inefficient in driving MDDC maturation.\u003c/p\u003e \u003cp\u003eTaken together, these observations, recapitulated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef, demonstrate that cell-associated HTLV-1 fails to fully mature MDDCs, suggesting that it is poorly sensed by these human innate cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs\u003c/h2\u003e \u003cp\u003eInterestingly, our previous work demonstrated that in contrast to MDDCs, plasmacytoid dendritic cells (pDC) do efficiently sense cell-associated HTLV-1\u003csup\u003e20\u003c/sup\u003e. Inefficient sensing of HTLV-1-infected T cells by MDDCs could be the result of either a stealth behavior of cell-associated virus towards MDDCs, resulting in a \u003cem\u003ebona fid\u003c/em\u003ee lack of response specifically in this cell type, or, alternatively, to the active manipulation of MDDC functions by HTLV-1-infected T cells, resulting in a specific response that differs from a typical maturation program. To discriminate between both these scenari, we aimed at determining the complete transcriptomic landscape of MDDCs after exposure to HTLV-1-infected T cells, or to control uninfected T cells, using bulk RNA-seq (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After 24h of coculture, MDDCs were magnetically separated from C91-PL or control Jurkat T cells, based on the exclusive expression of CADM1 on T cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;3a\u003c/b\u003e). Note that although the levels of CADM1 were higher at the surface of C91-PL cells compared to Jurkat cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;3a\u003c/b\u003e), a similar MDDC enrichment yield of around 99% was observed after separation in both conditions, with no significant T cell contamination (\u003cb\u003eSupplementary Fig.\u0026nbsp;3b\u003c/b\u003e). LPS-stimulated MDDCs were also included in the RNA-seq analysis, as a reference for fully matured MDDCs. RNA was extracted from each MDDC sample, and submitted to quality control followed by sequencing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFirst, to show global similarities in gene expression between samples, unsupervised hierarchical clustering and principal component analysis (PCA) were performed on normalized transcript count tables. Analysis of sample clustering along the two first PCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, PC1 and PC2), that explain 81 and 8% of the total variance, respectively, showed that the main source of variance in the dataset was the stimulation by LPS, followed by the infection status of cocultured T cells, while the identity of the MDDC donor contributed only weakly to the global variance. In agreement with flow cytometry data shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, this confirmed, at the transcriptional level, the inefficient activation of MDDCs after exposure to HTLV-1-infected T cells, which contrasts with the typical maturation program of fully activated MDDCs. This also indicates that exposure to HTLV-1-infected T cells does induce a detectable, yet subtle, transcriptional response, when compared to exposure to uninfected T cells.\u003c/p\u003e \u003cp\u003eTo characterize the changes in gene expression in MDDCs induced by exposure to HTLV-1-infected T cells, we used DESeq2 to identify differentially expressed genes (DEGs) between C91-PL- and Jurkat-exposed MDDCs. As a reference for a typical maturation program, we identified DEGs between LPS- and Jurkat-exposed MDDCs. Using a fold-change cut-off of 2, a total number of 474 DEGs were obtained between C91-PL- and Jurkat-exposed MDDCs (padj\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with 435 genes found significantly upregulated upon HTLV-1 exposure, and 39 genes found significantly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb and \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). A heatmap of the 474 DEGs showed clustering between samples, as expected (\u003cb\u003eSupplementary Fig.\u0026nbsp;4a\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eTo gain insight into the processes modulated in MDDCs after exposure to HTLV-1-infected T cells, we performed gene ontology analysis on the set of 435 upregulated genes. Over-represented KEGG pathways were retrieved and filtered to reduce redundancy (see \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e), leading to a final list of 7 pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and \u003cb\u003eSupplementary Tables\u0026nbsp;2 and 3\u003c/b\u003e). Strikingly, exposure to HTLV-1-infected T cells was characterized by significant over-representation of upregulated genes involved in lipid biosynthesis and metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Interestingly, genes involved in several pathways linked with response to viral infection were also over-represented, including genes involved in innate immune sensing (sub-pathways: RIG-I or Toll-like receptors and NOD-like receptors), in viral infection (sub-pathways: Influenza A, Measles, Hepatitis C, Hepatitis B, Human Papillomavirus, Herpes simplex virus 1, Coronavirus, HIV, EBV), and in the NF-κB signaling pathway. Taken together, these results confirm that exposure to HTLV-1-infected T cells does induce a transcriptional response in MDDCs, indicating that sensing does occur to some extent, but does not culminate in a typical maturation and anti-viral program.\u003c/p\u003e \u003cp\u003eTo further determine the extent to which this transcriptional response is distinct from a typical maturation signature, we compared the genes affected by LPS stimulation of Jurkat-exposed MDDC to those affected by MDDC exposure to C91-PL. Among the 474 DEGs, 373 genes were also differentially expressed after LPS stimulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed), representing only 5% of all LPS-modulated genes. Among these shared genes, 7 genes annotated as involved in the NF-κB signaling pathway were retrieved, including \u003cem\u003eCCL19, TNFSF13B, TRIM25, BCL2L1\u003c/em\u003e and \u003cem\u003eBCL2A1\u003c/em\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;4b\u003c/b\u003e). However, the level of up-regulation of these shared NF-κB-related genes was strikingly lower after HTLV-1 exposure compared to LPS stimulation (\u003cb\u003eSupplementary Fig.\u0026nbsp;4b\u003c/b\u003e). This observation of a lower magnitude of differential expression (either up- or downregulation) was general to most of the 373 shared DEGs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). Of note, the \u003cem\u003eRELA, RELB\u003c/em\u003e and \u003cem\u003eNFKB1\u003c/em\u003e genes that were upregulated by LPS stimulation were not upregulated upon C91-PL exposure (\u003cb\u003eSupplementary Fig.\u0026nbsp;4c\u003c/b\u003e), possibly contributing to the lower activation of the NF-κB-dependent genes observed above (\u003cb\u003eSupplementary Fig.\u0026nbsp;4b\u003c/b\u003e). In addition, among the 377 Interferon-Stimulated Genes (ISG) listed in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e, only 121 were retrieved in the set of significantly upregulated genes, and again, their up-regulation was lower to that induced by LPS stimulation (\u003cb\u003eSupplementary Fig.\u0026nbsp;4d\u003c/b\u003e). These observations strengthen the notion that while sensing of HTLV-1-infected T cells does occur to some extent, the magnitude of the maturation and antiviral transcriptional response remains very limited, which is consistent with the inefficient maturation of MDDCs observed at the protein level (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, among the 474 DEGs, 101 genes were not present in the list of DEGs between LPS- and Jurkat-exposed MDDCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed \u003cb\u003eand f\u003c/b\u003e), defining a unique transcriptional signature associated with the exposure to HTLV-1-infected C91PL cells. Due to the limited number of genes included in this specific signature, gene ontology analysis was not feasible. Interestingly however, several genes retrieved in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec as those involved in lipid biosynthesis and metabolism, were also included in this specific signature, such as \u003cem\u003eELOVL3\u003c/em\u003e (Elongation of Very Long Fatty Acid Elongase 3), \u003cem\u003eFADS1\u003c/em\u003e (Fatty Acid Desaturase 1), and \u003cem\u003eSLC27A6\u003c/em\u003e (Solute Carrier Family 27 Member 6, a member of the fatty acid transport protein family) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg). Altogether, these transcriptomic analyses demonstrate that exposure to HTLV-1-infected T cells is not completely silent in MDDCs, but rather results in a unique transcriptional response that differs from a typical maturation program. This supports the notion that HTLV-1-infected T cells might actively manipulate MDDC functions to limit their functional response, possibly by rewiring lipid biosynthesis and metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePre-exposure to HTLV-1-infected T cells dampens the responsiveness of MDDCs to subsequent stimulation\u003c/h2\u003e \u003cp\u003eWe next aimed at investigating whether this unique transcriptional response observed upon exposure to HTLV-1-infected T cells indeed translates into functional defects in MDDCs, beyond their inefficient maturation. To this end, we addressed whether pre-exposure to HTLV-1-infected cells influenced MDDC responsiveness when exposed to a subsequent stimulation. After 24h of coculture with HTLV-1-infected T cell lines, MDDCs were restimulated with strong inducers of MDDCs maturation, in the form of LPS (TLR-4 ligand) or R848 (TLR-7/8 ligand, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), for another 24h. When compared to MDDCs pre-exposed to uninfected control T cell lines (red bars), MDDCs pre-exposed to HTLV-1-transformed T cells (dark blue bars) upregulated CD86 (as well as other maturation markers) to a significantly lower extent when stimulated by LPS or R848 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, \u003cb\u003eSupplementary Fig.\u0026nbsp;5a-d\u003c/b\u003e). In addition, TNF-α secretion by MDDCs upon LPS stimulation was also significantly reduced by pre-exposure to HTLV-1-transformed T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, left panel, \u003cb\u003eSupplementary Fig.\u0026nbsp;5e\u003c/b\u003e), while IFN-I secretion was not affected (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, right panel, \u003cb\u003eSupplementary Fig.\u0026nbsp;5e\u003c/b\u003e). These results indicate that pre-exposure to HTLV-1-transformed T cells indeed influences the responsiveness of MDDCs to subsequent stimulation, by specifically dampening their pro-inflammatory response (monitored here through the upregulation of maturation markers and through TNF-α secretion), without hampering their antiviral response (monitored here through IFN-I secretion) (recapitulated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). This suggests that HTLV-1 might specifically manipulate the responsiveness of certain signaling pathways in MDDCs, such as the NF-κB pathway upstream of the pro-inflammatory program, while leaving the responsiveness of others unaffected, such as the IRF3 pathway upstream of the antiviral program.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003ePre-exposure to HTLV-1-transformed T cells alters the transcriptional response of MDDCs to subsequent stimulation\u003c/h2\u003e \u003cp\u003eTo obtain a broader overview of how pre-exposure to HTLV-1-transformed T cells affects the responsiveness of MDDCs, a second bulk RNA-seq analysis was conducted on MDDCs pre-exposed to an HTLV-1-infected T cell line (C91-PL), or to a control uninfected T cell line (Jurkat), and then restimulated by LPS (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). To address whether viral capture was required for this manipulation of MDDC responsiveness, we also included in the RNA-seq analysis MDDCs cocultured with the HTLV-1-infected C8166 T cell line that does not produce viral particles\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. As expected, no viral particle was captured by C8166-exposed MDDCs, in contrast to C91-PL-exposed MDDCs (\u003cb\u003eSupplementary Fig.\u0026nbsp;6\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePCA analysis of samples showed that both the donor and the infection status of cocultured T cells were the main sources of variance in the dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), confirming that pre-exposure to HTLV-1-transformed T cells does alter the transcriptional response of MDDCs to subsequent stimulation. In contrast, the ability to capture HTLV-1 did not contribute to a visible extent to the global variance, suggesting that viral capture might not be required for this alteration.\u003c/p\u003e \u003cp\u003eWe then retrieved the lists of genes differentially expressed between the different experimental conditions. In agreement with the PCA analysis, 1324 genes were found differentially expressed between LPS-stimulated C91-PL-pre-exposed MDDCs, and LPS-stimulated Jurkat-pre-exposed MDDCs (\u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e), with a total of 403 DEGs being downregulated and 921 DEGs being upregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Gene ontology analysis was conducted on these sets of downregulated and upregulated genes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, left and right panels, respectively). The set of downregulated genes was characterized by a significant over-representation of genes annotated as being involved in TNF-α or NF-κB signaling and innate immune sensing (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, left panel, arrows, see \u003cb\u003eSupplemental Table\u0026nbsp;5\u003c/b\u003e). Conversely, the set of upregulated genes was characterized by a significant over-representation of genes annotated as being involved in the TGF-β signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, right panel, arrow, see \u003cb\u003eSupplemental Table\u0026nbsp;6\u003c/b\u003e). This confirmed that pre-exposure to HTLV-1-transformed T cell does influence the transcriptional response to LPS stimulation.\u003c/p\u003e \u003cp\u003eTo further identify the expression patterns of these genes differentially expressed between LPS-stimulated C91-PL-pre-exposed MDDCs, and LPS-stimulated Jurkat-pre-exposed MDDCs, we classified these genes based on their differential expression across conditions (detailed in \u003cb\u003eSupplemental Fig.\u0026nbsp;7a\u003c/b\u003e, see also \u003cb\u003eSupplementary Table\u0026nbsp;4)\u003c/b\u003e as follows: (i) Genes whose responsiveness to LPS (be it repression or induction) is specifically conferred by pre-exposure to infected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, upper panel). (ii) Genes whose responsiveness to LPS (be it induction or repression) is exacerbated by pre-exposure to infected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, middle panel). (iii) Genes whose responsiveness to LPS is attenuated or (iv) abolished by pre-exposure to infected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, lower panel). This classification demonstrates that pre-exposure to HTLV-1-transformed T cells induces both a change in the identity of genes that transcriptionally respond to LPS stimulation, defining a unique LPS-induced transcriptional signature; and a change in the magnitude of the transcriptional response of genes that are normally responsive to LPS.\u003c/p\u003e \u003cp\u003eIn line with the gene ontology analysis presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, the responsiveness of genes involved in NF-κB signaling, such as \u003cem\u003eMYD88\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, lower panel, see graph), or the pro-inflammatory genes \u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eIL12B\u003c/em\u003e, \u003cem\u003eTNF\u003c/em\u003e, \u003cem\u003eCXCL10\u003c/em\u003e and \u003cem\u003eCXCL11\u003c/em\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;7b\u003c/b\u003e, upper panel), was found drastically attenuated by pre-exposure to infected cells (C91-PL or C8166). This could account for the inefficient maturation and production of pro-inflammatory cytokines by HTLV-1-pre-exposed MDDCs after LPS stimulation, which was observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. In addition, in line with the gene ontology analysis presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec, genes of the TGF-β signaling pathway, including \u003cem\u003eBMP6, BMP7\u003c/em\u003e, and \u003cem\u003eIL13\u003c/em\u003e (\u003cb\u003eSupplementary Fig.\u0026nbsp;7b\u003c/b\u003e, middle panel), which do not respond to LPS in normal conditions, were found to be responsive to LPS when MDDCs were pre-exposed to HTLV-1-transformed cells, while the responsiveness of \u003cem\u003eTGFB2\u003c/em\u003e, which is repressed upon LPS stimulation in normal conditions, was abolished by pre-exposure to HTLV-1-infected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, lower panel, see graph). Interestingly, these genes encode cytokines known to participate in the induction of a tolerogenic immune microenvironment, with Treg and T\u003csub\u003eH\u003c/sub\u003e2 responses, which are inefficient at controlling viral infection. Finally, pre-exposure to HTLV-1-transformed cells also conferred responsiveness to \u003cem\u003eDDIT4\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed, upper panel, see graph), a gene reported in other contexts of tolerogenicity\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Of note, and in agreement with the efficient induction of IFN-I after LPS stimulation in both Jurkat- or C91PL-pre-exposed MDDCs (see Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec), the responsiveness of \u003cem\u003eISGs\u003c/em\u003e such as \u003cem\u003eISG15, IFI44\u003c/em\u003e and \u003cem\u003eIRF2\u003c/em\u003e was not affected by pre-exposure to HTLV-1-infected cells (\u003cb\u003eSupplementary Fig.\u0026nbsp;7b\u003c/b\u003e, lower panel).\u003c/p\u003e \u003cp\u003eAltogether, this transcriptomic analysis indicated that pre-exposure to HTLV-1-transformed T cells influences the responsiveness of MDDCs to subsequent stimulation, by specifically dampening their pro-inflammatory response at the transcriptional level. In addition, it uncovered the fact that pre-exposure to HTLV-1-transformed T cells allows a unique set of genes to respond to LPS stimulation, triggering a biased, pro-tolerogenic response of MDDCs upon subsequent stimulation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNeither HTLV-1 viral capture, nor cell-cell contact with infected T cells, are strictly required to dampen the responsiveness of MDDCs to subsequent stimulation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs stated above, RNA-seq analysis using the C8166 infected cell line suggests that viral capture might not be required to alter the transcriptional response of MDDCs to a secondary stimulation. To confirm this notion at the functional level, we repeated the coculture experiment followed by LPS stimulation, and analyzed MDDC maturation profile by flow cytometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). Despite the lack of viral particle capture by C8166-exposed MDDCs (see \u003cb\u003eSupplementary Fig.\u0026nbsp;6\u003c/b\u003e), C8166 pre-exposure still dampened the responsiveness of MDDCs to LPS and R848 stimulation, as monitored through CD86, CD83 or CD80 upregulation, similar to C91-PL pre-exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea \u003cb\u003eand Supplemental Fig.\u0026nbsp;8a\u003c/b\u003e), confirming that viral capture is not strictly required. Although C8166 do not produce viral particles, they might still engage in cell-cell contacts with MDDCs\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, which could be the trigger of the dampening of MDDC responsiveness. We addressed this hypothesis by performing the cocultures in transwells, in which MDDCs were physically separated from infected T cells by a permeable membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Of note, reduced but detectable levels of viral capture were detected in MDDCs physically separated from C91-PL (\u003cb\u003eSupplementary Fig.\u0026nbsp;8b\u003c/b\u003e), most probably because the virus is preferentially associated to the cell surface of infected cells and might be released as large adhesive viral aggregates\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e poorly able to cross the 0.4\u0026micro;m pores of the permeable membrane. The absence of physical contact between MDDCs and infected T cells, either producing (C91-PL) or not producing viral particles (C8166), did not restore a fully efficient maturation after LPS stimulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), indicating that cell-cell contacts are not strictly required to allow HTLV-1-infected T cells to manipulate MDDC responsiveness. Of note however, C8166 cells appeared less efficient than C91PL cells in dampening MDDC responsiveness upon transwell coculture. This could result from additive effects of mechanisms dependent on viral capture on the one hand, and of cell-cell contact on the other hand: indeed, in the presence of cell-cell contacts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), the contribution of viral capture might be negligible; while in the absence of cell-cell contacts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb), such contribution might become relatively more important. Consistently, comparison of MDDC responsiveness in paired experiments of MDDC pre-exposed to infected cells with (coculture) or without (transwell) physical contacts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) showed that preventing physical contacts between MDDCs and infected cells resulted in a slightly higher, yet not significantly different, MDDC responsiveness (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). This indicates that viral capture and/or cell-cell contacts may participate, but are not strictly required to allow HTLV-1-infected T cells to manipulate MDDC responsiveness, and suggests the contribution of a distantly acting set of soluble mediators.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eA molecular dialogue between HTLV-1-infected T cells and MDDCs induces the release of soluble tolerogenic mediators\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSince neither viral particles nor cell-cell contacts are strictly required to manipulate MDDC responsiveness, we then tested the conditioning ability of the supernatant of HTLV-1-infected T cells. More specifically, we hypothesized that IL-10 produced by HTLV-infected T cells\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e could be a candidate mediator, as it was reported to have tolerogenic properties\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, except for the supernatant of the MT-2 infected T cell line, IL-10 was not detected in the supernatant of any of the other infected T cell lines (\u003cb\u003eSupplementary Fig.\u0026nbsp;9a\u003c/b\u003e). More surprisingly, none of these supernatants were sufficient to manipulate MDDC responsiveness, as MDDCs pre-incubated in these supernatants still efficiently matured upon LPS stimulation (\u003cb\u003eSupplementary Fig.\u0026nbsp;9b\u003c/b\u003e). This suggested that MDDC manipulation requires a molecular dialogue between HTLV-1-transformed T cells and MDDCs that would lead to the production of soluble tolerogenic mediators upon coculture. To test this hypothesis, we collected the conditioned medium of MDDCs cocultured with infected T cells for 24h, and used it to culture fresh, na\u0026iuml;ve MDDCs derived from the same monocyte donor (autologous cells) for 24h, before LPS stimulation for another 24h (see Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea for the experimental settings). In contrast to supernatant of infected T cells alone (\u003cb\u003eSupplementary Fig.\u0026nbsp;9b\u003c/b\u003e), the supernatant from the co-culture was still able to dampen the responsiveness of MDDCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb), although with less potency compared to coculture with infected T cells, as observed by analysis of paired experiments (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). This is consistent with the tendency observed upon transwell cultures (see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec), and confirms the release of soluble tolerogenic mediators following a molecular dialogue between infected T cells and MDDCs upon coculture, which could cooperate with other mechanisms dependent on viral capture and/or cell-cell contacts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we addressed the kinetics of the molecular dialogue required for the release of these mediators. Conditioned medium of MDDCs cocultured with infected T cells were collected over time, and used to culture fresh autologous MDDCs before the addition of LPS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). A lowered responsiveness of MDDCs was only observed with supernatants collected at least 18h after coculture (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee), suggesting that the mediators is produced and released after a transcriptional response. Alternatively, we tested the kinetics required for the mediators to manipulate MDDC responsiveness. Conditioned medium of MDDCs cocultured with infected T cells was collected after 24h, and used to culture fresh autologous MDDCs for a varying duration before the addition of LPS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). A lowered responsiveness of MDDCs was only observed when MDDCs were cultured for at least 18h with the conditioned medium before adding the LPS (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg). The manipulation of MDDC responsiveness might thus also rely on a transcriptional control, which is consistent with the unique transcriptional signature induced by exposure to HTLV-1-infected T cells observed by RNA-seq.\u003c/p\u003e \u003cp\u003eAltogether, our results (recapitulated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh) show that upon coculture, a molecular dialogue is initiated between HTLV-1-transformed T cells and MDDCs, which results in the transcriptionally-controlled release of a set of soluble tolerogenic mediators that manipulates MDDC responsiveness, in cooperation with additional mechanisms dependent on viral capture and/or cell-cell contacts.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe remarkable ability of viruses to manipulate intracellular pathways in infected host cells is essential for establishing and maintaining infection. In addition to these direct effects, viruses may also establish a specific microenvironment around infected cells, which may favor viral spread and persistence by influencing the signaling pathways and behavior of neighboring, uninfected cells, including immune cells\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. As a by-stander effect, this may alter immune responsiveness to other stimuli. Mechanisms by which viruses influence uninfected cells in their local environment are still poorly understood. In this study, we aimed to decipher how HTLV-1-infected cells indirectly manipulate cocultured DCs. We demonstrate that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in DCs, preventing their maturation and impairing their ability to be subsequently activated. This induction of tolerogenicity is not directly caused by infection of DCs, but instead results from a molecular dialogue between infected T cells and DCs, reminiscent of a viral microenvironment\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious work on the interplay between HTLV-1 and DCs has focused on the role of DCs as intermediate target cells for HTLV-1 transmission to T cells\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Several studies investigated whether viral capture by DCs could lead to T cell cis- and/or trans-infection, and whether specific DC subtypes or maturation statuses could impact this proviral function. In particular, in a previous paper, we demonstrated that immature MDDCs do efficiently capture and transmit HTLV-1 to T cells, while mature MDDCs do not efficiently transmit HTLV-1 to T cells, despite high levels of viral capture\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. While these data indicated that the maturation status of DCs could impact their proviral functions, they did not address whether exposure to HTLV-1 induced a antiviral immune response by DCs. Such a question was investigated in pDCs, which we showed to be efficient at sensing HTLV-1-infected cells after cell-cell contact, and at responding by producing IFN-I\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Here, we specifically addressed how MDDCs respond to HTLV-1 exposure. Intriguingly, our results are in stark contrast to those obtained in pDCs, as we show that MDDCs do not respond to HTLV-1-infected T cells by activating a typical maturation and antiviral program, even in the presence of cell-cell contact. The unique transcriptional response observed could be the result of a specific molecular dialogue occurring between HTLV-1-infected T cells and MDDCs, that does not occur with pDCs. Alternatively, this molecular dialogue could also occur with pDCs, but be outperformed by the highly efficient capacity of pDCs to produce IFN-I. Investigating how pDC added to the coculture between HTLV-1-infected T cells and MDDCs could modulate this induction of tolerogenicity, and how this tolerogenic behavior would shape HTLV-1 transmission to uninfected T cells, would give insight into how these distinct behaviors are integrated into the microenvironment system. Of note, our results are also in contrast with data obtained on murine DCs, using cell-free HTLV-1\u003csup\u003e15\u003c/sup\u003e. This underlines the importance of working with human cells when investigating HTLV-1/host interactions.\u003c/p\u003e \u003cp\u003eOur data point towards the release of soluble tolerogenic mediators following a molecular dialogue between infected T cells and MDDCs upon coculture, which could cooperate with other mechanisms dependent on viral capture and/or cell-cell contacts. The identity of the soluble mediators initiating the molecular dialogue observed between HTLV-1-infected T cells and MDDCs, as well as produced as a result of this dialogue, is currently under investigation in our laboratory. As we observed that conditioned medium from infected T cells alone did not induce the tolerogenic behavior of MDDCs, but that conditioned medium from infected T cells cocultured with MDDCs did, it raises the hypothesis that HTLV-1-infected T cells sense a soluble factor released by MDDCs, that activates the release of a second soluble factor by infected T cells. This second factor could then launch a specific transcriptomic response in MDDCs that would lead to tolerogenicity. Among potential soluble mediators produced by HTLV-1-infected cells, exosomes emerge as compelling candidates. Their composition could be modified by viral infection, explaining the differences observed in MDDC responses between exposure to uninfected or infected T cells. Also, their production by T cells could be boosted by coculture with MDDCs, explaining the requirement of a molecular dialogue between both cell types. Last, the diameter of exosomes, around 100 nm, is compatible with their diffusion through the pores of the transwell (0.4 \u0026micro;m) used in our experimental settings. Interestingly, several HTLV-1-infected T cell lines, independently of their ability to produce viral particles or not, do produce exosomes containing cytokines, viral proteins and RNA\u003csup\u003e\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e able to modulate target cells, resulting in an increased susceptibility to infection\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. We can thus hypothesize that in our experimental settings, these exosomes could modulate DC functions, inducing the unique transcriptional signature that we observe. This would be reminiscent of data obtained on Epstein-Barr Virus (EBV), where infection changes the ability of exosomes purified from gastric cancer cell lines to mature MDDCs, leading to a defect in CD86 upregulation and reduced tumor immunity\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWhether HTLV-1 proteins contained in exosomes could contribute to the induction of tolerogenicity remains to be investigated. Viral proteins such as p30, HBZ, and Tax are found in exosomes produced by infected cells\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, independently of the production of viral particles by these infected cells. In addition, these viral proteins have the potential to interfere with immune functions. For instance, p30 expressed in MDDCs reduces IFN-I responses upon TLR3/4 stimulation, but not upon TLR7/8 stimulation\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, suggesting a specific targeting of the TLR3/4 signaling pathway. However, as we found no alteration in the IFN response of LPS restimulated, HTLV-1-pre-exposed MDDCs, a role of p30 can be excluded. In contrast, HBZ is known to inhibit the NF-κB pathway\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e by degrading the transcription factor p65\u003csup\u003e35\u003c/sup\u003e. As we observed the repression of the NF-κB pathway in HTLV-1-pre-exposed MDDCs upon LPS restimulation, we could suggest that exosome-transferred HBZ could contribute to modulating MDDC functions.\u003c/p\u003e \u003cp\u003eInterestingly, following the molecular dialogue between infected T cells and MDDCs, we observed the upregulation of genes involved in fatty acid metabolism (such as \u003cem\u003eELOVL3\u003c/em\u003e, \u003cem\u003eFADS1\u003c/em\u003e, and \u003cem\u003eSLC27A6\u003c/em\u003e) in MDDCs. As these genes are not found in the typical maturation program of MDDCs, it raises the possibility that upon coculture with HTLV-1-infected T cells, MDDCs produce fatty acids, that may act in a autocrine and paracrine manner to modulate MDDC functions. Of note, fatty acid precursors such as squalene and vitamin D are recognized inducers of tolerogenic DCs\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Polyinsaturated fatty acids have also been shown to block DC activation and functions\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, and inhibition of fatty acid synthesis has been shown to increase their production of pro-inflammatory cytokines\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Whether HTLV-1-exposed MDDCs produce higher levels of fatty acids, and whether these could contribute to their observed tolerogenic behavior, is currently under investigation. Thus, our transcriptomic analysis reveals how viruses could indirectly rewire lipid metabolism in immune cells to modulate the immune microenvironment.\u003c/p\u003e \u003cp\u003eUpon restimulation with LPS, HTLV-1-pre-exposed MDDCs undergo a specific transcriptomic response, including an abolished downregulation of \u003cem\u003eTGFB\u003c/em\u003e expression, which remains highly expressed, and upregulation of \u003cem\u003eIL13\u003c/em\u003e expression, which could be the basis for their tolerogenic properties. Of note, from the literature, the exact transcriptomic program underlying the tolerogenic behavior of DCs is unclear, as different transcriptomic signatures have been reported\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Nonetheless, a set of common genes has been defined as a gene signature of tolerogenic DCs\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, including \u003cem\u003eDDIT4\u003c/em\u003e (DNA-damage-inducible transcript 4), which encodes an inhibitor of mTOR signaling\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Interestingly, responsiveness of \u003cem\u003eDDIT4\u003c/em\u003e was also specifically conferred by pre-exposure to infected cells. Thus, the transcriptomic program induced in HTLV-1-pre-exposed MDDCs by LPS restimulation partially mirrors the tolerogenic DC signature defined in other contexts.\u003c/p\u003e \u003cp\u003eIn conclusion, our study demonstrates that exposure to HTLV-1-transformed cells can indirectly distort the functionality of DCs and impair their response to subsequent stimulation. Our \u003cem\u003ein vitro\u003c/em\u003e results are consistent with \u003cem\u003ein vivo\u003c/em\u003e observations, which report that MDDCs from HTLV-1-infected patients exhibit deficiencies in both basal maturation and responsiveness to TNF-α treatment, as well as defects in the induction of T-cell response\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In addition, PBMCs from HTLV-1-infected patients stimulated with tuberculin produce fewer TNF-α than PBMC isolated from healthy individuals\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Finally, the fact that viral production is not necessary to dampen MDDC responsiveness, might reflect the \u003cem\u003ein vivo\u003c/em\u003e situation in which HTLV-1 expression is repressed in chronically infected cells\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Therefore, it is plausible that defects in the myeloid cell response, particularly in DCs, may represent a mechanism of HTLV-1 pathogenesis \u003cem\u003ein vivo\u003c/em\u003e. Thus, this work illustrates how HTLV-1 might induce a local immune microenvironment suitable for its own persistence. Such microenvironnement may additionally contribute to by-stander immune dysfunctions, in asymptomatic HTLV-1 carriers as well as symptomatic HTLV-1-infected patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCells lines\u003c/h2\u003e \u003cp\u003eHTLV-1 infected T-cell lines (C91-PL from Cellosaurus ref CVCL_0197, MT-2 ref CVCL_2631\u003csup\u003e45\u003c/sup\u003e, Hut102 ref CVCL_3526\u003csup\u003e46\u003c/sup\u003e and C8166 ref ECACC 88051601\u003csup\u003e21\u003c/sup\u003e) and control uninfected T-cell lines (Jurkat from ATCC ref ACC 282, CEM/C1 ref CRL-2265, Molt-4 Cellosaurus ref CVCL_0013) were maintained at a cell density of 0.5.10\u003csup\u003e6\u003c/sup\u003e cells/mL in complete RPMI medium: RPMI1640 GlutaMAX (Gibco; 61870010) supplemented with 10% fetal calf serum (FCS) and penicillin-streptomycin (100 U/mL and 100 \u0026micro;g/mL respectively).\u003c/p\u003e \u003cp\u003eThe human fibrosarcoma cell line HL116 stably expressing the firefly luciferase reporter gene under the control of the immediate early IFN-I inducible 6\u0026ndash;16 promoter (kindly provided by Dr. S. Pelligrini, Institut Pasteur, France\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e) was maintained under HAT selection (Gibco; 21060017, used at 1X final concentration) in DMEM GlutaMAX pyruvate medium (Gibco; 10569010) supplemented with 10% FCS and penicillin-streptomycin (100 U/mL and 100 \u0026micro;g/mL respectively).\u003c/p\u003e \u003cp\u003eAll cells were grown at 37\u0026deg;C in 5% CO\u003csub\u003e2\u003c/sub\u003e and tested negative for mycoplasma contamination on a regular basis. None of the cell lines were authenticated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eHuman primary monocyte-derived dendritic cells (MDDCs)\u003c/h2\u003e \u003cp\u003eMDDCs were derived from purified monocytes from healthy blood donors as described previously\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Briefly, blood samples were collected at Etablissement Fran\u0026ccedil;ais du Sang (EFS) from anonymous healthy blood donors according to the institutional Standard Operating Procedures for blood donation, including a signed informed consent. Blood was diluted in PBS 1X (Gibco) and peripheral blood mononuclear PBMCs were isolated using a density gradient separation using Ficoll-Paque (Fisher Scientific, 11778538). Monocytes were then isolated from PBMCs using a density gradient separation using Percoll Centrifugation Medium (Fisher Scientific, 10607095). Freshly or frozen monocytes were cultured in six-well plates at 3.10\u003csup\u003e6\u003c/sup\u003e cells/mL in complete MDDC medium: RPMI1640 GlutaMAX (Gibco) supplemented with 10% FCS, penicillin-streptomycin (100 U/mL and 100 \u0026micro;g/mL respectively), Hepes buffer (Gibco, 15630080; 10 mM), MEM non-essential amino acids (2,5mM, Gibco, 11140050), sodium pyruvate (Gibco, 11360070; 1 mM), and beta-mercaptoethanol (Gibco, 31350-010; 0.05 mM). MDDC medium was supplemented with IL-4 and GM-CSF (Miltenyi Biotec, 130-093-922 and 130-093-866; 100 ng/mL each) for differentiation. On day 3, the culture medium was refreshed by discarding half of the medium and adding the same volume of new MDDC medium and twice concentrated IL-4 and GM-CSF to all cell cultures. Immature MDDCs were harvested on day 5 or 6. Every experiment was repeated on MDDCs derived from independent blood donors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eReagents and antibodies\u003c/h2\u003e \u003cp\u003eToll-like receptor (TLR)-4 agonist (LPS, tlrl-3pelps; 1\u0026micro;g/mL) and TLR-7/8 agonist (R848, tlrl-r848; 3\u0026micro;g/mL) were purchased from Invivogen. MeV IC323-eGFP \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e is a recombinant MeV expressing the gene-encoding eGFP (using the plasmid-encoding MeV IC323-eGFP kindly provided by Yanagi, Kyushu University, Fukuoka, Japan). MeV IC323 recombinant virus was rescued in 293-3-46 cells, as previously described\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Production of the viruses was performed at 32\u0026deg;C. All viruses were propagated and titrated in Vero-SLAM/CD150 cells. MDDCs were infected using a multiplicity of infection (MOI) of 1.\u003c/p\u003e \u003cp\u003eThe following antibodies were used: V450-coupled mouse anti-Human CD11c (BD Biosciences, 560369; 1/100), PE-coupled mouse anti-Human CD86 (Invitrogen, 12-0869-42; 1/100), APC-coupled mouse anti-Human CD83 (Miltenyi Biotec, 130-094-186; 1/50), BV510-coupled mouse anti-Human CD83 (BD Biosciences, 563223; 1/50), APC-H7-coupled mouse anti-Human CD80 (BD Biosciences, 561134; 1/50), BB515-coupled mouse anti-Human PDL1 (BD Biosciences, 564554; 1/25), PE-Cy7-coupled mouse anti-Human ICOSL (BioLegend, 309410; 1/100), Mouse anti-Gagp19 clone TP7 (Zeptometrix, 081107; 1/500), AlexaFluor647-coupled Alpaca anti-Mouse IgG1 (Chromotek, sms1AF647-1-5; 1/500), Biotin-coupled mouse anti-Human CADM1 (MBL Life Sciences, CM004-6; 1/1000), AlexaFluor647-coupled mouse streptavidin (Invitrogen, S31374; 1/500).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMDDCs coculture experiment\u003c/h2\u003e \u003cp\u003eImmature MDDCs (3.10\u003csup\u003e5\u003c/sup\u003e cells) were plated in 48-well plates and cocultured with HTLV-1-infected or control uninfected T-cells (6.10\u003csup\u003e4\u003c/sup\u003e cells) in 300\u0026micro;L complete MDDC medium supplemented with IL-4 and GM-CSF for 24h or 48h. When indicated, transwell 24-well plates with permeable polycarbonate membrane inserts (0.4\u0026micro;m diameter) were used (Fisher Scientific, 10147291). Alternatively, MDDCs were cultured in supernatant collected from either HTLV-1-infected or control uninfected T-cell culture, or from coculture of MDDCs with HTLV-1-infected cells or control uninfected T-cell during 24h (or the indicated duration). After 24h, cells were harvested, or stimulated with LPS or R848 or medium for an additional 24h (or the indicated duration). At the indicated time points, cells and supernatants were collected for phenotyping using flow cytometry and for cytokine quantification, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry analysis\u003c/h2\u003e \u003cp\u003eTo assess surface marker expression, cells were fixed using 4% paraformaldehyde (PFA) diluted from 20% PFA (Electron Microscopy Science, 50-980-493) in PBS 1X, and stained with the indicated surface markers antibodies diluted in PBS 1X-1% Bovine Serum Albumin (BSA) for 20 min at 4\u0026deg;C. To assess viral capture, cells were fixed and permeabilized using the Fix/Perm FoxP3 and Transcription factors kit (Invitrogen, 00-5523-00) according to the manufacturer\u0026rsquo;s instructions, and stained with mouse anti-Gagp19 antibody followed by the AlexaFluor647-coupled anti-mouse antibody diluted in the PERM buffer supplemented with 7% Normal Goat Serum (NGS) for 25 min at room temperature. Cells were then stained for the indicated surface markers diluted in PBS 1X 1% BSA as described above. Compensation beads (BD Biosciences, 552843) were used to correct signal overlap between the emission spectra of the different fluorophores.\u003c/p\u003e \u003cp\u003eData were acquired using a flow cytometer FACS CantoII (BD Biosciences) and analyzed with FlowJo v10.7 software (BD Life Sciences). The full gating strategy is exemplified in \u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCytokine quantification\u003c/h2\u003e \u003cp\u003eTNF-α and IL-10 were quantified in the collected supernatants using Bio-Plex Pro Human Luminex kit (Bio-Rad) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eType I interferon quantification\u003c/h2\u003e \u003cp\u003eHL116 cells were seeded at 2.10\u003csup\u003e4\u003c/sup\u003e cells/well in 96-U-bottom-well plates and incubated for 24h. Supernatant collected from MDDCs culture (100 \u0026micro;L) or serial dilutions of recombinant IFN-α (Tebu-Bio, RPA033Gu02) used for standard curve determination were added for an additional 17h. Cells were then lysed (Promega Passive Lysis Buffer, E1941) and luciferase activity assayed according to the manufacturer\u0026rsquo;s instruction (Promega Luciferase Assay System, E1501).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMDDCs isolation after coculture\u003c/h2\u003e \u003cp\u003eCells from MDDC / T-cell lines coculture (1.10\u003csup\u003e6\u003c/sup\u003e MDDCs and 2.10\u003csup\u003e5\u003c/sup\u003e T-cells) were harvested and stained using biotin-coupled anti-CADM1 followed by AlexaFluor647-coupled streptavidin diluted in PBS 1X-1% BSA for 20 min at 4\u0026deg;C. After several washes in PBS, cells were then incubated with anti-AlexaFluor647 MicroBeads (Miltenyi Biotec, 130-091-395) and separated on MACS Separation LD Columns (Miltenyi Biotec, 130-042-901) according to the manufacturer\u0026rsquo;s instructions. To assess the purity and yield of enrichment of MDDCs after magnetic separation, 6.10\u003csup\u003e4\u003c/sup\u003e cells were collected before and after separation on LD columns, fixed in 4% PFA and stained with CD11c-V450 antibody, before analysis using FACS Canto II.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRNA preparation\u003c/h2\u003e \u003cp\u003eAfter magnetic separation, MDDCs were lysed and total RNA was extracted using the NucleoSpin RNA Mini kit for RNA purification (Macherey-Nagel, 740955) according to the manufacturer\u0026rsquo;s instructions. RNA concentration was determined with a NanoDropND1000 spectrophotometer (Thermo Fisher Scientific) and samples were stored at -80\u0026deg;C until shipment for external sequencing. Stranded RNA libraries were prepared after removal of rRNA. High throughput sequencing of 150 bp paired-end reads was performed with an Illumina HiSeq 2500 platform by Novogene Europe (Cambridge, United Kingdom). Each sample had on average 50\u0026nbsp;million matched pairs of reads.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eRNA-seq data analysis\u003c/h2\u003e \u003cp\u003eThe quality of sequences was checked using the FastQC tool. The reads were trimmed with PrinSeq\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e to remove low-quality bases and then mapped to the human reference transcriptome (hg19) using Kallisto pseudoalignment\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Differential gene analysis was carried out with DESeq2 package\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Genes with a basemean\u0026thinsp;\u0026gt;\u0026thinsp;10 showing an absolute fold change (FC)\u0026thinsp;\u0026ge;\u0026thinsp;2 with an adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Wald test using Benjamini and Hochberg method) were considered differentially expressed. All DEGs identified in this study are listed in Supplementary Tables\u0026nbsp;1 and 4. DAVID functional annotation tool using the KEGG pathways database was used for gene ontology analysis\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. For clarity, KEGG pathways were filtered and grouped as listed in Supplementary Table\u0026nbsp;2 to reduce redundancy.\u003c/p\u003e \u003cp\u003eTo identify the expression pattern responsiveness in LPS-stimulated MDDC pre-exposed to C91-PL, we retrieved the genes by Venn analysis using the following list of DEGs: MDDC/Jurkat restim.w/LPS vs MDDC/Jurkat; MDDC/C91-PL restim.w/LPS vs MDDC/Jurkat restim.w/LPS; MDDC/C91-PL restim.w/LPS vs MDDC/Jurkat. Then, genes were classified as follows (summarized in \u003cb\u003eSupplementary Fig.\u0026nbsp;7a\u003c/b\u003e): (i) responsiveness confered by pre-exposure to infected cells: genes that are not differentially expressed between mock- and LPS-stimulated Jurkat-pre-exposed MDDCs, but are differentially expressed (either up or down) between mock-stimulated Jurkat-pre-exposed MDDCs and LPS-stimulated C91-PL-pre-exposed MDDCs; (ii) responsiveness exacerbated by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, and further up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs compared, to mock-stimulated Jurkat-pre-exposed MDDCs, and further down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; (iii) responsiveness attenuated by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, but down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, but up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs; (iv) responsiveness abolished by pre-exposure to infected cells: genes that are either up-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as down-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs, but not differentially expressed in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs; or down-regulated in LPS-stimulated Jurkat-pre-exposed MDDCs compared to mock-stimulated Jurkat-pre-exposed MDDCs, as well as up-regulated in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to LPS-stimulated Jurkat-pre-exposed MDDCs, but not differentially expressed in LPS-stimulated C91-PL-pre-exposed MDDCs, compared to mock-stimulated Jurkat-pre-exposed MDDCs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eMedian fluorescence intensity and percentages of gated cells were determined from flow cytometry analysis with FlowJo software. Data were analyzed using Prism 8 (GraphPad Software). The central tendency represents the mean, and the error bar represents the standard error of the mean (SEM).Statistical analysis was performed as follows: normality of the dataset was tested using Shapiro Wilk test. If the dataset followed a Gaussian distribution, differences among means were tested using Repeated measures one-way ANOVA, or Ordinary one-way ANOVA when the dataset contained missing values. Post-hoc comparisons with the mean of the control condition (exposure to uninfected Jurkat T cells) were assessed with Dunnet's test. Note that for Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, Sidak's test was used to compare the means of the C91-PL-exposed MDDCs depending on their capture status.\u003c/p\u003e \u003cp\u003eWhen normality of the dataset was not met, analysis was performed using Friedman test, or Kruskal Wallis test when the dataset had missing values. Post-hoc comparisons with the mean of the control condition (exposure to uninfected Jurkat T cells) were performed using Dunn's test.\u003c/p\u003e \u003cp\u003eFor main Figures that are subsets of larger supplementary figures, the indicated p-values are reported from the analysis on the total dataset.\u003c/p\u003e \u003cp\u003eWhen only two groups were compared, statistical analysis was performed using parametric paired t-test (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec, Sup Fig.\u0026nbsp;8b) or its non-parametric equivalent Wilcoxon matched-pairs signed rank test (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). Note that a parametric unpaired Welch\u0026rsquo;s t-test was used to analyze Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg due to the uneven number of replicates.\u003c/p\u003e \u003cp\u003eThe potential correlation investigated in Supplementary Fig.\u0026nbsp;2i was fitted with a simple linear regression model. p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant, and statistics are denoted as * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, **** p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-seq raw data generated in the present study were deposited in GEO under the accession number GSE266976.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe dedicate this work to the memory of Pr. Renaud Mahieux. We thank the Retroviral Oncogenesis team, as well as Dr. Arnaud Moris, Dr. Sylvain Baize, Dr. Anne-Sophie Beignon, Pr. Luc Willems, Dr. Franck Halary, Dr. Claudine Pique, Pr. Mathias Faure and Dr. Delphine Muriaux for helpful discussion and/or critical reading of the manuscript. This work has benefited from the facilities and expertise of the SFR Biosciences Lyon (UMS3444/CNRS, US8/Inserm, ENS de Lyon, UCBL). We acknowledge the contribution of the Etablissement Fran\u0026ccedil;ais du Sang Auvergne - Rh\u0026ocirc;ne-Alpes, and we thank Dr. Marl\u0026egrave;ne Dreux (CIRI) and her team for the help with PBMC isolation. We thank Dr. Carine Rey (BIBS, CIRI, Lyon) for her help with RNA-seq data analysis. This work was supported by the \u0026ldquo;Fondation pour la Recherche M\u0026eacute;dicale, \u0026eacute;quipe labellis\u0026eacute;e\u0026rdquo; program (grant number DEQ. 20180339200), and by the \u0026ldquo;Agence Nationale de la Recherche\u0026rdquo; (grant number ANR-22-CE15-0044). AC and CJ are funded by the ENS de Lyon. FM, SA, and HD are funded by Inserm. CM is funded by CNRS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design of the work: HD. Acquisition, analysis, or interpretation of data: AC, FM, SA, CM, CJ, HD. Initial draft of the manuscript: AC, HD. Revision of the manuscript: HD, CM, FM and CJ. Approval of manuscript: AC, SA, CM, FM, CJ and HD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBangham CRM, Human T (2018) Cell Leukemia Virus Type 1: Persistence and Pathogenesis. Annu Rev Immunol 36:43\u0026ndash;71\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGordon CA et al (2021) HTLV-I and Strongyloides in Australia: The worm lurking beneath. Adv Parasitol 111:119\u0026ndash;201\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaziot ME et al (2019) Detection of clinical and neurological signs in apparently asymptomatic HTLV-1 infected carriers: Association with high proviral load. 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Nucleic Acids Res 50:W216\u0026ndash;221\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4413764/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4413764/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eManipulation of immune cell functions, independently of direct infection of these cells, emerges as a key process in viral pathophysiology. Chronic infection by Human T-cell Leukemia Virus type 1 (HTLV-1) is associated with immune dysfunctions, including misdirected responses of dendritic cells (DCs). Here, we interrogate the ability of HTLV-1-infected T cells to indirectly manipulate human DC functions. We show that upon coculture with chronically infected T cells, monocyte-derived DCs (MDDCs) fail to fully mature. We further show that exposure to HTLV-1-infected T cells induces a unique transcriptional signature in MDDCs, which differs from a typical maturation program, and which is correlated with a dampened ability of HTLV-1-exposed MDDCs to subsequently respond to restimulation. Induction of this tolerogenic behavior is not strictly dependent on capture of HTLV-1 viral particles by MDDCs, nor on cell-cell contacts between HTLV-1-infected T cells and MDDCs, but is instead the result of a molecular dialogue between HTLV-1-infected T cells and MDDCs upon coculture, illustrating how HTLV-1 might indirectly induce a local tolerogenic immune microenvironment suitable for its own persistence.\u003c/p\u003e","manuscriptTitle":"Induction of tolerogenicity following a molecular dialogue between HTLV-1-infected T cells and dendritic cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-27 03:19:46","doi":"10.21203/rs.3.rs-4413764/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6ee8573-1b25-438d-934a-fd657ee0bc1f","owner":[],"postedDate":"May 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32216473,"name":"Biological sciences/Microbiology/Virology/HTLV"},{"id":32216474,"name":"Biological sciences/Immunology/Infectious diseases/Viral infection"},{"id":32216475,"name":"Biological sciences/Immunology/Innate immune cells/Dendritic cells"}],"tags":[],"updatedAt":"2024-05-27T03:19:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-27 03:19:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4413764","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4413764","identity":"rs-4413764","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}