Tissue‐like environments shape functional interactions of HIV‐1 with immature dendritic cells

Abstract

Immature dendritic cells (iDCs) migrate in microenvironments with distinct cell and extracellular matrix densities in vivo and contribute to HIV‐1 dissemination and mounting of antiviral immune responses. Here, we find that, compared to standard 2D suspension cultures, 3D collagen as tissue‐like environment alters iDC properties and their response to HIV‐1 infection. iDCs adopt an elongated morphology with increased deformability in 3D collagen at unaltered activation, differentiation, cytokine secretion, or responsiveness to LPS. While 3D collagen reduces HIV‐1 particle uptake by iDCs, fusion efficiency is increased to elevate productive infection rates due to elevated cell surface exposure of the HIV‐1‐binding receptor DC‐SIGN. In contrast, 3D collagen reduces HIV transfer to CD4 T cells from iDCs. iDC adaptations to 3D collagen include increased pro‐inflammatory cytokine production and reduced antiviral gene expression in response to HIV‐1 infection. Adhesion to a 2D collagen matrix is sufficient to increase iDC deformability, DC‐SIGN exposure, and permissivity to HIV‐1 infection. Thus, mechano‐physical cues of 2D and 3D tissue‐like collagen environments regulate iDC function and shape divergent roles during HIV‐1 infection.

Immature dendritic cells contribute to HIV immune recognition and spread in tissue but are typically only studied in 2D suspension cultures. This study shows that 2D and 3D tissue environments markedly change the response of iDCs to HIV‐1 infection.

Introduction

Untreated HIV‐1 infection causes a complex disease that is primarily characterized by immunodeficiency induced by the progressive loss of CD4 T cells. In addition, systemic immune activation and HIV‐associated organ pathologies are associated with the development of AIDS. This broad spectrum of pathologies reflects that HIV infects and affects a wide range of cell types at various anatomical sites in the infected host. While transmission of HIV‐1 typically occurs at genital or rectal mucosal surfaces, transport to lymphoid organs is required to support pronounced virus replication and systemic dissemination (Hladik & McElrath, 2008). To achieve this complex journey, HIV‐1 must surmount mucosal, endothelial, and other substantial physical barriers to gain access to its target cells and cope with an array of innate and adaptive immune responses (Manches et al, 2014; Hertoghs et al, 2017; Nijmeijer et al, 2020). Moreover, the respective microenvironment in a given target tissue likely impacts the biological properties of target cells and their permissivity to HIV‐1 infection (Nijmeijer et al, 2020).

While HIV research increasingly focuses on studying the interactions of the virus with primary target cells instead of cell lines, these studies are mostly limited to investigation in standard two‐dimensional (2D) adhesion or suspension cultures that cannot take into account important parameters such as tissue architecture and composition, biophysical impact of the tissue environment, or cell communication and motility. To overcome these limitations and build on the overall characterization of HIV pathogenesis in in vivo animal models and AIDS patients, three‐dimensional (3D) culture models are increasingly employed to investigate the impact of local tissue environment on HIV replication and spread. This includes a series of organotypic explant models including tonsil, vaginal tissue, and skin to analyze functional cell–cell interactions at physiological tissue composition (Maher et al, 2005; Fackler et al, 2014; Real et al, 2018; Kaw et al, 2020). In parallel, synthetic 3D model systems emerge in which tighter control over experimental parameters such as biophysical and chemical cues of target tissue for mechanistic dissection can be obtained (Griffith & Swartz, 2006; Miron‐Mendoza et al, 2010; Muthinja et al, 2018; Abu‐Shah et al, 2019). We previously introduced 3D collagen matrices as scaffold for culturing primary human CD4 T lymphocytes to define that such tissue‐like environments markedly change kinetics and mode of HIV‐1 spread: while in standard 2D suspension cultures, HIV‐1 was able to spread with comparable efficiency via a cell‐free and cell‐associated transmission modes, cell‐free transmission was markedly reduced and cell‐associated spread significantly increased in 3D collagen (Imle et al, 2019; Ahmed et al, 2020). Consistent with intravital imaging analyses in infected humanized mice (Murooka et al, 2012; Usmani et al, 2019), the motility of infected CD4 T cells was a major determinant of HIV spread efficiency in 3D but not 2D cultures. While the infectivity of cell‐free HIV particles is reduced by tissue‐like environments, the permissivity of CD4 T cells for HIV‐1 infection increases in a 3D collagen environment (Lopez et al, 2022).

The results of these studies suggest that many fundamental aspects of interactions of HIV with its target cells can be affected by tissue‐like environments. Of particular interest in this context are dendritic cells (DCs), since they play multifactorial roles in innate immune recognition and dissemination of HIV‐1 (Luban, 2012; Nijmeijer et al, 2020). As DCs are among the first cells encountered by HIV‐1 at mucosal tissue during sexual transmission, they are believed to contribute to viral dissemination by capturing HIV‐1 particles and transferring them to CD4 T cells after having migrated to afferent lymph nodes (Geijtenbeek et al, 2000; Hladik et al, 2007). This can occur following productive cis‐infection of the DC, which requires fusion of the viral lipid envelope with the DC membrane, or upon transfer of cell associated or uptake of virus particles in the absence of infection (trans‐infection; Martin‐Moreno & Munoz‐Fernandez, 2019; Ruffin et al, 2019). DCs residing at mucosal surfaces are typically immature (immature DCs, iDCs) and more prone to productive infection than mature lymph‐node resident DCs (mature DCs, maDCs), which typically store HIV particles in an intracellular compartment for trans‐infection (Granelli‐Piperno et al, 1998; Felts et al, 2010; Izquierdo‐Useros et al, 2012). In addition, partially contradictory observations were made with iDCs, maDCs, and Langerhans cells with respect to reactions of DCs to exposure to HIV‐1 particles. These include innate sensing of various replication intermediates resulting in not only the production of pro‐inflammatory cytokines but also induction of antiviral gene expression by direct as well as paracrine mechanisms, alteration of cell activation, and induction of signaling cascades by abortive infection (Gringhuis et al, 2010; Manel et al, 2010; Lahaye et al, 2013, 2018; Hertoghs et al, 2017; Johnson et al, 2020). With respect to the physiological role of trans‐infection for virus spread in vivo, an important role of trans‐infection by maDCs has been established for the retrovirus murine leukemia virus (Sewald et al, 2015), but to which extent these results apply to HIV‐1 and iDCs remains unclear. While it is established that extrinsic conditions such as the general immune activation status or the local microbiota have marked impact on overall DC function as well as their interplay with HIV‐1 (Nijmeijer et al, 2020), the influence of a 3D scaffold has not been studied. We, therefore, set out to assess the impact of tissue‐like collagen environments on the ability of DCs to support and sense HIV‐1 replication. For these studies, we focused on iDCs to be able to study in parallel the impact of tissue‐like environments on iDC infection, HIV‐1 transfer to CD4 T cells, as well as on innate immune recognition. We report here that culturing in a 3D collagen matrix affects the functional properties of iDCs including their response to HIV‐1 infection and that adhesion to a 2D collagen surface is sufficient for some of these adaptations.

Results

iDCs adopt an elongated morphology associated with increased cell deformability in 3D collagen

To analyze the effect of a tissue‐like 3D collagen environment on the interplay of iDCs with HIV‐1, we adopted the comparison of 2D suspension and 3D collagen culture conditions we previously established for CD4 T lymphocytes to iDCs (Imle et al, 2019). iDCs were differentiated from peripheral blood monocytes by GM‐CSF/IL‐4 (Sallusto & Lanzavecchia, 1994) and then cultured in 2D suspension or embedded in 3D collagen (Fig 1A). FACS analysis of differentiation (CD1a) and activation (CD86, CD80, CD83, SIGLEC‐1, and DC‐SIGN) markers 6 days after the onset of differentiation confirmed the differentiation of monocytes into iDCs and the susceptibility of these iDCs to maturation by LPS (Fig EV1A). Spinning disc confocal microscopy revealed that culturing iDCs in 3D collagen resulted in a striking and rapid change in morphology from round cells with numerous and long dendrites in 2D suspension to elongated cells with short protrusions in 3D collagen (Fig 1B), which was maintained up to 4 days of culture (Fig EV1B). The morphology adopted by iDCs in 3D collagen is reminiscent of that found in DCs of mouse origin in vivo (Mempel et al, 2004; Lee et al, 2010). Quantifying these morphological characteristics revealed that the adaptation of an elongated shape of iDCs cultured in 3D collagen is characterized by a lower sphericity associated with an increased area at constant cell volume relative to iDCs cultured in 2D suspension (Fig EV1C and D).

Figure 1. iDCs adopt an elongated morphology associated with increased cell deformability in 3D collagen.

• A
  Experimental workflow. Monocytes isolated from PBMCs of healthy donors were differentiated into iDCs for 6 days by the addition of IL‐4/GM‐CSF. iDCs were then either seeded in 2D suspension or embedded in 3D collagen and analyzed at several time points post‐seeding.
• B
  Representative spinning disc confocal microscopy images of iDCs cultured in 2D suspension (left) or 3D collagen (middle) 8 h post‐seeding. Scale bars = 20 μm. Cells were stained with phalloidin‐Atto390 to visualize F‐actin and cell morphology. The dotted lines indicate which areas are shown in higher magnification in the panel on the right. Scale bars = 10 μm.
• C
  Schematic illustration of the RT‐DC measurement. Cells are flushed through a microfluidic channel and their deformation is quantified in real time. Representative brightfield images of iDCs after culturing in 2D suspension or 3D collagen and treatment with collagenase I captured while the cells were passing through the highlighted area of the channel are depicted.
• D
  Scatter plot of cell deformation versus cross‐sectional area of iDCs derived from one donor cultured in 2D suspension (top) or 3D collagen (bottom) and imaged in an RT‐DC measurement at a total flow rate of 0.04 μl/s. The presented data were down‐sampled to n = 1,000 for better visibility.
• E
  Contour plot of deformation versus cross‐sectional area of iDCs derived from one donor and measured via RT‐DC at a flow rate of 0.04 μl/s after culture in 2D suspension (red) and 3D collagen (blue) for 2 days.
• F–H
  Comparison of the deformation (F), volume (G), and Young's modulus (H) of iDCs derived from four donors (n = 1,559 to n = 4,675 each, mean ± SD) cultured either in 2D suspension or 3D collagen and measured with RT‐DC at a flow rate of 0.12 μl/s. A significant increase in deformability of iDCs when cultured in collagen was found (F, **P = 0.00277), whereas no significant difference in cell volume (G) or Young's modulus (H). For statistical significance testing, linear mixed‐model analysis was performed to calculate ANOVA P‐values; *P < 0.05, **P < 0.01, ***P < 0.001.
• I–J
  Two days post‐culturing in 2D suspension or 3D collagen, RNA was extracted and the transcriptome was determined by Clariom™ S Pico assay. The left panels show the heatmap related to the comparison of the expression between 2D suspension and 3D collagen profile of the untreated (mock, top) and LPS‐treated cells (bottom) (adjusted P‐value < 0.05). Inside each cluster, two subclusters identify the 2D suspension and the 3D collagen cells. The right panels show the set of statistically enriched pathways identified with the genes in the heatmap using metascape.

Figure EV1. 3D collagen alters iDC morphology and cell deformability.

Monocytes isolated from PBMCs of healthy donors were differentiated into iDCs for 6 days by the addition of IL‐4/GM‐CSF, and the presence of maturation markers was analyzed by FACS and compared to LPS‐treated control to verify that DCs were in an immature state.

• A
  Representative histograms of FACS analysis showing fluorescence intensity for each marker analyzed.
• B
  Representative spinning disc microscopy images of iDC cultured in 2D suspension (left) or 3D collagen (right) at 4 days post‐seeding. Cells were stained with phalloidin‐Atto390 to visualize F‐actin and cell morphology. Scale bar = 50 μm.
• C
  Representative spinning disc microscopy images of iDC cultured in 2D suspension (left) or 3D collagen (right) at 4 h post‐seeding. Cells were stained with Wga‐Alexa 647 to visualize the plasma membrane and cell morphology. Scale bar = 20 μm.
• D
  The graphs show the quantifications of cell area, sphericity, and volume, in 2D suspension and 3D collagen, obtained using Imaris's surface finder option, based on Wga‐Alexa 647 staining. Lines are set at median values and each dot represents an analyzed cell. ***P < 0.001 calculated with Mann–Whitney test.
• E–G
  Comparison of deformation (E), volume (F), and Young's modulus (G) of iDCs derived from four donors (n = 1,145 to n = 2,761 each, mean ± SD) cultured either in 2D suspension or 3D collagen for 2 days and measured with RT‐DC at a flow rate of 0.04 μl/s. For statistical significance testing, linear mixed‐model analysis was performed to calculate ANOVA P‐values; *P < 0.05, **P < 0.01, ***P < 0.001.

Source data are available online for this figure.

To understand whether differences in iDC morphology could be associated with distinct mechano‐physical properties of these cells, we quantitatively analyzed cellular deformability employing a high‐throughput microfluidic technique, real‐time deformability cytometry (RT‐DC). In RT‐DC experiments, cells are passed through a narrow microfluidic channel at kilohertz rates. Shear stresses and pressure gradients induce the deformation of the cells, which is tracked and quantified for individual cells in real time (Otto et al, 2015; Fig 1C). By employing an established analytical model, the cell deformation can be used to calculate the elasticity, that is, Young's modulus of individual cells (Mietke et al, 2015). iDCs were cultured in 2D suspension and 3D collagen for 2 days, retrieved by treatment with collagenase I, and immediately subjected to RT‐DC measurements (Fig 1D and E). We found that iDCs from all four donors showed significantly higher deformability following culture in 3D collagen than cells from 2D suspension cultures (Fig 1F 0.12 μl/s and Fig EV1E 0.04 μl/s), while the cell volume did not show significant differences (Fig 1G 0.12 μl/s) at both flow velocities used (Fig EV1F 0.04 μl/s). Consistently, iDCs retrieved from 3D collagen tended to display lower elasticity than cells kept in 2D suspension, although these differences were not statistically significant (Fig 1H 0.12 μl/s and Fig EV1G 0.04 μl/s).

A tissue‐like 3D environment thus affects the morphology and deformability of iDCs. Of note, alterations of these characteristics were not associated with notable differences in differentiation in specific subtypes, as iDCs were characterized by high cell surface levels of CD1c, low levels of CD141, and the lack of pronounced surface exposure of CD11c and SIGLEC‐6 under both culture conditions (Appendix Fig S1A). Transcriptome analyses, however, revealed marked differences between iDCs cultured in 2D suspension or 3D collagen. In addition to untreated iDCs, we analyzed the transcriptome profiles of LPS‐treated iDCs to characterize how the 3D collagen culture affects iDC gene expression in response to activation. Untreated cells had 513 differentially regulated genes, while LPS‐treated iDCs revealed 849 differentially regulated genes between 2D suspension and 3D collagen (adjusted P‐value < 0.05). Consistent with the fact that iDCs exert pronounced non‐adhesive motility in 3D collagen but not 2D suspension (Lammermann et al, 2008, 2009), pathway analysis revealed the differential expression of genes involved in the regulation of cell adhesion, response to external and mechanical stimulation, leucocyte migration, and, for LPS‐treated iDC, regulation of myeloid leukocyte activation (Fig 1I and J). This morphological and transcriptional adaptation of iDCs to the 3D collagen environment, however, did not affect their functional response to stimulation by LPS, which potently induced the production of a similar array of pro‐inflammatory cytokines by iDCs kept in 2D suspension or 3D collagen (Appendix Fig S1B). Together, these data show that the 3D collagen environment induces an elongated morphology in iDCs that is associated with the induction of transcriptional profiles related to mechanical stimulation and with an increase in cell deformability.

A 3D collagen environment renders iDCs more permissive to Vpx‐dependent HIV‐1 infection

We next assessed if the altered mechano‐physical properties of iDCs in 3D collagen are associated with differences in their interaction with HIV‐1. To this end, iDCs were treated 5 days post‐initiation of monocyte differentiation with Vpx‐containing virus‐like particles (Vpx‐VLPs) to overcome post‐entry blocks to HIV‐1 infection such as SAMHD1 (Hrecka et al, 2011; Descours et al, 2012; Baldauf et al, 2012; Baldauf et al, 2017). One day later, cells were challenged with HIV‐1NL4‐3 R5 (HIV‐1 R5), a CCR5 (R5)‐tropic HIV‐1 variant that infects myeloid target cells (Smed‐Sorensen et al, 2005; Wu & KewalRamani, 2006; Pierini et al, 2021), and were seeded in parallel in 2D suspension or embedded in 3D collagen (Fig 2A). Consistent with the literature (Smed‐Sorensen et al, 2005; Wu & KewalRamani, 2006), productive infection of iDCs by HIV‐1 R5, as assessed by intracellular p24 staining above the background of the raltegravir control, was low (1.1 ± 0.7% in suspension and 2.1 ± 1.6% in collagen at 4 d.p.i.), but could be enhanced by the pretreatment with Vpx‐VLPs (4.9 ± 2.1% in 2D suspension and 13.3 ± 5.2% in 3D collagen; Fig 2B and C). Interestingly, while background infection rates in the absence of Vpx were comparable between both culture conditions, the percentage of infected cells following Vpx‐VLP pretreatment was higher in 3D collagen than in 2D suspension. With 2.7‐fold, this increase was moderate but observed with cells from all donors tested and was statistically significant at 2 and 4 days post‐infection (d.p.i.; Fig 2B and C). A similar increase in productive infection at 4 d.p.i. was also observed with the reporter virus HIV‐1 NLENG1 R5 that harbors the eGFP IRES Nef sequence in the nef gene and reports productive infection by GFP expression, locus (Trinite et al, 2013; Appendix Fig S2). Culturing iDCs in 3D collagen post‐challenge with HIV‐1 thus increases Vpx‐dependent productive infection rates over those observed with iDCs cultured in 2D suspension.

Figure 2. 3D collagen environment renders iDCs more permissive to HIV‐1 infection.

1. Experimental workflow. iDCs differentiated from peripheral blood monocytes for 5 days were spin transduced with VLPs carrying Vpxmac239. One day later, iDCs were infected with HIV‐1 R5 and cultured in 2D suspension or 3D collagen. For the indicated samples, integrase inhibitor Raltegravir was added at the moment of infection. Productive infection was analyzed by p24 intracellular staining and FACS analysis at 2 and 4 (d.p.i).
2. Representative dot plots of FACS analysis at 4 d.p.i. to quantify the number of productively infected cells. Shown is SSC plotted against intracellular p24‐FITC after gating on live cells. The gate denotes the productive infected p24⁺ cell population with the percentage of p24⁺ cells indicated.
3. Percentage of p24⁺ cells at 2 d.p.i. (left) and 4 d.p.i. (right). Graphs depict mean values ± SD for cells from five donors. **P < 0.01 calculated with two‐way ANOVA test.

Source data are available online for this figure.

A 3D collagen environment reduces HIV‐1 particle uptake but enhances particle fusion on iDC target cells

To address what could cause higher infection rates in 3D collagen, we next sought to visualize and quantify the fate of HIV‐1 particles in iDCs cultured in 2D suspension or 3D collagen following challenge with virions. To this end, the HIV‐1 NLENG1 R5 provirus was used to produce viral particles in the presence of a Vpr.mRuby2 fusion protein which is efficiently incorporated into HIV‐1 virions. While virion‐associated Vpr.mRuby2 enables the detection of individual virus particles on target cells prior to and during uptake, productive infection is indicated by the GFP reporter expressed from the viral genome and is not impaired by the incorporation of Vpr.Ruby2 (Fig EV2A–C). iDCs were challenged with Vpr.mRuby2 containing HIV‐1 particles 1 day post‐pretreatment with Vpx‐VLPs, cultured in 2D suspension or 3D collagen, and harvested at various time points (Fig 3A). Labeling of the cytoplasm (anti‐GAPDH antibody) and F‐actin‐rich cellular protrusions (phalloidin) followed by image segmentation allowed us to distinguish between HIV‐1 particles that were bound to the cell surface or had been transported into the cell interior (Fig EV2D, see Materials and Methods for details). At 4 h post‐infection (h.p.i.), HIV‐1 particles were often detected as seemingly cell‐associated accumulations of multiple particles in 2D suspension while HIV‐1 virions in 3D collagen were mostly detected as dispersed fluorescent spots in the extracellular space (Fig 3B). Quantification revealed that in 2D suspension, the majority of viral particles were found either in the cytoplasm (61.7 ± 5.6%) or attached to the cell surface (14.9 ± 9.2%; Fig EV2E). In 3D collagen, in contrast, almost half of all particles (42.5 ± 21.5%) were detected in the extracellular space at 4 h.p.i., and the remaining particles were either associated with the cell surface or were inside the cytoplasm (Fig EV2E). Although we cannot exclude that the differences in the presence of extracellular particles may result from less efficient washing in 3D collagen relative to 2D suspension, these differences were also reflected in the number of Vpr.mRuby2‐positive particles detected per cell in suspension (7.3 ± 3.4) or in 3D collagen (3.6 ± 0.6) at 4 h.p.i. (Fig 3C). In suspension cultures, the number of HIV‐1 particles per cell tended to slightly increase over time, but these differences were not statistically significant and the numbers thus remained relatively constant over time. In contrast, the number of virions per cell detected in 3D collagen markedly decreased during the 48 h observation period (Fig 3C). Consistently, the fraction of cell‐associated virions among all particles detected in 3D collagen decreased over time while it remained constant in 2D suspension (Fig EV2E). In contrast, analyzing the fusion efficiency of HIV‐1 particles with iDC target cells, as assessed by the ability of virion‐incorporated Vpr‐Blam to convert the cytoplasmic β‐lactamase substrate CCF2 following fusion (Cavrois et al, 2002) at 4 h.p.i., revealed that fusion was rendered more efficient by the 3D collagen environment (Fig 3D and E). This effect ranged from 1.2‐ to 3.7‐fold for iDCs from different donors. When we analyzed fusion kinetics at 4 and 48 h.p.i. (Fig 3F and G), we observed that at 48 h.p.i. fusion activity was still detectable and at comparable magnitude under both culture conditions, indicating that the reduced fusion activity in suspension at early time points is not compensated later. Together, these data suggest that the 3D collagen environment affects efficacy and quality of HIV‐1 particle uptake by iDCs by promoting fusion of incoming HIV‐1 particles, while in 2D suspension, particles remain associated with iDCs for extended periods of time but less frequently undergo fusion.

Figure EV2. Setup and workflow of image analyses and quantifications.

1. Representative spinning disc confocal microscopy images of HIV‐1 NLENG R5 Vpr‐mRuby2 particles stained with anti‐HIV‐1 p24 antibody. Vpr‐mRuby2 is shown in red, while p24 is shown in green. Scale bar = 5 μm.
2. Relative infectivity of NLENG‐1 R5 particles in the presence or absence of Vpr‐mRuby2 produced in 293T cells. Particle infectivity was measured by infecting TZM‐bl reporter cells. The number of blue cells present was normalized to the RT activity of the respective virus stock determined by SG‐PERT assay. Bars represent mean ± SD of four technical replicates.
3. Representative spinning disc microscopy images of iDCs cultured in 2D suspension (top) or 3D collagen (bottom) at 48 h. p.i. GAPDH staining is shown in magenta, Vpr‐mRuby particles are shown in red, and GFP expression in productively infected iDCs is shown in green. Scale bar = 20 μm.
4. Imaris quantification workflow. The first left panels show an example of rendered particles created with the spot finder wizard using the signal from mRuby2. The second panels show an example of segmented cells (in green, purple, and violet) obtained through the cell finder wizard using the staining of cytoplasmic GAPDH. Phalloidin‐atto 390 signal, staining F‐actin, was used to find cell surface (represented in glass transparent color) and, finally, distance of each particle with respect to the cell cytoplasm, and surface was calculated. On the top, raw data are shown, while on the bottom, the rendering is shown. The last panel shows an example of cytoplasmic, surface‐associated, and extracellular particles in blue, yellow, and red, respectively. Scale bar = 4 μm.
5. Subcellular localization of Vpr‐mRuby2 particles in iDCs cultured in 2D suspension (left) or 3D collagen (right) for a representative donor, calculated following the workflow described in (D). For each time point, two to four pictures were analyzed and the graphs show mean values ± SD.

Source data are available online for this figure.

Figure 3. 3D collagen environment reduces HIV‐1 particle uptake but enhances particle fusion on iDC target cells.

• A
  Experimental workflow. iDC differentiated from peripheral blood monocytes for 5 days were spin transduced with VLPs carrying Vpxmac239. One day later, iDCs were infected with HIV‐1 NLENG‐1 R5‐harboring Vpr‐mRuby2 or HIV‐1 R5‐containing Vpr‐Blam and cultured in 2D suspension or cultured in 3D collagen. At the indicated time points, cells were either fixed and imaged with the spinning disc confocal microscope or used for Blam fusion assays.
• B
  Representative spinning disc confocal microscopy images of iDC cultured in 2D suspension (left) or 3D collagen (right) at 4 h.p.i. Cells were stained with Phalloidin‐Atto390 to visualize F‐actin. Vpr‐mRuby2 particles are shown in red. Scale bar = 20 μm. Arrowheads highlight virus particles in 3D collagen. The dotted lines indicate which areas are shown in higher magnification. Scale bars = 2 μm.
• C
  Vpr signal per cell. Graphs depict means values ± SD for cells from four donors. ***P < 0.001 calculated with two‐way ANOVA test.
• D–G
  Cells were infected with HIV‐1 R5 Vpr‐Blam for 4 or 48 h and then incubated with CCF2 for 5 h at 11°C to prevent particle fusion during the staining process. For the indicated sample, T20 was added at the moment of infection. (D) Representative dot plots of FACS analysis to quantify the formation of the CCF2 product generated by B‐lactamase enzymatic cleavage at 4 h.p.i. The fluorescence intensity of the CCF2 substrate is plotted against the fluorescence intensity of the CCF2 product. Gates show the percentage of CCF2 product‐positive cells. (E) Percentage of positive cells for the presence of the CFF2 product at 4 h.p.i. **P < 0.01 calculated with two‐way ANOVA test. (F, G) Percentage of positive cells for the presence of the CFF2 product at 4 h.p.i. (left) and 48 h.p.i. (right). *P < 0.05 calculated with two‐way ANOVA test. The graphs show mean values ± SD for cells from five and three donors, respectively.

Source data are available online for this figure.

A 3D collagen environment reduces transfer of HIV‐1 from iDCs to CD4 T cells

Although HIV‐1 trans‐infection to CD4 T cells by iDCs is less potent than that by maDCs and is limited to a 24 h timeframe (Turville et al, 2004; Izquierdo‐Useros et al, 2007; Wang et al, 2007), iDCs can trans‐infect CD4 T cells in addition to be subject of productive infection themselves (Menager & Littman, 2016). We, therefore, investigated if the transfer efficiency differs between the two culture conditions. iDCs pretreated with Vpx‐VLPs were challenged with HIV‐1 R5 particles, mixed with CD4 T cells after extensive washes, and seeded in 2D suspension or embedded in 3D collagen (Fig 4A). In 2D suspension co‐cultures, 3.3 ± 1.5 to 14.7 ± 8.3% of CD4 T cells became positive for intracellular p24 at days 2 and 4 of co‐culture, respectively (Fig 4B and C). The addition of an HIV protease inhibitor prevented the detection of p24⁺ CD4 T cells (Fig EV3A), indicating that these CD4 T cells were productively infected. Since the infectivity of cell‐free HIV‐1 particles is severely compromised in 3D collagen (Imle et al, 2019), the majority of these infection events likely resulted from cell‐associated transfer to target CD4 T‐cell, but the contribution of bystander infection cannot be fully excluded. In 3D collagen in contrast, such productive transfer from iDCs to CD4 T cells was not observed (0.3 ± 0.2%; day 2) or significantly reduced (3.5 ± 2.8%; day 4; Fig 4B and C). To address what could hamper the transfer of HIV‐1 to CD4 T cells in 3D collagen as compared to 2D suspension, we recorded cell organization, motility, and interactions in the two culture conditions by multiphoton imaging (Fig 4D and E, and Movies [Link], [Link]). Quantified over a 2‐h timeframe, approx. 75% of all iDCs were in physical contact with CD4 T cells in 2D suspension. This frequency was markedly reduced to less than 25% of interacting iDCs in 3D collagen (Fig 4F). These differences in interaction frequencies between the two culture systems were independent of the presence of HIV‐1 (Fig EV3B–D) and were paralleled by higher motility of iDCs as well as CD4 T cells in 2D suspension, which often included passive movement with medium flow, than in 3D collagen (Fig EV3E and F). While the frequency of iDC‐CD4 T cell contacts was reduced in 3D collagen, the few interaction events we were able to record were of extended duration (over 80 min; Fig EV3G). While such prolonged contacts facilitate the transfer of HIV‐1 to CD4 T cells, the low‐contact frequencies in 3D collagen likely explain why virus spread is more efficient in 2D suspension. These results suggest that, while 3D collagen promotes productive HIV‐1 infection of iDCs, HIV‐1 transfer to CD4 T cells is more efficient in 2D suspension due to an elevated number of iDC–CD4 T cell interactions that results from higher cell displacement speed.

Figure 4. 3D collagen environment reduces transfer of HIV‐1 from iDCs to CD4 T cells.

• A
  Experimental workflow. iDCs were differentiated from peripheral blood monocytes for 5 days, while CD4 T cells were isolated from peripheral blood and activated with CD28/CD3 beads for 3 days. iDCs were spin transduced with VLPs carrying Vpxmac239 1 day prior to pulsing. At day 0, iDCs were pulsed with HIV‐1 R5 and, after washing, co‐cultured with heterologous CD4 T cells in 2D suspension or 3D collagen. Percentage of p24‐positive cells was assessed by FACS at 2 and 4 d.p.i.
• B
  Representative dot plots of FACS analysis to quantify the number of productively infected cells. Shown is the CD3‐PerCp‐Cy5‐5 fluorescence intensity against intracellular p24‐FITC after gating on live cells. The gate denotes the productive infected p24⁺ cell population with the percentage of p24⁺ CD4 T cells indicated.
• C
  Percentage of p24⁺ cells at 2 d.p.i. (top) and 4 d.p.i. (bottom). Graphs depict mean values ± SD for cells from four donors.
• D–F
  iDCs were labeled with CellTracker blue CMAC (blue), pulsed with HIV‐1 R5, and, after washing, co‐cultured with heterologous CD4 T cells labeled with CellTracker orange CMTMR (red) in suspension (D) or 3D collagen (E) and imaged over 2 h. Shown are still images of Movies EV2 and EV4 and zoom‐ins (D′ and E′) as indicated, acquired at a 2‐Photon microscope. Scale bar = 50 μm. (F) Manual quantification of percentage of iDCs interacting with CD4 T cells over the 2 h time course. Bars indicate mean value for cells from two donors.

Source data are available online for this figure.

Figure EV3. 3D collagen affects iDC–CD4 T cell interactions.

• A
  iDC were pulsed with HIV‐1 R5 and, after washing, co‐cultured with heterologous CD4 T cells in 2D suspension or 3D collagen. Where indicated, the protease inhibitor Darunavir was added at the moment of pulsing. Percentage of p24‐positive cells was assessed by FACS at 2 (left) and 4 (right) d.p.i. Graphs depict mean values for cells from two donors.
• B–G
  Interactions of mock iDCs and CD4 T cells in 2D suspension and 3D collagen. iDCs were labeled with CellTracker blue CMAC (blue) and co‐cultured with CD4 T cells labeled with CellTracker orange CMTMR (red). (B) Mock pulsed iDCs in 2D suspension, (C) Mock pulsed iDCs in 3D collagen. Shown are still images of Movies EV1 and EV3 and zoom‐ins (B′ to C′) as indicated, acquired at a 2‐Photon microscope. Scale bar = 50 μm. (D) Manual quantification of percentage of iDCs interacting with CD4 T cells over the 2 h time course. Each symbol represents one donor; the bar indicates mean value. Mean displacement of CD4 T cells (E) and iDCs (F) were automatically tracked using Imaris. (G) Duration of CD4 T cell–iDC interactions manually tracked using InViewR. (E–G) Each symbol represents one interaction event or one track. Open squares represent events from donor 186 and closed circles events from donor 187. White and gray bars indicate median of donors 186 and 187, respectively.

A 3D collagen environment sensitizes iDCs for the secretion of proinflammatory cytokines in response to challenge with HIV‐1

We next sought to investigate the impact of 3D collagen on the innate immune response and activation of iDCs to challenge HIV‐1. To this end, a panel of 46 cytokines was quantified in supernatants of parallel 2D suspension and 3D collagen cultures at 2 and 4 d.p.i (Fig 5A). While marked variability was observed in breadth and magnitude of cytokine secretion between cells from different donors, at 2 and 4 d.p.i., embedding of iDCs infected with HIV‐1 R5 in the presence of Vpx in 3D collagen resulted in an increase in pro‐inflammatory cytokine secretion compared to cells kept in 2D suspension (Fig 5B). This included cytokines such as IP‐10 that were released upon HIV‐1 challenge in both culture conditions, but to higher extent by iDCs in 3D collagen than in 2D suspension. Additionally, cytokines such as TNFβ and Groα were produced to lower levels than in uninfected cultures by iDCs following challenge with HIV‐1 when kept in 2D, but their secretion increased beyond baseline production in the absence of HIV‐1 when iDCs were cultured in 3D collagen (Figs 5B and EV4A). Similar secretion profiles were observed in the absence of Vpx or the presence of the integrase inhibitor Raltegravir, suggesting that productive infection was dispensable for the induction of cytokine production in response to HIV‐1 in 3D collagen (Fig EV4B and C). Importantly, this sensitization to the production of proinflammatory cytokines was not associated with iDC activation and maturation as assessed by CD86 or SIGLEC‐1 cell surface exposure: although iDC activation was induced by stimuli such as LPS and IFNα in both culture conditions, iDCs treated with Vpx‐VLPs alone but also infected (p24⁺) or bystander (p24⁻) cells in iDC cultures following challenge with HIV‐1 did not reveal activation‐like CD86 or SIGLEC‐1 surface levels (Fig 5C and D, and Appendix Fig S3A–E). Within the limits of the low number of replicates analyzed, IP‐10 and TNFβ secretion efficiencies were not correlated with iDC infection rates. In contrast and possibly reflecting reported pro‐viral effects of Groα in macrophages and T cells (Lane et al, 2001), the amounts of secreted Groα were correlated with the number of productively infected iDCs (Fig EV4A). Together these data indicate that, in 3D collagen, HIV‐1 infection sensitizes iDCs for proinflammatory cytokine production without affecting iDC maturation.

Figure 5. 3D collagen environment sensitizes iDCs for the secretion of proinflammatory cytokines in response to challenges with HIV‐1.

1. Experimental workflow. iDC differentiated from peripheral blood monocytes for 5 days were spin transduced with VLPs carrying Vpxmac239. One day later, iDCs were infected with HIV‐1 R5 and cultured in 2D suspension or 3D collagen. Two and 4 d.p.i., cytokine secretion profile in the supernatant and CD86 surface expression were analyzed.
2. The heatmaps show the log2 fold change of each cytokine relative to the uninfected condition for iDC infected in the presence of Vpx at 2 d.p.i. (top) and 4 d.p.i. (bottom). Stars indicate samples where the cytokine amount is lower than 10 pg/ml in uninfected and infected conditions, and the log2 fold change is higher than 2.
3. Representative dot plots of FACS analysis to quantify the number of productively infected cells that upregulated CD86. Shown is CD86‐PerCp‐770 fluorescence intensity against intracellular p24‐FITC. The gates indicate the percentage of p24⁺ and p24⁻ cells together with the percentage of CD86⁺ and CD86⁻ cells.
4. Ratio between the percentage of CD86‐positive and CD86‐negative cells for HIV‐1 R5 infected iDC in the presence or absence of Vpx and for LPS‐treated iDCs, as positive control. The graph shows mean values ± SD for cells for five donors. n.s calculated with two‐way ANOVA and Sidak's multiple‐comparison test.

Source data are available online for this figure.

Figure EV4. 3D collagen alters the secretion profiles of specific cytokines in response to HIV‐1 infection.

iDCs differentiated from peripheral blood monocytes for 5 days were spin transduced with VLPs carrying Vpxmac239. One day later, iDCs were infected with HIV‐1 R5 and cultured in 2D suspension or 3D collagen. Two and 4 d.p.i., cytokine secretion profile in the supernatant and CD86 surface expression were analyzed.

1. Graphs depict the log2 fold change of selected cytokines (top) and their correlation with productive infection, as assessed by p24 intracellular staining and FACS analysis. Bars show mean ± SD for cells from three donors.
2. The heatmaps show the log2 fold change of each cytokine relative to the uninfected condition for iDC infected in the absence of Vpx at 2 d.p.i. (top) and 4 d.p.i. (bottom). * Indicates samples where the cytokine amount is lower than 10 pg/ml in uninfected and infected conditions, and the log2 fold change is higher than 2.
3. The heatmaps show the log2 fold change of each cytokine relative to the uninfected condition for iDC infected in the presence of Vpx and integrase inhibitor Raltegravir. * Indicates samples where the cytokine amount is lower than 10 pg/ml in uninfected and infected conditions, and the log2 fold change is higher than 2.

Source data are available online for this figure.

3D collagen environment reduces the expression of some antiviral genes by iDCs in response to HIV‐1 challenge

We next analyzed whether the 3D collagen environment affected iDC gene expression in response to HIV‐1 infection. iDCs were infected with HIV‐1 R5 virions in the presence or absence of Vpx and with or without the integrase inhibitor Raltegravir, cultured in 2D suspension or 3D collagen for 2 days, and then subjected to transcriptome analysis by Clariom™ S Pico assay microarray. Principal component analysis (PCA) revealed that the gene expression profiles of cells from the three different donors analyzed primarily clustered according to their donor origin (Fig 6A; see, e.g., Donor 71 in the bottom left corner). Within the samples of the same donor, specific transcriptional signatures, as indicated by right‐shifting of suspension samples in the PC1 axis of the PCA plot, were observed between culture conditions while the presence of HIV‐1 only had a moderate impact on this global level of the analysis. To more specifically assess the impact of 3D collagen on the transcriptional signatures induced by HIV‐1, we compared all HIV‐1 R5 + Vpx samples to the respective uninfected controls and identified 33 genes that were differentially expressed (adjusted P‐value < 0.001). Hierarchical clustering based on gene expression in all infected conditions showed that cells infected in the presence of Vpx from Donor 75 had the highest changes in expression of most of these genes (Fig 6B). Analyzing the fold change of each differentially expressed gene over its respective uninfected control revealed that 16 of the 33 differentially regulated genes have well‐established antiviral properties and were markedly more upregulated in 2D suspension than in 3D collagen (Fig 6C). Of note, this did not encompass all antiviral genes since, for example, expression of IP‐10 was more induced in 3D collagen than in 2D suspension (Fig EV4A). The molecular basis for the selective deregulation of specific genes in different culture conditions remains unclear. This increase in antiviral gene expression was highly variable between cells from different donors, but induction of at least two‐fold in 2D suspension was observed for five genes in cells of at least two of the three donors analyzed, and gene set enrichment analysis (GSEA) of genes related to the interferon pathway revealed a significant enrichment in 2D over 3D cultures when iDCs were infected subsequent to treatment with Vpx‐VLPs (Appendix Fig S4). This HIV‐1‐induced increase in antiviral gene expression required productive infection of iDCs since it was not observed in the absence of Vpx (Fig 6D) and was abrogated by the integrase inhibitor Raltegravir (Fig 6E). The induction of antiviral gene expression by productively infected iDCs is thus less pronounced in 3D collagen than in 2D suspension.

Figure 6. A 3D collagen environment reduces the expression of some antiviral genes by iDCs in response to HIV‐1 challenge.

• A
  PCA of uninfected and infected iDC cultured in 2D suspension or 3D collagen for 2 days (three donors).
• B
  Heatmap of differentially expressed genes. 33 genes were significantly up or down‐regulated HIV‐1‐infected cells upon challenge with Vpx‐VLPs and HIV‐1R5 (adjusted P‐value < 0.001).
• C–E
  Graphs show the fold change increase, over uninfected control, for infection with HIV‐1 R5 in the presence of Vpx (C), HIV‐1 R5 (D) or HIV‐1 R5 in the presence of Vpx, and Raltegravir control (E) of the 16 selected genes with antiviral properties for cells from three donors. Bars represent the mean ± SD. *P < 0.05 calculated with two‐way ANOVA with Sidak test.

Source data are available online for this figure.

Increased HIV‐1 infection of iDCs in 3D collagen environments is linked to rapid upregulation of DC‐SIGN cell surface levels

The above results revealed that relative to 2D suspension cultures, culturing iDCs in 3D collagen immediately after challenge with HIV‐1 particles increases their permissivity to productive infection and pro‐inflammatory cytokine production but reduced their ability to mount antiviral gene signatures and transfer HIV‐1 to new target cells. Since such effects, for example, at the level of virion–iDCs fusion, were observed rapidly post‐embedding, we reasoned that these effects could not exclusively be determined at the level of transcription and focused on the subcellular localization of host cell receptors involved in HIV‐1 entry. Surface exposure of the HIV‐1 entry receptor CD4 and its co‐receptor CCR5 was indistinguishable between iDCs cultures in 2D suspension or 3D collagen (Fig 7A and B). In contrast, cell surface levels of DC‐SIGN, an important binding receptor for HIV‐1 on DCs (Geijtenbeek et al, 2000), were markedly increased (2.6‐ to 7.1‐fold) on iDCs cultures in 3D collagen (Fig 7C). Among other receptors implicated to capture HIV‐1 (Izquierdo‐Useros et al, 2012; Tjomsland et al, 2013), cell surface levels of SIGLEC‐1 were unaffected by the 3D culture condition (Fig 7D), while those of macrophage mannose receptor (MMR) were induced (Fig 7E). For DC‐SIGN, this increase in cell surface levels was also apparent as a 6.8‐fold change increase in cell surface staining by spinning disc microscopy (Fig 7F and G; note that cells had been removed from 3D collagen for staining and thus no longer display the typical elongated morphology). Although cells had been permeabilized prior to staining, we detected DC‐SIGN almost exclusively at the cell surface of iDCs in 3D collagen and we did not observe a pronounced intracellular staining in iDCs kept in 2D suspension (Fig 7F). Of note, this increase in cell surface DC‐SIGN was an immediate response to the 3D culture condition and was observed as early as 2 h after embedding into 3D collagen (Fig 7F and G).

Figure 7. 3D collagen increases surface presence of DC‐SIGN.

• A–E
  iDCs differentiated from peripheral blood monocytes for 6 days were cultured in 3D collagen or 2D suspension for 2 days and the surface expression of CD4 (A), CCR5 (B), DC‐SIGN (C), SIGLEC‐1 (D), and MMR (E) was analyzed by FACS. Representative histograms of FACS analysis showing fluorescence intensity for each receptor analyzed (Top). The graph shows the ratio between the median fluorescence intensity of the stained sample and the unstained sample for cells from three to six donors (bottom). Bars represent mean ± SD. ***P < 0.001; **P < 0.01 calculated with paired t‐test.
• F
  Representative images showing sum slice z‐projections. Images from the DC‐SIGN channel of cells kept in 2D suspension or 3D collagen were identically processed and are shown with identical brightness/contrast settings. The actin signal was adjusted according to its brightness in each image individually to identify the cells. Scale bar = 20 μm.
• G
  The graph shows the fluorescence intensity mean of the DC‐SIGN channel from cells grown in 2D suspension or 3D collagen. Bars define the mean ± SD and dots represent individual cells analyzed. N of cells in 2D suspension = 34; N of cells in 3D collagen = 54. ***P < 0.001 calculated with Mann–Whitney test.
• H–J
  iDCs were spin transduced with VLPs carrying Vpxmac239, 1 day prior to infection. Cells were incubated with anti‐DC‐SIGN and anti‐MMR‐blocking antibody or isotype control for 30 min, infected with HIV‐1 R5 Vpr‐Blam for 4 h to assess fusion or for 48 h to assess productive infection. (H) Representative dot plots of FACS analysis to quantify the formation of the CCF2 product generated by B‐lactamase enzymatic cleavage at 4 h.p.i. The fluorescence intensity of the CCF2 substrate is plotted against the fluorescence intensity of the CCF2 product. Gates show the percentage of CCF2 product‐positive cells. (I) Percentage of positive cells for the presence of the CFF2 product at 4 h.p.i. (J) Percentage of p24⁺ cells at 48 h.p.i. The graphs show mean values ± SD for cells from three donors. *P < 0.05 calculated with two‐way ANOVA test.

Source data are available online for this figure.

To assess if the rapid upregulation of HIV‐binding receptors on iDCs upon embedding in 3D collagen was mechanistically linked to their increased permissivity to productive HIV‐1 infection, we applied blocking antibodies targeting DC‐SIGN or MMR known to interfere with capture of HIV‐1 (Geijtenbeek et al, 2000; Cambi et al, 2004; Tjomsland et al, 2013) and measured HIV‐1 particle fusion and productive infection. While fusion was unaffected by the anti‐MMR antibody, blocking DC‐SIGN reduced the fusion efficacy of HIV‐1 with iDCs in both 2D suspension and 3D collagen (Fig 7H and I) and this reduction was statistically significant in 3D collagen. To assess the impact of anti‐DC‐SIGN antibody treatment on productive infection, we analyzed the percentage of p24‐positive cells at 2 d.p.i. (i.e., the earliest time point with detectable infection in our experimental set‐up). In line with the reduction of fusion efficiency, the anti‐DC‐SIGN antibody significantly decreased infection rates in 3D collagen. In contrast, productive infection in 2D suspension was unaffected by the antibody (Fig 7J) but we cannot exclude that the low baseline infection in 2D suspension hindered the detection of a blocking effect. These results suggest that upregulation of cell surface DC‐SIGN on iDCs promotes their productive infection by HIV‐1 in 3D collagen. They also indicate that fusion efficacy is not limiting for the basal levels of productive infection achieved in 2D suspension. The adaptation of iDCs to 3D collagen thus includes a rapid increase in cell surface exposure of DC‐SIGN that likely contributes to the increase in productive HIV‐1 infection observed in this tissue‐like environment.

Adhesion of iDCs to a 2D collagen surface increases cell surface exposure of DC‐SIGN and permissivity to HIV‐1 infection

To address to which extent the effects of 3D collagen on functional interactions of iDCs with HIV‐1 require interactions with the 3D environment or can be induced by adhesion to a collagen surface (2D collagen), we compared the behavior of iDCs in 2D suspension and 3D collagen with that on 2D collagen. In the 2D collagen culture, iDCs were plated on top of and not embedded into a collagen matrix of the same thickness as that of the 3D collagen matrix. (Fig 8A). iDCs on 2D collagen appeared relatively round without many pronounced protrusions and were thus distinct from those observed in 2D suspension (round with many dendrites) and 3D collagen (elongated with only few dendrites; Fig 8B). iDCs thus require a 3D scaffold to fully acquire the elongated morphology observed in 3D collagen. In contrast, the RT‐DC measurements with two flow rates (Figs 8C–F and EV5A–D) revealed that the elasticity of iDCs was similar in all three culture conditions (Figs 8D and EV5B), but that 2D collagen was sufficient to slightly increase deformability and volume over 2D suspension (Figs 8E and F, and EV5C and D). Similarly, culturing iDCs on 2D collagen was sufficient to increase the surface expression of DC‐SIGN (Fig 8G) as well as their permissivity to HIV‐1 infection (Fig 8H). These results reveal that adhesion to a 2D collagen surface is sufficient to induce some of the biophysical and functional adaptations of iDCs to a tissue‐like 3D environment.

Figure 8. 2D collagen is sufficient to increase DC‐SIGN surface levels on iDCs and to render cells more permissive to HIV infection.

• A
  Schematic model of iDC cultured in 2D suspension (left), 3D collagen (middle), and 2D collagen (right). iDCs are shown in gray, while collagen fibers are shown in pink.
• B
  Representative spinning disc microscopy images of iDCs cultured in 2D suspension (left) or 3D collagen (middle) 4 days post‐seeding. Scale bars = 15 μm. Representative 2‐Photon microscopy images of iDCs cultured in 2D collagen (right). Scale bars = 15 μm. Cells were stained with phalloidin‐Atto390 to visualize F‐actin and cell morphology.
• C
  Contour plot of deformation versus cross‐sectional area of iDCs derived from one donor and measured via RT‐DC at a flow rate of 0.04 μl/s after culture in 2D suspension (red) 3D collagen (blue) and 2D collagen (green) for 2 days.
• D–F
  Comparison of Young's modulus (D), deformation (E), and volume (F) of iDCs derived from two donors (n = 2,233 to n = 16,619 each, mean ± SD cultured in 2D suspension, 2D collagen, or 3D collagen and measured with RT‐DC at a flow rate of 0.04 μl/s). A significant increase in deformability of iDCs when cultured on 2D collagen or in 3D collagen was found (E, ***P = 0.00004 and **P = 0.00733, respectively). Cells cultured in suspension were found to be smaller in comparison to cells cultured on 2D collagen (F, *P = 0.02263) or in 3D collagen (F, **P = 0.00293). For statistical significance testing, linear mixed‐model analysis was performed to calculate ANOVA P‐values; *P < 0.05, **P < 0.01, ***P < 0.001. Results obtained with cells from an additional donor were excluded since the properties of these cells were indistinguishable in all three culture conditions and this did not reveal the response to 3D collagen observed in the cells the six other donors analyzed (Fig 1 and this figure).
• G
  iDC differentiated from peripheral blood monocytes for 6 days were cultured in 3D collagen, 2D collagen, or 2D suspension for 2 days and the surface expression of DC‐SIGN was analyzed by FACS. The graph shows the ratio between the median fluorescence intensity of the stained sample and the unstained sample indicated as fold change. Graphs represent the mean for cells from two donors.
• H
  iDC differentiated from peripheral blood monocytes for 5 days were spin transduced with VLPs carrying Vpxmac239. One day later, iDCs were infected with HIV‐1 R5 and cultured in 2D suspension, 2D collagen, or 3D collagen. Productive infection was analyzed by p24 intracellular staining and FACS at 4 (d.p.i). The graph depicts mean values for cells from two donors.
• I
  Schematic model created with BioRender.com. When cultured in 3D collagen, iDCs assume an elongated shape associated with increased deformability and higher expression of DC‐SIGN, which accompany higher permissivity to HIV‐1 infection facilitated by membrane fusion. In 2D suspension, binding of HIV‐1 to iDCs targets virions to a non‐productive infection pathway that helps the transfer of the virions to target CD4 T cells. Culturing iDCs in a 2D collagen matrix is sufficient to increase deformability, surface expression of DC‐SIGN, and iDC permissivity to HIV‐1 infection, but not to allow iDCs to acquire an elongate shape reminiscent of the morphology of migrating DCs in vivo.

Figure EV5. 2D collagen is sufficient to alter iDC cell deformability.

• A
  Scatter plots of cell deformation versus cross‐sectional area of iDCs derived from one donor cultured in 2D suspension (left), 2D collagen (middle), or 3D collagen (right) and subjected to an RT‐DC measurement at a total flow rate of 0.04 μl/s. The presented data were down‐sampled to n = 1,000.
• B–D
  Comparison of the Young's modulus (B), deformation (C), and volume (D) of iDCs derived from two donors (n = 5,121 to n = 30,790 each, mean ± SD) cultured either in 2D suspension, 2D collagen, or 3D collagen and measured with RT‐DC at a flow rate of 0.12 μl/s. A significant increase in deformability of iDCs when cultured on 2D collagen or in 3D collagen was found (C, ***P = 0.00004 and *P = 0.00733, respectively). For statistical significance testing, linear mixed‐model analysis was performed to calculate ANOVA P‐values; *P < 0.05, **P < 0.01, ***P < 0.001.

Discussion

iDCs play important roles in dissemination and immune recognition of HIV‐1 particles at mucosal surfaces and in lymphoid tissue. To fulfill these functions, iDCs constantly migrate and encounter different microenvironments with distinct cell and extracellular matrix densities, and the extent to which iDCs are in physical contact with the extracellular matrix varies. To study the impact of such tissue environments on the interplay of iDCs with HIV‐1, we initially compared iDCs grown in 2D suspension or 3D collagen. Consistent with previous reports (Lammermann et al, 2008; Sapudom et al, 2020), iDCs immediately adopted an elongated cell morphology in 3D collagen that more closely reflects their architecture in tissue than the rounded morphology in 2D suspension (Mempel et al, 2004; Fig 8I). Likely reflecting that environmental cues in 3D collagen change mechano‐physical properties of iDCs, transcriptional programs associated with response to external and mechanical stimulation were induced under this condition. These adaptations to 3D collagen did not affect the activation and maturation state of iDCs or their response to stimulation by LPS. In contrast, interactions of iDCs with HIV‐1 particles markedly differed between 2D suspension or 3D collagen cultures. In 2D suspension, iDCs internalized HIV‐1 particles, which resulted in low levels of productive infection but efficient induction of antiviral gene expression and transfer of HIV‐1 to CD4 T cells. In 3D collagen, in contrast, iDCs were efficiently infected and produced increased levels of pro‐inflammatory cytokines but their ability to transfer HIV‐1 to CD4 T cells was limited. Differences in the transfer of HIV‐1 to CD4 T cells likely reflect that iDCs in 2D suspension undergo more frequent cell–cell conjugation with CD4 T cells than in 3D collagen. The usage of a tissue‐like environment thus revealed previously unappreciated plasticity of iDC interactions with HIV‐1 as the 3D collagen environment converts them from an efficient vehicle for virus transfer to target CD4 T cells that induces antiviral gene expression into a target for productive infection with increased pro‐inflammatory cytokine response. Interestingly, we observed that removing iDCs from 3D collagen and subsequent culture in 2D suspension was associated with significant cytotoxicity, indicating that this plasticity may be unidirectional.

Our analysis of HIV‐1 particle uptake and fusion provides insight into the ability of 3D collagen to regulate iDC function. Of note, increased productive infection in 3D collagen occurred at a significantly reduced particle uptake efficiency relative to 2D suspension cultures, suggesting that the 3D collagen environment affects how virions are up taken by iDCs. In this scenario, it is tempting to speculate that uptake in 2D suspension at reduced fusion activity promotes transfer to CD4 T cells while the fusion efficiency of HIV‐1 particles significantly increases when iDCs are embedded in 3D collagen (Fig 8I). Our results revealed elevation of cell surface DC‐SIGN as an adaptation of iDCs to the 3D collagen environment and the reduction of fusion, and productive infection by the anti‐DC‐SIGN blocking antibody suggests that the increased permissivity of iDCs to HIV‐1 infection in 3D collagen is mediated at least in part via this increased DC‐SIGN cell surface exposure. Although DC‐SIGN does not participate directly in the fusion process, its ability to capture HIV‐1 particles and thus increase their probability to fuse upon engagement of the CD4–co‐receptor complex can significantly increase infection rates of iDCs (Lee et al, 2001; Nobile et al, 2003; Hijazi et al, 2011). Additionally, engagement of DC‐SIGN can induce signaling cascades that increase infection rates and cytokine production (Gringhuis et al, 2010). The impact of the 3D collagen environment on HIV‐1 fusion and DC‐SIGN surface exposure was observed immediately following embedding of HIV‐challenged iDCs in 3D collagen. Since increased cell deformability was observed upon embedding of iDCs in 3D collagen with cells from six out of seven donors, we speculate that these alterations of the biophysical properties of iDCs can impact intracellular trafficking pathways to promote surface exposure of DC‐SIGN and/or alter its signaling competence. The short time required for increasing DC‐SIGN cell surface levels implies that recycling of intracellular proteins to the cell surface may be particularly affected by environmental cues. Since HIV virions appeared to be stable after uptake in 2D suspension, the uptake pathways employed by HIV‐1 virions may differ between 2D suspension and 3D collagen cultures. Expression of genes associated with proteasomal or lysosomal degradation was comparable between the culture conditions. The stability of internalized HIV‐1 particles is thus likely determined by the nature of this uptake pathway and the activity of degradation pathways. The molecular identity of the trafficking pathways employed by HIV‐1 particles in 2D suspension and 3D collagen and the mechanisms by which the 3D environment shapes endosomal sorting will be important topics of future studies.

The 3D collagen environment also modulated the intrinsic ability of iDCs to mount innate immune responses to HIV‐1 particles. While non‐productive uptake of HIV‐1 particles in 2D suspension was associated with the induction of some antiviral genes, productive infection in 3D collagen emphasized the secretion of pro‐inflammatory cytokines. It is tempting to speculate that the induction of antiviral genes in 2D suspension and the increase in pro‐inflammatory cytokine production in 3D collagen are linked to the low rates of productive infection in primary target and bystander cells, respectively. Thus, these different types of antiviral responses reflect that innate immune sensors in iDCs have access to different viral replication intermediates in these two culture conditions. Upregulation of antiviral interferon‐stimulated genes (ISGs) is typically the result of interferon secretion, but genes including IFITM1, IFIT1, IFIT3, OAS3, ISG15, and IFT5 that were induced in 2D suspension can also be induced directly by NF‐kB signaling elicited by the sensing of virus replication intermediates without requirement for IFN production (Harman et al, 2011). In line with this scenario, the induction of antiviral gene expression in iDCs in 2D suspension was strictly dependent on the presence of Vpx to overcome early post‐RT blocks and was inhibited by blocking integration by raltegravir and thus reflects sensing of a post‐entry replication intermediates that do not progress to establish productive infection. In contrast, increased pro‐inflammatory cytokine production in 3D collagen was unaffected by Vpx or integrase inhibition and thus likely reflects detection of viral genomes during abortive uptake events. These results suggest that the effects of the 3D collagen environment on HIV‐1 uptake, productive infection, and innate immune recognition are linked to one another.

Comparing the response of iDCs embedded in a 3D collagen environment to that of iDCs adhering to a 2D collagen surface revealed that interactions with 2D collagen are sufficient to trigger some of the morphological and functional adaptations observed in 3D collagen. While not adapting the elongated morphology observed in 3D collagen, iDCs cultured on 2D collagen displayed increased cell deformability, DC‐SIGN surface expression, and permissivity to HIV‐1 infection. How such 2D interactions with tissue‐like environments affect innate immune recognition of HIV‐1 by iDCs will be important to assess. Collectively, these findings reveal that 2D and 3D tissue‐like environments shape the functional plasticity of iDCs in response to challenges to HIV‐1 particles (Fig 8I). The observed differences in infection and immune recognition were implemented already after short timeframes of 2D or 3D culture. This implies that in vivo, local changes in the tissue microenvironment, for example, in the context of a migrating cell, may have immediate impact on iDC function without notable change in iDC activation or differentiation. Motile, tissue‐resident iDCs are thus likely more permissive to HIV‐1 infection than peripheral iDCs and since 2D interactions already induce functional adaptation, this increased permissivity should be maintained independently of the compactness of the local microenvironment. Molecular understanding of how chemo‐ and mechano‐sensing of environmental cues provided by the respective tissue environment impacts HIV‐target cell biology will be essential to decipher tissue‐resident pathogenesis mechanisms and will benefit from studying the function of iDCs on patterned surfaces that provide tight experimental control over cell shape and deformability. Including the ability of iDC to provide antigen‐specific activation to CD4 T cells will be an interesting expansion of the complexity of functional cell–cell communication.

Our analyses revealed a physical and functional adaptation of iDCs to 2D and 3D collagen environments. While these findings suggest that the mechanical properties of surrounding tissue impact iDC function in vivo, our study used 2D and 3D environments exclusively made of collagen. Moreover, iDCs were differentiated from peripheral blood monocytes and can thus not predict the behavior of iDCs residing in a tissue with physiological complexity. The analysis of iDCs immune response to challenge with HIV was complicated by the fact that many genes and cytokines were deregulated but the magnitude of deregulation of individual parameters was moderate and subject to significant variation for cells from different donors. This complexity hampered the analysis of the functional consequences of these deregulations and precluded, for example, testing whether the collective alterations in antiviral gene expression are sufficient for the induction of antiviral states. ISG induction is typically the result of interferon secretion but the low levels of interferon secretion we detected were close to the detection limit of the assay used. We, therefore, cannot conclude whether the 3D collagen environment affects production by or sensitivity of iDCs to interferons or primarily acts by direct activation of gene expression and future experiments assessing the impact of blocking interferon signaling will be required to clarify this question. Finally, productive infection of iDCs by HIV‐1 required pretreatment of the cells with Vpx‐VLPs and the functional adaptation of iDCs to the tissue‐like environments was thus not sufficient to render them permissive for infection by natural HIV‐1. This suggested that HIV‐2, the primate lentivirus encoding for Vpx, may be able to infect iDCs in 3D collagen. However, iDCs can only poorly be infected by HIV‐2 (Chauveau et al, 2015) and the relatively low affinity of HIV‐2 Env for DC‐SIGN (Pohlmann et al, 2001) may explain why we also failed to observe productive infection of iDCs in 3D collagen by HIV‐2 ROD. HIV‐2 thus faces restrictions for the infection of iDCs that are not overcome by the tissue‐like 3D environment provided here and the physiological role of productive iDC infection by HIV‐2 remains to be elucidated.

Materials and Methods

Cells

A total of 293T cells (CRL‐3216, obtained from ATCC) and TZM‐bl cells (courtesy of NIH AIDS Research and reference Reagent Programme (ARP5011), originally provided by Dr. John C. Kappes, Dr. Xiaoyun Wu, and Tranzyme Inc.) were cultured in Dulbecco's modified Eagle's medium (DMEM, Gibco) supplemented with 10% heat‐inactivated fetal calf serum (FCS, Capricorn Scientific) and 1% penicillin–streptomycin. Human peripheral blood of healthy, HIV‐negative donors was obtained from the blood bank HD, according to regulation by local ethics committee (S‐024/2022).

Monocytes‐derived immature dendritic cells (iDCs)

Monocytes were isolated from human peripheral blood mononuclear cells (PBMCs) of healthy, HIV‐negative donors using magnetic CD14 Microbeads (Miltenyi Biotech) and AutoMACS Pro Separator (Miltenyi Biotech) according to manufacturer instructions. 4 × 10⁶ Monocytes were seeded in 2 ml RPMI (Gibco) supplemented with 10% heat‐inactivated FCS, 1% penicillin–streptomycin, 20 ng/ml granulocyte–macrophage colony‐stimulating factor (GM‐CSF; PeproTech), and 20 ng/ml interleukin 4 (IL‐4; PeproTech). Two days after seeding, 2 ml of fresh media were added to cells in differentiation. Cells were allowed to differentiate for 6 days before starting the experiments. Where indicated, 50 ng/ml of LPS from E. coli (Sigma Aldrich) or 0.3 unit/μl of human IFNα (Sigma Aldrich) were added.

Plasmids

The proviral plasmids pHIV‐1NL4‐3 WT (SF2 Nef) R5 tropic was previously described (Bozek et al, 2012; Pierini et al, 2021). The proviral plasmid NLENG1‐IRES‐70 (R5) was previously described (Trinite et al, 2013) and kindly provided by David Levy. For lentiviral vectors carrying Vpxmac239, the vector backbone pWPI and the plasmid pMD2.G encoding the vesicular stomatitis virus glycoprotein (VSV‐G) were provided by Didier Trono through Addgene. The plasmids pcDNA3.1 Vpx SIVmac239‐Myc and the packaging plasmid harboring the Vpx‐binding motif (pΔR8.9 NSDP) were described previously (Baldauf et al, 2017). The Vpr‐Blam fusion protein encoding plasmid pMM310 was reported previously (Cavrois et al, 2002). The plasmid pmRuby2.Vpr, encoding Vpr fused to mRuby2, was generated by excision of the eGFP coding region of peGFP.Vpr (McDonald et al, 2002, a kind gift of Tom Hope) using AgeI and BsrGI restriction enzymes, followed by insertion of a PCR fragment encoding mRuby2 (Lam et al, 2012); amplified from pcDNA3‐mRuby2, a gift from Michael Lin (Addgene plasmid # 40260) and flanked by the same restriction sites.

Virus and VLPs production

Infectious HIV‐1NL4‐3 WT (SF2 Nef) CCR5 tropic virus (HIV‐1 R5) was produced after transfection of 293T cells with proviral plasmids pHIV‐1NL4‐3 WT (SF2 Nef) R5. Infectious HIV‐1 NLENG‐1 R5‐harboring Vpr‐mRuby 2 was produced by co‐transfection of proviral plasmid NLENG1‐IRES‐70 and Vpr‐mRuby2 plasmid at 3:1 ratio.

For immunofluorescence (IF) staining of HIV‐1 Gag, viral particles were fixed in 3% PFA in PBS for 10 min at RT, permeabilized with 0.1% Triton‐X‐100/PBS for 2 min, and stained with anti‐HIV‐1 p24 rabbit polyclonal CA1 (1:200 in 1% BSA in PBS) for 45 min at RT. Finally, viral particles were stained with anti‐Rabbit Alexa488 (1:2,000 1% BSA in PBS) for 30 min at RT. Spinning disk confocal microscopy was performed using a Nikon Ti2 microscope equipped with an Andor CSU‐W1 spinning disk head. Infectious HIV‐1 R5‐harboring Vpr‐Blam was produced by co‐transfection of proviral plasmid pHIV‐1NL4‐3 WT (SF2 Nef) R5 and pMM310 plasmid at 3:1 ratio. Lentiviral vectors carrying Vpxmac239 were produced in 293 T cells by co‐transfection of pWPI, pcDNA.Vpxmac239, pΔR8.9 NSDP, and VSV‐G at a molar ratio of 4:1:3:1 as previously described (Pierini et al, 2021). A total of 48 or 72 h post‐transfection, cell supernatants were collected, filtered with 0.45 μm filters, concentrated via ultracentrifugation (97,000 g for 1 h 30′ at 4°C) through a 20% (w/w) sucrose cushion, and finally, resuspended in PBS. Aliquots were stored at −80°C and handled in a Biosafety Level 3 (BSL‐3) laboratory for infectious viruses or in a BSL‐2 laboratory for lentiviral vectors carrying Vpxmac239. The number of infectious HIV‐1 particles was determined by infecting TZM‐bl reporter cells and determining ‐β galactosidase reporter activity as previously described (Wei et al, 2002; Sarzotti‐Kelsoe et al, 2014). Overall amounts of physical particles (infectious HIV‐1 or VLPs) were assessed by SYBR green I‐based product‐enhanced RT (SG‐PERT) as previously described (Pizzato et al, 2009).

iDCs cultures in 2D suspension or 2D/3D collagen

Collagen gels were prepared as previously described (Imle et al, 2019). Briefly, concentrated rat tail collagen I (Corning) was mixed with bicarbonate‐buffered MEM on ice (15 μl 10× MEM, 17 μl 7.5% NaHCO₃ (both Gibco), and 120 μl rat collagen I). To culture iDCs in 3D collagen, 2 × 10⁶ cells/ml were mixed 1:1 with collagen, and 100 μl cell‐collagen per‐well mix was transferred in 96‐well F‐bottom plates and let polymerize for 20 min at 37°C. For suspension cultures, 2 × 10⁶ iDCs/ml were mixed at 1:1 ratio with RPMI, and 100 μl per‐well of cell‐media mix was transferred in 96‐well U‐bottom plates. For 2D collagen cultures, 100 μl of collagen mix, polymerized in 96‐well F‐bottom plates, were overlaid with 2 × 10⁶ iDCs/ml supplemented with 20 ng/ml IL‐4 and 20 ng/ml GM‐CSF. 2D suspension and 3D collagen cultures were overlaid with 100 μl RPMI supplemented with 20 ng/ml IL‐4 and 20 ng/ml GM‐CSF per well.

RT‐DC

RT‐DC measurements were carried out using an AcCellerator (Zellmechanik Dresden) and a high‐speed CMOS camera (MC1362, Microtron) mounted on an inverted microscope (AxioObserver, Carl Zeiss AG) equipped with a xy‐stage and a 40×/0.65 objective. Two days post‐culturing in 2D suspension, 2D collagen, or 3D collagen, iDCs were treated with collagenase I (100 U Worthington) for 30–45 min at 37°C, washed in PBS, and resuspended in CellCarrier B (Zellmechanik Dresden). Resuspended iDCs were loaded into a 1 ml glass syringe with a PEEK tubing connector and a PTFE plunger (SETonic) and mounted on a syringe pump (neMESYS, Cetoni), together with a second 1 ml glass syringe filled with CellCarrier B as a sheath fluid. Both syringes were connected via PTFE tubing (S1810‐12, BOLA) to a microfluidic polydimethylsiloxane (PDMS) chip with a rectangular 20‐μm‐wide channel (Flic30, Zellmechanik Dresden), which was mounted on the microscope. Measurements were carried out at total flow rates of 0.04 and 0.12 μl/s, respectively, with a ratio of 3 between sheath flow and sample flow.

The measurement software Shape‐In 2 was used to acquire and analyze the contour, brightness, and area of the cells in real time. The data were analyzed using Shape‐Out 2 and gated manually for porosity and cell size. Statistical analysis was done in Shape‐Out 2 using a linear mixed model and each donor as a repetition. Scatter and contour plots were created using Shape‐Out 2, the data were plotted using GraphPad PRISM 9, and figures were assembled in Inkscape 1.0.

Infection

One day before infection, iDCs were spin transduced (centrifugation at 16 g for 1 h 30′ at 32°C) with 10¹⁰ SG‐Pert units of VLPs_VpxMac239. After washing, iDCs were infected using HIV‐1 R5 at MOI 0.1. Immediately after infection, equal aliquots of cells were mixed 1:1 with RPMI or collagen gel and seeded in a U‐ or F‐bottom 96‐well plate for suspension or 3D collagen cultures, respectively. Two days post‐infection, 100 μl cell supernatant were removed from each well and replaced with fresh RPMI supplemented with 20 ng/ml IL‐4 and 20 ng/ml GM‐CSF.

Antibodies used for flow cytometry

The following antibodies for the detection of cell surface markers were used at the indicated dilution: CD86 ANTIBODY, anti‐human, FITC, REAfinity™ (Miltenyi Biotec 130‐116‐262 1:100); CD86 antibody, anti‐human, PerCP‐Vio® 700, REAfinity™ (Miltenyi Biotec 130‐116‐164 1:100); CD80 antibody, anti‐human, PE (Miltenyi Biotec 130‐117‐683 1:100); PE mouse anti‐human CD83 (BD Pharmigen™ 556855 1:20); PE/cyanine7 anti‐human CD1a antibody (Biolegend 300121 1:100); CD169 (Siglec‐1) antibody, anti‐human, PerCP‐Vio® 700, REAfinity™ (Miltenyi Biotec 130‐101‐508 1:100); BV421 anti‐human CD169 (Biolegend 346018 1:100); BV421 mouse anti‐human CD206 (BD Pharmigen 564062 1:20); FITC ##man CD209 (DC‐SIGN; BD Pharmingen™ 551264 1:100); PerCP/cyanine5.5 anti‐human CD1c antibody (Biolegend 331514 1:50); Brilliant Violet 421™ anti‐human CD141 (Thrombomodulin) antibody (Biolegend 344113 1:50); CD327 (Siglec‐6) Antibody, anti‐human, FITC, REAfinity™ (Miltenyi Biotec 130‐112‐898 1:50); BV605 mouse anti‐human CD11c (Biolegend 301636 1:50); FITC anti‐human CD195 (CCR5) Antibody (Biolegend 359120 1:100); and PerCP/cyanine5.5 anti‐human CD4 Antibody (Biolegend 300530 1:100).

Flow cytometry

iDC maturation and differentiation were assessed by flow cytometry using a BD FACSCelesta with BD FACSDiva software. Gatings were done using FlowJo software and data were processed with Microsoft Office Excel and GraphPad Prism software. For staining, antibodies were diluted in MACS buffer (PBS, 2 mM EDTA, and 0.5% BSA), incubated with cells for 20 min at 4°C, and washed twice in PBS. When comparing iDCs from 2D suspension and 3D collagen cultures, at the indicated time point, cells from both conditions were treated with collagenase I (100 U Worthington) for 30–45 min at 37°C, washed in PBS, and then stained/analyzed. For FACS analysis of intracellular p24, cells were fixed in 3% PFA in PBS at 4°C O.N., permeabilized with 0.1% Triton‐X‐100/PBS, and stained with anti‐p24‐FITC (1:100 KC57 Beckmann Coulter, 6604665) in 0.1% Triton‐X‐100/PBS for 30 min at 4°C. Cells were then washed in PBS and analyzed. For FACS analysis of GFP expression, cells were fixed in 3% PFA in PBS at 4°C O.N., washed in PBS, and analyzed.

Imaging analysis

For HIV‐1 uptake, 1 day before infection, iDCs were spin transduced with 10¹⁰ SG‐Pert units of VLPs_VpxMac239. After washing, iDCs were infected using HIV‐1 NLENG‐1 R5‐harboring Vpr‐mRuby2 at MOI 0.2. Immediately after infection, equal aliquots of cells were mixed 1:1 with RPMI or collagen gel and seeded in a μ‐Slide Angiogenesis (ibidi). At the indicated time point, cells were washed twice in PBS and fixed in 3% PFA in PBS at 4°C O.N. Cells were then permeabilized 0.1% triton in PBS for 10′ at RT. Cell was stained using GAPDH (14C10) Rabbit mAb (Cell Signaling), diluted 1:150 in 10% FCS in PBS at 4°C O.N. After three washes in PBS, cells were stained with goat anti‐rabbit Alexa660 antibody together with ATTO390 Phalloidin (AttoTec AD390‐81) diluted 1:150 and 1:200, respectively. For plasma membrane staining, cells were stained using Wheat Germ Agglutinin, Alexa Fluor™ 647 Conjugate (Thermo Fisher Scientific), diluted in 1:250 in PBS, at 37°C for 20′.

For DC‐SIGN staining, 2 h after seeding in 2D suspension or embedding in 3D collagen, cells were treated with collagenase I (100 U Worthington) for 30–45 min at 37°C, washed in PBS, and fixed in 3% PFA in PBS ON at 4°C. After fixation, cells were permeabilized with 0.1% Triton‐X‐100/PBS and stained with anti‐DC‐SIGN (Santa Cruz Biotechnology sc‐65740) antibody ON at 4°C. After washing three times in PBS, cells were stained with Alexa Fluor 660 goat anti‐mouse antibody (Cat. No. A‐21054) and ATTO390 Phalloidin (AttoTec AD390‐81) diluted 1:150 and 1:200, respectively. Spinning disk confocal microscopy was performed using a Nikon Ti2 microscope equipped with an Andor CSU‐W1 spinning disk head. A Plan Apochromat VC 60×/1.2 WI or an Apochromat TIRF 100×/N.A. 1.49 oil immersion objective and EMCCD Andor iXon DU‐888 camera were used. Multichannel images were typically acquired using solid‐state lasers with excitation at 405, 488, 561, and 637 nm and matching single‐bandpass emission filters. Stacks were acquired with a z‐spacing of 300 nm.

Image processing

For HIV‐1 R5‐harboring Vpr fused with mRuby2 particles uptake, images were analyzed in a semi‐automated workflow using the Imaris Software (Oxford Instruments). Particles were found using the spot finder wizard based on mRuby2 signals, while cells were segmented using the cell finder wizard based on the cytoplasmic GAPDH staining. Phalloidin‐atto 390 signal, staining F‐actin, was used to find cell surface with the surface finder wizard, and finally, distance of each particle with respect to the cell cytoplasm and surface, as well as area, surface, and sphericity of each cell, was calculated by the software. For DC‐SIGN fluorescence intensity quantification, analyses were performed with Fiji. Background (measured in an area outside the cell) was subtracted from each image, z‐projections were created using “sum slices” function, and finally, mean of fluorescent intensity was calculated for each cell by manually drawing the region of interest around the border of the cell. For visualization purposes only, images from the DC‐SIGN channel were smoothened using the median filter (1 px radius).

Vpr‐Blam fusion assay

iDCs were infected using HIV‐1 R5 Vpr‐Blam at MOI 0.1. Immediately after addition of HIV‐1, equal cell aliquots were mixed 1:1 with RPMI or collagen gel and seeded in a 96‐well U‐ or F‐bottom plate for 2D suspension or 3D collagen cultures, respectively. Fusion of HIV‐1 particles was allowed to proceed for 4 h and 48 h at 37°C, then 2D suspension and 3D collagen cultures were treated with collagenase I (100 U Worthington) for 30–45 min at 37°C. Cells were extensively washed in PBS and stained 2 μM CCF2AM + 2.5 mM Probenecid in Fluorobrite DMEM 2% FCS for 5 h at 11°C to prevent particle fusion during the staining process. Where indicated, T20 was added to block fusion. Cells were then fixed in 3% PFA in PBS at 4°C O.N. and analyzed by FACS.

Cytokine quantification

A total volume of 100 μl cell supernatant was collected and inactivated with 0.5%Triton in PBS. The amounts of cytokines and chemokines were determined by Eve Technologies Corporation using the Discovery Assay: Human Cytokine Array/Chemokine Array 48‐Plex. When the cytokine amount was lower than the detection threshold, for calculating the log2 fold change, the value of the lowest detectable amount was used, as recommended by the manufacturer.

Transcriptome analysis

Two days post‐culturing in 2D suspension or 3D collagen and, where indicated, post‐infection, cells were treated with collagenase I (100 U Worthington) for 30–45 min at 37°C were extensively washed in PBS, and RNA was extracted using “Macherey‐Nagel NucleoSpin RNA” kit according to the manufacturer's instructions. Transcriptomes were determined by Clariom™ S Pico assay at the DKFZ microarray facility. The normalized expression values were further analyzed with R. In particular, dseq2 was used for the differential expression analysis of the normalized expression data and the multivariate evaluation of the samples (PCA analysis). The functional enrichment analysis on the subset of differentially expressed genes was performed using the online tool metascape (Love et al, 2014; Zhou et al, 2019). Gene Set Enrichment Analysis framework (GSEA, v4.1.0, Subramanian et al, 2005) was used to run the enrichment test on the REACTOME INTERFERON ALPHA BETA SIGNALING (v2022.1). The expression datasets (HIV‐1 R5 + VPX) were formatted as required by GSEA, and the phenotype labels were assigned accordingly. The statistical significance of the enrichment score was assessed by building the score null distribution estimated from the gene set with the number of permutations set to 1,000.

HIV‐1 transfer to CD4 T cells

CD4 T cells were isolated from human peripheral blood of healthy, HIV‐negative donors using the RosetteSep Human CD4 T cell enrichment kit (StemCell Technologies) according to the manufacturer's protocol, and were activated with Dynabeads™ Human T‐Activator CD3/CD28 (Gibco) for 72 h and cultured in RPMI supplemented with 10% heat‐inactivated FCS, 1% penicillin–streptomycin, and 10 ng/ml interleukin 2 (IL‐2 Biomol). One day before infection, iDCs were spin transduced with 10¹⁰ SG‐Pert units of VLPs_VpxMac239. After washing, iDCs were pulsed using HIV‐1 R5 at MOI 0.1 for 2 h at 37°C. After three washes, iDCs were mixed with heterologous CD4 T cells in 1:2 ratio. Immediately after mixing, equal aliquots of cells were mixed 1:1 with RPMI or collagen gel and seeded in a U‐ or F‐bottom 96‐well plate for suspension or collagen cultures, respectively.

Two days post‐co‐culturing, 100 μl cell supernatant was removed from each well and replaced with fresh media supplemented with 20 ng/ml IL‐4, 20 ng/ml GM‐CSF, and 10 ng/ml IL‐2.

Imaging analysis, 2‐photon microscopy (2PM) of iDC‐CD4 T cell interactions

CD4 T cell isolation, activation, and iDC differentiation were done as described above for transfer experiment. iDCs were labeled with CellTracker blue CMAC and pulsed using HIV‐1 R5 at MOI 0.1 for 2 h at 37°C. After three washes, iDC were mixed with heterologous CD4 T cells, labeled with CellTracker orange CMTMR, in 1:2 ratio. Immediately after mixing, equal aliquots of cells were mixed 1:1 with RPMI or collagen gel and seeded in a μ‐Slide Angiogenesis (ibidi) 10 μl/well. Cells were overlaid with 50 μl/well of RPMI supplemented with 20 mM HEPES. Imaging was performed using a Nikon Ti‐U inverted microscope equipped with a 25X Nikon CFI‐Apo (NA 1.1) objective and a TrimScope II 2PM system controlled by ImSpector software (LaVision BioTec) combined with an automated system for real‐time correction of tissue drift (Vladymyrov et al, 2016). For 2‐photon excitation, a Ti:Sapphire laser with an optical parametric oscillator (OPO, Coherent MPX Package) was tuned to 800 and 1,100 nm, respectively. For four‐dimensional analysis of cell migration, 10–62 x‐y sections with z‐spacing of 3 μm (30–186 μm depth) were acquired every 60 s for 2 h; the field of view was 268 × 268 μm at 512 × 512 pixels. Emitted light was detected through 447/60‐, 525/50‐, 595/50‐, and 690/50‐nm bandpass filters using non‐descanned detectors. Time‐lapse movies were reconstructed using Vision4D software (Arivis). Interactions were manually tracked using InViewR (Arivis). DCs and T cells were automatically tracked and manually corrected using segments in the Imaris software (Bitplane).

HIV‐1 infection in the presence of anti‐DC‐SIGN and anti‐MMR‐blocking antibodies

One day before infection, iDCs were spin transduced (centrifugation at 300 rpm for 1 h 30′ at 32°C) with 10¹⁰ SG‐Pert units of VLPs_VpxMac239. After washing, iDCs were incubated with 3 μg/ml of Anti CD209‐PE clone AZND1 (Beckman) or with 10 μg/ml of Anti‐Human CD206 (MMR; Biolegend 321102) or with 10 μg/ml of Mouse IgG1 k Isotype Control Antibody (Biolegend 400102) for 30 min RT. Cells were then infected using HIV‐1 R5 at MOI 0.1. Immediately after infection, equal aliquots of cells were mixed 1:1 with RPMI or collagen gel and seeded in a U‐ or F‐bottom 96‐well plate for suspension or 3D collagen cultures, respectively. Fusion efficiency was assessed at 4 h.p.i. by Vpr‐Blam assay as described above, and productive infection was analyzed 2 d.p.i. by FACS analysis of intracellular p24 as described above.

Biosafety

All aspects of the study were approved by the local authorities (Regierungspräsidien Karlsruhe and Tübingen) before initiation of this study. Work with infectious HIV‐1 was performed in a biosafety level 3 laboratory by trained personnel.

Statistical analyses

Where not specifically indicated, statistical analyses were performed using Prism version 8.0 (GraphPad).

Author contributions

Lara Gallucci: Formal analysis; investigation; methodology; writing – original draft; writing – review and editing. Tobias Abele: Formal analysis; investigation; methodology. Raffaele Fronza: Formal analysis; methodology. Bettina Stolp: Formal analysis; investigation; methodology. Vibor Laketa: Formal analysis; methodology; writing – review and editing. Samy Sid Ahmed: Methodology. Annica Flemming: Resources. Barbara Müller: Resources; supervision; writing – review and editing. Kerstin Göpfrich: Supervision; writing – review and editing. Oliver T Fackler: Conceptualization; supervision; funding acquisition; writing – original draft; writing – review and editing.

Disclosure and competing interests statement

The authors declare that they have no conflict of interest.

Supporting information

Appendix

Expanded View Figures PDF

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Source Data for Expanded View and Appendix

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EMBO reports (2023) 24: e56818

Data availability

The microarray data present in this paper are available on the GEO database: ID of the data is GSE218367 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE218367). Source data for the microscopy images are available on the Bioimage database at the following link https://www.ebi.ac.uk/biostudies/bioimages/studies/S‐BIAD621.