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Mouse T cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex

  1. Daniel Blumenthal  Is a corresponding author
  2. Vidhi Chandra
  3. Lyndsay Avery
  4. Janis K Burkhardt  Is a corresponding author
  1. Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute and Perelman School of Medicine at the University of Pennsylvania, United States
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Cite this article as: eLife 2020;9:e55995 doi: 10.7554/eLife.55995

Abstract

T cell activation by dendritic cells (DCs) involves forces exerted by the T cell actin cytoskeleton, which are opposed by the cortical cytoskeleton of the interacting antigen-presenting cell. During an immune response, DCs undergo a maturation process that optimizes their ability to efficiently prime naïve T cells. Using atomic force microscopy, we find that during maturation, DC cortical stiffness increases via a process that involves actin polymerization. Using stimulatory hydrogels and DCs expressing mutant cytoskeletal proteins, we find that increasing stiffness lowers the agonist dose needed for T cell activation. CD4+ T cells exhibit much more profound stiffness dependency than CD8+ T cells. Finally, stiffness responses are most robust when T cells are stimulated with pMHC rather than anti-CD3ε, consistent with a mechanosensing mechanism involving receptor deformation. Taken together, our data reveal that maturation-associated cytoskeletal changes alter the biophysical properties of DCs, providing mechanical cues that costimulate T cell activation.

Introduction

The initiation of an adaptive immune response requires priming of naïve T cells by professional antigen-presenting cells (APCs). This process involves multiple receptor-ligand interactions, which occur in concert at a specialized cell-cell contact site called the immunological synapse (Dustin, 2014). Through these interactions, APCs transmit a highly orchestrated series of signals that induce T cell activation and direct differentiation of T cell populations (Friedl et al., 2005). While the biochemical aspects of this process have been the subject of many studies, the contribution of mechanical cues is only now being uncovered.

Following initial T cell receptor (TCR) engagement, T cells apply cycles of pushing and pulling forces on interacting APCs (Bashour et al., 2014; Blumenthal and Burkhardt, 2020; Hui et al., 2015; Husson et al., 2011; Sawicka et al., 2017). These forces are essential for proper T cell activation (Li et al., 2010; Pryshchep et al., 2014). Moreover, force application is responsible, at least in part, for the ability of T cells to rapidly discriminate between agonist and antagonist antigens (Das et al., 2015; Liu et al., 2014). While the mechanism by which force is translated into biochemical cues remains controversial (Das et al., 2015; Hong et al., 2015; Kim et al., 2009), there is evidence that early tyrosine phosphorylation events downstream of TCR engagement occur at sites where applied force is maximal (Bashour et al., 2014). Interestingly, the amount of force a T cell applies is directly affected by the stiffness of the stimulatory substrate (Husson et al., 2011; Sawicka et al., 2017). Thus, it appears that force application is mechanically coupled to the T cell’s ability to sense stiffness (mechanosensing). In other cell types, substrate stiffness has been shown to affect a variety of cell functions including differentiation, migration, growth, and survival (Byfield et al., 2009; Discher et al., 2005; Engler et al., 2006; Lo et al., 2000; Oakes et al., 2009; Pelham and Wang, 1997; Solon et al., 2007; Trappmann et al., 2012). Stiffness sensing in T cells has not been well studied, though there is some evidence that substrate stiffness affects both initial priming and effector functions (Alatoom et al., 2020; Basu et al., 2016; Judokusumo et al., 2012; O'Connor et al., 2012; Saitakis et al., 2017). Since the physiologically relevant substrate for T cell priming is the surface of the interacting APC, one might predict that changes in cortical stiffness of the APC will profoundly influence T cell priming. However, this prediction remains untested, and studies addressing the role of substrate stiffness in T cell priming did not take into consideration the physiological stiffness of APCs.

Dendritic cells (DCs) are the dominant APCs that prime T cells in vivo (Jung et al., 2002). One of the hallmarks of DC biology is the process of maturation. Immature DCs are sentinels of the immune system, specialized for immune surveillance and antigen processing (Mellman and Steinman, 2001). In response to infection or injury, inflammatory stimuli trigger signaling pathways that induce molecular reprogramming of the cell. The resulting mature DCs express high levels of surface ligands and cytokines needed for efficient T cell priming (Burns et al., 2004). A central feature of DC maturation is remodeling of the actin cytoskeleton, a process that underlies other maturation-associated changes such as downregulation of endocytosis and increased migratory behavior (Garrett et al., 2000; West et al., 2000). Cytoskeletal remodeling also has a direct impact on the ability of mature DCs to prime T cells (Al-Alwan et al., 2001; Comrie et al., 2015). Indeed, depolymerization of actin filaments perturbs the ability of mature peptide-pulsed DCs to activate T cells, indicating that actin plays an important role on the DC side of the immunological synapse. We hypothesized that maturation-associated changes in the actin cytoskeleton modulate the stiffness of the DC cortex and promote T cell priming by providing physical resistance to the pushing and pulling forces exerted by the interacting T cell.

In this study, we aimed to better understand the relationship between DC cortical stiffness and T cell activation. We found that during maturation, DCs undergo a 2–3-fold increase in cortical stiffness and that T cell activation is sensitive to stiffness over the same range. Stiffness sensitivity was observed in all T cell populations tested and was particularly robust in naïve CD4+ T cells. Moreover, stiffness responses were most profound when T cells were engaged through TCRαβ directly, consistent with a mechanosensing mechanism involving receptor deformation. Since we find that stiffer surfaces lower the threshold signal required for T cell activation, we conclude that stiffness serves as a novel biophysical costimulatory mechanism that functions in concert with canonical signaling cues to facilitate T cell priming.

Results

Dendritic cell stiffness increases upon maturation

During maturation, DCs undergo a set of phenotypic changes that transform them into highly effective APCs (Mellman and Steinman, 2001). We hypothesized that as part of this maturation process, DCs might also modulate their cortical stiffness. To test this, we used atomic force microscopy (AFM) to directly measure cortical stiffness of immature and mature DCs. Murine bone marrow-derived DCs (BMDCs) were prepared as described in the Materials and methods and cultured in the absence or presence of lipopolysaccharide to induce maturation. Cells were plated on poly L-lysine (PLL) coated coverslips and allowed to spread for at least 4 hr before the measurement of cortical stiffness by AFM microindentation. Because the population of LPS-treated cells was heterogeneous with respect to maturation markers, cells were labeled with fluorescent anti-CD86, and immature (CD86 negative) or mature (CD86 high) cells were selected for AFM measurements (Figure 1—figure supplement 1). As shown in Figure 1A, immature BMDCs were quite soft, with a mean Young’s modulus of 2.2 ± 1.7 kPa. Mature BMDCs were almost 2-fold stiffer, with a Young’s modulus of 3.3 ± 1.4 kPa. Importantly, the stiffness of CD86-negative BMDCs within the LPS-treated population was 2.0 ± 1.0, the same as that of untreated, immature DCs. This demonstrates that the observed increase in stiffness is a property of DC maturation rather than an unrelated response to lipopolysaccharide treatment. Since BMDCs do not recapitulate all of the properties of classical, tissue-resident DCs (Guilliams and Malissen, 2015; Lutz et al., 2016; Na et al., 2016), we verified our results by measuring the stiffness of ex vivo DCs purified from spleens of untreated or LPS-injected mice. Results were very similar; the stiffness of immature splenic DCs was 1.9 ± 0.7, and lipopolysaccharide treatment induced a 2.5-fold increase in stiffness resulting in mature splenic DCs with a mean Young’s modulus of 4.8 ± 1.7 kPa (Figure 1B). These results demonstrate that stiffness modulation is a bona fide trait of DC maturation. Moreover, they establish that the biologically relevant range of DC stiffness lies between 2 and 8 kPa.

Figure 1 with 4 supplements see all
DC maturation induces an actin-dependent increase in cortical stiffness.

(A) BMDCs were untreated or matured by treatment with LPS, and cortical stiffness was measured by AFM microindentation. Fluorescent anti-CD86 labeling was used to select immature (CD86-negative) or mature (CD86 high) cells. (B) Ex vivo DCs were purified from spleens of untreated mice or from mice injected with lipopolysaccharide 24 hr before harvesting the spleen, and analyzed as in A. (C) Immature or LPS-matured BMDCs either left untreated or treated with 10 µm of the actin depolymerizing agents latrunculin-B or cytochalasin-D before AFM measurements. (D) Immature or LPS-matured BMDCs were plated on substrates of different stiffness before AFM measurements. Data are pooled from 2 to 3 independent experiments. Each data point represents an average of two stiffness measurements at different locations around a single cell nucleus. Error bars denote standard deviation. n.s non-significant, **p<0.01, ***p<0.001, ****p<0.0001 calculated by an unpaired one-way ANOVA, post-hoc Tukey corrected test.

The maturation-induced increase in stiffness is actin dependent and substrate independent

One well-known feature of DC maturation is remodeling of the actin cytoskeleton. This process involves changes in the activation status of Rho GTPases and downstream actin regulatory proteins, and it is known to downregulate antigen uptake and increase cell motility (Garrett et al., 2000; West et al., 2000). To know if changes in actin cytoarchitecture can also result in increased cortical stiffness, we treated immature and mature BMDCs with actin-depolymerizing agents cytochalasin-D or latrunculin-B. Neither drug affected the stiffness of immature BMDCs, indicating that the basal level of stiffness depends on factors other than the actin cytoskeleton (Figure 1C). By contrast, both drugs induced a significant decrease in the stiffness of mature DCs, with cytochalasin reducing their stiffness to that of immature DCs. We conclude that the increased cortical stiffness observed upon DC maturation is another feature of actin cytoskeletal reprogramming.

Some cell types regulate their stiffness in response to the stiffness of their substrate (Byfield et al., 2009; Tee et al., 2011). To test whether DCs exhibit this behavior, immature and mature BMDCs were plated on PLL-coated substrates of different compliances (hydrogels of 2 or 25 kPa, or glass surfaces in the GPa range) and allowed to spread on the surface for at least 4 hr before AFM measurement. Importantly, when allowed to spread on different PLL-coated surfaces, no notable changes were detected in BMDC morphology, and changes in cell spreading area were minimal (less than 10%, Figure 1—figure supplement 2). Hydrogel compliance was verified by measuring the elastic modulus of the surface in areas devoid of cells (Figure 1—figure supplement 3). As shown in Figure 1D, substrate compliance did not affect cortical stiffness of either immature or mature BMDCs. In control studies, we could readily detect substrate-dependent changes in stiffness of normal fibroblast cells (not shown). Thus, we conclude that DCs maintain a specific cortical stiffness, which is characteristic of their maturation state.

DC cortical stiffness is primarily controlled by actin polymerization

Next, we sought to identify the molecular mechanisms controlling DC cortical stiffness. Several actin regulatory mechanisms are known to change during DC maturation. In particular, mature DCs upregulate the actin bundling protein fascin (Yamashiro, 2012), show activation of myosin-dependent processes (van Helden et al., 2008), and undergo changes in the activation and localization of Rho-GTPases, which in turn regulate actin polymerization via the Arp2/3 complex and formins (Burns et al., 2001; Garrett et al., 2000; West et al., 2000). To ask how each of these pathways influences cortical stiffness, we used small molecule inhibitors and DCs from relevant knockout mice. Note that to facilitate comparison between experiments, control immature and mature DCs were tested in each experiment, and results were normalized based on values for mature DCs. First, we tested the role of fascin, which is known to generate very stiff actin bundles in vitro (Démoulin et al., 2014). Surprisingly, the stiffness of BMDCs from fascin-/- mice was not significantly different from that of WT BMDCs either before or after LPS-induced maturation (Figure 2A). Next, we tested the contribution of myosin contractility, which is known to control stiffness and membrane tension in other cell types (Salbreux et al., 2012). As shown in Figure 2B, treating mature BMDCs with the myosin II inhibitor blebbistatin reduced stiffness by a small, albeit statistically significant amount. Similar results were obtained with the Rho-kinase (ROCK) inhibitor Y27623, which indirectly inhibits myosin function.

Effects of actin regulatory proteins on DC cortical stiffness.

Murine BMDCs from WT mice or mice lacking key actin-associated proteins were untreated or matured by treatment with LPS, and cortical stiffness was measured by AFM microindentation. To facilitate comparison between experiments, results were normalized to values of mature WT BMDCs in each experiment. (A) Cortical stiffness of BMDCs from mice lacking important actin modulating proteins. (B) Cortical stiffness of WT BMDCs treated with cytoskeletal inhibitors. CK666 (100 µM) was used to inhibit branched actin polymerization by Arp2/3. SMIFH2 (10 µm) was used to inhibit linear actin polymerization by formins. Acto-myosin contractility was inhibited directly with blebbstatin (50 µM) or indirectly with the Rho-kinase inhibitor Y27632 (25 µM). All drugs do not affect immature BMDCs (data not shown). Data points for untreated WT BMDCs (both immature and mature) were pooled from all experiments as a reference. The dashed line represents the average stiffness of untreated mature WT BMDCs from all experiments. Data are pooled from two to three independent experiments. Each data point represents an average of two stiffness measurements at different locations around a single cell nucleus. Error bars denote standard deviation. n.s non-significant, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 calculated by an unpaired one-way ANOVA, with post-hoc Tukey correction.

Next, we considered the possibility that cortical stiffness is modulated by actin polymerization. Broadly speaking, actin polymerization is induced by two sets of proteins: formins generate linear actin filaments, while activators of the Arp2/3 complex produce branched actin structures. Treatment of DCs with the pan-formin inhibitor SMIFH2 significantly reduced the cortical stiffness of mature DCs (Figure 2B). The most profound reduction was observed after inhibition of Arp2/3-mediated branched actin polymerization by CK666. DCs express multiple activators of Arp2/3 complex, of which two have been implicated in maturation-associated changes in actin architecture: Hematopoietic lineage cell-specific protein 1 (HS1), the hematopoietic homolog of cortactin (Huang et al., 2011), and WASp, the protein defective in Wiskott-Aldrich syndrome (Bouma et al., 2007; Bouma et al., 2011; Calle et al., 2004). To individually assess the role of these two proteins, we used BMDCs cultured from HS1 and WASp knockout mice. As shown in Figure 2A, the loss of HS1 had no impact on cortical stiffness of either immature or mature BMDCs. By contrast, mature WASp knockout BMDCs were significantly less stiff than WT controls. This difference mirrors that seen after inhibition of Arp2/3 complex by CK666, suggesting that WASp is the primary activator of Arp2/3 complex-dependent changes in cortical stiffness. The defect in WASp knockout DCs was observed only after maturation; immature WASp knockout DCs did not differ in stiffness from WT controls. This is consistent with our finding that the stiffness of immature DCs is unaffected by actin depolymerizing agents. Taken together, these results show that activation of the WASp-dependent actin polymerization pathway, and to a lesser extent increased myosin contractility and formin-mediated actin polymerization, all contribute to the increased cortical stiffness of mature DCs.

Stiffness lowers the threshold for activation of CD4+ T cells but not CD8+ T cells

Our findings raise the possibility that changes in DC cortical stiffness, like other maturation-induced changes, enhance the ability of these cells to prime a T cell response. Previous studies have shown that T cells are sensitive to the stiffness of stimulatory surfaces (Alatoom et al., 2020; Judokusumo et al., 2012; O'Connor et al., 2012), and that the TCR serves as the mechanosensor (Judokusumo et al., 2012). However, the results are conflicting, and these studies were not performed within the physiological stiffness range that we have defined for DCs. Thus, we tested T cell responses on hydrogels with a stiffness range spanning that of immature and mature DCs (2–25 kPa). Compliance of the hydrogel surfaces was verified by measuring the elastic modulus of the surfaces directly by AFM. Hydrogel stiffnesses were found to be similar to those reported by the manufacturer (Figure 3—figure supplement 1). Surfaces were coated with varying doses of peptide-loaded major histocompatibility complex (pMHC) molecules, together with a constant dose of anti-CD28. Surfaces were coated with H-2Kb class I MHC loaded with the N4 (SIINFEKL) peptide (pMHC-I), or I-Ab class II MHC loaded with the OVA329-337 (AAHAEINEA) peptide (pMHC-II), to stimulate OT-I CD8+ or OT-II CD4+ T cells, respectively. Plastic surfaces, which are commonly used for stimulation with surface-bound ligands, were included as a familiar reference point. Importantly, the surface chemistry and ligand-binding properties of plastic and hydrogel surfaces are fundamentally different, so direct comparison is not meaningful. To test the effects of substrate stiffness on early T cell activation, we measured surface expression of the activation markers CD25 and CD69, as well as the production of IL-2, all at 24 hr post stimulation. As shown in Figure 3A–C, CD4+ T cells showed a profound stiffness-dependent response at 24 hr across all measures. This response was most clearly seen for upregulation of CD25 and CD69, where increasing substrate stiffness enhanced the CD4+ T cell response in a graded manner. As expected, for any given substrate stiffness T cell activation increased with increasing peptide dose. However, comparison among stimulatory surfaces revealed that increasing substrate stiffness lowered the pMHC-II dose required to obtain the same level of activation. Over the stiffness range associated with DC maturation (2–8 kPa), the dose of TCR signal needed to induce surface marker upregulation was shifted by 1–2 logs. Analysis of IL-2 production revealed a similar effect, although the stiffness sensitivity was more bi-modal. IL-2 production increased almost 3-fold when CD4+ T cells were stimulated on surfaces of 8 kPa, as opposed to 2 kPa, for the same antigen dose.

Figure 3 with 2 supplements see all
CD4+ and CD8+ T cells demonstrate vastly different stiffness responses.

Murine T cells were purified from lymph nodes and spleen and activated on stimulatory acrylamide hydrogel surfaces with a stiffness range of 2–25 kPa and plastic (PL). Stimulatory surfaces were coated with the indicated concentrations of pMHC-I or pMHC-II together with 2 µg/mL anti-CD28 to stimulate OT-I CD8+ or OTI-II CD4+ T cells, respectively. (A,B,D,E) Cells were harvested 24 hr post activation and expression of early activation markers was measured by flow cytometry. Data represent averages +/- SEM of percent positive cells from N = 3 independent experiments. (A,B) CD4+ T cells show profound stiffness dependent expression of both markers. (C,F) Cell supernatants were collected at 24 hr and IL-2 expression was analyzed by ELISA. Data represent means +/- StDev from three to six replicate samples from one representative experiment, N = 2 experiments.

Strikingly, the robust stiffness response we observed in CD4+ T cells was not recapitulated for CD8+ T cells, especially when T cell activation was assessed based on surface marker upregulation (Figure 3D,E). Analysis of IL-2 production did reveal stiffness-enhanced activation of naïve CD8+ T cells; as in CD4+ T cells, this was clearest across the stiffness range associated with DC maturation. To determine if the stiffness dependency of CD4+ T cells seen at early times after TCR engagement is maintained at later times, we measured T cell proliferation based on CFSE dilution at 72 hr post stimulation. Similar to what was observed for early activation markers, increasing substrate stiffness produced graded increases in CD4+ T cell proliferation, and the threshold dose required to induce robust proliferation shifted as a function of substrate stiffness (Figure 4A,B). This effect was particularly evident at low doses of pMHC-II (0.1–1 ug/mL). Interestingly, although soft hydrogels (2–4 kPa) elicited only very low levels of CD4+ T cell proliferation, these substrates did induce upregulation of CD25 in a high percentage of CD4+ T cells, even in the undivided populations (Figure 4C,D). This indicates that an activating signal was received, but was insufficient to drive proliferation.

CD4 T cell proliferation is stiffness dependent and IL-2 independent.

OT-II CD4+ T cells were purified from lymph nodes and spleen and activated on stimulatory acrylamide hydrogel surfaces with a stiffness range of 2–25 kPa and plastic (PL). Stimulatory surfaces were coated with the indicated concentrations of pMHC-II together with 2 µg/mL anti-CD28. (A,B) Proliferation of CD4+ T cells was measured by CFSE dilution at 72 hr post activation, showing profound stiffness-dependent proliferation. (A) Representative CFSE dilution matrix from a single experiment. (B) Average division index from three independent experiments. (C) Representative plots of CD25 expression as a function of CFSE dilution at 72 hr from a single experiment shows that upregulation of CD25 on T cell membrane precedes proliferation. (D) Average percent of T cells expressing CD25 from three independent experiments. (E) Division index of CD4+ T cells activated with or without addition of 25 U/mL of exogenous IL-2. Data in B, D, and E represent averages +/- SEM from at least three independent experiments.

Since the threshold stimuli (stiffness and dose of pMHC-II) required to induce significant IL-2 production and proliferation were very similar (Figures 3C and 4B), we reasoned that the threshold for proliferation might be driven by IL-2 availability. To test this, OT-II CD4+ T cells were stimulated on hydrogels with or without addition of 25 U/mL exogenous IL-2. Interestingly, addition of IL-2 did not rescue the proliferation of T cells stimulated on soft surfaces, nor did it increase proliferation on stiffer ones (Figure 4E). Thus, we conclude that in addition to influencing the signaling threshold for IL-2 production, substrate stiffness also affects other IL-2 independent events needed for efficient T cell proliferation.

Although early activation events in CD8+ T cells showed little to no stiffness sensitivity, CD8+ T cells showed mild stiffness-dependent proliferation (Figure 5A,B). The concentration of stimulatory ligand needed to induce at least one round of division was similar across the entire stiffness range Over successive rounds, increased stiffness did enhance the extent of proliferation, but the differences were relatively small (Figure 5B). Interestingly, analysis of CFSE dilution as a function of CD25 expression reveals evidence that CD8+ T cells exhibit a binary stiffness response (Figure 5C,D); at low doses of peptide ligand, cells stimulated on very stiff substrates (25 kPa or plastic) survived and proliferated, whereas cells stimulated on softer substrates were mostly lost (Figure 5C). From the standpoint of T cell priming, the significance of this observation is unclear as these stiffnesses are well outside the biologically relevant range we measured for DCs.

Figure 5 with 1 supplement see all
CD8+ T cell proliferation and degranulation show moderate stiffness dependency.

Naïve OT-I CD8+ T cells were purified from lymph nodes and spleen and activated on stimulatory acrylamide hydrogel surfaces with a stiffness range of 2–25 kPa and plastic (PL). Stimulatory surfaces were coated with the indicated concentrations of pMHC-I together with 2 µg/mL anti-CD28. (A,B) Proliferation of CD8+ T cells was measured by CFSE dilution at 72 hr post activation, showing only moderate stiffness-dependent proliferation. (A) Representative CFSE dilution matrix from a single experiment. Note that the threshold pMHC-I concentration needed to induce proliferation is very similar between the different stiffness surfaces. (B) Average division index from three independent experiments. (C) Representative plot of CD25 expression as a function of CFSE dilution at 72 hr from a single experiment shows a binary stiffness response. Note that with low doses of pMHC-I, only cells stimulated on very stiff substrates (25 kPa or plastic) survived and proliferated. Percent of live cells is given for each condition. (D) Average percent of T cells expressing CD25 from two independent experiments. Levels of CD25 membrane expression are very similar between the different substrates, probably reflecting the fact that only T cells that upregulate CD25 survive. (E) Cytotoxic CD8+ T cells on day 8 or 9 of culture were restimulated on hydrogel surfaces with a range of pMHC-I concentrations, and degranulation was measured based on surface exposure of CD107a (N = 3). Data in B, D, and E represent averages +/- SEM from at least three independent experiments.

The observed difference between CD4+ and CD8+ T cell stiffness response could be associated with the difference in antigen strength between the AAHAEINEA (OVA323-339) pMHC-II complex used to stimulate CD4+ T cells, and the SIINFEKL (N4) pMHC-I complex used to stimulate CD8+ T cells. To verify that this is not the case, both CD4+ and CD8+ T cells were stimulated in the same way, using surfaces of different stiffness with varying concentrations of αCD3ε together with 2 µg/mL of αCD28. Proliferation was measured based on CFSE dilution at 72 hr post stimulation (Figure 5—figure supplement 1). We found that even when both are stimulated through the CD3 complex, CD4+ T cells exhibit profound stiffness sensitivity (especially within the physiological range), while the stiffness responses of CD8+ T cells are more modest. Thus, we conclude that the more robust stiffness response of CD4+ vs CD8+ T cells stems from differences in the cells themselves, rather than the properties of the particular pMHC/TCR pairs used for investigation.

Taken together, our findings point to a mechanism in which stiffer substrates have a sensitizing effect on CD4+ T cells, similar to that of classical costimulatory molecules such as CD28 (Harding et al., 1992). When considered in this way, the relative lack of stiffness responses in CD8+ T cells fits with the fact that CD8+ T cells are much less dependent on costimulatory signals (McAdam et al., 1998).

Degranulation of cytotoxic T cells shows mild stiffness sensitivity

Whereas naïve T cells are activated by DCs, effector T cells interact with many cell types. In particular, cytotoxic CD8+ T cells (CTLs) must respond to a variety of possible target cells, which may differ widely with respect to stiffness. We therefore reasoned that CTL effectors might be stiffness independent. To test this, we measured the extent of cytotoxic granule release (degranulation) of effector OTI CTLs stimulated on different stiffness hydrogel surfaces. CTLs were re-stimulated on hydrogels coated with a range of pMHC-I concentrations in the presence of fluorescent anti-CD107a antibody and the amount of CD107a on the cell membrane was analyzed using flow cytometry. Degranulation showed only a mild stiffness dependency (Figure 5E), and stiffness tended to affect the magnitude of degranulation rather than whether or not a degranulation response was triggered. Interestingly, changes in substrate stiffness within the range of defined for DCs (2–8 kPa) had little or no impact on degranulation. Increased degranulation was only seen on stiffer surfaces (12 and 25 kPa). This could have functional consequences for effector function in vivo as target cells in inflamed tissues can reach this stiffness range.

Engagement of the TCR complex by pMHC elicits the most prominent stiffness response

Many current models for TCR mechanosensing are founded on the notion of TCR deformation following the engagement of cognate pMHC (Ma et al., 2008). According to this concept, forces applied by the T cell on the TCR-pMHC bond result in conformational changes within TCRαβ (primarily the β chain), which are transmitted to intracellular components of the TCR/CD3 complex, leading to the initiation of downstream signaling (Das et al., 2015; Lee et al., 2015; Swamy et al., 2016). Given this, we wondered whether engaging the TCR complex through the CD3ε chain, as compared to direct TCRαβ engagement, would differentially affect T cell mechanosensing. To test this, CD4+ OT-II T cells were stimulated on hydrogels coated with anti-CD3ε antibodies, anti-TCRβ antibodies, or pMHC-II monomers. T cell activation was measured at 72 hr based on proliferation (CFSE dilution) and expression of CD25 (Figure 6). All three ligands induced a stiffness-dependent response for both proliferation and CD25 expression, but the responses differed in significant ways. In general, stimulating T cells with pMHC-II resulted in the strongest responses on the hydrogel surfaces; only on plastic surfaces did anti-CD3ε stimulation yield a similarly strong response (Figure 6A,C). Importantly, on surfaces with a stiffness similar to that of mature DCs (8 kPa), stimulation with pMHC resulted in robust proliferation, while stimulation with anti-CD3ε yielded a minimal response. On softer substrates (2–4 kPa), pMHC elicited some proliferation, whereas stimulation with anti-CD3 did not. Interestingly, stimulation with anti-TCRβ resulted in a mixed response. At high doses of antigen, stimulation with anti-TCRβ yielded clear proliferative responses on substrates within the biologically-relevant stiffness range. Analysis of CD25 expression patterns revealed a similar trend (Figure 6D–F); on soft surfaces, pMHC yielded the strongest response, and anti-TCRβ was more effective than anti-CD3ε. Taken together, these results indicate that T cells sense substrate stiffness best through direct engagement of TCRαβ as predicted by the receptor deformation model.

Stimulation of TCR with pMHC leads to the strongest stiffness-dependent response.

OT-II CD4+ T cells were stimulated on acrylamide hydrogels of different stiffnesses coated with the indicated range of stimulatory ligands. Proliferation and membrane expression of CD25 were measured 72 hr post activation using flow cytometry. (A,D) Stimulation with anti-CD3ε antibody. (B,E) Stimulation with anti-TCRβ antibody. (C,F) Stimulation with pMHC-II. Plots show the average division index or CD25 expression from three independent experiment. Gray areas denote a similar range of stimulatory ligand molar concentrations to aid comparison.

Increased stiffness of mature DCs enhances their ability to prime T cells

Our hydrogel assays show that T cell activation is enhanced by changes in stiffness over the range observed for DC maturation, consistent with the idea that modulation of cortical stiffness is a biophysical mechanism by which DCs control T cell activation. To test this directly, we sought conditions under which we could manipulate the stiffness of mature DCs. We took advantage of our finding that mature WASp-KO BMDCs are approximately 20% softer than WT controls (Figure 2A; data are presented as absolute values in Figure 7A). WT and WASp-KO BMDCs were pulsed with increasing concentrations of OVA323-339 peptide and used to prime OT-II CD4+ T cells. As shown in Figure 7B, WASp-KO BMDCs did not prime T cells as efficiently as WT BMDCs at low OVA concentrations. Higher concentrations of OVA rescued this defect, showing that loss of WASp shifts the dose of peptide needed rather than affecting T cell priming per se, in keeping with the view that DC stiffness provides a costimulatory signal. Next, we attempted to test T cell priming activity of DCs that are stiffer than WT cells. We tested several genetic manipulations, most of which did not significantly increase the cortical stiffness of mature BMDCs. We did find that overexpression of a constitutively active form of WASp (I294T, CA-WASp [Beel et al., 2009]) increased cortical stiffness of mature BMDCs by approximately 20% relative to WT cells (Figure 7A), but these BMDCs failed to prime T cells more efficiently (Figure 7C). Expression of CA-WASp only enhances BMDC stiffness to approximately 5 kPa, and based on our hydrogel studies, this increase is unlikely to be sufficient to enhance T cell activation. It seems likely that conditions that stiffen DCs to 10 kPa or more would further enhance T cell responses, but we were unable to test this directly, and it is not clear whether this happens in vivo. Nonetheless, the studies using WASp-KO DCs show that changes in DC stiffness impact their ability to efficiently prime a T cell response.

DC cortical stiffness acts as a costimulatory signal for T cell activation.

WT or WASp-/- BMDCs, or WT BMDCs transduced with constituently active form of WASp (CA-WASp) were untreated or matured by treatment with LPS. (A) Cortical stiffness was measured by AFM microindentation. Each data point represents an average of two stiffness measurements at different locations around a single cell nucleus. Error bars denote standard deviation. ***p<0.001, ****p<0.0001 calculated by an unpaired one-way ANOVA, comparing mature WT with all other treatments, with post-hoc Tukey correction. (B,C) LPS-matured BMDCs were pulsed with a range of OVA323-339 peptide concentrations and co-cultured with ex-vivo OT-II CD4+ T cells for 72 hr. Proliferation was measured by CFSE dilution. (D,E) Proliferation index pooled from two independent experiments. (F–G) Division index values pooled from two independent experiments. Error bars represent StDev.

Discussion

Recent studies have shown that T cell activation involves mechanical cues (reviewed in Blumenthal and Burkhardt, 2020). We have previously shown that the DC cytoskeleton constrains the mobility of stimulatory ligands on the DC surface, enhancing T cell activation by opposing the forces exerted by the T cell on the corresponding receptors (Comrie et al., 2015). In this study, we elucidate a second mechanism whereby the DC cytoskeleton enhances T cell activation. We show that actin remodeling during DC maturation increases the cortical stiffness of DC by 2–3-fold, and that T cell activation is enhanced by increases in stiffness over the same range. Importantly, increased stiffness lowers the threshold dose of TCR ligand needed for T cell activation, as expected if substrate stiffness serves as a costimulatory signal. In keeping with this concept, CD4+ T cells showed more profound stiffness-sensitivity than CD8+ T cells, especially at early times in the activation process. Together, these results indicate that stiffening of the DC cortex during maturation provides biophysical cues that work together with canonical costimulatory cues to enhance T cell priming.

Modulation of actin architecture has long been appreciated as an essential feature of DC maturation. Changes in the DC actin cytoskeleton facilitate the transition from highly endocytic tissue-resident cells to migratory cells specialized for antigen presentation (Burns et al., 2004; Burns et al., 2001). Our findings reveal a new facet of this process. We show that immature DCs are very soft, and that upon maturation, their cortical stiffness is increased by 2–3-fold. This is true for cultured BMDCs treated with lipopolysaccharide in vitro, as well and splenic DCs harvested from LPS-treated mice. A similar trend was reported by Bufi et al., 2015 for human monocyte-derived DCs, although that study reported lower absolute Young’s modulus values. While we used AFM indentation, Bufi et al. used microplate rheology. Since different methods for measuring cell mechanical properties produce absolute Young’s modulus values that can vary by as much as 100-fold (Wu et al., 2018), it seems likely that the apparent discrepancy in absolute values stems from technical differences between the two studies. Nevertheless, it is clear from both studies that the stiffness of the DC cortex is modulated during maturation.

It is important to note that DCs have complex surface topologies with prominent invaginations and projections that change dramatically during maturation (Knight et al., 1986; Verdijk et al., 2004). In particular, mature DCs exhibit characteristic membrane veils, as well as microvilli-rich regions that serve as preferred docking sites for T cells (Fisher et al., 2008). This complexity makes the interpretation of AFM measurements of cortical stiffness more challenging, as measuring stiffness on a protrusive veil may yield a different result than measuring stiffness directly over the cell body. Because these different structures cannot be resolved by light microscopy we were unable to test for regional stiffness differences (apart from avoiding the nucleus of the cell). Importantly, there were very few instances where measurement of stiffness at two different locations of the same cell resulted in significantly different values (data not shown). Going forward, it will be interesting to determine whether the area of the DC cortex directly underlying an interacting T cell has distinct stiffness properties, and whether this represents a feature of T cell docking sites, or a localized effect of T cell interaction on the DC cytoskeleton.

The observed increase in stiffness depends on changes in actin architecture; whereas depolymerization of actin filaments does not affect on the stiffness of immature DCs, the increase associated with maturation depends on intact filaments, and is sensitive to inhibitors of actin polymerizing molecules. While it remains to be determined exactly which actin regulatory pathways control cortical stiffness in mature DCs, our data show that both Arp2/3 complex and formins are involved. Moreover, we find that DCs lacking the Arp2/3 activator WASp are abnormally soft. In keeping with these findings, DC maturation is known to induce changes in the activation state and localization of Rho family GTPases, especially Cdc42, a molecule that can activate both WASp and formins (Garrett et al., 2000; Vargas et al., 2016; West et al., 2000). Since the overall levels of active Cdc42 are diminished during DC activation, it seems likely that the observed increase in cortical stiffness results from redistribution of the active pool.

We show that DC cortical stiffness is a cell-intrinsic property that is unaffected by substrate stiffness. In this respect, DCs are different from other cell types that adapt their stiffness to differences in substrate compliance (Byfield et al., 2009; Tee et al., 2011). The ability of DCs to maintain constant stiffness despite changing environmental cues is reminiscent of previous work showing that DCs rapidly change their method of locomotion to maintain consistent migration speed and shape while crossing over different surfaces (Renkawitz et al., 2009). This behavior has been proposed to allow DCs to pass through tissues with widely different mechanical properties. In the same way, we propose that the ability of DCs to regulate cortical stiffness as a function of maturation state in spite of environmental cues reflects the importance of this property for priming an appropriate T cell response.

A central finding of this study is that changes in DC stiffness serves as a costimulatory signal for T cell priming. By using a matrix of different hydrogels spanning the biologically relevant range defined for immature and mature DCs (2–8 kPa), coated with increasing pMHC concentrations, we found that stimulatory substrates with higher stiffness required lower concentrations of pMHC to achieve T cell activation. Similarly, when compared to WT DCs, softer WASp knockout DCs required higher concentrations of OVA peptide to induce the same level of proliferation. Our results indicate that increases in cortical stiffness, together with diminished ligand mobility (Comrie et al., 2015), represent biophysical cues that are modulated in parallel with upregulation of costimulatory ligands and cytokines as a fundamental part of DC maturation. When interacting T cells engage pMHC complexes and costimulatory ligands on the DC surface, they integrate this biophysical input along with other canonical costimulatory signals.

In addition to lowering the antigenic threshold for T cell activation, changes in stiffness may present a new signaling mechanism by which DCs control T cell fate and differentiation. Bufi et al., 2015 showed previously that human monocyte-derived DCs responding to different maturation signals vary in their stiffness. Interestingly, they found that treatment with the tolerizing cytokines TNFα and prostaglandin E2 results in DCs that are even softer than immature cells. Tolerogenic DCs exhibiting partially immature phenotypes have been shown to induce differentiation of regulatory T cells (Doan et al., 2009; Gleisner et al., 2011; Gordon et al., 2014). This effect is usually attributed to low expression of T cell ligands or cytokines, but based on our data, we propose that biophysical properties of the DC cortex also play a role. Going forward, it will be important to ask how DC stiffness is modulated in response to different environmental cues, and whether this further shapes T cell responses.

While we demonstrate T cell stiffness responses on soft surfaces emulating DCs, others have reported T cell stiffness responses on very stiff surfaces (Judokusumo et al., 2012; O'Connor et al., 2012). We found that very stiff substrates (25 kPa hydrogels and plastic surfaces in the GPa range) elicit strong responses. This was true for proliferation, IL-2 secretion and degranulation. Similarly, recent analysis of human CD4+ effector T cells shows that re-stimulation on soft surfaces induces upregulation of genes related to cytokine signaling and proliferation, while restimulation on very stiff surfaces (100 kPa) triggers expression of an additional genetic program that includes metabolic proteins related to glycolysis and respiratory electron transport (Saitakis et al., 2017). The physiological relevance of these augmented responses is unclear as T cells probably never encounter such stiff stimulatory surfaces in vivo. Nonetheless, such findings raise important questions about traditional in vitro assays of T cell function, which often utilize glass or plastic stimulatory surfaces.

The observation that T cells respond to APC stiffness is best understood in the context of evidence that T cells exert force on an interacting APC through the TCR complex (Bashour et al., 2014; Blumenthal and Burkhardt, 2020; Hui et al., 2015; Husson et al., 2011; Li et al., 2010; Sawicka et al., 2017), with the amount of force corresponding to APC stiffness (Husson et al., 2011; Sawicka et al., 2017). Apart from being a requirement for activation (Li et al., 2010; Pryshchep et al., 2014), force transduction has been shown to promote peptide discrimination by influencing bond lifetimes (Das et al., 2015; Liu et al., 2014). Importantly, it appears that the TCR’s ability to sense stiffness is closely related to its ability to transduce force-dependent signals during T cell-APC interaction. Indeed, there is evidence that signaling downstream of TCR engagement is increased on stiffer substrates (Alatoom et al., 2020; Judokusumo et al., 2012) and that the intracellular location of early tyrosine phosphorylation events corresponds to sites of maximum traction force (Bashour et al., 2014). We propose that stiffer substrates allow T cells to exert more force through TCR interactions, and consequently induce more effective signaling. This accounts for the costimulatory property of substrate stiffness on T cell activation.

The mechanism by which force application on the TCR is translated into biochemical signals remains controversial. Nevertheless, there is evidence to suggest that force applied on the TCR complex induces conformational changes within TCRαβ that exposes ITAM sites on the CD3 and TCRζ chains for phosphorylation and downstream signaling (Lee et al., 2015; Swamy et al., 2016) Importantly, conformational changes are mainly attributed to the extension of the CβFG loop region within TCRβ (Das et al., 2015), which serves as a lever to push down on the CD3 complex (Sun et al., 2001), exposing ITAM sites (Xu et al., 2008). In support of this idea, we found that the way in which the TCR is engaged influences T cell stiffness sensing. Within the biologically relevant stiffness range (2–8 kPa), T cells were activated only when TCRαβ was engaged directly; indirect engagement through anti-CD3 resulted in almost no response. We postulate that direct TCRαβ engagement leads to conformational changes that are transmitted appropriately for efficient initiation of downstream signaling, whereas engagement of CD3 induces smaller changes and more limited downstream signaling. This effect may be most evident on soft substrates, because force-dependent signaling is limiting in this setting. We note that on these soft substrates, pMHC induced stronger T cell activation than anti-TCRβ. This may reflect the involvement of CD4 in the former, which leads to more efficient recruitment of Lck to the TCR complex. One caveat to our work is that pMHC complexes are immobilized on the hydrogel surfaces used here, whereas pMHC complexes show relatively high lateral mobility in the DC membrane, even after maturation (Comrie et al., 2015). Future studies addressing how the biophysical properties of the DC surface contribute to tension on the TCR and receptor deformation will need to address the relationship between stiffness and mobility.

Although our focus here is on the role of stiffness sensing in priming of naïve T cells, we find that effector CD8+ T cells also exhibit stiffness-dependent degranulation; stiffness-dependent cytokine production by CTLs has also recently been reported (Tello-Lafoz et al., 2020). Similarly, Saitakis et al. have shown that restimulating CD4+ effector T cells on surfaces of different stiffness induces differential gene expression and cytokine production (Saitakis et al., 2017). Since DCs increase their cortical stiffness during maturation, a stiffness dependent mechanism for naïve T cell priming makes biological sense. Effector T cells, however, interact with a variety of APCs. In particular, cytotoxic CD8+ T cells are expected to kill any infected cell throughout the body with no stiffness bias. The physiological significance of stiffness sensitivity for effector T cells remains unclear. It is possible that mechanosensing is not needed for effector function per se, but that it is an obligate component of the feedback loop that underlies force-dependent TCR triggering.

The IS is often described as a platform for information exchange between the T cell and APC. Together with our recent work on ligand mobility, the findings presented here indicate that the mechanical properties of the APC side of the IS influence T cell priming, likely because they augment force-dependent conformational changes in TCRs, integrins, and potentially other molecules. Going forward, it will be important to determine how these properties are modulated during DC maturation, and whether there are also local changes induced by signaling events taking place at the IS. In addition, it will be important to tease apart the molecular events through which T cells sense and respond to these mechanical cues.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional
information
AntibodyAPC/APC-Cy7 anti-CD4 (rat, clone GK1.5)BiolegendBiolegend:100411/10041; RRID:100411/AB_312698Flow (1:350)
AntibodyAPC/PE-Cy7 anti-CD8a (rat, clone 53–6.7)BiolegendBiolegend: 00711/100721; RRID:AB_312750/AB_312760Flow (1:350)
Antibodyanti-CD3ε (A. hamster, clone 145–2 C11)BioXCellBioXcell: BE0001-1;
RRID:AB_1107634
0.003 µg/mL - 10 µg/mL
Antibodyanti-CD28 (Syrian hamster, clone PV1)BioXCellBioXcell:BE0015-5; RRID:AB_11076281 µg/mL - 2 µg/mL
AntibodyAnti-CD86 (rat, clone GL-1)BioXCellBioXcell: BE0025;
RRID:AB_1107678
Stain (1:100)
AntibodyAlexa647 anti-CD86 (rat, clone GL-1)BioLegendBioLegend: 105020; RRID:AB_493464Stain (1:100)
AntibodyAPC-Cy7 anti-CD86 (rat, clone GL-1)BioLegendBioLegend:105029; RRID:AB_2074993Flow (1:100)
AntibodyAnti I-A/I-E (rat, clone M5/114)BioXCellBioXcell:BE0108-5; RRID:AB_10949298Stain (10 µg/mL)
AntibodyPE anti- I-A/I-E (rat, clone M5/114.15.2)BioLegendBioLegend:107607; RRID:AB_313322Flow (1:100)
AntibodyAPC anti-CD11c (rat, clone N418)BioLegendBioLegend:117309; RRID:AB_313778Flow (1:100)
AntibodyPE-antiCD107a (LAMP-1)
(rat, clone 1D4B)
BioLegendBioLegend:121611; RRID:AB_1732051Assay (2 µg/mL)
AntibodyAlexa680 goat anti-Rat IgG (H+L)ThermoFisherThermoFisher: A-21096
RRID:AB_2535750
Stain (1:500)
Chemical compound, drugCytochalasin-DEMD MilliporeEMD Millipore: 250255; CAS:22144-77-010 µM
Chemical compound, drugLatrunculin-BEMD MilliporeEMD Millipore: 428020; CAS:76343-94-710 µM
Chemical compound, drug(S)-nitro-BlebbistatinCayman ChemicalCayman Chemical:13891; CAS:856925-75-250 µM
Chemical compound, drugCK666EMD MilliporeMillipore: 182515; CAS:442633-00-3100 µM
Chemical compound, drugY27632SIGMASIGMA:688000; CAS:146986-50-725 µM
Chemical compound, drugSMIFH2SIGMASIGMA:344092; CAS:340316-62-310 µM
Chemical compound, drugEscherichia coli 026:B6; LPSSIGMASIGMA:L2762;
ECN:297-473-0
200 ng/mL
Chemical compound, drugCollagenase DSIGMASIGMA: COLLD-RO; EC#:3.4.25.32 mg/mL
Chemical compound, drugIL-2NIAID, NIHN/A25U;100U
Chemical compound, drugstreptavidin-coated polystyrene beadsSpherotechSpherotech: SVP-60–5
Chemical compound, drugEZ-link NHS biotin kitThermo Fisher ScientificThermo Fisher Scientific: 21217
Chemical compound, drugCFSEInvitrogenInvitrogen: C34570
Commercial assay or kitCF555 Mix-n-StainBiotiumBiotium:92234
Commercial assay or kitMACS pan-dendritic cell isolation kitMiltenyi BiotecMiltenyi: 130-100-875
Commercial assay or kitmouse IL-2 ELISA kitInvitrogenInvitrogen: 88-7024-88
Gene (mouse)Was; Wiskott–Aldrich syndrome geneDOI:10.1084/jem.20091245MGI:105059;
NCBI Gene: 22376
OtherHydrogel surfaces (96-well plates)MatrigenEasyCoat Softwell 96GCustomized plates
OtherAFM 1 µM spherical polystyrene probeNovascanNovascan: PT.PSSi3N4 cantilever k = 0.06 N/m
Peptide, recombinant proteinPeptide MHC-II ComplexNIH Tetramer CoreI-AbSequence: HAAHAEINEA
Peptide, recombinant proteinOvalbumin 323–339; OVA323–339AnaspecAnaspec: AS-27025; LOT:1755317Sequence: ISQAVHAAHAEINEAGR
Recombinant DNA reagentpLX301 (plasmid)AddgeneAddgene: 25895;
RRID:Addgene_25895
DOI:10.1038/nmeth.1638
Software,
algorithm
FlowJoFlowJo LLCRRID:SCR_008520
Software, algorithmNanoScope AnalysisBrokerN/A
Strain, strain background (Mice)OT-II Transgenic mice/OT-IIJackson LaboratoriesStock: 004194; RRID:IMSR_JAX:004194B6.Cg-Tg(TcraTcrb)425Cbn/J
Strain, strain background (Mice)OT-I Transgenic mice/OT-IJackson LaboratoriesStock: 003831; RRID:IMSR_JAX:003831C57BL/6-Tg(TcraTcrb)1100Mjb/J
Strain, strain background (Mice)Was-/-; WASP-,WASp-KOJackson LaboratoriesStock: 003292;
RRID:IMSR_JAX:003292
129S6/SvEvTac-Wastm1Sbs/J
Strain, strain background (Mice)Hcls1-/-; HS1-KODavid Rawlings, MD.PMCID:PMC394441
Strain, strain background (Mice)Fscn1-/-KOMP Repository, UC DavisMGI:5605764Fscn1tm1.1(KOMP) Vlcg

Inhibitors and antibodies

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Cytochalasin-D and latrunculin-B were obtained from EMD Millipore, (S)-nitro-Blebbistatin was purchased from Cayman Chemical, CK666 was from Calbiochem, and Y27632 and SMIFH2 were from Sigma-Aldrich. Flow cytometry antibodies: rat anti-CD4 APC/APC-Cy7 (clone RM4-5), rat anti-CD8a APC/PE-Cy7 (clone 53–6.7), Armenian hamster anti-CD69 APC (clone H1.2F3) and rat anti-CD25 PE (clone PC61) were all purchased from BioLegend. Surface coating antibodies: Armenian hamster anti-CD3ε (clone 2C11) and Armenian hamster anti-CD28 (Clone PV1) were from BioXCell. Biotinylated Armenian hamster anti-CD3ε (clone 2C11) was from Invitrogen, and biotinylated mouse anti-TCRVβ5.1/5.2 (clone MR9-4) was from BD Bioscience. Dendritic cell staining: anti-CD86 CF555 was made by conjugating purified rat anti-CD86 (BioXCell) with CF555 conjugated dye from Biotium as per the manufacturer’s protocol.

Mice

All mice were originally obtained from The Jackson Laboratory and housed in the Children’s Hospital of Philadelphia animal facility, according to the guidelines put forth by the Institutional Animal Care and Use Committee. C57BL/6 mice (WT) were purchased from Jackson Labs. HS1-KO mice on the C57BL/6 background have been previously described (Taniuchi et al., 1995) and were a kind gift from Dr. David Rawlings at the University of Washington. Was-/- mice were purchased from Jackson Labs (Snapper et al., 1998) and fully backcrossed to a C57BL/6 background. All mouse strains were used as a source of bone marrow from which to generate BMDCs. Mice bearing a gene trap mutation in the Fscn1 gene (Fscn1tm1(KOMP)Vlcg), which abrogates the expression of the protein Fascin 1, were generated by the KOMP Repository at UC Davis, using C57BL/6 embryonic stem cells generated by the Texas A & M Institute for Genomic Medicine. Because these mice proved to have an embryonic lethal phenotype, fetal liver chimeras were used as a source of bone marrow precursors. Heterozygous mating was performed, and fetal livers were collected after 15 days of gestation and processed into a single-cell suspension by mashing through a 35 μm filter. Embryos were genotyped at the time of harvest. Cells were resuspended in freezing media (90% FCS, 10% DMSO) and kept at −80°C until used. Thawed cells were washed, counted, resuspended in sterile PBS and injected intravenous into sub-lethally irradiated 6-week-old C57BL/6 recipients, 1 × 106 cells per mouse. Chimeras were used as a source for fascin KO bone marrow ∼6 weeks after transfer. OT-I T cells were prepared from heterozygous OT-I TCR Tg mice, which express a TCR specific for ovalbumin 257–264 (amino acid sequence SIINFEKL) presented on H-2Kb (Hogquist et al., 1994). OT-II T cells were prepared from heterozygous OT-II TCR Tg mice, which express a TCR specific for ovalbumin 323–339 (amino acid sequence ISQAVHAAHAEINEAGR) presented on I-Ab (Barnden et al., 1998).

Cell culture

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Unless otherwise specified, all tissue culture reagents were from Invitrogen/Life Technologies. GM-CSF was produced from the B78H1/GMCSF.1 cell line (Levitsky et al., 1996). HEK-293T cells (ATCC) were cultured in DMEM supplemented with 10% FBS, 25 mM Hepes, penicillin/streptomycin, GlutaMAX, and non-essential amino acids.

Generation of bone marrow-derived dendritic cells (BMDCs) was similar to Inaba et al., 1992. Briefly, mouse long bones were flushed with cold PBS, the resulting cell solution was passed through a 40 µm strainer, and red blood cells were lysed by ACK lysis. Cells were washed once with RPMI-1640 and then either frozen for later use in RPMI-1640 containing 20% FBS, 10% DMSO, or plated in 10 cm bacterial plates in BMDC culture media (RPMI-1640, 10% FBS, penicillin/streptomycin, GlutaMax and 1% GM-CSF supernatant). On day 3 of culture, dishes were supplemented with 10 mL of BMDC culture media. On day 6, 10 mL of media were replaced, by carefully collecting media from the top of the dish and slowly adding fresh media. BMDC differentiation was verified using flow cytometry, showing 80–90% CD11c positive cells. BMDC maturation was induced on day 7 or 8; immature BMDCs were harvested and replated on a 6 cm tissue culture dish in 5 mL of BMDC media supplemented with 200 ng/mL lipopolysaccharide (Escherichia coli 026:B6; Sigma-Aldrich) for at least 24 hr. Maturation was verified using flow cytometry, with mature BMDCs defined as Live/CD11c+/CD86high/MHC-IIHigh cells. To generate splenic DCs, spleens from C57BL/6 mice were cut into smaller pieces and digested with collagenase D (2 mg/mL, Sigma) for 30 min at 37°C, 5% CO2. Cells were washed and labeled for separation by negative selection using a MACS pan-dendritic cell isolation kit (Miltenyi Biotec).

Primary mouse T cells were purified from lymph nodes and spleens using MACS negative selection T cell isolation kits (Miltenyi Biotec). In the case of CD4+ T cells, ex vivo cells were used. Since isolation yielded mostly naïve cells (>90%, data not shown), we refer to them as naïve CD4+ T cells. In the case of CD8+ T cells, approx. 45% of T cells isolated from OT-I mice showed some level of activation. Thus, we specifically isolated naïve T cells by MACS purification. To generate cytotoxic CD8+ T cells (CTLs), purified murine CD8+ cells were activated on 24-well plates coated with anti-CD3ε and anti-CD28 (2C11 and PV1, 10 μg/mL and 2 µg/mL, respectively) at 1 × 106 cells per well. After 24 hr, cells were removed from activation and mixed at a 1:1 vol ratio with complete T cell media (DMEM supplemented with penicillin/streptomycin, 10% FBS, 55 μM β-mercaptoethanol GlutaMAX, and non-essential amino acids), containing recombinant IL-2 (obtained through the NIH AIDS Reagent Program, Division of AIDS, NIAID, NIH from Dr. Maurice Gately, Hoffmann - La Roche Inc [Lahm and Stein, 1985]), to give a final IL-2 concentration of 100 units/mL. Cells were cultured at 37°C and 10% CO2, and passaged as needed to be kept at 0.8 × 106 cells/mL for 7 more days. CTLs were used at day 8 or 9 after activation.

Plasmid construction, viral production, and transduction of DCs

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A constitutively active form of WASp (CA-WASp) was engineered by subcloning WASp cDNA into a pLX301 vector (Addgene), introducing an I294T point mutation (Westerberg et al., 2010) by site-directed mutagenesis, and confirming by sequencing. To generate recombinant lentivirus, HEK-293T cells were co-transfected using the calcium phosphate method with psPAX2 and pMD2.G, together with the DNA of interest in pLX301. For transduction, BMDCs were plated in untreated six well plates at 2 × 106 cells/well in 3 mL of BMDC media. BMDC transduction was carried out on day 2 of culture; lentiviral supernatants were harvested from HEK-293T cells 40 hr post transfection, supplemented with 8 µg/mL polybrene (Sigma-Aldrich), and used immediately to transduce BMDCs by spin-infection at 1000×g, 37°C for 2 hr. After resting the cells for 30 min at 37°C, 5% CO2, lentivirus-containing media was replaced with normal BMDC culture media. On day 5 of culture, puromycin (Sigma-Aldrich) was added to a final concentration of 2 μg/mL to allow selection of transduced BMDCs. Maturation of transduced cells was induced on day 8 by adding 200 ng/mL of lipopolysaccharide in puromycin-free media.

Flow cytometry

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All cells were stained with Live/Dead aqua (ThermoFisher) following labeling with appropriate antibodies in FACS buffer (PBS, 5% FBS, 0.02% NaN3, and 1 mM EDTA). Flow cytometry was performed using either the Cytoflex LX or CytoFlex S cytometer (Beckman Coulter) and analyzed using FlowJo software (FlowJo LLC). T cells were gated based on size, live cells, and expression of CD4 or CD8 (depending on the experiment). DCs were incubated for 10 min on ice with the Fc blocking antibody 2.4G2 before staining. DCs were gated based on size, live cells, and CD11c expression. Mature DCs were further gated based on high expression of MHC-II, CD86, or CD80.

T cell activation on stimulatory gel surfaces

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96-well plates coated with polyacrylamide hydrogels spanning a stiffness range of 2–25 kPa were obtained from Matrigen. Hydrogel stiffness was verified by AFM at different locations around the hydrogel surface (Figure 3—figure supplement 1). Surfaces were first coated with 10 µg/mL of NeutrAvidin (ThermoFisher) and 2 µg/mL anti-CD28 (clone PV1) overnight at 4°C. Primary amines in the NeutrAvidin form covalent bonds with quinone functional groups within the hydrogels. The gel pore size is on the order of tens of nanometers, such that cells can only interact with ligands bound on the gel surface. Surfaces were then washed twice with 200 µL of PBS and coated with varying concentrations of biotinylated pMHC monomers (NIH tetramer core facility) for 2 hr at 37°C. In cases where antibody stimulation was compared to pMHC stimulation, surfaces were coated with varying concentrations of either biotinylated anti-CD3ε (clone 2C11), or biotinylated anti-TCRvβ5.1/5.2 (clone MR9-4). In experiments where only antibody stimulation was used, surfaces were coated directly with varying concentrations of anti-CD3ε (clone 2C11) together with 2 µg/mL anti-CD28 (clone PV1) for 2 hr at 37°C. Following coating, surfaces were washed two times with 200 µL of PBS, and blocked for 10 min with T cell media containing 10% FBS before addition of 2.0 × 105 cells/well. Control studies showed that stimulatory ligands bound slightly less well to stiffer hydrogel surfaces (Figure 3—figure supplement 2). Stiffer surfaces show the same or higher activating properties across all assays, ruling out the possibility that differences in T cell activation are due to differential ligand binding. Importantly, initial experiments included a 1 kPa hydrogel surface that yielded no response across all assays. Therefore, data from this condition is not shown and was not included in repeated experiments. For experiments where exogenous IL-2 was added, media was supplemented with IL-2 to a final concentration of 25 U/mL. For measurements of CD69/CD25 expression and IL-2 production, cells were harvested 22–24 hr post stimulation for flow cytometry, and supernatants were used to measure IL-2 concentration using a mouse IL-2 ELISA kit (Invitrogen). For early activation marker expression assays, cells were plated immediately after isolation, and harvested 22–24 hr post stimulation for flow cytometry analysis. For CFSE dilution assays, purified cells were washed once with PBS and stained for 3 min with 2.5 µM CFSE (ThermoFisher). After quenching the excess CFSE by addition of 1 mL FBS for 30 s, cells were washed and plated. Cells were harvested 44–48 hr (CD8+ T cells) or 68–72 hr (CD4+ T cells) post stimulation for flow cytometry analysis. For ligand comparison assays, surfaces were first coated with 10 µg/mL of NeutrAvidin (Thermo Fisher) and 2 µg/mL anti-CD28 (PV1) overnight at 4°C. Surfaces were then washed twice with 200 µL of PBS and coated with varying concentrations of biotinylated ligands (anti-TCRVβ5.1/5.2, anti-CD3ε, or pMHC-II monomers) for 2 hr at 37°C.

Cytotoxic T cell degranulation assays

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Assays were conducted on day 8 or 9 of culture. About 2 × 105 CTLs were plated onto surfaces coated with various concentrations of pMHC-I in the presence of 2 µg/mL PE-conjugated anti-CD107a. After 3 hr of re-stimulation, CD107a labeling was quantified using flow cytometry . Cells were gated based on size, live cells, and expression of CD8+. CD107a mean fluorescence intensity (MFI) was extracted using FlowJo.

Hydrogel ligand-binding assays

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Hydrogel surfaces were coated with 1 µg/mL pMHC-II monomers as described earlier. Hydrogel wells were washed thrice with 200 µL of PBS and blocked for 1 hr with 0.25% bovine gelatin in PBS solution. After blocking, pMHC-II molecules were stained with 10 µg/mL rat anti-mouse I-A/I-E antibody (Clone M5/114) in 0.25% bovine gelatin in PBS solution for 1 hr at room temperature. Wells were than washed thrice and stained with Alexa 680 conjugated goat anti-rat secondary antibody diluted 1:500 in 0.25% bovine gelatin in PBS solution for 1 hr at room temperature. Finally, wells were washed and imaged using a Licor Odyssey CLx reader.

T cell priming assays

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Priming assays were carried out in round bottom 96-well plates. About 5 × 104 LPS-matured BMDCs were plated in each well and pulsed with OVA323–339 peptide at various concentrations (0.1–1 µg/mL). 1.5 × 105 CFSE stained, OT-II CD4+ T cells were added to each well and incubated for 68–72 hr. Cells were then harvested and analyzed using flow cytometry.

Atomic force microscopy

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All experiments were carried out at room temperature using a Bruker Bioscope Catalyst AFM mounted on a Nikon TE200 inverted microscope. Microindentation measurements were made with a spherical tip from Novascan. The tip was comprised of a 1 µm silicon dioxide particle mounted on a silicon nitride cantilever with a nominal spring constant of 0.06 N/m; each cantilever was calibrated using the thermal fluctuation method. The AFM was operated in fluid contact mode, with 2 Hz acquisition. Total vertical cantilever displacement was set to 5 µm, producing a maximal approach/retraction speed of ~20 µm/s. Maximal deflection (Trigger threshold) was adjusted for each cantilever to apply a maximal force of 6 nN on the measured cell (e.g. for a 0.06 N/m cantilever, the trigger threshold was set to 100 nm). The actual indentation depth was ~1.5 µm depending on the measured cell stiffness (Figure 1—figure supplement 4A, B). Analysis of force-distance curves was carried out using the Nanoscope Analysis software (Bruker). The Young’s modulus was extracted using the Hertzian model for spherical tips with a contact point-based fitting on the extend curve data. Importantly, one of the Hertzian model requirements is that indentation depth does not exceed the radius of the spherical tip. Since the Bruker software we use does not allow one to restrict the fitting algorithm based on Z axis displacement, we were unable to restrict fitting to exactly 0.5 µm. Instead, we restricted the Hertzian model fitting to 30% of total force applied, which we found corresponds to ~0.5 µm indentation depth (Figure 1—figure supplement 4C). For each individual cell, two separate measurements were conducted at different locations near but not directly over the nucleus. The reported cell stiffness value represents the average between these independent measurements. Note that when measurements of cortical stiffness were made over the nucleus, no significant differences in Young’s modulus values were found (not shown). To measure BMDC stiffness, 1 × 105 cells (untreated or lipopolysaccharide matured) were seeded onto poly L-lysine coated coverslips and allowed to spread for 4 hr at 37°C, 5% CO2. Before data acquisition, cells were incubated for 10 min with the Fc blocking antibody 2.4G2, washed and stained for CD86 for 20 min, then washed and mounted on the AFM. All antibody incubations and data acquisition steps were performed in L-15 media (Gibco) supplemented with 2 mg/mL glucose. For treated cell measurements, drugs [latrunculin-B (10 µM), cytochalasin-D (10 µM), s-nitro-blebbistatin (50 µM), Y27632 (25 µM), CK666 (100 µM), or SMIFH2 (10 µM)] were pre-incubated with the cells at 37°C, 5% CO2 for 30 min before Fc blocking and maintained in the cultures throughout staining and data acquisition. Measured cells were visually selected based on fluorescence; immature/mature cells were distinguished based on CD86 staining. In experiments where the GFP-CA-WASp construct was expressed, GFP positive cells were selected in conjunction with CD86 staining using a dual-band fluorescence filter set.

Dendritic cell imaging

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About 1 × 105 DCs (untreated or lipopolysaccharide matured) either from WT or GFP-Lifeact Tg mice were seeded onto poly L-lysine coated hydrogels or glass coverslips and allowed to spread for 4 hr at 37°C, 5% CO2. Before imaging, cells were incubated for 10 min with the Fc blocking antibody 2.4G2, washed and stained with Alexa647 conjugated anti-CD86 (Clone GL-1) for 20 min, then washed and mounted on the microscope. Antibody incubations and data acquisition steps were performed in L-15 media (Gibco) supplemented with 2 mg/mL glucose. Imaging DCs on hydrogels was done using a 40X, long working distance objective through the hydrogels.

Statistical methods

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All datasets were subjected to outlier analysis before execution of statistical testing. Outliers were defined as data points with values outside the range of mean +/- 2.5 xStDev and were deleted from the dataset. Testing for a statistically significant difference between experimental groups was done using an unpaired one-way ANOVA test with a post-hoc Tukey correction for multiple comparisons.

Throughout the paper, data shown represents biological, and not technical, replicates. For BMDC assays, a single experiment constitutes measurement of multiple cells from a fresh DC culture, starting from frozen or freshly harvested bone marrow. For splenic DCs, a single experiment constitutes measurement of multiple cells freshly purified from the spleen of a single mouse. In each experiment, WT or untreated cells were measured side by side with treated cells as a standard control. For T cell assays, a single experiment constitutes cells freshly purified from spleen and lymph nodes of a single animal. All CFSE dilution assays were executed in technical duplicates, although a single data set is presented. When needed, figure legends describe the quantity of technical repeats used in an experiment.

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Decision letter

  1. Anna Akhmanova
    Senior Editor; Utrecht University, Netherlands
  2. Michael L Dustin
    Reviewing Editor; University of Oxford, United Kingdom
  3. Claire Hivroz
    Reviewer; Institut Curie, France
  4. Morgan Huse
    Reviewer; Memorial Sloan Kettering Cancer Center, USA

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Your carefully conducted study is particularly interesting since it represents a coherent and complete analysis of the response (expression of activation markers, IL-2 production and proliferation) of mouse T cells to stiffness. It also demonstrates that the program of maturation of DC includes changing in their mechanical properties that is most probably involved in their ability to activate T lymphocytes. Your work also open new fields of investigation for example: what are the mechanisms involved in the modification of the DC cytoskeleton leading to changes in their stiffness? What are the molecular mechanisms, which explain the difference of sensitivity to stiffness between CD4 and CD8 T cells?

Decision letter after peer review:

Thank you for submitting your article "T-cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex" for consideration by eLife. Your article has been reviewed by three peer reviewers, including Michael L Dustin as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by a Reviewing Editor and Michel Nussenzweig as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Claire Hivroz (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

This is an informative study that addresses an important topic related to the stiffness of dendritic cells and response to T cells to stimuli provided on artificial surfaces with bulk stiffness in this range. This is an important area in immunology and biophysics. Key findings include that DC increase in stiffness during maturation and the stiffness is nearly 5-fold greater than the previous best measurements. T cells respond better to anti-CD3 antibodies presented on gels of similar stillness to mature DC than to stiffness of immature DC. Response to anti-CD28 is not sensitive to stiffness. Peripheral blood T cells are not sensitive in this range of stiffness. DC don't become stiffer on a stiffer substrate like other cells, which makes it hard to experimentally manipulate their stiffness. WASp contributes to DC stiffness and WASp deficient DC are less stimulatory. However, stiffer active WASp expressing DC do not stimulate T cells better. There are strengths and weaknesses to this study. The most important major issues are addressed below.

Essential revisions:

1) AFM measurements – Earlier measurements from Bufi et al., 2015 showed the same trend as here, but lower values. P.-H. Wu et al., 2018 shows that AFM probes of different dimensions generate different stiffness values with smaller probes giving higher values of Young's modulus. Since Bufi et al., used an infinitely large probe (a flat paddle) and this study used a 1 µm bead as the probe that larger value measured here may be a consequence of this and this should be discussed. The gels that are used for the T cell activation experiments are commercial and their stiffness is presumably specified by the supplier. The authors should measure the stiffness of these gels under the same conditions as the cells and determine the measured stiffness, which will ensure that the gels truly replicate the cellular stiffness. There are also some details of the measurements that should be better described. The indentation length cannot be of 5 μm since this is more the tip size (1 μm bead)…I think this is probably the range of vertical displacement of the cantilever, the motion of the cantilever being stopped when the force it is facing reaches 6 nN. As far as I understand, this indicates a cantilever deflection of 0.1 μm (100 nm), but does not say anything about the indentation depth in the cell, and this is important information to evaluate to what extent it is possible to claim that the authors have only probed the cortex of the cells. Finally, the authors should also explain the meaning of the 2 Hz acquistion frequency. Contact mode measurements are not supposed to be sine waves. So, I think this is the frequency at which measurements were repeated. It would be better to indicate the approach/retraction rate, i.e. a speed in μm/s. This parameter has indeed an important impact on the measured stiffness value. The authors should also provide information about where on the cell they were indenting and if the location mattered?

2) The experiments to manipulate DC stiffness are important to the impact of the paper beyond earlier work. It’s interesting that mature DC lacking WASp are both softer and less potent in T cell stimulation, but there may be many other explanations for this. The disappointing result that CA-WASp didn't further increase T cell responses might reflect saturation of the response to stiffness. Can the authors express CA-WASp in immature or semi-mature DC, stiffen them and record stronger T cell responses. It seems essential to be able to measure some surface parameters in these experiments – most importantly – the pMHC density. This can be accomplished with available antibodies to the SIINFEKL-Kb complex – so it might be appropriate to use OTI in this study to allow us of this reagent – which I think may be the only one for the OVA system. Since anti-CD28 costimulatory signals can be presented from solution and are not sensitive to stiffness anyway (which was published in Judokusumo et al., 2012), it should be possible to match pMHC with immature DC without and with CA-WASp and soluble anti-CD28 costim to determine if T cell respond better to stiffer immature DC generated with CA-WASp (assuming this is true). Along these lines, it was surprising that the DC didn't at all take on the stiffness of the substrate. This may be due to poor DC adhesion, particularly for mature DC. Can the author confirm that the DC can spread on the hydrogels and if not, can the authors add attachment factors or molecules like podoplanin to be able to enhance spreading and establish a link between the substrate and cortical stiffness for DC? This might be a good alternative approach if the first approach fails. Of course, the author can solve this problem in other ways, but it would much more convincing to make DC better by making them stiffer than to make them worse by removing WASp, which may also affect protrusion dynamics and change many things.

3) The result that peripheral blood cells from mouse and human are not sensitive to the substrate stiffness is interesting, but not very well documented. In several instances the authors simply show signal dye dilution profiles as the only results to make a point. For all results, the authors must provide quantification for multiple experiments (mouse) or donors (human). This also applies to results in Figure 6. When there is quantification, the authors simply use percent cell division as a method to quantify the dye dilution experiments, but this throws out a lot of information and it would be better to use a proliferation index algorithm that take into account all the data through fitting the number of cells in each division number. Hopefully this data is all available and just needs to be presented with greater rigor. The other issue is that earlier studies that showed stiffness sensitivity of human peripheral blood T cells use much stiffer PDMS elastomers so perhaps peripheral blood cells are sensitive to greater stiffnesses, perhaps related to coping with conditions in circulation. I don't feel the author need to address this last point, but they just need to acknowledge the limitations of their measurements.

[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the second round of review.]

Thank you for submitting your work entitled "Mouse T-cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex" for consideration by eLife. Your article has been reviewed by a Senior Editor, a Reviewing Editor, and two reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Claire Hivroz (Reviewer #3).

Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife.

The reviewers and reviewing editor appreciate your ability to provide the AFM measurements on the hydrogels and the details of the indentation depth at which the DC measurements were made. These additions improve the paper. However, there are concerns about both the reliability of the commercial hydrogels and the lack of correlation between DC stiffness and T cell response in the data series manipulating WASp and other actin regulators/inhibitors. The reproducibility of the materials is a significant issue, and while it is out of your control to some extent, the possibility exists that the initial results were the outliers and the new results with the present generation of commercial gels are a better reflection the actual ability to T cells to resolve these differences in substrate stiffness. You also state that you have performed a range of manipulations to try to alter DC stiffness and have only obtained the desired correlation with WASp-KO in mature DC. This, along with the data you present in the revision, seems like a multiple testing problem that could invalidate the significance of the WASp-KO effect. But even if this is not the case, the problem still exists that details of what each manipulation does to antigen presentation by DC seems to dominate the effects of stiffness. If you can take all the efforts to manipulate DC cytoskeleton and plot stiffness against T cell response to achieve a correlation, then this would suggest an effect that cuts across the particular molecular details. But given that this doesn't seem to be the case, the WASp-KO effect in mature DC may also be an outlier that fits the model, but there are equal numbers of results that contradict the conclusion in an unbiased inspection of all the data. We greatly appreciate your sharing the information with us very openly. Unfortunately, the conclusions are not well enough supported for publication in eLife at this time.

Reviewer #2:

This revised manuscript substantially addresses the critiques of the initial report. The details on rigidity measurement and interpretation are important and have been addressed. I also applaud the efforts taken to understand and resolve issues regarding the Matrigen substrates. It is unfortunate that the associated experiments were not able to be carried out, but as noted by the authors those were not the main impact of this report. I support acceptance of this manuscript for publication.

Reviewer #3:

In their revised manuscript Daniel Blumenthal and co-workers have answered some of the essential revisions required by the reviewers. In particular, they really explain more thoroughly the methods used to measure the stiffness of the cells. They also present the data with more rigor.

Concerning the point raised by the reviewers on the fact that the lack of efficiency of WASp deficient dendritic cells to activate T cells can be related to something else that the viscoelastic properties, the authors have been more cautious in the text. Yet, they did not investigate if the phenotype of DC is modified at least for the main actors of Ag presentation MHC class II expression, CD28-ligands expression, ability of the cells to present peptide versus processed Ag (OVA). Thus, it is very difficult to draw any conclusion from results presented in Figure 6. are less efficient than wild type dendritic cells to activate T cells. Moreover, the overexpression of WASp in the DC, although increasing the Young modulus of T cells, decreased the ability of DC to activate T cells. This shows that the interpretation of the results on WASp-KO cells just in term of stiffness is not correct.

Another point raised by the reviewers was that it was surprising that the dendritic cells did not take on the stiffness of substrate. It is indeed very different from other adherent cells. Although the authors state in their new manuscript that DC spread and attach to the PLL coated gels it would be important to show these data and document qualitatively and quantitatively this point in the different conditions used.

One of the points was also to document better the results obtained on peripheral T cells. Yet, because it was not possible to perform new experiments with gels of different stiffness due to problem of production of the gels by the manufacturer, some of the experiments asked by the reviewers could not be performed. In their new manuscript, the authors thus took out all the experiments performed on the peripheral T cells showing that peripheral T cells and T cells from tissues do not behave the same. As a result, some of the original aspects of the previous manuscript are not present anymore.

In conclusion, in its present form, although the experiments presented in the revised manuscript are well performed, they add too little to the understanding of the modifications of the viscoelastic properties of DC and mainly present data that have already been published in other models. I thus think that the manuscript does not full fill the requirement to be published in eLife.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "T cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Anna Akhmanova as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Claire Hivroz (Reviewer #1); Morgan Huse (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Your study addresses the question of the mechanosensitivity of mouse T lymphocytes, in particular their sensitivity to stiffness.

You perform AFM on mouse dendritic cells (BMDC and ex vivo splenic DC) and measure the Young's modulus of the cortex of immature and LPS-matured DC and show that mature DC have an increased stiffness. You show that increasing stiffness (in the range measured for mature DC) increases the sensitivity of mouse CD4 more than of mouse CD8 T lymphocytes to low concentration of agonist peptide-MHC complexes. Exploring the role of the actin cytoskeleton in the stiffness of mature DC, they show that the Arp2/3 complex, the formins and WASp are involved. Finally, you show that DC from WASp-KO mice are less efficient than WT DC for T cell priming.

Your study is performed with care and is particularly interesting since it represents a coherent and rather complete analysis of the response of mouse T cells to stiffness: CD4 and CD8 T cells, activation with peptide-MHC complex with a careful assessment of T cell responses including measurement of CD69 and CD25, plus IL-2 secretion and cell division.

Essential revisions:

1) Interpretation of AFM-based data of Young's modulus needs to be developed more. Indentation depths appear to be in the range of several micrometers for the cells, which is on the order of cellular structures. The Hertzian model assumes a homogenous Young's modulus for several multiples of the indentation depth. Such distances include cell cytoplasm and may also reflect the rigidity of the underlying substrate. Figure 1D provides some evidence that this is not the case, but given the overall small impacts on measured modulus and comparatively soft nature of the dendritic cells, it is still possible that flattening of the cells upon maturation contributes to the changes in calculated modulus. Reanalysis of the force-indentation curves over lower ranges of indentation would help address this issue.

2) It would also be helpful for you to report on the adhesion of the DC on different rigidity substrates as DC are not typically highly adherent cells, but you are using a unique substrate so this is uncharted territory. Degree of adhesion and cell height above the substrate under all relevant conditions would be important data that could be conveyed in a table.

3) As only one TCR-pMHC combination is studies for CD4 and CD8 T cells, it’s possible that the different response might be a function of the potency of the pMHC, rather than a difference between CD4 and CD8 T cells. Do you have data comparing naive CD4 and CD8 T cells with otherwise identical anti-CD3 substrates? This might still provide the best comparison as supplemental data, although less physiological than the pMHC data.

4) You could discuss the potential impact of differences in lateral mobility of pMHC on the hydrogels vs DC.

[Editors’ note: further revisions were suggested prior to acceptance, as described below.]

Thank you for submitting your article "Mouse T cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Anna Akhmanova as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Claire Hivroz (Reviewer #1); Morgan Huse (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

Your carefully conducted study is particularly interesting since it represents a coherent and complete analysis of the response (expression of activation markers, IL-2 production and proliferation) of mouse T cells to stiffness. It also demonstrates that the program of maturation of DC includes changing in their mechanical properties that is most probably involved in their ability to activate T lymphocytes. Your work also open new fields of investigation for example: what are the mechanisms involved in the modification of the DC cytoskeleton leading to changes in their stiffness? What are the molecular mechanisms, which explain the difference of sensitivity to stiffness between CD4 and CD8 T cells?

However, there were still some concerns about the discussion of the AFM results. No additional experiments are suggested, the reviewers concurred that the second paragraph of the Discussion section (discussing different methods of measuring Young's modulus) would be a natural place for raising these issues. You should discuss further how cortex, nucleus, invaginations and projections at the DC surface can affect the AFM measurements. In this paragraph, the authors may also comment on the limits of the technique on cells such as DC that are known for their complex surface topology.

https://doi.org/10.7554/eLife.55995.sa1

Author response

Essential revisions:

1) AFM measurements – Earlier measurements from Bufi et al., 2015 showed the same trend as here, but lower values. P.-H. Wu et al., 2018. shows that AFM probes of different dimensions generate different stiffness values with smaller probes giving higher values of Young's modulus. Since Bufi et al., used an infinitely large probe (a flat paddle) and this study used a 1 µm bead as the probe that larger value measured here may be a consequence of this and this should be discussed.

We agree with the reviewer – it is well known that differences in technical approach (AFM probes, whole cell rheology, etc.) can yield significant differences in absolute Young’s Modulus values. This study has now been cited, and the basis for the difference in absolute measurements has been addressed in the Discussion section.

The gels that are used for the T cell activation experiments are commercial and their stiffness is presumably specified by the supplier. The authors should measure the stiffness of these gels under the same conditions as the cells and determine the measured stiffness, which will ensure that the gels truly replicate the cellular stiffness.

We absolutely agree and we had done this from the outset but had not presented the data. These measurements are now shown in the new Figure 1—figure supplement 1 and Figure 2—figure supplement 1.

There are also some details of the measurements that should be better described. The indentation length cannot be of 5 μm since this is more the tip size (1 μm bead)…I think this is probably the range of vertical displacement of the cantilever, the motion of the cantilever being stopped when the force it is facing reaches 6 nN. As far as I understand, this indicates a cantilever deflection of 0.1 μm (100 nm), but does not say anything about the indentation depth in the cell, and this is important information to evaluate to what extent it is possible to claim that the authors have only probed the cortex of the cells. Finally, the authors should also explain the meaning of the 2 Hz acquistion frequency. Contact mode measurements are not supposed to be sine waves. So, I think this is the frequency at which measurements were repeated. It would be better to indicate the approach/retraction rate, i.e. a speed in μm/s. This parameter has indeed an important impact on the measured stiffness value. The authors should also provide information about where on the cell they were indenting and if the location mattered?

We apologize if this was not clear. The reviewer is correct – 5μm refers to the total z-displacement of the AFM cantilever, which is stopped when the force reaches 6nN. We have expanded the explanation of AFM measurements in the Materials and methods section and have included information on the approach/retraction speed, and where in the cell measurements were made (near, but not over the nucleus). These details are also stressed in the Results section. The actual indentation length (roughly 1.5 μm) was quantified in representative experiments and is now shown in the new Figure 1—figure supplement 2.

2) The experiments to manipulate DC stiffness are important to the impact of the paper beyond earlier work. It’s interesting that mature DC lacking WASp are both softer and less potent in T cell stimulation, but there may be many other explanations for this. The disappointing result that CA-WASp didn't further increase T cell responses might reflect saturation of the response to stiffness.

We agree that the decrease in stiffness and potency of WASp-KO DCs could have other explanations, and so took care not to overinterpret this result. With respect to mature DCs expressing CA-WASp, our data using the hydrogel system clearly show that the T cell stiffness response is not saturated. However, the relatively subtle increase in stiffness that we observe in mature DCs transduced with CA-WASp (approx. 4 kPa to approx. 5 kPa) is not great enough to result in an increased T cell response. We included a figure (now Figure 6—figure supplement 1) to make this comparison clearer to the reader.

Can the authors express CA-WASp in immature or semi-mature DC, stiffen them and record stronger T cell responses. It seems essential to be able to measure some surface parameters in these experiments – most importantly – the pMHC density. This can be accomplished with available antibodies to the SIINFEKL-Kb complex – so it might be appropriate to use OTI in this study to allow us of this reagent – which I think may be the only one for the OVA system. Since anti-CD28 costimulatory signals can be presented from solution and are not sensitive to stiffness anyway (which was published in Judokusumo et al., 2012), it should be possible to match pMHC with immature DC without and with CA-WASp and soluble anti-CD28 costim to determine if T cell respond better to stiffer immature DC generated with CA-WASp (assuming this is true).

This is a very interesting and constructive suggestion. We had already tried several approaches to modifying DC stiffness. In addition to the HS1 and fascin knockouts shown in the paper, we tried FMNL1/m-Dia-1 double knockouts, transduction with constitutively active and dominant negative RhoA, and overexpression of L-plastin and T-plastin, as well as several other pharmacological strategies. None of these approaches had a significant effect on stiffness of mature DCs as measured by AFM. In response to the reviewer’s promising suggestion, we attempted to modulate the stiffness of immature DCs. We transduced BM precursors with CA-WASp or a control, selected transduced cells without lipopolysaccharide stimulation, and analyzed T cell priming using the OTII system. As shown below, T cell priming was actually diminished by CA-WASp expression, even when CD28 costimulation was provided in trans. AFM analysis of the transduced cells revealed that when immature DCs are made to express CA-WASp, there is no significant increase in cortical stiffness. This is likely because WASp plays a very different role in immature vs mature DCs. In immature DCs, it is primarily deployed to the ventral surface, where it is essential for the formation of podosomes. In keeping with this, we showed in Figure 2 that depolymerization of F-actin has no impact on the stiffness of immature DCs. These new data suggest that even if you force expression of active WASp in these cells, it has little or no impact on the properties of the cell cortex. We agree with the reviewer that if the forced expression of CA-WASp had, as hoped, increased stiffness and T cell priming, we would have needed to normalize for expression of pMHC and costimulatory ligands. However, under the circumstances, there was little point in pursuing those controls. Based on this analysis, we do not think that the cortical cytoskeleton in immature DCs can be manipulated in interpretable ways, even if one compensates for other features of maturation. The data on CA-WASp-transduced immature DCs is shown in Author response image 1. We opted not to incorporate it into the revised manuscript because we felt that it was not particularly illuminating for the reader. However, if the reviewers feel that it should be included, these data could be incorporated into Figure 6, or provided as an additional supplemental figure.

Author response image 1
(A) CFSE dilution plots comparing T cell priming by WT (grayfilled histogram) or CA-WASp (redopen histogram) immature DCs in the presence of a range of OVA peptide with CD28 costimulation given in trans.

(B) AFM analysis of CA-WASp transduced cells. immature CA-WASp DC stiffness (green) is shown side-by-side with older data (Figure 6 in the manuscript) to facilitate comparison with WT CA-WASp mature cells.

Along these lines, it was surprising that the DC didn't at all take on the stiffness of the substrate. This may be due to poor DC adhesion, particularly for mature DC. Can the author confirm that the DC can spread on the hydrogels and if not, can the authors add attachment factors or molecules like podoplanin to be able to enhance spreading and establish a link between the substrate and cortical stiffness for DC? This might be a good alternative approach if the first approach fails. Of course, the author can solve this problem in other ways, but it would much more convincing to make DC better by making them stiffer than to make them worse by removing WASp, which may also affect protrusion dynamics and change many things.

The reviewer is correct that attachment of mature DCs to the hydrogels (actually to any surface) is problematic. For this reason, we have always attached them using Poly L-lysine, which we found to be superior to fibronectin. Thus, all cells in the study were well adhered to the substrate. We have clarified this in the text and have specified that we observed no change in the extent of cell spreading or morphology on the different hydrogels. The non-responsiveness of DCs to substrate stiffness and their failure to undergo significant increases in stiffness after genetic manipulation suggests that these cells maintain homeostatic control of cortical stiffness, regardless of external manipulations. This property is reminiscent of their tendency to migrate at a constant rate as they move along substrates with different adhesive properties, as characterized by the Sixt lab (Renkawitz et al., 2009).

3) The result that peripheral blood cells from mouse and human are not sensitive to the substrate stiffness is interesting, but not very well documented. In several instances the authors simply show signal dye dilution profiles as the only results to make a point. For all results, the authors must provide quantification for multiple experiments (mouse) or donors (human). This also applies to results in Figure 6. When there is quantification, the authors simply use percent cell division as a method to quantify the dye dilution experiments, but this throws out a lot of information and it would be better to use a proliferation index algorithm that take into account all the data through fitting the number of cells in each division number. Hopefully this data is all available and just needs to be presented with greater rigor. The other issue is that earlier studies that showed stiffness sensitivity of human peripheral blood T cells use much stiffer PDMS elastomers so perhaps peripheral blood cells are sensitive to greater stiffnesses, perhaps related to coping with conditions in circulation. I don't feel the author need to address this last point, but they just need to acknowledge the limitations of their measurements.

We have now added quantification from multiple experiments as division index for all figures involving T cell proliferation, retaining primary data (CFSE plots) from single representative experiments as well, where this will be helpful to the reader. As detailed in the cover letter, we have eliminated studies involving peripheral blood T cells.

[Editors’ note: the authors resubmitted a revised version of the paper for consideration. What follows is the authors’ response to the second round of review.]

The reviewers and reviewing editor appreciate your ability to provide the AFM measurements on the hydrogels and the details of the indentation depth at which the DC measurements were made. These additions improve the paper. However, there are concerns about both the reliability of the commercial hydrogels and the lack of correlation between DC stiffness and T cell response in the data series manipulating WASp and other actin regulators/inhibitors. The reproducibility of the materials is a significant issue, and while it is out of your control to some extent, the possibility exists that the initial results were the outliers and the new results with the present generation of commercial gels are a better reflection the actual ability to T cells to resolve these differences in substrate stiffness.

We completely agree with the reviewers on this point. Indeed, the old set of hydrogels were found to have several issues. For that reason, we have taken every precaution with the new hydrogel surfaces. We have worked closely with the manufacturer to ensure that their new surfaces are consistent from batch-to-batch over the course of many months, that they bind stimulatory ligands in a reproducible manner, and that they have no physical defects (e.g. shrinkage exposing plastic surface). We are now confident that our results are reproducible within our own lab, and that others should be able to reproduce and build on our findings. In addition, we have taken several steps to ensure that our new results reflect the actual ability of T cells to sense substrate stiffness:

1) We have redone all the studies in the manuscript that involve T cell activation by hydrogel substrates with the new hydrogel surfaces, with a high number of repeats to ensure reproducible results.

2) To better examine T cell stiffness sensing, we have incorporated several new ways to measure T cell activation in response to stimulatory hydrogel surfaces:

a) In a set of new experiments, we looked at T cell activation at an earlier time point, by measuring upregulation of the activation markers CD69 and CD25, and IL-2 production at 24 hours post stimulation. This new time point reveals an intriguing difference between CD4+ and CD8+ T cells. While CD4+ T cells showed profound stiffness-dependent responses, CD8+ T cells were much less stiffness dependent.

b) In these new studies, we measure expression of CD25 in all CFSE dilution proliferation assays (done at 72 hours post stimulation). This new addition validates our results further and adds a new facet to understanding the phenomenon.

3) We have added a new set of experiments where we compare T cell activation by pMHC, anti-CD3ε, and anti-TCRvβ side-by-side. These studies reveal that stiffness-dependent responses are best detected when T cells are stimulated by pMHC. This new set of studies adds to the manuscript by relating T cell mechanosensing to the current models of TCR deformation.

You also state that you have performed a range of manipulations to try to alter DC stiffness and have only obtained the desired correlation with WASp-KO in mature DC. This, along with the data you present in the revision, seems like a multiple testing problem that could invalidate the significance of the WASp-KO effect. But even if this is not the case, the problem still exists that details of what each manipulation does to antigen presentation by DC seems to dominate the effects of stiffness. If you can take all the efforts to manipulate DC cytoskeleton and plot stiffness against T cell response to achieve a correlation, then this would suggest an effect that cuts across the particular molecular details. But given that this doesn't seem to be the case, the WASp-KO effect in mature DC may also be an outlier that fits the model, but there are equal numbers of results that contradict the conclusion in an unbiased inspection of all the data. We greatly appreciate your sharing the information with us very openly. Unfortunately, the conclusions are not well enough supported for publication in eLife at this time.

There may be some misunderstanding here. We never obtained any data in which the correlation between DC stiffness and T cell responses was contradictory to our findings using hydrogels. The problem was that we could not manipulate DC stiffness. We tried numerous ways to alter DC stiffness for the previous submission and have tried more since then. These include knockouts of HS1, moesin, Fascin-1, L-plastin, T-plastin Ena/Vasp, and mDia/FMNL1, expression of constitutively active and dominant negative Rho-A, overexpression of a constitutively active moesin mutant, treatment with RhoA activator, and light fixation. Some of these manipulations were not tolerated by the cells, while other did not significantly alter cortical stiffness based on AFM analysis. It seems that DCs maintain constant cortical stiffness in the face of many cytoskeletal manipulations. Thus, while we would very much like to plot DC stiffness against T cell responses, we did not even test T cell responses in most cases, as correlative results where the variable in question was not altered would not be informative. It is disappointing we were unable to manipulate DC stiffness, but at this point, it’s clear that the hydrogel data is the best way to test T cell stiffness responses. We have included the data on DCs lacking WASp or expressing the constitutively active WASp mutant, as these were the best ways we could find to alter DC stiffness. The data do fit our model, but we have taken care in the revised manuscript to address the limitations of this experiment, and we have tried not to overstate the significance of these findings.

[Editors’ note: what follows is the authors’ response to the third round of review.]

Essential revisions:

1) Interpretation of AFM-based data of Young's modulus needs to be developed more. Indentation depths appear to be in the range of several micrometers for the cells, which is on the order of cellular structures. The Hertzian model assumes a homogenous Young's modulus for several multiples of the indentation depth. Such distances include cell cytoplasm and may also reflect the rigidity of the underlying substrate. Figure 1D provides some evidence that this is not the case, but given the overall small impacts on measured modulus and comparatively soft nature of the dendritic cells, it is still possible that flattening of the cells upon maturation contributes to the changes in calculated modulus. Reanalysis of the force-indentation curves over lower ranges of indentation would help address this issue.

We totally agree with the reviewer on this matter and made the following changes to address this. All AFM data was reanalyzed with new constraints on the fitting algorithm to ensure that fitting is done based on ~0.5 µm indentation depth. Since the Bruker software does not allow fitting restriction by Z axis separation, we had to take a different approach to restrict fitting to ~0.5 µm. After consultations with other scientists in the field, we achieved this by restricting the Hertzian model fitting to 30% of total force applied, which we found corresponds to ~0.5 µm indentation depth. This new procedure and the reasoning for it are now included in the Materials and methods section under the description of AFM procedures. For clarity, we have added an example of the implementation of this procedure in Figure 1—figure supplement 4. Figure 1, Figure 2 and Figure 7 were revised to reflect resulting changes to the exact stiffness values, and the accompanying text in the Results section was modified accordingly. Importantly, this new analysis did not significantly alter the overall relationships among the different samples or the interpretation of our results.

2) It would also be helpful for you to report on the adhesion of the DC on different rigidity substrates as DC are not typically highly adherent cells, but you are using a unique substrate so this is uncharted territory. Degree of adhesion and cell height above the substrate under all relevant conditions would be important data that could be conveyed in a table.

We thank the reviewer for pointing this out to us. We have used Poly-L-Lysine to stick the BMDCs down to the surfaces to minimize the effect of differences in adhesive properties of the cells, and we did not observe major differences in cell morphology during AFM measurements. To clarify this for readers, we have now added a new figure (Figure 1—figure supplement 2 ) showing the footprint (spreading area) of BMDCs (immature and mature) on hydrogel and glass surfaces (always coated with Poly L-lysine). Representative images, as well as the analysis of mean cell size are shown, and described in the manuscript. We found that all cells show a similar footprint on the different surfaces, with mature cells being slightly smaller than immature ones. Although there is one exception where immature DCs have a statistically significantly larger footprint on the 25kPa surface, the change in size is small (less than 10%).

Unfortunately, due to the covid-19 situation, we were unable to locate an upright confocal microscope to image the cells height above the surface as requested. Instead, we had to default to using a long working distance 40X objective and image the cells through the hydrogels, resulting in reduced image quality. Nevertheless, our data clearly shows that our use of PLL does, in fact, allow for similar spreading of BMDCs on the different surfaces. Together with the changes in the AFM analysis, we feel confident that cell spreading does not affect the AFM measurements, and that our results reflect a biological mechanism.

3) As only one TCR-pMHC combination is studies for CD4 and CD8 T cells, it’s possible that the different response might be a function of the potency of the pMHC, rather than a difference between CD4 and CD8 T cells. Do you have data comparing naive CD4 and CD8 T cells with otherwise identical anti-CD3 substrates? This might still provide the best comparison as supplemental data, although less physiological than the pMHC data.

The reviewer raises an excellent point, with an excellent suggestion on how to resolve this issue. We did the experiment suggested by the reviewer and the results are now given in Figure 5—figure supplement 1 and addressed in the accompanying text. Briefly, we stimulated OT-II CD4+ and OT-I CD8+ T cells side-by-side on the same set of surfaces used throughout the manuscript, using a varying concentration of αCD3ε (2C11) and constant αCD28 (PV1) T cell proliferation was measured using CFSE dilution. To facilitate comparisons between this experiment other studies using pMHC stimulation, division indices were normalized. This makes it possible to compare the trends in stiffness responses and not the actual division index numbers, which are naturally higher for antibody stimulation. We find that similar to pMHC stimulation, stimulating CD4+ T cells with 2C11 results in a profound stiffness dependent response, whereas soft hydrogels (2,4 kPa) do not even stimulate a response. Similarly, CD8+ T cells stimulated with antibody show only a weak stiffness dependency, similar to the pMHC-I stimulated counterparts. We thus conclude that the difference between CD4+ and CD8+ stiffness responses is not due to different antigen strengths but representing of a different biological mechanism.

4) You could discuss the potential impact of differences in lateral mobility of pMHC on the hydrogels vs DC.

This is an important point, which will need to be addressed experimentally in future work. We have added text addressing this point in the Discussion section.

[Editors’ note: what follows is the authors’ response to the fourth round of review.]

Your carefully conducted study is particularly interesting since it represents a coherent and complete analysis of the response (expression of activation markers, IL-2 production and proliferation) of mouse T cells to stiffness. It also demonstrates that the program of maturation of DC includes changing in their mechanical properties that is most probably involved in their ability to activate T lymphocytes. Your work also open new fields of investigation for example: what are the mechanisms involved in the modification of the DC cytoskeleton leading to changes in their stiffness? What are the molecular mechanisms, which explain the difference of sensitivity to stiffness between CD4 and CD8 T cells?

However, there were still some concerns about the discussion of the AFM results. No additional experiments are suggested, the reviewers concurred that the second paragraph of the Discussion section (discussing different methods of measuring Young's modulus) would be a natural place for raising these issues. You should discuss further how cortex, nucleus, invaginations and projections at the DC surface can affect the AFM measurements. In this paragraph, the authors may also comment on the limits of the technique on cells such as DC that are known for their complex surface topology.

We are pleased to resubmit this revised version of our manuscript entitled “T cell priming is enhanced by maturation-dependent stiffening of the dendritic cell cortex” for publication in eLife. We have addressed all the remaining reviewers’ concerns. In particular, we added a new paragraph to the Discussion section to address the topological complexity of the DC surface, and how this may influence AFM measurements. In addition, we have corrected the missing reference and made the other recommended changes to spelling and grammar. To designate plastic surfaces and avoid confusion, Pl was changed to PL in several figures and their legends, so all figures have been re-uploaded.

https://doi.org/10.7554/eLife.55995.sa2

Article and author information

Author details

  1. Daniel Blumenthal

    Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing
    For correspondence
    daniel.blumenthal.chop@gmail.com
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9207-5848
  2. Vidhi Chandra

    Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3642-2144
  3. Lyndsay Avery

    Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
    Contribution
    Formal analysis, Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8148-1648
  4. Janis K Burkhardt

    Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia Research Institute and Perelman School of Medicine at the University of Pennsylvania, Philadelphia, United States
    Contribution
    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing - review and editing
    For correspondence
    jburkhar@pennmedicine.upenn.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8176-1375

Funding

National Institute of General Medical Sciences (GM104867)

  • Janis K Burkhardt

National Institute of Allergy and Infectious Diseases (AI32828)

  • Janis K Burkhardt

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The authors thank Florin Tuluc and Jennifer Murray from the Children’s Hospital of Philadelphia Flow Cytometry core. We thank the biomechanics core of the Institute of Translational Medicine and Therapeutics (ITMAT) at the University of Pennsylvania for use of the Atomic Force Microscope and the NIH tetramer core facility for provision of MHC-peptide complexes. We thank Dr. Shuixing Li and Dr. Nathan Roy for expert technical assistance, Dr. Nathan Roy and Mr. Tanner Robertson for critical reading of the manuscript, and members of the Burkhardt laboratory for many helpful discussions. This work was supported by NIH grants R01 GM104867 and R21 AI32828 to JKB.

Ethics

Animal experimentation: All studies, breeding and maintenance of animals was performed under Animal Care and Use Protocol #667, as approved by The Children's Hospital of Philadelphia Institutional Animal Care and Use Committee.

Senior Editor

  1. Anna Akhmanova, Utrecht University, Netherlands

Reviewing Editor

  1. Michael L Dustin, University of Oxford, United Kingdom

Reviewers

  1. Claire Hivroz, Institut Curie, France
  2. Morgan Huse, Memorial Sloan Kettering Cancer Center, USA

Publication history

  1. Received: February 14, 2020
  2. Accepted: July 27, 2020
  3. Accepted Manuscript published: July 27, 2020 (version 1)
  4. Version of Record published: August 10, 2020 (version 2)

Copyright

© 2020, Blumenthal et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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