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PKCθ links proximal T cell and Notch signaling through localized regulation of the actin cytoskeleton

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Cite as: eLife 2017;6:e20003 doi: 10.7554/eLife.20003

Abstract

Notch is a critical regulator of T cell differentiation and is activated through proteolytic cleavage in response to ligand engagement. Using murine myelin-reactive CD4 T cells, we demonstrate that proximal T cell signaling modulates Notch activation by a spatiotemporally constrained mechanism. The protein kinase PKCθ is a critical mediator of signaling by the T cell antigen receptor and the principal costimulatory receptor CD28. PKCθ selectively inactivates the negative regulator of F-actin generation, Coronin 1A, at the center of the T cell interface with the antigen presenting cell (APC). This allows for effective generation of the large actin-based lamellum required for recruitment of the Notch-processing membrane metalloproteinase ADAM10. Such enhancement of Notch activation is critical for efficient T cell proliferation and Th17 differentiation. We reveal a novel mechanism that, through modulation of the cytoskeleton, controls Notch activation at the T cell:APC interface thereby linking T cell receptor and Notch signaling pathways.

https://doi.org/10.7554/eLife.20003.001

eLife digest

The body’s immune system recognizes and responds to foreign agents such as bacteria and viruses. Immune cells known as T cells recognize foreign substances through a protein on their surface called the T cell receptor. Specifically, the T cell receptor binds to fragments of foreign proteins displayed on the surface of other cells, which sets in motion a chain of events that leads to the T cell becoming activated. An activated T cell divides to form new cells that develop into “effector” T cells, which can mount an effective immune response.

The T cell engages with the cell displaying the foreign proteins via an interface referred to as the immunological synapse. This zone of contact brings together the signaling machinery of the T cell. Like many other cells, T cells contain an internal skeleton-like structure made up of actin filaments. These filaments are crucial for the formation of the immunological synapse, in part because they help to transport the T cell receptor and other signaling proteins to the immunological synapse.

Recent research suggests that a signaling protein called Notch plays an important role in instructing activated T cells to develop into effector cells. Notch is found on the surface of many cells, including T cells, and it becomes activated when it is cut by a specific enzyme. However, it was not entirely clear how T cell signaling drives the activation of the Notch protein.

Britton et al. have now investigated the mechanism that leads to Notch activation in T cells from mice. The results show that a protein found inside the T cell, called PKCθ, is a major contributor to Notch activation when T cells become activated. So how does the PKCθ protein control the activation of Notch? Britton et al. observed that PKCθ inactivates a protein that normally inhibits actin filaments from forming, and does so specifically at the center of the immunological synapse. This inhibition promotes the generation of a large actin-rich structure known as the lamellal actin network. This structure is required to recruit the Notch-cutting enzyme to the immunological synapse. Further analysis revealed that Notch gets cut and activated during the first few minutes of T cell activation leading to cell division and the development of effector T cells.

Following on from this work, the next challenge will be to explore if altering signaling from the T cell receptor – for example, using drugs or small molecules – can modify the activation of Notch. If so, it will be important to explore if the chemicals could potentially be used to treat diseases that develop when T cells go awry, such as rheumatoid arthritis, psoriasis and Crohn’s disease.

https://doi.org/10.7554/eLife.20003.002

Introduction

T cell activation is mediated by antigen recognition through the T cell receptor (TCR). To allow physiological adaptation, the TCR signal is modulated by co-regulatory signals. Here, we address co-stimulation through Notch. Notch family proteins are large, heterodimeric transmembrane receptors. Upon Notch ligation by one of a family of Notch ligands (Osborne and Minter, 2007), a plasma membrane-tethered matrix metalloproteinase, ADAM10 or ADAM17, removes the Notch extracellular domain. Subsequently, the plasma membrane-embedded γ-secretase complex liberates the Notch intracellular domain (NICD). The NICD constitutively translocates to the nucleus where it displaces transcriptional repressors and recruits enhancers to genomic loci characterized by binding of the transcription factor RPBJκ (Borggrefe and Oswald, 2009).

An essential role for Notch1 in T cell thymic development is well established (Robey et al., 1996; Washburn et al., 1997); a Notch1 deficient hematopoietic compartment yields no T cells (Radtke et al., 1999). Notch1 signaling also plays a pivotal role in mature T cells. Notch1 is activated following TCR stimulation (Amsen et al., 2004; Guy et al., 2013; Ong et al., 2008) and is required for effector cell development (Amsen et al., 2004; Keerthivasan et al., 2011). The degree of Notch1 activation is directly proportional to the strength of the TCR signal (Guy et al., 2013). Antigen-induced Notch1 activation in T cells may be ligand independent (Adler et al., 2003) (Ayaz and Osborne, 2014; Palaga et al., 2003). However, the cellular mechanism coupling proximal T cell signaling to Notch activation is unresolved. Here we reveal a spatially constrained mechanism of Notch1 activation. We demonstrate that PKCθ, a serine/threonine kinase integrating TCR and CD28 signals (Altman and Kong, 2016), enhances T cell actin dynamics through localization and phosphorylation of the negative actin regulator Coronin1A (Coro 1A) and thus mediates actin-based recruitment of ADAM10 to the T cell:APC interface for efficient Notch activation.

Results and discussion

PKCθ enhances Notch activation

To study the role of TCR/CD28-proximal signaling in Notch1 activation, we bred PKCθ-deficient Tg4 mice (Tg4KO). PKCθ integrates TCR and CD28 signals. PKCθ-deletion renders peripheral T cells hyporesponsive but allows normal thymic selection (Sun et al., 2000). Tg4 CD4+ T cells (Liu et al., 1995) recognize the acetylated N-terminal peptide of myelin basic protein Ac1-9[4K] and its high affinity MHC-binding analogue Ac1-9[4Y].

To determine whether Notch activation could play a role in mature T cells that is comparable to that in thymocytes, where Notch drives critical developmental decisions (Radtke et al., 2013), we assayed NICD expression in Tg4 thymocytes, naïve and primed T cells in response to anti-CD3 and anti-CD28. NICD expression and changes thereof upon cellular activation were similar (Figure 1—figure supplement 1A and B). However, Notch activation was impaired in mature T cells from Tg4KO mice. Tg4KO mice showed reduced Notch1 expression sixteen hours after in vivo T cell activation by injecting mice with 80 µg [4Y] peptide s.c. (Figure 1A,B) even though Tg4KO mice were grossly normal with a reduced number and proportion of CD4+ splenocytes but unaffected Tg4 TCR expression (Figure 2A; Figure 2—figure supplement 1). Reduced Notch expression was confirmed by Western blot analysis 60 min after s.c. administration of [4Y] peptide (Figure 1C) and through analysis of Notch1-dependent hes1 expression (Figure 1D). Corroborating these data in non-TCR transgenic T cells, Notch1 cleavage in naïve CD4+ T cells (CD4+, CD44, CD25) from PKCθ-deficient B10.PL mice was diminished following overnight activation with anti-CD3 and anti-CD28 (Figure 1E). Such Notch activation was CD28-dependent (Figure 1F), consistent with an important role of PKCθ downstream of CD28 (Huang et al., 2002; Kong et al., 2011; Yokosuka et al., 2008). As biochemical signaling activity in T cell activation peaks within the first few minutes, we verified that PKCθ-dependent Notch activation can also occur at this time scale. Increased nuclear Notch enrichment could be detected 5 to 20 min after in vitro T cell activation or after injecting mice with 80 µg [4Y] peptide s.c. (Figure 1G–I). This effect was corroborated using a second TCR transgenic system, 5C.C7 (Singleton et al., 2009) (Figure 1J).

Figure 1 with 1 supplement see all
PKCθ enhances antigen-induced Notch activation.

(A) Tg4WT and Tg4KO mice were injected subcutaneously with 80 µg of MBPAc1-9[4Y] peptide or PBS. After 18 hr splenocytes were immunostained to assess intracellular Notch1 expression and analyzed by flow cytometry. Gated on live, CD4+ cells. (B) The expression (geometric mean fluorescence intensity, gMFI) of intracellular Notch1 in CD4+ T cells from spleens of Tg4WT and Tg4KO mice treated as in A is shown as the mean ± SEM. **p=0.002, ns p=0.06 (ANOVA). One experiment of 2, n = 3 mice per condition. (C) Tg4WT and Tg4KO mice were injected subcutaneously with 80 µg of MBPAc1-9[4Y] peptide or PBS. CD4+ T cells were isolated from the spleen after 60 min by MACS and protein extracts analyzed by Western blotting with anti-NICD, anti c-myc and GAPDH. One representative Western blot of three. (D) Naïve Tg4WT and Tg4KO CD4+ T cells were isolated from splenocytes and stimulated with plate-bound anti-CD3 and anti-CD28 for 30 min. Expression of Hes1 was determined by RT-PCR. One representative experiment of four. (E) Naïve CD4+ T cells were isolated from B10.PL PKCθ WT or KO splenocytes by magnetic selection and stimulated for 18 hr with plate-bound anti-CD3 and anti-CD28 as indicated. An equal amount of protein extract from each sample was analyzed for expression of the NICD and GAPDH by Western blotting. (F) Naïve CD4+ T cells isolated from Tg4WT and Tg4KO mice were stimulated for 18 hr with a titration of plate-bound anti-CD3 ±2 µg/ml anti-CD28, as indicated. Expression of NICD and GAPDH was assessed by Western blotting. One representative Western blot of two. (G, H) Tg4WT and Tg4KO T cell blasts were incubated for 15 min with [4Y]-loaded PL8 cells before fixation and immunostaining against the IC domain of Notch1. The cells were counterstained with phalloidin and DAPI before imaging by confocal microscopy. The proportion of NICD staining in the nucleus (defined by DAPI staining) and the cytoplasm (defined by phalloidin staining) was measured and the ratio of nuclear:cytoplasmic NICD calculated. **p=0.0014, *p=0.02, ns p=0.2 (ANOVA). 32–58 cells analyzed per condition, combined data from two independent experiments. (I) Tg4WT mice were injected subcutaneously with 80 µg of MBPAc1-9[4Y] peptide or PBS. CD4+ T cells were isolated from the spleen after 5 or 20 min by MACS, fixed and immunostained against the IC domain of Notch1. The ratio of nuclear:cytoplasmic NICD is given. T cell treatment with 2 mM EDTA serves as a positive control of Notch activation. The difference between the 0 min time point and the EDTA control is significant with p=0.02 (ANOVA). One representative experiment of 4. (J) 5C.C7 mice were injected subcutaneously with 80 µg of MCC (89–103) peptide or PBS. CD4+ T cells were isolated from the spleen after 5 or 20 min by MACS, fixed and immunostained against the IC domain of Notch1. The ratio of nuclear:cytoplasmic NICD is given. Differences between the 0 versus 5 and 20 min time points are significant with p=0.005/0.002, respectively (ANOVA). One representative experiment of 3.

https://doi.org/10.7554/eLife.20003.003
Figure 2 with 1 supplement see all
Constitutively active Notch rescues defective proliferation, Th17 polarization and IL-17A secretion in PKCθ deficient T cells.

(A) Splenocytes from Tg4WT and Tg4KO mice were stained for the indicated molecules and absolute cell numbers or percentages are given as indicated. Each data point represents one mouse. Data are combined from mice assayed across three experiments. As previously reported (Gupta et al., 2008; Sun et al., 2000) in non-TCR transgenic mouse strains, PKCθ deficiency in Tg4 mice resulted in a reduced number and proportion of CD4+ T cells. p values by Student’s unpaired two-tailed t-test. (B) The proliferation of naïve Tg4WT and Tg4KO CD4+ T cells stimulated with irradiated B10.PL splenocytes and a titration of MBPAc1-9[4K] is given. n = 8 Tg4WT, n = 15 Tg4KO mice, each assayed in triplicate for each peptide concentration. Shown is the mean ± SEM. ****p<0.0001 by Student’s unpaired two-tailed t-test. (C) Naïve Tg4WT and Tg4KO mice were injected subcutaneously with 80 µg of MBPAc1-9[4Y] peptide or PBS. After 18 hr splenocytes were immunostained to assess CD69 expression and analyzed by flow cytometry. Gated on live, CD4+ cells. The mean expression (geometric mean fluorescence intensity, gMFI) ± SEM of CD69 is given. ns p=0.08. One experiment of 2, n = 3 mice per condition. (D) Tg4WT or Tg4KO mice were injected subcutaneously with 80 µg [4Y] peptide. After 60 min, CD4+ splenocytes were isolated by MACS, RNA was isolated and the expression of c-myc and IL-2 determined by RT-PCR. n = 3 mice per condition, shown is mean ± SEM. ns = 0.68 by unpaired Student’s t-test. (EG) Splenocytes from Tg4WT or Tg4KO mice were stimulated with 10 µg/ml [4K] peptide, IL-12 and IL-2 for 7–9 days before restimulation with PMA and ionomycin in the presence of monensin. The proportion of IFNγ and IL-2-producing CD4+ T cells was determined by intracellular cytokine staining. Shown are representative FACS plots, gated on live, CD4+ cells and the combined data from all replicates shown as mean ± SEM n = 7–11 independent biological replicates ns = 0.71 (F) and 0.73 (G) by unpaired Student’s t-test. (IJ) Splenocytes from Tg4WT or Tg4KO mice were stimulated with 10 µg/ml [4K] peptide, IL-6, IL-1β, IL-23, anti-IFNγ and anti-IL-4 for 7–9 days before restimulation with PMA and ionomycin in the presence of monensin. The proportion of IFNγ and IL-17A-producing CD4+ T cells was determined by intracellular cytokine staining. Shown are representative FACS plots, gated on live, CD4+ cells and the combined data from all replicates shown as mean ± SEM. n = 8 independent biological replicates, p<0.0001 (I) p=0.03 (J) by Student’s t-test. (K) Splenocytes from Tg4WT and Tg4KO mice were stimulated with [4K] peptide and IL-2 before transduction with a retrovirus encoding NICD and GFP or GFP alone. After 72 hr the incorporation of 3H thymidine was measured. n = 3 replicate transductions per condition, mean values ± SEM. *** = 0.0005, ns = 0.31. One representative experiment of four. (L, M) Splenocytes from Tg4WT and Tg4KO mice were stimulated with [4K] peptide in the presence of IL-6, IL-1β, TGFβ and IL-23 before transduction with a retrovirus encoding NICD and GFP or GFP alone. After 96 hr of further culture with IL-6, IL-1β, TGFβ and IL-23 the cells were restimulated with PMA and ionomycin in the presence of monensin before intracellular staining for the expression of IL-17A. (L) shows representative FACS data. The mean ± SEM of three replicates from one experiment of four is shown in M. ns = 0.06 by Student’s t-test. (N) The mean concentration of IL-17A was measured in supernatants from triplicate cultures of Tg4WT and Tg4KO cells T cells transduced with NICD or GFP alone under Th17-polarising conditions. p values by Student’s t-test. One representative experiment of three.

https://doi.org/10.7554/eLife.20003.005

PKCθ enhances in vitro Th17 T cell differentiation and T cell proliferation via Notch

To determine functional outcomes of diminished Notch processing in PKCθ-deficient T cells, we analyzed T cell proliferation and differentiation. In accordance with published data (Keerthivasan et al., 2011; Marsland et al., 2004; Tan et al., 2006), T cell proliferation, CD69 and c-Myc upregulation were defective in Tg4KO T cells whereas IL-2 was unaffected (Figure 2B–D). Tg4KO T cells showed no defect in Th1 cell differentiation (Figure 2E–G). Conversely, the proportion of IL-17A+ T cells was significantly reduced under conditions favoring Th17 development (Figure 2H–J). Overexpression of NICD at 18.5 ± 1.5 fold the level in non-activated primed Tg4WT cells (Figure 1—figure supplement 1C and D) so as to constitutively activate Notch in Tg4KO cells led to restoration of T cell proliferation (Figure 2K), Th17 cell differentiation and IL-17A secretion (Figure 2L–N). Notch1 thus enhances T cell proliferation and differentiation downstream of PKCθ.

PKCθ enhances actin-dependent enrichment of ADAM10 at the T cell:APC interface

We investigated ADAM10 as a key signaling molecule potentially employed by PKCθ for Notch1 activation. We visualized ADAM10 recruitment to the interface between the T cell and the APC by virally transducing Tg4WT and Tg4KO CD4+ T cells with ADAM10-GFP. ADAM10-GFP+ T cells were imaged as they interacted with H-2u PL8 lymphoma APC presenting the Ac1-9[4Y] antigen. Tg4KO T cells, whether transduced to express ADAM10-GFP or other sensors, formed tight cell couples upon APC contact albeit with a slightly reduced frequency compared to Tg4WT T cells (30 ± 5% versus 50 ± 4%, p=0.02) with comparable gross T cell morphology, as characterized in the next paragraph. Such effective cell coupling allowed an analysis of the interface recruitment of GFP-tagged signaling intermediates and the spatiotemporal patterns thereof. ADAM10-GFP was recruited rapidly and transiently to the interface of Tg4WT T cells and APC (Figure 3A,B; Figure 3—figure supplement 1A, Video 1) consistent with previous work in AND T cells (Guy et al., 2013). In contrast, ADAM10-GFP was not enriched at the interface of Tg4KO T cells (Figure 3A,B; Figure 3—figure supplement 1A, Video 2). In Tg4WT cells, ADAM10 was enriched in the interface lamellum, an actin-based signaling structure (Roybal et al., 2015b). Impairment of lamellum formation with 40 nM Jasplakinolide (Figure 3—figure supplement 1B) (Roybal et al., 2015a) prevented ADAM10 interface recruitment (Figure 3A,B; Figure 3—figure supplement 1A) and Notch cleavage following stimulation with anti-CD3/28 (Figure 3C). The defect in lamellal ADAM10 recruitment upon PKCθ-deficiency was selective since the lamellal accumulation of Themis, a protein with substantially more prominent and persistent lamellal accumulation than ADAM10, was only moderately impaired (Figure 3—figure supplement 1C–E). Together, these data suggest that actin-dependent ADAM10 recruitment to the T cell:APC interface at the early peak of T cell signaling activity mediates efficient Notch1 activation downstream of PKCθ. In AND T cells strong stimuli cause concerted accumulation of the TCR, Vav and Notch at the T cell/APC interface as related to efficient Notch activation (Guy et al., 2013). Actin dynamics may thus mediate coordinated interface accumulation of both ADAM10 and Notch. It needs to be determined how PKCθ and Vav-dependent actin dynamics are related.

Figure 3 with 2 supplements see all
PKCθ mediates transient actin-dependent recruitment of ADAM10 to the T cell lamellum.

(A) Tg4WT CD4+ T cells, treated with 40 nM Jasplakinolide (bottom) or not (top), and Tg4KO (middle) CD4+ T cells expressing ADAM10-GFP were activated with PL8 cells presenting the Ac1-9[4Y] peptide. Given are representative images showing pseudocolored (purple to red) maximum projections of the ADAM10-GFP fluorescence and a reference DIC bright field image at times relative to the formation of a tight couple between T cell and APC. The entire image sequences are given in Video 1 (Tg4WT) and 2 (Tg4KO). (B) The graph shows the percentage of T cells with lamellal accumulation of ADAM10-GFP at the time relative to couple formation ± SEM. Differences in lamellal accumulation between Tg4WT and Tg4KO and Jasplakinolide-treated Tg4WT T cells at time points 0:00 and 0:20 were each significant with p≤0.005 (Tg4KO versus Tg4WT 0:00 p=0.001, 0:20 p=0.005; Tg4WT +Jasp versus Tg4WT 0:00 p=0.004, 0:20 p=0.001, by proportions z-test). 18–28 cell couples were analyzed per condition (57 total). Full pattern analysis is given in Figure 3—figure supplement 1A. (C) CD4+ blasts from Tg4WT and Tg4KO mice (four days after stimulation) were restimulated for 18 hr with anti-CD3 and anti-CD28 ±40 nM Jasplakinolide or left unstimulated as indicated. NICD and GAPDH expression in protein extracts was measured by Western blotting. One representative experiment of three. (D) Tg4WT and Tg4KO CD4+ T cells expressing F-tractin-GFP were activated with PL8 cells presenting the Ac1-9[4Y] peptide. Representative images are given as in A. The entire image sequences are given in Video 3 (Tg4WT) and 4 (Tg4KO). (E) The percentage of cell couples with predominantly peripheral F-tractin-GFP accumulation is given as in B. The difference in peripheral accumulation between Tg4WT and Tg4KO T cells at joint time points 0:00 and 0:20 was significant (p=0.01 by proportions z-test, 31, 47 cell couples were analyzed per condition). Full pattern analysis is given in Figure 3—figure supplement 2A. (F) An example image of a T cell exhibiting the ‘bottleneck’ phenotype, defined as having a diameter minimum between the interface and the widest part of the cell body, is given as a grey scale F-tractin-GFP maximum projection together with a matching DIC bright field image. Measurement positions to determine the interface width (yellow) relative to the cell body (red) or the presence of a necking phenotype (blue) are shown. (G) The relative interface diameter was determined by relating the interface diameter to the widest part of the cell body and is given relative to the time of tight cell coupling. Shown is the mean ratio ± SEM. ns p=0.33 (0 s) and 0.149 (20 s) by unpaired, two-tailed Student’s t-test. 49 (WT) 35 (KO) cell couples were analyzed per condition. (H) The percentage of T cells displaying a bottleneck phenotype in at least one timepoint during the first 60 s after coupling is given. ***p<0.001 by proportions z-test. 35 cell couples were analyzed per condition.

https://doi.org/10.7554/eLife.20003.007
Video 1
ADAM10-GFP accumulates rapidly and transiently at the interface between Tg4WT CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4WT CD4+ T cell expressing ADAM10-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown. Top: DIC images. Bottom: Top-down maximum projections of 3D fluorescence data are shown in a rainbow-like, false-color intensity scale (increasing from blue to red). 20 s intervals in video acquisition are played back as two frames per second. Tight cell coupling occurs in frame 3 (1 s indicated video time).

https://doi.org/10.7554/eLife.20003.010
Video 2
ADAM10-GFP does not accumulate at the interface between Tg4KO CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4KO CD4+ T cell expressing ADAM10-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown as in Video 1. Tight cell coupling occurs in frame 5 (2 s indicated video time).

https://doi.org/10.7554/eLife.20003.011

Previous work has linked PKCθ to actin regulation (Sasahara et al., 2002; Sims et al., 2007; Villalba et al., 2002). By visualizing actin dynamics in Tg4WT and Tg4KO T cells with F-tractin-GFP (Johnson and Schell, 2009) (Videos 3 and 4), multiple elements of the actin-dependent establishment of a tight T cell:APC interface were modestly impaired in cells lacking PKCθ. The spreading of F-actin to the periphery of the interface was delayed in Tg4KO T cells (Figure 3D,E; Figure 3—figure supplement 2A). The interface diameter of Tg4KO T cells was significantly (p<0.05) reduced across multiple time points (Figure 3F,G), as confirmed by electron microscopy (Figure 3—figure supplement 2B). The lamellum connecting the T cell body to the interface was smaller in Tg4KO T cells as it showed a significantly (p<0.001) larger constriction or ‘neck’ (Figure 3F,H). Long lamella (>2.5 µm) did not occur (Figure 3—figure supplement 2C). Tg4KO T cells thus displayed modest defects across multiple elements of actin-driven cell spreading consistent with the slightly reduced efficiency of tight cell coupling.

Video 3
F-tractin-GFP accumulates rapidly at the interface between Tg4WT CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4WT CD4+ T cell expressing F-tractin-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is show as in Video 1. Tight cell coupling occurs in frame 6 (4 s indicated video time). Immediate spreading of the majority of F-actin to the edge of the interface is visible.

https://doi.org/10.7554/eLife.20003.012
Video 4
F-tractin-GFP accumulates rapidly at the interface between Tg4KO CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4KO CD4+ T cell expressing F-tractin-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown as in Video 1. Tight cell coupling occurs in frame 4 (2 s indicated video time). Delayed spreading of the majority of F-actin to the edge of the interface is visible.

https://doi.org/10.7554/eLife.20003.013

PKCθ phosphorylates and localizes Coronin1A

We sought to identify actin regulators mediating the modest actin modulation by PKCθ. Coronin1A inhibits the Arp2/3 complex (Humphries et al., 2002; Oku et al., 2005) and regulates clearance of actin from the NK immune synapse (Mace and Orange, 2014). Furthermore, Coronin is an established interactor with and substrate of PKC (Cai et al., 2005; Siegmund et al., 2015). Coronin1A was highly enriched at the interface of Tg4WT and Tg4KO T cells (Figure 4A,B; Figure 4—figure supplement 1A; Videos 5 and 6). Similar to actin, Coronin1A spreading to the interface periphery was delayed in Tg4KO cells, leaving substantially more Coronin 1A in the lamellum. Given that Coronin 1A is a negative regulator of actin dynamics its enhanced enrichment in the lamellum is consistent with the concurrent, localized impairments in actin, T cell morphology and ADAM10 recruitment. As a specificity control, the spatiotemporal distribution of the dominant F-actin severing protein Cofilin (Roybal et al., 2016; Singleton et al., 2011) was unaffected by PKCθ deficiency (Figure 4—figure supplement 1A).

Figure 4 with 1 supplement see all
PKCθ phosphorylates and localizes Coronin1A.

(A) Tg4WT and Tg4KO T cell expressing coronin1A-GFP were activated with PL8 cells presenting the Ac1-9[4Y] peptide. Representative images are given as in Figure 3A. The entire image sequences are given in Video 5 (Tg4WT) and 6 (Tg4KO). (B) The percentage of cell couples with predominantly lamellal (top) and peripheral (bottom) Coronin1A-GFP accumulation is given as in Figure 3B. The differences in lamellal accumulation between Tg4WT and Tg4KO T cells at time points −40 to 80 were each significant with p≤0.05 by proportions z-test. 50, 34 cell couples were analyzed per condition. Full pattern analysis is given in Figure 4—figure supplement 1A. (C) Shown is a representative Phos-tag western blot of protein extracts from Tg4WT or Tg4KO T cells stimulated with PMA and/or Calyculin A (Caly) for 5 min as probed with anti-coronin1A. (D) Given is the quantification of four independent experiment as in C as the mean ratio of the top (phospho) and lower (non-phospho) Coronin 1A bands ± SEM. * indicates p<0.05 Tg4WT versus Tg4KO T cells by two-way ANOVA with Sidak’s correction for multiple comparisons. (E) A graphical summary of the proposed mechanism of the enhancement of Notch activation by PKCθ is given. The top and bottom rows illustrate Tg4WT or Tg4KO T cells, respectively. Each individual panel shows the interface part of the T cell that contacts the APC (not shown on top). Separate panels are drawn from left to right for PKCθ (as also included in the other panels), Coronin1A, F-actin and ADAM10. Colors denote preferential accumulation patterns, central (red), lamellal (green) and peripheral (blue). Shade of color denotes the extent of accumulation.

https://doi.org/10.7554/eLife.20003.014
Video 5
Coronin1A-GFP accumulates rapidly at the interface between Tg4WT CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4WT CD4+ T cell expressing Coronin1A-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown as in Video 1. Tight cell coupling occurs in frame 4 (2 s indicated video time). Immediate spreading of the majority of Coronin1A-GFP to the edge of the interface is visible.

https://doi.org/10.7554/eLife.20003.016
Video 6
Coronin1A-GFP accumulates rapidly at the interface between Tg4KO CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4KO CD4+ T cell expressing Coronin1A-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown as in Video 1. Tight cell coupling occurs in frame 3 (1 s indicated video time). Transient lamellal accumulation of the majority of Coronin1A-GFP is visible.

https://doi.org/10.7554/eLife.20003.017

Next, we investigated phosphorylation of Coronin 1A by PKCθ in Tg4 T cells. Coronin activity is negatively regulated by serine/threonine phosphorylation, which can be induced by phorbol ester treatment (Cai et al., 2005; Oku et al., 2008, 2012). To allow detection of changes in Coronin1A phosphorylation, we prevented Coronin1A dephosphorylation by treating cells with the phosphatase inhibitor Calyculin A (Oku et al., 2008, 2012). Treating Tg4WT T cells with PMA and Calyculin A resulted in a shift in the ratio of phosphorylated to non-phosphorylated Coronin1A from 0.3 ± 0.1 to 2.8 ± 1.1 fold, indicative of efficient Coronin1A phosphorylation (Figure 4C,D). This shift was significantly (p<0.05) smaller in Tg4KO cells (0.25 ± 0.05 to 0.8 ± 0.25 fold) (Figure 4C,D) demonstrating that PKCθ is required for efficient PMA-induced phosphorylation of Coronin1A. Together, our data suggest (Figure 4E) that in Tg4WT T cells PKCθ (Figure 4—figure supplement 1B; Video 7) inactivates Coronin 1A selectively in the region of most intense stimulating signaling, i.e. the center of the T cell:APC interface with effects extending across the entire lamellum but not reaching the peripheral actin ring. Thus PKCθ locally inhibits Coronin 1A-mediated attenuation of actin dynamics, promoting the formation of a strong actin-based lamellum. With regard to Notch1 activation this allows for the efficient actin-driven recruitment of ADAM10 to the T cell:APC interface. This mechanism of enhanced Notch processing peaks within the first few minutes of T cell activation. Such early signaling emphasis is consistently observed in Tg4WT cells (Figure 4—figure supplement 1B) and other TCR transgenic systems, where it extends to the nuclear localization of other transcription factors, NFAT and NFκB (Roybal et al., 2015b; Singleton et al., 2009). We have thus identified a spatially restricted, actin-dependent mechanism of Notch activation downstream of PKCθ (Figure 4E). Future work will determine how the enhancement of Notch activation by PKCθ is integrated with PKCθ-dependent NFκB activation (Gruber et al., 2009; Sun et al., 2000) in the regulation of T cell differentiation.

Video 7
PKCθ-GFP accumulates at the center of the interface between Tg4WT CD4+ T cells and PL8 APCs.

A representative interaction of a Tg4WT CD4+ T cell expressing PKCθ-GFP with a PL8 APC presenting the Ac1-9[4Y] peptide is shown as in Video 1. Tight cell coupling occurs in frame 4 (2 s indicated video time). Central accumulation of the majority of PKCθ-GFP is visible.

https://doi.org/10.7554/eLife.20003.018

A key feature of our mechanism of PKCθ function is that it connects signaling at the time scale of minutes to outcomes in cellular differentiation over days. While causally connecting such divergent time scales is a great challenge, there is precedent. 15 min of contact between a primed T cell and a professional APC is sufficient to trigger T cell proliferation 24 hr later (Iezzi et al., 1998). Similarly, 1 hr of ZAP-70 activity can trigger substantial negative selection (Au-Yeung et al., 2014). Differential signaling kinetics may also regulate Treg induction (Miskov-Zivanov et al., 2013). On an even shorter time scale 5 min of TGFβ incubation saturates Smad2 phosphorylation at 1 hr (Vizán et al., 2013). In T cell activation, it has been argued that a time delay in the onset of activating versus inhibitory signaling from 2 to more than 5 min, respectively, may play an important role in the induction of anergy in response to high doses of antigen (Wolchinsky et al., 2014). In B cells a single pulse of BCR engagement can trigger the nuclear accumulation of NFκB for 6 hr (Damdinsuren et al., 2010). While mechanisms linking rapid proximal signaling to later cell function largely remain to be determined, the well-supported existence of such causal links is consistent with our model of PKCθ-dependent Notch activation.

Materials and methods

Mice

All mice were maintained under SPF conditions with ad libitum access to water and standard chow at the University of Bristol. All animal experiments were carried out under the UK Home Office Project Licence number 30/2705 held by David Wraith and the study was approved by the University of Bristol ethical review committee. B10.PL, 5C.C7 (Seder et al., 1992) and Tg4 (Liu et al., 1995) mice were bred in-house at the University of Bristol. PKCθ-deficient Tg4 mice were generated by cross-breeding Tg4 mice with C57BL/6 prkcq−/−mice (a gift of A. Poole, University of Bristol, originally generated by D. Littman (Sun et al., 2000) for >8 generations. The genetic status of each animal was assessed by PCR as previously described (Sun et al., 2000). B10.PL PKCθ KO mice were obtained by breeding Tg4KO mice with B10.PL mice.

Cell lines

The PL8 H-2u expressing, antigen-presenting B cell lymphoma was prepared in our laboratory (Wraith et al., 1992). The H-2k expressing CH27 B cell lymphoma was prepared as described previously (Haughton et al., 1986) and obtained from Mark Davis, Stanford University. Both cell lines proved mycoplasma free by PCR and were validated by staining for MHC class II expression and assessing their ability to present antigen to relevant T cell lines.

Cell culture

Lymphoid tissue was dissociated using standard protocols and red blood cells removed using Red Cell Lysis buffer (Sigma). Unless otherwise stated, cells were cultured in complete RPMI 1640 (Lonza; supplemented with 25 mM HEPES, 50 U/ml Pen/Strep, 2 mM L-Glutamine and 50 µM 2-mercaptoethanol) with 5–10% FCS (BioSera, Hyclone). PL8 and CH27 cells were maintained in complete RPMI with 10% FCS. Th17 cells were generated and maintained in IMDM (Lonza; supplemented with 50 U/ml Pen/Strep, 2 mM L-Glutamine and 50 µM 2-mercaptoethanol) containing 10% FCS.

T cell isolation and stimulation

For isolation of double negative thymocytes, thymi were gently disaggregated on ice in 5% FCS/PBS. Cells were stained at 4°C with CD4-FITC and CD8a-APC antibodies. Propidium iodide was added immediately prior to flow cytometric sorting of viable CD4-CD8a- thymocytes using a BD Influx cell sorter. For in vitro stimulation experiments, naïve CD4+ T cells were isolated from spleen and axillary, brachial and inguinal lymph nodes using either EasySep Mouse Naïve CD4+ T cell isolation kit (Stem Cell Technologies) or MagniSort Mouse Naïve CD4+ T cell enrichment kit (eBioscience) according to the manufacturers’ instructions. For ex-vivo analysis of activated T cells, CD4+ cells were enriched with Mouse CD4+ T cell enrichment kit II (Miltenyi Biotech) according to the manufacturer’s instructions. Naïve or pre-activated CD4+ T cell cells were stimulated with plate-bound anti-CD3 (2C11, eBioscience or BioExcel, 1 µg/ml or as indicated) and anti-CD28 (37.51, eBioscience or BioExcel, 2 µg/ml). Alternatively, cells were stimulated with PL8 cells and MBPAc1-9 [4K] or [4Y] peptide (GL Biochem) or CH27 cells and MCC 88–103 peptide at the concentration indicated. Where indicated, cells were incubated with PMA (Sigma, 20 ng/ml), Calyculin A (Sigma, 100 nM) or Jasplakinolide (Tocris, 40 nM).

T helper differentiation

Suspensions of splenocytes from Tg4WT and Tg4KO mice were stimulated with 10 µg/ml MBP Ac1-9 [4K] peptide. For TH1 generation, cells were cultured in complete RPMI containing 10 ng/ml IL-12 (Peprotech) and 20 U/ml rhIL-2 (R and D systems). For TH17 cells, culture was performed in complete IMDM containing 25 ng/ml IL-6, 10 ng/ml IL-1β, 2 ng/ml TGFβ (all Peprotech), 10 ng/ml IL-23 (eBioscience), 50 µg/ml anti-IFNγ (XMG1; BioExcel) and 10 µg/ml anti-IL-4 (11B11; BioExcel).

Western blotting

CD4+ T cells were stimulated as indicated and washed with ice-cold PBS before protein was extracted in RIPA buffer supplemented with protease and phosphatase inhibitor cocktails (all from Pierce) (1−2 × 107 cells/ml). Lysates were centrifuged for 10 min at 17,000xg and the soluble fraction denatured in Laemmli buffer before resolution by SDS-PAGE on 4–12% gels (NuPAGE), transfer to PVDF membrane and immunodetection using standard ECL protocols. Where indicated, samples were resolved on 12.5% gels supplemented with 50 µM PhosTag reagent (Wako) and 100 µM ZnCl2. For PhosTag experiments, cells were washed with HBSS instead of PBS. The following antibodies were used Notch1; (D1E11, Cell Signaling), GAPDH (D16H11, Cell Signaling), c-myc (E910, Santa Cruz Biotechnology), Coronin1A (H300, Santa Cruz Biotechnology), anti-rabbit and anti-mouse HRP conjugates (Sigma).

Flow cytometry and cytokine measurements

Non-viable cells were excluded from all analyses using Live/Dead eF780 dye (1:1000, eBioscience). Surface staining was performed in PBS containing 0.5% FCS and 2 mM EDTA. Intracellular cytokine staining (ICCS) was performed on cells stimulated with PMA (10 ng/ml) and ionomycin (1 µg/ml) in the presence of GolgiStop (BD Bioscience, 1:1000) for 4 hr. Cells were surface stained before fixation and permeabilization using eBioscience reagents. Staining for intracellular Notch1 and FoxP3 was performed after fixation and permeabilization using FoxP3 staining kit reagents (eBioscience). The following antibodies, all purchased from eBioscience and/or Biolegend, were used; CD4 Alexa700 (GK1.5, 1:100), CD69 FITC (H1.2F3, 1:100), Notch1-PE (mN1A, 1:100, Biolegend), CD8a APC (53–6.7, 1:200), CD19 (1D3, 1:200), B220 FITC (RA3-6B2, 1:100), Vb8.1/2 FITC (KJ16-133, 1:100), FoxP3 PE (FJK-16S, 1:100, eBioscience), CD25 PE-Cy7 (PC61.5, 1:300), IFNγ PE-Cy7 (XMG1, 1:400), IL-2 eF450 (JES6-5H4, 1:100) and IL-17A PE or PE-Cy7 (17B7, 1:2–400).

Soluble IL-17A was detected in culture supernatant by ELISA using Ready-Set-Go ELISA kit (eBioscience).

T cell transduction

The cDNA encoding the IC domain of murine Notch1 was obtained from Addgene (plasmid number 20183). The IC domain was amplified by PCR with the primers ACCGCGGTGGCGGCCATGCAGCATGGCCAGCTCT and CGGGCTAGAGCGGCCTTATTTAAATGCCTCTGGAATGT and cloned into the Not1 site of pGC-IRES-GFP (Costa et al., 2000) using In-Fusion HD reagents (Clontech). cDNA encoding murine Adam10, obtained from Sinobiological (Genbank number NM_007399.3), was amplified with primers ACCGCGGTGGAGGCCAAGATGGTGTTGCCGACAGT and GGCGACCGGTGGATCTCCACCGCGTCGCATGTGTCCCATT and cloned into BamH1 and Not1 sites of pGC-GFP using In-Fusion reagents such that the C-terminus of ADAM10 was fused to GFP. The pGC-IRES-GFP vector was used as a negative control. The constructs used to express other sensors including Coronin1A-GFP, Cofilin-GFP, Themis-GFP, F-Tractin-GFP and PKCθ–GFP have been previously described (Table 1 in [Roybal et al., 2015b] and [Roybal et al., 2016]). Retrovirus was generated by transfecting Phoenix-E cells using calcium phosphate precipitation. For imaging experiments, Tg4 T cells were infected by centrifugation with viral supernatant 24 hr after stimulation with 10 µg.ml−1 [4K] and 20 U.ml−1 rhIL-2. Immediately following transduction culture media was replaced with complete RPMI supplemented with 20–40 U/ml rhIL-2. For TH17 Notch rescue experiments, Tg4WT and Tg4KO splenocytes were cultured for 24 hr under TH17-polarising conditions (as described above) before transduction. Immediately following transduction, the culture medium was replaced with complete IMDM containing 20 ng/ml IL-23 and 50 µg/ml anti-IFNγ. T cells were analyzed by imaging or flow cytometry 4–5 days after transduction.

Proliferation measurements

72 hr following transduction, 2.5 µCi 3H thymidine/ml (Perkin Elmer) was added to culture wells. After 16 hr incubation, incorporation of 3H thymidine was measured by scintillation counting.

RT-PCR

CD4+ T cells were stimulated and isolated as indicated in figure legends and RNA was extracted using either RNeasy Mini kit (Qiagen) or TRI Reagent (Sigma Aldrich). cDNA was generated using Superscript III polymerase (Life Technologies) and real time PCR performed using a SYBR green PCR Mastermix (Life Technologies). Primers; il2 sense; AGCAGCTGTTGATGGACCTA, il2 antisense; CGCAGAGGTCCAAGTTCAT, cmyc sense; TTGAAGGCTGGATTTCCTTTGGGC, cmyc antisense; TCGTCGCAGATGAAATAGGGCTGT, Hes1 sense; AAAGATAGCTCCCGGCATTC, Hes1 antisense; TGCTTCACAGTCATTTCCAGA, β2M sense; GCTATCCAGAAAACCCCTCAA, β2M antisense; CGGGTGGAACTGTGTTACGT. Data were analysed using the 2-△△CT method, normalized to β2microglobulin.

Live cell imaging

Live cell imaging was performed as described in detail before (Singleton et al., 2009). Using FACS, GFP+ transductants were sorted to a five-fold range of expression around 2 µM, the lowest concentration visible by microscopy and often within the range of endogenous protein amounts (Roybal et al., 2016). PL8 cells were pre-loaded with 10 µg/ml [4Y] for >4 hr and combined with pre-sorted GFP+ Tg4 T cells in a glass-bottom plate on the stage of a spinning disk microscope system (UltraVIEW 6FE system, Perkin Elmer; DMI6000 microscope, Leica; CSU22 spinning disk, Yokogawa). GFP data were collected as 21 z-sections at 1 µm intervals every 20 s. All imaging was performed at 37⁰C in PBS containing 10% FCS, 1 mM CaCl2 and 0.5 mM MgCl2. Images were exported in TIFF format and analyzed with the Metamorph software (Molecular Devices). Cell couples were identified using the differential interference contrast (DIC) bright field images. The subcellular localization of GFP-tagged protein sensors at each time point was classified into one of six previously defined stereotypical patterns (Singleton et al., 2009) that reflect cell biological structures driving signaling organization (Roybal et al., 2013). Briefly, interface enrichment of fluorescent proteins at less than 35% of the cellular background was classified as no accumulation. For enrichment above 35% the six, mutually exclusive interface patterns were: accumulation in a large protein complex at the center of the T cell:APC interface (central), accumulation in a large T cell invagination (invagination), accumulation that covered the cell cortex across central and peripheral regions (diffuse), accumulation in a broad actin-based interface lamellum (lamellum), accumulation at the periphery of the interface (peripheral) or in smaller membrane protrusions (asymmetric).

Immunofluorescence staining

Pre-activated Tg4WT and Tg4KO CD4+ T cells (4 days after activation) were combined with PL8 APC pre-incubated with 10 µM MBPAc1-9[4Y] for 15 min before fixation with 4% PFA. Alternatively, Tg4 or 5C.C7 T cells were activated in vivo by s.c. injection with 80 µg MBPAc1-9[4Y] or MCC (88-103) respectively before cell isolation and fixation. Following permeabilization with 0.05% Triton X-100 cells were immunolabelled with anti-Notch1 IC domain (D1E11, Cell Signaling) with an anti-rabbit Alexa488-conjugated secondary antibody (Life Technologies) and counterstained with DAPI and Phalloidin Alexa647 (Life Technologies). Alternatively, cell couples were stained with anti-Notch Alexa647 (Abcam, ab194122) and anti-CD4 FITC. Images were acquired on a Leica SP5 confocal microscope and image analysis was performed in Metamorph and Volocity (Perkin Elmer).

Electron microscopy

Electron microscopy experiments were executed as described in detail in Roybal et al. (2015b). Briefly, Tg4WT or Tg4KO CD4+ T cells and peptide-loaded PL8s were centrifuged together for 30 s at 350 g to synchronize cell coupling, the cell pellet was immediately resuspended to minimize unspecific cell coupling and cellular deformation and the cell suspension was further incubated at 37 degree C. After 2 and 5 min for early and late time points, respectively, the cell suspension was high pressure frozen and freeze substituted to Epon. Ultrathin sections were analyzed in an FEI Tecnai12 BioTwin equipped with a bottom-mount 4*4K EAGLE CCD camera. T cell:APC couples were identified in electron micrographs through their wide cellular interface. As described in detail in Roybal et al. (2015b), the time point assignment of cell couples was filtered with morphological criteria post acquisition using the presence of a uropod and T cell elongation.

Statistical methods

No statistical methods were used to predetermine the sample size. The significance of pairwise comparisons was measured by Student’s t-test. Where multiple comparisons were made, significance was determined by ANOVA with Tukey correction. The statistical significance in differences in percentage occurrence was calculated with a proportions z-test.

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    Notch activity influences the alphabeta versus gammadelta T cell lineage decision
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Decision letter

  1. Michael L Dustin
    Reviewing Editor; University of Oxford, United Kingdom

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "PKCθ links proximal T cell and Notch signaling through localized regulation of the actin cytoskeleton" for consideration by eLife. Your article has been favorably evaluated by Tadatsugu Taniguchi (Senior Editor) and three reviewers, one of whom, Michael L Dustin (Reviewer #1), is a member of our Board of Reviewing Editors. The following individual involved in review of your submission has agreed to reveal their identity: Bernard Malissen (Reviewer #2).

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:

Tg4 CD4+ T cells isolated from Tg4 mice that are deprived of the serine-threonine kinase PKCq and were injected 18 h previously with the Tg4 cognate antigen showed a reduction in intracellular Notch1 expression as compared to Tg4 CD4+ T cells isolated from WT mice. A finding further confirmed by analysis of Notch1-dependent hes1 expression. There is a concern regarding the level of Hes1 activation in relation to cells that utilise bona fide ligand dependent Notch signalling, such as thymocytes, and using thymocytes from the same mouse strains as positive controls would be helpful to put this in perspective. Following CD3 + CD28 stimulation for 18 hours, naive CD4+ T cells from B10.PL mice deprived of PKCq showed reduced Notch1 cleavage. This cleavage occurred within a time frame compatible with TCR signalling. T cell proliferation, CD69 and c-Myc upregulation and Th17 development were defective in Tg4KO T cells whereas IL-2 and Th1 cell differentiation were unaffected. Importantly, constitutive activation of Notch in Tg4KO cells restored T cell proliferation and Th17 cell differentiation. The authors admit that this is an over-expression experiment, but it would be helpful to see the level of expression, normalised to cell number, for early DN thymocytes, mature T cells undergoing activation and the retrovirally transduced cells. Visualization of ADAM10 at the T cell-APC interface showed that it was recruited rapidly and transiently to interfaces involving of Tg4WT T cells but not Tg4KO T cells. Therefore, the actin-dependent (Jasplakinolide sensitive) early recruitment of ADAM10 to the T cell-APC interface likely contributes to efficient Notch1 activation downstream of PKC There is a concern as to how jJasplakinolide, a non-specific F-actin stabilizer, can be used in this manner without inhibiting synapse formation – it would be useful to see titration data to better understand the degree to which the width of the optimum Jasplakinolide concentration for this effect θ. Treating Tg4WT T cells with PMA and Calyculin A – a phosphatase inhibitor – resulted in PKCq-dependent Coronin1A phosphorylation. There was a concern that a Calyculin A alone condition was not shown and whether or not PMA is required to see the increase phosphorylation. This gel shown is also sub-optimal due to artefacts and repeating this with the additional condition will also provide an opportunity to improve the quality of the data. This led the authors to propose that PKCθq enhances T cell actin dynamics through co-localization with and phosphorylation of the negative actin regulator Coronin1A, thereby mediating actin-based recruitment of ADAM10 to the T cell-APC interface and efficient Notch activation.

I do not have any specific concerns. The data are solid and the proposed model interesting in that it concurs to integrate the TCR-CD28 signaling pathways with the Notch pathway. As shown by the authors this is of biological relevance since impairment of such integrated loop affects Th17 differentiation. Importantly those studies were performed in primary T cells and not transformed T cells.

Overall, the model is interesting and some of the data are generally convincing, but the series of experiments is marred by use of different time points without explanation. Further explanation of these choices and how this relates to the operation of the proposed mechanism in the line of T-APC interaction would strengthen the work.

Essential revisions:

1) Provide data on Notch ICD and Hes1 levels in mature T cells undergoing activation, DN thymocytes, which are known to use the pathway and show clear Hes1 signatures in public data, and the NICD over-expressing cells used later on. This data could be supplemental, its significance should be clearly discussed.

2) In relation to evidence for CoroninA phosphorylation by PKCtheta, it is a concern that the calyculin A alone condition is omitted. The authors should repeat the experiment with this condition included. How would the authors interpret the result if PMA is not needed to see the effect? The gel shown is also suboptimal and an effort should be made in this new experiment to reduce artefacts that make the interpretation ambiguous.

3) To test whether ADAM10 recruitment to the synapse is mediated by PKC-theta dependent actin changes, they use Jasplakinolide. But this drug would also be expected to impair synapse formation by stabilising F-actin which is then collapsed by myosin II based contractility. Its assumed that this rescue effect is seen only in a narrow range of Jasplakinolide concentrations to semiselectively counteract the loss of CoroninA inhibition. The authors should show a Jasplakinolide titration to clarify this and also it would be helpful to see the total F-actin at each point to understand that nature of this effect. Otherwise it’s hard to understand how a saturating concentration of Jasplakinolide would accomplish the desired effect. The authors could discuss if there is any reason to expect that Jasplakinolide would specifically counteract CoroninA function.

4) The mix of time scales from minutes to hours to days makes it difficult to parse out exactly the kinetics of the mechanism. The authors need to provide a rationale for these timings and how these relate to T-APC interaction time lines that are established in the literature. When is this effect most important?

https://doi.org/10.7554/eLife.20003.019

Author response

Essential revisions:

1) Provide data on Notch ICD and Hes1 levels in mature T cells undergoing activation, DN thymocytes, which are known to use the pathway and show clear Hes1 signatures in public data, and the NICD over-expressing cells used later on. This data could be supplemental, its significance should be clearly discussed.

Reviewers requested the inclusion of supplementary data on Notch ICD and Hes1 levels in mature T cells, undergoing activation, in relation to DN thymocytes and cells overexpressing NICD following retroviral transduction. Figure 1—figure supplement 1A and B present data representing 4 experiments in which the influence of T cell activation on Notch ICD (NICD) expression was compared in DN thymocytes, naïve and previously primed T cells from Tg4 mice. NICD levels are constitutively high in DN thymocytes and barely affected by cell activation with anti-CD3 antibodies, presumably because DN thymocytes are either CD3 low or negative. Naïve T cells upregulate NICD on activation while this is less evident in previously primed Tg4 cells. Hes 1 gene expression is a downstream consequence of the generation of NICD; therefore, we focused on NICD generation as the direct readout for our supplementary experiments. Figure 1—figure supplement 1C and D reveal levels of NICD expressed following retroviral transduction of Tg4 T cells. Clearly, retroviral transduction generates cells with high levels of NICD reproducibly.

2) In relation to evidence for CoroninA phosphorylation by PKCtheta, it is a concern that the calyculin A alone condition is omitted. The authors should repeat the experiment with this condition included. How would the authors interpret the result if PMA is not needed to see the effect? The gel shown is also suboptimal and an effort should be made in this new experiment to reduce artefacts that make the interpretation ambiguous.

The Coronin 1A phosphorylation data has been repeated to provide clearer primary data and to include further controls. Data shown in Figure 4 reveals that cell activation with PMA leads to phosphorylation of Coronin 1A; however, this is only observed in samples treated with the phosphatase inhibitor Calyculin A. Treatment of cells with Calyculin A alone was without effect. Notably, Coronin 1A phosphorylation observed in WT Tg4 cells was markedly diminished in CD4+ T cells from PKCθ knockout mice (Figure 4C and D).

3) To test whether ADAM10 recruitment to the synapse is mediated by PKC-theta dependent actin changes, they use Jasplakinolide. But this drug would also be expected to impair synapse formation by stabilising F-actin which is then collapsed by myosin II based contractility. Its assumed that this rescue effect is seen only in a narrow range of Jasplakinolide concentrations to semiselectively counteract the loss of CoroninA inhibition. The authors should show a Jasplakinolide titration to clarify this and also it would be helpful to see the total F-actin at each point to understand that nature of this effect. Otherwise it’s hard to understand how a saturating concentration of Jasplakinolide would accomplish the desired effect. The authors could discuss if there is any reason to expect that Jasplakinolide would specifically counteract CoroninA function.

Reviewers have requested further data showing titration of the Jasplakinolide drug. As previously communicated with the editorial office, Christoph Wülfing and colleagues recently published a paper in which they conducted a titration of this drug using similar TCR transgenic T cells (5CC7). This paper (Roybal et al. PLOS ONE 10 (8) e0133231) addresses the questions raised by the reviewer. Furthermore, we have shown that 5CC7 and Tg4, the TCR transgenic used in this study, behave identically in cell coupling assays when treated with the drug. The cell coupling-frequencies of Jasplakinolide-treated Tg4 cells, shown relative to 5CC7, are added in the text and are displayed in Figure 3—figure supplement 1B. The relevance of the comparative data is referred to in the legend to Figure 3—figure supplement 1B. In summary, the cell coupling data shown in this figure establish that Tg4 and 5C.C7 T cells respond comparably to increasing concentrations of Jasplakinolide. The extensive characterization of the effect of 40 nM Jasplakinolide on T cell actin dynamics in (Roybal et al., 2015a) therefore applies to the Tg4WT T cells.

4) The mix of time scales from minutes to hours to days makes it difficult to parse out exactly the kinetics of the mechanism. The authors need to provide a rationale for these timings and how these relate to T-APC interaction time lines that are established in the literature. When is this effect most important?

The reviewers have asked us to discuss the mix of time scales from minutes to hours to days. We have included a short paragraph at the end of the paper that emphasises how signalling events of relatively short duration lead to longer-term cellular changes. The extremely rapid signalling events taking place at the immune synapse are best revealed by the type of spatio-temporal analysis used in this paper. Longer-term changes in cell function i.e. cell activation, surface phenotype, cytokine production require medium term analysis, on the scale of hours, while changes in cell differentiation require days to be observed. We have defined the role of PKCθ on such cellular events using techniques that are appropriate for the time scale of the specific event.

https://doi.org/10.7554/eLife.20003.020

Article and author information

Author details

  1. Graham J Britton

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    GJB, Conceptualization, Data curation, Formal analysis, Investigation, Writing—original draft, Writing—review and editing
    Competing interests
    The authors declare that no competing interests exist.
  2. Rachel Ambler

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    RA, Investigation
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0002-6647-4116
  3. Danielle J Clark

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    DJC, Methodology
    Competing interests
    The authors declare that no competing interests exist.
  4. Elaine V Hill

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    EVH, Investigation
    Competing interests
    The authors declare that no competing interests exist.
  5. Helen M Tunbridge

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    HMT, Investigation
    Competing interests
    The authors declare that no competing interests exist.
  6. Kerrie E McNally

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    KEM, Investigation
    Competing interests
    The authors declare that no competing interests exist.
  7. Bronwen R Burton

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    BRB, Investigation
    Competing interests
    The authors declare that no competing interests exist.
  8. Philomena Butterweck

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    PB, Investigation
    Competing interests
    The authors declare that no competing interests exist.
  9. Catherine Sabatos-Peyton

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    CS-P, Conceptualization, Supervision
    Competing interests
    The authors declare that no competing interests exist.
  10. Lea A Hampton-O’Neil

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    LAH-O’N, Investigation
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0002-9665-170X
  11. Paul Verkade

    1. School of Biochemistry, University of Bristol, Bristol, United Kingdom
    Contribution
    PV, Investigation, Methodology
    Competing interests
    The authors declare that no competing interests exist.
  12. Christoph Wülfing

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Contribution
    CW, Conceptualization, Data curation, Formal analysis, Supervision, Funding acquisition, Investigation, Methodology, Writing—original draft, Project administration, Writing—review and editing
    Contributed equally with
    David Cameron Wraith
    For correspondence
    1. Christoph.Wuelfing@bristol.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0002-6156-9861
  13. David Cameron Wraith

    1. School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom
    Present address
    1. Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, United Kingdom
    Contribution
    DCW, Conceptualization, Formal analysis, Supervision, Funding acquisition, Methodology, Writing—original draft, Project administration
    Contributed equally with
    Christoph Wülfing
    For correspondence
    1. d.wraith@bham.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0003-2147-5614

Funding

Wellcome Trust (086779/Z/08/A)

  • Graham J Britton

Wellcome Trust (102387/Z/13/Z)

  • Rachel Ambler
  • Helen M Tunbridge
  • Kerrie E McNally
  • Lea A Hampton-O’Neil

University of Bristol (PhD studentship)

  • Danielle J Clark

Wellcome Trust (091074/Z/09/Z)

  • Elaine V Hill
  • David Cameron Wraith

Multiple Sclerosis Society (900/08)

  • Catherine Sabatos-Peyton

European Research Council (PCIG-GA-2012-321554)

  • Christoph Wülfing

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

Acknowledgements

GJB was supported by the Wellcome Trust Dynamic Cell Biology programme grant 086779/Z/08/A RA, HMT, KEM, LAH were supported by the Wellcome Trust Dynamic Cell Biology programme grant 102387/Z/13/Z DJC was supported by a University of Bristol PhD studentship CSP was supported by a senior research fellowship from the Multiple Sclerosis Society CW was supported by the ERC grant PCIG-GA-2012–321554 DW was supported by a Wellcome Trust Programme Grant 091074/Z/09/Z We acknowledge the MRC, the Wolfson Foundation and the University of Bristol for supporting the Wolfson Bioimaging Facility. We thank Alan Leard and Dr Katy Jepson for microscopy support, Dr Andrew Herman and the University of Bristol Flow Cytometry Facility for cell sorting and analysis and Ella Sheppard, Louise Falk and Anna Lewis for technical support.

Ethics

Animal experimentation: All animal experiments were carried out under the UK Home Office Project Licence number 30/2705 held by David Wraith and the study was approved by the University of Bristol ethical review committee.

Reviewing Editor

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

Publication history

  1. Received: July 24, 2016
  2. Accepted: January 22, 2017
  3. Accepted Manuscript published: January 23, 2017 (version 1)
  4. Accepted Manuscript updated: January 31, 2017 (version 2)
  5. Version of Record published: February 15, 2017 (version 3)
  6. Version of Record updated: April 5, 2017 (version 4)

Copyright

© 2017, Britton 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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