Arp2/3 complex-driven spatial patterning of the BCR enhances immune synapse formation, BCR signaling and B cell activation

The binding of membrane-bound ligands to their receptors can initiate multiscale spatial reorganization of receptors and their signal transduction machinery. This presumably optimizes receptor signaling and is often driven by remodeling of the cortical cytoskeleton. The formation of an immune synapse between a lymphocyte and an antigen-presenting cell (APC) is an excellent model for studying the dynamic changes in receptor and cytoskeleton organization that occur during cell-cell interactions and how they impact cellular activation (Dustin and Groves, 2012; Harwood and Batista, 2010; Harwood and Batista, 2011; Song et al., 2014). B lymphocytes play a critical role in health and disease by producing antibodies and cytokines. Although B cells can be activated by the binding of soluble antigens (Ags) to the B cell receptor (BCR), APCs that capture and concentrate Ags are potent activators of B cells (Batista and Harwood, 2009).

The immune synapse is a transient and highly dynamic structure that is characterized by a rapidly evolving reorganization of plasma membrane components and signaling proteins. When B cells encounter Ag on the surface of an APC, BCRs undergo rapid actin-dependent spatial reorganization that amplifies BCR signaling (Harwood and Batista, 2010) and reduces the amount of Ag required for B cell activation (Batista et al., 2001; Depoil et al., 2008; Weber et al., 2008). Initial BCR signaling induces localized actin severing and transiently uncouples the cortical cytoskeleton from the plasma membrane (Freeman et al., 2011; Gupta et al., 2006; Treanor et al., 2011). These changes allow for increased mobility of BCRs within the plasma membrane and enable the formation of BCR microclusters that are initially distributed throughout the B cell-APC contact site (Batista et al., 2001; Depoil et al., 2008). Because BCR signaling output depends on BCR-BCR interactions, microcluster formation amplifies BCR signaling. BCR clustering leads to phosphorylation of the CD79a/b (Ig-$\alpha$/$\beta$) signaling subunit of the BCR (Abraham et al., 2016; Dal Porto et al., 2004). This allows recruitment of the Syk tyrosine kinase to the BCR, which nucleates the formation of a ‘microsignalosome’, a microcluster-based signaling complex that includes the Btk tyrosine kinase, phospholipase Cγ2 (PLCγ2), and phosphoinositide 3-kinase (PI3K) (Treanor et al., 2009; Weber et al., 2008). BCR signaling stimulates actin polymerization at the periphery of the B cell-APC contact site (Fleire et al., 2006), which exerts outward force on the plasma membrane to generate membrane protrusions (Mogilner and Oster, 1996). This allows the B cell to scan the APC surface for additional Ag, resulting in further BCR microcluster formation and enhancement of BCR signaling (Fleire et al., 2006; Weber et al., 2008).

Subsequent retraction of the B cell membrane is accompanied by the centripetal movement of BCR-Ag microclusters, which coalesce to form the characteristic central supramolecular activation complex (cSMAC) of an immune synapse (Fleire et al., 2006). BCR-mediated extraction of Ag from the APC membrane, which allows B cells to present Ags and elicit T cell help, occurs at the cSMAC in naive B cells (Nowosad et al., 2016; Yuseff et al., 2013). In T cells, centripetal (i.e. retrograde) actin flow is a driving force for T cell receptor (TCR) microcluster centralization and cSMAC formation (Babich et al., 2012; Hammer and Burkhardt, 2013; Yi et al., 2012). As new actin is polymerized at the cell periphery, the elastic resistance of the plasma membrane causes the peripheral actin network to flow toward the center of the synapse (Ponti et al., 2004). Actin dynamics are required for cSMAC formation in B cells (Liu et al., 2012; Treanor et al., 2011) but a role for actin retrograde flow has not been established.

Although the actin-dependent formation, movement, and spatial organization of BCR micoclusters are critical for APC-induced B cell activation, the molecular mechanisms that orchestrate this process are not fully understood. Actin organization and dynamics are controlled by a large network of actin-regulatory proteins (Bezanilla et al., 2015; Chhabra and Higgs, 2007; Michelot and Drubin, 2011; Tolar, 2017). There are two main modes of actin polymerization (Pollard, 2007). Formin-mediated linear actin polymerization, which is controlled by the RhoA GTPase, generates thin membrane protrusions such as filopodia (Mattila and Lappalainen, 2008). Alternatively, branched actin polymerization is mediated by the 7-subunit actin-related protein (Arp) 2/3 complex, which binds to existing actin filaments and nucleates new filaments that grow at a 70° angle from the mother filament (Goley and Welch, 2006). Receptor-induced activation of the Cdc42 and Rac GTPases causes conformational changes in nucleation-promoting factors (NPFs) belonging to the Wiskott-Aldrich Syndrome protein (WASp) family, which allows them to activate the Arp2/3 complex (Rotty et al., 2013). The Arp2/3 complex nucleates the branched actin networks that underlie the formation of sheet-like membrane protrusions such as lamellipodia (Pollard and Borisy, 2003). The peripheral actin network at the T cell immune synapse resembles that of the lamellipodia of migrating cells (Dustin, 2007; Dustin and Cooper, 2000).

A key role for the Arp2/3 complex in T and B cells is suggested by the dysregulated lymphocyte function in patients with Wiskott-Aldrich Syndrome (WAS). WAS is caused by mutations in either WASp or WASp-interacting protein (WIP) (Candotti, 2018) and is characterized by increased susceptibility to autoimmune disease, recurring infections, and predisposition to lymphomas and leukemias. In B cells, the WASp and N-WASP NPFs, as well as WIP, regulate actin dynamics and BCR signaling at the immune synapse (Keppler et al., 2015; Liu et al., 2013; Liu et al., 2011; Westerberg et al., 2010). Although WASp and N-WASP act upstream of the Arp2/3 complex, the role of Arp2/3 complex-dependent actin dynamics in B cell immune synapse formation and function has not been investigated.

B cell immune synapse formation was first demonstrated in the context of B cell-APC interactions (Batista et al., 2001). However, most subsequent studies have employed Ags that are attached to artificial planar lipid bilayers or to the cytoplasmic face of plasma membrane sheets in order to facilitate imaging of the contact site. We have developed systems for imaging APC-induced B cell immune synapse formation in real time (Wang et al., 2018) and now use this approach to investigate the role of Arp2/3 complex-dependent actin dynamics in B cell immune synapse formation and function. Here, we show that B cells interacting with live, intact APCs form BCR-Ag microclusters within dynamic actin-rich membrane protrusions that are dependent on the Arp2/3 complex. The coalescence of BCR-Ag microclusters into a cSMAC is also dependent on the dynamic branched actin networks that are nucleated by the Arp2/3 complex. Importantly, we show that Arp2/3 complex activity amplifies BCR signaling and is required for maximal B cell activation and proliferation.

Using high spatiotemporal resolution imaging of actin in B cells interacting with APCs, we observed that B cells scan the surface of the APC using complex and dynamic actin-rich protrusions that constantly extend and retract across the APC surface. This dynamic probing is mediated by Arp2/3 complex activity, which also generates retrograde actin flow that facilitates the initial centripetal movement of BCR microclusters and is required for cSMAC formation. Importantly, these Arp2/3 complex-dependent processes amplify proximal and distal BCR signaling, transcriptional responses, and B cell proliferation in response to APC-bound Ag.

In contrast to the highly dynamic lamellipodia and filopodia that B cells extend asymmetrically over the APC surface, the actin-rich protrusions that B and T cells form when they spread on Ag-bearing lipid bilayers (Fleire et al., 2006; Murugesan et al., 2016) or Ag-coated coverslips (Bunnell et al., 2001; Freeman et al., 2011) are predominantly symmetrical, sheet-like lamellipodia. This difference in spreading and probing behavior may reflect the physical properties of the Ag-bearing substrate. In fibroblasts and epithelial cells, stiffer substrates favor Rac1- and Arp2/3 complex-dependent formation of lamellipodia, whereas softer substrates favor Cdc42- and formin-dependent formation of filopodia (Collins et al., 2017; Wong et al., 2014). The greater prevalence of filopodia when B cells spread on APCs, compared to artificial lipid bilayers, is consistent with the finding that the APC membrane is less stiff than the artificial lipid bilayers that have been used to mimic APCs (Natkanski et al., 2013). Whether local variations in the stiffness of the APC membrane shape B cell probing behavior is not known. However, the membranes of FDCs and dendritic cells differ in their stiffness (Spillane and Tolar, 2017) and this could impact the type of probing behavior that B cells use to scan the surface of these APCs.

The filopodia-like structures formed by control B cells interacting with APCs allowed the formation of BCR-Ag microclusters at sites distant from the cell body. Branched actin networks that were nucleated around these linear protrusions then encased the BCR-Ag microclusters and generated centripetal flow that was required for BCR-Ag microcluster centralization. When the Arp2/3 complex was inhibited, lamellipodial branched actin protrusions were not generated in response to either APC-bound Ag or anti-Ig-coated coverslips, and instead the formation of filopodia was greatly enhanced. This is consistent with the idea that the Arp2/3 complex and formins compete for a limited pool of actin monomers (Suarez and Kovar, 2016). In B cells in which the Arp2/3 complex was inhibited, the filopodia that formed were able to extend over the surface of the APC and gather Ag into microclusters. However, these filopodia and their associated BCR-Ag microclusters, were not efficiently retracted toward the cell body.

We showed that Arp2/3 complex-dependent branched actin nucleation is essential for actin retrograde flow at the cell periphery and is required for BCR-Ag microcluster centralization and cSMAC formation. In T cells, both pushing forces generated by actin retrograde flow and contractile forces generated by actomyosin arcs have been shown to drive the centripetal movement of TCR microclusters to form a cSMAC (Babich et al., 2012; Ilani et al., 2009; Jacobelli et al., 2004; Kumari et al., 2012; Murugesan et al., 2016; Yi et al., 2012). In B cells spreading on anti-Ig-coated coverslips, we observed that similar actomyosin arcs formed at the inner face of the peripheral ring of branched actin. Consistent with the idea that these linear actin arcs are generated by formins, these structures appeared to form in B cells in which the Arp2/3 complex was inhibited, as has been observed in T cells (Murugesan et al., 2016). Myosin IIA is important for B cells to extract Ags from APC membranes (Hoogeboom et al., 2018; Natkanski et al., 2013) and has been implicated in BCR microcluster centralization (Tolar, 2017). However, inhibition of myosin IIA did not affect cSMAC formation or the upregulation of B activation markers in our system. Although this does not rule out a role for myosin in B cell immune synapse formation and APC-induced B cell activation, it highlights that the Arp2/3 complex has a more important role in these processes, at least in our experimental system.

TCR microcluster centralization and cSMAC formation in T cells has been proposed to involve three cytoskeleton-dependent mechanisms that act sequentially: actin retrograde flow, actomyosin contraction, and movement along microtubules that span the actin-poor central region of the immune synapse (Kumari et al., 2014). Dynein-dependent movement of BCR and TCR microclusters along juxtamembrane microtubules is required for cSMAC formation in both B and T cells (Hashimoto-Tane et al., 2011; Schnyder et al., 2011). We have shown that the formation of branched actin at the periphery of the immune synapse is required for capturing the plus ends of microtubules and for moving the microtubule network toward the Ag-presenting surface (Wang et al., 2017). In B cells spreading on anti-Ig-coated coverslips, microtubule plus end binding proteins contact the inner face of the dense peripheral actin ring, which is depleted of microtubules, much like the leading edge of a migrating cell. Hence, initial microcluster centralization mediated by Arp2/3 complex-dependent actin retrograde flow may be required for BCR microclusters to associate with microtubules and coalesce into a cSMAC at the center of the immune synapse. Thus, inhibiting Arp2/3 complex activity may block a critical initial step in BCR-Ag microcluster centralization and prevent the microtubule-based centralization that leads to cSMAC formation, the site where Ags are often internalized.

We showed that Arp2/3 complex activity amplifies BCR signaling in response to APC-bound Ags. The molecular mechanisms by which the actin cytoskeleton regulates Ag receptor signaling are still being explored. In T cells, actin retrograde flow is important for sustained TCR signaling in response to Ag-bearing artificial lipid bilayers (Babich et al., 2012; Kumari et al., 2015). Because the TCR is a mechanosensitive receptor, actin retrograde flow could exert tension on the TCR that enhances its signaling (Basu and Huse, 2017). The BCR is also highly sensitive to mechanical force, such that increasing the stiffness of Ag-presenting surfaces causes greater recruitment of Syk and other signaling components (Wan et al., 2013; Wan et al., 2015). Hence, Arp2/3 complex-dependent actin retrograde flow could increase the mechanical tension on Ag-bound BCRs and enhance their signaling. Consistent with this idea, we observed that peak BCR signaling occurred during the first 5 min of APC encounter, when BCR-Ag microclusters are undergoing the greatest centripetal movement.

BCR signaling is enhanced by the formation of large and stable microclusters, which is dependent on Ag mobility and the actin cytoskeleton (Ketchum et al., 2014). In control B cells, microcluster size increased most rapidly between 2 and 6 min after the B cells were added to the APCs, which corresponds with the peak of proximal BCR signaling. Inhibition of the Arp2/3 complex decreased both microcluster merge events and BCR signaling, consistent with the idea that actin-dependent microcluster aggregation enhances BCR signaling. Microcluster growth may increase the frequency at which Ag-bound BCRs that have recruited Syk can trap BCRs that are not bound to Ag, and activate them via Syk-mediated phosphorylation. Alternatively, larger microclusters may more efficiently shield activated BCRs from negative regulators such as CD22 (Gasparrini et al., 2016).

Arp2/3 complex-dependent actin polymerization could also enhance BCR signaling by maintaining the integrity of the BCR-Ag microclusters and by acting as a platform for the assembly of signaling complexes. We observed that BCR-Ag microclusters were surrounded by actin cages. The idea that these cages maintain the integrity of BCR microclusters is supported by the finding that microclusters become more diffuse when B cells are treated with the actin-depolymerizing drug latrunculin A (Treanor et al., 2011). In T cells, signaling proteins such as PLCγ1 accumulate at actin foci that surround TCR microclusters (Kumari et al., 2015). Deletion of WASp or inhibition of the Arp2/3 complex has no effect on proximal TCR signaling or microcluster formation but results in impaired recruitment and activation of PLCγ1 (Kumari et al., 2015). Whether Arp2/3 complex-dependent actin structures surrounding BCR microclusters act as scaffolds that amplify and diversify BCR signaling remains to be determined.

Although Ag-induced actin reorganization enhances BCR signaling, the submembrane actin cytoskeleton limits the lateral mobility of the BCR in resting B cells and thereby prevents spontaneous BCR signaling. Indeed, disrupting the actin cytoskeleton with latrunculin A is sufficient to induce robust Ag-independent BCR signaling (Treanor et al., 2010). We found that inhibiting Arp2/3 complex activity in resting primary B cells resulted in increased basal levels of pERK and pAkt, and that this correlated with increased lateral mobility of both IgM-BCRs and IgD-BCRs within the plasma membrane. Hence, Arp2/3 complex-mediated actin polymerization is also important for maintaining the quiescent state of resting B cells and for preventing aberrant Ag-independent BCR signaling.

We also showed that Arp2/3 complex activity enhances functional interactions between the BCR and its co-receptor CD19. Ag binding promotes the tyrosine phosphorylation of CD19, allowing it to recruit key effectors of BCR signaling such as PI3K and Vav. CD19 associates with the Lyn tyrosine kinase, which can phosphorylate the CD79a/b signaling subunit of the BCR, and has also been reported to enhance recruitment of the Syk and Btk tyrosine kinases to the BCR (Depoil et al., 2008; Fujimoto et al., 2000; Fujimoto et al., 2002). Hence, the interaction of the BCR with CD19 facilitates processive signaling reactions that amplify BCR signaling. We found that inhibiting the Arp2/3 complex resulted in decreased CD19 phosphorylation, as well as reduced overlap between BCR-Ag clusters and pCD19 clusters, at 3 min after the initiating B cell-APC contact. By 5 min, the differences between CK-666-treated B cells and control cells were smaller. Hence, inhibiting the Arp2/3 complex reduces and delays initial Ag-induced BCR-CD19 interactions. Initial BCR-CD19 interactions are dependent on the immobilization of CD19 by the tetraspanin network (Mattila et al., 2013). We found that inhibiting Arp2/3 complex-dependent actin polymerization increased the lateral mobility of CD19 within the plasma membrane, suggesting that branched actin structures also restrain its mobility. This increased mobility of CD19 may decrease the initial rate at which productive BCR-CD19 collisions occur.

Although inhibiting the Arp2/3 complex significantly reduced proximal BCR signaling during the first 5 min of B cell-APC encounter, a key question was whether this would translate into decreased B cell activation. Indeed, CK-666 treatment reduced the ability of Ag-bearing APCs to stimulate a transcriptional response at 3 hr, activation marker upregulation at 18 hr, and B cell proliferation at 72 hr. Importantly, we found that adding CK-666 to B cells shortly after they had engaged APCs did not impair the upregulation of B cell activation markers. As well, we found that Arp2/3 complex activity was not required for the upregulation of activation markers in response to PMA plus ionomycin, stimuli that bypass the BCR but initiate many of the same downstream signaling reactions. Taken together, these findings support the idea that Arp2/3 complex-dependent effects on BCR-Ag microclusters that occur within the first few minutes of B cell-APC interactions amplify initial BCR signaling reactions that are translated into B cell responses that occur up to 3 days later.

Consistent with our findings that Arp2/3 complex activity regulates both tonic BCR signaling and APC-induced B cell activation, upstream activators of the Arp2/3 complex are important regulators of B cell activation. Murine B cells lacking WASp, an NPF that activates the Arp2/3 complex, exhibit reduced cell spreading, BCR-Ag microcluster formation, and BCR-induced tyrosine phosphorylation in response to Ag-bearing lipid bilayers (Liu et al., 2011). The WASp-interacting protein WIP regulates the activity and subcellular distribution of WASp, and also stabilizes existing actin filaments. Murine B cells lacking WIP have defective CD19-mediated PI3K signaling and antibody responses (Keppler et al., 2015). WASp activation is regulated by the Cdc42 GTPase and B-cell-specific loss of Cdc42 results in aberrant actin organization, diminished BCR signaling, and a severe impairment in antibody production (Burbage et al., 2015).

In line with its central role in many aspects of B cell function, human mutations that impair the activation Arp2/3 complex result in disease. Mutations in WASp or WIP result in Wiskott-Aldrich syndrome, an X-linked immunodeficiency disorder (Candotti, 2018). Similarly, missense mutations in the ARPC1B gene have recently been described as causing a Wiskott-Aldrich syndrome-like disease (Kahr et al., 2017). Although Wiskott-Aldrich syndrome is associated with increased susceptibility to infections, many patients also develop autoimmunity and B-cell malignancies (Candotti, 2018). Our finding that the loss of Arp2/3 complex activity in B cells results in increased tonic BCR signaling but impaired APC-induced B cell activation may help explain this paradox.

Custom image analysis scripts are available online at https://github.com/madscience12/FIJImacros (copy archived at https://github.com/elifesciences-publications/FIJImacros) and https://bitbucket.org/jscurll/bolger-munro_image_analysis_scripts/src (copy archived at https://github.com/elifesciences-publications/Bolger-Munro_image_analysis_scripts).

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Author details

1. Madison Bolger-Munro

   1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
   2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing, Designed and performed the majority of the experiments, Analyzed data, Wrote the manuscript

   For correspondence

   mbolgerm@mail.ubc.ca

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8176-4824

2. Kate Choi

   1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
   2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada

   Contribution

   Investigation, Writing—review and editing, Designed, performed, and analyzed experiments

   Competing interests

   No competing interests declared

3. Joshua M Scurll

   Department of Mathematics, Institute of Applied Mathematics, University of British Columbia, Vancouver, Canada

   Contribution

   Data curation, Software, Formal analysis, Validation, Methodology, Generated image analysis scripts, Performed data analysis

   Competing interests

   No competing interests declared

4. Libin Abraham

   1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
   2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada
   3. Department of Mathematics, Institute of Applied Mathematics, University of British Columbia, Vancouver, Canada

   Contribution

   Conceptualization, Formal analysis, Investigation, Visualization, Designed, performed, and analyzed experiments

   Competing interests

   No competing interests declared

5. Rhys S Chappell

   Department of Mathematics, Institute of Applied Mathematics, University of British Columbia, Vancouver, Canada

   Contribution

   Software, Generated image analysis scripts, Performed data analysis

   Competing interests

   No competing interests declared

6. Duke Sheen

   1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
   2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada

   Contribution

   Investigation, Designed, generated, and validated essential reagents

   Competing interests

   No competing interests declared

7. May Dang-Lawson

   1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
   2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada

   Contribution

   Investigation, Designed, generated, and validated essential reagents

   Competing interests

   No competing interests declared

8. Xufeng Wu

   Cell Biology and Physiology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States

   Contribution

   Investigation, Provided critical support for experimental set-up and data acquisition using the Zeiss Airyscan and instant structured illumination microscopes

   Competing interests

   No competing interests declared

9. John J Priatel

   1. Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada
   2. BC Children’s Hospital Research Institute, Vancouver, Canada

   Contribution

   Resources, Provided the Nur77GFP mice, Commented on the manuscript

   Competing interests

   No competing interests declared

10. Daniel Coombs

    Department of Mathematics, Institute of Applied Mathematics, University of British Columbia, Vancouver, Canada

    Contribution

    Resources, Software, Funding acquisition, Methodology, Provided advice on quantitative image analysis

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8038-6278

11. John A Hammer

    Cell Biology and Physiology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States

    Contribution

    Resources, Methodology, Project administration, Helped design experiments and interpret data

    Competing interests

    No competing interests declared

12. Michael R Gold

    1. Department of Microbiology and Immunology, University of British Columbia, Vancouver, Canada
    2. Life Sciences Institute, I3 Research Group, University of British Columbia, Vancouver, Canada

    Contribution

    Conceptualization, Supervision, Funding acquisition, Validation, Visualization, Writing—original draft, Project administration, Writing—review and editing, Analyzed data, Wrote the manuscript

    For correspondence

    mgold@mail.ubc.ca

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-1222-3191

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