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).

1. 1. Bolger-Munro M
   2. Choi K
   3. Scurll JM
   4. Abraham L
   5. Chappell R
   6. Sheen D
   7. Dang-Lawson M
   8. Wu X
   9. Priatel JJ
   10. Coombs D
   11. Hammer JA
   12. Gold MR

   (2019) Dryad Digital Repository

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

   https://doi.org/10.5061/dryad.j1fd7

1. Book

   1. Abraham L
   2. Wang JC
   3. Bolger-Munro M
   4. Gold MR

   (2016) Structure, Function, and Spatial Organization of the B Cell Receptor

   In: Ratcliffe Michael J. H, editors. Encyclopedia of Immunobiology, 2. Academic Press. pp. 40–54.

   https://doi.org/10.1016/b978-0-12-374279-7.05005-0

   • Google Scholar
2. 1. Abraham L
   2. Lu HY
   3. Falcão RC
   4. Scurll J
   5. Jou T
   6. Irwin B
   7. Tafteh R
   8. Gold MR
   9. Coombs D

   (2017) Limitations of Qdot labelling compared to directly-conjugated probes for single particle tracking of B cell receptor mobility

   Scientific Reports 7:11379.

   https://doi.org/10.1038/s41598-017-11563-9

   • PubMed
   • Google Scholar
3. 1. Ait-Azzouzene D
   2. Verkoczy L
   3. Peters J
   4. Gavin A
   5. Skog P
   6. Vela JL
   7. Nemazee D

   (2005) An immunoglobulin C kappa-reactive single chain antibody fusion protein induces tolerance through receptor editing in a normal polyclonal immune system

   The Journal of Experimental Medicine 201:817–828.

   https://doi.org/10.1084/jem.20041854

   • PubMed
   • Google Scholar
4. 1. Babich A
   2. Li S
   3. O'Connor RS
   4. Milone MC
   5. Freedman BD
   6. Burkhardt JK

   (2012) F-actin polymerization and retrograde flow drive sustained PLCγ1 signaling during T cell activation

   The Journal of Cell Biology 197:775–787.

   https://doi.org/10.1083/jcb.201201018

   • PubMed
   • Google Scholar
5. 1. Basu R
   2. Huse M

   (2017) Mechanical communication at the immunological synapse

   Trends in Cell Biology 27:241–254.

   https://doi.org/10.1016/j.tcb.2016.10.005

   • PubMed
   • Google Scholar
6. 1. Batista FD
   2. Iber D
   3. Neuberger MS

   (2001) B cells acquire antigen from target cells after synapse formation

   Nature 411:489–494.

   https://doi.org/10.1038/35078099

   • PubMed
   • Google Scholar
7. 1. Batista FD
   2. Harwood NE

   (2009) The who, how and where of antigen presentation to B cells

   Nature Reviews Immunology 9:15–27.

   https://doi.org/10.1038/nri2454

   • PubMed
   • Google Scholar
8. 1. Batista FD
   2. Neuberger MS

   (1998) Affinity dependence of the B cell response to antigen: a threshold, a ceiling, and the importance of off-rate

   Immunity 8:751–759.

   https://doi.org/10.1016/S1074-7613(00)80580-4

   • PubMed
   • Google Scholar
9. 1. Berglund AJ

   (2010) Statistics of camera-based single-particle tracking

   Physical Review E 82:011917.

   https://doi.org/10.1103/PhysRevE.82.011917

   • Google Scholar
10. 1. Bezanilla M
    2. Gladfelter AS
    3. Kovar DR
    4. Lee WL

    (2015) Cytoskeletal dynamics: a view from the membrane

    The Journal of Cell Biology 209:329–337.

    https://doi.org/10.1083/jcb.201502062

    • PubMed
    • Google Scholar
11. Software

    1. Bolger-Munro M

    (2019) FIJI macros, version 313a653

    GitHub.

    https://github.com/madscience12/FIJImacros
12. 1. Buhl AM
    2. Pleiman CM
    3. Rickert RC
    4. Cambier JC

    (1997) Qualitative regulation of B cell antigen receptor signaling by CD19: selective requirement for PI3-kinase activation, inositol-1,4,5-trisphosphate production and Ca²⁺ mobilization

    The Journal of Experimental Medicine 186:1897–1910.

    https://doi.org/10.1084/jem.186.11.1897

    • PubMed
    • Google Scholar
13. 1. Bunnell SC
    2. Kapoor V
    3. Trible RP
    4. Zhang W
    5. Samelson LE

    (2001) Dynamic actin polymerization drives T cell receptor–induced spreading: A role for the signal transduction adaptor LAT

    Immunity 14:315–329.

    https://doi.org/10.1016/S1074-7613(01)00112-1

    • Google Scholar
14. 1. Burbage M
    2. Keppler SJ
    3. Gasparrini F
    4. Martínez-Martín N
    5. Gaya M
    6. Feest C
    7. Domart MC
    8. Brakebusch C
    9. Collinson L
    10. Bruckbauer A
    11. Batista FD

    (2015) Cdc42 is a key regulator of B cell differentiation and is required for antiviral humoral immunity

    The Journal of Experimental Medicine 212:53–72.

    https://doi.org/10.1084/jem.20141143

    • PubMed
    • Google Scholar
15. 1. Candotti F

    (2018) Clinical manifestations and pathophysiological mechanisms of the Wiskott-Aldrich syndrome

    Journal of Clinical Immunology 38:13–27.

    https://doi.org/10.1007/s10875-017-0453-z

    • PubMed
    • Google Scholar
16. 1. Chenouard N
    2. Bloch I
    3. Olivo-Marin JC

    (2013) Multiple hypothesis tracking for cluttered biological image sequences

    IEEE Transactions on Pattern Analysis and Machine Intelligence 35:2736–3750.

    https://doi.org/10.1109/TPAMI.2013.97

    • PubMed
    • Google Scholar
17. 1. Chenouard N
    2. Smal I
    3. de Chaumont F
    4. Maška M
    5. Sbalzarini IF
    6. Gong Y
    7. Cardinale J
    8. Carthel C
    9. Coraluppi S
    10. Winter M
    11. Cohen AR
    12. Godinez WJ
    13. Rohr K
    14. Kalaidzidis Y
    15. Liang L
    16. Duncan J
    17. Shen H
    18. Xu Y
    19. Magnusson KE
    20. Jaldén J
    21. Blau HM
    22. Paul-Gilloteaux P
    23. Roudot P
    24. Kervrann C
    25. Waharte F
    26. Tinevez JY
    27. Shorte SL
    28. Willemse J
    29. Celler K
    30. van Wezel GP
    31. Dan HW
    32. Tsai YS
    33. Ortiz de Solórzano C
    34. Olivo-Marin JC
    35. Meijering E

    (2014) Objective comparison of particle tracking methods

    Nature Methods 11:281–289.

    https://doi.org/10.1038/nmeth.2808

    • PubMed
    • Google Scholar
18. 1. Chhabra ES
    2. Higgs HN

    (2007) The many faces of actin: matching assembly factors with cellular structures

    Nature Cell Biology 9:1110–1121.

    https://doi.org/10.1038/ncb1007-1110

    • PubMed
    • Google Scholar
19. 1. Collins C
    2. Denisin AK
    3. Pruitt BL
    4. Nelson WJ

    (2017) Changes in E-cadherin rigidity sensing regulate cell adhesion

    PNAS 114:E5835–E5844.

    https://doi.org/10.1073/pnas.1618676114

    • PubMed
    • Google Scholar
20. 1. Dal Porto JM
    2. Gauld SB
    3. Merrell KT
    4. Mills D
    5. Pugh-Bernard AE
    6. Cambier J

    (2004) B cell antigen receptor signaling 101

    Molecular Immunology 41:599–613.

    https://doi.org/10.1016/j.molimm.2004.04.008

    • PubMed
    • Google Scholar
21. 1. de Chaumont F
    2. Dallongeville S
    3. Chenouard N
    4. Hervé N
    5. Pop S
    6. Provoost T
    7. Meas-Yedid V
    8. Pankajakshan P
    9. Lecomte T
    10. Le Montagner Y
    11. Lagache T
    12. Dufour A
    13. Olivo-Marin JC

    (2012) Icy: an open bioimage informatics platform for extended reproducible research

    Nature Methods 9:690–696.

    https://doi.org/10.1038/nmeth.2075

    • PubMed
    • Google Scholar
22. 1. DeFranco AL

    (1985)

    Separate control of B lymphocyte early activation and proliferation in response to anti-IgM antibodies

    Journal of Immunology 135:87–94.

    • PubMed
    • Google Scholar
23. 1. Depoil D
    2. Fleire S
    3. Treanor BL
    4. Weber M
    5. Harwood NE
    6. Marchbank KL
    7. Tybulewicz VL
    8. Batista FD

    (2008) CD19 is essential for B cell activation by promoting B cell receptor-antigen microcluster formation in response to membrane-bound ligand

    Nature Immunology 9:63–72.

    https://doi.org/10.1038/ni1547

    • PubMed
    • Google Scholar
24. 1. Dustin ML

    (2007) Cell adhesion molecules and actin cytoskeleton at immune synapses and kinapses

    Current Opinion in Cell Biology 19:529–533.

    https://doi.org/10.1016/j.ceb.2007.08.003

    • PubMed
    • Google Scholar
25. 1. Dustin ML
    2. Cooper JA

    (2000) The immunological synapse and the actin cytoskeleton: molecular hardware for T cell signaling

    Nature Immunology 1:23–29.

    https://doi.org/10.1038/76877

    • PubMed
    • Google Scholar
26. 1. Dustin ML
    2. Groves JT

    (2012) Receptor signaling clusters in the immune synapse

    Annual Review of Biophysics 41:543–556.

    https://doi.org/10.1146/annurev-biophys-042910-155238

    • PubMed
    • Google Scholar
27. 1. Ennomani H
    2. Letort G
    3. Guérin C
    4. Martiel J-L
    5. Cao W
    6. Nédélec F
    7. De La Cruz EM
    8. Théry M
    9. Blanchoin L

    (2016) Architecture and connectivity govern actin network contractility

    Current Biology 26:616–626.

    https://doi.org/10.1016/j.cub.2015.12.069

    • Google Scholar
28. 1. Fleire SJ
    2. Goldman JP
    3. Carrasco YR
    4. Weber M
    5. Bray D
    6. Batista FD

    (2006) B cell ligand discrimination through a spreading and contraction response

    Science 312:738–741.

    https://doi.org/10.1126/science.1123940

    • PubMed
    • Google Scholar
29. 1. Freeman SA
    2. Lei V
    3. Dang-Lawson M
    4. Mizuno K
    5. Roskelley CD
    6. Gold MR

    (2011) Cofilin-mediated F-actin severing is regulated by the Rap GTPase and controls the cytoskeletal dynamics that drive lymphocyte spreading and BCR microcluster formation

    The Journal of Immunology 187:5887–5900.

    https://doi.org/10.4049/jimmunol.1102233

    • PubMed
    • Google Scholar
30. 1. Freeman SA
    2. Jaumouillé V
    3. Choi K
    4. Hsu BE
    5. Wong HS
    6. Abraham L
    7. Graves ML
    8. Coombs D
    9. Roskelley CD
    10. Das R
    11. Grinstein S
    12. Gold MR

    (2015) Toll-like receptor ligands sensitize B-cell receptor signalling by reducing actin-dependent spatial confinement of the receptor

    Nature Communications 6:6168.

    https://doi.org/10.1038/ncomms7168

    • PubMed
    • Google Scholar
31. 1. Fujimoto M
    2. Fujimoto Y
    3. Poe JC
    4. Jansen PJ
    5. Lowell CA
    6. DeFranco AL
    7. Tedder TF

    (2000) CD19 regulates Src family protein tyrosine kinase activation in B lymphocytes through processive amplification

    Immunity 13:47–57.

    https://doi.org/10.1016/S1074-7613(00)00007-8

    • PubMed
    • Google Scholar
32. 1. Fujimoto M
    2. Poe JC
    3. Satterthwaite AB
    4. Wahl MI
    5. Witte ON
    6. Tedder TF

    (2002) Complementary roles for CD19 and Bruton's tyrosine kinase in B lymphocyte signal transduction

    The Journal of Immunology 168:5465–5476.

    https://doi.org/10.4049/jimmunol.168.11.5465

    • PubMed
    • Google Scholar
33. 1. Gasparrini F
    2. Feest C
    3. Bruckbauer A
    4. Mattila PK
    5. Müller J
    6. Nitschke L
    7. Bray D
    8. Batista FD

    (2016) Nanoscale organization and dynamics of the siglec CD22 cooperate with the cytoskeleton in restraining BCR signalling

    The EMBO Journal 35:258–280.

    https://doi.org/10.15252/embj.201593027

    • PubMed
    • Google Scholar
34. 1. Geahlen RL

    (2009) Syk and pTyr'd: signaling through the B cell antigen receptor

    Biochimica Et Biophysica Acta (BBA) - Molecular Cell Research 1793:1115–1127.

    https://doi.org/10.1016/j.bbamcr.2009.03.004

    • Google Scholar
35. 1. Gold MR
    2. Matsuuchi L
    3. Kelly RB
    4. DeFranco AL

    (1991) Tyrosine phosphorylation of components of the B-cell antigen receptors following receptor crosslinking

    PNAS 88:3436–3440.

    https://doi.org/10.1073/pnas.88.8.3436

    • PubMed
    • Google Scholar
36. 1. Goley ED
    2. Welch MD

    (2006) The ARP2/3 complex: an actin nucleator comes of age

    Nature Reviews Molecular Cell Biology 7:713–726.

    https://doi.org/10.1038/nrm2026

    • PubMed
    • Google Scholar
37. 1. Goodnow CC
    2. Crosbie J
    3. Adelstein S
    4. Lavoie TB
    5. Smith-Gill SJ
    6. Brink RA
    7. Pritchard-Briscoe H
    8. Wotherspoon JS
    9. Loblay RH
    10. Raphael K

    (1988) Altered immunoglobulin expression and functional silencing of self-reactive B lymphocytes in transgenic mice

    Nature 334:676–682.

    https://doi.org/10.1038/334676a0

    • PubMed
    • Google Scholar
38. 1. Grimm JB
    2. English BP
    3. Chen J
    4. Slaughter JP
    5. Zhang Z
    6. Revyakin A
    7. Patel R
    8. Macklin JJ
    9. Normanno D
    10. Singer RH
    11. Lionnet T
    12. Lavis LD

    (2015) A general method to improve fluorophores for live-cell and single-molecule microscopy

    Nature Methods 12:244–250.

    https://doi.org/10.1038/nmeth.3256

    • PubMed
    • Google Scholar
39. 1. Gupta N
    2. Wollscheid B
    3. Watts JD
    4. Scheer B
    5. Aebersold R
    6. DeFranco AL

    (2006) Quantitative proteomic analysis of B cell lipid rafts reveals that Ezrin regulates antigen receptor-mediated lipid raft dynamics

    Nature Immunology 7:625–633.

    https://doi.org/10.1038/ni1337

    • PubMed
    • Google Scholar
40. 1. Hammer JA
    2. Burkhardt JK

    (2013) Controversy and consensus regarding myosin II function at the immunological synapse

    Current Opinion in Immunology 25:300–306.

    https://doi.org/10.1016/j.coi.2013.03.010

    • PubMed
    • Google Scholar
41. 1. Harwood NE
    2. Batista FD

    (2010) Early events in B cell activation

    Annual Review of Immunology 28:185–210.

    https://doi.org/10.1146/annurev-immunol-030409-101216

    • PubMed
    • Google Scholar
42. 1. Harwood NE
    2. Batista FD

    (2011) The cytoskeleton coordinates the early events of B-cell activation

    Cold Spring Harbor Perspectives in Biology 3:a002360.

    https://doi.org/10.1101/cshperspect.a002360

    • PubMed
    • Google Scholar
43. 1. Hashimoto-Tane A
    2. Yokosuka T
    3. Sakata-Sogawa K
    4. Sakuma M
    5. Ishihara C
    6. Tokunaga M
    7. Saito T

    (2011) Dynein-driven transport of T cell receptor microclusters regulates immune synapse formation and T cell activation

    Immunity 34:919–931.

    https://doi.org/10.1016/j.immuni.2011.05.012

    • PubMed
    • Google Scholar
44. 1. Hetrick B
    2. Han MS
    3. Helgeson LA
    4. Nolen BJ

    (2013) Small molecules CK-666 and CK-869 inhibit actin-related protein 2/3 complex by blocking an activating conformational change

    Chemistry & Biology 20:701–712.

    https://doi.org/10.1016/j.chembiol.2013.03.019

    • PubMed
    • Google Scholar
45. 1. Hoogeboom R
    2. Natkanski EM
    3. Nowosad CR
    4. Malinova D
    5. Menon RP
    6. Casal A
    7. Tolar P

    (2018) Myosin IIa promotes antibody responses by regulating B cell activation, acquisition of antigen, and proliferation

    Cell Reports 23:2342–2353.

    https://doi.org/10.1016/j.celrep.2018.04.087

    • PubMed
    • Google Scholar
46. 1. Ilani T
    2. Vasiliver-Shamis G
    3. Vardhana S
    4. Bretscher A
    5. Dustin ML

    (2009) T cell antigen receptor signaling and immunological synapse stability require myosin IIA

    Nature Immunology 10:531–539.

    https://doi.org/10.1038/ni.1723

    • PubMed
    • Google Scholar
47. 1. Jacobelli J
    2. Chmura SA
    3. Buxton DB
    4. Davis MM
    5. Krummel MF

    (2004) A single class II myosin modulates T cell motility and stopping, but not synapse formation

    Nature Immunology 5:531–538.

    https://doi.org/10.1038/ni1065

    • PubMed
    • Google Scholar
48. 1. Jacobelli J
    2. Bennett FC
    3. Pandurangi P
    4. Tooley AJ
    5. Krummel MF

    (2009) Myosin-IIA and ICAM-1 regulate the interchange between two distinct modes of T cell migration

    The Journal of Immunology 182:2041–2050.

    https://doi.org/10.4049/jimmunol.0803267

    • PubMed
    • Google Scholar
49. 1. Johnson HW
    2. Schell MJ

    (2009) Neuronal IP₃ 3-kinase is an F-actin-bundling protein: role in dendritic targeting and regulation of spine morphology

    Molecular Biology of the Cell 20:5166–5180.

    https://doi.org/10.1091/mbc.e09-01-0083

    • PubMed
    • Google Scholar
50. 1. Kahr WH
    2. Pluthero FG
    3. Elkadri A
    4. Warner N
    5. Drobac M
    6. Chen CH
    7. Lo RW
    8. Li L
    9. Li R
    10. Li Q
    11. Thoeni C
    12. Pan J
    13. Leung G
    14. Lara-Corrales I
    15. Murchie R
    16. Cutz E
    17. Laxer RM
    18. Upton J
    19. Roifman CM
    20. Yeung RS
    21. Brumell JH
    22. Muise AM

    (2017) Loss of the Arp2/3 complex component ARPC1B causes platelet abnormalities and predisposes to inflammatory disease

    Nature Communications 8:14816.

    https://doi.org/10.1038/ncomms14816

    • PubMed
    • Google Scholar
51. 1. Keppler SJ
    2. Gasparrini F
    3. Burbage M
    4. Aggarwal S
    5. Frederico B
    6. Geha RS
    7. Way M
    8. Bruckbauer A
    9. Batista FD

    (2015) Wiskott-Aldrich syndrome interacting protein deficiency uncovers the role of the co-receptor CD19 as a generic hub for PI3 kinase signaling in B cells

    Immunity 43:660–673.

    https://doi.org/10.1016/j.immuni.2015.09.004

    • PubMed
    • Google Scholar
52. 1. Ketchum C
    2. Miller H
    3. Song W
    4. Upadhyaya A

    (2014) Ligand mobility regulates B cell receptor clustering and signaling activation

    Biophysical Journal 106:26–36.

    https://doi.org/10.1016/j.bpj.2013.10.043

    • PubMed
    • Google Scholar
53. 1. Kirk SJ
    2. Cliff JM
    3. Thomas JA
    4. Ward TH

    (2010) Biogenesis of secretory organelles during B cell differentiation

    Journal of Leukocyte Biology 87:245–255.

    https://doi.org/10.1189/jlb.1208774

    • PubMed
    • Google Scholar
54. 1. Kumari S
    2. Vardhana S
    3. Cammer M
    4. Curado S
    5. Santos L
    6. Sheetz MP
    7. Dustin ML

    (2012) T lymphocyte myosin IIA is required for maturation of the immunological synapse

    Frontiers in Immunology 3:.

    https://doi.org/10.3389/fimmu.2012.00230

    • PubMed
    • Google Scholar
55. 1. Kumari S
    2. Curado S
    3. Mayya V
    4. Dustin ML

    (2014) T cell antigen receptor activation and actin cytoskeleton remodeling

    Biochimica Et Biophysica Acta (BBA) - Biomembranes 1838:546–556.

    https://doi.org/10.1016/j.bbamem.2013.05.004

    • Google Scholar
56. 1. Kumari S
    2. Depoil D
    3. Martinelli R
    4. Judokusumo E
    5. Carmona G
    6. Gertler FB
    7. Kam LC
    8. Carman CV
    9. Burkhardt JK
    10. Irvine DJ
    11. Dustin ML

    (2015) Actin foci facilitate activation of the phospholipase C-γ in primary T lymphocytes via the WASP pathway

    eLife 4:e04953.

    https://doi.org/10.7554/eLife.04953

    • Google Scholar
57. 1. Lin KB
    2. Freeman SA
    3. Zabetian S
    4. Brugger H
    5. Weber M
    6. Lei V
    7. Dang-Lawson M
    8. Tse KW
    9. Santamaria R
    10. Batista FD
    11. Gold MR

    (2008) The rap GTPases regulate B cell morphology, immune-synapse formation, and signaling by particulate B cell receptor ligands

    Immunity 28:75–87.

    https://doi.org/10.1016/j.immuni.2007.11.019

    • PubMed
    • Google Scholar
58. 1. Liu C
    2. Miller H
    3. Hui KL
    4. Grooman B
    5. Bolland S
    6. Upadhyaya A
    7. Song W

    (2011) A balance of Bruton's tyrosine kinase and SHIP activation regulates B cell receptor cluster formation by controlling actin remodeling

    The Journal of Immunology 187:230–239.

    https://doi.org/10.4049/jimmunol.1100157

    • PubMed
    • Google Scholar
59. 1. Liu C
    2. Miller H
    3. Orlowski G
    4. Hang H
    5. Upadhyaya A
    6. Song W

    (2012) Actin reorganization is required for the formation of polarized B cell receptor signalosomes in response to both soluble and membrane-associated antigens

    The Journal of Immunology 188:3237–3246.

    https://doi.org/10.4049/jimmunol.1103065

    • PubMed
    • Google Scholar
60. 1. Liu C
    2. Bai X
    3. Wu J
    4. Sharma S
    5. Upadhyaya A
    6. Dahlberg CI
    7. Westerberg LS
    8. Snapper SB
    9. Zhao X
    10. Song W

    (2013) N-WASP is essential for the negative regulation of B cell receptor signaling

    PLOS Biology 11:e1001704.

    https://doi.org/10.1371/journal.pbio.1001704

    • PubMed
    • Google Scholar
61. 1. Manders EMM
    2. Verbeek FJ
    3. Aten JA

    (1993) Measurement of co-localization of objects in dual-colour confocal images

    Journal of Microscopy 169:375–382.

    https://doi.org/10.1111/j.1365-2818.1993.tb03313.x

    • Google Scholar
62. 1. Mattila PK
    2. Feest C
    3. Depoil D
    4. Treanor B
    5. Montaner B
    6. Otipoby KL
    7. Carter R
    8. Justement LB
    9. Bruckbauer A
    10. Batista FD

    (2013) The actin and tetraspanin networks organize receptor nanoclusters to regulate B cell receptor-mediated signaling

    Immunity 38:461–474.

    https://doi.org/10.1016/j.immuni.2012.11.019

    • PubMed
    • Google Scholar
63. 1. Mattila PK
    2. Lappalainen P

    (2008) Filopodia: molecular architecture and cellular functions

    Nature Reviews Molecular Cell Biology 9:446–454.

    https://doi.org/10.1038/nrm2406

    • PubMed
    • Google Scholar
64. 1. Michelot A
    2. Drubin DG

    (2011) Building distinct actin filament networks in a common cytoplasm

    Current Biology 21:R560–R569.

    https://doi.org/10.1016/j.cub.2011.06.019

    • PubMed
    • Google Scholar
65. 1. Mogilner A
    2. Oster G

    (1996) Cell motility driven by actin polymerization

    Biophysical Journal 71:3030–3045.

    https://doi.org/10.1016/S0006-3495(96)79496-1

    • PubMed
    • Google Scholar
66. 1. Moran AE
    2. Holzapfel KL
    3. Xing Y
    4. Cunningham NR
    5. Maltzman JS
    6. Punt J
    7. Hogquist KA

    (2011) T cell receptor signal strength in Treg and iNKT cell development demonstrated by a novel fluorescent reporter mouse

    The Journal of Experimental Medicine 208:1279–1289.

    https://doi.org/10.1084/jem.20110308

    • PubMed
    • Google Scholar
67. 1. Motulsky HJ
    2. Brown RE

    (2006) Detecting outliers when fitting data with nonlinear regression - a new method based on robust nonlinear regression and the false discovery rate

    BMC Bioinformatics 7:.

    https://doi.org/10.1186/1471-2105-7-123

    • PubMed
    • Google Scholar
68. 1. Murugesan S
    2. Hong J
    3. Yi J
    4. Li D
    5. Beach JR
    6. Shao L
    7. Meinhardt J
    8. Madison G
    9. Wu X
    10. Betzig E
    11. Hammer JA

    (2016) Formin-generated actomyosin arcs propel T cell receptor microcluster movement at the immune synapse

    The Journal of Cell Biology 215:383–399.

    https://doi.org/10.1083/jcb.201603080

    • PubMed
    • Google Scholar
69. 1. Natkanski E
    2. Lee WY
    3. Mistry B
    4. Casal A
    5. Molloy JE
    6. Tolar P

    (2013) B cells use mechanical energy to discriminate antigen affinities

    Science 340:1587–1590.

    https://doi.org/10.1126/science.1237572

    • PubMed
    • Google Scholar
70. 1. Nicholson-Dykstra SM
    2. Higgs HN

    (2008) Arp2 depletion inhibits sheet-like protrusions but not linear protrusions of fibroblasts and lymphocytes

    Cell Motility and the Cytoskeleton 65:904–922.

    https://doi.org/10.1002/cm.20312

    • PubMed
    • Google Scholar
71. 1. Nowosad CR
    2. Spillane KM
    3. Tolar P

    (2016) Germinal center B cells recognize antigen through a specialized immune synapse architecture

    Nature Immunology 17:870–877.

    https://doi.org/10.1038/ni.3458

    • PubMed
    • Google Scholar
72. 1. O'Rourke LM
    2. Tooze R
    3. Turner M
    4. Sandoval DM
    5. Carter RH
    6. Tybulewicz VL
    7. Fearon DT

    (1998) CD19 as a membrane-anchored adaptor protein of B lymphocytes: costimulation of lipid and protein kinases by recruitment of Vav

    Immunity 8:635–645.

    https://doi.org/10.1016/S1074-7613(00)80568-3

    • PubMed
    • Google Scholar
73. 1. Pollard TD

    (2007) Regulation of actin filament assembly by Arp2/3 complex and formins

    Annual Review of Biophysics and Biomolecular Structure 36:451–477.

    https://doi.org/10.1146/annurev.biophys.35.040405.101936

    • PubMed
    • Google Scholar
74. 1. Pollard TD
    2. Borisy GG

    (2003) Cellular motility driven by assembly and disassembly of actin filaments

    Cell 112:453–465.

    https://doi.org/10.1016/S0092-8674(03)00120-X

    • PubMed
    • Google Scholar
75. 1. Ponti A
    2. Machacek M
    3. Gupton SL
    4. Waterman-Storer CM
    5. Danuser G

    (2004) Two distinct actin networks drive the protrusion of migrating cells

    Science 305:1782–1786.

    https://doi.org/10.1126/science.1100533

    • PubMed
    • Google Scholar
76. 1. Rotty JD
    2. Wu C
    3. Bear JE

    (2013) New insights into the regulation and cellular functions of the ARP2/3 complex

    Nature Reviews Molecular Cell Biology 14:7–12.

    https://doi.org/10.1038/nrm3492

    • Google Scholar
77. 1. Rowley RB
    2. Burkhardt AL
    3. Chao HG
    4. Matsueda GR
    5. Bolen JB

    (1995) Syk protein-tyrosine kinase is regulated by tyrosine-phosphorylated Ig alpha/Ig beta immunoreceptor tyrosine activation motif binding and autophosphorylation

    Journal of Biological Chemistry 270:11590–11594.

    https://doi.org/10.1074/jbc.270.19.11590

    • PubMed
    • Google Scholar
78. 1. Schindelin J
    2. Arganda-Carreras I
    3. Frise E
    4. Kaynig V
    5. Longair M
    6. Pietzsch T
    7. Preibisch S
    8. Rueden C
    9. Saalfeld S
    10. Schmid B
    11. Tinevez JY
    12. White DJ
    13. Hartenstein V
    14. Eliceiri K
    15. Tomancak P
    16. Cardona A

    (2012) Fiji: an open-source platform for biological-image analysis

    Nature Methods 9:676–682.

    https://doi.org/10.1038/nmeth.2019

    • PubMed
    • Google Scholar
79. 1. Schnyder T
    2. Castello A
    3. Feest C
    4. Harwood NE
    5. Oellerich T
    6. Urlaub H
    7. Engelke M
    8. Wienands J
    9. Bruckbauer A
    10. Batista FD

    (2011) B cell receptor-mediated antigen gathering requires ubiquitin ligase Cbl and adaptors Grb2 and Dok-3 to recruit dynein to the signaling microcluster

    Immunity 34:905–918.

    https://doi.org/10.1016/j.immuni.2011.06.001

    • PubMed
    • Google Scholar
80. Software

    1. Scurll JM

    (2019) Image Analysis Scripts, version a9dffe5

    BitBucket.

    https://bitbucket.org/jscurll/bolger-munro_image_analysis_scripts/src/master/
81. 1. Song W
    2. Liu C
    3. Upadhyaya A

    (2014) The pivotal position of the actin cytoskeleton in the initiation and regulation of B cell receptor activation

    Biochimica Et Biophysica Acta (BBA) - Biomembranes 1838:569–578.

    https://doi.org/10.1016/j.bbamem.2013.07.016

    • Google Scholar
82. 1. Spillane KM
    2. Tolar P

    (2017) B cell antigen extraction is regulated by physical properties of antigen-presenting cells

    The Journal of Cell Biology 216:217–230.

    https://doi.org/10.1083/jcb.201607064

    • PubMed
    • Google Scholar
83. 1. Suarez C
    2. Kovar DR

    (2016) Internetwork competition for monomers governs actin cytoskeleton organization

    Nature Reviews Molecular Cell Biology 17:799–810.

    https://doi.org/10.1038/nrm.2016.106

    • PubMed
    • Google Scholar
84. 1. Tolar P

    (2017) Cytoskeletal control of B cell responses to antigens

    Nature Reviews Immunology 17:621–634.

    https://doi.org/10.1038/nri.2017.67

    • PubMed
    • Google Scholar
85. 1. Treanor B
    2. Harwood NE
    3. Batista FD

    (2009) Microsignalosomes: spatially resolved receptor signalling

    Biochemical Society Transactions 37:1014–1018.

    https://doi.org/10.1042/BST0371014

    • PubMed
    • Google Scholar
86. 1. Treanor B
    2. Depoil D
    3. Gonzalez-Granja A
    4. Barral P
    5. Weber M
    6. Dushek O
    7. Bruckbauer A
    8. Batista FD

    (2010) The membrane skeleton controls diffusion dynamics and signaling through the B cell receptor

    Immunity 32:187–199.

    https://doi.org/10.1016/j.immuni.2009.12.005

    • PubMed
    • Google Scholar
87. 1. Treanor B
    2. Depoil D
    3. Bruckbauer A
    4. Batista FD

    (2011) Dynamic cortical actin remodeling by ERM proteins controls BCR microcluster organization and integrity

    The Journal of Experimental Medicine 208:1055–1068.

    https://doi.org/10.1084/jem.20101125

    • PubMed
    • Google Scholar
88. 1. Tuveson DA
    2. Carter RH
    3. Soltoff SP
    4. Fearon DT

    (1993) CD19 of B cells as a surrogate kinase insert region to bind phosphatidylinositol 3-kinase

    Science 260:986–989.

    https://doi.org/10.1126/science.7684160

    • PubMed
    • Google Scholar
89. 1. Wan Z
    2. Zhang S
    3. Fan Y
    4. Liu K
    5. Du F
    6. Davey AM
    7. Zhang H
    8. Han W
    9. Xiong C
    10. Liu W

    (2013) B cell activation is regulated by the stiffness properties of the substrate presenting the antigens

    The Journal of Immunology 190:4661–4675.

    https://doi.org/10.4049/jimmunol.1202976

    • PubMed
    • Google Scholar
90. 1. Wan Z
    2. Chen X
    3. Chen H
    4. Ji Q
    5. Chen Y
    6. Wang J
    7. Cao Y
    8. Wang F
    9. Lou J
    10. Tang Z
    11. Liu W

    (2015) The activation of IgM- or isotype-switched IgG- and IgE-BCR exhibits distinct mechanical force sensitivity and threshold

    eLife 4:e06925.

    https://doi.org/10.7554/eLife.06925

    • Google Scholar
91. 1. Wang JC
    2. Lee JY
    3. Christian S
    4. Dang-Lawson M
    5. Pritchard C
    6. Freeman SA
    7. Gold MR

    (2017) The Rap1-cofilin-1 pathway coordinates actin reorganization and MTOC polarization at the B cell immune synapse

    Journal of Cell Science 130:1094–1109.

    https://doi.org/10.1242/jcs.191858

    • PubMed
    • Google Scholar
92. 1. Wang JC
    2. Bolger-Munro M
    3. Gold MR

    (2018)

    Methods in Molecular Biology

    131–161, Imaging the Interactions Between B Cells and Antigen-Presenting Cells, Methods in Molecular Biology, 1707, New York, Humana Press, 10.1007/978-1-4939-7474-0_10.

    • Google Scholar
93. 1. Weber M
    2. Treanor B
    3. Depoil D
    4. Shinohara H
    5. Harwood NE
    6. Hikida M
    7. Kurosaki T
    8. Batista FD

    (2008) Phospholipase C-γ2 and Vav cooperate within signaling microclusters to propagate B cell spreading in response to membrane-bound antigen

    The Journal of Experimental Medicine 205:853–868.

    https://doi.org/10.1084/jem.20072619

    • PubMed
    • Google Scholar
94. 1. Westerberg LS
    2. Meelu P
    3. Baptista M
    4. Eston MA
    5. Adamovich DA
    6. Cotta-de-Almeida V
    7. Seed B
    8. Rosen MK
    9. Vandenberghe P
    10. Thrasher AJ
    11. Klein C
    12. Alt FW
    13. Snapper SB

    (2010) Activating WASP mutations associated with X-linked neutropenia result in enhanced actin polymerization, altered cytoskeletal responses, and genomic instability in lymphocytes

    The Journal of Experimental Medicine 207:1145–1152.

    https://doi.org/10.1084/jem.20091245

    • PubMed
    • Google Scholar
95. 1. Wong S
    2. Guo WH
    3. Wang YL

    (2014) Fibroblasts probe substrate rigidity with filopodia extensions before occupying an area

    PNAS 111:17176–17181.

    https://doi.org/10.1073/pnas.1412285111

    • PubMed
    • Google Scholar
96. 1. Xu L
    2. Li G
    3. Wang J
    4. Fan Y
    5. Wan Z
    6. Zhang S
    7. Shaheen S
    8. Li J
    9. Wang L
    10. Yue C
    11. Zhao Y
    12. Wang F
    13. Brzostowski J
    14. Chen YH
    15. Zheng W
    16. Liu W

    (2014) Through an ITIM-independent mechanism the FcγRIIB blocks B cell activation by disrupting the colocalized microclustering of the B cell receptor and CD19

    The Journal of Immunology 192:5179–5191.

    https://doi.org/10.4049/jimmunol.1400101

    • PubMed
    • Google Scholar
97. 1. Yang Q
    2. Zhang XF
    3. Pollard TD
    4. Forscher P

    (2012) Arp2/3 complex-dependent actin networks constrain myosin II function in driving retrograde actin flow

    The Journal of Cell Biology 197:939–956.

    https://doi.org/10.1083/jcb.201111052

    • PubMed
    • Google Scholar
98. 1. Yi J
    2. Wu XS
    3. Crites T
    4. Hammer JA

    (2012) Actin retrograde flow and actomyosin II arc contraction drive receptor cluster dynamics at the immunological synapse in Jurkat T cells

    Molecular Biology of the Cell 23:834–852.

    https://doi.org/10.1091/mbc.e11-08-0731

    • PubMed
    • Google Scholar
99. 1. York AG
    2. Chandris P
    3. Nogare DD
    4. Head J
    5. Wawrzusin P
    6. Fischer RS
    7. Chitnis A
    8. Shroff H

    (2013) Instant super-resolution imaging in live cells and embryos via analog image processing

    Nature Methods 10:1122–1126.

    https://doi.org/10.1038/nmeth.2687

    • PubMed
    • Google Scholar
100. 1. Yuseff MI
     2. Pierobon P
     3. Reversat A
     4. Lennon-Duménil AM

     (2013) How B cells capture, process and present antigens: a crucial role for cell polarity

     Nature Reviews Immunology 13:475–486.

     https://doi.org/10.1038/nri3469

     • PubMed
     • Google Scholar
101. 1. Zhang Y
     2. Shen H
     3. Liu H
     4. Feng H
     5. Liu Y
     6. Zhu X
     7. Liu X

     (2017) Arp2/3 complex controls T cell homeostasis by maintaining surface TCR levels via regulating TCR⁺ endosome trafficking

     Scientific Reports 7:8952.

     https://doi.org/10.1038/s41598-017-08357-4

     • PubMed
     • Google Scholar

Thank you for submitting your article "Arp2/3 complex-driven spatial patterning of the BCR enhances immune synapse formation, BCR signaling and cell activation" for consideration by eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Arup Chakraborty as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Pavel Tolar (Reviewer #1); Bebhinn Treanor (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:

This is a well done study that extends previous works on the organization of the B cell immune synapse and on the role of actin polymerization in BCR clustering, transport and signaling. The main conclusion is that actin polymerization specifically by the ARP2/3 complex drives movement and fusion of BCR/Ag clusters in B cells interacting with membrane antigen and that this boosts proximal BCR signaling as well as late events, such as B cell activation. These results are compatible with the previous idea that dynamic B cell lamellipodia are involved in grabbing antigen and that actin-based membrane shape, mechanics and flow promote BCR clustering and signaling.

The experimental system uses COS-7 cells expressing B cell antigen, which is good as this system mimics B cell-APC interactions better than artificial substrates. The COS-7 cells are paired with the established A20 B cell model, or in the signaling experiments with naive mouse B cells. The imaging and tools for visualisation of the immune synapse are cutting edge.

Using the CK666 inhibitor and siRNA, the authors report that actin polymerization through the ARP2/3 complex did not affect spreading of the B cells or the amount of the antigen gathered, but affected the movement and fusion of the antigen clusters. This is also illustrated by videos of the antigen flowing with the actin. SIM imaging of the B cells on glass substrates shows this clearly, as here the dramatic actin flow clearly depends on ARP2/3, similarly as it does in T cells.

The ARP2/3-inhibited cells show reduced proximal BCR signaling, particularly the early tyrosine phosphorylation of the BCR and of CD19, suggesting that the actin mediated movement and clustering is important in amplifying antigen-mediated B cell activation. Remarkably, the authors also see importance of this early ARP2/3 activity on late responses, such as expression of activation markers and proliferation, which are reduced in their intensity. Controls show that indeed this is through activity of ARP2/3 during the early contact of the B cells with the APCs. Inhibiting of ARP2/3 also leads to enhanced "tonic" signaling, similarly as inhibition of all actin polymerisation, suggesting that the ARP2/3-generated F-actin pool is the relevant structure regulating this aspect of BCR signaling.

Essential revisions:

The major concern with the otherwise excellent study is that the authors may overreach in some interpretations and there is some concern that the CK666 displays effects that go beyond the Arp3 siRNA, raising issues about interpretations based on CK666 using in this way (1 hr pretreat at 100 µM).

1) Video 1 (Figure 1B) shows the process of BCR-Ag clustering and SMAC formation over time. Clusters appear (t=0-1min), presumably upon B-cell contact, clusters move ~1µm centripetally where they coalesce into larger assemblies t=2-3 min), a few straggler clusters flow into the central array (t=3-5 min) and a SMAC assembly forms by ~10 min) although the forces acting on clusters and driving coalescence into a single SMAC structure are not obvious. The example illustrated in this video is unique. BCR-Ag formation and clustering in other cells shown in other videos do not exhibit all of these properties. Specifically, centripetal movement of BCR-Ag clusters is not commonly observed.

2) To assess BCR-Ag clustering and SMAC formation together with B-cell F-actin structures, the authors use F-tractin-GFP to visualize dynamic B-cell actin structures and BCR-Ag clustering after B-cells contact an APC (Video 2). BCR-Ag clusters first form upon initial contact of the B-cell and APC. These initial clusters increase in size as the B-cell spreads and extends across the APC surface via cycles of protrusion and retraction. Little centripetal movement of clusters occurs in this cell. Peripheral F-actin retrograde flow is not detectable in the time-lapse sequence (perhaps the time interval is too long to detect it). In this sequence, a single BCR-Ag microcluster was observed to move centripetally ~1µm before merging into an existing larger cluster (this movement was analyzed by kymography in Figure 1E). It is striking that as BCR-Ag clusters expand within the growing B-cell-APC contact zone, the regions become devoid of B-cell F-actin, a point that may be relevant to formation or stability of the emerging SMAC. There are no predominant F-actin structures flowing centripetally during formation of the SMAC. Indeed, BCR-Ag clusters expand in size and often coalesce with each other, but they do not appear to experience much directed retrograde flow; many simply expand in place or merge upon contact with neighboring clusters.

3) In video 3, the authors observe the behavior of B-cells spreading on a rigid glass IgG-coated coverslip using GFP-F-tractin probe. The authors describe B-cell behavior on glass as having long-lived membrane protrusions with no obvious membrane retraction events over the 10 min sequence. In contrast, the well-spread cell in video 3 exhibits dynamic membrane extension (lamellipodia and filopodia) and retraction around its circumference during the entire 10 min sequence. Moreover, one could quantify the rate of retrograde flow in this well-spread cell because the rate of time-lapse collection is sufficient to capture lamellipodial retrograde flow in some regions. The authors conclude that B-cells encountering antigen on an APC display complex and dynamic membrane probing and retraction behavior compared to when they are on glass. This appears to be the case, however, a comparison with B-cells spread on glass is comparing apples and oranges, especially when different rates of time-lapse collection are used. Nonetheless, it is important to describe observed cell behaviors and cluster dynamics as accurately as possible. To observe B-cells spreading on APCs may require different imaging modalities (faster image acquisition, additional focal planes) to appreciate its complex and intriguing behaviors.

4) Experiments aimed at blocking Arp2/3 complex activity implicated Arp2/3 complex in coalescence of BRC-Ag microclusters to form SMAC structures. The effects on BCR-Ag cluster dynamics were slightly different for Arp3 siRNA-mediated depletion compared to pharmacologic inhibition using CK-666; specifically, several examples of clusters experiencing centripetal flow are observed in the cell treated with Arp3 siRNA (Video 5). Additionally, in the cell treated with CK-666, the nature of cluster formation is quite different from that in cells depleted of Arp2/3 complex using siRNA; clusters are linear and appear to align and expand along filopodial-like protrusive structures. What accounts for this difference in formation and behavior of clusters under these two conditions?

5) Requirement of retrograde flow to form a SMAC. The authors do not provide compelling evidence in support of a role for Arp2/3-mediated retrograde flow in SMAC formation in B-cell-APC pairs. However, since they demonstrate that washout of CK-666 restored upregulation of CD69, a downstream effect of BCR-induced B cell activation (Figure 9—figure supplement 3), a question is whether or not a SMAC will form in B-cell-APC pairs upon washout of CK666. If the appropriate time-lapse imaging were used to simultaneously observe GFP-F-tractin in B-cells during washout of a CK-666 block, direct observations of F-actin retrograde flow and cluster flow during SMAC formation may be possible.

6) Finally, centripetal retrograde flow could be driven by a myosin-dependent process. This could be examined directly using inhibitors of myosin II. Disruption of global Arp2/3 complex actin networks is expected to exert perturbations on the whole cell cytoskeleton. Pinpointing the specific Arp2/3 dependent-activities during B-cell signaling will be challenging using this somewhat sledge-hammer approach.

Regarding essential experiments, as discussed above the videos are quite instructive in that the A20 cell synapse has a <1 µm rim of centripetal F-actin flow that transitions rapidly into < 1 µm myosin arc zone that leave the BCR microclusters in a loose assembly of ~1 µm BCR-Ag clusters/condensates scattered across a large area >5 µm in diameter. The final stage of "cSMAC" formation looks more like condensate fusion than transport. The tests for this would be different than for cytoskeletal transport. One way or the other, BCR consolidates in the center, but the F-actin appears to be permitting this rather than driving it. In the Arp3 KD the filopodia display robust centripetal F-actin flow as expected so the BCR clusters are transported similarly to the control siRNA, but there appear to be greater barriers to consolidation of the BCR clusters, so perhaps F-actin structures under these conditions are less permissive along the lines of work of Batista on F-actin constraining BCR movement. The CK666 seems to kill both the flow in the filopodia and create barriers to condensate fusion, so it is a very different picture that looks "poisoned" with the cell being paralysed in an unexpected way. The critical experiment that should be done is to use CK666 in the Arp3 KD to determine if CK666 has effects that go beyond the best Arp3 KD you can achieve in A20? If so, it could be because of incomplete KD, dominant effects of how CK666 inhibits Apr2/3, or off target effects perhaps also targeting cellular energy. Reversibility of CK666 effects would be good to see, but might not address the issues as any toxicity that makes the effects different than the Arp3 siRNA might also be reversed. In these experiments and controls, the authors could be asked to ensure that the frequency of imaging is optimised to best reveal proposed transport processes and to distinguish these from other non-correlated events. What is hoped is that this complete set of experiments (that completes the matrix of conditions set out in the study) will resolve if CK666 has activities that are beyond Arp3 siRNA (and thus could be off target) and are all of the events associated with cSMAC formation truly correlated with F-actin mediated transport or are their processes that are either independent or even hindered by some F-actin structures. Analysis of diffusive movement or random transport of the microclusters could aid identifying/discussing underlying mechanisms.

Essential revisions:

The major concern with the otherwise excellent study is that the authors may overreach in some interpretations and there is some concern that the CK666 displays effects that go beyond the Arp3 siRNA, raising issues about interpretations based on CK666 using in this way (1 hr pretreat at 100 µM).

1) Video 1 (Figure 1B) shows the process of BCR-Ag clustering and SMAC formation over time. Clusters appear (t=0-1min), presumably upon B-cell contact, clusters move ~1µm centripetally where they coalesce into larger assemblies t=2-3 min), a few straggler clusters flow into the central array (t=3-5 min) and a SMAC assembly forms by ~10 min) although the forces acting on clusters and driving coalescence into a single SMAC structure are not obvious. The example illustrated in this video is unique. BCR-Ag formation and clustering in other cells shown in other videos do not exhibit all of these properties. Specifically, centripetal movement of BCR-Ag clusters is not commonly observed.

We have addressed these comments in the following ways:

1) The reviewer is correct in that it is mainly the BCR microclusters that form at the periphery of the B cell-APC contact site, especially on newly-formed membrane protrusions, that move centripetally. To more accurately describe overall BCR microcluster movement, we now state “When A20 murine B-lymphoma cells expressing the HEL-specific D1.3 transgenic BCR (A20 D1.3 B cells) were added to the APCs, they rapidly formed BCR-Ag microclusters throughout the contact site. Microclusters that formed at the periphery moved centripetally. Closer to the center of the contact site, microclusters coalesced with each other such that a cSMAC developed within ~10 min (Figure 1B).”

2) We now show additional videos of microcluster dynamics in control cells (4 control siRNA-transfected cells in Video 4 and 4 CK-689-treated cells in Video 6). In these videos, a number of BCR microclusters are seen to move centripetally. To illustrate this, we now show additional kymographs of microclusters that exhibit centripetal movement in Figure 2—figure supplement 4G, H, including one in which two microclusters both move centripetally before coalescing. The reader is referred to these additional videos and kymographs in the third paragraph of the subsection “The Arp2/3 complex is required for centralization of BCR-Ag microclusters”.

3) For all of the cells (18-48 cells per condition) that had been previously quantified in Figure 2E, F and Figure 2—figure supplement 3), we now quantify the centripetal movement of BCR microclusters. To do this, we calculated for every frame in the video the distance between each microcluster and the center of mass of the Ag fluorescence (which at later times, this is the center of the cSMAC). The average value for all of the microclusters on a single cell was determined at each time point and was normalized to the maximum average distance for that cell. These new graphs (Figure 2—figure supplement 4E, F) show that, on average, net microcluster movement towards the center of the cell is minimal when the Arp2/3 complex is inhibited. The reader is referred to these additional graphs in the aforementioned paragraph.

With regard to the forces that promote the condensation of aggregated microclusters within the actin-depleted regions, this process may be driven by other cytoskeletal forces such as actomyosin contraction or microtubule-based mechanism. We note this in the Discussion (fifth paragraph).

2) To assess BCR-Ag clustering and SMAC formation together with B-cell F-actin structures, the authors use F-tractin-GFP to visualize dynamic B-cell actin structures and BCR-Ag clustering after B-cells contact an APC (Video 2). BCR-Ag clusters first form upon initial contact of the B-cell and APC. These initial clusters increase in size as the B-cell spreads and extends across the APC surface via cycles of protrusion and retraction. Little centripetal movement of clusters occurs in this cell. Peripheral F-actin retrograde flow is not detectable in the time-lapse sequence (perhaps the time interval is too long to detect it). In this sequence, a single BCR-Ag microcluster was observed to move centripetally ~1µm before merging into an existing larger cluster (this movement was analyzed by kymography in Figure 1E). It is striking that as BCR-Ag clusters expand within the growing B-cell-APC contact zone, the regions become devoid of B-cell F-actin, a point that may be relevant to formation or stability of the emerging SMAC. There are no predominant F-actin structures flowing centripetally during formation of the SMAC. Indeed, BCR-Ag clusters expand in size and often coalesce with each other, but they do not appear to experience much directed retrograde flow; many simply expand in place or merge upon contact with neighboring clusters.

We agree with the reviewer(s) and some of these points were addressed in our response to comment #1. We have inserted additional statements into the text that highlight the distinction between the centripetal movement of microclusters that form within actin-rich regions (especially those that form on membrane protrusions) and those that are closer to the center of the cell and which coalesce and condense in these actin-depleted regions (subsection “B cells generate dynamic actin-rich protrusions to scan for Ags on APCs”, second paragraph).

Moreover, we now show kymographs of additional microclusters exhibiting centripetal motion within actin-rich regions (Figure 1E). With regard to the kymograph shown in Figure 1E, we more clearly indicate that this refers specifically to microclusters that form in actin-rich regions and now state: “BCR-Ag microclusters formed within actin-rich regions, including newly formed protrusions Figure 1C, Video 2). […] As determined from the kymographs in Figure 1E, the velocities at which the peripheral F-actin structures and BCR-Ag microclusters moved towards the center of the synapse were similar, suggesting that actin dynamics drive the initial centripetal movement of these microclusters.”

The reviewer is correct that the peripheral F-actin flow is not obvious in the time-lapse series shown in Figure 1C because the time intervals are too large. However, they are clearly evident in Video 2, from which these still images are taken from, and in the kymographs in Figure 1E.

3) In video 3, the authors observe the behavior of B-cells spreading on a rigid glass IgG-coated coverslip using GFP-F-tractin probe. The authors describe B-cell behavior on glass as having long-lived membrane protrusions with no obvious membrane retraction events over the 10 min sequence. In contrast, the well-spread cell in video 3 exhibits dynamic membrane extension (lamellipodia and filopodia) and retraction around its circumference during the entire 10 min sequence. Moreover, one could quantify the rate of retrograde flow in this well-spread cell because the rate of time-lapse collection is sufficient to capture lamellipodial retrograde flow in some regions. The authors conclude that B-cells encountering antigen on an APC display complex and dynamic membrane probing and retraction behavior compared to when they are on glass. This appears to be the case, however, a comparison with B-cells spread on glass is comparing apples and oranges, especially when different rates of time-lapse collection are used. Nonetheless, it is important to describe observed cell behaviors and cluster dynamics as accurately as possible. To observe B-cells spreading on APCs may require different imaging modalities (faster image acquisition, additional focal planes) to appreciate its complex and intriguing behaviors.

We agree that the membrane dynamics of B cells spreading on immobilized anti-Ig versus an Ag-bearing APC are very different phenomena and that it is sufficient to describe the behaviors without belaboring the differences. Hence we replaced the section of the original manuscript, with what we feel is a more accurate description of the mode in which B cells spread on immobilized anti-Ig. Importantly, we have qualified our statement about how this differs from B cells probing the surface of an APC. We now say: “B cells spreading on immobilized anti-Ig formed multiple large lamellipodia, some of which persisted for up to 10 min (for example, Figure 1F [blue arrowheads]). They also formed short dynamic filopodia, many of which were retracted or engulfed by newly formed lamellipodia.”

With regard to quantifying the rate of actin retrograde flow in B cells spreading on immobilized anti-Ig, we did this in Figure 3E and Video 8 and conclude: “In control CK-689-treated cells (Figure 3E, Video 8), the F-actin networks were highly dynamic at the cell edge, with actin retrograde flow rates of ~2.5 μm/min”.

4) Experiments aimed at blocking Arp2/3 complex activity implicated Arp2/3 complex in coalescence of BRC-Ag microclusters to form SMAC structures. The effects on BCR-Ag cluster dynamics were slightly different for Arp3 siRNA-mediated depletion compared to pharmacologic inhibition using CK-666; specifically, several examples of clusters experiencing centripetal flow are observed in the cell treated with Arp3 siRNA (Video 5). Additionally, in the cell treated with CK-666, the nature of cluster formation is quite different from that in cells depleted of Arp2/3 complex using siRNA; clusters are linear and appear to align and expand along filopodial-like protrusive structures. What accounts for this difference in formation and behavior of clusters under these two conditions?

Regarding essential experiments, as discussed above the videos are quite instructive in that the A20 cell synapse has a <1 µm rim of centripetal F-actin flow that transitions rapidly into < 1 µm myosin arc zone that leave the BCR microclusters in a loose assembly of ~1 µm BCR-Ag clusters/condensates scattered across a large area >5 µm in diameter. The final stage of "cSMAC" formation looks more like condensate fusion than transport. The tests for this would be different than for cytoskeletal transport. One way or the other, BCR consolidates in the center, but the F-actin appears to be permitting this rather than driving it. In the Arp3 KD the filopodia display robust centripetal F-actin flow as expected so the BCR clusters are transported similarly to the control siRNA, but there appear to be greater barriers to consolidation of the BCR clusters, so perhaps F-actin structures under these conditions are less permissive along the lines of work of Batista on F-actin constraining BCR movement. The CK666 seems to kill both the flow in the filopodia and create barriers to condensate fusion, so it is a very different picture that looks "poisoned" with the cell being paralysed in an unexpected way. The critical experiment that should be done is to use CK666 in the Arp3 KD to determine if CK666 has effects that go beyond the best Arp3 KD you can achieve in A20? If so, it could be because of incomplete KD, dominant effects of how CK666 inhibits Apr2/3, or off target effects perhaps also targeting cellular energy. Reversibility of CK666 effects would be good to see, but might not address the issues as any toxicity that makes the effects different than the Arp3 siRNA might also be reversed. In these experiments and controls, the authors could be asked to ensure that the frequency of imaging is optimised to best reveal proposed transport processes and to distinguish these from other non-correlated events. What is hoped is that this complete set of experiments (that completes the matrix of conditions set out in the study) will resolve if CK666 has activities that are beyond Arp3 siRNA (and thus could be off target) and are all of the events associated with cSMAC formation truly correlated with F-actin mediated transport or are their processes that are either independent or even hindered by some F-actin structures.

As shown in Figure 2—figure supplement 1, the Arp3 KD is not complete, so there is likely some residual Arp2/3 activity in the siRNA-transfected cells. We feel that this is the most likely explanation for why CK-666 has a more profound effect on actin and BCR microcluster dynamics/organization. We feel that the proposed experiment in which we would treat Arp3 siRNA-transfected cells with CK-666 would not distinguish between the drug inhibiting the activity of the residual Arp2/3 complexes in the KD cells from potential off-target effects of the drug. With regard to the comment that BCR microclusters in CK-666-treated and Arp3 siRNA-transfected cells exhibit different morphology and movement, we feel that this is largely attributable to the unique morphological changes and actin remodeling exhibited by different B cells when they interact with APCs that have complex plasma membrane organization. To address this, associated with Figure 2A, B we now show videos of BCR microcluster movement in 4 representative CK-689-treated, CK-666-treated, control siRNA-transfected, and Arp3 siRNA-transfected cells (Videos 4-7) instead of just one representative cell for each condition. Importantly, to extend these analyses to larger numbers of control and Arp2/3 complex-inhibited cells, we have quantified BCR microcluster movement and cSMAC formation in multiple ways. These quantitative analyses show that, when averaged over tens of cells, the inhibition of BCR microcluster dynamics is inhibited to a similar extent by CK-666 and Arp3 siRNA. This is true for average BCR microcluster area (Figure 2E, F; note that the y-axis scales on panels E and F are different), the number of BCR-Ag clusters per cell (Figure 2—figure supplement 4C, D), the average distance of BCR microclusters from the center of total Ag fluorescence (new data in Figure 2—figure supplement 4E, F), and the number of clusters required to contain 90% of the Ag fluorescence (Figure 2—figure supplement 4I, J). Moreover, we show that CK-666 and Arp3 siRNA inhibit cSMAC formation to the same extent. In these experiments, ~15% of the CK-666-treated and Arp3 siRNA-transfected cells are still able to form cSMACs (Figure 2A, B). Consistent with this, some microclusters do exhibit centripetal movement in the CK-666-treated and Arp3 siRNA-treated cells.

With regard to the possibility that the CK-666 is poisoning the cells or targeting cellular energy generation, BCR signaling in response to soluble Ags is completely normal in the presence of CK-666 (Figure 6D, Figure 6—figure supplement 2B, Figure 8—figure supplement 1B). Moreover, PMA-induced upregulation of CD69 and CD86 is unaffected by the presence of CK-666 for the entire 18 hr duration of this experiment (Figure 9E). Finally, we also used flow cytometry to directly show that treating primary B cells with CK-666 for up to 24 hr did not result in significant cell death (Figure 2—figure supplement 2A, B, referred to in the first paragraph of the subsection “The Arp2/3 complex is required for centralization of BCR-Ag microclusters”).

In our response to previous comments, we indicated that we agree with the reviewer and now describe more clearly that centripetal movement of microclusters occurs in actin-rich regions whereas within actin-depleted microclusters aggregate and condense. Specifically, we added the following sentences:

“[…] these data suggest that Arp2/3 complex-dependent actin structures encage BCR-Ag microclusters, such that the actin retrograde flow drives their initial centripetal movement. This appears to be required for the subsequent formation of a cSMAC, which occurs in the actin-depleted central region of the cell.”

The reviewer notes that microclusters within actin-depleted regions of the CK-666-treated and Arp3 siRNA-transfected cells appear not to coalesce to the same extent as those in actin-depleted regions of control cells. In the fifth paragraph of the Discussion, we discuss how microtubules may mediate the centripetal movement of BCR microclusters across the actin-depleted central region of the contact site and facilitate the final stages of cSMAC formation. In this paragraph we note 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 towards the Ag-presenting surface. Hence, Arp2/3 complex activity may be a prerequisite for the microtubule-based centralization that leads to cSMAC formation.

Analysis of diffusive movement or random transport of the microclusters could aid identifying/discussing underlying mechanisms.

Distinguishing random diffusion from directed super-diffusive motion would indeed be interesting but is not practical in our system because the B cells are also moving on the surface of the APC to some extent. Hence, this type moment scaling spectrum analysis is not feasible in this system.

5) Requirement of retrograde flow to form a SMAC. The authors do not provide compelling evidence in support of a role for Arp2/3-mediated retrograde flow in SMAC formation in B-cell-APC pairs.

We have endeavored to clarify this point and to be more precise about the requirement of Arp2/3 complex function versus retrograde flow in cSMAC formation (which we define as >90% of the total Ag fluorescence be contained in 1-2 large central clusters). In describing how inhibiting the Arp2/3 complex impairs cSMAC formation (Figure 2), we state: “The failure to form a cSMAC when the Arp2/3 complex is depleted or inhibited was due to decreased merger of individual BCR microclusters into larger clusters … Thus, BCR-mediated gathering of APC-bound Ags into a cSMAC at the center of the synapse is strongly dependent on the functions of the Arp2/3 complex.”

We go on to say in the Discussion that our data are consistent with Arp2/3 complex-dependent retrograde flow within actin-rich regions being an initial requisite step in cSMAC formation. The coalescence of BCR microclusters in the central actin-depleted regions of the cell may not be directly dependent on the Arp2/3 complex and likely does not involve actin retrograde flow. Specifically, in the first paragraph of the Discussion, we say that Arp2/3 complex activity, which generates retrograde actin flow, facilitates the initial centripetal movement of BCR microclusters and is required for cSMAC formation. We also say that “[…] inhibiting Arp2/3 complex activity may block a critical initial step in BCR-Ag microcluster centralization”.

We feel that these are precise and accurate statements as they implicate Arp2/3 complex function in cSMAC formation but do not imply that the coalescence of BCR microclusters into a cSMAC within the actin-depleted central region of the cell is dependent on actin retrograde flow.

However, since they demonstrate that washout of CK-666 restored upregulation of CD69, a downstream effect of BCR-induced B cell activation (Figure 9—figure supplement 3), a question is whether or not a SMAC will form in B-cell-APC pairs upon washout of CK666. If the appropriate time-lapse imaging were used to simultaneously observe GFP-F-tractin in B-cells during washout of a CK-666 block, direct observations of F-actin retrograde flow and cluster flow during SMAC formation may be possible.

Confirming that washing out the CK-666 drug restores BCR microcluster coalescence and cSMAC formation, and that this correlates with the restoration of CD69 upregulation (which had been shown in Figure 9—figure supplement 4 of the original manuscript) is an excellent suggestion. We have now carried out such an experiment using fixed cell imaging, which was sufficient to demonstrate that this is in fact the case. These new data are shown in Figure 9—figure supplement 4B-D. We now say “Once the drug was removed, the cells recovered their ability to aggregate BCR microclusters and form a cSMAC (Figure 9—figure supplement 4B-D) and B cell activation could proceed normally, consistent with the effects of CK-666 on actin dynamics being rapidly reversible (Yang et al., 2012).”

6) Finally, centripetal retrograde flow could be driven by a myosin-dependent process. This could be examined directly using inhibitors of myosin II. Disruption of global Arp2/3 complex actin networks is expected to exert perturbations on the whole cell cytoskeleton. Pinpointing the specific Arp2/3 dependent-activities during B-cell signaling will be challenging using this somewhat sledge-hammer approach.

We addressed this question by using pnBB to directly inhibit myosin and now show in Figure 9—figure supplement 5C, D that this does not prevent BCR microclusters from coalescing into a cSMAC, a process that we demonstrated is dependent on Arp2/3 complex activity and is associated with microcluster centripetal movement that is mediated by actin retrograde flow. This argues that the Arp2/3 complex does not act via a myosin-dependent process to drive centripetal movement of BCR microclusters.

However, the role of myosin in B cell responses to APC-bound Ags is an interesting question and we have now addressed this in Figure 9—figure supplement 5A, B. We found that treating primary B cells with pnBB caused a small decrease in the upregulation of CD69 or CD86, which was not statistically significant (i.e. p>0.05). This is in contrast to the Arp2/3 complex inhibitor CK-666, which caused significant reductions in these B cell activation responses. This indicates that the Arp2/3 complex has a more important role in APC-induced B cell activation than myosin. These new experiments are described in the sixth paragraph of the Results subsection “Arp2/3 complex activity is important for BCR-induced B cell activation responses”.

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

• 3,882

  Page views

• 508

  Downloads

• 26

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.