A B-cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation

  1. Jia C Wang
  2. Yang-In Yim
  3. Xufeng Wu
  4. Valentin Jaumouille
  5. Andrew Cameron
  6. Clare M Waterman
  7. John H Kehrl
  8. John A Hammer  Is a corresponding author
  1. Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, United States
  2. Light Microscopy Core, National Heart, Lung and Blood Institute, National Institutes of Health, United States
  3. B Cell Molecular Immunology Section, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, United States

Abstract

B-cell activation and immune synapse (IS) formation with membrane-bound antigens are actin-dependent processes that scale positively with the strength of antigen-induced signals. Importantly, ligating the B-cell integrin, LFA-1, with ICAM-1 promotes IS formation when antigen is limiting. Whether the actin cytoskeleton plays a specific role in integrin-dependent IS formation is unknown. Here, we show using super-resolution imaging of mouse primary B cells that LFA-1:ICAM-1 interactions promote the formation of an actomyosin network that dominates the B-cell IS. This network is created by the formin mDia1, organized into concentric, contractile arcs by myosin 2A, and flows inward at the same rate as B-cell receptor (BCR):antigen clusters. Consistently, individual BCR microclusters are swept inward by individual actomyosin arcs. Under conditions where integrin is required for synapse formation, inhibiting myosin impairs synapse formation, as evidenced by reduced antigen centralization, diminished BCR signaling, and defective signaling protein distribution at the synapse. Together, these results argue that a contractile actomyosin arc network plays a key role in the mechanism by which LFA-1 co-stimulation promotes B-cell activation and IS formation.

Editor's evaluation

This study has used striking live-cell super-resolution microscopy methods to demonstrate the direct relationship between integrin dependent F-actin/myosin arcs and transport of surface immunoglobulin-antigen clusters in B-cell synapses. The function of the F-actin arcs in signaling at limiting antigen levels where integrins are important is also demonstrated. In addition, this study has shown that both follicular and germinal center B cells utilize the F-actin arcs, suggesting that this machinery can operate in both initiation and affinity maturation phases of antibody-based adaptive immunity. The work will be of interests to immunologists, cell biologists, and biophysicists, and the data sets should be of future use in modeling the process.

https://doi.org/10.7554/eLife.72805.sa0

eLife digest

The immune system has the ability to recognize a vast array of infections and trigger rapid responses. This defense mechanism is mediated in part by B cells which make antibodies that can neutralize or destroy specific disease-causing agents. When pathogens (such as bacteria or viruses) invade the body, a specialized immune cell called an ‘antigen presenting cell’ holds it in place and presents it to the B cell to examine. Receptors on the surface of the B cell then bind to the infectious agent and launch the B cell into action, triggering the antibody response needed to remove the pathogen.

This process relies on B cells and antigen presenting cells making a close connection called an immune synapse, which has a bulls-eye pattern with the receptor in the middle surrounded by sticky proteins called adhesion molecules. A network of actin filaments coating the inside of the B cell are responsible for arranging the proteins into this bulls-eye shape. Once fully formed, the synapse initiates the production of antibodies and helps B cells to make stronger versions of these defensive proteins.

So far, most studies have focused on the role the receptor plays in B cell activation. However, when there are only small amounts of the pathogen available, these receptors bind to the antigen presenting cell very weakly. When this happens, adhesion molecules have been shown to step in and promote the formation of the mature synapse needed for B cell activation. But it is not fully understood how adhesion molecules do this.

To investigate, Wang et al. looked at mouse B cells using super resolution microscopes. This revealed that when B cells receive signals through both their receptors and their adhesion molecules, they rearrange their actin into a circular structure composed of arc shapes. Motors on the actin arcs then contract the structure inwards, pushing the B cell receptors into the classic bullseye pattern. This only happened when adhesion molecules were present and signals through the B cell receptors were weak.

These findings suggest that adhesion molecules help form immune synapses and activate B cells by modifying the actin network so it can drive the re-patterning of receptor proteins. B cells are responsible for the long-term immunity provided by vaccines. Thus, it is possible that the findings of Wang et al. could be harnessed to create vaccines that trigger a stronger antibody response.

Introduction

B-cell receptor (BCR) engagement with cognate antigen triggers striking changes in B-cell physiology that promote B-cell activation, immune synapse (IS) formation, and B-cell effector functions (Forthal, 2014; Heesters et al., 2016; Harwood and Batista, 2011). These changes include dramatic increases in actin filament assembly and dynamics that are thought to drive IS formation in B cells engaged with membrane-bound antigen (Forthal, 2014; Heesters et al., 2016; Harwood and Batista, 2011; Gonzalez et al., 2011). For B cells in vivo, this usually involves interactions with antigen bound to the surface of an antigen-presenting cell (APC) (Gonzalez et al., 2011; Carrasco and Batista, 2006a; Cyster, 2010), although activating surfaces such as antigen-coated glass and planar lipid bilayers (PLBs) containing freely diffusing antigen are used to mimic these in vivo interactions. IS formation in these contexts is initiated by the formation of a radially symmetric, Arp2/3 complex-dependent branched actin network at the outer edge of the IS (i.e., in the distal supramolecular activation cluster [dSMAC]) (Wang and Hammer, 2020; Song et al., 2014). This lamellipodia-like actin network drives the spreading of the B cell across the antigen-coated surface, thereby promoting BCR:antigen interactions (Harwood and Batista, 2011; Fleire et al., 2006). Once the B cell is fully spread, the continued polymerization of branched actin at the outer edge of the dSMAC generates a centripetal or retrograde flow of actin that drives the movement of BCR:antigen clusters (Tolar et al., 2009; Mattila et al., 2016; Treanor et al., 2009) towards the center of the synapse (i.e., to the central SMAC [cSMAC]) (Song et al., 2014; Bolger-Munro et al., 2019). This centripetal actin flow, combined with an overall contraction of the B cell, is thought to be responsible for the transport of BCR:antigen clusters to the center of the maturing synapse (Bolger-Munro et al., 2019). Importantly, this process of antigen centralization is required for robust BCR signaling (Harwood and Batista, 2011; Mattila et al., 2016; Batista et al., 2010) and is thought to be a prerequisite for antigen internalization by follicular B cells (Batista et al., 2001; Yuseff et al., 2013; Yuseff and Lennon-Duménil, 2015).

Antigen-induced IS formation scales with the strength of antigen-induced signals such that IS formation and B-cell activation are attenuated when membrane-bound antigen binds the BCR weakly or is presented at low density. Importantly, co-stimulatory signals can promote IS formation and B-cell activation under both of these conditions (Carrasco et al., 2004; Carrasco and Batista, 2006b). Seminal work from Carrasco and colleagues showed that the B-cell integrin LFA-1, which binds the adhesion molecule ICAM-1 present on the surface of APCs (Springer, 1990; Springer et al., 1987), serves as one such co-stimulatory signal (Carrasco et al., 2004). This conclusion was based on four key observations. First, B cells responded robustly to higher affinity membrane-bound antigens presented at high density whether or not ICAM-1 was present on the membrane. Second, the robust activation of B cells in response to antigens of all affinities increasingly required ICAM-1 in the membrane as the density of the antigen was lowered. Third, this co-stimulatory effect was most dramatic for weaker antigens. Finally, this latter effect was not observed in B cells lacking LFA-1. With regard to the underlying mechanism, IRM imaging suggested that LFA-1:ICAM-1 interactions, which were shown to concentrate in the medial portion of the synapse (i.e., the peripheral SMAC [pSMAC]), lower the threshold for B-cell activation by enhancing cell adhesion.

While the actin cytoskeleton clearly plays a central role in driving IS formation, whether it plays a specific role in integrin-dependent IS formation is unknown. This is an important question as most B-cell interactions with professional APCs presenting cognate antigen involve integrin ligation. Relevant to this question, the dendritic actin network occupying the outer dSMAC ring, which is thought to be the main driver of IS formation, has been observed primarily in cells that received antigen stimulation alone and almost exclusively in immortalized B cell lines (Bolger-Munro et al., 2019; Wang et al., 2018; Freeman et al., 2011; Liu et al., 2012; Wang et al., 2017). It is not known, therefore, whether integrin-co-stimulation alters the organization and/or dynamics of actin at the B-cell IS. Moreover, we are only just beginning to elucidate the organization and dynamics of synaptic actin networks formed by primary B cells. Here, we show that LFA-1:ICAM-1 interactions in primary B cells stimulate the formation of a contractile actomyosin arc network that occupies the pSMAC portion of the synapse. This actomyosin network represents the major actin structure at the IS of primary B cells receiving integrin co-stimulation, and its dynamics drive antigen centralization by sweeping antigen centripetally. Importantly, under conditions of limiting antigen, where integrin co-stimulation is required for IS formation, blocking the contractility of this pSMAC network inhibits IS formation and BCR signaling. Finally, we show that germinal center (GC) B cells can also create this actomyosin structure, suggesting that it may contribute to the function of GC B cells as well. Together, our data demonstrate that a contractile actomyosin arc network created downstream of integrin ligation plays a major role in the mechanism by which integrin co-stimulation promotes B-cell activation and IS formation when antigen is limiting. Importantly, these findings highlight the need for including integrin co-stimulation when examining the role of actin during B-cell activation, especially under physiologically relevant conditions.

Results

Integrin co-stimulation promotes the formation of an actin arc network in the pSMAC

To investigate the possibility that LFA-1 ligation might also promote B-cell activation by triggering a significant change in synaptic actin organization, we imaged F-actin at ISs formed by primary mouse B cells on glass surfaces coated with either anti-IgM or anti-IgM plus ICAM-1. F-actin was visualized using GFP-F-Tractin, a dynamic reporter for F-actin (Yi et al., 2012; Murugesan et al., 2016), and two super-resolution imaging modalities: Airyscan (xy resolution ~140 nm) and total internal reflection fluorescence-structured illumination microscopy (TIRF-SIM; xy resolution ~100 nm). Individual video frames of anti-IgM-engaged B cells using both imaging modalities (Figure 1A and B), together with the corresponding videos (Video 1A and B), revealed a thin, bright, highly dynamic outer rim of F-actin (white arrows in Figure 1A and B) that likely corresponds to the branched actin network comprising the dSMAC (Bolger-Munro et al., 2019; Wang et al., 2018; Wang et al., 2017). Both modalities (but especially TIRF-SIM) showed that the F-actin present inside this outer dSMAC rim is composed of a highly disorganized mixture of short-actin filaments/fibers and actin foci (blue brackets in Figure 1A and B), similarly to those observed previously in HeLa cells (Fritzsche et al., 2017). In sharp contrast, individual video frames of anti-IgM + ICAM-1-engaged B cells using both modalities (Figure 1C and D), together with the corresponding videos (Video 2A and B), showed a highly organized network inside the outer dSMAC rim (i.e., in the pSMAC) that is comprised of concentric actin arcs (blue brackets and magenta arrows in Figure 1C and D). The difference in synaptic actin organization between anti-IgM-engaged B cells and anti-IgM + ICAM-1-engaged B cells is very evident in enlarged TIRF-SIM images. While it is challenging to define SMAC boundaries and any pattern of F-actin organization in the pSMAC of B cells engaged with anti-IgM alone (Figure 1E1 and E2), SMAC boundaries and pSMAC F-actin organization are both very distinct in B cells engaged using anti-IgM + ICAM-1 (Figure 1F1 and F2). Consistently, scoring B cells for the presence of any discernable arcs showed that the addition of ICAM-1 increases the percentage of such cells from ~30% to ~70% (Figure 1G). Importantly, static and dynamic imaging showed that the arcs in cells engaged with anti-IgM alone are sparse and transient (Figure 1A and B, Video 1A and B), while those in cells engaged with both anti-IgM and ICAM-1 are dense and persistent (Figure 1C and D, Video 2A and B). In other words, when B cells receiving only anti-IgM stimulation do form discernible arcs (e.g., see those marked by magenta arrows in Figure 1A and B), they are much sparser and less persistent than those formed by cells also receiving ICAM-1 stimulation. Moreover, we could not find any B cells receiving anti-IgM stimulation alone that possessed a robust actin arc network. Consistently, measuring the degree of alignment between actin filaments in the pSMAC portion of B cells stimulated with anti-IgM alone versus both anti-IgM and ICAM-1, which were made using FibrilTool (Boudaoud et al., 2014), revealed a large shift towards more organized pSMAC actin when ICAM-1 was included (Figure 1—figure supplement 1A1–A3; see the figure legend for details). Finally, measuring the percentage of total synaptic F-actin content within each SMAC (Figure 1H), and the percentage of total IS footprint occupied by each SMAC (Figure 1I), showed that the actin arc-containing pSMAC comprises the major actin network at the IS of primary B cells engaged using both anti-IgM and ICAM-1. Together, these results demonstrate that LFA-1 co-stimulation promotes the formation of a pSMAC actin arc network that dominates the B-cell IS.

Figure 1 with 1 supplement see all
ICAM-1 co-stimulation promotes the formation of actin arcs at the B-cell immune synapse.

(A–F) GFP-F-Tractin-expressing primary B cells on glass coated with anti-IgM alone (A, B, E1, E2) or with anti-IgM + ICAM-1 (C, D, F1, F2) and imaged using Airyscan (A, C) or TIRF-SIM (B, D, E1, E2, F1, F2). The white arrows in (A) and (B) indicate the thin outer rim of dendritic actin in the dSMAC. The blue bars in (A–D) indicate the pSMAC. (E2) and (F2) correspond to the boxed regions in (E1) and (F1), respectively. Of note, the cell shown in (E1/E2) is representative of ~70% of anti-IgM-stimulated cells, while the cell shown in (F1/F2) is representative of ~70% of anti-IgM + ICAM-1-stimulated cells. (G) Percent of cells with pSMAC actin arcs (N > 67 cells/condition from three experiments). (H, I) Percent of total synaptic F-actin (H) and percent of total IS footprint (I) contained within the dSMAC, pSMAC, and cSMAC portions of the synapse for primary B cells on anti-IgG/ICAM-1-coated glass (N = 44 cells/condition from six experiments). (J1, J2) GFP-F-Tractin-expressing A20 B cell on anti-IgG/ICAM-1-coated glass. (J2) corresponds to the boxed region in (J1). The magenta arrows in (A–D) and (J1) indicate actin arcs. Scale bars: 10 µm.

Video 1
Representative primary B cells expressing GFP-F-Tractin on glass coated with anti-IgM that were imaged every 3 s for 120 s using Airyscan (A) and TIRF-SIM (B).

Played back at 10 fps. Scale bar: 5 μm.

Video 2
Representative primary B cells expressing GFP-F-Tractin on glass coated with anti-IgM and ICAM-1 that were imaged every 2 s for 120 s using Airyscan (A) and every 5 s for 600 s using TIRF-SIM (B).

Played back at 10 fps. Scale bars: 5 μm.

Linear actin filaments generated by the formin mDia1 at the outer edge of the synapse give rise to the pSMAC actin arc network

We next sought to define the origin of the actin arcs that comprise the pSMAC of B cells stimulated using both anti-IgM and ICAM-1. Primary B cells stimulated in this way exhibit small, actin-rich surface spikes at the outer synapse edge (Figure 2A). Importantly, magnified images revealed that the actin within these spikes continues into the cytoplasm in the form of linear actin filaments (Figure 2B1 and B2). Moreover, tracing these linear actin filaments showed that they are contiguous with the pSMAC actin arcs (Figure 2C1 and C2, Video 3A and B). These results argue that linear actin filaments nucleated at the plasma membrane at the outer edge of the synapse give rise to the actin arcs populating the pSMAC. While these results do not identify the specific nucleator involved, they do point to it being a member of the formin family based on the fact that the actin being made is linear and nucleated at the plasma membrane (Goode and Eck, 2007; Breitsprecher and Goode, 2013). Consistent with this conjecture, and with the fact that formins incorporate fluorescent protein-labeled actin monomer into filaments poorly (Yi et al., 2012; Murugesan et al., 2016; Chen et al., 2012), we did not see fluorescent actin arcs in B cells expressing mEOS-labeled G-actin (Video 4).

Figure 2 with 2 supplements see all
The actin arcs are created by the formin mDia1 acting at the outer edge of the immune synapse.

(A) GFP-F-Tractin-expressing primary B cell on anti-IgG/ICAM-1-coated glass. (B1, B2) Boxed regions in (A). (C1, C2) B1 and B2 with magenta lines applied to highlight linear actin filaments/bundles arising from surface spikes at the IS edge that are contiguous with actin arcs in the pSMAC. (D1, D2) GFP-F-Tractin-expressing primary B cell on anti-IgG/ICAM-1-coated glass before (D1) and 6 min after SMIFH2 addition (D2). (E) F-actin intensity profiles corresponding to the line scans in (D1) (blue, before SMIFH2 addition) and (D2) (magenta, after SMIFH2 addition). (F1–F4) F-Tractin mNeonGreen-expressing A20 B cells transfected with vector only or the indicated mDia1 miRNA constructs and activated on anti-IgG/ICAM-1-coated glass. (G) Ratio of pSMAC to dSMAC F-actin (N > 20 cells/condition from two experiments). (H) pSMAC F-actin content (N = 20–26 cells/condition from two experiments). (A–C, F) TIRF-SIM images; (D) Airyscan images. Scale bars: 5 µm in (A, D2, F1); 2 µm in (B1).

Video 3
A representative primary B cell expressing GFP-F-Tractin on glass coated with anti-IgM and ICAM-1 that was imaged every 3 s for 300 s using TIRF-SIM (A).

A magnified view of the region boxed in white in (A) is shown in (B).Played back at 10 fps. Scale bars: 5 μm (A), 1 μm (B).

Video 4
A representative A20 B cell expressing mEOS-actin on glass coated with anti-IgG and ICAM-1 that was imaged every 1.8 s for 70 s using Airyscan.

Played back at 7 fps. Scale bar: 5 μm.

To test if a formin is indeed responsible for creating the pSMAC actin arc network, we used the pan-formin inhibitor SMIFH2 (Rizvi et al., 2009). Figure 2D1 and D2, together with the line scan in Figure 2E, show that the pSMAC actin arcs present in a representative primary B cell immediately before SMIFH2 addition (blue trace) had largely disappeared 6 min after adding SMIFH2 (magenta trace). Given recent concerns about the specificity of SMIFH2 (Nishimura et al., 2021), we used three different miRNAs to knock down the formin mDia1 in the lymphoma B cell line A20 (Figure 2—figure supplement 1A and B), which also forms pSMAC actin arcs when stimulated using anti-IgG + ICAM-1 (Figure 1J1 and J2, Video 5A). mDia1 was chosen as the miRNA target as it is highly expressed in B cells (ImmGen Database) and is largely responsible for making actin arcs in T cells (Murugesan et al., 2016). Compared to control A20 B cells (Figure 2F1), representative B cells expressing each of the three miRNAs (Figure 2F2–F4) were largely devoid of actin arcs. This difference was supported by quantitating the ratio of pSMAC to dSMAC F-actin (Figure 2G), as well as the amount of F-actin in the pSMAC (Figure 2H). Finally, actin arcs were unaffected by the expression of two different nontargeting miRNAs (Figure 2—figure supplement 1C1–C4 and D1–D4). Together, these results argue that the pSMAC actin arcs are indeed created by a formin, and that the formin mDia1 likely plays a major role.

Video 5
A representative A20 B cell expressing GFP-F-Tractin on glass coated with anti-IgG and ICAM-1 that was imaged every 1.5 s for 120 s using TIRF-SIM (A).

A representative A20 B cell in which we had inserted mScarleti at the N-terminus of M2A using CRISPR (magenta) that was transfected with GFP-F-Tractin (green), activated on glass coated with anti-IgG and ICAM-1, and imaged every 3 s for 120 s using TIRF-SIM (B). Played back at 10 fps. Scale bars: 5 μm.

To provide further evidence that the arcs are created by a formin, we imaged A20 B cells following the addition of the Arp2/3 inhibitor CK-666. The rationale for this experiment lies in the recent revelation that the two major consumers of actin monomer in cells, the Arp2/3 complex and formins, are always competing for a limiting pool of actin monomer (Burke et al., 2014; Lomakin et al., 2015; Fritzsche et al., 2016; Hammer et al., 2019). One consequence of this competition is that when one of these nucleators is inhibited, the actin structures created by the other nucleator get more robust because that nucleator now gets more monomer. For example, inhibiting the Arp2/3 complex promotes the formation of formin-dependent actin networks in both yeast and vertebrate cells (Murugesan et al., 2016; Burke et al., 2014; Lomakin et al., 2015; Fritzsche et al., 2016; Hammer et al., 2019). Given this, and assuming that the arcs in B cells are formin-generated, then inhibiting the Arp2/3 complex in B cells should lead not only to a diminution of the branched actin network in the dSMAC, but also to an amplification of the arc network in the pSMAC. Consistently, Figure 2—figure supplement 2A1/A2 (before CK-666 addition) and Figure 2—figure supplement 2A3/A4 (after CK-666 addition) together show that CK-666 addition leads not only to a reduction in the size of the dSMAC (magenta brackets), but also to an increase in arc content in the pSMAC (blue brackets). These changes were supported by measuring the percentage of total synaptic F-actin content residing within each SMAC (Figure 2—figure supplement 2B), which revealed a significant shift away from dSMAC F-actin and toward pSMAC F-actin following CK-666 treatment. This shift was also reflected in measurements of total pSMAC F-actin content (Figure 2—figure supplement 2C), the ratio of pSMAC to cSMAC F-actin content (Figure 2—figure supplement 2D), and the ratio of pSMAC to cSMAC area (Figure 2—figure supplement 2E). Taken together, these data argue strongly that linear actin filaments generated by the formin mDia1 at the outer edge of the synapse give rise to the pSMAC actin arc network.

Myosin 2A co-localizes with the actin arcs

Having established that ICAM-1 co-stimulation promotes the formin-dependent formation of actin arcs in the pSMAC, we asked how these arcs are organized into concentric structures. Formin-derived linear actin filaments are commonly organized into well-defined structures such as stress fibers, transverse arcs, and the contractile ring in dividing cells by bipolar filaments of the actin-based motor protein myosin 2 (Vicente-Manzanares et al., 2009; Sellers, 2000; Shutova and Svitkina, 2018). We decided, therefore, to test whether myosin 2 co-localizes with the actin arcs and is required for their concentric organization.

To define the localization and dynamics of myosin 2 at the B-cell IS, we used primary B cells isolated from a mouse in which GFP had been knocked into the N- terminus of the myosin 2A heavy chain gene Myh9 (referred to herein as M2A) (Zhang et al., 2012) as M2A is the only myosin 2 isoform expressed in B cells (ImmGen Database). Individual video frames of these cells following transfection with Td-Tomato-F-Tractin and attachment to coverslips coated with anti-IgM and ICAM-1 revealed a dramatic co-localization between M2A and the actin arcs in the pSMAC (Figure 3A1–A3, Video 6). Magnified TIRF-SIM images show that the myosin signals align with actin arcs in a periodic fashion (Figure 3A4) that resembles other myosin 2-rich, linear actin structures like stress fibers and the contractile ring (Beach et al., 2014). Moreover, these myosin signals exhibit the SIM signature for M2A bipolar filaments when M2A is GFP-labeled at its N-terminus (Beach et al., 2017), which is a pair of GFP puncta spaced ~300 nm apart (Figure 3A5; 304 ± 32 nm; n = 230 filaments from 12 cells). The presence of M2A filaments in the medial portion of the synapse was also evident in primary B cells isolated from a mouse in which mCherry had been knocked into the N-terminus of M2A (Figure 3—figure supplement 1A), primary B cells that we genome-edited using CRISPR to place GFP at the N-terminus of M2A (Figure 3—figure supplement 1B), and A20 B cells that we genome edited using CRISPR to place mScarleti at the N-terminus of M2A and then transfected with GFP-F-Tractin (Figure 3—figure supplement 1C1–C3, Video 5B). Finally, 3D-SIM images of A20 B cells that were fixed and stained for M2A and F-actin showed that endogenous M2A also co-localizes with the actin arcs (Figure 3—figure supplement 1D1–D3; note that the signature for M2A filaments using this antibody, which recognizes the C-terminus of M2A, is a single fluorescent punctum that corresponds to the center of an individual M2A filament) (Beach et al., 2014; Beach and Hammer, 2015). The extent of this co-localization was even clearer in enlarged images of immunostained cells (Figure 3—figure supplement 1E1–E3), where line scans showed endogenous M2A coinciding with actin arcs (Figure 3—figure supplement 1F). Together, these results show that the actin arc network in primary B cells receiving ICAM-1 co-stimulation is in fact an actomyosin arc network.

Figure 3 with 2 supplements see all
Myosin 2A decorates the actin arcs and is required for their concentric organization.

(A1–A5) Td-Tomato-F-Tractin-expressing primary B cell from the M2A-GFP knockin mouse on anti-IgM/ICAM-1-coated glass. (A4) and (A5) correspond to the boxed regions in (A1) and (A2), respectively. (B1–B6) Still images at the indicated time points taken from a region within Video 7 of a Td-Tomato-F-Tractin-expressing primary B cell from the M2A-GFP knockin mouse. Different color arrowheads mark the formation and centripetal movement of individual M2A bipolar filaments (see text for details). (C, D) Phalloidin-stained primary B cell from the M2A-GFP knockin mouse on glass coated with anti-IgM alone (C) or with anti-IgM + ICAM-1 (D). (E) Total synaptic M2A content (N = 91–115 cells/condition from three experiments). (F, G) GFP-F-Tractin-expressing primary B cells that had been pretreated with DMSO (F) or pnBB (G) for 30 min and activated on anti-IgM/ICAM-1-coated glass. (H) Anisotropy of the actin filaments/bundles present within the pSMAC (N = 369–423 regions of interest [ROIs] from 30 to 37 cells from three experiments). All panels: TIRF-SIM images. Scale bars: 5 µm in (A3, D, G); 3 µm in (A4, B6); 250 nm in (A5).

Video 6
A representative primary B cell from a M2A-GFP knockin mouse expressing Td-Tomato-F-Tractin on glass coated with anti-IgM and ICAM-1 that was imaged every 3 s for 300 s using TIRF-SIM.

Played back at 10 fps. Scale bar: 5 μm.

To gain insight into how the arcs become decorated with M2A filaments, we examined time-lapse TIRF-SIM images of GFP-M2A knockin primary B cells expressing Td-Tomato F-Tractin. Individual video frames (Figure 3B1–B6), as well as the corresponding video (Video 7), show that bipolar filaments of M2A begin to appear near the dSMAC:pSMAC boundary in association with the linear actin filaments/bundles exiting the dSMAC (white, yellow, and fuchsia arrowheads mark such myosin filaments at time 0 s in Figure 3B1). As time progresses, these filaments move centripetally and undergo expansion into filament clusters (Figure 3B1–B6; see also Video 7). This expansion, in which individual myosin filaments expand into a small cluster of filaments, is presumably driven by the same sequential amplification pathway described previously for M2A filament assembly in fibroblasts (Beach et al., 2017). Finally, the myosin filaments in these clusters begin to align with the arcs forming at the outer edge of the pSMAC, which then merge with the larger actomyosin arc network in the pSMAC (Figure 3B1–B6). As all this is happening, new myosin filaments keep appearing near the dSMAC:pSMAC boundary to repeat the process (Figure 3B2–B6; follow the blue, green, and purple arrowheads).

Video 7
A magnified view of a region within Video 6.

The applied arrowheads mark various aspects of M2A filament assembly and organization as explained in the text for Figure 3B1–B6. Scale bar: 1 μm.

Given that ICAM-1 co-stimulation promotes the formation of actin arcs and that the arcs recruit M2A, ICAM-1 co-stimulation should also result in an increase in the amount of M2A at the IS. Consistently, primary GFP-M2A knockin B cells receiving both anti-IgM and ICAM-1 stimulation exhibited a greater amount of synaptic M2A than B cells receiving only anti-IgM stimulation (Figure 3C–E). Of note, this difference remained significant even after normalizing the M2A fluorescence for a small difference in the average cell-spread area under these two conditions (Figure 3—figure supplement 1G1–G2).

Myosin 2A contractility is required for the concentric organization of the actin arcs and integrin-dependent traction force

The organization of formin-generated linear actin filaments into well-defined structures is typically driven by the contractility of myosin 2 filaments (Vicente-Manzanares et al., 2009; Sellers, 2000). Therefore, we asked if M2A contractility is required for the concentric organization of the pSMAC actin arcs by treating cells with para-nitroblebbistatin (pnBB), a blue light-insensitive version of the cell-permeable, small molecule myosin 2 inhibitor blebbistatin (BB) that blocks myosin 2-based contractility by locking the myosin in its weak actin binding state (Képiró et al., 2014). While control, DMSO-treated cells exhibited concentric actin arcs in their pSMAC as expected (Figure 3F), cells treated with 25 μM pnBB displayed highly disorganized, mesh-like actin arrays in their pSMAC (Figure 3G). Consistently, anisotropy measurements made using FibrilTool revealed a dramatic shift towards more disorganized pSMAC actin when B cells are treated with pnBB (Figure 3H). Together, these results demonstrate that M2A contractility is indeed required for the concentric organization of the pSMAC actin arcs.

We used traction force microscopy in combination with pnBB to ask if integrin-dependent traction forces that B cells exert on a deformable substrate require M2A contractility. As expected (Wang, 2018; Kumari et al., 2019), B cells engaged with substrate coated with anti-IgM and ICAM-1 generated significantly more traction force than B cells engaged with substrate coated with anti-IgM alone (Figure 3—figure supplement 2A1, A2, B1, B2, and D). Importantly, ICAM-1-dependent traction forces were completely abrogated by pretreating the cells with pnBB (Figure 3—figure supplement 2C1, C2, and D), indicating that the generation of integrin-dependent traction forces requires M2A contractility. This requirement likely reflects pulling forces exerted by M2A on the substrate through LFA-1:ICAM-1 pairs, combined with the increase in M2A content at the synapse caused by ligating LFA-1 with ICAM-1, and the contribution that M2A-dependent pulling forces make in keeping LFA-1 in its open, active conformation (Gardel et al., 2010; Case and Waterman, 2015; Comrie and Burkhardt, 2016). These results, together with the fact that integrin clusters are known to accumulate in the pSMAC portion of the B-cell IS (Carrasco et al., 2004; Carrasco and Batista, 2006b), suggest a feed-forward relationship where integrin ligation promotes the formation of pSMAC actomyosin arcs, and the contractile forces exerted by these actomyosin arcs promote further integrin activation and robust adhesion in the pSMAC.

The actomyosin arc network in the pSMAC exhibits centripetal flow

Inward flows of cortical actin networks are thought to drive the transport of antigen receptor clusters to the center of maturing synapses in both T cells and B cells (Wang and Hammer, 2020; Hammer et al., 2019; Blumenthal and Burkhardt, 2020; although see Schnyder et al., 2011; Babich and Burkhardt, 2011). For B cells, the clearest example of this to date is the demonstration that the centripetal flow of the branched actin network comprising the dSMAC propels BCR:antigen clusters towards the cSMAC (Bolger-Munro et al., 2019). As a prelude to asking whether the actomyosin arcs comprising the pSMAC also contribute to antigen centralization, we asked if this contractile network exhibits centripetal flow. Kymograph analyses of actin flow across synapses made by primary B cells expressing GFP-F-Tractin showed that their pSMAC actomyosin arc network indeed flows centripetally at 1.07 ± 0.07 µm/min, or about one-third the rate of centripetal actin flow in the dSMAC (2.89 ± 0.18 µm/min) (Figure 4—figure supplement 1A1–A3). Similar results were obtained for A20 B cells (pSMAC rate: 0.97 ± 0.13 µm/min; dSMAC rate: 3.16 ± 0.35 µm/min) (Figure 4—figure supplement 1B1–B3). Together, these results indicate that the actomyosin arcs could contribute along with the branched actin network in the dSMAC to the inward transport of BCR:antigen clusters.

Actomyosin arcs contribute to antigen centralization by sweeping BCR:antigen clusters inward

We used PLBs to determine if the actomyosin arcs do in fact contribute to antigen centralization. As expected, primary B cells expressing GFP-F-Tractin readily formed actin arcs when PLBs contained both anti-IgM and ICAM-1 (Video 8A), but not when they contained anti-IgM alone (Video 8B). Also as expected, primary B cells engaged with PLBs containing fluorescent anti-IgM (magenta) and unlabeled ICAM-1 yielded mature synapses in which concentric actin arcs surrounded antigen accumulated in the cSMAC (Figure 4A1–A3, white arrows). To obtain a holistic view of antigen centralization, we imaged antigen clusters in the dSMAC and pSMAC of primary B cells over time with the aim of correlating their rates of centripetal transport with the distinct rates of centripetal actin flow exhibited by these two IS zones (Video 9). Tracking of single-antigen microclusters showed that they moved inward at 2.36 ± 1.1 µm/min and 1.03 ± 0.3 µm/min across the dSMAC (magenta tracks) and pSMAC (green tracks), respectively (Figure 4B and C). Importantly, these rates are very similar to the rates of centripetal actin flow across the dSMAC and pSMAC, respectively (Figure 4—figure supplement 1A1–A3). Together, these observations argue that the pSMAC actomyosin arc network works together with the dSMAC branched actin network to drive antigen centralization.

Video 8
Representative primary B cells expressing GFP-F-Tractin on PLBs containing anti-IgM and ICAM-1 (A) or anti-IgM alone (B) that were imaged every 5 s for 300 s using TIRF-SIM and played back at 8 fps.

Scale bar: 5 μm.

Figure 4 with 1 supplement see all
Actin arcs sweep antigen clusters centripetally.

(A1–A3) Phalloidin-stained (green) primary B cell 15 min after engagement with a PLB containing unlabeled ICAM-1 and limiting anti-IgM (magenta). The white arrows in (A1) and (A3) mark the actin arcs. (B) Tracks of single anti-IgM microclusters traveling centripetally across the dSMAC (magenta tracks) and pSMAC (green tracks) acquired from Video 9. The white line indicates the outer edge of this cell. (C) Mean speed of single anti-IgM microclusters moving centripetally across the dSMAC and pSMAC (N = 180–273 tracks from three well-spread cells). (D1–D6) Still images at the indicated time points from Video 10 showing the centripetal movement of actin arcs and a representative anti-IgM microcluster (white arrows) (the center of the synapse is directly below the images). Transparent white lines highlight the actin arcs that moved the microcluster centripetally. (E1–E6) Same as (D1–D6) except showing only the anti-IgM microcluster and indicating its centripetal path in blue. (F) Temporally pseudo-colored, projected image of the anti-IgM microcluster in (D) and (E). (G) Kymograph of the 3-µm-long paths taken by the microcluster and the actin arcs in (D) and (E) over a period of 400 s. The white brackets on the right indicate where actin arcs overlapped with and moved the microcluster, while the magenta brackets indicate where the movement of the microcluster stalled. (A) Airyscan images; (D–G) TIRF-SIM images. Scale bars: 5 µm in (A3, B); 300 nm in (D6, F).

Video 9
A representative primary B cell on a PLB containing fluorescent anti-IgM (white) and unlabeled ICAM-1 that was imaged every 5 s for 345 s using TIRF-SIM.

Played back at 10 fps. Scale bar: 5 μm.

To identify the mechanism by which the actomyosin arcs drive antigen centralization, we imaged F-actin and anti-IgM in the medial portion of forming synapses at high magnification using TIRF-SIM. Anti-IgM microclusters were seen to move across the pSMAC towards the cSMAC (which in the following images was in the down direction) while embedded in an arc network moving in the same direction (Video 10). White lines in Video 10 and in the corresponding still images in Figure 4D1–D6 mark actin arcs that were sweeping an individual anti-IgM microcluster inward (Figure 4E1–E6). Figure 4F shows the trajectory of this microcluster (temporally color-coded) as it moved towards the cSMAC. Finally, a kymograph of this trajectory (Figure 4G) shows that several actin arcs contributed to the inward movement of this microcluster (areas bracketed in white), and that pauses in movement (areas bracketed in pink) occurred where no actin signal was immediately adjacent to the microcluster. Together, these results argue that individual actin arcs move individual BCR:antigen microclusters inward via a sweeping mechanism that likely depends on frictional coupling between the actin arc and microcluster (Yu et al., 2010; Ditlev et al., 2019; Smoligovets et al., 2012). While arcs can slip past microclusters, the overall incidence of such slippage must be fairly small as the rate of inward antigen transport across the pSMAC (Figure 4C) is not significantly slower than the rate of inward actin arc flow across the pSMAC (Figure 4—figure supplement 1A3).

Video 10
A region within the pSMAC of a representative primary B cell expressing GFP-F-Tractin (green), engaged with a PLB containing fluorescent anti-IgM (red) and unlabeled ICAM-1, and imaged every 5 s for 400 s using TIRF-SIM.

The applied white lines mark actin arcs that are sweeping an antigen cluster centripetally, as explained in the text for Figure 4D1–D6. The inward tracks of this cluster and two other clusters are then shown in blue, green, and red, respectively. Played back at 10 fps. Scale bar: 1 μm.

Integrin ligation-dependent IS formation requires myosin 2A contractility

B cells engaged with membrane-bound antigen at low density fail to centralize antigen unless their integrin LFA-1 is also engaged with ICAM-1 in the target membrane (Carrasco et al., 2004). As a prelude to investigating the myosin dependence of this integrin co-stimulatory effect, we sought to recapitulate these findings using primary B cells and PLBs containing varying amounts of mobile, fluorophore-labeled anti-IgM antibody in the presence or absence of unlabeled ICAM-1. Using this approach, we determined an amount of anti-IgM antibody that would not elicit robust antigen centralization in the absence of ICAM-1, but would in its presence. B cells exhibited robust antigen centralization/cSMAC formation over 10 min without the need for ICAM-1 when the PLB was loaded using a solution containing anti-IgM at a concentration of 2 µg/ml (hereafter referred to as ‘high-density antigen’) (Figure 5—figure supplement 1A1–A3). By contrast, B cells formed antigen microclusters across their synaptic interface but failed to centralize them over 10 min when the PLB was loaded using a solution containing anti-IgM at a concentration 0.15 µg/ml (hereafter referred to as ‘low or limiting density antigen’) (Figure 5—figure supplement 1B1–B3). Importantly, when unlabeled ICAM-1 was included in these low-density antigen bilayers, B cells now exhibited robust antigen centralization/cSMAC formation (Figure 5—figure supplement 1C1–C3). This co-stimulatory effect was supported by scoring antigen distribution as centralized, partially centralized or noncentralized (Figure 5—figure supplement 1D1–D3 and E). It was also supported by scoring the percent of total synaptic antigen present within the cSMAC, which was defined by a circular area encompassing 20% of the entire synaptic interface and centered around the center of mass of the fluorescent antigen-containing pixels within the interface (Figure 5—figure supplement 1F). Finally, it was supported by measuring the size of antigen clusters as a function of their distance from the center of the cSMAC (defined as above) (Figure 5—figure supplement 1G). Specifically, B cells engaged with PLBs containing antigen at the limiting density and no ICAM-1 exhibited small antigen clusters (~0.3 µm2) located roughly evenly across the synaptic interface (Figure 5—figure supplement 1G, black trace), while B cells engaged with PLBs containing ICAM-1 in addition to antigen at the limiting density exhibited large antigen clusters (up to 3 µm2), the largest of which were located at the center of the cSMAC (Figure 5—figure supplement 1G, green trace). Of note, the total amount of antigen present at the synaptic interface was also greater for cells engaged with low-density anti-IgM + ICAM-1 than for cells engaged with low-density anti-IgM alone (Figure 5—figure supplement 1H). Together, these results recapitulated a central aspect of the integrin co-stimulatory effect described by Carrasco et al., 2004, and they established the specific conditions we used next to test the myosin dependence of this co-stimulatory effect.

To score the myosin dependence of the integrin co-stimulatory effect, we measured the ability of primary B cells treated with either vehicle control (DMSO) or pnBB to centralize antigen and form a cSMAC when engaged for 10 min with PLBs containing ICAM-1 and anti-IgM at the limiting density. While DMSO-treated cells exhibited robust antigen centralization/cSMAC formation (Figure 5A1–A3), pnBB-treated cells failed to centralize antigen/create a cSMAC (Figure 5B1–B3). Consistently, the actin arcs that surround centralized antigen in DMSO-treated cells (Figure 5C1–C3, white arrows) were absent in pnBB-treated cells (Figure 5D1–D3). The fact that myosin inhibition abrogates the integrin co-stimulatory effect was further supported by scoring antigen distribution in control and pnBB-treated cells as centralized, partially centralized, or noncentralized (Figure 5E), byscoring the percent of total synaptic antigen present within the cSMAC (Figure 5F), and bymeasuring the size of antigen clusters as a function of their distance from the center of the cSMAC (Figure 5G). Of note, the total amount of antigen present at the synaptic interface was also greater for cells treated with DMSO than for cells treated with pnBB (Figure 5H). Together, these results show that the ability of integrin ligation to promote antigen centralization and cSMAC formation when antigen is limiting requires myosin contractility. This in turn argues that the contractile actomyosin arc network created downstream of integrin ligation plays an important role in the mechanism by which LFA-1 co-stimulation promotes B-cell activation.

Figure 5 with 2 supplements see all
Integrin ligation-dependent immune synapse (IS) formation requires myosin 2A contractility.

(A1–A3) DMSO-treated, phalloidin-stained primary B cells 15 min after engagement with a PLB containing ICAM-1 and limiting anti-IgM. (B1–B3) Same as (A1–A3) except the B cells were treated with pnBB. (C1–C3) Images of a representative, DMSO-treated primary B cell (white arrows mark actin arcs). (D1–D3) Images of a representative, pnBB-treated primary B cell. (E) Percent of cells exhibiting centralized, partially centralized, and noncentralized antigen (see Figure 5—figure supplement 1D1–D3 for representative examples of these three types of antigen distribution) (N = 126–144 cells/condition from three experiments). (F) Percent of total synaptic antigen in the cSMAC (N = 81–86 cells/condition from three experiments). (G) Antigen cluster size as a function of normalized distance from the cSMAC center (N = 113–144 cells/condition from three experiments). (H) Total synaptic antigen content (N = 56–62 cells/condition from three experiments). All panels: Airyscan images. Scale bars: 10 µm in (A1, B1, A3, B3); 5 µm in (D3).

Finally, we were curious if the robust centralization of antigen that occurs in the absence of LFA-1 ligation when the density of antigen is high is also dependent on myosin contractility, at least to some extent. Indeed, we found that treatment with para-amino BB (paBB), a newer, slightly more water-soluble version of BB (Várkuti et al., 2016), attenuated antigen centralization significantly even when the density of antigen was high (Figure 5—figure supplement 2; see legend for details), although the magnitude of the inhibition was smaller than for B cells engaged with limiting antigen plus ICAM-1 (compare the results in Figure 5—figure supplement 2 to the results in Figure 5). We conclude, therefore, that M2A contractility potentiates antigen centralization when antigen density is high as well as when antigen density is low enough that LFA-1 co-stimulation becomes important for IS formation. That said, additional experiments should help define how myosin contributes to antigen centralization in B cells receiving only strong anti-IgM stimulation.

Myosin 2A contractility promotes BCR-dependent signaling

To measure the contribution that actomyosin arcs might make to BCR-dependent signaling, we determined the effect that pnBB has on the distribution and synaptic content of phosphorylated CD79a (P-CD79a), an early signaling molecule responsible for signal transduction downstream of BCR-antigen interaction (Batista et al., 2010; Tanaka and Baba, 2020). Consistent with results above and with the known properties of CD79a, DMSO-treated primary B cells engaged for 10 min with PLBs containing ICAM-1 and limiting antigen and then fixed/stained for P-CD79a exhibited robust cSMAC formation, with P-CD79a and anti-IgM concentrated in the cSMAC (Figure 6A1–A4). Also as expected, pnBB-treated B cells failed to form a clear cSMAC, resulting in CD79a and anti-IgM spread across the synapse (Figure 6B1–B4). Importantly, quantitation showed that pnBB-treated cells also exhibited a significant reduction relative to control cells in synaptic P-CD79a content (Figure 6C). This defect was also seen after only 5 min on PLBs (Figure 6—figure supplement 1A), and the defects at both time points were not due to differences between BB-treated cells and control cells in synaptic CD79a content (Figure 6—figure supplement 1B).

Figure 6 with 1 supplement see all
Myosin 2A contractility promotes B-cell receptor (BCR) signaling.

(A1–A4) DMSO-treated primary B cell 10 min after engagement with a PLB containing ICAM-1 and limiting anti-IgM, and stained for F-actin and P-CD79a. (B1–B4) Same as (A1–A4) except the B cell was treated with pnBB. (C) Synaptic P-CD79a content (N = 55–81 cells/condition from three experiments). (D1–D4) DMSO-treated primary B cell 10 min after engagement with a PLB containing ICAM-1 and limiting anti-IgM, and stained for F-actin and P-CD19. (E1–E4) Same as (D1–D4) except the cell was treated with pnBB. (F) Synaptic P-CD19 content (N = 115–140 cells/condition from three experiments). (G) Fluorescence intensities across synapses for P-CD19 (red), antigen (gray), and F-actin (green) in B cells treated with DMSO (N = 22 cells from two experiments). The position of the pSMAC is highlighted in blue. (H) Same as (G) except the cells were treated with pnBB (N = 16 cells from two experiments). All panels: Airyscan images. Scale bars: 5 µm in (B4); 3 µm in (E4).

To extend these results, we determined the effect that pnBB has on the distribution and synaptic content of phosphorylated CD19, an important co-receptor for the BCR that is responsible for PI3K activation (Harwood and Batista, 2011; Tuveson et al., 1993; Keppler et al., 2015; Depoil et al., 2008). DMSO-treated primary B cells engaged with PLBs as above exhibited robust cSMAC formation, with P-CD19 enriched at the outer edge of the IgM concentrated in the cSMAC (Figure 6D1–D4). This enrichment of P-CD19 at the pSMAC/cSMAC boundary was confirmed by line scans of the fluorescence intensities for F-actin, anti-IgM, and P-CD19 (Figure 6G, see boxed pSMAC regions). In contrast to control cells, pnBB-treated B cells failed to concentrate anti-IgM at the center of the synapse, and P-CD19 staining was now spread across the synaptic interface (Figure 6E1–E4 and H). Moreover, quantitation showed that pnBB-treated cells also exhibited a significant reduction relative to control cells in synaptic P-CD19 content (Figure 6F) that was not due to a difference in synaptic CD19 content (Figure 6—figure supplement 1C). Together, these results indicate that the actomyosin arcs promote BCR-dependent signaling.

Germinal center B cells can make actomyosin arcs and centralize antigen

Recent studies have presented evidence that GC B cells differ markedly from naïve B cells with regard to the distribution and fate of antigen at mature synapses. Rather than concentrating antigen at the center of the synapse and using actomyosin force to extract it there, GC B cells accumulate antigen in clusters at the periphery of the synapse and use actomyosin force to extract it there (Hammer et al., 2019; Nowosad et al., 2016; Kwak et al., 2018). These and other results argue that GC B cells differ dramatically from naïve B cells with regard to the organization of actomyosin at their synapse. We wondered, however, if actomyosin arcs could be detected in mouse GC B cells using our imaging approaches. Consistently, TIRF-SIM imaging of mouse GC B cells isolated from the GFP-M2A knockin mouse that were stained with CellMask Deep Red and plated on coverslips coated with anti-IgM, anti-IgG, and ICAM-1 revealed a subset of cells exhibiting enrichment of M2A filaments in the medial, pSMAC portion of the synapse (Video 11), just as in naïve B cells. Moreover, these myosin filaments move centripetally (Video 11) and co-localize with pSMAC actin arcs in phalloidin-stained samples (Figure 7A1–A3, white arrows), just as in naïve B cells. Importantly, scoring showed that about one-third of GC B cells exhibited robust accumulation of M2A filaments in the pSMAC when engaged with anti-IgM/IgG-coated glass (Figure 7B). Similarly, about one-third of GC B cells engaged for 10 min with PLBs containing fluorophore-labeled anti-IgM/IgG and unlabeled ICAM-1, and then fixed and stained with phalloidin, exhibited robust accumulation of M2A filaments in the pSMAC (Figure 7C1–C4 and D,). Importantly, these actomyosin arcs can be seen to surround antigen accumulated at the center of the synapse (see the white arrows in Figure 7C1, C2, and C4). This finding, together with the fact that the myosin moves centripetally during IS formation (Video 11), suggests that actomyosin arcs can contribute to antigen centralization in GC B cells as well as in naïve B cells.

Video 11
A representative primary GC B cell isolated from the GFP-M2A knockin mouse that was stained with CellMask Deep Red (magenta) to label its plasma membrane, activated on glass coated with anti-IgM and ICAM-1, and imaged every 5 s for 300 s using TIRF-SIM.

The first 11 frames show a still image of the magenta cell membrane. Played back at 10 fps. Scale bar: 5 μm.

Figure 7 with 1 supplement see all
Germinal center B cells make actomyosin arcs.

(A1–A3) Phalloidin-stained primary GC B cell from the M2A-GFP knockin mouse on anti-IgM/anti-IgG/ICAM-1-coated glass. White arrows mark the actomyosin arcs. (B) Percent of cells on glass that did or did not show M2A enrichment in the pSMAC (N = 140 cells from four experiments). (C) Phalloidin-stained primary GC B cell from the M2A-GFP knockin mouse 15 min after engagement with a PLB containing anti-IgM, anti-IgG, and ICAM-1. (D) Percent of cells on PLBs that did or did not show M2A enrichment in the pSMAC (N = 89 cells from four experiments). (E1–E4) Representative images of the three types of anti-Ig distribution exhibited by GC B cells 15 min after engagement with a PLB containing anti-IgG and ICAM-1 (cell outlines are shown in blue). (F) Percent of GC cells displaying the three types of anti-Ig distribution shown in (E1–E4) (N = 157 cells from six experiments). All panels: TIRF-SIM images. Scale bars: 5 µm in (A3); 3 µm in (C4, E4).

Given these results, we asked if our PLB-engaged mouse GC B cells can centralize antigen. In partial agreement with previous findings (Nowosad et al., 2016; Kwak et al., 2018), ~45% of synapses exhibited small to medium-sized antigen clusters distributed to varying degrees in the synapse periphery (Figure 7E1, E2, and F). In addition, ~20% of synapses exhibited antigen microclusters spread throughout the synaptic interface (Figure 7E3 and F). Importantly, the remaining ~35% of synapses exhibited highly centralized antigen (Figure 7E4 and F). Images of these synapses showed a pSMAC-like accumulation of GFP-M2A surrounding much of the centralized antigen (Figure 7—figure supplement 1A1; see also Video 12). Conversely, images of synapses containing either peripheral antigen clusters or microclusters showed no obvious pattern to the distribution of GFP-M2A (Figure 7—figure supplement 1A2 and A3; see also Video 13). Moreover, the synapses containing peripheral antigen clusters exhibited less total GFP-M2A signal than the synapses with centralized antigen (Figure 7—figure supplement 1B), and the signals appeared more transient (compare Video 13 to Video 12). These results, together with the images in Figure 7C1–C4, argue that GC B cells with centralized antigen (about one-third of cells) are the ones that make actomyosin arcs (again, about one-third of cells). We conclude, therefore, that GC B cells can make actomyosin arcs and that they likely use this structure to centralize antigen, although the degree to which they do this is considerably less than for naïve B cells. We note, however, that our conclusions regarding GC B cells require additional supporting data that include testing the ICAM-1 dependence of actomyosin arc formation and quantitating the contributions that this contractile structure makes to GC B cell traction forces, signaling, and antigen centralization.

Video 12
A representative primary GC B cell isolated from the GFP-M2A knockin mouse that exhibited centralized antigen clusters on a PLB containing anti-Igs (magenta), imaged every 5 s for 300 s using TIRF-SIM and played back at 7 fps.

Scale bar: 3 μm.

Video 13
A representative primary GC B cell isolated from the GFP-M2A knockin mouse that exhibited peripheral antigen clusters on a PLB containing anti-Igs (magenta), imaged every 5 s for 180 s using TIRF-SIM and played back at 7 fps.

Scale bar: 5 μm.

Discussion

Integrin co-stimulation promotes B-cell activation and IS formation when antigen is limiting by promoting B-cell adhesion (Carrasco et al., 2004; Carrasco and Batista, 2006b). Here, we identified an actomyosin-dependent component of this integrin co-stimulatory effect. By combining super-resolution imaging with specific cytoskeletal perturbations, we showed that integrin ligation induces the formation of a pSMAC actomyosin arc network that comprises the major actin network at the primary B-cell IS. This network is created by the formin mDia1, organized into a concentric, contractile structure by the molecular motor M2A, and promotes synapse formation by mechanically sweeping antigen clusters centripetally into the cSMAC. Most importantly, we showed that integrin-dependent synapse formation under conditions of limiting antigen requires M2A as inhibiting its contractility significantly impairs antigen centralization. Consistently, myosin inhibition also diminishes the synaptic content of the key BCR signaling proteins P-CD79a and P-CD19 and disrupts their synaptic distribution. Finally, we showed that a significant fraction of GC B cells also make this contractile pSMAC actomyosin arc network. Together, our results argue that integrin co-stimulation promotes B-cell activation and synapse formation not only by enhancing B-cell adhesion (Carrasco et al., 2004), but also by eliciting the formation of a contractile actomyosin arc network that drives mechanical force-dependent IS formation. These findings invite a critical ‘reset’ for the way in which future B-cell studies should be approached by highlighting the need for integrin co-stimulation when examining the roles of actin and myosin during B-cell activation. This reset is especially important given that most in vitro studies of B-cell IS formation and activation have been performed under conditions of excess antigen, while antigen is rarely available in excess in vivo.

A central player in the link between integrin co-stimulation and the formation of the actomyosin arc network is almost certainly active RhoA. First, active RhoA would drive arc formation by simultaneously targeting, unfolding, and activating mDia1 at the plasma membrane (Kühn and Geyer, 2014; Rose et al., 2005). Second, active RhoA would drive arc organization and contractility by activating the ROCK-dependent phosphorylation of the regulatory light chains on M2A (Beach and Hammer, 2015), thereby promoting the assembly of the M2A bipolar filaments that decorate, organize, and contract the arcs. Finally, it is likely that active RhoA would promote actomyosin arc formation by activating the ROCK-dependent phosphorylation of mDia1’s autoinhibitory domain, thereby blocking its refolding and subsequent inactivation (Nezami et al., 2006; Maiti et al., 2012; Staus et al., 2011). Given all this, it seems very likely that integrin ligation promotes actomyosin arc formation at least in part by promoting the loading of RhoA with GTP. Consistent with this idea, adhesion signaling has been linked in a variety of systems to the activation of guanine nucleotide exchange factors (GEFs) for RhoA (e.g., p190RhoGEF, GEF H1) (Guilluy et al., 2011; Lawson and Burridge, 2014). Future work should seek, therefore, to clarify the outside-in signaling pathway in B cells that links integrin ligation to the activation of one or more GEFs for RhoA. Such efforts should also take into account parallel activation pathways, such as the PI3K-dependent activation of RhoA downstream of BCR signaling (Saci and Carpenter, 2005), the myosin-dependent activation of B-cell adhesion downstream of CXCR5 signaling (Sáez de Guinoa et al., 2011), and the diacylglycerol kinase-dependent regulation of adhesion and actomyosin force generation at the B-cell synapse (Merino-Cortes, 2020). Given our results here, the ability of the B-cell integrin VLA-4, which binds VCAM-1 on APCs, to promote IS formation under limiting antigen conditions (Carrasco and Batista, 2006b) may also involve an actomyosin-dependent mechanism. Indeed, actomyosin-dependent B-cell IS formation may be a mechanism harnessed by multiple co-stimulatory pathways to promote B-cell activation. Finally, future studies should also seek to clarify the extent to which integrin ligation promotes the formation of actomyosin arcs by driving their creation versus stabilizing them once created.

Consistent with our findings, a recent study by Bolger-Munro et al. reported that GFP-tagged M2A localizes to the medial portion of synapses formed by A20 B cells (Bolger-Munro et al., 2019). In their hands, however, BB treatment did not inhibit antigen centralization, arguing that synapse formation does not require M2A. The disparity between their results and ours as regards the functional significance of M2A may be due to numerous differences in experimental design, including the cell type used (primary B cells versus the A20 B cell line), the mode of antigen presentation (anti-IgM-containing PLBs versus transmembrane antigen expressed by APCs), and the density of antigen (known in PLBs versus unknown and variable on APCs). Our pSMAC actomyosin arcs may also be related to the myosin-rich regions that form in primary HEL-specific naïve B cells bound to acrylamide gels coated with HEL antigen (Kumari et al., 2019).

The contractile actomyosin structure identified here occupies the portion of the B-cell synapse defined by the presence of an integrin ring, that is, the pSMAC (Harwood and Batista, 2011; Carrasco et al., 2004; Carrasco and Batista, 2006b; Dustin et al., 2010). This co-localization should support a feed-forward relationship where integrin co-stimulation promotes the formation of the actomyosin arcs, and the contractile forces that these arcs then promote further integrin activation and robust adhesion. Indeed, the B-cell pSMAC can be viewed as roughly analogous to the lamellar region of mesenchymal cells, where integrins present within ECM-anchored focal adhesions are kept in their open, extended, high-affinity conformation by the forces that myosin-rich stress fibers exert on them (Nordenfelt et al., 2016; Parsons et al., 2010). By analogy, the contribution that the centering forces exerted by the actomyosin arcs make to integrin activation in the pSMAC may be enhanced in the context of an APC by the fact that the APC restricts ICAM-1 mobility (Comrie et al., 2015b). Of note, the activation of integrins by contractile actin arcs created by formins and myosin 2 is also seen in other cell types (Tee et al., 2015; Tojkander et al., 2015; Burnette et al., 2014).

Recent studies have presented evidence that GC B cells differ dramatically from naïve B cells with regard to the organization of actomyosin at their synapse (Nowosad et al., 2016; Kwak et al., 2018). We found, however, that about one-third of GC B cells exhibit robust actomyosin arcs in the medial, pSMAC portion of their synapse that are indistinguishable from those made by naïve B cells. Moreover, staining data, together with images of GFP-M2A distribution in synapses made by PLB-engaged GC B cells, suggest that, like naïve B cells, GC B cells can use this contractile structure to centralize antigen. Given that the selection of GC B cells with higher affinity BCRs likely depends to a significant extent on their ability to gather antigen in the context of strong competition for limiting antigen presented by follicular dendritic cells (Heesters et al., 2016; Heesters et al., 2014), we suggest that actomyosin arcs might contribute to this selection process by promoting antigen gathering.

The actomyosin arcs described here in B cells and the actomyosin arcs described previously in T cells (Murugesan et al., 2016) have a great deal in common as regards their formation, organization, and dynamics (Wang and Hammer, 2020; Hammer et al., 2019). Consistently, this contractile structure supports a number of synaptic processes that are shared by these two cell types, including antigen centralization, proximal signaling, and the formation of an adhesive ring in the medial portion of the IS. A major question, then, is how these two immune cell types harness the force generated by this shared contractile structure to perform their unique functions, that is, target cell killing by the T cell and antibody creation by the B cell. Stated another way, how does the T cell use the force generated by this contractile structure to support the effectiveness of an exocytic event (lytic granule secretion), while the B cell uses the force to support the effectiveness of an endocytic event (antigen extraction and uptake). With regard to T cells, a seminal study by Basu et al., 2016 showed that actomyosin-dependent forces placed on the target cell membrane by the T cell increase the efficiency of target cell killing by straining the target cell membrane in such a way as to increase the pore-forming activity of perforin. One clear goal, therefore, is to determine if the T cell’s actomyosin arcs are responsible for creating this strain. Imaging the actomyosin arcs during the process of target cell killing, and blocking the force they generate just prior to lytic granule secretion, should reveal their contribution to this essential effector function.

The idea that B cells would use the actomyosin arcs identified here to support the extraction and endocytic uptake of membrane-bound antigens stems from the seminal work of Tolar and colleagues, who showed that M2A plays an important role in antigen extraction (Nowosad et al., 2016; Natkanski et al., 2013; Hoogeboom, 2018). These authors also presented evidence that M2A-dependent pulling forces select for BCRs with higher affinity for antigen as such interactions survive the myosin-dependent strain placed on them, resulting in antigen extraction (Nowosad et al., 2016; Natkanski et al., 2013; for review, see Wang and Hammer, 2020 and Spillane and Tolar, 2018). That said, a recent, imaging-based effort to define the mechanism by which antigen is extracted did not provide clear insight into how M2A contributes to this process. Specifically, Roper et al., 2019 reported that the synapses of naïve B cells bound to antigen-bearing plasma membrane sheets (PMSs) are composed of a dynamic mixture of actin foci generated by the Arp2/3 complex and disorganized linear filaments/fibers generated by a formin. While static images showed little co-localization between the actin foci and antigen clusters, dynamic imaging suggested that the foci promote antigen extraction (although formin activity was also required). Based on these and other observations, Roper et al. concluded that naïve B cells use a foci-filament network to drive force-dependent antigen extraction (Roper et al., 2019). How M2A contributes to this force was unclear, however, as M2A (visualized using an antibody to the phosphorylated form of M2A’s RLC) did not co-localize with either actin structure (Roper et al., 2019). Moreover, neither actin structure was affected by BB treatment. These two findings are notably at odds with our findings that M2A (visualized by endogenous tagging of the M2A heavy chain) co-localizes dramatically with actin arcs, and that BB treatment profoundly disrupts the organization of the pSMAC actin arc network. Regarding this discrepancy, we note that the images of synaptic actin presented by Roper et al. look similar to our images of naïve B cells stimulated with anti-IgM alone, where the synapse was also composed of a disorganized and dynamic mixture of actin foci and short-actin filaments/fibers. The fact that the PMSs used by Roper et al. did not contain integrin ligands may explain, therefore, why they did not see a more organized synapse containing actomyosin arcs. In the same vein, two other recent studies examined antigen extraction using substrates that lacked integrin ligands (PLBs and PMSs in Kwak et al., 2018 and acrylamide gels in Kumari et al., 2019). Given our results, we suggest that future efforts to define the mechanism by which M2A promotes antigen extraction should follow the myosin as the B cell extracts antigen from an APC, where the B cell’s integrins will be engaged, and where the antigen can be presented in a physiologically relevant way (e.g., opsonized and bound to an Fc or complement receptor). Such efforts will hopefully reveal how the B cell harnesses the forces generated by the actomyosin arcs identified here to drive antigen extraction and uptake.

Materials and methods

Mice and cell culture

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Primary B cells were isolated from the spleens of 6–12-week-old C57BL/6 mice (Jackson Laboratories #002595) and GFP-M2A (Myh9) KI mice (gift of R. Adelstein, NHLBI/NIH) of either sex using negative selection B cell isolation (StemCell Technologies). Euthanasia was performed in accordance with protocols approved by the National Human Genome Research Institute Animal Use and Care Committee at the National Institutes of Health. The A20 murine IgG+ B cell line was purchased from ATCC (ATCC TIB-208), verified by responsiveness to anti-IgG stimulation, and confirmed to be free of mycoplasma. B cells were cultured in complete medium (RPMI-1640, 10% heat-inactivated fetal calf serum [FCS], 2  mM l-glutamine, 1  mM sodium pyruvate, 50  µM 2-mercaptoethanol, and 1X Antibiotic-Antimycotic) at 37°C with 5% CO2. Primary B-cell complete media also contains 5 ng/ml of BAFF (R&D Systems).

Plasmids and reagents

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GFP- and tdTomato-tagged F-Tractin were gifts from Michael Schell (Uniformed Services University, Maryland). Alexa Fluor-conjugated phalloidins were purchased from Thermo Fisher. Anti-mDia1 antibody was purchased from Thermo Fisher (PA5-27607). HRP-conjugated mouse anti-β-actin antibody was purchased from Santa Cruz (SC-47778 HRP). Rabbit anti-CD79a (#3351), anti-PCD79a (#5173), anti-CD19 (#3574), and anti-PCD19 (#3571) were purchased from Cell Signaling Technologies. Anti-M2A was purchased from MilliporeSigma (#M8064). CK-666 and SMIFH2 were purchased from MilliporeSigma and used at final concentrations of 100 μM and 25 μM, respectively. pnBB and paBB were purchased from Cayman Chemicals and used at a final concentration of 25 μM. DMSO vehicle control was purchased from MilliporeSigma. CellMask Deep Red Plasma Membrane Stain was purchased from Thermo Fisher. Alexa Fluor 488- (#111-545-003), 594- (#111-585-003), and 647- (#111-605-003) conjugated goat, anti-rabbit secondary antibodies were purchased from Jackson ImmunoResearch. Goat anti-mouse IgG Fcγ fragment-specific antibody (#115-005-008) and goat anti-mouse IgM, µ-chain-specific antibodies (#115-005-020) were purchased from Jackson ImmunoResearch. Anti-rabbit-HRP (#32260) was purchased from Thermo Fisher.

GC B-cell generation and sorting

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GC B cells were generated and sorted using a previously described protocol (Hwang et al., 2015). Briefly, 6–12-week-old M2A-GFP KI mice were immunized with sheep’s red blood cells. After 8–10 days, total B cells from the spleens and lymph nodes were isolated using the Negative Selection B cell isolation kit (StemCell Technologies) according to the manufacturer’s instructions. Dead cells were stained using Zombie Yellow viability stain (BioLegend) and Fc receptors were blocked with the mouse TruStain FcX antibody (#156604). Cells were immunostained with anti-mouse CD38 (#102719), B220 (#103235), and GL-7 (#144617) purchased from BioLegend. GC B cells were sorted on a BD Aria III FACs sorter (Beckton Dickinson) for GFP+, Zombie Yellow-, B220+, CD38low and GL-7+ cells, and were used immediately.

B-cell transfection

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A20 B cells and primary B cells were transfected as previously described (Wang et al., 2017). Briefly, ex vivo primary B cells were first cultured for 12 hr in complete media supplemented with 5 ng/ml BAFF (R&D Systems) and 2.5 µg/ml Escherichia coli O111:B4 LPS (MilliporeSigma) (LPS was included to promote cell survival during nucleofection). 2 × 106 B cells were then nucleofected with 2 μg of plasmid DNA using Nucleofector Kit V (Lonza) and rested for at least 16–24 hr using complete media containing 5 ng/ml BAFF and lacking LPS. We refer to both rested, transfected cells and ex vivo nonmanipulated cells as naïve B cells because neither had been activated by antigen.

CRISPR

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Mouse GFP-M2A and Scarleti-M2A template plasmids were gifts from Jordan Beach (Loyola University, Chicago). Mouse M2A sgRNAs were synthesized by Synthego and used according to the manufacturer’s instructions. Briefly, sgRNAs were mixed with Cas9 (IDT) to form ribonucleoproteins and then added together with 0.5 μg of template plasmid to 2 × 106 cells suspended in the solution for Nucleofector Kit V. Following nucleofection, the cells were cultured in complete media for 24 hr before fluorescence-activated cell sorting (FACS) for GFP or Scarleti expression using the Aria III (Becton Dickinson).

miRNA-mediated knockdown of mDia1

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miRNAs targeting the 3′ UTR of mouse mDia1 were designed as previously described (Alexander and Hammer, 2016) using BLOCK-iT RNAi Designer (Thermo Fisher), synthesized (Gene Universal), and fused to the C-terminus of mNeonGreen-F-Tractin using In-Fusion cloning (Takara). As a control, a version of this plasmid containing an miRNA sequence that has been verified as nontargeting in mouse (Cai et al., 2006) was used. A20 B cells were transfected with 2 μg of F-Tractin-mNeonGreen vector control, F-Tractin-mNeonGreen-mDia1-miRNAs, F-Tractin-mNeonGreen-nontargeting miRNA, or a combination of F-Tractin-mNeonGreen and 300 nM of mirVana-negative control and cultured in complete media for 16 hr. Cells were then lysed and immunoblotted using an antibody to mDia1 (1:250) and an HRP-conjugated antibody to β-actin (1:5000) to confirm knockdown. Cells that had received the miRNA were identified based on the expression of F-Tractin-mNeonGreen and then quantified after staining with phalloidin. F-Tractin-mNeonGreen-positive cells were also used in a cell spreading assay as described below.

Cell spreading on functionalized glass

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Eight-well Labtek chambers (Nunc) were coated with 15 μg/ml of anti-IgM and/or anti-IgG with or without 0.5 μg/ml of mouse histidine-tagged ICAM-1 (Sino Biological) for 1 hr at room temperature. B cells were resuspended in modified HEPES-buffered saline (mHBS) (Wang et al., 2017) and adhered to functionalized glass for 15 min at 37°C before live imaging or fixing with 4% paraformaldehyde for staining (see Materials and methods). Where inhibitors were used, cells were pretreated for 30 min with 100 μM CK-666, 25 μM SMIFH2, 25 μM pnBB or paBB, or dH2O/DMSO vehicle control in mHBS at 37°C. Cells were then added to functionalized Labtek chambers in mHBS containing the same concentrations of inhibitors or vehicle control as the pretreatment.

Supported planar lipid bilayers

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Liposomes were prepared as described previously (Yi et al., 2012; Murugesan et al., 2016; Hong et al., 2017). Briefly, 0.4 mM 1,2-dioleoyl-sn-glycero-3-phosphocholine, biotin–CAP-PE, 1,2-dioleoyl-sn-glycero-3-[(N-(5-amino-1-carboxypentyl)iminodiacetic acid)succinyl] (DGS)–NTA and 1,2-dioleoyl-sn-glycero-3-phosphocholine (Avanti Polar Lipids, Inc) were mixed at 1:3:96 molar % ratio. Lipids were dried under a stream of argon and then desiccated in a vacuum chamber. Unilamellar liposomes were generated from lyophilized lipids hydrated in Tris-buffered saline via extrusion through a 50 nm pore membrane using a mini-extruder kit (Avanti Polar Lipids, Inc). PLBs were assembled in Sticky-Slide VI0.4 Luer closed chambers (Ibidi) as previously described (Comrie et al., 2015a). 25 × 75 mm glass coverslips (Ibidi) were cleaned using Piranha solution (1:3 ratio of sulfuric acid and 30% hydrogen peroxide). After depositing liposomes onto the flow channels, the channels were washed with HBS buffer containing 1% BSA. A solution containing mono-biotinylated, Alexa Fluor 647-labeled anti-IgM antibody (0.15 µg/ml [300 molecules/μm2] for the limiting antigen condition and 2 µg/ml [4000 molecules/μm2] for the high antigen condition) and streptavidin (Sigma-Aldrich) were added to the flow chambers with or without 0.5 µg/ml unlabeled histidine-tagged ICAM-1. Anti-IgM antibody (µ-chain specific) was monobiotinylated and labeled with Alexa Fluor 647 (Thermo Fisher) as described previously (Carrasco et al., 2004). The uniformity and lateral mobility of PLBs were assessed using FRAP as described previously (Yi et al., 2012). Photobleached circles with a diameter of 4 µm typically recovered within 60 s. B cells were resuspended in modified HEPES-buffered saline and allowed to engage PLBs at 37°C and imaged immediately, or fixed with 4% paraformaldehyde after 5 and 10 min for immunostaining.

Traction force microscopy

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Polyacrylamide gels (PA, 0.23  kPa shear modulus, 40  μm thickness) were prepared on glass coverslips with embedded 40 nm fluorescent beads (TransFluoSpheres [633/720], Thermo Scientific), as described previously (Jaumouillé et al., 2019). B cells were resuspended in mHBS with 2% FCS and added to PA gels. Images of B cells that had engaged PA gels for 20 min were captured. A no-stress reference image of the PA gels with beads was captured after lifting cells from the PA gel by adding 1% sodium dodecyl sulfate in 1× PBS to the imaging chamber at a final concentration of 0.04%. Particle image velocimetry was used to calculate bead displacements relative to the reference position, and the corresponding contractile energy was quantified using ImageJ plugins as previously described (Jaumouillé et al., 2019; Martiel et al., 2015). Traction forces were reported as the mean magnitude of traction stress within the cell relative to the cell surface area.

Immunostaining

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Fixed cells were permeabilized with 0.2% Triton-X-100 and blocked for 30 min at room temperature using PBS containing 2% BSA. Cells were incubated with primary antibodies (1:200) overnight at 4°C and then secondary antibodies (1:250) with Alexa Fluor-conjugated phalloidins for 1 hr at room temperature. Antibodies and phalloidins were diluted in blocking buffer. All washes were performed with 1× PBS.

Microscopy

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All live-cell imaging was performed at 37°C in mHBS supplemented with 2% FCS. TIRF-SIM and 3D-SIM imaging were performed on a GE DeltaVision OMX SR microscope (Cytiva) equipped with a 60 × 1.42 NA oil objective (Olympus). For 3D-SIM, z-stacks were acquired at 0.125 µm increments. Raw data were reconstructed using Softworx software (Cytiva) with a Wiener filter constant of 0.002–0.003. Airyscan imaging was performed using an LSM 880 Zeiss confocal microscope equipped with Airyscan and using a Plan-Apochromat 63 × 1.4 NA oil objective. Airyscan image reconstruction was performed using Zeiss ZEN imaging software. TFM was imaged using a Nikon Eclipse Ti2 microscope equipped with a 60 × 1.2  NA water objective. Linear adjustments to images were made using ImageJ 1.53 (NIH).

Image analyses

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All image analyses were performed using ImageJ (NIH). To draw ROIs for measurements of the fraction of total IS footprint occupied by each SMAC, the content of F-actin in each SMAC, and the anisotropy of actin filaments within the pSMAC, we relied on the distinctive appearance of actin in each SMAC. This was straightforward in TIRF-SIM images of B cells stimulated with both anti-IgM and ICAM-1, where the thin outer dSMAC was comprised of moderately bright pixels with not much fluctuation in intensity, the medial pSMAC was comprised of bright actin arcs with intervening dim signals, and the central cSMAC was comprised mostly of dim signals. For B cells engaged with anti-IgM alone, the thin outer dSMAC was still readily identifiable, the central cSMAC was identifiable in lower mag images as a central circle with less signal than the area between it and the dSMAC, and the medial pSMAC corresponded to the area between the dSMAC and the cSMAC. Fluorescence intensities within the SMAC regions were quantified using ROIs and reported as the total background-corrected fluorescence within the ROI, which was quantified as described (Burgess et al., 2010) using the following equation: Integrated density – [(area of ROI) × (mean background fluorescence per unit area)], where the integrated density is equal to [(area of ROI) × (mean fluorescence per unit area within the ROI)]. Mean background fluorescence was determined using the same ROI size at three separate positions less than 3 μm away from the cell. The myosin fluorescence intensity in 3D-SIM images was quantified using a maximum projection image of the image stacks where the cell ROI was determined based on the F-actin threshold and the background-corrected myosin fluorescence within the cell ROI was reported. The FibrilTool plugin for ImageJ was used to measure actin arc morphology based on the intensity gradients between pixels as described previously (Murugesan et al., 2016; Boudaoud et al., 2014). Briefly, the pSMAC regions in TIRF-SIM images were divided into 10–12 trapezoid-shaped ROIs of similar size to measure the anisotropy of arcs in the radially symmetric pSMAC. The values obtained range from 0, when the orientation of the structures is random, to 1, when the structures show higher orientation in the same direction. The velocity of centripetal actin flow was assessed by assembling kymographs from TIRF-SIM videos using the Kymograph Builder plugin from ImageJ, as previously described (Murugesan et al., 2016). Briefly, the dSMAC and pSMAC regions were identified by the relatively abrupt slope change for F-actin flow, and slope angles were used to quantify the rates of actin movement. The size of each antigen cluster and their relative distance from the cSMAC center were quantified using an ImageJ macro. First, the perimeter of the synaptic interface was determined based on thresholds for F-actin, and an ROI that encompassed the interface area was drawn (the synaptic ROI). The coordinates for each pixel contained in the ROI were determined and the linear distance of each pixel from the center of mass of the total synaptic antigen (defined as cSMAC center) was determined. The longest distance was defined as the furthest distance to travel from the outermost edge of the cell. A binary image of the antigen channel combined with the ImageJ watershed algorithm was used to segment individual antigen clusters within the synaptic ROI. The area of each antigen cluster was quantified using the Analyze Particles function in ImageJ. The relative distance of each antigen cluster was reported as the distance between the center of mass of the antigen cluster and the cSMAC center after normalizing to the furthest distance from the cell edge to the cSMAC center. To quantify the antigen fluorescence in the cSMAC, a circular ROI corresponding to 20% of the total synaptic area (based on the average area of the cSMAC at the synaptic interface) was drawn such that the center of the circle lies at the same coordinates as the center of mass of the total antigen signal. Antigen fluorescence within this circle was quantified and presented as a percent of the total synaptic antigen fluorescence. The fluorescence intensities of the signaling molecules CD79a, P-CD79a, CD19, and P-CD19 were all reported as the total fluorescence intensity within the synaptic ROI. All fluorescence intensities were corrected for background as described above. Fluorescence intensity profiles were obtained by drawing a 10 μm line across the center of the synaptic interface and using the ImageJ function ‘Plot Profiles’ to obtain fluorescence intensity values across the line. The intensity profiles of several cells were combined, and the average fluorescence intensity ± standard deviation was reported. The speeds of antigen cluster movement were quantified using the ImageJ plugin TrackMate as previously described (Tinevez et al., 2017) where a combination of automated and manual tracking was performed. Prior to quantification, the perimeter of the cell was identified by oversaturating the signal for GFP-M2A, and the anti-IgM fluorescence signal outside of the cell was removed so that only antigen clusters formed by that cell were quantified. Antigen clusters were determined using a blob diameter of 0.2 μm2, and tracks were obtained using a threshold of 2000 units with sub-pixel localization. Mean antigen cluster movement speeds were reported as distance traveled over time. Kymographs of moving antigen clusters were created using the ImageJ plugin Kymograph Builder.

Statistical analyses

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All statistical analyses were performed using Prism 9 (GraphPad). Statistical comparisons of dot plots were performed using unpaired, two-tailed t-tests, and data are represented as mean ± standard deviation. Statistical comparisons of bar charts were performed using paired, two-tailed t-tests, and data are represented as mean ± standard error of the mean, unless otherwise stated. The following annotations are used to indicate significance: *p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Strain, strain background (Mus musculus)C57BL/6Jackson LaboratoriesCat# 002595;
RRID:MGI:5656552
Strain, strain background (M. musculus)M2A-GFP KIRobert Adelstein, NHLBI/NIH
Cell line (M. musculus)A20American Type Culture CollectionATCC TIB-208;
RRID:CVCL_1940
IgG+ B cell line
Recombinant DNA reagentGFP-F-TractinMichael Schell (Uniformed Services University, MD)
Recombinant DNA reagenttdTomato-F-TractinMichael Schell (Uniformed Services University, MD)
Chemical compound, drugAlexa Fluor 488 PhalloidinThermo Fisher ScientificCat# A12379Fluorescence labeling (1:500)
Chemical compound, drugAlexa Fluor 568 PhalloidinThermo Fisher ScientificCat# A12380Fluorescence labeling (1:500)
Chemical compound, drugCellMask Deep
Red Plasma Membrane Stain
Thermo Fisher ScientificCat# C10046Cell labeling (1:10000)
Chemical compound, drugDMSOMilliporeSigmaCat# D4540
Chemical compound, drugSMIFH2MilliporeSigmaCat# 34409225 μM
Chemical compound, drugCK-666MilliporeSigmaCat# 182515100 μM
Chemical compound, drug(S)-nitro-
blebbistatin
(pnBB)
Cayman ChemicalsCat# 2417125 μM
Chemical compound, drugPara-amino blebbistatinCayman ChemicalsCat# 2269925 μM
Chemical compound, drugZombie Yellow
viability stain
BioLegendCat# 423103Dead cell staining (1:300)
Chemical compound, drug18:1 Biotinyl Cap PE IN CHLOROFORM 1,2-dioleoyl-
sn-glycero-3-phosphoethanolamine-
N-(cap biotinyl)
Avanti Polar LipidsCat# 870273C
Chemical compound, drug18:1 DGS-NTA(Ni) in Chloroform 1,2-dioleoyl-sn-glycero-
3-[(N-(5-amino-1-carboxypentyl) iminodiacetic acid)succinyl]
(nickel salt)
Avanti Polar LipidsCat# 790404C
Chemical compound, drug18:1 (9-Cis) PC (DOPC) in CHLOROFORM 1,2-dioleoyl-sn-glycero-
3-phosphocholine
Avanti Polar LipidsCat# 850375C
Chemical compound, drugTransFluoSpheres (633/720)Thermo Fisher ScientificCat# T8870
OtherEscherichia coli O111:B4 LPSMilliporeSigmaCat# L2630Cell culture 2.5 µg/ml
Biological sample (Ovis aries)Sheep’s red blood cellsInnovative Research NoviCat# ISHRBC100P15MLInjection 2 × 108 cells
AntibodyAlexa Fluor 488- conjugated goat,
anti-rabbit, polyclonal
Jackson Immuno
Research
Cat# 111-545-003;
RRID:AB_2338046
Immunofluorescence (1:500)
AntibodyAlexa Fluor 594 conjugated goat,
anti-rabbit, polyclonal
Jackson Immuno
Research
Cat# 111-585-003;
RRID:AB_2338059
Immunofluorescence (1:500)
AntibodyAlexa Fluor 647- conjugated goat, anti-rabbit, polyclonalJackson Immuno
Research
Cat# 111-605-003;
RRID:AB_2338072
Immunofluorescence (1:500)
AntibodyGoat anti-mouse IgG, Fcγ fragment-specific, polyclonalJackson Immuno
Research
Cat# 115-005-008;
RRID:AB_2338449
Coverslip coating 2.5 µg/cm2
AntibodyGoat anti-mouse IgM, µ-chain-specific, polyclonalJackson Immuno
Research
Cat# 115-005-020;
RRID:AB_2338450
Coverslip coating 2.5 µg/cm2
AntibodyGoat anti-rabbit IgG (H + L) Poly-HRP, polyclonalThermo FisherCat# 32260;
RRID:AB_1965959
Western blot (1:3000)
AntibodyRabbit anti-DIAPH1, polyclonalThermo FisherCat# PA5-27607;
RRID:AB_2545083
Western blot (1:250)
Antibodyβ-actin antibody (C4), mouse monoclonalSanta CruzCat# SC-47778 HRP;
RRID:AB_2714189
Western blot (1:5000)
AntibodyRabbit anti-CD79a, polyclonalCell Signaling TechnologiesCat# 3351;
RRID:AB_2075745
Immunofluorescence (1:250)
AntibodyRabbit anti-phospho-CD79a, polyclonalCell Signaling TechnologiesCat# 5173;
RRID:AB_10694763
Immunofluorescence (1:250)
AntibodyRabbit anti-CD19, polyclonalCell Signaling TechnologiesCat# 3574;
RRID:AB_2275523
Immunofluorescence (1:250)
AntibodyRabbit anti-phospho-CD19, polyclonalCell Signaling TechnologiesCat# 3571;
RRID:AB_2072836
Immunofluorescence (1:250)
AntibodyRabbit anti-M2A, polyclonalMilliporeSigmaCat# M8064;
RRID:AB_260673
Immunofluorescence (1:200)
AntibodyTruStain FcX PLUS (anti-mouse CD16/32) antibody, rat monoclonalBioLegendCat# 156604;
RRID:AB_2783138
FcR block (0.25 μg/106 cells)
AntibodyPacific Blue anti-mouse CD38, rat monoclonalBioLegendCat# 102719;
RRID:AB_10613289
FACS (1:100)
AntibodyPerCP/Cyanine5.5 anti-mouse/human CD45R/B220, rat monoclonalBioLegendCat# 103235;
RRID:AB_893356
FACS (1:100)
AntibodyAPC anti-MU/HU GL7 antigen, rat monoclonalBioLegendCat# 144617;
RRID:AB_2800674
FACS (1:200)
Recombinant DNA reagentmNeonGreen-F-TractinThis paperSee Materials and methods
Sequence-based reagentNon-targeting
miRNA
This papermiRNAACCTAAGGTTA
AGTCGCCCTCG;
see also Materials and methods
Sequence-based reagentmDia1 miRNA #1This papermiRNACAGCATGGCT
AAATGGTCA;
see also Materials and methods
Sequence-based reagentmDia1 miRNA #2This papermiRNAGGGTCCGTTT
GCTGCCTTA;
see also Materials and methods
Sequence-based reagentmDia1 miRNA #3This papermiRNAGGGTAGCAAT
GCTGTGTTT;
see also
Materials and methods
Sequence-based reagentmirVana miRNA Mimic, Negative Control #1Thermo Fisher ScientificCat# 4464058
Sequence-based reagentMYH9 sgRNASynthegosgRNAAAACUUCAUCA
AUAACCCGC
Recombinant DNA reagentMouse GFP-M2AJordan Beach (Loyola University, Chicago)CRISPR GFP-
M2A template
Recombinant DNA reagentMouse Scarleti-M2AJordan Beach (Loyola University, Chicago)mScarleti-CRISPR
M2A template
Peptide, recombinant proteinAlt-R S.p. HiFi
Cas9 Nuclease V3
IDTCat# 1081060
Peptide, recombinant proteinBAFFR&D SystemsCat# 8876-BF-010Cell culture 5 ng/ml
peptide, recombinant proteinStreptavidinMilliporeSigmaCat# 189730
peptide, recombinant proteinMouse histidine-tagged ICAM-1Sino BiologicalCat# 50440-M08H
Commercial assay or kitNucleofector Kit VLonzaCat# VCA-1003
Commercial assay or kitIn-Fusion HD CloningTakaraCat# 638911
Commercial assay or kitMini-extruder kitAvanti Polar LipidsCat# 610000
Commercial assay or kitSticky-Slide VI0.4
Luer closed chambers
IbidiCat# 80608
Commercial assay or kitAlexa Fluor 647 Antibody Labeling
Kit
Thermo Fisher ScientificCat# A20186
Commercial assay or kitEZ-Link Micro
Sulfo-NHS-Biotinylation Kit
Thermo Fisher ScientificCat# 21925
Software, algorithmImageJNIH
Software, algorithmFijiSchindelin et al., 2012RRID:SCR_002285https://imagej.net/Fiji
Software, algorithmSoftworxApplied Precision Ltd.; GE Healthcare Life SciencesRRID:SCR_019157
Software, algorithmZENZeissRRID:SCR_018163
Software, algorithmFibrilToolBoudaoud et al., 2014RRID:SCR_016773
Software, algorithmBLOCK-iT RNAi DesignerThermo Fisher ScientificRRID:SCR_002794https://rnaidesigner.thermofisher.com/rnaiexpress/
Software, algorithmPrismGraphPadRRID:SCR_002798
Software, algorithmTraction Force
plugin
Martiel et al., 2015

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. Numerical data have been provided as source data and are available from the Dryad database.

The following data sets were generated
    1. Wang JC
    (2022) Dryad Digital Repository
    A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation.
    https://doi.org/10.5061/dryad.9kd51c5km

References

    1. Tanaka S
    2. Baba Y
    (2020) B Cell Receptor Signaling
    Advances in Experimental Medicine and Biology 1254:23–36.
    https://doi.org/10.1007/978-981-15-3532-1_2

Decision letter

  1. Michael L Dustin
    Reviewing Editor; University of Oxford, United Kingdom
  2. Anna Akhmanova
    Senior Editor; Utrecht University, Netherlands
  3. Pieta K Mattila
    Reviewer; University of Turku, Finland

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Pieta Mattila (Reviewer #2).

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

Essential revisions:

Your paper is of interest to immunologists studying mechanisms of lymphocyte activation and scientists in the broader field of cell mechanics. The work provides new insight into the cooperation among receptors, the actin cytoskeleton, and myosin motors that is required for the formation of a B cell immune synapse. The data support the key claims of the manuscript.

There are a few instances where more complete analysis and presentation of results would strengthen the paper.

1) The requirement for LFA-1:ICAM-1 ligation in the formation of the actomyosin arcs is not clear. The authors observe that ~30% of B cells form actomyosin arcs with anti-IgM stimulation only (Figure 1). Does LFA-1:ICAM-1 ligation simply stabilise the arcs and therefore make their appearance more likely, or does it promote the formation of a distinct actomyosin network with unique functions? The images and videos selected to represent cells stimulated with anti-IgM only (Figure 1; Videos 1A and 1B) seem form a highly branched actin network throughout the synapse, but it would be informative to see cells having the actomyosin arcs for comparison. Since B cells stimulated with anti- IgM alone are capable of signalling and centralising antigen, it would be interesting to know whether and how these two populations (with and without arcs) differ.

2) The observation that some GC B cells centralise antigen is very interesting, but there are a few aspects of this investigation that should be expanded upon. The authors show that with LFA-1:ICAM-1 interactions, GC B cells are about equally likely to organise BCR:antigen complexes into peripheral clusters and centralised clusters. It would be informative to have, in the same study (Figure 7), a comparison with GC B cells stimulated with antigen alone. The reason is that other studies investigating GC B cell synapse architecture did not quantify antigen organisation in this way, so it is difficult to make comparisons with previous work. It would also be very useful to see how the actomyosin network is organised in GC B cells exhibiting different synaptic architectures (i.e. peripheral versus central clusters), especially given the critical role of myosin IIa activity in GC B cell antigen affinity discrimination. Additionally, while it is a very interesting observation that LFA-1:ICAM-1 interactions may affect GC B cell synapse organisation, it is not clear whether this has an impact on cellular function. For instance, does antigen and actomyosin organisation in GC B cell synapses contribute to differences in signalling or traction force generation? In the introduction the authors suggest that actomyosin arcs contribute to antibody affinity maturation (line 87-88), but without functional studies to support this claim I think it is too speculative.

3) mDia1 miRNA data requires supporting experiments with rescue of the phenotype upon re-expression or, at minimum, scrambled controls. Also the suggestion that mDia1 nucleates the F- actin at the distal edge spikes remains a hypothesis that would be easy to test with immunofluorescence stainings. Can you say or hypothesize how LFA-1 activates mDia1, and if ROCK is important for that, did you try experiments using the Y27632 compound to block it (optional)?

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

Thank you for submitting your article "A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Darius Vasco Köster (Reviewer #3).

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

Essential revisions:

The reviewers and editors appreciate that manuscript is improved by the revisions, but there remained concerns about the evidence for the role of mDia in forming arcs and the lack of functional data or consideration of function in the discussion.

1. The appropriate controls need to be included to publish the siRNA data on mDia1. As the formin inhibitor is known to be problematic, strengthening the siRNA experiment is necessary to make the conclusion.

2. The definition of an arc still needs to be clarified and relate to the distribution of antigen receptor-antigen complexes. In cells with a more peripheral antigen distribution are their fewer arcs in the interface with the substrate?

3. The parallels between the earlier analysis of myosin arcs in T cells and this study are remarkable, but a discussion of how these compare considering the distinct functions of the two cell types is lacking. A discussion of this comparison could also be helpful to bring more consideration of function to the paper.

Reviewer #1 (Recommendations for the authors):

The authors have addressed most of my comments. There is a point raised in my original review that the authors addressed with some modifications/additions to the text, but I think additional analysis of existing data would really strengthen the paper. This is summarised below.

1) The authors suggest that GC B cells with actomyosin arcs are likely those that centralise antigen, but further data analysis is needed to support this claim. Specifically, I think the authors should quantitate the overlap of GC B cells that centralise antigen and those that have actomyosin arcs. Additionally, to give better insight into how actomyosin helps to organise antigen in the synapse, it would be informative to include example images of actomyosin organisation in GC B cells that have peripheral antigen clusters and microclusters (to complement Figure 7, E1-E3) alongside the images already shown of a GC B cell that has centralised antigen (Figure 7, C1-C4). The authors are likely to already have these data in hand so it should not require additional experiments. I think these additions to Figure 7 would strengthen the paper by giving more insight into how antigen organisation in the synapse is dependent on the presence of actomyosin arcs.

Reviewer #2 (Recommendations for the authors):

Unfortunately, I feel that the authors have not really acted upon the concerns of the reviewers. No new data, analysis or even any considerable discussion points have been added. The concerns about manual segmentation, yes/no -type of analysis of the actin arcs, and the limited description of the breadth of data remain. Also, siRNA silencing data without scrambled controls or rescue experiments does not belong to today's high quality cell biological publications. This lack of rigor in some experimental parts without efforts to improve it is concerning.

Reviewer #3 (Recommendations for the authors):

The authors have considered and included a number of the reviewer comments in their revised version of the article 'A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation'. The manuscript has gained in clarity and the figures and supplement data underline strongly the findings and claims made by the authors that LFA-1 ligation plays and important role in B-cell activation through the formation of actin arcs that push engaged ICAM-1 clusters towards the cSMAC.

However, one weakness is the lack of additional data to support the findings on the role of mDia1 as the use of scrambled miRNA or immunostaining for mDia1 would be typical control experiments here. The response to reviewers also does not provide any further information why these experiments could not be performed.

Apart from that there are a few points that should be addressed/ clarified:

– line 312 onwards (about kymograph analysis): the image provided does not show convincingly how the velocities could be measured with such precision (2 digit precision with 21 data points). E.g. I cannot make out a clear line for velocity calculation in the dSMAC region of Figure 4-Figure sup 1 A2, and the lines in the pSMAC show a variety of slopes that would result in a higher standard deviation. How many readings from each kymograph were used per cell? Does the bar diagrams in Figure 4-Figure sup1 compare the average values of each cell or compare the measurements from all cells pooled together?

line 951-953 and methods section (line 820-822) (about anisotropy measurements): since the number of measurements differs between the two conditions, it would be better to represent the histogram in relative numbers (frequency or probability) instead of absolute numbers. in addition, it would be good if the description in the methods section could be a bit more insightful, e.g. what criteria were followed to draw ROIs, did you draw ROIs of similar size in the dSMAC and pSMAC regions (the box drawing seems a bit random in the example image, which is puzzling)? It would also be good to indicate that the anisotropy measurement is based on the intensity gradients between pixels.

line 970-971: please add to the legend that the red line indicates the average orientation of the filaments in the ROI.

Figure 5 – sup Figure 2: Within the anti-IgM zones seem to be clusters of phalloidin that are void of anti-IgM signal. is that just an odd effect of the interplay between the fluorescent markers or do these zones have a biological meaning, i.e. are these zones containing some other proteins that bind strongly to actin and exclude the anti-IgM?

https://doi.org/10.7554/eLife.72805.sa1

Author response

Essential revisions:

Your paper is of interest to immunologists studying mechanisms of lymphocyte activation and scientists in the broader field of cell mechanics. The work provides new insight into the cooperation among receptors, the actin cytoskeleton, and myosin motors that is required for the formation of a B cell immune synapse. The data support the key claims of the manuscript.

There are a few instances where more complete analysis and presentation of results would strengthen the paper.

1) The requirement for LFA-1:ICAM-1 ligation in the formation of the actomyosin arcs is not clear. The authors observe that ~30% of B cells form actomyosin arcs with anti-IgM stimulation only (Figure 1). Does LFA-1:ICAM-1 ligation simply stabilise the arcs and therefore make their appearance more likely, or does it promote the formation of a distinct actomyosin network with unique functions? The images and videos selected to represent cells stimulated with anti-IgM only (Figure 1; Videos 1A and 1B) seem form a highly branched actin network throughout the synapse, but it would be informative to see cells having the actomyosin arcs for comparison. Since B cells stimulated with anti- IgM alone are capable of signalling and centralising antigen, it would be interesting to know whether and how these two populations (with and without arcs) differ.

We thank the reviewers for their questions regarding this central aspect of our study. In response to the reviewers’ statement “The requirement for LFA-1:ICAM-1 ligation in the formation of the actomyosin arcs is not clear”, our results state that “Consistently, scoring B cells for the presence of a discernable actin arc network showed that the addition of ICAM-1 increases the percentage of such cells from ~30% to ~70% (Figure 1G).” Importantly, we then state that “dynamic imaging showed that the arcs in cells engaged with anti-IgM alone are typically sparse and transient (Videos 1A and 1B), while those in cells engaged with both anti-IgM and ICAM-1 are dense and persistent (Videos 2A and 2B).” To emphasize this point, which we think is clear when comparing Videos 1A/1B to Videos 2A/2B, we have now added the following two sentences to the text: “In other words, when B cells receiving only anti-IgM stimulation do form discernable arcs (see, for example, those marked by magenta arrows in Figure 1A and 1B), they are much sparser and less robust than those formed by cells also receiving ICAM-1 stimulation. Moreover, we never saw even one B cell receiving anti-IgM stimulation alone that possessed a robust actin arc network.” Please note that the magenta arrows in Figure 1A and 1B were added upon revision. In summary, the cell shown in Figure 1E, which lacks discernable arcs, is representative of ~70% of anti-IgM stimulated cells, while the cell shown in Figure 1F, which possesses a robust arc network, is representative of ~70% of anti-IgM+ICAM-1 stimulated cells.

We would also like to address what we think is a misunderstanding regarding our images in Figure 1, as reflected in reviewer 1’s statement: “The images and videos selected to represent cells stimulated with anti-IgM only (Figure 1; Videos 1A and 1B) seem form a highly branched actin network throughout the synapse”. The outer, Arp2/3-generated, branched network comprising the dSMAC/lamellipodium in primary B cells is really quite thin under both stimulation conditions (please see Figure 1, E1, E2, F1 and F2). In other words, we would not characterize the region between this thin, outer, canonical branched actin network and the central actin hypodense area (i.e. the region corresponding to the pSMAC) in B cells engaged with anti-IgM alone as “a highly branched actin network throughout”. We described it in the text as “a highly disorganized mixture of short actin filaments/fibers and actin foci”. While it likely contains some branched filaments, it is not a canonical branched actin network like the one comprising the dSMAC. Indeed, it is a lot like the mixture of actin asters, actin foci, branched actin and linear filaments described in Hela cells using the same imaging technique ((Fritzsche et al., 2017); we have now cited this paper). Of note, A20 B cells make a much bigger branched actin/dSMAC/lamellipodium than do primary B cells (compare the image of the representative A20 B cell in Figure 1J to the various images of primary B cells in this figure). Interestingly, this difference between immortalized cells and primary cells is conserved in T cells, as Jurkat T cells make a much bigger branched actin/dSMAC/lamellipodium than do primary T cells (Murugesan et al., JCB 2016).

Although the reviewers did not specifically comment on why only ~70% of primary B cells engaged with both anti-IgM and ICAM-1 make actomyosin arcs, we note that this is also the case for both Jurkat T cells and primary T cells (Murugesan et al., JCB 2016). We do not know why the number does not go to 100%, but the ~70% limit is the case for both B cells and T cells. Of note, in unpublished work we see that LFA-1 ligation also promotes actomyosin arc formation in T cells.

With regard to the reviewers’ question “Does LFA-1:ICAM-1 ligation simply stabilize the arcs and therefore make their appearance more likely, or does it promote the formation of a distinct actomyosin network with unique functions?”, we think that ICAM-1 engagement likely leads to the strong activation of RhoA, which then serves to drive both the formation of actin arcs by recruiting, unfolding, and activating mDia at the plasma membrane, and the stabilization and concentric organization of these arcs by activating myosin 2A filament assembly and contractility. In other words, we think ICAM-1 engagement leads simultaneously to the creation and stabilization/organization of the arcs. While it is true that BCR stimulation alone activates RhoA signaling to some extent (see Saci and Carpenter, Mol Cell 2005 and Caloca et al., J Biol Chem 2008), and that this may account for the sparse actin arcs seen in cells stimulated with anti-IgM alone, it is likely that RhoA signaling is more robust with the addition of integrin co-stimulation (Lawson and Burridge, 2014) and that this would promote the creation of the actomyosin arcs seen in these cells. That said, without independent measures of the creation and stabilization/turnover of the arcs, we cannot gauge the relative significance of creation versus stabilization/turnover in determining the steady state amount of arcs. To address this limitation, we have added the following sentence to the section of the Discussion dealing with integrin-dependent signaling pathways leading to actomyosin arc formation: “Finally, future studies should also seek to clarify the extent to which integrin ligation promotes the formation of actomyosin arcs by driving their creation versus stabilizing them once created.

With regard to the reviewers’ comment that “B cells stimulated with anti-IgM alone are capable of signalling and centralising antigen” we would like to emphasize that our study focuses on B cell immune synapse formation under limiting antigen conditions, where a previous study (Carrasco et al., Immunity 2004) and our data in Figure 4 – supplement 1 show that the impairments in BCR signaling and antigen centralization seen under this condition are rescued by integrin co-stimulation. We expand upon these findings by showing in Figures 5 and 6 that this integrin-dependent rescue of antigen centralization and BCR signaling requires actomyosin. In other words, the actomyosin arc network described here is required for integrin co-stimulation to promote antigen centralization and signaling under limiting antigen conditions. We agree with the reviewer that under non-limiting antigen conditions B cells can signal and centralize antigen in the absence of ICAM-1. That said, these high levels of BCR stimulation are probably not as physiological as limiting BCR stimulation. Finally, our data in Figure 5 – supplement 2 shows that antigen centralization in primary B cells receiving non-limiting anti-IgM stimulation alone is also significantly impaired when myosin is inhibited. This suggests that cells receiving high levels of BCR stimulation employ myosin in some fashion to drive antigen centralization. We now close the section describing these results with the following statement:

“That said, additional experiments should help define exactly how myosin contributes to antigen centralization in B cells receiving only strong anti-IgM stimulation."

Finally, and most generally, we avoided the use of the word “requirement” as in the reviewer’s statement “the requirement for LFA-1:ICAM-1 ligation in the formation of the actomyosin arcs is not clear”. Given that some B cells receiving only anti-IgM stimulation create arcs (albeit sparse and transient), we were careful to say throughout the text that ICAM-1 engagement “promotes” actomyosin arc formation. We think our evidence for this is compelling.

2) The observation that some GC B cells centralise antigen is very interesting, but there are a few aspects of this investigation that should be expanded upon. The authors show that with LFA-1:ICAM-1 interactions, GC B cells are about equally likely to organise BCR:antigen complexes into peripheral clusters and centralised clusters. It would be informative to have, in the same study (Figure 7), a comparison with GC B cells stimulated with antigen alone. The reason is that other studies investigating GC B cell synapse architecture did not quantify antigen organisation in this way, so it is difficult to make comparisons with previous work. It would also be very useful to see how the actomyosin network is organised in GC B cells exhibiting different synaptic architectures (i.e. peripheral versus central clusters), especially given the critical role of myosin IIa activity in GC B cell antigen affinity discrimination. Additionally, while it is a very interesting observation that LFA-1:ICAM-1 interactions may affect GC B cell synapse organisation, it is not clear whether this has an impact on cellular function. For instance, does antigen and actomyosin organisation in GC B cell synapses contribute to differences in signalling or traction force generation? In the introduction the authors suggest that actomyosin arcs contribute to antibody affinity maturation (line 87-88), but without functional studies to support this claim I think it is too speculative.

We thank the reviewer for their comments and suggestions regarding our GC data. Our sole purpose in performing the experiments in Figure 7 was to see if GC B cells can also make actomyosin arcs. We did this because recent papers and reviews state that the organization and dynamics of actin at GC B cell synapses are completely different from the organization and dynamics of actin at naive B cells synapses. As such, these initial observations are meant to add to previous work on GC B cells rather than generate direct comparisons. The reviewers appear to agree that the data in Figure 7 shows convincingly that a subset of GC B cells can make actomyosin arcs that are indistinguishable in appearance from those formed by naive B cells (so the specific claim we are making does not “require additional supporting data”). Rather, the reviewers request that we expand on the data in Figure 7 in several ways, some of which we had already mentioned in the Discussion (“While additional work is required to prove that the subset of GC B cells with actomyosin arcs are the ones that centralize antigen, this seems likely given our evidence here that actomyosin arcs drive antigen centralization in naïve B cells.”, and “Future work will also be required to understand why GC B cells vary with regard to actomyosin organization and the ability to centralize antigen 18 (e.g. dark zone versus light zone GCs)”). In addition to these statements, we now end the section describing the results in Figure 7 with the following statement:

“We note, however, that our conclusions regarding actomyosin arcs in GC B cells require additional supporting data that include testing the ICAM-1 dependence of actomyosin arc formation and quantitating the contributions that this contractile structure makes to GC B cell traction force, signaling, and antigen centralization.”

With regard to the reviewers concerns indicated by their comment “In the introduction the authors suggest that actomyosin arcs contribute to antibody affinity maturation (line 87-88), but without functional studies to support this claim I think it is too speculative”, we have changed the relevant sentence to “Finally, we show that germinal center (GC) B cells can also create this actomyosin structure, suggesting that it may contribute to the functions of GC B cells as well”.

3) mDia1 miRNA data requires supporting experiments with rescue of the phenotype upon re-expression or, at minimum, scrambled controls. Also the suggestion that mDia1 nucleates the F- actin at the distal edge spikes remains a hypothesis that would be easy to test with immunofluorescence stainings. Can you say or hypothesize how LFA-1 activates mDia1, and if ROCK is important for that, did you try experiments using the Y27632 compound to block it (optional)?

We now end the section on mDia1 with the following sentence: “We note, however, that this latter conclusion requires additional supporting data, including quantitative imaging of cells treated with a scrambled miRNA control and immunostaining for mDia1.”

With regard to ROCK, we did do one experiment that showed Y27632 disrupts actin organization much like BB does. We would prefer, if possible, to save this data (and the required repeats) for an ongoing study exploring the signaling pathways leading to actomyosin arc formation following LFA-1 ligation.

References

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Hammer, J. A., Wang, J. C., Saeed, M., and Pedrosa, A. T. (2019). Origin, Organization, Dynamics, and Function of Actin and Actomyosin Networks at the T Cell Immunological Synapse. Annual Review of Immunology, 37, 201-224. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/30576253. doi:10.1146/annurev-immunol-042718-041341

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

Essential revisions:

The reviewers and editors appreciate that manuscript is improved by the revisions, but there remained concerns about the evidence for the role of mDia in forming arcs and the lack of functional data or consideration of function in the discussion.

1. The appropriate controls need to be included to publish the siRNA data on mDia1. As the formin inhibitor is known to be problematic, strengthening the siRNA experiment is necessary to make the conclusion.

We thank the reviewers and the editor, and have now included two nontargeting miRNA controls, both of which had no effect on the formation actin arcs in A20 cells (please see new Figure 2 —figure supplement C1-C4 and D1-D4). Of note, this result is consistent with the fact that three different mDia1 miRNAs abrogated arc formation, as eliciting the same phenotype with multiple RNAi sequences is generally accepted as good evidence that the phenotype is not due to off-target effects.

Regarding our use of the pan formin inhibitor SMIFH2, which has been reported to inhibit myosin 2 as well as formins, it is important to note that myosin inhibition and formin inhibition have very different effects on arc actin in both T cells (Murugesan JCB 2016) and B cells (reported here): while arc actin disappears when formin activity is inhibited or depleted, arc actin forms when myosin is inhibited but is no longer organized into concentric structures (see Figure 3G). We see the former not the latter in our SMIFH2 experiment (see Figure 2 D2), consistent with a block in arc actin formation downstream of a block in formin activity.

2. The definition of an arc still needs to be clarified and relate to the distribution of antigen receptor-antigen complexes. In cells with a more peripheral antigen distribution are their fewer arcs in the interface with the substrate?

We thank the reviewers and the editor for the opportunity to further clarify how we defined and scored arcs, and to further highlight the major difference between primary B cells that do or do not receive ICAM-1-co-stimulation. With regard to the yes/no scoring of arcs in Figure 1, Panel G, we revised the text to make it clearer that the scores are for the presence of any discernible arcs. So, B cells like the ones shown in Figure 1A and B, which received only anti-IgM stimulation, and that have only a couple of arc-like actin filaments in their entire synapse, were scored as yes, just like the B cells in Figure 1C and D, which received both anti-IgM and ICAM-1 stimulation, and that have very robust actin arc networks. We scored this way to be as conservative as possible (and even then, the difference between anti-IgM and anti-IgM plus ICAM-1 was P<0.01). Importantly, in the revised text we then state that “static and dynamic imaging showed that the arcs in cells engaged with anti-IgM alone are sparse and transient (Figure 1A, B; Videos 1A and 1B), while those in cells engaged with both anti-IgM and ICAM-1 are dense and persistent (Figure 1C, D; Videos 2A and 2B)”. To further stress this important point, we added two sentences to the revised manuscript. The first is: “In other words, when B cells receiving only anti-IgM stimulation do form discernable arcs (see, for example, those marked by magenta arrows in Figure 1A, B), they are much sparser and less robust than those formed by cells also receiving ICAM-1 stimulation.” The second is: “Moreover, we could not find any B cells receiving anti-IgM stimulation alone that possessed a robust actin arc network”. We also added the following sentence to the Figure 1 legend:

“Of note, the cell shown in E1/E2 is representative of ~70% of anti-IgM stimulated cells, while the cell shown in F1/F2 is representative of ~70% of anti-IgM+ICAM-1 stimulated cells.” In terms of providing a grey scale quantitation of arcs by counting them in our TIRF-SIM images, we hope the reviewers would agree that doing this is not feasible. That said, we have now included in new Figure 1 —figure supplement 1A1-A3 measurements of the degree of alignment of actin filaments in the pSMAC of B cells stimulated with anti-IgM alone versus B cells stimulated with both anti-IgM and ICAM-1. These anisotropy measurements provide numeric support for our overall conclusion that ICAM-1 co-stimulation promotes the formation of an organized actin arc network in the pSMAC. The text describing this new data reads: “Consistently, measurements of the degree of alignment between actin filaments in the pSMAC portion of B cells stimulated with anti-IgM alone versus both anti-IgM and ICAM-1, which were made using FibrilTool (29), revealed a dramatic shift towards more organized pSMAC actin when ICAM-1 is included (Figure 1 —figure supplement 1A1-A3; see the figure legend for details).”

With regard to how the actin arcs relate to the distribution of antigen, we showed that (i) actin arcs surround centralized antigen in B cells on planar lipid bilayers containing anti-IgM and ICAM-1 (Figure 4A1-A3B), (ii) that the speeds with which antigen clusters and actin arcs move inward across the pSMAC match (Figure 4C, 4D; Figure 4 —figure supplement 1A1-A3), (iii) that individual actin arcs sweep individual BCR antigen clusters inward (Figure 4D-G), and (iv) that the ability of ICAM-1 ligation, which we established promotes the formation of actomyosin arcs, to promote antigen centralization under conditions of limiting antigen requires myosin contractility (Figure 5). Finally, in new data added to the section on GC B cells (see new Figure 7– supplement 1A1-A3 and new Videos 12 and 13) we show that PLB-engaged GC B cells exhibiting centralized antigen show a pSMAC-like accumulation of GFP-M2A surrounding much of the centralized antigen. GC B cells exhibiting peripheral antigen clusters or microclusters, on the other hand, showed no obvious pattern to the distribution of GFP-M2A at the synapse. Moreover, the synapses with peripheral antigen clusters exhibited less total GFP-M2A than the synapses with centralized antigen (new Figure 7– supplement 1B), and the signals that were present appeared quite transient (new Videos 12 and 13). These new results are described in more detail below in our response to Reviewer #1.

In summary, we think our evidence here that the co-stimulatory effect provided by integrin ligation requires the formation of a contractile actomyosin arc network is important for a number of reasons. First, it provides mechanistic insight into the seminal discovery by Carrasco and colleagues that engaging the B cell’s integrin LFA-1 promotes B cell activation and IS formation when membrane-bound antigen binds the BCR weakly or is presented at low density. Second, our results provide a counterpoint to the results in a 2018 eLife paper using A20 B cells that concluded myosin has no obvious role in either B cell activation or synapse formation. We think this difference highlights the importance of studying primary B cells. Third, our results show that an actomyosin arc network, not the Arp2/3-complex-dependent branched network, is the major actin network in primary B cells receiving integrin co-stimulation. Fourth, our evidence that myosin promotes B cell activation and synapse formation under conditions of limiting antigen likely has physiological relevance, as the response of follicular B cells to membrane-bound antigen early in the immune response typically involves antigens that bind the BCR weakly, where integrin co-stimulation from ICAM-1 on surface of the APC and subsequent actomyosin arc formation would promote B cell activation. Our results may also have physiological relevance for GC B cells given that the selection of GC B cells with higher affinity BCRs is thought to depend to a significant extent on their ability to gather antigen in the context of strong competition for limiting antigen presented by follicular dendritic cells. Finally, for those interested in defining the roles of actin and myosin in antigen extraction by the B cells, our results highlight the importance of including integrin ligation in understanding the mechanistic basis for this essential B cell function. We think this “reset” is particularly important as several recent studies addressing the mechanism of antigen extraction, including one in eLife, did not include a ligand for LFA-1 in their assays. Of note, all of the above points are included at various places in the revised manuscript.

3. The parallels between the earlier analysis of myosin arcs in T cells and this study are remarkable, but a discussion of how these compare considering the distinct functions of the two cell types is lacking. A discussion of this comparison could also be helpful to bring more consideration of function to the paper.

We thank the reviewers and the editor for asking us to speculate about how T cells and B cells might use the force generated by a similar contractile synaptic structure to perform their distinct functions. To address this important question, we revised the second half of the Discussion by consolidating the points made in the previous version and adding specific ideas regarding how T cells and B cells might use the force generated by the same contractile synaptic structure to perform their distinct functions. Here is the relevant portion of the revised Discussion:

“The actomyosin arcs described here in B cells and the actomyosin arcs described previously in T cells (27) have a great deal in common as regards their formation, organization and dynamics (7, 38). Consistently, this contractile structure supports a number of synaptic processes that are shared by these two cell types, including antigen centralization, proximal signaling, and the formation of an adhesive ring in the medial portion of the IS. A major question, then, is how these two immune cell types harness the force generated by this shared contractile structure to perform their unique functions, i.e. target cell killing by the T cell and antibody creation by the B cell. Stated another way, how does the T cell use the force generated by this contractile structure to support the effectiveness of an exocytic event (lytic granule secretion), while the B cell uses the force to support the effectiveness of an endocytic event (antigen extraction and uptake). With regard to T cells, a seminal study by Basu and colleagues (83) showed that actomyosin-dependent forces placed on the target cell membrane by the T cell increase the efficiency of target cell killing by straining the target cell membrane in such a way as to increase the pore-forming activity of perforin. One clear goal, therefore, is to determine if the T cell’s actomyosin arcs are responsible for creating this strain. Imaging the actomyosin arcs during the process of target cell killing, and blocking the force they generate just prior to lytic granule secretion, should reveal their contribution to this essential effector function.

The idea that B cells would use the actomyosin arcs identified here to support the extraction and endocytic uptake of membrane-bound antigens stems from the seminal work of Tolar and colleagues, who showed that M2A plays an important role in antigen extraction (63, 84, 85). These authors also presented evidence that M2A-dependent pulling forces select for BCRs with higher affinity for antigen, as such interactions survive the myosin-dependent strain placed on them, resulting in antigen extraction ((63, 84); for review see (7) and (86)). That said, a recent, imaging-based effort to define the mechanism by which antigen is extracted did not provide clear insight into how M2A contributes to this process. Specifically, Roper et al., (87) reported that the synapses of naïve B cells bound to antigen-bearing plasma membrane sheets (PMSs) are composed of a dynamic mixture of actin foci generated by the Arp2/3 complex and disorganized linear filaments/fibers generated by a formin. While static images showed little co-localization between the actin foci and antigen clusters, dynamic imaging suggested that the foci promote antigen extraction (although formin activity was also required). Based on these and other observations, Roper et al., concluded that naive B cells use a foci-filament network to drive force-dependent antigen extraction (87). How M2A contributes to this force was unclear, however, as M2A (visualized using an antibody to the phosphorylated form of M2A’s RLC) did not co-localize with either actin structure (87). Moreover, neither actin structure was affected by BB treatment. These two findings are notably at odds with our findings that M2A (visualized by endogenous tagging of the M2A heavy chain) co-localizes dramatically with actin arcs, and that BB treatment profoundly disrupts the organization of the pSMAC actin arc network. Regarding this discrepancy, we note that the images of synaptic actin presented by Roper et al., look similar to our images of naïve B cells stimulated with anti-IgM alone, where the synapse was also composed of a disorganized and dynamic mixture of actin foci and short actin filaments/fibers. The fact that the PMSs used by Roper et al., did not contain integrin ligands may explain, therefore, why they did not see a more organized synapse containing actomyosin arcs. In the same vein, two other recent studies examined antigen extraction using substrates that lacked integrin ligands (PLBs and PMSs in (64), and acrylamide gels in (48)). Given our results, we suggest that future efforts to define the mechanism by which M2A promotes antigen extraction should follow the myosin as the B cell extracts antigen from an APC, where the B cell’s integrins will be engaged, and where the antigen can be presented in a physiologically relevant way (e.g. opsonized and bound to an Fc or complement receptor). Such efforts will hopefully reveal how the B cell harnesses the forces generated by the actomyosin arcs identified here to drive antigen extraction and uptake.”

Reviewer #1 (Recommendations for the authors):

The authors have addressed most of my comments. There is a point raised in my original review that the authors addressed with some modifications/additions to the text, but I think additional analysis of existing data would really strengthen the paper. This is summarised below.

1) The authors suggest that GC B cells with actomyosin arcs are likely those that centralise antigen, but further data analysis is needed to support this claim. Specifically, I think the authors should quantitate the overlap of GC B cells that centralise antigen and those that have actomyosin arcs. Additionally, to give better insight into how actomyosin helps to organise antigen in the synapse, it would be informative to include example images of actomyosin organisation in GC B cells that have peripheral antigen clusters and microclusters (to complement Figure 7, E1-E3) alongside the images already shown of a GC B cell that has centralised antigen (Figure 7, C1-C4). The authors are likely to already have these data in hand so it should not require additional experiments. I think these additions to Figure 7 would strengthen the paper by giving more insight into how antigen organisation in the synapse is dependent on the presence of actomyosin arcs.

We thank Reviewer #1 for their positive assessment of our paper, and for their specific suggestion as to how we might further clarify the connection between antigen centralization and the actomyosin arcs we see in a subset of GC B cells. Before discussing new data related to their suggestion, we would like to mention that we revised the text regarding Figure 7C1-C4 to better emphasize how those images support the connection between the actomyosin arcs and antigen:

“Importantly, scoring showed that about one third of glass-engaged GFP-M2A knockin GC B cells exhibited robust accumulation of M2A filaments in the pSMAC (Figure 7B). Similarly, about one third of GFP-M2A knockin GC B cells engaged for 10 minutes with PLBs containing fluorophore-labeled anti-IgM/IgG and unlabeled ICAM-1, and then fixed and stained with phalloidin, exhibited robust accumulation of M2A filaments in the pSMAC (Figure 7C1-C4, and D). Importantly, these actomyosin arcs can be seen to surround antigen accumulated at the center of the synapse (see the white arrows in Figure 7C1, C2 and C4). This finding, together with the fact that the myosin moves centripetally during IS formation (Video 11), suggests that actomyosin arcs can contribute to antigen centralization in GC B cells as well as in naïve B cells.”

We thank Reviewer #1 for their excellent suggestion to include images of actomyosin distribution in GC B cells that have peripheral antigen clusters and microclusters alongside images of actomyosin distribution in GC B cells that have centralized antigen. Towards that end, we have now included representative images of GFP-M2A distribution in all three types of synapses shown in Figure 7E1-E4 in new Figure 7 —figure supplement 1. The addition of these images, the conclusions we draw from them, and the remaining unanswered questions are covered in the following section of the revised manuscript:

“Given these results, we asked if our PLB-engaged mouse GC B cells can centralize antigen. In partial agreement with previous findings (63,64), ~45% of synapses exhibited small to medium sized antigen clusters distributed to varying degrees in the synapse periphery (Figure 7E1, E2 and F). In addition, ~20% of synapses exhibited antigen microclusters spread throughout the synaptic interface (Figure 7E3 and F). Importantly, the remaining ~35% of synapses exhibited highly centralized antigen (Figure 7E4 and F). Images of these synapses showed a pSMAC-like accumulation of GFP-M2A surrounding much of the centralized antigen (Figure 7 —figure supplement 1A1; see also Video 12). Conversely, images of synapses containing either peripheral antigen clusters or microclusters showed no obvious pattern to the distribution of GFP-M2A (Figure 7 —figure supplement 1A2, A3; see also Video 13). Moreover, the synapses containing peripheral antigen clusters exhibited less total GFP-M2A signal than the synapses with centralized antigen (Figure 7 —figure supplement 1B), and the signals appeared more transient (compare Video 13 to Video 12). These results, together with the images in Figure 7C1-C4, argue that GC B cells with centralized antigen (about one third of cells) are the ones that make actomyosin arcs (again, about one third of cells). We conclude, therefore, that GC B cells can make actomyosin arcs and that they likely use this structure to centralize antigen, although the degree to which they do this is considerably less than for naïve B cells. We note, however, that our conclusions regarding GC B cells require additional supporting data that include testing the ICAM-1 dependence of actomyosin arc formation and quantitating the contributions that this contractile structure makes to GC B cell traction forces, signaling, and antigen centralization.”

Finally, we will comply with eLife’s COVID policy on revisions by performing these latter experiments at a later date and uploading our findings on the preprint server.

Reviewer #2 (Recommendations for the authors):

Unfortunately, I feel that the authors have not really acted upon the concerns of the reviewers. No new data, analysis or even any considerable discussion points have been added. The concerns about manual segmentation, yes/no -type of analysis of the actin arcs, and the limited description of the breadth of data remain. Also, siRNA silencing data without scrambled controls or rescue experiments does not belong to today's high quality cell biological publications. This lack of rigor in some experimental parts without efforts to improve it is concerning.

We thank Reviewer #2 for their comments. With regard to their concerns about the yes/no -scoring of actin arcs, we ask that they please read our response to Essential Revision #2 above. With regard to their concerns about manual segmentation, we ask that they please read our response to Reviewer #3 below. With regard to their comment about the limited description of the breadth of data, we ask that they please read our response to Essential Revision #3 above. Finally, with regard to Reviewer #2’s comments regarding the lack of a scrambled miRNA control, it was not our intention to be dismissive of this reviewer’s very reasonable request, and we apologize for that. As discussed above, our decision to respond to this request by qualifying our conclusions in the revised text and stating that additional experiments are required to solidify the conclusions rather than by performing the experiments was based on eLife’s current policy on revisions made in response to COVID-19, which states that “when editors judge that a submitted work as a whole belongs in eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.” We also think that getting the same phenotype with three different miRNAs, as we did here for mDia1 (loss of arcs), is generally accepted as good evidence that the phenotype is not due to off-site targets. Given this, given that mDia1 is the most abundant formin in B cells, given that it is responsible for forming arcs in T cells (Murugesan et al., 2016), and given eLife’s COVID-era revision policy, we thought that our qualification regarding the role of mDia1 in creating the arcs, as encapsulated by the following sentences in our initial revision “Together, these results argue that the pSMAC actin arcs are indeed created by a formin, and that the formin mDia1 plays a major role. We note, however, that this latter conclusion requires additional supporting data, including quantitative imaging of cells treated with a scrambled miRNA control and immunostaining for mDia1”, was reasonable. That said, we have now included two scrambled/nontargeting miRNA controls and modified the text accordingly (please see our response to Essential Revision Request #1).

Reviewer #3 (Recommendations for the authors):

The authors have considered and included a number of the reviewer comments in their revised version of the article 'A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation'. The manuscript has gained in clarity and the figures and supplement data underline strongly the findings and claims made by the authors that LFA-1 ligation plays and important role in B-cell activation through the formation of actin arcs that push engaged ICAM-1 clusters towards the cSMAC.

However, one weakness is the lack of additional data to support the findings on the role of mDia1 as the use of scrambled miRNA or immunostaining for mDia1 would be typical control experiments here. The response to reviewers also does not provide any further information why these experiments could not be performed.

We thank Reviewer #3 for their positive assessment of our paper. With regard to their last point (why we did not include a scrambled miRNA control on our first revision), we ask that they please read the first paragraph of our rebuttal and the confidential information below. Importantly, have now included two nontargeting miRNA controls, both of which had no effect on the formation actin arcs in A20 cells (please see new Figure 2 —figure supplement C1-C4 and D1-D4).

Apart from that there are a few points that should be addressed/ clarified:

– line 312 onwards (about kymograph analysis): the image provided does not show convincingly how the velocities could be measured with such precision (2 digit precision with 21 data points). E.g. I cannot make out a clear line for velocity calculation in the dSMAC region of Figure 4-Figure sup 1 A2, and the lines in the pSMAC show a variety of slopes that would result in a higher standard deviation. How many readings from each kymograph were used per cell? Does the bar diagrams in Figure 4-Figure sup1 compare the average values of each cell or compare the measurements from all cells pooled together?

First, we agree that the lines within the dSMAC in the kymograph for the primary B cell in Panel A2 are hard to see (especially as compared to A20 cells), so we added some white arrowheads to Panel 2A to point out several of them. We note that this difference between A20 B cells and primary B cells, where A20 cells have a much more robust dSMAC than primary B cells, is also seen for T cells, where Jurkats have a much more robust dSMAC than primary T cells (Murugesan et al., JCB 2016).

With regard to the flow rates in Figure 4 —figure supplement 1A3 and B3, we thank the reviewer for bringing this up as we did not make it clear in the text, legend or Methods what the numbers represent. We took ~7 measurements per cell for each SMAC. The values reported in A3 and B3 are an average of the mean rates per cell (with 21 and 14 cells scored for A3 and B3, respectively). This is now stated in the revised legend to Figure 4 —figure supplement 1, where we make clear that the bar graphs in A3 and B3 show standard error of the means (i.e. not standard deviations).

line 951-953 and methods section (line 820-822) (about anisotropy measurements): since the number of measurements differs between the two conditions, it would be better to represent the histogram in relative numbers (frequency or probability) instead of absolute numbers.

We thank the reviewer for this suggestion and now present the pre-existing anisotropy data comparing control and BB-treated cells, as well as the new anisotropy data comparing cells stimulated with anti-IgM alone versus anti-IgM plus ICAM1, as frequency measurements.

in addition, it would be good if the description in the methods section could be a bit more insightful, e.g. what criteria were followed to draw ROIs, did you draw ROIs of similar size in the dSMAC and pSMAC regions (the box drawing seems a bit random in the example image, which is puzzling)?

We thank the reviewer for seeking clarification regarding how we segmented our TIRF-SIM images. Drawing ROIs encompassing the pSMAC to measure the anisotropy of actin filaments within it, as well as many other measurements in the paper (e.g. the content of F-actin in SMACs), required that we segment synapses into their three SMACs. To accomplish this, we relied on the distinctive appearance of actin in each SMAC. This was easiest for B cells stimulated with both anti-IgM and ICAM-1, where the distinctions between the three SMACs were usually very clear in TIRF-SIM images (see for example Figure 1F1 and F2). Specifically, the thin outer dSMAC was comprised of moderately bright pixels with not much fluctuation in intensity, the medial pSMAC was comprised of bright actin arcs with intervening dim signals, and the central cSMAC was comprised mostly of dim signals. These distinctions were, however, less obvious in cells engaged with anti-IgM alone (see for example Figure 1E1 and E2), although the thin outer dSMAC was still identifiable, and the cSMAC was evident in lower mag images as a central circle with less signal than the area between it and the dSMAC (see for example Figure 1B). The latter area corresponded, then, to the pSMAC in cells stimulated with anti-IgM alone. As requested, we improved our description for how we performed manual segmentation of our TIRF-SIM images by including a version of the explanation above in the revised Methods section.

It would also be good to indicate that the anisotropy measurement is based on the intensity gradients between pixels.

We thank the reviewer for this comment and we have now included the following sentence in the methods “The FibrilTool plugin for ImageJ was used to measure actin arc morphology based on the intensity gradients between pixels as described previously (27, 29).”

line 970-971: please add to the legend that the red line indicates the average orientation of the filaments in the ROI.

We have added this to the figure legend for Figure 1—figure supplement 1. Thank you.

Figure 5 – sup Figure 2: Within the anti-IgM zones seem to be clusters of phalloidin that are void of anti-IgM signal. is that just an odd effect of the interplay between the fluorescent markers or do these zones have a biological meaning, i.e. are these zones containing some other proteins that bind strongly to actin and exclude the anti-IgM?

We thank Reviewer #3 for this question. That said, we cannot at this time weigh in on the biological meaning of the phalloidin clusters they are referring to.

https://doi.org/10.7554/eLife.72805.sa2

Article and author information

Author details

  1. Jia C Wang

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8666-4662
  2. Yang-In Yim

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Resources
    Competing interests
    No competing interests declared
  3. Xufeng Wu

    Light Microscopy Core, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  4. Valentin Jaumouille

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Data curation, Formal analysis, Investigation
    Competing interests
    No competing interests declared
  5. Andrew Cameron

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Data curation, Resources
    Competing interests
    No competing interests declared
  6. Clare M Waterman

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Methodology, Resources
    Competing interests
    No competing interests declared
  7. John H Kehrl

    B Cell Molecular Immunology Section, National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, United States
    Contribution
    Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6526-159X
  8. John A Hammer

    Cell and Developmental Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, United States
    Contribution
    Conceptualization, Data curation, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing
    For correspondence
    hammerj@nhlbi.nih.gov
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2496-5179

Funding

National Heart, Lung, and Blood Institute (1ZIAHL006121-04)

  • John A Hammer

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

Acknowledgements

This work was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute (NHLBI) (1ZIAHL006121-04 to JAH). The authors thank the NHLBI Flow Cytometry Core, Dr. Xuefei Ma for providing M2A-GFP mice, Dr. Il-Young Hwang for immunizing mice to prepare GC B cells, and Dr. Christopher J Alexander for advice on miRNA design.

Ethics

This study was performed in strict accordance with the recommendations and protocols approved by the National Human Genome Research Institute Animal Use and Care Committee at the National Institutes of Health. All animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#H-0337) of the National Institutes of Health.

Senior Editor

  1. Anna Akhmanova, Utrecht University, Netherlands

Reviewing Editor

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

Reviewer

  1. Pieta K Mattila, University of Turku, Finland

Publication history

  1. Received: August 5, 2021
  2. Preprint posted: August 13, 2021 (view preprint)
  3. Accepted: April 10, 2022
  4. Accepted Manuscript published: April 11, 2022 (version 1)
  5. Version of Record published: May 27, 2022 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Jia C Wang
  2. Yang-In Yim
  3. Xufeng Wu
  4. Valentin Jaumouille
  5. Andrew Cameron
  6. Clare M Waterman
  7. John H Kehrl
  8. John A Hammer
(2022)
A B-cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation
eLife 11:e72805.
https://doi.org/10.7554/eLife.72805

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