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. 2019 Aug 21;8:e47015. doi: 10.7554/eLife.47015

B cell receptor and Toll-like receptor signaling coordinate to control distinct B-1 responses to both self and the microbiota

Lieselotte SM Kreuk 1, Meghan A Koch 1,, Leianna C Slayden 1, Nicholas A Lind 1, Sophia Chu 1, Hannah P Savage 2, Aaron B Kantor 3, Nicole Baumgarth 2, Gregory M Barton 1,
Editors: Andrew J MacPherson4, Wendy S Garrett5
PMCID: PMC6703855  PMID: 31433298

Abstract

B-1a cells play an important role in mediating tissue homeostasis and protecting against infections. They are the main producers of ‘natural’ IgM, spontaneously secreted serum antibodies predominately reactive to self antigens, like phosphatidylcholine (PtC), or antigens expressed by the intestinal microbiota. The mechanisms that regulate the B-1a immunoglobulin (Ig) repertoire and their antibody secretion remain poorly understood. Here, we use a novel reporter mouse to demonstrate that production of self- and microbiota-reactive antibodies is linked to BCR signaling in B-1a cells. Moreover, we show that Toll-like receptors (TLRs) are critical for shaping the Ig repertoire of B-1a cells as well as regulating their antibody production. Strikingly, we find that both the colonization of a microbiota as well as microbial-sensing TLRs are required for anti-microbiota B-1a responses, whereas nucleic-acid sensing TLRs are required for anti-PtC responses, demonstrating that linked activation of BCR and TLRs controls steady state B-1a responses to both self and microbiota-derived antigens.

Research organism: Mouse

Introduction

B-1a cells were discovered 35 years ago and have characteristics that bridge the innate and adaptive immune system (Herzenberg et al., 1986). Unlike follicular B cells, termed B-2, B-1a cells are rapidly recruited to sites of infection and produce antibodies independently of T cell help. B-1a cells are the main producers of serum IgM antibodies (Lalor et al., 1989a; Baumgarth et al., 1999; Ohdan et al., 2000; Haas et al., 2005; Choi and Baumgarth, 2008; Holodick et al., 2009), which promote tissue homeostasis and provide protection against infections (Haas et al., 2005; Choi and Baumgarth, 2008; Boes et al., 1998; Ochsenbein et al., 1999; Boes et al., 2000; Ehrenstein et al., 2000; Baumgarth et al., 2000; Alugupalli et al., 2003; Notley et al., 2011; Vas et al., 2013). More recently B-1a cells have been implicated as a source of microbiota-reactive, class-switched IgG and IgA antibodies, which are important for intestinal homeostasis (Kroese et al., 1989; Kroese et al., 1993; Lalor, 1991; Kroese et al., 1996; Bos et al., 1996; Macpherson et al., 2000; Koch et al., 2016; Savage et al., 2017).

B-1a cell-derived antibodies are often reactive with self epitopes (Hayakawa et al., 1999; Mercolino et al., 1988; Yang et al., 2015). For example, the most common B-1a specificity is for phosphatidylcholine (PtC), a phospholipid present within the plasma membranes of eukaryotic cells (Mercolino et al., 1988). Other specificities include nucleic acids, LPS, and carbohydrates. Early studies from Hayakawa and colleagues showed that the absence of a specific self-antigen, such as Thy-1, results in the absence of self-reactive B-1a specificities to that antigen (Khan et al., 1995a). Moreover, mice harboring mutations in BCR signaling molecules such as Btk exhibit a reduction in B-1a B cell numbers (Khan et al., 1995b), whereas mice with deficiencies in BCR coinhibitory molecules such as CD72 have increased frequencies of B-1a cells (Pan et al., 1999). These studies strongly suggest that positive selection via BCR signaling is critical for B-1a cell development and/or maintenance.

Many B-1a derived antibodies have been termed polyreactive due to their ability to bind shared structures present on a variety of apparently unrelated self and foreign antigens. For example, B-1a-derived monoclonal antibodies can recognize epitopes present on cell membranes of apoptotic cells but also on bacterial cell wall polysaccharides (Boes et al., 2000; Ehrenstein et al., 2000; Notley et al., 2011; Nguyen et al., 2015). A recent study by Yang et al. (2015) reported no significant difference in the immunoglobulin heavy chain repertoire of B-1a cells from adult germ free (GF) and specific-pathogen-free (SPF) mice, supporting a model whereby the B-1a repertoire is not defined by microbiota-derived antigens. Consequently, B-1a antibody responses directed against the microbiota are generally thought to arise from BCR specificities selected on self but cross-reactive to microbial antigens. However, the extent to which self versus microbiota-derived antigens contribute to the clonal expansion or antibody secretion of B-1a cells remains unknown.

B-1a derived serum antibodies are termed ‘natural’ IgM due to their constitutive secretion, which is thought to be independent of antigen exposure (Ochsenbein et al., 1999; Baumgarth et al., 2015). Additionally, whereas the B-2 cellular compartment is maintained by BM-derived hematopoietic cells (HSCs), B-1a cells are primarily of fetal and neonatal origin and are maintained by self-renewal throughout life (Lalor et al., 1989a; Lalor et al., 1989b; Montecino-Rodriguez et al., 2006; Yoshimoto et al., 2011; Kobayashi et al., 2014; Hardy and Hayakawa, 2015). Unlike B-2 cells, in vitro ligation of the BCR with anti-IgM on mature B-1a cells leads to reduced calcium mobilization and induction of apoptosis (Morris and Rothstein, 1993; Bikah et al., 1996; Ochi and Watanabe, 2000). The inability of mature B-1a cells to proliferate in response to BCR-mediated stimulation in vitro has been attributed to their expression of CD5, a negative regulator of TCR and BCR signaling (Bikah et al., 1996; Azzam et al., 1998; Hippen et al., 2000; Perez-Villar et al., 1999). These observations have led to a model whereby B-1a cell development is mediated by positive selection on self antigens, whereas activation and antibody production is regulated by non-clonal activation through pattern recognition receptors, such as Toll-like receptors (TLRs) or cytokine receptors (Nisitani et al., 1995; Waffarn et al., 2015; Ha et al., 2006). Indeed, B-1a cells express a variety of TLRs (TLR1, 2, 3, 4, 7, 8, and 9) and are more prone to terminal plasma cell differentiation than B-2 cells upon in vitro stimulation by TLR ligands (Genestier et al., 2007; Meyer-Bahlburg et al., 2009). B-1a cell-intrinsic TLR signaling has also been implicated in the egress of B-1a cells from the peritoneal cavity to the spleen and intestinal sites following challenge (Ha et al., 2006; Murakami et al., 1994). However, studies investigating TLR-dependent B-1a responses have largely been performed either in the context of infection or in vitro. Thus, the contribution of TLR signaling to steady state in vivo B-1a responses remains unclear.

In addition to positive selection, there is evidence that B-1a cells receive intermittent or ongoing BCR signaling throughout life, leading to their activation and expansion. A high frequency (15–30% of peritoneal cavity and 10–15% of splenic) of PtC-reactive B-1a cells is consistently observed in all strains of inbred mice, a significant percentage of which express the canonical VH11-2/VK14 heavy and light chain gene pair. Additionally, while young mice have a more diverse B-1a repertoire, dramatic BCR restriction occurs as animals age (Yang et al., 2015). This restriction suggests an antigen-specific BCR-mediated expansion process. In support of this model, a recent study from Zikherman and colleagues found that B-1a cells express high levels of Nur77 (Huizar et al., 2017), a gene associated with BCR signaling. Therefore, it is likely that B-1a cells are indeed receiving antigen specific BCR signaling in vivo, which may be important for their activation and expansion. However, it is still unclear how B-1a cells are able to respond to BCR-mediated activation, given their inherent inability to response to anti-IgM stimulation in vitro and expression of negative regulators of BCR signaling such as CD5.

In the present study we investigate the contribution of BCR and TLR signaling in regulating B-1a activation and function. We use a novel reporter mouse to show that the generation of self- and microbiota-reactive antibodies is linked to BCR signaling in B-1a cells. Moreover, we show that Toll-like receptors (TLRs) are critical not only for antibody secretion but also for defining the steady state B-1a immunoglobulin repertoire. Specifically, we find that nucleic acid-sensing TLRs are required for anti-PtC responses, whereas both a microbiota and bacterial-sensing TLRs are required for anti-commensal responses. Altogether, we propose a model whereby dual BCR and TLR signaling is required for the maintenance and antibody secretion of steady state B-1a responses to both self and gut microbial antigens, which may be important for preventing inappropriate responses leading to autoimmunity while aiding in the maintenance of tissue and intestinal homeostasis.

Results

Ighg3 reporter mouse marks a subset of activated, antibody secreting B-1a cells

Previous findings from our group showed that healthy mice make class-switched IgG3 and IgG2b serum antibodies reactive with the microbiota, which coordinate with IgA to dampen neonatal mucosal T cell responses (Koch et al., 2016). In order to better understand the origin and fate of IgG3+ B cells we created a knock-in mouse in which IgG3+ B cells express Cre recombinase (Cre) (Figure 1A). A targeting vector was used to introduce T2A-Cre followed by a frt-flanked neomycin-resistance gene into the Ighg3 constant region, just after the exon encoding the last Ighg3 transmembrane domain (Figure 1—figure supplement 1A). This design should link expression of Cre to translation of IgG3 protein. Southern blotting confirmed correct targeting of the Ighg3 locus (Figure 1—figure supplement 1B). We also confirmed a single insertion into the genome by southern blotting for the neomycin-resistance gene (Figure 1—figure supplement 1C). Ighg3T2A-Cre mice were crossed to β-actinFlippase mice to delete the neomycin-resistance gene. The resulting Ighg3T2A-Cre mice were intercrossed to Rosa26STOPflox-TdTomato reporter mice to generate mice homozygous for Ighg3T2A-Cre and Rosa26STOPflox-TdTomato, hereafter referred to as Ighg3T2A-Cre:TdTomato. In these mice the Tomato fluorescent protein should be expressed in any cell that expresses or has previously expressed IgG3 protein.

Figure 1. A reporter mouse marks activated B-1a cells.

(A) Schematic of targeted insertion of T2A-Cre into the Ighg3 (Iγ3) heavy chain locus to generate the Ighg3T2A-Cre reporter mouse. (B) Representative flow cytometry plot of IgG3 and IgM expression on pregated CD19+Tomato+ splenocytes from 6 wk old Ighg3T2A-Cre mice crossed to Rosa26STOP-flox-TdTomato mice (Ighg3T2A-Cre:TdTomato). (C) Percentage Tomato expression in B cell subsets from the peritoneal cavity (PerC) and spleen (Spl) of 6 wk old Ighg3T2A-Cre:TdTomato mice by flow cytometry. Total B cells defined as CD19+; B-2 cells defined as CD19+CD23+CD43CD5; B-1a cells defined as CD19+CD23CD43+CD5+. (D) Representative flow cytometry gating of Tomato and Tomato+ splenic B-1a cells from 3 wk old Ighg3T2A-Cre:TdTomato mice, pregated on Live/CD19+CD23 cells. (E) Representative histogram and quantification of FSC-A and (F) IgD expression on pre-gated Tomato (black) and Tomato+ (red) splenic B-1a cells. (G) Number of IgM+ antibody secreting cells (ASCs)/106 present in purified Tomato (black) or Tomato+ (red) splenic (closed circles) or peritoneal cavity (PerC) (open circles) B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice, as measured by ELISpot. (H) Serum IgM titers of 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red) and Ighg3T2A-Cre mice crossed to Rosa26STOP-flox-DTA (Ighg3T2A-Cre:DTA) (blue) mice. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Each data point represents an individual mouse (C, E-H). Data are representative of at least three independent experiments (B-G) or pooled from five independent experiments (H).

Figure 1.

Figure 1—figure supplement 1. Validation of correct targeting of knock-in mouse.

Figure 1—figure supplement 1.

(A) Southern blot strategy to identify targeted insertion of T2A-Cre after the last transmembrane exon of Ighg3 (Iγ3) using DNA probes 5’ of Ighg3 (5‘ probe) and to the neomycin-resistance gene (Neo probe). (B) Southern blot of BglII restriction-digested ES cell DNA from clone D6, which was used to generate the Ighg3T2A-Cre mouse using a 5’ probe to detect 10.5 Kb band corresponding to WT DNA and a 8.4 Kb band corresponding to targeted insertion of T2A-Cre. (C) Southern blot of BglII restriction-digested ES cell DNA from clone D6 using a Neo probe to detect a single 5.5 Kb band indicating a single copy, targeted insertion. Data are representative of at least two independent experiments.
Figure 1—figure supplement 2.. TdTomato expression in IgM+ cells correlates with Ighg3 germ-line transcription in Ighg3 reporter mouse.

Figure 1—figure supplement 2.

(A) IgM expression on sorted IgM+Tomato+ splenocytes (red histogram) compared to TomatoCD19+ splenocytes (black histogram) after 48hr ex vivo culture, as measured by flow cytometry. (B) Splenocytes from 3 wk old Ighg3T2A-Cre:TdTomato mice were stimulated with LPS for 72 hr, followed by single-cell sorting and subsequent RT-PCR. (C) Schematic of murine heavy chain locus depicting the generation of Ighg3 (Iγ3) germ-line transcript (GLT) prior to AID-mediated class switch recombination from IgM to IgG3. (D) RT-PCR of single-cell sorted IgG3IgM+Tomato+ or IgG3+IgMTomato+ cells, as described in (B), for Ighm mRNA and Ighg3 mRNA, visualized by agarose gel electrophoresis. Arrows indicate primer binding sites. (E) Single-cell RT-PCR of Ighg3 germ-line transcript (GLT) and Ighm mRNA of IgG3IgM+Tomato+ as described in (B), visualized by agarose gel electrophoresis. Arrows indicate primer binding sites. (F) Serum IgG3 titers of 7 wk old Ighg3T2A-Cre:TdTomato (black) and Ighg3T2A-Cre mice crossed to Rosa26STOP-flox-DTA (Ighg3T2A-Cre:DTA) (blue) mice.(G) Expression of IgM versus IgG3 protein on 3-day in vitro LPS-stimulated splenocytes from Ighg3T2A-Cre:TdTomato and Ighg3-/- mice (top panel), as measured by flow cytometry. IgD and Tomato expression on pregated IgM+ in vitro stimulated B cells (bottom panel). FSC-A of pregated IgM+IgD+Tomato (gray histogram), IgM+IgD+Tomato (black histogram), and IgM+IgDTomato+ (red histogram) LPS-stimulated Ighg3T2A-Cre:TdTomato splenocytes. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Data are representative of at least two independent experiments.
Figure 1—figure supplement 3. Single-cell RT-PCR Primers.

Figure 1—figure supplement 3.

(A) Table summarizing the forward (5’) and reverse (3’) primers names and sequences for single-cell semi-nested RT-PCR of Ighm mRNA, Ighg3 mRNA, and Ighg3 germ-line transcript (GLT).
Figure 1—figure supplement 4. B cell development in bone marrow is unaltered in reporter mouse.

Figure 1—figure supplement 4.

(A) Representative flow cyometry gating of B cell subsets in the bone marrow of 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), and Ighg3T2A-Cre:DTA (blue) mice. Pre-B, Late Pro-B and, Early Pro-B cells were pregated as B220+IgM and identified according to their expression of CD19 and CD43. Mature and Immature B cells were pregated as B220+IgM+ and identified according to their expression of IgM and IgD. (B) Absolute counts of B220+ cells in the bone marrow from one femur in 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), and Ighg3T2A-Cre:DTA (blue) mice. (C) Absolute counts of Early Pro-B, Late Pro-B, Pre-B, Immature, and Mature B cells in the bone marrow from one femur in 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), and Ighg3T2A-Cre:DTA (blue) mice. (D) Representative flow cytometry dot plot showing the expression of CD19 and CD43 on pregated B220bone marrow cells (gray) overlayed with pregated Tomato+B220+ bone marrow cells (red) from Ighg3T2A-Cre:TdTomato mice (left); representative flow cytometry dot plot showing the expression of IgD and IgM on pregated B220+IgM+ bone marrow cells (gray) overlayed with pregated Tomato+B220+IgM+ bone marrow cells (red) from Ighg3T2A-Cre:TdTomato mice (middle); representative flow cytometry dot plot showing the expression of IgD and CD43 on pregated ‘immature’ B220+IgM+IgD bone marrow cells (gray) overlayed with pregated ‘immature’ Tomato+B220+IgM+IgD bone marrow cells (red) from Ighg3T2A-Cre:TdTomato mice (right). (E) Percentage Tomato expression in various bone marrow B cell subsets in 7 wk old Ighg3T2A-Cre:TdTomato mice. Each data point represents an individual mouse. Data are representative of two independent experiments.
Figure 1—figure supplement 5. Characterization of B cell subsets in the spleen and peritoneal cavity of reporter mice.

Figure 1—figure supplement 5.

(A) Absolute counts of CD19+ and CD19+CD23+ Follicular (FO) B cells from the spleens of 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), and Ighg3T2A-Cre:DTA (blue) mice. (B) Absolute counts of marginal zone B (MZ) (CD19+CD23CD21+), B-1a (CD19+CD23CD23CD43+CD5+), and B-1b (CD19+CD23CD23CD43+CD5) cells in the spleens of 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), or Ighg3T2A-Cre:DTA (blue) mice. (C) Percentage Tomato expression in various B cell subsets, as described in (B), in the spleens of 7 wk old Ighg3T2A-Cre:TdTomato mice. (D) Representative flow cytometry plot characterizing expression of CD43 and CD19 on pregated Tomato+CD19+IgMIgG3 splenocytes from a 7 wk old Ighg3T2A-Cre:TdTomato mice. (E) Absolute counts of CD19+, B-1a (CD19+CD23CD23CD43+CD5+), and B-1b (CD19+CD23CD23CD43+CD5) cells in the peritoneal cavities (PerC) of 7 wk old C57BL/6 (black), Ighg3T2A-Cre:TdTomato (red), or Ighg3T2A-Cre:DTA (blue) mice. (F) Percentage Tomato expression in various B cell subsetsm as described in (E), in the peritoneal cavity (PerC) of 7 wk old Ighg3T2A-Cre:TdTomato mice. Each data point represents an individual mouse. Data are representative of two (A, B, E) or at 5 (C, D, F) independent experiments.

In adult Ighg3T2A-Cre:TdTomato mice, Tomato expression was restricted to CD19+ B cells in the spleen (Figure 1B). However, we found that only a small fraction of Tomato+ cells were IgG3+ (Figure 1B). Unexpectedly, over half of Tomato+ splenic B cells were IgG3IgM+ (Figure 1B). We considered three possible mechanisms that could lead to the high frequency of IgG3IgM+Tomato+ cells. First, these cells may have recently class-switched to IgG3 and therefore still express surface IgM. However, sorted IgM+Tomato+ splenic B cells retained surface IgM after 48 hr in culture and did not gain expression of IgG3 (Figure 1—figure supplement 2A). Furthermore, single-cell RT-PCR of in vitro LPS stimulated Tomato splenocytes revealed that the resulting IgM+IgG3Tomato+ B cells expressed Ighm mRNA but not Ighg3 mRNA (Figure 1—figure supplement 2B,D; Figure 1—figure supplement 3A). Altogether, these results argue against the possibility that IgG3IgM+Tomato+ cells lack IgG3 because they recently class switched to IgG3. Second, we ruled out that Ighg3T2A-Cre:TdTomato mice were simply defective in IgG3 class switch recombination (CSR) by inducing IgG3 CSR via LPS stimulation of splenocytes in vitro (Figure 1—figure supplement 2B,G).

Therefore, we considered the possibility that IgG3IgM+Tomato+ cells express Cre without class switching to IgG3. The simplest way Cre expression could occur in the absence of CSR is translation of the T2A-Cre fusion protein from the Ighg3 germ-line transcript (GLT), which precedes IgG3 CSR, especially since there is an in frame ATG upstream of the Cre recombinase gene (Figure 1—figure supplement 2C). Such a mechanism would not be unprecedented, as previous work by Wabl and colleagues showed the translatability of the Ighm GLT (Bachl et al., 1996). As predicted, IgM+IgG3Tomato+ B cells expressed both Ighm mRNA and the Ighg3 GLT (Figure 1—figure supplement 2E; Figure 1—figure supplement 3A). Thus, the Ighg3T2A-Cre:TdTomato mouse appears to report induction of the Ighg3 GLT rather than class switching to IgG3. Moreover, the presence of large numbers of IgG3IgM+Tomato+ cells indicates that a significant fraction of B cells has received signals that induce Ighg3 GLT but not CSR to IgG3.

When we examined different subsets of B cells from Ighg3T2A-Cre:TdTomato mice in vivo, we discovered that the highest frequency of Tomato expression was in IgM+ B-1a cells (CD19+CD43+CD5+) (Figure 1C; Figure 1—figure supplement 5C,F). To begin to characterize the signals controlling induction of Cre in B cells of Ighg3T2A-Cre:TdTomato mice, we tracked Tomato expression in B cells in vivo. The Tomato+ splenic B-1a cells were larger in size (Figure 1D–E) and had lower surface IgD expression (Figure 1F) relative to Tomato splenic B-1a cells. Moreover, the frequency of cells spontaneously secreting IgM was much higher in sorted Tomato+ B-1a cells when compared to Tomato B-1a cells (Figure 1G). Based on these findings, we considered the possibility that the Ighg3T2A-Cre:TdTomato mouse marks a subset of activated B-1a cells and that activation of these cells correlates with induction of the Ighg3 GLT rather than CSR to IgG3. To test this model, we stimulated splenocytes from Ighg3T2A-Cre:TdTomato mice with LPS in vitro. Induction of Tomato expression correlated with reduction of surface IgD expression and increased size, indicative of cells that have undergone activation and/or plasmablast differentiation (Figure 1—figure supplement 2G). Finally, to test the functional significance of the Cre-expressing cells in Ighg3T2A-Cre mice, we crossed Ighg3T2A-Cre mice with Rosa26STOP-flox-DTA mice to ablate any Cre-expressing cells due to forced expression of diphtheria toxin and induction of cell death. As expected, the resulting Ighg3T2A-Cre:DTA mice had a complete loss of serum IgG3 (Figure 1—figure supplement 2F), but also significantly reduced titers of serum IgM (Figure 1H), indicating that the Tomato+ activated B-1a cells marked in the Ighg3T2A-Cre:TdTomato mice are a significant source of serum IgM.

Importantly, Ighg3T2A-Cre:TdTomato and Ighg3T2A-Cre:DTA mice had no apparent defects in B cell development in the bone marrow (Figure 1—figure supplement 4A-C). Moreover, Tomato expression was restricted to both mature and likely re-circulating B-1 cells in the bone marrow (Figure 1—figure supplement 4D-E). Ighg3T2A-Cre:TdTomato and Ighg3T2A-Cre:DTA mice also had normal absolute counts of follicular, marginal zone, B-1a, and B-1b cells in the spleen and peritoneal cavity (Figure 1—figure supplement 5A,B,E). Intriguingly, a significant fraction of Tomato+CD19+ cells in the spleens of Ighg3T2A-Cre:TdTomato mice lack IgM expression (Figure 1B, Figure 1—figure supplement 5D). However, the majority of these cells express the B-1 marker CD43 and likely represent another subset of spontaneously secreting B-1 cells recently described by Savage et. al. (Figure 1—figure supplement 5D) (Savage et al., 2017).

Thus, while the Ighg3T2A-Cre:TdTomato mouse did not function as we originally intended, our results indicate that the mouse can be used as a tool to track an activated, antibody-secreting subset of B-1a cells. This serendipitous outcome enabled us to study the signals that regulate B-1a cell activation in vivo.

B-1a cells have a history of B cell receptor-mediated activation

B-1a cells are known to spontaneously secrete IgM, but the contribution of BCR-mediated antigenic stimulation to steady-state B-1a antibody secretion is not well understood. Because we determined that the Ighg3T2A-Cre:TdTomato mouse marks a subset of activated B-1a cells with enhanced ‘spontaneous’ IgM secretion, we next sought to determine the contribution of BCR signaling to Tomato expression. In agreement with recent studies, we found that B-1a cells express high levels of Nur77, a gene whose expression is tightly linked to BCR-mediated signaling (Figure 2A). Interestingly, we found that splenic B-1a cells express even higher levels of Nur77 than peritoneal cavity B-1a cells (Figure 2A), consistent with our findings and previous studies showing that splenic, but not peritoneal cavity, B-1a cells secrete IgM when cultured (Figure 1G), and that the spleen is the site where B-1a cells are initially activated (Wardemann et al., 2002). We therefore focused our analysis on splenic B-1a cells.

Figure 2. B-1a cells have a history of B cell receptor-mediated activation.

Figure 2.

(A) Representative flow cytometry histogram (left) and quantification of mean fluorescence intensity (right) of GFP expression on splenic (SB-1a) (black) and peritoneal cavity (PB-1a) (blue) B-1a cells (CD19+CD23CD43+CD5+) in 3 wk old Nur77-GFP reporter mice (filled histogram, closed circles) or reporter-negative mice as controls (FMO Ctrl) (unfilled histogram, open circles). (B) Representative flow cytometry plots (left) and quantification (right) of the percentage of Tomato and Tomato+ splenic B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice stained with fluorescein-labeled phosphatidylcholine liposomes. (C) Schematic showing the generation of hIgG1 recombinant monoclonal antibodies (mAb) from single-cell sorted Tomato or Tomato+ splenic B-1a cells (SB-1a) from 6wk old Ighg3T2A-Cre:TdTomato mice. There are two source files associated with this figure with a comprehensive description of all of the mAbs generated. (D) The percentage VH11-2/VK14 gene usage in monoclonal antibodies (mAbs) generated from Tomato (black) and Tomato+ (red) splenic B-1a (SB-1a) cells from 6 wk old Ighg3T2A-Cre:TdTomato mice, as described in (C); Tom+ mAb n= 48; Tom mAb n= 37. (E) Representative flow cyometry plots (left) and quantification (right) of pregated SYBR+ fecal bacteria bound by recombinant hIgG1 monoclonal antibodies generated as described in (C); PtC-reactive VH11-2/VK14 expressing mAb’s were excluded from this analysis; Tom+ mAb n= 32; Tom mAb n= 23. (F) Representative flow cytometry plot of IgM versus Tomato expression in pre-gated CD19+ D0 liver cells or (G) CD19+ D4 spleen cells from Ighg3T2A-Cre:TdTomato mice; representative flow cytometry histogram of CD5 expression on pre-gated CD19+IgM+Tomato+ D4 spleen cells (red, unfilled) compared to CD19+IgM+CD23+CD43CD5 B2 cells (gray, filled) (G, right). (H) Quantification of percentage Tomato expression in B-1a cells from the spleens (SB-1a) of D4, D10, 2 wk, and 6 wk old Ighg3T2A-Cre:TdTomato mice by flow cytometry. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test (B, E) or one-way ANOVA (A)). Each data point represents an individual mouse (A,B,H) or monoclonal antibody (E). Data are representative of at least three independent experiments (A-B, E-H).

Figure 2—source data 1. Summary of monoclonal antibodies generated from Tomato spleen B-1a cells.
The variable heavy chain gene (VH gene), joining heavy chain gene (JH), heavy chain CDR3 peptide sequence, variable kappa chain gene (VH gene), joining kappa chain gene (JH gene), and kappa chain CDR3 peptide sequence for monoclonal antibodies generated from single-cell sorted Tomato splenic B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice (n = 38).
DOI: 10.7554/eLife.47015.009
Figure 2—source data 2. Summary of monoclonal antibodies generated from Tomato+ spleen B-1a cells.
The variable heavy chain gene (VH gene), joining heavy chain gene (JH), heavy chain CDR3 peptide sequence, variable kappa chain gene (VH gene), joining kappa chain gene (JH gene), and kappa chain CDR3 peptide sequence for monoclonal antibodies generated from single-cell sorted Tomato+ splenic B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice (n = 48).
DOI: 10.7554/eLife.47015.010

To explore more directly whether B-1a activation and antibody secretion are mediated by BCR signaling, we probed the BCR specificities of splenic Tomato+ B-1a cells to determine whether certain specificities were enriched relative to Tomato B-1a cells. Using fluorescently labeled PtC-coated liposomes to quantify PtC-reactive B-1a cells by flow cytometry, we observed a higher frequency of PtC-reactivity within Tomato+ B-1a cells versus Tomato cells (Figure 2B). We also cloned the immunoglobulin light (IgL) and heavy (IgH) chain genes from individual Tomato+ and Tomato splenic IgM+ B-1a cells from adult mice and generated recombinant monoclonal antibodies (mAbs) using a hIgG1 scaffold (Tiller et al., 2009) (Figure 2C). Consistent with the higher frequency of PtC-reactive Tomato+ splenic B-1a cells measured by flow cytometry, the canonical VH11-2/VK14 heavy and light chain paired genes that encode PtC-reactive BCRs were enriched in mAbs generated from Tomato+ B-1a cells in comparison to mAbs generated from Tomato B-1a cells (Figure 2D).

We also examined the reactivity of mAbs generated from Tomato+ and Tomato B-1a cells with the microbiota. We excluded the PtC-reactive antibodies from this analysis to ensure that any observed skewing was not due to this specificity. Binding of each mAb to fecal microbiota was measured by flow cytometry, using an assay we have previously described (Koch et al., 2016). Briefly, after incubating with individual hIgG1 mAbs, fecal contents are stained with the DNA-binding dye SYBR to differentiate bacteria (SYBR+) from other components present in the feces such as food (SYBR). Remarkably, mAbs generated from Tomato+ B-1a cells were significantly more reactive (Figure 2E). While this assay cannot track specific epitopes, the data indicate that the BCRs of Tomato+ cells are enriched for specificities against the microbiota.

Altogether, the increased frequency of BCR specificities for common B-1a antigens like PtC and the microbiota in the activated, antibody-secreting Tomato+ pool of splenic B-1a cells indicates that antigen-specific BCR signaling, as opposed to antigen-independent polyclonal expansion, mediates the activation and function of at least certain B-1a cells at steady state. In further support of this conclusion, we did not detect Tomato expression in D0 neonatal liver IgM+CD19+ B cells (Figure 2F); instead, Tomato+ cells first appeared at about 4 days of age in splenic CD5+ B-1a cells (Figure 2G) and increased in frequency during the first few weeks of life (Figure 2H). Thus, Tomato expression correlates with the acquisition of a microbiota and migration of B-1a cells from the neonatal liver to distal sites such as the spleen, where they likely first encounter antigen.

Colonization with a microbiota is required for the production of B-1 derived microbiota-reactive IgM

We next sought to determine the extent to which self antigens versus microbial antigens impact B-1a responses. A recent study reported no significant difference in B-1a immunoglobulin heavy chain repertoire between adult GF and SPF mice, favoring a model whereby microbiota-reactive serum IgM present in healthy SPF mice arises from antibodies selected on self antigens that are cross-reactive to microbial antigens present on constituents of the microbiota (e.g. PtC) (Yang et al., 2015). However, our results described in the previous section raise the possibility that other microbiota-derived epitopes can trigger antibody production by B-1a cells with distinct specificities.

Before investigating the importance of various antigens for driving the expansion and/or secretion of microbiota-reactive B-1a cells, we first determined what fraction of the microbiota-reactive IgM is derived from B-1 cells by generating Ig allotype disparate chimeric mice. In this system IgHb peritoneal cavity B-1 cells are transferred into neonatal mice of the IgHa allotype that are treated with anti-IgMa for the first 6 weeks of life. This treatment depletes the host IgHa B cells but not the transferred IgMb B-1 cells. The anti-IgMa treatment is stopped at 6 weeks of age, at which point endogenous B-1 cells are no longer generated, since they are of fetal and neonatal origin (Lalor et al., 1989b). However, bone marrow-derived IgHa cells are able to reconstitute the B-2 cell compartment, allowing one to determine the cellular origin of antibodies using Ig allotype specific antibodies (Figure 3A). Consistent with previous studies validating the B-1 chimera experimental model (Lalor et al., 1989a; Savage et al., 2017; Baumgarth et al., 1999), we found that the majority of serum IgM in adult B-1 chimeras was B-1 derived. This was determined by the almost complete absence of endogenous B-2 derived serum IgMa (also serving as a control for efficient endogenous B-1 cell depletion) (Figure 3B). Moreover, in adult B-1 chimeric mice essentially all microbiota-reactive IgM was derived from IgMb B-1 cells, comparable to the levels of microbiota-reactive IgM in WT mice (Figure 3C,E). Thus, B-1 cells are the main producers of microbiota-reactive IgM.

Figure 3. Colonization of a microbiota is required for B-1 derived microbiota-reactive IgM.

Figure 3.

(A) Schematic showing the generation of B-1 disparate allotype chimera mice. (B) Serum titers of B-2-derived IgMa and B-1-derived IgMb in 14 wk old B-1 chimeras, as described in (A). (C) Representative flow cytometry plot (left) and quantification (right) of percentage of SYBR+ fecal bacteria bound by B-1-derived serum IgMb and B-2-derived serum IgMa from 14 wk old B-1 chimeras, as described in (A); μMT-/- mouse serum included as a negative control (orange). (D) Representative SYBR staining of germ-free (GF) (left) or SPF μMT-/- (middle) feces, as measured by flow cytometry. Representative flow cytometry histogram plot showing IgM staining of SYBR+μMT-/- fecal bacteria with serum from 7 wk old SPF (black line, no fill) or germ free (GF) mice (gray line, filled) (right). (E) Quantification of percentage of SYBR+μMT-/- fecal bacteria bound by serum IgM from seven wk old SPF (black), GF (gray), or μMT-/- control (orange) mice (right). (F) Serum titers of IgM in 7 wk old SPF (black) or GF (gray) mice, as measured by ELISA. (G-H) Percentage fluorescein-labeled PtC-liposome positive (PtC+) B-1a cells (CD19+CD23CD43+CD5+) in the (G) peritoneal cavity (PerC) and (H) spleen of 7 wk old SPF (black) or GF (gray) mice, as measured by flow cytometry. Each data point represents an individual mouse (B-C, E-H). Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Data are representative of at least three independent experiments (B-H).

Next we asked whether colonization with a microbiota is necessary for B-1a cells to produce microbiota-reactive IgM. Staining of fecal bacteria from µMT-/- mice with sera from SPF or GF mice revealed that GF mice produce significantly reduced titers of microbiota-reactive IgM (Figure 3D–E), despite normal serum IgM titers (Figure 3F). In contrast, the frequency of PtC-reactive B-1a cells in the peritoneal cavity and spleen was similar in SPF and GF mice (Figure 3G–H), consistent with previous reports (Hooijkaas et al., 1984; Bos et al., 1989; Haury et al., 1997). These data suggest that steady state microbiota-reactive IgM cannot merely be explained by the cross-reactivity of antibodies produced by B-1a cells in response to self-antigens; instead, microbiota-reactive antibody production by B-1a cells is dependent on microbial colonization. Importantly, these results also demonstrate different requirements for the production of microbiota-reactive versus PtC-reactive IgM.

Loss of Toll-like receptor signaling results in reduced B-1a responses to both phosphatidylocholine and the microbiota

Our results thus far provide evidence that B-1a cells require BCR signaling for their selection and activation, yet previous work from numerous groups have suggested that B-1a cells are non-responsive to BCR cross-linking and instead respond in a non-clonal fashion to TLR ligands (Ha et al., 2006; Genestier et al., 2007). Indeed, TLR ligands induce B-1a cell proliferation, plasma cell differentiation, and CSR in vitro, whereas IgM crosslinking induces apoptosis (Morris and Rothstein, 1993; Bikah et al., 1996; Ochi and Watanabe, 2000). Moreover, with the use of TLR reporter mice generated in our lab (Price et al., 2018; Roberts et al., 2017), we determined that B-1a cells express significantly higher levels of TLR2, TLR4, TLR7, and TLR9 than B-2 cells (Figure 4—figure supplement 1). Whether TLRs are required for B-1a function in vivo and how TLR signaling may integrate with BCR signaling to control B-1a activation are unanswered questions.

We used mice deficient in TLR signaling to assess the contributions of TLRs to B-1a function. Specifically, we analyzed Tlr2-/-Tlr4-/-Unc93b13d/3d mice, which lack TLR2 and TLR4 and have a mutation in Unc93b1, which renders all remaining TLRs non-functional. Unlike Myd88-/-Trif-/- mice, Tlr2-/-Tlr4-/-Unc93b13d/3d mice have functional IL-1 receptor family signaling and do not suffer from intestinal barrier defects which may complicate analysis (Sivick et al., 2014). Additionally, Tlr2-/-Tlr4-/-Unc93b13d/3d mice allow us to dissect the contribution of subsets of TLRs on B-1a antibody production (i.e. Tlr2-/-Tlr4-/- vs. Unc93b13d/3d). Tlr2-/-Tlr4-/-Unc93b13d/3d mice had the same frequency of B-1a cells in the peritoneal cavity (Figure 4A) and the spleen (Figure 4B), suggesting that TLR signaling is not required for general B-1a cell development. Tlr2-/-Tlr4-/-Unc93b13d/3d mice had and comparable IgM titers to WT mice (Figure 4C), suggesting that TLR signaling is not reguired for general B-1a antibody secretion, although we noted a slight reduction that was not statistically significant. However, we observed a significant reduction in microbiota-reactive IgM in Tlr2-/-Tlr4-/-Unc93b13d/3d mice (Figure 4D), and a marked reduction in the frequency of PtC-reactive B-1a cells in both the peritoneal cavity and spleen (Figure 4E–G). Importantly, these TLR-dependent B-1a responses were also observed in WT and Tlr2-/-Tlr4-/-Unc93b13d/3d mice after co-housing, showing that the significant reduction in PtC- and microbiota- reactive B-1a responses in Tlr2-/-Tlr4-/-Unc93b13d/3d mice are not due to differences in the microbiota between separately housed strains of mice (Figure 4—figure supplement 2). When considered together with our earlier results, these data indicate that TLR and BCR signaling are both required for activation of distinct subsets of B-1a cells. Not all B-1a cells are subject to this dual requirement, though, as total frequencies of B-1a cells and total serum IgM titers appeared normal in Tlr2-/-Tlr4-/-Unc93b13d/3d mice.

Figure 4. Loss of Toll-like receptor signaling results in reduced B-1a responses to both phosphatidylcholine and the microbiota.

(A) Frequency of live B-1a cells in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice in the peritoneal cavity (PerC) and (B) spleen, as measured by flow cytometry. B-1a cells defined as CD19+CD23CD43+CD5+. (C) Serum IgM titers in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice, as measured by ELISA. (D) Percentage of SYBR+μMT-/- fecal bacteria bound by serum IgM from WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice, as measured by flow cytometry. (E) Representative flow cytometry plot and quantification (F-G) of percentage of B-1a cells in the (F) peritoneal cavity (PerC) and (G) spleen bound by fluorescein-labeled phosphatidylcholine liposomes in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice. (H) Schematic showing adoptive transfer of CD19+ pooled bone marrow and spleen cells (B cells) from either C57BL/6 (WT) (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) into B cell deficient μMT-/- recipeint mice at 2 days of age and sacrificed at 10 weeks of age. (I-J) Frequency of live B-1a cells in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) B cell recipient mice in the (J) peritoneal cavity (PerC) and (J) spleen, as measured by flow cytometry. (K) Serum IgM titers in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) B cell recipient mice, as measured by ELISA. (L) Percentage of SYBR+ fecal bacteria bound by serum IgM from WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) B cell recipient mice, as measured by flow cytometry. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Each data point represents an individual mouse. Data are pooled from at least three independent experiments (A-G; I-L).

Figure 4.

Figure 4—figure supplement 1. TLR expression on B cell subsets using TLR reporter mice.

Figure 4—figure supplement 1.

(A–E) Expression of TLR2, TLR4, TLR5, TLR7, and TLR9 on peritoneal cavity B-2 cells (CD19+CD23+) and B-1a cells (CD19+CD23CD43+CD5+) using Tlr2IRES-GFP, Tlr4IRES-YFP, Tlr5IRES-TdTomato, Tlr7IRES-TdTomato, Tlr9IRES-GFP reporter mice, respectively, or C57BL/6 mice as controls. Each data point represents an individual mouse. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Data are representative of at least two experiments.
Figure 4—figure supplement 2. Loss of Toll-like receptor signaling results in reduced B-1a responses to both phosphatidylcholine and the microbiota in co-housed mice.

Figure 4—figure supplement 2.

WT (black) and Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice were cohoused for 4 weeks post weaning to normalize microbiota between mice. (A-B) Percentage of B-1a cells bound by fluorescein-labeled phosphatidylcholine liposomes (PtC+) in the (A) peritoneal cavity (PerC) and (B) spleen in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice, as measured by flow cytometry. B-1a cells defined as CD19+CD23CD43+CD5+. (C) Serum IgM titers in 7 wk old WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice, as measured by ELISA. (D) Percentage of SYBR+ fecal bacteria bound by serum IgM from WT (black) or Tlr2-/-Tlr4-/-Unc93b13d/3d (blue) mice, as measured by flow cytometry. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (unpaired two-tailed Student's t-test). Each data point represents an individual mouse. Data are pooled from four independent experiments.

In order to determine whether the requirement for TLRs was B-cell intrinsic, we performed adoptive transfers of B cells from WT or Tlr2-/-Tlr4-/-Unc93b13d/3d mice into B-cell deficient µMT-/- neonates and measured serum IgM responses 10 weeks post transfer (Figure 4H). Despite comparable frequencies of donor CD19+ cells in the PerC and spleen of adult recipient mice (Figure 4I–J), we observed significantly lower total serum IgM titers (Figure 4K) and a concomitant decrease in microbiota reactivity (Figure 4L) in mice adoptively transferred with Tlr2-/-Tlr4-/-Unc93b13d/3d B cells. Of note, we did not see this same reduction in serum IgM titers in global Tlr2-/-Tlr4-/-Unc93b13d/3d mice (Figure 4C). It is therefore possible that the apparently normal serum IgM titers that we observe in global Tlr2-/-Tlr4-/-Unc93b13d/3d mice is caused by a compensatory increase in serum IgM due to TLR deficiency in additional cells types. Altogether, these data show that B-cell cell intrinsic TLR signaling is required for both antibody secretion as well as microbiota reactivity.

TLR2 and TLR4 regulate microbiota-reactive B1a responses, whereas Unc93b1-dependent TLRs regulate anti-PtC reactivities

To further investigate how TLRs control activation of microbiota-reactive and PtC-reactive B-1a cells, we examined mice lacking subsets of TLRs. We broadly divided TLRs into two categories: TLRs involved in recognition of pathogen associated molecular patterns (PAMPs) on the surface of microbes (TLR2 and TLR4) and TLRs that localize to endosomes and recognize self nucleic acids and PAMPs within microbes (TLR3, TLR7, TLR9, TLR11, TLR12, and TLR13). All TLRs in the latter category require Unc93B1 to function, enabling us to use Unc93b13d/3d mice to study the importance of these TLRs. Note that TLR5 is also Unc93B1-dependent but is not expressed on B cells (Figure 4—figure supplement 1). Both Tlr2-/-Tlr4-/- and Unc93b13d/3d mice had normal frequencies of B-1a cells in the peritoneal cavity (Figure 5A) and spleen (Figure 5B) as well as normal serum IgM titers (Figure 5C), consistent with our previous results analyzing global TLR deficient mice (Figure 4). Strikingly, mice lacking function of specific subsets of TLRs showed differential defects in B-1a responses. Unc93b13d/3d mice had normal levels of microbiota-reactive IgM (Figure 5D) but significantly reduced frequencies of PtC-reactive B-1a cells in both the peritoneal cavity (Figure 5E) and the spleen (Figure 5F). In contrast, Tlr2-/-Tlr4-/- mice had a significant reduction in microbiota-reactive IgM (Figure 5D) but only slightly reduced frequencies of PtC-reactive B-1a cells (Figure 5E–F). Furthermore, IgM ELISpot analysis of PtC-reactive splenic B-1a cells from WT, Tlr2-/-Tlr4-/-, and Unc93b13d/3d mice revealed that Unc93B1-dependent TLRs, but not TLR2 and TLR4, are required for optimal secretion of PtC-reactive IgM (Figure 5G).

Figure 5. TLR2 and TLR4 regulate B-1a responses to the microbiota, whereas Unc93B1-dependent TLRs regulate phosphatidylcholine-reactive B-1a responses.

Figure 5.

(A–B) Frequency of live B-1a cells in 7 wk old WT (black), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice in the (A) peritoneal cavity (PerC) and (B) spleen, as measured by flow cytometry. (C) Serum IgM titers in 7 wk old WT (black), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice, as measured by ELISA. (D) Percentage of SYBR+μMT-/- fecal bacteria bound by serum IgM from 7 wk old WT (black), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice, as measured by flow cytometry. (E-F) Percentage fluorescein-labeled phosphatidylcholine-liposome positive (PtC+) (E) peritoneal cavity (PerC) B-1a and (F) spleen (Spl) B-1a cells in 7 wk old WT (black), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice, as measured by flow cytometry. (G) Quantification of the mean spot size of IgM secreted by sorted PtC– (left) or PtC+ (right) splenic B-1a cells from WT (black), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice after 20 hr in culture, as measured by ELISpot. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (One-way ANOVA). Each data point represents an individual mouse. Data are pooled from at least three independent experiments (A-G).

Because there are currently no tools to track microbiota-reactive B-1a cells in vivo, we were unable to directly correlate the reduction in microbiota-reactive serum IgM in mice lacking TLR2 and TLR4 with changes in the B-1a repertoire. Therefore, in order to investigate the role of specific subsets of TLRs in regulating the B-1a repertoire more directly, we sorted B-1a cells from the spleen and peritoneal cavity of WT, Tlr2-/-Tlr4-/-Unc93b13d/3d, Unc93b13d/3d, and Tlr2-/-Tlr4-/- mice (Figure 6A), and performed bulk RNA immunoglobulin heavy chain sequencing. Overall, the VH gene usage in WT, Tlr2-/-Tlr4-/-Unc93b13d/3d, Unc93b13d/3d, and Tlr2-/-Tlr4-/- mice was almost indistinguishable (Figure 6—figure supplement 1). However, we did observe a significant reduction in the frequency of VH9-3 and VH3-6 gene usage in B-1a samples from mice lacking TLR2 and TLR4 that was not present in mice lacking only Unc93B1 (Figure 6B–C). Intriguingly, we had previously generated three monoclonal antibodies from splenic B-1a cells expressing VH3-6, two of which were reactive against the microbiota by mFLOW, further supporting the link between TLR2/4 and microbiota-reactivity (Figure 6D). These data suggest that the observed reduction in microbiota-reactive serum IgM in Tlr2-/-Tlr4-/- mice by mFLOW (Figure 5D) is at least in part due to the selective reduction of certain specificities from the B-1a repertoire at steady state.

Figure 6. B-1a immunoglobulin repertoire analysis reveals unique regulation of a subset of heavy chain genes by distinct subsets of TLRs.

(A) Representative flow cytometry gating strategy for sorting IgM+IgDloCD43+CD5+B-1a cells (pregated as CD19+/DAPI) in the peritoneal cavity (PerC) (left) and spleen (right). Prior to sorting, splenocytes were depleted of CD3+CD4+CD8+F4/80+NK1.1+GR-1+ cells using biotinylated antibodies and streptavidin magnetic beads. (B-C) The percentage of heavy chain CDR3 nucleotide sequencing reads expressing the germline (B) VH9-3 allele or the (C) VH3-6 allele in peritoneal cavity (PerC) (left) and spleen (right) B-1a samples (% usage). (D) Percentage of pre-gated SYBR+ fecal bacteria bound by two individual recombinant hIgG1 monoclonal antibodies (#1 and #2) expressing the germline VH3-6 allele generated from splenic B-1a cells from 6 wk old mice, described in Figure 2C, as measured by flow cytometry. (E) The percentage of heavy chain CDR3 nucleotide sequencing reads expressing the germline VH11-2 allele in peritoneal cavity (PerC) (left) and spleen (right) B-1a samples (% usage). (F) The combined normalized read counts of PtC-binding CDR3 peptide sequences (MRYSNYWYFDV, MRYGSSYWYFDV, and MRYGNYWYFDV) in peritoneal cavity (PerC) (left) and spleen (right) B-1a samples. Black circles represent WT mice, blue circles represent Tlr2-/-Tlr4-/-Unc93b13d/3d mice, green circles represent Unc93b13d/3d mice, and pink circles represent Tlr2-/-Tlr4-/- mice (B, C, E, F). CDR3 frequencies were artificially scaled to 10 million reads to account for differences in read depth among samples (F). Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (One-way ANOVA). Each data point represents an individual mouse (B, C, E, F). Data representative of 3 independent experiments (D). There are three source files associated with this figure.

Figure 6—source data 1. Top 10 highly recurring CDR3 sequences (peptide and V(D)J recombination) detected in peritoneal cavity B-1a samples from age-matched mice lacking different subsets of TLRs.
The CDR3 peptide sequence, variable heavy chain gene, joining heavy chain gene, total read counts (copy), normalized read counts (norm.copy), and the sum of normalized counts of PtC-binding CDR3 peptide sequences in peritoneal cavity (PerC) B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. PtC-binding CDR3 peptide sequences include MRYSNYWYFDV (highlighted in blue), MRYGSSYWYFDV (highlighted in orange), and MRYGNYWYFDV (highlighted in purple). CDR3 sequences in italic font denotes that they did not appear in the top 10 CDR3 sequences for that sample, but were included to be able to determine the sum of PtC-binding CDR3 sequencing reads. Sequencing reads were normalized by artificially scaling to 10 million reads to account for differences in read depth among samples. There are three biological replicates for each genotype in one experiment.
DOI: 10.7554/eLife.47015.019
Figure 6—source data 2. Top 10 highly recurring CDR3 sequences (peptide and V(D)J recombination) detected in spleen B-1a samples from age-matched mice lacking different subsets of TLRs.
The CDR3 peptide sequence, variable heavy chain gene, joining heavy chain gene, total read counts (copy), normalized read counts (norm.copy), and the sum of normalized counts of PtC-binding CDR3 peptide sequences in spleen (Spl) B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. PtC-binding CDR3 peptide sequences include MRYSNYWYFDV (highlighted in blue), MRYGSSYWYFDV (highlighted in orange), and MRYGNYWYFDV (highlighted in purple). CDR3 sequences in italic font denotes that they did not appear in the top 10 CDR3 sequences for that sample, but were included to be able to determine the sum of PtC-binding CDR3 sequencing reads. Sequencing reads were normalized by artificially scaling to 10 million reads to account for differences in read depth among samples. There are three biological replicates for each genotype in one experiment.
DOI: 10.7554/eLife.47015.020
Figure 6—source data 3. Variable heavy chain gene usage summary in spleen and peritoneal cavity B-1a cells in mice lacking different subsets of TLRs.
Table summarizing the variable heavy chain gene usage frequency in peritoneal cavity and spleen B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. There are three biological replicates for each genotype in one experiment.
DOI: 10.7554/eLife.47015.021

Figure 6.

Figure 6—figure supplement 1. VH gene-usage distribution in splenic and peritoneal cavity B-1a samples.

Figure 6—figure supplement 1.

(A–B) The percentage of heavy chain CDR3 nucleotide sequencing reads expressing different germline V-alleles in (A) peritoneal cavity (PerC) and (B) spleen B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), or Unc93b13d/3d (green) mice. Each data point represents an individual mouse. Error bars indicate the mean (± SEM). *p<0.05, **p<0.01, and ***p<0.001 (One-way ANOVA). Asterisks denote a statistical difference in a unique Ig VH gene between at least two different genotypes.
Figure 6—figure supplement 2. There is considerable variation in B-1a IgH CDR3 repertoire between different mice, independent of TLR signaling.

Figure 6—figure supplement 2.

(A–B) CDR3 peptide pair-wise sharing analysis of IgH repertoire similarity between (A) peritoneal cavity (PerC) and (B) spleen B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/- (pink), Unc93b13d/3d (green), or TLR KO (blue) mice. CDR3 peptide pair-wise analysis was conducted between WT mice (WT/WT), Tlr2-/-Tlr4-/- mice (Tlr2-/-Tlr4-/-/Tlr2-/-Tlr4-/-), Unc93b13d/3d mice (Unc93b13d/3d/Unc93b13d/3d), TLR KO mice (TLR KO/TLR KO) and between WT vs Tlr2-/-Tlr4-/- mice (WT/Tlr2-/-Tlr4-/-), WT vs. Unc93b13d/3d mice (WT/Unc93b13d/3d), and WT vs TLR KO mice (WT/TLR KO). TLR KO mice refers to Tlr2-/-Tlr4-/-Unc93b13d/3d mice. Each dot represents the percentage of shared CDR3 peptide sequences between two mice. A total of 3 mice per genotype were included in the analysis, yielding six pair-wise comparisons within the same genotype ((% shared CDR3 in WT1 and WT2)/(Total CDR3 sequences in WT 1), (% shared CDR3 in WT1 and WT2)/(Total CDR3 sequences in WT 2), etc.) and 18 pair-wise comparisons when comparing two different genotypes. Data are presented as percentage of total CDR3 nucleotide sequencing reads. CDR3 frequencies were artificially scaled to 10 million reads to account for differences in read depth among samples, and a CDR3 frequency of 1000 was set as the minimum cutoff for pairwise-analysis. There are three source files associated with this figure.

As expected, we observed a significant reduction in VH11-2 gene usage in Tlr2-/-Tlr4-/-Unc93b13d/3d, and Unc93b13d/3d mice (Figure 6E), but not in Tlr2-/-Tlr4-/- mice, consistent with our previous results showing an Unc93B1-dependent loss of PtC-reactive B-1a cells using PtC-liposomes (Figure 5E–F). Moreover, the total frequencies of known PtC-reactive CDR3 peptide sequences MRYSNYWYFDV, MRYGSSYWYFD, and MRYGNYWYFDV were also reduced in both peritoneal cavity and splenic B-1a samples from mice lacking Unc93B1, but not in mice lacking TLR2 and TLR4 (Figure 6F).

Altogether, these data show that distinct VH genes are differentially regulated by unique subsets of TLRs in B-1a cells—namely, that VH11-2-expressing B-1a cells require Unc93B1-dependent TLRs, whereas VH3-6 and VH9-3 expressing B-1a cells require TLR2/4. Of note, pair-wise comparisons of CDR3 peptide sequences between mice revealed considerable variation in the IgH repertoire within individual mice, independent of genotype (Figure 6—figure supplement 2). Therefore, while we were able to observe significant differences in the VH usage patterns in mice lacking subsets of TLRs, it is possible that there are additional TLR-dependent changes to the B-1a repertoire not revealed by these sequencing methods.

TLR stimulation results in downregulation of CD5 on B-1a cells

Finally, we sought a mechanism for how signaling by TLRs could be linked to activation of B-1a cells with certain specificities. To examine how TLR signaling modulates B-1a activation, we performed an in vitro stimulation of B-1a cells with various TLR ligands. Strikingly, in vitro TLR activation of B-1a cells with TLR2, TLR4, TLR7, and TLR9 agonists resulted in the reduction of surface CD5 (Figure 7A–B), a known inhibitor of BCR signaling. These results support a model in which TLR activation renders B-1a cells responsive to BCR stimulation by negatively regulating an inhibitor of BCR signaling. In work co-submitted with this manuscript, Savage and colleagues show that TLR activation of B-1a cells both in vitro and in the context of influenza infection results in the loss of surface CD5 and a concomitant increase in BCR-downstream signaling. Taken together with our previous mFLOW and PtC-liposome results, these data suggest that the specificity of the BCR determines the nature of the TLR ligand encountered by a given B-1a cell. More specifically, we propose a model whereby BCR engagement with the self antigen PtC present on dead or dying cells may facilitate Unc93B1-dependent TLR engagement by ‘self’ nucleic acids within endosomes, whereas BCR engagement with microbiota-derived antigens may coordinate with PAMP sensing by TLR2 or TLR4 to regulate responses to the microbiota (Figure 7C).

Figure 7. TLR stimulation results in CD5 downregulation on B-1a cells.

Figure 7.

(A) Representative flow cytometry histogram plot and quantification of mean fluorescence intensity of CD5 expression (B) of in vitro Pam3CSK (black), LPS- (gray), R848- (red) and CpG-B- (blue) stimulated peritoneal cavity B-1a cells at 0, 1, 2, 3, and 4 cycles of division as determined by their CFSE dilution (n = 3, technical replicates). (C) Model depicting how TLR and BCR signaling integrate to control distinct B-1a responses. Data are representative of at least three independent experiments (A-B).

Discussion

The study of B-1a biology has been hampered by a lack of tools to elucidate the signals that regulate B-1a activation and function. In this study, we generated Ighg3T2A-Cre:TdTomato mice, which serendipitously mark a subset of activated, antibody-secreting IgM+ B-1a cells, allowing us to define the signals that regulate B-1a activation in vivo. The significantly higher expression of the BCR-downstream signaling gene Nur77 in splenic versus peritoneal cavity B-1a cells combined with the enrichment of BCR reactivities to both PtC and the intestinal microbiota in the Tomato+ activated subset of splenic B-1a cells from reporter mice strongly suggests a BCR-mediated expansion process. Interestingly, we did not see Tomato expression in fetal or neonatal liver B-1a cells; rather, Tomato expression in B-1a cells correlated with their entry into the spleen or other distal sites where they likely first encounter antigen. Given the observed reduction in microbiota reactive B-1-derived serum IgM in GF mice, we hypothesize that the microbiota is one such source of antigen. Moreover, we demonstrate that TLR signaling is important for defining the B-1a repertoire and the steady state antibody secretion by B-1a cells, and implicate specific and distinct TLRs for PtC-reactive versus microbiota-reactive B1a responses. Altogether, our data suggest a model whereby dual BCR and TLR activation regulates the steady state maintenance and antibody secretion of a distinct subset of B-1a cells.

While we found that Tomato expression in Ighg3T2A-Cre:TdTomato mice correlated with GLT in the Ighg3 locus, the exact signals that modulate Tomato expression in reporter mice are still not fully understood. Moreover, why there is preferential expression of Tomato in B-1 cells over other B cell subsets is also not known. One likely explanation is that B-1 cells are the primary source of serum IgG3 (Savage et al., 2017), and therefore may preferentially receive signals that ‘poise’ B-1 cells for IgG3 CSR. Additionally, NF-κB binding sites have been identified in enhancers linked to IgG3 CSR (Michaelson et al., 1996). Accordingly, p50-/- activated B cells fail to induce Ighg3 GLT (Snapper et al., 1996). Therefore, BCR and/or TLR signaling, which both result in NF-κB activation, could mediate induction of Ighg3 GLT (Snapper et al., 1996; Cogné et al., 1994). The presence of these signals would induce Ighg3 GLT but not CSR, unless Aicda is also expressed. This mechanism is supported by evidence of BCR-mediated activation in Tomato+ B-1a cells and the ability to induce Tomato expression in Ighg3T2A-Cre:TdTomato splenocytes activated in vitro with TLR ligands. Future studies involving the re-derivation Ighg3T2A-Cre:TdTomato mice to GF status would be very interesting, since we would expect the loss of microbiota-reactive Tomato+ B-1a cells.

Our data also shed light on the role of self versus foreign antigens in shaping B-1a responses. Previous studies have shown that B-1a cell numbers and serum IgM titers are unaltered in GF mice, demonstrating that exogenous antigens are not required for ‘natural’ serum IgM. IgH sequencing studies in GF and SPF mice have shown that the mature B-1a repertoire is not significantly different in mice lacking a microbiota (Yang et al., 2015). We were therefore surprised to observe a significant reduction in microbiota-reactive serum antibodies in GF mice, despite no change in the frequency of PtC reactivity. This finding reveals that a subset of B-1a cells require a microbiota for their expansion and/or antibody secretion.

Like GF mice, we found that mice lacking TLR2 and TLR4 also had a significant reduction in serum IgM reactive against the microbiota. Taken together, these results suggest that the reduction in anti-commensal serum IgM observed in GF mice may be due to the loss of a microbiota-dependent TLR2/4 signal that drives the expansion and antibody secretion of a subset of commensal-reactive B-1a cells. Consistent with previous studies showing no significant differences in the IgH B-1a repertoire in SPF versus GF mice, the VH usage patterns in Tlr2-/-Tlr4-/- mice are almost indistinguishable from WT mice. We did, however, find a significant reduction in VH3-6 and VH9-3 gene usage in B-1a cells from mice lacking TLR2 and TLR4. Moreover, monoclonal antibodies generated from WT splenic B-1a cells expressing VH3-6 germline alleles are reactive against the microbiota, suggesting that commensal bacteria may result in the selective expansion and antibody secretion of a subset of B-1a cells through dual BCR and TLR2/4 stimulation. This model is further supported by our results showing the selective reduction in steady state generation of and antibody secretion by PtC-reactive, VH11-2-expressing B-1a cells in mice lacking Unc93B1-dependent TLRs. In this context, BCR engagement with PtC present on dead or dying cells may provide an environment where exposed nucleic acids can be sensed by Unc93B1-dependent TLRs within endosomes. The development of new tools capable of specifically tracking commensal-reactive B cells or the generation of monoclonal antibodies from GF or Tlr2-/-Tlr4-/- mice B-1a cells will be important to further elucidate the contribution of a microbiota to the development and/or expansion of commensal-reactive B-1a cells.

Of note, we were surprised that TLR-deficient mice did not have significantly altered serum IgM titers and B-1a frequencies despite a significant reduction in anti-microbiota and PtC reactivity. However, adoptive transfer of TLR-deficient B cells into B-cell deficient mice resulted in ~2–4 fold reduction in total serum IgM titers when compared to mice adoptively transferred with WT B cells, suggesting that a significant source of serum IgM is indeed mediated through TLR activation of B-1 cells. Of note, as evidenced by the incomplete abrogation of serum IgM, microbiota- and PtC- reactive B-1a responses, and otherwise very similar B-1a IgH BCR repertoire in TLR-deficient mice when compared to WT counterparts, other signals, such as cytokines, also likely play a role in regulating TLR-independent B-1a derived antibody responses at steady state. Previous studies have identified IL-5, IL-10, and IFN-γ as important regulators of B-1 responses (Nisitani et al., 1995; Waffarn et al., 2015). These mechanisms may even compensate for the absence of TLR signaling, resulting in apparently normal total IgM titers and B-1a frequency, despite differences in the B-1a repertoire and specificities of B-1a derived serum IgM.

The presence of a B cell subset that produces self-reactive antibodies contradicts the paradigm that self-reactive clones are deleted in B cell development to avoid autoimmunity. However, B-1a-derived serum IgM likely evolved as an important first line of defense important for both tissue and intestinal homeostasis. Our finding that microbial sensing TLRs regulate anti-microbiota responses, whereas nucleic acid sensing TLRs regulate responses to PtC present on dead or dying cells where DNA or RNA may be sensed, strongly supports a model wherein TLR signaling integrates with BCR signaling to control B-1a responses at steady state. The balance between protective and harmful B-1a responses is likely achieved, in part, through the integration of these two signals. These results could be especially relevant to autoimmune disease where several studies have linked disease severity with hyper-responsive nucleic acid-sensing TLR responses and increased autoantibody production (Leadbetter et al., 2002; Lau et al., 2005; Fukui et al., 2009; Subramanian et al., 2006; Pisitkun et al., 2006).

Our in vitro results showing that TLR activation of B-1a cells results in downregulation of the BCR inhibitory protein CD5, provide a possible mechanism for how TLRs may render B-1a cells responsive to BCR-mediated activation. Supporting our model of coordinated integration of TLR/BCR signaling in regulating B-1a responses at steady state, Savage et al. (in an accompanying manuscript) found that B-intrinsic TLR signaling is also critical for the differentiation of B-1a cells into antibody secreting cells in the context of influenza infection. Moreover, Savage et al. reveal through biochemical analysis that TLR activation of B-1a cells results in both reduced expression of CD5 and reduced association of CD5 with the IgM-BCR complex, which correlates with an increase in BCR downstream signaling. These results raise important questions regarding the precise molecular mechanism of how TLR and BCR signaling coordinate to control B-1a responses in vivo. Of particular interest is the relative timing of TLR versus BCR signaling on B-1a cells. It is possible that TLR signaling precedes the subsequent ability of B-1a cells to respond to BCR-mediated activation by inducing downregulation of CD5. It is not clear, however, how this mechanism explains our finding that certain B-1a BCR specificities are linked with subsets of TLRs. One possible explanation is that TLR ligands are not present at sufficiently high levels in vivo, so BCR-mediated acquisition of TLR ligands may be required for efficient TLR activation and conversion of B-1a cells into antibody-secreting CD5‘ex-B-1a’ B-1b cells. In vitro stimulation with high concentrations of TLR ligands may bypass this requirement. Future studies using conjugates of antigens and TLR ligands could enable a more precise delineation of the sequence of events leading to B-1a proliferation and antibody secretion.

Materials and methods

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 6. Data files associated with RNA sequencing experiments of B-1a cells have been deposited on Dryad (doi:10.5061/dryad.660js04).

Mice

C57BL/6, µMT-/- (002288), Nur77GFP (016617), Rosa26STOP-flox-TdTomato (007905), Rosa26STOP-flox-DTA (009669), β-actinFippase (005703) were obtained from The Jackson Laboratories. Ighg3T2A-Cre mice were generated by constructing a targeting vector encoding the self-cleaving peptide T2A followed by the Cre recombinase gene to be inserted immediately 3’ of the last Ighg3 transmembrane exon. This vector was electroporated into C57BL/6-derived embryonic stem cells by the Mouse Biology Program at UC Davis. The vector also introduced a frt-flanked neomycin resistance gene. Targeting was assessed by Southern blot and correctly targeted ES cells were injected into ICR/CD1 blastocysts. Chimeric males were mated with C57BL/6 background β-actinFippase females to remove the neomycin resistance cassette. Mice were then crossed to either Rosa26STOP-flox-TdTomato to permanently mark Cre+ cells with TdTomato or to Rosa26STOP-flox-DTA to ablate Cre+ cells. Tlr2-/- and Tlr4-/- mice were generated and provided by S. Akira (Osaka University) (Takeuchi et al., 1999; Hoshino et al., 1999). Unc93b13d/3d were purchased from MMRCC (Tabeta et al., 2006). All mice were bred and maintained in specific pathogen-free conditions at UC Berkeley. Germ-free C57BL/6 mice were maintained at the UC Berkeley Germ-Free Facility. Experiments were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocol (#2017-03-9679) of the University of California, Berkeley and IACUC protocol (#18797) of the University of California, Davis.

For co-housing experiments, at the time of weaning (3 weeks of age) mice were co-housed for at least 4 weeks prior to sacrifice to normalize their microbiota.

Cell lines

HEK293T cells were obtained from American Type Culture Collection (ATCC CRL-11268, Manassas, VA). Authentication of the cell line was performed by STR profiling and had a negative mycoplasma contamination testing status. Cells used in experiments were below 10 passages.

Adoptive transfer experiments

To generate neonatal B-1 cell chimeras, newborn B6.Cg IgHa Thy1a Gpi1a /J (IgHa) (Jackson, 001317) were treated with 2 mg per mouse of anti-IgMa (clone DS1.1) intraperitoneally twice weekly for 6 weeks to temporarily deplete B cells. 2–3 days after birth, pups were reconstituted with peritoneal lavage cells from C57BL/6 (IgHb), as a source of wild-type allotypically marked IgHb B-1 cells. Mice were analyzed at least 2 months after the end of anti-IgMa treatment, where B-2 cells were host derived (IgHa) and the majority of B-1 cells were derived from the donor peritoneal cavity (IgHb).

For adoptive transfer of either WT or Tlr2-/-Tlr4-/-Unc93b13d/3d B cells, CD19+ cells from the bone marrow and spleen were isolated by using biotinylated antibodies and Streptavidin conjugated to magnetic beads (MACS Miltenyi), and 5 × 106 cells were retro-orbitally transferred into 2 day old µMT-/- neonates. Mice were analyzed 10 weeks after transfer.

Cell isolation and in vitro stimulation assays

Peritoneal cavity cells were isolated by peritoneal lavage with 5 mL PBS. Bone marrow cells were isolated from a single femur and red blood cells were lysed using Ammonium-Chloride-Potassium (ACK) buffer (Gibco). Spleens were digested with collagenase 8 (Sigma) and DNAse-I for 45 min and red blood cells were lysed using Ammonium-Chloride-Potassium (ACK) buffer (Gibco). For stimulation assays, 200,000 cells were incubated in media (RPMI/10%FCS/L-glutamine/Pen-Strep/HEPES/Sodium pyruvate/βME) with LPS (25 μg/mL) in 96-well round-bottom plates for 72 hr. Flow cytometry was used to analyze stimulated cells.

Southern blotting

Murine embryonic stem cell DNA was screened for single-copy targeted insertion of T2ACre in the Ighg3 locus by digesting DNA with BglII restriction endonuclease, transferring agarose-gel run digested DNA onto a nitrocellulose membrane, and hybridizing membrane with P-32 labeled DNA probe specific for the 5’ UTR of Ighg3 (forward primer: 5’-TGAGCCAGGGTAAGTGGGAGTATG-3’; reverse primer: 5’-ATGAGGTGCAGAGTGGCTACAGG-3’) and the Neomycin resistance gene (forward primer: 5’-ACCGTAAAGCACGAGGAAGCG-3’; Reverse primer: 5’-GCACGCAGGTTCTCCGGC-3’). Southern blots were visualized with the use of a Typhoon scanner (Amersham Biosciences).

Flow Cytometry

Single-cell suspensions from the spleen and peritoneal cavity were stained with anti-CD16/32 for 20 min at 4 °C to block Fc receptors. Cells were stained with the following conjugated antibodies: anti-CD19 (eBio; clone: 1D3; BV711 or PECy7), anti-IgG3 (BD; clone R40-82; FITC), IgM (eBio; clone: 11/41; APC-780), anti-CD5 (eBio; clone: 53–7.3; APC), anti-CD43 (BD; clone: S7; PE or BV421), anti-IgD (eBio; clone: 11–26 c; PECy7), anti-CD23 (eBio; clone: B3B4; PerCP-710), anti-CD21/35 (eBio; clone: eBio8D9; APC-780), anti-IgMb (BD; clone: AF6-78; BV650), anti-Nur77 (BD; clone: 12.14; PerCP-710), anti-CD4 (BD; clone: L3T4; Biotin or FITC), anti-CD3e (eBio; clone: 145–2 C11; Biotin or FITC), anti-CD8 (Tonbo; clone: 53–6.7; Biotin or FITC), anti-NK1.1 (eBio; clone PK136; Biotin or FITC), anti-Ly6-G (eBio; clone: RB6-8C5; Biotin or FITC), anti-F4/80 (eBio; clone: BM8; Biotin or FITC), or streptavidin (eBio; conjugated to FITC). Dead cells were excluded by DAPI viability dye and near-IR fixable viability stain for experiments where cells were fixed and permeabilized. Flow cytometry was performed using an LSRFortessa (BD Biosciences) and cell sorting was performed using a FACSAria (BD Biosciences).

For intranuclear staining for Nur77, cells were surface stained for 30 min at 4 °C prior to fixation (Thermo Fisher) for 1 hr at room temperature. Cells were washed and stained with anti-Nur77 for 1 hr at room temperature.

For fluorescein-labeled PtC liposome flow cytometry, cells were co-incubated with PtC-Liposomes and surface stain for 1 hr at 4 °C. PtC-liposomes were prepared by modification of a previously described method (Mercolino et al., 1988). Briefly, liposomes were prepared by high pressure extrusion though a final filter pore size of 0.05 microns and consisted of DSPC:DSPG:Chol in a molar ratio of 45:5:50 encapsulated with fluorescein sulfonic acid (5 mM). For some experiments Oregon Green 488-DHPE Liposomes (DOPC/CHOL/OG-PE (54:45:1) were used (FormuMax, Sunnyvale, CA).

Microbiota flow cytometry (mFLOW)

For microbiota flow cytometry, a fecal pellet from a B-cell deficient µMT-/- mouse from our mouse colony was resuspended in sterile-filtered PBS and spun at 200 rcf for 5 min. Supernatant was transferred to a new sterile tube and washed 2 times with PBS by spinning at 8,000 RPM for 5 min. OD600 of suspension was measured, and bacteria was diluted in 1% bovine serum albumin (BSA; Fisher) at final OD600 of 0.01. Mouse serum was diluted 1:25 in PBS/BSA buffer, and 25 µl of this solution was added to 25 µl diluted fecal bacteria in a 96-well v-bottom plate, and incubated overnight at 4C. For hIgG1 microbiota flow, a fecal pellet from the same mouse from which recombinant hIgG1 monoclonal antibodies (mAbs) were generated was stained with 4 µg/mL hIgG1 mAbs overnight. mAbs that did not yield above 4 ug/mL antibody by ELISA were excluded from microbiota flow analysis. Staining was performed with fluorochrome conjugated anti-IgM (eBio; clone: 11/41; Biotin), anti-IgMb (BD; clone: AF6-78; BV650), anti-IgMa (BD; clone: DS-1; BV711), or goat anti-hIgG1-biotin (Jackon Immunoresearch) followed by streptavidin-PECy7 (eBio) when using biotinylated primary antibodies. Cells were washed and resuspended in SYBR Green (Invitrogen) and analyzed by FACS using an LSRFortessa (BD Biosciences). For analyses, Sybr+ events were defined as the population of Sybrhi events not present in GF mouse feces.

Recombinant hIgG1 monoclonal antibody generation

hIgG1 monoclonal antibodies were generated from single-cell sorted Tomato or Tomato+ IgM+ splenic B-1a cells (CD19+CD23CD5+CD43+IgM+) from a 6 week old Ighg3T2A-Cre:TdTomato mouse according to previously described protocol (Tiller et al., 2009). hIgG1 and hkappa expression plasmids have been previously described (Smith et al., 2009). HEK293T cells were obtained from American Type Culture Collection (ATCC, Manassas, VA). Productively rearranged paired heavy and light chain sequences were included in analysis of VH gene usage comparisons between Tomato and Tomato+ mAbs.

Single-cell RT-PCR of Ighg3 germ-line transcript (GLT)

Tomato+IgM+IgG3CD19+ cells or Tomato+IgMIgG3+CD19+ from Ighg3T2A-Cre:TdTomato LPS stimulated splenocytes were single cell sorted into 96-well plates and cDNA was synthesized as previously described (Tiller et al., 2009), with the only deviation being the use of iScript (Thermo Scientific). Single-cell semi-nested RT-PCR for Ighm mRNA, Ighg3 mRNA, and Ighg3 GLT was performed and products were run on agarose gel for visualization.

ELISA and ELISPOT Assays

Nunc Hi Affinity ELISA plates were coated with goat anti-murine IgM (500 ng/mL; Jackson Immunoresearch) or human kappa chain (1 µg/mL; MyBioSource), and blocked with PBS with 1% BSA (w/v) and 2% goat serum (Gibco; v/v). Secondary peroxidase conjugated goat antibodies to murine IgM or to human IgG (Jackson Immunoresearch) were used at 1:5000 in PBS. Purified murine IgM and human IgG1 standards were from eBioscience and Sigma, respectively. Plates were developed with 1 mg/mL OPD (Sigma) in Citrate Buffer (PBS with 0.05M NaH2PO4 and 0.02M Citric acid) with 3M HCl acid stop. Absorbance at 490 nm was measured on a SpectraMax M2.

For ELISpot analysis, multiscreen plates (Millipore) were coated with goat isotype-specific antibodies to murine IgM (5 µg/mL; Jackson Immunoresearch) in PBS and blocked with PBS with 1% BSA (w/v) and 5% goat serum (v/v). Plates were washed with PBS and cells were serially diluted in complete RPMI and incubated at 37°C overnight. Following several washes in PBS, secondary peroxidase conjugated antibodies to IgM (Jackson Immunoresearch) were used at 1:1000 in PBS to detect antibody-secreting cells. Plates were developed with AEC developing reagent (Vector Laboratories) according to manufacturer’s instructions. Plates were read on an ImmunoSpot C.T.L. Analyzer (v3.2) and quantitated using ImmunoSpot 5.1 Pro.

Immunoglobulin heavy chain CDR3 RNA sequencing and analysis

Splenocytes were depleted of CD3+CD4+CD8+NK1.1+F4/80+GR-1+ cells using biotinylated antibodies and Streptavidin conjugated to magnetic bead MACS Miltenyi magnetic bead depletion prior to sorting. CD19+IgMhiIgDloCD43+CD5+ depleted spleen and peritoneal cavity lavage cells were sorted using a FACS Aria (BD Biosciences). Sorted cells were immediately resuspended in TRIzol (Invitrogen) and snap frozen. Samples were subsequently processed using the services provided by iRepertoire Inc. Briefly, bulk RNA was extracted, heavy chain cDNA libraries were generated, and CDR3 nucleotide sequences were amplified and sequenced using paired-end MiSeq sequencing technology. Regular un-normalized or normalized CDR3 nucleotide sequencing data were analyzed. For CDR3 length and N-nucleotide addition analysis, each unique CDR3-VDJ combination was treated as a quantity of one regardless of read count, allowing us to view the repertoire independent of skewing which may occur to just one or a few highly dominant clones. Because our analysis was performed on sorted B-1a cells, excluding plasma cells, which do not express CD5, the frequency of a given Ig transcript is roughly viewed as the relative index of frequency of cells expressing this Ig transcript. Additionally, clonal expansion starting at around the time of weaning is a hallmark of self-replenishing B-1a cells. Therefore, for VH gene usage frequencies, we did not normalize the data by scoring each distinct IgH CDR3 nucleotide sequence expressing a given VH gene as one, independent of how often this sequence was detected, as is often done with bulk RNA-based Ig sequencing methods. For VH gene usage frequencies and pair-wise comparisons of percentage shared CDR3 sequences between samples, total read counts were normalized to 10 million reads to account for differences in read depth between samples. A minimum frequency cutoff of 1000 was applied to pair-wise comparison analysis.

Statistical analysis

All data are presented as mean (± SEM). Statistical analysis was done using paired or unpaired two-tailed Student’s t-test for comparisons between two groups, or one-way ANOVA for multiple comparisons. p<0.05 was considered significantly different.

Acknowledgements

We thank members of the Barton and Vance Labs for helpful discussions and critical reading of the manuscript. We thank Hector Nolla and Alma Valeros for assistance with cell sorting at the Flow Cytometry Facility of the Cancer Research Laboratory at UC Berkeley and Dr. David Rawlings for sharing hIgG1 and hkappa recombinant antibody expression plasmids. This work was supported by the NIH (AI072429 and AI063302 to GMB; T32 GM007232 and T32 AI100829 to LSMK) and by an Investigator in the Pathogenesis of Infectious Disease award to GMB from the Burroughs Wellcome Fund.

Funding Statement

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

Contributor Information

Gregory M Barton, Email: barton@berkeley.edu.

Andrew J MacPherson, University of Bern, Switzerland.

Wendy S Garrett, Harvard T.H. Chan School of Public Health, United States.

Funding Information

This paper was supported by the following grants:

  • National Institute of Allergy and Infectious Diseases AI142926 to Lieselotte SM Kreuk, Meghan A Koch, Leianna C Slayden, Nicholas A Lind, Sophia Chu, Gregory M Barton.

  • National Institute of Allergy and Infectious Diseases AI063302 to Lieselotte SM Kreuk, Meghan A Koch, Leianna C Slayden, Nicholas A Lind, Sophia Chu, Gregory M Barton.

  • National Institute of General Medical Sciences GM007232-36 to Lieselotte SM Kreuk.

  • National Institute of Allergy and Infectious Diseases AI100829 to Lieselotte SM Kreuk.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing—original draft, Project administration, Writing—review and editing.

Conceptualization, Methodology, Writing—review and editing.

Investigation, Methodology, Writing—review and editing.

Investigation, Writing—review and editing, Generated monoclonal antibodies and performed key experiments for manuscript.

Investigation, Performed key in vivo experiments for manuscript.

Resources, Investigation, Methodology, Performed key B-1 chimera experiments.

Resources, Methodology, Writing—review and editing, Provided PtC-liposome reagent and methodology for use in flow cytometry.

Conceptualization, Resources, Investigation, Writing—review and editing.

Conceptualization, Resources, Data curation, Supervision, Funding acquisition, Methodology, Writing—review and editing.

Ethics

Animal experimentation: Experiments were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocol (#2017-03-9679) of the University of California, Berkeley and IACUC protocol (#18797) of the University of California, Davis.

Additional files

Transparent reporting form
DOI: 10.7554/eLife.47015.023

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 6. Data files associated with RNA sequencing experiments of B-1a cells are available from the Dryad Digital Repository: https://dx.doi.org/10.5061/dryad.660js04.

The following dataset was generated:

Kreuk LSM, Koch MA, Slayden LC, Lind NA, Chu S, Savage HP, Kantor AB, Baumgarth N, Barton GM. 2019. Data from: B cell receptor and TLR signaling coordinate to control distinct B-1 responses to both self and the microbiota. Dryad Digital Repository.

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Decision letter

Editor: Andrew J MacPherson1

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

Thank you for sending your article entitled "B cell receptor and TLR signaling coordinate to control distinct B-1 responses to both self and the microbiota" for peer review at eLife. Your article is being evaluated by three peer reviewers, and the evaluation is being overseen by a Reviewing Editor and Wendy Garrett as the Senior Editor.

Thank you for your patience during the evaluation process. Since your paper was submitted in parallel with the manuscript "TLR-signaling induces reorganization of the IgM-BCR complex regulating B-1 cell responses to infections" from Baumgarth and colleagues, we aimed to secure two reviews of both manuscripts (Nos. 1 and 3) and to carry out the consultation in parallel.

We believe that the work addresses an extremely important problem of the coordination of B cell receptor and TLR signaling, although a major concern of reviewer 2 (who had not seen the other manuscript) was the evidence in this paper for the B cell intrinsic TLR effects. The 2 rounds of consultation came to the view that although there is no exact complementarity between the two papers in terms of antigens examined and experimental systems, a combination of cross-referencing between the papers and express caveats for the evidence on this point in your manuscript may address the issue without necessarily requiring in vivo chimeras. We do not think that further germ-free colonization experiments are in the current scope.

Reviewer #1:

In this manuscript, Barton et al. describe the serendipitous development of a B1 B cell reporter mouse and the subsequent use of this mouse (and derivations of) to interrogate the mechanisms that lead to the development of self-reactive and commensal-reactive IgM. Most notably, they identify unique contributions of nucleic acid-sensing versus bacterial-sensing TLRs to the emergence of these two antibody specificities, respectively. Overall, this is an elegant and nicely-done study that addresses long-standing issues regarding B1 cell biology and reveals a new mechanism of integration of innate and adaptive signals in B cells themselves. I only have one major experimental concern, which revolves around the data arguing for a role of TLR2/4 in commensal reactivity. It seems highly likely that gut microbiota composition (particularly the presence or absence of pathobionts like Helicobacter or others) could influence the development of commensal-specific IgM. Thus, different mouse colonies (or even lines within a facility that are bred separately) might exhibit differing levels of anti-commensal IgM based merely on differences in commensal composition.

Unless I am mistaken, it appears that the authors performed nearly all of their experiments using mice that were bred as lines rather than using littermate controls, which would be the proper standard in this case for determining the effect of a gene(s) on the observed phenotype. I am certainly sympathetic to the fact that breeding lines with multiple alleles creates a challenge here.

Nonetheless, I would have hoped that the authors would have at least co-housed the different lines to partially correct for potential effects of the microbiota, but based on the methods it seems that these lines were all bred and housed separately. There is even an outside possibility that microbiota-dependent differences could explain the seeming discrepancy between the authors' data and the recently published data by Yang showing that GF and SPF mice have equivalent B1a repertoires-that is, that the Yang experiments were done with a microbiota that failed to induce the specificities that Barton et al. discover here. I would strongly suggest that the authors perform at least a few of the critical experiments (e.g., Figure 5D and E) using littermates or (at minimum) comparing mice that are co-housed to normalized the microbiota. Even more interesting, but likely beyond the scope of this manuscript, would be to colonize GF mice with different microbes or communities and then evaluate the effects on commensal-specific IgM.

Reviewer #2:

The crosstalk of TLRs and the BCR on B1 cells is still poorly understood. Kreuk et al. generated a novel mouse strain by targeting Cre into the constant region of Igg3. In combination with a Rosa26-Tomato allele, this strain was used as a reporter mouse. Tomato was found to be expressed in IgG3+ and (predominantly) IgG3- B cells, with the highest frequencies in peritoneal B-1a cells. Splenic Tomato+ B-1a cells showed an increased cell size and enhanced spontaneous antibody secretion compared to their Tomato- counterpart, along with increased frequencies of PtC-specific cells. Moreover, the percentage of splenic Tomato+ B-1a increased with age, which the authors connect to the acquisition of microbiota. Based on transfer and depletion experiments, the authors conclude that the microbiota-reactive IgMs are B1-derived and that their presence in the serum is microbiota-dependent. In a second set of experiments, the authors show that a smaller fraction of the microbiota is bound by IgMs derived from TLR-deficient mice compared to wild-type controls, and that the fraction of splenic and peritoneal PtC-specific B-1a cells is reduced in these animals. By BCR repertoire sequencing, the authors show that the usage of some VH segments is altered in the absence of certain TLR subsets. Overall, the study contains interesting results, but needs to be improved (and restructured) significantly, as pointed out below.

- As the authors are well aware, TLRs are expressed on many cell types. Thus, the phenotype observed in TLR germline-knockout animals may be due to TLR-deficiency on other cell types, i.e. not B-cell intrinsic. As the paper addresses B cell-intrinsic BCR-TLR cross-talk, it is essential that the authors clarify this issue by e.g. mixed bone marrow reconstitution experiments.

- The data on the B1 cell transfer experiments do not include a phenotypic analysis of the B cell subsets in the recipients after depletion of endogenous B cells and at the time of serum isolation. Did the B-cell depletion work? Do the donor cells solely give rise to B1a cells in the recipients? These controls are essential and should be included.

- The Igg3-Cre mouse line is presented as a reporter line for activated B-1a cells. However, a complete characterization of the mouse (B cell development, expression of Tomato in various B cell subsets (including pro-B, pre-B, MZ, B1-b, etc.), comparison of B cell subset frequencies and absolute cell numbers to wild-type counterparts, etc.) is missing and should be provided, as this is a new, previously unpublished transgenic mouse line. Furthermore, how B cell development was affected when Igg3-Cre expressing cells were eliminated through DTA might be very informative and thus worth to be included in the manuscript.

- A substantial fraction of Tomato+ B cells is negative for IgM and IgG3. Do these cells represent plasma cells, or what else do they represent?

- The subset of Tomato+ B-1a cells should be characterized in more detail (e.g. by analyzing B1-typical markers, responses to stimuli, etc.). Furthermore, given that B-1a cells predominantly reside in the peritoneal cavity, the analysis of Tomato+ cells should not be restricted to the spleen, as it appears to be the case in some figures (such as Figure 2H).

- It is an obvious deficit of the paper that Tomato+ cells are not analyzed under GF conditions. This may be technically impossible to achieve, but the authors may comment in the text.

- Some conclusions of the authors are overstatements, such as the title of Figure 4 ("Toll-like receptor signaling is required for B-1a responses to both phosphatidylcholine and the microbiota"). In reality, microbiota reactive IgM and PtC-specific B-1a cells are reduced, but not absent in the TLR knockout animals. Thus, TLRs may be involved but not required. The same applies for the title of Figure 6: Most CDR frequencies in B-1a cells are not affected by the absence of TLRs in the mutant mice.

Reviewer #3:

The authors generated IgG3-Tomato reporter mouse and observed that Tomato expression was preferentially found in IgM-secreting, activated fraction of B1a cells. The Tomato+ B1a cells express high levels of Nur77, and the IgM generated by Tomato+ cells efficiently recognize PtC and fecal microbiota. These results show that Tomato+ B1a cells received BCR-signal upon their differentiation, probably through PtC and microbiota. Microbiota binding serum IgM was produced by B1, but not by B2 cells, and the differentiation of this fraction of B1a cells required microbiota colonization and also TLR2/4 signals. Interestingly, the differentiation of PtC reactive B1a cells require the function of Unc93B1 but not TLR2/4 signals. Thus, the authors proposed the model in which the responses of B1a cells to microbiota and self-antigen PtC are regulated by coordinated signals through the BCR and the distinct TLR signaling. This is very interesting study based on their serendipitous observation with IgG3-Tomato reporter mouse. The experiments are well-done and the manuscript is well-written.

Some confusion come from the data in which normal amount of IgM was detected in the serum of GF and TLR-/- animals (Figure 3DFigure 4CFigure 5C). Since Tomato+B1a cells are not present in day0 neonatal liver and accumulate upon microbiota colonization (Figure 2F-H), germ free mice are expected to have fewer amount of Tomato+B1a cells. If so, IgM-secreting B1a cells should be fewer in GF and TLR-/- animals. This can be tested by ELISPOT assay for sorted B1a cells in PerC and SPL of GF and TLR-/- mice, like the authors show in Figure 1G. The normal amount of serum IgM gives the impression that there is no defect on Tomato+B1a cells in GF and TLR animals, which gives confusion and disturbance for interpretation of the results related with these animal models.

Another confusion comes from the data by showing the in vitro down-regulation of CD5 upon TLR stimulations (Figure 7), because the authors suggest that TLR stimulation "induce" the IgM-secreting B1a cells. Especially, Figure 4E directly shows that CD5+ B1a cells were reduced in TLR-/- mice. This is confusing, because if TLR stimulation down-regulate CD5 expression, the numbers of CD5+ B1a cells should be increased in TLR-/- mice. One possible explanation is that the strength of TLR signal (or amount of the TLR ligands) might be totally different for in vivo B1a induction and for in vitro CD5 down-regulation. The authors can test this possibility by injecting TLR ligands into WT and TLR-/- mice, and compare the numbers of CD5+B1a cells, like in Figure 4E.

eLife. 2019 Aug 21;8:e47015. doi: 10.7554/eLife.47015.028

Author response


Reviewer #1:

[…] I only have one major experimental concern, which revolves around the data arguing for a role of TLR2/4 in commensal reactivity. It seems highly likely that gut microbiota composition (particularly the presence or absence of pathobionts like Helicobacter or others) could influence the development of commensal-specific IgM. Thus, different mouse colonies (or even lines within a facility that are bred separately) might exhibit differing levels of anti-commensal IgM based merely on differences in commensal composition.

Unless I am mistaken, it appears that the authors performed nearly all of their experiments using mice that were bred as lines rather than using littermate controls, which would be the proper standard in this case for determining the effect of a gene(s) on the observed phenotype. I am certainly sympathetic to the fact that breeding lines with multiple alleles creates a challenge here. Nonetheless, I would have hoped that the authors would have at least co-housed the different lines to partially correct for potential effects of the microbiota, but based on the methods it seems that these lines were all bred and housed separately. There is even an outside possibility that microbiota-dependent differences could explain the seeming discrepancy between the authors' data and the recently published data by Yang showing that GF and SPF mice have equivalent B1a repertoires-that is, that the Yang experiments were done with a microbiota that failed to induce the specificities that Barton et al. discover here. I would strongly suggest that the authors perform at least a few of the critical experiments (e.g., Figure 5D and E) using littermates or (at minimum) comparing mice that are co-housed to normalized the microbiota. Even more interesting, but likely beyond the scope of this manuscript, would be to colonize GF mice with different microbes or communities and then evaluate the effects on commensal-specific IgM.

We agree with the reviewer that this is a very important control, since it is formally possible that lacking TLRs drives changes in the microbiota, resulting in altered B-1a responses. Therefore, in order to normalize the microbiota between different strains of mice, we cohoused WT and TLR KO mice for 4 weeks after weaning, prior to analyzing PtC and microbiota-reactive B-1a responses. We observed the same reduction in anti-PtC and anti-microbiota B-1a responses in TLR KO mice when cohoused with WT mice as we show in Figure 4, allowing us to conclude that the observed differences we see in B-1a responses in TLR KO mice are not due to alterations in their microbiota but rather due to the loss of TLR signaling. We have included these data as a supplement for Figure 4 (Figure 4—figure supplement 2).

Reviewer #2:

[…] Overall, the study contains interesting results, but needs to be improved (and restructured) significantly, as pointed out below.

- As the authors are well aware, TLRs are expressed on many cell types. Thus, the phenotype observed in TLR germline-knockout animals may be due to TLR-deficiency on other cell types, i.e. not B-cell intrinsic. As the paper addresses B cell-intrinsic BCR-TLR cross-talk, it is essential that the authors clarify this issue by e.g. mixed bone marrow reconstitution experiments.

We agree with reviewer 2 that it is important to address the B-cell intrinsic nature of TLR-dependent B-1a responses. Additionally, we appreciate reviewer 3’s comment concerning the confusion presented by the unaltered serum IgM titers in TLR KO mice, given that the data presented in the manuscript supports a model whereby TLR KO B-1a cells secrete less IgM. In order to address these two points in parallel, we performed WT versus TLR KO B cell transfers into B-cell deficient neonates and measured serum IgM responses 10 weeks post transfer. While we had originally proposed including analysis of WT vs. TLR KO B-1 chimeras (generated in collaboration with Baumgarth’s group) to address the question of whether the requirement for TLR function is B cell intrinsic, we were unable to use these data due to technical issues related to the chimera generation.. Fortunately, in parallel we had performed B cell transfers (WT or TLR KO) into B cell deficient mice, as an independent approach to address this question. These experiments clearly demonstrate that B-cell intrinsic TLR signaling is required for optimal antibody secretion and anti-microbiota reactivity (Figure 5K, L). We have included the results from the transfer experiments in our revised manuscript and hope that the Editor and reviewers agree that these data are sufficient to address the B cell intrinsic issue.

We observed significantly reduced microbiota-reactive serum IgM in mice that received TLR KO B cells when compared to WT B cell transfer recipients, allowing us to conclude that TLR-dependent microbiota-reactive B-1 responses are B-cell intrinsic. Additionally, we also observed significantly lower total serum IgM titers in TLR KO B cell transfer recipients. Importantly, while it is not statistically significant, we do see a trend of lower total serum IgM in global TLR deficient animals (Figure 4C). We therefore speculate that the loss of TLRs on other cell subsets may contribute to elevated IgM levels, masking the requirement of B-cell intrinsic TLR signaling for IgM secretion revealed by these B-cell transfer experiments. We have added discussion of this point of confusion in the main text, and have added WT vs. TLR KO B cell transfer data to Figure 4 (Figure 4H-L).

- The data on the B1 cell transfer experiments do not include a phenotypic analysis of the B cell subsets in the recipients after depletion of endogenous B cells and at the time of serum isolation. Did the B-cell depletion work? Do the donor cells solely give rise to B1a cells in the recipients? These controls are essential and should be included.

While we do not have cellular data for the B-1 chimeras upon sacrifice, we have added ELISA data that show endogenous B-1 cell depletion efficiency. Specifically, we have added a panel to Figure 3 (Figure 3B) showing serum IgMa (endogenous B-2 derived) versus IgMb (Donor B-1 derived) titers in the B-1 chimeras presented in Figure 3, which shows that essentially all of the serum IgM is B-1 derived (consistent with previously published data on B-1 Chimeras). This readout is a proxy for endogenous B-1 cell depletion efficiency, as IgMa titers negatively correlate with endogenous B-1 depletion efficiency. We have added to the main text of the manuscript a more detailed description of the B-1 chimera system, which is an extensively validated approach originally published in detail by Lalor et al., 1989. Cellular analyses of B-1 chimeras are further described by Baumgarth et al., 1999. In short, transfer of either purified B-1 cells or total PerC lavage results in only B-1 cells surviving for longer than a few days (i.e. the transferred B-2 cell do not survive post transfer). We hope that the combination of serum ELISA data, which we have added to Figure 3, and referencing previous studies validating the B-1 chimera model in the main text of the manuscript will be sufficient to address this point.

As pointed out by reviewer 2, a PerC lavage contains both CD5+ B-1a (~80%) and CD5 B-1b (~20%) cells, which are both self-renewing. However, as shown in the accompanying manuscript from Savage et al., CD5+ B-1a differentiate into IgM-secreting CD5 “ex B-1a” B-1b cells, whereas CD5 PerC B-1b cells do not. Moreover, while in the context of influenza infection, Savage et al. generated B-1 chimeras with either purified CD5+ B-1a cells or purified CD5 B-1b cells and show that B-1a cells are the main source of IgM ASCs (whereas transferred B-1b cells were not). We therefore feel it is appropriate to conclude that serum IgM derived from transferred PerC lavage cells are largely of B-1a origin.

- The Igg3-Cre mouse line is presented as a reporter line for activated B-1a cells. However, a complete characterization of the mouse (B cell development, expression of Tomato in various B cell subsets (including pro-B, pre-B, MZ, B1-b, etc.), comparison of B cell subset frequencies and absolute cell numbers to wild-type counterparts, etc.) is missing and should be provided, as this is a new, previously unpublished transgenic mouse line. Furthermore, how B cell development was affected when Igg3-Cre expressing cells were eliminated through DTA might be very informative and thus worth to be included in the manuscript.

We have included a number of new figure panels to address the reviewer’s request for a more complete characterization of the Igg3T2A-Cre knock-in mouse. We have included two additional supplementary figures to Figure 1 (Figure 1—figure supplements 4 and 5) where we compare C57BL/6, Igg3T2A-Cre:TdTomato, and Igg3T2A-Cre:DTA age-matched mice. B cell development was assayed by plotting absolute counts of total B220+, Pre-B, Pro-B, early Pro-B, immature B, and mature B cells in the bone marrow, which is unaltered in Igg3T2ACre:TdTomato and Igg3T2A-Cre:DTA mice when compared to C57BL/6 mice. We also show Tomato expression is predominantly restricted to mature IgM+ and likely re-circulating IgMCD43+ B-1 B cells in the bone marrow. The absolute numbers of total CD19+, follicular B, marginal zone B, B-1a, and B-1b cells in the spleen and PerC of Igg3T2ACre:TdTomato and Igg3T2A-Cre:DTA mice is also comparable to C57BL/6 mice. We also provide Tomato expression in these various splenic and PerC B cell subsets.

- A substantial fraction of Tomato+ B cells is negative for IgM and IgG3. Do these cells represent plasma cells, or what else do they represent?

Upon further characterization of these Tomato+IgMIgG3 cells, a significant percentage of these cells express CD43, and are likely of B-1 origin. Recent work from Savage et al., 2017, identified a population of CD19+CD43+IgM cells, that also spontaneously secrete IgM. We have included a representative flow cytometry plot of CD43 expression on Tomato+IgMIgG3 in Figure 1—figure supplement 5D, and we reference the Savage et al. study when discussing these data.

- The subset of Tomato+ B-1a cells should be characterized in more detail (e.g. by analyzing B1-typical markers, responses to stimuli, etc.). Furthermore, given that B-1a cells predominantly reside in the peritoneal cavity, the analysis of Tomato+ cells should not be restricted to the spleen, as it appears to be the case in some figures (such as Figure 2H).

The reviewer importantly points out that the predominant B cell subset in the peritoneal cavity is B-1a cells. However, while only a small percentage of the total B cells in the spleen, B-1a cell numbers are actually comparable in both sites. We, and published work from several other groups, have found that, unlike splenic B-1a cells, peritoneal cavity B-1a cells do not spontaneously secrete IgM. We apologize for not including these data in our original submission, and have added PerC ELISPOT data (comparing Tomato and Tomato+ B-1a cells) to Figure 1G. The rationale behind not including the same time course of Tomato expression in PerC B-1a cells, like we show for splenic B-1a cells in Figure 2H, is that B-1a cells are not detectible in the PerC until about 2 weeks of age. We have revised the main text to better highlight the growing body of evidence that suggests that the spleen is an important site of B-1a activation and spontaneous IgM secretion, which was the rationale behind focusing our analyses on splenic B-1a cells.

- It is an obvious deficit of the paper that Tomato+ cells are not analyzed under GF conditions. This may be technically impossible to achieve, but the authors may comment in the text.

While we agree that this is an exciting future direction, we believe re-deriving the Igg3T2Acre:TdTomato reporter mouse in germ-free conditions is currently beyond the scope of this work. We have however added a discussion of this to the main text of the manuscript.

- Some conclusions of the authors are overstatements, such as the title of Figure 4 ("Toll-like receptor signaling is required for B-1a responses to both phosphatidylcholine and the microbiota"). In reality, microbiota reactive IgM and PtC-specific B-1a cells are reduced, but not absent in the TLR knockout animals. Thus, TLRs may be involved but not required. The same applies for the title of Figure 6: Most CDR frequencies in B-1a cells are not affected by the absence of TLRs in the mutant mice.

We apologize for any overstatements, as we agree titles should accurately summarize the findings. The title of Figure 4 has been changed to “Loss of Toll-like receptor signaling results in reduced B-1a responses to both phosphatidylocholine and the microbiota”. The title of Figure 6 has been changed to “B-1a immunoglobulin repertoire analysis reveals unique regulation of a subset of heavy chain genes by distinct subsets of TLRs”.

Reviewer #3:

[…] Some confusion come from the data in which normal amount of IgM was detected in the serum of GF and TLR-/- animals (Figure 3DFigure 4CFigure 5C). Since Tomato+B1a cells are not present in day0 neonatal liver and accumulate upon microbiota colonization (Figure 2F-H), germ free mice are expected to have fewer amount of Tomato+B1a cells. If so, IgM-secreting B1a cells should be fewer in GF and TLR-/- animals. This can be tested by ELISPOT assay for sorted B1a cells in PerC and SPL of GF and TLR-/- mice, like the authors show in Figure 1G. The normal amount of serum IgM gives the impression that there is no defect on Tomato+B1a cells in GF and TLR animals, which gives confusion and disturbance for interpretation of the results related with these animal models.

Please see our first response to reviewer #1.

Another confusion comes from the data by showing the in vitro down-regulation of CD5 upon TLR stimulations (Figure 7), because the authors suggest that TLR stimulation "induce" the IgM-secreting B1a cells. Especially, Figure 4E directly shows that CD5+ B1a cells were reduced in TLR-/- mice. This is confusing, because if TLR stimulation down-regulate CD5 expression, the numbers of CD5+ B1a cells should be increased in TLR-/- mice. One possible explanation is that the strength of TLR signal (or amount of the TLR ligands) might be totally different for in vivo B1a induction and for in vitro CD5 down-regulation. The authors can test this possibility by injecting TLR ligands into WT and TLR-/- mice, and compare the numbers of CD5+B1a cells, like in Figure 4E.

It appears the reviewer may have misinterpreted the data presented in Figure 4E, which actually shows that there is reduction in PtC+ B-1a cells in TLR KO mice. We have spatially reorganized this part of the figure for clarity. We thank the reviewer for this insight, however, since there actually is a trend towards an increased frequency of CD5+ B-1a cells in TLR KO mice when compared to WT counterparts (Figure 4B). However, this difference is not significant, which is why we did not feel comfortable originally discussing it in the text. This trend towards an increased frequency of B-1a cells in TLR KO mice indeed fits with our model of TLR stimulation resulting in the down regulation of CD5 on B-1a cells, resulting in “ex-B-1a” B-1b cells. While only speculative, one possible explanation for this difference not being greater is that B-1a cells can regenerate, which may be occurring in WT mice at a more frequent rate to renew the B-1a niche.

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Data Citations

    1. Kreuk LSM, Koch MA, Slayden LC, Lind NA, Chu S, Savage HP, Kantor AB, Baumgarth N, Barton GM. 2019. Data from: B cell receptor and TLR signaling coordinate to control distinct B-1 responses to both self and the microbiota. Dryad Digital Repository. [DOI] [PMC free article] [PubMed]

    Supplementary Materials

    Figure 2—source data 1. Summary of monoclonal antibodies generated from Tomato spleen B-1a cells.

    The variable heavy chain gene (VH gene), joining heavy chain gene (JH), heavy chain CDR3 peptide sequence, variable kappa chain gene (VH gene), joining kappa chain gene (JH gene), and kappa chain CDR3 peptide sequence for monoclonal antibodies generated from single-cell sorted Tomato splenic B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice (n = 38).

    DOI: 10.7554/eLife.47015.009
    Figure 2—source data 2. Summary of monoclonal antibodies generated from Tomato+ spleen B-1a cells.

    The variable heavy chain gene (VH gene), joining heavy chain gene (JH), heavy chain CDR3 peptide sequence, variable kappa chain gene (VH gene), joining kappa chain gene (JH gene), and kappa chain CDR3 peptide sequence for monoclonal antibodies generated from single-cell sorted Tomato+ splenic B-1a cells from 6 wk old Ighg3T2A-Cre:TdTomato mice (n = 48).

    DOI: 10.7554/eLife.47015.010
    Figure 6—source data 1. Top 10 highly recurring CDR3 sequences (peptide and V(D)J recombination) detected in peritoneal cavity B-1a samples from age-matched mice lacking different subsets of TLRs.

    The CDR3 peptide sequence, variable heavy chain gene, joining heavy chain gene, total read counts (copy), normalized read counts (norm.copy), and the sum of normalized counts of PtC-binding CDR3 peptide sequences in peritoneal cavity (PerC) B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. PtC-binding CDR3 peptide sequences include MRYSNYWYFDV (highlighted in blue), MRYGSSYWYFDV (highlighted in orange), and MRYGNYWYFDV (highlighted in purple). CDR3 sequences in italic font denotes that they did not appear in the top 10 CDR3 sequences for that sample, but were included to be able to determine the sum of PtC-binding CDR3 sequencing reads. Sequencing reads were normalized by artificially scaling to 10 million reads to account for differences in read depth among samples. There are three biological replicates for each genotype in one experiment.

    DOI: 10.7554/eLife.47015.019
    Figure 6—source data 2. Top 10 highly recurring CDR3 sequences (peptide and V(D)J recombination) detected in spleen B-1a samples from age-matched mice lacking different subsets of TLRs.

    The CDR3 peptide sequence, variable heavy chain gene, joining heavy chain gene, total read counts (copy), normalized read counts (norm.copy), and the sum of normalized counts of PtC-binding CDR3 peptide sequences in spleen (Spl) B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. PtC-binding CDR3 peptide sequences include MRYSNYWYFDV (highlighted in blue), MRYGSSYWYFDV (highlighted in orange), and MRYGNYWYFDV (highlighted in purple). CDR3 sequences in italic font denotes that they did not appear in the top 10 CDR3 sequences for that sample, but were included to be able to determine the sum of PtC-binding CDR3 sequencing reads. Sequencing reads were normalized by artificially scaling to 10 million reads to account for differences in read depth among samples. There are three biological replicates for each genotype in one experiment.

    DOI: 10.7554/eLife.47015.020
    Figure 6—source data 3. Variable heavy chain gene usage summary in spleen and peritoneal cavity B-1a cells in mice lacking different subsets of TLRs.

    Table summarizing the variable heavy chain gene usage frequency in peritoneal cavity and spleen B-1a samples from 7 wk old WT (black), Tlr2-/-Tlr4-/-Unc93b13d/3d (blue), Tlr2-/-Tlr4-/- (pink), and Unc93b13d/3d (green) mice. There are three biological replicates for each genotype in one experiment.

    DOI: 10.7554/eLife.47015.021
    Transparent reporting form
    DOI: 10.7554/eLife.47015.023

    Data Availability Statement

    All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 6. Data files associated with RNA sequencing experiments of B-1a cells have been deposited on Dryad (doi:10.5061/dryad.660js04).

    All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2 and 6. Data files associated with RNA sequencing experiments of B-1a cells are available from the Dryad Digital Repository: https://dx.doi.org/10.5061/dryad.660js04.

    The following dataset was generated:

    Kreuk LSM, Koch MA, Slayden LC, Lind NA, Chu S, Savage HP, Kantor AB, Baumgarth N, Barton GM. 2019. Data from: B cell receptor and TLR signaling coordinate to control distinct B-1 responses to both self and the microbiota. Dryad Digital Repository.


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