Supplementary Table 1. Expression pattern of MKL1/MKL2/SRF downstream in BXD2 mice post-LTbR-Fc administration or are deficient of type I IFNAR

Targeted Effects by LTR-Fc vs. Ifnar-/- vs. Symbol MKL1/2/SRF Vehicle Ifnar+/+ Type(s) Coding IL4 Inhibit 2.616 1.949 cytokine Interleukin 4 CYBA Inhibit 2.071 2.282 enzyme Cytochrome B-245, Alpha Polypeptide EPX Inhibit 7.301 -1.107 enzyme Eosinophil peroxidase GSTM5 Inhibit 3.447 -1.165 enzyme Glutathione S-transferase mu 5 CDKN1A Inhibit 2.501 1.41 kinase cyclin-dependent kinase inhibitor 1A CLDN15 Inhibit 3.851 -1.546 other Claudin 15 Dmkn Inhibit 2.127 -1.101 other Dermokine DNAJB4 Inhibit 2.876 1.308 other DnaJ (Hsp40) homolog, subfamily B, member 4 DSTN Inhibit 2.092 -1.21 other Destrin (actin depolymerizing factor) FCN1 Inhibit 3.347 -1.112 other Ficolin (collagen/fibrinogen domain containing) 1 IER2 Inhibit 5.059 1.267 other immediate early response 2 Membrane-spanning 4-domains, subfamily A, member 3 MS4A3 Inhibit 3.886 -1.917 other (hematopoietic cell-specific) Proteoglycan 2, bone marrow (natural killer cell activator, PRG2 Inhibit 4.664 -1.335 other eosinophil granule major basic protein) PRG3 Inhibit 6.03 -1.065 other Proteoglycan 3 SLPI Inhibit 2.649 -1.374 other Secretory leukocyte peptidase inhibitor CPA3 Inhibit 4.017 -1.053 peptidase Carboxypeptidase A3 (mast cell) CTSG Inhibit 2.602 -2.806 peptidase Cathepsin G ELANE Inhibit 5.809 -1.817 peptidase Elastase, neutrophil expressed Mcpt8 Inhibit 2.039 -3.154 peptidase Mast cell protease 8 Prss34 Inhibit 3.552 -2.848 peptidase Protease, serine 34 PRTN3 Inhibit 3.695 -2.243 peptidase Proteinase 3 CEBPE Inhibit 3.351 -1.178 transcription regulator CCAAT/enhancer binding protein (C/EBP), epsilon EGR1 Inhibit 3.02 1.507 transcription regulator Early growth response 1 ETS1 Enhance -2.066 -1.096 transcription regulator v-ets avian erythroblastosis virus E26 oncogene homolog 1 FOS Inhibit 2.791 2.236 transcription regulator FBJ murine osteosarcoma viral oncogene homolog FOSB Inhibit 6.372 3.19 transcription regulator FBJ murine osteosarcoma viral oncogene homolog B GFI1 Inhibit 2.007 -1.239 transcription regulator Growth factor independent 1 transcription repressor JUN Inhibit 3.46 1.658 transcription regulator Jun proto-oncogene JUNB Inhibit 4.532 3.13 transcription regulator Jun B proto-oncogene IFITM1 Inhibit 3.369 2.255 transmembrane receptor Interferon induced transmembrane protein 1 RAMP1 Inhibit 3.176 1.467 transporter Receptor (G protein-coupled) activity modifying protein 1

Upregulated Downregulated

A B6 BXD2 B6.TC BXD2-Ifnar PNA

12

mo *** - 10 3 *** B6 8 BXD2 6 B6.TC

region region (%) ***

+ 4 BXD2-Ifnar

mo **

- 2

PNA 11 0 PNA (GC) 3-mo 11-mo

B 2.0 B6 BXD2 B6.TC BXD2-Ifnar-/-

1.6 *** *** ** 1.2 ***

0.8 ** ** 0.4 * * * * 0.0

3-mo 11-mo 3-mo 11-mo 3-mo 11-mo 3-mo 11-mo ELISA OD450 Absorbance OD450 ELISA MARCO dsDNA Sm-RNP BiP

Supplemental Figure 1. Age-related development of spontaneous germinal centers and circulating autoantibodies in BXD2 and B6.TC mice. (A) Spleens obtained from B6, BXD2, B6.TC, and BXD2-Ifnar-/- mice at 3-mo-old and 11-mo-old were analyzed by confocal imaging microscopy. Representative fluorescent photomicrographs of PNA+ GCs (circled blue) (Objective lens, 4x) are shown in the left, and quantitation of the percent of PNA + area per microscopic region is shown in the right. All images are representative spleen regions. (B) ELISA analysis of the indicated IgG autoantibody titers in sera obtained from 3- or 11-mo-old mice of the indicated strains. All data are mean ± SEM. (*P < 0.05, **P < 0.01, ***P < 0.005 vs control or B6. n = 2-3 mice per group for 2 independent experiments, Student’s test). A C B6 BXD2 B6-Rag1 BXD2-Rag1 B6-Rag1 50 1.2±0.3 1.8±0.3 1.3±0.4 1.6±0.2 B6 *** BXD2-Rag1 *** 2-mo-old 40

BXD2

*** 30

1.3±0.2 2.9±0.3** 1.1±0.2 3.0±0.5** **

Gapdh

/ CD11c 3 *** ** 6-mo-old 20 * *

x10 *

Ifn *

10 PDCA1

0 B B6 BXD2 B6-Rag1 BXD2-Rag1 Ifna1 Ifna4 Ifna7 Ifna9 Ifna11 Ifnb

2-mo-old

6-mo-old

PDCA1

Supplemental Figure 2. Comparable numbers and localization of pDCs in the spleen of WT and Rag1‒/‒ mice. (A) FACS analysis of the percent of PDCA1+CD11cInt pDCs in the spleens of the indicated strains of mice at 2-mo-old (top panels) or 6- mo-old (bottom panels). (B) Confocal microscopic imaging analysis of PDCA1 expression in the indicated strains of mouse spleen at either 2-mo-old (top panels) or 6-mo-old (bottom panels). Images shown are derived from a representative spleen follicle from each group. (C) Quantitative qRT-PCR analysis of the expression of genes encoding the indicated type I IFNs in PBMCs in 6-mo-old mice. All data are mean ± SEM (n = 2-3 per group for 2 independent experiments; *P < 0.05, **P < 0.01, ***P < 0.005 between the indicated comparisons, Student’s t-test). A B C Isotype α-Dll-1 Isotype α-Dll-1 Isotype α-Dll-1 Isotype α-Dll-1 28.3±4.6 11.3±2.8** B6 B6 B6 (1-mo)

(1-mo) (1-mo)

R1

3.3±0.4 2.2±0.3* -

26.9±3.8 8.2±1.9** F4/80 BXD2 SIGN BXD2 BXD2 (1-mo) (1-mo) (1-mo)

2.9±0.3 2.1±0.2* PNA SIGN-R1 CD11b b CD23 CD1d 20 MADCAM-1 I-A D E F B6 BXD2 Isotype α-Dll-1 Isotype α-Dll-1 9±1 2±1** MZ FO B6 41±3 44±5

MZ

1.6 ) 8

B6 ) 4 6 15 BXD2 (1-mo)

12 (x10 6 68±8 66±5 1.2 8±2 8±2 FO

9 7±1 2±1** 0.8 4

CD21 3±0 3±1 BXD2 6 MZM (1-mo) 0.4 ** ** 2 B Cell count count Cell B (10 3 3±1 3±1 CD4

66±7 66±8 Notch2/Gapdh

B6 1 -mo 9 -mo 0.0 0 B6 1 -mo 9 -mo 0 CD23 B6 BXD2 B6 BXD2 MZ FO MZM CD4 Notch2

Supplemental Figure 3. Depletion of Notch2+ MZ B cells resulted in reduction of MZMs. (A-D) B6 and BXD2 mice (both 1-mo-old) were treated with either an isotype control or an anti-Dll-1 antibody (200 g/mouse, 1x per wk for 1 month). (A) Confocal microscopic imaging analysis of PNA+ GC B cells, SIGN-R1+ MZMs and MADCAM-1+ endothelial cells in the spleen. A representative image from each group is shown. (B) Flow cytometry analysis showing the frequency of CD11bloF4/80negSIGN-R1+I-Ab- MZMs (rectangle) gated cells in the spleen, (C) Confocal microscopic imaging analysis of CD1d+ MZ B cells and CD23+ B cells in the spleen. A representative image from each group is shown. (D) FACS analysis of the percent (left) and total cell count (right) of MZ (CD21hiCD23lo, boxed in upper left) or FO (CD21loCD23hi, circled in lower right) in CD19+ gated B cells. (E) qRT-PCR analysis of Notch2 expression in FACS sorted MZ (IgMhiCD21hiCD23lo) CD19+ B cells, FO (IgMloCD21loCD23hi) CD19+ B cells, MZMs (CD11bloF4/80negSIGN-R1+I-Ab‒) and CD4 T cells from the spleen of naïve B6 and BXD2 mice. (F) Flow cytometry analysis of Notch2 expression on the surface of MZ, FO, MZM, and CD4 T cells in B6 and BXD2 mice. All data are mean ± SEM (n = 3 per group for 2 independent experiments. *P < 0.05 and **P < 0.01 between results from isotype treated B6 or BXD2 mice versus anti-Dll-1 treated B6 or BXD2 mice, Student’s t-test). A LTbR-Fc vs Vehicle B BXD2-Ifnar‒⁄‒ vs BXD2 Ets1 Prg3 Prg2 Prtn3 ** *** *** 0.4 *** 14 2000 4500

MKL1 MKL2 SRF 12 1600 3600 4 0.3 10 *** * 7.1E-08 *** 1200 2700 7.2E-08 0.2 8

3 2.9E-04 Gapdh 6 800 1800 0.1 * 4 B6 400 * 900 * 2 2 BXD2 0 1 2 3 4 0 0 0 1 BXD2-Ifnar‒⁄‒ Slip1 Epx Cpa3 Cldn15 BXD2 LTbR-Fc 0 4.0E-04 2.0E-05 *** 0.03 1500 * -1 1.6E-05 0.03 ** 3.0E-04 ** *** ** 0.02 -2 1000 *** 1.2E-05 ActivationScore Z *** 2.0E-04 ** 0.02 ** Expression relative to 8.0E-06 -3 2.3E-16 0.01 500 ** ** 1.0E-04 4.0E-06 0.01 -4 6.2E-23 2.3E-22 0 0.0E+00 0.0E+00 0.00 -5

Supplemental Figure 4. Alteration of the MKL1/MKL2/SRF pathway in BXD2 mice that were treated with LTβR-Fc or are deficient of IFNAR. MZMs were sorted by flow cytometry from the spleens of 2.5-mo-old BXD2 mice that were treated with PBS or LTβR-Fc (injected i.v. with 25 μg sLTβR-Fc), and BXD2-Ifnar‒⁄‒ mice treated with PBS. Mice were sacrificed 10 hrs following the treatment. RNA was isolated via a TRIzol method (Invitrogen). (A) Gene array upstream pathway analysis of genes regulated by MKL1, MKL2 and SRF in sorted MZMs from vehicle- vs LTβR-Fc-administered BXD2 mice or BXD2-Ifnar+/+ vs. BXD2-Ifnar‒⁄‒ mice. Gene expression analysis was performed using the mouse WG- 6 BeadChip and iScan system from Illumina, Inc. Total RNA was converted to cDNA by reverse transcription, followed by second-strand synthesis to generate double-stranded cDNA. After purification, the cDNA was converted to biotin-labeled cRNA, hybridized to a mouse WG-6 BeadChip and stained with strepavidin-Cy3 for visualization. The mouse WG-6 BeadChips contain sequences representing approximately 45,200 curated and putative genes and ESTs. Quality standards for hybridization, labeling, staining, background signal, and basal level of housekeeping gene expression for each chip were verified. After scanning the probe array, the resulting image was analyzed using GenomeStudio software (v2011.1, Illumina, Inc.). Gene lists were further analyzed using GeneSpring version 12.1 (Agilent) software. Data were analyzed through the use of Ingenuity Pathways Analysis (IPA, Ingenuity® Systems, www.ingenuity.com). Upstream Regulator Analysis from IPA was used to identify the upstream regulators that were responsible for gene expression changes observed in the data. The activation z-score (an algorithm designed to reduce the chance that random data will generate significant predictions) identifies upstream regulators that can explain observed gene expression changes in the data, and predicts the activation state of the upstream regulators. An absolute z-score ≥ 2 is considered significant. Predictions where both the z-score is significant (absolute value ≥ 2) and the p-value is significant (<10E-3) are the most reliable predictions. The results were obtained from a pool of 2 mouse spleens per chip from each group for 2 chips from BXD2 mice and 1 chip from the other 2 groups). The P value for each comparison is shown. (B) qRT-PCR analysis of representative genes that are regulated by the MKL-SRF axis in sorted MZMs from the indicated strains. All data are mean ± SEM from each group (*P < 0.05, **P < 0.01, ***P < 0.005 between the indicated groups. n = 2-3 mice per group for 2 independent experiments, Student’s t- test). The full name of each gene is shown in Supplementary Table 1. Max 200 Max 50 100 Min 25 Min 5 MARCO 80

B6 60 40 ***

20

0 Ltβf/fCD19. B6 LTbxCD19 BXD2 IFNAR 25 Cre B6 MKL1 20 15

Intensity (Arbitrary Unit) 10 BXD2 ** 5 ***

Intensity (Arbitrary Unit) 0 B6 LTbxCD19 BXD2 IFNAR

BXD2- Ifnar‒⁄‒

MARCO MKL1

Supplemental Figure 5. Defective LTβR signaling or increased IFNAR signaling is associated with decreased expression of MKL1 in MZMs. Right: Representative ImageJ 3D intensity plots of MARCO (green) or MKL1 (red) in the indicated mouse spleen follicle. Original images were acquired using confocal imaging microscopy (objective lens 20). The maximal and minimal intensity scales set for the plots are shown on the top. left: ImageJ quantitation of the intensity of either MARCO or MKL1. Results are the average from 3–5 randomly chosen follicles analyzed per section (**P < 0.01 or ** P < 0,005 versus B6. n = 2-3 mice per group for 2 independent experiments, Student’s t-test). MKL1 Phalloidin

B6 Ltβf/fCD19.Cre B6 B6 Ltβf/fCD19.Cre B6

178±15 73±6*** 182±16 61±3***

Ltbrf/f B6 Ltbrf/fLys.Cre B6 Ltbrf/f B6 Ltbrf/fLys.Cre B6

225±26 54±4*** 177±10 53±4***

BXD2 BXD2-Ifnar‒⁄‒ BXD2 BXD2-Ifnar‒⁄‒

57±5 196±12*** 49±5 174±11***

Intensity (Arbitrary Unit)

Supplemental Figure 6. Defective LTβR signaling is associated with decreased mechanosensing MKL1 in MZMs. MZMs from the indicated mouse spleens FACS sorted as CD11bloF4/80negSIGN- R1+I-Ab- cells. Cells were cytospun to histology slides and were stained for intracellular expression of MKL1 and were further countered stained with phalloidin for F-actin polymerization (green). Photomicrographs were obtained and the intensity of MKL1 and F-actin was quantitated using the ImageJ program. Representative histograms of the intensity of MKL1 (left panels) or phalloidin (right panels) in sorted MZMs from each indicated mouse group were shown (≥ 20 cells were quantitated per mouse). All data are mean intensity ± SEM (*** P < 0.005 between the indicated groups. n = 2-3 mice per group for 2 independent experiments, Student’s t-test). A Donor Group1 Recipient Group 1 Donor Group 2 Recipient Group 2

BM BM B6.CD45.1 B6.CD45.1 (WT) (WT) 1-mo or 4-mo 1-mo or 4-mo 7 1  107 Analysis 1  10 Analysis BM BM B6.CD45.2 B6.CD45.2 350 cGy Irradiated 350 cGy Irradiated (Ltbrf/fLys.Cre) (WT) ‒⁄‒ 7 B6-Rag1‒⁄‒ 1  107 B6-Rag1 1  10

B 1-mo 4-mo 1-mo 4-mo 1-mo 4-mo-post transfer CD45.1 (WT) 22.9±4.3 23.1±4.1 48 ±6 52±5 +

B6: CD45.2(WT) 2.4± 2.3±

46±3 45±5

0.3 0.3 R1 -

CD45.1 (WT) 21.4±2.9 9.6±1.8** 51 ±5 77±6

CD45.1 F4/80

+ SIGN B6:CD45.2 (Ltbrf/fLys.Cre) 2.4± 1.7± 44±5 18±2*** 0.3 0.2* CD11b MHC CD45.2

C

15 15 CD45.1 (WT) 53±4 44±5 12 10 93±4 96±4 9 88±7 90±6 + 29 6 2.9± 5 B6: CD45.2(WT) 3 ±6 0.5 0 0

SSC 15 F4/80 15 12 CD45.1 (WT) R1 SIGN 69±5 27±2*** 10 16±3 89±7*** 9 31±4 95±10*** +

Number Number Events of 6 12 Number Events of 1.8± 5 f/f 3 B6:CD45.2 (Ltbr Lys.Cre) 0.3* ±2** 0 0 CD11b F4/80 CD45.2 MKL1 F-actin

Supplemental Figure 7. Decreased percent of MZMs derived from B6 Ltbrf/f Lys.Cre mice after mixed BM reconstitution. (A) Mixed BM chimeric mice were generated by reconstitution of equal numbers of Group 1 (CD45.1 B6:CD45.2 B6 BM cells) or Group 2 (CD45.1 B6:CD45.2 B6 Ltbrf/f Lys.Cre BM cells (107 each) into irradiated B6-Rag1 ‒⁄‒ mice (6-week-old) and analyzed 1 or 4 months later. (B) FACS analysis of the percent of MZMs derived from either WT or Ltbrf/fLys.Cre donor BMs. MZMs were gated as CD11bloF4/80negSIGN-R1+I- Ab- cells and were further gated to show the distribution of CD45.1 or CD45.2 donor cells. (C) Sequential ImageStream gating for the expression of MKL1 and F-actin in recipient spleen MZMs 4 months following the transfer of BM cells. Results are mean percent of cells in the gated region ± SEM (n = 2-3 per group for 2 independent experiments, *P < 0.05, **P < 0.01, ***P < 0.005 between results from the indicated groups, Student’s t-test). A Donor Group1 Recipient Group 1 Donor Group 2 Recipient Group 2 BM BM B6.CD45.1 B6.CD45.1 (WT) 1-mo or 4-mo (WT) 1-mo or 4-mo 1  107 1  107 Analysis Analysis BM BM B6.CD45.2 B6.CD45.2 350 cGy Irradiated ‒⁄‒ 350 cGy Irradiated (WT) ‒⁄‒ (Mkl1 ) ‒⁄‒ 1  107 B6-Rag1 1  107 B6-Rag1

B 1-mo 4-mo 1-mo 4-mo 1-mo 4-mo-post transfer CD45.1 (WT) 2.7±0.3 2.6±0.3 24±5 23±4 51±6 51±5

+

CD45.2 (WT) 46 47

R1

- ±5 ±4 2.4±0.2 1.9±0.2*

F4/80 25±4 12±3** 52±4 78±4 CD45.1 CD45.1 (WT) SIGN + 44 19 CD45.2 Mkl1‒⁄‒ ±4 ±3*** CD11b I-Ab CD45.2

C

15 CD45.1 (WT) 15 51±3 48±3 12 93±5 96±3 10 98±3 99±4 9 + 2.6± 5 6

CD45.2 (WT)

28±4 3

0.4 0 0

SSC 15

CD45.1 (WT) F4/80 15 12

SIGN R1 SIGN 74±6 20±4*** + 10 1±0 98±6*** 9 13±2 97±7***

‒⁄‒ 6 Number Number of Events 1.7± Number of Events CD45.2 Mkl1 5 3 0.2* 11±2** 0 0 CD11b F4/80 CD45.2 MKL1 F-actin

Supplemental Figure 8. Decreased percent and abnormal actin polymerization in MZMs from Mkl1‒⁄‒ mice after mixed BM reconstitution. (A) Mixed bone marrow chimeric mice were generated by reconstitution of equal numbers (107) of Group 1 (CD45.1 [WT]:CD45.2 [WT] BM cells) or Group 2 (CD45.1 [WT]:CD45.2 [Mkl1‒⁄‒] BM cells into B6-Rag1‒⁄‒ mice (6-weeks-old) and analyzed 1 or 4 months later. (B) FACS analysis of the percent of MZMs derived from either WT or Mkl1‒⁄‒ donor BMs. MZMs were gated as CD11bloF4/80negSIGN-R1+I- Ab- cells and were further gated to show the distribution of CD45.1 or CD45.2 donor cells. (C) Sequential ImageStream gating for the expression of MKL1 and F-actin in recipient spleen MZMs 4 months following the transfer of BM derived from WT or Mkl1‒⁄‒ donors. Results are mean percent of cells in the gated region ± SEM (n = 2-3 per group for 2 independent experiments, *P < 0.05, **P < 0.01, and ***P < 0.005 between results from the indicated groups, Student’s t-test). A Liposomes B Liposomes C Liposomes

PBS CCG100602 PBS CCG100602 PBS CCG100602

8.5±1.0 14.7±2.1* B6

60.3±5.8 115.8±9.3**

BXD2

IgG DAPI 4 IgG DAPI Intensity of green fluorescent IgG staining (Arbitrary Unit)

Supplemental Figure 9. Liposome-CCG100602 administration resulted in increased IgG deposition in kidney glomeruli. B6 and BXD2 mice (3-mo-old) were administered i.v. every other day for 4 weeks with liposome-CCG-100602 (100 μg/mouse) or control liposome-PBS. Mice were sacrificed 4 weeks later at 4 months of age. (A) Florescence microscopic imaging analysis of IgG+ glomeruli in the kidney (objective lens, 4). (B) Boxed regions in Panel A are digitally magnified to show a higher power view of the selected region. (C) ImageJ analysis of the intensity of IgG in each glomerulus. A representative histogram quantitating the IgG intensity in a representative glomerulus is shown. At least 20 glomeruli were quantitated for each kidney section. Numbers represent mean intensity of green fluorescent ± SEM (*P < 0.05 or ** P < 0.01 between the indicated comparisons. n ≥ 6 mice/group, Student’s t-test). Spleen Follicle Spleen Marginal Zone

CD69 Type I IFN pDC

Follicular IFNAR MZ translocation MZ B B cells CD69 AC

mLT Lupus MZ MZ B mLTbR B cells

F-actin AC AC: apoptotic cell mLT polymerization IFN: interferon MKL1: megakaryoblastic leukemia 1 MKL1 expression & mLT: membrane lymphotoxin α1β2 nuclear translocation mLTβR: membrane lymphotoxin β receptor MZ: marginal zone MKL1 SRF MZM: marginal zone macrophage pDC: plasmacytoid dendritic cells MZM SRF: Gene expression Promote Inhibit

Supplemental Figure 10. Type I IFN disrupts the LTβR/MKL1/F-actin axis leading to defective mechanoreceptor signaling for AC clearance of spleen MZMs. ACs are normally taken up by scavenger receptors (SR), such as MARCO and SIGN-R1, on MZMs. This process normally leads to tolerogenic signals and decreased AC autoantigens. In lupus, increased interactions of ACs with pDCs in the MZ leads to type I IFN-induced follicular translocation of MZ B cells that disrupts the ability of MZ B cells to signal via mLT through mLTβR on MZMs. Decreased LTβR signaling in MZMs leads to decreased expression and nuclear translocation of MKL1 and defects in SRF. MKL1 is normally localized in the cytoplasm by binding to cytoplasmic G-actin. Mechanical stimulation triggers actin polymerization, liberating MKL1 from G-actin, increasing its nuclear import and accumulation of MKL1, where it co-activates SRF to turn on genes regulating cellular motility and contractility, including vinculin, actin, and SRF. MKL1 and SRF regulate efficient development of endolysosomal vacuoles important for uptake of ACs. In addition, defects in the MKL1/SRF pathway in MZMs leads to altered expression of other genes that can affect function and survival of MZMs. Defects in F-actin polymerization and AC uptake leads to increased ACs and AC debris which further accentuates follicular translocation of MZ B cells. Also, defects in MKL1 and SRF pathways in MZMs lead to first, their loss of AC uptake function and later, decreased MZM survival and loss of MZMs.