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Distinct fibroblast subsets drive inflammation and damage in arthritis

Abstract

The identification of lymphocyte subsets with non-overlapping effector functions has been pivotal to the development of targeted therapies in immune-mediated inflammatory diseases (IMIDs)1,2. However, it remains unclear whether fibroblast subclasses with non-overlapping functions also exist and are responsible for the wide variety of tissue-driven processes observed in IMIDs, such as inflammation and damage3,4,5. Here we identify and describe the biology of distinct subsets of fibroblasts responsible for mediating either inflammation or tissue damage in arthritis. We show that deletion of fibroblast activation protein-α (FAPα)+ fibroblasts suppressed both inflammation and bone erosions in mouse models of resolving and persistent arthritis. Single-cell transcriptional analysis identified two distinct fibroblast subsets within the FAPα+ population: FAPα+THY1+ immune effector fibroblasts located in the synovial sub-lining, and FAPα+THY1 destructive fibroblasts restricted to the synovial lining layer. When adoptively transferred into the joint, FAPα+THY1 fibroblasts selectively mediate bone and cartilage damage with little effect on inflammation, whereas transfer of FAPα+ THY1+ fibroblasts resulted in a more severe and persistent inflammatory arthritis, with minimal effect on bone and cartilage. Our findings describing anatomically discrete, functionally distinct fibroblast subsets with non-overlapping functions have important implications for cell-based therapies aimed at modulating inflammation and tissue damage.

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Fig. 1: FAPα+ SFs accumulate in the arthritic joint.
Fig. 2: Deletion of FAPα-expressing cells attenuates synovial inflammation and damage.
Fig. 3: Single-cell RNA sequencing reveals distinct fibroblast subsets.
Fig. 4: Fibroblast subsets are responsible for different aspects of disease pathology.

Data availability

STIA single cell and bulk fibroblast RNA sequencing data that support the findings of this study have been deposited in Gene Expression Omnibus (GEO) with the accession codes GSE129087 and GSE129451. Source Data for Figs. 1, 2, 4 and Extended Data Figs. 13, 10 are provided with the online version of the paper.

Code availability

The source code repository of the computational pipeline for single-cell data analysis and integration is located at https://www.github.com/sansomlab/tenx/.

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Acknowledgements

A.P.C. was supported by a Wellcome Trust Clinical Career Development Fellowship no. WT104551MA; A.F. was supported by Arthritis Research UK Clinician Scientist Fellowship no. 18547; F.B. was supported by an Arthritis Research UK Senior Fellowship; H.M.M. was supported by an Arthritis Research UK Career Development Fellowship (19899); C.W. was supported by a Deutsche Forschungsgemeinschaft (DFG) Fellowship (ref. 319464273); A.J.N was supported by a Versus Arthritis Career Development Fellowship no. 21743; K.W. was supported by Rheumatology Research Foundation Scientist Development Award; K.J. was supported by a Wellcome Trust PhD studentship; S.N.S. and M.A. are supported by the Kennedy Trust for Rheumatology Research. K.D. was supported by a Deutsche Forschungsgemeinschaft (DFG) award CRC1181. This work was supported by the Arthritis Research UK Rheumatoid Arthritis Pathogenesis Centre of Excellence no. 20298 (RACE); The National Institutes of Health Accelerating Medicines Partnership in RA/SLE and Arthritis Research UK programme grant no. 19791 (to C.D.B.). This paper presents independent research supported by the NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, our funding bodies or the Department of Health.

Reviewer information

Nature thanks Jason Cyster, Thomas A. Wynn and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

Authors

Contributions

A.P.C. conceived the project, performed experiments, analysed data and wrote the manuscript. J.C. performed experiments, analysed data and helped to write the manuscript. K.J. analysed the single-cell RNA sequencing data and helped to write the manuscript. J.D.T. performed flow cytometry on human synovial biopsy tissue. J.M. performed immunofluorescence microscopy. M.A. performed single cell capture and library preparation. L.S. performed tissue histology and microscopy. C.W. and A.J.N. performed osteoclast differentiation assays. S.K. assisted with the CIA experimental arthritis model. J.B. performed micro-CT analysis. K.D. performed flow cytometry from CIA mouse joints. H.P. generated serum from KBxN mice. F.B. and H.M.M. helped in the design and interpretation of experimental mouse data. D.T.F. generated the FAPα-DTR mouse. K.W. performed and analysed mass cytometry of human synovial biopsy tissue. S.R. and I.K. helped generate, analyse and interpret human single-cell transcriptomic data. M.B.B. and M.C. provided critical interpretation of experimental data. S.N.S. supervised the design, execution, analysis and interpretation of the single-cell transcriptomics experiments and helped to write the manuscript. A.F. participated in study design, patient recruitment, sample acquisition and review of the data. C.D.B. conceived the project, supervised the work, analysed data and co-wrote the manuscript. All authors discussed the results and commented on the manuscript.

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Correspondence to Christopher D. Buckley.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Mouse synovial FAPα expression.

a, Expression of PDPN and FAPα by immunohistochemistry in ankle joints (representative of n = 8 mice). be, Flow cytometry of digested synovia. Gating strategy for synovial fibroblasts in digested synovia (b) representative expression of PDPN and FAPα during STIA (c), corresponding absolute numbers of FAPα+ cells (n = 10 mice per group) (d), and plot of FAPα expression in THY1 (LL, blue) or THY1+ (SL, red) PDPN+ cells and PDPNTHY1+ pericytes (black) in day 9 STIA synovia (e). Each plot is representative of n = 12 mice; numbers represent the percentage of cells. f, Quantification of Fap transcript expression in sort-purified cells (day 9 STIA synovia, n = 12 mice). g, Immunofluorescence staining for PDPN, FAPα and THY1 expression in day 9 STIA ankle joints (representative of n = 12 mice). hj, Spearman’s correlation analysis between the total (black), LL (blue) and SL (red) FAPα expressing cells quantified by flow cytometry and the change in ankle joint thickness (h), cartilage destruction (i) and bone erosion (j; cartilage destruction and bone erosion assessed by histology) (n = 40 mice). k, l, Representative bioluminescence of in vivo imaging of FAPα-DTR+ mice treated with diphtheria toxin or vehicle (Veh) (k) and quantification of bioluminescence (l; n = 8 mice per group). m, Quantification of synovial FAPα+ cells following administration of either diphtheria toxin or vehicle (n = 8 mice per group). n, Immunohistochemistry staining of FAPα (red) expression in ankle joints following diphtheria toxin (representative of n = 8 mice). o, Total number of CD45CD31 cells by flow cytometry in day 9 STIA synovia compared to non-arthritic (control) mice following diphtheria toxin (n = 7 mice per group). p, H&E staining and quantification of cellularity following diphtheria toxin treatment. Arrow indicates synovial membrane. Data are expressed as the average number of cells per quantified per histological section (n = 8 mice per group). Statistics: two-way ANOVA with Tukey’s post hoc test (fmop). Data are mean ± s.d., except in f, mo, which are shown as box plots (centre line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values).

Source data

Extended Data Fig. 2 Effects of FAPα cell deletion.

ac, Change in wrist and ankle joint thickness during STIA with AUC analysis following treatment with diphtheria toxin (FAPα cell deletion) at days 5 and 7 (a), and days 10 and 12 (b), or prophylactically before the induction of STIA (c) (all, n = 8, mice per group). d, Representative time-course analysis of structural joint damage assessed by micro-CT following treatment with diphtheria toxin (FAPα cell deletion) at days 3 and 5 following induction of STIA. e, Quantification of bone erosion and new bone formation (e; n = 8 mice per group), combined for front and hind paws. f, Histological examination of ankle joint tissue sections at day 12 STIA with quantification of bone erosion, pannus formation and bone formation (all by H&E) and cartilage destruction (by safranin O staining) (n = 12 mice per group). g, Representative images of cathepsin K immunohistochemical staining of osteoclasts (brown) in the ankle joints of day 12 STIA mice. h, Number of osteoclasts (cathepsin K positive) per tissue section in DTR versus DTR+ mice at day 12 STIA compared to non-arthritic control mice (n = 12 mice per group). i, Expression of bone turnover markers including osteoclast and osteoblast markers in whole paw tissue analysed by RT−qPCR (n = 8 mice per group, data are expressed as mean fold change in expression compared to expression in non-arthritic mice). Statistics: Mann–Whitney test (ac); two-way ANOVA with Tukey’s post hoc test (e); one-way ANOVA with Tukey’s post hoc test (f, h). Data are mean ± s.d., except AUC analysis in ac, which are shown as box plots (centre line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values).

Source data

Extended Data Fig. 3 Effect of FAPα cell deletion on leukocyte infiltration.

a, Flow cytometry plot of peripheral blood monocytes (numbers, percentage of positive cells) with quantification at day 9 STIA following diphtheria toxin at day 3 and day 5 (n = 6 mice per group). b, Flow cytometry gating strategy for leukocyte populations in digested synovia. c, Numbers of leukocytes and percentage of MHC class II expressing F4/80 cells (M1) in hind limb joints of day 28 persistent STIA mice analysed by flow cytometry (n = 13 mice per group). d, Representative immunohistochemical staining of macrophages (F4/80+, brown; nuclei, blue) in the ankle joint tissue sections at day 12 STIA mice following diphtheria toxin at day 3 and 5 (representative of n = 6 mice). e, Percentage of F4/80+ macrophages staining positive for MHC class II as detected by flow cytometry in day 12 STIA digested synovia from DTR+/− mice following diphtheria toxin at day 3 and 5 (n = 13 mice per group). f, Expression of functional macrophage markers detected by RT−qPCR in sort-purified macrophages (CD45+CD11b+F4/80+) isolated from the synovia of day 12 STIA mice following diphtheria toxin at day 3 and 5 (n = 7 mice per group). g, h, Number of FAPα expressing cells quantified by flow cytometry from digested synovia (n = 8 mice), popliteal (draining) and mesenteric (non-draining) lymph nodes (n = 6 mice) following intra-articular administration of diphtheria toxin into the ankle joint during STIA (harvested day 14) (g) and daily change in weight from baseline (expressed as percentage of original body weight) in STIA mice compared to non-arthritic mice (h) (n = 6 mice). i, Effect of local deletion of synovial FAPα-expressing cells (by intra-articular injection of diphtheria toxin) on ankle joint thickness in the resolving model of STIA model when compared to the wrist joints on the same mouse (non-deleted limbs) (n = 8 mice) and to non-arthritic DTR+ and DTR injected mice (n = 6 mice per group) with AUC analysis. j, Representative micro-CT images of day 14 STIA and non-arthritic control mice following intra-articular injection of diphtheria toxin and quantification of bone erosion and new bone formation (STIA DTR n = 10, STIA DTR+ n = 13, DTR and DTR+ n = 8). k, Quantification of the number of fibroblasts and leukocytes in digested synovia of day 9 STIA mice analysed by flow cytometry following intra-articular administration of diphtheria toxin (n = 8 mice). Statistics: two-way ANOVA with Tukey’s post hoc test (a, c, e, j, k), two-tailed paired Student’s t-test (f, g), one-way ANOVA with Tukey’s multiple comparison tests (i, j). Data are mean ± s.d., except in a, c, e, f, g, k and AUC analysis in i, which are shown as box plots (centre line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values).

Source data

Extended Data Fig. 4 10X Chromium single-cell RNA sequencing (droplet-based single-cell) analysis of CD45 cell populations from inflamed synovium.

a, t-SNE projection of non-haematopoietic stromal cells from the inflamed mouse joint (n = 3 biological replicates, day 9 STIA) showing the initial automatic cluster assignments from Seurat (projection is identical to that shown in Fig. 3a). b, The same t-SNE plot coloured by biological replicate. c, The bar plot shows the number of cells in each cluster stratified by replicate. d, Cluster cell identification: the five panels of violin plots show expression (normalized, log-transformed counts of the cells from all of the n = 3 biological replicates, y axes) of known cell-type marker genes (for fibroblasts, LL fibroblasts, osteoblasts, chondrocytes and vascular cells) in each of the automatically assigned clusters (x axes). The colours of violin plots correspond to those shown in Extended Data Fig. 4a.

Extended Data Fig. 5 Continued cluster identification analysis.

The four panels of violin plots show expression (normalized, log-transformed counts of the cells from all of the n = 3 biological replicates, y axes) of known cell-type marker genes (for pericytes, muscle cells, erythrocytes and the cell cycle) in each of the automatically assigned clusters (x axes). The colours of violin plots correspond to those shown in Extended Data Fig. 4a.

Extended Data Fig. 6 Differential gene expression between fibroblast clusters.

The heat map shows the (row-scaled) expression of the top-20 (by P value) discovered significant, conserved marker genes for each cluster (Benjamini–Hochberg adjusted P < 0.1 in separate tests of cells from each of the n = 3 biological replicate samples, two-sided Wilcoxon tests). Each column represents a single fibroblast and each row shows the given gene. The cluster identification is indicated for each column. LL fibroblasts correspond to F5 and are PDPN+THY1 and SL fibroblasts correspond to F1–F4 fibroblast subsets and are PDPN+THY1.

Extended Data Fig. 7 Differential gene expression in specific fibroblast clusters.

a, A set of violin plots showing gene expression (normalized, log-transformed counts of the cells from all of the n = 3 biological replicates, x axes) of additional fibroblast markers in each of the F1–F5 fibroblast clusters (y axes) (corresponds to Fig. 3b). b, t-SNE projection of fibroblasts from the inflamed mouse joint coloured by replicate (corresponds to Fig. 3b). c, A set of violin plots showing gene expression (normalized, log-transformed counts of the cells from all of the n = 3 biological replicates, x axes) of known markers for chemokines in each of the F1–F5 fibroblast clusters (y axes) (corresponds to Fig. 3b). d, Number of cells in each cluster stratified by replicate.

Extended Data Fig. 8 Trajectory analysis and identification of fibroblast subpopulations from human RA patients.

a, The heat map shows genes most strongly up- or downregulated across the inferred F1–F2–F5 trajectory in the mouse fibroblasts from the STIA model (as determined by Slingshot14). be, Reanalysis of CEL-Seq2 single-cell RNA sequencing dataset from 20 RA patients15. b, t-SNE projection of the RA patient fibroblasts indicating the automatic cluster assignments from Seurat. c, The sets of violin plots show expression (normalized, log-transformed counts, cells from all n = 20 RA patients, x axes) of cluster marker genes in each of the RA patient fibroblast clusters (y axes). The violin plots are grouped into six sets comprising ‘other markers’ (known markers or markers reported by Zhang et al.15) or of markers characteristic of each of the human RA F1–F5 clusters, as indicated. d, The same t-SNE plot as in b, coloured by patient ID. e, The bar plot shows the number of patients represented in each assigned cluster.

Extended Data Fig. 9 Bulk RNA sequencing of sort-purified FAPα expressing LL and SL cell populations from the inflamed hind limb joints of day 9 STIA mice.

a, Gating strategy for flow cytometry based cell sorting from day 9 STIA digested synovia gated on CD45CD31 live cells. Coloured gates correspond to each sort-purified population and the percentage gated cell population is indicated. b, Principal component analysis reveals that each population clusters according to either a SL phenotype or a LL phenotype. Each dot presents a single biological replicate sample and is coloured according to the gating strategy outlined in a. c, The heat map shows the differential expression of the 50 most-significant genes (by P value) for each population (Benjamini-Hochberg adjusted P < 0.1) and reveals distinct transcriptional profiles between THY1+ and THY1 cell populations. d, Expression of specific genes RNA sequencing in PDPN+FAPα+THY1 versus PDPN+FAPα+THY1+ sort-purified cells. For each heat map, a column represents a single biological replicate, coloured according to the gating strategy in a. Biological replicates represent cells isolated and purified from the digestion of synovia from the hind limbs of a single mouse (n = 10 THY1FAPα+, n = 5 THY1FAPα, n = 6 THY1+FAPα and n = 12 THY1+FAPα+ samples).

Extended Data Fig. 10 Effect of intra-articular injection of fibroblast subsets.

a, Effect on ankle joint thickness of intra-articular injection of 500,000 sort-purified PDPN+FAPα+THY1 (blue) or PDPN+FAPα+THY1+ (red) cells into the ankle joint of CIA mice at the first sign of joint inflammation (day 0) compared to contralateral sham injected joints (n = 8 mice per group). b, Representative images of micro-CT analysis and quantification of bone erosion and new bone formation (n = 8 mice per group). c, Flow cytometric analysis of leukocytes in the digested synovia of injected joints, 7 days post injection (n = 8 mice per group). d, Representative confocal microscopy of ankle joint tissue of mice injected with tomato red-expressing PDPN+FAPα+THY1 or PDPN+FAPα+THY1+ isolated from day 9 STIA cells and injected into day 3 STIA recipient mice (representative images from n = 6 mice, 14 days post injection). e, Flow cytometric analysis of digested synovia, 14 days after injection of cell trace labelled cells (isolated from day 9 STIA mice and injected into the ankle joint of day 3 STIA recipient mice), gated on the CD45CD31PDPN+ cell fraction. Percentage of THY1+ (red) or THY1 (blue) cell in this gated cell fraction is indicated (representative of n = 6 per group). f, Percentage of engraftment and viability of injected cells 14 days after injection into the ankle joints of STIA mice (n = 8 per treatment group, two tailed Student’s t-test). Engraftment is expressed as the percentage recovery of the original injected cell number. Statistics: one-way ANOVA with Bonferroni post hoc test (b, c) and AUC analysis (a), paired two-tailed Student’s t-test (f). Data represented as mean ± s.d., except in c, e and AUC analysis in a, which are shown as shown as box plots (centre line, median; box limits, upper and lower quartiles; whiskers, maximum and minimum values).

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Mouse STIA cluster markers. The conserved cluster marker genes identified for the clusters of single cells shown in Figure 3A ("CD45- cells") and Figure 3B ("Fibroblasts"). Conserved cluster marker genes were identified as those with a maximum Benjamini Hochberg (BH) adjusted p-value <0.1 in separate tests of cells belonging to each of the n=3 biological replicates (two-sided Wilcoxon tests)

Supplementary Table 2

Mouse STIA fibroblast cluster gene set analysis. GO biological process significantly over-represented (Benjamini-Hochberg corrected p value <0.05, one-sided Fisher's tests) amongst the conserved cluster marker genes (n=3 biological replicates, see Supplementary Table 1) for the mouse STIA fibroblast clusters (Figure 3C)

Supplementary Table 3

Gene expression analysis of THY1- FAPα- versus THY1- FAPα+ fibroblasts. Differential gene expression comparison between THY1- FAPα- (n=5 biological replicates) and THY1- FAPα+ (n=10 biological replicates) sort purified fibroblasts from day 9 STIA digested hind limb synovia using DESeq2. Biological replicates represent digested synovia from the hind limb joints of a single mouse. Genes were tested for differential expression using the Wald test and p-values were adjusted using the Benjamini-Hochberg method. Comparisons of gene expression between biological groups for which the adjusted p-values were <0.05 were considered significant

Supplementary Table 4

Gene expression analysis of THY1+ FAPα- versus THY1+ FAPα+ fibroblasts. Differential gene expression comparison between THY1+ FAPα- (n=7 biological replicates) and THY1+ FAPα+ (n=13 biological replicates) sort purified fibroblasts from day 9 STIA digested hind limb synovia using DESeq2. Biological replicates represent digested synovia from the hind limb joints of a single mouse. Genes were tested for differential expression using the Wald test and p-values were adjusted using the Benjamini-Hochberg method. Comparisons of gene expression between biological groups for which the adjusted p-values were <0.05 were considered significant

Supplementary Table 5

Gene expression analysis of THY1- FAPα+ versus THY1+ FAPα+ fibroblasts. Differential gene expression comparison between THY1- FAPα+ (n=10 biological replicates) and THY1+ FAPα+ (n=13 biological replicates) sort purified fibroblasts from day 9 STIA digested hind limb synovia using DESeq2. Biological replicates represent digested synovia from the hind limb joints of a single mouse. Genes were tested for differential expression using the Wald test and p-values were adjusted using the Benjamini-Hochberg method. Comparisons of gene expression between biological groups for which the adjusted p-values were <0.05 were considered significant

Supplementary Table 6

Gene set analysis THY1- FAPα+ versus THY1+ FAPα+ fibroblasts. Significant differences in GO biological process gene enrichment (Benjamini-Hochberg corrected p value <0.05) comparison between THY1- FAPα+ (n=10 biological replicates) and THY1+ FAPα+ (n=13 biological replicates) cell populations. Biological replicates represent cells sort purified from digested synovia from the hind limbs of a single mouse

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Croft, A.P., Campos, J., Jansen, K. et al. Distinct fibroblast subsets drive inflammation and damage in arthritis. Nature 570, 246–251 (2019). https://doi.org/10.1038/s41586-019-1263-7

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