Fibrosis is a common pathological feature of chronic disease. Deletion of the NF-κB subunit c-Rel limits fibrosis in multiple organs, although the mechanistic nature of this protection is unresolved. Using cell-specific gene-targeting manipulations in mice undergoing liver damage, we elucidate a critical role for c-Rel in controlling metabolic changes required for inflammatory and fibrogenic activities of hepatocytes and macrophages and identify Pfkfb3 as the key downstream metabolic mediator of this response. Independent deletions of Rel in hepatocytes or macrophages suppressed liver fibrosis induced by carbon tetrachloride, while combined deletion had an additive anti-fibrogenic effect. In transforming growth factor-β1-induced hepatocytes, c-Rel regulates expression of a pro-fibrogenic secretome comprising inflammatory molecules and connective tissue growth factor, the latter promoting collagen secretion from HMs. Macrophages lacking c-Rel fail to polarize to M1 or M2 states, explaining reduced fibrosis in RelΔLysM mice. Pharmacological inhibition of c-Rel attenuated multi-organ fibrosis in both murine and human fibrosis. In conclusion, activation of c-Rel/Pfkfb3 in damaged tissue instigates a paracrine signalling network among epithelial, myeloid and mesenchymal cells to stimulate fibrogenesis. Targeting the c-Rel–Pfkfb3 axis has potential for therapeutic applications in fibrotic disease.
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Wynn, T. A. & Ramalingam, T. R. Mechanisms of fibrosis: therapeutic translation for fibrotic disease. Nat. Med. 18, 1028–1040 (2012).
Rockey, D. C., Bell, P. D. & Hill, J. A. Fibrosis—a common pathway to organ injury and failure. N. Engl. J. Med. 373, 95–96 (2015).
Bataller, R. & Brenner, D. A. Liver fibrosis. J. Clin. Invest. 115, 209–218 (2005).
Friedman, S. L. Liver fibrosis—from bench to bedside. J. Hepatol. 38, 38–53 (2003).
Cox, T. R. & Erler, J. T. Molecular pathways: connecting fibrosis and solid tumor metastasis. Clin. Cancer Res. 20, 3637–3643 (2014).
Cernaro, V. et al. Fibrosis, regeneration and cancer: what is the link? Nephrol. Dial. Transplant. 27, 21–27 (2012).
Rybinski, B., Franco-Barraza, J. & Cukierman, E. The wound healing, chronic fibrosis and cancer progression triad. Physiol. Genomics 46, 223–244 (2014).
Klingler, W., Jurkat-Rott, K., Lehmann-Horn, F. & Schleip, R. The role of fibrosis in Duchenne muscular dystrophy. Acta Myol. 31, 184–195 (2012) http://www.ncbi.nlm.nih.gov/pubmed/23620650 http://www.ncbi.nlm.nih.gov/pubmed/23620650.
Torres, V. E. & Leof, E. B. Fibrosis, regeneration, and aging: playing chess with evolution. J. Am. Soc. Nephrol. 22, 1393–1396 (2011).
Hecker, L. et al. Reversal of persistent fibrosis in aging by targeting Nox4–Nrf2 redox imbalance. Sci. Transl. Med. 6, 231ra47 (2014).
Mehal, W. Z., Iredale, J. & Friedman, S. L. Scraping fibrosis: expressway to the core of fibrosis. Nat. Med. 17, 552–553 (2011).
Wynn, T. Cellular and molecular mechanisms of fibrosis. J. Pathol. 214, 199–210 (2008).
Koyama, Y. & Brenner, D. A. Liver inflammation and fibrosis. J. Clin. Invest. 127, 55–64 (2017).
Hayden, M. S. & Ghosh, S. NF-κB, the first quarter-century: remarkable progress and outstanding questions. Genes Dev. 26, 203–234 (2012).
Oeckinghaus, A. & Ghosh, S. The NF-κB family of transcription factors and its regulation. Cold Spring Harb. Perspect. Biol. 1, a000034 (2009).
Lawrence, T. The nuclear factor NF-κB pathway in inflammation. Cold Spring Harb. Perspect. Biol. 1, a001651 (2009).
Tak, P. P. & Firestein, G. S. NF-κB: a key role in inflammatory diseases. J. Clin. Invest. 107, 7–11 (2001).
Zhang, Q., Lenardo, M. J. & Baltimore, D. 30 years of NF-κB: a blossoming of relevance to human pathobiology. Cell 168, 37–57 (2017).
Luedde, T. & Schwabe, R. F. NF-κB in the liver—linking injury, fibrosis and hepatocellular carcinoma. Nat. Rev. Gastroenterol. Hepatol. 8, 108–118 (2011).
Perkins, N. D. & Gilmore, T. D. Good cop, bad cop: the different faces of NF-κB. Cell Death Differ. 13, 759–772 (2006).
Piva, R., Belardo, G. & Santoro, M. G. NF-κB: a stress-regulated switch for cell survival. Antioxid. Redox Signal. 8, 478–486 (2006).
Wong, D. et al. Extensive characterization of NF-κB binding uncovers non-canonical motifs and advances the interpretation of genetic functional traits. Genome Biol. 12, R70 (2011).
Geisler, F., Algül, H., Paxian, S. & Schmid, R. M. Genetic inactivation of RelA/p65 sensitizes adult mouse hepatocytes to TNF-induced apoptosis in vivo and in vitro. Gastroenterology 132, 2489–2503 (2007).
Rosenfeld, M. E., Prichard, L., Shiojiri, N. & Fausto, N. Prevention of hepatic apoptosis and embryonic lethality in RelA/TNFR-1 double knockout mice. Am. J. Pathol. 156, 997–1007 (2000).
Beg, A. A., Sha, W. C., Bronson, R. T., Ghosh, S. & Baltimore, D. Embryonic lethality and liver degeneration in mice lacking the RelA component of NF-κB. Nature 376, 167–170 (1995).
Lenardo, M. J. & Baltimore, D. NF-κB: a pleiotropic mediator of inducible and tissue-specific gene control. Cell 58, 227–229 (1989).
Fullard, N., Wilson, C. L. & Oakley, F. Roles of c-Rel signalling in inflammation and disease. Int. J. Biochem. Cell Biol. 44, 851–860 (2012).
Neo, W. H., Lim, J. F., Grumont, R., Gerondakis, S. & Su, I. c-Rel regulates Ezh2 expression in activated lymphocytes and malignant lymphoid cells. J. Biol. Chem. 289, 31693–31707 (2014).
Zeybel, M. et al. A proof-of-concept for epigenetic therapy of tissue fibrosis: inhibition of liver fibrosis progression by 3-deazaneplanocin A. Mol. Ther. 25, 218–231 (2017).
Fullard, N. et al. The c-Rel subunit of NF-κB regulates epidermal homeostasis and promotes skin fibrosis in mice. Am. J. Pathol. 182, 2109–2120 (2013).
Gaspar-Pereira, S. et al. The NF-κB Subunit c-Rel stimulates cardiac hypertrophy and fibrosis. Am. J. Pathol. 180, 929–939 (2012).
Luli, S. et al. A new fluorescence-based optical imaging method to non-invasively monitor hepatic myofibroblasts in vivo. J. Hepatol. 65, 75–83 (2016).
Hunter, J. E., Leslie, J. & Perkins, N. D. C-Rel and its many roles in cancer: an old story with new twists. Br. J. Cancer. 114, 1–6 (2016).
Schwabe, R. F., Tabas, I. & Pajvani, U. B. Mechanisms of fibrosis development in nonalcoholic steatohepatitis. Gastroenterology 158, 1913–1928 (2020).
Swamy, M., Jamora, C., Havran, W. & Hayday, A. Epithelial decision makers: in search of the ‘epimmunome’. Nat. Immunol. 11, 656–665 (2010).
Duffield, J. S. et al. Selective depletion of macrophages reveals distinct, opposing roles during liver injury and repair. J. Clin. Invest. 115, 56–65 (2005).
Seki, E. et al. CCR2 promotes hepatic fibrosis in mice. Hepatology 50, 185–197 (2009).
Wynn, T. A. & Vannella, K. M. Macrophages in tissue repair, regeneration and fibrosis. Immunity 44, 450–462 (2016).
Garcia-Lazaro, J. F. et al. Hepatic over-expression of TGF-β1 promotes LPS-induced inflammatory cytokine secretion by liver cells and endotoxemic shock. Immunol. Lett. 101, 217–222 (2005).
Yang, L. et al. Transforming growth factor-β signaling in hepatocytes promotes hepatic fibrosis and carcinogenesis in mice with hepatocyte-specific deletion of TAK1. Gastroenterology 144, 1042–1054 (2013).
Bird, T. G. et al. TGF-β inhibition restores a regenerative response in acute liver injury by suppressing paracrine senescence. Sci. Transl. Med. 10, eaan1230 (2018).
Niu L., et al. Involvement of TGF-β1/Smad3 signaling in carbon tetrachloride-induced acute liver injury in mice. PLoS ONE 11, e0156090 (2016).
Travis, M. A. & Sheppard, D. TGF-β activation and function in immunity. Annu Rev. Immunol. 32, 51–82 (2014).
Grgurevic, L. et al. Systemic inhibition of BMP1-3 decreases progression of CCl4-induced liver fibrosis in rats. Growth Factors 35, 201–215 (2017).
Lipson, K. E., Wong, C., Teng, Y. & Spong, S. CTGF is a central mediator of tissue remodeling and fibrosis and its inhibition can reverse the process of fibrosis. Fibrogenesis Tissue Repair 5, S24 (2012).
Fox, C. et al. Inhibition of lysosomal protease cathepsin D reduces renal fibrosis in murine chronic kidney disease. Sci Rep. 6, 20101 (2016).
Moles, A., Tarrats, N., Fernández-Checa, J. C. & Marí, M. Cathepsins B and D drive hepatic stellate cell proliferation and promote their fibrogenic potential. Hepatology 49, 1297–1307 (2009).
Ghosh, A. K. & Vaughan, D. E. PAI-1 in tissue fibrosis. J. Cell. Physiol. 227, 493–507 (2012).
Kodama, T. et al. Increases in p53 expression induce CTGF synthesis by mouse and human hepatocytes and result in liver fibrosis in mice. J. Clin. Invest. 121, 3343–3356 (2011).
Mathieu, J. & Ruohola-Baker, H. Metabolic remodeling during the loss and acquisition of pluripotency. Development 144, 541–551 (2017).
Sciacovelli, M. & Frezza, C. Metabolic reprogramming and epithelial-to-mesenchymal transition in cancer. FEBS J. 284, 3132–3144 (2017).
Nieto, M. A., Huang, R. Y.-J., Jackson, R. A. & Thiery, J. P. EMT: 2016. Cell 166, 21–45 (2016).
Kelly, B. & O’Neill, L. A. Metabolic reprogramming in macrophages and dendritic cells in innate immunity. Cell Res. 25, 771–784 (2015).
Taura, K. et al. Hepatocytes do not undergo epithelial–mesenchymal transition in liver fibrosis in mice. Hepatology 51, 1027–1036 (2010).
Humphreys, B. D. et al. Fate tracing reveals the pericyte and not epithelial origin of myofibroblasts in kidney fibrosis. Am. J. Pathol. 176, 85–97 (2010).
Grande, M. T. et al. Snail1-induced partial epithelial-to-mesenchymal transition drives renal fibrosis in mice and can be targeted to reverse established disease. Nat. Med. 21, 989–997 (2015).
Rowe, R. G. et al. Hepatocyte-derived Snail1 propagates liver fibrosis progression. Mol. Cell. Biol. 31, 2392–2403 (2011).
Hee Kim, N. et al. Snail reprograms glucose metabolism by repressing phosphofructokinase PFKP allowing cancer cell survival under metabolic stress. Nat. Commun. 8, 14374 (2017).
Mills, E. L. & O’Neill, L. A. Reprogramming mitochondrial metabolism in macrophages as an anti-inflammatory signal. Eur. J. Immunol. 46, 13–21 (2016).
Gieling, R. G. et al. The c-Rel subunit of NF-κB regulates murine liver inflammation, wound healing and hepatocyte proliferation. Hepatology 51, 922–931 (2010).
Shono, Y. et al. A small-molecule c-Rel inhibitor reduces alloactivation of T cells without compromising antitumor activity. Cancer Discov. 4, 578–591 (2014).
Paish, H. L. et al. A bioreactor technology for modelling fibrosis in human and rodent precision-cut liver slices. Hepatology 70, 1377–1391 (2019).
Nielsen, M. J. et al. Plasma Pro-C3 (N-terminal type III collagen propeptide) predicts fibrosis progression in patients with chronic hepatitis C. Liver Int. 35, 429–437 (2015).
Krawczyk, C. M. et al. Toll-like receptor-induced changes in glycolytic metabolism regulate dendritic cell activation. Blood 115, 4742–4749 (2010).
Lees, J. G., Gardner, D. K. & Harvey, A. J. Mitochondrial and glycolytic remodeling during nascent neural differentiation of human pluripotent stem cells. Development 145, dev168997 (2018).
Peng, M. et al. Aerobic glycolysis promotes T helper 1 cell differentiation through an epigenetic mechanism. Science 354, 481–484 (2016).
Wei, Q. et al. Glycolysis inhibitors suppress renal interstitial fibrosis via divergent effects on fibroblasts and tubular cells. Am. J. Physiol. Renal Physiol. 316, F1162–F1172 (2018).
Ding, H. et al. Inhibiting aerobic glycolysis suppresses renal interstitial fibroblast activation and renal fibrosis. Am. J. Physiol. Renal Physiol. 313, F561–F575 (2017).
Xie, N. et al. Glycolytic reprogramming in myofibroblast differentiation and lung fibrosis. Am. J. Respir. Crit. Care Med. 92, 1462–1474 (2015).
MacParland, S. A. et al. Single-cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).
Chang, N. et al. Single-cell transcriptomes reveal characteristic features of mouse hepatocytes with liver cholestatic injury. Cells. 8, 1069 (2019).
Huang, G. & Brigstock, D. R. Regulation of hepatic stellate cells by connective tissue growth factor. Front. Biosci. 17, 2495–2507 (2012).
Paradis, V. et al. Effects and regulation of connective tissue growth factor on hepatic stellate cells. Lab Invest. 82, 767–774 (2002).
Gressner, O. A., Lahme, B., Demirci, I., Gressner, A. M. & Weiskirchen, R. Differential effects of TGF-β on connective tissue growth factor (CTGF/CCN2) expression in hepatic stellate cells and hepatocytes. J. Hepatol. 47, 699–710 (2007).
Friedman, S. L. Hepatic stellate cells: protean, multifunctional and enigmatic cells of the liver. Physiol. Rev. 88, 125–172 (2008).
Gressner, O. A. et al. Intracrine signalling of activin A in hepatocytes upregulates connective tissue growth factor (CTGF/CCN2) expression. Liver Int. 28, 1207–1216 (2008).
Fearn, A. et al. The NF-κB1 is a key regulator of acute but not chronic renal injury. Cell Death Dis. 8, e2883 (2017).
Wang, F. et al. NF-κB inhibition alleviates carbon tetrachloride-induced liver fibrosis via suppression of activated hepatic stellate cells. Exp. Ther. Med. 8, 95–99 (2014).
Chan, L. K. et al. Epithelial NEMO/IKK-γ limits fibrosis and promotes regeneration during pancreatitis. Gut 66, 1995–2007 (2017).
Karin, M., Yamamoto, Y. & Wang, Q. M. The IKK NF-κB system: a treasure trove for drug development. Nat. Rev. Drug Discov. 3, 17–26 (2004).
Bennett, J. et al. NF-κB in the crosshairs: rethinking an old riddle. Int. J. Biochem. Cell Biol. 95, 108–112 (2018).
Oakley, F. et al. Inhibition of inhibitor of κB kinases stimulates hepatic stellate cell apoptosis and accelerated recovery from rat liver fibrosis. Gastroenterology 128, 108–120 (2005).
Oakley, F. et al. Angiotensin II activates I κB kinase phosphorylation of RelA at Ser 536 to promote myofibroblast survival and liver fibrosis. Gastroenterology 136, 2334–2344 (2009).
Chen, L.-W. et al. The two faces of IKK and NF-κB inhibition: prevention of systemic inflammation but increased local injury following intestinal ischemia–reperfusion. Nat. Med. 9, 575–581 (2003).
Li, Z.-W. et al. The IKKβ subunit of IκB Kinase (IKK) is essential for nuclear factor κB activation and prevention of apoptosis. J. Exp. Med. 189, 1839–1845 (1999).
Li, Q., Van Antwerp, D., Mercurio, F., Lee, K. F. & Verma, I. M. Severe liver degeneration in mice lacking the IκB kinase 2 gene. Science 284, 321–325 (1999).
Li, Q. & Verma, I. M. NF-κB regulation in the immune system. Nat. Rev. Immunol. 2, 725–734 (2002).
Perkins, N. D. Integrating cell-signalling pathways with NF-κB and IKK function. Nat. Rev. Mol. Cell Biol. 8, 49–62 (2007).
Shono, Y. et al. Characterization of a c-Rel inhibitor that mediates anticancer properties in hematologic malignancies by blocking NF-κB-controlled oxidative stress responses. Cancer Res. 76, 377–389 (2016).
Grinberg-Bleyer, Y. et al. NF-κB c-Rel Is crucial for the regulatory T cell immune checkpoint in cancer. Cell 170, 1096–1108 (2017).
De Bock, K. et al. Role of PFKFB3-driven glycolysis in vessel sprouting. Cell 154, 651–663 (2013).
Heise, N. et al. Germinal center B cell maintenance and differentiation are controlled by distinct NF-κB transcription factor subunits. J. Exp. Med. 211, 2103–2118 (2014).
Mederacke, I. et al. Fate tracing reveals hepatic stellate cells as dominant contributors to liver fibrosis independent of its aetiology. Nat. Commun. 4, 2823 (2013).
Higgins, G. A. & Anderson, R. E. Experimental pathology of liver: restoration of liver in white rat following partial surgical removal. Arch. Pathol. 12, 186–202 (1931).
Oakley, F. et al. Nuclear factor-κB1 (p50) limits the inflammatory and fibrogenic responses to chronic injury. Am. J. Pathol. 166, 695–708 (2005).
This work was funded by a UK Medical Research Council PhD studentship to J.L. and program grants MR/K0019494/1 (to D.A.M., J.M. and F.O.) and MR/R023026/1 (to D.A.M., J.M., L.A.B. and F.O.). An Arthritis Research UK grant (20812) supports F.O., D.A.M., J.L. and J.C.W. A CRUK program grant (C18342/A23390) supports J.L. and D.A.M. The cross-council Lifelong Health and Wellbeing initiative, funded by the MRC (L016354) funds D.A.M. and F.O. C.N. is supported by CRUK Beatson Institute Core funding (A171196). T.G.B. is funded by the Wellcome Trust (WT107492Z) and a CRUK/AECC/AIRC Accelerator Award (A26813). M.Y.W.Z. has a personal Ph.D award from Newton-Mosharafa fund. P.C., L.S. and L.-A.T. are financed by Methusalem funding, FWO, ERC Proof of Concept (ERC-713758) and an Advanced ERC Research Grant (EU-ERC743074). The IVIS spectrum was purchased under a Wellcome Trust Equipment Grant (087961) awarded to D.A.M. and others. We thank the Newcastle University bioimaging unit and the Newcastle University Flow cytometry core facility for technical assistance.
F.O., D.A.M., J.M. and L.A.B. are directors of Fibrofind. J.L., H.P., F.O., D.A.M., J.M. and L.A.B. are shareholders in Fibrofind. C.B.N. is shareholder in GSK. M.K. is a stock owner of Nordic Bioscience.
Peer review information Primary Handling Editor: Christoph Schmitt.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended Data Fig. 1 c-Rel correlates with disease progression in chronic kidney disease and is elevated in chronic lung disease. Investigation of the cell specific actions of c-Rel in preclinical models of liver injury.
a, Graph showing average percentage area of c-Rel stained tissue in (n=5) normal lung and (n=7) chronic obstructive pulmonary disorder (COPD) (P value = 0.0003). b, Graph showing average percentage area of c-Rel stained tissue in (n=5) normal human kidney and patients with stable (n=4, p value =0.0185) or progressive kidney disease (n=8, p value = 0.003). Normal vs progressive p value <0.0001) (c) Graphs showing the Mean Fluorescence Intensity (MFI) of GFP in hepatocytes (p value = 0.0026), Cholangiocytes (EPCAM+, p value = 0.0026) and non-parenchymal (EPCAM-) cells from the livers of Relfl/fl and RelΔAlb mice. Data are mean ± s.e.m of 3 mice/group. d, Heatmap showing gene expression of Cxcl1, Cxcl2, Ccl2, Cxcl9, Cxcl10, Il1b, Il6 and Tnfα in olive oil vehicle control and acute CCl4 injured Relfl/fl and RelΔAlb mice. Asterisk denotes significance between CCl4 injured Relfl/fl and RelΔAlb mice; there is no significant difference between olive oil treated groups. (e) Histological assessment of αSMA, PCNA and CD68 stained liver sections in acute CCl4 injured Relfl/fl and RelΔLrat mice. Data in graphs are mean ± s.e.m of n=5. a, c, e, P values were calculated using unpaired two-sided T test. b, P value was calculated using a one-way ANOVA with Tukey post-hoc t-test (* P <0.05, ** P <0.01, *** P <0.001 and **** P <0.0001).
a, Representative images of c-Rel staining in CCl4 injured Relflfl and RelΔHep mice. Representative of n=7 mice/group. Scale bar represents 100 μm. b, Graph shows mRNA levels of inflammatory cytokines Tnfa, Il-1b (p=0.00038) and Il6 (p value = 0.022)and the inflammatory chemokines Cxcl1 (p value = 0.034), Cxcl2 (p=0.054) and Ccl2 (p=0.029), in CCl4 injured livers of Relfl/fl and RelΔHep mice. Data are mean ± s.e.m of 7 mice/group. c, Heatmap showing relative mRNA expression of Il-6, Cxcl1, Cxcl2, Ccl2, Ccl4 and Ccl5 in WT and Rel−/− proximal tubular epithelial cells (PTEC) stimulated with or without TGFβ1. d, Graphs show relative levels of Ctgf (p value = 0.034), Ctsd (p= 0.039), Serpine1 (p=0.04) and Bmp1 (p=0.0054) protein expressed as Intensity in control and TGFβ1 treated WT and Rel-/- hepatocytes. Data are from 4 independent cell isolations/group. e, Quantification of soluble collagen (pg/ml) released from precision cut liver slices (PCLS) generated from WT and Rel-/- liver, stimulated ± TGFβ1 ± CTGF where (control p value = 0.012 and TGFβ1 p value = 0.045). Data are from PCLS generated 3 different donors/genotype. b, d, P values were calculated using unpaired two-sided t-test. (d) P values were calculated using the R package LIMMA (* P <0.05, ** P <0.01 and ***P<0.001).
Extended Data Fig. 3 c-Rel regulates metabolic enzymes to induce epithelial dedifferentiation and fibrogenic gene expression.
a, Seahorse analysis of basal (p<0.0001) and maximal (p<0.0001) glycolysis (extracellular acidification rate, ECAR) and basal (p<0.0007) and maximal (p<0.0004) mitochondrial respiration (oxygen consumption rate, OCR) in WT and Rel-/- hepatocytes stimulated ± TGFβ1. b, Graph shows mRNA expression of Pfkfb1 in WT and Rel-/- hepatocytes stimulated ± TGFβ1. c, Graph shows mRNA expression of Pfkfb3 in WT and Rel-/- hepatocytes stimulated ± IL-1β. (p value=0.025) (d) Schematic representation of RelA, NF-κB1 and NF-κB binding sites in the murine Pfkfb1 and Pfkfb3 promoters. e, ChIP analysis of c-Rel at the proximal and distal regions of the Pfkfb1 promoter and the proximal (p<0.0001) and distal (p=0.0185) regions of the Pfkfb3 promoter in WT hepatocytes treated ± TGFβ1. f, Representative images show PFKFB3 immunohistochemical staining in liver sections from acute CCl4 injured Pfkfb3flfl and Pfkfb3Δhep mice. Images are representative of n=5 mice/group. Scale bar is 100μm. g, Graphs show media lactate in control and TGFβ1 (p=0.0064) stimulated and glucose levels in control (p=0.0227) and TGFβ1 (p=0.00284) stimulated in hepatocytes isolated from Pfkfb3flfl and Pfkfb3Δhep mice and stimulated ± TGFβ1. h, Heatmap showing secreated Il-6, Cxcl1, Cxcl2, Cxcl10, Ccl2, Ccl3, Ccl4 and Ccl5, measured by MSD in the media of hepatocytes isolated from Pfkfb3flfl and Pfkfb3Δhep mice and stimulated ± TGFβ1. (i) Quantification of connective tissue growth factor (CTGF) in pg/ml in the culture media of hepatocytes isolated from Pfkfb3flfl and Pfkfb3Δhep mice and stimulated ± TGFβ1 (p=0.0027) (j) Heatmap showing secreated Il-6, Cxcl1, Cxcl2, Cxcl10, Ccl2, Ccl3, Ccl4 and Ccl5, measured by MSD in the media of WT hepatocytes stimulated ± TGFβ1 ± the Pfkfb3 inhibitor 3PO. k, Quantification of connective tissue growth factor (CTGF) in pg/ml in the culture media of WT hepatocytes stimulated ± TGFβ1 ± the Pfkfb3 inhibitor 3PO (p=0.0013). Data in graphs are mean ± s.e.m. in n=3 (g, i, k), n=4 (a, b, c) or n=5 (e) independent cell isolations/condition. All p values were calculated using a two-way ANOVA with Tukey post-hoc t-test (* P <0.05, ** P <0.01 and *** P <0.001).
a, Representative images show expression of Snail in normal and chronic CCl4 injured liver. b, Representative images show Snail in normal and UUO injured kidney. c, Representative images of Snail transcript in epithelial cells detected by RNAScope in fibrotic chronic CCl4 injured fibrotic mouse liver. d, Representative images of Snail transcript in epithelial cells detected by RNAScope in fibrotic UUO mouse kidney. All representative images are representative of n=5 mice/group. a, b, Scale bars equal 100 microns (c, d) Scale bars equal 50 microns. e, Graph showing mRNA levels of Snail in TGFβ1 treated hepatocytes (p=0.0001) and proximal tubular epithelial cells (PTEC) (p=0.02) isolated from WT and Rel-/- mice. Data in graphs are mean ± s.e.m. in n=3 independent cell isolations. f, Graph showing ChIP analysis of c-Rel binding to distal (p=0.0074) and proximal (p=0.0063) regions of the Snail promoter in WT hepatocytes stimulated ± TGFβ1. Data in graphs are mean ± s.e.m. in n=5 independent cell isolations. P values were calculated using unpaired two-sided t-test (e) and a ratio paired t-test (f) (* P <0.05, ** P <0.01 and *** P <0.001).
a, Histological assessment and representative images of αSMA stained liver sections in acute CCl4 injured in (n=13) Relflfl, (n=7) RelΔAlb (p=0.0116), and (n=10) RelΔLysM (p=0.0051) mice. Data are mean ± s.e.m. Scale bar equals 100 microns. P values were calculated using a one-way ANOVA with Tukey post- hoc t-test. b, Representative low power immuno-fluorescence images show c-Rel (red), CD68 (green) and nuclear (blue) staining in diagnosed idiopathic pulmonary fibrosis lung sections. Yellow arrows denote co-localisaton of c-Rel and CD68. Scale bar equals 50 microns. Images are representative of n=8 IPF stained sections. (c) Heat map showing relative mRNA expression of fibrogenic markers; Tgfb1, Tgfb2, Tgfb3, TIMP1, Fn1, Pdgfa, Pdgfb, Mmp3, Mmp9 and Mmp13 in M1 and M2 polarised WT and Rel-/- BMDMs. d, Graphs show, seahorse analysis of basal (p<0.0001) and maximal (p=0.0004) glycolysis (extracellular acidification rate, ECAR) and basal (p=0.0002) and maximal (p=0.0024) mitochondrial respiration (oxygen consumption rate, OCR) in M1 and M2 polarised WT and Rel-/- BMDMs. Data are mean ± s.e.m. from 3 independent cell isolations/group. e, ChIP analysis of c-Rel binding to distal and proximal (p=0.0004) regions of the Pfkfb3 promoter and to distal and proximal (p=0.003) regions of the Pfkfb1 promoters in WT BMDM in response to M1 and M2 polarisation. Data are mean ± s.e.m. from 3 independent cell isolations/group. d-e, P values were calculated using two-way ANOVA with Tukey post-hoc t-test. Denoted significance refers to comparisons between WT and Rel-/- macrophages polarised to either an M1 or M2 phenotype. f, Volcano plots show differentially expressed proteins detected by proteomic analysis of the secretome of M0, M1 and M2 polarised WT and Rel-/- BMDMs. g, Graphs show relative levels of Galectin 1 (p=0.031), Galectin 3 (p=0.013), Vimentin (p=0.0128) and Matrix Metalloproteinase 12 (MMP12) (p<0.001) expressed as Intensity x108 in M0, M1 and M2 polarised WT and Rel-/- BMDMs. Data are mean ± s.e.m. from 4 independent cell isolations/group generated 4 different donors/genotype. P values were calculated using the R package LIMMA (* P <0.05, ** P <0.01 and *** P <0.001).
Extended Data Fig. 6 Validation of epithelial specific deletion of c-Rel in kidney and lung fibrosis models.
a, Flow cytometry gating strategy to identify immune cells (CD45+), epithelial cells (EPCAM+) and endothelial cells (CD31+) isolated from the kidney or lungs of Relflfl, RelΔTEC or RelΔAEC mice respectively. b-c, Ex vivo images of GFP fluorescence signal in the left and right kidneys, heart, liver, lungs and spleen of RelΔTEC mice (b) or RelΔAEC mice (c) imaged using an In Vivo Imaging System (IVIS). Graph and flow cytometry histograms show the Mean Fluorescence Intensity (MFI) of GFP in EpCAM+, CD31+, CD45+ and EpCAM-CD31-CD45- cells from the kidney of RelΔTEC and Relfl/fl control mice (b) or from the lung of RelΔAEC and Relfl/fl control mice (c), n=5 mice/group. d, Heatmap showing mRNA levels of Tgfb1, Col1a1, Col1a2, Acta2 and Timp1 in control versus UUO kidney of Relflfl, RelΔTEC and RelΔLysM mice (left) or control versus bleomycin lung of Relflfl, RelΔAEC and RelΔLysM mice (right). Heatmap data are from 2 mice/group in control kidney or lung and 5 mice/group in the injured kidney or lung. e, Quantification of hydroxyproline levels in nM per left lobe of lung tissue from bleomycin injured in Relflfl, RelΔAEC (p=0.0105), and RelΔLysM (p=0.0006) mice. f, Histological assessment and representative images of TUNEL stained lung sections in day 3 bleomycin injured in Relflfl, RelΔAEC, and RelΔLysM mice. Scale bar is 50 microns. Data are mean ± s.e.m. in n=5 mice/group. g, Quantification of neutrophil numbers in UUO injured kidneys of Relflfl, RelΔTEC (p=0.0014) and RelΔLysM (p<0.0001) mice and macrophage numbers in UUO injured kidneys of Relflfl, RelΔTEC (p=0.00045) and RelΔLysM (p=0.0004) mice. h, Quantification of neutrophil numbers in Bleomycin injured lungs of Relflfl, RelΔAEC and RelΔLysM mice and macrophage numbers in Bleomycin injured lungs of Relflfl, RelΔAEC (p=0.0018) and RelΔLysM (p=0.0327) mice. e, g, h, Data are mean ± s.e.m. in a minimum of 7 mice/group for the kidney and 10 mice/group for the lung. P values were calculated using one-way ANOVA with Tukey post-hoc t-test (* P <0.05, **P <0.01 and ***P <0.001).
Extended Data Fig. 7 Validation of single myeloid or dual hepatocyte- and myeloid- specific deletion of c-Rel in mice and analysis of fibrogenic gene expression in these mice during chronic liver injury.
a, Flow cytometry plot and graphs show the Mean Fluorescence Intensity (MFI) of GFP expression in hepatocytes, macrophages (CD45+F4/80+CD11b+) (p=0.011), T-cells (CD45+CD3+) and non-parenchymal cells (CD45-) from the liver of Relflfl versus RelΔLysM mice, n=3 mice/group. b, Flow cytometry plot and graphs show the Mean Fluorescence Intensity (MFI) of GFP expression in hepatocytes (p=0.007), macrophages (CD45+F4/80+CD11b+) (p=0.007), T-cells (CD45+CD3+) and non-parenchymal cells (CD45-) from the liver of Relflfl versus RelΔHep/ΔLysM mice, n=3 mice/group. (c) Heatmap showing mRNA levels of Tgfb1, Col1a1, Col1a2, Acta2 and Timp1 in the CCl4 injured liver of Relflfl, RelΔHep, RelΔLysM and RelΔHep/ΔLysM mice. P values were calculated using two-sided t-test (* P <0.05).
Extended Data Fig. 8 c-Rel signaling in hepatocyte and macrophages differentially regulate liver regeneration via regulation of cell cycle genes and mitogenic factors.
a, Histological assessment and representative images of PCNA positive hepatocytes in 48h partial hepatectomy injured Relflfl, RelΔAlb (p=0.0003) and RelΔLysM (p=0.0096) mice. Scale bar is 100 microns. b, Graph shows average liver/body weight ratio 48h post partial hepatectomy in Relflfl, RelΔAlb (p=0.0318) and RelΔLysM (p=0.0178) mice. c, Heat map showing relative hepatic mRNA expression of cell cycle genes; Ccna1, Ccnd1, Ccne1, Cdk2, Cdk4 and mitogenic proteins; Hgf and Egf at 48h post partial hepatectomy in Relflfl, RelΔAlb and RelΔLysM mice. Data are mean ± s.e.m. in n=5 mice/group. P values were calculated using one-way ANOVA with Tukey post-hoc t-test (* P <0.05 and ** P <0.01).
a, U937 cells stably expressing 3xNF-κB-Luc reporter were transiently transfected with RelA or c-Rel expression plasmids. Graph shows RelA and c-Rel induced NF-κB luciferase reporter activity ± IT-603 therapy. Data are mean ± s.e.m. P value = 0.00039. P value was calculated using an unpaired two-sided t-test (***P<0.001) of 3 independent experiments. b, c, Histological quantification of αSMA stained kidney (p=0.0004) or lungs (p=0.009) following their respective injury. Data are mean ± s.e.m. in 7 and 10 mice/group for kidney and lung respectively. P values were calculated using an unpaired two-sided t-test. d, Histological quantification of αSMA stained chronic MCD diet injured livers at 2 weeks (pre-treatment) and 5 weeks ± therapeutic administration of IT-603 (p=0.0044). e, Graphs showing relative hepatic expression of the fibrogenic genes; Tgfb1 (p=0.039), Acta2 (p=0.028), Col1a1 (p=0.036), Col1a2, and Timp1(p=0.015) in 2-week (pre-treatment) and 5-week methionine choline deficient diet (MCD) fed mice ± therapeutic administration of IT-603. Data are mean ± s.e.m. in n=4 control mice 8 vehicle and n=7 IT-603 treated mice/group. f, Histological quantification of αSMA stained chronic CCl4 injured livers at 3 weeks (pre-treatment) or 8 weeks ± therapeutic administration of IT-603 (p=0.0105). g, Graphs showing relative hepatic expression of the fibrogenic genes; Tgfb1 (p=0.029), Acta2 (p=0.032), Col1a1 (p=0.04), Col1a2 (p=0.016), and Timp1 (p=0.09) in chronic CCl4 injured livers at 3 week (pre-treatment), 8 week and ± therapeutic administration of IT-603 (from weeks 3-8). Data are mean ± s.e.m. in n=4 control mice 7 experimental mice/group. c, e, P values were calculated using one-way ANOVA with Tukey post-hoc t-test. d, f, P values were calculated using two-way ANOVA with Tukey post-hoc t-test (*P<0.05, ***P<0.001).
Extended Data Fig. 10 IT-603 attenuates fibrosis in ex vivo human tissues slice models of liver and kidney fibrosis.
a, Diagrams show the experimental timelines of TGFβ1 induced fibrosis in ex vivo normal human liver and kidney precision cut slices (PCS). b, Representative images of CD68 stained liver and kidney tissue slices. c, Representative images and histological quantification of Picrosirius red stained fibrotic kidney slices ± IT-603 therapy (p<0.0001). Representative images and histological quantification of αSMA stained fibrotic kidney slices ± IT-603 therapy (p<0.0001). Red line denotes the value for the T=0 slice. e, Quantification of soluble collagen released from fibrotic kidney slices ± IT-603 therapy (p=0.0015). f, Quantification of the neo-epitope pro C3 released from fibrotic kidney slices ± IT-603 therapy (p=0.0493). g, Graph showing average LDH release in the media expressed as a percentage (%) of positive control (LDH levels in media from a PCS where maximal death was induced by multiple freeze/thaws – normalized to media volume). (IT-603 p=0.023 and IT-603+TGFβ1 p=0.02). Images representative of n=3 independent slice experiments. Data are mean ± s.e.m. and representative of slices generated from 3 independent donors performed in duplicate. Scale bars equal 100 microns. P values were calculated using two-way ANOVA with Tukey post- hoc t-test (*P<0.05, **P<0.01, ***P<0.001 and ****P<0.0001).
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Leslie, J., Macia, M.G., Luli, S. et al. c-Rel orchestrates energy-dependent epithelial and macrophage reprogramming in fibrosis. Nat Metab 2, 1350–1367 (2020). https://doi.org/10.1038/s42255-020-00306-2
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