Medzhitov, R. Origin and physiological roles of inflammation. Nature 454, 428–435 (2008).
Franceschi, C., Garagnani, P., Vitale, G., Capri, M. & Salvioli, S. Inflammaging and ‘Garb-aging’. Trends Endocrinol. Metab. 28, 199–212 (2017).
Hotamisligil, G. S. Inflammation and metabolic disorders. Nature 444, 860–867 (2006).
Furman, D. et al. Chronic inflammation in the etiology of disease across the life span. Nat. Med. 25, 1822–1832 (2019).
Ferrucci, L. & Fabbri, E. Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty. Nat. Rev. Cardiol. 15, 505–522 (2018).
Deretic, V. Autophagy in inflammation, infection, and immunometabolism. Immunity 54, 437–453 (2021).
Cadwell, K. Crosstalk between autophagy and inflammatory signalling pathways: balancing defence and homeostasis. Nat. Rev. Immunol. 16, 661–675 (2016).
Levine, B., Mizushima, N. & Virgin, H. W. Autophagy in immunity and inflammation. Nature 469, 323–335 (2011).
Deretic, V. Autophagy as an innate immunity paradigm: expanding the scope and repertoire of pattern recognition receptors. Curr. Opin. Immunol. 24, 21–31 (2012).
Mochida, K. et al. Receptor-mediated selective autophagy degrades the endoplasmic reticulum and the nucleus. Nature 522, 359–362 (2015).
Dou, Z. et al. Autophagy mediates degradation of nuclear lamina. Nature 527, 105–109 (2015).
Liu, H. et al. VAMP2 controls murine epidermal differentiation and carcinogenesis by regulation of nucleophagy. Dev. Cell 59, 2005–2016 (2024).
Xu, C. et al. SIRT1 is downregulated by autophagy in senescence and ageing. Nat. Cell Biol. 22, 1170–1179 (2020).
Papandreou, M.-E., Konstantinidis, G. & Tavernarakis, N. Nucleophagy delays aging and preserves germline immortality. Nat Aging 3, 34–46 (2023).
Zhao, H. et al. Destabilizing heterochromatin by APOE mediates senescence. Nat Aging 2, 303–316 (2022).
Lamark, T. & Johansen, T. Mechanisms of selective autophagy. Annu. Rev. Cell Dev. Biol. 37, 143–169 (2021).
Behrends, C., Sowa, M. E., Gygi, S. P. & Harper, J. W. Network organization of the human autophagy system. Nature 466, 68–76 (2010).
Mizushima, N., Yamamoto, A., Matsui, M., Yoshimori, T. & Ohsumi, Y. In vivo analysis of autophagy in response to nutrient starvation using transgenic mice expressing a fluorescent autophagosome marker. Mol. Biol. Cell 15, 1101–1111 (2004).
Clapier, C. R., Iwasa, J., Cairns, B. R. & Peterson, C. L. Mechanisms of action and regulation of ATP-dependent chromatin-remodelling complexes. Nat. Rev. Mol. Cell Biol. 18, 407–422 (2017).
Campisi, J. Cellular senescence: putting the paradoxes in perspective. Curr. Opin. Genet. Dev. 21, 107–112 (2011).
Dou, Z. et al. Cytoplasmic chromatin triggers inflammation in senescence and cancer. Nature 550, 402–406 (2017).
Bozhenok, L., Wade, P. A. & Varga-Weisz, P. WSTF-ISWI chromatin remodeling complex targets heterochromatic replication foci. EMBO J. 21, 2231–2241 (2002).
Corona, D. F. et al. ISWI is an ATP-dependent nucleosome remodeling factor. Mol. Cell 3, 239–245 (1999).
Yadon, A. N. & Tsukiyama, T. SnapShot: chromatin remodeling: ISWI. Cell 144, 453–453 (2011).
Rodier, F. et al. Persistent DNA damage signalling triggers senescence-associated inflammatory cytokine secretion. Nat. Cell Biol. 11, 973–979 (2009).
Paull, T. T. Mechanisms of ATM activation. Annu. Rev. Biochem. 84, 711–738 (2015).
Xiao, A. et al. WSTF regulates the H2A.X DNA damage response via a novel tyrosine kinase activity. Nature 457, 57–62 (2009).
Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).
Chien, Y. et al. Control of the senescence-associated secretory phenotype by NF-κB promotes senescence and enhances chemosensitivity. Genes Dev. 25, 2125–2136 (2011).
Kang, T.-W. et al. Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature 479, 547–551 (2011).
Nusinow, D. P. et al. Quantitative proteomics of the Cancer Cell Line Encyclopedia. Cell 180, 387–402 (2020).
Pezone, A. et al. Inflammation and DNA damage: cause, effect or both. Nat. Rev. Rheumatol. 19, 200–211 (2023).
Lewis, H. D. et al. Creation of a novel peptide with enhanced nuclear localization in prostate and pancreatic cancer cell lines. BMC Biotechnol. 10, 79 (2010).
Brunt, E. M. Pathology of nonalcoholic fatty liver disease. Nat. Rev. Gastroenterol. Hepatol. 7, 195–203 (2010).
Brown, G. T. & Kleiner, D. E. Histopathology of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Metabolism 65, 1080–1086 (2016).
Michelotti, G. A. et al. Smoothened is a master regulator of adult liver repair. J. Clin. Invest. 123, 2380–2394 (2013).
Syn, W.-K. et al. Hedgehog-mediated epithelial-to-mesenchymal transition and fibrogenic repair in nonalcoholic fatty liver disease. Gastroenterology 137, 1478–1488 (2009).
Du, K. et al. Increased glutaminolysis marks active scarring in nonalcoholic steatohepatitis progression. Cell Mol. Gastroenterol. Hepatol. 10, 1–21 (2020).
Hansen, H. H. et al. Human translatability of the GAN diet-induced obese mouse model of non-alcoholic steatohepatitis. BMC Gastroenterol. 20, 210 (2020).
Woodell-May, J. E. & Sommerfeld, S. D. Role of inflammation and the immune system in the progression of osteoarthritis. J. Orthop. Res. 38, 253–257 (2020).
Robinson, W. H. et al. Low-grade inflammation as a key mediator of the pathogenesis of osteoarthritis. Nat. Rev. Rheumatol. 12, 580–592 (2016).
Glasson, S. S., Blanchet, T. J. & Morris, E. A. The surgical destabilization of the medial meniscus (DMM) model of osteoarthritis in the 129/SvEv mouse. Osteoarthritis Cartilage 15, 1061–1069 (2007).
Glasson, S. S., Chambers, M. G., Van Den Berg, W. B. & Little, C. B. The OARSI histopathology initiative—recommendations for histological assessments of osteoarthritis in the mouse. Osteoarthritis Cartilage 18, S17–S23 (2010).
Sherwood, J. C., Bertrand, J., Eldridge, S. E. & Dell’Accio, F. Cellular and molecular mechanisms of cartilage damage and repair. Drug Discov. Today 19, 1172–1177 (2014).
Wang, Y. et al. Nuclear autophagy interactome unveils WSTF as a constitutive nuclear inhibitor of inflammation. Preprint at bioRxiv https://doi.org/10.1101/2022.10.04.510822 (2022).
Chen Lf, Fischle, W., Verdin, E. & Greene, W. C. Duration of nuclear NF-kappaB action regulated by reversible acetylation. Science 293, 1653–1657 (2001).
Murley, A. & Dillin, A. Macroautophagy in quiescent and senescent cells: a pathway to longevity? Trends Cell Biol. 33, 495–504 (2023).
Kaur, J. & Debnath, J. Autophagy at the crossroads of catabolism and anabolism. Nat. Rev. Mol. Cell Biol. 16, 461–472 (2015).
Vizioli, M. G. et al. Mitochondria-to-nucleus retrograde signaling drives formation of cytoplasmic chromatin and inflammation in senescence. Genes Dev. 34, 428–445 (2020).
Kundakovic, M. et al. Practical guidelines for high-resolution epigenomic profiling of nucleosomal histones in postmortem human brain tissue. Biol. Psychiatry 81, 162–170 (2017).
Bai, B. et al. Deep profiling of proteome and phosphoproteome by isobaric labeling, extensive liquid chromatography, and mass spectrometry. Methods Enzymol. 585, 377–395 (2017).
Xu, P., Duong, D. M. & Peng, J. Systematical optimization of reverse-phase chromatography for shotgun proteomics. J. Proteome Res. 8, 3944–3950 (2009).
Pagala, V. R. et al. Quantitative protein analysis by mass spectrometry. Methods Mol. Biol. 1278, 281–305 (2015).
Niu, M. et al. Extensive peptide fractionation and y ion-based interference detection method for enabling accurate quantification by isobaric labeling and mass spectrometry. Anal. Chem. 89, 2956–2963 (2017).
Wang, H. et al. Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome. J. Proteome Res. 14, 829–838 (2015).
Wang, X. et al. JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol. Cell. Proteomics 13, 3663–3673 (2014).
Li, Y. et al. JUMPg: an integrative proteogenomics pipeline identifying unannotated proteins in human brain and cancer cells. J. Proteome Res. 15, 2309–2320 (2016).
Shi, H. et al. Amino acids license kinase mTORC1 activity and Treg cell function via small G proteins Rag and Rheb. Immunity 51, 1012–1027 (2019).
Peng, J., Elias, J. E., Thoreen, C. C., Licklider, L. J. & Gygi, S. P. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J. Proteome Res. 2, 43–50 (2003).
Nesvizhskii, A. I. & Aebersold, R. Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics 4, 1419–1440 (2005).
Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41, 1313–1321 (2005).
Stringer, C., Wang, T., Michaelos, M. & Pachitariu, M. Cellpose: a generalist algorithm for cellular segmentation. Nat. Methods 18, 100–106 (2021).
Carpenter, A. E. et al. CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7, R100 (2006).
McQuin, C. et al. CellProfiler 3.0: next-generation image processing for biology. PLoS Biol. 16, e2005970 (2018).
Kamekura, S. et al. Osteoarthritis development in novel experimental mouse models induced by knee joint instability. Osteoarthritis Cartilage 13, 632–641 (2005).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).
Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).
Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).
Freund, A., Orjalo, A. V., Desprez, P.-Y. & Campisi, J. Inflammatory networks during cellular senescence: causes and consequences. Trends Mol. Med. 16, 238–246 (2010).
Babicki, S. et al. Heatmapper: web-enabled heat mapping for all. Nucleic Acids Res. 44, W147–W153 (2016).
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
John, S. et al. Chromatin accessibility pre-determines glucocorticoid receptor binding patterns. Nat. Genet. 43, 264–268 (2011).
Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012).
An, H. et al. TEX264 is an endoplasmic reticulum-resident ATG8-interacting protein critical for ER remodeling during nutrient stress. Mol. Cell 74, 891–908 (2019).
Paulo, J. A., Mancias, J. D. & Gygi, S. P. Proteome-wide protein expression profiling across five pancreatic cell lines. Pancreas 46, 690–698 (2017).
McAlister, G. C. et al. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 86, 7150–7158 (2014).
Huttlin, E. L. et al. A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143, 1174–1189 (2010).
Paulo, J. A., Gaun, A. & Gygi, S. P. Global analysis of protein expression and phosphorylation levels in nicotine-treated pancreatic stellate cells. J. Proteome Res. 14, 4246–4256 (2015).
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
Chen, H. et al. cGAS suppresses genomic instability as a decelerator of replication forks. Sci. Adv. 6, eabb8941 (2020).
Kirkin, V. et al. A role for NBR1 in autophagosomal degradation of ubiquitinated substrates. Mol. Cell 33, 505–516 (2009).
Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N. & Sternberg, M. J. E. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 10, 845–858 (2015).
Kim, E. Y. et al. Structures of CaV2 Ca2+/CaM-IQ domain complexes reveal binding modes that underlie calcium-dependent inactivation and facilitation. Structure 16, 1455–1467 (2008).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Varadi, M. et al. AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. 50, D439–D444 (2022).
Kozakov, D. et al. The ClusPro web server for protein-protein docking. Nat. Protoc. 12, 255–278 (2017).