A Treg

Blog

HomeHome / Blog / A Treg

Oct 12, 2023

A Treg

Nature Aging (2023)Cite this

Nature Aging (2023)Cite this article

2 Altmetric

Metrics details

Regulatory T (Treg) cells modulate several aging-related liver diseases. However, the molecular mechanisms regulating Treg function in this context are unknown. Here we identified a long noncoding RNA, Altre (aging liver Treg-expressed non-protein-coding RNA), which was specifically expressed in the nucleus of Treg cells and increased with aging. Treg-specific deletion of Altre did not affect Treg homeostasis and function in young mice but caused Treg metabolic dysfunction, inflammatory liver microenvironment, liver fibrosis and liver cancer in aged mice. Depletion of Altre reduced Treg mitochondrial integrity and respiratory capacity, and induced reactive oxygen species accumulation, thus increasing intrahepatic Treg apoptosis in aged mice. Moreover, lipidomic analysis identified a specific lipid species driving Treg aging and apoptosis in the aging liver microenvironment. Mechanistically, Altre interacts with Yin Yang 1 to orchestrate its occupation on chromatin, thereby regulating the expression of a group of mitochondrial genes, and maintaining optimal mitochondrial function and Treg fitness in the liver of aged mice. In conclusion, the Treg-specific nuclear long noncoding RNA Altre maintains the immune-metabolic homeostasis of the aged liver through Yin Yang 1-regulated optimal mitochondrial function and the Treg-sustained liver immune microenvironment. Thus, Altre is a potential therapeutic target for the treatment of liver diseases affecting older adults.

This is a preview of subscription content, access via your institution

Access Nature and 54 other Nature Portfolio journals

Get Nature+, our best-value online-access subscription

$29.99 / 30 days

cancel any time

Subscribe to this journal

Receive 12 digital issues and online access to articles

$119.00 per year

only $9.92 per issue

Rent or buy this article

Get just this article for as long as you need it

$39.95

Prices may be subject to local taxes which are calculated during checkout

All data needed to evaluate the conclusions in this article are present in the paper or the supplementary materials (or both). The bulk RNA-seq data generated in this study are available at the Gene Expression Omnibus (accession nos. GSE227799, GSE227837, GSE229374 and GSE227838). The Nanopore long-read sequencing data are available from the Genome Sequence Archive (https://bigd.big.ac.cn/gsa/browse/) under accession no. CRA010415. The MS proteomics data are available via the PRIDE database (http://www.proteomexchange.org) under accession no. PXD041040. The loxP Altre mouse strain can be provided by H.-B.L. pending scientific review and a completed materials transfer agreement. Requests for those mouse lines should be submitted to H.-B.L.

Almanzar, N. et al. A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. Nature 583, 590–595 (2020).

Article CAS Google Scholar

Huang, Y.-L., Shen, Z.-Q., Huang, C.-H., Lin, C.-H. & Tsai, T.-F. Cisd2 slows down liver aging and attenuates age-related metabolic dysfunction in male mice. Aging Cell 20, e13523 (2021).

Article CAS PubMed PubMed Central Google Scholar

Albillos, A. et al. Cirrhosis-associated immune dysfunction. Nat. Rev. Gastroenterol. Hepatol. 19, 112–134 (2022).

Article PubMed Google Scholar

Anstee, Q. M., Reeves, H. L., Kotsiliti, E., Govaere, O. & Heikenwalder, M. From NASH to HCC: current concepts and future challenges. Nat. Rev. Gastroenterol. Hepatol. 16, 411–428 (2019).

Article PubMed Google Scholar

Noureddin, M. et al. Clinical and histological determinants of nonalcoholic steatohepatitis and advanced fibrosis in elderly patients. Hepatology 58, 1644–1654 (2013).

Article CAS PubMed Google Scholar

Hann, A., Oo, Y. H. & Perera, M. T. P. R. Regulatory T-cell therapy in liver transplantation and chronic liver disease. Front. Immunol. 12, 719954 (2021).

Article CAS PubMed PubMed Central Google Scholar

Wawman, R. E., Bartlett, H. & Oo, Y. H. Regulatory T cell metabolism in the hepatic microenvironment. Front. Immunol. 8, 1889 (2018).

Article PubMed PubMed Central Google Scholar

Yao, R. W., Wang, Y. & Chen, L. L. Cellular functions of long noncoding RNAs. Nat. Cell Biol. 21, 542–551 (2019).

Article CAS PubMed Google Scholar

Wohlwend, M. et al. The exercise-induced long noncoding RNA CYTOR promotes fast-twitch myogenesis in aging. Sci. Transl. Med. 623, eabc7367 (2021).

Article Google Scholar

Sousa-Franco, A., Rebelo, K., da Rocha, S. T. & Bernardes de Jesus, B. LncRNAs regulating stemness in aging. Aging Cell 18, e12870 (2019).

Article PubMed Google Scholar

Zhang, H. et al. LncRNA NEAT1 controls the lineage fates of BMSCs during skeletal aging by impairing mitochondrial function and pluripotency maintenance. Cell Death Differ. 29, 351–365 (2022).

Article CAS PubMed Google Scholar

Vendramin, R., Marine, J.-C. & Leucci, E. Non-coding RNAs: the dark side of nuclear-mitochondrial communication. EMBO J. 36, 1123–1133 (2017).

Article CAS PubMed PubMed Central Google Scholar

Jiang, R. et al. The long noncoding RNA lnc-EGFR stimulates T-regulatory cells differentiation thus promoting hepatocellular carcinoma immune evasion. Nat. Commun. 8, 15129 (2017).

Article CAS PubMed PubMed Central Google Scholar

Brajic, A. et al. The long non-coding RNA Flatr anticipates Foxp3 expression in regulatory T cells. Front. Immunol. 9, 1989 (2018).

Article PubMed PubMed Central Google Scholar

Zemmour, D., Pratama, A., Loughhead, S. M., Mathis, D. & Benoist, C. Flicr, a long noncoding RNA, modulates Foxp3 expression and autoimmunity. Proc. Natl Acad. Sci. USA 114, E3472–E3480 (2017).

Article CAS PubMed PubMed Central Google Scholar

Gerriets, V. A. et al. Metabolic programming and PDHK1 control CD4+ T cell subsets and infammation. J. Clin. Invest. 125, 194–207 (2014).

Article PubMed PubMed Central Google Scholar

Michalek, R. D. et al. Cutting edge: distinct glycolytic and lipid oxidative metabolic programs are essential for effector and regulatory CD4+ T cell subsets. J. Immunol. 186, 3299–3303 (2011).

Article CAS PubMed Google Scholar

Weinberg, S. E. et al. Mitochondrial complex III is essential for suppressive function of regulatory T cells. Nature 565, 495–499 (2019).

Article CAS PubMed PubMed Central Google Scholar

Li, C. et al. TCR transgenic mice reveal stepwise, multi-site acquisition of the distinctive fat-Treg phenotype. Cell 174, 285–299 (2018).

Article CAS PubMed PubMed Central Google Scholar

Harman, C. C. D. et al. An in vivo screen of noncoding loci reveals that Daedalus is a gatekeeper of an Ikaros-dependent checkpoint during haematopoiesis. Proc. Natl Acad. Sci. USA 118, e1918062118 (2021).

Article CAS PubMed PubMed Central Google Scholar

Chougnet, C. A. et al. A major role for Bim in regulatory T cell homeostasis. J. Immunol. 186, 156–163 (2011).

Article CAS PubMed Google Scholar

Ji, P. et al. MALAT-1, a novel noncoding RNA, and thymosin β4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene 22, 8031–8041 (2003).

Article PubMed Google Scholar

Petukhova, L. et al. Genome-wide association study in alopecia areata implicates both innate and adaptive immunity. Nature 466, 113–117 (2010).

Article CAS PubMed PubMed Central Google Scholar

Bedke, T., Pretsch, L., Karakhanova, S., Enk, A. H. & Mahnke, K. Endothelial cells augment the suppressive function of CD4+CD25+Foxp3+ regulatory T cells: involvement of programmed death-1 and IL-10. J. Immunol. 184, 5562–5570 (2010).

Article CAS PubMed Google Scholar

Van Herck, M. A. et al. The differential roles of T cells in non-alcoholic fatty liver disease and obesity. Front. Immunol. 10, 82 (2019).

Article CAS PubMed PubMed Central Google Scholar

Rios, D. A. et al. Chronic hepatitis C liver microenvironment: role of the Th17/Treg interplay related to fibrogenesis. Sci. Rep. 7, 13283 (2017).

Article PubMed PubMed Central Google Scholar

Roh, Y. S. et al. Toll-like receptor-7 signaling promotes nonalcoholic steatohepatitis by inhibiting regulatory T cells in mice. Am. J. Pathol. 188, 2574–2588 (2018).

Article CAS PubMed Google Scholar

Sena, L. A. et al. Mitochondria are required for antigen-specific T cell activation through reactive oxygen species signaling. Immunity 38, 225–236 (2013).

Article CAS PubMed PubMed Central Google Scholar

Torrão, R. C., Bennett, S. J., Brown, J. E. & Griffiths, H. R. Does metabolic reprogramming underpin age-associated changes in T cell phenotype and function? Free Radic. Biol. Med. 71, 26–35 (2014).

Article PubMed Google Scholar

Ron-Harel, N. et al. Defective respiration and one-carbon metabolism contribute to impaired naïve T cell activation in aged mice. Proc. Natl Acad. Sci. USA 115, 13347–13352 (2018).

Article CAS PubMed PubMed Central Google Scholar

Ron-Harel, N. et al. Mitochondrial biogenesis and proteome remodeling promote one-carbon metabolism for T cell activation. Cell Metab. 24, 104–117 (2016).

Article CAS PubMed PubMed Central Google Scholar

Sakamuru, S., Attene-Ramos, M. S. & Xia, M. Mitochondrial membrane potential assay. Methods Mol. Biol. 1473, 17–22 (2016).

Article PubMed PubMed Central Google Scholar

Pellegrini, M. et al. p66SHC promotes T cell apoptosis by inducing mitochondrial dysfunction and impaired Ca2+ homeostasis. Cell Death Differ. 14, 338–347 (2007).

Article CAS PubMed Google Scholar

Kopp, F. & Mendell, J. T. Functional classification and experimental dissection of long noncoding RNAs. Cell 172, 393–407 (2018).

Article CAS PubMed PubMed Central Google Scholar

Chang, L. S., Shi, Y. & Shenk, T. Adeno-associated virus P5 promoter contains an adenovirus E1A-inducible element and a binding site for the major late transcription factor. J. Virol. 63, 3479–3488 (1989).

Article CAS PubMed PubMed Central Google Scholar

Shi, Y., Lee, J. S. & Galvin, K. M. Everything you have ever wanted to know about Yin Yang 1…. Biochim. Biophys. Acta 1332, F49–F66 (1997).

CAS PubMed Google Scholar

Gordon, S., Akopyan, G., Garban, H. & Bonavida, B. Transcription factor YY1: structure, function, and therapeutic implications in cancer biology. Oncogene 25, 1125–1142 (2006).

Article CAS PubMed Google Scholar

Kitagawa, Y. et al. Guidance of regulatory T cell development by Satb1-dependent super-enhancer establishment. Nat. Immunol. 18, 173–183 (2017).

Article CAS PubMed Google Scholar

Fan, M. et al. Structure and mechanism of the mitochondrial Ca2+ uniporter holocomplex. Nature 582, 129–133 (2020).

Article CAS PubMed PubMed Central Google Scholar

Mallilankaraman, K. et al. MCUR1 is an essential component of mitochondrial Ca2+ uptake that regulates cellular metabolism. Nat. Cell Biol. 14, 1336–1343 (2012).

Article CAS PubMed PubMed Central Google Scholar

Papsdorf, K. & Brunet, A. Linking lipid metabolism to chromatin regulation in aging. Trends Cell Biol. 29, 97–116 (2019).

Article CAS PubMed Google Scholar

Gong, Z., Tas, E., Yakar, S. & Muzumdar, R. Hepatic lipid metabolism and non-alcoholic fatty liver disease in aging. Mol. Cell. Endocrinol. 455, 115–130 (2017).

Article CAS PubMed Google Scholar

Field, C. S. et al. Mitochondrial integrity regulated by lipid metabolism is a cell-intrinsic checkpoint for Treg suppressive function. Cell Metab. 31, 422–437 (2020).

Article CAS PubMed PubMed Central Google Scholar

Matias, M. I. et al. Regulatory T cell differentiation is controlled by αKG-induced alterations in mitochondrial metabolism and lipid homeostasis. Cell Rep. 37, 109911 (2021).

Article CAS PubMed PubMed Central Google Scholar

Bapat, S. P. et al. Depletion of fat-resident Treg cells prevents age-associated insulin resistance. Nature 528, 137–141 (2015).

Article CAS PubMed PubMed Central Google Scholar

Darrigues, J., van Meerwijk, J. P. M. & Romagnoli, P. Age-dependent changes in regulatory T lymphocyte development and function: a mini-review. Gerontology 64, 28–35 (2018).

Article CAS PubMed Google Scholar

Kumar, P., Bhattacharya, P. & Prabhakar, B. S. A comprehensive review on the role of co-signaling receptors and Treg homeostasis in autoimmunity and tumor immunity. J. Autoimmun. 95, 77–99 (2018).

Article CAS PubMed PubMed Central Google Scholar

Rosenkranz, D. et al. Higher frequency of regulatory T cells in the elderly and increased suppressive activity in neurodegeneration. J. Neuroimmunol. 188, 117–127 (2007).

Article CAS PubMed Google Scholar

Kuswanto, W. et al. Poor repair of skeletal muscle in aging mice reflects a defect in local, interleukin-33-dependent accumulation of regulatory T cells. Immunity 44, 355–367 (2016).

Article CAS PubMed PubMed Central Google Scholar

Cipolletta, D. et al. PPAR-γ is a major driver of the accumulation and phenotype of adipose tissue Treg cells. Nature 486, 549–553 (2012).

Article CAS PubMed PubMed Central Google Scholar

Burzyn, D. et al. A special population of regulatory T cells potentiates muscle repair. Cell 155, 1282–1295 (2013).

Article CAS PubMed PubMed Central Google Scholar

Kim, I. H., Kisseleva, T. & Brenner, D. A. Aging and liver disease. Curr. Opin. Gastroenterol. 31, 184–191 (2015).

Article CAS PubMed PubMed Central Google Scholar

Sheedfar, F., Di Biase, S., Koonen, D. & Vinciguerra, M. Liver diseases and aging: friends or foes? Aging Cell 12, 950–954 (2013).

Article CAS PubMed Google Scholar

Ma, X. et al. A high-fat diet and regulatory T cells influence susceptibility to endotoxin-induced liver injury. Hepatology 46, 1519–1529 (2007).

Article CAS PubMed Google Scholar

Choi, Y. S. et al. Liver injury in acute hepatitis A is associated with decreased frequency of regulatory T cells caused by Fas-mediated apoptosis. Gut 64, 1303–1313 (2015).

Article PubMed Google Scholar

Ikeno, Y. et al. Foxp3+ regulatory T cells inhibit CCL4-induced liver inflammation and fibrosis by regulating tissue cellular immunity. Front. Immunol. 11, 584048 (2020).

Article CAS PubMed PubMed Central Google Scholar

Ronaldson, A. et al. Increased percentages of regulatory T cells are associated with inflammatory and neuroendocrine responses to acute psychological stress and poorer health status in older men and women. Psychopharmacology 233, 1661–1668 (2016).

Article CAS PubMed Google Scholar

Paquissi, F. C. Immunity and fibrogenesis: the role of Th17/IL-17 axis in HBV and HCV-induced chronic hepatitis and progression to cirrhosis. Front. Immunol. 8, 1195 (2017).

Article PubMed PubMed Central Google Scholar

Ravichandran, G. et al. Interferon-γ-dependent immune responses contribute to the pathogenesis of sclerosing cholangitis in mice. J. Hepatol. 71, 773–782 (2019).

Article CAS PubMed Google Scholar

Li, J. et al. IFN-γ facilitates liver fibrogenesis by CD161+CD4+ T cells through a regenerative IL-23/IL-17 axis in chronic hepatitis B virus infection. Clin. Transl. Immunology 10, e1353 (2021).

Article CAS PubMed PubMed Central Google Scholar

Guo, Z. et al. DCAF1 regulates Treg senescence via the ROS axis during immunological aging. J. Clin. Invest. 130, 5893–5908 (2020).

Article CAS PubMed PubMed Central Google Scholar

Cheung, E. C. & Vousden, K. H. The role of ROS in tumour development and progression. Nat. Rev. Cancer 22, 280–297 (2022).

Article CAS PubMed Google Scholar

Jeffery, H. C., Braitch, M. K., Brown, S. & Oo, Y. H. Clinical potential of regulatory T cell therapy in liver diseases: an overview and current perspectives. Front. Immunol. 7, 334 (2016).

Article PubMed PubMed Central Google Scholar

Franceschi, C., Garagnani, P., Parini, P., Giuliani, C. & Santoro, A. Inflammaging: a new immune-metabolic viewpoint for age-related diseases. Nat. Rev. Endocrinol. 14, 576–590 (2018).

Article CAS PubMed Google Scholar

De Cecco, M. et al. L1 drives IFN in senescent cells and promotes age-associated inflammation. Nature 566, 73–78 (2019).

Article CAS PubMed Google Scholar

Sutterwala, F. S. et al. Critical role for NALP3/CIAS1/cryopyrin in innate and adaptive immunity through its regulation of caspase-1. Immunity 24, 317–327 (2006).

Article CAS PubMed Google Scholar

Li, H.-B. et al. m6A mRNA methylation controls T cell homeostasis by targeting the IL-7/STAT5/SOCS pathways. Nature 548, 338–342 (2017).

Article CAS PubMed PubMed Central Google Scholar

Miller, S. D. & Karpus, W. J. Experimental autoimmune encephalomyelitis in the mouse. Curr. Protoc. Immunol. 77, 15.1.1–15.1.18 (2007).

Google Scholar

Nallagangula, K. S., Nagaraj, S. K., Venkataswamy, L. & Chandrappa, M. Liver fibrosis: a compilation on the biomarkers status and their significance during disease progression. Future Sci. OA 4, FSO250 (2017).

Article PubMed PubMed Central Google Scholar

Luo, X. et al. Expression of STING is increased in liver tissues from patients with NAFLD and promotes macrophage-mediated hepatic inflammation and fibrosis in mice. Gastroenterology 155, 1971–1984 (2018).

Article CAS PubMed Google Scholar

Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

Article CAS PubMed Google Scholar

Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

Article CAS PubMed PubMed Central Google Scholar

Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

Article PubMed PubMed Central Google Scholar

Tsai, M.-C. et al. Long noncoding RNA as modular scaffold of histone modification complexes. Science 329, 689–693 (2010).

Article CAS PubMed PubMed Central Google Scholar

Ying, Z. et al. CCT6A suppresses SMAD2 and promotes prometastatic TGF-β signaling. J. Clin. Invest. 127, 1725–1740 (2017).

Article PubMed PubMed Central Google Scholar

Kotzin, J. J. et al. The long non-coding RNA Morrbid regulates Bim and short-lived myeloid cell lifespan. Nature 537, 239–243 (2016).

Article CAS PubMed PubMed Central Google Scholar

Wu, N. et al. MAP3K2-regulated intestinal stromal cells define a distinct stem cell niche. Nature 592, 606–610 (2021).

Article CAS PubMed Google Scholar

Download references

We thank W. Li for helping with the mass spectrometry analysis; J. Zhao and J. Hu for their help with genotyping and sample collection; P. Ranney and C. Hughes for their initial help and suggestions in the generation of the Altre loxP mice; X. Wang and H. Li for their contribution to the key discussion; all members of the Li laboratories for discussions and suggestions; and the sequencing and flow cytometry core facilities at Shanghai Institute of Immunology for their support. This work was supported by the National Natural Science Foundation of China (nos. 82341017, 82030042, 32070917 and 82111540277 to H.-B.L.; no. 82202017 to C.D.; no. 82271756 to J.Z.), the Chongqing International Institute for Immunology (no. 2021YJC01 to H.-B.L.), the Ministry of Science and Technology of China (no. 2021YFA1100800 to H.-B.L.), the Shanghai Science and Technology Commission (nos. 20JC1417400, 201409005500 and 20JC1410100 to H.-B.L.; no. 20ZR1472900 to Y.Y.; no. 22QA1408100 to J.Z.), the Shanghai Municipal Health Commission (nos. 2022XD047 and 2022JC001 to H.-B.L.), the Innovative Research Team of High-Level Local Universities in Shanghai (no. SHSMU-ZDCX20212501 to H.-B.L.; no. SHSMU-ZDCX20212500 to J.Z.), and the China Postdoctoral Science Foundation (no. 2021M702160 to C.D.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

These authors contributed equally: Chenbo Ding, Zhibin Yu, Esen Sefik, Jing Zhou.

Medical Center on Aging, Center for Immune-Related Diseases at Shanghai Institute of Immunology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Chenbo Ding, Zhibin Yu, Jing Zhou, Gaoyang Wang, Bin Li, Youqiong Ye & Hua-Bing Li

Shanghai Jiao Tong University School of Medicine-Yale Institute for Immune Metabolism, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Chenbo Ding, Zhibin Yu, Jing Zhou & Hua-Bing Li

Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA

Esen Sefik, Eleanna Kaffe & Richard A. Flavell

Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, CT, USA

Esen Sefik & Richard A. Flavell

Department of Geriatrics, Medical Center on Aging of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

Weiguo Hu & Hua-Bing Li

Chongqing International Institute for Immunology, Chongqing, China

Hua-Bing Li

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

You can also search for this author in PubMed Google Scholar

H.-B.L. conceived, supervised and directed the study. C.D. and Z.Y. performed all the main experiments with help from E.S. and J.Z. J.Z. and E.K. provided expert advice on liver biology. E.S. and Y.Y. provided help with the RNA-seq. Y.Y. performed the bulk RNA-seq and MS analyses. G.W. performed the Nanopore long-read sequencing analysis. C.D., Z.Y. and Y.Y. analyzed the data. B.L., W.H., R.A.F. and Y.Y. contributed to key discussions. C.D. drafted and revised the paper. H.-B.L. wrote and revised the paper. All authors discussed the results and commented on the paper.

Correspondence to Hua-Bing Li.

R.A.F. is a consultant for GSK and Zai Lab; H.-B.L. is a consultant for CARsgen Therapeutics. The other authors declare no competing interests.

Nature Aging thanks Nikolai Timchenko, Ye Zheng and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

a, Foxp3 and Gm16157 mRNAs level in conventional T (Tconv) and Treg cells isolated from FOXP3-IRES-mRFP reporter mice (n = 4). Two-tailed t-test. b, Relative level of Gm16157 in different T cell subsets based on our previous CRISPR screen data (GSE153862). c, Percent input of Altre in cytoplasm nuclearplasm and chromatin, Hprt is protein-coding gene as cytoplasma positive control, Neat1 and Malat1 are long non-coding RNAs as nuclearplasm and chromatin positive controls (n = 3 biologically independent cells). Data are mean ± s.d.

Source data

Nanopore long-read sequencing analysis of the lncRNA Altre.

a, The two lox sites were inserted into the third and fourth exons of the Altre locus by embryonic stem cell recombination technology. b, Representative flow cytometry gating strategy for thymocyte. c, Representative flow cytometry gating strategy for CD4+ T cell and CD8+ T cell in spleen, lymph nodes, liver, VAT (visceral adipose tissue), and colon. d, Representative flow cytometry plots of CD4+ and CD8+ subsets in the thymus (up panel) and spleen (down panel) from Altref/f and Altref/f Cd4Cre mice (2 months old; n = 3). e, Statistical analysis of the percentage of different T cell subsets in the thymus and spleen from young Altref/f and Altref/f Cd4Cre mice as in d. Two-tailed t-test. f, The relative level of Altre and its neighboring genes Igf1r, Pgpep1l, and Fam169b were analyzed by qRT-PCR in Treg cells from Altref/f and Altref/f Cd4Cre mice (n = 4). Two-tailed t-test. g, Statistical analysis of the percentage of CD45+CD4+CD25+Foxp3+ Treg cells in the thymus, spleen, liver, and VAT from Altref/f and Altref/f Cd4Cre mice (2 months old; Altref/f, n = 5; Altref/f Cd4Cre, n = 6). Two-tailed t-test. h, The relative level of Il10, Pdcd1, Ctla4, and Il2ra were analyzed by qRT-PCR in Treg cells from young Altref/f and Altref/f Cd4Cre mice (2 months old; n = 4). Two-tailed t-test. Data are mean ± s.d. NS, non-significant.

Source data

a, Representative flow cytometry plots of naïve T cells differentiation into Treg (n = 3 biologically independent cells) and Th17 (n = 4 biologically independent cells) effector subsets. b, Statistical analysis of frequency for the gated population as in a. Two-tailed t-test. Data are mean ± s.d. c, Representative flow cytometry (left panel) and statistical analysis (right panel) of suppression of naïve T cells proliferation mediated by Treg cells, as determined by flow cytometry using CellTrace Violet dilution, for peripheral (pool of splenic and lymph node) Treg cells isolated from Altref/f and Altref/f Cd4Cre mice (2 months old; n = 3) and co-cultured with WT naïve T cells at the indicated ratios, two-way ANOVA. Data are mean ± s.d. d, EAE scoring of Altref/f and Altref/f Cd4Cre mice (2 months old; Altref/f, n = 9; Altref/f Cd4Cre, n = 10), two-way ANOVA. Data are mean ± s.e.m. e, Tumor size analysis of Altref/f and Altref/f Cd4Cre mice (2 months old; n = 7), two-tailed Mann–Whitney U test. Data are mean ± s.e.m. f, Body weight changes after CD45RBhi naïve T cells and Treg cells adoptive transfer into Rag2−/− host mice (n = 5), two-way ANOVA. Treg cells isolated from Altref/f and Altref/f Cd4Cre young mice (2 months old). Data are mean ± s.d. NS, non-significant.

Source data

a, Relative level of Altre in Tregs isolated from several tissues (spleen, liver, colon, and VAT) in 8-week-old mice (n = 3). b, Relative level of Altre in Tregs isolated from several tissues (spleen, liver, colon, and VAT) in 6-month-old mice (n = 3). c, Relative level of Altre in Tregs isolated from several tissues (spleen, liver, colon, and VAT) in 14-month-old mice (n = 3). Data are mean ± s.d.

Source data

a, Body weight changes after CD45RBhi naïve T cells and Tregs adoptive transfer into Rag2−/− host mice (n = 6), two-way ANOVA. Tregs were isolated from Altre-WT and Altre-KO young mice (2 months old). b, The relative level of Altre neighbored genes Igf1r, Pgpep1l, and Fam169b was analyzed by qRT-PCR in Tregs from young Altre-WT and Altre-KO mice (2 months old; n = 3). Two-tailed t-test. c, The relative level of Altre neighbored genes Igf1r, Pgpep1l, and Fam169b was analyzed by qRT-PCR in Tregs from aged Altre-WT and Altre-KO mice (14 months old; n = 4). Two-tailed t-test. Data are mean ± s.d. NS, non-significant.

Source data

a, Representative flow cytometry plots of CD44 and CD62L staining in the liver CD4+ T cells isolated from Altre-WT and Altre-KO mice (14 months old). b, Statistical analysis of the percentage of CD62L+CD44−, CD62L+CD44+, and CD62L−CD44+ subsets in CD4+ T cell in the liver from Altre-WT and Altre-KO aged mice (n = 6) as in a. Two-tailed t-test. c, Representative flow cytometry plots of CD44 and CD62L staining in the liver CD8+ T cells isolated from Altre-WT and Altre-KO mice (14 months old). d, Statistical analysis of the percentage of CD62L+CD44−, CD62L+CD44+, and CD62L−CD44+ subsets in CD8+ T cell in the liver from Altre-WT and Altre-KO aged mice (n = 6) as in c. Two-tailed t-test. e, Statistical analysis of the percentage of CD45+CD4+ T cells in the spleen, liver, and VAT from Altre-WT and Altre-KO mice (14 months old; n = 6). Two-tailed t-test. f, Statistical analysis of the percentage of CD45+CD8+ T cells in the spleen (n = 6), liver (n = 6), and VAT (n = 5) from Altre-WT and Altre-KO aged mice (14 months old). Two-tailed t-test. g, Statistical analysis of the percentage of CD45+ γδ T cells in the spleen (Altre-WT, n = 6; Altre-KO, n = 6), liver (Altre-WT, n = 5; Altre-KO, n = 6), and VAT (Altre-WT, n = 4; Altre-KO, n = 4) from aged mice (14 months old). Two-tailed t-test. Data are mean ± s.d. NS, non-significant.

Source data

a, Statistical analysis of the percentage of IFN-γ+ in CD45+CD4+ T cells in the spleen (Altre-WT, n = 6; Altre-KO, n = 5) and liver (Altre-WT, n = 6; Altre-KO, n = 6) from aged mice (14 months old). Two-tailed t-test. b, Statistical analysis of the percentage of IFN-γ+ in CD45+CD8+ T cells in the spleen (Altre-WT, n = 6; Altre-KO, n = 5) and liver (Altre-WT, n = 6; Altre-KO, n = 6) from aged mice (14 months old). Two-tailed t-test. c, Statistical analysis of the percentage of IL-17A+ in CD45+CD4+ T cells in the spleen (n = 6) and liver (n = 5) from Altre-WT and Altre-KO mice (14 months old). Two-tailed t-test. d, Statistical analysis of the percentage of IL-17A+ in CD45+CD8+ T cells in the spleens (Altre-WT, n = 4; Altre-KO, n = 6) and livers (Altre-WT, n = 4; Altre-KO, n = 4) from aged mice (14 months old). Two-tailed t-test. Data are mean ± s.d. NS, non-significant.

Source data

a, Representative flow cytometry plots of aged Altre-KO Tregs (n = 6), aged Altre-KO Tregs infected with NC (n = 3) and mouse Altre-overexpression lentivirus vectors (n = 3), and then performed mitochondrial membrane potential (MMP) analysis by using the cationic fluorescent dye JC-10. Treg cells were isolated from Altre-KO mice (14 months old). b, Statistical analysis of mean fluorescence intensity (MFI) of JC-10 in aged Altre-KO Tregs, aged Altre-KO Tregs infected with negative control (NC) and Altre-overexpression lentivirus vectors as in a. Two-tailed t-test. Data are mean ± s.d.

Source data

a, Representative hematoxylin and eosin (H&E) and oil-red stained livers from Altre-WT and Altre-KO mice with the high fat diet for 8 months. Circline indicates a typic infiltrating area. b, Quantification of the corresponding histology scores based on oil-red staining (n = 13). Scale bar, 25 μm. Two-tailed t-test. c, Statistical analysis of frequency for cell early apoptosis in young Tregs co-cultured with phosphatidylethanolamine (PE 18:0/20:4) (n = 4 biologically independent cells). Two-tailed t-test. d, Statistical analysis of frequency for cell early apoptosis in young Tregs co-cultured with polycarbonate (PC 16:0/20:4) (n = 4 biologically independent cells). Two-tailed t-test. e, Statistical analysis of frequency for cell early apoptosis in young Tregs co-cultured with polycarbonate (PC 18:0/20:4) (n = 4 biologically independent cells). Two-tailed t-test. f, The relative level of YY1 was analyzed by qRT-PCR in Tregs infected with negative control (NC), YY1-sgRNA1, YY1-sgRNA2, and YY1-sgRNA3 lentivirus vectors. Tregs were isolated from WT mice (2 months old; n = 3). Two-tailed t-test. Data are mean ± s.d. NS, non-significant.

Source data

Altre isoform sequences from Nanopore sequencing.

Supplementary Table 1

Supplementary Table 2

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Unprocessed western blots.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Statistical source data.

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

Ding, C., Yu, Z., Sefik, E. et al. A Treg-specific long noncoding RNA maintains immune-metabolic homeostasis in aging liver. Nat Aging (2023). https://doi.org/10.1038/s43587-023-00428-8

Download citation

Received: 27 July 2022

Accepted: 28 April 2023

Published: 05 June 2023

DOI: https://doi.org/10.1038/s43587-023-00428-8

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative