1
|
Sun ED, Zhou OY, Hauptschein M, Rappoport N, Xu L, Navarro Negredo P, Liu L, Rando TA, Zou J, Brunet A. Spatiotemporal transcriptomic profiling and modeling of mouse brain at single-cell resolution reveals cell proximity effects of aging and rejuvenation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.16.603809. [PMID: 39071282 PMCID: PMC11275735 DOI: 10.1101/2024.07.16.603809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk1. Brain aging is complex and accompanied by many cellular changes2-20. However, the influence that aged cells have on neighboring cells and how this contributes to tissue decline is unknown. More generally, the tools to systematically address this question in aging tissues have not yet been developed. Here, we generate spatiotemporal data at single-cell resolution for the mouse brain across lifespan, and we develop the first machine learning models based on spatial transcriptomics ('spatial aging clocks') to reveal cell proximity effects during brain aging and rejuvenation. We collect a single-cell spatial transcriptomics brain atlas of 4.2 million cells from 20 distinct ages and across two rejuvenating interventions-exercise and partial reprogramming. We identify spatial and cell type-specific transcriptomic fingerprints of aging, rejuvenation, and disease, including for rare cell types. Using spatial aging clocks and deep learning models, we find that T cells, which infiltrate the brain with age, have a striking pro-aging proximity effect on neighboring cells. Surprisingly, neural stem cells have a strong pro-rejuvenating effect on neighboring cells. By developing computational tools to identify mediators of these proximity effects, we find that pro-aging T cells trigger a local inflammatory response likely via interferon-γ whereas pro-rejuvenating neural stem cells impact the metabolism of neighboring cells possibly via growth factors (e.g. vascular endothelial growth factor) and extracellular vesicles, and we experimentally validate some of these predictions. These results suggest that rare cells can have a drastic influence on their neighbors and could be targeted to counter tissue aging. We anticipate that these spatial aging clocks will not only allow scalable assessment of the efficacy of interventions for aging and disease but also represent a new tool for studying cell-cell interactions in many spatial contexts.
Collapse
Affiliation(s)
- Eric D. Sun
- Department of Biomedical Data Science, Stanford University, CA, USA
- Department of Genetics, Stanford University, CA, USA
| | - Olivia Y. Zhou
- Department of Genetics, Stanford University, CA, USA
- Stanford Biophysics Program, Stanford University, CA, USA
- Stanford Medical Scientist Training Program, Stanford University, CA, USA
| | | | | | - Lucy Xu
- Department of Genetics, Stanford University, CA, USA
- Department of Biology, Stanford University, CA, USA
| | | | - Ling Liu
- Department of Neurology, Stanford University, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
- Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Biology, UCLA, Los Angeles, CA, USA
| | - Thomas A. Rando
- Department of Neurology, Stanford University, CA, USA
- Department of Neurology, UCLA, Los Angeles, CA, USA
- Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Biology, UCLA, Los Angeles, CA, USA
| | - James Zou
- Department of Biomedical Data Science, Stanford University, CA, USA
- These authors contributed equally: James Zou, Anne Brunet
| | - Anne Brunet
- Department of Genetics, Stanford University, CA, USA
- Glenn Center for the Biology of Aging, Stanford University, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, CA, USA
- These authors contributed equally: James Zou, Anne Brunet
| |
Collapse
|
2
|
Cebrian-Silla A, Assis Nascimento M, Mancia W, Gonzalez-Granero S, Romero-Rodriguez R, Obernier K, Steffen DM, Lim DA, Garcia-Verdugo JM, Alvarez-Buylla A. Neural Stem Cell Relay from B1 to B2 cells in the adult mouse Ventricular-Subventricular Zone. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.28.600695. [PMID: 39005355 PMCID: PMC11244865 DOI: 10.1101/2024.06.28.600695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Neurogenesis and gliogenesis continue in the Ventricular-Subventricular Zone (V-SVZ) of the adult rodent brain. B1 cells are astroglial cells derived from radial glia that function as primary progenitors or neural stem cells (NSCs) in the V-SVZ. B1 cells, which have a small apical contact with the ventricle, decline in numbers during early postnatal life, yet neurogenesis continues into adulthood. Here we found that a second population of V-SVZ astroglial cells (B2 cells), that do not contact the ventricle, function as NSCs in the adult brain. B2 cell numbers increase postnatally, remain constant in 12-month-old mice and decrease by 18 months. Transcriptomic analysis of ventricular-contacting and non-contacting B cells revealed key molecular differences to distinguish B1 from B2 cells. Transplantation and lineage tracing of B2 cells demonstrate their function as primary progenitors for adult neurogenesis. This study reveals how NSC function is relayed from B1 to B2 progenitors to maintain adult neurogenesis.
Collapse
|
3
|
Xu L, Ramirez-Matias J, Hauptschein M, Sun ED, Lunger JC, Buckley MT, Brunet A. Restoration of neuronal progenitors by partial reprogramming in the aged neurogenic niche. NATURE AGING 2024; 4:546-567. [PMID: 38553564 DOI: 10.1038/s43587-024-00594-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 02/13/2024] [Indexed: 04/21/2024]
Abstract
Partial reprogramming (pulsed expression of reprogramming transcription factors) improves the function of several tissues in old mice. However, it remains largely unknown how partial reprogramming impacts the old brain. Here we use single-cell transcriptomics to systematically examine how partial reprogramming influences the subventricular zone neurogenic niche in aged mouse brains. Whole-body partial reprogramming mainly improves neuroblasts (cells committed to give rise to new neurons) in the old neurogenic niche, restoring neuroblast proportion to more youthful levels. Interestingly, targeting partial reprogramming specifically to the neurogenic niche also boosts the proportion of neuroblasts and their precursors (neural stem cells) in old mice and improves several molecular signatures of aging, suggesting that the beneficial effects of reprogramming are niche intrinsic. In old neural stem cell cultures, partial reprogramming cell autonomously restores the proportion of neuroblasts during differentiation and blunts some age-related transcriptomic changes. Importantly, partial reprogramming improves the production of new neurons in vitro and in old brains. Our work suggests that partial reprogramming could be used to rejuvenate the neurogenic niche and counter brain decline in old individuals.
Collapse
Affiliation(s)
- Lucy Xu
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | | | - Max Hauptschein
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Eric D Sun
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Judith C Lunger
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Anne Brunet
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
- Glenn Center for the Biology of Aging, Stanford University, Stanford, CA, USA.
| |
Collapse
|
4
|
Moradi K, Mitew S, Xing YL, Merson TD. HB-EGF and EGF infusion following CNS demyelination mitigates age-related decline in regeneration of oligodendrocytes from neural precursor cells originating in the ventricular-subventricular zone. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582092. [PMID: 38529498 PMCID: PMC10962700 DOI: 10.1101/2024.02.26.582092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
In multiple sclerosis (MS), chronic demyelination initiated by immune-mediated destruction of myelin, leads to axonal damage and neuronal cell death, resulting in a progressive decline in neurological function. The development of interventions that potentiate remyelination could hold promise as a novel treatment strategy for MS. To this end, our group has demonstrated that neural precursor cells (NPCs) residing in the ventricular-subventricular zone (V-SVZ) of the adult mouse brain contribute significantly to remyelination in response to central nervous system (CNS) demyelination and can regenerate myelin of normal thickness. However, aging takes its toll on the regenerative potential of NPCs and reduces their contribution to remyelination. In this study, we investigated how aging influences the contribution of NPCs to oligodendrogenesis during the remyelination process and whether the delivery of growth factors into the brains of aged mice could potentiate the oligodendrogenic potential of NPCs. To enable us to map the fate of NPCs in response to demyelination induced at different postnatal ages, Nestin-CreERT2;Rosa26-LSL-eYFP mice were gavaged with tamoxifen at either 8 weeks, 30 weeks or one year of age before being challenged with cuprizone for a period of six weeks. Using osmotic minipumps, we infused heparin-binding EGF-like growth factor (HB-EGF), and/or epidermal growth factor (EGF) into the cisterna magna for a period of two weeks beginning at the peak of cuprizone-induced demyelination (n=6-8 mice per group). Control mice received artificial cerebrospinal fluid (vehicle) alone. Mice were perfused six weeks after cuprizone withdrawal and the contribution of NPCs to oligodendrocyte regeneration in the corpus callosum was assessed. Our data reveal that although NPC-derived oligodendrocyte generation declined dramatically with age, this decline was partially reversed by growth factor infusion. Notably, co-infusion of EGF and HB-EGF increased oligodendrocyte regeneration twofold in some regions of the corpus callosum. Our results shed light on the beneficial effects of EGF and HB-EGF for increasing the contribution of NPCs to remyelination and indicate their therapeutic potential to combat the negative effects of aging upon remyelination efficacy.
Collapse
Affiliation(s)
- Kaveh Moradi
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Stanislaw Mitew
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton, Victoria, Australia
| | - Yao Lulu Xing
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton, Victoria, Australia
| | - Tobias D. Merson
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton, Victoria, Australia
- Current address: Oligodendroglial Interactions Group, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| |
Collapse
|
5
|
Yeo RW, Zhou OY, Zhong BL, Sun ED, Navarro Negredo P, Nair S, Sharmin M, Ruetz TJ, Wilson M, Kundaje A, Dunn AR, Brunet A. Chromatin accessibility dynamics of neurogenic niche cells reveal defects in neural stem cell adhesion and migration during aging. NATURE AGING 2023; 3:866-893. [PMID: 37443352 PMCID: PMC10353944 DOI: 10.1038/s43587-023-00449-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 06/02/2023] [Indexed: 07/15/2023]
Abstract
The regenerative potential of brain stem cell niches deteriorates during aging. Yet the mechanisms underlying this decline are largely unknown. Here we characterize genome-wide chromatin accessibility of neurogenic niche cells in vivo during aging. Interestingly, chromatin accessibility at adhesion and migration genes decreases with age in quiescent neural stem cells (NSCs) but increases with age in activated (proliferative) NSCs. Quiescent and activated NSCs exhibit opposing adhesion behaviors during aging: quiescent NSCs become less adhesive, whereas activated NSCs become more adhesive. Old activated NSCs also show decreased migration in vitro and diminished mobilization out of the niche for neurogenesis in vivo. Using tension sensors, we find that aging increases force-producing adhesions in activated NSCs. Inhibiting the cytoskeletal-regulating kinase ROCK reduces these adhesions, restores migration in old activated NSCs in vitro, and boosts neurogenesis in vivo. These results have implications for restoring the migratory potential of NSCs and for improving neurogenesis in the aged brain.
Collapse
Affiliation(s)
- Robin W Yeo
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Olivia Y Zhou
- Department of Genetics, Stanford University, Stanford, CA, USA
- Stanford Biophysics Program, Stanford University, Stanford, CA, USA
- Stanford Medical Scientist Training Program, Stanford University, Stanford, CA, USA
| | - Brian L Zhong
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA
| | - Eric D Sun
- Department of Genetics, Stanford University, Stanford, CA, USA
- Biomedical Informatics Graduate Program, Stanford University, Stanford, CA, USA
| | | | - Surag Nair
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Mahfuza Sharmin
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Tyson J Ruetz
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Mikaela Wilson
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Alexander R Dunn
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA
| | - Anne Brunet
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Glenn Laboratories for the Biology of Aging, Stanford University, Stanford, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.
| |
Collapse
|
6
|
Bao H, Cao J, Chen M, Chen M, Chen W, Chen X, Chen Y, Chen Y, Chen Y, Chen Z, Chhetri JK, Ding Y, Feng J, Guo J, Guo M, He C, Jia Y, Jiang H, Jing Y, Li D, Li J, Li J, Liang Q, Liang R, Liu F, Liu X, Liu Z, Luo OJ, Lv J, Ma J, Mao K, Nie J, Qiao X, Sun X, Tang X, Wang J, Wang Q, Wang S, Wang X, Wang Y, Wang Y, Wu R, Xia K, Xiao FH, Xu L, Xu Y, Yan H, Yang L, Yang R, Yang Y, Ying Y, Zhang L, Zhang W, Zhang W, Zhang X, Zhang Z, Zhou M, Zhou R, Zhu Q, Zhu Z, Cao F, Cao Z, Chan P, Chen C, Chen G, Chen HZ, Chen J, Ci W, Ding BS, Ding Q, Gao F, Han JDJ, Huang K, Ju Z, Kong QP, Li J, Li J, Li X, Liu B, Liu F, Liu L, Liu Q, Liu Q, Liu X, Liu Y, Luo X, Ma S, Ma X, Mao Z, Nie J, Peng Y, Qu J, Ren J, Ren R, Song M, Songyang Z, Sun YE, Sun Y, Tian M, Wang S, Wang S, Wang X, Wang X, Wang YJ, Wang Y, Wong CCL, Xiang AP, Xiao Y, Xie Z, Xu D, Ye J, Yue R, Zhang C, Zhang H, Zhang L, Zhang W, Zhang Y, Zhang YW, Zhang Z, Zhao T, Zhao Y, Zhu D, Zou W, Pei G, Liu GH. Biomarkers of aging. SCIENCE CHINA. LIFE SCIENCES 2023; 66:893-1066. [PMID: 37076725 PMCID: PMC10115486 DOI: 10.1007/s11427-023-2305-0] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 02/27/2023] [Indexed: 04/21/2023]
Abstract
Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant.
Collapse
Affiliation(s)
- Hainan Bao
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Jiani Cao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mengting Chen
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China
| | - Min Chen
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China
| | - Wei Chen
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China
| | - Xiao Chen
- Department of Nuclear Medicine, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Yanhao Chen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yu Chen
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Yutian Chen
- The Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China
| | - Zhiyang Chen
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China
| | - Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yingjie Ding
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Junlin Feng
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jun Guo
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China
| | - Mengmeng Guo
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China
| | - Chuting He
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Yujuan Jia
- Department of Neurology, First Affiliated Hospital, Shanxi Medical University, Taiyuan, 030001, China
| | - Haiping Jiang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Ying Jing
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Dingfeng Li
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jingyi Li
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Qinhao Liang
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China
| | - Rui Liang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China
| | - Feng Liu
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaoqian Liu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Zuojun Liu
- School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Oscar Junhong Luo
- Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Jianwei Lv
- School of Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Jingyi Ma
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Kehang Mao
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Jiawei Nie
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinhua Qiao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xinpei Sun
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China
| | - Xiaoqiang Tang
- Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE, State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China
| | - Jianfang Wang
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Siyuan Wang
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China
| | - Xuan Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China
| | - Yaning Wang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Yuhan Wang
- University of Chinese Academy of Sciences, Beijing, 100049, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Rimo Wu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China
| | - Kai Xia
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China
| | - Fu-Hui Xiao
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Lingyan Xu
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yingying Xu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China
| | - Haoteng Yan
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Liang Yang
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China
| | - Ruici Yang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yuanxin Yang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China
| | - Yilin Ying
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China
| | - Le Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiwei Zhang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China
| | - Wenwan Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Xing Zhang
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China
| | - Zhuo Zhang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Min Zhou
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China
| | - Rui Zhou
- Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China
| | - Qingchen Zhu
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Zhengmao Zhu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China
| | - Feng Cao
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, National Clinical Research Center for Geriatric Diseases, Beijing, 100853, China.
| | - Zhongwei Cao
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Chang Chen
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Guobing Chen
- Department of Microbiology and Immunology, School of Medicine, Jinan University, Guangzhou, 510632, China.
- Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, Guangzhou, 510000, China.
| | - Hou-Zao Chen
- Department of Biochemistryand Molecular Biology, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Jun Chen
- Peking University Research Center on Aging, Beijing Key Laboratory of Protein Posttranslational Modifications and Cell Function, Department of Biochemistry and Molecular Biology, Department of Integration of Chinese and Western Medicine, School of Basic Medical Science, Peking University, Beijing, 100191, China.
| | - Weimin Ci
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
| | - Bi-Sen Ding
- State Key Laboratory of Biotherapy, West China Second University Hospital, Sichuan University, Chengdu, 610041, China.
| | - Qiurong Ding
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Feng Gao
- Key Laboratory of Ministry of Education, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, 710032, China.
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
| | - Kai Huang
- Clinic Center of Human Gene Research, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Clinical Research Center of Metabolic and Cardiovascular Disease, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Hubei Key Laboratory of Metabolic Abnormalities and Vascular Aging, Huazhong University of Science and Technology, Wuhan, 430022, China.
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
| | - Zhenyu Ju
- Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Ageing and Regenerative Medicine, Jinan University, Guangzhou, 510632, China.
| | - Qing-Peng Kong
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
- State Key Laboratory of Genetic Resources and Evolution, Key Laboratory of Healthy Aging Research of Yunnan Province, Kunming Key Laboratory of Healthy Aging Study, KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Ji Li
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- Hunan Key Laboratory of Aging Biology, Xiangya Hospital, Central South University, Changsha, 410008, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, China.
| | - Jian Li
- The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
| | - Xin Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Baohua Liu
- School of Basic Medical Sciences, Shenzhen University Medical School, Shenzhen, 518060, China.
| | - Feng Liu
- Metabolic Syndrome Research Center, The Second Xiangya Hospital, Central South Unversity, Changsha, 410011, China.
| | - Lin Liu
- Department of Genetics and Cell Biology, College of Life Science, Nankai University, Tianjin, 300071, China.
- Haihe Laboratory of Cell Ecosystem, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China.
- Institute of Translational Medicine, Tianjin Union Medical Center, Nankai University, Tianjin, 300000, China.
- State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin, 300350, China.
| | - Qiang Liu
- Department of Neurology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230036, China.
| | - Qiang Liu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
- Tianjin Institute of Immunology, Tianjin Medical University, Tianjin, 300070, China.
| | - Xingguo Liu
- CAS Key Laboratory of Regenerative Biology, Joint School of Life Sciences, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou Medical University, Guangzhou, 510530, China.
| | - Yong Liu
- College of Life Sciences, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430072, China.
| | - Xianghang Luo
- Department of Endocrinology, Endocrinology Research Center, Xiangya Hospital of Central South University, Changsha, 410008, China.
| | - Shuai Ma
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Xinran Ma
- Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Zhiyong Mao
- Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Jing Nie
- The State Key Laboratory of Organ Failure Research, National Clinical Research Center of Kidney Disease, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Yaojin Peng
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ruibao Ren
- Shanghai Institute of Hematology, State Key Laboratory for Medical Genomics, National Research Center for Translational Medicine (Shanghai), International Center for Aging and Cancer, Collaborative Innovation Center of Hematology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Center for Aging and Cancer, Hainan Medical University, Haikou, 571199, China.
| | - Moshi Song
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Zhou Songyang
- MOE Key Laboratory of Gene Function and Regulation, Guangzhou Key Laboratory of Healthy Aging Research, School of Life Sciences, Institute of Healthy Aging Research, Sun Yat-sen University, Guangzhou, 510275, China.
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Yi Eve Sun
- Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
| | - Yu Sun
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Department of Medicine and VAPSHCS, University of Washington, Seattle, WA, 98195, USA.
| | - Mei Tian
- Human Phenome Institute, Fudan University, Shanghai, 201203, China.
| | - Shusen Wang
- Research Institute of Transplant Medicine, Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, 300384, China.
| | - Si Wang
- Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, International Center for Aging and Cancer, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| | - Xia Wang
- School of Pharmaceutical Sciences, Tsinghua University, Beijing, 100084, China.
| | - Xiaoning Wang
- Institute of Geriatrics, The second Medical Center, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Yan-Jiang Wang
- Department of Neurology and Center for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China.
| | - Yunfang Wang
- Hepatobiliary and Pancreatic Center, Medical Research Center, Beijing Tsinghua Changgung Hospital, Beijing, 102218, China.
| | - Catherine C L Wong
- Clinical Research Institute, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing, 100730, China.
| | - Andy Peng Xiang
- Center for Stem Cell Biologyand Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, 510080, China.
- National-Local Joint Engineering Research Center for Stem Cells and Regenerative Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Yichuan Xiao
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Zhengwei Xie
- Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, 100101, China.
- Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, 100101, China.
| | - Daichao Xu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 201210, China.
| | - Jing Ye
- Department of Geriatrics, Medical Center on Aging of Shanghai Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- International Laboratory in Hematology and Cancer, Shanghai Jiao Tong University School of Medicine/Ruijin Hospital, Shanghai, 200025, China.
| | - Rui Yue
- Institute for Regenerative Medicine, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China.
| | - Cuntai Zhang
- Gerontology Center of Hubei Province, Wuhan, 430000, China.
- Institute of Gerontology, Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Hongbo Zhang
- Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, China.
| | - Liang Zhang
- CAS Key Laboratory of Tissue Microenvironment and Tumor, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yong Zhang
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Yun-Wu Zhang
- Fujian Provincial Key Laboratory of Neurodegenerative Disease and Aging Research, Institute of Neuroscience, School of Medicine, Xiamen University, Xiamen, 361102, China.
| | - Zhuohua Zhang
- Key Laboratory of Molecular Precision Medicine of Hunan Province and Center for Medical Genetics, Institute of Molecular Precision Medicine, Xiangya Hospital, Central South University, Changsha, 410078, China.
- Department of Neurosciences, Hengyang Medical School, University of South China, Hengyang, 421001, China.
| | - Tongbiao Zhao
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, School of Pharmacy, East China University of Science and Technology, Shanghai, 200237, China.
- Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Dahai Zhu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), Guangzhou, 510005, China.
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, 100005, China.
| | - Weiguo Zou
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Pei
- Shanghai Key Laboratory of Signaling and Disease Research, Laboratory of Receptor-Based Biomedicine, The Collaborative Innovation Center for Brain Science, School of Life Sciences and Technology, Tongji University, Shanghai, 200070, China.
| | - Guang-Hui Liu
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
| |
Collapse
|
7
|
Murtaj V, Butti E, Martino G, Panina-Bordignon P. Endogenous neural stem cells characterization using omics approaches: Current knowledge in health and disease. Front Cell Neurosci 2023; 17:1125785. [PMID: 37091923 PMCID: PMC10113633 DOI: 10.3389/fncel.2023.1125785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/03/2023] [Indexed: 04/08/2023] Open
Abstract
Neural stem cells (NSCs), an invaluable source of neuronal and glial progeny, have been widely interrogated in the last twenty years, mainly to understand their therapeutic potential. Most of the studies were performed with cells derived from pluripotent stem cells of either rodents or humans, and have mainly focused on their potential in regenerative medicine. High-throughput omics technologies, such as transcriptomics, epigenetics, proteomics, and metabolomics, which exploded in the past decade, represent a powerful tool to investigate the molecular mechanisms characterizing the heterogeneity of endogenous NSCs. The transition from bulk studies to single cell approaches brought significant insights by revealing complex system phenotypes, from the molecular to the organism level. Here, we will discuss the current literature that has been greatly enriched in the “omics era”, successfully exploring the nature and function of endogenous NSCs and the process of neurogenesis. Overall, the information obtained from omics studies of endogenous NSCs provides a sharper picture of NSCs function during neurodevelopment in healthy and in perturbed environments.
Collapse
Affiliation(s)
- Valentina Murtaj
- Division of Neuroscience, San Raffaele Vita-Salute University, Milan, Italy
- Neuroimmunology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Erica Butti
- Neuroimmunology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Gianvito Martino
- Division of Neuroscience, San Raffaele Vita-Salute University, Milan, Italy
- Neuroimmunology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Panina-Bordignon
- Division of Neuroscience, San Raffaele Vita-Salute University, Milan, Italy
- Neuroimmunology, Division of Neuroscience, Institute of Experimental Neurology, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Paola Panina-Bordignon
| |
Collapse
|
8
|
Jiang JC, Hu C, McIntosh AM, Shah S. Investigating the potential anti-depressive mechanisms of statins: a transcriptomic and Mendelian randomization analysis. Transl Psychiatry 2023; 13:110. [PMID: 37015906 PMCID: PMC10073189 DOI: 10.1038/s41398-023-02403-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 04/06/2023] Open
Abstract
Observational studies and randomized controlled trials presented inconsistent findings on the effects of cholesterol-lowering statins on depression. It therefore remains unclear whether statins have any beneficial effects on depression, and if so, what the underlying molecular mechanisms are. Here, we aimed to use genomic approaches to investigate this further. Using Connectivity Map (CMap), we first investigated whether statins and antidepressants shared pharmacological effects by interrogating gene expression responses to drug exposure in human cell lines. Second, using Mendelian randomization analysis, we investigated both on-target (through HMGCR inhibition) and potential off-target (through ITGAL and HDAC2 inhibition) causal effects of statins on depression risk and depressive symptoms, and traits related to the shared biological pathways identified from CMap analysis. Compounds inducing highly similar gene expression responses to statins in HA1E cells (indicated by an average connectivity score with statins > 90) were found to be enriched for antidepressants (12 out of 38 antidepressants; p = 9E-08). Genes perturbed in the same direction by both statins and antidepressants were significantly enriched for diverse cellular and metabolic pathways, and various immune activation, development and response processes. MR analysis did not identify any significant associations between statin exposure and depression risk or symptoms after multiple testing correction. However, genetically proxied HMGCR inhibition was strongly associated with alterations in platelets (a prominent serotonin reservoir) and monocyte percentage, which have previously been implicated in depression. Genetically proxied ITGAL inhibition was strongly associated with basophil, monocyte and neutrophil counts. We identified biological pathways that are commonly perturbed by both statins and antidepressants, and haematological biomarkers genetically associated with statin targets. Our findings warrant pre-clinical investigation of the causal role of these shared pathways in depression and potential as therapeutic targets, and investigation of whether blood biomarkers may be important considerations in clinical trials investigating effects of statins on depression.
Collapse
Affiliation(s)
- Jiayue-Clara Jiang
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Chenwen Hu
- The University of Queensland, St Lucia, QLD, Australia
| | | | - Sonia Shah
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia.
| |
Collapse
|
9
|
Kalinina A, Lagace D. Single-Cell and Single-Nucleus RNAseq Analysis of Adult Neurogenesis. Cells 2022; 11:1633. [PMID: 35626670 PMCID: PMC9139993 DOI: 10.3390/cells11101633] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/02/2022] [Accepted: 05/07/2022] [Indexed: 02/04/2023] Open
Abstract
The complexity of adult neurogenesis is becoming increasingly apparent as we learn more about cellular heterogeneity and diversity of the neurogenic lineages and stem cell niches within the adult brain. This complexity has been unraveled in part due to single-cell and single-nucleus RNA sequencing (sc-RNAseq and sn-RNAseq) studies that have focused on adult neurogenesis. This review summarizes 33 published studies in the field of adult neurogenesis that have used sc- or sn-RNAseq methods to answer questions about the three main regions that host adult neural stem cells (NSCs): the subventricular zone (SVZ), the dentate gyrus (DG) of the hippocampus, and the hypothalamus. The review explores the similarities and differences in methodology between these studies and provides an overview of how these studies have advanced the field and expanded possibilities for the future.
Collapse
Affiliation(s)
| | - Diane Lagace
- Neuroscience Program, Department of Cellular and Molecular Medicine, Ottawa Hospital Research Institute, Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada;
| |
Collapse
|
10
|
Terstege DJ, Addo-Osafo K, Campbell Teskey G, Epp JR. New neurons in old brains: implications of age in the analysis of neurogenesis in post-mortem tissue. Mol Brain 2022; 15:38. [PMID: 35501905 PMCID: PMC9063342 DOI: 10.1186/s13041-022-00926-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 04/20/2022] [Indexed: 11/10/2022] Open
Abstract
Adult neurogenesis, the proliferation and integration of newly generated neurons, has been observed in the adult mammalian hippocampus of many species. Numerous studies have also found adult neurogenesis in the human hippocampus, but several recent high-profile studies have suggested that this process is considerably reduced in humans, occurring in children but not in adults. In comparison, rodent studies also show age-related decline but a greater degree of proliferation of new neurons in adult animals. These differences may represent biological species differences or could alternatively be explained by methodological differences in tissue handling and fixation. Here, we examine whether differences in the post-mortem interval between death and tissue fixation might impact subsequent detection of adult neurogenesis due to increased tissue degradation. Because there are fewer new neurons present in older subjects to begin with we hypothesized that, subject age might interact significantly with post-mortem interval in the detection of adult neurogenesis. We analyzed neurogenesis in the hippocampus of rats that were either perfusion-fixed or the brains extracted and immersion-fixed at various post-mortem intervals. We observed an interaction between animal age and the time delay between death and tissue fixation. While similar levels of neurogenesis were observed in young rats regardless of fixation, older rats had significantly fewer labeled neurons when fixation was not immediate. Furthermore, the morphological detail of the labeled neurons was significantly reduced in the delayed fixation conditions at all ages. This study highlights critical concerns that must be considered when using post-mortem tissue to quantify adult neurogenesis.
Collapse
Affiliation(s)
- Dylan J Terstege
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, HMRB 162, Health Sciences Centre, 3330 Hospital Drive NW, AB, T2N 4N1, Calgary, Canada
| | - Kwaku Addo-Osafo
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, HMRB 162, Health Sciences Centre, 3330 Hospital Drive NW, AB, T2N 4N1, Calgary, Canada
| | - G Campbell Teskey
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, HMRB 162, Health Sciences Centre, 3330 Hospital Drive NW, AB, T2N 4N1, Calgary, Canada
| | - Jonathan R Epp
- Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, HMRB 162, Health Sciences Centre, 3330 Hospital Drive NW, AB, T2N 4N1, Calgary, Canada.
| |
Collapse
|
11
|
Identifying gene expression profiles associated with neurogenesis and inflammation in the human subependymal zone from development through aging. Sci Rep 2022; 12:40. [PMID: 34997023 PMCID: PMC8742079 DOI: 10.1038/s41598-021-03976-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 12/02/2021] [Indexed: 12/11/2022] Open
Abstract
The generation of new neurons within the mammalian forebrain continues throughout life within two main neurogenic niches, the subgranular zone (SGZ) of the hippocampal dentate gyrus, and the subependymal zone (SEZ) lining the lateral ventricles. Though the SEZ is the largest neurogenic niche in the adult human forebrain, our understanding of the mechanisms regulating neurogenesis from development through aging within this region remains limited. This is especially pertinent given that neurogenesis declines dramatically over the postnatal lifespan. Here, we performed transcriptomic profiling on the SEZ from human post-mortem tissue from eight different life-stages ranging from neonates (average age ~ 2 months old) to aged adults (average age ~ 86 years old). We identified transcripts with concomitant profiles across these decades of life and focused on three of the most distinct profiles, namely (1) genes whose expression declined sharply after birth, (2) genes whose expression increased steadily with age, and (3) genes whose expression increased sharply in old age in the SEZ. Critically, these profiles identified neuroinflammation as becoming more prevalent with advancing age within the SEZ and occurring with time courses, one gradual (starting in mid-life) and one sharper (starting in old age).
Collapse
|
12
|
Zhang H, Li J, Ren J, Sun S, Ma S, Zhang W, Yu Y, Cai Y, Yan K, Li W, Hu B, Chan P, Zhao GG, Belmonte JCI, Zhou Q, Qu J, Wang S, Liu GH. Single-nucleus transcriptomic landscape of primate hippocampal aging. Protein Cell 2021; 12:695-716. [PMID: 34052996 PMCID: PMC8403220 DOI: 10.1007/s13238-021-00852-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 04/24/2021] [Indexed: 12/12/2022] Open
Abstract
The hippocampus plays a crucial role in learning and memory, and its progressive deterioration with age is functionally linked to a variety of human neurodegenerative diseases. Yet a systematic profiling of the aging effects on various hippocampal cell types in primates is still missing. Here, we reported a variety of new aging-associated phenotypic changes of the primate hippocampus. These include, in particular, increased DNA damage and heterochromatin erosion with time, alongside loss of proteostasis and elevated inflammation. To understand their cellular and molecular causes, we established the first single-nucleus transcriptomic atlas of primate hippocampal aging. Among the 12 identified cell types, neural transiently amplifying progenitor cell (TAPC) and microglia were most affected by aging. In-depth dissection of gene-expression dynamics revealed impaired TAPC division and compromised neuronal function along the neurogenesis trajectory; additionally elevated pro-inflammatory responses in the aged microglia and oligodendrocyte, as well as dysregulated coagulation pathways in the aged endothelial cells may contribute to a hostile microenvironment for neurogenesis. This rich resource for understanding primate hippocampal aging may provide potential diagnostic biomarkers and therapeutic interventions against age-related neurodegenerative diseases.
Collapse
Affiliation(s)
- Hui Zhang
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- China National Center for Bioinformation, Beijing, 100101, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 101408, China
- Sino-Danish Center for Education and Research, Beijing, 101408, China
| | - Jie Ren
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- China National Center for Bioinformation, Beijing, 100101, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Shuhui Sun
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Shuai Ma
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- China National Center for Bioinformation, Beijing, 100101, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 101408, China
| | - Yang Yu
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Peking University Third Hospital, Beijing, 100191, China
- Stem Cell Research Center, Peking University Third Hospital, Beijing, 100191, China
| | - Yusheng Cai
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Kaowen Yan
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Wei Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Baoyang Hu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Piu Chan
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Guo-Guang Zhao
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | | | - Qi Zhou
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| | - Si Wang
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- Aging Translational Medicine Center, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
| | - Guang-Hui Liu
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- Advanced Innovation Center for Human Brain Protection, National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, 100053, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Beijing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
| |
Collapse
|
13
|
Rojas-Vázquez S, Blasco-Chamarro L, López-Fabuel I, Martínez-Máñez R, Fariñas I. Vascular Senescence: A Potential Bridge Between Physiological Aging and Neurogenic Decline. Front Neurosci 2021; 15:666881. [PMID: 33958987 PMCID: PMC8093510 DOI: 10.3389/fnins.2021.666881] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 03/25/2021] [Indexed: 01/25/2023] Open
Abstract
The adult mammalian brain contains distinct neurogenic niches harboring populations of neural stem cells (NSCs) with the capacity to sustain the generation of specific subtypes of neurons during the lifetime. However, their ability to produce new progeny declines with age. The microenvironment of these specialized niches provides multiple cellular and molecular signals that condition NSC behavior and potential. Among the different niche components, vasculature has gained increasing interest over the years due to its undeniable role in NSC regulation and its therapeutic potential for neurogenesis enhancement. NSCs are uniquely positioned to receive both locally secreted factors and adhesion-mediated signals derived from vascular elements. Furthermore, studies of parabiosis indicate that NSCs are also exposed to blood-borne factors, sensing and responding to the systemic circulation. Both structural and functional alterations occur in vasculature with age at the cellular level that can affect the proper extrinsic regulation of NSCs. Additionally, blood exchange experiments in heterochronic parabionts have revealed that age-associated changes in blood composition also contribute to adult neurogenesis impairment in the elderly. Although the mechanisms of vascular- or blood-derived signaling in aging are still not fully understood, a general feature of organismal aging is the accumulation of senescent cells, which act as sources of inflammatory and other detrimental signals that can negatively impact on neighboring cells. This review focuses on the interactions between vascular senescence, circulating pro-senescence factors and the decrease in NSC potential during aging. Understanding the mechanisms of NSC dynamics in the aging brain could lead to new therapeutic approaches, potentially include senolysis, to target age-dependent brain decline.
Collapse
Affiliation(s)
- Sara Rojas-Vázquez
- Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València-Universitat de València, Valencia, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valencia, Spain.,Departamento de Biología Celular, Biología Funcional y Antropología Física, Universitat de València, Valencia, Spain
| | - Laura Blasco-Chamarro
- Departamento de Biología Celular, Biología Funcional y Antropología Física, Universitat de València, Valencia, Spain.,Instituto de Biotecnología y Biomedicina (BioTecMed), Universitat de València, Valencia, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Irene López-Fabuel
- Departamento de Biología Celular, Biología Funcional y Antropología Física, Universitat de València, Valencia, Spain.,Instituto de Biotecnología y Biomedicina (BioTecMed), Universitat de València, Valencia, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Ramón Martínez-Máñez
- Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València-Universitat de València, Valencia, Spain.,Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valencia, Spain.,Unidad Mixta UPV-CIPF de Investigación en Mecanismos de Enfermedades y Nanomedicina, Universitat Politècnica de València, Centro de Investigación Príncipe Felipe, Valencia, Spain.,Unidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València, IIS La Fe, Valencia, Spain
| | - Isabel Fariñas
- Departamento de Biología Celular, Biología Funcional y Antropología Física, Universitat de València, Valencia, Spain.,Instituto de Biotecnología y Biomedicina (BioTecMed), Universitat de València, Valencia, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| |
Collapse
|
14
|
High-resolution mouse subventricular zone stem-cell niche transcriptome reveals features of lineage, anatomy, and aging. Proc Natl Acad Sci U S A 2020; 117:31448-31458. [PMID: 33229571 DOI: 10.1073/pnas.2014389117] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Adult neural stem cells (NSC) serve as a reservoir for brain plasticity and origin for certain gliomas. Lineage tracing and genomic approaches have portrayed complex underlying heterogeneity within the major anatomical location for NSC, the subventricular zone (SVZ). To gain a comprehensive profile of NSC heterogeneity, we utilized a well-validated stem/progenitor-specific reporter transgene in concert with single-cell RNA sequencing to achieve unbiased analysis of SVZ cells from infancy to advanced age. The magnitude and high specificity of the resulting transcriptional datasets allow precise identification of the varied cell types embedded in the SVZ including specialized parenchymal cells (neurons, glia, microglia) and noncentral nervous system cells (endothelial, immune). Initial mining of the data delineates four quiescent NSC and three progenitor-cell subpopulations formed in a linear progression. Further evidence indicates that distinct stem and progenitor populations reside in different regions of the SVZ. As stem/progenitor populations progress from neonatal to advanced age, they acquire a deficiency in transition from quiescence to proliferation. Further data mining identifies stage-specific biological processes, transcription factor networks, and cell-surface markers for investigation of cellular identities, lineage relationships, and key regulatory pathways in adult NSC maintenance and neurogenesis.
Collapse
|
15
|
Wang F, Yang J, Lin H, Li Q, Ye Z, Lu Q, Chen L, Tu Z, Tian G. Improved Human Age Prediction by Using Gene Expression Profiles From Multiple Tissues. Front Genet 2020; 11:1025. [PMID: 33101366 PMCID: PMC7546819 DOI: 10.3389/fgene.2020.01025] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 08/11/2020] [Indexed: 12/19/2022] Open
Abstract
Studying transcriptome chronological change from tissues across the whole body can provide valuable information for understanding aging and longevity. Although there has been research on the effect of single-tissue transcriptomes on human aging or aging in mice across multiple tissues, the study of human body-wide multi-tissue transcriptomes on aging is not yet available. In this study, we propose a quantitative model to predict human age by using gene expression data from 46 tissues generated by the Genotype-Tissue Expression (GTEx) project. Specifically, the biological age of a person is first predicted via the gene expression profile of a single tissue. Then, we combine the gene expression profiles from two tissues and compare the predictive accuracy between single and two tissues. The best performance as measured by the root-mean-square error is 3.92 years for single tissue (pituitary), which deceased to 3.6 years when we combined two tissues (pituitary and muscle) together. Different tissues have different potential in predicting chronological age. The prediction accuracy is improved by combining multiple tissues, supporting that aging is a systemic process involving multiple tissues across the human body.
Collapse
Affiliation(s)
- Fayou Wang
- School of Computer and Data Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo, China.,Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, Shanghai Institute of Life Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jialiang Yang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.,Geneis Beijing Co., Ltd., Beijing, China.,Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China
| | - Huixin Lin
- Geneis Beijing Co., Ltd., Beijing, China.,Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China
| | - Qian Li
- Geneis Beijing Co., Ltd., Beijing, China.,Reproductive Center, Northwest Women and Children's Hospital, Xi'an, China
| | - Zixuan Ye
- Geneis Beijing Co., Ltd., Beijing, China
| | - Qingqing Lu
- Geneis Beijing Co., Ltd., Beijing, China.,Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China
| | - Luonan Chen
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, Shanghai Institute of Life Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhidong Tu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Geng Tian
- Geneis Beijing Co., Ltd., Beijing, China.,Qingdao Geneis Institute of Big Data Mining and Precision Medicine, Qingdao, China
| |
Collapse
|
16
|
Gao J, Wu Y, He D, Zhu X, Li H, Liu H, Liu H. Anti-aging effects of Ribes meyeri anthocyanins on neural stem cells and aging mice. Aging (Albany NY) 2020; 12:17738-17753. [PMID: 32920547 PMCID: PMC7521483 DOI: 10.18632/aging.103955] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Accepted: 07/23/2020] [Indexed: 02/06/2023]
Abstract
Aging is associated with neurological impairment and cognitive decline. Flavonoids are very promising in anti-aging research in mouse models. Ribes meyeri anthocyanins are rich in abundant flavonoids, but their anti-aging biological activities remain unknown. In this study, we prepared an R. meyeri anthocyanin extract and analyzed its effects on neural stem cell (NSC) senescence in vivo and in vitro. We isolated mouse NSCs and used cell counting kit-8 (CCK-8), cell cycle, reactive oxygen species (ROS), and immunofluorescence methods to analyze the anti-aging effects of R. meyeri anthocyanins as well as naringenin (Nar), which metabolic analysis revealed as an important flavonoid in R. meyeri anthocyanins. RNA-sequencing (RNA-seq) and enzyme-linked immuno sorbent assay (ELISA) methods were also used to investigate Nar-specific mechanisms of anti-aging. After R. meyeri anthocyanin treatment, NSC proliferation accelerated, and NSCs had decreased senescence markers, and reduced P16ink4a expression. R. meyeri anthocyanin treatment also reversed age-dependent neuronal loss in vivo and in vitro. Nar blocked mNSC aging in vitro and improved spatial memory and cognitive abilities in aging mice through downregulation of plasma TNF-α protein. These findings suggest that R. meyeri anthocyanins increase NSC proliferation and improve neurogenesis with aging via Nar-induced reductions in TNF-α protein levels in vivo.
Collapse
Affiliation(s)
- Jiaming Gao
- Institute for Regenerative Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200123, China
| | - Yating Wu
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, College of Life Sciences, Shihezi University, Shihezi 832003, China
| | - Dajun He
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, College of Life Sciences, Shihezi University, Shihezi 832003, China
| | - Xiaoqi Zhu
- Institute for Regenerative Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200123, China
| | - Hongbin Li
- Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, College of Life Sciences, Shihezi University, Shihezi 832003, China
| | - Haifeng Liu
- China Colored-Cotton (Group) Co., Ltd., Urumqi 830014, Xinjiang, China
| | - Hailiang Liu
- Institute for Regenerative Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200123, China,Key Laboratory of Xinjiang Phytomedicine Resource and Utilization of Ministry of Education, College of Life Sciences, Shihezi University, Shihezi 832003, China
| |
Collapse
|
17
|
Navarro Negredo P, Yeo RW, Brunet A. Aging and Rejuvenation of Neural Stem Cells and Their Niches. Cell Stem Cell 2020; 27:202-223. [PMID: 32726579 DOI: 10.1016/j.stem.2020.07.002] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Aging has a profound and devastating effect on the brain. Old age is accompanied by declining cognitive function and enhanced risk of brain diseases, including cancer and neurodegenerative disorders. A key question is whether cells with regenerative potential contribute to brain health and even brain "rejuvenation." This review discusses mechanisms that regulate neural stem cells (NSCs) during aging, focusing on the effect of metabolism, genetic regulation, and the surrounding niche. We also explore emerging rejuvenating strategies for old NSCs. Finally, we consider how new technologies may help harness NSCs' potential to restore healthy brain function during physiological and pathological aging.
Collapse
Affiliation(s)
| | - Robin W Yeo
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Anne Brunet
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Glenn Laboratories for the Biology of Aging, Stanford, CA 94305, USA.
| |
Collapse
|
18
|
Moreno-Cugnon L, Arrizabalaga O, Llarena I, Matheu A. Elevated p38MAPK activity promotes neural stem cell aging. Aging (Albany NY) 2020; 12:6030-6036. [PMID: 32243258 PMCID: PMC7185101 DOI: 10.18632/aging.102994] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 02/20/2020] [Indexed: 12/19/2022]
Abstract
Age-progressive neural stem cell (NSC) dysfunction leads to impaired neurogenesis, cognitive decline and the onset of age-related neurodegenerative pathologies. p38MAPK signalling pathway limits stem cell activity during aging in several tissues. Its role in NSCs remains controversial. In this work, we show that p38MAPK activity increases in NSCs with age in the subventricular zone (SVZ) and its pharmacological inhibition is sufficient to rejuvenate their activity in vitro. These data reveal a cell-autonomous role for p38MAPK increase in decreasing NSC homeostasis with age. This information shed light in the role of p38MAPK in NSC aging.
Collapse
Affiliation(s)
- Leire Moreno-Cugnon
- Biodonostia Health Research Institute, Group of Cellular Oncology, San Sebastian, Spain
| | - Olatz Arrizabalaga
- Biodonostia Health Research Institute, Group of Cellular Oncology, San Sebastian, Spain
| | - Irantzu Llarena
- Optical Spectroscopy Platform, CIC biomaGUNE, Basque Research and Technology Alliance (BRTA), San Sebastian, Spain
| | - Ander Matheu
- Biodonostia Health Research Institute, Group of Cellular Oncology, San Sebastian, Spain.,CIBERfes, Madrid, Spain.,IKERBASQUE Basque Foundation for Science, Bilbao, Spain
| |
Collapse
|
19
|
He X, Memczak S, Qu J, Belmonte JCI, Liu GH. Single-cell omics in ageing: a young and growing field. Nat Metab 2020; 2:293-302. [PMID: 32694606 DOI: 10.1038/s42255-020-0196-7] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 03/17/2020] [Indexed: 12/28/2022]
Abstract
Organismal ageing results from interlinked molecular changes in multiple organs over time. The study of ageing at the molecular level is complicated by varying decay characteristics and kinetics-both between and within organs-driven by intrinsic and extracellular factors. Emerging single-cell omics methods allow for molecular and spatial profiling of cells, and probing of regulatory states and cell-fate determination, thus providing promising tools for unravelling the heterogeneous process of ageing and making it amenable to intervention. These new strategies are enabled by advances in genomic, epigenomic and transcriptomic technologies. Combined with methods for proteome and metabolome analysis, single-cell techniques provide multidimensional, integrated data with unprecedented detail and throughput. Here, we provide an overview of the current state, and perspectives on the future, of this emerging field. We discuss how single-cell approaches can advance understanding of mechanisms underlying organismal ageing and aid in the development of interventions for ageing and ageing-associated diseases.
Collapse
Affiliation(s)
- Xiaojuan He
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Sebastian Memczak
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Jing Qu
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Institute of Stem Cells and Regeneration, Chinese Academy of Sciences, Beijing, China.
| | | | - Guang-Hui Liu
- Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital Capital Medical University, Beijing, China.
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Institute of Stem Cells and Regeneration, Chinese Academy of Sciences, Beijing, China.
| |
Collapse
|
20
|
Crane MM, Chen KL, Blue BW, Kaeberlein M. Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging. Proteomics 2020; 20:e1800420. [PMID: 31385433 PMCID: PMC7000301 DOI: 10.1002/pmic.201800420] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 07/02/2019] [Indexed: 02/02/2023]
Abstract
All organisms age, but the extent to which all organisms age the same way remains a fundamental unanswered question in biology. Across species, it is now clear that at least some aspects of aging are highly conserved and are perhaps universal, but other mechanisms of aging are private to individual species or sets of closely related species. Within the same species, however, it has generally been assumed that the molecular mechanisms of aging are largely invariant from one individual to the next. With the development of new tools for studying aging at the individual cell level in budding yeast, recent data has called this assumption into question. There is emerging evidence that individual yeast mother cells may undergo fundamentally different trajectories of aging. Individual trajectories of aging are difficult to study by traditional population level assays, but through the application of systems biology approaches combined with novel microfluidic technologies, it is now possible to observe and study these phenomena in real time. Understanding the spectrum of mechanisms that determine how different individuals age is a necessary step toward the goal of personalized geroscience, where healthy longevity is optimized for each individual.
Collapse
Affiliation(s)
- Matthew M Crane
- Department of Pathology, School of Medicine, University of Washington, Seattle, WA, USA
| | - Kenneth L Chen
- Department of Pathology, School of Medicine, University of Washington, Seattle, WA, USA,Department of Genome Sciences, University of Washington, Seattle, WA, USA,Medical Scientist Training Program, University of Washington, Seattle, WA, USA
| | - Ben W. Blue
- Department of Pathology, School of Medicine, University of Washington, Seattle, WA, USA
| | - Matt Kaeberlein
- Department of Pathology, School of Medicine, University of Washington, Seattle, WA, USA,Department of Genome Sciences, University of Washington, Seattle, WA, USA
| |
Collapse
|
21
|
Walker LA, Sovic MG, Chiang CL, Hu E, Denninger JK, Chen X, Kirby ED, Byrd JC, Muthusamy N, Bundschuh R, Yan P. CLEAR: coverage-based limiting-cell experiment analysis for RNA-seq. J Transl Med 2020; 18:63. [PMID: 32039730 PMCID: PMC7008572 DOI: 10.1186/s12967-020-02247-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 01/28/2020] [Indexed: 01/07/2023] Open
Abstract
Background Direct cDNA preamplification protocols developed for single-cell RNA-seq have enabled transcriptome profiling of precious clinical samples and rare cell populations without the need for sample pooling or RNA extraction. We term the use of single-cell chemistries for sequencing low numbers of cells limiting-cell RNA-seq (lcRNA-seq). Currently, there is no customized algorithm to select robust/low-noise transcripts from lcRNA-seq data for between-group comparisons. Methods Herein, we present CLEAR, a workflow that identifies reliably quantifiable transcripts in lcRNA-seq data for differentially expressed genes (DEG) analysis. Total RNA obtained from primary chronic lymphocytic leukemia (CLL) CD5+ and CD5− cells were used to develop the CLEAR algorithm. Once established, the performance of CLEAR was evaluated with FACS-sorted cells enriched from mouse Dentate Gyrus (DG). Results When using CLEAR transcripts vs. using all transcripts in CLL samples, downstream analyses revealed a higher proportion of shared transcripts across three input amounts and improved principal component analysis (PCA) separation of the two cell types. In mouse DG samples, CLEAR identifies noisy transcripts and their removal improves PCA separation of the anticipated cell populations. In addition, CLEAR was applied to two publicly-available datasets to demonstrate its utility in lcRNA-seq data from other institutions. If imputation is applied to limit the effect of missing data points, CLEAR can also be used in large clinical trials and in single cell studies. Conclusions lcRNA-seq coupled with CLEAR is widely used in our institution for profiling immune cells (circulating or tissue-infiltrating) for its transcript preservation characteristics. CLEAR fills an important niche in pre-processing lcRNA-seq data to facilitate transcriptome profiling and DEG analysis. We demonstrate the utility of CLEAR in analyzing rare cell populations in clinical samples and in murine neural DG region without sample pooling.
Collapse
Affiliation(s)
- Logan A Walker
- Department of Physics, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA.,The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Michael G Sovic
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Chi-Ling Chiang
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Eileen Hu
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Jiyeon K Denninger
- Department of Psychology, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA
| | - Xi Chen
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Elizabeth D Kirby
- Department of Psychology, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA.,Chronic Brain Injury Program, The Ohio State University, Columbus, OH, USA
| | - John C Byrd
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Natarajan Muthusamy
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA.,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Ralf Bundschuh
- Department of Physics, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA. .,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA. .,Department of Chemistry & Biochemistry, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA. .,Center for RNA Biology, The Ohio State University, Columbus, OH, USA.
| | - Pearlly Yan
- The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. .,Division of Hematology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA.
| |
Collapse
|
22
|
Poiana G, Gioia R, Sineri S, Cardarelli S, Lupo G, Cacci E. Transcriptional regulation of adult neural stem/progenitor cells: tales from the subventricular zone. Neural Regen Res 2020; 15:1773-1783. [PMID: 32246617 PMCID: PMC7513981 DOI: 10.4103/1673-5374.280301] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
In rodents, well characterized neurogenic niches of the adult brain, such as the subventricular zone of the lateral ventricles and the subgranular zone of the hippocampus, support the maintenance of neural/stem progenitor cells (NSPCs) and the production of new neurons throughout the lifespan. The adult neurogenic process is dependent on the intrinsic gene expression signatures of NSPCs that make them competent for self-renewal and neuronal differentiation. At the same time, it is receptive to regulation by various extracellular signals that allow the modulation of neuronal production and integration into brain circuitries by various physiological stimuli. A drawback of this plasticity is the sensitivity of adult neurogenesis to alterations of the niche environment that can occur due to aging, injury or disease. At the core of the molecular mechanisms regulating neurogenesis, several transcription factors have been identified that maintain NSPC identity and mediate NSPC response to extrinsic cues. Here, we focus on REST, Egr1 and Dbx2 and their roles in adult neurogenesis, especially in the subventricular zone. We review recent work from our and other laboratories implicating these transcription factors in the control of NSPC proliferation and differentiation and in the response of NSPCs to extrinsic influences from the niche. We also discuss how their altered regulation may affect the neurogenic process in the aged and in the diseased brain. Finally, we highlight key open questions that need to be addressed to foster our understanding of the transcriptional mechanisms controlling adult neurogenesis.
Collapse
Affiliation(s)
- Giancarlo Poiana
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| | - Roberta Gioia
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| | - Serena Sineri
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| | - Silvia Cardarelli
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| | - Giuseppe Lupo
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| | - Emanuele Cacci
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Rome, Italy
| |
Collapse
|
23
|
Single-cell analysis reveals T cell infiltration in old neurogenic niches. Nature 2019; 571:205-210. [PMID: 31270459 PMCID: PMC7111535 DOI: 10.1038/s41586-019-1362-5] [Citation(s) in RCA: 329] [Impact Index Per Article: 54.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 06/04/2019] [Indexed: 02/06/2023]
Abstract
The mammalian brain contains neurogenic niches comprising neural stem cells (NSCs) and other cell types. Neurogenic niches become less functional with age, but how they change during aging remains unclear. Here we perform single cell RNA-sequencing of young and old neurogenic niches in mice. Analysis of 14,685 single cell transcriptomes reveals a decrease in activated NSCs, changes in endothelial cells and microglia, and infiltration of T cells in old neurogenic niches. Surprisingly, T cells in old brains are clonally expanded and generally distinct from those in old blood, suggesting they may experience specific antigens. T cells from old brains express interferon γ, and the subset of NSCs with a high interferon response shows decreased proliferation in vivo. Interestingly, T cells can inhibit NSC proliferation in co-cultures and in vivo, in part by secreting interferon. Our study reveals an interaction between T cells and NSCs in old brains, opening potential avenues to counter age-related decline in brain function.
Collapse
|
24
|
Lupo G, Gaetani S, Cacci E, Biagioni S, Negri R. Molecular Signatures of the Aging Brain: Finding the Links Between Genes and Phenotypes. Neurotherapeutics 2019; 16:543-553. [PMID: 31161490 PMCID: PMC6694319 DOI: 10.1007/s13311-019-00743-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Aging is associated with cognitive decline and increased vulnerability to neurodegenerative diseases. The progressive extension of the average human lifespan is bound to lead to a corresponding increase in the fraction of cognitively impaired elderly individuals among the human population, with an enormous societal and economic burden. At the cellular and tissue levels, cognitive decline is linked to a reduction in specific neuronal subpopulations, a widespread decrease in synaptic plasticity and an increase in neuroinflammation due to an enhanced activation of astrocytes and microglia, but the molecular mechanisms underlying these functional changes during normal aging and in neuropathological conditions remain poorly understood. In this review, we summarize very recent and outstanding progress in elucidating the molecular changes associated with cognitive decline through the genome-wide profiling of aging brain cells at different molecular levels (genomic, epigenomic, transcriptomic, proteomic). We discuss how the correlation of different molecular and phenotypic traits driven by mathematical and computational analyses of large datasets has led to the prediction of key molecular nodes of neurodegenerative pathways, and provide a few examples of candidate regulators of cognitive decline identified with these approaches. Furthermore, we highlight the dysregulation of the synaptic transcriptome in neuronal cells and of the inflammatory transcriptome in glial cells as some of the key events during normal and neuropathological human brain aging.
Collapse
Affiliation(s)
- Giuseppe Lupo
- Department of Chemistry, Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy.
| | - Silvana Gaetani
- Department of Physiology and Farmacology "V. Erspamer", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Emanuele Cacci
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Stefano Biagioni
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| | - Rodolfo Negri
- Department of Biology and Biotechnology "C. Darwin", Sapienza University of Rome, Piazzale A. Moro, 00185, Rome, Italy
| |
Collapse
|
25
|
Lupo G, Gioia R, Nisi PS, Biagioni S, Cacci E. Molecular Mechanisms of Neurogenic Aging in the Adult Mouse Subventricular Zone. J Exp Neurosci 2019; 13:1179069519829040. [PMID: 30814846 PMCID: PMC6381424 DOI: 10.1177/1179069519829040] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 01/10/2019] [Indexed: 12/31/2022] Open
Abstract
In the adult rodent brain, the continuous production of new neurons by neural stem/progenitor cells (NSPCs) residing in specialized neurogenic niches and their subsequent integration into pre-existing cerebral circuitries supports odour discrimination, spatial learning, and contextual memory capabilities. Aging is recognized as the most potent negative regulator of adult neurogenesis. The neurogenic process markedly declines in the aged brain, due to the reduction of the NSPC pool and the functional impairment of the remaining NSPCs. This decline has been linked to the progressive cognitive deficits of elderly individuals and it may also be involved in the onset/progression of neurological disorders. Since the human lifespan has been dramatically extended, the incidence of age-associated neuropsychiatric conditions in the human population has increased. This has prompted efforts to shed light on the mechanisms underpinning the age-related decline of adult neurogenesis, whose knowledge may foster therapeutic approaches to prevent or delay cognitive alterations in elderly patients. In this review, we summarize recent progress in elucidating the molecular causes of neurogenic aging in the most abundant NSPC niche of the adult mouse brain: the subventricular zone (SVZ). We discuss the age-associated changes occurring both in the intrinsic NSPC molecular networks and in the extrinsic signalling pathways acting in the complex environment of the SVZ niche, and how all these changes may steer young NSPCs towards an aged phenotype.
Collapse
Affiliation(s)
- Giuseppe Lupo
- Department of Chemistry, Sapienza University of Rome, Rome, Italy
| | - Roberta Gioia
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Paola Serena Nisi
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Stefano Biagioni
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, Rome, Italy
| | - Emanuele Cacci
- Department of Biology and Biotechnology "Charles Darwin", Sapienza University of Rome, Rome, Italy
| |
Collapse
|
26
|
Lupo G, Nisi PS, Esteve P, Paul YL, Novo CL, Sidders B, Khan MA, Biagioni S, Liu HK, Bovolenta P, Cacci E, Rugg-Gunn PJ. Molecular profiling of aged neural progenitors identifies Dbx2 as a candidate regulator of age-associated neurogenic decline. Aging Cell 2018; 17:e12745. [PMID: 29504228 PMCID: PMC5946077 DOI: 10.1111/acel.12745] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/04/2018] [Indexed: 12/22/2022] Open
Abstract
Adult neurogenesis declines with aging due to the depletion and functional impairment of neural stem/progenitor cells (NSPCs). An improved understanding of the underlying mechanisms that drive age‐associated neurogenic deficiency could lead to the development of strategies to alleviate cognitive impairment and facilitate neuroregeneration. An essential step towards this aim is to investigate the molecular changes that occur in NSPC aging on a genomewide scale. In this study, we compare the transcriptional, histone methylation and DNA methylation signatures of NSPCs derived from the subventricular zone (SVZ) of young adult (3 months old) and aged (18 months old) mice. Surprisingly, the transcriptional and epigenomic profiles of SVZ‐derived NSPCs are largely unchanged in aged cells. Despite the global similarities, we detect robust age‐dependent changes at several hundred genes and regulatory elements, thereby identifying putative regulators of neurogenic decline. Within this list, the homeobox gene Dbx2 is upregulated in vitro and in vivo, and its promoter region has altered histone and DNA methylation levels, in aged NSPCs. Using functional in vitro assays, we show that elevated Dbx2 expression in young adult NSPCs promotes age‐related phenotypes, including the reduced proliferation of NSPC cultures and the altered transcript levels of age‐associated regulators of NSPC proliferation and differentiation. Depleting Dbx2 in aged NSPCs caused the reverse gene expression changes. Taken together, these results provide new insights into the molecular programmes that are affected during mouse NSPC aging, and uncover a new functional role for Dbx2 in promoting age‐related neurogenic decline.
Collapse
Affiliation(s)
- Giuseppe Lupo
- Department of Chemistry; Sapienza University of Rome; Rome Italy
| | - Paola S. Nisi
- Department of Biology and Biotechnology “C. Darwin”; Sapienza University of Rome; Rome Italy
| | - Pilar Esteve
- Centro de Biologia Molecular “Severo Ochoa”; Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid; Madrid Spain
- CIBER of Rare Diseases; ISCIII; Madrid Spain
| | - Yu-Lee Paul
- Epigenetics Programme; The Babraham Institute; Cambridge UK
| | | | - Ben Sidders
- Bioscience; Oncology; IMED Biotech Unit; AstraZeneca; Cambridge UK
| | - Muhammad A. Khan
- Division of Molecular Neurogenetics; German Cancer Research Centre (DKFZ); DKFZ-ZMBH Alliance; Heidelberg Germany
| | - Stefano Biagioni
- Department of Biology and Biotechnology “C. Darwin”; Sapienza University of Rome; Rome Italy
| | - Hai-Kun Liu
- Division of Molecular Neurogenetics; German Cancer Research Centre (DKFZ); DKFZ-ZMBH Alliance; Heidelberg Germany
| | - Paola Bovolenta
- Centro de Biologia Molecular “Severo Ochoa”; Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid; Madrid Spain
- CIBER of Rare Diseases; ISCIII; Madrid Spain
| | - Emanuele Cacci
- Department of Biology and Biotechnology “C. Darwin”; Sapienza University of Rome; Rome Italy
| | - Peter J. Rugg-Gunn
- Epigenetics Programme; The Babraham Institute; Cambridge UK
- Wellcome Trust - Medical Research Council Cambridge Stem Cell Institute; University of Cambridge; Cambridge UK
| |
Collapse
|
27
|
Yoder MC. Endothelial stem and progenitor cells (stem cells): (2017 Grover Conference Series). Pulm Circ 2018; 8:2045893217743950. [PMID: 29099663 PMCID: PMC5731724 DOI: 10.1177/2045893217743950] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 10/31/2017] [Indexed: 12/11/2022] Open
Abstract
The capacity of existing blood vessels to give rise to new blood vessels via endothelial cell sprouting is called angiogenesis and is a well-studied biologic process. In contrast, little is known about the mechanisms for endothelial cell replacement or regeneration within established blood vessels. Since clear definitions exist for identifying cells with stem and progenitor cell properties in many tissues and organs of the body, several groups have begun to accumulate evidence that endothelial stem and progenitor cells exist within the endothelial intima of existing blood vessels. This paper will review stem and progenitor cell definitions and highlight several recent papers purporting to have identified resident vascular endothelial stem and progenitor cells.
Collapse
Affiliation(s)
- Mervin C. Yoder
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| |
Collapse
|