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Deota S, Pendergast JS, Kolthur-Seetharam U, Esser KA, Gachon F, Asher G, Dibner C, Benitah SA, Escobar C, Muoio DM, Zhang EE, Hotamışlıgil GS, Bass J, Takahashi JS, Rabinowitz JD, Lamia KA, de Cabo R, Kajimura S, Longo VD, Xu Y, Lazar MA, Verdin E, Zierath JR, Auwerx J, Drucker DJ, Panda S. The time is now: accounting for time-of-day effects to improve reproducibility and translation of metabolism research. Nat Metab 2025; 7:454-468. [PMID: 40097742 DOI: 10.1038/s42255-025-01237-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2024] [Accepted: 02/07/2025] [Indexed: 03/19/2025]
Abstract
The constant expansion of the field of metabolic research has led to more nuanced and sophisticated understanding of the complex mechanisms that underlie metabolic functions and diseases. Collaborations with scientists of various fields such as neuroscience, immunology and drug discovery have further enhanced the ability to probe the role of metabolism in physiological processes. However, many behaviours, endocrine and biochemical processes, and the expression of genes, proteins and metabolites have daily ~24-h biological rhythms and thus peak only at specific times of the day. This daily variation can lead to incorrect interpretations, lack of reproducibility across laboratories and challenges in translating preclinical studies to humans. In this Review, we discuss the biological, environmental and experimental factors affecting circadian rhythms in rodents, which can in turn alter their metabolic pathways and the outcomes of experiments. We recommend that these variables be duly considered and suggest best practices for designing, analysing and reporting metabolic experiments in a circadian context.
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Affiliation(s)
- Shaunak Deota
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Ullas Kolthur-Seetharam
- Department of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, India
- Tata Institute of Fundamental Research, Hyderabad, India
| | - Karyn A Esser
- Department of Physiology and Aging, University of Florida, Gainesville, FL, USA
| | - Frédéric Gachon
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Gad Asher
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Charna Dibner
- Department of Surgery and Department of Cell Physiology and Metabolism, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Salvador Aznar Benitah
- Institute for Research in Biomedicine (IRB Barcelona), the Barcelona Institute for Science and Technology, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Carolina Escobar
- Departamento de Anatomía, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Deborah M Muoio
- Departments of Medicine and Pharmacology & Cancer Biology, Duke Molecular Physiology Institute, Durham, NC, USA
| | | | - Gökhan S Hotamışlıgil
- Sabri Ülker Center for Metabolic Research, Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joseph Bass
- Department of Medicine, Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Joseph S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Joshua D Rabinowitz
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Katja A Lamia
- Department of Molecular and Cellular Biology and Department of Molecular Medicine, the Scripps Research Institute, La Jolla, CA, USA
| | - Rafael de Cabo
- Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
| | - Shingo Kajimura
- Division of Endocrinology, Beth Israel Deaconess Medical Center, Harvard Medical School and Howard Hughes Medical Institute, Boston, MA, USA
| | - Valter D Longo
- Longevity Institute, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
- AIRC Institute of Molecular Oncology, Italian Foundation for Cancer Research Institute of Molecular Oncology, Milan, Italy
| | - Ying Xu
- CAM-SU Genomic Resource Center, Soochow University, Suzhou, China
| | - Mitchell A Lazar
- Institute for Diabetes, Obesity and Metabolism and Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Eric Verdin
- Buck Institute for Research on Aging, Novato, CA, USA
| | - Juleen R Zierath
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Daniel J Drucker
- The Lunenfeld-Tanenbaum Research Institute, Mt. Sinai Hospital and the Department of Medicine, University of Toronto, Toronto, Ontario, Canada
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Lloyd KCK. Commentary: The International Mouse Phenotyping Consortium: high-throughput in vivo functional annotation of the mammalian genome. Mamm Genome 2024; 35:537-543. [PMID: 39254744 PMCID: PMC11522054 DOI: 10.1007/s00335-024-10068-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 08/30/2024] [Indexed: 09/11/2024]
Abstract
The International Mouse Phenotyping Consortium (IMPC) is a worldwide effort producing and phenotyping knockout mouse lines to expose the pathophysiological roles of all genes in human diseases and make mice and data available and accessible to the global research community. It has created new knowledge on the function of thousands of genes for which little to anything was known. This new knowledge has informed the genetic basis of rare diseases, posited gene product influences on common diseases, influenced research on targeted therapies, revealed functional pleiotropy, essentiality, and sexual dimorphism, and many more insights into the role of genes in health and disease. Its scientific contributions have been many and widespread, however there remain thousands of "dark" genes yet to be illuminated. Nearing the end of its current funding cycle, IMPC is at a crossroads. The vision forward is clear, the path to proceed less so.
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Affiliation(s)
- K C Kent Lloyd
- Department of Surgery, School of Medicine, University of California, Davis, California, USA.
- Mouse Biology Program, University of California, Davis, California, USA.
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3
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Zhang X, Wang Y, Zheng M, Wei Q, Zhang R, Zhu K, Zhai Q, Xu Y. IMPC-based screening revealed that ROBO1 can regulate osteoporosis by inhibiting osteogenic differentiation. Front Cell Dev Biol 2024; 12:1450215. [PMID: 39439909 PMCID: PMC11494888 DOI: 10.3389/fcell.2024.1450215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Accepted: 09/26/2024] [Indexed: 10/25/2024] Open
Abstract
Introduction The utilization of denosumab in treating osteoporosis highlights promising prospects for osteoporosis intervention guided by gene targets. While omics-based research into osteoporosis pathogenesis yields a plethora of potential gene targets for clinical transformation, identifying effective gene targets has posed challenges. Methods We first queried the omics data of osteoporosis clinical samples on PubMed, used International Mouse Phenotyping Consortium (IMPC) to screen differentially expressed genes, and conducted preliminary functional verification of candidate genes in human Saos2 cells through osteogenic differentiation and mineralization experiments. We then selected the candidate genes with the most significant effects on osteogenic differentiation and further verified the osteogenic differentiation and mineralization functions in mouse 3T3-E1 and bone marrow mesenchymal stem cells (BMSC). Finally, we used RNA-seq to explore the regulation of osteogenesis by the target gene. Results We identified PPP2R2A, RRBP1, HSPB6, SLC22A15, ADAMTS4, ATP8B1, CTNNB1, ROBO1, and EFR3B, which may contribute to osteoporosis. ROBO1 was the most significant regulator of osteogenesis in both human and mouse osteoblast. The inhibitory effect of Robo1 knockdown on osteogenic differentiation may be related to the activation of inflammatory signaling pathways. Conclusion Our study provides several novel molecular mechanisms involved in the pathogenesis of osteoporosis. ROBO1 is a potential target for osteoporosis intervention.
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Affiliation(s)
- Xiangzheng Zhang
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yike Wang
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Miao Zheng
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qi Wei
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Ruizhi Zhang
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Keyu Zhu
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Qiaocheng Zhai
- Division of Spine Surgery, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People’s Hospital, Quzhou, China
| | - Youjia Xu
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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4
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Groza T, Gomez FL, Mashhadi HH, Muñoz-Fuentes V, Gunes O, Wilson R, Cacheiro P, Frost A, Keskivali-Bond P, Vardal B, McCoy A, Cheng TK, Santos L, Wells S, Smedley D, Mallon AM, Parkinson H. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease. Nucleic Acids Res 2023; 51:D1038-D1045. [PMID: 36305825 PMCID: PMC9825559 DOI: 10.1093/nar/gkac972] [Citation(s) in RCA: 217] [Impact Index Per Article: 108.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/05/2022] [Accepted: 10/14/2022] [Indexed: 01/30/2023] Open
Abstract
The International Mouse Phenotyping Consortium (IMPC; https://www.mousephenotype.org/) web portal makes available curated, integrated and analysed knockout mouse phenotyping data generated by the IMPC project consisting of 85M data points and over 95,000 statistically significant phenotype hits mapped to human diseases. The IMPC portal delivers a substantial reference dataset that supports the enrichment of various domain-specific projects and databases, as well as the wider research and clinical community, where the IMPC genotype-phenotype knowledge contributes to the molecular diagnosis of patients affected by rare disorders. Data from 9,000 mouse lines and 750 000 images provides vital resources enabling the interpretation of the ignorome, and advancing our knowledge on mammalian gene function and the mechanisms underlying phenotypes associated with human diseases. The resource is widely integrated and the lines have been used in over 4,600 publications indicating the value of the data and the materials.
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Affiliation(s)
- Tudor Groza
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Federico Lopez Gomez
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Hamed Haseli Mashhadi
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Violeta Muñoz-Fuentes
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Osman Gunes
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Robert Wilson
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
| | - Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Anthony Frost
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | | | - Bora Vardal
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Aaron McCoy
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Tsz Kwan Cheng
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Luis Santos
- Research Data Team, The Turing Institute, 96 Euston Rd, London NW1 2DB, UK
| | - Sara Wells
- Mary Lyon Centre at MRC Harwell, Harwell Campus OX11 7UE, UK
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Ann-Marie Mallon
- Research Data Team, The Turing Institute, 96 Euston Rd, London NW1 2DB, UK
| | - Helen Parkinson
- European Bioinformatics Institute, European Molecular Biology Laboratory, Welcome Genome Campus, Hinxton CB10 1SD, UK
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Wotton JM, Peterson E, Flenniken AM, Bains RS, Veeraragavan S, Bower LR, Bubier JA, Parisien M, Bezginov A, Haselimashhadi H, Mason J, Moore MA, Stewart ME, Clary DA, Delbarre DJ, Anderson LC, D'Souza A, Goodwin LO, Harrison ME, Huang Z, Mckay M, Qu D, Santos L, Srinivasan S, Urban R, Vukobradovic I, Ward CS, Willett AM, Braun RE, Brown SD, Dickinson ME, Heaney JD, Kumar V, Lloyd KK, Mallon AM, McKerlie C, Murray SA, Nutter LM, Parkinson H, Seavitt JR, Wells S, Samaco RC, Chesler EJ, Smedley D, Diatchenko L, Baumbauer KM, Young EE, Bonin RP, Mandillo S, White JK. Identifying genetic determinants of inflammatory pain in mice using a large-scale gene-targeted screen. Pain 2022; 163:1139-1157. [PMID: 35552317 PMCID: PMC9100450 DOI: 10.1097/j.pain.0000000000002481] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 08/17/2021] [Accepted: 09/07/2021] [Indexed: 02/03/2023]
Abstract
ABSTRACT Identifying the genetic determinants of pain is a scientific imperative given the magnitude of the global health burden that pain causes. Here, we report a genetic screen for nociception, performed under the auspices of the International Mouse Phenotyping Consortium. A biased set of 110 single-gene knockout mouse strains was screened for 1 or more nociception and hypersensitivity assays, including chemical nociception (formalin) and mechanical and thermal nociception (von Frey filaments and Hargreaves tests, respectively), with or without an inflammatory agent (complete Freund's adjuvant). We identified 13 single-gene knockout strains with altered nocifensive behavior in 1 or more assays. All these novel mouse models are openly available to the scientific community to study gene function. Two of the 13 genes (Gria1 and Htr3a) have been previously reported with nociception-related phenotypes in genetically engineered mouse strains and represent useful benchmarking standards. One of the 13 genes (Cnrip1) is known from human studies to play a role in pain modulation and the knockout mouse reported herein can be used to explore this function further. The remaining 10 genes (Abhd13, Alg6, BC048562, Cgnl1, Cp, Mmp16, Oxa1l, Tecpr2, Trim14, and Trim2) reveal novel pathways involved in nociception and may provide new knowledge to better understand genetic mechanisms of inflammatory pain and to serve as models for therapeutic target validation and drug development.
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Affiliation(s)
| | - Emma Peterson
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Ann M. Flenniken
- The Centre for Phenogenomics, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Rasneer S. Bains
- The Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Surabi Veeraragavan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, United States
| | - Lynette R. Bower
- Mouse Biology Program, University of California-Davis, Davis, CA, United States
| | | | - Marc Parisien
- Department of Anesthesia, Faculty of Medicine, Faculty of Dentistry, McGill University, Genome Building, Montreal, QC, Canada
| | - Alexandr Bezginov
- The Centre for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | - Hamed Haselimashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, United Kingdom
| | - Jeremy Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, United Kingdom
| | | | - Michelle E. Stewart
- The Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Dave A. Clary
- Mouse Biology Program, University of California-Davis, Davis, CA, United States
| | - Daniel J. Delbarre
- Mammalian Genetics Unit, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | | | - Abigail D'Souza
- The Centre for Phenogenomics, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | | | - Mark E. Harrison
- The Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Ziyue Huang
- The Centre for Phenogenomics, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Matthew Mckay
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Dawei Qu
- The Centre for Phenogenomics, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Luis Santos
- Mammalian Genetics Unit, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Subhiksha Srinivasan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | - Rachel Urban
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - Igor Vukobradovic
- The Centre for Phenogenomics, Toronto, ON, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Christopher S. Ward
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, United States
| | | | | | - Steve D.M. Brown
- Mammalian Genetics Unit, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Mary E. Dickinson
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX, United States
| | - Jason D. Heaney
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | - Vivek Kumar
- The Jackson Laboratory, Bar Harbor, ME, United States
| | - K.C. Kent Lloyd
- Mouse Biology Program, University of California-Davis, Davis, CA, United States
- Department of Surgery, School of Medicine, University of California-Davis, Davis, CA, United States
| | - Ann-Marie Mallon
- Mammalian Genetics Unit, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Colin McKerlie
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | | | - Lauryl M.J. Nutter
- The Centre for Phenogenomics, Toronto, ON, Canada
- The Hospital for Sick Children, Toronto, ON, Canada
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire, United Kingdom
| | - John R. Seavitt
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | - Sara Wells
- The Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxfordshire, United Kingdom
| | - Rodney C. Samaco
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, United States
| | | | - Damian Smedley
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Luda Diatchenko
- Department of Anesthesia, Faculty of Medicine, Faculty of Dentistry, McGill University, Genome Building, Montreal, QC, Canada
| | | | - Erin E. Young
- Anesthesiology, University of Kansas School of Medicine, KU Medical Center, Kansas City, KS, United States
| | - Robert P. Bonin
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| | - Silvia Mandillo
- Institute of Biochemistry and Cell Biology-National Research Council, IBBC-CNR, Monterotondo (RM), Italy
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Novel insights into the SPOP E3 ubiquitin ligase: From the regulation of molecular mechanisms to tumorigenesis. Biomed Pharmacother 2022; 149:112882. [PMID: 35364375 DOI: 10.1016/j.biopha.2022.112882] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/13/2022] [Accepted: 03/23/2022] [Indexed: 11/20/2022] Open
Abstract
Ubiquitin-mediated protein degradation is the primary biological process by which protein abundance is regulated and protein homeostasis is maintained in eukaryotic cells. Speckle-type pox virus and zinc finger (POZ) protein (SPOP) is a typical substrate adaptor of the Cullin 3-RING ligase (CRL3) family; it serves as a bridge between the Cullin 3 (Cul3) scaffold protein and its substrates. In recent years, SPOP has received increasing attention because of its versatility in its regulatory pathways and the diversity of tumor types involved. Mechanistically, SPOP substrates are involved in a wide range of biological processes, and abnormalities in SPOP function perturb downstream biological processes and promote tumorigenesis. Additionally, liquid-liquid phase separation (LLPS), a potential mechanism of membraneless organelle formation, was recently found to mediate the self-triggered colocalization of substrates with higher-order oligomers of SPOP. Herein, we summarize the structure of SPOP and the specific mechanisms by which it mediates the efficient ubiquitination of substrates. Additionally, we review the biological functions of SPOP, the regulation of SPOP expression, the role of SPOP in tumorigenesis and its therapeutic value.
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7
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Abstract
For many years, the laboratory mouse has been the favored model organism to study mammalian development, biology and disease. Among its advantages for these studies are its close concordance with human biology, the syntenic relationship between the mouse and other mammalian genomes, the existence of many inbred strains, its short gestation period, its relatively low cost for housing and husbandry, and the wide array of tools for genome modification, mutagenesis, and for cryopreserving embryos, sperm and eggs. The advent of CRISPR genome modification techniques has considerably broadened the landscape of model organisms available for study, including other mammalian species. However, the mouse remains the most popular and utilized system to model human development, biology, and disease processes. In this review, we will briefly summarize the long history of mice as a preferred mammalian genetic and model system, and review current large-scale mutagenesis efforts using genome modification to produce improved models for mammalian development and disease.
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Affiliation(s)
- Thomas Gridley
- Center for Clinical and Translational Research, Maine Medical Center Research Institute, Scarborough, ME, United States.
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8
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Minami Y, Yuan Y, Ueda HR. High-throughput Genetically Modified Animal Experiments Achieved by Next-generation Mammalian Genetics. J Biol Rhythms 2022; 37:135-151. [PMID: 35137623 DOI: 10.1177/07487304221075002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Animal models are essential tools for modern scientists to conduct biological experiments and investigate their hypotheses in vivo. However, for the past decade, raising the throughput of such animal experiments has been a great challenge. Conventionally, in vivo high-throughput assay was achieved through large-scale mutagen-driven forward genetic screening, which took years to find causal genes. In contrast, reverse genetics accelerated the causal gene identification process, but its throughput was also limited by 2 barriers, that is, the genome modification step and the time-consuming crossing step. Defined as genetics without crossing, next-generation genetics is able to produce gene-modified animals that can be analyzed at the founder generation (F0). This method is or can be accomplished through recent technological advances in gene editing and virus-based efficient gene modifications. Notably, next-generation genetics has accelerated the process of cross-species studies, and it will be a useful technique during animal experiments as it can provide genetic perturbation at an individual level without crossing. In this review, we begin by introducing the history of animal-based high-throughput analysis, with a specific focus on chronobiology. We then describe ways that gene modification efficiency during animal experiments was enhanced and why crossing remained a barrier to reaching higher efficiency. Moreover, we mention the Triple CRISPR as a critical technique for achieving next-generation genetics. Finally, we discuss the potential applications and limitations of next-generation mammalian genetics.
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Affiliation(s)
- Yoichi Minami
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yufei Yuan
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroki R Ueda
- Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.,Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, Suita, Japan
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9
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Minami Y, Yuan Y, Ueda HR. Towards organism-level systems biology by next-generation genetics and whole-organ cell profiling. Biophys Rev 2021; 13:1113-1126. [PMID: 35059031 PMCID: PMC8724464 DOI: 10.1007/s12551-021-00859-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 10/18/2021] [Indexed: 02/06/2023] Open
Abstract
The system-level identification and analysis of molecular and cellular networks in mammals can be accelerated by "next-generation" genetics, which is defined as genetics that can achieve desired genetic makeup in a single generation without any animal crossing. We recently established a highly efficient procedure for producing knock-out (KO) mice using the "Triple-CRISPR" method, which targets a single gene by triple gRNAs in the CRISPR/Cas9 system. This procedure achieved an almost perfect KO efficiency (96-100%). We also established a highly efficient procedure, the "ES-mouse" method, for producing knock-in (KI) mice within a single generation. In this method, ES cells were treated with three inhibitors to keep their potency and then injected into 8-cell-stage embryos. These procedures dramatically shortened the time required to produce KO or KI mice from years down to about 3 months. The produced KO and KI mice can also be systematically profiled at a single-cell resolution by the "whole-organ cell profiling," which was realized by tissue-clearing methods, such as CUBIC, and an advanced light-sheet microscopy. The review describes the establishment and application of these technologies above in analyzing the three states (NREM sleep, REM sleep, and awake) of mammalian brains. It also discusses the role of calcium and muscarinic receptors in these states as well as the current challenges and future opportunities in the next-generation mammalian genetics and whole-organ cell profiling for organism-level systems biology.
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Affiliation(s)
- Yoichi Minami
- Department of Systems Pharmacology, Graduate School of Medicine, the University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan
| | - Yufei Yuan
- Department of Systems Pharmacology, Graduate School of Medicine, the University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan
| | - Hiroki R. Ueda
- Department of Systems Pharmacology, Graduate School of Medicine, the University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan
- Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, 1-3 Yamadaoka, Suita, Osaka 565-0871 Japan
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10
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Brown SDM. Advances in mouse genetics for the study of human disease. Hum Mol Genet 2021; 30:R274-R284. [PMID: 34089057 PMCID: PMC8490014 DOI: 10.1093/hmg/ddab153] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/28/2021] [Accepted: 06/01/2021] [Indexed: 01/11/2023] Open
Abstract
The mouse is the pre-eminent model organism for studies of mammalian gene function and has provided an extraordinarily rich range of insights into basic genetic mechanisms and biological systems. Over several decades, the characterization of mouse mutants has illuminated the relationship between gene and phenotype, providing transformational insights into the genetic bases of disease. However, if we are to deliver the promise of genomic and precision medicine, we must develop a comprehensive catalogue of mammalian gene function that uncovers the dark genome and elucidates pleiotropy. Advances in large-scale mouse mutagenesis programmes allied to high-throughput mouse phenomics are now addressing this challenge and systematically revealing novel gene function and multi-morbidities. Alongside the development of these pan-genomic mutational resources, mouse genetics is employing a range of diversity resources to delineate gene-gene and gene-environment interactions and to explore genetic context. Critically, mouse genetics is a powerful tool for assessing the functional impact of human genetic variation and determining the causal relationship between variant and disease. Together these approaches provide unique opportunities to dissect in vivo mechanisms and systems to understand pathophysiology and disease. Moreover, the provision and utility of mouse models of disease has flourished and engages cumulatively at numerous points across the translational spectrum from basic mechanistic studies to pre-clinical studies, target discovery and therapeutic development.
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Hesse J, Malhan D, Yalҫin M, Aboumanify O, Basti A, Relógio A. An Optimal Time for Treatment-Predicting Circadian Time by Machine Learning and Mathematical Modelling. Cancers (Basel) 2020; 12:cancers12113103. [PMID: 33114254 PMCID: PMC7690897 DOI: 10.3390/cancers12113103] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/15/2020] [Accepted: 10/20/2020] [Indexed: 02/07/2023] Open
Abstract
Tailoring medical interventions to a particular patient and pathology has been termed personalized medicine. The outcome of cancer treatments is improved when the intervention is timed in accordance with the patient's internal time. Yet, one challenge of personalized medicine is how to consider the biological time of the patient. Prerequisite for this so-called chronotherapy is an accurate characterization of the internal circadian time of the patient. As an alternative to time-consuming measurements in a sleep-laboratory, recent studies in chronobiology predict circadian time by applying machine learning approaches and mathematical modelling to easier accessible observables such as gene expression. Embedding these results into the mathematical dynamics between clock and cancer in mammals, we review the precision of predictions and the potential usage with respect to cancer treatment and discuss whether the patient's internal time and circadian observables, may provide an additional indication for individualized treatment timing. Besides the health improvement, timing treatment may imply financial advantages, by ameliorating side effects of treatments, thus reducing costs. Summarizing the advances of recent years, this review brings together the current clinical standard for measuring biological time, the general assessment of circadian rhythmicity, the usage of rhythmic variables to predict biological time and models of circadian rhythmicity.
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Affiliation(s)
- Janina Hesse
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
| | - Deeksha Malhan
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
| | - Müge Yalҫin
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
| | - Ouda Aboumanify
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
| | - Alireza Basti
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
| | - Angela Relógio
- Institute for Theoretical Biology (ITB), Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany; (J.H.); (D.M.); (M.Y.); (O.A.); (A.B.)
- Molecular Cancer Research Center (MKFZ), Medical Department of Hematology, Oncology and Tumor Immunology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin Humboldt—Universität zu Berlin and Berlin Institute of Health, 10117 Berlin, Germany
- Department of Human Medicine, Institute for Systems Medicine and Bioinformatics, MSH Medical School Hamburg—University of Applied Sciences and Medical University, 20457 Hamburg, Germany
- Correspondence: or
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Brown LA, Banks GT, Horner N, Wilcox SL, Nolan PM, Peirson SN. Simultaneous Assessment of Circadian Rhythms and Sleep in Mice Using Passive Infrared Sensors: A User's Guide. CURRENT PROTOCOLS IN MOUSE BIOLOGY 2020; 10:e81. [PMID: 32865891 PMCID: PMC7617235 DOI: 10.1002/cpmo.81] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The 24-hr cycle of activity and sleep provides perhaps the most familiar example of circadian rhythms. In mammals, circadian activity rhythms are generated by a master biological clock located in the hypothalamic suprachiasmatic nuclei (SCN). This clock is synchronized (entrained) to the external light environment via light input from retinal photoreceptors. However, sleep is not a simple circadian output and also is regulated by a homeostatic process whereby extended wakefulness increases the need for subsequent sleep. As such, the amount and distribution of sleep depends upon the interaction between both circadian and homeostatic processes. Moreover, the study of circadian activity and sleep is not confined only to these specialized fields. Sleep and circadian rhythm disruption is common in many conditions, ranging from neurological and metabolic disorders to aging. Such disruption is associated with a range of negative consequences including cognitive impairment and mood disorders, as well as immune and metabolic dysfunction. As circadian activity and sleep are hallmarks of normal healthy physiology, they also provide valuable welfare indicators. However, traditional methods for the monitoring of circadian rhythms and sleep in mice can require separate specialized resources as well as significant expertise. Here, we outline a low-cost, non-invasive, and open-source method for the simultaneous assessment of circadian activity and sleep in mice. This protocol describes both the assembly of the hardware used and the capture and analysis of data without the need for expertise in electronics or data processing. © 2020 Wiley Periodicals LLC. Basic Protocol: Assembly of a PIR system for basic activity and sleep recordings Alternate Protocol: Data collection using Raspberry Pi Support Protocol: Circadian analysis using PIR sensors.
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Affiliation(s)
- Laurence A. Brown
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
- Research Support Team, IT Services, University of Oxford, UK
| | | | - Neil Horner
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Sian L. Wilcox
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | | | - Stuart N. Peirson
- Sleep and Circadian Neuroscience Institute (SCNi), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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