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Lambourne L, Mattioli K, Santoso C, Sheynkman G, Inukai S, Kaundal B, Berenson A, Spirohn-Fitzgerald K, Bhattacharjee A, Rothman E, Shrestha S, Laval F, Yang Z, Bisht D, Sewell JA, Li G, Prasad A, Phanor S, Lane R, Campbell DM, Hunt T, Balcha D, Gebbia M, Twizere JC, Hao T, Frankish A, Riback JA, Salomonis N, Calderwood MA, Hill DE, Sahni N, Vidal M, Bulyk ML, Fuxman Bass JI. Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.584681. [PMID: 38617209 PMCID: PMC11014633 DOI: 10.1101/2024.03.12.584681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Most human Transcription factors (TFs) genes encode multiple protein isoforms differing in DNA binding domains, effector domains, or other protein regions. The global extent to which this results in functional differences between isoforms remains unknown. Here, we systematically compared 693 isoforms of 246 TF genes, assessing DNA binding, protein binding, transcriptional activation, subcellular localization, and condensate formation. Relative to reference isoforms, two-thirds of alternative TF isoforms exhibit differences in one or more molecular activities, which often could not be predicted from sequence. We observed two primary categories of alternative TF isoforms: "rewirers" and "negative regulators", both of which were associated with differentiation and cancer. Our results support a model wherein the relative expression levels of, and interactions involving, TF isoforms add an understudied layer of complexity to gene regulatory networks, demonstrating the importance of isoform-aware characterization of TF functions and providing a rich resource for further studies.
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Affiliation(s)
- Luke Lambourne
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kaia Mattioli
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clarissa Santoso
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
| | - Gloria Sheynkman
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sachi Inukai
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Babita Kaundal
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Anna Berenson
- Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, MA, USA
| | - Kerstin Spirohn-Fitzgerald
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Anukana Bhattacharjee
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Elisabeth Rothman
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Florent Laval
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- TERRA Teaching and Research Centre, University of Liège, Gembloux, Belgium
- Laboratory of Viral Interactomes, GIGA Institute, University of Liège, Liège, Belgium
| | - Zhipeng Yang
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Deepa Bisht
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jared A Sewell
- Department of Biology, Boston University, Boston, MA, USA
| | - Guangyuan Li
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Anisa Prasad
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard College, Cambridge MA, USA
| | - Sabrina Phanor
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ryan Lane
- Department of Biology, Boston University, Boston, MA, USA
| | | | - Toby Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Dawit Balcha
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Marinella Gebbia
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute (LTRI), Sinai Health System, Toronto, Ontario, Canada
| | - Jean-Claude Twizere
- TERRA Teaching and Research Centre, University of Liège, Gembloux, Belgium
- Laboratory of Viral Interactomes, GIGA Institute, University of Liège, Liège, Belgium
| | - Tong Hao
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Adam Frankish
- Laboratory of Viral Interactomes, GIGA Institute, University of Liège, Liège, Belgium
| | - Josh A Riback
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
| | - Nathan Salomonis
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Michael A Calderwood
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - David E Hill
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Nidhi Sahni
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Marc Vidal
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Martha L Bulyk
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Juan I Fuxman Bass
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
- Molecular Biology, Cell Biology & Biochemistry Program, Boston University, Boston, MA, USA
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2
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de Biase MS, Massip F, Wei TT, Giorgi FM, Stark R, Stone A, Gladwell A, O'Reilly M, Schütte D, de Santiago I, Meyer KB, Markowetz F, Ponder BAJ, Rintoul RC, Schwarz RF. Smoking-associated gene expression alterations in nasal epithelium reveal immune impairment linked to lung cancer risk. Genome Med 2024; 16:54. [PMID: 38589970 PMCID: PMC11000304 DOI: 10.1186/s13073-024-01317-4] [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: 03/31/2023] [Accepted: 03/18/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, 40% of which occur more than 15 years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk remain unclear. We thus set out to examine whether risk stratification in the clinic and in the general population can be improved upon by the addition of genetic data and to explore the mechanisms of the persisting risk in former smokers. METHODS We analysed transcriptomic data from accessible airway tissues of 487 subjects, including healthy volunteers and clinic patients of different smoking statuses. We developed a computational model to assess smoking-associated gene expression changes and their reversibility after smoking is stopped, comparing healthy subjects to clinic patients with and without lung cancer. RESULTS We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune- and interferon-related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. CONCLUSIONS Our results provide initial evidence for germline-mediated personalized smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.
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Affiliation(s)
- Maria Stella de Biase
- Berlin Institute of Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Strasse 28, 10115, Berlin, Germany.
| | - Florian Massip
- Berlin Institute of Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Strasse 28, 10115, Berlin, Germany.
- MINES Paris, PSL University, CBIO-Centre for Computational Biology, 60 bd Saint Michel, 75006, Paris, France.
- Institut Curie, Cedex, Paris, France.
- INSERM, U900, Cedex, Paris, France.
| | - Tzu-Ting Wei
- Berlin Institute of Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Strasse 28, 10115, Berlin, Germany
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Federico M Giorgi
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
- Present Address: Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Rory Stark
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
| | - Amanda Stone
- Papworth Trials Unit Collaboration, Department of Oncology, Royal Papworth Hospital NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0AY, UK
| | - Amy Gladwell
- Papworth Trials Unit Collaboration, Department of Oncology, Royal Papworth Hospital NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0AY, UK
| | - Martin O'Reilly
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
- Present Address: MRC Toxicology Unit, Tennis Court Road, Cambridge, CB2 1QR, UK
| | - Daniel Schütte
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Am Weyertal 115C, Gebäude 74, 50931, Cologne, Germany
| | - Ines de Santiago
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
- Present Address: e-therapeutics plc, 17 Blenheim Office Park, Long Hanborough, OX29 8LN, UK
| | - Kerstin B Meyer
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
- Present Address: The Wellcome Sanger Institute, Hinxton, CB10 1SA, UK
| | - Florian Markowetz
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK
| | - Bruce A J Ponder
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK.
| | - Robert C Rintoul
- Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0AY, UK.
- Papworth Trials Unit Collaboration, Department of Oncology, Royal Papworth Hospital NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, CB2 0AY, UK.
- Department of Oncology, Early Cancer Institute, University of Cambridge, Cambridge, CB2 0XZ, UK.
| | - Roland F Schwarz
- Berlin Institute of Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Hannoversche Strasse 28, 10115, Berlin, Germany.
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany.
- Institute for Computational Cancer Biology (ICCB), Center for Integrated Oncology (CIO), Cancer Research Center Cologne Essen (CCCE), Faculty of Medicine and University Hospital Cologne, University of Cologne, Am Weyertal 115C, Gebäude 74, 50931, Cologne, Germany.
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Inge MM, Miller R, Hook H, Bray D, Keenan JL, Zhao R, Gilmore TD, Siggers T. Rapid profiling of transcription factor-cofactor interaction networks reveals principles of epigenetic regulation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588333. [PMID: 38617258 PMCID: PMC11014505 DOI: 10.1101/2024.04.05.588333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Transcription factor (TF)-cofactor (COF) interactions define dynamic, cell-specific networks that govern gene expression; however, these networks are understudied due to a lack of methods for high-throughput profiling of DNA-bound TF-COF complexes. Here we describe the Cofactor Recruitment (CoRec) method for rapid profiling of cell-specific TF-COF complexes. We define a lysine acetyltransferase (KAT)-TF network in resting and stimulated T cells. We find promiscuous recruitment of KATs for many TFs and that 35% of KAT-TF interactions are condition specific. KAT-TF interactions identify NF-κB as a primary regulator of acutely induced H3K27ac. Finally, we find that heterotypic clustering of CBP/P300-recruiting TFs is a strong predictor of total promoter H3K27ac. Our data supports clustering of TF sites that broadly recruit KATs as a mechanism for widespread co-occurring histone acetylation marks. CoRec can be readily applied to different cell systems and provides a powerful approach to define TF-COF networks impacting chromatin state and gene regulation.
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Affiliation(s)
- MM Inge
- Department of Biology, Boston University, Boston, MA, USA
- Biological Design Center, Boston University, Boston, MA, USA
- These authors contributed equally
| | - R Miller
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
- Biological Design Center, Boston University, Boston, MA, USA
- These authors contributed equally
| | - H Hook
- Department of Biology, Boston University, Boston, MA, USA
| | - D Bray
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
| | - JL Keenan
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
| | - R Zhao
- Department of Biology, Boston University, Boston, MA, USA
| | - TD Gilmore
- Department of Biology, Boston University, Boston, MA, USA
| | - T Siggers
- Department of Biology, Boston University, Boston, MA, USA
- Bioinformatics Program, Boston University, Boston, MA, USA
- Biological Design Center, Boston University, Boston, MA, USA
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Fu M, Lu S, Gong L, Zhou Y, Wei F, Duan Z, Xiang R, Gonzalez FJ, Li G. Intermittent fasting shifts the diurnal transcriptome atlas of transcription factors. Mol Cell Biochem 2024:10.1007/s11010-024-04928-y. [PMID: 38528297 DOI: 10.1007/s11010-024-04928-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/05/2024] [Indexed: 03/27/2024]
Abstract
Intermittent fasting remains a safe and effective strategy to ameliorate various age-related diseases, but its specific mechanisms are not fully understood. Considering that transcription factors (TFs) determine the response to environmental signals, here, we profiled the diurnal expression of 600 samples across four metabolic tissues sampled every 4 over 24 h from mice placed on five different feeding regimens to provide an atlas of TFs in biological space, time, and feeding regimen. Results showed that 1218 TFs exhibited tissue-specific and temporal expression profiles in ad libitum mice, of which 974 displayed significant oscillations at least in one tissue. Intermittent fasting triggered more than 90% (1161 in 1234) of TFs to oscillate somewhere in the body and repartitioned their tissue-specific expression. A single round of fasting generally promoted TF expression, especially in skeletal muscle and adipose tissues, while intermittent fasting mainly suppressed TF expression. Intermittent fasting down-regulated aging pathway and upregulated the pathway responsible for the inhibition of mammalian target of rapamycin (mTOR). Intermittent fasting shifts the diurnal transcriptome atlas of TFs, and mTOR inhibition may orchestrate intermittent fasting-induced health improvements. This atlas offers a reference and resource to understand how TFs and intermittent fasting may contribute to diurnal rhythm oscillation and bring about specific health benefits.
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Affiliation(s)
- Min Fu
- Department of Neurology, The Fourth Hospital of Changsha, Affiliated Changsha Hospital of Hunan Normal University, Changsha, 410006, Hunan, China
| | - Siyu Lu
- Key Laboratory of Hunan Province for Model Animal and Stem Cell Biology, School of Medicine, Hunan Normal University, Changsha, 410081, Hunan, China
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China
| | - Lijun Gong
- Key Laboratory of Hunan Province for Model Animal and Stem Cell Biology, School of Medicine, Hunan Normal University, Changsha, 410081, Hunan, China
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China
| | - Yiming Zhou
- Key Laboratory of Hunan Province for Model Animal and Stem Cell Biology, School of Medicine, Hunan Normal University, Changsha, 410081, Hunan, China
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China
| | - Fang Wei
- Department of Neurology, The Fourth Hospital of Changsha, Affiliated Changsha Hospital of Hunan Normal University, Changsha, 410006, Hunan, China.
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China.
| | - Zhigui Duan
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China
| | - Rong Xiang
- Department of Cell Biology, School of Life Sciences, Central South University, Changsha, 41001, Hunan, China
| | - Frank J Gonzalez
- Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Guolin Li
- Key Laboratory of Hunan Province for Model Animal and Stem Cell Biology, School of Medicine, Hunan Normal University, Changsha, 410081, Hunan, China.
- Center for Aging Biomedicine, National & Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China.
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Xu X, Charrier A, Congrove S, Buchner DA. Cell-state dependent regulation of PPAR γ signaling by ZBTB9 in adipocytes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.04.583402. [PMID: 38496622 PMCID: PMC10942320 DOI: 10.1101/2024.03.04.583402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Adipocytes play a critical role in metabolic homeostasis. Peroxisome proliferator-activated receptor- γ (PPAR γ ) is a nuclear hormone receptor that is a master regulator of adipocyte differentiation and function. ZBTB9 was predicted to interact with PPAR γ based on large-scale protein interaction experiments. In addition, GWAS studies in the type 2 diabetes (T2D) Knowledge Portal revealed associations between Z btb9 and both BMI and T2D risk. Here we show that ZBTB9 positively regulates PPAR γ activity in mature adipocytes. Surprisingly Z btb9 knockdown (KD) also increased adipogenesis in 3T3-L1 cells and human preadipocytes. E2F activity was increased and E2F downstream target genes were upregulated in Zbtb9 -KD preadipocytes. Accordingly, RB phosphorylation, which regulates E2F activity, was enhanced in Zbtb9 -KD preadipocytes. Critically, an E2F1 inhibitor blocked the effects of Zbtb9 deficiency on adipogenic gene expression and lipid accumulation. Collectively, these results demonstrate that Zbtb9 inhibits adipogenesis as a negative regulator of Pparg expression via altered RB-E2F1 signaling. Our findings reveal complex cell-state dependent roles of ZBTB9 in adipocytes, identifying a new molecule that regulates adipogenesis and adipocyte biology as both a positive and negative regulator of PPAR γ signaling depending on the cellular context, and thus may be important in the pathogenesis and treatment of obesity and T2D.
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Liao Z, Tang S, Jiang P, Geng T, Cope DI, Dunn TN, Guner J, Radilla LA, Guan X, Monsivais D. Impaired bone morphogenetic protein (BMP) signaling pathways disrupt decidualization in endometriosis. Commun Biol 2024; 7:227. [PMID: 38402336 PMCID: PMC10894266 DOI: 10.1038/s42003-024-05898-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 02/07/2024] [Indexed: 02/26/2024] Open
Abstract
Endometriosis is linked to increased infertility and pregnancy complications due to defective endometrial decidualization. We hypothesized that identification of altered signaling pathways during decidualization could identify the underlying cause of infertility and pregnancy complications. Our study reveals that transforming growth factor β (TGFβ) pathways are impaired in the endometrium of individuals with endometriosis, leading to defective decidualization. Through detailed transcriptomic analyses, we discovered abnormalities in TGFβ signaling pathways and key regulators, such as SMAD4, in the endometrium of affected individuals. We also observed compromised activity of bone morphogenetic proteins (BMP), a subset of the TGFβ family, that control endometrial receptivity. Using 3-dimensional models of endometrial stromal and epithelial assembloids, we showed that exogenous BMP2 improved decidual marker expression in individuals with endometriosis. Our findings reveal dysfunction of BMP/SMAD signaling in the endometrium of individuals with endometriosis, explaining decidualization defects and subsequent pregnancy complications in these individuals.
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Affiliation(s)
- Zian Liao
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Graduate Program of Genetics and Genomics, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Suni Tang
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Peixin Jiang
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Thoracic/Head and Neck Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ting Geng
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Dominique I Cope
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Timothy N Dunn
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
- Division of Reproductive Endocrinology & Infertility, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Joie Guner
- Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, University of Southern California, Los Angeles, CA, 90033, USA
| | - Linda Alpuing Radilla
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Xiaoming Guan
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Diana Monsivais
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA.
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA.
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7
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Kucinski I, Campos J, Barile M, Severi F, Bohin N, Moreira PN, Allen L, Lawson H, Haltalli MLR, Kinston SJ, O'Carroll D, Kranc KR, Göttgens B. A time- and single-cell-resolved model of murine bone marrow hematopoiesis. Cell Stem Cell 2024; 31:244-259.e10. [PMID: 38183977 PMCID: PMC7615671 DOI: 10.1016/j.stem.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 09/25/2023] [Accepted: 12/04/2023] [Indexed: 01/08/2024]
Abstract
The paradigmatic hematopoietic tree model is increasingly recognized to be limited, as it is based on heterogeneous populations largely defined by non-homeostatic assays testing cell fate potentials. Here, we combine persistent labeling with time-series single-cell RNA sequencing to build a real-time, quantitative model of in vivo tissue dynamics for murine bone marrow hematopoiesis. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of differentiation at specific stages of erythroid and neutrophil production, illustrating how the model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a kinetoscope allows sequential images to merge into a movie. We posit that this approach is generally applicable to understanding tissue-scale dynamics at high resolution.
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Affiliation(s)
- Iwo Kucinski
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Joana Campos
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; Institute of Cancer Research, London SM2 5NG, UK
| | - Melania Barile
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK; Centre for Translational Stem Cell Biology, Hong Kong SAR, China
| | - Francesco Severi
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Natacha Bohin
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Pedro N Moreira
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Lewis Allen
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; Institute of Cancer Research, London SM2 5NG, UK
| | - Hannah Lawson
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; Institute of Cancer Research, London SM2 5NG, UK
| | - Myriam L R Haltalli
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Sarah J Kinston
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK
| | - Dónal O'Carroll
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh EH16 4UU, UK; Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, UK.
| | - Kamil R Kranc
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK; Institute of Cancer Research, London SM2 5NG, UK.
| | - Berthold Göttgens
- Wellcome-MRC Cambridge Stem Cell Institute, Department of Haematology, Jeffrey Cheah Biomedical Centre, University of Cambridge, Cambridge, UK.
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8
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Swain T, Pflueger C, Freytag S, Poppe D, Pflueger J, Nguyen T, Li J, Lister R. A modular dCas9-based recruitment platform for combinatorial epigenome editing. Nucleic Acids Res 2024; 52:474-491. [PMID: 38000387 PMCID: PMC10783489 DOI: 10.1093/nar/gkad1108] [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: 08/05/2022] [Revised: 09/28/2023] [Accepted: 11/02/2023] [Indexed: 11/26/2023] Open
Abstract
Targeted epigenome editing tools allow precise manipulation and investigation of genome modifications, however they often display high context dependency and variable efficacy between target genes and cell types. While systems that simultaneously recruit multiple distinct 'effector' chromatin regulators can improve efficacy, they generally lack control over effector composition and spatial organisation. To overcome this we have created a modular combinatorial epigenome editing platform, called SSSavi. This system is an interchangeable and reconfigurable docking platform fused to dCas9 that enables simultaneous recruitment of up to four different effectors, allowing precise control of effector composition and spatial ordering. We demonstrate the activity and specificity of the SSSavi system and, by testing it against existing multi-effector targeting systems, demonstrate its comparable efficacy. Furthermore, we demonstrate the importance of the spatial ordering of the recruited effectors for effective transcriptional regulation. Together, the SSSavi system enables exploration of combinatorial effector co-recruitment to enhance manipulation of chromatin contexts previously resistant to targeted editing.
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Affiliation(s)
- Tessa Swain
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
| | - Christian Pflueger
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Saskia Freytag
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
| | - Daniel Poppe
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Jahnvi Pflueger
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
| | - Trung Viet Nguyen
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
| | - Ji Kevin Li
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
| | - Ryan Lister
- Harry Perkins Institute of Medical Research, Nedlands, Western Australia 6009, Australia
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Crawley, Western Australia 6009, Australia
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9
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Feng C, Song C, Song S, Zhang G, Yin M, Zhang Y, Qian F, Wang Q, Guo M, Li C. KnockTF 2.0: a comprehensive gene expression profile database with knockdown/knockout of transcription (co-)factors in multiple species. Nucleic Acids Res 2024; 52:D183-D193. [PMID: 37956336 PMCID: PMC10767813 DOI: 10.1093/nar/gkad1016] [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: 09/15/2023] [Revised: 10/17/2023] [Accepted: 10/28/2023] [Indexed: 11/15/2023] Open
Abstract
Transcription factors (TFs), transcription co-factors (TcoFs) and their target genes perform essential functions in diseases and biological processes. KnockTF 2.0 (http://www.licpathway.net/KnockTF/index.html) aims to provide comprehensive gene expression profile datasets before/after T(co)F knockdown/knockout across multiple tissue/cell types of different species. Compared with KnockTF 1.0, KnockTF 2.0 has the following improvements: (i) Newly added T(co)F knockdown/knockout datasets in mice, Arabidopsis thaliana and Zea mays and also an expanded scale of datasets in humans. Currently, KnockTF 2.0 stores 1468 manually curated RNA-seq and microarray datasets associated with 612 TFs and 172 TcoFs disrupted by different knockdown/knockout techniques, which are 2.5 times larger than those of KnockTF 1.0. (ii) Newly added (epi)genetic annotations for T(co)F target genes in humans and mice, such as super-enhancers, common SNPs, methylation sites and chromatin interactions. (iii) Newly embedded and updated search and analysis tools, including T(co)F Enrichment (GSEA), Pathway Downstream Analysis and Search by Target Gene (BLAST). KnockTF 2.0 is a comprehensive update of KnockTF 1.0, which provides more T(co)F knockdown/knockout datasets and (epi)genetic annotations across multiple species than KnockTF 1.0. KnockTF 2.0 facilitates not only the identification of functional T(co)Fs and target genes but also the investigation of their roles in the physiological and pathological processes.
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Affiliation(s)
- Chenchen Feng
- National Health Commission Key Laboratory of Birth Defect Research and Prevention & School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing, 163319, China
| | - Chao Song
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Shuang Song
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Guorui Zhang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Yuexin Zhang
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Fengcui Qian
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Qiuyu Wang
- National Health Commission Key Laboratory of Birth Defect Research and Prevention & School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Maozu Guo
- School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
| | - Chunquan Li
- National Health Commission Key Laboratory of Birth Defect Research and Prevention & School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan, 421001, China
- MOE Key Lab of Rare Pediatric Diseases, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
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10
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Acencio ML, Vazquez M, Chawla K, Lægreid A, Kuiper M. TFCheckpoint database update, a cross-referencing system for transcription factors from human, mouse and rat. Nucleic Acids Res 2024; 52:D334-D344. [PMID: 37992291 PMCID: PMC10767992 DOI: 10.1093/nar/gkad1030] [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: 08/29/2023] [Revised: 10/20/2023] [Accepted: 10/21/2023] [Indexed: 11/24/2023] Open
Abstract
Prior knowledge about DNA-binding transcription factors (dbTFs), transcription co-regulators (coTFs) and general transcriptional factors (GTFs) is crucial for the study and understanding of the regulation of transcription. This is reflected by the many publications and database resources describing knowledge about TFs. We previously launched the TFCheckpoint database, an integrated resource focused on human, mouse and rat dbTFs, providing users access to a comprehensive overview of these proteins. Here, we describe TFCheckpoint 2.0 (https://www.tfcheckpoint.org/index.php), comprising 13 collections of dbTFs, coTFs and GTFs. TFCheckpoint 2.0 provides an easy and versatile cross-referencing system for users to view and download collections that may otherwise be cumbersome to find, compare and retrieve.
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Affiliation(s)
- Marcio L Acencio
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NO-7491, Norway
| | - Miguel Vazquez
- Barcelona Supercomputing Center, Barcelona, 08034, Spain
| | - Konika Chawla
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NO-7491, Norway
- Bioinformatics Core Facility, St. Olavs hospital HF, Trondheim, NO-7491, Norway
| | - Astrid Lægreid
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, NO-7491, Norway
| | - Martin Kuiper
- Department of Biology, Norwegian University of Science and Technology, Trondheim, NO-7491, Norway
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11
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Lu C, Garipler G, Dai C, Roush T, Salome-Correa J, Martin A, Liscovitch-Brauer N, Mazzoni EO, Sanjana NE. Essential transcription factors for induced neuron differentiation. Nat Commun 2023; 14:8362. [PMID: 38102126 PMCID: PMC10724217 DOI: 10.1038/s41467-023-43602-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/14/2023] [Indexed: 12/17/2023] Open
Abstract
Neurogenins are proneural transcription factors required to specify neuronal identity. Their overexpression in human pluripotent stem cells rapidly produces cortical-like neurons with spiking activity and, because of this, they have been widely adopted for human neuron disease models. However, we do not fully understand the key downstream regulatory effectors responsible for driving neural differentiation. Here, using inducible expression of NEUROG1 and NEUROG2, we identify transcription factors (TFs) required for directed neuronal differentiation by combining expression and chromatin accessibility analyses with a pooled in vitro CRISPR-Cas9 screen targeting all ~1900 TFs in the human genome. The loss of one of these essential TFs (ZBTB18) yields few MAP2-positive neurons. Differentiated ZBTB18-null cells have radically altered gene expression, leading to cytoskeletal defects and stunted neurites and spines. In addition to identifying key downstream TFs for neuronal differentiation, our work develops an integrative multi-omics and TFome-wide perturbation platform to rapidly characterize essential TFs for the differentiation of any human cell type.
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Affiliation(s)
- Congyi Lu
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Görkem Garipler
- Department of Biology, New York University, New York, NY, USA
| | - Chao Dai
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Timothy Roush
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Jose Salome-Correa
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Alex Martin
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Noa Liscovitch-Brauer
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
| | - Esteban O Mazzoni
- Department of Biology, New York University, New York, NY, USA.
- Department of Cell Biology, NYU Grossman School of Medicine, New York, NY, USA.
| | - Neville E Sanjana
- New York Genome Center, New York, NY, USA.
- Department of Biology, New York University, New York, NY, USA.
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12
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Ruan Z, Cao G, Qian Y, Fu L, Hu J, Xu T, Wu Y, Lv Y. Single-cell RNA sequencing unveils Lrg1's role in cerebral ischemia‒reperfusion injury by modulating various cells. J Neuroinflammation 2023; 20:285. [PMID: 38037097 PMCID: PMC10687904 DOI: 10.1186/s12974-023-02941-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral ischemia‒reperfusion injury causes significant harm to human health and is a major contributor to stroke-related deaths worldwide. Current treatments are limited, and new, more effective prevention and treatment strategies that target multiple cell components are urgently needed. Leucine-rich alpha-2 glycoprotein 1 (Lrg1) appears to be associated with the progression of cerebral ischemia‒reperfusion injury, but the exact mechanism of it is unknown. METHODS Wild-type (WT) and Lrg1 knockout (Lrg1-/-) mice were used to investigate the role of Lrg1 after cerebral ischemia‒reperfusion injury. The effects of Lrg1 knockout on brain infarct volume, blood‒brain barrier permeability, and neurological score (based on 2,3,5-triphenyl tetrazolium chloride, evans blue dye, hematoxylin, and eosin staining) were assessed. Single-cell RNA sequencing (scRNA-seq), immunofluorescence, and microvascular albumin leakage tests were utilized to investigate alterations in various cell components in brain tissue after Lrg1 knockout. RESULTS Lrg1 expression was increased in various cell types of brain tissue after cerebral ischemia‒reperfusion injury. Lrg1 knockout reduced cerebral edema and infarct size and improved neurological function after cerebral ischemia‒reperfusion injury. Single-cell RNA sequencing analysis of WT and Lrg1-/- mouse brain tissues after cerebral ischemia‒reperfusion injury revealed that Lrg1 knockout enhances blood‒brain barrier (BBB) by upregulating claudin 11, integrin β5, protocadherin 9, and annexin A2. Lrg1 knockout also promoted an anti-inflammatory and tissue-repairing phenotype in microglia and macrophages while reducing neuron and oligodendrocyte cell death. CONCLUSIONS Our results has shown that Lrg1 mediates numerous pathological processes involved in cerebral ischemia‒reperfusion injury by altering the functional states of various cell types, thereby rendering it a promising therapeutic target for cerebral ischemia‒reperfusion injury.
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Affiliation(s)
- Zhaohui Ruan
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Guosheng Cao
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China
| | - Yisong Qian
- School of Clinical Medicine, Nanchang University, Nanchang, China
| | - Longsheng Fu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Jinfang Hu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tiantian Xu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yaoqi Wu
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yanni Lv
- Department of Pharmacy, The First Affiliated Hospital of Nanchang University, Nanchang, China.
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13
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Monsivais D, Liao Z, Tang S, Jiang P, Geng T, Cope D, Dunn T, Guner J, Radilla LA, Guan X. Impaired bone morphogenetic protein (BMP) signaling pathways disrupt decidualization in endometriosis. RESEARCH SQUARE 2023:rs.3.rs-3471243. [PMID: 37986901 PMCID: PMC10659538 DOI: 10.21203/rs.3.rs-3471243/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Endometriosis is linked to increased infertility and pregnancy complications due to defective endometrial decidualization. We hypothesized that identification of altered signaling pathways during decidualization could identify the underlying cause of infertility and pregnancy complications. Our study reveals that transforming growth factor β (TGFβ) pathways are impaired in the endometrium of individuals with endometriosis, leading to defective decidualization. Through detailed transcriptomic analyses, we discovered abnormalities in TGFβ signaling pathways and key regulators, such as SMAD4, in the endometrium of affected individuals. We also observed compromised activity of bone morphogenetic proteins (BMP), a subset of the TGFβ family, that control endometrial receptivity. Using 3-dimensional models of endometrial stromal and epithelial assembloids, we showed that exogenous BMP2 improved decidual marker expression in individuals with endometriosis. Our findings unveil a previously unidentified dysfunction in BMP/SMAD signaling in the endometrium of individuals with endometriosis, explaining decidualization defects and subsequent pregnancy complications in these individuals.
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14
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Chen HY, Phan BN, Shim G, Hamersky GR, Sadowski N, O'Donnell TS, Sripathy SR, Bohlen JF, Pfenning AR, Maher BJ. Psychiatric risk gene Transcription Factor 4 (TCF4) regulates the density and connectivity of distinct inhibitory interneuron subtypes. Mol Psychiatry 2023; 28:4679-4692. [PMID: 37770578 PMCID: PMC11144438 DOI: 10.1038/s41380-023-02248-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 08/17/2023] [Accepted: 08/30/2023] [Indexed: 09/30/2023]
Abstract
Transcription factor 4 (TCF4) is a basic helix-loop-helix transcription factor that is implicated in a variety of psychiatric disorders including autism spectrum disorder (ASD), major depression, and schizophrenia. Autosomal dominant mutations in TCF4 are causal for a specific ASD called Pitt-Hopkins Syndrome (PTHS). However, our understanding of etiological and pathophysiological mechanisms downstream of TCF4 mutations is incomplete. Single cell sequencing indicates TCF4 is highly expressed in GABAergic interneurons (INs). Here, we performed cell-type specific expression analysis (CSEA) and cellular deconvolution (CD) on bulk RNA sequencing data from 5 different PTHS mouse models. Using CSEA we observed differentially expressed genes (DEGs) were enriched in parvalbumin expressing (PV+) INs and CD predicted a reduction in the PV+ INs population. Therefore, we investigated the role of TCF4 in regulating the development and function of INs in the Tcf4+/tr mouse model of PTHS. In Tcf4+/tr mice, immunohistochemical (IHC) analysis of subtype-specific IN markers and reporter mice identified reductions in PV+, vasoactive intestinal peptide (VIP+), and cortistatin (CST+) expressing INs in the cortex and cholinergic (ChAT+) INs in the striatum, with the somatostatin (SST+) IN population being spared. The reduction of these specific IN populations led to cell-type specific alterations in the balance of excitatory and inhibitory inputs onto PV+ and VIP+ INs and excitatory pyramidal neurons within the cortex. These data indicate TCF4 is a critical regulator of the development of specific subsets of INs and highlight the inhibitory network as an important source of pathophysiology in PTHS.
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Affiliation(s)
- Huei-Ying Chen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - BaDoi N Phan
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA
| | - Gina Shim
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Gregory R Hamersky
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Norah Sadowski
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Thomas S O'Donnell
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Srinidhi Rao Sripathy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Joseph F Bohlen
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA
| | - Andreas R Pfenning
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA
| | - Brady J Maher
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, 21205, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA.
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.
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15
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Berenson A, Lane R, Soto-Ugaldi LF, Patel M, Ciausu C, Li Z, Chen Y, Shah S, Santoso C, Liu X, Spirohn K, Hao T, Hill DE, Vidal M, Fuxman Bass JI. Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors. Nat Commun 2023; 14:6570. [PMID: 37853017 PMCID: PMC10584920 DOI: 10.1038/s41467-023-42445-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 10/11/2023] [Indexed: 10/20/2023] Open
Abstract
Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.
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Affiliation(s)
- Anna Berenson
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Ryan Lane
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Luis F Soto-Ugaldi
- Tri-Institutional Program in Computational Biology and Medicine, New York, NY, USA
| | - Mahir Patel
- Department of Computer Science, Boston University, Boston, MA, 02215, USA
| | - Cosmin Ciausu
- Department of Computer Science, Boston University, Boston, MA, 02215, USA
| | - Zhaorong Li
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Yilin Chen
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Sakshi Shah
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Clarissa Santoso
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Xing Liu
- Department of Biology, Boston University, Boston, MA, 02215, USA
| | - Kerstin Spirohn
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Tong Hao
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - David E Hill
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Marc Vidal
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, 02115, USA
| | - Juan I Fuxman Bass
- Department of Biology, Boston University, Boston, MA, 02215, USA.
- Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, 02215, USA.
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16
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Fancher AT, Hua Y, Close DA, Xu W, McDermott LA, Strock CJ, Santiago U, Camacho CJ, Johnston PA. Characterization of allosteric modulators that disrupt androgen receptor co-activator protein-protein interactions to alter transactivation-Drug leads for metastatic castration resistant prostate cancer. SLAS DISCOVERY : ADVANCING LIFE SCIENCES R & D 2023; 28:325-343. [PMID: 37549772 DOI: 10.1016/j.slasd.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/06/2023] [Accepted: 08/04/2023] [Indexed: 08/09/2023]
Abstract
Three series of compounds were prioritized from a high content screening campaign that identified molecules that blocked dihydrotestosterone (DHT) induced formation of Androgen Receptor (AR) protein-protein interactions (PPIs) with the Transcriptional Intermediary Factor 2 (TIF2) coactivator and also disrupted preformed AR-TIF2 PPI complexes; the hydrobenzo-oxazepins (S1), thiadiazol-5-piperidine-carboxamides (S2), and phenyl-methyl-indoles (S3). Compounds from these series inhibited AR PPIs with TIF2 and SRC-1, another p160 coactivator, in mammalian 2-hybrid assays and blocked transcriptional activation in reporter assays driven by full length AR or AR-V7 splice variants. Compounds inhibited the growth of five prostate cancer cell lines, with many exhibiting differential cytotoxicity towards AR positive cell lines. Representative compounds from the 3 series substantially reduced both endogenous and DHT-enhanced expression and secretion of the prostate specific antigen (PSA) cancer biomarker in the C4-2 castration resistant prostate cancer (CRPC) cell line. The comparatively weak activities of series compounds in the H3-DHT and/or TIF2 box 3 LXXLL-peptide binding assays to the recombinant ligand binding domain of AR suggest that direct antagonism at the orthosteric ligand binding site or AF-2 surface respectively are unlikely mechanisms of action. Cellular enhanced thermal stability assays (CETSA) indicated that compounds engaged AR and reduced the maximum efficacy and right shifted the EC50 of DHT-enhanced AR thermal stabilization consistent with the effects of negative allosteric modulators. Molecular docking of potent representative hits from each series to AR structures suggest that S1-1 and S2-6 engage a novel binding pocket (BP-1) adjacent to the orthosteric ligand binding site, while S3-11 occupies the AR binding function 3 (BF-3) allosteric pocket. Hit binding poses indicate spaces and residues adjacent to the BP-1 and BF-3 pockets that will be exploited in future medicinal chemistry optimization studies. Small molecule allosteric modulators that prevent/disrupt AR PPIs with coactivators like TIF2 to alter transcriptional activation in the presence of orthosteric agonists might evade the resistance mechanisms to existing prostate cancer drugs and provide novel starting points for medicinal chemistry lead optimization and future development into therapies for metastatic CRPC.
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Affiliation(s)
- Ashley T Fancher
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; Nucleus Global, 2 Ravinia Drive, Suite 605, Atlanta, GA 30346, USA
| | - Yun Hua
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - David A Close
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Wei Xu
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA
| | - Lee A McDermott
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; PsychoGenics Inc, 215 College Road, Paramus, NJ 07652, USA
| | | | - Ulises Santiago
- Department of Computational and Systems Biology, School of Medicine, at the University of Pittsburgh, USA
| | - Carlos J Camacho
- Department of Computational and Systems Biology, School of Medicine, at the University of Pittsburgh, USA
| | - Paul A Johnston
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; University of Pittsburgh Hillman Cancer Center, Pittsburgh, PA 15232, USA.
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17
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Liao Z, Tang S, Jiang P, Geng T, Cope DI, Dunn TN, Guner J, Radilla LA, Guan X, Monsivais D. Impaired bone morphogenetic protein signaling pathways disrupt decidualization in endometriosis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.21.558268. [PMID: 37790548 PMCID: PMC10542516 DOI: 10.1101/2023.09.21.558268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
It is hypothesized that impaired endometrial decidualization contributes to decreased fertility in individuals with endometriosis. To identify the molecular defects that underpin defective decidualization in endometriosis, we subjected endometrial stromal cells from individuals with or without endometriosis to time course in vitro decidualization with estradiol, progesterone, and 8-bromo-cyclic-AMP (EPC) for 2, 4, 6, or 8 days. Transcriptomic profiling identified differences in key pathways between the two groups, including defective bone morphogenetic protein (BMP)/SMAD4 signaling (ID2, ID3, FST), oxidate stress response (NFE2L2, ALOX15, SLC40A1), and retinoic acid signaling pathways (RARRES, RARB, ALDH1B1). Genome-wide binding analyses identified an altered genomic distribution of SMAD4 and H3K27Ac in the decidualized stromal cells from individuals without endometriosis relative to those with endometriosis, with target genes enriched in pathways related to signaling by transforming growth factor β (TGFβ), neurotrophic tyrosine kinase receptors (NTRK), and nerve growth factor (NGF)-stimulated transcription. We found that direct SMAD1/5/4 target genes control FOXO, PI3K/AKT, and progesterone-mediated signaling in decidualizing cells and that BMP2 supplementation in endometriosis patient-derived assembloids elevated the expression of decidualization markers. In summary, transcriptomic and genome-wide binding analyses of patient-derived endometrial cells and assembloids identified that a functional BMP/SMAD1/5/4 signaling program is crucial for engaging decidualization.
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Affiliation(s)
- Zian Liao
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Graduate Program of Genetics and Genomics, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Suni Tang
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Peixin Jiang
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Thoracic/Head and Neck Medical Oncology, the University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ting Geng
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Dominique I. Cope
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Timothy N. Dunn
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
- Division of Reproductive Endocrinology & Infertility, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Joie Guner
- Department of Obstetrics and Gynecology, Division of Reproductive Endocrinology and Infertility, University of Southern California, Los Angeles, CA, 90033, USA
| | - Linda Alpuing Radilla
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Xiaoming Guan
- Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Diana Monsivais
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, TX, 77030, USA
- Center for Drug Discovery, Baylor College of Medicine, Houston, TX, 77030, USA
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18
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Mukund AX, Tycko J, Allen SJ, Robinson SA, Andrews C, Sinha J, Ludwig CH, Spees K, Bassik MC, Bintu L. High-throughput functional characterization of combinations of transcriptional activators and repressors. Cell Syst 2023; 14:746-763.e5. [PMID: 37543039 PMCID: PMC10642976 DOI: 10.1016/j.cels.2023.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 06/26/2023] [Accepted: 07/06/2023] [Indexed: 08/07/2023]
Abstract
Despite growing knowledge of the functions of individual human transcriptional effector domains, much less is understood about how multiple effector domains within the same protein combine to regulate gene expression. Here, we measure transcriptional activity for 8,400 effector domain combinations by recruiting them to reporter genes in human cells. In our assay, weak and moderate activation domains synergize to drive strong gene expression, whereas combining strong activators often results in weaker activation. In contrast, repressors combine linearly and produce full gene silencing, and repressor domains often overpower activation domains. We use this information to build a synthetic transcription factor whose function can be tuned between repression and activation independent of recruitment to target genes by using a small-molecule drug. Altogether, we outline the basic principles of how effector domains combine to regulate gene expression and demonstrate their value in building precise and flexible synthetic biology tools. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Adi X Mukund
- Biophysics Program, Stanford University, Stanford, CA 94305, USA
| | - Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Sage J Allen
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | | | - Cecelia Andrews
- Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA
| | - Joydeb Sinha
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA 94305, USA
| | - Connor H Ludwig
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Kaitlyn Spees
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Michael C Bassik
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
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Wiegreffe C, Ehricke S, Schmid L, Andratschke J, Britsch S. Using i-GONAD for Cell-Type-Specific and Systematic Analysis of Developmental Transcription Factors In Vivo. BIOLOGY 2023; 12:1236. [PMID: 37759634 PMCID: PMC10526018 DOI: 10.3390/biology12091236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 09/08/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023]
Abstract
Transcription factors (TFs) regulate gene expression via direct DNA binding together with cofactors and in chromatin remodeling complexes. Their function is thus regulated in a spatiotemporal and cell-type-specific manner. To analyze the functions of TFs in a cell-type-specific context, genome-wide DNA binding, as well as the identification of interacting proteins, is required. We used i-GONAD (improved genome editing via oviductal nucleic acids delivery) in mice to genetically modify TFs by adding fluorescent reporter and affinity tags that can be exploited for the imaging and enrichment of target cells as well as chromatin immunoprecipitation and pull-down assays. As proof-of-principle, we showed the functional genetic modification of the closely related developmental TFs, Bcl11a and Bcl11b, in defined cell types of newborn mice. i-GONAD is a highly efficient procedure for modifying TF-encoding genes via the integration of small insertions, such as reporter and affinity tags. The novel Bcl11a and Bcl11b mouse lines, described in this study, will be used to improve our understanding of the Bcl11 family's function in neurodevelopment and associated disease.
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Affiliation(s)
- Christoph Wiegreffe
- Medical Faculty, Institute of Molecular and Cellular Anatomy, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany
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20
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Figiel M, Górka AK, Górecki A. Zinc Ions Modulate YY1 Activity: Relevance in Carcinogenesis. Cancers (Basel) 2023; 15:4338. [PMID: 37686614 PMCID: PMC10487186 DOI: 10.3390/cancers15174338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/17/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
YY1 is widely recognized as an intrinsically disordered transcription factor that plays a role in development of many cancers. In most cases, its overexpression is correlated with tumor progression and unfavorable patient outcomes. Our latest research focusing on the role of zinc ions in modulating YY1's interaction with DNA demonstrated that zinc enhances the protein's multimeric state and affinity to its operator. In light of these findings, changes in protein concentration appear to be just one element relevant to modulating YY1-dependent processes. Thus, alterations in zinc ion concentration can directly and specifically impact the regulation of gene expression by YY1, in line with reports indicating a correlation between zinc ion levels and advancement of certain tumors. This review concentrates on other potential consequences of YY1 interaction with zinc ions that may act by altering charge distribution, conformational state distribution, or oligomerization to influence its interactions with molecular partners that can disrupt gene expression patterns.
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Affiliation(s)
| | | | - Andrzej Górecki
- Faculty of Biochemistry, Biophysics and Biotechnology, Department of Physical Biochemistry, Jagiellonian University, Gronostajowa 7, 30-387 Kraków, Poland; (M.F.); (A.K.G.)
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21
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Wang Y, Wei Z, Su J, Coenen F, Meng J. RgnTX: Colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity. Comput Struct Biotechnol J 2023; 21:4110-4117. [PMID: 37671241 PMCID: PMC10475473 DOI: 10.1016/j.csbj.2023.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 08/13/2023] [Accepted: 08/23/2023] [Indexed: 09/07/2023] Open
Abstract
Colocalization analysis of genomic region sets has been widely adopted to unveil potential functional interactions between corresponding biological attributes, which often serves as the basis for further investigation. A number of methods have been developed for colocalization analysis of genomic elements. However, none of them explicitly considered the transcriptome heterogeneity and isoform ambiguity, making them less appropriate for analyzing transcriptome elements. Here, we developed RgnTX, an R/Bioconductor tool for the colocalization analysis of transcriptome elements with permutation tests. Different from existing approaches, RgnTX directly takes advantage of transcriptome annotation, and offers high flexibility in the null model to simulate realistic transcriptome-wide background, such as the complex alternative splicing patterns. Importantly, it supports the testing of transcriptome elements without clear isoform association, which is often the real scenario due to technical limitations. Proposed package offers a wide selection of pre-defined functions, easy to be utilized by users for visualizing permutation results, calculating shifted z-scores and conducting multiple hypothesis testing under Benjamini-Hochberg correction. Moreover, with synthetic and real datasets, we show that RgnTX novel testing modes return distinct and more significant results compared to existing genome-based methods. We believe RgnTX should make a useful tool to characterize the randomness of the transcriptome, and for conducting statistical association analysis for genomic region sets within the heterogeneous transcriptome. The package now has been accepted by Bioconductor and is freely available at: https://bioconductor.org/packages/RgnTX.
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Affiliation(s)
- Yue Wang
- Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Department of Computer Science, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Zhen Wei
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Jionglong Su
- School of AI and Advanced Computing, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
| | - Frans Coenen
- Department of Computer Science, University of Liverpool, L69 7ZB Liverpool, United Kingdom
| | - Jia Meng
- Department of Biological Sciences, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- AI University Research Centre, Xi’an Jiaotong-Liverpool University, Suzhou, Jiangsu 215123, China
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, L69 7ZB Liverpool, United Kingdom
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22
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Illingworth EJ, Maertens A, Sillé FCM. Transcriptomic Effects of Low-Dose Inorganic Arsenic Exposure on Murine Bone Marrow-Derived Macrophages. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.26.550543. [PMID: 37546857 PMCID: PMC10402011 DOI: 10.1101/2023.07.26.550543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Both tissue-resident macrophages and monocytes recruited from the bone marrow that transform into tissue-resident cells play critical roles in mediating homeostasis as well as in the pathology of inflammatory diseases. Inorganic arsenic (iAs) is the most common drinking water contaminant worldwide and represents a major public health concern. Several diseases that macrophages have implicated involvement in are caused by iAs exposure, including cardiovascular disease, cancer, and increased risk of infectious disease. Therefore, understanding the effects of iAs exposure on macrophages can help us better grasp the full range of arsenic immunotoxicity and better design therapeutic targets for iAs-induced diseases particularly in exposed populations. In this study, we analyzed the transcriptome of low dose iAs-exposed male and female murine bone marrow-derived macrophages (BMDMs) with either M0, M1, or M2 stimulation. We identified differentially expressed genes by iAs in a sex- and stimulation-dependent manner and used bioinformatics tools to predict protein-protein interactions, transcriptional regulatory networks, and associated biological processes. Overall, our data suggest that M1-stimulated, especially female-derived, BMDMs are most susceptible to iAs exposure. Most notably, we observed significant downregulation of major proinflammatory transcription factors, like IRF8, and its downstream targets, as well as genes encoding proteins involved in pattern recognition and antigen presentation, such as TLR7, TLR8, and H2-D1, potentially providing causal insight regarding arsenic's role in perturbing immune responses to infectious diseases. We also observed significant downregulation of genes involved in processes crucial to coordinating a proinflammatory response including leukocyte migration, differentiation, and cytokine and chemokine production and response. Finally, we discovered that 24 X-linked genes were dysregulated in iAs-exposed female stimulation groups compared to only 3 across the iAs-exposed male stimulation groups. These findings elucidate the potential mechanisms underlying the sex-differential iAs-associated immune-related disease risk.
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23
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D'Artista L, Moschopoulou AA, Barozzi I, Craig AJ, Seehawer M, Herrmann L, Minnich M, Kang TW, Rist E, Henning M, Klotz S, Heinzmann F, Harbig J, Sipos B, Longerich T, Eilers M, Dauch D, Zuber J, Wang XW, Zender L. MYC determines lineage commitment in KRAS-driven primary liver cancer development. J Hepatol 2023; 79:141-149. [PMID: 36906109 PMCID: PMC10330789 DOI: 10.1016/j.jhep.2023.02.039] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/24/2023] [Accepted: 02/28/2023] [Indexed: 03/13/2023]
Abstract
BACKGROUND & AIMS Primary liver cancer (PLC) comprises hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), two frequent and lethal tumour types that differ regarding their tumour biology and responses to cancer therapies. Liver cells harbour a high degree of cellular plasticity and can give rise to either HCC or iCCA. However, little is known about the cell-intrinsic mechanisms directing an oncogenically transformed liver cell to either HCC or iCCA. The scope of this study was to identify cell-intrinsic factors determining lineage commitment in PLC. METHODS Cross-species transcriptomic and epigenetic profiling was applied to murine HCCs and iCCAs and to two human PLC cohorts. Integrative data analysis comprised epigenetic Landscape In Silico deletion Analysis (LISA) of transcriptomic data and Hypergeometric Optimization of Motif EnRichment (HOMER) analysis of chromatin accessibility data. Identified candidate genes were subjected to functional genetic testing in non-germline genetically engineered PLC mouse models (shRNAmir knockdown or overexpression of full-length cDNAs). RESULTS Integrative bioinformatic analyses of transcriptomic and epigenetic data pinpointed the Forkhead-family transcription factors FOXA1 and FOXA2 as MYC-dependent determination factors of the HCC lineage. Conversely, the ETS family transcription factor ETS1 was identified as a determinant of the iCCA lineage, which was found to be suppressed by MYC during HCC development. Strikingly, shRNA-mediated suppression of FOXA1 and FOXA2 with concomitant ETS1 expression fully switched HCC to iCCA development in PLC mouse models. CONCLUSIONS The herein reported data establish MYC as a key determinant of lineage commitment in PLC and provide a molecular explanation why common liver-damaging risk factors such as alcoholic or non-alcoholic steatohepatitis can lead to either HCC or iCCA. IMPACT AND IMPLICATIONS Liver cancer is a major health problem and comprises hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA), two frequent and lethal tumour types that differ regarding their morphology, tumour biology, and responses to cancer therapies. We identified the transcription factor and oncogenic master regulator MYC as a switch between HCC and iCCA development. When MYC levels are high at the time point when a hepatocyte becomes a tumour cell, an HCC is growing out. Conversely, if MYC levels are low at this time point, the result is the outgrowth of an iCCA. Our study provides a molecular explanation why common liver-damaging risk factors such as alcoholic or non-alcoholic steatohepatitis can lead to either HCC or iCCA. Furthermore, our data harbour potential for the development of better PLC therapies.
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Affiliation(s)
- Luana D'Artista
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Athina Anastasia Moschopoulou
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Iros Barozzi
- Institute of Cancer Research, Department of Medicine I, Medical University of Vienna, Vienna, Austria; Department of Surgery and Cancer, Imperial College London, London, UK
| | - Amanda J Craig
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Marco Seehawer
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Lea Herrmann
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Martina Minnich
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria
| | - Tae-Won Kang
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Elke Rist
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Melanie Henning
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Sabrina Klotz
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Florian Heinzmann
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Jule Harbig
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Bence Sipos
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany
| | - Thomas Longerich
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | - Martin Eilers
- Theodor Boveri Institute, Department of Biochemistry and Molecular Biology, Biocenter, University of Wuerzburg, Wuerzburg, Germany
| | - Daniel Dauch
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany
| | - Johannes Zuber
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria; Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
| | - Xin Wei Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA; Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Lars Zender
- Department of Medical Oncology and Pneumology (Internal Medicine VIII), University Hospital Tuebingen, Tuebingen, Germany; iFIT Cluster of Excellence EXC 2180 'Image Guided and Functionally Instructed Tumor Therapies', University of Tuebingen, Tuebingen, Germany; German Cancer Research Consortium (DKTK), Partner Site Tübingen, German Cancer Research Center (DKFZ), Heidelberg, Germany.
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24
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Catta-Preta R, Lindtner S, Ypsilanti A, Price J, Abnousi A, Su-Feher L, Wang Y, Juric I, Jones IR, Akiyama JA, Hu M, Shen Y, Visel A, Pennacchio LA, Dickel D, Rubenstein JLR, Nord AS. Combinatorial transcription factor binding encodes cis-regulatory wiring of forebrain GABAergic neurogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.28.546894. [PMID: 37425940 PMCID: PMC10327028 DOI: 10.1101/2023.06.28.546894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Transcription factors (TFs) bind combinatorially to genomic cis-regulatory elements (cREs), orchestrating transcription programs. While studies of chromatin state and chromosomal interactions have revealed dynamic neurodevelopmental cRE landscapes, parallel understanding of the underlying TF binding lags. To elucidate the combinatorial TF-cRE interactions driving mouse basal ganglia development, we integrated ChIP-seq for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and transcriptional state, and transgenic enhancer assays. We identified TF-cREs modules with distinct chromatin features and enhancer activity that have complementary roles driving GABAergic neurogenesis and suppressing other developmental fates. While the majority of distal cREs were bound by one or two TFs, a small proportion were extensively bound, and these enhancers also exhibited exceptional evolutionary conservation, motif density, and complex chromosomal interactions. Our results provide new insights into how modules of combinatorial TF-cRE interactions activate and repress developmental expression programs and demonstrate the value of TF binding data in modeling gene regulatory wiring.
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Affiliation(s)
- Rinaldo Catta-Preta
- Department of Neurobiology, Physiology and Behavior, and Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95618, USA
- Current Address: Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Susan Lindtner
- Nina Ireland Laboratory of Developmental Neurobiology, Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Athena Ypsilanti
- Nina Ireland Laboratory of Developmental Neurobiology, Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - James Price
- Nina Ireland Laboratory of Developmental Neurobiology, Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Armen Abnousi
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44106, USA
- Current Address: NovaSignal, Los Angeles, CA 90064, USA
| | - Linda Su-Feher
- Department of Neurobiology, Physiology and Behavior, and Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95618, USA
| | - Yurong Wang
- Department of Neurobiology, Physiology and Behavior, and Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95618, USA
| | - Ivan Juric
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44106, USA
| | - Ian R Jones
- Institute for Human Genetics, Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Jennifer A Akiyama
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44106, USA
| | - Yin Shen
- Institute for Human Genetics, Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Neurology, University of California, San Francisco, CA 94143, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
- School of Natural Sciences, University of California, Merced, Merced, CA 95343, USA
| | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
- Comparative Biochemistry Program, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Diane Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - John L R Rubenstein
- Nina Ireland Laboratory of Developmental Neurobiology, Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alex S Nord
- Department of Neurobiology, Physiology and Behavior, and Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis, CA 95618, USA
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25
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Huang W, Lin W, Chen B, Zhang J, Gao P, Fan Y, Lin Y, Wei P. NFAT and NF-κB dynamically co-regulate TCR and CAR signaling responses in human T cells. Cell Rep 2023; 42:112663. [PMID: 37347664 DOI: 10.1016/j.celrep.2023.112663] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 04/02/2023] [Accepted: 06/02/2023] [Indexed: 06/24/2023] Open
Abstract
While it has been established that the responses of T cells to antigens are combinatorially regulated by multiple signaling pathways, it remains elusive what mechanisms cells utilize to quantitatively modulate T cell responses during pathway integration. Here, we show that two key pathways in T cell signaling, calcium/nuclear factor of activated T cells (NFAT) and protein kinase C (PKC)/nuclear factor κB (NF-κB), integrate through a dynamic and combinatorial strategy to fine-tune T cell response genes. At the cis-regulatory level, the two pathways integrate through co-binding of NFAT and NF-κB to immune response genes. Pathway integration is further regulated temporally, where T cell receptor (TCR) and chimeric antigen receptor (CAR) activation signals modulate the temporal relationships between the nuclear localization dynamics of NFAT and NF-κB. Such physical and temporal integrations together contribute to distinct modes of expression modulation for genes. Thus, the temporal relationships between regulators can be modulated to affect their co-targets during immune responses, underscoring the importance of dynamic combinatorial regulation in cellular signaling.
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Affiliation(s)
- Wen Huang
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Wei Lin
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Baoqiang Chen
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China; School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jianhan Zhang
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China
| | - Peifen Gao
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Yingying Fan
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yihan Lin
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; The MOE Key Laboratory of Cell Proliferation and Differentiation, School of Life Sciences, Peking University, Beijing 100871, China.
| | - Ping Wei
- Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.
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26
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Wang Y, Peng J, Song C, Yang Y, Qin T. Zinc finger and SCAN domain-containing 18 suppresses the proliferation, self-renewal, and drug resistance of glioblastoma cells. Heliyon 2023; 9:e17000. [PMID: 37389038 PMCID: PMC10300323 DOI: 10.1016/j.heliyon.2023.e17000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 07/01/2023] Open
Abstract
Elucidation of cellular and molecular mechanisms key to glioblastoma growth, self-renewal, survival, and metastasis is important for developing novel therapeutic strategies. In this study, the expression and function of zinc finger and SCAN domain-containing 18 (ZSCAN18) in human glioblastoma cell lines were characterized. Compared with normal astrocytes, ZSCAN18 was significantly down-regulated in all tested glioblastoma cell lines, with the LN-229 cell line having the lowest ZSCAN18 expression. Lentivirus-mediated ZSCAN18 overexpression suppressed glioblastoma cell proliferation, sphere formation, and SOX2 and OCT4 expression, implying the negative role of ZSCAN18 in glioblastoma development. ZSCAN18 overexpression enhanced the sensitivity of glioblastoma cells to Temozolomide. The glioblastoma implantation model showed a consistent inhibitory effect of ZSCAN18 on the proliferation and self-renewal of glioblastoma cells in vivo. Notably, ZSCAN18 overexpression resulted in the down-regulation of glioma-associated oncogene homolog 1 (GLI1) which is the terminal component of the Hedgehog signaling. Lentivirus-mediated GLI1 overexpression restored the proliferation and promoted the resistance of glioblastoma cells to Temozolomide. However, GLI1 overexpression did not affect the self-renewal of ZSCAN18-overexpressing glioblastoma cells. Taken together, this research uncovers the role of ZSCAN18 in regulating glioblastoma cell growth and maintenance. ZSCAN18 could be a potential glioblastoma biomarker.
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Affiliation(s)
- Yan Wang
- The Pediatric Care and Rehabilitation Division at Affiliated Renhe Hospital of China Three Gorges University, Yichang City, Hubei Province, 443000, China
| | - Jingwei Peng
- The Department of Pediatrics at Affiliated Renhe Hospital of China Three Gorges University, Yichang City, Hubei Province, 443000, China
| | - Chenchen Song
- The Pediatric Care and Rehabilitation Division at Affiliated Renhe Hospital of China Three Gorges University, Yichang City, Hubei Province, 443000, China
| | - Yining Yang
- The Pediatric Care and Rehabilitation Division at Affiliated Renhe Hospital of China Three Gorges University, Yichang City, Hubei Province, 443000, China
| | - Tao Qin
- The Department of Radiology and Radiotherapy at Xingshan County People's Hospital, Yichang City, Hubei Province, 443700, China
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27
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Kumar DK, Jonas F, Jana T, Brodsky S, Carmi M, Barkai N. Complementary strategies for directing in vivo transcription factor binding through DNA binding domains and intrinsically disordered regions. Mol Cell 2023; 83:1462-1473.e5. [PMID: 37116493 DOI: 10.1016/j.molcel.2023.04.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 01/17/2023] [Accepted: 01/30/2023] [Indexed: 04/30/2023]
Abstract
DNA binding domains (DBDs) of transcription factors (TFs) recognize DNA sequence motifs that are highly abundant in genomes. Within cells, TFs bind a subset of motif-containing sites as directed by either their DBDs or DBD-external (nonDBD) sequences. To define the relative roles of DBDs and nonDBDs in directing binding preferences, we compared the genome-wide binding of 48 (∼30%) budding yeast TFs with their DBD-only, nonDBD-truncated, and nonDBD-only mutants. With a few exceptions, binding locations differed between DBDs and TFs, resulting from the cumulative action of multiple determinants mapped mostly to disordered nonDBD regions. Furthermore, TFs' preferences for promoters of the fuzzy nucleosome architecture were lost in DBD-only mutants, whose binding spread across promoters, implicating nonDBDs' preferences in this hallmark of budding yeast regulatory design. We conclude that DBDs and nonDBDs employ complementary DNA-targeting strategies, whose balance defines TF binding specificity along genomes.
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Affiliation(s)
- Divya Krishna Kumar
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Felix Jonas
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Tamar Jana
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Sagie Brodsky
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Miri Carmi
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Naama Barkai
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.
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28
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Balagannavar G, Basavaraju K, Bajpai AK, Davuluri S, Kannan S, S Srini V, S Chandrashekar D, Chitturi N, K Acharya K. Transcriptomic analysis of the Non-Obstructive Azoospermia (NOA) to address gene expression regulation in human testis. Syst Biol Reprod Med 2023; 69:196-214. [PMID: 36883778 DOI: 10.1080/19396368.2023.2176268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
There is a need to understand the molecular basis of testes under Non-Obstructive Azoospermia (NOA), a state of failed spermatogenesis. There has been a lack of attention to the transcriptome at the level of alternatively spliced mRNAs (iso-mRNAs) and the mechanism of gene expression regulation. Hence, we aimed to establish a reliable iso-mRNA profile of NOA-testes, and explore molecular mechanisms - especially those related to gene expression regulation. We sequenced mRNAs from testicular samples of donors with complete spermatogenesis (control samples) and a failure of spermatogenesis (NOA samples). We identified differentially expressed genes and their iso-mRNAs via standard NGS data analyses. We then listed these iso-mRNAs hierarchically based on the extent of consistency of differential quantities across samples and groups, and validated the lists via RT-qPCRs (for 80 iso-mRNAs). In addition, we performed extensive bioinformatic analysis of the splicing features, domains, interactions, and functions of differentially expressed genes and iso-mRNAs. Many top-ranking down-regulated genes and iso-mRNAs, i.e., those down-regulated more consistently across the NOA samples, are associated with mitosis, replication, meiosis, cilium, RNA regulation, and post-translational modifications such as ubiquitination and phosphorylation. Most down-regulated iso-mRNAs correspond to full-length proteins that include all expected domains. The predominance of alternative promoters and termination sites in these iso-mRNAs indicate their gene expression regulation via promoters and UTRs. We compiled a new, comprehensive list of human transcription factors (TFs) and used it to identify TF-'TF gene' interactions with potential significance in down-regulating genes under the NOA condition. The results indicate that RAD51 suppression by HSF4 prevents SP1-activation, and SP1, in turn, could regulate multiple TF genes. This potential regulatory axis and other TF interactions identified in this study could explain the down-regulation of multiple genes in NOA-testes. Such molecular interactions may also have key regulatory roles during normal human spermatogenesis.
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Affiliation(s)
- Govindkumar Balagannavar
- Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru, Karnataka, India.,Research Scholar, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India
| | - Kavyashree Basavaraju
- Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru, Karnataka, India.,BdataA: Biological data Analyzers' Association (virtual organization http://startbioinfo.com/BdataA/), India
| | - Akhilesh Kumar Bajpai
- BdataA: Biological data Analyzers' Association (virtual organization http://startbioinfo.com/BdataA/), India
| | - Sravanthi Davuluri
- BdataA: Biological data Analyzers' Association (virtual organization http://startbioinfo.com/BdataA/), India
| | - Shruthi Kannan
- Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru, Karnataka, India
| | - Vasan S Srini
- Manipal Fertility, Manipal Hospital, Bengaluru, Karnataka, India
| | | | - Neelima Chitturi
- BdataA: Biological data Analyzers' Association (virtual organization http://startbioinfo.com/BdataA/), India
| | - Kshitish K Acharya
- Institute of Bioinformatics and Applied Biotechnology (IBAB), Bengaluru, Karnataka, India.,BdataA: Biological data Analyzers' Association (virtual organization http://startbioinfo.com/BdataA/), India
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29
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Köse TB, Li J, Ritz A. Growing Directed Acyclic Graphs: Optimization Functions for Pathway Reconstruction Algorithms. J Comput Biol 2023. [PMID: 36862510 DOI: 10.1089/cmb.2022.0376] [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: 03/03/2023] Open
Abstract
A major challenge in molecular systems biology is to understand how proteins work to transmit external signals to changes in gene expression. Computationally reconstructing these signaling pathways from protein interaction networks can help understand what is missing from existing pathway databases. We formulate a new pathway reconstruction problem, one that iteratively grows directed acyclic graphs (DAGs) from a set of starting proteins in a protein interaction network. We present an algorithm that provably returns the optimal DAGs for two different cost functions and evaluate the pathway reconstructions when applied to six diverse signaling pathways from the NetPath database. The optimal DAGs outperform an existing k-shortest paths method for pathway reconstruction, and the new reconstructions are enriched for different biological processes. Growing DAGs is a promising step toward reconstructing pathways that provably optimize a specific cost function.
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Affiliation(s)
- Tunç Başar Köse
- Department of Computer Science and Reed College, Portland, Oregon, USA
| | - Jiarong Li
- Department of Computer Science and Reed College, Portland, Oregon, USA
| | - Anna Ritz
- Department of Biology, Reed College, Portland, Oregon, USA
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30
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Neill G, Masson GR. A stay of execution: ATF4 regulation and potential outcomes for the integrated stress response. Front Mol Neurosci 2023; 16:1112253. [PMID: 36825279 PMCID: PMC9941348 DOI: 10.3389/fnmol.2023.1112253] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 01/19/2023] [Indexed: 02/10/2023] Open
Abstract
ATF4 is a cellular stress induced bZIP transcription factor that is a hallmark effector of the integrated stress response. The integrated stress response is triggered by phosphorylation of the alpha subunit of the eukaryotic initiation factor 2 complex that can be carried out by the cellular stress responsive kinases; GCN2, PERK, PKR, and HRI. eIF2α phosphorylation downregulates mRNA translation initiation en masse, however ATF4 translation is upregulated. The integrated stress response can output two contradicting outcomes in cells; pro-survival or apoptosis. The mechanism for choice between these outcomes is unknown, however combinations of ATF4 heterodimerisation partners and post-translational modifications have been linked to this regulation. This semi-systematic review article covers ATF4 target genes, heterodimerisation partners and post-translational modifications. Together, this review aims to be a useful resource to elucidate the mechanisms controlling the effects of the integrated stress response. Additional putative roles of the ATF4 protein in cell division and synaptic plasticity are outlined.
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Affiliation(s)
- Graham Neill
- Division of Cellular and Systems Medicine, School of Medicine, University of Dundee, Dundee, United Kingdom
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31
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Redina OE, Babenko VN, Smagin DA, Kovalenko IL, Galyamina AG, Efimov VM, Kudryavtseva NN. Effects of Positive Fighting Experience and Its Subsequent Deprivation on the Expression Profile of Mouse Hippocampal Genes Associated with Neurogenesis. Int J Mol Sci 2023; 24:ijms24033040. [PMID: 36769363 PMCID: PMC9918130 DOI: 10.3390/ijms24033040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/19/2023] [Accepted: 02/01/2023] [Indexed: 02/09/2023] Open
Abstract
The hippocampus is known as the brain region implicated in visuospatial processes and processes associated with learning and short- and long-term memory. An important functional characteristic of the hippocampus is lifelong neurogenesis. A decrease or increase in adult hippocampal neurogenesis is associated with a wide range of neurological diseases. We have previously shown that in adult male mice with a chronic positive fighting experience in daily agonistic interactions, there is an increase in the proliferation of progenitor neurons and the production of young neurons in the dentate gyrus (in hippocampus), and these neurogenesis parameters remain modified during 2 weeks of deprivation of further fights. The aim of the present work was to identify hippocampal genes associated with neurogenesis and involved in the formation of behavioral features in mice with the chronic experience of wins in aggressive confrontations, as well as during the subsequent 2-week deprivation of agonistic interactions. Hippocampal gene expression profiles were compared among three groups of adult male mice: chronically winning for 20 days in the agonistic interactions, chronically victorious for 20 days followed by the 2-week deprivation of fights, and intact (control) mice. Neurogenesis-associated genes were identified whose transcription levels changed during the social confrontations and in the subsequent period of deprivation of fights. In the experimental males, some of these genes are associated with behavioral traits, including abnormal aggression-related behavior, an abnormal anxiety-related response, and others. Two genes encoding transcription factors (Nr1d1 and Fmr1) were likely to contribute the most to the between-group differences. It can be concluded that the chronic experience of wins in agonistic interactions alters hippocampal levels of transcription of multiple genes in adult male mice. The transcriptome changes get reversed only partially after the 2-week period of deprivation of fights. The identified differentially expressed genes associated with neurogenesis and involved in the control of a behavior/neurological phenotype can be used in further studies to identify targets for therapeutic correction of the neurological disturbances that develop in winners under the conditions of chronic social confrontations.
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Affiliation(s)
- Olga E. Redina
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Vladimir N. Babenko
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Dmitry A. Smagin
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Irina L. Kovalenko
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Anna G. Galyamina
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Vadim M. Efimov
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Natalia N. Kudryavtseva
- Federal Research Center, Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
- Pavlov Institute of Physiology, Russian Academy of Sciences, Saint Petersburg 199034, Russia
- Correspondence:
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32
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Discovering Entities Similarities in Biological Networks Using a Hybrid Immune Algorithm. INFORMATICS 2023. [DOI: 10.3390/informatics10010018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Disease phenotypes are generally caused by the failure of gene modules which often have similar biological roles. Through the study of biological networks, it is possible to identify the intrinsic structure of molecular interactions in order to identify the so-called “disease modules”. Community detection is an interesting and valuable approach to discovering the structure of the community in a complex network, revealing the internal organization of the nodes, and has become a leading research topic in the analysis of complex networks. This work investigates the link between biological modules and network communities in test-case biological networks that are commonly used as a reference point and which include Protein–Protein Interaction Networks, Metabolic Networks and Transcriptional Regulation Networks. In order to identify small and structurally well-defined communities in the biological context, a hybrid immune metaheuristic algorithm Hybrid-IA is proposed and compared with several metaheuristics, hyper-heuristics, and the well-known greedy algorithm Louvain, with respect to modularity maximization. Considering the limitation of modularity optimization, which can fail to identify smaller communities, the reliability of Hybrid-IA was also analyzed with respect to three well-known sensitivity analysis measures (NMI, ARI and NVI) that assess how similar the detected communities are to real ones. By inspecting all outcomes and the performed comparisons, we will see that on one hand Hybrid-IA finds slightly lower modularity values than Louvain, but outperforms all other metaheuristics, while on the other hand, it can detect communities more similar to the real ones when compared to those detected by Louvain.
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33
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Joung J, Ma S, Tay T, Geiger-Schuller KR, Kirchgatterer PC, Verdine VK, Guo B, Arias-Garcia MA, Allen WE, Singh A, Kuksenko O, Abudayyeh OO, Gootenberg JS, Fu Z, Macrae RK, Buenrostro JD, Regev A, Zhang F. A transcription factor atlas of directed differentiation. Cell 2023; 186:209-229.e26. [PMID: 36608654 PMCID: PMC10344468 DOI: 10.1016/j.cell.2022.11.026] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 08/04/2022] [Accepted: 11/23/2022] [Indexed: 01/07/2023]
Abstract
Transcription factors (TFs) regulate gene programs, thereby controlling diverse cellular processes and cell states. To comprehensively understand TFs and the programs they control, we created a barcoded library of all annotated human TF splice isoforms (>3,500) and applied it to build a TF Atlas charting expression profiles of human embryonic stem cells (hESCs) overexpressing each TF at single-cell resolution. We mapped TF-induced expression profiles to reference cell types and validated candidate TFs for generation of diverse cell types, spanning all three germ layers and trophoblasts. Targeted screens with subsets of the library allowed us to create a tailored cellular disease model and integrate mRNA expression and chromatin accessibility data to identify downstream regulators. Finally, we characterized the effects of combinatorial TF overexpression by developing and validating a strategy for predicting combinations of TFs that produce target expression profiles matching reference cell types to accelerate cellular engineering efforts.
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Affiliation(s)
- Julia Joung
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Sai Ma
- Department of Biology, MIT, Cambridge, MA 02139, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tristan Tay
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kathryn R Geiger-Schuller
- Department of Biology, MIT, Cambridge, MA 02139, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Paul C Kirchgatterer
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Vanessa K Verdine
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Baolin Guo
- McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mario A Arias-Garcia
- McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - William E Allen
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA; Society of Fellows, Harvard University, Cambridge, MA, USA
| | - Ankita Singh
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Olena Kuksenko
- Department of Biology, MIT, Cambridge, MA 02139, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Omar O Abudayyeh
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Jonathan S Gootenberg
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Zhanyan Fu
- McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Rhiannon K Macrae
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Jason D Buenrostro
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Aviv Regev
- Department of Biology, MIT, Cambridge, MA 02139, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Feng Zhang
- Department of Biological Engineering, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Science, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; McGovern Institute for Brain Research at MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA.
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34
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Abstract
Deregulation of transcription factors is critical to hallmarks of cancer. Genetic mutations, gene fusions, amplifications or deletions, epigenetic alternations, and aberrant post-transcriptional modification of transcription factors are involved in the regulation of various stages of carcinogenesis, including cancer initiation, progression, and metastasis. Thus, targeting the dysfunctional transcription factors may lead to new cancer therapeutic strategies. However, transcription factors are conventionally considered as "undruggable." Here, we summarize the recent progresses in understanding the regulation of transcription factors in cancers and strategies to target transcription factors and co-factors for preclinical and clinical drug development, particularly focusing on c-Myc, YAP/TAZ, and β-catenin due to their significance and interplays in cancer.
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35
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Wu X, Liu S, Liang G. Detecting clusters of transcription factors based on a nonhomogeneous poisson process model. BMC Bioinformatics 2022; 23:535. [PMID: 36494794 PMCID: PMC9738027 DOI: 10.1186/s12859-022-05090-2] [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: 09/01/2022] [Accepted: 11/30/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Rapidly growing genome-wide ChIP-seq data have provided unprecedented opportunities to explore transcription factor (TF) binding under various cellular conditions. Despite the rich resources, development of analytical methods for studying the interaction among TFs in gene regulation still lags behind. RESULTS In order to address cooperative TF binding and detect TF clusters with coordinative functions, we have developed novel computational methods based on clustering the sample paths of nonhomogeneous Poisson processes. Simulation studies demonstrated the capability of these methods to accurately detect TF clusters and uncover the hierarchy of TF interactions. A further application to the multiple-TF ChIP-seq data in mouse embryonic stem cells (ESCs) showed that our methods identified the cluster of core ESC regulators reported in the literature and provided new insights on functional implications of transcrisptional regulatory modules. CONCLUSIONS Effective analytical tools are essential for studying protein-DNA relations. Information derived from this research will help us better understand the orchestration of transcription factors in gene regulation processes.
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Affiliation(s)
- Xiaowei Wu
- grid.438526.e0000 0001 0694 4940Department of Statistics, Virginia Tech, 250 Drillfield Drive, Blacksburg, VA 24061 USA
| | - Shicheng Liu
- grid.438526.e0000 0001 0694 4940Department of Mathematics, Virginia Tech, 225 Stanger Street, Blacksburg, VA 24061 USA
| | - Guanying Liang
- grid.438526.e0000 0001 0694 4940Department of Mathematics, Virginia Tech, 225 Stanger Street, Blacksburg, VA 24061 USA
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36
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Integrated proteomic and transcriptomic landscape of macrophages in mouse tissues. Nat Commun 2022; 13:7389. [PMID: 36450731 PMCID: PMC9712610 DOI: 10.1038/s41467-022-35095-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 11/18/2022] [Indexed: 12/03/2022] Open
Abstract
Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server ( http://macrophage.mouseprotein.cn ) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.
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Cha J, Yu J, Cho JW, Hemberg M, Lee I. scHumanNet: a single-cell network analysis platform for the study of cell-type specificity of disease genes. Nucleic Acids Res 2022; 51:e8. [PMID: 36350625 PMCID: PMC9881140 DOI: 10.1093/nar/gkac1042] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/19/2022] [Accepted: 10/25/2022] [Indexed: 11/10/2022] Open
Abstract
A major challenge in single-cell biology is identifying cell-type-specific gene functions, which may substantially improve precision medicine. Differential expression analysis of genes is a popular, yet insufficient approach, and complementary methods that associate function with cell type are required. Here, we describe scHumanNet (https://github.com/netbiolab/scHumanNet), a single-cell network analysis platform for resolving cellular heterogeneity across gene functions in humans. Based on cell-type-specific gene networks (CGNs) constructed under the guidance of the HumanNet reference interactome, scHumanNet displayed higher functional relevance to the cellular context than CGNs built by other methods on single-cell transcriptome data. Cellular deconvolution of gene signatures based on network compactness across cell types revealed breast cancer prognostic markers associated with T cells. scHumanNet could also prioritize genes associated with particular cell types using CGN centrality and identified the differential hubness of CGNs between disease and healthy conditions. We demonstrated the usefulness of scHumanNet by uncovering T-cell-specific functional effects of GITR, a prognostic gene for breast cancer, and functional defects in autism spectrum disorder genes specific for inhibitory neurons. These results suggest that scHumanNet will advance our understanding of cell-type specificity across human disease genes.
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Affiliation(s)
- Junha Cha
- Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Jiwon Yu
- Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Jae-Won Cho
- Evergrande Center for Immunologic Disease, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | - Martin Hemberg
- Correspondence may also be addressed to Martin Hemberg. Tel: +1 857 307 1422;
| | - Insuk Lee
- To whom correspondence should be addressed. Tel: +82 2 2123 5559; Fax: +82 2 362 7265;
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Diacou R, Nandigrami P, Fiser A, Liu W, Ashery-Padan R, Cvekl A. Cell fate decisions, transcription factors and signaling during early retinal development. Prog Retin Eye Res 2022; 91:101093. [PMID: 35817658 PMCID: PMC9669153 DOI: 10.1016/j.preteyeres.2022.101093] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/02/2022] [Accepted: 06/03/2022] [Indexed: 12/30/2022]
Abstract
The development of the vertebrate eyes is a complex process starting from anterior-posterior and dorso-ventral patterning of the anterior neural tube, resulting in the formation of the eye field. Symmetrical separation of the eye field at the anterior neural plate is followed by two symmetrical evaginations to generate a pair of optic vesicles. Next, reciprocal invagination of the optic vesicles with surface ectoderm-derived lens placodes generates double-layered optic cups. The inner and outer layers of the optic cups develop into the neural retina and retinal pigment epithelium (RPE), respectively. In vitro produced retinal tissues, called retinal organoids, are formed from human pluripotent stem cells, mimicking major steps of retinal differentiation in vivo. This review article summarizes recent progress in our understanding of early eye development, focusing on the formation the eye field, optic vesicles, and early optic cups. Recent single-cell transcriptomic studies are integrated with classical in vivo genetic and functional studies to uncover a range of cellular mechanisms underlying early eye development. The functions of signal transduction pathways and lineage-specific DNA-binding transcription factors are dissected to explain cell-specific regulatory mechanisms underlying cell fate determination during early eye development. The functions of homeodomain (HD) transcription factors Otx2, Pax6, Lhx2, Six3 and Six6, which are required for early eye development, are discussed in detail. Comprehensive understanding of the mechanisms of early eye development provides insight into the molecular and cellular basis of developmental ocular anomalies, such as optic cup coloboma. Lastly, modeling human development and inherited retinal diseases using stem cell-derived retinal organoids generates opportunities to discover novel therapies for retinal diseases.
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Affiliation(s)
- Raven Diacou
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Prithviraj Nandigrami
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, 10461, USA; Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Andras Fiser
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, 10461, USA; Department of Biochemistry, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Wei Liu
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Ruth Ashery-Padan
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel
| | - Ales Cvekl
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA; Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, 10461, USA.
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Chen T, Xu B, Chen H, Sun Y, Song J, Sun X, Zhang X, Hua W. Transcription factor NFE2L3 promotes the proliferation of esophageal squamous cell carcinoma cells and causes radiotherapy resistance by regulating IL-6. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 226:107102. [PMID: 36108571 DOI: 10.1016/j.cmpb.2022.107102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/23/2022] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVE To scrutinize the impact of overexpression and interference of NFE2L3 on radiosensitivity of esophageal squamous cell carcinoma cells (ESCC) and its downstream mechanism and to assess whether NFE2L3 expression alters in vivo radiosensitivity of ESCC by developing a subcutaneous tumor model in mice. METHODS Through RNA-Seq, we compared the differentially expressed genes between the ECA-109R cell line and its parent ECA-109 cell line. The differentially expressed genes were selected and verified by qRT-PCR. Transfection of ESCC cell lines with NFE2L3 inhibitor or mimic lentivirus constructs was done to study the activity of NFE2L3. To assess the effect of NFE2L3 on cellular growth and proliferation, clonogenic survival assay, EdU incorporation assay, and CCK-8 assay were done after irradiation. To probe how many irradiated DNA double-strand breaks were produced, the corresponding intensity of γ-H2AX foci were detected by immunofluorescence. Apoptotic cells were assayed by flow cytometry assay after irradiation; To investigate the downstream genes of NFE2L3, we knocked NFE2L3, and RNA-Seq was used to find out the downstream genes. qRT-PCR and western blot ensued to score associated protein profiles. The in vivo ESCC cell radiosensitivity was scrutinized by nude mouse xenograft models. RESULTS The differential genes between ECA-109R cells and its parent ECA-109 cells were compared by qRT-PCR to unveil a significant increase in NFE2L3 expression. Functional analysis indicated that NFE2L3 increased radioresistance in ESCC cells. Then, through high-throughput sequencing and bioinformatics analysis, IL-6 was found to be a hub gene that played a role downstream of NFE2L3 and was verified by qRT-PCR, western blot, and double luciferase reporter gene experiment. NFE2L3 could regulate ESCC cell radiosensitivity via the IL-6-STAT3 signaling pathway, and downregulation of IL-6 expression could reverse the effects of highly expressed NFE2L3. In vivo tumor xenograft experiments confirmed that NFE2L3 affects the sensitivity to radiation therapy. CONCLUSION NFE2L3 can affect the radiosensitivity of ESCC cells through IL-6 transcription and IL-6/STAT3 signaling pathway. This makes NFE2L3 a putative target to regulate ESCC cell radiosensitivity.
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Affiliation(s)
- Tingting Chen
- Department of Oncology, Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu Province, PR China
| | - Bing Xu
- Department of Oncology, Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu Province, PR China
| | - Hui Chen
- Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Yuanyuan Sun
- Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Jiahang Song
- Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China
| | - Xinchen Sun
- Department of Radiation Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu Province, PR China.
| | - Xizhi Zhang
- Department of Oncology, Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu Province, PR China.
| | - Wei Hua
- Department of Oncology, Clinical Medical College, Yangzhou University, Yangzhou, Jiangsu Province, PR China.
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Ni P, Wilson D, Su Z. A map of cis-regulatory modules and constituent transcription factor binding sites in 80% of the mouse genome. BMC Genomics 2022; 23:714. [PMID: 36261804 PMCID: PMC9583556 DOI: 10.1186/s12864-022-08933-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/11/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mouse is probably the most important model organism to study mammal biology and human diseases. A better understanding of the mouse genome will help understand the human genome, biology and diseases. However, despite the recent progress, the characterization of the regulatory sequences in the mouse genome is still far from complete, limiting its use to understand the regulatory sequences in the human genome. RESULTS Here, by integrating binding peaks in ~ 9,000 transcription factor (TF) ChIP-seq datasets that cover 79.9% of the mouse mappable genome using an efficient pipeline, we were able to partition these binding peak-covered genome regions into a cis-regulatory module (CRM) candidate (CRMC) set and a non-CRMC set. The CRMCs contain 912,197 putative CRMs and 38,554,729 TF binding sites (TFBSs) islands, covering 55.5% and 24.4% of the mappable genome, respectively. The CRMCs tend to be under strong evolutionary constraints, indicating that they are likely cis-regulatory; while the non-CRMCs are largely selectively neutral, indicating that they are unlikely cis-regulatory. Based on evolutionary profiles of the genome positions, we further estimated that 63.8% and 27.4% of the mouse genome might code for CRMs and TFBSs, respectively. CONCLUSIONS Validation using experimental data suggests that at least most of the CRMCs are authentic. Thus, this unprecedentedly comprehensive map of CRMs and TFBSs can be a good resource to guide experimental studies of regulatory genomes in mice and humans.
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Affiliation(s)
- Pengyu Ni
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - David Wilson
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA
| | - Zhengchang Su
- Department of Bioinformatics and Genomics, the University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
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Bélanger S, Haupt S, Freeman BL, Getzler AJ, Diao H, Pipkin ME, Crotty S. The Transcription Factor YY-1 Is an Essential Regulator of T Follicular Helper Cell Differentiation. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2022; 209:1566-1573. [PMID: 36096645 PMCID: PMC11139054 DOI: 10.4049/jimmunol.2101176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 08/15/2022] [Indexed: 05/09/2024]
Abstract
T follicular helper (TFH) cells are a specialized subset of CD4 T cells that deliver critical help signals to B cells for the production of high-affinity Abs. Understanding the genetic program regulating TFH differentiation is critical if one wants to manipulate TFH cells during vaccination. A large number of transcription factor (TFs) involved in the regulation of TFH differentiation have been characterized. However, there are likely additional unknown TFs required for this process. To identify new TFs, we screened a large short hairpin RNA library targeting 353 TFs in mice using an in vivo RNA interference screen. Yin Yang 1 (YY-1) was identified as a novel positive regulator of TFH differentiation. Ablation of YY-1 severely impaired TFH differentiation following acute viral infection and protein immunization. We found that the zinc fingers of YY-1 are critical to support TFH differentiation. Thus, we discovered a novel TF involved in the regulation of TFH cells.
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Affiliation(s)
- Simon Bélanger
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA
| | - Sonya Haupt
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA
- Biomedical Sciences Graduate Program, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Brian L Freeman
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA
| | - Adam J Getzler
- Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL
| | - Huitian Diao
- Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL
| | - Matthew E Pipkin
- Department of Immunology and Microbiology, The Scripps Research Institute, Jupiter, FL
| | - Shane Crotty
- Division of Vaccine Discovery, La Jolla Institute for Immunology, La Jolla, CA;
- Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego, La Jolla, CA; and
- Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery, The Scripps Research Institute, La Jolla, CA
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42
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Identification of Hypothalamic Long Noncoding RNAs Associated with Hypertension and the Behavior/Neurological Phenotype of Hypertensive ISIAH Rats. Genes (Basel) 2022; 13:genes13091598. [PMID: 36140769 PMCID: PMC9498762 DOI: 10.3390/genes13091598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/30/2022] [Accepted: 09/02/2022] [Indexed: 12/21/2022] Open
Abstract
Long noncoding RNAs (lncRNAs) play an important role in the control of many physiological and pathophysiological processes, including the development of hypertension and other cardiovascular diseases. Nonetheless, the understanding of the regulatory function of many lncRNAs is still incomplete. This work is a continuation of our earlier study on the sequencing of hypothalamic transcriptomes of hypertensive ISIAH rats and control normotensive WAG rats. It aims to identify lncRNAs that may be involved in the formation of the hypertensive state and the associated behavioral features of ISIAH rats. Interstrain differences in the expression of seven lncRNAs were validated by quantitative PCR. Differential hypothalamic expression of lncRNAs LOC100910237 and RGD1562890 between hypertensive and normotensive rats was shown for the first time. Expression of four lncRNAs (Snhg4, LOC100910237, RGD1562890, and Tnxa-ps1) correlated with transcription levels of many hypothalamic genes differentially expressed between ISIAH and WAG rats (DEGs), including genes associated with the behavior/neurological phenotype and hypertension. After functional annotation of these DEGs, it was concluded that lncRNAs Snhg4, LOC100910237, RGD1562890, and Tnxa-ps1 may be involved in the hypothalamic processes related to immune-system functioning and in the response to various exogenous and endogenous factors, including hormonal stimuli. Based on the functional enrichment analysis of the networks, an association of lncRNAs LOC100910237 and Tnxa-ps1 with retinol metabolism and an association of lncRNAs RGD1562890 and Tnxa-ps1 with type 1 diabetes mellitus are proposed for the first time. Based on a discussion, it is hypothesized that previously functionally uncharacterized lncRNA LOC100910237 is implicated in the regulation of hypothalamic processes associated with dopaminergic synaptic signaling, which may contribute to the formation of the behavioral/neurological phenotype and hypertensive state of ISIAH rats.
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43
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Liu Z, Li H, Jin Z, Li Y, Guo F, He Y, Liu X, Qi Y, Yuan L, He F, Li D. Exploration of Target Spaces in the Human Genome for Protein and Peptide Drugs. GENOMICS, PROTEOMICS & BIOINFORMATICS 2022; 20:780-794. [PMID: 35338014 PMCID: PMC9881050 DOI: 10.1016/j.gpb.2021.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 10/20/2021] [Accepted: 11/01/2021] [Indexed: 01/31/2023]
Abstract
After decades of development, protein and peptide drugs have now grown into a major drug class in the marketplace. Target identification and validation are crucial for the discovery of protein and peptide drugs, and bioinformatics prediction of targets based on the characteristics of known target proteins will help improve the efficiency and success rate of target selection. However, owing to the developmental history in the pharmaceutical industry, previous systematic exploration of the target spaces has mainly focused on traditional small-molecule drugs, while studies related to protein and peptide drugs are lacking. Here, we systematically explore the target spaces in the human genome specifically for protein and peptide drugs. Compared with other proteins, both successful protein and peptide drug targets have many special characteristics, and are also significantly different from those of small-molecule drugs in many aspects. Based on these features, we develop separate effective genome-wide target prediction models for protein and peptide drugs. Finally, a user-friendly web server, Predictor Of Protein and PeptIde drugs' therapeutic Targets (POPPIT) (http://poppit.ncpsb.org.cn/), is established, which provides not only target prediction specifically for protein and peptide drugs but also abundant annotations for predicted targets.
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Affiliation(s)
- Zhongyang Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China,School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China,College of Chemistry and Environmental Science, Hebei University, Baoding 071002, China,Corresponding authors.
| | - Honglei Li
- Suzhou Geneworks Technology Co., Ltd., Suzhou 215028, China
| | - Zhaoyu Jin
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yang Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Feifei Guo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yangzhige He
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Beijing 100730, China
| | - Xinyue Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yaning Qi
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China,College of Life Sciences, Hebei University, Baoding 071002, China
| | - Liying Yuan
- College of Life Sciences, Hebei University, Baoding 071002, China
| | - Fuchu He
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China,Corresponding authors.
| | - Dong Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing 102206, China,School of Basic Medical Sciences, Anhui Medical University, Hefei 230032, China,Corresponding authors.
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Temporally divergent regulatory mechanisms govern neuronal diversification and maturation in the mouse and marmoset neocortex. Nat Neurosci 2022; 25:1049-1058. [PMID: 35915179 PMCID: PMC9343253 DOI: 10.1038/s41593-022-01123-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 06/16/2022] [Indexed: 11/08/2022]
Abstract
Mammalian neocortical neurons span one of the most diverse cell type spectra of any tissue. Cortical neurons are born during embryonic development, and their maturation extends into postnatal life. The regulatory strategies underlying progressive neuronal development and maturation remain unclear. Here we present an integrated single-cell epigenomic and transcriptional analysis of individual mouse and marmoset cortical neuron classes, spanning both early postmitotic stages of identity acquisition and later stages of neuronal plasticity and circuit integration. We found that, in both species, the regulatory strategies controlling early and late stages of pan-neuronal development diverge. Early postmitotic neurons use more widely shared and evolutionarily conserved molecular regulatory programs. In contrast, programs active during later neuronal maturation are more brain- and neuron-specific and more evolutionarily divergent. Our work uncovers a temporal shift in regulatory choices during neuronal diversification and maturation in both mice and marmosets, which likely reflects unique evolutionary constraints on distinct events of neuronal development in the neocortex.
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45
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Zhou JJ, Pham PD, Han H, Wang W, Cho KWY. Foxh1 engages in chromatin regulation revealed by protein interactome analyses. Dev Growth Differ 2022; 64:297-305. [PMID: 35848281 PMCID: PMC9474667 DOI: 10.1111/dgd.12799] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/06/2022] [Accepted: 07/13/2022] [Indexed: 11/29/2022]
Abstract
Early embryonic cell fates are specified through coordinated integration of transcription factor activities and epigenetic states of the genome. Foxh1 is a key maternal transcription factor controlling the mesendodermal gene regulatory program. Proteomic interactome analyses using FOXH1 as a bait in mouse embryonic stem cells revealed that FOXH1 interacts with PRC2 subunits and HDAC1. Foxh1 physically interacts with Hdac1, and confers transcriptional repression of mesendodermal genes in Xenopus ectoderm. Our findings reveal a central role of Foxh1 in coordinating the chromatin states of the Xenopus embryonic genome.
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Affiliation(s)
- Jeff Jiajing Zhou
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Paula Duyen Pham
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Han Han
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Wenqi Wang
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Ken W Y Cho
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA.,Center for Complex Biological Systems, University of California, Irvine, CA, USA
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Fotuhi Siahpirani A, Knaack S, Chasman D, Seirup M, Sridharan R, Stewart R, Thomson J, Roy S. Dynamic regulatory module networks for inference of cell type-specific transcriptional networks. Genome Res 2022; 32:1367-1384. [PMID: 35705328 PMCID: PMC9341506 DOI: 10.1101/gr.276542.121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 06/02/2022] [Indexed: 11/25/2022]
Abstract
Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled bulk multi-omic data sets with parallel transcriptomic and epigenomic measurements at different stages of a developmental process. However, integrating these data to infer cell type–specific regulatory networks is a major challenge. We present dynamic regulatory module networks (DRMNs), a novel approach to infer cell type–specific cis-regulatory networks and their dynamics. DRMN integrates expression, chromatin state, and accessibility to predict cis-regulators of context-specific expression, where context can be cell type, developmental stage, or time point, and uses multitask learning to capture network dynamics across linearly and hierarchically related contexts. We applied DRMNs to study regulatory network dynamics in three developmental processes, each showing different temporal relationships and measuring a different combination of regulatory genomic data sets: cellular reprogramming, liver dedifferentiation, and forward differentiation. DRMN identified known and novel regulators driving cell type–specific expression patterns, showing its broad applicability to examine dynamics of gene regulatory networks from linearly and hierarchically related multi-omic data sets.
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Affiliation(s)
| | - Sara Knaack
- Wisconsin Institute for Discovery, University of Wisconsin-Madison
| | - Deborah Chasman
- Wisconsin Institute for Discovery, University of Wisconsin-Madison
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Bévant K, Desoteux M, Angenard G, Pineau R, Caruso S, Louis C, Papoutsoglou P, Sulpice L, Gilot D, Zucman-Rossi J, Coulouarn C. TGFβ-induced FOXS1 controls epithelial-mesenchymal transition and predicts a poor prognosis in liver cancer. Hepatol Commun 2022; 6:1157-1171. [PMID: 34825776 PMCID: PMC9035581 DOI: 10.1002/hep4.1866] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/12/2021] [Accepted: 10/26/2021] [Indexed: 01/13/2023] Open
Abstract
Transforming growth factor beta (TGF-β) plays a key role in tumor progression, notably as a potent inducer of epithelial-mesenchymal transition (EMT). However, all of the molecular effectors driving TGFβ-induced EMT are not fully characterized. Here, we report that forkhead box S1 (FOXS1) is a SMAD (mothers against decapentaplegic)-dependent TGFβ-induced transcription factor, which regulates the expression of genes required for the initial steps of EMT (e.g., snail family transcription repressor 1) and to maintain a mesenchymal phenotype in hepatocellular carcinoma (HCC) cells. In human HCC, we report that FOXS1 is a biomarker of poorly differentiated and aggressive tumor subtypes. Importantly, FOXS1 expression level and activity are associated with a poor prognosis (e.g., reduced patient survival), not only in HCC but also in colon, stomach, and kidney cancers. Conclusion: FOXS1 constitutes a clinically relevant biomarker for tumors in which the pro-metastatic arm of TGF-β is active (i.e., patients who may benefit from targeted therapies using inhibitors of the TGF-β pathway).
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Affiliation(s)
- Kevin Bévant
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - Matthis Desoteux
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - Gaëlle Angenard
- InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - Raphaël Pineau
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance
| | - Stefano Caruso
- Centre de Recherche des CordeliersInsermSorbonne UniversitéUniversité de ParisUniversité Paris 13Functional Genomics of Solid Tumors LaboratoryParisFrance
| | - Corentin Louis
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - Panagiotis Papoutsoglou
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - Laurent Sulpice
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
| | - David Gilot
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance
| | - Jessica Zucman-Rossi
- Centre de Recherche des CordeliersInsermSorbonne UniversitéUniversité de ParisUniversité Paris 13Functional Genomics of Solid Tumors LaboratoryParisFrance.,European Hospital Georges PompidouAP-HPParisFrance
| | - Cédric Coulouarn
- InsermUniv RennesUMR_S 1242ChemistryOncogenesis, Stress SignalingCentre de Lutte contre le Cancer Eugène MarquisService de Chirurgie Hépatobiliaire et DigestiveCHU RennesRennesFrance.,InsermUniv RennesInraeUMR_S 1241NuMeCan (Nutrition, Metabolisms and Cancer)RennesFrance
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48
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Single-cell analysis of transcription factor regulatory networks reveals molecular basis for subtype-specific dysregulation in acute myeloid leukemia. BLOOD SCIENCE 2022; 4:65-75. [PMID: 35957668 PMCID: PMC9362874 DOI: 10.1097/bs9.0000000000000113] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 03/30/2022] [Indexed: 11/26/2022] Open
Abstract
Highly heterogeneous acute myeloid leukemia (AML) exhibits dysregulated transcriptional programs. Transcription factor (TF) regulatory networks underlying AML subtypes have not been elucidated at single-cell resolution. Here, we comprehensively mapped malignancy-related TFs activated in different AML subtypes by analyzing single-cell RNA sequencing data from AMLs and healthy donors. We first identified six modules of regulatory networks which were prevalently dysregulated in all AML patients. AML subtypes featured with different malignant cellular composition possessed subtype-specific regulatory TFs associated with differentiation suppression or immune modulation. At last, we validated that ERF was crucial for the development of hematopoietic stem/progenitor cells by performing loss- and gain-of-function experiments in zebrafish embryos. Collectively, our work thoroughly documents an abnormal spectrum of transcriptional regulatory networks in AML and reveals subtype-specific dysregulation basis, which provides a prospective view to AML pathogenesis and potential targets for both diagnosis and therapy.
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49
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Garipler G, Lu C, Morrissey A, Lopez-Zepeda LS, Pei Y, Vidal SE, Zen Petisco Fiore AP, Aydin B, Stadtfeld M, Ohler U, Mahony S, Sanjana NE, Mazzoni EO. The BTB transcription factors ZBTB11 and ZFP131 maintain pluripotency by repressing pro-differentiation genes. Cell Rep 2022; 38:110524. [PMID: 35294876 PMCID: PMC8972945 DOI: 10.1016/j.celrep.2022.110524] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 10/21/2021] [Accepted: 02/22/2022] [Indexed: 12/15/2022] Open
Abstract
In pluripotent cells, a delicate activation-repression balance maintains pro-differentiation genes ready for rapid activation. The identity of transcription factors (TFs) that specifically repress pro-differentiation genes remains obscure. By targeting ∼1,700 TFs with CRISPR loss-of-function screen, we found that ZBTB11 and ZFP131 are required for embryonic stem cell (ESC) pluripotency. ESCs without ZBTB11 or ZFP131 lose colony morphology, reduce proliferation rate, and upregulate transcription of genes associated with three germ layers. ZBTB11 and ZFP131 bind proximally to pro-differentiation genes. ZBTB11 or ZFP131 loss leads to an increase in H3K4me3, negative elongation factor (NELF) complex release, and concomitant transcription at associated genes. Together, our results suggest that ZBTB11 and ZFP131 maintain pluripotency by preventing premature expression of pro-differentiation genes and present a generalizable framework to maintain cellular potency.
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Affiliation(s)
- Görkem Garipler
- Department of Biology, New York University, New York, NY 10003, USA
| | - Congyi Lu
- Department of Biology, New York University, New York, NY 10003, USA; New York Genome Center, New York, NY 10013, USA
| | - Alexis Morrissey
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA 16802, USA
| | - Lorena S Lopez-Zepeda
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany; Berlin Institute for Medical Systems Biology, Max-Delbrück-Center for Molecular Medicine, Berlin 13125, Germany
| | - Yingzhen Pei
- Department of Biology, New York University, New York, NY 10003, USA
| | - Simon E Vidal
- Sanford I Weill Department of Medicine, Division of Regenerative Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | | | - Begüm Aydin
- Department of Biology, New York University, New York, NY 10003, USA
| | - Matthias Stadtfeld
- Sanford I Weill Department of Medicine, Division of Regenerative Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Uwe Ohler
- Department of Biology, Humboldt Universität zu Berlin, Berlin 10117, Germany; Berlin Institute for Medical Systems Biology, Max-Delbrück-Center for Molecular Medicine, Berlin 13125, Germany
| | - Shaun Mahony
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA 16802, USA
| | - Neville E Sanjana
- Department of Biology, New York University, New York, NY 10003, USA; New York Genome Center, New York, NY 10013, USA.
| | - Esteban O Mazzoni
- Department of Biology, New York University, New York, NY 10003, USA.
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50
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Casalino L, Talotta F, Cimmino A, Verde P. The Fra-1/AP-1 Oncoprotein: From the "Undruggable" Transcription Factor to Therapeutic Targeting. Cancers (Basel) 2022; 14:cancers14061480. [PMID: 35326630 PMCID: PMC8946526 DOI: 10.3390/cancers14061480] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 02/06/2023] Open
Abstract
The genetic and epigenetic changes affecting transcription factors, coactivators, and chromatin modifiers are key determinants of the hallmarks of cancer. The acquired dependence on oncogenic transcriptional regulators, representing a major determinant of cancer cell vulnerability, points to transcription factors as ideal therapeutic targets. However, given the unavailability of catalytic activities or binding pockets for small-molecule inhibitors, transcription factors are generally regarded as undruggable proteins. Among components of the AP-1 complex, the FOS-family transcription factor Fra-1, encoded by FOSL1, has emerged as a prominent therapeutic target. Fra-1 is overexpressed in most solid tumors, in response to the BRAF-MAPK, Wnt-beta-catenin, Hippo-YAP, IL-6-Stat3, and other major oncogenic pathways. In vitro functional analyses, validated in onco-mouse models and corroborated by prognostic correlations, show that Fra-1-containing dimers control tumor growth and disease progression. Fra-1 participates in key mechanisms of cancer cell invasion, Epithelial-to-Mesenchymal Transition, and metastatic spreading, by driving the expression of EMT-inducing transcription factors, cytokines, and microRNAs. Here we survey various strategies aimed at inhibiting tumor growth, metastatic dissemination, and drug resistance by interfering with Fra-1 expression, stability, and transcriptional activity. We summarize several tools aimed at the design and tumor-specific delivery of Fra-1/AP-1-specific drugs. Along with RNA-based therapeutics targeting the FOSL1 gene, its mRNA, or cognate regulatory circRNAs, we will examine the exploitation of blocking peptides, small molecule inhibitors, and innovative Fra-1 protein degraders. We also consider the possible caveats concerning Fra-1 inhibition in specific therapeutic contexts. Finally, we discuss a recent suicide gene therapy-based approach, aimed at selectively killing the Fra-1-overexpressing neoplastic cells.
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Affiliation(s)
- Laura Casalino
- Institute of Genetics and Biophysics “Adriano Buzzati Traverso”, Consiglio Nazionale dele Ricerche (CNR), 80131 Naples, Italy;
- Correspondence: (L.C.); (P.V.)
| | | | - Amelia Cimmino
- Institute of Genetics and Biophysics “Adriano Buzzati Traverso”, Consiglio Nazionale dele Ricerche (CNR), 80131 Naples, Italy;
| | - Pasquale Verde
- Institute of Genetics and Biophysics “Adriano Buzzati Traverso”, Consiglio Nazionale dele Ricerche (CNR), 80131 Naples, Italy;
- Correspondence: (L.C.); (P.V.)
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