Angelika Schmidt1,2, Francesco Marabita3,4, Narsis A Kiani3, Catharina C Gross5, Henrik J Johansson6, Szabolcs Éliás3, Sini Rautio7, Matilda Eriksson3, Sunjay Jude Fernandes3, Gilad Silberberg3, Ubaid Ullah8, Urvashi Bhatia5, Harri Lähdesmäki7, Janne Lehtiö6, David Gomez-Cabrero3,9, Heinz Wiendl5, Riitta Lahesmaa10, Jesper Tegnér11,12. 1. Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden. Schmidt_Angelika@outlook.com. 2. Department of Signaling and Gene Expression, La Jolla Institute for Allergy and Immunology, La Jolla, CA, 92037, USA. Schmidt_Angelika@outlook.com. 3. Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden. 4. Neuroimmunology Unit, Center for Molecular Medicine, Department of Clinical Neuroscience, Karolinska Institutet & Karolinska University Hospital, 17176, Stockholm, Sweden. 5. Department of Neurology, University Hospital Münster and University of Münster, 48149, Münster, Germany. 6. Department Oncology-Pathology, Cancer Proteomics Mass Spectrometry, Science for Life Laboratory, Karolinska Institutet, 17176, Stockholm, Sweden. 7. Department of Computer Science, Aalto University, FI-00076, Aalto, Finland. 8. Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20521, Turku, Finland. 9. Mucosal and Salivary Biology Division, King's College London Dental Institute, London, SE1 9RT, UK. 10. Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, FI-20521, Turku, Finland. rilahes@utu.fi. 11. Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital and Science for Life Laboratory, 17176, Stockholm, Sweden. jesper.tegner@ki.se. 12. Biological and Environmental Sciences and Engineering Division, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, 23955-6900, Kingdom of Saudi Arabia. jesper.tegner@ki.se.
Abstract
BACKGROUND: Regulatory T cells (Tregs) expressing the transcription factor FOXP3 are crucial mediators of self-tolerance, preventing autoimmune diseases but possibly hampering tumor rejection. Clinical manipulation of Tregs is of great interest, and first-in-man trials of Treg transfer have achieved promising outcomes. Yet, the mechanisms governing induced Treg (iTreg) differentiation and the regulation of FOXP3 are incompletely understood. RESULTS: To gain a comprehensive and unbiased molecular understanding of FOXP3 induction, we performed time-series RNA sequencing (RNA-Seq) and proteomics profiling on the same samples during human iTreg differentiation. To enable the broad analysis of universal FOXP3-inducing pathways, we used five differentiation protocols in parallel. Integrative analysis of the transcriptome and proteome confirmed involvement of specific molecular processes, as well as overlap of a novel iTreg subnetwork with known Treg regulators and autoimmunity-associated genes. Importantly, we propose 37 novel molecules putatively involved in iTreg differentiation. Their relevance was validated by a targeted shRNA screen confirming a functional role in FOXP3 induction, discriminant analyses classifying iTregs accordingly, and comparable expression in an independent novel iTreg RNA-Seq dataset. CONCLUSION: The data generated by this novel approach facilitates understanding of the molecular mechanisms underlying iTreg generation as well as of the concomitant changes in the transcriptome and proteome. Our results provide a reference map exploitable for future discovery of markers and drug candidates governing control of Tregs, which has important implications for the treatment of cancer, autoimmune, and inflammatory diseases.
BACKGROUND: Regulatory T cells (Tregs) expressing the transcription factor FOXP3 are crucial mediators of self-tolerance, preventing autoimmune diseases but possibly hampering tumor rejection. Clinical manipulation of Tregs is of great interest, and first-in-man trials of Treg transfer have achieved promising outcomes. Yet, the mechanisms governing induced Treg (iTreg) differentiation and the regulation of FOXP3 are incompletely understood. RESULTS: To gain a comprehensive and unbiased molecular understanding of FOXP3 induction, we performed time-series RNA sequencing (RNA-Seq) and proteomics profiling on the same samples during human iTreg differentiation. To enable the broad analysis of universal FOXP3-inducing pathways, we used five differentiation protocols in parallel. Integrative analysis of the transcriptome and proteome confirmed involvement of specific molecular processes, as well as overlap of a novel iTreg subnetwork with known Treg regulators and autoimmunity-associated genes. Importantly, we propose 37 novel molecules putatively involved in iTreg differentiation. Their relevance was validated by a targeted shRNA screen confirming a functional role in FOXP3 induction, discriminant analyses classifying iTregs accordingly, and comparable expression in an independent novel iTreg RNA-Seq dataset. CONCLUSION: The data generated by this novel approach facilitates understanding of the molecular mechanisms underlying iTreg generation as well as of the concomitant changes in the transcriptome and proteome. Our results provide a reference map exploitable for future discovery of markers and drug candidates governing control of Tregs, which has important implications for the treatment of cancer, autoimmune, and inflammatory diseases.
Entities:
Keywords:
Data integration; FOXP3; Proteomics; RNA sequencing (RNA-Seq); Regulatory T cells; T cell differentiation; TGF-β; Treg; iTreg
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