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Vathrakokoili Pournara A, Miao Z, Beker OY, Nolte N, Brazma A, Papatheodorou I. CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues. BIOINFORMATICS ADVANCES 2024; 4:vbae048. [PMID: 38638280 PMCID: PMC11023940 DOI: 10.1093/bioadv/vbae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/20/2024] [Accepted: 03/21/2024] [Indexed: 04/20/2024]
Abstract
Motivation Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods. Results In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods. Availability and implementation https://github.com/Papatheodorou-Group/CATD_snakemake.
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Affiliation(s)
- Anna Vathrakokoili Pournara
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Zhichao Miao
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
- Open Targets, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
- GMU-GIBH Joint School of Life Sciences, Guangzhou Laboratory, Guangzhou Medical University, Guangzhou, 511436, China
| | - Ozgur Yilimaz Beker
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
- Faculty of Engineering and Natural Sciences, Sabanci University, Tuzla 34956, Turkey
| | - Nadja Nolte
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
- Department of Biotechnology and Systems Biology, National Institute of Biology, Ljubljana, 121-1000, Slovenia
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
| | - Irene Papatheodorou
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, United Kingdom
- Open Targets, Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom
- Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, United Kingdom
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2
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Buono R, Tucci J, Cutri R, Guidi N, Mangul S, Raucci F, Pellegrini M, Mittelman SD, Longo VD. Fasting-Mimicking Diet Inhibits Autophagy and Synergizes with Chemotherapy to Promote T-Cell-Dependent Leukemia-Free Survival. Cancers (Basel) 2023; 15:5870. [PMID: 38136414 PMCID: PMC10741737 DOI: 10.3390/cancers15245870] [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: 11/07/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023] Open
Abstract
Fasting mimicking diets (FMDs) are effective in the treatment of many solid tumors in mouse models, but their effect on hematologic malignancies is poorly understood, particularly in combination with standard therapies. Here we show that cycles of a 3-day FMD given to high-fat-diet-fed mice once a week increased the efficacy of vincristine to improve survival from BCR-ABL B acute lymphoblastic leukemia (ALL). In mice fed a standard diet, FMD cycles in combination with vincristine promoted cancer-free survival. RNA seq and protein assays revealed a vincristine-dependent decrease in the expression of multiple autophagy markers, which was exacerbated by the fasting/FMD conditions. The autophagy inhibitor chloroquine could substitute for fasting/FMD to promote cancer-free survival in combination with vincristine. In vitro, targeted inhibition of autophagy genes ULK1 and ATG9a strongly potentiated vincristine's toxicity. Moreover, anti-CD8 antibodies reversed the effects of vincristine plus fasting/FMD in promoting leukemia-free survival in mice, indicating a central role of the immune system in this response. Thus, the inhibition of autophagy and enhancement of immune responses appear to be mediators of the fasting/FMD-dependent cancer-free survival in ALL mice.
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Affiliation(s)
- Roberta Buono
- Department of Biological Sciences, Longevity Institute, School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles, CA 90089, USA
- Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697, USA
| | - Jonathan Tucci
- Center for Endocrinology, Diabetes & Metabolism, Children’s Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles, CA 90027, USA
| | - Raffaello Cutri
- Department of Biological Sciences, Longevity Institute, School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles, CA 90089, USA
| | - Novella Guidi
- Department of Biological Sciences, Longevity Institute, School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles, CA 90089, USA
| | - Serghei Mangul
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
- Institute for Quantitative and Computational Biosciences, Boyer Hall, 611 Charles Young Drive, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Franca Raucci
- IFOM AIRC Institute of Molecular Oncology, Via Adamello 16, 20139 Milan, Italy
| | - Matteo Pellegrini
- Institute for Quantitative and Computational Biosciences, Boyer Hall, 611 Charles Young Drive, University of California Los Angeles, Los Angeles, CA 90095, USA
- Department of Molecular, Cell and Developmental Biology, University of California Los Angeles, 801 Hilgard Avenue, Los Angeles, CA 90095, USA
| | - Steven D. Mittelman
- Center for Endocrinology, Diabetes & Metabolism, Children’s Hospital Los Angeles, 4650 Sunset Blvd, Los Angeles, CA 90027, USA
- Division of Pediatric Endocrinology, UCLA Mattel Children’s Hospital, 10833 Le Conte Avenue, MDCC 22-315, Los Angeles, CA 90095, USA
| | - Valter D. Longo
- Department of Biological Sciences, Longevity Institute, School of Gerontology, University of Southern California, 3715 McClintock Avenue, Los Angeles, CA 90089, USA
- IFOM AIRC Institute of Molecular Oncology, Via Adamello 16, 20139 Milan, Italy
- Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
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3
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Cheng C, Chen W, Jin H, Chen X. A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication. Cells 2023; 12:1970. [PMID: 37566049 PMCID: PMC10417635 DOI: 10.3390/cells12151970] [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: 06/13/2023] [Revised: 07/10/2023] [Accepted: 07/21/2023] [Indexed: 08/12/2023] Open
Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell-cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell-cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.
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Affiliation(s)
- Changde Cheng
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA;
| | - Wenan Chen
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA; (W.C.); (H.J.)
| | - Hongjian Jin
- Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA; (W.C.); (H.J.)
| | - Xiang Chen
- Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA;
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4
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Kolomeets M, Desnitsky V, Kotenko I, Chechulin A. Graph Visualization: Alternative Models Inspired by Bioinformatics. SENSORS (BASEL, SWITZERLAND) 2023; 23:3747. [PMID: 37050807 PMCID: PMC10099065 DOI: 10.3390/s23073747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 03/05/2023] [Accepted: 03/13/2023] [Indexed: 06/19/2023]
Abstract
Currently, the methods and means of human-machine interaction and visualization as its integral part are being increasingly developed. In various fields of scientific knowledge and technology, there is a need to find and select the most effective visualization models for various types of data, as well as to develop automation tools for the process of choosing the best visualization model for a specific case. There are many data visualization tools in various application fields, but at the same time, the main difficulty lies in presenting data of an interconnected (node-link) structure, i.e., networks. Typically, a lot of software means use graphs as the most straightforward and versatile models. To facilitate visual analysis, researchers are developing ways to arrange graph elements to make comparing, searching, and navigating data easier. However, in addition to graphs, there are many other visualization models that are less versatile but have the potential to expand the capabilities of the analyst and provide alternative solutions. In this work, we collected a variety of visualization models, which we call alternative models, to demonstrate how different concepts of information representation can be realized. We believe that adapting these models to improve the means of human-machine interaction will help analysts make significant progress in solving the problems researchers face when working with graphs.
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5
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Do TH, Ma F, Andrade PR, Teles R, de Andrade Silva BJ, Hu C, Espinoza A, Hsu JE, Cho CS, Kim M, Xi J, Xing X, Plazyo O, Tsoi LC, Cheng C, Kim J, Bryson BD, O'Neill AM, Colonna M, Gudjonsson JE, Klechevsky E, Lee JH, Gallo RL, Bloom BR, Pellegrini M, Modlin RL. TREM2 macrophages induced by human lipids drive inflammation in acne lesions. Sci Immunol 2022; 7:eabo2787. [PMID: 35867799 PMCID: PMC9400695 DOI: 10.1126/sciimmunol.abo2787] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Acne affects 1 in 10 people globally, often resulting in disfigurement. The disease involves excess production of lipids, particularly squalene, increased growth of Cutibacterium acnes, and a host inflammatory response with foamy macrophages. By combining single-cell and spatial RNA sequencing as well as ultrahigh-resolution Seq-Scope analyses of early acne lesions on back skin, we identified TREM2 macrophages expressing lipid metabolism and proinflammatory gene programs in proximity to hair follicle epithelium expressing squalene epoxidase. We established that the addition of squalene induced differentiation of TREM2 macrophages in vitro, which were unable to kill C. acnes. The addition of squalene to macrophages inhibited induction of oxidative enzymes and scavenged oxygen free radicals, providing an explanation for the efficacy of topical benzoyl peroxide in the clinical treatment of acne. The present work has elucidated the mechanisms by which TREM2 macrophages and unsaturated lipids, similar to their involvement in atherosclerosis, may contribute to the pathogenesis of acne.
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Affiliation(s)
- Tran H Do
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.,Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Feiyang Ma
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.,Institute for Quantitative and Computational Biosciences-The Collaboratory, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Priscila R Andrade
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Rosane Teles
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Bruno J de Andrade Silva
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Chanyue Hu
- Institute for Quantitative and Computational Biosciences-The Collaboratory, University of California, Los Angeles, Los Angeles, CA 90095, USA.,Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Alejandro Espinoza
- Institute for Quantitative and Computational Biosciences-The Collaboratory, University of California, Los Angeles, Los Angeles, CA 90095, USA.,Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jer-En Hsu
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Chun-Seok Cho
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Myungjin Kim
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Jingyue Xi
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Xianying Xing
- Department of Dermatology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Olesya Plazyo
- Department of Dermatology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Carol Cheng
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Jenny Kim
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA
| | - Bryan D Bryson
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alan M O'Neill
- Department of Dermatology, University of California San Diego, La Jolla, CA 92093, USA
| | - Marco Colonna
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | | | - Eynav Klechevsky
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jun Hee Lee
- Department of Molecular and Integrative Physiology, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Richard L Gallo
- Department of Dermatology, University of California San Diego, La Jolla, CA 92093, USA
| | - Barry R Bloom
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Matteo Pellegrini
- Institute for Quantitative and Computational Biosciences-The Collaboratory, University of California, Los Angeles, Los Angeles, CA 90095, USA.,Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Robert L Modlin
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles,, Los Angeles, CA 90095, USA.,Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA
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6
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Gideon HP, Hughes TK, Tzouanas CN, Wadsworth MH, Tu AA, Gierahn TM, Peters JM, Hopkins FF, Wei JR, Kummerlowe C, Grant NL, Nargan K, Phuah JY, Borish HJ, Maiello P, White AG, Winchell CG, Nyquist SK, Ganchua SKC, Myers A, Patel KV, Ameel CL, Cochran CT, Ibrahim S, Tomko JA, Frye LJ, Rosenberg JM, Shih A, Chao M, Klein E, Scanga CA, Ordovas-Montanes J, Berger B, Mattila JT, Madansein R, Love JC, Lin PL, Leslie A, Behar SM, Bryson B, Flynn JL, Fortune SM, Shalek AK. Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control. Immunity 2022; 55:827-846.e10. [PMID: 35483355 PMCID: PMC9122264 DOI: 10.1016/j.immuni.2022.04.004] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 02/08/2022] [Accepted: 04/07/2022] [Indexed: 12/12/2022]
Abstract
Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB. Timing of granuloma formation influences local microenvironment and bacterial burden Mast cells, type 2 immunity, and tissue remodeling underlie early, high-burden granulomas Type1-type17 and cytotoxic T cells associate with late-forming, low-burden granulomas Distinct interaction circuits across granuloma phenotypes nominate therapeutic targets
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Affiliation(s)
- Hannah P Gideon
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA
| | - Travis K Hughes
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Constantine N Tzouanas
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marc H Wadsworth
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ang Andy Tu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Todd M Gierahn
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joshua M Peters
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Forrest F Hopkins
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jun-Rong Wei
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Conner Kummerlowe
- Program in Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Nicole L Grant
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Jia Yao Phuah
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - H Jacob Borish
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Pauline Maiello
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Alexander G White
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Caylin G Winchell
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA; Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Sarah K Nyquist
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Computational and Systems Biology, Massachusetts Institute of Technology, Cambridge, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sharie Keanne C Ganchua
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Amy Myers
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kush V Patel
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Cassaundra L Ameel
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Catherine T Cochran
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Samira Ibrahim
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jaime A Tomko
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lonnie James Frye
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jacob M Rosenberg
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Angela Shih
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA
| | - Michael Chao
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Edwin Klein
- Division of Laboratory Animal Research, University of Pittsburgh, Pittsburgh PA, USA
| | - Charles A Scanga
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jose Ordovas-Montanes
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bonnie Berger
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joshua T Mattila
- Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA; Department of Infectious Diseases and Microbiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rajhmun Madansein
- Department of Cardiothoracic Surgery, University of KwaZulu Natal, Durban, South Africa
| | - J Christopher Love
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA; The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Philana Ling Lin
- Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA; Department of Pediatrics, University of Pittsburgh School of Medicine, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA
| | - Alasdair Leslie
- Africa Health Research Institute, Durban, South Africa; School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa; Department of Infection and Immunity, University College London, London, UK
| | - Samuel M Behar
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA, USA
| | - Bryan Bryson
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - JoAnne L Flynn
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Center for Vaccine Research, University of Pittsburgh, Pittsburgh, PA, USA.
| | - Sarah M Fortune
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Alex K Shalek
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA; The Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
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7
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Nadel BB, Oliva M, Shou BL, Mitchell K, Ma F, Montoya DJ, Mouton A, Kim-Hellmuth S, Stranger BE, Pellegrini M, Mangul S. Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samples. Brief Bioinform 2021; 22:bbab265. [PMID: 34346485 PMCID: PMC8768458 DOI: 10.1093/bib/bbab265] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/07/2021] [Accepted: 06/21/2021] [Indexed: 11/13/2022] Open
Abstract
Estimating cell type composition of blood and tissue samples is a biological challenge relevant in both laboratory studies and clinical care. In recent years, a number of computational tools have been developed to estimate cell type abundance using gene expression data. Although these tools use a variety of approaches, they all leverage expression profiles from purified cell types to evaluate the cell type composition within samples. In this study, we compare 12 cell type quantification tools and evaluate their performance while using each of 10 separate reference profiles. Specifically, we have run each tool on over 4000 samples with known cell type proportions, spanning both immune and stromal cell types. A total of 12 of these represent in vitro synthetic mixtures and 300 represent in silico synthetic mixtures prepared using single-cell data. A final 3728 clinical samples have been collected from the Framingham cohort, for which cell populations have been quantified using electrical impedance cell counting. When tools are applied to the Framingham dataset, the tool Estimating the Proportions of Immune and Cancer cells (EPIC) produces the highest correlation, whereas Gene Expression Deconvolution Interactive Tool (GEDIT) produces the lowest error. The best tool for other datasets is varied, but CIBERSORT and GEDIT most consistently produce accurate results. We find that optimal reference depends on the tool used, and report suggested references to be used with each tool. Most tools return results within minutes, but on large datasets runtimes for CIBERSORT can exceed hours or even days. We conclude that deconvolution methods are capable of returning high-quality results, but that proper reference selection is critical.
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Affiliation(s)
- Brian B Nadel
- Corresponding authors: Brian B. Nadel, Tel: 310-963-7077; E-mail: ; Matteo Pellegrini, Tel: 310-825-0012, E-mail: ; Serghei Mangul, Tel: 323-442-0043, E-mail:
| | | | | | | | | | | | | | | | | | | | - Serghei Mangul
- Corresponding authors: Brian B. Nadel, Tel: 310-963-7077; E-mail: ; Matteo Pellegrini, Tel: 310-825-0012, E-mail: ; Serghei Mangul, Tel: 323-442-0043, E-mail:
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8
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Wang M, Wang Y, Zhang M, Duan Q, Chen C, Sun Q, Liu M, Zheng Y, Shao Y. Kynureninase contributes to the pathogenesis of psoriasis through pro-inflammatory effect. J Cell Physiol 2021; 237:1044-1056. [PMID: 34553380 DOI: 10.1002/jcp.30587] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 08/31/2021] [Accepted: 09/02/2021] [Indexed: 11/09/2022]
Abstract
Kynureninase (KYNU) is a key enzyme in the tryptophan metabolism pathway with elevated expression in psoriatic lesions relative to normal skin. However, whether KYNU contributes to the pathogenesis of psoriasis remains unknown. We sought to investigate the role of KYNU in psoriasis and its possible regulation mechanism. In the results, KYNU is upregulated in psoriatic skin samples from patients or animal models compared with normal skin control which was assayed in psoriatic patient samples, IMQ-induced psoriasis-like skin inflammation in BABL/c mice and M5-stimulated keratinocyte cell lines by immunohistochemistry (IHC). KYNU knockdown had a trivial impact on keratinocyte proliferation, but significantly inhibited the production of inflammatory cytokines in HaCaT, HEKα, and HEKn cells by quantitative reverse-transcription polymerase chain reaction, enzyme-linked immunosorbent assay, and western blot analysis. The 3'-untranslated region of KYNU contains a conserved target site of a skin-specific microRNA (miRNA), miR-203a, as predicted by TargetScan software. Furthermore, miR-203a exhibited an inversed expression kinetics to KYNU during the development of IMQ-induced psoriasis-like skin inflammation in BABL/c mice. Overexpression of miR-203 subsequently leading to the inhibition of KYNU, could significantly reduce the production of M5-induced, psoriasis-related inflammatory factors in keratinocytes. Finally, KYNU inhibitors could alleviate the pathological phenotypes in IMQ-mice. Our study supported the contributive role of KYNU in the development of psoriasis and provided preliminary evidence for KYNU as a potential therapeutic target in psoriasis.
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Affiliation(s)
- Min Wang
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Yuqian Wang
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Mengdi Zhang
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Qiqi Duan
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Caifeng Chen
- Department of Dermatology, Fujian Provincial Hospital, Clinical Medical College, Fujian Medical University, Fuzhou, China
| | - Qiong Sun
- Department of Life Science and Technology, Institute of Mitochondria, Xi'an Jiaotong University, Xi'an, China
| | - Meng Liu
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Yan Zheng
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
| | - Yongping Shao
- Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Xi'an Jiaotong University, Xi'an, China
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9
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Shreeve N, Depierreux D, Hawkes D, Traherne JA, Sovio U, Huhn O, Jayaraman J, Horowitz A, Ghadially H, Perry JRB, Moffett A, Sled JG, Sharkey AM, Colucci F. The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice. Immunity 2021; 54:1231-1244.e4. [PMID: 33887202 PMCID: PMC8211638 DOI: 10.1016/j.immuni.2021.03.021] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/13/2020] [Accepted: 03/25/2021] [Indexed: 12/13/2022]
Abstract
The conserved CD94/NKG2A inhibitory receptor is expressed by nearly all human and ∼50% of mouse uterine natural killer (uNK) cells. Binding human HLA-E and mouse Qa-1, NKG2A drives NK cell education, a process of unknown physiological importance influenced by HLA-B alleles. Here, we show that NKG2A genetic ablation in dams mated with wild-type males caused suboptimal maternal vascular responses in pregnancy, accompanied by perturbed placental gene expression, reduced fetal weight, greater rates of smaller fetuses with asymmetric growth, and abnormal brain development. These are features of the human syndrome pre-eclampsia. In a genome-wide association study of 7,219 pre-eclampsia cases, we found a 7% greater relative risk associated with the maternal HLA-B allele that does not favor NKG2A education. These results show that the maternal HLA-B→HLA-E→NKG2A pathway contributes to healthy pregnancy and may have repercussions on offspring health, thus establishing the physiological relevance for NK cell education. Video Abstract
CD94/NKG2A educates uterine NK cells NKG2A-deficient dams display reduced utero-placental hemodynamic adaptations Asymmetric growth restriction and abnormal brain development in NKG2A-deficient dams Non-functional HLA-B→HLA-E→NKG2A pathway exposes women to greater pre-eclampsia risk
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Affiliation(s)
- Norman Shreeve
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK; University of Cambridge Centre for Trophoblast Research, Cambridge, UK
| | - Delphine Depierreux
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK; University of Cambridge Centre for Trophoblast Research, Cambridge, UK
| | - Delia Hawkes
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK
| | | | - Ulla Sovio
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK; University of Cambridge Centre for Trophoblast Research, Cambridge, UK
| | - Oisin Huhn
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK; University of Cambridge Centre for Trophoblast Research, Cambridge, UK; Department of Pathology, University of Cambridge, Cambridge, UK; AstraZeneca, Granta Park, Cambridge CB21 6GH, UK
| | - Jyothi Jayaraman
- University of Cambridge Centre for Trophoblast Research, Cambridge, UK; Department of Pathology, University of Cambridge, Cambridge, UK; Department of Physiology, Development and Neurobiology, University of Cambridge, Cambridge, UK
| | - Amir Horowitz
- Department of Oncological Sciences, Precision Immunology Institute and Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge, Cambridge UK
| | - Ashley Moffett
- University of Cambridge Centre for Trophoblast Research, Cambridge, UK; Department of Pathology, University of Cambridge, Cambridge, UK
| | - John G Sled
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Translational Medicine, Hospital for Sick Children, Toronto, Canada
| | - Andrew M Sharkey
- University of Cambridge Centre for Trophoblast Research, Cambridge, UK; Department of Pathology, University of Cambridge, Cambridge, UK
| | - Francesco Colucci
- Department of Obstetrics & Gynaecology, University of Cambridge, National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge CB2 0SW, UK; University of Cambridge Centre for Trophoblast Research, Cambridge, UK.
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10
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Nadel BB, Lopez D, Montoya DJ, Ma F, Waddel H, Khan MM, Mangul S, Pellegrini M. The Gene Expression Deconvolution Interactive Tool (GEDIT): accurate cell type quantification from gene expression data. Gigascience 2021; 10:6137724. [PMID: 33590863 PMCID: PMC7931818 DOI: 10.1093/gigascience/giab002] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/13/2020] [Accepted: 01/07/2021] [Indexed: 12/25/2022] Open
Abstract
Background The cell type composition of heterogeneous tissue samples can be a critical variable in both clinical and laboratory settings. However, current experimental methods of cell type quantification (e.g., cell flow cytometry) are costly, time consuming and have potential to introduce bias. Computational approaches that use expression data to infer cell type abundance offer an alternative solution. While these methods have gained popularity, most fail to produce accurate predictions for the full range of platforms currently used by researchers or for the wide variety of tissue types often studied. Results We present the Gene Expression Deconvolution Interactive Tool (GEDIT), a flexible tool that utilizes gene expression data to accurately predict cell type abundances. Using both simulated and experimental data, we extensively evaluate the performance of GEDIT and demonstrate that it returns robust results under a wide variety of conditions. These conditions include multiple platforms (microarray and RNA-seq), tissue types (blood and stromal), and species (human and mouse). Finally, we provide reference data from 8 sources spanning a broad range of stromal and hematopoietic types in both human and mouse. GEDIT also accepts user-submitted reference data, thus allowing the estimation of any cell type or subtype, provided that reference data are available. Conclusions GEDIT is a powerful method for evaluating the cell type composition of tissue samples and provides excellent accuracy and versatility compared to similar tools. The reference database provided here also allows users to obtain estimates for a wide variety of tissue samples without having to provide their own data.
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Affiliation(s)
- Brian B Nadel
- Bioinformatics Interdepartmental Degree Program, Molecular Biology Institute, Department of Molecular Cellular and Developmental Biology, and Institute for Genomics and Proteomics, University of California Los Angeles, 610 Charles E Young Dr S, Los Angeles, CA 90095, USA
| | - David Lopez
- Bioinformatics Interdepartmental Degree Program, Molecular Biology Institute, Department of Molecular Cellular and Developmental Biology, and Institute for Genomics and Proteomics, University of California Los Angeles, 610 Charles E Young Dr S, Los Angeles, CA 90095, USA
| | - Dennis J Montoya
- Bioinformatics Interdepartmental Degree Program, Molecular Biology Institute, Department of Molecular Cellular and Developmental Biology, and Institute for Genomics and Proteomics, University of California Los Angeles, 610 Charles E Young Dr S, Los Angeles, CA 90095, USA
| | - Feiyang Ma
- Bioinformatics Interdepartmental Degree Program, Molecular Biology Institute, Department of Molecular Cellular and Developmental Biology, and Institute for Genomics and Proteomics, University of California Los Angeles, 610 Charles E Young Dr S, Los Angeles, CA 90095, USA
| | - Hannah Waddel
- Department of Mathematics, University of Utah, 155 1400 E, Salt Lake City, UT 84112, USA
| | - Misha M Khan
- Departments of Biology and Computer Science, Swarthmore College, 500 College Ave, Swarthmore, PA 19081, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, USC School of Pharmacy, 1450 Alcazar Street Los Angeles, CA 90089, USA
| | - Matteo Pellegrini
- Bioinformatics Interdepartmental Degree Program, Molecular Biology Institute, Department of Molecular Cellular and Developmental Biology, and Institute for Genomics and Proteomics, University of California Los Angeles, 610 Charles E Young Dr S, Los Angeles, CA 90095, USA.,Department of Dermatology, David Geffen School of Medicine, University of California Los Angeles, 10833 Le Conte Ave, Los Angeles, CA 90095, USA
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11
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Bergstrom K, Shan X, Casero D, Batushansky A, Lagishetty V, Jacobs JP, Hoover C, Kondo Y, Shao B, Gao L, Zandberg W, Noyovitz B, McDaniel JM, Gibson DL, Pakpour S, Kazemian N, McGee S, Houchen CW, Rao CV, Griffin TM, Sonnenburg JL, McEver RP, Braun J, Xia L. Proximal colon-derived O-glycosylated mucus encapsulates and modulates the microbiota. Science 2020; 370:467-472. [PMID: 33093110 DOI: 10.1126/science.aay7367] [Citation(s) in RCA: 118] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 07/10/2020] [Accepted: 09/04/2020] [Indexed: 12/13/2022]
Abstract
Colon mucus segregates the intestinal microbiota from host tissues, but how it organizes to function throughout the colon is unclear. In mice, we found that colon mucus consists of two distinct O-glycosylated entities of Muc2: a major form produced by the proximal colon, which encapsulates the fecal material including the microbiota, and a minor form derived from the distal colon, which adheres to the major form. The microbiota directs its own encapsulation by inducing Muc2 production from proximal colon goblet cells. In turn, O-glycans on proximal colon-derived Muc2 modulate the structure and function of the microbiota as well as transcription in the colon mucosa. Our work shows how proximal colon control of mucin production is an important element in the regulation of host-microbiota symbiosis.
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Affiliation(s)
- Kirk Bergstrom
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA. .,Department of Biology, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - Xindi Shan
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - David Casero
- Inflammatory Bowel and Immunobiology Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Albert Batushansky
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Venu Lagishetty
- Vatche and Tamar Manoukian Division of Digestive Diseases, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Jonathan P Jacobs
- Division of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, Los Angeles, CA 90025, USA
| | - Christopher Hoover
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Yuji Kondo
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Bojing Shao
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Liang Gao
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Wesley Zandberg
- Department of Chemistry, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - Benjamin Noyovitz
- Department of Chemistry, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - J Michael McDaniel
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Deanna L Gibson
- Department of Biology, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - Sepideh Pakpour
- School of Engineering, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - Negin Kazemian
- School of Engineering, University of British Columbia, Okanagan Campus, Kelowna, British Columbia V1V 1V7, Canada
| | - Samuel McGee
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA
| | - Courtney W Houchen
- Department of Internal Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Chinthalapally V Rao
- Department of Internal Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Timothy M Griffin
- Aging and Metabolism Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA.,Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Justin L Sonnenburg
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Rodger P McEver
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA.,Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
| | - Jonathan Braun
- Inflammatory Bowel and Immunobiology Institute, Cedars Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Lijun Xia
- Cardiovascular Biology Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK 73104, USA. .,Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
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12
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Del Vecchio G, Li Q, Li W, Thamotharan S, Tosevska A, Morselli M, Sung K, Janzen C, Zhou X, Pellegrini M, Devaskar SU. Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes. Epigenetics 2020; 16:642-661. [PMID: 33045922 DOI: 10.1080/15592294.2020.1816774] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. Here we investigated cell-free DNA and RNA content of 102 maternal and 25 cord plasma samples. Employing a novel deconvolution methodology, we found that during the first trimester, placenta-specific DNA increased prior to the subsequent development of gestational diabetes with no change in patients with preeclampsia while decreasing with maternal obesity. Moreover, using cell-free RNA sequencing, APOs revealed 71 differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3, and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.
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Affiliation(s)
- Giorgia Del Vecchio
- Departments of Pediatrics David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Qingjiao Li
- The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Wenyuan Li
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Shanthie Thamotharan
- Departments of Pediatrics David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Anela Tosevska
- Departments of Molecular, Cellular and Developmental Biology, University of California Los Angeles, California, USA
| | - Marco Morselli
- Departments of Molecular, Cellular and Developmental Biology, University of California Los Angeles, California, USA
| | - Kyunghyun Sung
- Department of Radiological Sciences, University of California Los Angeles, California, USA
| | - Carla Janzen
- Department of Obstetrics & Gynecology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Xianghong Zhou
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Matteo Pellegrini
- Departments of Molecular, Cellular and Developmental Biology, University of California Los Angeles, California, USA
| | - Sherin U Devaskar
- Departments of Pediatrics David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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13
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Hughes TK, Wadsworth MH, Gierahn TM, Do T, Weiss D, Andrade PR, Ma F, de Andrade Silva BJ, Shao S, Tsoi LC, Ordovas-Montanes J, Gudjonsson JE, Modlin RL, Love JC, Shalek AK. Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies. Immunity 2020; 53:878-894.e7. [PMID: 33053333 PMCID: PMC7562821 DOI: 10.1016/j.immuni.2020.09.015] [Citation(s) in RCA: 137] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 05/21/2020] [Accepted: 09/18/2020] [Indexed: 01/10/2023]
Abstract
High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.
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Affiliation(s)
- Travis K Hughes
- Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Department of Immunology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemistry, MIT, Cambridge, Massachusetts, USA
| | - Marc H Wadsworth
- Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemistry, MIT, Cambridge, Massachusetts, USA
| | - Todd M Gierahn
- Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemical Engineering, MIT, Cambridge, MA, USA
| | - Tran Do
- Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - David Weiss
- Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Priscila R Andrade
- Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Feiyang Ma
- Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Bruno J de Andrade Silva
- Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Shuai Shao
- Department of Dermatology, University of Michigan, Ann Arbor, MI, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, MI, USA
| | - Jose Ordovas-Montanes
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Gastroenterology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | | | - Robert L Modlin
- Division of Gastroenterology, Boston Children's Hospital, Boston, MA, USA
| | - J Christopher Love
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemical Engineering, MIT, Cambridge, MA, USA.
| | - Alex K Shalek
- Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Department of Immunology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA.
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14
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Mandric I, Rotman J, Yang HT, Strauli N, Montoya DJ, Van Der Wey W, Ronas JR, Statz B, Yao D, Petrova V, Zelikovsky A, Spreafico R, Shifman S, Zaitlen N, Rossetti M, Ansel KM, Eskin E, Mangul S. Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing. Nat Commun 2020; 11:3126. [PMID: 32561710 PMCID: PMC7305308 DOI: 10.1038/s41467-020-16857-7] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Accepted: 05/24/2020] [Indexed: 11/09/2022] Open
Abstract
Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases. Information on immune receptor repertoire provides important insights on disease progression and therapy development, but can be expensive and time-consuming to obtain. Here the authors report ImReP, a computational method that can extract detailed immune repertoire information from existing tissue-specific RNA sequencing data.
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Affiliation(s)
- Igor Mandric
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Jeremy Rotman
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA, 90033, USA
| | - Harry Taegyun Yang
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095-1570, USA
| | - Nicolas Strauli
- Biomedical Sciences Graduate Program, University of California, San Francisco, 1675 Owens Street, Suite 310, San Francisco, CA, 94143-0523, USA
| | - Dennis J Montoya
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, 610 Charles E. Young Drive South, Los Angeles, CA, 90095, USA
| | - William Van Der Wey
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Jiem R Ronas
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, 609 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Benjamin Statz
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Douglas Yao
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, 610 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.,Program in Bioinformatics and Integrative Genomics, Harvard Medical School, 10 Shattuck Street, Suite 514, Boston, MA, 02115, USA
| | - Velislava Petrova
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Alex Zelikovsky
- Department of Computer Science, Georgia State University, 33 Gilmer Street SE, Atlanta, GA, 30303, USA.,The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Roberto Spreafico
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Noah Zaitlen
- Department of Medicine, University of California, San Francisco, 533 Parnassus Avenue, San Francisco, CA, 94143, USA
| | - Maura Rossetti
- Immunogenetics Center, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, 1000 Veteran Avenue, Los Angeles, CA, 90095-1652, USA
| | - K Mark Ansel
- Sandler Asthma Basic Research Center, Department of Microbiology and Immunology, University of California, San Francisco, 513 Parnassus Avenue, San Francisco, CA, 94143-0414, USA
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine at UCLA, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA, 90095, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, 73-235 CHS, Los Angeles, CA, 90095, USA
| | - Serghei Mangul
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA. .,Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA, 90033, USA. .,Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
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15
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So AR, Si JM, Lopez D, Pellegrini M. Molecular signatures for inflammation vary across cancer types and correlate significantly with tumor stage, sex and vital status of patients. PLoS One 2020; 15:e0221545. [PMID: 32330128 PMCID: PMC7182171 DOI: 10.1371/journal.pone.0221545] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 02/19/2020] [Indexed: 01/02/2023] Open
Abstract
Cancer affects millions of individuals worldwide. One shortcoming of traditional cancer classification systems is that, even for tumors affecting a single organ, there is significant molecular heterogeneity. Precise molecular classification of tumors could be beneficial in personalizing patients’ therapy and predicting prognosis. To this end, here we propose to use molecular signatures to further refine cancer classification. Molecular signatures are collections of genes characterizing particular cell types, tissues or disease. Signatures can be used to interpret expression profiles from heterogeneous samples. Large collections of gene signatures have previously been cataloged in the MSigDB database. We have developed a web-based Signature Visualization Tool (SaVanT) to display signature scores in user-generated expression data. Here we have undertaken a systematic analysis of correlations between inflammatory signatures and cancer samples, to test whether inflammation can differentiate cancer types. Inflammatory response signatures were obtained from MsigDB and SaVanT and a signature score was computed for samples associated with 7 different cancer types. We first identified types of cancers that had high inflammation levels as measured by these signatures. The correlation between signature scores and metadata of these patients (sex, age at initial cancer diagnosis, cancer stage, and vital status) was then computed. We sought to evaluate correlations between inflammation with other clinical parameters and identified four cancer types that had statistically significant association (p-value < 0.05) with at least one clinical characteristic: pancreas adenocarcinoma (PAAD), cholangiocarcinoma (CHOL), kidney chromophobe (KICH), and uveal melanoma (UVM). These results may allow future studies to use these approaches to further refine cancer subtyping and ultimately treatment.
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Affiliation(s)
- Alexandra Renee So
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
- * E-mail:
| | - Jeong Min Si
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
| | - David Lopez
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
- Gilead Pharmaceuticals, Foster City, California, United States of America
| | - Matteo Pellegrini
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, California, United States of America
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16
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Wang H, Jiang H, Teles RMB, Chen Y, Wu A, Lu J, Chen Z, Ma F, Pellegrini M, Modlin RL. Cellular, Molecular, and Immunological Characteristics of Langhans Multinucleated Giant Cells Programmed by IL-15. J Invest Dermatol 2020; 140:1824-1836.e7. [PMID: 32092350 DOI: 10.1016/j.jid.2020.01.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Revised: 01/28/2020] [Accepted: 01/30/2020] [Indexed: 10/24/2022]
Abstract
Langhans multinucleated giant cells (LGCs) are a specific type of multinucleated giant cell containing a characteristic horseshoe-shaped ring of nuclei that are present within granulomas of infectious etiology. Although cytokines that trigger macrophage activation (such as IFN-γ) induce LGC formation, it is not clear whether cytokines that trigger macrophage differentiation contribute to LGC formation. Here, we found that IL-15, a cytokine that induces M1 macrophage differentiation, programs human peripheral blood adherent cells to form LGCs. Analysis of the IL-15‒treated adherent cell transcriptome identified gene networks for T cells, DNA damage and replication, and IFN-inducible genes that correlated with IL-15 treatment and LGC-type multinucleated giant cell formation. Gene networks enriched for myeloid cells were anticorrelated with IL-15 treatment and LGC formation. Functional studies revealed that T cells were required for IL-15‒induced LGC formation, involving a direct contact with myeloid cells through CD40L-CD40 interaction and IFN-γ release. These data indicate that IL-15 induces LGC formation through the direct interaction of activated T cells and myeloid cells.
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Affiliation(s)
- Hongsheng Wang
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA; Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Haiqin Jiang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Rosane M B Teles
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA
| | - Yanqing Chen
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Aiping Wu
- Suzhou Institute of Systems Medicine Center of Systems Medicine, Chinese Academy of Medical Sciences, Suzhou, China
| | - Jing Lu
- Department of Molecular, Cell and Developmental Biology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA
| | - Zhimin Chen
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
| | - Feiyang Ma
- Department of Molecular, Cell and Developmental Biology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA
| | - Robert L Modlin
- Department of Medicine, Division of Dermatology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA; Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA.
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17
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Sun M, Wadehra M, Casero D, Lin MC, Aguirre B, Parikh S, Matynia A, Gordon L, Chu A. Epithelial Membrane Protein 2 (EMP2) Promotes VEGF-Induced Pathological Neovascularization in Murine Oxygen-Induced Retinopathy. Invest Ophthalmol Vis Sci 2020; 61:3. [PMID: 32031575 PMCID: PMC7325623 DOI: 10.1167/iovs.61.2.3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 11/07/2019] [Indexed: 02/07/2023] Open
Abstract
Purpose Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. ROP occurs as a consequence of postnatal hyperoxia exposure in premature infants, resulting in vasoproliferation in the retina. The tetraspan protein epithelial membrane protein-2 (EMP2) is highly expressed in the retinal pigment epithelium (RPE) in adults, and it controls vascular endothelial growth factor (VEGF) production in the ARPE-19 cell line. We, therefore, hypothesized that Emp2 knockout (Emp2 KO) protects against neovascularization in murine oxygen-induced retinopathy (OIR). Methods Eyes were obtained from wildtype (WT) and Emp2 KO mouse pups at P7, P12, P17, and P21 after normoxia or hyperoxia (P7-P12) exposure. Following hyperoxia exposure, RNA sequencing was performed using the retina/choroid layers obtained from WT and Emp2 KO at P17. Retinal sections from P7, P12, P17, and P21 were evaluated for Emp2, hypoxia-inducible factor 1α (Hif1α), and VEGF expression. Whole mount images were generated to assess vaso-obliteration at P12 and neovascularization at P17. Results Emp2 KO OIR mice demonstrated a decrease in pathologic neovascularization at P17 compared with WT OIR mice through evaluation of retinal vascular whole mount images. This protection was accompanied by a decrease in Hif1α at P12 and VEGFA expression at P17 in Emp2 KO animals compared with the WT animals in OIR conditions. Collectively, our results suggest that EMP2 enhances the effects of neovascularization through modulation of angiogenic signaling. Conclusions The protection of Emp2 KO mice against pathologic neovascularization through attenuation of HIF and VEGF upregulation in OIR suggests that hypoxia-induced upregulation of EMP2 expression in the neuroretina modulates HIF-mediated neuroretinal VEGF expression.
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Affiliation(s)
- Michel Sun
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - Madhuri Wadehra
- Department of Pathology Lab Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
- Jonsson Comprehensive Cancer, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - David Casero
- Department of Pathology Lab Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - Meng-Chin Lin
- Division of Neonatology and Developmental Biology, Department of Pediatrics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - Brian Aguirre
- Department of Pathology Lab Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - Sachin Parikh
- Laboratory of Ocular and Molecular Biology and Genetics, Jules Stein Institute, University of California-Los Angeles, Los Angeles, California, United States
| | - Anna Matynia
- Laboratory of Ocular and Molecular Biology and Genetics, Jules Stein Institute, University of California-Los Angeles, Los Angeles, California, United States
| | - Lynn Gordon
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
| | - Alison Chu
- Division of Neonatology and Developmental Biology, Department of Pediatrics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California, United States
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18
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Teles RMB, Lu J, Tió-Coma M, Goulart IMB, Banu S, Hagge D, Bobosha K, Ottenhoff THM, Pellegrini M, Geluk A, Modlin RL. Identification of a systemic interferon-γ inducible antimicrobial gene signature in leprosy patients undergoing reversal reaction. PLoS Negl Trop Dis 2019; 13:e0007764. [PMID: 31600201 PMCID: PMC6805014 DOI: 10.1371/journal.pntd.0007764] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Revised: 10/22/2019] [Accepted: 09/09/2019] [Indexed: 12/11/2022] Open
Abstract
Reversal reactions (RRs) in leprosy are characterized by a reduction in the number of bacilli in lesions associated with an increase in cell-mediated immunity against the intracellular bacterium Mycobacterium leprae, the causative pathogen of leprosy. To identify the mechanisms that contribute to cell-mediated immunity in leprosy, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified an ‘RR signature’ of 1017 genes that were upregulated at the time of the clinical diagnosis of RR. Using weighted gene correlated network analysis (WGCNA), we detected a module of 794 genes, bisque4, that was significantly correlated with RR, of which 434 genes were part of the RR signature. An enrichment for both IFN-γ and IFN-β downstream gene pathways was present in the RR signature as well as the RR upregulated genes in the bisque4 module, including those encoding proteins of the guanylate binding protein (GBP) family that contributes to antimicrobial responses against mycobacteria. Specifically, GBP1, GBP2, GBP3 and GBP5 mRNAs were upregulated in the RR peripheral blood transcriptome, with GBP1, GBP2 and GBP5 mRNAs also upregulated in the RR disease lesion transcriptome. These data indicate that RRs involve a systemic upregulation of IFN-γ downstream genes including GBP family members as part of the host antimicrobial response against mycobacteria. Reversal reaction (RR) is a major cause of tissue injury and disabilities in leprosy, resulting from the rapid onset of cell-mediated immune responses to the intracellular bacterium Mycobacterium leprae. To identify the mechanisms related to the increase in cell-mediated immunity in RR, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified that RRs are associated with an IFN-γ induced inflammatory response including an antimicrobial gene network containing the GBP1, GBP2, GBP3 and GBP5 mRNAs in the peripheral blood. Furthermore, we show that GBP1, GBP2 and GBP5 mRNAs are also upregulated at the site of disease in RR patients. In summary, our study suggests that RR involves a systemic induction of IFN-γ regulated genes that contributes to an antimicrobial response against the pathogen, releasing ligands and antigens that can further amplify the inflammatory response.
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Affiliation(s)
- Rosane M. B. Teles
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, United States of America
| | - Jing Lu
- Department of Molecular, Cell and Developmental Biology, University of California (UCLA), Los Angeles, California, United States of America
| | - Maria Tió-Coma
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands
| | - Isabela M. B. Goulart
- National Reference Center for Sanitary Dermatology and Leprosy, Faculty of Medicine, Federal University of Uberlandia, Minas Gerais, Brazil
| | - Sayera Banu
- International Center for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Deanna Hagge
- Mycobacterial Research Laboratories, Anandaban Hospital, Kathmandu, Nepal
| | - Kidist Bobosha
- Armauer Hansen Research Institute, Addis Ababa, Ethiopia
| | - Tom H. M. Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California (UCLA), Los Angeles, California, United States of America
| | - Annemieke Geluk
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands
| | - Robert L. Modlin
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, United States of America
- Department of Microbiology, Immunology and Molecular Genetics, University of California (UCLA), Los Angeles, California, United States of America
- * E-mail:
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19
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Pioli PD, Casero D, Montecino-Rodriguez E, Morrison SL, Dorshkind K. Plasma Cells Are Obligate Effectors of Enhanced Myelopoiesis in Aging Bone Marrow. Immunity 2019; 51:351-366.e6. [PMID: 31303400 DOI: 10.1016/j.immuni.2019.06.006] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Revised: 04/10/2019] [Accepted: 06/12/2019] [Indexed: 12/25/2022]
Abstract
Aging results in increased myelopoiesis, which is linked to the increased incidence of myeloid leukemias and production of myeloid-derived suppressor cells. Here, we examined the contribution of plasma cells (PCs) to age-related increases in myelopoiesis, as PCs exhibit immune regulatory function and sequester in bone marrow (BM). PC number was increased in old BM, and they exhibited high expression of genes encoding inflammatory cytokines and pathogen sensors. Antibody-mediated depletion of PCs from old mice reduced the number of myeloid-biased hematopoietic stem cells and mature myeloid cells to levels in young animals, but lymphopoiesis was not rejuvenated, indicating that redundant mechanisms inhibit that process. PCs also regulated the production of inflammatory factors from BM stromal cells, and disruption of the PC-stromal cell circuitry with inhibitors of the cytokines IL-1 and TNF-α attenuated myelopoiesis in old mice. Thus, the age-related increase in myelopoiesis is driven by an inflammatory network orchestrated by PCs.
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Affiliation(s)
- Peter D Pioli
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - David Casero
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | | | - Sherie L Morrison
- Department of Microbiology, Immunology and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Kenneth Dorshkind
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA.
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20
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Zemke NR, Gou D, Berk AJ. Dedifferentiation by adenovirus E1A due to inactivation of Hippo pathway effectors YAP and TAZ. Genes Dev 2019; 33:828-843. [PMID: 31171701 PMCID: PMC6601516 DOI: 10.1101/gad.324814.119] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 04/26/2019] [Indexed: 01/09/2023]
Abstract
In this study, Zemke et al. show that E1A inactivates the Hippo pathway-regulated TEAD coactivators YAP and TAZ by causing their sequestration in the cytoplasm. Their findings suggest that YAP/TAZ function in a developmental checkpoint controlled by signaling from the actin cytoskeleton that prevents differentiation of a progenitor cell until it is in the correct cellular and tissue environment. Adenovirus transformed cells have a dedifferentiated phenotype. Eliminating E1A in transformed human embryonic kidney cells derepressed ∼2600 genes, generating a gene expression profile closely resembling mesenchymal stem cells (MSCs). This was associated with a dramatic change in cell morphology from one with scant cytoplasm and a globular nucleus to one with increased cytoplasm, extensive actin stress fibers, and actomyosin-dependent flattening against the substratum. E1A-induced hypoacetylation at histone H3 Lys27 and Lys18 (H3K27/18) was reversed. Most of the increase in H3K27/18ac was in enhancers near TEAD transcription factors bound by Hippo signaling-regulated coactivators YAP and TAZ. E1A causes YAP/TAZ cytoplasmic sequestration. After eliminating E1A, YAP/TAZ were transported into nuclei, where they associated with poised enhancers with DNA-bound TEAD4 and H3K4me1. This activation of YAP/TAZ required RHO family GTPase signaling and caused histone acetylation by p300/CBP, chromatin remodeling, and cohesin loading to establish MSC-associated enhancers and then superenhancers. Consistent results were also observed in primary rat embryo kidney cells, human fibroblasts, and human respiratory tract epithelial cells. These results together with earlier studies suggest that YAP/TAZ function in a developmental checkpoint controlled by signaling from the actin cytoskeleton that prevents differentiation of a progenitor cell until it is in the correct cellular and tissue environment.
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Affiliation(s)
- Nathan R Zemke
- Molecular Biology Institute, University of California at Los Angeles, Los Angeles, California 90095, USA
| | - Dawei Gou
- Molecular Biology Institute, University of California at Los Angeles, Los Angeles, California 90095, USA
| | - Arnold J Berk
- Molecular Biology Institute, University of California at Los Angeles, Los Angeles, California 90095, USA
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21
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Montoya DJ, Andrade P, Silva BJA, Teles RMB, Ma F, Bryson B, Sadanand S, Noel T, Lu J, Sarno E, Arnvig KB, Young D, Lahiri R, Williams DL, Fortune S, Bloom BR, Pellegrini M, Modlin RL. Dual RNA-Seq of Human Leprosy Lesions Identifies Bacterial Determinants Linked to Host Immune Response. Cell Rep 2019; 26:3574-3585.e3. [PMID: 30917313 PMCID: PMC6508871 DOI: 10.1016/j.celrep.2019.02.109] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Revised: 10/05/2018] [Accepted: 02/27/2019] [Indexed: 01/20/2023] Open
Abstract
To understand how the interaction between an intracellular bacterium and the host immune system contributes to outcome at the site of infection, we studied leprosy, a disease that forms a clinical spectrum, in which progressive infection by the intracellular bacterium Mycobacterium leprae is characterized by the production of type I IFNs and antibody production. Dual RNA-seq on patient lesions identifies two independent molecular measures of M. leprae, each of which correlates with distinct aspects of the host immune response. The fraction of bacterial transcripts, reflecting bacterial burden, correlates with a host type I IFN gene signature, known to inhibit antimicrobial responses. Second, the bacterial mRNA:rRNA ratio, reflecting bacterial viability, links bacterial heat shock proteins with the BAFF-BCMA host antibody response pathway. Our findings provide a platform for the interrogation of host and pathogen transcriptomes at the site of infection, allowing insight into mechanisms of inflammation in human disease.
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Affiliation(s)
- Dennis J Montoya
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Priscila Andrade
- Division of Dermatology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Bruno J A Silva
- Division of Dermatology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Rosane M B Teles
- Division of Dermatology, David Geffen School of Medicine, Los Angeles, CA, USA
| | - Feiyang Ma
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Bryan Bryson
- Harvard T.H. Chan School of Public Health, Department of Immunology and Infectious Diseases, Boston, MA, USA
| | | | - Teia Noel
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Jing Lu
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Euzenir Sarno
- Department of Mycobacteriosis, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Kristine B Arnvig
- Institute for Structural and Molecular Biology, University College London, London WC1E 6BT, UK
| | - Douglas Young
- National Institute for Medical Research, Mycobacterial Research Division, London NW7 1AA, UK; The Francis Crick Institute, Mill Hill Laboratory, The Ridgeway, Mill Hill, London NW7 1AA, UK
| | - Ramanuj Lahiri
- Health Resources and Services Administration (HRSA), National Hansen's Disease Program (NHDP), Baton Rouge, LA, USA
| | - Diana L Williams
- Health Resources and Services Administration (HRSA), National Hansen's Disease Program (NHDP), Baton Rouge, LA, USA; Department of Pathobiological Sciences, Louisiana State University (LSU), Baton Rouge, LA, USA
| | - Sarah Fortune
- Harvard T.H. Chan School of Public Health, Department of Immunology and Infectious Diseases, Boston, MA, USA
| | - Barry R Bloom
- Harvard T.H. Chan School of Public Health, Department of Immunology and Infectious Diseases, Boston, MA, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Robert L Modlin
- Division of Dermatology, David Geffen School of Medicine, Los Angeles, CA, USA.
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22
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Montecino-Rodriguez E, Kong Y, Casero D, Rouault A, Dorshkind K, Pioli PD. Lymphoid-Biased Hematopoietic Stem Cells Are Maintained with Age and Efficiently Generate Lymphoid Progeny. Stem Cell Reports 2019; 12:584-596. [PMID: 30799276 PMCID: PMC6409485 DOI: 10.1016/j.stemcr.2019.01.016] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 01/18/2019] [Accepted: 01/21/2019] [Indexed: 12/26/2022] Open
Abstract
Current models propose that reductions in the number of lymphoid-biased hematopoietic stem cells (Ly-HSCs) underlie age-related declines in lymphopoiesis. We show that Ly-HSCs do not decline in number with age. Old Ly-HSCs exhibit changes in gene expression and a myeloid-biased genetic profile, but we demonstrate that they retain normal lymphoid potential when removed from the old in vivo environment. Additional studies showing that interleukin-1 inhibits Ly-HSC lymphoid potential provide support for the hypothesis that increased production of inflammatory cytokines during aging underlies declines in lymphocyte production. These results indicate that current models proposing that lymphopoiesis declines with age due to loss of Ly-HSCs require revision and provide an additional perspective on why lymphocyte development in the elderly is attenuated. Ly-HSCs do not decline in number with age Transcriptome changes in old Ly-HSCs result in the acquisition of a myeloid signature Ly-HSCs efficiently generate lymphocytes when removed from the old environment IL-1 blocks lymphoid potential from Ly-HSCs and My-HSCs
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Affiliation(s)
| | - Ying Kong
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - David Casero
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Adrien Rouault
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Kenneth Dorshkind
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA.
| | - Peter D Pioli
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
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23
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Chu A, Casero D, Thamotharan S, Wadehra M, Cosi A, Devaskar SU. The Placental Transcriptome in Late Gestational Hypoxia Resulting in Murine Intrauterine Growth Restriction Parallels Increased Risk of Adult Cardiometabolic Disease. Sci Rep 2019; 9:1243. [PMID: 30718791 PMCID: PMC6361888 DOI: 10.1038/s41598-018-37627-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 12/11/2018] [Indexed: 12/19/2022] Open
Abstract
Intrauterine growth restriction (IUGR) enhances risk for adult onset cardiovascular disease (CVD). The mechanisms underlying IUGR are poorly understood, though inadequate blood flow and oxygen/nutrient provision are considered common endpoints. Based on evidence in humans linking IUGR to adult CVD, we hypothesized that in murine pregnancy, maternal late gestational hypoxia (LG-H) exposure resulting in IUGR would result in (1) placental transcriptome changes linked to risk for later CVD, and 2) adult phenotypes of CVD in the IUGR offspring. After subjecting pregnant mice to hypoxia (10.5% oxygen) from gestational day (GD) 14.5 to 18.5, we undertook RNA sequencing from GD19 placentas. Functional analysis suggested multiple changes in structural and functional genes important for placental health and function, with maximal dysregulation involving vascular and nutrient transport pathways. Concordantly, a ~10% decrease in birthweights and ~30% decrease in litter size was observed, supportive of placental insufficiency. We also found that the LG-H IUGR offspring exhibit increased risk for CVD at 4 months of age, manifesting as hypertension, increased abdominal fat, elevated leptin and total cholesterol concentrations. In summary, this animal model of IUGR links the placental transcriptional response to the stressor of gestational hypoxia to increased risk of developing cardiometabolic disease.
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Affiliation(s)
- Alison Chu
- David Geffen School of Medicine at UCLA, Department of Pediatrics, Division of Neonatology & Developmental Biology, Neonatal Research Center of the UCLA Children's Discovery and Innovation Institute, 10833 Le Conte Avenue, MDCC B2-375, Los Angeles, CA, 90095, USA.
| | - David Casero
- David Geffen School of Medicine at UCLA, Department of Pathology and Laboratory Medicine, 3000 Terasaki Life Sciences Building, 610 Charles Young Drive East, Los Angeles, CA, 90095, USA.
| | - Shanthie Thamotharan
- David Geffen School of Medicine at UCLA, Department of Pediatrics, Division of Neonatology & Developmental Biology, Neonatal Research Center of the UCLA Children's Discovery and Innovation Institute, 10833 Le Conte Avenue, MDCC B2-375, Los Angeles, CA, 90095, USA
| | - Madhuri Wadehra
- David Geffen School of Medicine at UCLA, Department of Pathology and Laboratory Medicine, 4525 MacDonald Research Laboratories, Los Angeles, CA, 90095, USA
| | - Amy Cosi
- David Geffen School of Medicine at UCLA, Department of Pediatrics, Division of Neonatology & Developmental Biology, Neonatal Research Center of the UCLA Children's Discovery and Innovation Institute, 10833 Le Conte Avenue, MDCC B2-375, Los Angeles, CA, 90095, USA
| | - Sherin U Devaskar
- David Geffen School of Medicine at UCLA, Department of Pediatrics, Division of Neonatology & Developmental Biology, Neonatal Research Center of the UCLA Children's Discovery and Innovation Institute, 10833 Le Conte Avenue, MDCC B2-375, Los Angeles, CA, 90095, USA
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Organoid-Induced Differentiation of Conventional T Cells from Human Pluripotent Stem Cells. Cell Stem Cell 2019; 24:376-389.e8. [PMID: 30661959 DOI: 10.1016/j.stem.2018.12.011] [Citation(s) in RCA: 125] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 11/05/2018] [Accepted: 12/13/2018] [Indexed: 11/21/2022]
Abstract
The ability to generate T cells from pluripotent stem cells (PSCs) has the potential to transform autologous T cell immunotherapy by facilitating universal, off-the-shelf cell products. However, differentiation of human PSCs into mature, conventional T cells has been challenging with existing methods. We report that a continuous 3D organoid system induced an orderly sequence of commitment and differentiation from PSC-derived embryonic mesoderm through hematopoietic specification and efficient terminal differentiation to naive CD3+CD8αβ+ and CD3+CD4+ conventional T cells with a diverse T cell receptor (TCR) repertoire. Introduction of an MHC class I-restricted TCR in PSCs produced naive, antigen-specific CD8αβ+ T cells that lacked endogenous TCR expression and showed anti-tumor efficacy in vitro and in vivo. Functional assays and RNA sequencing aligned PSC-derived T cells with primary naive CD8+ T cells. The PSC-artificial thymic organoid (ATO) system presented here is an efficient platform for generating functional, mature T cells from human PSCs.
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Hulsen T, Jamuar SS, Moody AR, Karnes JH, Varga O, Hedensted S, Spreafico R, Hafler DA, McKinney EF. From Big Data to Precision Medicine. Front Med (Lausanne) 2019; 6:34. [PMID: 30881956 PMCID: PMC6405506 DOI: 10.3389/fmed.2019.00034] [Citation(s) in RCA: 172] [Impact Index Per Article: 34.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Accepted: 02/04/2019] [Indexed: 02/05/2023] Open
Abstract
For over a decade the term "Big data" has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, "Big data" no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as "data analytics" and "data science" have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises "Big Advances," significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set "Big data" analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.
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Affiliation(s)
- Tim Hulsen
- Department of Professional Health Solutions and Services, Philips Research, Eindhoven, Netherlands
- *Correspondence: Tim Hulsen
| | - Saumya S. Jamuar
- Department of Paediatrics, KK Women's and Children's Hospital, and Paediatric Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore
| | - Alan R. Moody
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Jason H. Karnes
- Pharmacy Practice and Science, College of Pharmacy, University of Arizona Health Sciences, Phoenix, AZ, United States
| | - Orsolya Varga
- Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen, Hungary
| | - Stine Hedensted
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | | | - David A. Hafler
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT, United States
| | - Eoin F. McKinney
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Eoin F. McKinney
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