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Wilson GE, Knight J, Liu Q, Shelar A, Stewart E, Wang X, Yan X, Sanders J, Visness C, Gill M, Gruchalla R, Liu AH, Kattan M, Khurana Hershey GK, Togias A, Becker PM, Altman MC, Busse WW, Jackson DJ, Montgomery RR, Chupp GL. Activated sputum eosinophils associated with exacerbations in children on mepolizumab. J Allergy Clin Immunol 2024:S0091-6749(24)00241-0. [PMID: 38485057 DOI: 10.1016/j.jaci.2024.01.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/22/2023] [Accepted: 01/30/2024] [Indexed: 03/21/2024]
Abstract
BACKGROUND MUPPITS-2 was a randomized, placebo-controlled clinical trial that demonstrated mepolizumab (anti-IL-5) reduced exacerbations and blood and airway eosinophils in urban children with severe eosinophilic asthma. Despite this reduction in eosinophilia, exacerbation risk persisted in certain patients treated with mepolizumab. This raises the possibility that subpopulations of airway eosinophils exist that contribute to breakthrough exacerbations. OBJECTIVE We aimed to determine the effect of mepolizumab on airway eosinophils in childhood asthma. METHODS Sputum samples were obtained from 53 MUPPITS-2 participants. Airway eosinophils were characterized using mass cytometry and grouped into subpopulations using unsupervised clustering analyses of 38 surface and intracellular markers. Differences in frequency and immunophenotype of sputum eosinophil subpopulations were assessed based on treatment arm and frequency of exacerbations. RESULTS Median sputum eosinophils were significantly lower among participants treated with mepolizumab compared with placebo (58% lower, 0.35% difference [95% CI 0.01, 0.74], P = .04). Clustering analysis identified 3 subpopulations of sputum eosinophils with varied expression of CD62L. CD62Lint and CD62Lhi eosinophils exhibited significantly elevated activation marker and eosinophil peroxidase expression, respectively. In mepolizumab-treated participants, CD62Lint and CD62Lhi eosinophils were more abundant in participants who experienced exacerbations than in those who did not (100% higher for CD62Lint, 0.04% difference [95% CI 0.0, 0.13], P = .04; 93% higher for CD62Lhi, 0.21% difference [95% CI 0.0, 0.77], P = .04). CONCLUSIONS Children with eosinophilic asthma treated with mepolizumab had significantly lower sputum eosinophils. However, CD62Lint and CD62Lhi eosinophils were significantly elevated in children on mepolizumab who had exacerbations, suggesting that eosinophil subpopulations exist that contribute to exacerbations despite anti-IL-5 treatment.
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Affiliation(s)
- Gabriella E Wilson
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn
| | - James Knight
- Department of Genetics and Yale Center for Genome Analysis, Yale School of Medicine, New Haven, Conn
| | - Qing Liu
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn
| | - Ashish Shelar
- Department of Genetics and Yale Center for Genome Analysis, Yale School of Medicine, New Haven, Conn
| | - Emma Stewart
- Committee on Immunology, University of Chicago, Chicago, Ill
| | - Xiaomei Wang
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn
| | - Xiting Yan
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn
| | | | | | - Michelle Gill
- Department of Pediatric Infectious Diseases, Washington University in St Louis School of Medicine, St Louis, Mo
| | - Rebecca Gruchalla
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Tex
| | - Andrew H Liu
- Department of Pediatrics, Children's Hospital Colorado and University of Colorado School of Medicine, Aurora, Colo
| | - Meyer Kattan
- Department of Pediatric Pulmonology, Columbia University Irving Medical Center, New York, NY
| | | | - Alkis Togias
- National Institute of Allergy and Infectious Diseases, Bethesda, Md
| | - Patrice M Becker
- National Institute of Allergy and Infectious Diseases, Bethesda, Md
| | | | - William W Busse
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Daniel J Jackson
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, Wis
| | - Ruth R Montgomery
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn
| | - Geoffrey L Chupp
- Department of Internal Medicine, Yale School of Medicine, New Haven, Conn.
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2
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Lee HJ, Zhao Y, Fleming I, Mehta S, Wang X, Wyk BV, Ronca SE, Kang H, Chou CH, Fatou B, Smolen KK, Levy O, Clish CB, Xavier RJ, Steen H, Hafler DA, Love JC, Shalek AK, Guan L, Murray KO, Kleinstein SH, Montgomery RR. Early cellular and molecular signatures correlate with severity of West Nile virus infection. iScience 2023; 26:108387. [PMID: 38047068 PMCID: PMC10692672 DOI: 10.1016/j.isci.2023.108387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 10/04/2023] [Accepted: 10/27/2023] [Indexed: 12/05/2023] Open
Abstract
Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.
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Affiliation(s)
- Ho-Joon Lee
- Department of Genetics and Yale Center for Genome Analysis, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yujiao Zhao
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA
| | - Ira Fleming
- The Institute of Medical Science and Engineering, Department of Chemistry, and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Sameet Mehta
- Department of Genetics and Yale Center for Genome Analysis, Yale School of Medicine, New Haven, CT 06520, USA
| | - Xiaomei Wang
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA
| | - Brent Vander Wyk
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA
| | - Shannon E. Ronca
- Department of Pediatrics, National School of Tropical Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, TX 77030, USA
| | - Heather Kang
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Chih-Hung Chou
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Benoit Fatou
- Department of Pathology, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Kinga K. Smolen
- Department of Pathology, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ofer Levy
- Department of Infectious Disease, Precision Vaccines Program, Boston Children’s Hospital, and Harvard Medical School, Boston, MA 02115, USA
| | - Clary B. Clish
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ramnik J. Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Computational and Integrative Biology and Department of Molecular Biology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Hanno Steen
- Department of Pediatrics, National School of Tropical Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, TX 77030, USA
| | - David A. Hafler
- Departments of Neurology and Immunobiology, Yale School of Medicine, New Haven, CT 06510, USA
| | - J. Christopher Love
- The Institute of Medical Science and Engineering, Department of Chemistry, and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Alex K. Shalek
- The Institute of Medical Science and Engineering, Department of Chemistry, and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Leying Guan
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA
| | - Kristy O. Murray
- Department of Pediatrics, National School of Tropical Medicine, Baylor College of Medicine and Texas Children’s Hospital, Houston, TX 77030, USA
| | - Steven H. Kleinstein
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Ruth R. Montgomery
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06520, USA
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3
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Siamwala JH, Pagano FS, Dubielecka PM, Ivey MJ, Guirao-Abad JP, Zhao A, Chen S, Granston H, Jeong JY, Rounds S, Kanisicak O, Sadayappan S, Gilbert RJ. IL-1β-mediated adaptive reprogramming of endogenous human cardiac fibroblasts to cells with immune features during fibrotic remodeling. Commun Biol 2023; 6:1200. [PMID: 38001239 PMCID: PMC10673909 DOI: 10.1038/s42003-023-05463-0] [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: 05/09/2022] [Accepted: 10/13/2023] [Indexed: 11/26/2023] Open
Abstract
The source and roles of fibroblasts and T-cells during maladaptive remodeling and myocardial fibrosis in the setting of pulmonary arterial hypertension (PAH) have been long debated. We demonstrate, using single-cell mass cytometry, a subpopulation of endogenous human cardiac fibroblasts expressing increased levels of CD4, a helper T-cell marker, in addition to myofibroblast markers distributed in human fibrotic RV tissue, interstitial and perivascular lesions in SUGEN/Hypoxia (SuHx) rats, and fibroblasts labeled with pdgfrα CreERt2/+ in R26R-tdTomato mice. Recombinant IL-1β increases IL-1R, CCR2 receptor expression, modifies the secretome, and differentiates cardiac fibroblasts to form CD68-positive cell clusters. IL-1β also activates stemness markers, such as NANOG and SOX2, and genes involved in dedifferentiation, lymphoid cell function and metabolic reprogramming. IL-1β induction of lineage traced primary mouse cardiac fibroblasts causes these cells to lose their fibroblast identity and acquire an immune phenotype. Our results identify IL-1β induced immune-competency in human cardiac fibroblasts and suggest that fibroblast secretome modulation may constitute a therapeutic approach to PAH and other diseases typified by inflammation and fibrotic remodeling.
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Affiliation(s)
- Jamila H Siamwala
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI, USA.
- Warren Alpert Medical School of Brown University, Providence VA Medical Center, Providence, RI, USA.
| | - Francesco S Pagano
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI, USA
| | - Patrycja M Dubielecka
- Division of Hematology/Oncology, Department of Medicine, Rhode Island Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Malina J Ivey
- Department of Pathology & Laboratory Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Jose Pedro Guirao-Abad
- Department of Pathology & Laboratory Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Alexander Zhao
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI, USA
| | - Sonja Chen
- Warren Alpert Medical School of Brown University, Providence VA Medical Center, Providence, RI, USA
- Department of Pathology & Laboratory Medicine, Rhode Island Hospital, Providence, RI, USA
| | - Haley Granston
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI, USA
| | - Jae Yun Jeong
- Department of Molecular Pharmacology, Physiology and Biotechnology, Brown University, Providence, RI, USA
| | - Sharon Rounds
- Warren Alpert Medical School of Brown University, Providence VA Medical Center, Providence, RI, USA
- Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Onur Kanisicak
- Department of Pathology & Laboratory Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Sakthivel Sadayappan
- Heart, Lung and Vascular Institute, Division of Cardiovascular Health and Disease, Department of Internal Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Richard J Gilbert
- Ocean State Research Institute, Providence VA Medical Center, Providence, RI, USA
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4
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Raju Paul S, Scholzen A, Reeves PM, Shepard R, Hess JM, Dzeng RK, Korek S, Garritsen A, Poznansky MC, Sluder AE. Cytometry profiling of ex vivo recall responses to Coxiella burnetii in previously naturally exposed individuals reveals long-term changes in both adaptive and innate immune cellular compartments. Front Immunol 2023; 14:1249581. [PMID: 37885896 PMCID: PMC10598782 DOI: 10.3389/fimmu.2023.1249581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/26/2023] [Indexed: 10/28/2023] Open
Abstract
Introduction Q fever, caused by the intracellular bacterium Coxiella burnetii, is considered an occupational and biodefense hazard and can result in debilitating long-term complications. While natural infection and vaccination induce humoral and cellular immune responses, the exact nature of cellular immune responses to C. burnetii is incompletely understood. The current study seeks to investigate more deeply the nature of long-term cellular recall responses in naturally exposed individuals by both cytokine release assessment and cytometry profiling. Methods Individuals exposed during the 2007-2010 Dutch Q fever outbreak were grouped in 2015, based on a C. burnetii-specific IFNγ release assay (IGRA), serological status, and self-reported clinical symptoms during initial infection, into asymptomatic IGRA-negative/seronegative controls, and three IGRA-positive groups (seronegative/asymptomatic; seropositive/asymptomatic and seropositive/symptomatic). Recall responses following in vitro re-stimulation with heat-inactivated C. burnetii in whole blood, were assessed in 2016/2017 by cytokine release assays (n=55) and flow cytometry (n=36), and in blood mononuclear cells by mass cytometry (n=36). Results Cytokine release analysis showed significantly elevated IL-2 responses in all seropositive individuals and elevated IL-1β responses in those recovered from symptomatic infection. Comparative flow cytometry analysis revealed significantly increased IFNγ, TNFα and IL-2 recall responses by CD4 T cells and higher IL-6 production by monocytes from symptomatic, IGRA-positive/seropositive individuals compared to controls. Mass cytometry profiling and unsupervised clustering analysis confirmed recall responses in seropositive individuals by two activated CD4 T cell subsets, one characterized by a strong Th1 cytokine profile (IFNγ+IL-2+TNFα+), and identified C. burnetii-specific activation of CD8 T cells in all IGRA-positive groups. Remarkably, increased C. burnetii-specific responses in IGRA-positive individuals were also observed in three innate cell subpopulations: one characterized by an IFNγ+IL-2+TNFα+ Th1 cytokine profile and lack of canonical marker expression, and two IL-1β-, IL-6- and IL-8-producing CD14+ monocyte subsets that could be the drivers of elevated secretion of innate cytokines in pre-exposed individuals. Discussion These data highlight that there are long-term increased responses to C. burnetii in both adaptive and innate cellular compartments, the latter being indicative of trained immunity. These findings warrant future studies into the protective role of these innate responses and may inform future Q fever vaccine design.
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Affiliation(s)
- Susan Raju Paul
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | | | - Patrick M. Reeves
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | - Robert Shepard
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | - Joshua M. Hess
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | - Richard K. Dzeng
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | - Skylar Korek
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | | | - Mark C. Poznansky
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
| | - Ann E. Sluder
- Vaccine and Immunotherapy Center, Massachusetts General Hospital, Boston, MA, United States
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5
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Shapiro MR, Dong X, Perry DJ, McNichols JM, Thirawatananond P, Posgai AL, Peters LD, Motwani K, Musca RS, Muir A, Concannon P, Jacobsen LM, Mathews CE, Wasserfall CH, Haller MJ, Schatz DA, Atkinson MA, Brusko MA, Bacher R, Brusko TM. Human immune phenotyping reveals accelerated aging in type 1 diabetes. JCI Insight 2023; 8:e170767. [PMID: 37498686 PMCID: PMC10544250 DOI: 10.1172/jci.insight.170767] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/19/2023] [Indexed: 07/29/2023] Open
Abstract
The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.
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Affiliation(s)
- Melanie R. Shapiro
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Xiaoru Dong
- Diabetes Institute and
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA
| | - Daniel J. Perry
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - James M. McNichols
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Puchong Thirawatananond
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Amanda L. Posgai
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Leeana D. Peters
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Keshav Motwani
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Richard S. Musca
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Andrew Muir
- Department of Pediatrics, Emory University, Atlanta, Georgia, USA
| | - Patrick Concannon
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
- Genetics Institute and
| | - Laura M. Jacobsen
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Clayton E. Mathews
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Clive H. Wasserfall
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Michael J. Haller
- Diabetes Institute and
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Desmond A. Schatz
- Diabetes Institute and
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Mark A. Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, Florida, USA
| | - Maigan A. Brusko
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
| | - Rhonda Bacher
- Diabetes Institute and
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, USA
| | - Todd M. Brusko
- Department of Pathology, Immunology, and Laboratory Medicine, College of Medicine, and
- Diabetes Institute and
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, Florida, USA
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6
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Duque AF, Morin S, Wolf G, Moon KR. Geometry Regularized Autoencoders. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2023; 45:7381-7394. [PMID: 36374884 PMCID: PMC10339657 DOI: 10.1109/tpami.2022.3222104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
A fundamental task in data exploration is to extract low dimensional representations that capture intrinsic geometry in data, especially for faithfully visualizing data in two or three dimensions. Common approaches use kernel methods for manifold learning. However, these methods typically only provide an embedding of the input data and cannot extend naturally to new data points. Autoencoders have also become popular for representation learning. While they naturally compute feature extractors that are extendable to new data and invertible (i.e., reconstructing original features from latent representation), they often fail at representing the intrinsic data geometry compared to kernel-based manifold learning. We present a new method for integrating both approaches by incorporating a geometric regularization term in the bottleneck of the autoencoder. This regularization encourages the learned latent representation to follow the intrinsic data geometry, similar to manifold learning algorithms, while still enabling faithful extension to new data and preserving invertibility. We compare our approach to autoencoder models for manifold learning to provide qualitative and quantitative evidence of our advantages in preserving intrinsic structure, out of sample extension, and reconstruction. Our method is easily implemented for big-data applications, whereas other methods are limited in this regard.
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Affiliation(s)
- Andres F. Duque
- Department of Mathematics & Statistics, Utah State University, Logan, UT 84322 US
| | - Sacha Morin
- Departments of Computer Science & Operations Research and Mathematics & Statistics (correspondingly), Université de Montréal, Montréal, Quebec, H3T 1J4, Canada; Mila - Quebec AI Institute, Montreal, Quebec, H2S 3H1, Canada
| | - Guy Wolf
- Departments of Computer Science & Operations Research and Mathematics & Statistics (correspondingly), Université de Montréal, Montréal, Quebec, H3T 1J4, Canada; Mila - Quebec AI Institute, Montreal, Quebec, H2S 3H1, Canada
| | - Kevin R. Moon
- Department of Mathematics & Statistics, Utah State University, Logan, UT 84322 US
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7
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Robinson ML, Glass DR, Duran V, Agudelo Rojas OL, Sanz AM, Consuegra M, Sahoo MK, Hartmann FJ, Bosse M, Gelvez RM, Bueno N, Pinsky BA, Montoya JG, Maecker H, Estupiñan Cardenas MI, Villar Centeno LA, Garrido EMR, Rosso F, Bendall SC, Einav S. Magnitude and kinetics of the human immune cell response associated with severe dengue progression by single-cell proteomics. SCIENCE ADVANCES 2023; 9:eade7702. [PMID: 36961888 PMCID: PMC10038348 DOI: 10.1126/sciadv.ade7702] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 02/21/2023] [Indexed: 06/17/2023]
Abstract
Approximately 5 million dengue virus-infected patients progress to a potentially life-threatening severe dengue (SD) infection annually. To identify the immune features and temporal dynamics underlying SD progression, we performed deep immune profiling by mass cytometry of PBMCs collected longitudinally from SD progressors (SDp) and uncomplicated dengue (D) patients. While D is characterized by early activation of innate immune responses, in SDp there is rapid expansion and activation of IgG-secreting plasma cells and memory and regulatory T cells. Concurrently, SDp, particularly children, demonstrate increased proinflammatory NK cells, inadequate expansion of CD16+ monocytes, and high expression of the FcγR CD64 on myeloid cells, yet a signature of diminished antigen presentation. Syndrome-specific determinants include suppressed dendritic cell abundance in shock/hemorrhage versus enriched plasma cell expansion in organ impairment. This study reveals uncoordinated immune responses in SDp and provides insights into SD pathogenesis in humans with potential implications for prediction and treatment.
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Affiliation(s)
- Makeda L. Robinson
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - David R. Glass
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Veronica Duran
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, 499 Illinois St., 4th Floor, San Francisco, CA 94158, USA
| | | | - Ana Maria Sanz
- Clinical Research Center, Fundación Valle del Lili, Cali, Colombia
| | - Monika Consuegra
- Centro de Atención y Diagnóstico de Enfermedades Infecciosas (CDI), Fundación INFOVIDA, Bucaramanga, Colombia
| | - Malaya Kumar Sahoo
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Felix J. Hartmann
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Marc Bosse
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Rosa Margarita Gelvez
- Centro de Atención y Diagnóstico de Enfermedades Infecciosas (CDI), Fundación INFOVIDA, Bucaramanga, Colombia
| | - Nathalia Bueno
- Centro de Atención y Diagnóstico de Enfermedades Infecciosas (CDI), Fundación INFOVIDA, Bucaramanga, Colombia
| | - Benjamin A. Pinsky
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jose G. Montoya
- Palo Alto Medical Foundation, Dr. Jack S. Remington Laboratory for Specialty Diagnostics, Palo Alto, CA, USA
| | - Holden Maecker
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Luis Angel Villar Centeno
- Centro de Atención y Diagnóstico de Enfermedades Infecciosas (CDI), Fundación INFOVIDA, Bucaramanga, Colombia
| | - Elsa Marina Rojas Garrido
- Centro de Atención y Diagnóstico de Enfermedades Infecciosas (CDI), Fundación INFOVIDA, Bucaramanga, Colombia
| | - Fernando Rosso
- Clinical Research Center, Fundación Valle del Lili, Cali, Colombia
- Department of Internal Medicine, Division of Infectious Diseases, Fundación Valle del Lili, Cali, Colombia
| | - Sean C. Bendall
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Shirit Einav
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, 499 Illinois St., 4th Floor, San Francisco, CA 94158, USA
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA
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8
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Xu G, Gao Y, Pan T, Li S, Zhang Y, Guo J, Tian Z, Xu J, Li Y, Li X. Dynamic immune ecosystem of dengue infection revealed by single-cell sequencing. J Leukoc Biol 2022; 112:1621-1631. [PMID: 35766188 DOI: 10.1002/jlb.6ma0622-738rr] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 06/06/2022] [Indexed: 01/04/2023] Open
Abstract
Dengue is the most common human arboviral disease worldwide, which can result in severe complications. A dysfunctional immune response in dengue infective patients is a recurrent theme impacting symptoms and mortality, but the heterogeneity and dynamics of immune infiltrates during dengue infection remain poorly characterized. Here, we identified the immune cell types in scRNA-seq data from 13127 cells of 10 dengue infective patients and discovered the dynamic immune ecosystems of dengue infection. Notably, genes that exhibited higher expression in specific cell types play important roles in response to virus infection in a module manner. Transcription factors (TFs) are the major regulators (i.e., PAX5, IRF7, KLF4, and IRF8) that can potentially regulate infection-related genes. We demonstrated that the dynamic rewired regulatory network during dengue infection. Moreover, our data revealed the complex cell-cell communications from control to fever and severe dengue patients and prevalent cell-cell communication rewiring was observed. We further identified the IFN-II and CXCL signaling pathways that medicated the communications and play important roles in dengue infection. Together, our comprehensive analysis of dynamic immune ecosystem of dengue infection provided novel insights for understanding the pathogenesis of and developing effective therapeutic strategies for dengue infection.
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Affiliation(s)
- Gang Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Yueying Gao
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Tao Pan
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Si Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Ya Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Jing Guo
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Zhanyu Tian
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Juan Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
| | - Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China
| | - Xia Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, China.,College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
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9
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Biondi BE, Mohanty S, Wyk BV, Montgomery RR, Shaw AC, Springer SA. Design and implementation of a prospective cohort study of persons living with and without HIV infection who are initiating medication treatment for opioid use disorder. Contemp Clin Trials Commun 2021; 21:100704. [PMID: 33490708 PMCID: PMC7807244 DOI: 10.1016/j.conctc.2021.100704] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 10/15/2020] [Accepted: 01/01/2021] [Indexed: 02/02/2023] Open
Abstract
Background Opioid use disorder (OUD) negatively impacts the HIV continuum of care for persons living with HIV. Medication treatment for OUD (MOUD) may have differential biological effects in individuals with HIV and OUD. To address the question of modulation of immune responses by MOUDs, we describe state of the art systems biology approaches to carry out the first prospective, longitudinal study of persons with and without HIV infection with OUD initiating MOUD. Methods A prospective cohort study of persons with DSM-5 diagnosed OUD who are living with and without HIV infection and initiating treatment with methadone or buprenorphine is underway to assess biological effects of these medications on immunobiological outcomes. Results We describe the recruitment, laboratory, and statistical methods of this study as well as the protocol details. Of those screened for enrollment into the study, 468 (36%) were eligible and 135 were enrolled thus far. Retention through month 6 has been high at 80%. Conclusions This study will use state of the art systems biology approaches to carry out the first prospective, longitudinal studies of persons living with and without HIV with DSM-5 OUD initiating treatment with MOUD.
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Affiliation(s)
- Breanne E Biondi
- Department of Internal Medicine, Section of Infectious Diseases, AIDS Program, Yale School of Medicine, New Haven, CT, USA
| | - Subhasis Mohanty
- Department of Internal Medicine, Section of Infectious Diseases, AIDS Program, Yale School of Medicine, New Haven, CT, USA
| | - Brent Vander Wyk
- Department of Internal Medicine, Section of Geriatrics, Yale School of Medicine, New Haven, CT, USA
| | - Ruth R Montgomery
- Department of Internal Medicine, Section of Rheumatology, Yale School of Medicine, New Haven, CT, USA
| | - Albert C Shaw
- Department of Internal Medicine, Section of Infectious Diseases, AIDS Program, Yale School of Medicine, New Haven, CT, USA
| | - Sandra A Springer
- Department of Internal Medicine, Section of Infectious Diseases, AIDS Program, Yale School of Medicine, New Haven, CT, USA.,Center for Interdisciplinary Research on AIDS, Yale University School of Public Health, New Haven, CT, USA
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10
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Kotliar D, Lin AE, Logue J, Hughes TK, Khoury NM, Raju SS, Wadsworth MH, Chen H, Kurtz JR, Dighero-Kemp B, Bjornson ZB, Mukherjee N, Sellers BA, Tran N, Bauer MR, Adams GC, Adams R, Rinn JL, Melé M, Schaffner SF, Nolan GP, Barnes KG, Hensley LE, McIlwain DR, Shalek AK, Sabeti PC, Bennett RS. Single-Cell Profiling of Ebola Virus Disease In Vivo Reveals Viral and Host Dynamics. Cell 2020; 183:1383-1401.e19. [PMID: 33159858 PMCID: PMC7707107 DOI: 10.1016/j.cell.2020.10.002] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 08/10/2020] [Accepted: 10/02/2020] [Indexed: 12/14/2022]
Abstract
Ebola virus (EBOV) causes epidemics with high mortality yet remains understudied due to the challenge of experimentation in high-containment and outbreak settings. Here, we used single-cell transcriptomics and CyTOF-based single-cell protein quantification to characterize peripheral immune cells during EBOV infection in rhesus monkeys. We obtained 100,000 transcriptomes and 15,000,000 protein profiles, finding that immature, proliferative monocyte-lineage cells with reduced antigen-presentation capacity replace conventional monocyte subsets, while lymphocytes upregulate apoptosis genes and decline in abundance. By quantifying intracellular viral RNA, we identify molecular determinants of tropism among circulating immune cells and examine temporal dynamics in viral and host gene expression. Within infected cells, EBOV downregulates STAT1 mRNA and interferon signaling, and it upregulates putative pro-viral genes (e.g., DYNLL1 and HSPA5), nominating pathways the virus manipulates for its replication. This study sheds light on EBOV tropism, replication dynamics, and elicited immune response and provides a framework for characterizing host-virus interactions under maximum containment.
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Affiliation(s)
- Dylan Kotliar
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA; FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
| | - Aaron E Lin
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard Program in Virology, Harvard Medical School, Boston, MA 02115, USA.
| | - James Logue
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Travis K Hughes
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Chemistry, Institute for Medical Engineering and Sciences (IMES), and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA; Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Nadine M Khoury
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Siddharth S Raju
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA; FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Marc H Wadsworth
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Chemistry, Institute for Medical Engineering and Sciences (IMES), and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA; Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Han Chen
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Jonathan R Kurtz
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Bonnie Dighero-Kemp
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - Zach B Bjornson
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | | | - Brian A Sellers
- Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation, National Institutes of Health, Bethesda, MD 20814, USA
| | - Nancy Tran
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Matthew R Bauer
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Gordon C Adams
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ricky Adams
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
| | - John L Rinn
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, USA
| | - Marta Melé
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia 08034, Spain
| | - Stephen F Schaffner
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Garry P Nolan
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Kayla G Barnes
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA; MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK
| | - Lisa E Hensley
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA.
| | - David R McIlwain
- Department of Pathology, Stanford University, Stanford, CA 94305, USA.
| | - Alex K Shalek
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Chemistry, Institute for Medical Engineering and Sciences (IMES), and Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA; Ragon Institute of MGH, Harvard, and MIT, Cambridge, MA 02139, USA
| | - Pardis C Sabeti
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA
| | - Richard S Bennett
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD 21702, USA
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11
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McKechnie JL, Beltrán D, Ferreira AMM, Vergara R, Saenz L, Vergara O, Estripeaut D, Araúz AB, Simpson LJ, Holmes S, López-Vergès S, Blish CA. Mass Cytometry Analysis of the NK Cell Receptor-Ligand Repertoire Reveals Unique Differences between Dengue-Infected Children and Adults. Immunohorizons 2020; 4:634-647. [PMID: 33067399 PMCID: PMC8608029 DOI: 10.4049/immunohorizons.2000074] [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: 08/13/2020] [Accepted: 09/24/2020] [Indexed: 12/05/2022] Open
Abstract
Dengue virus (DENV) is a significant cause of morbidity in many regions of the world, with children at the greatest risk of developing severe dengue. NK cells, characterized by their ability to rapidly recognize and kill virally infected cells, are activated during acute DENV infection. However, their role in viral clearance versus pathogenesis has not been fully elucidated. Our goal was to profile the NK cell receptor-ligand repertoire to provide further insight into the function of NK cells during pediatric and adult DENV infection. We used mass cytometry to phenotype isolate NK cells and PBMCs from a cohort of DENV-infected children and adults. Using unsupervised clustering, we found that pediatric DENV infection leads to a decrease in total NK cell frequency with a reduction in the percentage of CD56dimCD38bright NK cells and an increase in the percentage of CD56dimperforinbright NK cells. No such changes were observed in adults. Next, we identified markers predictive of DENV infection using a differential state test. In adults, NK cell expression of activation markers, including CD69, perforin, and Fas-L, and myeloid cell expression of activating NK cell ligands, namely Fas, were predictive of infection. In contrast, increased NK cell expression of the maturation marker CD57 and myeloid cell expression of inhibitory ligands, such as HLA class I molecules, were predictive of pediatric DENV infection. These findings suggest that acute pediatric DENV infection may result in diminished NK cell activation, which could contribute to enhanced pathogenesis and disease severity.
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Affiliation(s)
- Julia L. McKechnie
- Program in Immunology, Stanford University School of Medicine, Stanford, CA 94305
| | - Davis Beltrán
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute for Health Studies, Panama City, Panama
- Institute for Scientific Research and Technology Services, Panama City, Panama
- Department of Biotechnology, Acharya Nagarjuna University, Guntur 522002, India
| | | | - Rosemary Vergara
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305
| | - Lisseth Saenz
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute for Health Studies, Panama City, Panama
| | - Ofelina Vergara
- Hospital del Niño Doctor José Renán Esquivel, Panama City, Panama
| | - Dora Estripeaut
- Hospital del Niño Doctor José Renán Esquivel, Panama City, Panama
| | | | - Laura J. Simpson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305
| | - Susan Holmes
- Department of Statistics, Stanford University, Stanford, CA 94305
| | - Sandra López-Vergès
- Department of Research in Virology and Biotechnology, Gorgas Memorial Institute for Health Studies, Panama City, Panama
- Institute for Scientific Research and Technology Services, Panama City, Panama
- Universidad de Panama, Panama City, Panama
| | - Catherine A. Blish
- Program in Immunology, Stanford University School of Medicine, Stanford, CA 94305
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305
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12
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Zhang T, Warden AR, Li Y, Ding X. Progress and applications of mass cytometry in sketching immune landscapes. Clin Transl Med 2020; 10:e206. [PMID: 33135337 PMCID: PMC7556381 DOI: 10.1002/ctm2.206] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/28/2020] [Accepted: 09/28/2020] [Indexed: 12/16/2022] Open
Abstract
Recently emerged mass cytometry (cytometry by time-of-flight [CyTOF]) technology permits the identification and quantification of inherently diverse cellular systems, and the simultaneous measurement of functional attributes at the single-cell resolution. By virtue of its multiplex ability with limited need for compensation, CyTOF has led a critical role in immunological research fields. Here, we present an overview of CyTOF, including the introduction of CyTOF principle and advantages that make it a standalone tool in deciphering immune mysteries. We then discuss the functional assays, introduce the bioinformatics to interpret the data yield via CyTOF, and depict the emerging clinical and research applications of CyTOF technology in sketching immune landscape in a wide variety of diseases.
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Affiliation(s)
- Ting Zhang
- State Key laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
| | - Antony R. Warden
- State Key laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
| | - Yiyang Li
- State Key laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
| | - Xianting Ding
- State Key laboratory of Oncogenes and Related Genes, Institute for Personalized Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghaiChina
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13
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Stewart E, Wang X, Chupp GL, Montgomery RR. Profiling cellular heterogeneity in asthma with single cell multiparameter CyTOF. J Leukoc Biol 2020; 108:1555-1564. [PMID: 32911570 DOI: 10.1002/jlb.5ma0720-770rr] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 07/13/2020] [Accepted: 08/04/2020] [Indexed: 12/17/2022] Open
Abstract
Asthma is a chronic inflammatory disease of the airways that afflicts over 30 million individuals in the United States and over 300 million individuals worldwide. The inflammatory response in the airways is often characterized by the analysis of sputum, which contains multiple types of cells including neutrophils, macrophages, lymphocytes, and rare bronchial epithelial cells. Subtyping patients using microscopy of the sputum has identified both neutrophilic and eosinophilic infiltrates in airway inflammation. However, with the extensive heterogeneity among these cell types, a higher resolution understanding of the inflammatory cell types present in the sputum is needed to dissect the heterogeneity of disease. Improved recognition of the distinct phenotypes and sources of inflammation in asthmatic granulocytes may identify relevant pathways for clinical management or investigation of novel therapeutic mediators. Here, we employed mass cytometry or cytometry by time-of-flight to quantify frequency and define functional status of sputum derived airway cells in asthmatic patients and healthy controls. This in-depth single cell analysis method identified multiple distinct subtypes of airway immune cells, especially in neutrophils. Significance was discovered by statistical analysis as well as a data-driven unbiased clustering approach. Our multidimensional assessment method identifies differences in cellular function and supports identification of cellular status that may contribute to diverse clinical responses. This technical advance is relevant for studies of pathogenesis and may provide meaningful insights to advance our knowledge of asthmatic inflammation.
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Affiliation(s)
- Emma Stewart
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Xiaomei Wang
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Geoffrey L Chupp
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Ruth R Montgomery
- Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
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14
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The Role of Single-Cell Technology in the Study and Control of Infectious Diseases. Cells 2020; 9:cells9061440. [PMID: 32531928 PMCID: PMC7348906 DOI: 10.3390/cells9061440] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 06/03/2020] [Accepted: 06/05/2020] [Indexed: 02/07/2023] Open
Abstract
The advent of single-cell research in the recent decade has allowed biological studies at an unprecedented resolution and scale. In particular, single-cell analysis techniques such as Next-Generation Sequencing (NGS) and Fluorescence-Activated Cell Sorting (FACS) have helped show substantial links between cellular heterogeneity and infectious disease progression. The extensive characterization of genomic and phenotypic biomarkers, in addition to host-pathogen interactions at the single-cell level, has resulted in the discovery of previously unknown infection mechanisms as well as potential treatment options. In this article, we review the various single-cell technologies and their applications in the ongoing fight against infectious diseases, as well as discuss the potential opportunities for future development.
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