2022
Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19
Unterman A, Sumida TS, Nouri N, Yan X, Zhao AY, Gasque V, Schupp JC, Asashima H, Liu Y, Cosme C, Deng W, Chen M, Raredon MSB, Hoehn KB, Wang G, Wang Z, DeIuliis G, Ravindra NG, Li N, Castaldi C, Wong P, Fournier J, Bermejo S, Sharma L, Casanovas-Massana A, Vogels CBF, Wyllie AL, Grubaugh ND, Melillo A, Meng H, Stein Y, Minasyan M, Mohanty S, Ruff WE, Cohen I, Raddassi K, Niklason L, Ko A, Montgomery R, Farhadian S, Iwasaki A, Shaw A, van Dijk D, Zhao H, Kleinstein S, Hafler D, Kaminski N, Dela Cruz C. Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19. Nature Communications 2022, 13: 440. PMID: 35064122, PMCID: PMC8782894, DOI: 10.1038/s41467-021-27716-4.Peer-Reviewed Original ResearchMeSH KeywordsAdaptive ImmunityAgedAntibodies, Monoclonal, HumanizedCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesCells, CulturedCOVID-19COVID-19 Drug TreatmentFemaleGene Expression ProfilingGene Expression RegulationHumansImmunity, InnateMaleReceptors, Antigen, B-CellReceptors, Antigen, T-CellRNA-SeqSARS-CoV-2Single-Cell AnalysisConceptsProgressive COVID-19B cell clonesSingle-cell analysisT cellsImmune responseMulti-omics single-cell analysisCOVID-19Cell clonesAdaptive immune interactionsSevere COVID-19Dynamic immune responsesGene expressionSARS-CoV-2 virusAdaptive immune systemSomatic hypermutation frequenciesCellular effectsProtein markersEffector CD8Immune signaturesProgressive diseaseHypermutation frequencyProgressive courseClassical monocytesClonesImmune interactions
2020
Transcriptomic and clonal characterization of T cells in the human central nervous system
Pappalardo JL, Zhang L, Pecsok MK, Perlman K, Zografou C, Raddassi K, Abulaban A, Krishnaswamy S, Antel J, van Dijk D, Hafler DA. Transcriptomic and clonal characterization of T cells in the human central nervous system. Science Immunology 2020, 5 PMID: 32948672, PMCID: PMC8567322, DOI: 10.1126/sciimmunol.abb8786.Peer-Reviewed Original ResearchConceptsCentral nervous systemCSF of patientsT cellsCerebrospinal fluidMultiple sclerosisImmune surveillanceNervous systemCSF T cellsHuman central nervous systemHealthy human donorsT cell activationImmune dysfunctionNeuroinflammatory diseasesCytotoxic capacityHealthy donorsHealthy individualsCell activationHuman donorsTissue adaptationPatientsClonal characterizationExpression of genesCellsSurveillanceFurther characterization
2019
Exploring single-cell data with deep multitasking neural networks
Amodio M, van Dijk D, Srinivasan K, Chen WS, Mohsen H, Moon KR, Campbell A, Zhao Y, Wang X, Venkataswamy M, Desai A, Ravi V, Kumar P, Montgomery R, Wolf G, Krishnaswamy S. Exploring single-cell data with deep multitasking neural networks. Nature Methods 2019, 16: 1139-1145. PMID: 31591579, PMCID: PMC10164410, DOI: 10.1038/s41592-019-0576-7.Peer-Reviewed Original Research
2016
PD-1 marks dysfunctional regulatory T cells in malignant gliomas
Lowther DE, Goods BA, Lucca LE, Lerner BA, Raddassi K, van Dijk D, Hernandez AL, Duan X, Gunel M, Coric V, Krishnaswamy S, Love JC, Hafler DA. PD-1 marks dysfunctional regulatory T cells in malignant gliomas. JCI Insight 2016, 1: e85935. PMID: 27182555, PMCID: PMC4864991, DOI: 10.1172/jci.insight.85935.Peer-Reviewed Original ResearchTumor-infiltrating TregsPD-1IFN-γ productionGlioblastoma multiformeT cellsImmune responseHealthy subjectsDysfunctional regulatory T cellsHigh PD-1 expressionCell death protein 1PD-1-blocking antibodiesPD-1 expressionEffector T cellsRegulatory T cellsDeath protein 1Antitumoral immune responseImmune checkpoint receptorsProduction of IFNExhausted phenotypeExhaustion signaturesCheckpoint receptorsHuman TregsTumor infiltratesFunctional statusMalignant gliomas