2022
Inflammasome activation in infected macrophages drives COVID-19 pathology
Sefik E, Qu R, Junqueira C, Kaffe E, Mirza H, Zhao J, Brewer JR, Han A, Steach HR, Israelow B, Blackburn HN, Velazquez SE, Chen YG, Halene S, Iwasaki A, Meffre E, Nussenzweig M, Lieberman J, Wilen CB, Kluger Y, Flavell RA. Inflammasome activation in infected macrophages drives COVID-19 pathology. Nature 2022, 606: 585-593. PMID: 35483404, PMCID: PMC9288243, DOI: 10.1038/s41586-022-04802-1.Peer-Reviewed Original ResearchConceptsInflammasome activationLung inflammationInflammatory responseInfected macrophagesSARS-CoV-2 infectionHuman macrophagesChronic lung pathologyPersistent lung inflammationSevere COVID-19Immune inflammatory responseInflammatory cytokine productionHumanized mouse modelNLRP3 inflammasome pathwayCOVID-19 pathologyCOVID-19SARS-CoV-2Productive viral cycleHyperinflammatory stateChronic stageIL-18Cytokine productionInflammatory cytokinesLung pathologyInflammasome pathwayInterleukin-1
2021
A humanized mouse model of chronic COVID-19
Sefik E, Israelow B, Mirza H, Zhao J, Qu R, Kaffe E, Song E, Halene S, Meffre E, Kluger Y, Nussenzweig M, Wilen CB, Iwasaki A, Flavell RA. A humanized mouse model of chronic COVID-19. Nature Biotechnology 2021, 40: 906-920. PMID: 34921308, PMCID: PMC9203605, DOI: 10.1038/s41587-021-01155-4.Peer-Reviewed Original ResearchConceptsChronic COVID-19Humanized mouse modelImmune responseMouse modelAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionSyndrome coronavirus 2 infectionCOVID-19Adaptive human immune responsesInterferon-stimulated gene signaturePersistent viral RNACoronavirus 2 infectionPatient-derived antibodiesT-cell lymphopeniaHuman immune responseHyperactive immune responseCoronavirus disease 2019Inflammatory macrophage responseImmunological injuryLung pathologyCell lymphopeniaDisease 2019Severe diseaseRodent modelsInflammatory macrophagesDetection of differentially abundant cell subpopulations in scRNA-seq data
Zhao J, Jaffe A, Li H, Lindenbaum O, Sefik E, Jackson R, Cheng X, Flavell RA, Kluger Y. Detection of differentially abundant cell subpopulations in scRNA-seq data. Proceedings Of The National Academy Of Sciences Of The United States Of America 2021, 118: e2100293118. PMID: 34001664, PMCID: PMC8179149, DOI: 10.1073/pnas.2100293118.Peer-Reviewed Original ResearchMeSH KeywordsAgingB-LymphocytesBrainCell LineageCOVID-19CytokinesDatasets as TopicDendritic CellsGene Expression ProfilingGene Expression RegulationHigh-Throughput Nucleotide SequencingHumansMelanomaMonocytesPhenotypeRNA, Small CytoplasmicSARS-CoV-2Severity of Illness IndexSingle-Cell AnalysisSkin NeoplasmsT-LymphocytesTranscriptomeConceptsDA subpopulationsIll COVID-19 patientsImmune checkpoint therapyCOVID-19 patientsSingle-cell RNA sequencing analysisCheckpoint therapyBrain tissueCell subpopulationsRNA sequencing analysisTime pointsSubpopulationsDiseased individualsDistinct phenotypesOriginal studyCell typesAbundant subpopulationSequencing analysisCellsDA measuresPhenotypeImportant differencesNonrespondersPatientsTherapy