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
2021
Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity
Bui LT, Winters NI, Chung MI, Joseph C, Gutierrez AJ, Habermann AC, Adams TS, Schupp JC, Poli S, Peter LM, Taylor CJ, Blackburn JB, Richmond BW, Nicholson AG, Rassl D, Wallace WA, Rosas IO, Jenkins RG, Kaminski N, Kropski JA, Banovich NE. Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity. Nature Communications 2021, 12: 4314. PMID: 34262047, PMCID: PMC8280215, DOI: 10.1038/s41467-021-24467-0.Peer-Reviewed Original ResearchConceptsChronic lung diseaseLung diseaseImmune responseSARS-CoV-2 entry factorsSevere coronavirus disease-19SARS-CoV-2 infectionWorse COVID-19 outcomesSARS-CoV-2 entryAdaptive immune responsesCoronavirus disease-19COVID-19 outcomesInnate immune responseInflammatory gene expression programSimilar cellular distributionPoor outcomePeripheral lungViral exposureDisease-19Inflammatory microenvironmentEntry factorsLung epitheliumLung cellsViral replicationAT2 cellsBasal differences
2019
Integrating multiomics longitudinal data to reconstruct networks underlying lung development
Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N. Integrating multiomics longitudinal data to reconstruct networks underlying lung development. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2019, 317: l556-l568. PMID: 31432713, PMCID: PMC6879899, DOI: 10.1152/ajplung.00554.2018.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAnimals, NewbornChildChild, PreschoolDNA MethylationEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Regulatory NetworksHigh-Throughput Nucleotide SequencingHumansImmunity, InnateInfantInfant, NewbornLungMaleMiceMice, Inbred C57BLMicroRNAsOrganogenesisProteomicsPulmonary AlveoliRNA, MessengerSingle-Cell AnalysisTranscriptomeConceptsSingle-cell RNA-seq dataLung developmentDynamic regulatory networksOmics data setsRNA-seq dataIndividual cell typesHuman lung developmentRegulatory networksDNA methylationLaser capture microdissectionEpigenetic changesExpression trajectoriesKey pathwaysCell typesActive pathwaysCapture microdissectionRegulatorKey eventsInnate immunityNew insightsSpecific key eventsPathwayComprehensive understandingProteomicsMethylation
2017
Microbes Are Associated with Host Innate Immune Response in Idiopathic Pulmonary Fibrosis
Huang Y, Ma SF, Espindola MS, Vij R, Oldham JM, Huffnagle GB, Erb-Downward JR, Flaherty KR, Moore BB, White ES, Zhou T, Li J, Lussier YA, Han MK, Kaminski N, Garcia JG, Hogaboam CM, Martinez FJ, Noth I. Microbes Are Associated with Host Innate Immune Response in Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2017, 196: 208-219. PMID: 28157391, PMCID: PMC5519968, DOI: 10.1164/rccm.201607-1525oc.Peer-Reviewed Original ResearchConceptsProgression-free survivalMicrobial diversityRegulated signaling pathwaysNOD-like receptor signalingRNA sequencing dataGene expression dataMicroarray gene expression dataImmune response pathwaysMicrobial interactionsMicrobial communitiesHost innate immune responseResponse pathwaysLung microbial communityLeukocyte phenotypeImmune responseSequencing dataNetwork analysisShannon indexSignaling pathwaysToll-like receptor 9 stimulationExpression associationsExpression dataIndividual generaIdiopathic pulmonary fibrosis progressionOligomerization domain
2007
A Functional and Regulatory Map of Asthma
Novershtern N, Itzhaki Z, Manor O, Friedman N, Kaminski N. A Functional and Regulatory Map of Asthma. American Journal Of Respiratory Cell And Molecular Biology 2007, 38: 324-336. PMID: 17921359, PMCID: PMC2258452, DOI: 10.1165/rcmb.2007-0151oc.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAllergensAnimalsAsthmaDisease Models, AnimalGene Expression ProfilingHumansHypersensitivityImmunity, InnateInterleukin-13MiceMice, Inbred AMice, Inbred BALB CMice, Inbred C3HMice, KnockoutModels, BiologicalOligonucleotide Array Sequence AnalysisOvalbuminProtein Interaction MappingReproducibility of ResultsSystems BiologyTranscription, GeneticTransforming Growth Factor beta1ConceptsCo-regulated gene modulesGene expression compendiumProtein interaction networksModule network analysisMouse microarray datasetsSystems-level viewExpression compendiumRegulatory mapGene modulesModule membersFunctional themesInteraction networksKey regulatorAnimal modelsMicroarray datasetsGeneral inductionAnnotation setsChronic inflammatory airway diseasesMorbidity of asthmaInflammatory airway diseasesMechanisms of asthmaAdaptive immune responsesSystem-level approachSimilar roleDistinct responsesGenomics and proteomics of lung disease: conference summary
Raj JU, Aliferis C, Caprioli RM, Cowley AW, Davies PF, Duncan MW, Erle DJ, Erzurum SC, Finn PW, Ischiropoulos H, Kaminski N, Kleeberger SR, Leikauf GD, Loyd JE, Martin TR, Matalon S, Moore JH, Quackenbush J, Sabo-Attwood T, Shapiro SD, Schnitzer JE, Schwartz DA, Schwiebert LM, Sheppard D, Ware LB, Weiss ST, Whitsett JA, Wurfel MM, Matthay MA. Genomics and proteomics of lung disease: conference summary. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2007, 293: l45-l51. PMID: 17468134, PMCID: PMC4212816, DOI: 10.1152/ajplung.00139.2007.Peer-Reviewed Original Research