Featured Publications
Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung
Schupp JC, Adams TS, Cosme C, Raredon MSB, Yuan Y, Omote N, Poli S, Chioccioli M, Rose KA, Manning EP, Sauler M, DeIuliis G, Ahangari F, Neumark N, Habermann AC, Gutierrez AJ, Bui LT, Lafyatis R, Pierce RW, Meyer KB, Nawijn MC, Teichmann SA, Banovich NE, Kropski JA, Niklason LE, Pe’er D, Yan X, Homer RJ, Rosas IO, Kaminski N. Integrated Single-Cell Atlas of Endothelial Cells of the Human Lung. Circulation 2021, 144: 286-302. PMID: 34030460, PMCID: PMC8300155, DOI: 10.1161/circulationaha.120.052318.Peer-Reviewed Original ResearchConceptsDifferential expression analysisPrimary lung endothelial cellsLung endothelial cellsCell typesMarker genesExpression analysisSingle-cell RNA sequencing dataCross-species analysisVenous endothelial cellsEndothelial marker genesSingle-cell atlasMarker gene setsRNA sequencing dataEndothelial cellsSubsequent differential expression analysisDifferent lung cell typesResident cell typesLung cell typesCellular diversityEndothelial cell typesCapillary endothelial cellsHuman lung endothelial cellsPhenotypic diversityEndothelial diversityIndistinguishable populations
2024
SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchDedifferentiated early postnatal lung myofibroblasts redifferentiate in adult disease
Chandran R, Adams T, Kabir I, Gallardo-Vara E, Kaminski N, Gomperts B, Greif D. Dedifferentiated early postnatal lung myofibroblasts redifferentiate in adult disease. Frontiers In Cell And Developmental Biology 2024, 12: 1335061. PMID: 38572485, PMCID: PMC10987733, DOI: 10.3389/fcell.2024.1335061.Peer-Reviewed Original ResearchRNA sequencing analysisSMA+ myofibroblastsGene expression profilesLung myofibroblastsAdult lungSequence analysisResponse to lung injurySingle cell RNA sequencing analysisTissue remodeling genesSmooth muscle cell markersLung to hypoxiaExpression profilesRemodeling genesMuscle cell markersResponse to injuryCell typesSMA cellsLineage tracingLung injuryCell markersLineagesGenesAdult diseaseDrug bleomycinLung surface areaFibrotic cocktail treated human precision lung slices replicate the cellular diversity of the IPF lung
Justet A, Pineda H, Adams T, Balayev A, Mitash N, Ishizuka M, Kim H, Khoury J, Cala-García J, Flint J, Schupp J, Ahangari F, Yan X, Rosas I, Kaminski N, Königshoff M. Fibrotic cocktail treated human precision lung slices replicate the cellular diversity of the IPF lung. Revue Des Maladies Respiratoires 2024, 41: 218. DOI: 10.1016/j.rmr.2024.01.074.Peer-Reviewed Original ResearchCellular repertoireCell typesSingle cell platformsSequence readsCDNA libraryIllumina platformHuman genomeNucleus transcriptomicsCellular diversityIPF lungsPulmonary fibrosisEMT markersAirway epithelial cellsBasaloid cellsCellular populationsEpithelial cellsFibrotic fibroblastsCell platformLung slicesLung cell populationsHuman precision-cut lung slicesCell populationsSenescence markersCellsBasal markers
2023
A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases
Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain L, Cho M, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLOS Genetics 2023, 19: e1010825. PMID: 37523391, PMCID: PMC10414598, DOI: 10.1371/journal.pgen.1010825.Peer-Reviewed Original ResearchConceptsCell typesDisease-associated tissuesWide association studyComplex diseasesCell type proportionsDisease-relevant tissuesReal GWAS dataFunctional genesTranscriptomic dataGWAS dataGenetic dataAssociation studiesNovel statistical frameworkChronic obstructive pulmonary diseaseStatistical frameworkObstructive pulmonary diseaseIdiopathic pulmonary fibrosisBreast cancer riskType proportionsBlood CD8Pulmonary diseasePulmonary fibrosisPredictive biomarkersLung tissueBreast cancerAn integrated cell atlas of the lung in health and disease
Sikkema L, Ramírez-Suástegui C, Strobl D, Gillett T, Zappia L, Madissoon E, Markov N, Zaragosi L, Ji Y, Ansari M, Arguel M, Apperloo L, Banchero M, Bécavin C, Berg M, Chichelnitskiy E, Chung M, Collin A, Gay A, Gote-Schniering J, Hooshiar Kashani B, Inecik K, Jain M, Kapellos T, Kole T, Leroy S, Mayr C, Oliver A, von Papen M, Peter L, Taylor C, Walzthoeni T, Xu C, Bui L, De Donno C, Dony L, Faiz A, Guo M, Gutierrez A, Heumos L, Huang N, Ibarra I, Jackson N, Kadur Lakshminarasimha Murthy P, Lotfollahi M, Tabib T, Talavera-López C, Travaglini K, Wilbrey-Clark A, Worlock K, Yoshida M, van den Berge M, Bossé Y, Desai T, Eickelberg O, Kaminski N, Krasnow M, Lafyatis R, Nikolic M, Powell J, Rajagopal J, Rojas M, Rozenblatt-Rosen O, Seibold M, Sheppard D, Shepherd D, Sin D, Timens W, Tsankov A, Whitsett J, Xu Y, Banovich N, Barbry P, Duong T, Falk C, Meyer K, Kropski J, Pe’er D, Schiller H, Tata P, Schultze J, Teichmann S, Misharin A, Nawijn M, Luecken M, Theis F. An integrated cell atlas of the lung in health and disease. Nature Medicine 2023, 29: 1563-1577. PMID: 37291214, PMCID: PMC10287567, DOI: 10.1038/s41591-023-02327-2.Peer-Reviewed Original ResearchConceptsCell atlasGene modulesCell typesCell type definitionsHuman Cell AtlasSingle-cell technologiesSingle-cell datasetsUndescribed cell typeMultiple lung diseasesCell statesMarker genesMonocyte-derived macrophagesDistal axisStudy of diseasesHuman tissuesAnnotationAtlasGenesSPP1DiversityExpressionTreesLimited numberCellsNew dataEmergence of division of labor in tissues through cell interactions and spatial cues
Adler M, Moriel N, Goeva A, Avraham-Davidi I, Mages S, Adams T, Kaminski N, Macosko E, Regev A, Medzhitov R, Nitzan M. Emergence of division of labor in tissues through cell interactions and spatial cues. Cell Reports 2023, 42: 112412. PMID: 37086403, PMCID: PMC10242439, DOI: 10.1016/j.celrep.2023.112412.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingMost cell typesCell-type populationsCell-cell interactionsDistinguishable expression patternsCell population levelSpatial transcriptomics dataCell interactionsLigand-receptor networkMulticellular organismsTranscriptomic dataRNA sequencingInstructive signalsExpression patternsSpecialist cellsCell typesIndividual cellsDivision of laborMultiple functionsTissue environmentSame cellsDifferent functionsPopulation levelCellsDivision
2022
Single-cell RNA-seq uncovers cellular heterogeneity and provides a signature for paediatric sleep apnoea.
Cortese R, Adams T, Cataldo K, Hummel J, Kaminski N, Kheirandish-Gozal L, Gozal D. Single-cell RNA-seq uncovers cellular heterogeneity and provides a signature for paediatric sleep apnoea. European Respiratory Journal 2022, 61: 2201465. PMID: 36356973, DOI: 10.1183/13993003.01465-2022.Peer-Reviewed Original ResearchConceptsObstructive sleep apnoeaSleep apnoeaImpact of OSASystemic immune functionMononuclear cell compositionMolecular signaturesCell-specific markersSystemic inflammationCardiovascular dysfunctionImmune cellsImmune functionSingle-cell transcriptomic analysisPaediatric sleep apnoeaUndescribed cell typePrevalent diseaseMajor causeCellular compositionApnoeaCell compositionRNA expression datasetsDiagnostic settingCell typesCell lineagesMolecular diagnostic settingScRNA-seqLung Cell Atlases in Health and Disease
Adams T, Marlier A, Kaminski N. Lung Cell Atlases in Health and Disease. Annual Review Of Physiology 2022, 85: 47-69. PMID: 36351366, DOI: 10.1146/annurev-physiol-032922-082826.Peer-Reviewed Original ResearchConceptsCell atlasesSingle-cell profiling technologiesLung biologyProfiling technologiesCell typesCellular morphologyProgressive lung diseaseCellular measurementsHuman lung biologyGas exchangeLung diseaseComplex branching structuresRecent advancesDiseaseIndividual markersBiologyBranching structureUnprecedented levelHealthStructural changesCINS: Cell Interaction Network inference from Single cell expression data
Yuan Y, Cosme C, Adams TS, Schupp J, Sakamoto K, Xylourgidis N, Ruffalo M, Li J, Kaminski N, Bar-Joseph Z. CINS: Cell Interaction Network inference from Single cell expression data. PLOS Computational Biology 2022, 18: e1010468. PMID: 36095011, PMCID: PMC9499239, DOI: 10.1371/journal.pcbi.1010468.Peer-Reviewed Original ResearchConceptsCell type interactionsSingle-cell expression dataSingle-cell RNA-seq dataRNA-seq dataScRNA-seq experimentsCell-cell interactionsExpression dataCell typesMouse datasetsNetwork inferenceCell interactionsInteraction predictionNetwork analysisInference pipelineGenesCINSProteinInteractionBayesian network analysisMicroenvironmental sensing by fibroblasts controls macrophage population size
Zhou X, Franklin RA, Adler M, Carter TS, Condiff E, Adams TS, Pope SD, Philip NH, Meizlish ML, Kaminski N, Medzhitov R. Microenvironmental sensing by fibroblasts controls macrophage population size. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2205360119. PMID: 35930670, PMCID: PMC9371703, DOI: 10.1073/pnas.2205360119.Peer-Reviewed Original ResearchConceptsCell typesDensity-dependent gene expressionTGF-β target genesDiverse cell typesActin-dependent mechanismLineage-specific growth factorsDistinct cell typesGrowth factor availabilityActivation of YAP1Different cell typesExpression programsMicroenvironmental sensingTranscriptional coactivatorTarget genesGene expressionPopulation sizeFactor availabilityPopulation numbersTissue environmentTissue integrityHippoProliferation of macrophagesYAP1Animal tissuesMechanical forcesBronchial epithelium epithelial-mesenchymal plasticity forms aberrant basaloid-like cells in vitro
Uthaya Kumar DB, Motakis E, Yurieva M, Kohar V, Martinek J, Wu TC, Khoury J, Grassmann J, Lu M, Palucka K, Kaminski N, Koff JL, Williams A. Bronchial epithelium epithelial-mesenchymal plasticity forms aberrant basaloid-like cells in vitro. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2022, 322: l822-l841. PMID: 35438006, PMCID: PMC9142163, DOI: 10.1152/ajplung.00254.2021.Peer-Reviewed Original ResearchConceptsProtein codingEpithelial-mesenchymal transitionLncRNA genesEMT inductionSingle-cell RNA sequencingSingle-cell RNA-seq dataEpithelial-mesenchymal plasticityRNA-seq dataMechanisms of EMTSingle-cell levelEpithelial cell typesRole of EMTTranscriptional reprogrammingHuman bronchial epithelial cellsRNA genesEMT gene signatureTranscriptional changesTranscriptional differencesRNA sequencingSpecific lncRNAsBronchial epithelial cellsDifferential expressionMyofibroblast conversionCell typesGenes
2021
Distinct roles of KLF4 in mesenchymal cell subtypes during lung fibrogenesis
Chandran RR, Xie Y, Gallardo-Vara E, Adams T, Garcia-Milian R, Kabir I, Sheikh AQ, Kaminski N, Martin KA, Herzog EL, Greif DM. Distinct roles of KLF4 in mesenchymal cell subtypes during lung fibrogenesis. Nature Communications 2021, 12: 7179. PMID: 34893592, PMCID: PMC8664937, DOI: 10.1038/s41467-021-27499-8.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell ProliferationDisease Models, AnimalDown-RegulationExtracellular MatrixFemaleFibroblastsFibrosisHumansKruppel-Like Factor 4LungLung InjuryMaleMesenchymal Stem CellsMiceMice, Inbred C57BLMyofibroblastsReceptor, Platelet-Derived Growth Factor betaRespiratory Tract DiseasesSignal TransductionTransforming Growth Factor betaConceptsMesenchymal cell typesPlatelet-derived growth factor receptorSmooth muscle actinLung fibrosisKruppel-like factor 4Forkhead box M1Growth factor receptorCell transitionCell typesExtracellular matrixDistinct rolesKLF4Box M1C chemokine ligandMesenchymal cell subtypesFactor receptorPro-fibrotic effectsFactor 4PDGFRMesenchymeCellsMacrophage accumulationKLF4 levelsChemokine ligandLung fibrogenesisA Markov random field model for network-based differential expression analysis of single-cell RNA-seq data
Li H, Zhu B, Xu Z, Adams T, Kaminski N, Zhao H. A Markov random field model for network-based differential expression analysis of single-cell RNA-seq data. BMC Bioinformatics 2021, 22: 524. PMID: 34702190, PMCID: PMC8549347, DOI: 10.1186/s12859-021-04412-0.Peer-Reviewed Original ResearchConceptsMarkov random field modelRandom field modelMean field-like approximationField modelSpecific DEGsExpectation maximizationSingle-cell sequencing technologiesProtein-coding genesRNA sequencing data setsSingle-cell RNA-seq dataCell-type levelCell typesGibbs samplerSingle-cell RNA sequencing data setsCell-cell networksDifferential expression analysisRNA-seq dataGene network informationStatistical powerType I error ratesDifferent expression levelsMRF modelI error rateModel parametersBiological networks
2019
Single-cell connectomic analysis of adult mammalian lungs
Raredon MSB, Adams TS, Suhail Y, Schupp JC, Poli S, Neumark N, Leiby KL, Greaney AM, Yuan Y, Horien C, Linderman G, Engler AJ, Boffa DJ, Kluger Y, Rosas IO, Levchenko A, Kaminski N, Niklason LE. Single-cell connectomic analysis of adult mammalian lungs. Science Advances 2019, 5: eaaw3851. PMID: 31840053, PMCID: PMC6892628, DOI: 10.1126/sciadv.aaw3851.Peer-Reviewed Original ResearchConceptsTissue homeostasisMammalian lungSingle-cell RNA sequencing techniquesAdult mammalian lungRNA sequencing techniquesCell-cell interactionsSequencing techniquesKey pathwaysAlveolar type IFunctional roleCell typesCell populationsRegenerative medicineHomeostatic mechanismsHomeostasisFine architectureFunctional lung tissueIncomplete understandingMajor roleType ITissueRegulationPathwayAlveolar cell populationsDistal lungIntegrating 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 understandingProteomicsMethylationThe Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease
Schiller HB, Montoro DT, Simon LM, Rawlins EL, Meyer KB, Strunz M, Braga F, Timens W, Koppelman GH, Budinger GRS, Burgess JK, Waghray A, van den Berge M, Theis F, Regev A, Kaminski N, Rajagopal J, Teichmann S, Misharin A, Nawijn M. The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease. American Journal Of Respiratory Cell And Molecular Biology 2019, 61: 31-41. PMID: 30995076, PMCID: PMC6604220, DOI: 10.1165/rcmb.2018-0416tr.Peer-Reviewed Original ResearchConceptsCell atlasHuman Cell Atlas consortiumCell typesCell-cell interactionsHigh-throughput techniquesFunction of geneticsLung cell typesTranscriptomic analysisDevelopmental processesIndividual cellsMolecular descriptionReference mapTissue microenvironmentDisease mechanismsCellular neighborhoodsHealthy human bodyMolecular profilePersonalized therapeutic regimensCellsLung diseaseTherapeutic regimensImmune cellsLung tissueRecent progressTissue matrixAlveolar and Fibroblast Foci Specific Genome-Wide Gene Expression Profiling Identifies Common Dysregulated Expression of CREB1, a Regulator Across Cell Types, in IPF
Vukmirovic M, Brereton C, Yan X, Xylourgidis N, Deluliis G, Woolard T, Hu B, Mihaljinec A, Homer R, Maya J, Ahangari F, Fabre A, Smart D, Conforti F, Marshall B, Alzetani A, Davies D, Richeldi L, Kaminski N, Jones M. Alveolar and Fibroblast Foci Specific Genome-Wide Gene Expression Profiling Identifies Common Dysregulated Expression of CREB1, a Regulator Across Cell Types, in IPF. 2019, a5262-a5262. DOI: 10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a5262.Peer-Reviewed Original ResearchIncreased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study
Scott MKD, Quinn K, Li Q, Carroll R, Warsinske H, Vallania F, Chen S, Carns MA, Aren K, Sun J, Koloms K, Lee J, Baral J, Kropski J, Zhao H, Herzog E, Martinez FJ, Moore BB, Hinchcliff M, Denny J, Kaminski N, Herazo-Maya JD, Shah NH, Khatri P. Increased monocyte count as a cellular biomarker for poor outcomes in fibrotic diseases: a retrospective, multicentre cohort study. The Lancet Respiratory Medicine 2019, 7: 497-508. PMID: 30935881, PMCID: PMC6529612, DOI: 10.1016/s2213-2600(18)30508-3.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisPulmonary fibrosisAbsolute monocyte countMonocyte countImmune cell typesElectronic health recordsPoor outcomeHigh riskSystemic sclerosisMonocyte percentageHypertrophic cardiomyopathyHigh absolute monocyte countPeripheral blood mononuclear cell samplesComplete blood count valuesSpecific immune cell typesTransplant-free survivalMulticentre cohort studyHealth recordsHigh-risk patientsBlood count valuesSame clinical presentationHigher monocyte countMononuclear cell samplesRisk of mortalityCell types
2018
Reconstructing differentiation networks and their regulation from time series single-cell expression data
Ding J, Aronow BJ, Kaminski N, Kitzmiller J, Whitsett JA, Bar-Joseph Z. Reconstructing differentiation networks and their regulation from time series single-cell expression data. Genome Research 2018, 28: 383-395. PMID: 29317474, PMCID: PMC5848617, DOI: 10.1101/gr.225979.117.Peer-Reviewed Original ResearchTranscription factorsSingle-cell expression dataSingle-cell RNA-seq dataRNA-seq dataDiverse cell populationsGene expression levelsDifferent cell typesStages of organogenesisCell fateDescendant cellsDifferentiation networkExpression similarityKey regulatorRegulatory informationExpression dataCell typesProgenitor cellsCell trajectoriesExpression levelsCell populationsDevelopmental dataCellsLineagesOrganogenesisRegulator