2023
When Development of the Alveolar Gas Exchange Unit Fails: Universal Single-Cell Lessons from Rare Monogenic Disorders
Schupp J, Kaminski N. When Development of the Alveolar Gas Exchange Unit Fails: Universal Single-Cell Lessons from Rare Monogenic Disorders. American Journal Of Respiratory And Critical Care Medicine 2023, 208: 652-654. PMID: 37555730, PMCID: PMC10515565, DOI: 10.1164/rccm.202307-1271ed.Commentaries, Editorials and Letters
2022
Type I interferon transcriptional network regulates expression of coinhibitory receptors in human T cells
Sumida TS, Dulberg S, Schupp JC, Lincoln MR, Stillwell HA, Axisa PP, Comi M, Unterman A, Kaminski N, Madi A, Kuchroo VK, Hafler DA. Type I interferon transcriptional network regulates expression of coinhibitory receptors in human T cells. Nature Immunology 2022, 23: 632-642. PMID: 35301508, PMCID: PMC8989655, DOI: 10.1038/s41590-022-01152-y.Peer-Reviewed Original ResearchMeSH KeywordsCOVID-19Gene Regulatory NetworksHumansInterferon Type IReceptors, Antigen, T-CellReceptors, ImmunologicSARS-CoV-2T-LymphocytesConceptsCoinhibitory receptor expressionHuman T cellsIFN-I responsesCoinhibitory receptorsT cellsTIGIT expressionReceptor expressionAcute SARS-CoV-2 infectionPD-1/TimSARS-CoV-2 infectionEnhancement of immunotherapyType 1 interferonT-cell featuresLAG-3Infectious diseasesDifferent temporal kineticsTranscription factorsCancer therapyReceptorsCell featuresKey transcription factorIFNPresent studyMRNA profilingKey regulatorCharacterization of the COPD alveolar niche using single-cell RNA sequencing
Sauler M, McDonough JE, Adams TS, Kothapalli N, Barnthaler T, Werder RB, Schupp JC, Nouws J, Robertson MJ, Coarfa C, Yang T, Chioccioli M, Omote N, Cosme C, Poli S, Ayaub EA, Chu SG, Jensen KH, Gomez JL, Britto CJ, Raredon MSB, Niklason LE, Wilson AA, Timshel PN, Kaminski N, Rosas IO. Characterization of the COPD alveolar niche using single-cell RNA sequencing. Nature Communications 2022, 13: 494. PMID: 35078977, PMCID: PMC8789871, DOI: 10.1038/s41467-022-28062-9.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingRNA sequencingCell-specific mechanismsChronic obstructive pulmonary diseaseAdvanced chronic obstructive pulmonary diseaseTranscriptomic network analysisSingle-cell RNA sequencing profilesCellular stress toleranceAberrant cellular metabolismStress toleranceRNA sequencing profilesTranscriptional evidenceCellular metabolismAlveolar nicheSequencing profilesHuman alveolar epithelial cellsChemokine signalingAlveolar epithelial type II cellsObstructive pulmonary diseaseSitu hybridizationType II cellsEpithelial type II cellsSequencingCOPD pathobiologyHuman lung tissue samples
2021
A 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 ResearchMeSH KeywordsAlgorithmsGene Expression ProfilingGene Regulatory NetworksHumansRNA-SeqSequence Analysis, RNASingle-Cell AnalysisConceptsMarkov 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
2020
Gene coexpression networks reveal novel molecular endotypes in alpha-1 antitrypsin deficiency
Chu JH, Zang W, Vukmirovic M, Yan X, Adams T, DeIuliis G, Hu B, Mihaljinec A, Schupp JC, Becich MJ, Hochheiser H, Gibson KF, Chen ES, Morris A, Leader JK, Wisniewski SR, Zhang Y, Sciurba FC, Collman RG, Sandhaus R, Herzog EL, Patterson KC, Sauler M, Strange C, Kaminski N. Gene coexpression networks reveal novel molecular endotypes in alpha-1 antitrypsin deficiency. Thorax 2020, 76: 134-143. PMID: 33303696, PMCID: PMC10794043, DOI: 10.1136/thoraxjnl-2019-214301.Peer-Reviewed Original ResearchConceptsWeighted gene co-expression network analysisAlpha-1 antitrypsin deficiencyGene modulesGene co-expression network analysisDifferential gene expression analysisCo-expression network analysisPeripheral blood mononuclear cellsGene expression patternsPBMC gene expression patternsGene coexpression networksAATD individualsGene expression profilesGene expression analysisBronchoalveolar lavageAugmentation therapyClinical variablesAntitrypsin deficiencyGene expression assaysRNA-seqCoexpression networkGene validationExpression analysisExpression assaysWGCNA modulesExpression patterns
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
2018
Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis
McDonough JE, Kaminski N, Thienpont B, Hogg JC, Vanaudenaerde BM, Wuyts WA. Gene correlation network analysis to identify regulatory factors in idiopathic pulmonary fibrosis. Thorax 2018, 74: 132. PMID: 30366970, PMCID: PMC6467239, DOI: 10.1136/thoraxjnl-2018-211929.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisLung functionPulmonary fibrosisExtensive pathological changesSevere lung diseaseLung Tissue Research ConsortiumCorrelation network analysisIPF cohortIPF groupLung diseaseControl subjectsUpregulated modulesT cellsImmune responsePathological changesLeucocyte activationB cellsClinical relevanceSurfactant metabolismDisease pathologyInterferon responseFibrosisBlood vesselsPathological processesGene correlation network analysisFibrosis: Lessons from OMICS analyses of the human lung
Yu G, Ibarra GH, Kaminski N. Fibrosis: Lessons from OMICS analyses of the human lung. Matrix Biology 2018, 68: 422-434. PMID: 29567123, PMCID: PMC6015529, DOI: 10.1016/j.matbio.2018.03.014.Peer-Reviewed Original ResearchConceptsIdiopathic pulmonary fibrosisDramatic phenotypic alterationsTranscriptomic studiesOmics analysisOmics profilingOmics technologiesPulmonary fibrosisNumerous aberrationsPhenotypic alterationsMechanistic understandingHuman idiopathic pulmonary fibrosisIPF lung tissueEpithelial cellsCentral roleHuman tissuesIPF samplesNew insightsMolecular featuresIPF lungsInflammatory cellsPatient cohortLung tissueAnimal modelsLethal disorderHuman lungiDREM: Interactive visualization of dynamic regulatory networks
Ding J, Hagood JS, Ambalavanan N, Kaminski N, Bar-Joseph Z. iDREM: Interactive visualization of dynamic regulatory networks. PLOS Computational Biology 2018, 14: e1006019. PMID: 29538379, PMCID: PMC5868853, DOI: 10.1371/journal.pcbi.1006019.Peer-Reviewed Original ResearchConceptsDynamic regulatory networksRegulatory networksHigh-throughput time series dataInteraction dataProtein-DNA interaction dataSingle-cell RNA-seqTime series gene expression dataStatic datasetsInteractive visualizationGene expression dataData typesRNA-seqTime series dataBiological processesExpression dataMiRNA expressionNetworkSeries dataImportant challengeNew versionDevelopmental dataNovel hypothesisUnified modelMultiple labsRecent years
2017
LungMAP: The Molecular Atlas of Lung Development Program
Ardini-Poleske ME, Clark RF, Ansong C, Carson JP, Corley RA, Deutsch GH, Hagood JS, Kaminski N, Mariani TJ, Potter SS, Pryhuber GS, Warburton D, Whitsett JA, Palmer SM, Ambalavanan N, . LungMAP: The Molecular Atlas of Lung Development Program. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2017, 313: l733-l740. PMID: 28798251, PMCID: PMC5792185, DOI: 10.1152/ajplung.00139.2017.Peer-Reviewed Original ResearchModified mesenchymal stem cells using miRNA transduction alter lung injury in a bleomycin model
Huleihel L, Sellares J, Cardenes N, Álvarez D, Faner R, Sakamoto K, Yu G, Kapetanaki MG, Kaminski N, Rojas M. Modified mesenchymal stem cells using miRNA transduction alter lung injury in a bleomycin model. American Journal Of Physiology - Lung Cellular And Molecular Physiology 2017, 313: l92-l103. PMID: 28385811, PMCID: PMC5538868, DOI: 10.1152/ajplung.00323.2016.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBiomarkersBleomycinBone Marrow CellsCollagenCytokinesDisease Models, AnimalFemaleGene Expression RegulationGene Regulatory NetworksHumansInterleukin-6Leukocyte Common AntigensLung InjuryMesenchymal Stem Cell TransplantationMesenchymal Stem CellsMice, Inbred C57BLMicroRNAsRNA, MessengerSurvival AnalysisTransduction, GeneticTransfectionWeight LossConceptsBone marrow-derived mesenchymal stem cellsMesenchymal stem cellsLung fibrosisLate administrationBleomycin modelMiR-154Different preclinical modelsStem cellsCD45-positive cellsMurine bleomycin modelMarrow-derived mesenchymal stem cellsInitial weight lossLower survival rateAshcroft scoreLung injuryBleomycin instillationFibrotic changesCytokine expressionMice groupsLung tissueOH-prolinePreclinical modelsProtective effectTreatment groupsSurvival rateIdentification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis
Vukmirovic M, Herazo-Maya JD, Blackmon J, Skodric-Trifunovic V, Jovanovic D, Pavlovic S, Stojsic J, Zeljkovic V, Yan X, Homer R, Stefanovic B, Kaminski N. Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis. BMC Pulmonary Medicine 2017, 17: 15. PMID: 28081703, PMCID: PMC5228096, DOI: 10.1186/s12890-016-0356-4.Peer-Reviewed Original ResearchConceptsPaired-end sequencingTranscript profilingHuman genomeRNA sequencingTranscriptomic profilingFFPE lung tissuesSequencing readsLung tissueTotal RNABackgroundIdiopathic pulmonary fibrosisLethal lung diseaseSequencingReadsProfilingPulmonary fibrosisLung diseaseUnknown etiologyIPF tissueGenomeHiSeqTissueTopHat2GenesIPFRNA
2016
Integrated Genomics Reveals Convergent Transcriptomic Networks Underlying Chronic Obstructive Pulmonary Disease and Idiopathic Pulmonary Fibrosis
Kusko RL, Brothers JF, Tedrow J, Pandit K, Huleihel L, Perdomo C, Liu G, Juan-Guardela B, Kass D, Zhang S, Lenburg M, Martinez F, Quackenbush J, Sciurba F, Limper A, Geraci M, Yang I, Schwartz DA, Beane J, Spira A, Kaminski N. Integrated Genomics Reveals Convergent Transcriptomic Networks Underlying Chronic Obstructive Pulmonary Disease and Idiopathic Pulmonary Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2016, 194: 948-960. PMID: 27104832, PMCID: PMC5067817, DOI: 10.1164/rccm.201510-2026oc.Peer-Reviewed Original ResearchMeSH KeywordsAdultEmphysemaFemaleGene Regulatory NetworksHumansHypoxia-Inducible Factor 1, alpha SubunitIdiopathic Pulmonary FibrosisI-kappa B ProteinsMaleMembrane ProteinsMiddle AgedNerve Tissue ProteinsOligonucleotide Array Sequence AnalysisPlatelet-Derived Growth FactorProto-Oncogene Proteins c-mdm2Pulmonary Disease, Chronic ObstructiveConceptsChronic obstructive pulmonary diseaseIdiopathic pulmonary fibrosisObstructive pulmonary diseasePulmonary diseasePulmonary fibrosisNCounter Analysis SystemHypoxia pathwayQuantitative polymerase chain reactionTranscriptomic pathwaysPolymerase chain reactionIndependent cohortEmphysemaIndependent sample setDiseaseGene expression arraysEnvironmental exposuresChain reactionFibrosisLungMolecular mechanismsExpression arraysMiR96Integrative genomics approachTranscriptional regulatory hubsPathway
2013
Reconstructing dynamic microRNA-regulated interaction networks
Schulz MH, Pandit KV, Cardenas C, Ambalavanan N, Kaminski N, Bar-Joseph Z. Reconstructing dynamic microRNA-regulated interaction networks. Proceedings Of The National Academy Of Sciences Of The United States Of America 2013, 110: 15686-15691. PMID: 23986498, PMCID: PMC3785769, DOI: 10.1073/pnas.1303236110.Peer-Reviewed Original ResearchConceptsTranscription factorsGene expressionDynamic Regulatory Events MinerTemporal gene expressionDynamic regulatory networksSpecific developmental phasesMRNA expression dataLung developmentRegulatory networksMiRNA targetsInteraction networksImportant miRNAsExpression dataMiRNAsAdditional miRNAsLung differentiationDevelopmental phasesMiRNAPostnatal lung developmentProgression pathwaysProliferation assaysExpressionRegulationMRNA expressionMicroRNAs
2012
Toward Systems Biology of Pulmonary Hypertension
Ahmad F, Champion HC, Kaminski N. Toward Systems Biology of Pulmonary Hypertension. Circulation 2012, 125: 1477-1479. PMID: 22371329, PMCID: PMC5115209, DOI: 10.1161/circulationaha.112.096396.Peer-Reviewed Original ResearchAnimalsComputational BiologyGene Regulatory NetworksHumansHypertension, PulmonaryMicroRNAsSignal Transduction
2009
FACS-Assisted Microarray Profiling Implicates Novel Genes and Pathways in Zebrafish Gastrointestinal Tract Development
Stuckenholz C, Lu L, Thakur P, Kaminski N, Bahary N. FACS-Assisted Microarray Profiling Implicates Novel Genes and Pathways in Zebrafish Gastrointestinal Tract Development. Gastroenterology 2009, 137: 1321-1332. PMID: 19563808, PMCID: PMC2785077, DOI: 10.1053/j.gastro.2009.06.050.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAnimals, Genetically ModifiedCell SeparationChromosomes, Human, Pair 8Digestive System NeoplasmsFlow CytometryGastrointestinal TractGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Expression Regulation, NeoplasticGene Regulatory NetworksGreen Fluorescent ProteinsHumansIn Situ HybridizationLarvaMicroRNAsOligonucleotide Array Sequence AnalysisOrganogenesisReproducibility of ResultsTime FactorsZebrafishZebrafish ProteinsConceptsFluorescence-activated cell sortingNovel genesGreen fluorescent proteinGene networksPutative transcription factorTransgenic zebrafish lineZebrafish Danio rerioPhosphatidylinositol-3-kinase (PI3K) pathwayExcellent model systemDevelopmental time pointsChromosome arm 8qGastrointestinal developmentZebrafish lineHuman orthologDanio rerioTranscription factorsKinase pathwayMicroarray profilingFluorescent proteinGFP expressionGenesNovel pathwayGFP cellsCell sortingOrganogenesis
2008
Network analysis of temporal effects of intermittent and sustained hypoxia on rat lungs
Wu W, Dave NB, Yu G, Strollo PJ, Kovkarova-Naumovski E, Ryter SW, Reeves SR, Dayyat E, Wang Y, Choi AM, Gozal D, Kaminski N. Network analysis of temporal effects of intermittent and sustained hypoxia on rat lungs. Physiological Genomics 2008, 36: 24-34. PMID: 18826996, PMCID: PMC2604785, DOI: 10.1152/physiolgenomics.00258.2007.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsEstrogen Receptor alphaGene Expression ProfilingGene Regulatory NetworksHypoxiaLungMaleMicroarray AnalysisRatsRats, Sprague-DawleyConceptsSystems biology approachEstrogen receptor 1Lung responseQuantitative real-time PCRRat lungBiology approachIntermittent hypoxiaExpression patternsSustained hypoxiaReal-time PCRDistinct gene expression patternsDifferent temporal expression patternsDownstream physiological effectsGene expression patternsTemporal expression patternsSteroid hormone receptor activityGene expression profilesTemporal expression changesRegulatory networksHormone receptor activityPulmonary hypertensionKey proteinsGene expressionMolecular networksExpression changes