2025
Changes in the FXR-cistrome and alterations in bile acid physiology in Wilson disease
Wooton-Kee C, Yalamanchili H, Mohamed I, Hassan M, Setchell K, Rivas M, Coskun A, Putluri V, Putluri N, Jalal P, Schilsky M, Moore D. Changes in the FXR-cistrome and alterations in bile acid physiology in Wilson disease. Hepatology Communications 2025, 9: e0707. PMID: 40408300, PMCID: PMC12106221, DOI: 10.1097/hc9.0000000000000707.Peer-Reviewed Original ResearchConceptsWild-type miceFarnesoid X receptorWilson's diseaseNon-parenchymal cellsDistal intergenic regionsLiver bile acid concentrationWD patientsHealthy controlsMetabolic target genesFarnesoid X Receptor RegulationBile salt export pumpIntergenic regionFXR activationAutosomal recessive disorderBile acid homeostasisBile acid physiologyFarnesoid X receptor activationPromoter regionHomeostasis pathwaysBile acid metabolismDecreasing FXR activityTarget genesBile acid profilesMarker genesStress pathways
2024
SINGLE-CELL ANALYSIS OF SOMATIC MUTATIONS IN HUMAN LUNG REVEALS ASSOCIATION WITH TRANSCRIPTIONAL CHANGES IN AGING
De Man R, Adams T, McDonough J, Cala-Garcia J, Moss B, Yan X, Rosas I, Kaminski N. SINGLE-CELL ANALYSIS OF SOMATIC MUTATIONS IN HUMAN LUNG REVEALS ASSOCIATION WITH TRANSCRIPTIONAL CHANGES IN AGING. Innovation In Aging 2024, 8: 571-572. PMCID: PMC11690935, DOI: 10.1093/geroni/igae098.1872.Peer-Reviewed Original ResearchSomatic mutationsMutational burdenCell type annotationAlveolar type 1DNA damage response genesAnalysis of somatic mutationsSomatic mutation accumulationAccumulation of somatic mutationsCell typesUbiquitin ligase geneDamage response genesLoss of cell functionAnalyzed somatic mutationsDecreased expressionSingle-cell RNAseqLigase geneMutation accumulationTop genesSignaling GenesCell marker genesResponse genesTranscriptional changesAlveolar type 1 cellsGenesMarker genesSingle-nucleus multi-omics analyses reveal cellular and molecular innovations in the anterior cingulate cortex during primate evolution
Yuan J, Dong K, Wu H, Zeng X, Liu X, Liu Y, Dai J, Yin J, Chen Y, Guo Y, Luo W, Liu N, Sun Y, Zhang S, Su B. Single-nucleus multi-omics analyses reveal cellular and molecular innovations in the anterior cingulate cortex during primate evolution. Cell Genomics 2024, 4: 100703. PMID: 39631404, PMCID: PMC11701334, DOI: 10.1016/j.xgen.2024.100703.Peer-Reviewed Original ResearchConceptsChromatin accessibilitySingle-nucleusGene expressionTranscription factor bindingPatterns of gene expressionSingle-nucleus resolutionCell lineage originACC gene expressionPrimate evolutionMulti-omics analysisAnterior cingulate cortexFactor bindingEvolutionary roleFunctional innovationSequence changesMolecular innovationsVon Economo neuronsMolecular regulationMarker genesPublished mouse dataCell typesChromatinMolecular identityHuman originCingulate cortexCosGeneGate selects multi-functional and credible biomarkers for single-cell analysis
Liu T, Long W, Cao Z, Wang Y, He C, Zhang L, Strittmatter S, Zhao H. CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis. Briefings In Bioinformatics 2024, 26: bbae626. PMID: 39592241, PMCID: PMC11596696, DOI: 10.1093/bib/bbae626.Peer-Reviewed Original ResearchA scalable approach to topic modelling in single-cell data by approximate pseudobulk projection
Subedi S, Sumida T, Park Y. A scalable approach to topic modelling in single-cell data by approximate pseudobulk projection. Life Science Alliance 2024, 7: e202402713. PMID: 39107066, PMCID: PMC11303850, DOI: 10.26508/lsa.202402713.Peer-Reviewed Original ResearchConceptsCell type-specific marker genesSingle-cell RNA-seq data analysisRNA-seq data analysisSingle-cell data analysisTopic modelsSingle-cell dataProbabilistic topic modelPathway annotationScalable approximation methodsLow memory consumptionComputation timeCellular statesMarker genesDictionary matrixLatent representationSingle-cellMemory consumptionTopic assignmentsComputing unitsFrequency vectorSelection stepCellsData analysisScalable approachData matrixCell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data
Mah J, Dunn C. Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data. Nature Ecology & Evolution 2024, 8: 325-338. PMID: 38182680, DOI: 10.1038/s41559-023-02281-9.Peer-Reviewed Original ResearchSingle-cell datasetsCell typesSingle-cell RNA sequencing dataFundamental evolutionary questionsCell type evolutionSister cell typesGene expression dynamicsRNA sequencing dataSingle-cell dataEvolutionary relationshipsEvolutionary questionsEvolutionary historyEvolutionary biologyExpression dynamicsPhylogenetic methodsPhylogenetic charactersMarker genesPhylogenySequencing dataEye cellsCladeType evolutionSpeciesCellsNon-myelinating Schwann cells
2023
An 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 dataA Novel MIP-1-Expressing Macrophage Subtype in BAL Fluid from Healthy Volunteers.
Reyfman PA, Malsin ES, Khuder B, Joshi N, Gadhvi G, Flozak AS, Carns MA, Aren K, Goldberg IA, Kim S, Alexander M, Sporn PHS, Misharin AV, Budinger GRS, Lam AP, Hinchcliff M, Gottardi CJ, Winter DR. A Novel MIP-1-Expressing Macrophage Subtype in BAL Fluid from Healthy Volunteers. American Journal Of Respiratory Cell And Molecular Biology 2023, 68: 176-185. PMID: 36174229, PMCID: PMC9986555, DOI: 10.1165/rcmb.2021-0123oc.Peer-Reviewed Original ResearchConceptsSingle-cell genomic technologiesCell typesSet of genesSingle-cell approachesSingle-cell RNASingle-cell dataSingle-cell studiesAmbient RNAGenomic technologiesMarker genesGene expressionCellular heterogeneityCellular environmentProtein 1RNAMacrophage heterogeneityGenesValuable resourceDistinct subpopulationsMacrophage subtypesHealthy volunteersLung environmentMacrophage subpopulationsMacrophage inflammatory protein-1Inflammatory protein-1
2021
Data-Dependent Acquisition Ladder for Capillary Electrophoresis Mass Spectrometry-Based Ultrasensitive (Neuro)Proteomics
Choi S, Muñoz-LLancao P, Manzini M, Nemes P. Data-Dependent Acquisition Ladder for Capillary Electrophoresis Mass Spectrometry-Based Ultrasensitive (Neuro)Proteomics. Analytical Chemistry 2021, 93: 15964-15972. PMID: 34812615, DOI: 10.1021/acs.analchem.1c03327.Peer-Reviewed Original ResearchConceptsData-dependent acquisitionHigh-resolution mass spectrometryTraditional data-dependent acquisitionAnalytical toolbox of neuroscienceCE-ESIElectrospray ionizationUltrasensitive proteomicsDynamic exclusionMass spectrometryPeptide signalsReplicate measurementsTrace amountsNeuronal marker genesIdentification success rateAnalytical toolboxIdentified proteinsNonredundant proteinsData acquisition strategyMarker genesProtein digestibilityProteinNeurobiological importanceMolecular pathwaysCultured hippocampalIonizationLineages of embryonic stem cells show non-Markovian state transitions
Udomlumleart T, Hu S, Garg S. Lineages of embryonic stem cells show non-Markovian state transitions. IScience 2021, 24: 102879. PMID: 34401663, PMCID: PMC8353490, DOI: 10.1016/j.isci.2021.102879.Peer-Reviewed Original ResearchIntegrated 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 populationsMacroporous scaffold surface modified with biological macromolecules and piroxicam-loaded gelatin nanofibers toward meniscus cartilage repair
Abpeikar Z, Javdani M, Mirzaei S, Alizadeh A, Moradi L, Soleimannejad M, Bonakdar S, Asadpour S. Macroporous scaffold surface modified with biological macromolecules and piroxicam-loaded gelatin nanofibers toward meniscus cartilage repair. International Journal Of Biological Macromolecules 2021, 183: 1327-1345. PMID: 33932422, DOI: 10.1016/j.ijbiomac.2021.04.151.Peer-Reviewed Original ResearchConceptsAdipose-derived mesenchymal stem cellsChondrocyte marker genesRabbit adipose-derived mesenchymal stem cellsHigh expression levelsNative meniscus tissueGelatin nanofibersMarker genesSurface-modified scaffoldsGene expressionCompressive Young's modulusMesenchymal stem cellsCell migrationDAPI stainingMeniscus tissue engineeringDegradation rateSelf-healing capacityStem cellsExpression levelsCell-seeded scaffoldsMechanical testsScaffold surfaceYoung's modulusPoor self-healing capacityBiological macromoleculesViability assays
2018
Metaviz: interactive statistical and visual analysis of metagenomic data
Wagner J, Chelaru F, Kancherla J, Paulson J, Zhang A, Felix V, Mahurkar A, Elmqvist N, Bravo H. Metaviz: interactive statistical and visual analysis of metagenomic data. Nucleic Acids Research 2018, 46: gky136-. PMID: 29529268, PMCID: PMC5887897, DOI: 10.1093/nar/gky136.Peer-Reviewed Original ResearchConceptsWeb servicesInteractive exploratory data analysisMetagenomic shotgun sequencingState-of-the-artState-of-the-art analysis toolsMetagenomic samplesShotgun sequencingUser navigationMicrobial communitiesCommunity profilesData featuresData valuesDisease phenotypeMarker genesMetavizUsersData resourcesProcess dataVisual analysisAnalysis toolsHierarchical structureSignificant effortBioconductorMetagenomicsMicrobiome
2016
Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease
Wang M, Roussos P, McKenzie A, Zhou X, Kajiwara Y, Brennand K, De Luca G, Crary J, Casaccia P, Buxbaum J, Ehrlich M, Gandy S, Goate A, Katsel P, Schadt E, Haroutunian V, Zhang B. Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer’s disease. Genome Medicine 2016, 8: 104. PMID: 27799057, PMCID: PMC5088659, DOI: 10.1186/s13073-016-0355-3.Peer-Reviewed Original ResearchConceptsGene expression changesCell type-specific marker genesExpression changesSingle-cell RNA-sequencing dataCo-expressed gene modulesLarge-scale gene expressionTranscriptomic network analysisCo-expression networkRNA-sequencing dataIntegrative network analysisNervous system developmentSelective regional vulnerabilityCritical molecular pathwaysActin cytoskeletonGenomic studiesGene modulesGenomic analysisGene expression abnormalitiesMarker genesMolecular basisGene expressionNetwork analysisMolecular mechanismsAxon guidanceMolecular pathways
2015
Molecular and neuronal homology between the olfactory systems of zebrafish and mouse
Saraiva L, Ahuja G, Ivandic I, Syed A, Marioni J, Korsching S, Logan D. Molecular and neuronal homology between the olfactory systems of zebrafish and mouse. Scientific Reports 2015, 5: 11487. PMID: 26108469, PMCID: PMC4480006, DOI: 10.1038/srep11487.Peer-Reviewed Original ResearchConceptsDegree of molecular conservationYears of evolutionary divergenceVomeronasal organOlfactory mucosaOlfactory organChemosensory receptor genesOlfactory systemTranscriptome of miceDual olfactory systemEvolutionary divergenceMolecular conservationNeuronal homologRepertoire sizeRNA abundanceMolecular relationshipsCell-specific markersClasses of neuronsMolecular basisChemosensory receptorsMarker genesOrgans of rodentsAbsolute abundanceZebrafishReceptor geneVertebrates
2014
Secretion of a Truncated Osteopetrosis-associated Transmembrane Protein 1 (OSTM1) Mutant Inhibits Osteoclastogenesis through Down-regulation of the B Lymphocyte-induced Maturation Protein 1 (BLIMP1)-Nuclear Factor of Activated T Cells c1 (NFATc1) Axis*
Shin B, Yu J, Park E, Choi S, Yu J, Hwang J, Yun H, Chung Y, Hong K, Choi J, Takami M, Rho J. Secretion of a Truncated Osteopetrosis-associated Transmembrane Protein 1 (OSTM1) Mutant Inhibits Osteoclastogenesis through Down-regulation of the B Lymphocyte-induced Maturation Protein 1 (BLIMP1)-Nuclear Factor of Activated T Cells c1 (NFATc1) Axis*. Journal Of Biological Chemistry 2014, 289: 35868-35881. PMID: 25359771, PMCID: PMC4276856, DOI: 10.1074/jbc.m114.589614.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBone ResorptionCell DifferentiationCell FusionCell SurvivalCells, CulturedDown-RegulationGene ExpressionLipopolysaccharidesMaleMembrane ProteinsMice, Inbred C57BLNFATC Transcription FactorsOsteoclastsOsteoporosisPositive Regulatory Domain I-Binding Factor 1Signal TransductionTranscription FactorsConceptsSecreted formTransmembrane domainOsteopetrosis-associated transmembrane protein 1Down-regulationAutosomal recessive osteopetrosis patientsTransmembrane protein 1Marker genesCell surfaceActivated T cells c1Genetic defectsExpression of OC marker genesCell fusionFunctional roleGenetic mutationsAutosomal recessive osteopetrosisMutationsProtein 1Bone destruction in vivoGene mutationsGenesDestruction in vivoRecessive osteopetrosisOsteoclast (OCOsteopetrosis patientsOsteoclastogenic genesDevelopmental stage determines efficiency of gene transfer to muscle satellite cells by in utero delivery of adeno-associated virus vector serotype 2/9
Stitelman DH, Brazelton T, Bora A, Traas J, Merianos D, Limberis M, Davey M, Flake AW. Developmental stage determines efficiency of gene transfer to muscle satellite cells by in utero delivery of adeno-associated virus vector serotype 2/9. Molecular Therapy — Methods & Clinical Development 2014, 1: 14040. PMID: 26015979, PMCID: PMC4362369, DOI: 10.1038/mtm.2014.40.Peer-Reviewed Original ResearchSatellite cell migrationGene transferCell migrationSatellite cellsMuscle stem cellsGreen fluorescent protein marker geneProtein marker geneMuscle satellite cellsEfficient gene expressionSkeletal muscle expressionMarker genesGene expressionDevelopmental stagesDifferentiated myofibersMyofiber isolationCellular migrationEfficient gene transferSatellite cell expressionAAV-9Stem cellsConfocal microscopyCell transductionMuscle expressionUtero deliveryTransduction
2010
Robust In Vivo Transduction of Nervous System and Neural Stem Cells by Early Gestational Intra Amniotic Gene Transfer Using Lentiviral Vector
Stitelman DH, Endo M, Bora A, Muvarak N, Zoltick PW, Flake AW, Brazelton TR. Robust In Vivo Transduction of Nervous System and Neural Stem Cells by Early Gestational Intra Amniotic Gene Transfer Using Lentiviral Vector. Molecular Therapy 2010, 18: 1615-1623. PMID: 20571539, PMCID: PMC2956924, DOI: 10.1038/mt.2010.125.Peer-Reviewed Original ResearchConceptsNeural stem cellsAdult neural stem cellsCell typesGene transferStem cellsGreen fluorescent protein marker geneProtein marker geneNervous system developmentNeural cell typesMajor neural cell typesLentiviral vectorsNeural cell populationsMajor cell typesAdult nervous systemGene functionMarker genesEmbryonic day 8Subventricular zoneEntire nervous systemNervous systemVivo transductionCell populationsFuture clinical applicationsGenetic disordersNeural groove
2008
Molecular Staging of Epithelial Maturation Using Secretory Cell–Specific Genes as Markers
Zemke AC, Snyder JC, Brockway BL, Drake JA, Reynolds SD, Kaminski N, Stripp BR. Molecular Staging of Epithelial Maturation Using Secretory Cell–Specific Genes as Markers. American Journal Of Respiratory Cell And Molecular Biology 2008, 40: 340-348. PMID: 18757308, PMCID: PMC2645532, DOI: 10.1165/rcmb.2007-0380oc.Peer-Reviewed Original ResearchConceptsCell-specific genesCategories of genesUnique gene expression profileDevelopmental expression patternsSecretory cellsGene expression profilesCell marker genesExpression of FMO3Messenger RNA abundanceUnique developmental expression patternTransgenic approachesClara cell markerRNA abundanceMarker genesClara cellsExpression patternsExpression profilesMolecular markersEpithelial maturationPhenotypic changesFlavin monooxygenase 3GenesTemporal inductionBronchiolar Clara cellsEmbryonic day
2007
The Notch ligand Delta‐like 4 (Dll4) negatively regulates endothelial tip cell formation and vessel branching
Suchting S, Freitas C, del Toro R, le Noble F, Benedito R, Breant C, Duarte A, Eichmann A. The Notch ligand Delta‐like 4 (Dll4) negatively regulates endothelial tip cell formation and vessel branching. The FASEB Journal 2007, 21: a15-a15. DOI: 10.1096/fasebj.21.5.a15-a.Peer-Reviewed Original ResearchTip cell formationEndothelial tip cell formationTip cellsCell formationNovel negative regulatorCell marker genesEndothelial tip cellsLigand Delta-like 4Severe vascular abnormalitiesVessel branchingDelta-like 4Notch ligand Delta-like 4Embryonic lethalExpression of Dll4Vascular network formationTransmembrane ligandsNotch receptorsMarker genesNotch signalingNegative regulatorAngiogenic sproutingVEGF stimulationVEGF receptor 2Filopodia extensionGenetic background
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