Featured Publications
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 interactionsCardiac dopamine D1 receptor triggers ventricular arrhythmia in chronic heart failure
Yamaguchi T, Sumida TS, Nomura S, Satoh M, Higo T, Ito M, Ko T, Fujita K, Sweet ME, Sanbe A, Yoshimi K, Manabe I, Sasaoka T, Taylor MRG, Toko H, Takimoto E, Naito AT, Komuro I. Cardiac dopamine D1 receptor triggers ventricular arrhythmia in chronic heart failure. Nature Communications 2020, 11: 4364. PMID: 32868781, PMCID: PMC7459304, DOI: 10.1038/s41467-020-18128-x.Peer-Reviewed Original ResearchConceptsVentricular arrhythmiasDopamine D1 receptorsD1 receptorsChronic heart failureHeart failure patientsSustained ventricular tachycardiaNormal calcium handlingFailure patientsHeart failureModel miceVentricular tachycardiaPathophysiological roleCalcium handlingTherapeutic targetDopamine systemSingle-cell resolution analysisArrhythmiasD1RCardiomyocytesReceptorsTachycardiaPatientsMice
2024
A 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 ResearchMeSH KeywordsAlgorithmsComputational BiologyGene Expression ProfilingHumansModels, StatisticalRNA-SeqSequence Analysis, RNASingle-Cell AnalysisConceptsCell 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 matrix
2021
NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data
He L, Davila-Velderrain J, Sumida TS, Hafler DA, Kellis M, Kulminski AM. NEBULA is a fast negative binomial mixed model for differential or co-expression analysis of large-scale multi-subject single-cell data. Communications Biology 2021, 4: 629. PMID: 34040149, PMCID: PMC8155058, DOI: 10.1038/s42003-021-02146-6.Peer-Reviewed Original ResearchMeSH KeywordsAlzheimer DiseaseApolipoproteins EBinomial DistributionComputational BiologyGene ExpressionGene Expression ProfilingHumansMicrogliaModels, StatisticalSingle-Cell AnalysisConceptsNegative binomial mixed modelsBinomial mixed modelsSingle-cell dataHigh-dimensional integralsLarge sample approximationLaplace approximationCell-level expressionMixed modelsApproximationNebulaSpeed gainData setsOrders of magnitudeMarker gene identificationIntegralsModelOverdispersionFalse positive errors
2018
Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure
Nomura S, Satoh M, Fujita T, Higo T, Sumida T, Ko T, Yamaguchi T, Tobita T, Naito AT, Ito M, Fujita K, Harada M, Toko H, Kobayashi Y, Ito K, Takimoto E, Akazawa H, Morita H, Aburatani H, Komuro I. Cardiomyocyte gene programs encoding morphological and functional signatures in cardiac hypertrophy and failure. Nature Communications 2018, 9: 4435. PMID: 30375404, PMCID: PMC6207673, DOI: 10.1038/s41467-018-06639-7.Peer-Reviewed Original ResearchConceptsCardiac hypertrophyCardiomyocyte remodelingGene programHeart failurePressure overloadMorphological hypertrophyHeart functionHypertrophyP53 deletionEarly hypertrophyFunctional signaturesFunctional phenotypeLate hypertrophyP53 signalingTranscriptional signatureProgram activationMitochondrial inhibitionUnderlying mechanismCardiomyocyte identityCardiomyocytesMitochondrial activationRemodelingFailureTranscriptional programsActivation