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
Single cell immunophenotyping of the skin lesion erythema migrans Identifies IgM memory B cells
Jiang R, Meng H, Raddassi K, Fleming I, Hoehn KB, Dardick KR, Belperron AA, Montgomery RR, Shalek AK, Hafler DA, Kleinstein SH, Bockenstedt LK. Single cell immunophenotyping of the skin lesion erythema migrans Identifies IgM memory B cells. JCI Insight 2021, 6: e148035. PMID: 34061047, PMCID: PMC8262471, DOI: 10.1172/jci.insight.148035.Peer-Reviewed Original ResearchConceptsMemory B cellsErythema migransB cellsEM lesionsIgM memory B cellsLyme diseaseB-cell receptor sequencingSkin infection siteCell receptor sequencingEarly Lyme diseaseLocal antigen presentationSkin immune responsesB cell populationsSingle-cell immunophenotypingMHC class II genesUninvolved skinImmune cellsSpirochetal infectionAntigen presentationCell immunophenotypingT cellsImmune responseIsotype usageAntibody productionInitial signsSingle-cell longitudinal analysis of SARS-CoV-2 infection in human airway epithelium identifies target cells, alterations in gene expression, and cell state changes
Ravindra NG, Alfajaro MM, Gasque V, Huston NC, Wan H, Szigeti-Buck K, Yasumoto Y, Greaney AM, Habet V, Chow RD, Chen JS, Wei J, Filler RB, Wang B, Wang G, Niklason LE, Montgomery RR, Eisenbarth SC, Chen S, Williams A, Iwasaki A, Horvath TL, Foxman EF, Pierce RW, Pyle AM, van Dijk D, Wilen CB. Single-cell longitudinal analysis of SARS-CoV-2 infection in human airway epithelium identifies target cells, alterations in gene expression, and cell state changes. PLOS Biology 2021, 19: e3001143. PMID: 33730024, PMCID: PMC8007021, DOI: 10.1371/journal.pbio.3001143.Peer-Reviewed Original ResearchConceptsSARS-CoV-2 infectionSARS-CoV-2Human bronchial epithelial cellsInterferon-stimulated genesCell state changesAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionSyndrome coronavirus 2 infectionCell tropismCoronavirus 2 infectionCoronavirus disease 2019Onset of infectionCell-intrinsic expressionCourse of infectionAir-liquid interface culturesHost-viral interactionsBronchial epithelial cellsSingle-cell RNA sequencingCell typesIL-1Disease 2019Human airwaysDevelopment of therapeuticsDrug AdministrationViral replication
2020
Single-Cell Transcriptional Archetypes of Airway Inflammation in Cystic Fibrosis.
Schupp JC, Khanal S, Gomez JL, Sauler M, Adams TS, Chupp GL, Yan X, Poli S, Zhao Y, Montgomery RR, Rosas IO, Dela Cruz CS, Bruscia EM, Egan ME, Kaminski N, Britto CJ. Single-Cell Transcriptional Archetypes of Airway Inflammation in Cystic Fibrosis. American Journal Of Respiratory And Critical Care Medicine 2020, 202: 1419-1429. PMID: 32603604, PMCID: PMC7667912, DOI: 10.1164/rccm.202004-0991oc.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAirway ResistanceCystic FibrosisFemaleHumansInflammationMaleMiddle AgedSingle-Cell AnalysisTranscriptional ActivationConceptsCF lung diseaseHealthy control subjectsImmune dysfunctionLung diseaseCystic fibrosisControl subjectsSputum cellsAbnormal chloride transportLung mononuclear phagocytesInnate immune dysfunctionDivergent clinical coursesImmune cell repertoireMonocyte-derived macrophagesCF monocytesAirway inflammationClinical courseProinflammatory featuresCell survival programInflammatory responseTissue injuryCell repertoireImmune functionTranscriptional profilesAlveolar macrophagesMononuclear phagocytesProfiling cellular heterogeneity in asthma with single cell multiparameter CyTOF
Stewart E, Wang X, Chupp GL, Montgomery RR. Profiling cellular heterogeneity in asthma with single cell multiparameter CyTOF. Journal Of Leukocyte Biology 2020, 108: 1555-1564. PMID: 32911570, PMCID: PMC8087109, DOI: 10.1002/jlb.5ma0720-770rr.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAsthmaFemaleHumansLymphocytesMacrophagesMaleMiddle AgedNeutrophilsSingle-Cell AnalysisSputumConceptsAirway immune cellsSource of inflammationChronic inflammatory diseaseInflammatory cell typesStudy of pathogenesisMultiple distinct subtypesHeterogeneity of diseaseBronchial epithelial cellsAirway inflammationCell typesAsthmatic patientsClinical responseEosinophilic infiltrateAnalysis of sputumAsthmatic inflammationFunctional statusClinical managementImmune cellsInflammatory diseasesHealthy controlsInflammatory responseAirway cellsSputumDistinct subtypesInflammation
2019
Exploring single-cell data with deep multitasking neural networks
Amodio M, van Dijk D, Srinivasan K, Chen WS, Mohsen H, Moon KR, Campbell A, Zhao Y, Wang X, Venkataswamy M, Desai A, Ravi V, Kumar P, Montgomery R, Wolf G, Krishnaswamy S. Exploring single-cell data with deep multitasking neural networks. Nature Methods 2019, 16: 1139-1145. PMID: 31591579, PMCID: PMC10164410, DOI: 10.1038/s41592-019-0576-7.Peer-Reviewed Original ResearchA Modified Injector and Sample Acquisition Protocol Can Improve Data Quality and Reduce Inter‐Instrument Variability of the Helios Mass Cytometer
Lee BH, Kelly G, Bradford S, Davila M, Guo XV, Amir E, Thrash EM, Solga MD, Lannigan J, Sellers B, Candia J, Tsang J, Montgomery RR, Tamaki SJ, Sigdel TK, Sarwal MM, Lanier LL, Tian Y, Kim C, Hinz D, Peters B, Sette A, Rahman AH. A Modified Injector and Sample Acquisition Protocol Can Improve Data Quality and Reduce Inter‐Instrument Variability of the Helios Mass Cytometer. Cytometry Part A 2019, 95: 1019-1030. PMID: 31364278, PMCID: PMC6750971, DOI: 10.1002/cyto.a.23866.Peer-Reviewed Original ResearchDissecting alterations in human CD8+ T cells with aging by high-dimensional single cell mass cytometry
Shin MS, Yim K, Moon K, Park HJ, Mohanty S, Kim JW, Montgomery RR, Shaw AC, Krishnaswamy S, Kang I. Dissecting alterations in human CD8+ T cells with aging by high-dimensional single cell mass cytometry. Clinical Immunology 2019, 200: 24-30. PMID: 30659916, PMCID: PMC6443094, DOI: 10.1016/j.clim.2019.01.005.Peer-Reviewed Original Research
2017
Gating mass cytometry data by deep learning
Li H, Shaham U, Stanton KP, Yao Y, Montgomery RR, Kluger Y. Gating mass cytometry data by deep learning. Bioinformatics 2017, 33: 3423-3430. PMID: 29036374, PMCID: PMC5860171, DOI: 10.1093/bioinformatics/btx448.Peer-Reviewed Original ResearchRemoval of batch effects using distribution-matching residual networks
Shaham U, Stanton KP, Zhao J, Li H, Raddassi K, Montgomery R, Kluger Y. Removal of batch effects using distribution-matching residual networks. Bioinformatics 2017, 33: 2539-2546. PMID: 28419223, PMCID: PMC5870543, DOI: 10.1093/bioinformatics/btx196.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyCytophotometryData AccuracyHumansMachine LearningSequence Analysis, RNASingle-Cell AnalysisStatistics as TopicConceptsMeasurement errorNovel deep learning approachRandom measurement errorMultivariate distributionsResidual neural networkDeep learning approachNovel biological technologiesMaximum mean discrepancyPhysical phenomenaResidual networkNeural networkLearning approachSystematic componentSupplementary dataSystematic errorsMean discrepancyScRNA-seq datasetsBatch effectsErrorNetworkStatistical analysis
2015
Neutralizing antibodies against West Nile virus identified directly from human B cells by single-cell analysis and next generation sequencing
Tsioris K, Gupta NT, Ogunniyi AO, Zimnisky RM, Qian F, Yao Y, Wang X, Stern JN, Chari R, Briggs AW, Clouser CR, Vigneault F, Church GM, Garcia MN, Murray KO, Montgomery RR, Kleinstein SH, Love JC. Neutralizing antibodies against West Nile virus identified directly from human B cells by single-cell analysis and next generation sequencing. Integrative Biology 2015, 7: 1587-1597. PMID: 26481611, PMCID: PMC4754972, DOI: 10.1039/c5ib00169b.Peer-Reviewed Original ResearchConceptsHumoral responseNext-generation sequencingB cellsWest Nile virus infectionSevere neurological illnessMemory B cellsAntibody-secreting cellsCohort of subjectsWNV-specific antibodiesHuman B cellsMosquito-borne diseaseWest Nile virusAnamnestic responseAntibody responseAvailable treatmentsClinical severityAntibody isotypesNeurological illnessVaccine studiesVirus infectionGeneration sequencingInfectious diseasesPrevious exposureTherapeutic antibodiesAntibodies
2014
CyTOF supports efficient detection of immune cell subsets from small samples
Yao Y, Liu R, Shin MS, Trentalange M, Allore H, Nassar A, Kang I, Pober JS, Montgomery RR. CyTOF supports efficient detection of immune cell subsets from small samples. Journal Of Immunological Methods 2014, 415: 1-5. PMID: 25450003, PMCID: PMC4269324, DOI: 10.1016/j.jim.2014.10.010.Peer-Reviewed Original ResearchConceptsImmune cell subsetsCell subsetsImmune cell statesPatient biopsiesTranslational investigationsFlow cytometryClinical researchCellular analysisMass cytometryMultiple cell populationsCell populationsCytometryCyTOFSingle-cell analysisMultiparameter single cell analysisFluorescence cytometryFluorescence-based flow cytometryCell statesHuman diseasesMarkersTremendous detailBiopsyPathogenesis