2023
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Zhu B, Wang Y, Ku L, van Dijk D, Zhang L, Hafler D, Zhao H. scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles. Genome Biology 2023, 24: 292. PMID: 38111007, PMCID: PMC10726524, DOI: 10.1186/s13059-023-03129-y.Peer-Reviewed Original ResearchDistinguishing features of long COVID identified through immune profiling
Klein J, Wood J, Jaycox J, Dhodapkar R, Lu P, Gehlhausen J, Tabachnikova A, Greene K, Tabacof L, Malik A, Silva Monteiro V, Silva J, Kamath K, Zhang M, Dhal A, Ott I, Valle G, Peña-Hernández M, Mao T, Bhattacharjee B, Takahashi T, Lucas C, Song E, McCarthy D, Breyman E, Tosto-Mancuso J, Dai Y, Perotti E, Akduman K, Tzeng T, Xu L, Geraghty A, Monje M, Yildirim I, Shon J, Medzhitov R, Lutchmansingh D, Possick J, Kaminski N, Omer S, Krumholz H, Guan L, Dela Cruz C, van Dijk D, Ring A, Putrino D, Iwasaki A. Distinguishing features of long COVID identified through immune profiling. Nature 2023, 623: 139-148. PMID: 37748514, PMCID: PMC10620090, DOI: 10.1038/s41586-023-06651-y.Peer-Reviewed Original ResearchConceptsLong COVIDSARS-CoV-2Infection syndromeExaggerated humoral responseSoluble immune mediatorsEpstein-Barr virusPost-exertional malaiseCross-sectional studyHigher antibody responseImmune mediatorsImmune phenotypingImmune profilingHumoral responseAntibody responseLymphocyte populationsCOVID statusUnbiased machineCortisol levelsLC statusRelevant biomarkersViral pathogensSyndromeCOVIDFuture studiesBiological featuresNasal host response-based screening for undiagnosed respiratory viruses: a pathogen surveillance and detection study
Cheemarla N, Hanron A, Fauver J, Bishai J, Watkins T, Brito A, Zhao D, Alpert T, Vogels C, Ko A, Schulz W, Landry M, Grubaugh N, van Dijk D, Foxman E. Nasal host response-based screening for undiagnosed respiratory viruses: a pathogen surveillance and detection study. The Lancet Microbe 2023, 4: e38-e46. PMID: 36586415, PMCID: PMC9835789, DOI: 10.1016/s2666-5247(22)00296-8.Peer-Reviewed Original ResearchConceptsRespiratory virus panelPg/mLCXCL10 concentrationsSARS-CoV-2Bacterial pathobiontsRespiratory virusesSARS-CoV-2 negative samplesViral respiratory infectionsSARS-CoV-2 positive samplesClinical virology laboratoryHealth care systemVirus-positive samplesQuantitative RT-PCRInfluenza C virusSymptomatic patientsRespiratory infectionsSeasonal coronavirusesNasopharyngeal swabsVirus panelC virusCommon virusesCXCL10Host responseInterferon responseVirology laboratory
2022
Interspecies commensal interactions have nonlinear impacts on host immunity
Rice TA, Bielecka AA, Nguyen MT, Rosen CE, Song D, Sonnert ND, Yang Y, Cao Y, Khetrapal V, Catanzaro JR, Martin AL, Rashed SA, Leopold SR, Hao L, Yu X, van Dijk D, Ring AM, Flavell RA, de Zoete MR, Palm NW. Interspecies commensal interactions have nonlinear impacts on host immunity. Cell Host & Microbe 2022, 30: 988-1002.e6. PMID: 35640610, PMCID: PMC9283318, DOI: 10.1016/j.chom.2022.05.004.Peer-Reviewed Original ResearchConceptsImmunological outcomesCell activationIntestinal epithelial cell activationInflammatory bowel disease patientsBowel disease patientsDendritic cell activationMesenteric lymph nodesSystemic antibody responsesEpithelial cell activationImmunological milieuLymph nodesAntibody responseDisease patientsAkkermansia muciniphilaGnotobiotic miceHost immunityCommensal microbesHuman cohortsHuman gut bacteriaGut bacteriaMiceAllobaculumMuciniphilaDiseaseIncomplete penetranceSingle-cell multiomics reveals persistence of HIV-1 in expanded cytotoxic T cell clones
Collora JA, Liu R, Pinto-Santini D, Ravindra N, Ganoza C, Lama JR, Alfaro R, Chiarella J, Spudich S, Mounzer K, Tebas P, Montaner LJ, van Dijk D, Duerr A, Ho YC. Single-cell multiomics reveals persistence of HIV-1 in expanded cytotoxic T cell clones. Immunity 2022, 55: 1013-1031.e7. PMID: 35320704, PMCID: PMC9203927, DOI: 10.1016/j.immuni.2022.03.004.Peer-Reviewed Original ResearchConceptsHIV-1 eradicationHIV-1 RNAHIV-1Effector memory Th1 cellsHIV-1-infected individualsHIV-1-infected CD4Clonal expansionCell clonesMemory Th1 cellsCell clonal expansionPersistent antigenAntiretroviral therapyViral suppressionCytotoxic CD4Cytotoxic TTh1 cellsAntigen stimulationClonal expansion dynamicsUninfected individualsSurface protein expressionTNF responseUnstimulated conditionsTCR sequencesProtein expressionCD4Single-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
A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST)
Oikonomou EK, Van Dijk D, Parise H, Suchard MA, de Lemos J, Antoniades C, Velazquez EJ, Miller EJ, Khera R. A phenomapping-derived tool to personalize the selection of anatomical vs. functional testing in evaluating chest pain (ASSIST). European Heart Journal 2021, 42: 2536-2548. PMID: 33881513, PMCID: PMC8488385, DOI: 10.1093/eurheartj/ehab223.Peer-Reviewed Original ResearchConceptsStable chest painChest painPrimary endpointMajor adverse cardiovascular eventsNon-fatal myocardial infarctionAdverse cardiovascular eventsStudy's primary endpointCoronary artery diseaseClinical trial populationsCox regression modelParticipant-level dataSCOT-HEARTCardiovascular eventsCause mortalityHazard ratioPatients 5Artery diseaseFunctional testingPROMISE trialTrial populationMyocardial infarctionLower incidenceStudy populationPainCollected variablesImmune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children
Ramaswamy A, Brodsky NN, Sumida TS, Comi M, Asashima H, Hoehn KB, Li N, Liu Y, Shah A, Ravindra NG, Bishai J, Khan A, Lau W, Sellers B, Bansal N, Guerrerio P, Unterman A, Habet V, Rice AJ, Catanzaro J, Chandnani H, Lopez M, Kaminski N, Dela Cruz CS, Tsang JS, Wang Z, Yan X, Kleinstein SH, van Dijk D, Pierce RW, Hafler DA, Lucas CL. Immune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children. Immunity 2021, 54: 1083-1095.e7. PMID: 33891889, PMCID: PMC8043654, DOI: 10.1016/j.immuni.2021.04.003.Peer-Reviewed Original ResearchConceptsMIS-C patientsDisease severityInflammatory syndromeTCR repertoireSARS-CoV-2-associated multisystem inflammatory syndromeAsymptomatic SARS-CoV-2 infectionSARS-CoV-2 infectionAdult COVID-19Post-infectious complicationsMultisystem inflammatory syndromeCytotoxicity genesHealthy pediatricImmune dysregulationMemory TActive infectionMyeloid dysfunctionPatientsSingle-cell RNA sequencingFlow cytometrySerum proteomicsRepertoire analysisElevated expressionSeverityAlarminsCOVID-19Single-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 replicationA neutrophil activation signature predicts critical illness and mortality in COVID-19
Meizlish ML, Pine AB, Bishai JD, Goshua G, Nadelmann ER, Simonov M, Chang CH, Zhang H, Shallow M, Bahel P, Owusu K, Yamamoto Y, Arora T, Atri DS, Patel A, Gbyli R, Kwan J, Won CH, Dela Cruz C, Price C, Koff J, King BA, Rinder HM, Wilson FP, Hwa J, Halene S, Damsky W, van Dijk D, Lee AI, Chun HJ. A neutrophil activation signature predicts critical illness and mortality in COVID-19. Blood Advances 2021, 5: 1164-1177. PMID: 33635335, PMCID: PMC7908851, DOI: 10.1182/bloodadvances.2020003568.Peer-Reviewed Original ResearchConceptsCritical illnessHealth system databaseNeutrophil activationCOVID-19Neutrophil activation signatureSevere COVID-19Intensive care unitGranulocyte colony-stimulating factorHigh mortality rateColony-stimulating factorSystem databaseHepatocyte growth factorClinical decompensationNeutrophil countImmune hyperactivationCare unitEarly elevationLipocalin-2Interleukin-8Longitudinal cohortClinical dataMortality ratePatientsIllnessActivation signatureQuantifying the effect of experimental perturbations at single-cell resolution
Burkhardt DB, Stanley JS, Tong A, Perdigoto AL, Gigante SA, Herold KC, Wolf G, Giraldez AJ, van Dijk D, Krishnaswamy S. Quantifying the effect of experimental perturbations at single-cell resolution. Nature Biotechnology 2021, 39: 619-629. PMID: 33558698, PMCID: PMC8122059, DOI: 10.1038/s41587-020-00803-5.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencing datasetsClusters of cellsRNA sequencing datasetsSingle-cell resolutionSingle-cell levelTranscriptomic spaceSequencing datasetsExperimental perturbationsCell populationsGene signatureVertex frequencyDiscrete regionsCellsEffects of perturbationsMultiple conditionsPerturbation responseClustersPopulationPerturbationsLikelihood estimatesGraph signal processingNeuroinvasion of SARS-CoV-2 in human and mouse brain
Song E, Zhang C, Israelow B, Lu-Culligan A, Prado AV, Skriabine S, Lu P, Weizman OE, Liu F, Dai Y, Szigeti-Buck K, Yasumoto Y, Wang G, Castaldi C, Heltke J, Ng E, Wheeler J, Alfajaro MM, Levavasseur E, Fontes B, Ravindra NG, Van Dijk D, Mane S, Gunel M, Ring A, Kazmi SAJ, Zhang K, Wilen CB, Horvath TL, Plu I, Haik S, Thomas JL, Louvi A, Farhadian SF, Huttner A, Seilhean D, Renier N, Bilguvar K, Iwasaki A. Neuroinvasion of SARS-CoV-2 in human and mouse brain. Journal Of Experimental Medicine 2021, 218: e20202135. PMID: 33433624, PMCID: PMC7808299, DOI: 10.1084/jem.20202135.Peer-Reviewed Original ResearchConceptsSARS-CoV-2Central nervous systemSARS-CoV-2 neuroinvasionImmune cell infiltratesCOVID-19 patientsType I interferon responseMultiple organ systemsCOVID-19I interferon responseHuman brain organoidsNeuroinvasive capacityCNS infectionsCell infiltrateNeuronal infectionPathological featuresCortical neuronsRespiratory diseaseDirect infectionCerebrospinal fluidNervous systemMouse brainInterferon responseOrgan systemsHuman ACE2Infection
2020
Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection
Wei J, Alfajaro MM, DeWeirdt PC, Hanna RE, Lu-Culligan WJ, Cai WL, Strine MS, Zhang SM, Graziano VR, Schmitz CO, Chen JS, Mankowski MC, Filler RB, Ravindra NG, Gasque V, de Miguel FJ, Patil A, Chen H, Oguntuyo KY, Abriola L, Surovtseva YV, Orchard RC, Lee B, Lindenbach BD, Politi K, van Dijk D, Kadoch C, Simon MD, Yan Q, Doench JG, Wilen CB. Genome-wide CRISPR Screens Reveal Host Factors Critical for SARS-CoV-2 Infection. Cell 2020, 184: 76-91.e13. PMID: 33147444, PMCID: PMC7574718, DOI: 10.1016/j.cell.2020.10.028.Peer-Reviewed Original ResearchMeSH KeywordsAngiotensin-Converting Enzyme 2AnimalsCell LineChlorocebus aethiopsClustered Regularly Interspaced Short Palindromic RepeatsCoronavirusCoronavirus InfectionsCOVID-19Gene Knockout TechniquesGene Regulatory NetworksGenome-Wide Association StudyHEK293 CellsHMGB1 ProteinHost-Pathogen InteractionsHumansSARS-CoV-2Vero CellsVirus InternalizationConceptsSARS-CoV-2 infectionSARS-CoV-2Vesicular stomatitis virusGenome-wide CRISPR screenSWI/SNF chromatinSARS-CoV-2 host factorsAcute respiratory syndrome coronavirus 2 infectionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectionTherapeutic targetHost factorsCoronavirus disease 2019 (COVID-19) pathogenesisSyndrome coronavirus 2 infectionCRISPR screensHost genesGene productsMiddle East respiratory syndrome CoVCoronavirus 2 infectionGenetic hitsHuman cellsSARS-CoV-2 spikeNovel therapeutic targetPotential therapeutic targetVero E6 cellsSARS-CoV-1Small molecule antagonistsTranscriptomic and clonal characterization of T cells in the human central nervous system
Pappalardo JL, Zhang L, Pecsok MK, Perlman K, Zografou C, Raddassi K, Abulaban A, Krishnaswamy S, Antel J, van Dijk D, Hafler DA. Transcriptomic and clonal characterization of T cells in the human central nervous system. Science Immunology 2020, 5 PMID: 32948672, PMCID: PMC8567322, DOI: 10.1126/sciimmunol.abb8786.Peer-Reviewed Original ResearchConceptsCentral nervous systemCSF of patientsT cellsCerebrospinal fluidMultiple sclerosisImmune surveillanceNervous systemCSF T cellsHuman central nervous systemHealthy human donorsT cell activationImmune dysfunctionNeuroinflammatory diseasesCytotoxic capacityHealthy donorsHealthy individualsCell activationHuman donorsTissue adaptationPatientsClonal characterizationExpression of genesCellsSurveillanceFurther characterizationDevelopment and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation
Haimovich AD, Ravindra NG, Stoytchev S, Young HP, Wilson FP, van Dijk D, Schulz WL, Taylor RA. Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation. Annals Of Emergency Medicine 2020, 76: 442-453. PMID: 33012378, PMCID: PMC7373004, DOI: 10.1016/j.annemergmed.2020.07.022.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedBetacoronavirusClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingEmergency Service, HospitalFemaleHumansMaleMiddle AgedOxygen Inhalation TherapyPandemicsPneumonia, ViralRespiratory InsufficiencyRetrospective StudiesRisk AssessmentSARS-CoV-2Severity of Illness IndexYoung AdultConceptsCOVID-19 Severity IndexQuick COVID-19 severity indexQuick Sequential Organ Failure AssessmentSequential Organ Failure AssessmentOrgan Failure AssessmentHours of admissionRespiratory failureSeverity IndexScoring systemSevere acute respiratory syndrome coronavirus 2Acute respiratory syndrome coronavirus 2Respiratory syndrome coronavirus 2Bedside scoring systemOxygen requirementPneumonia severity scoresHours of hospitalizationElixhauser Comorbidity IndexEmergency department patientsSeverity Index scoreCOVID-19 patientsSyndrome coronavirus 2Coronavirus disease 2019Failure AssessmentSimple scoring systemIndependent test cohortSingle cell immune profiling of dengue virus patients reveals intact immune responses to Zika virus with enrichment of innate immune signatures
Zhao Y, Amodio M, Vander Wyk B, Gerritsen B, Kumar MM, van Dijk D, Moon K, Wang X, Malawista A, Richards MM, Cahill ME, Desai A, Sivadasan J, Venkataswamy MM, Ravi V, Fikrig E, Kumar P, Kleinstein SH, Krishnaswamy S, Montgomery RR. Single cell immune profiling of dengue virus patients reveals intact immune responses to Zika virus with enrichment of innate immune signatures. PLOS Neglected Tropical Diseases 2020, 14: e0008112. PMID: 32150565, PMCID: PMC7082063, DOI: 10.1371/journal.pntd.0008112.Peer-Reviewed Original ResearchConceptsZika virusCell subsetsDengue virusConcurrent dengue infectionInnate cell responsesInnate immune signaturesVirus-infected individualsDivergent clinical outcomesMosquito-borne human pathogenIntact immune responsePre-existing infectionInnate cell typesSingle-cell immune profilingPublic health importanceCell typesImmune signaturesVirus patientsWest Nile virusAcute patientsClinical outcomesImmune profilingDengue infectionImmune statusFunctional statusImmune cellsNeurohormonal Blockade and Clinical Outcomes in Patients With Heart Failure Supported by Left Ventricular Assist Devices
McCullough M, Caraballo C, Ravindra NG, Miller PE, Mezzacappa C, Levin A, Gruen J, Rodwin B, Reinhardt S, van Dijk D, Ali A, Ahmad T, Desai NR. Neurohormonal Blockade and Clinical Outcomes in Patients With Heart Failure Supported by Left Ventricular Assist Devices. JAMA Cardiology 2020, 5: 175-182. PMID: 31738366, PMCID: PMC6865330, DOI: 10.1001/jamacardio.2019.4965.Peer-Reviewed Original ResearchConceptsKansas City Cardiomyopathy Questionnaire scoreNeurohormonal blockadeAngiotensin receptor blockersVentricular assist deviceQuality of lifeMineralocorticoid antagonistsReceptor blockersHeart failureWalk testQuestionnaire scoresΒ-blockersEnzyme inhibitorsAssist deviceGuideline-directed medical therapyAngiotensin-converting enzyme inhibitorMechanically Assisted Circulatory SupportHeart failure regimenLeft ventricular assist deviceAdvanced heart failureRetrospective cohort analysisContinuous-flow LVADBetter survival rateOutcomes of interestInteragency RegistryTriple therapyUncovering axes of variation among single-cell cancer specimens
Chen WS, Zivanovic N, van Dijk D, Wolf G, Bodenmiller B, Krishnaswamy S. Uncovering axes of variation among single-cell cancer specimens. Nature Methods 2020, 17: 302-310. PMID: 31932777, PMCID: PMC7339867, DOI: 10.1038/s41592-019-0689-z.Peer-Reviewed Original ResearchAlgorithmsAnimalsAntineoplastic AgentsBiopsyBreast NeoplasmsCluster AnalysisCytophotometryDrug Screening Assays, AntitumorEnzyme InhibitorsEpithelial-Mesenchymal TransitionFemaleHumansImage Interpretation, Computer-AssistedMammary Neoplasms, AnimalMiceNeoplasm MetastasisPattern Recognition, AutomatedPhenotypeRecombinant ProteinsSingle-Cell AnalysisSoftwareTransforming Growth Factor beta
2019
Visualizing structure and transitions in high-dimensional biological data
Moon KR, van Dijk D, Wang Z, Gigante S, Burkhardt DB, Chen WS, Yim K, Elzen AVD, Hirn MJ, Coifman RR, Ivanova NB, Wolf G, Krishnaswamy S. Visualizing structure and transitions in high-dimensional biological data. Nature Biotechnology 2019, 37: 1482-1492. PMID: 31796933, PMCID: PMC7073148, DOI: 10.1038/s41587-019-0336-3.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencing datasetsSingle-cell RNA sequencingUnique biological insightsRNA sequencing datasetsGerm layer differentiationMain developmental branchesHigh-throughput technologiesGut microbiome dataRNA sequencingUndescribed subpopulationsHigh-dimensional biological dataSequencing datasetsBiological insightsDevelopmental branchesExploring 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 Research