2023
Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine
de Assis F, Hoehn K, Zhang X, Kardava L, Smith C, Merhebi O, Buckner C, Trihemasava K, Wang W, Seamon C, Chen V, Schaughency P, Cheung F, Martins A, Chiang C, Li Y, Tsang J, Chun T, Kleinstein S, Moir S. Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine. Cell Reports 2023, 42: 112780. PMID: 37440409, PMCID: PMC10529190, DOI: 10.1016/j.celrep.2023.112780.Peer-Reviewed Original ResearchConceptsMemory B cellsB cell receptorB cellsAtypical memory B cellsInfection-naïve individualsTwo-dose SARSSARS-CoV-2 mRNAB cell responsesAntibody-secreting cellsMonth 6Protective immunityCell responsesCell receptorClonal expansionImmunoglobulin GEarly timepointsLater timepointsPlasmablastsVaccinationCD71TimepointsSurface proteinsCellsMultimodal single-cell analysisMRNA
2022
Normalizing and denoising protein expression data from droplet-based single cell profiling
Mulè M, Martins A, Tsang J. Normalizing and denoising protein expression data from droplet-based single cell profiling. Nature Communications 2022, 13: 2099. PMID: 35440536, PMCID: PMC9018908, DOI: 10.1038/s41467-022-29356-8.Peer-Reviewed Original ResearchConceptsProtein expression dataSingle-cell profiling methodsExpression dataSingle-cell profilingOligo-conjugated antibodiesTechnical noiseProtein populationCITE-seqCellular heterogeneityComprehensive dissectionDownstream analysisCell profilingDSBsSingle cellsProtein levelsProtein expressionCell populationsOpen-source R packageProfiling methodProtein countsEmpty dropletsR packageComputational analysisCellsBiological variation
2021
Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential
Rogers D, Sood A, Wang H, van Beek J, Rademaker T, Artusa P, Schneider C, Shen C, Wong D, Bhagrath A, Lebel M, Condotta S, Richer M, Martins A, Tsang J, Barreiro L, François P, Langlais D, Melichar H, Textor J, Mandl J. Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential. Cell Reports 2021, 37: 110064. PMID: 34852223, DOI: 10.1016/j.celrep.2021.110064.Peer-Reviewed Original ResearchConceptsSingle-cell RNA sequencingGene expression differencesCell receptor signalingChromatin accessibilityLineage choiceTCR signal strengthCell chromatinTranscriptional differencesRNA sequencingExpression differencesReceptor signalingLandscape differencesEffector potentialEffector lineagesThymic developmentCellsNaive CD4Self-peptide MHCChromatinCognate antigenLineagesGenesSignalingTCR interactionsKey drivers
2019
Differential Expression of the Transcription Factor GATA3 Specifies Lineage and Functions of Innate Lymphoid Cells
Zhong C, Zheng M, Cui K, Martins A, Hu G, Li D, Tessarollo L, Kozlov S, Keller J, Tsang J, Zhao K, Zhu J. Differential Expression of the Transcription Factor GATA3 Specifies Lineage and Functions of Innate Lymphoid Cells. Immunity 2019, 52: 83-95.e4. PMID: 31882362, PMCID: PMC6962539, DOI: 10.1016/j.immuni.2019.12.001.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsCell LineageCells, CulturedGATA3 Transcription FactorInhibitor of Differentiation Protein 2Interleukin Receptor Common gamma SubunitMiceMice, Inbred C57BLMice, KnockoutNuclear Receptor Subfamily 1, Group F, Member 3Programmed Cell Death 1 ReceptorPromyelocytic Leukemia Zinc Finger ProteinStem CellsT-Lymphocyte SubsetsT-Lymphocytes, Helper-InducerConceptsILC progenitorsDifferential expressionTranscription factor PLZFTranscriptional regulator Id2Common progenitorLymphoid progenitorsGATA3 expressionConditional deletionProgenitorsPLZFInnate lymphoid cellsExpressionLymphoid tissue inducer cellsLymphoid cellsLTi cellsCellsGATA3FateTranscription factor RORγtILC subsetsLineagesTranscriptionId2DeletionHigh amountsResident Macrophages Cloak Tissue Microlesions to Prevent Neutrophil-Driven Inflammatory Damage
Uderhardt S, Martins A, Tsang J, Lämmermann T, Germain R. Resident Macrophages Cloak Tissue Microlesions to Prevent Neutrophil-Driven Inflammatory Damage. Cell 2019, 177: 541-555.e17. PMID: 30955887, PMCID: PMC6474841, DOI: 10.1016/j.cell.2019.02.028.Peer-Reviewed Original ResearchConceptsTissue-resident macrophagesTissue homeostasisDiverse tissuesCell deathOrgan architectureIndividual cellsNeutrophil swarmsResident macrophagesDense swarmsLocal cell injuryIntravital imagingLocal disruptionParenchymal cell deathDynamic intravital imagingInescapable consequenceCell damageCell injuryHomeostasisMacrophagesCascadeInflammatory damageDamageCellsAccumulationDisruption
2017
Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network
Martins A, Narayanan M, Prüstel T, Fixsen B, Park K, Gottschalk R, Lu Y, Andrews-Pfannkoch C, Lau W, Wendelsdorf K, Tsang J. Environment Tunes Propagation of Cell-to-Cell Variation in the Human Macrophage Gene Network. Cell Systems 2017, 4: 379-392.e12. PMID: 28365150, PMCID: PMC8392141, DOI: 10.1016/j.cels.2017.03.002.Peer-Reviewed Original ResearchConceptsGene networksCellular adaptationCell variationSingle-cell transcriptomic studiesGene-gene correlationsUnderlying regulatory mechanismsDegree of phosphorylationPhenotypic diversityTranscriptomic studiesEnvironmental adaptationMultiple molecular parametersGene expressionRegulatory mechanismsCellular heterogeneityDistinct environmentsSingle cellsHuman macrophagesQuantitative tuningCell populationsNatural perturbationsGenesDifferent environmentsSuch variationCellsStochastic simulation analysis
2016
Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling
Narayanan M, Martins A, Tsang J. Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling. PLOS Computational Biology 2016, 12: e1005016. PMID: 27438699, PMCID: PMC4954693, DOI: 10.1371/journal.pcbi.1005016.Peer-Reviewed Original ResearchConceptsSingle-cell expression levelsExpression levelsNovel biological informationSingle cellsKey inflammatory genesExpression variationGene expressionCellular heterogeneityBiological informationRandom poolSingle populationHuman macrophagesBiological conditionsCell populationsGenesMultiplexed technologiesK cellsInflammatory genesCellsBiological varianceQuantifying differencesSensitive technologyContinuous variationRobust inferenceProfiling
2010
The multifaceted effects of granulocyte colony‐stimulating factor in immunomodulation and potential roles in intestinal immune homeostasis
Martins A, Han J, Kim S. The multifaceted effects of granulocyte colony‐stimulating factor in immunomodulation and potential roles in intestinal immune homeostasis. IUBMB Life 2010, 62: 611-617. PMID: 20681025, PMCID: PMC2916186, DOI: 10.1002/iub.361.Commentaries, Editorials and LettersConceptsColony-stimulating factorIntestinal immune homeostasisGranulocyte colony-stimulating factorImmune homeostasisMacrophage colony-stimulating factorG-CSFLocal immune homeostasisEndogenous G-CSFPotential roleMonocytes/macrophagesExogenous G-CSFGranulocyte/macrophage colony-stimulating factorDendritic cellsImmunosuppressive effectsImmunomodulatory effectsImmune cellsT lymphocytesImmune functionGM-CSFMyeloid hematopoiesisM-CSFImmunomodulationHomeostasisCellsFactors