2022
Type I interferon transcriptional network regulates expression of coinhibitory receptors in human T cells
Sumida TS, Dulberg S, Schupp JC, Lincoln MR, Stillwell HA, Axisa PP, Comi M, Unterman A, Kaminski N, Madi A, Kuchroo VK, Hafler DA. Type I interferon transcriptional network regulates expression of coinhibitory receptors in human T cells. Nature Immunology 2022, 23: 632-642. PMID: 35301508, PMCID: PMC8989655, DOI: 10.1038/s41590-022-01152-y.Peer-Reviewed Original ResearchConceptsCoinhibitory receptor expressionHuman T cellsIFN-I responsesCoinhibitory receptorsT cellsTIGIT expressionReceptor expressionAcute SARS-CoV-2 infectionPD-1/TimSARS-CoV-2 infectionEnhancement of immunotherapyType 1 interferonT-cell featuresLAG-3Infectious diseasesDifferent temporal kineticsTranscription factorsCancer therapyReceptorsCell featuresKey transcription factorIFNPresent studyMRNA profilingKey regulatorSingle-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
Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity
Bui LT, Winters NI, Chung MI, Joseph C, Gutierrez AJ, Habermann AC, Adams TS, Schupp JC, Poli S, Peter LM, Taylor CJ, Blackburn JB, Richmond BW, Nicholson AG, Rassl D, Wallace WA, Rosas IO, Jenkins RG, Kaminski N, Kropski JA, Banovich NE. Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity. Nature Communications 2021, 12: 4314. PMID: 34262047, PMCID: PMC8280215, DOI: 10.1038/s41467-021-24467-0.Peer-Reviewed Original ResearchConceptsChronic lung diseaseLung diseaseImmune responseSARS-CoV-2 entry factorsSevere coronavirus disease-19SARS-CoV-2 infectionWorse COVID-19 outcomesSARS-CoV-2 entryAdaptive immune responsesCoronavirus disease-19COVID-19 outcomesInnate immune responseInflammatory gene expression programSimilar cellular distributionPoor outcomePeripheral lungViral exposureDisease-19Inflammatory microenvironmentEntry factorsLung epitheliumLung cellsViral replicationAT2 cellsBasal differencesSingle-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics
Muus C, Luecken M, Eraslan G, Sikkema L, Waghray A, Heimberg G, Kobayashi Y, Vaishnav E, Subramanian A, Smillie C, Jagadeesh K, Duong E, Fiskin E, Torlai Triglia E, Ansari M, Cai P, Lin B, Buchanan J, Chen S, Shu J, Haber A, Chung H, Montoro D, Adams T, Aliee H, Allon S, Andrusivova Z, Angelidis I, Ashenberg O, Bassler K, Bécavin C, Benhar I, Bergenstråhle J, Bergenstråhle L, Bolt L, Braun E, Bui L, Callori S, Chaffin M, Chichelnitskiy E, Chiou J, Conlon T, Cuoco M, Cuomo A, Deprez M, Duclos G, Fine D, Fischer D, Ghazanfar S, Gillich A, Giotti B, Gould J, Guo M, Gutierrez A, Habermann A, Harvey T, He P, Hou X, Hu L, Hu Y, Jaiswal A, Ji L, Jiang P, Kapellos T, Kuo C, Larsson L, Leney-Greene M, Lim K, Litviňuková M, Ludwig L, Lukassen S, Luo W, Maatz H, Madissoon E, Mamanova L, Manakongtreecheep K, Leroy S, Mayr C, Mbano I, McAdams A, Nabhan A, Nyquist S, Penland L, Poirion O, Poli S, Qi C, Queen R, Reichart D, Rosas I, Schupp J, Shea C, Shi X, Sinha R, Sit R, Slowikowski K, Slyper M, Smith N, Sountoulidis A, Strunz M, Sullivan T, Sun D, Talavera-López C, Tan P, Tantivit J, Travaglini K, Tucker N, Vernon K, Wadsworth M, Waldman J, Wang X, Xu K, Yan W, Zhao W, Ziegler C. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics. Nature Medicine 2021, 27: 546-559. PMID: 33654293, PMCID: PMC9469728, DOI: 10.1038/s41591-020-01227-z.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overAlveolar Epithelial CellsAngiotensin-Converting Enzyme 2Cathepsin LCOVID-19Datasets as TopicDemographyFemaleGene Expression ProfilingHost-Pathogen InteractionsHumansLungMaleMiddle AgedOrgan SpecificityRespiratory SystemSARS-CoV-2Sequence Analysis, RNASerine EndopeptidasesSingle-Cell AnalysisVirus InternalizationConceptsSingle-cell RNA-sequencing studiesRNA-sequencing studiesSpecific expression patternsExpression programsKey immune functionsExpression patternsSARS-CoV-2 entry genesSpecific expressionAlveolar type 2 cellsMolecular pathwaysLung parenchyma samplesCoronavirus disease 2019 (COVID-19) transmissionDifferent tissuesCellular entryGenesRespiratory epithelial cellsAirway secretory cellsSecretory cellsTumor necrosis factorEntry genesExpression levelsType 2 cellsEpithelial cellsGut tissueSpecific subset