2025
Psychiatric genetics in the diverse landscape of Latin American populations
Bruxel E, Rovaris D, Belangero S, Chavarría-Soley G, Cuellar-Barboza A, Martínez-Magaña J, Nagamatsu S, Nievergelt C, Núñez-Ríos D, Ota V, Peterson R, Sloofman L, Adams A, Albino E, Alvarado A, Andrade-Brito D, Arguello-Pascualli P, Bandeira C, Bau C, Bulik C, Buxbaum J, Cappi C, Corral-Frias N, Corrales A, Corsi-Zuelli F, Crowley J, Cupertino R, da Silva B, De Almeida S, De la Hoz J, Forero D, Fries G, Gelernter J, González-Giraldo Y, Grevet E, Grice D, Hernández-Garayua A, Hettema J, Ibáñez A, Ionita-Laza I, Lattig M, Lima Y, Lin Y, López-León S, Loureiro C, Martínez-Cerdeño V, Martínez-Levy G, Melin K, Moreno-De-Luca D, Muniz Carvalho C, Olivares A, Oliveira V, Ormond R, Palmer A, Panzenhagen A, Passos-Bueno M, Peng Q, Pérez-Palma E, Prieto M, Roussos P, Sanchez-Roige S, Santamaría-García H, Shansis F, Sharp R, Storch E, Tavares M, Tietz G, Torres-Hernández B, Tovo-Rodrigues L, Trelles P, Trujillo-ChiVacuan E, Velásquez M, Vera-Urbina F, Voloudakis G, Wegman-Ostrosky T, Zhen-Duan J, Zhou H, Santoro M, Nicolini H, Atkinson E, Giusti-Rodríguez P, Montalvo-Ortiz J. Psychiatric genetics in the diverse landscape of Latin American populations. Nature Genetics 2025, 57: 1074-1088. PMID: 40175716, PMCID: PMC12133068, DOI: 10.1038/s41588-025-02127-z.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesPsychiatric genomicsPsychiatric genome-wide association studiesLarge-scale genome-wide association studiesGenetic risk lociNon-European populationsGenetic diversityRisk lociGenetic admixtureBurden of psychiatric disordersAssociation studiesPsychiatric disordersEuropean ancestryPsychiatric geneticsGenomeHealthcare disparitiesConsortium effortLatin American populationsPromote equityEnvironmental factorsDiversityAmerican populationDiverse landscapeLociAncestry
2024
Diverse phage communities are maintained stably on a clonal bacterial host
Pyenson N, Leeks A, Nweke O, Goldford J, Schluter J, Turner P, Foster K, Sanchez A. Diverse phage communities are maintained stably on a clonal bacterial host. Science 2024, 386: 1294-1300. PMID: 39666794, PMCID: PMC7617280, DOI: 10.1126/science.adk1183.Peer-Reviewed Original ResearchConceptsPhage communitiesBacterial hostsPhage speciesEcology of bacteriophagesDiverse biological entitiesPhage diversityGrowth phenotypeCommunity ecologyEcological mechanismsPhageBacterial cellsPhenotypic heterogeneityHost populationsBacteriophageBiological entitiesDiversityHostSpeciesPhylogeneticallyNichePhenotypeStrainCellsCommunityPhenotypic Heterogeneity in Pathogens
Sherry J, Rego E. Phenotypic Heterogeneity in Pathogens. Annual Review Of Genetics 2024, 58: 183-209. PMID: 39083846, DOI: 10.1146/annurev-genet-111523-102459.Peer-Reviewed Original ResearchPhenotypic heterogeneityGenetically identical populationSalmonella typhimurium</i>Genetic diversityPathogen diversityPathogen populationsBacterial pathogensPathogen subpopulationsGenetic heterogeneityInvading pathogensHost organismFluctuating environmentsInfectious disease progressionPathogensIdentical populationsTreatment escapeInfection outcomesHeterogeneous subpopulationsDisease progressionInfecting organismDiversityCausative linkGeneticsSubpopulationsPhenotypeTissue spaces are reservoirs of antigenic diversity for Trypanosoma brucei
Beaver A, Keneskhanova Z, Cosentino R, Weiss B, Awuoche E, Smallenberger G, Buenconsejo G, Crilly N, Smith J, Hakim J, Zhang B, Bobb B, Rijo-Ferreira F, Figueiredo L, Aksoy S, Siegel T, Mugnier M. Tissue spaces are reservoirs of antigenic diversity for Trypanosoma brucei. Nature 2024, 636: 430-437. PMID: 39478231, PMCID: PMC11634766, DOI: 10.1038/s41586-024-08151-z.Peer-Reviewed Original ResearchVariant surface glycoproteinAntigenic diversityAntigenic variationHigh-throughput sequencing approachDense variant surface glycoproteinPopulations of T. bruceiDynamics of antigenic variationGenomic repertoirePathogen diversificationSequencing approachExtravascular spaceTrypanosoma bruceiVariation in vivoHost immune systemAntigenic variation in vivoSurface glycoproteinSlow immune responseDiversitySwitching expressionParasite populationsReproductive endocrinology and aging in human males: An evolutionary perspective
Bribiescas R. Reproductive endocrinology and aging in human males: An evolutionary perspective. Neuroscience & Biobehavioral Reviews 2024, 167: 105898. PMID: 39293503, DOI: 10.1016/j.neubiorev.2024.105898.Peer-Reviewed Original ResearchA new lineage nomenclature to aid genomic surveillance of dengue virus
Hill V, Cleemput S, Pereira J, Gifford R, Fonseca V, Tegally H, Brito A, Ribeiro G, de Souza V, Brcko I, Ribeiro I, De Lima I, Slavov S, Sampaio S, Elias M, Tran V, Kien D, Huynh T, Yacoub S, Dieng I, Salvato R, Wallau G, Gregianini T, Godinho F, Vogels C, Breban M, Leguia M, Jagtap S, Roy R, Hapuarachchi C, Mwanyika G, Giovanetti M, Alcantara L, Faria N, Carrington C, Hanley K, Holmes E, Dumon W, Lima A, de Oliveira T, Grubaugh N. A new lineage nomenclature to aid genomic surveillance of dengue virus. PLOS Biology 2024, 22: e3002834. PMID: 39283942, PMCID: PMC11426435, DOI: 10.1371/journal.pbio.3002834.Peer-Reviewed Original ResearchConceptsGenomic surveillanceSub-genotype levelPartial genome sequencesDengue virusViral genomic diversityClade sizeGenome sequenceGenomic diversityPhylogenetic studiesPhylogenetic distanceSequence dataMinor lineageVirus classificationLineagesSurveillance of dengue virusDiversityAssignment toolComplex patternsVirusCladeSequenceGeographical areasGenotypesNomenclatureEndemic settingsMeta-analysis identifies common gut microbiota associated with multiple sclerosis
Lin Q, Dorsett Y, Mirza A, Tremlett H, Piccio L, Longbrake E, Choileain S, Hafler D, Cox L, Weiner H, Yamamura T, Chen K, Wu Y, Zhou Y. Meta-analysis identifies common gut microbiota associated with multiple sclerosis. Genome Medicine 2024, 16: 94. PMID: 39085949, PMCID: PMC11293023, DOI: 10.1186/s13073-024-01364-x.Peer-Reviewed Original ResearchConceptsRRNA gene sequence dataGroups of microbial taxaGene sequence dataMicrobiome community structureAbundance of FaecalibacteriumAbundance of PrevotellaAbundance of ActinomycesSequence dataBeta diversityMicrobial taxaGut microbiotaMicrobial compositionCommunity structureNetwork analysisGutBacterial correlationsMicrobiotaAbundanceMultiple sclerosisDiverse groupMeta-analysisDiversityTaxaFaecalibacteriumConclusionsOur meta-analysisSignal integration and adaptive sensory diversity tuning in Escherichia coli chemotaxis
Moore J, Kamino K, Kottou R, Shimizu T, Emonet T. Signal integration and adaptive sensory diversity tuning in Escherichia coli chemotaxis. Cell Systems 2024, 15: 628-638.e8. PMID: 38981486, PMCID: PMC11307269, DOI: 10.1016/j.cels.2024.06.003.Peer-Reviewed Original ResearchEscherichia coli chemotaxisPopulation of E. coliMeasure kinase activityPhenotypic diversitySensory diversityDecreased diversityKinase activityDiverse phenotypesChemical signalsDiversitySingle cellsResponse to changesCellsSignalPhenotypePopulationChemotaxisSignal integrityLigandCompetitive ligandChemoattractantThe multidimensional roles of intermediate filaments - bridging genetic diversity with form, functions, and targets
Lusk C, Eriksson J. The multidimensional roles of intermediate filaments - bridging genetic diversity with form, functions, and targets. Current Opinion In Cell Biology 2024, 88: 102354. PMID: 38604107, DOI: 10.1016/j.ceb.2024.102354.Peer-Reviewed Original ResearchGenetic diversityDiversitycnnImpute: missing value recovery for single cell RNA sequencing data
Zhang W, Huckaby B, Talburt J, Weissman S, Yang M. cnnImpute: missing value recovery for single cell RNA sequencing data. Scientific Reports 2024, 14: 3946. PMID: 38365936, PMCID: PMC10873334, DOI: 10.1038/s41598-024-53998-x.Peer-Reviewed Original ResearchConceptsScRNA-seqAdvent of single-cell RNA sequencingScRNA-seq data analysisSingle cell RNA sequencing dataSingle-cell RNA sequencingRNA sequencing dataConvolutional neural networkSequence dataRNA sequencingCellular diversityExpression valuesCNN-based modelsMissing valuesCell clustersNeural networkIntricate diseaseIssue of missing dataSuperior performanceMissing probabilitySequenceBenchmark experimentsDiversityData analysisExpressionMemory B cell subsets have divergent developmental origins that are coupled to distinct imprinted epigenetic states
Callahan D, Smita S, Joachim S, Hoehn K, Kleinstein S, Weisel F, Chikina M, Shlomchik M. Memory B cell subsets have divergent developmental origins that are coupled to distinct imprinted epigenetic states. Nature Immunology 2024, 25: 562-575. PMID: 38200277, PMCID: PMC12036331, DOI: 10.1038/s41590-023-01721-9.Peer-Reviewed Original ResearchGerminal center B cellsDistinct genomic featuresDP cellsDevelopmental originsEpigenetic stateFunctional diversityEpigenetic patternsTranscriptional profilingGenomic featuresDN cellsDistinct developmental historiesB cellsReporter miceFunctional responseCellsMemory B cellsChromatinB cell subsetsCell-dependent responsesMultiple approachesProgenyDiversityT cell-dependent responsesGerminal centersDevelopmental history
2023
A Novel Subcluster of Closely Related Bacillus Phages with Distinct Tail Fiber/Lysin Gene Combinations
Loney R, Delesalle V, Chaudry B, Czerpak M, Guffey A, Goubet-McCall L, McCarty M, Strine M, Tanke N, Vill A, Krukonis G. A Novel Subcluster of Closely Related Bacillus Phages with Distinct Tail Fiber/Lysin Gene Combinations. Viruses 2023, 15: 2267. PMID: 38005943, PMCID: PMC10674732, DOI: 10.3390/v15112267.Peer-Reviewed Original ResearchReframing macrophage diversity with network motifs
Pizzurro G, Miller-Jensen K. Reframing macrophage diversity with network motifs. Trends In Immunology 2023, 44: 965-970. PMID: 37949786, PMCID: PMC11057955, DOI: 10.1016/j.it.2023.10.009.Commentaries, Editorials and LettersConceptsNetwork motifsDistinct biological functionsSystems biology conceptsMacrophage stateMacrophage responseBiological functionsMacrophage diversityExtracellular networkMacrophage activationDisease contextsMotifLocal molecular interactionsMolecular interactionsFunctional modulesBiology conceptsDiversityActivationTissueIntracellularResponseStructure and molecular mechanism of bacterial transcription activation
Kompaniiets D, Wang D, Yang Y, Hu Y, Liu B. Structure and molecular mechanism of bacterial transcription activation. Trends In Microbiology 2023, 32: 379-397. PMID: 37903670, DOI: 10.1016/j.tim.2023.10.001.Peer-Reviewed Original ResearchTranscription activation mechanismTranscription activation complexTranscription activationGene expressionActivation mechanismRecent structural studiesSignal transduction processesTranscription activatorExtracellular signalsTAC componentsActivation complexMechanistic diversityMolecular mechanismsTransduction processesDifferent intracellularImportant checkpointStructural studiesStructural featuresActivationExpressionMechanismCheckpointDiversitySystematic classificationActivatorTissue Biology: In Search of a New Paradigm
Adler M, Chavan A, Medzhitov R. Tissue Biology: In Search of a New Paradigm. Annual Review Of Cell And Developmental Biology 2023, 39: 67-89. PMID: 37607470, DOI: 10.1146/annurev-cellbio-120420-113830.Peer-Reviewed Original ResearchFibroblasts – the cellular choreographers of wound healing
Knoedler S, Broichhausen S, Guo R, Dai R, Knoedler L, Kauke-Navarro M, Diatta F, Pomahac B, Machens H, Jiang D, Rinkevich Y. Fibroblasts – the cellular choreographers of wound healing. Frontiers In Immunology 2023, 14: 1233800. PMID: 37646029, PMCID: PMC10461395, DOI: 10.3389/fimmu.2023.1233800.Peer-Reviewed Original ResearchConceptsFibroblast diversityInnate immune cellsNovel treatment modalitiesWound healing functionsFascial connective tissueRole of fibroblastsTreatment modalitiesImmune cellsWound repairScar tissueDiversityFibroblastsConnective tissueHealing processWound healingComprehensive understandingMachineryTissueHealing functionCascadeA guide to the BRAIN Initiative Cell Census Network data ecosystem
Hawrylycz M, Martone M, Ascoli G, Bjaalie J, Dong H, Ghosh S, Gillis J, Hertzano R, Haynor D, Hof P, Kim Y, Lein E, Liu Y, Miller J, Mitra P, Mukamel E, Ng L, Osumi-Sutherland D, Peng H, Ray P, Sanchez R, Regev A, Ropelewski A, Scheuermann R, Tan S, Thompson C, Tickle T, Tilgner H, Varghese M, Wester B, White O, Zeng H, Aevermann B, Allemang D, Ament S, Athey T, Baker C, Baker K, Baker P, Bandrowski A, Banerjee S, Bishwakarma P, Carr A, Chen M, Choudhury R, Cool J, Creasy H, D’Orazi F, Degatano K, Dichter B, Ding S, Dolbeare T, Ecker J, Fang R, Fillion-Robin J, Fliss T, Gee J, Gillespie T, Gouwens N, Zhang G, Halchenko Y, Harris N, Herb B, Hintiryan H, Hood G, Horvath S, Huo B, Jarecka D, Jiang S, Khajouei F, Kiernan E, Kir H, Kruse L, Lee C, Lelieveldt B, Li Y, Liu H, Liu L, Markuhar A, Mathews J, Mathews K, Mezias C, Miller M, Mollenkopf T, Mufti S, Mungall C, Orvis J, Puchades M, Qu L, Receveur J, Ren B, Sjoquist N, Staats B, Tward D, van Velthoven C, Wang Q, Xie F, Xu H, Yao Z, Yun Z, Zhang Y, Zheng W, Zingg B. A guide to the BRAIN Initiative Cell Census Network data ecosystem. PLOS Biology 2023, 21: e3002133. PMID: 37390046, PMCID: PMC10313015, DOI: 10.1371/journal.pbio.3002133.Peer-Reviewed Original ResearchAn integrated cell atlas of the lung in health and disease
Sikkema L, Ramírez-Suástegui C, Strobl D, Gillett T, Zappia L, Madissoon E, Markov N, Zaragosi L, Ji Y, Ansari M, Arguel M, Apperloo L, Banchero M, Bécavin C, Berg M, Chichelnitskiy E, Chung M, Collin A, Gay A, Gote-Schniering J, Hooshiar Kashani B, Inecik K, Jain M, Kapellos T, Kole T, Leroy S, Mayr C, Oliver A, von Papen M, Peter L, Taylor C, Walzthoeni T, Xu C, Bui L, De Donno C, Dony L, Faiz A, Guo M, Gutierrez A, Heumos L, Huang N, Ibarra I, Jackson N, Kadur Lakshminarasimha Murthy P, Lotfollahi M, Tabib T, Talavera-López C, Travaglini K, Wilbrey-Clark A, Worlock K, Yoshida M, van den Berge M, Bossé Y, Desai T, Eickelberg O, Kaminski N, Krasnow M, Lafyatis R, Nikolic M, Powell J, Rajagopal J, Rojas M, Rozenblatt-Rosen O, Seibold M, Sheppard D, Shepherd D, Sin D, Timens W, Tsankov A, Whitsett J, Xu Y, Banovich N, Barbry P, Duong T, Falk C, Meyer K, Kropski J, Pe’er D, Schiller H, Tata P, Schultze J, Teichmann S, Misharin A, Nawijn M, Luecken M, Theis F. An integrated cell atlas of the lung in health and disease. Nature Medicine 2023, 29: 1563-1577. PMID: 37291214, PMCID: PMC10287567, DOI: 10.1038/s41591-023-02327-2.Peer-Reviewed Original ResearchConceptsCell atlasGene modulesCell typesCell type definitionsHuman Cell AtlasSingle-cell technologiesSingle-cell datasetsUndescribed cell typeMultiple lung diseasesCell statesMarker genesMonocyte-derived macrophagesDistal axisStudy of diseasesHuman tissuesAnnotationAtlasGenesSPP1DiversityExpressionTreesLimited numberCellsNew dataHelical allophycocyanin nanotubes absorb far-red light in a thermophilic cyanobacterium
Gisriel C, Elias E, Shen G, Soulier N, Flesher D, Gunner M, Brudvig G, Croce R, Bryant D. Helical allophycocyanin nanotubes absorb far-red light in a thermophilic cyanobacterium. Science Advances 2023, 9: eadg0251. PMID: 36961897, PMCID: PMC10038336, DOI: 10.1126/sciadv.adg0251.Peer-Reviewed Original ResearchConceptsFar-red lightLight-harvesting proteinsLight-harvesting phycobiliproteinsCryo-electron microscopyStructure-function relationshipsLow-light environmentsAP complexesThermophilic cyanobacteriumLow lightBiological plasticityPhotosystem I.Likely associatesAllophycocyaninParalogsEnhanced abilityCyanobacteriaCyanobacteriumAcclimationSubunitsPhycobiliproteinsProteinResource accessibilityDiversityAssemblesChlorophyllSolving a molecular cryptogram for the human fingerprint
Myung P, Ito M. Solving a molecular cryptogram for the human fingerprint. Cell 2023, 186: 899-901. PMID: 36868211, DOI: 10.1016/j.cell.2023.01.032.Peer-Reviewed Original Research
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