2025
Integrating gut microbiome and neuroplasticity genomics in alcohol use disorder therapy
Koutromanos I, Legaki E, Dovrolis N, Vassilopoulos E, Stem A, Vasiliou V, Tzavellas E, Gazouli M. Integrating gut microbiome and neuroplasticity genomics in alcohol use disorder therapy. Human Genomics 2025, 19: 78. PMID: 40646629, PMCID: PMC12255058, DOI: 10.1186/s40246-025-00793-y.Peer-Reviewed Original ResearchConceptsGut microbiotaShort-chain fatty acid (SCFA)-producing bacteriaMetabolic pathwaysStress-related metabolic pathwaysHost-microbiota interactionsMicrobial metabolic pathwaysMulti-omics approachGut barrier integrityGene expression changesGene expression profilesNeuroplasticity-related genesRRNA sequencingGut microbiomeFamily genesGenomic signaturesMicrobiome compositionMicrobial compositionAUD patientsMicrobial dysbiosisTreatment responseFunctional pathwaysGene expressionMicrobiomeGenesExpression changesGut microbial composition and diversity varies by CREBRF genotype among Samoan infants
Oyama S, Arslanian K, Savo Sardaro M, Duckham R, Kershaw E, Wood A, Fidow U, Naseri T, Reupena M, Amato K, Hawley N. Gut microbial composition and diversity varies by CREBRF genotype among Samoan infants. Physiological Genomics 2025, 57: 473-484. PMID: 40366801, PMCID: PMC12276851, DOI: 10.1152/physiolgenomics.00014.2024.Peer-Reviewed Original ResearchGut microbiotaMicrobiome compositionBacterial gene sequencesDifferentially abundant taxaGut microbial compositionGut microbial diversityMicrobiota community structureOverall microbiome compositionGut microbiome compositionGenotypic differencesDifferential abundance analysisImmune signaling pathwaysEscherichia-Shigella</i>,Low relative abundanceAbundant taxaGene sequencesGut microbiomeMicrobial diversityMicrobial compositionAssociated with functional differencesCommunity structureAssociated with lower relative abundanceMinor A alleleRelative abundanceMicrobiotaSpecies and Tissue-Specific Microbiomes Drive Methane Fluxes from Trees
Gewirtzman J, Arnold W, Raymond P, Peccia J, Bradford M. Species and Tissue-Specific Microbiomes Drive Methane Fluxes from Trees. 2025 DOI: 10.5194/egusphere-egu25-14365.Peer-Reviewed Original ResearchMethanogenesis pathwaySurrounding soilDroplet digital PCRTree microbiomeLandscape positionUpland forestsCH4 sinkForest typesWetland sitesFermentation pathwaySoil communitiesUpland treesUpland soilsMicrobial sequencesUpland ecosystemsElevated CH4 concentrationsFunctional inferenceCH4 fluxesSulfur metabolismMicrobial compositionSyntrophic interactionsTree tissuesCopy numberCH4 emissionsSoil
2024
Comparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia
Nuncio-Mora L, Nicolini H, Lanzagorta N, García-Jaimes C, Sosa-Hernández F, González-Covarrubias V, Cabello-Rangel H, Sarmiento E, Glahn D, Genis-Mendoza A. Comparative Analysis of Fecal Microbiota Between Adolescents with Early-Onset Psychosis and Adults with Schizophrenia. Microorganisms 2024, 12: 2071. PMID: 39458380, PMCID: PMC11510430, DOI: 10.3390/microorganisms12102071.Peer-Reviewed Original ResearchEarly-onset psychosisPsychiatric disordersAtypical antipsychotic treatmentNon-psychotic individualsTreated with sertralineAntipsychotic treatmentSchizophrenia groupSchizophrenia patientsSchizophreniaGut-brain axisPsychosisGene orthology analysisPotential metabolic functionsAssociated with gut dysbiosisFunctional prediction analysisValproate treatmentPharmacological treatmentOscillospiraceae familiesOrthology analysisDecreased levelsFatty acid metabolismGut microbiomeExpressed genesMicrobial communitiesMicrobial compositionGut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles
Chang D, Gupta V, Hur B, Cobo-López S, Cunningham K, Han N, Lee I, Kronzer V, Teigen L, Karnatovskaia L, Longbrake E, Davis J, Nelson H, Sung J. Gut Microbiome Wellness Index 2 enhances health status prediction from gut microbiome taxonomic profiles. Nature Communications 2024, 15: 7447. PMID: 39198444, PMCID: PMC11358288, DOI: 10.1038/s41467-024-51651-9.Peer-Reviewed Original ResearchConceptsMicrobiome taxonomic profilingTaxonomic profilesOpen-source command-line toolGut microbiome researchGut microbial compositionGut microbiome signaturesFecal microbiota transplantationCommand-line toolShotgun metagenomicsTaxonomic signalMicrobiome researchMicrobial compositionMicrobiome signaturesGut healthMicrobiota transplantationGutPublished datasetsMultiple diseasesAntibiotic exposureEffects of dietMetagenomicsHigh confidencePhenotypeCross-validated balanced accuracyLubricating gel influence on vaginal microbiome sampling
Amitai Komem D, Hadar R, Paulson J, Mordechai Y, Eskandarian H, Efroni G, Amir A, Haberman Y, Tsur A. Lubricating gel influence on vaginal microbiome sampling. Scientific Reports 2024, 14: 18223. PMID: 39107405, PMCID: PMC11303677, DOI: 10.1038/s41598-024-68948-w.Peer-Reviewed Original ResearchConceptsMicrobial compositionVaginal samplesVaginal microbiome samplesBeta diversityVaginal microbiome studiesMicrobiome studiesMicrobiome samplesTaxa abundanceGynecological examinationPregnant womenLubricant gelReduce painMicrobial dataGel exposureEmergency roomSterile swabsEffect of gelMicrobial analysisMeta-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-analysisStress-induced mucin 13 reductions drive intestinal microbiome shifts and despair behaviors
Rivet-Noor C, Merchak A, Render C, Gay N, Beiter R, Brown R, Keeler A, Moreau G, Li S, Olgun D, Steigmeyer A, Ofer R, Phan T, Vemuri K, Chen L, Mahoney K, Shin J, Malaker S, Deppmann C, Verzi M, Gaultier A. Stress-induced mucin 13 reductions drive intestinal microbiome shifts and despair behaviors. Brain Behavior And Immunity 2024, 119: 665-680. PMID: 38579936, PMCID: PMC11187485, DOI: 10.1016/j.bbi.2024.03.028.Peer-Reviewed Original ResearchMicrobiome shiftsDespair behaviorTranscription factor familyChronic stressRegulation of mucinsState of dysbiosisMicrobiome composition changesAssociated with disease pathologyDepressive-like symptomsModel of chronic stressLimited treatment optionsContext of stressHuman microbiomeMicrobiome compositionPsychological stress exposureMicrobial compositionFactor familyMicrobial dysbiosisMicrobial changesMicrobiome dysbiosisMicrobiomeTreatment optionsUpstream mediatorDepressive symptomsStress exposureLongitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease
Zhou X, Shen X, Johnson J, Spakowicz D, Agnello M, Zhou W, Avina M, Honkala A, Chleilat F, Chen S, Cha K, Leopold S, Zhu C, Chen L, Lyu L, Hornburg D, Wu S, Zhang X, Jiang C, Jiang L, Jiang L, Jian R, Brooks A, Wang M, Contrepois K, Gao P, Rose S, Tran T, Nguyen H, Celli A, Hong B, Bautista E, Dorsett Y, Kavathas P, Zhou Y, Sodergren E, Weinstock G, Snyder M. Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease. Cell Host & Microbe 2024, 32: 506-526.e9. PMID: 38479397, PMCID: PMC11022754, DOI: 10.1016/j.chom.2024.02.012.Peer-Reviewed Original ResearchHost healthMicrobiome dynamicsBacterial taxaBody sitesMicrobiome stabilityIndividual taxaHuman microbiomeMicrobial compositionMicrobial dynamicsMulti-OmicsNasal microbiomeMicrobiomeDisrupt interactionsMolecular markersBody-sitesTaxaHostMetabolic diseasesOral microbiomeInsulin-resistant individualsIndividual-specificTemporal dynamicsClinical featuresComprehensive viewClinical markers
2022
Maternal weight status and the composition of the human milk microbiome: A scoping review
Daiy K, Harries V, Nyhan K, Marcinkowska U. Maternal weight status and the composition of the human milk microbiome: A scoping review. PLOS ONE 2022, 17: e0274950. PMID: 36191014, PMCID: PMC9529148, DOI: 10.1371/journal.pone.0274950.Peer-Reviewed Original ResearchConceptsMaternal weight statusGestational weight gainHuman milk microbiomeWeight statusMilk microbiomeExcessive gestational weight gainGut microbiomeCross-sectional studyInfant gut microbiomeWeb of ScienceBifidobacterium abundancePostpartum BMIInfant healthHuman milkWeight gainLower alpha diversityAdult gut microbiomeBMIMilk microbiotaCurrent literatureMicrobiomeStatusMicrobial compositionAssociationReviewphyloMDA: an R package for phylogeny-aware microbiome data analysis
Liu T, Zhou C, Wang H, Zhao H, Wang T. phyloMDA: an R package for phylogeny-aware microbiome data analysis. BMC Bioinformatics 2022, 23: 213. PMID: 35668363, PMCID: PMC9169257, DOI: 10.1186/s12859-022-04744-5.Peer-Reviewed Original ResearchConceptsHost-associated microbial communitiesShared evolutionary historyMicrobiome data analysisEvolutionary historyPhylogenetic informationPhylogenetic treeMicrobial communitiesR packageSequencing technologiesAbundance dataMicrobial compositionRelative abundanceMicrobiome dataSample sitesUser-friendly toolMultivariate abundance dataAbundanceUnique opportunityUnprecedented scaleDifferent patternsTrees
2021
Lung microbiome alterations in NSCLC patients
Zheng L, Sun R, Zhu Y, Li Z, She X, Jian X, Yu F, Deng X, Sai B, Wang L, Zhou W, Wu M, Li G, Tang J, Jia W, Xiang J. Lung microbiome alterations in NSCLC patients. Scientific Reports 2021, 11: 11736. PMID: 34083661, PMCID: PMC8175694, DOI: 10.1038/s41598-021-91195-2.Peer-Reviewed Original ResearchConceptsNon-small cell lung cancerNon-small cell lung cancer patientsRare speciesOral taxaLung microbiotaDiverse array of microbesNon-cancer controlsLobectomy samplesArray of microbesGlobal microbial compositionAssociated with lung cancer progressionLung cancerLung microbiome compositionBronchoscopy samplesPseudomonas entomophilaMetagenomic sequencingBronchoalveolar lavageLactobacillus rossiaeBacteroides pyogenesMicrobiota dysbiosisMicrobial communitiesMicrobiome compositionPaenibacillus odoriferMicrobial compositionLung microbiota dysbiosisStatistical Methods for Analyzing Tree-Structured Microbiome Data
Wang T, Zhao H. Statistical Methods for Analyzing Tree-Structured Microbiome Data. Frontiers In Probability And The Statistical Sciences 2021, 193-220. DOI: 10.1007/978-3-030-73351-3_8.Peer-Reviewed Original ResearchStatistical methodsOnly relative informationMicrobiome data analysisMicrobiome dataEmpirical Bayes estimationCompositional predictorsBayes estimationComputational challengesRelative informationDimension reductionAbundance matrixTaxa countsMultinomial modelMicrobiome datasetsPhylogenetic informationMicrobial taxaPhylogenetic treeSequencing technologiesOriginal ecosystemMicrobial compositionOrders of magnitudeMatrixExperimental methodsLibrary sizeZeros
2020
Crosstalk between circadian rhythms and the microbiota
Pearson JA, Wong FS, Wen L. Crosstalk between circadian rhythms and the microbiota. Immunology 2020, 161: 278-290. PMID: 33090484, PMCID: PMC7692254, DOI: 10.1111/imm.13278.Peer-Reviewed Original ResearchConceptsHost circadian rhythmsMicrobial oscillationsGene/protein expressionAspects of biologyCircadian rhythmMicrobial associationsMolecular oscillationsCircadian oscillationsMicrobial compositionMicrobial influenceCause diseaseMolecular techniquesHost metabolismDisease susceptibilityMicrobial changesProtein expressionPeripheral rhythmsMain inducerMicrobiotaSleep-wake cycleHost immunityCrosstalkClinical successPotential connectionMicrobes
2015
Species-Specific Dynamic Responses of Gut Bacteria to a Mammalian Glycan
Raghavan V, Groisman EA. Species-Specific Dynamic Responses of Gut Bacteria to a Mammalian Glycan. Journal Of Bacteriology 2015, 197: 1538-1548. PMID: 25691527, PMCID: PMC4403648, DOI: 10.1128/jb.00010-15.Peer-Reviewed Original ResearchConceptsUtilization genesRelated speciesBacterial speciesBacteroides speciesPolysaccharide utilization genesCase of genesGut bacteriaGut bacterial speciesOrthologous genesCommunity compositionExpression dynamicsMammalian glycansSole carbon sourceRelated microbesBacterial communitiesMicrobial speciesMammalian intestineSame geneStable coexistenceGut microbial compositionDifferential regulationExpression behaviorGenesMicrobial compositionSustained activation
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