Multi-omic meta-analysis identifies functional signatures of airway microbiome in chronic obstructive pulmonary disease

[1]  C. Brightling,et al.  Sputum microbiome profiling in COPD: beyond singular pathogen detection , 2020, Thorax.

[2]  Yiwen Wang,et al.  Managing batch effects in microbiome data , 2019, Briefings Bioinform..

[3]  I. Adcock,et al.  Functional effects of the microbiota in chronic respiratory disease. , 2019, The Lancet. Respiratory medicine.

[4]  P. Bork,et al.  Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation , 2019, Nature Medicine.

[5]  Paul Theodor Pyl,et al.  Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer , 2019, Nature Medicine.

[6]  E. Borenstein,et al.  Defining and Evaluating Microbial Contributions to Metabolite Variation in Microbiome-Metabolome Association Studies , 2018, mSystems.

[7]  MingKun Li,et al.  Transcriptionally Active Lung Microbiome and Its Association with Bacterial Biomass and Host Inflammatory Status , 2018, mSystems.

[8]  Francesco Asnicar,et al.  QIIME 2: Reproducible, interactive, scalable, and extensible microbiome data science , 2018 .

[9]  Yongqing Hou,et al.  Glutamate alleviates intestinal injury, maintains mTOR and suppresses TLR4 and NOD signaling pathways in weanling pigs challenged with lipopolysaccharide , 2018, Scientific Reports.

[10]  L. Fajas,et al.  Dietary Fiber Confers Protection against Flu by Shaping Ly6c− Patrolling Monocyte Hematopoiesis and CD8+ T Cell Metabolism , 2018, Immunity.

[11]  David S. Wishart,et al.  MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis , 2018, Nucleic Acids Res..

[12]  A. Goday,et al.  The Gut Microbiome Profile in Obesity: A Systematic Review , 2018, International journal of endocrinology.

[13]  Claire Duvallet,et al.  Correcting for batch effects in case-control microbiome studies , 2018, bioRxiv.

[14]  G. Siuzdak,et al.  METLIN: A Technology Platform for Identifying Knowns and Unknowns. , 2018, Analytical chemistry.

[15]  David S. Wishart,et al.  HMDB 4.0: the human metabolome database for 2018 , 2017, Nucleic Acids Res..

[16]  Zhang Wang,et al.  Meta-analysis of human gene expression in response to Mycobacterium tuberculosis infection reveals potential therapeutic targets , 2018, BMC Systems Biology.

[17]  James R. Brown,et al.  Sputum microbiome temporal variability and dysbiosis in chronic obstructive pulmonary disease exacerbations: an analysis of the COPDMAP study , 2017, Thorax.

[18]  Rafael A. Irizarry,et al.  Meta-analysis of gut microbiome studies identifies disease-specific and shared responses , 2017, Nature Communications.

[19]  I. Adcock,et al.  Metabolic re-patterning in COPD airway smooth muscle cells , 2017, European Respiratory Journal.

[20]  Xiuying Wang,et al.  Aspartate attenuates intestinal injury and inhibits TLR4 and NODs/NF-κB and p38 signaling in weaned pigs after LPS challenge , 2017, European Journal of Nutrition.

[21]  W. R. Wikoff,et al.  Randomised, double-blind, placebo-controlled trial with azithromycin selects for anti-inflammatory microbial metabolites in the emphysematous lung , 2016, Thorax.

[22]  Patrick D. Schloss,et al.  Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome , 2016, mBio.

[23]  J. Parkhill,et al.  Community dynamics and the lower airway microbiota in stable chronic obstructive pulmonary disease, smokers and healthy non-smokers , 2016, Thorax.

[24]  Paul J. McMurdie,et al.  DADA2: High resolution sample inference from Illumina amplicon data , 2016, Nature Methods.

[25]  W. R. Wikoff,et al.  Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype , 2016, Nature Microbiology.

[26]  J. Xia,et al.  Comprehensive Transcriptome Meta-analysis to Characterize Host Immune Responses in Helminth Infections , 2016, PLoS neglected tropical diseases.

[27]  James R. Brown,et al.  Lung microbiome dynamics in COPD exacerbations , 2016, European Respiratory Journal.

[28]  Casey M. Theriot,et al.  Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation , 2016, mSystems.

[29]  Damian Szklarczyk,et al.  STITCH 5: augmenting protein–chemical interaction networks with tissue and affinity data , 2015, Nucleic Acids Res..

[30]  Duy Tin Truong,et al.  MetaPhlAn2 for enhanced metagenomic taxonomic profiling , 2015, Nature Methods.

[31]  Matthew E. Ritchie,et al.  limma powers differential expression analyses for RNA-sequencing and microarray studies , 2015, Nucleic acids research.

[32]  Yingwei Chen,et al.  Curcumin suppresses NLRP3 inflammasome activation and protects against LPS-induced septic shock. , 2013, Molecular nutrition & food research.

[33]  W. Huber,et al.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.

[34]  F. Martinez,et al.  The role of the microbiome in exacerbations of chronic lung diseases , 2014, The Lancet.

[35]  Erika von Mutius,et al.  The microbiome and the lung. , 2014, Annals of the American Thoracic Society.

[36]  H. Boushey,et al.  Airway Microbiome Dynamics in Exacerbations of Chronic Obstructive Pulmonary Disease , 2014, Journal of Clinical Microbiology.

[37]  J. Crane,et al.  Pro-inflammatory effects of uric acid in the gastrointestinal tract , 2014, Immunological investigations.

[38]  Hiroki Sato,et al.  Palmitate induces reactive oxygen species production and β‐cell dysfunction by activating nicotinamide adenine dinucleotide phosphate oxidase through Src signaling , 2013, Journal of diabetes investigation.

[39]  Jia-an Zhang,et al.  Palmitic Acid Induces Production of Proinflammatory Cytokines Interleukin-6, Interleukin-1β, and Tumor Necrosis Factor-α via a NF-κB-Dependent Mechanism in HaCaT Keratinocytes , 2013, Mediators of inflammation.

[40]  Jesse R. Zaneveld,et al.  Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences , 2013, Nature Biotechnology.

[41]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[42]  W. Shi,et al.  The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote , 2013, Nucleic acids research.

[43]  Yan Zeng,et al.  Nitric oxide suppresses NLRP3 inflammasome activation and protects against LPS-induced septic shock , 2013, Cell Research.

[44]  Thomas R. Gingeras,et al.  STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..

[45]  Richard E. Isaacson,et al.  The Lung Microbiome in Moderate and Severe Chronic Obstructive Pulmonary Disease , 2012, PloS one.

[46]  Yan Lin,et al.  An R package suite for microarray meta-analysis in quality control, differentially expressed gene analysis and pathway enrichment detection , 2012, Bioinform..

[47]  Bernard Henrissat,et al.  Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome , 2012, PLoS Comput. Biol..

[48]  Steven L Salzberg,et al.  Fast gapped-read alignment with Bowtie 2 , 2012, Nature Methods.

[49]  R. Coleman,et al.  Diabetes promotes an inflammatory macrophage phenotype and atherosclerosis through acyl-CoA synthetase 1 , 2012, Proceedings of the National Academy of Sciences.

[50]  B. Hargadon,et al.  Profiling of Sputum Inflammatory Mediators in Asthma and Chronic Obstructive Pulmonary Disease , 2011, Respiration.

[51]  Kevin P. Keegan,et al.  Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset , 2011, Microbial Informatics and Experimentation.

[52]  Joshua D. Knowles,et al.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry , 2011, Nature Protocols.

[53]  Marcel Martin.  Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[54]  I. Čepelak,et al.  Glutathione cycle in stable chronic obstructive pulmonary disease , 2010, Cell biochemistry and function.

[55]  Jean-Louis Foulley,et al.  Gene expression Moderated effect size and P-value combinations for microarray meta-analyses , 2009 .

[56]  Douglas G Altman,et al.  Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets , 2008, PLoS medicine.

[57]  T. Seemungal,et al.  Plasma homocysteine is elevated in COPD patients and is related to COPD severity , 2007, International journal of chronic obstructive pulmonary disease.

[58]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[59]  I. Douglas,et al.  Is alveolar destruction and emphysema in chronic obstructive pulmonary disease an immune disease? , 2006, Proceedings of the American Thoracic Society.

[60]  S. Tyagi,et al.  Regulation of homocysteine-induced MMP-9 by ERK1/2 pathway. , 2006, American journal of physiology. Cell physiology.

[61]  C. D. Mathers,et al.  Chronic obstructive pulmonary disease: current burden and future projections , 2006, European Respiratory Journal.

[62]  Peter D. Karp,et al.  MetaCyc: a multiorganism database of metabolic pathways and enzymes , 2005, Nucleic Acids Res..

[63]  Peter D. Karp,et al.  MetaCyc: a multiorganism database of metabolic pathways and enzymes. , 2004, Nucleic acids research.

[64]  Susumu Goto,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 2000, Nucleic Acids Res..

[65]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..