Complex and unexpected outcomes of antibiotic therapy against a polymicrobial infection

[1]  Martin H. Christian,et al.  A restructuring of microbiome niche space is associated with Elexacaftor-Tezacaftor-Ivacaftor therapy in the cystic fibrosis lung , 2021, Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society.

[2]  Thomas Ropars,et al.  An observational study of anaerobic bacteria in cystic fibrosis lung using culture dependant and independent approaches , 2021, Scientific Reports.

[3]  M. A. Henson,et al.  One versus Many: Polymicrobial Communities and the Cystic Fibrosis Airway , 2021, mBio.

[4]  James T. Morton,et al.  High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy , 2020, mSystems.

[5]  S. El Aidy,et al.  Understanding the host-microbe interactions using metabolic modeling , 2020, bioRxiv.

[6]  William R. Harcombe,et al.  Disruption of Cross-Feeding Inhibits Pathogen Growth in the Sputa of Patients with Cystic Fibrosis , 2020, mSphere.

[7]  L. Hoffman,et al.  Lung function and microbiota diversity in cystic fibrosis , 2020, Microbiome.

[8]  L. Hoffman,et al.  Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration. , 2019, Trends in molecular medicine.

[9]  Juho Rousu,et al.  SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information , 2019, Nature Methods.

[10]  V. Waters,et al.  Antimicrobial susceptibility testing (AST) and associated clinical outcomes in individuals with cystic fibrosis: A systematic review. , 2019, Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society.

[11]  Mingxun Wang,et al.  Qiita: rapid, web-enabled microbiome meta-analysis , 2018, Nature Methods.

[12]  Rob Knight,et al.  Niche partitioning of a pathogenic microbiome driven by chemical gradients , 2018, Science Advances.

[13]  Aleksandra Tarkowska,et al.  Benchmarking taxonomic assignments based on 16S rRNA gene profiling of the microbiota from commonly sampled environments , 2018, GigaScience.

[14]  H. Goossens,et al.  Global increase and geographic convergence in antibiotic consumption between 2000 and 2015 , 2018, Proceedings of the National Academy of Sciences.

[15]  Oliver Ebenhöh,et al.  Review and perspective on mathematical modeling of microbial ecosystems , 2018, Biochemical Society transactions.

[16]  M. Rogers,et al.  Fluctuations in airway bacterial communities associated with clinical states and disease stages in cystic fibrosis , 2018, PloS one.

[17]  Eugenio Cinquemani,et al.  Mathematical modelling of microbes: metabolism, gene expression and growth , 2017, Journal of The Royal Society Interface.

[18]  P. Dorrestein,et al.  The WinCF Model - An Inexpensive and Tractable Microcosm of a Mucus Plugged Bronchiole to Study the Microbiology of Lung Infections. , 2017, Journal of visualized experiments : JoVE.

[19]  Jose A Navas-Molina,et al.  Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns , 2017, mSystems.

[20]  F. Rohwer,et al.  Ecological networking of cystic fibrosis lung infections , 2016, npj Biofilms and Microbiomes.

[21]  Kristian Fog Nielsen,et al.  Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking , 2016, Nature Biotechnology.

[22]  M. Tunney,et al.  The role of anaerobic bacteria in the cystic fibrosis airway , 2016, Current opinion in pulmonary medicine.

[23]  L. Lopez,et al.  Pyrosequencing Unveils Cystic Fibrosis Lung Microbiome Differences Associated with a Severe Lung Function Decline , 2016, PloS one.

[24]  K. Shepard,et al.  The Pseudomonas aeruginosa efflux pump MexGHI-OpmD transports a natural phenazine that controls gene expression and biofilm development , 2016, Proceedings of the National Academy of Sciences.

[25]  R. Hunter,et al.  Evidence and Role for Bacterial Mucin Degradation in Cystic Fibrosis Airway Disease , 2016, bioRxiv.

[26]  Orkun S. Soyer,et al.  Challenges in microbial ecology: building predictive understanding of community function and dynamics , 2016, The ISME Journal.

[27]  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.

[28]  Joanne K. Liu,et al.  Networks of energetic and metabolic interactions define dynamics in microbial communities , 2015, Proceedings of the National Academy of Sciences.

[29]  Barbara A. Bailey,et al.  A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation , 2014, The ISME Journal.

[30]  Forest Rohwer,et al.  Biogeochemical Forces Shape the Composition and Physiology of Polymicrobial Communities in the Cystic Fibrosis Lung , 2014, mBio.

[31]  Sarah L. Westcott,et al.  Development of a Dual-Index Sequencing Strategy and Curation Pipeline for Analyzing Amplicon Sequence Data on the MiSeq Illumina Sequencing Platform , 2013, Applied and Environmental Microbiology.

[32]  J. Erb-Downward,et al.  The role of the bacterial microbiome in lung disease , 2013, Expert review of respiratory medicine.

[33]  Susan Holmes,et al.  phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data , 2013, PloS one.

[34]  P. Salamon,et al.  Cystic fibrosis therapy: a community ecology perspective. , 2013, American journal of respiratory cell and molecular biology.

[35]  K. Katoh,et al.  MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability , 2013, Molecular biology and evolution.

[36]  Eric P. Nawrocki,et al.  An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea , 2011, The ISME Journal.

[37]  S. Hubbell,et al.  The unified neutral theory of biodiversity and biogeography at age ten. , 2011, Trends in ecology & evolution.

[38]  Margaret Rosenfeld,et al.  Failure to recover to baseline pulmonary function after cystic fibrosis pulmonary exacerbation. , 2010, American journal of respiratory and critical care medicine.

[39]  Pedro M. Valero-Mora,et al.  ggplot2: Elegant Graphics for Data Analysis , 2010 .

[40]  Matej Oresic,et al.  MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data , 2010, BMC Bioinformatics.

[41]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[42]  N. Høiby,et al.  Pseudomonas aeruginosa biofilms in the respiratory tract of cystic fibrosis patients , 2009, Pediatric pulmonology.

[43]  Adam P. Arkin,et al.  FastTree: Computing Large Minimum Evolution Trees with Profiles instead of a Distance Matrix , 2009, Molecular biology and evolution.

[44]  M. Wolfgang,et al.  Detection of anaerobic bacteria in high numbers in sputum from patients with cystic fibrosis. , 2008, American journal of respiratory and critical care medicine.

[45]  U. Römling,et al.  Microcolony formation: a novel biofilm model of Pseudomonas aeruginosa for the cystic fibrosis lung. , 2005, Journal of medical microbiology.

[46]  Neil Hunter,et al.  Determination of bacterial load by real-time PCR using a broad-range (universal) probe and primers set. , 2002, Microbiology.

[47]  Donald L. DeAngelis,et al.  Ecological modelling and disturbance evaluation , 1985 .