Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Morgan G. I. Langille,Jesse R. Zaneveld,J. Gregory Caporaso,J. Gregory Caporaso,Daniel McDonald,Dan Knights,Joshua A Reyes,Jose C. Clemente,Deron E. Burkepile,Rebecca Vega Thurber,Rob Knight,Rob Knight,Robert G. Beiko,Curtis Huttenhower,Curtis Huttenhower +14 more
TLDR
The results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.Abstract:
Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.read more
Citations
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Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
Evan Bolyen,Jai Ram Rideout,Matthew R. Dillon,Nicholas A. Bokulich,Christian C. Abnet,Gabriel A. Al-Ghalith,Harriet Alexander,Harriet Alexander,Eric J. Alm,Manimozhiyan Arumugam,Francesco Asnicar,Yang Bai,Jordan E. Bisanz,Kyle Bittinger,Asker Daniel Brejnrod,Colin J. Brislawn,C. Titus Brown,Benjamin J. Callahan,Andrés Mauricio Caraballo-Rodríguez,John Chase,Emily K. Cope,Ricardo Silva,Christian Diener,Pieter C. Dorrestein,Gavin M. Douglas,Daniel M. Durall,Claire Duvallet,Christian F. Edwardson,Madeleine Ernst,Madeleine Ernst,Mehrbod Estaki,Jennifer Fouquier,Julia M. Gauglitz,Sean M. Gibbons,Sean M. Gibbons,Deanna L. Gibson,Antonio Gonzalez,Kestrel Gorlick,Jiarong Guo,Benjamin Hillmann,Susan Holmes,Hannes Holste,Curtis Huttenhower,Curtis Huttenhower,Gavin A. Huttley,Stefan Janssen,Alan K. Jarmusch,Lingjing Jiang,Benjamin D. Kaehler,Benjamin D. Kaehler,Kyo Bin Kang,Kyo Bin Kang,Christopher R. Keefe,Paul Keim,Scott T. Kelley,Dan Knights,Irina Koester,Tomasz Kosciolek,Jorden Kreps,Morgan G. I. Langille,Joslynn S. Lee,Ruth E. Ley,Ruth E. Ley,Yong-Xin Liu,Erikka Loftfield,Catherine A. Lozupone,Massoud Maher,Clarisse Marotz,Bryan D Martin,Daniel McDonald,Lauren J. McIver,Lauren J. McIver,Alexey V. Melnik,Jessica L. Metcalf,Sydney C. Morgan,Jamie Morton,Ahmad Turan Naimey,Jose A. Navas-Molina,Jose A. Navas-Molina,Louis-Félix Nothias,Stephanie B. Orchanian,Talima Pearson,Samuel L. Peoples,Samuel L. Peoples,Daniel Petras,Mary L. Preuss,Elmar Pruesse,Lasse Buur Rasmussen,Adam R. Rivers,Michael S. Robeson,Patrick Rosenthal,Nicola Segata,Michael Shaffer,Arron Shiffer,Rashmi Sinha,Se Jin Song,John R. Spear,Austin D. Swafford,Luke R. Thompson,Luke R. Thompson,Pedro J. Torres,Pauline Trinh,Anupriya Tripathi,Peter J. Turnbaugh,Sabah Ul-Hasan,Justin J. J. van der Hooft,Fernando Vargas,Yoshiki Vázquez-Baeza,Emily Vogtmann,Max von Hippel,William A. Walters,Yunhu Wan,Mingxun Wang,Jonathan Warren,Kyle C. Weber,Kyle C. Weber,Charles H. D. Williamson,Amy D. Willis,Zhenjiang Zech Xu,Jesse R. Zaneveld,Yilong Zhang,Qiyun Zhu,Rob Knight,J. Gregory Caporaso +123 more
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Journal ArticleDOI
Diet rapidly and reproducibly alters the human gut microbiome
Lawrence A. David,Corinne F. Maurice,Rachel N. Carmody,David B. Gootenberg,Julie E. Button,Benjamin E. Wolfe,Alisha V. Ling,A. Sloan Devlin,Yug Varma,Michael A. Fischbach,Sudha B. Biddinger,Rachel J. Dutton,Peter J. Turnbaugh +12 more
TL;DR: Increases in the abundance and activity of Bilophila wadsworthia on the animal-based diet support a link between dietary fat, bile acids and the outgrowth of microorganisms capable of triggering inflammatory bowel disease.
Journal ArticleDOI
Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies.
TL;DR: An integrated database, called EzBioCloud, that holds the taxonomic hierarchy of the Bacteria and Archaea, which is represented by quality-controlled 16S rRNA gene and genome sequences, with accompanying bioinformatics tools.
Journal ArticleDOI
STAMP: statistical analysis of taxonomic and functional profiles
TL;DR: UNLABELLED STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles and a user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots.
Journal ArticleDOI
The Treatment-Naive Microbiome in New-Onset Crohn’s Disease
Dirk Gevers,Subra Kugathasan,Lee A. Denson,Yoshiki Vázquez-Baeza,Will Van Treuren,Boyu Ren,Emma Schwager,Dan Knights,Se Jin Song,Moran Yassour,Xochitl C. Morgan,Aleksandar Kostic,Chengwei Luo,Antonio Gonzalez,Daniel McDonald,Yael Haberman,Thomas D. Walters,Susan S. Baker,Joel R. Rosh,Michael C. Stephens,Melvin B. Heyman,James Markowitz,Robert N. Baldassano,Anne M. Griffiths,Francisco A. Sylvester,David R. Mack,Sandra C. Kim,Wallace Crandall,Jeffrey S. Hyams,Curtis Huttenhower,Curtis Huttenhower,Rob Knight,Rob Knight,Ramnik J. Xavier,Ramnik J. Xavier +34 more
TL;DR: Comparing the microbial signatures between the ileum, the rectum, and fecal samples indicates that at this early stage of disease, assessing the rectal mucosal-associated microbiome offers unique potential for convenient and early diagnosis of CD.
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