Literature DB >> 34074026

General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways.

Boštjan Murovec1, Leon Deutsch2, Blaž Stres2,3,4,5.   

Abstract

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

Entities:  

Keywords:  16S rRNA; ASV; Mothur; OTU; PICRUSt 2; Piphillin; amplicon; genus; gut; human microbiome; intestine; mice; predicted enzymatic reactions; predicted metabolic pathways; predicted metagenomes; reproducible analyses

Year:  2021        PMID: 34074026     DOI: 10.3390/metabo11060336

Source DB:  PubMed          Journal:  Metabolites        ISSN: 2218-1989


  26 in total

1.  Intragenomic heterogeneity of 16S rRNA genes causes overestimation of prokaryotic diversity.

Authors:  Dong-Lei Sun; Xuan Jiang; Qinglong L Wu; Ning-Yi Zhou
Journal:  Appl Environ Microbiol       Date:  2013-07-19       Impact factor: 4.792

2.  Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome.

Authors:  Malte Christoph Rühlemann; Britt Marie Hermes; Corinna Bang; Shauni Doms; Lucas Moitinho-Silva; Louise Bruun Thingholm; Fabian Frost; Frauke Degenhardt; Michael Wittig; Jan Kässens; Frank Ulrich Weiss; Annette Peters; Klaus Neuhaus; Uwe Völker; Henry Völzke; Georg Homuth; Stefan Weiss; Harald Grallert; Matthias Laudes; Wolfgang Lieb; Dirk Haller; Markus M Lerch; John F Baines; Andre Franke
Journal:  Nat Genet       Date:  2021-01-18       Impact factor: 38.330

3.  Blood metabolome predicts gut microbiome α-diversity in humans.

Authors:  Tomasz Wilmanski; Noa Rappaport; John C Earls; Andrew T Magis; Ohad Manor; Jennifer Lovejoy; Gilbert S Omenn; Leroy Hood; Sean M Gibbons; Nathan D Price
Journal:  Nat Biotechnol       Date:  2019-09-02       Impact factor: 54.908

4.  Reconciliation between operational taxonomic units and species boundaries.

Authors:  Mohamed Mysara; Peter Vandamme; Ruben Props; Frederiek-Maarten Kerckhof; Natalie Leys; Nico Boon; Jeroen Raes; Pieter Monsieurs
Journal:  FEMS Microbiol Ecol       Date:  2017-04-01       Impact factor: 4.194

5.  Piphillin: Improved Prediction of Metagenomic Content by Direct Inference from Human Microbiomes.

Authors:  Shoko Iwai; Thomas Weinmaier; Brian L Schmidt; Donna G Albertson; Neil J Poloso; Karim Dabbagh; Todd Z DeSantis
Journal:  PLoS One       Date:  2016-11-07       Impact factor: 3.240

Review 6.  Metabolome-Microbiome Crosstalk and Human Disease.

Authors:  Kathleen A Lee-Sarwar; Jessica Lasky-Su; Rachel S Kelly; Augusto A Litonjua; Scott T Weiss
Journal:  Metabolites       Date:  2020-05-01

7.  Cross-omics analysis revealed gut microbiome-related metabolic pathways underlying atherosclerosis development after antibiotics treatment.

Authors:  Ben Arpad Kappel; Lorenzo De Angelis; Michael Heiser; Marta Ballanti; Robert Stoehr; Claudia Goettsch; Maria Mavilio; Anna Artati; Omero A Paoluzi; Jerzy Adamski; Geltrude Mingrone; Bart Staels; Remy Burcelin; Giovanni Monteleone; Rossella Menghini; Nikolaus Marx; Massimo Federici
Journal:  Mol Metab       Date:  2020-03-13       Impact factor: 7.422

Review 8.  Reintroducing mothur: 10 Years Later.

Authors:  Patrick D Schloss
Journal:  Appl Environ Microbiol       Date:  2020-01-07       Impact factor: 4.792

9.  The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses.

Authors:  Tomáš Větrovský; Petr Baldrian
Journal:  PLoS One       Date:  2013-02-27       Impact factor: 3.240

10.  Interplay between the human gut microbiome and host metabolism.

Authors:  Alessia Visconti; Caroline I Le Roy; Fabio Rosa; Niccolò Rossi; Tiphaine C Martin; Robert P Mohney; Weizhong Li; Emanuele de Rinaldis; Jordana T Bell; J Craig Venter; Karen E Nelson; Tim D Spector; Mario Falchi
Journal:  Nat Commun       Date:  2019-10-03       Impact factor: 14.919

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