Literature DB >> 29624889

PhyMet2 : a database and toolkit for phylogenetic and metabolic analyses of methanogens.

Burdukiewicz Michał1, Przemysław Gagat1, Sławomir Jabłoński2, Jarosław Chilimoniuk1, Michał Gaworski2, Paweł Mackiewicz1, Łukaszewicz Marcin2.   

Abstract

The vast biodiversity of the microbial world and how little is known about it, has already been revealed by extensive metagenomics analyses. Our rudimentary knowledge of microbes stems from difficulties concerning their isolation and culture in laboratory conditions, which is necessary for describing their phenotype, among other things, for biotechnological purposes. An important component of the understudied ecosystems is methanogens, archaea producing a potent greenhouse-effect gas methane. Therefore, we created PhyMet2 , the first database that combines descriptions of methanogens and their culturing conditions with genetic information. The database contains a set of utilities that facilitate interactive data browsing, data comparison, phylogeny exploration and searching for sequence homologues. The most unique feature of the database is the web server MethanoGram, which can be used to significantly reduce the time and cost of searching for the optimal culturing conditions of methanogens by predicting them based on 16S RNA sequences. The database will aid many researchers in exploring the world of methanogens and their applications in biotechnological processes. PhyMet2 with the MethanoGram predictor is available at http://metanogen.biotech.uni.wroc.pl.
© 2018 The Authors. Environmental Microbiology published by Society for Applied Microbiology and JohnWiley & Sons Ltd.

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Year:  2018        PMID: 29624889     DOI: 10.1111/1758-2229.12648

Source DB:  PubMed          Journal:  Environ Microbiol Rep        ISSN: 1758-2229            Impact factor:   3.541


  5 in total

1.  A bioenergetic model to predict habitability, biomass and biosignatures in astrobiology and extreme conditions.

Authors:  P M Higgins; C S Cockell
Journal:  J R Soc Interface       Date:  2020-10-21       Impact factor: 4.118

2.  Proteomic Screening for Prediction and Design of Antimicrobial Peptides with AmpGram.

Authors:  Michał Burdukiewicz; Katarzyna Sidorczuk; Dominik Rafacz; Filip Pietluch; Jarosław Chilimoniuk; Stefan Rödiger; Przemysław Gagat
Journal:  Int J Mol Sci       Date:  2020-06-17       Impact factor: 5.923

3.  Prebiotics and Community Composition Influence Gas Production of the Human Gut Microbiota.

Authors:  Xiaoqian Yu; Thomas Gurry; Le Thanh Tu Nguyen; Hunter S Richardson; Eric J Alm
Journal:  mBio       Date:  2020-09-08       Impact factor: 7.867

4.  Seeding Biochemistry on Other Worlds: Enceladus as a Case Study.

Authors:  Harrison B Smith; Alexa Drew; John F Malloy; Sara Imari Walker
Journal:  Astrobiology       Date:  2020-10-16       Impact factor: 4.335

5.  Redox Potential Heterogeneity in Fixed-Bed Electrodes Leads to Microbial Stratification and Inhomogeneous Performance.

Authors:  Jose Rodrigo Quejigo; Benjamin Korth; Anne Kuchenbuch; Falk Harnisch
Journal:  ChemSusChem       Date:  2021-01-19       Impact factor: 8.928

  5 in total

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