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Comparison of two bioinformatics tools used to characterize the microbial diversity and predictive functional attributes of microbial mats from Lake Obersee, Antarctica.
Koo, Hyunmin; Hakim, Joseph A; Morrow, Casey D; Eipers, Peter G; Davila, Alfonso; Andersen, Dale T; Bej, Asim K.
Afiliação
  • Koo H; Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA. Electronic address: khmkhm87@uab.edu.
  • Hakim JA; Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Morrow CD; Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Eipers PG; Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, USA.
  • Davila A; NASA Ames Research Center, MS 245-3, Moffett Field, CA, USA.
  • Andersen DT; Carl Sagan Center, SETI Institute, Mountain View, CA, USA.
  • Bej AK; Department of Biology, University of Alabama at Birmingham, Birmingham, AL, USA. Electronic address: abej@uab.edu.
J Microbiol Methods ; 140: 15-22, 2017 09.
Article em En | MEDLINE | ID: mdl-28655556
ABSTRACT
In this study, using NextGen sequencing of the collective 16S rRNA genes obtained from two sets of samples collected from Lake Obersee, Antarctica, we compared and contrasted two bioinformatics tools, PICRUSt and Tax4Fun. We then developed an R script to assess the taxonomic and predictive functional profiles of the microbial communities within the samples. Taxa such as Pseudoxanthomonas, Planctomycetaceae, Cyanobacteria Subsection III, Nitrosomonadaceae, Leptothrix, and Rhodobacter were exclusively identified by Tax4Fun that uses SILVA database; whereas PICRUSt that uses Greengenes database uniquely identified Pirellulaceae, Gemmatimonadetes A1-B1, Pseudanabaena, Salinibacterium and Sinobacteraceae. Predictive functional profiling of the microbial communities using Tax4Fun and PICRUSt separately revealed common metabolic capabilities, while also showing specific functional IDs not shared between the two approaches. Combining these functional predictions using a customized R script revealed a more inclusive metabolic profile, such as hydrolases, oxidoreductases, transferases; enzymes involved in carbohydrate and amino acid metabolisms; and membrane transport proteins known for nutrient uptake from the surrounding environment. Our results present the first molecular-phylogenetic characterization and predictive functional profiles of the microbial mat communities in Lake Obersee, while demonstrating the efficacy of combining both the taxonomic assignment information and functional IDs using the R script created in this study for a more streamlined evaluation of predictive functional profiles of microbial communities.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Lagos / Biologia Computacional / Consórcios Microbianos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Microbiol Methods Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Lagos / Biologia Computacional / Consórcios Microbianos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Microbiol Methods Ano de publicação: 2017 Tipo de documento: Article