Back to Search Start Over

A Metagenomic Analysis of Bacterial Microbiota in the Digestive Tract of Triatomines.

Authors :
Carels, Nicolas
Gumiel, Marcial
da Mota, Fabio Faria
de Carvalho Moreira, Carlos José
Azambuja, Patricia
Source :
Bioinformatics & Biology Insights. Jan-Dec2017, Issue 11, p1-19. 19p.
Publication Year :
2017

Abstract

The digestive tract of triatomines (DTT) is an ecological niche favored by microbiota whose enzymatic profile is adapted to the specific substrate availability in this medium. This report describes the molecular enzymatic properties that promote bacterial prominence in the DTT. The microbiota composition was assessed previously based on 16S ribosomal DNA, and whole sequenced genomes of bacteria from the same genera were used to calculate the GC level of rare and prominent bacterial species in the DTT. The enzymatic reactions encoded by coding sequences of both rare and common bacterial species were then compared and revealed key functions explaining why some genera outcompete others in the DTT. Representativeness of DTT microbiota was investigated by shotgun sequencing of DNA extracted from bacteria grown in liquid Luria-Bertani broth (LB) medium. Results showed that GC-rich bacteria outcompete GC-poor bacteria and are the dominant components of the DTT microbiota. In addition, oxidoreductases are the main enzymatic components of these bacteria. In particular, nitrate reductases (anaerobic respiration), oxygenases (catabolism of complex substrates), acetate-CoA ligase (tricarboxylic acid cycle and energy metabolism), and kinase (signaling pathway) were the major enzymatic determinants present together with a large group of minor enzymes including hydrogenases involved in energy and amino acid metabolism. In conclusion, despite their slower growth in liquid LB medium, bacteria from GC-rich genera outcompete the GC-poor bacteria because their specific enzymatic abilities impart a selective advantage in the DTT. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
11779322
Issue :
11
Database :
Academic Search Index
Journal :
Bioinformatics & Biology Insights
Publication Type :
Academic Journal
Accession number :
127543606
Full Text :
https://doi.org/10.1177/1177932217733422