Metataxonomic and metagenomic analysis of mangrove microbiomes reveals community patterns driven by salinity and pH gradients in Paranaguá Bay, Brazil

Sci Total Environ. 2019 Dec 1:694:133609. doi: 10.1016/j.scitotenv.2019.133609. Epub 2019 Jul 27.

Abstract

While environmental drivers regulate the structure of mangrove microbial communities, their exact nature and the extent of their influence require further elucidation. By means of 16S rRNA gene-based sequencing, we determined the microbial taxonomic profiles of mangroves in the subtropical Paranaguá Bay, Brazil, considering as potential drivers: salinity, as represented by two sectors in the extremes of a salinity gradient (<5 PSU and >30 PSU); proximity to/absence of the prevailing plants, Avicennia schaueriana, Laguncularia racemosa, Rhizophora mangle, and Spartina alterniflora; and the chemical composition of the sediments. Salinity levels within the estuary had the strongest influence on microbial structure, and pH was important to separate two communities within the high salinity environment. About one fourth of the total variation in community structure resulted from covariation of salinity and the overall chemical composition, which might indicate that the chemical profile was also related to salinity. The most prevalent bacterial phyla associated with the mangrove soils analyzed included Proteobacteria, Actinobacteria, Chloroflexi, Bacteroidetes, Acidobacteria, and Cyanobacteria. Taxonomic and functional comparisons of our results for whole-genome sequencing with available data from other biomes showed that the studied microbiomes cluster first according to biome type, then to matrix type and salinity status. Metabolic functions were more conserved than organisms within mangroves and across all biomes, indicating that core functions are preserved in any of the given conditions regardless of the specific organisms harboring them.

Keywords: Functional structure; Mangrove; Microbial community; Paranaguá Bay; Taxonomic structure.

MeSH terms

  • Bays / chemistry
  • Bays / microbiology*
  • Brazil
  • Environmental Monitoring*
  • Hydrogen-Ion Concentration
  • Metagenomics*
  • Microbiota*
  • Salinity*