From the Andes to the desert: 16S rRNA metabarcoding characterization of aquatic bacterial communities in the Rimac river, the main source of water for Lima, Peru

PLoS One. 2021 Apr 22;16(4):e0250401. doi: 10.1371/journal.pone.0250401. eCollection 2021.

Abstract

The Rimac river is the main source of water for Lima, Peru's capital megacity. The river is constantly affected by different types of contamination including mine tailings in the Andes and urban sewage in the metropolitan area. In this work, we aim to produce the first characterization of aquatic bacterial communities in the Rimac river using a 16S rRNA metabarcoding approach which would be useful to identify bacterial diversity and potential understudied pathogens. We report a lower diversity in bacterial communities from the Lower Rimac (Metropolitan zone) in comparison to other sub-basins. Samples were generally grouped according to their geographical location. Bacterial classes Alphaproteobacteria, Bacteroidia, Campylobacteria, Fusobacteriia, and Gammaproteobacteria were the most frequent along the river. Arcobacter cryaerophilus (Campylobacteria) was the most frequent species in the Lower Rimac while Flavobacterium succinicans (Bacteroidia) and Hypnocyclicus (Fusobacteriia) were the most predominant in the Upper Rimac. Predicted metabolic functions in the microbiota include bacterial motility and quorum sensing. Additional metabolomic analyses showed the presence of some insecticides and herbicides in the Parac-Upper Rimac and Santa Eulalia-Parac sub-basins. The dominance in the Metropolitan area of Arcobacter cryaerophilus, an emergent pathogen associated with fecal contamination and antibiotic multiresistance, that is not usually reported in traditional microbiological quality assessments, highlights the necessity to apply next-generation sequencing tools to improve pathogen surveillance. We believe that our study will encourage the integration of omics sciences in Peru and its application on current environmental and public health issues.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aquatic Organisms / genetics*
  • Arcobacter / genetics*
  • Computational Biology / methods
  • DNA Barcoding, Taxonomic / methods*
  • Environmental Monitoring / methods
  • Flavobacterium / genetics*
  • Fusobacteria / genetics*
  • Microbiota / genetics*
  • Peru
  • RNA, Ribosomal, 16S / genetics*
  • Rivers / microbiology*
  • Sewage / microbiology
  • Water / analysis
  • Water Microbiology
  • Water Pollution / analysis

Substances

  • RNA, Ribosomal, 16S
  • Sewage
  • Water

Supplementary concepts

  • Arcobacter cryaerophilus
  • Flavobacterium succinicans

Grants and funding

This work was funded by the Facultad de Medicina Humana (Universidad de Piura) [grant number PI2002, “Metabarcoding del Río Rímac, el principal afluente de la ciudad de Lima”]; GenLab del Perú SAC [Programa de Incentivos 2019, “Aplicaciones de la secuenciación masiva (NGS) en metagenómica y secuenciación de genes”]; and the Max Planck Society [Max Planck Partner Groups: Chemical-Ecology + Pontificia Universidad Católica del Perú]. Additionally, PER was funded by the Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt - Perú) [grant number 34-2019, “Proyecto de Mejoramiento y Ampliación de los Servicios del Sistema Nacional de Ciencia, Tecnología e Innovación Tecnológica”]. JLR received a grant from Concytec - Banco Mundial, through the Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica (Fondecyt) [grant number 022-2019]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. PW works for Universidad de Piura.