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

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.

Assessing Freshwater Microbiomes from Different Storage Sources in the Caribbean Using DNA Metabarcoding

“…At the phylum level, we detected Proteobacteria and Bacteroidetes at a high relative abundance in our cistern sample. Similar results have been detected in freshwater and domestic sewage sludges from China, Brazil, and Peru [7,[17][18][19][20][21]. The abundance of metabolically active Proteobacteria has been related to global nitrogen, carbon, and sulfur cycling [22].…”

“…General taxonomic surveys and pathogen detection were the focus of a large proportion of these [2]. Recent studies have reported the use of metagenomics or metabarcoding to investigate seasonal variation of cyanobacteria in drinking water reservoirs [3], the microbiome of tap water and bottled mineral water [4], the presence of pathogenic bacteria in private well water and premises plumbing [5], the microbiome of rainwater tanks [6], and the microbiome of a river used as a source of drinking water [7].…”

Monitoring Bacterial Community Dynamics in a Drinking Water Treatment Plant: An Integrative Approach Using Metabarcoding and Microbial Indicators in Large Water Volumes

“…Changes in microbial communities related to ambient temperature were also observed in different treatment stages, with a correlation of higher diversity with higher temperatures, specially at DEC and CF. Such temporal variability has been widely described [10,13,14,67]. Higher temperatures can trigger changes in bacterial communities, as they facilitate bacterial growth of different genera.…”

“…High-throughput sequencing techniques, such as 16S rRNA metabarcoding, have the potential to provide in-depth information that complements standard bacterial quality parameters, and they can help to generate a more accurate picture of microbial communities at different water treatment stages. Several water microbiome studies based on 16S rRNA amplicon sequencing have described microbial composition in DWTPs and distribution networks, which differs according to the water source (e.g., river [10][11][12][13][14], lake [15], groundwater [13,16] or seawater [17]).…”

Fine-Tuning of DADA2 Parameters for Multiregional Metabarcoding Analysis of 16S rRNA Genes from Activated Sludge and Comparison of Taxonomy Classification Power and Taxonomy Databases

“…Metabarcoding is usually used in environmental microbiology to classify bacteria at different taxonomic levels, detect the occurrence of taxonomic groups over time, seek differences between samples taken under different conditions, and determine biodiversity within or between samples. For example, the V3–V4 region was used to perform taxonomic classification and deeper analysis in studies that focused on tropical warm springs and different areas of the Rimac river [ 3 , 4 ]. In other examples, the V4–V5 region was used to study the microbial communities in rainwater and precipitation in a forest area and to compare five different ways to extract DNA from marine bacterial communities [ 5 , 6 ].…”