Tracking microeukaryotic footprint in a peri-urban watershed, China through machine-learning approaches
Journal
Science of the Total Environment
Journal Volume
806
Date Issued
2022
Author(s)
Abstract
Microeukaryotes play a significant role in biogeochemical cycling and can serve as bioindicators of water quality in freshwater ecosystems. However, there is a knowledge gap on how freshwater microeukaryotic communities are assembled, especially that how terrestrial microeukaryotes influence freshwater microeukaryotic assemblages. Here, we used a combination of 18S rRNA gene amplicon sequencing and community-based microbial source tracking (MST) approaches (i.e., SourceTracker and FEAST) to assess the contribution of microeukaryotes from surrounding environments (i.e., soils, river sediments, swine wastewater, influents and effluents of decentralized wastewater treatment plants) to planktonic microeukaryotes in the main channel, tributaries and reservoir of a peri-urban watershed, China in wet and dry seasons. The results indicated that SAR (~ 49% of the total communities), Opithokonta (~ 34%), Archaeplastida (~ 9%), and Amoebozoa (~ 2%) were dominant taxa in the watershed. The community-based MST analysis revealed that sewage effluents (7.96 – 21.84%), influents (2.23 – 13.97%), and river sediments (2.56 – 11.71%) were the major exogenous sources of riverine microeukaryotes. At the spatial scale, the downstream of the watershed (i.e., main channel and tributaries) received higher proportions of exogenous microeukaryotic OTUs compared to the upstream reservoirs, while at the seasonal scale, the sewage effluents and influents contributed higher exogenous microeukaryotes to river water in wet season than in dry season. Moreover, the swine and domestic wastewater led to the presence of Apicomplexa in wet season only, implying rainfall runoff may enhance the spread of parasitic microeukaryotes. Taken together, our study provides novel insights into the immigration patterns of microeukaryotes and their dominant supergroups between terrestrial and riverine habitats. ? 2021 Elsevier B.V.
Subjects
18S rRNA amplicon sequencing
Changle River watershed
Microeukaryotic supergroup
Planktonic microeukaryotes
SourceTracker
Drought
Effluents
Machine learning
Reservoirs (water)
Rivers
RNA
Sediments
Sewage
Wastewater treatment
Water quality
18s rRNA
18s rRNA amplicon sequencing
Amplicons
Changle
Changle river watershed
Micro-eukaryotes
Planktonic microeukaryote
River watersheds
Sourcetracker
Watersheds
RNA 18S
computer simulation
gene expression
machine learning
microbial community
river pollution
river water
water quality
watershed
Amoebozoa
amplicon
Apicomplexa
Archaeplastida
Article
China
domestic waste
eukaryote
microeukaryote
nonhuman
Opithokonta
pig
plankton
river
RNA sequencing
seasonal variation
sediment
sewage effluent
species habitat
animal
ecosystem
Changle River
Zhejiang
Animals
Ecosystem
Machine Learning
Plankton
Swine
Water Quality
Type
journal article