Tracking microeukaryotic footprint in a peri-urban watershed, China through machine-learning approaches

Mahmoud Gad; Liyuan Hou; Meixian Cao; Bob Adyari; Lanping Zhang; Dan Qin; Chang-Ping Yu; Qian Sun; Anyi Hu

doi:10.1016/j.scitotenv.2021.150401

Tracking microeukaryotic footprint in a peri-urban watershed, China through machine-learning approaches

Sci Total Environ. 2022 Feb 1;806(Pt 1):150401. doi: 10.1016/j.scitotenv.2021.150401. Epub 2021 Sep 17.

Authors

Mahmoud Gad¹, Liyuan Hou², Meixian Cao³, Bob Adyari⁴, Lanping Zhang³, Dan Qin⁵, Chang-Ping Yu⁶, Qian Sun⁵, Anyi Hu⁷

Affiliations

¹ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Water Pollution Research Department, National Research Centre, Giza 12622, Egypt.
² Department of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA.
³ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
⁴ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Environmental Engineering, Universitas Pertamina, Jakarta 12220, Indonesia.
⁵ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
⁶ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate Institute of Environmental Engineering, National Taiwan University, Taipei 106, Taiwan.
⁷ CAS Key Laboratory of Urban pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China. Electronic address: ayhu@iue.ac.cn.

PMID: 34562761
DOI: 10.1016/j.scitotenv.2021.150401

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.

Keywords: 18S rRNA amplicon sequencing; Changle River watershed; Microeukaryotic supergroup; Planktonic microeukaryotes; SourceTracker.

MeSH terms

Animals
China
Ecosystem*
Machine Learning
Plankton
Rivers*
Swine
Water Quality