Amoeba community dynamics and assembly mechanisms in full-scale drinking water distribution networks under various disinfectant regimens

Yuxing Hu; Kaiyang Jiang; Siqing Xia; Weixian Zhang; Jianhua Guo; Hong Wang

doi:10.1016/j.watres.2024.122861

Amoeba community dynamics and assembly mechanisms in full-scale drinking water distribution networks under various disinfectant regimens

Water Res. 2024 Nov 26:271:122861. doi: 10.1016/j.watres.2024.122861. Online ahead of print.

Authors

Yuxing Hu¹, Kaiyang Jiang², Siqing Xia³, Weixian Zhang², Jianhua Guo⁴, Hong Wang⁵

Affiliations

¹ State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China; Australian Centre for Water and Environmental Biotechnology (ACWEB, formerly AWMC), The University of Queensland, St Lucia, Queensland 4072, Australia.
² State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.
³ State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
⁴ Australian Centre for Water and Environmental Biotechnology (ACWEB, formerly AWMC), The University of Queensland, St Lucia, Queensland 4072, Australia.
⁵ State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China. Electronic address: hongwang@tongji.edu.cn.

PMID: 39615115
DOI: 10.1016/j.watres.2024.122861

Abstract

Free-living amoebae (FLA) are prevalent in drinking water distribution networks (DWDNs), yet our understanding of FLA community dynamics and assembly mechanisms in DWDNs remains limited. This study characterized the occurrence patterns of amoeba communities and identified key factors influencing their assembly across four full-scale DWDNs in three Chinese cities, each utilizing different disinfectants (chlorine, chloramine, and chlorine dioxide). High-throughput sequencing of full-length 18S rRNA genes revealed highly diverse FLA communities and an array of rare FLA species in DWDNs. Unique FLA community structures and higher gene copy numbers of three amoeba taxa of concern (Vermamoeba vermiformis, Acanthamoeba, and Naegleria fowleri) were observed in the chloraminated DWDN, highlighting the distinct impact of chloramine on shaping the amoeba community. The FLA communities in DWDNs were primarily driven by deterministic processes, with disinfectant and nitrogen compounds (nitrate, nitrite, and ammonia) identified as the main influencing factors. Machine learning models revealed high SHapley Additive exPlanations (SHAP) values of dominant amoeba genera (e.g., Vannella and Vermamoeba), indicating their critical ecological roles in shaping broader bacterial and eukaryotic communities. Correlation analyses between amoeba genera and bacterial taxa revealed that 82 % of the bacterial taxa exhibiting a negative correlation with amoebae were gram-negative, suggesting the preferred predation of amoebae toward gram-negative bacteria. Network analysis revealed the presence of only one to two amoebae in distinct modules, suggesting that individual amoebae might be selective in grazing. These findings provide insight into the amoeba community dynamics, assembly mechanisms and ecological roles of amoebae in drinking water, which can aid in risk assessments and mitigation strategies within DWDNs.

Keywords: Amoeba community; Community assembly mechanism; Disinfectant; Ecological interaction; Machine learning model.