Different response of bacterial community to the changes of nutrients and pollutants in sediments from an urban river network

doi:10.1007/s11783-019-1207-3

Front. Environ. Sci. Eng.

2020, Vol. 14

Issue (2) : 28 https://doi.org/10.1007/s11783-019-1207-3

RESEARCH ARTICLE

Different response of bacterial community to the changes of nutrients and pollutants in sediments from an urban river network

Fang Zhang¹, Hao Zhang¹, Ying Yuan¹, Dun Liu¹, Chenyu Zhu¹, Di Zheng¹, Guanghe Li¹, Yuquan Wei²(

), Dan Sun³(

)

¹. School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
². College of Resource and Environmental Science, China Agricultural University, Beijing 100193, China
³. Ocean College, Zhejiang University, Zhoushan 316021, China

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Abstract

• Bacterial community varied spatially in sediments from the urban river network.

• Key environmental factors shaping bacterial community were detected by RDA.

• Bacterial co-occurrence networks changed at different levels of nutrient and metal.

• Potential indicator species were selected to predict pollution risk in sediment.

Microbial communities in sediment are an important indicator linking to environmental pollution in urban river systems. However, how the diversity and structure of bacterial communities in sediments from an urban river network respond to different environmental factors has not been well studied. The goal of this study was to understand the patterns of bacterial communities in sediments from a highly dense urbanized river network in the lower Yangtze River Delta by Illumina MiSeq sequencing. The correlations between bacterial communities, the environmental gradient and geographical distance were analyzed by redundancy analysis (RDA) and network methods. The diversity and richness of bacterial community in sediments increased from upstream to downstream consistently with the accumulation of nutrient in the urban river network. Bacterial community composition and structure showed obvious spatial changes, leading to two distinct groups, which were significantly related to the characteristics of nutrient and heavy metal in sediments. Humic substance, available nitrogen, available phosphorus, Zn, Cu, Hg and As were selected as the key environmental factors shaping the bacterial community in sediments based on RDA. The co-occurrence patterns of bacterial networks showed that positive interaction between bacterial communities increased but the connectivity among bacterial genera and stability of sediment ecosystem reduced under a higher content of nutrient and heavy metal in average. The sensitive and ubiquitous taxa with an overproportional response to key environmental factors were detected as indicator species, which provided a novel method for the prediction of the pollution risk of sediment in an urban river network.

Keywords Sediment Urban river network Bacterial community Network analysis Indicator species

Corresponding Author(s): Yuquan Wei,Dan Sun

Issue Date: 13 January 2020

Cite this article:

Fang Zhang,Hao Zhang,Ying Yuan, et al. Different response of bacterial community to the changes of nutrients and pollutants in sediments from an urban river network[J]. Front. Environ. Sci. Eng., 2020, 14(2): 28.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-019-1207-3
https://academic.hep.com.cn/fese/EN/Y2020/V14/I2/28

Fig.1 The locations of the sampling sites. The black solid dots represent the sampling points where the sediments were taken in the unban river network.

Fig.2 Distribution of total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) contents in the sediments of unban river network. The columns in the diagram indicate the mean values (n = 3).

Fig.3 The concentration of different heavy metal in each spot in sediments.

Fig.4 Community composition of bacteria in (a) the phylum level and (b) the class level in sediment samples. (c) Nonmetric multidimensional scaling (NMDS) plot depicts the distance of bacterial communities in sediment samples at genus level. (d) ANOSIM analysis of similarities for two selected groups (differences between groups and differences within groups). * P<0.05; ** P<0.01.

Fig.5 Relationship between (a) Bray-Curtis dissimilarity of bacterial communities and geographic distance, (b) Bray-Curtis dissimilarity of bacterial communities and metal characteristics, (c) geographic distance and nutrient characteristics, (d) geographic distance and metal characteristics in the sediment samples of unban river network.

Fig.6 (a) Partitioning of variation in bacterial community in the sediment samples of unban river network explained by two sets of independent variables, nutrient and metal characteristics. (b) Redundancy analysis (RDA) of the correlation between primary bacterial phyla and significant environmental factors.

Fig.7 Node connectedness and distribution of bacterial networks. (a) Bacterial species interactions (degree) in the group 2 decreased compared to group 1. (b) Positive connectedness of bacterial communities in the group 2 increased compared to group 1. (c) Comparison of the abundance of the key bacterial genera in two groups that were both significantly related to the key factors of nutrient or metal and included in co-occurrence networks. Lines in boxes represent median, top and bottom of boxes represent first and third quartiles, and whiskers represent 1.5 interquartile range; dots represent single observations. Boxes with the same lower-case letters are not statistically different. Asterisks indicate the significance of the difference (*P<0.05, **P<0.01).

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