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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

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2018 Impact Factor: 3.883

Front. Environ. Sci. Eng.    2019, Vol. 13 Issue (6) : 90
Identifying human-induced influence on microbial community: A comparative study in the effluent-receiving areas in Hangzhou Bay
Yuhan Zheng1, Zhiguo Su2, Tianjiao Dai2, Feifei Li1, Bei Huang3, Qinglin Mu3, Chuanping Feng1(), Donghui Wen2()
1. School of Water Resource and Environmental Science, China University of Geosciences (Beijing), Beijing 100083, China
2. College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
3. Zhejiang Provincial Zhoushan Marine Ecological Environmental Monitoring Station, Zhoushan 316021, China
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Microbial compositions showed high differences in two study areas.

COD was the key anthropogenic indicator in the coastal wastewater disposal area.

Distinctive microbes capable of degrading toxic pollutants were screened.

Microbial communities in effluent-receiving areas followed “niche theory”.

Microbial community structure is affected by both natural processes and human activities. In coastal area, anthropegenetic activity can usually lead to the discharge of the effluent from wastewater treatment plant (WWTP) to sea, and thus the water quality chronically turns worse and marine ecosystem becomes unhealthy. Microorganisms play key roles in pollutants degradation and ecological restoration; however, there are few studies about how the WWTP effluent disposal influences coastal microbial communities. In this study, sediment samples were collected from two WWTP effluent-receiving areas (abbreviated as JX and SY) in Hangzhou Bay. First, based on the high-throughput sequencing of 16S rRNA gene, microbial community structure was analyzed. Secondly, several statistical analyses were conducted to reveal the microbial community characteristics in response to the effluent disposal. Using PCoA, the significant difference of in microbial community structure was determined between JX and SY; using RDA, water COD and temperature, and sediment available phosphate and ammonia nitrogen were identified as the key environmental factors for the community difference; using LDA effect size analysis, the most distinctive microbes were found and their correlations with environmental factors were investigated; and according to detrended beta-nearest-taxon-index, the sediment microbial communities were found to follow “niche theory”. An interesting and important finding was that in SY that received more and toxic COD, many distinctive microbes were related to the groups that were capable of degrading toxic organic pollutants. This study provides a clear illustration of eco-environmental deterioration under the long-term human pressure from the view of microbial ecology.

Keywords Microbial community structure      Effluent-receiving area      High-throughput sequencing      Costal sediments      Wastewater treatment plant (WWTP)     
Corresponding Authors: Chuanping Feng,Donghui Wen   
Issue Date: 29 November 2019
 Cite this article:   
Yuhan Zheng,Zhiguo Su,Tianjiao Dai, et al. Identifying human-induced influence on microbial community: A comparative study in the effluent-receiving areas in Hangzhou Bay[J]. Front. Environ. Sci. Eng., 2019, 13(6): 90.
Site Longitude (E) Latitude (N)
JX1 121°02′32″ 30°36′4″
JX2 121°02′41″ 30°33′34″
JX3 121°02′54″ 30°33′12″
JX4 121°02′57″ 30°34′7″
JX5 121°3′22″ 30°33′52″
JX6 121°3′40″ 30°33′34″
JX7 121°3′40″ 30°33′24″
JX8 121°3′48″ 30°34′6″
JX9 121°3′56″ 30°33′43″
SY1 120°51′43″ 30°13′5″
SY2 120°51′11″ 30°12′50″
SY3 120°51′8″ 30°12′56″
SY4 120°51′32″ 30°12′55″
SY5 120°52′9″ 30°13′1″
SY6 120°51′59″ 30°13′7″
Tab.1  The locations of the sampling sites
Fig.1  Boxplot of environmental factors in JX (red) and SY (green): (a) Seawater and (b) sediments.
Fig.2  The microbial community structures and taxonomic compositions at (a) phylum level and (b) class level.
Fig.3  Principal coordinate analysis (PCoA) of the microbial community compositions based on Bray-Curtis distance.
Fig.4  Redundancy analysis (RDA) between the microbial compositions and the environmental factors. Red arrows indicate environment factors. Gray points represent sampling sites.
Fig.5  Indicators of microbial classes or genera in JX and SY with LDA values higher than 2.0, and their Pearson correlations with the environmental factors: red is negatively correlated, blue is positively correlated, and circle size indicates the size of the correlation.
Fig.6  Boxplot of beta nearest taxon Index (bNTI) in JX and SY.
Area Microbes Reported characteristics References
SY Novosphingobium Aromatic-compound-degrading Sohn et al. (2004); Liu et al. (2005)
Dechloromonas Aromatic-compound-degrading Salinero et al. (2009)
Acidovorax Phenanthrene-degrading;
Degradation of chlorobenzenes
Monferrán et al. (2005); Singleton et al. (2009)
Polaromonas Hydrocarbon- and xenobiotic-degrading bacterium;
Naphthalene-degrading bacterium;
Benzene degraders
Jeon et al. (2004); Mattes et al. (2008); Xie et al. (2011)
Vogesella Degradation of peptidoglycan Jørgensen et al. (2010)
Aquabacterium Oil-degrading bacterium;
Dominant member in hydrocarbon-contaminated environment;
Jechalke et al. (2013); Masuda et al. (2014)Pham et al. (2015);
Rhodoferax Photosynthetic bacteria;
Degrade phenoxypropionate derivatives
Ehrig et al. (1997)
Limnohabitans Photosynthetic bacteria Zeng et al. (2012); Kasalický et al. (2017)
Pseudomonas High natural resistance to beta-lactam antibiotics Van Eldere (2003)
JX Rhodovibrio Halophiles Makhdoumi-Kakhki et al. (2012); Ntougias (2014)
Tab.2  Characteristics about the differential microbes reported in literatures
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