Insights from metagenomic, metatranscriptomic, and molecular ecological network analyses into the effects of chromium nanoparticles on activated sludge system

doi:10.1007/s11783-020-1239-8

Front. Environ. Sci. Eng.

2020, Vol. 14

Issue (4) : 60 https://doi.org/10.1007/s11783-020-1239-8

RESEARCH ARTICLE

Insights from metagenomic, metatranscriptomic, and molecular ecological network analyses into the effects of chromium nanoparticles on activated sludge system

Quan Zheng¹, Minglu Zhang², Tingting Zhang¹, Xinhui Li¹, Minghan Zhu¹, Xiaohui Wang¹(

)

¹. Beijing Engineering Research Center of Environmental Material for Water Purification, College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, China
². Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University, Beijing 100048, China

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Abstract

• Cr NPs significantly promoted the denitrifying process and phosphorus removal.

• The quantities of denitrifying and phosphorus genes greatly increased.

• The transcription of denitrifying and phosphorus genes greatly increased.

• The networks associated with nitrogen and phosphorus removal became complicated.

• Cr NPs decreased some genera related to GAOs.

The objectives of this study were to investigate the influence of chromium nanoparticles (Cr NPs) on the nitrogen and phosphorus removal performance and the bacterial structures of an activated sludge (AS) system. Also, we through molecular ecological networks (MENs) discussed the bacterial interactions. At last we researched the change of the functional genes and their expression patterns related to nitrogen and phosphorus removal in an AS system. The results showed that long-term exposure to 1 mg/L Cr NPs significantly promoted the denitrifying process and phosphorus removal in the AS system. The relative abundance of denitrifying and phosphorus removal microorganisms, such as Denitratisoma, Thauera, Dechloromonas, and Defluviicoccus, increased significantly. Candidatus Accumulibacter, well-known as polyphosphate-accumulating organisms (PAOs), increased significantly; the relative abundance of Candidatus Competibacter, known as glycogen-accumulating organisms (GAOs), decreased significantly. Furthermore, metagenomic and metatranscriptomic analysis revealed that most of the genera related to denitrifying and phosphorus removal had greatly increased, according to the quantities of denitrifying and phosphorus genes, and the corresponding transcription likewise greatly increased. Lastly, MENs analysis showed that although the overall network became smaller and looser in the presence of Cr NPs, the microbial connections among members related to nitrogen and phosphorus removal were enhanced. The abundance increases of denitrifiers and PAOs, and their increased transcription of functional genes, together with the enhanced interactions may be associated with the promotion of the denitrifying process and phosphorus removal.

Keywords Chromium nanoparticles (Cr NPs) Metagenomic analysis Metatranscriptomic analysis Molecular ecological networks (MENs) Nitrogen and phosphorus removal

Corresponding Author(s): Xiaohui Wang

Issue Date: 17 April 2020

Cite this article:

Quan Zheng,Minglu Zhang,Tingting Zhang, et al. Insights from metagenomic, metatranscriptomic, and molecular ecological network analyses into the effects of chromium nanoparticles on activated sludge system[J]. Front. Environ. Sci. Eng., 2020, 14(4): 60.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-020-1239-8
https://academic.hep.com.cn/fese/EN/Y2020/V14/I4/60

Fig.1 (A) XRD pattern of Cr NPs, (B) TEM image of Cr NPs, (C) Hydrodynamic particle size distribution of Cr NPs in deionized water (red line), influent (green line), and effluent (blue line).

Fig.2 Effects of Cr NPs on SBR performance. (A) COD, (B) NH₄⁺-N, (C) SOP, (D) NO₂^–-N and NO₃^–-N. The value of the performance were calculated by average in the three parallel reactors.

Fig.3 PCoA on OTU level of bacterial communities for both Cr NPs and control samples. The characters CK and Cr represent the samples from control check and Cr reactors, respectively.

Fig.4 Average relative abundance of bacterial composition at the phylum level in 20 samples. The characters CK and Cr represent the samples from control check and Cr NPs reactors, respectively. We calculated the average value within the 10 CK samples and 10 Cr samples respectively.

Fig.5 Heatmap of bacterial genera in the AS samples. The characters CK and Cr represent the samples from control check and Cr NPs reactors, respectively; the arabic number after the characters represents number of the parallel samples.

Fig.6 Effects of Cr NPs on the network interactions of the bacterial community. (A) and (B) show seven OTUs with the highest node degree on day 0 and the corresponding node degrees of these OTUs on the 160th day. (C) and (D) show seven OTUs with the highest node degree on the 160th day and the corresponding node degrees of the OTUs on day 0. The OTU circle size of nodes represent the node degree, the bigger OUT circle size means the higher node degree. The characters CK and Cr represent the samples from control check and Cr NPs reactors, respectively.

Fig.7 Relative abundance of nitrifying and denitrifying functional genes in the SBR system under Cr NPs stress. (A) shows the gene changes using metagenomic analysis. (B) shows the gene changes using metatranscriptomic analysis. We calculated the mean value of the three parallel reactor samples named CKMG, CrMG, CKMT, CrMT, respectively. The characters CK and Cr represent the samples from control check and Cr NPs reactors, respectively; the characters MG and MT represent metagenomic and metatranscriptomic, respectively.

Fig.8 Heatmap of the relative abundance of ppk1- and ppx-type genera in the SBR system. We calculated the mean value of the three parallel reactor samples named CKMG, CrMG, CKMT, CrMT, respectively. The characters CK and Cr represent the samples from control check and Cr NPs reactors, respectively; the characters MG and MT represent metagenomic and metatranscriptomic, respectively.

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