污水地下渗滤系统微生物代谢组学分析

Abstract
Figure/Table
References (25)
Related Citation (15)

Download: PDF (683 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Based on metabolomics method, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was used to screen potential biomarkers of subsurface infiltration systems under different organic loads. The samples were typed by partial least squares (PLS-DA) and principal component analysis (PCA) pattern recognition methods, and potential biomarkers were screened according to the model's variable importance factor (VIP). Furthermore, biological information involved in metabolites and metabolic pathways were revealed. Finally, correlation between metabolites and environmental factors was explored by RDA analysis. The results of PLS-DA model showed that when the influent organic load gradually increased from 250mg/L to 400mg/L and 500mg/L, there was a significant difference between the metabolites in the same soil profile. A total of 230differential metabolites with a VIP value greater than 1.5 were screened out, which were mainly composed of organic acids, such as lactic acid, tartronic acid, dioleoylphosphatidic acid. The microbial metabolites had a significant correspondence with the soil profile. Under the condition of hydraulic load 0.14m³/(m²·d) and COD 400mg/L, 53metabolites with a VIP value greater than 1.5 were screened out from H2 (500mm), H4 (1000mm) and H6 (1500mm), respectively, which was mainly composed of acid and ketone substances, such as 6-Hydroxyondansetron sulfate, 19-Norandrosterone glucuronide and Methylcarbamyl PAF C-8. The results of RDA suggested that with the variation of pollution load and substrate profile, metabolites were negatively influenced by oxidation reduction potential (ORP) and nitrate (NO₃^-).

Key words： subsurface wastewater infiltration system metabolomics microorganism potential biomarke

Received: 29 April 2019

PACS:

X523

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	YANG Lei
	LI Ying-hua
	LI Hai-bo
	SU Fei

Cite this article:

YANG Lei,LI Ying-hua,LI Hai-bo等. Microbial metabolomics analysis of subsurface wastewater infiltration system[J]. CHINA ENVIRONMENTAL SCIENCECE, 2019, 39(11): 4812-4822.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2019/V39/I11/4812

[1]	Yang Z Z, Zhang S, Li C J, et al. Study on mechanism of nitrogen and phosphorus removal in matrix mixing subsurface wastewater infiltration system[J]. Water Treatment Technology, 2016,42(1):56-61.
[2]	Pan J. Study on microbial diversity and enzyme activity of subsurface wastewater infiltration system[D]. Shenyang:Northeastern University, 2009.
[3]	Li Y H, Li H B, Yang C, et al. Characteristics of decontamination and release of N2O in subsurface wastewater infiltration system under nitrogen load fluctuation[J]. Journal of Safety and Environment, 2018, 18:270-273.
[4]	Badri D V, Chaparro J M, Zhang R F, et al. Application of natural blends of phytochemicals derived from the root exudates of arabidopsis to the soil reveal that phenolicrelated compounds predominantly modulate the soil microbiome[J]. Journal of Biological Chemistry, 2013,288:4502-4512.
[5]	Wang X, Sun T H, Li H B, et al. Nitrogen removal enhanced by shunt distributing wastewater in a subsurface wastewater infiltration system[J]. Ecological Engineering, 2010,36:1433-1438.
[6]	Pan J, Yuan F, Huang L L, et al. Nitrogen removal in subsurface wastewater infiltration system with and without intermittent aeration[J]. Ecological Engineering, 2016,94:471-477.
[7]	Tan Y F. Molecular mechanism of nitrogen-transformation microecological processes in multi-media ecological treatment systems[D]. Beijing:Peking University, 2011.
[8]	Guo Y Z, Zhao Y P, Zhu T T, et al. A metabolomic view of how low nitrogen strength favors anammox biomass yield and nitrogen removal capability[J]. Water Research, 2018,143:387-398.
[9]	Justyna A, Hubert B, Jacek N, et al. Main strategies, analytical trends and challenges in LC-MS and ambient mass spectrometry-based metabolomics[J]. Trends in Analytical Chemistry, 2018,108:278-295.
[10]	Ma J F. ORP value variation characteristics of underground infiltration system[D]. Shenyang:Northeastern University, 2014.
[11]	Duan Y L, Li Y H, Li H B, et al. Influence of hydraulic load on microbial distribution and N2O release in subsurface infiltration system[J]. Chinese Journal of Environmental Engineering, 2016, 10(11):6431-6438.
[12]	Wang M M, Cheng H T, Xue M, et al. Cell metabolomics analysis process and technology based on combined nuclear magnetic resonance and mass spectrometry techniques[J]. International Journal of Pharmaceutical Research, 2011,38(2):130-136.
[13]	Paola M, Giovanna F. Modeling of the microbial inactivation by high hydrostatic pressure freezing[J]. Food Control, 2017,73:8-17.
[14]	Wang B B, Teng Y, Xu Y F, et al. Effect of mixed soil microbiomes on pyrene removal and the response of the soil microorganisms[J]. Science of the Total Environment, 2018,640:9-17.
[15]	Shen G A, Duan L X, Qi X Q. Plant Metabolomics Data Analysis and Database[J]. Life Science, 2015,8:996-999.
[16]	David E G, Edward E B, Peter I B, et al. Separation and mass spectrometry in microbial metabolomics[J]. Science Direct, 2008,11:233-239.
[17]	Malgorzata P, Julia J, Michal J M. Sample preparation procedures utilized in microbial metabolomics:An overview[J]. Chromatography B, 2017,1043:150-157.
[18]	Shao T T, Miki K, Yasummune N, et al. Random sample consensus combined with partial least squares regression (RANSAC-PLS) for microbial metabolomics data mining and phenotype improvement[J]. Bioscience and Bioengineering, 2016,122:168-175.
[19]	Cui C Y, Ma L M, Zhao J F. Study on Microbial Characteristics of Artificial Rapid Infiltration System[J]. China Population Resources and Environment, 2008,18:539-541.
[20]	Wang Y Q, Zhang W J, Nie C X, et al. Evaluation of sample extracting methods of FCSM by Lactobacillus acidophilus based on a UPLC-Q-TOF-MS global metabolomics analysis[J]. Biotechnology and Industrial Microbiology, 2018,49:392-400.
[21]	Xiao R, Ma Y, Zhang D J, et al. Discrimination of conventional and organic rice using untargeted LC-MS-based metabolomics[J]. Cereal Science, 2018,82:73-81.
[22]	Li Y H, Li H B, Wang X, et al. Denitrification of domestic sewage by biological packing underground infiltration system[J]. Chinese Journal of Environmental Engineering, 2013,7(9):3369-3374.
[23]	Yang X H, Gu J F. Advances in research on soil microbes and their metabolites in mangrove forests[J]. International Pharmaceutical Antibiotics, 2011,32(3):97-102.
[24]	Zhang P J, Li Y M, Zhang Y N, et al. Application and prospect of toxicity quality markers of Chinese materia medica based on metabolomics[J]. Chinese Herbal Medicines, 2018,10:108-116.
[25]	Tong L L. Discussion on the application of RDA analysis in CANOCO4.5 in water ecological assessment[J]. Environmental Science, 2018,1:45-47.