WO2023098239A1 - Procédé d'évaluation de la santé d'un écosystème de cours d'eau basé sur une réponse spécifique de la communauté microbienne - Google Patents

Procédé d'évaluation de la santé d'un écosystème de cours d'eau basé sur une réponse spécifique de la communauté microbienne Download PDF

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WO2023098239A1
WO2023098239A1 PCT/CN2022/120048 CN2022120048W WO2023098239A1 WO 2023098239 A1 WO2023098239 A1 WO 2023098239A1 CN 2022120048 W CN2022120048 W CN 2022120048W WO 2023098239 A1 WO2023098239 A1 WO 2023098239A1
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microorganisms
microbial
cod
water
water quality
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PCT/CN2022/120048
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English (en)
Chinese (zh)
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许玫英
杨山
林立洲
董美君
杨旭楠
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广东省科学院微生物研究所(广东省微生物分析检测中心)
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Publication of WO2023098239A1 publication Critical patent/WO2023098239A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
    • C02F3/00—Biological treatment of water, waste water, or sewage
    • C02F3/34—Biological treatment of water, waste water, or sewage characterised by the microorganisms used
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/20—Polymerase chain reaction [PCR]; Primer or probe design; Probe optimisation
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A20/00—Water conservation; Efficient water supply; Efficient water use
    • Y02A20/152—Water filtration

Definitions

  • the invention belongs to the technical field of water body environment monitoring and protection, and in particular relates to a river ecosystem health evaluation method based on the specific response of microbial communities.
  • River ecosystems provide important service functions such as water resources, food, and shipping for human and urban development. With the intensification of human disturbance, water pollution and deterioration occur frequently, seriously threatening the health of river ecosystems. Researching and establishing health assessment methods for river ecosystems is an important basic support for long-term monitoring, development and utilization of river ecosystems, as well as pollution control and restoration.
  • Microorganisms are the decomposers and important producers of the ecosystem. They play an important role in the control and restoration of environmental pollution. They are very sensitive to changes in the surrounding environmental conditions. Their diversity and community structure are closely related to the health of the ecosystem.
  • the use of microbial communities as an indicator of ecosystem health has the following advantages: First, different types of microorganisms have different tolerances and resistances to different pollutants and environmental changes, and changes in the abundance and functional activities of specific microorganisms can be used for health evaluation. Provide important information; secondly, because microorganisms in the ecosystem function in the form of communities, changes in the structure and function of microbial communities can more accurately reflect changes in the health of the ecosystem.
  • the present invention utilizes the specific response characteristics of sensitive microorganisms to environmental changes and combines the uniqueness of microbial ecological niches to establish a scientific and reasonable index system to ensure the objectivity and practicability of index weights.
  • the purpose of the present invention is to provide a method for evaluating the health of river ecosystems based on the specific response of microbial communities.
  • the method of the present invention is highly directional, indicating characteristic pollutants by utilizing changes in the structure and function of specific microbial groups.
  • the river ecosystem health evaluation method based on microbial community specific response of the present invention comprises the following steps:
  • step b is:
  • n is the number of selected factors
  • SIi is the factor score
  • microbial susceptibility is classified as follows:
  • yi is the relative abundance of microorganisms
  • xi is an environmental parameter
  • s1(x1), s2(x2) are non-parametric smooth functions
  • Log() is an example of a correlation function
  • a second object of the present invention is to provide the use of an increase in g__Jeotgalicoccus as an indicator of water quality deterioration.
  • the third object of the present invention is to provide the reduction of g__Sphingobium in indicating the deterioration of water body and the application of the reduction of dissolved oxygen.
  • the fourth object of the present invention is to provide the reduction of g__Treponma to reflect the application of COD reduction in water bodies.
  • the fifth object of the present invention is to provide an increase in g_Yersinia to reflect the application of an increase in total phosphorus in water bodies.
  • a sixth object of the present invention is to provide the use of an increase in g__Pleomorphomomas as an indicator of water quality deterioration.
  • the present invention has the following technical effects:
  • This method is highly directional, indicating characteristic pollutants by using changes in the structure and function of specific microbial groups
  • This method uses microbial indicators to reflect changes in water quality, and at the same time has an indicative effect on characteristic pollutants;
  • This method is not limited to special environmental indicators, and has good applicability to urban river ecosystems
  • the method can quickly, accurately and objectively reflect the health status of urban river ecosystems.
  • Figure 1 is a sampling map of river ecosystems in Guangzhou
  • Fig. 2 is sensitive microorganism type 1-environmental factor water temperature (WT);
  • Fig. 3 is sensitive microorganism type 2-environmental factor nitrate nitrogen (NO 3 -N );
  • Fig. 4 is sensitive microorganism type 3-environmental factor pH
  • Figure 5 shows the relative abundance of sensitive microorganisms in different water quality grades.
  • Sampling point selection This sampling point is located in Guangzhou and surrounding rivers, mainly concentrated in the Pearl River Delta, which is a typical river city.
  • the flow direction of the river it is mainly divided into urban areas, suburban areas, and rural areas far away from the city.
  • Sampling points 8, 8, and 8 were selected respectively, and 3 repetitions were taken each time.
  • a total of 10 samples were taken, with a total of 240 samples.
  • the scale of repeated sampling was Differences, data based on science.
  • the distance between the urban area, the suburban area and the rural area is about 100km, and the total span is 200km, which is used to cover the urban area of Guangzhou and the surrounding river plots.
  • the collection time of water samples is 1 year, with a total of 10 collections in monthly units, and the time span is April, May, June, July, September, October, November, December and January 2019 in 2018 ,February.
  • Determination of 12 indicators of water quality environment indicators pH, water temperature (WT), dissolved oxygen (DO), COD, TN, total organic carbon, nitrate nitrogen, ammonium nitrogen, nitrite nitrogen, total phosphorus, sulfide and fluoride .
  • n is the number of selected factors
  • SIi is the factor score
  • V and VI were 55 and 76 times in a total of 240 tests (Table 1), and the characteristic pollutants were the main contribution frequencies: 0 times for pH, 42 times for DO, 45 times for COD, TP A total of 38 times, NO 3 - a total of 39 times (Table 2).
  • the 2L water sample was filtered through a 0.22 ⁇ m filter membrane, and the PowerWater DNA extraction kit (power Isolation Kit) to extract the microbial DNA of the filter membrane, and carry out DNA extraction according to the operation steps of the kit, and the extracted DNA sample adopts an ultramicro spectrophotometer to measure the concentration and purity of the DNA. Qualified DNA samples were sent to Biomark Biotechnology Co., Ltd. for sequencing.
  • the pCR amplification test of the microbial 16S rRNA fragment was performed by using the bacterial universal primer 338F/806R to amplify the bacterial V3-V4 hypervariable region.
  • primer sequence used is: pre- Primer 338F (5'-ACTCCTACGGGAGGCAGCA-3') and back primer 806R (5'-GGACTACHVGGGATCTWTCTAAT-3') were sequenced by paired-end sequencing using the Illumina HiSeq 2500 system (Illumina, Unite States) desktop sequencer.
  • the high-quality 16S rRNA gene amplicon sequence was analyzed using the open-source quantitative analysis software for microbial ecology (QIIME2), and the sequence reads of DATA2 in the QIIME2 system were used for denoising, and the denoised sequences were normalized with 100% similarity. It is a type of OTU, and finally use SILVA 132 to perform taxonomic classification analysis on the OTU sequence (http://www.mothur.org/wiki/Taxonnomy_outline).
  • the number of amplicon sequences obtained after the determination is equalized, that is, the same number of sequences is randomly selected for all samples based on the lowest sequence number in the sample (flattened) After obtaining 12365 sequences), and obtain the genus level information table.
  • the genus level information table statistics are made according to the relative abundance of the genus level higher than 1%, 0.5% and 0.01%. After the total relative abundance is higher than 90%, it is divided into an independent table, and then the unnamed OTU of the genus hit is removed , or change the nomenclature to the species level (both classes and orders are acceptable), so as to obtain the effective bacterial genera information table.
  • Microbial susceptibility is classified as follows:
  • yi is the relative abundance of microorganisms
  • xi is an environmental parameter
  • s1(x1), s2(x2) are non-parametric smooth functions
  • Log() is an example of a related function
  • the value of the environmental parameter corresponding to the peak value is the most suitable ecological niche for the microorganism.
  • the environmental factor water temperature (TW) screening results are g__Altererythrobacter and g__Facklamia, which are fitted to a unimodal model (as shown in Figure 2a ,b); if there are multiple species in a similar niche, the species with the narrowest niche will be used as the sensitive microorganism.
  • TW results the peak value of g__Altererythrobacter is 8.85, while the peak value of g__Facklamia is 7.98.
  • Altererythrobacter has a stronger response, and the niche of Altererythrobacter is narrower, and Altererythrobacter is more suitable as a sensitive microorganism for TW than Facklamia.
  • the microorganism with the largest correlation coefficient was selected as the sensitive microorganism.
  • the environmental factor nitrate nitrogen screening results as an example: g__Nitrospira and g__Trichococcus obtained in the results are one-way linear fitting (as shown in Figure 3a, b); The fitted r value was 0.173, the significance level was ⁇ 0.05, and Trichococcu had a stronger response than Nitrospira.
  • the microorganism is taken as the sensitive microorganism in the mutation interval of the environmental factor.
  • the environmental factor pH screening results as an example: g__Jeotgalicoccus suddenly increases when pH>8.2 is obtained in the results ( Figure 4), and g__Jeotgalicoccus can be regarded as a pH-sensitive microorganism as a factor.
  • the health level of urban water ecosystems is affected by many factors, such as: urban development progress, domestic sewage discharge, land use and management, etc., which cause complex pollutants in urban water bodies, which leads to the deterioration of the overall water environment. Therefore, rapid, An accurate and objectively feasible evaluation system requires the identification of water quality deterioration and characteristic pollutants. Therefore, the present invention can quickly judge the water quality and specify the pollution type by screening the sensitive microbial groups of environmental factors (including water body characteristic pollutants) through the change of their relative abundance.

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  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
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  • Spectroscopy & Molecular Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Microbiology (AREA)
  • Biotechnology (AREA)
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  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Molecular Biology (AREA)
  • Genetics & Genomics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Hydrology & Water Resources (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Organic Chemistry (AREA)
  • Water Supply & Treatment (AREA)
  • Environmental & Geological Engineering (AREA)
  • Analytical Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

La présente invention concerne un procédé d'évaluation de la santé d'un écosystème de cours d'eau basé sur une réponse spécifique de la communauté microbienne. Le procédé consiste : a : à définir respectivement des points d'échantillonnage de zones rurales, de zones périurbaines urbaines et de centres-villes urbains le long d'un cours d'eau ; b : à mesurer la masse d'eau pour déterminer 12 indicateurs de pH, la température d'eau (WT), l'oxygène dissous (DO), COD, TN, le carbone organique total, l'azote nitrique, l'azote d'ammonium, l'azote de nitrite, le phosphore total, le sulfure et le fluorure, et calculer un indice de qualité d'eau (IWQ) ; c : à extraire l'ADN microbien de la masse d'eau et à réaliser un séquençage d'amplicon d'ARNr 16s bactérien ; d : à obtenir une table d'informations de niveau de genres bactériens, et à dépister des informations de genres bactériens efficaces ; e : à effectuer une division de sensibilité microbienne sur la base d'un modèle de niveau écologique ; et f : à effectuer une analyse de fiabilité de résultat d'évaluation. Au moyen du présent procédé, l'état de santé d'un écosystème de cours d'eau urbain peut être observé rapidement, avec précision et objectivement.
PCT/CN2022/120048 2022-08-16 2022-09-21 Procédé d'évaluation de la santé d'un écosystème de cours d'eau basé sur une réponse spécifique de la communauté microbienne WO2023098239A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116758976A (zh) * 2023-08-21 2023-09-15 中国建筑设计研究院有限公司 一种功能微生物定量贡献的识别方法
CN117171597A (zh) * 2023-11-02 2023-12-05 北京建工环境修复股份有限公司 一种基于微生物的污染场地分析方法、系统及介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060147976A1 (en) * 1999-08-25 2006-07-06 National Institute Of Advanced Industrial Science And Technology Method of detecting and quantitating microorganism having specific function and its gene from natural environment using novel 16SrRNA gene data or probes
CN109063962A (zh) * 2018-06-28 2018-12-21 河海大学 一种基于权重的城市内河生态系统健康评价方法
CN110675036A (zh) * 2019-09-09 2020-01-10 河海大学 一种基于随机森林优化微生物指数的高原河流生态健康评价方法
CN114707786A (zh) * 2021-12-07 2022-07-05 郑州师范学院 一种基于共现性网络的河流生态系统健康评价方法

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20020023747A (ko) * 2001-12-14 2002-03-29 김상길 조류를 이용한 수질감시방법
CN102507885B (zh) * 2011-09-28 2014-05-07 首都师范大学 应用底泥微生物数量预报复杂水环境综合质量的方法
CA2911416C (fr) * 2013-05-09 2018-07-03 The Procter & Gamble Company Procede et systeme d'identification d'un marqueur biologique
US11648259B2 (en) * 2015-11-02 2023-05-16 Mycotox Solutions Inc. Aptamers for mycotoxin detoxification
CN105868545B (zh) * 2016-03-28 2018-01-16 中国科学院城市环境研究所 一种地下水生态系统健康评价方法
CN107198972B (zh) * 2017-05-26 2020-10-27 浙江大学 一种用于水体微污染物脱除的膜色谱材料及其制备方法
CN107805658A (zh) * 2017-09-19 2018-03-16 华南师范大学 一种对水质敏感的真核微型生物t‑rflp片段的筛选方法
CN107894451A (zh) * 2017-11-13 2018-04-10 南开大学 一种微生物传感器在线检测不同浓度水体絮凝剂毒性的方法
CN108629502A (zh) * 2018-05-02 2018-10-09 苏州农业职业技术学院 一种基于微生物完整性指数的湿地生态系统健康评价方法
CN112651548B (zh) * 2020-12-11 2023-01-13 中国电建集团昆明勘测设计研究院有限公司 一种高原湖滨生态景观修复规划的评估识别方法
CN113095719B (zh) * 2021-04-29 2022-05-06 中国科学院水生生物研究所 一种湖泊生态系统健康评价和修复方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060147976A1 (en) * 1999-08-25 2006-07-06 National Institute Of Advanced Industrial Science And Technology Method of detecting and quantitating microorganism having specific function and its gene from natural environment using novel 16SrRNA gene data or probes
CN109063962A (zh) * 2018-06-28 2018-12-21 河海大学 一种基于权重的城市内河生态系统健康评价方法
CN110675036A (zh) * 2019-09-09 2020-01-10 河海大学 一种基于随机森林优化微生物指数的高原河流生态健康评价方法
CN114707786A (zh) * 2021-12-07 2022-07-05 郑州师范学院 一种基于共现性网络的河流生态系统健康评价方法

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116758976A (zh) * 2023-08-21 2023-09-15 中国建筑设计研究院有限公司 一种功能微生物定量贡献的识别方法
CN116758976B (zh) * 2023-08-21 2023-12-19 中国建筑设计研究院有限公司 一种功能微生物定量贡献的识别方法
CN117171597A (zh) * 2023-11-02 2023-12-05 北京建工环境修复股份有限公司 一种基于微生物的污染场地分析方法、系统及介质
CN117171597B (zh) * 2023-11-02 2024-01-02 北京建工环境修复股份有限公司 一种基于微生物的污染场地分析方法、系统及介质

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