A method for absolute quantification and host identification of antibiotic resistance genes in water

Abstract

The present invention discloses a method for absolute quantification and host identification of antibiotic resistance genes in water. The method comprises: determining the absolute concentration of microbial cells in water by flow cytometry; obtaining raw sequencing data; obtaining high-quality sequencing data; performing ARG classification and abundance estimation on the high-quality sequencing data, and performing BLASTX comparison with the SARG 2.0 database to obtain the relative abundance and absolute abundance of antibiotic resistance genes in water; using Megahit to perform metagenomic assembly on the sample, and evaluating the assembly quality by MetaQUAST, and comparing the SARG 2.0 database by BLASTX to identify the Contig (ACC) containing ARG, and using Kaiju to perform species annotation on ACC, and using PlasFlow to determine the genetic position, thereby identifying the ARGs host. The method of the present invention significantly improves the detection accuracy and comprehensiveness of antibiotic resistance genes.

Description

Technical Field

[0001] The invention belongs to the technical field of microbiome and bioinformatics, and particularly relates to a method for absolute quantification of antibiotic resistance genes in water and host identification. Background Art

[0002] Antibiotic resistance has become a global public health challenge. The widespread use of antibiotics has accelerated the spread of antibiotic resistance genes (ARGs), which can spread through horizontal gene transfer and become new pollutants in water bodies, especially potential threats in drinking water systems.

[0003] At present, existing detection methods (such as quantitative PCR and metagenomics) have the limitations of low detection accuracy, inability to absolutely quantify and identify new resistance genes, and new methods are urgently needed to more accurately evaluate the abundance and transmission mechanism of ARGs in aquatic environments. At present, the detection of antibiotic resistance genes (ARGs) in water bodies usually relies on relative quantification methods of metagenomics or quantitative PCR, which often have multiple technical limitations. The main disadvantages of existing technologies such as quantitative PCR and metagenomics include: 1) they can only detect known ARGs and cannot effectively identify new resistance genes; 2) they can only provide relative quantification, fail to consider the dynamic changes of microbial biomass in the environment, and it is difficult to accurately evaluate the absolute abundance of resistance genes, resulting in reduced detection accuracy, especially in low biomass environments, which is prone to bias; 3) there is a lack of effective quantitative means for uncultured microbial populations in the environment. Therefore, the accurate absolute quantification of ARGs in water bodies still faces technical bottlenecks.

[0004] Through searching, the closest solutions are:

[0005] A device for removing antibiotic resistance genes in aquaculture waters and a rapid detection method: CN202311365924.7

[0006] A quantitative detection method for free antibiotic resistance genes in tap water: CN202010744621.6

[0007] A quantitative detection method for free antibiotic resistance genes in sewage: CN202010214165.4

[0008] Although these schemes involve resistance gene detection, none of them proposes the use of flow cytometry combined with metagenomics for absolute quantitative detection and host analysis. Summary of the invention

[0009] In order to overcome the deficiencies in the prior art, the present invention combines flow cytometry with metagenomic sequencing to provide a method for absolute quantification of antibiotic resistance genes in water and host identification. By accurately measuring the absolute concentration of microorganisms in water, the absolute abundance detection of ARGs is achieved, and the host microorganisms carrying the resistance genes can be identified. This method solves the shortcomings of the existing methods in terms of accuracy, wide applicability and identification of new resistance genes, greatly improves the detection ability of ARGs in different water environments, especially for resistance gene and host analysis in complex environmental samples, and provides more comprehensive and accurate data.

[0010] The specific technical solutions of the present invention are as follows:

[0011] The present invention provides a method for absolute quantification of antibiotic resistance genes in water and host identification, comprising the following steps:

[0012] (1) Determine the absolute concentration of microbial cells in water by flow cytometry;

[0013] (2) Extracting microbial genomic DNA from water bodies and constructing sequencing libraries to obtain raw sequencing data;

[0014] (3) performing quality control on the raw sequencing data to obtain high-quality sequencing data;

[0015] (4) ARG classification and abundance estimation were performed on the high-quality sequencing data, and BLASTX comparison was performed with the SARG 2.0 database to obtain the relative abundance and absolute abundance of antibiotic resistance genes in water bodies. The relative abundance of the ARGs was expressed as the number of ARG copies per cell, and the absolute abundance of the ARGs was calculated by the relative abundance of the ARGs × the absolute concentration of microbial cells in the water body;

[0016] (5) The samples were assembled using Megahit and the assembly quality was evaluated using MetaQUAST. The ARG-containing Contig (ACC) was identified by comparing it with the SARG 2.0 database using BLASTX. The ACC was annotated to species using Kaiju and the genetic position was determined using PlasFlow to identify the ARGs host.

[0017] Furthermore, the dye used in the flow cytometry is selected from SYBR Green I, SYBR Gold or Propidium Iodide, and flow cytometry with different dyes can be used to adapt to different water sample characteristics.

[0018] Furthermore, before extracting the microbial genomic DNA from the water body, a filter membrane with a pore size of 0.1 μm was used for filtration.

[0019] Furthermore, the microbial genomic DNA is extracted using a FastDNATM 50mL SPIN for Soil kit or a DNeasy PowerWater Kit. Different kits are used to improve extraction efficiency or adapt to other water conditions.

[0020] Furthermore, the sequencing library is constructed by randomly breaking the microbial genomic DNA fragments into 350 bp in length and then using UltraTM DNA Library Prep Kit was used for library construction.

[0021] Furthermore, the method for quality control of the raw sequencing data is: using FastQC to evaluate the quality of the raw sequencing data, removing sequences with a quality score lower than 20, and using fastp to trim the adapter sequence.

[0022] Furthermore, the parameters of the metagenomic assembly of the samples using Megahit were: --k-min 61 --k-step8 --min-contig-len 1000.

[0023] Furthermore, PlasFlow was used to determine genetic positions with a threshold of 0.7.

[0024] The beneficial effects of the present invention are:

[0025] The present invention uses flow cytometry to quantify microbial cell concentration and combines it with metagenomics technology to achieve absolute quantification of ARGs and host identification, making up for the shortcomings of current technology in terms of accuracy and operability. This scheme not only improves the sensitivity of detection, but also can better capture the dynamic changes of ARGs. It is suitable for different water environments and water treatment stages, and provides new ideas for the monitoring and prevention of ARGs in water bodies.

[0026] Compared with traditional quantitative PCR and metagenomic sequencing methods, this invention significantly improves the detection accuracy and comprehensiveness of antibiotic resistance genes by combining flow cytometry and metagenomics technology. First, this method can achieve absolute quantitative detection of ARGs, overcoming the impact of microbial concentration fluctuations on the results; second, through metagenomic assembly and host analysis, new resistance genes can be identified and their transmission pathways in water microbial populations can be tracked; finally, this solution not only improves detection efficiency, but also provides more targeted decision-making basis for the operation and management of water treatment facilities. DETAILED DESCRIPTION

[0027] In order to understand the present invention more clearly, the present invention is further described with reference to the following examples. The examples are only used for explanation and are not intended to limit the present invention in any way. In the examples, each raw material reagent is commercially available, and the experimental methods without specifying specific conditions are conventional methods and conventional conditions well known in the art, or according to the conditions recommended by the instrument manufacturer.

[0028] Example 1

[0029] This embodiment provides a method for absolute quantification of antibiotic resistance genes in water and host identification, which specifically includes the following steps:

[0030] (1) Determination of microbial cell concentration

[0031] 1 mL of water sample was taken into a 2 mL centrifuge tube and SYBR Green I dye (10 μL / mL, diluted in dimethyl sulfoxide, 100-fold dilution, Invitrogen, USA) was added for nucleic acid staining. After the sample was incubated at 25°C in the dark for 15 minutes, the absolute cell concentration (unit: number of cells / mL) was determined by BD FACSCalibur flow cytometer (BD Biosciences, USA). Flow cytometry has high cell counting accuracy and is suitable for samples with low microbial concentrations, and the number of microorganisms can be detected based on the fluorescent signal.

[0032] (2) Microbial enrichment and nucleic acid extraction

[0033] 200 to 1000 liters of water samples were filtered using a 0.1 μm pore size filter (Torayvino, Toray Industries Inc., Japan). The filter was stored at -80 °C for subsequent nucleic acid extraction. Microbial genomic DNA was extracted from the filter using the FastDNATM50mL SPIN for Soil kit (MP Biomedicals, USA). DNA quality was assessed by 0.8% agarose gel electrophoresis, and DNA concentration was detected using Nanodrop to ensure high-quality genomic DNA was used in subsequent analysis.

[0034] (3) Metagenomic sequencing

[0035] 3 μg of genomic DNA was used to construct a sequencing library for each sample and sequenced on the Illumina NovaSeq 6000 platform (Novogene, Tianjin) (2×150 bp, depth 15G). The DNA fragments were randomly sheared to 350 bp in length using a Covaris ultrasonic crusher (USA) and then The library was constructed using UltraTM DNA Library Prep Kit (NEB, USA).

[0036] (4) Data analysis

[0037] 1) Identification and absolute quantification of novel resistance genes

[0038] FastQC (v0.11.6) was used to evaluate the quality of the original sequencing sequences, and sequences with a quality score of less than 20 were removed. Fastp (v0.23) was used to trim the adapter sequences. The ARGs-OAP v2.0 framework was used to classify and estimate the abundance of high-quality sequences after quality control, and BLASTX was compared with the SARG 2.0 database. The relative abundance was expressed as the number of ARG copies per cell (copy number / cell), and the absolute abundance of ARGs was obtained by multiplying the relative abundance of ARGs by the absolute concentration of water cells.

[0039] 2) Metagenomic assembly and ARG host identification

[0040] The samples were assembled using Megahit (v1.2.9) with parameters: --k-min 61 --k-step 8 --min-contig-len 1000, and the assembly quality was evaluated by MetaQUAST (v3.2). Contigs (ACCs) containing ARGs were identified by BLASTX comparison with the SARG database (v2.0). ACCs were annotated to species using Kaiju (v1.7.2), and PlasFlow (v1.1) was used to determine genetic positions with a threshold of 0.7 to identify ARGs hosts and their transmission potential.

[0041] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for absolute quantification of antibiotic resistance genes in water and host identification, characterized in that: The steps include: (1) Determine the absolute concentration of microbial cells in water by flow cytometry; (2) Extracting microbial genomic DNA from water bodies and constructing sequencing libraries to obtain raw sequencing data; (3) performing quality control on the raw sequencing data to obtain high-quality sequencing data; (4) ARG classification and abundance estimation were performed on the high-quality sequencing data, and BLASTX comparison was performed with the SARG 2.0 database to obtain the relative abundance and absolute abundance of antibiotic resistance genes in water bodies. The relative abundance of the ARGs was expressed as the number of ARG copies per cell, and the absolute abundance of the ARGs was calculated by the relative abundance of the ARGs × the absolute concentration of microbial cells in the water body; (5) The samples were assembled using Megahit and the assembly quality was evaluated using MetaQUAST. The ARG-containing Contig (ACC) was identified by comparing it with the SARG 2.0 database using BLASTX. The ACC was annotated to species using Kaiju and the genetic position was determined using PlasFlow to identify the ARGs host.

2. The method according to claim 1, characterized in that The dye used in the flow cytometry is selected from SYBR Green I, SYBR Gold or Propidium Iodide.

3. The method according to claim 1, characterized in that Before extracting the microbial genomic DNA from the water, it was filtered using a filter membrane with a pore size of 0.1 μm.

4. The method according to claim 1, characterized in that: The microbial genomic DNA was extracted using FastDNA TM 50mL SPIN for Soil Kit or DNeasy PowerWater Kit.

5. The method according to claim 1, characterized in that The sequencing library is constructed by randomly breaking the microbial genomic DNA fragments into 350 bp in length and then using UltraTM DNA Library Prep Kit was used for library construction.

6. The method according to claim 1, characterized in that The method for quality control of the raw sequencing data is: using FastQC to evaluate the quality of the raw sequencing data, removing sequences with a quality score lower than 20, and using fastp to trim the adapter sequence.

7. The method according to claim 1, characterized in that The parameters for metagenomic assembly of samples using Megahit were: --k-min 61 --k-step 8 --min-contig-len 1000.

8. The method according to claim 1, characterized in that Genetic positions were determined using PlasFlow with a threshold of 0.7.