A sequencing-based metagenomic quantification method

Abstract

The present invention belongs to the field of biotechnology, and specifically relates to a composition for quantitative infection metagenomic sequencing and a metagenomic quantification method based on sequencing. The method has the advantages of low sample requirement, short time consumption, simple operation, and reduced cost.

Description

Technical Field

[0001] The present application belongs to the field of in vitro diagnostic technology, and specifically relates to a metagenomic quantification method based on sequencing. Technical Background

[0002] Nearly all infectious agents contain a DNA or RNA genome, making sequencing an attractive approach for pathogen detection. Since 2004, the cost of high-throughput or next-generation sequencing has decreased by several orders of magnitude and has become an important technology platform for testing patient clinical samples. Next-generation sequencing (NGS), also known as high-throughput or massively parallel sequencing, is a type of technology that allows thousands to billions of DNA fragments to be sequenced simultaneously and independently. The applications of NGS in clinical microbiology testing are multifaceted, including metagenomic NGS (mNGS), which allows an unbiased approach to pathogen detection. mNGS provides a sensitive and thorough method for detecting all pathogens in clinical samples, from traditional bacteria to atypical and rare pathogens, allowing for rapid diagnosis. Metagenomic analysis facilitates the identification of pathogens, including those responsible for bacterial, fungal, and viral infections.

[0003] With the development needs, clinicians not only pay attention to the microbial infection of patients, but also have an increasing demand for microbial quantification. The conventional methods currently used in clinical practice are blood culture, nucleic acid detection, etc. However, the limitations of traditional culture methods challenge doctors to make accurate diagnoses and appropriately reduce antimicrobial drugs. Non-culture methods, such as nucleic acid PCR tests, may help to fully diagnose, but the experimental cycle is long and the diagnostic cost is high. There are currently many ways to quantify non-culture DNA, such as Qubit, SYBR Green, Taqman, and ddPCR. However, most of these methods require a large amount of DNA to provide accurate titration. In comparison, sequencing platforms only require micrograms of library DNA for quantification. The amount of DNA required for sequencing (an average of 12pM per lane) is about 1000 times less than that required for the above-mentioned quantification, which is good news for some samples that may not be able to obtain this amount of DNA. Based on this, the present application is proposed. Summary of the Invention

[0004] To solve the above technical problems, this application proposes a metagenomic quantification method based on sequencing. Specifically, the application has at least the following objectives:

[0005] The first purpose of this application is to provide a metagenomic quantification method based on sequencing;

[0006] The second purpose of this application is to provide a quantitative product GKSPK3.

[0007] To achieve the above objectives, this application specifically proposes the following technical solutions:

[0008] The present application provides a composition GKSPK3 for infection metagenomic sequencing quantification, wherein the composition GKSPK3 comprises Gram-negative bacteria A with a high GC content, Gram-negative bacteria B with a normal GC content, and Gram-positive bacteria C with a normal GC content.

[0009] Furthermore, the Gram-negative bacteria strain A is Halomonas xianhensis, the Gram-negative bacteria B is Shewanella nanhaiensis, and the Gram-positive bacteria C is Jeotgalibacillus campisalis.

[0010] Furthermore, the concentration ratio of Halomonas xianhensis, Shewanella nanhaiensis and Jeotgalibacillus campisalis is 100-1000:10-100:1-10;

[0011] More preferably, the concentration ratio is 100:10:1.

[0012] The present application also provides a kit for quantitative infection metagenomic sequencing, comprising any of the above-described compositions GKSPK3.

[0013] The present application also provides the use of the above-mentioned composition GKSPK3 in infection metagenomic sequencing quantification.

[0014] The present application also provides a sequencing-based quantitative method for infectious metagenomes, comprising the following steps: adding any of the above-mentioned compositions GKSPK3 to the sample mNGS extraction and library construction stage, calculating the relative abundance of each species in the sample based on the species-level raw reads of Halomonasxianhensis, Shewanella nanhaiensis, and Jeotgalibacillus campisalis obtained by sequencing, drawing a linear equation with the relative abundance as the independent variable and the known actual mass as the dependent variable; substituting the relative abundance of each species in the sample to obtain the theoretical mass corresponding to the pathogen in the sample, and then converting the theoretical copy concentration of the corresponding pathogen species through the formula.

[0015] Furthermore, the known actual mass is the actual mass of the three deep-sea bacteria in GKSPK3 calculated by combining the copy value of each species in GKSPK3 (based on the copy quantified by dPCR) and the genome size;

[0016] In some specific embodiments, the known actual mass calculation formula is:

[0017]

[0018] In some specific embodiments, the linear equation is:

[0019] y = 0.2973x;

[0020] R2=0.9999.

[0021] In some specific embodiments, the theoretical copy concentration is calculated as follows:

[0022]

[0023]

[0024] The present application also provides a method for establishing an infection metagenomic quantification system, the method comprising the following steps:

[0025] Step 1: Preparation of quantitative composition GKSPK3:

[0026] Gram-negative bacterial strains A (Halomonas xianhensis), Gram-negative bacteria B (Shewanella nanhaiensis), and Gram-positive bacteria C (Jeotgalibacillus campisalis) were screened and subcultured separately; purity was verified by mNGS and large-scale propagation was performed; after propagation, the cultures were quantified by dPCR, and after quantification, the cultures were mixed in a concentration ratio of 100-1000:10-100:1-10 to prepare any of the above-described quantitative compositions GKSPK3;

[0027] Step 2: Preparation of simulation reference disk:

[0028] Pathogens were selected for the simulated reference plate, including Gram-positive bacteria, Gram-negative bacteria, yeast-like fungi, and common clinical viruses. The human cell and pathogen concentrations of the simulated reference plate were set based on the clinical pathogen detection level and the detection limit of the mNGS process. The final concentration of each pathogen in the reference plate was quantified by dPCR, and a simulated reference plate with a certain concentration gradient was established. After the reference plate was prepared, the actual copy concentration of the species in the reference plate (i.e., the dPCR quantification result) was quantified by dPCR to verify the stability of the reference plate.

[0029] Step 3: Construction of quantitative model:

[0030] The quantitative composition GKSPK3 was added to a simulated clinical reference plate, and DNA extraction, library construction, and mNGS process were performed together. A linear equation was constructed based on the species-level original read ratios of the three bacteria of GKSPK3 in the sequencing results and the actual masses of the three known bacteria. The species original read ratios of each pathogen in the simulated reference plate were obtained by sequencing, and the theoretical masses corresponding to each pathogen in the simulated reference plate were calculated based on the linear equation to obtain the copy concentration of each pathogen (i.e., the mNGS quantitative result). The co-extracted DNA was then used for dPCR quantification to obtain the actual copy concentration of each pathogen in the simulated reference plate (i.e., the dPCR quantitative result). The mNGS quantitative results and dPCR quantitative results obtained under different concentration gradients were compared to obtain the species conversion coefficients between the two quantitative methods.

[0031] Preferably, the method further comprises:

[0032] Step 4: Verification of conversion factors:

[0033] Clinical samples containing species in the simulated reference panel were randomly selected. The quantitative composition GKSPK3 was added during DNA extraction and library construction, and the sequencing process was performed. The same operation as in step 3 was performed. After calculating the copy concentration, the conversion factor of each species was used to obtain the theoretical copy concentration (i.e., the mNGS quantitative result). The results were then compared with the dPCR results to verify the consistency of the results.

[0034] Furthermore, in step 2, the Gram-positive bacteria is Staphylococcus aureus, the Gram-negative bacteria is Klebsiella pneumoniae, the yeast-like fungus is Candida albicans, and the common clinical virus is human herpes virus type 4-EBv;

[0035] Furthermore, in step 2, the concentration of human cells in the reference plate is 5.00E+04-1.00E+06 cell / mL, and the concentration of the pathogens is 1.00E+03-1.00E+05 copy / mL.

[0036] Furthermore, the dPCR quantification in step 1 is performed based on the primer probe sequences shown in SEQ ID NOs. 8-16; the dPCR quantification in step 2 is performed based on the primer probe sequences shown in SEQ ID NOs. 17-28; and the dPCR quantification in step 3 is performed based on the primer probe sequences shown in SEQ ID NOs. 8-28.

[0037] Furthermore, in step 3, the amount of the quantitative composition GKSPK3 added is 20ul.

[0038] Furthermore, in step 3, the construction of the linear equation is specifically as follows: the relative abundance of each species in the sample is calculated based on the original reads of Halomonasxianhensis, Shewanella nanhaiensis and Jeotgalibacillus campisalis obtained by sequencing, and the relative abundance is used as the independent variable and the known actual mass is used as the dependent variable to draw a linear equation.

[0039] In some specific embodiments, the known actual mass calculation formula is:

[0040]

[0041] In some specific embodiments, the linear equation is:

[0042] y = 0.2973x;

[0043] R2=0.9999.

[0044] In some specific embodiments, the theoretical copy concentration is calculated as follows:

[0045]

[0046] Sample copy concentration = species copy number (copy) / sample volume.

[0047] In some preferred specific embodiments, the conversion factors of the species are as follows:

[0048] Klebsiella pneumoniae: dPCR quantitative result (true value) = mNGS quantitative result × 1.8597;

[0049] Staphylococcus aureus: dPCR quantitative result (true value) = mNGS quantitative result × 1.8854;

[0050] Candida albicans: dPCR quantitative result (true value) = mNGS quantitative result × 1.3144;

[0051] Human herpesvirus type 4: dPCR quantitative result (true value) = mNGS quantitative result × 1.3951.

[0052] In the above text, "theoretical mass" or "theoretical copy concentration" refers to the results obtained by sequencing quantification, and "actual mass" or "actual copy concentration" refers to the results obtained by dPCR quantification.

[0053] Compared with the prior art, the beneficial technical effects of this application include at least:

[0054] 1) This application is based on a sequencing-based infectious pathogen quantification method. By exploring and determining three rare non-pathogenic bacteria as internal references, and establishing a reasonable ratio to establish a quantitative relationship, the accuracy of the quantitative results is guaranteed.

[0055] 2) This application requires significantly less sample volume than currently available quantitative methods and is particularly suitable for trace sample areas such as infection metagenomes.

[0056] 3) Compared with the existing technical means, the method of the present application is less time-consuming, simpler to operate, does not require additional experiments, and is lower in cost.

[0057] 4) This application can achieve order-of-magnitude quantification of pathogens by adding the present composition on the basis of the original mNGS. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 , storage stability evaluation results of strain HX;

[0059] Figure 2 , evaluation results of storage stability of strain SN;

[0060] Figure 3 , storage stability evaluation results of strain JC;

[0061] Figure 4 , specific amplification evaluation results of primer set SN-1;

[0062] Figure 5 , specific amplification evaluation results of primer set SN-2;

[0063] Figure 6 , specific amplification evaluation results of primer set SN-3;

[0064] Figure 7 , specific amplification evaluation results of primer set SN-4;

[0065] Figure 8 , evaluation results of the optimal quantitative system of qPCR in group SN-1;

[0066] Figure 9 , evaluation results of the optimal quantitative system of qPCR in group SN-2;

[0067] Figure 10 , evaluation results of the optimal quantitative system of qPCR in group SN-3;

[0068] Figure 11 , The result graph of the first-order linear equation with an intercept of 0 was obtained by comparing the relative abundance and actual mass of the three deep-sea bacteria in the sequencing data;

[0069] Figure 12, The result graph of the first-order linear equation with the intercept set to 0 based on the relative abundance of HX, SN, and JC and the actual mass. DETAILED DESCRIPTION

[0070] The embodiments of the present application will be described in detail below with reference to the examples, but it will be understood by those skilled in the art that the following examples are merely illustrative of the present application and should not be construed as limiting the scope of the present application. In the examples, if no specific conditions are specified, the conditions are carried out according to conventional conditions or manufacturer recommendations. The reagents or instruments used are not specified by the manufacturer and are conventional products that can be purchased on the market.

[0071] Unless otherwise defined below, the meanings of all technical and scientific terms used in the specific embodiments of the present application are intended to be the same as those generally understood by those skilled in the art. Although it is believed that the following terms are well understood by those skilled in the art, the following definitions are still set forth to better explain this application.

[0072] The term "about" in this application indicates an accuracy range that can be understood by those skilled in the art and still ensures the technical effect of the characteristics discussed. This term usually indicates a deviation from the indicated value by ±10%, preferably ±5%.

[0073] As used in this application, the terms "comprises," "comprising," "having," "containing," or "involving" are inclusive or open-ended and do not exclude other unrecited elements or method steps. The term "consisting of" is considered a preferred embodiment of the term "comprising." If a group is defined below as comprising at least a certain number of embodiments, this should also be understood to disclose a group that preferably consists only of these embodiments.

[0074] Furthermore, the terms first, second, third, (a), (b), (c), and the like, in the specification and claims, are used to distinguish between similar elements and are not necessarily intended to describe a sequential or chronological order. It is understood that the terms so used are interchangeable under appropriate circumstances, and that the embodiments described herein can be practiced in other sequences than described or illustrated herein.

[0075] The present application is described below with reference to specific embodiments.

[0076] Example 1. Screening of raw material strains

[0077] 1. Strain screening

[0078] In order to avoid clinical interference and to consider the characteristics of the actual species being tested, this application screened and optimized the raw material bacteria using the following ideas:

[0079] First, we screened strains that were simple to culture and had a high success rate. Furthermore, we did not find any clinically pathogenic strains, as the detection rate in clinical practice was extremely low. Furthermore, when comparing with our own strain database, the homology must be at least less than 1%, and there must be no quantitative impact from clinical detection. The candidate strains for the initial screening are as follows:

[0080]

[0081]

[0082] After obtaining the above-mentioned preliminary bacterial strains, this applicant conducted culture tests and found that some strains were difficult to culture and the culture purity of some strains did not meet the 99.9% requirement; secondly, for easily culturable species, bioinformatics analysis was performed to find highly conserved specific segments in the genomes of each species.

[0083] At the same time, the stability of the culture of each species within two months under the existing storage conditions was tested experimentally. Specifically, the culture medium of each species was inactivated by pasteurization, and then a rapid stability test was performed (the inactivated culture medium was placed at 37°C for 2 days, and dPCR quantification was performed every 12 hours) to screen out the strains with relatively stable storage (part of the results are shown in the attached Figure 1-3 ).

[0084] After comprehensively comparing the simplicity of culture, the highly conservative specific range, and the storage stability of the culture, the applicant, based on clinical experience with infection and combined with bioinformatics analysis, established the flora characteristics and nucleic acid characteristics of clinical infection microorganisms, and finally made appropriate selections of Gram-negative and Gram-positive bacteria, and also made appropriate selections for the GC content of nucleic acids. This application ultimately screened the following combination of raw material strains.

[0085] Halomonas xianhensis isolated from Xianhe Town, Shandong Province, is a high GC content Gram-negative (G-) strain; Shewanella nanhaiensis isolated from marine sediments in the northern South China Sea, is a normal GC content G- strain; and Jeotgalibacillus campisalis isolated from sea ash on the coast of the Yellow Sea, is a normal GC content G+ strain.

[0086] The above three strains are simple to culture with a high success rate. Currently, no clinical pathogenicity has been found, and their detection rate in clinical practice is extremely low. A comparison with our own strain database revealed that the homologous region of the above strains is less than 1%, indicating that there is no quantitative impact of clinical detection. Furthermore, among the selected species, the GC content of negative strains ranges from normal (approximately 40%) to high GC (approximately 60%), while the GC content of positive strains is at normal levels.

[0087] Example 2: Establishment of PCR Quantification System

[0088] In order to construct a quantitative mathematical model, this application needs to further select high-purity cultures of clinically representative pathogenic bacteria, and prepare different concentration gradient reference materials according to a certain human-source ratio, including one Gram-positive bacterium (Staphylococcus aureus), one Gram-negative bacterium (Klebsiella pneumoniae), one yeast-like fungus (Candida albicans) and one clinically common virus (human herpes virus type 4 - EBv).

[0089] Based on the specific sequences of the three raw deep-sea bacteria determined in Example 1 and the four species of bacteria in the reference plate, primers and probe sets for PCR amplification and quantitative analysis were designed.

[0090] The detailed design and screening process is as follows, taking the strain Shewanella nanhaiensis (SN) as an example:

[0091] 1) First, based on the applicant's proprietary primer design and evaluation system, a targeted segment (SEQ ID NO. 22) was screened and designed for SN-specific amplification detection. Furthermore, based on this sequence, four sets of single-copy primers and probes (numbered: SN-1, SN-2, SN-3, and SN-4) were preliminarily designed and commissioned for synthesis.

[0092] 2) After the primer probe is synthesized, the primers are first tested by SYBR. The test system and procedure are as follows:

[0093] Reagents Volume (μL) Final concentration NFW 4.4 SYBR Green PCR Master Mix 10 Upstream primer (10 μM) 0.8 0.4 μM Downstream primer (10 μM) 0.8 0.4 μM Species nucleic acid (1ng / μL) 4 total 20

[0094]

[0095] Based on the above test system, the four pairs of primers (SN-1, SN-2, SN-3 and SN-4) designed were confirmed to be able to perform effective specific amplification. Figure 4-7 As shown, the results show that, except Figure 7 Except for the SN-4 group, the other three primer pairs all performed specific amplification and were ready for the next step of screening.

[0096] 3) Taqman assay of the probes for the corresponding SN-1, SN-2, and SN-3 groups using the following system and procedure:

[0097]

[0098]

[0099]

[0100] The optimal qPCR quantitative system for this species was obtained, and the results were as follows Figure 8-10 The results show that except Figure 9 The other two pairs of primer probes are all effective, and the most preferred ones are the primer probes of the SN-3 group.

[0101] 4) Apply the validated quantitative system to the dPCR platform and test the annealing temperature. The system and procedure are as follows:

[0102]

[0103]

[0104] After the above experiments, the final quantitative primer and probe sequences for Shewanella nanhaiensis (SN) were obtained as follows:

[0105]

[0106]

[0107] By analogy with the above experiments, this application finally obtained the 7 quantitative systems used:

[0108]

[0109]

[0110] Example 3: Preparation of quantitative finished composition GKSPK3

[0111] 1) Bacterial Recovery and Purification: Use 2216E to recover deep-sea bacteria Halomonas xianhensis (HX, G-), Shewanella nanhaiensis (SN, G-), and Jeotgalibacillus campisalis (JC, G+). After 20 hours of culture, measure the OD value to be greater than 1. At this point, streak the recovered bacterial suspension and isolate and purify single colonies.

[0112] 2) Strain Preservation and Identification: A single colony was selected and propagated in liquid culture medium until the logarithmic phase (approximately 22 hours). A portion of the culture was mixed with an equal amount of sterile glycerol and frozen at -80°C. The remaining culture was subjected to second-generation sequencing and third-generation sequencing, respectively, to assemble the genome information of three deep-sea bacterial strains. The sequencing results confirmed that the purity of the three deep-sea bacterial cultures reached greater than 99.9%.

[0113] 3) GKSPK3 Preparation: The HX strain in this product has a high GC content, making cell wall disruption difficult. While both SN and JC strains are of normal concentration, SN is a G- strain, making cell wall disruption more challenging than G+. Furthermore, considerations were taken to minimize cross-contamination between samples during instrumentation. In summary, the designed concentration ratio for this GKSPK3 product is HX:SN:JC = (5×10^4 to 5×10^5):(5×10^3 to 5×10^4):(5×10^2 to 5×10^3), with the optimal ratio being 1×10^5:1×10^4:1×10^3. The table below shows a set of combinations based on the optimal concentration ratio and the actual concentrations quantified by dPCR.

[0114] Three strains of deep-sea bacteria culture were added with equal amounts of 2× DNA Shield to prepare deep-sea bacteria preservation solution. The concentrations of the three strains of preservation solution were quantified by dPCR, and the GKSPK3 product was prepared according to the concentrations in the table below.

[0115]

[0116] Example 4: Quantitative model construction

[0117] 1) Prepare reference plates within the detection limit: Gram-positive bacteria (Staphylococcus aureus), Gram-negative bacteria (Klebsiella pneumoniae), yeast-like fungi (Candida albicans), and DNA viruses (EBv) were selected for the reference plates. After culturing and preparing reference samples of the above four species, dPCR was performed to determine the original copy concentration of the reference sample. Then, reference plates with target gradient concentrations (T1-T5) were prepared according to the following gradient:

[0118]

[0119] 2) dPCR quantitative reference plate concentration: After preparing the reference plate, dPCR is used to quantify the actual copy concentrations of the four species again to verify whether the reference plate is stable (whether the actual concentration of the reference plate matches the target concentration). The dPCR quantitative results in the reference plate are as follows:

[0120]

[0121]

[0122] 3) Take 800ul of the reference plate and add 20ul of GKSPK3 to extract and construct the DNA library. Sequencing is performed on the BGI platform SE50. To avoid sample dilution due to excessive reference concentration, and to ensure the detection of the reference sample, a final injection volume of 20ul was used in this experiment.

[0123] 4) Data analysis is as follows: First, the actual mass of the three deep-sea bacteria strains in GKSPK3 is calculated by the copy value and genome size of each species in GKSPK3, as shown in the following formula 1:

[0124] Formula 1:

[0125] The information and actual mass of the three deep-sea bacteria in 20ul GKSPK3 are as follows:

[0126]

[0127] Secondly, the relative abundance and actual mass of the three deep-sea bacteria in the sequencing data were used to obtain a first-order linear equation with an intercept of 0: y = 0.2973x; R2 = 0.9999 (see Figure 11 ).

[0128] Finally, the relative abundances of the four pathogenic bacteria were substituted to obtain the theoretical mass of the four species in the reference plate:

[0129] sample Species Latin name Relative abundance Mass (ng) T1-1-UDB-137 Jeotgalibacillus campisalis 0.01740 0.0017 T1-1-UDB-137 Shewanella nanhaiensis 0.15100 0.0459 T1-1-UDB-137 Halomonas xianhensis 1.04260 0.3098 T1-1-UDB-137 Klebsiella pneumoniae 0.87600 0.2604 T1-1-UDB-137 Staphylococcus aureus 1.68000 0.4995 T1-1-UDB-137 Candida albicans 0.53700 0.1597 T1-1-UDB-137 Human gammaherpesvirus 4 0.03770 0.0112

[0130] Finally, the theoretical masses of the four species were converted back to the copy concentration (copy / mL) in the original sample, as shown in Formulas 2 and 3. For each concentration gradient reference plate, the ratio A of the theoretical copy concentration to the reference plate's dPCR-quantified copy concentration was calculated. The quantitative conversion factor for a given species was determined by averaging A across the five concentration gradient reference plates.

[0131] Formula 2:

[0132] Formula 3:

[0133] The conversion factors for the four species are as follows:

[0134] Klebsiella pneumoniae: dPCR quantitative result (true value) = mNGS quantitative result × 1.8597;

[0135] Staphylococcus aureus: dPCR quantitative result (true value) = mNGS quantitative result × 1.8854;

[0136] Candida albicans: dPCR quantitative result (true value) = mNGS quantitative result × 1.3144;

[0137] Human herpesvirus type 4: dPCR quantitative result (true value) = mNGS quantitative result × 1.3951.

[0138] Experiment 4: Clinical validation of mathematical models

[0139] 1) Clinical samples containing Klebsiella pneumoniae, Staphylococcus aureus, Candida albicans, and human herpes virus-4 were selected and 20 μl of GKSPK3 was added to perform the mNGS process. The analysis was performed according to the method of Example 3 as follows:

[0140] During this experiment, 7 clinical samples of Klebsiella pneumoniae, 6 clinical samples of Candida albicans, 4 clinical samples of Staphylococcus aureus, and 4 clinical samples of human herpes virus type 4 were selected. After the estimated mass of each species was obtained by the calculation method mentioned in Example 3, the copy concentration of the target species in the sample was calculated using Formula 2. After correction of the conversion factor, the two quantitative methods were compared to see whether they were similar. The clinical sample list is as follows:

[0141] Klebsiella pneumoniae Staphylococcus aureus Candida albicans human herpesvirus-4 S6 S3 S8 S5 S8 S4 S9 S16 S14 S9 S11 S31 S30 S33 S12 S33 S35 S31 S36 S34 S38

[0142] 2) Example of result analysis:

[0143]

[0144] The relative abundance of HX, SN, and JC was plotted against the actual mass, and the intercept was set to 0. The linear equation was as follows: y = 6.2511x, R2 = 0.9991 (see Figure 12 The relative abundance of KP in this library yielded a theoretical mass of 3.86E-02 ng. The mNGS quantification result for KP in this sample was calculated to be 7.87E+03 copies / mL. Using the conversion factor from Experiment 2, the estimated dPCR quantification result was 1.46E+04 copies / mL. The actual dPCR quantification result for this sample was 2.79E+04 copies / mL. The dPCR quantification result / estimated dPCR quantification result yielded a coefficient of m=1.90, with -1 < 1 g and m = 0.2796 < 1. Therefore, the estimated dPCR quantification result from the mNGS quantification using the conversion factor is consistent with the actual dPCR quantification result, confirming the conclusion that the order of magnitude is consistent.

[0145] The "estimated dPCR quantitative results" mentioned above are the estimated dPCR quantitative results obtained by multiplying the mNGS quantitative results by the conversion factor in Experiment 3.

[0146] The statistics of all clinical sample data are as follows:

[0147]

[0148]

[0149] Conclusion: The above experimental results show that GKSPK3 can achieve quantitative level quantification in Klebsiella pneumoniae, Staphylococcus aureus, Candida albicans and human herpes virus type 4.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. Application of the composition GKSPK3 in quantitative infection metagenomic sequencing; the composition GKSPK3 comprises Gram-negative bacteria A with high GC content, Gram-negative bacteria B with normal GC content, and Gram-positive bacteria C with normal GC content; the Gram-negative bacteria strain A is Halomonas xianhensis, the Gram-negative bacteria B is Shewanella nanhaiensis, and the Gram-positive bacteria C is Jeotgalibacillus campisalis; the concentration ratio of Halomonas xianhensis, Shewanella nanhaiensis, and Jeotgalibacillus campisalis is 100:10:

1.

2. A sequencing-based quantitative method for infectious metagenomes, characterized in that The method includes the following steps: adding the composition GKSPK3 to the sample mNGS library construction step, calculating the relative abundance of each species in the sample based on the species-level raw reads of Halomonas xianhensis, Shewanella nanhaiensis, and Jeotgalibacillus campisalis obtained by sequencing, and plotting a linear equation using the relative abundance as the independent variable and the known actual mass as the dependent variable; Substitute the relative abundance of each species in the sample to obtain the theoretical mass of the pathogen in the sample, and then convert it into the theoretical copy concentration of the corresponding pathogen species through the formula; The composition GKSPK3 comprises Gram-negative bacteria A with a high GC content, Gram-negative bacteria B with a normal GC content, and Gram-positive bacteria C with a normal GC content; the Gram-negative bacteria strain A is Halomonas xianhensis, the Gram-negative bacteria B is Shewanella nanhaiensis, and the Gram-positive bacteria C is Jeotgalibacilluscampisalis; the concentration ratio of Halomonas xianhensis, Shewanella nanhaiensis, and Jeotgalibacilluscampisalis is 100:10:

1.

3. A method for establishing a quantitative system for infection metagenomes, characterized in that: The method comprises the following steps: Step 1: Preparation of quantitative composition GKSPK3: Gram-negative bacterial strains Halomonas xianhensis, Gram-negative bacteria Shewanella nanhaiensis, and Gram-positive bacteria Jeotgalibacillus campisalis were screened and subcultured separately; purity was verified by mNGS and large-scale propagation was performed; after propagation, the cultures were quantified by dPCR, and after quantification, the cultures were mixed in a concentration ratio of 100:10:1 to prepare a composition GKSPK3; the composition GKSPK3 comprises Gram-negative bacteria A with a high GC content, Gram-negative bacteria B with a normal GC content, and Gram-positive bacteria C with a normal GC content; the Gram-negative bacteria strain A is Halomonas xianhensis, the Gram-negative bacteria B is Shewanella nanhaiensis, and the Gram-positive bacteria C is Jeotgalibacillus campisalis; the concentration ratio of Halomonas xianhensis, Shewanella nanhaiensis, and Jeotgalibacillus campisalis is 100:10:1; Step 2: Preparation of simulation reference disk: Pathogens were selected for the simulated reference plate, including Gram-positive bacteria, Gram-negative bacteria, yeast-like fungi, and common clinical viruses. The human cell and pathogen concentrations of the simulated reference plate were set based on the clinical pathogen detection level and the detection limit of the mNGS process. The final concentration of each pathogen in the reference plate was quantified by dPCR, and a simulated reference plate with a concentration gradient was established. After the reference plate was prepared, the actual copy concentration of the species in the reference plate was quantified by dPCR to verify the stability of the reference plate. Step 3: Construction of quantitative model: The quantitative composition GKSPK3 was added to a simulated clinical reference plate, and DNA extraction, library construction, and mNGS sequencing were performed together. A linear equation was constructed based on the proportion of original reads of the three bacterial species at the GKSPK3 level in the sequencing results and the actual mass of the three known bacteria. The original read proportion of each pathogen in the simulated reference plate was obtained by sequencing, and the theoretical mass corresponding to each pathogen in the simulated reference plate was calculated based on the linear equation to obtain the theoretical copy concentration of the target species, i.e., the mNGS quantitative result. The co-extracted DNA was then used for dPCR quantitative analysis to obtain the copy concentration of each pathogen in the simulated reference plate, i.e., the dPCR quantitative result. The mNGS quantitative results and dPCR quantitative results obtained under different concentration gradients were compared to obtain the conversion coefficients for each species between the two quantitative methods. Step 4: Verification of conversion factors: Randomly select clinical samples containing species in the simulated reference plate. During DNA extraction and library construction, add the quantitative composition GKSPK3 and perform the mNGS process. The same operation as in step 3 is used. After obtaining the calculation results, the conversion coefficient of each species is used to obtain the theoretical copy concentration. The results are then compared with the dPCR quantitative results to verify the consistency of the results.

4. The establishment method according to claim 3, characterized in that: In step 3, the construction of the linear equation is specifically as follows: based on the original reads of Halomonas xianhensis, Shewanella nanhaiensis and Jeotgalibacillus campisalis obtained by sequencing, the relative abundance of each species in the sample is calculated, and the relative abundance is used as the independent variable and the known actual mass is used as the dependent variable to draw a linear equation.

5. The establishment method according to any one of claims 3-4, characterized in that: In step 2, the Gram-positive bacteria are Staphylococcus aureus, the Gram-negative bacteria are Klebsiella pneumoniae, the yeast-like fungus is Candida albicans, and the common clinical virus is human herpes virus type 4-EBv; in step 2, the concentration of human cells in the reference plate is 5.00E+04-1.00E+06 cell / mL, and the concentration of the pathogens is 1.00E+03-1.00E+05 copy / mL, respectively.

6. The establishment method according to any one of claims 3-4, characterized in that: In step 1, the dPCR quantification is performed based on the primer probe sequences shown in SEQ ID NOs. 8-16; in step 2, the dPCR quantification is performed based on the primer probe sequences shown in SEQ ID NOs. 17-28; and in step 3, the dPCR quantification is performed based on the primer probe sequences shown in SEQ ID NOs. 8-28.

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