Non-valued composite quality control product for high-throughput sequencing of RNA (Ribonucleic Acid) pathogen metagenome and preparation method of non-valued composite quality control product

Abstract

The invention relates to an unvalued composite quality control product for RNA (Ribonucleic Acid) pathogen metagenome high-throughput sequencing and a preparation method of the unvalued composite quality control product, and belongs to the technical field of RNA detection. The preparation method comprises the following steps: S1, preparing an RNA positive quality control product: (1) designing and synthesizing a genome full-length sequence of a target RNA virus and preparing pseudovirus particles of protein capsid coated RNA; and (2) mixing each milliliter of the RNA positive quality control product with the pseudovirus particle stock solution corresponding to each target RNA virus i according to a preset relative abundance ppRi. When the quality control product is prepared from the raw materials, enough quality control products can be produced in a single batch, so that the long-time use of a user can be met, and the frequency of batch replacement is greatly reduced; even if the batch is changed and the pathogen concentration in the raw material is fixed, multiple times of repeated value fixing can be executed, the concentration level of the previous batch is gradually adjusted, then preparation is carried out according to the fixed input volume, and the uniformity of different batches is guaranteed to the maximum extent.

Description

Technical Field

[0001] This invention belongs to the field of RNA detection technology, specifically relating to a non-fixed-value composite quality control product for high-throughput sequencing of RNA pathogen metagenomics and its preparation method. Background Technology

[0002] The rapid development of next-generation sequencing (NGS) technology has made metagenomic sequencing a powerful tool for analyzing microbial communities in complex samples. This method can comprehensively capture the genomic information of microorganisms in a sample, enabling the simultaneous identification of multiple pathogens, and showing broad prospects in infectious disease diagnosis, microbial ecology research, and other fields. The advantages of metagenomic sequencing lie in its unbiasedness and ability to discover unknown pathogens, but it also faces challenges such as the easy degradation of RNA samples, low viral abundance, strong host interference, and inconsistent analytical algorithms. In the field of quality control, existing methods often rely on synthetic cDNA fragments or inactivated viruses as positive controls and blank buffers as negative controls; however, these protocols lack standardization, leading to significant differences in results between laboratories and insufficient reproducibility.

[0003] Existing quality control products are mainly divided into commercial and self-made quality control products. While commercial quality control products are convenient to use, they have limited target coverage, high costs, and poor stability. Self-made quality control products, although economical, are complex to prepare, cannot fully simulate the characteristics of RNA in clinical samples, and exhibit large batch-to-batch variability. With the increase in NGS read length and throughput, its application in clinical diagnosis is growing, placing higher demands on the RNA stability, multi-virus compatibility, and traceability of quality control products. Currently, quality control products often neglect the degradation susceptibility, abundance gradient continuity, and simulation of human background of RNA viruses, resulting in an inability to comprehensively control the efficiency of RNA extraction and the accuracy of sequencing. The market lacks composite quality control products that integrate multiple RNA viruses from different species with human host backgrounds, failing to meet the diverse needs of NGS. Therefore, there is an urgent need to establish an innovative quality control system for RNA pathogen metagenomic sequencing and develop novel preparation methods for RNA pathogen metagenomic quality control products to ensure that the entire detection process can be monitored, thereby ensuring the reliability of results.

[0004] Currently, the main technical solutions for quality control in metagenomic sequencing of RNA pathogens fall into three categories: synthetic nucleic acid quality control products, pathogen culture material quality control products, and mixed matrix quality control products. Synthetic nucleic acid quality control products are mainly prepared through chemical synthesis and plasmid cloning techniques. Chemical synthesis can obtain oligonucleotide fragments of 20-200 bp, and longer sequences can be constructed through PCR amplification and fragment ligation. Plasmid cloning techniques can amplify target gene fragments of 0.1-15 kb.

[0005] Pathogenic microorganism culture control materials are mainly prepared by inactivating pathogens. Inactivation methods include heat inactivation (56-121℃), irradiation (gamma rays or electron beams), and treatment with chemical reagents (formaldehyde, β-propiolactone, etc.). Pathogens that have undergone inactivation treatment can be used as quality control materials to evaluate the sensitivity and specificity of detection methods.

[0006] Mixed matrix quality control products mainly include cell line matrices and clinical sample simulants. Cell line matrices are prepared using human immortalized cell lines, primary cultured cells, or genetically engineered cells, and are obtained through steps such as cell culture amplification, collection and counting, and lysis to extract nucleic acids; clinical sample simulants are prepared by mixing multiple clinical specimens and adding known concentrations of pathogens.

[0007] Existing technologies have led to the development of various products for commercial applications, including quality control products from both international and domestic manufacturers, which are used in scenarios such as inter-laboratory quality assessment, methodology validation, and routine quality control.

[0008] Current metagenomic sequencing technology for RNA pathogens has the following problems in the field of laboratory quality control: 1. While existing synthetic nucleic acid quality control products offer the advantage of sequence control, their application is limited in several ways. Due to limitations in synthesis technology, synthetically produced DNA fragments are generally short, making it difficult to simulate a complete pathogen genome. Furthermore, quality control products obtained through plasmid cloning exhibit DNA conformations that differ significantly from natural ribonucleic acid (RNA), failing to accurately reflect the RNA characteristics in clinical samples. In addition, the high costs of chemical synthesis and plasmid cloning technologies make it difficult to achieve a balance between economic efficiency and cost-effectiveness in large-scale production.

[0009] 2. The preparation and application of quality control materials for pathogenic microorganisms face numerous technical bottlenecks. Many important pathogens, due to their specific growth requirements or biosafety requirements, are difficult to cultivate and require high-level biosafety facilities. During the preparation process, regardless of the inactivation method used, the nucleic acids of the pathogen may be damaged to varying degrees, reducing the reliability of the quality control materials. This problem is particularly prominent in the preparation of quality control materials for RNA viruses, because RNA molecules are inherently extremely unstable and easily degraded during inactivation. Furthermore, differences in the growth status of different batches of cultures lead to significant batch-to-batch variations in the final product, making standardized production difficult.

[0010] 3. Mixed matrix quality control products offer unique advantages in simulating real clinical samples, but their preparation process faces multiple challenges. When using cell lines to prepare quality control products, the growth state of the cells is difficult to control precisely, leading to fluctuations in product quality. The preparation of clinical sample simulants is limited by the source of the samples, making it difficult to consistently obtain sufficient quantities of raw materials. Furthermore, due to the complexity of the matrix composition, interference from various physicochemical factors can affect the performance of the quality control products. These characteristics make the standardized production and large-scale application of mixed matrix quality control products quite difficult.

[0011] 4. Current commercial quality control products generally suffer from several common problems that severely restrict their widespread application. First, the high production cost of existing quality control products leads to expensive prices and increases laboratory operating costs. Second, the poor stability of these products, requiring strict storage and transportation conditions, causes numerous inconveniences in logistics and use. Furthermore, insufficient traceability makes it difficult to establish a unified quality standard system. Finally, due to limitations in the production process, the uniformity between different batches of products is difficult to guarantee, affecting the comparability of test results.

[0012] 5. Currently, there is no comprehensive quality control system on the market that can simultaneously meet the detection needs of multiple RNA pathogens. Most existing quality control products are designed for a single type of pathogen or a single detection process. Traditional quality control products are mostly developed for traditional molecular detection methods such as PCR, and their design concepts and performance characteristics are difficult to meet the multiplex quality control requirements of metagenomic sequencing. This singularity forces laboratories to purchase and use multiple quality control products simultaneously, which not only increases testing costs but may also affect result interpretation due to performance differences between different quality control products. Furthermore, due to the lack of unified quality control standards, it is difficult to effectively compare test results between different types of quality control products. This situation makes it difficult for laboratories to comprehensively evaluate the detection performance of RNA pathogen metagenomic sequencing and to accurately control the quality of detection results for different species of RNA pathogens.

[0013] 6. Lack of standardized quality control system: The existing internal quality control for RNA pathogen metagenomic sequencing lacks unified positive and negative control materials, making it impossible to effectively assess the sensitivity, specificity, and accuracy of the sequencing process.

[0014] 7. Insufficient simulation of real samples by quality control products: Some quality control products are prepared only from synthetic fragments or samples from a single source, which makes it difficult to simulate the complex sample background of humans and the actual proportion of RNA pathogens.

[0015] 8. Difficulty in verifying technical performance: Existing quality control products are mostly limited to a single detection technology and cannot be adapted to the widespread application of next-generation sequencing (NGS) technology in RNA pathogen metagenomic analysis, lacking versatility and flexibility. Summary of the Invention

[0016] To address the aforementioned problems in existing technologies, this invention provides a non-fixed-value composite quality control product for high-throughput sequencing of RNA pathogen metagenomics and its preparation method.

[0017] The technical solution of the present invention is as follows: A method for preparing a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens, comprising the following steps: S1. Preparation of RNA positive control samples: (1) Design and synthesize the full-length genome sequence of the target RNA virus and prepare pseudovirus particles with protein capsids encapsulating RNA; (2) Each milliliter of RNA positive control sample was prepared at the following preset relative abundance. p pRi Mix the stock solutions of pseudovirus particles corresponding to each target RNA virus i; The mixing process includes the following steps: 1) According to the formula ( a Calculate the number of copies that need to be added for each target RNA virus i. N i : ( a ) formula( a )middle, N base This represents the initial copy number added to the baseline RNA virus. p pRi The preset relative abundance of target RNA virus i; p pRbase The preset relative abundance representing the baseline RNA virus base; The target RNA virus i is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus, human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The baseline RNA virus is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus or human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The target RNA virus i is not the same as the baseline RNA virus base; The initial copy number added to the baseline RNA virus base N base Not higher than 10 8 Any value within the range of copies / mL; 2) According to the formula ( b1 )and( b2 Calculate the initial volume of the pseudovirus particle stock solution corresponding to target RNA virus i. V pR1i and the initial input volume of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. V pR1base : ( b1 ) ( b2 ) formula( b1 )and( b2 )middle, C i The copy number concentration is the pseudovirus particle stock solution corresponding to target RNA virus i. C base The copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base; 3) Calculated according to step 2). V pR1i and V pR1base The pseudovirus particle stock solutions corresponding to each target RNA virus i and the pseudovirus particle stock solutions corresponding to the baseline RNA virus base were mixed separately, and finally protein preservation solution was added to form a sample. 4) Take 20%-40% of the sample volume and add it to human NC146 cells. Construct a library using RNA pathogen metagenomic sequencing technology, perform sequencing, and conduct bioinformatics analysis to obtain the standardized sequence number of the target RNA virus i aligned to the species. R R1i And the number of sequences aligned to the species after standardization of the baseline RNA virus base. R R1base ; 5) According to the formula ( c Calculate the actual volume of pseudovirus particle stock solution added corresponding to the baseline RNA virus base. V pR2base This allows the value obtained from bioinformatics analysis of the baseline RNA virus to be determined. R R2base Adjust to the range of 0 to 1000; (c ) Mode( c )middle, R R2base Randomly assign values ​​within the range of 0 to 1000 and R R2base ≠0; Benchmark RNA virus base Corresponding pseudovirus particles and target RNA virus i The corresponding pseudovirus particles each R R2i Satisfy the following formula ( d Conversion relationships: ( d ) formula( d )middle, R R2i Representative RNA virus i The number of valid sequences after adjustment of the corresponding pseudovirus particles; R R2base Representative RNA virus base The corresponding pseudovirus particles were adjusted to have an effective sequence count in the range of 0 to 1000. p pR2i Representative RNA virus i The corresponding preset relative abundance of pseudovirus particle stock solution, p pR2base Representative RNA virus base The preset relative abundance of the corresponding pseudovirus particle stock solution; 6) The adjusted effective sequence number of the pseudovirus particle corresponding to the target RNA virus i, calculated based on step 5). R R2i Using the formula ( e Calculate the actual volume of pseudovirus particle stock solution added for each target RNA virus i. V pR2i : ( e ) 7) The pseudovirus particle stock solution corresponding to the baseline RNA virus base and the pseudovirus particle stock solution corresponding to each target RNA virus i are calculated according to steps 5) and 6). V pR2base and V pR2i The mixture is then added to a protein preservation solution to obtain an RNA-positive quality control sample.

[0018] In step (1) of S1, the preparation of pseudovirus particles with protein caps encapsulated RNA refers to: using an intracellular expression assembly system constructed with the E. coli phage system, transfecting E. coli, and obtaining pseudovirus particles with protein caps encapsulated RNA through fermentation, lysis and purification processes. Preferably, prior to the mixing step 1), the copy number concentration of the pseudovirus particle stock solution corresponding to the target RNA virus i is determined using digital PCR. C i and the copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. C base Perform absolute quantification; Preferably, the pseudovirus particle stock solutions corresponding to each target RNA virus i and their respective relative abundances are as follows: novel coronavirus 25%, human respiratory syncytial virus type B 25%, human metapneumovirus 15%, human parainfluenza virus type 1 10%, rhinovirus type B 10%, influenza B virus 7.5%, and human immunodeficiency virus type 1 7.5%.

[0019] After preparing pseudovirus particles with protein capsids encapsulating RNA, the pseudovirus particles were collected and purified, and then diluted in protein preservation solution.

[0020] The protein preservation solution is MS2 protein preservation solution.

[0021] The method for preparing a non-fixed-value composite quality control for high-throughput sequencing of RNA pathogen metagenomics further includes the following steps: S2. Preparation of negative quality control: human cell line precipitate free from virus or other exogenous microbial contamination after 3-5 washings of human cell lines.

[0022] A non-valued composite quality control for high-throughput metagenomic sequencing of RNA pathogens is prepared using the aforementioned preparation method; the non-valued composite quality control includes: an RNA positive quality control.

[0023] RNA-positive quality control samples contain the following components in relative abundance: 25% novel coronavirus, 25% human respiratory syncytial virus type B, 15% human metapneumovirus, 10% human parainfluenza virus type 1, 10% rhinovirus type B, 7.5% influenza B virus, and 7.5% human immunodeficiency virus type 1. Preferably, the non-fixed value composite quality control product further includes: negative quality control product; the negative quality control product includes: human cell line precipitate that has been washed 3-5 times and is free from virus or other exogenous microorganism contamination.

[0024] The human-derived cell line refers to a cell line obtained by immortalizing human-derived cells and allowing for in vitro passage.

[0025] Human cell line precipitate contains 1×105 Each cell.

[0026] The human cell line is a cell line free from viral or other exogenous microbial contamination.

[0027] The innovation of this invention lies in: 1. Provide a standardized quality control system: A dual internal quality control system was constructed using innovatively designed RNA positive (RPC) and negative (NC) quality control products to evaluate the sensitivity, specificity, and consistency of RNA pathogen metagenomic sequencing.

[0028] 2. Simulates real sample background: The quality control material contains fake virus particles and human host cell background in precise proportions, which can highly simulate the complexity of real clinical samples.

[0029] 3. Supports multiple detection technologies: The quality control products are compatible with next-generation sequencing (NGS) platforms, support RNA detection workflows, and can be widely used in clinical, research and laboratory standardized testing.

[0030] 4. Innovative relative abundance gradient design: RNA pathogens in the quality control samples are designed in a gradient ratio from high to low to form a continuous relative abundance gradient, which can comprehensively evaluate the detection system's ability to detect pathogens of different abundances.

[0031] The beneficial effects of the present invention are as follows: First, this invention achieves complete coverage of the entire RNA pathogen metagenomic sequencing workflow by integrating multiple quality control methods. The RNA positive control utilizes pseudovirus particle technology, solving the instability problem of RNA virus control products; the negative control provides a realistic human background, ensuring detection specificity. The overall design scheme of the composite quality control system, the combination design of RNA positive and negative control products, and the specific ratio of the two types of control products are all presented. This invention is the first to propose and implement an innovative design of composite RNA pathogen metagenomic sequencing quality control products. By integrating RNA pseudoviruses and human background cell precipitates into the same quality control system, a complete quality control scheme is constructed. The RNA positive control utilizes pseudovirus particle technology to ensure stability, while the negative control provides a realistic human background to guarantee detection specificity, achieving an innovative breakthrough in the quality control system.

[0032] Secondly, this invention employs pseudovirus particle technology to prepare RNA virus quality control products, avoiding the risks and nucleic acid damage associated with live virus culture and inactivation, while ensuring the stability of the RNA quality control products, thus overcoming the technical bottlenecks in the preparation of existing RNA virus quality control products. By mixing pseudovirus particles with human background cell precipitates to prepare quality control products with a fixed ratio, it effectively simulates the real situation of RNA virus contamination with a large number of human host cells in clinical samples, ensuring the comparability and accuracy of sequencing results. This invention utilizes an efficient and reliable production process, successfully avoiding the risks associated with live virus culture and inactivation through pseudovirus technology, ensuring batch-to-batch stability through standardized preparation processes, and guaranteeing the reliability of test results through precise quantitative design, significantly improving the production efficiency and product quality of quality control products.

[0033] Third, this invention achieves precise quantification and batch-to-batch uniformity of quality control products through standardized preparation processes and formulation design. By adding human cell precipitate to RNA-positive quality control products and using negative quality control products prepared with human cells, a complex background system highly similar to clinical samples is successfully constructed, providing a more realistic quality control effect. Full-process adaptability: The quality control products are applicable to the entire workflow of metagenomic sequencing, including RNA extraction, library construction, and sequencing analysis, covering a wide range. This invention has significant advantages in simulating clinical samples. By innovatively mixing RNA-positive quality control products with human cell precipitate and using human cells to prepare negative quality control products, a realistic and complex nucleic acid background is provided, maximally simulating the actual situation of pathogens coexisting with host nucleic acids in clinical samples, ensuring the authenticity and reliability of quality control results.

[0034] Fourth, this invention is the first to propose the design concept of composite quality control products. By integrating multiple RNA viruses from different species and human background nucleic acids into a single quality control system, it overcomes the limitations of existing single quality control solutions, providing clinical laboratories with a complete quality control solution that can simultaneously meet the detection needs of different types of pathogens. Innovative simulated background: Human cell precipitates provide a complex nucleic acid background, accurately simulating the real environment in clinical samples. Stability and long-term storage: The quality control products undergo homogeneity and stability assessments to ensure consistent performance during short-term and long-term storage. This invention's quality control system achieves unprecedented comprehensive quality control coverage, simultaneously meeting the detection needs of multiple RNA pathogens from different species, supporting end-to-end quality control from sample processing to bioinformatics analysis, and is particularly suitable for high-throughput sequencing platforms such as NGS. Through the complementary advantages of different types of quality control products, multiple quality control functions are successfully achieved, overcoming the limitations of existing single quality control solutions.

[0035] Fifth, this invention employs an innovative abundance gradient design, forming a continuous gradient distribution from high to low by precisely controlling the relative abundance of pathogens. In the RNA-positive quality control, the gradient distribution from 25% SARS-CoV-2 to 7.5% HAVIDI not only comprehensively evaluates the detection system's ability to detect pathogens at different concentrations but also provides a reliable basis for determining the lower limit of detection sensitivity. This gradient design is significantly superior to the simple high and low concentration settings in existing quality control materials, providing a more comprehensive and accurate reference standard for clinical laboratories to evaluate the performance of the detection system. The innovative abundance gradient design: the relative abundance of pathogens is precisely formulated according to a gradient ratio from high to low, forming a continuous concentration gradient, which can effectively evaluate the detection sensitivity of the detection system for different concentrations of targets.

[0036] Sixth, this invention provides an innovative composite quality control system for RNA pathogen metagenomic sequencing quality control. It not only achieves quality control throughout the entire detection process but also significantly improves the accuracy and reliability of quality control by simulating the nucleic acid composition of real clinical samples. This effectively meets the requirements of clinical diagnosis for the stability, reliability, and comprehensiveness of quality control materials. Through the above innovative design, this invention's composite quality control system significantly improves the quality control level of RNA pathogen metagenomic sequencing, providing more reliable and comprehensive quality control assurance for clinical diagnosis. This invention provides an economical and practical quality control solution; a single quality control system can meet multiple quality control needs, effectively reducing laboratory procurement and usage costs. Simultaneously, the products have excellent stability, reducing storage and transportation requirements, and are simple and easy to operate, facilitating widespread application in clinical laboratories and demonstrating significant practical value.

[0037] In addition, the present invention also has the following beneficial effects: 1. The RNA pseudovirus of this invention covers the full length of the virus, and the genome exists in the form of RNA, which can simulate real clinical samples.

[0038] 2. The RNA-positive quality control of this invention is a pseudovirus, which is non-infectious, requires no inactivation, and is stored in MS2 protein preservation solution. It is stable and has low biosafety requirements, making it suitable for use in P2 and lower-level laboratories. The RNA-positive quality control can be produced in a standardized manner.

[0039] 3. The raw materials for this invention are stable and continuously available. The prepared quality control samples are stored in MS2 protein preservation solution, with a simple matrix composition, avoiding instability in test results due to interference from other factors. This achieves standardized production of quality control samples and ensures stable performance. RNA viruses exist in the form of pseudoviruses, with RNA encapsulated in a protein coat. These pseudoviruses are very stable when stored in protein preservation solution. RNA viruses are in pseudoviral form. Plasmids are introduced into E. coli or cells to achieve protein coat encapsulation and form pseudoviral particles. Theoretically, they can reproduce indefinitely. Since chemically synthesized plasmids are not used directly in large-scale production, cost control can be achieved during large-scale production.

[0040] 4. Existing quality control products are mostly targeted at single pathogens. To cover multiple types of RNA viruses from different species, multiple quality control products must be prepared and produced simultaneously, which increases material consumption and manpower hours exponentially, significantly increasing production costs. This invention covers multiple types of RNA pathogens in a single tube, reducing material consumption and manpower hours, and significantly reducing production costs. The raw materials used in this invention can be prepared in large quantities per batch. When using raw materials to prepare quality control products, a single batch can produce a sufficient quantity of quality control products, which can meet the user's needs for a long period of time, greatly reducing the frequency of batch changes. Even when changing batches, the pathogen concentration in the raw materials is determined by multiple repeated determinations, gradually adjusting to the concentration level of the previous batch, and then prepared according to a fixed input volume, maximizing the uniformity between different batches. The coefficient of variation (CV) in Experimental Example 1 reflects the uniformity of the quality control products of this invention.

[0041] 5. Experimental Examples 1-2 of this invention include RNA positive and negative control samples. These contain multiple pathogens of clinical interest, covering seven different viruses and encompassing the full-length genomes of the pathogens, thus meeting the requirements for RNA pathogen metagenomic sequencing. Theoretically, RNA pathogen metagenomic sequencing (mNGS) can detect all pathogens, unlike traditional molecular detection methods such as PCR which only detect specific pathogens. This invention covers multiple types of pathogens, eliminating the need for users to purchase multiple single-pathogen control samples and to construct separate libraries for sequencing and analysis. This invention only requires the construction of one RNA library, with 20 M reads of sequencing data for analysis, effectively reducing detection costs, eliminating performance differences between different types of control samples, and achieving simultaneous quality control of multiple pathogens in a single tube. This helps laboratories comprehensively evaluate the detection performance of RNA pathogen mNGS.

[0042] 6. Examples 1-2 of this invention include RNA positive and negative quality controls. In Example 1, the abundance of pathogens in the RNA positive quality control is set in a gradient from high to low, including concentration levels of moderate and weak positivity, which can effectively evaluate the sensitivity and accuracy of the sequencing process. Example 2 describes the operation method of the negative quality control, which can effectively evaluate the specificity and accuracy of the sequencing process. RPC is a positive quality control, focusing on sensitivity and accuracy, requiring the detection of the declared pathogens and that the relative abundance meets expectations; it does not evaluate specificity. The negative quality control is used to evaluate specificity.

[0043] 7. The RNA pseudoviruses contained in Experimental Example 1 of this invention all cover the full length of their respective genomes, effectively simulating real samples. When using the RNA positive control from Experimental Example 1, it must be added to the negative control, which contains human cell line precipitate, and both are involved in the extraction. The sequencing data ultimately shows a host ratio of over 99%, effectively simulating real clinical samples.

[0044] 8. Existing quality control products are mostly single-pathogen-containing products, often prepared from pseudoviruses or nucleic acids, covering only a portion of the pathogen's genome, and are only suitable for PCR-based in vitro diagnostic reagents. Example 1 of this invention prepared an RNA-positive quality control product containing multiple pathogens of clinical interest and covering the full-length genome of the pathogens, which can meet the requirements of RNA pathogen metagenomic sequencing. Some laboratories only perform mNGS detection of RNA, using only RNA-positive and negative quality control products. In the composite quality control product of this invention, RPC and NC are separate and independent in the kit, but can also be used together. The quality control product of this invention can meet the needs of such laboratories, demonstrating the flexibility of this invention. Attached Figure Description

[0045] Figure 1 Box plot showing the relative abundance of pathogens detected in the RNA-positive control (RPC) of Experiment 2 of this invention.

[0046] Figure 2 Line graph showing the relative abundance of pathogens detected in the RNA-positive control (RPC) of Experiment 2 of this invention. Detailed Implementation

[0047] The following detailed description of the present invention, in conjunction with the accompanying drawings, specific experimental examples, and experimental cases, does not limit the scope of protection of the present invention.

[0048] Sources of biomaterials I. The novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus, and human immunodeficiency virus type 1 used in Experiment Example 1 were all artificially prepared RNA pseudovirus particles, covering the complete genome sequence of each virus. The complete genome sequences of each virus can be downloaded from the NCBI database (the GenBank accession number for the novel coronavirus is NC_045512.2; the GenBank accession number for the human respiratory syncytial virus type B is NC_001781.1; the human...). The GenBank accession number for the complete genome sequence of metapneumovirus is NC_039199.1; the GenBank accession number for the complete genome sequence of human parainfluenza virus type 1 is NC_003461.1; the GenBank accession number for the complete genome sequence of rhinovirus type B is NC_038312.1; the GenBank accession number for the complete genome sequence of influenza B virus is KX614159.1; and the GenBank accession number for the complete genome sequence of human immunodeficiency virus type 1 is NC_001802.1. Escherichia coli was purchased from Beijing Solarbio Science & Technology Co., Ltd.

[0049] II. The human cell line used in Experiment 2 was LN229 (ATCC® CRL-2611™), sourced from the U.S. Type Culture Collection. Those skilled in the art can use nucleic acids from cell lines of different origins (such as other human cell lines, for example: GM12878 (human lymphoblastic cell line), HEK293 (human embryonic kidney cells, immortalized from healthy human embryonic kidney cells via adenovirus 5 (Ad5) DNA fragment), MCF-10A (mammary epithelial cells, healthy female breast tissue, non-tumorigenic immortalized cells), HUVEC (human umbilical vein endothelial cells, primary cells from the umbilical vein of healthy newborns, which can be passaged or immortalized)) to replace the LN229 cell genomic DNA used in this invention. The replacement will produce consistent and predictable results, which is routinely achievable by those skilled in the art. All of the above cell lines are commercially available.

[0050] Group 1 Examples: Preparation Method of Non-fixed Value Composite Quality Control Product of the Present Invention This set of embodiments provides a method for preparing a non-valued composite quality control for high-throughput metagenomic sequencing of RNA pathogens. All embodiments in this set share the following common feature: the method for preparing the non-valued composite quality control for high-throughput metagenomic sequencing of RNA pathogens includes the following steps: S1. Preparation of RNA positive control samples: (1) Design and synthesize the full-length genome sequence of the target RNA virus and prepare pseudovirus particles with protein capsids encapsulating RNA; (2) Each milliliter of RNA positive control sample was prepared at the following preset relative abundance. p pRi Mix the stock solutions of pseudovirus particles corresponding to each target RNA virus i; The mixing process includes the following steps: 1) According to the formula ( a Calculate the number of copies that need to be added for each target RNA virus i. N i : ( a ) formula( a )middle, N base This represents the initial copy number added to the baseline RNA virus. p pRi The preset relative abundance of target RNA virus i; p pRbase The preset relative abundance representing the baseline RNA virus base; The target RNA virus i is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus, human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The baseline RNA virus is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus or human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The target RNA viruses mentioned in this set of embodiments have the common technical meaning that is generally understood by those skilled in the art, for example, The term "novel coronavirus" can refer to the meaning of the word "novel coronavirus" as recorded in the article "An Exploration of the Construction of a Long-Term Mechanism for the Prevention and Control of Infections in Medical Laboratories After Novel Coronavirus Infection," or it can refer to the meaning of "novel coronavirus" in the Baidu Encyclopedia entry "novel coronavirus infection." Human respiratory syncytial virus type B can be understood as the term "human respiratory syncytial virus type B" as described in the article "Prospective study on diagnostic efficacy of targeted NGS vs. traditional testing for respiratory infections in myelosuppressed hematology patients"; Human metapneumovirus can refer to the meaning of the term "human metapneumovirus" as recorded in the article "Design of Metapneumovirus T-cell Epitope Vaccine Based on Reverse Vaccination Methods" or the meaning of the term "human metapneumovirus" in the Baidu Encyclopedia entry. Human parainfluenza virus type 1 can be the meaning of the term "human parainfluenza virus type 1" as recorded in the article "Etiological Distribution Characteristics and Drug Sensitivity Analysis of Acute Respiratory Infections in Children: A Single-Center Retrospective Study in Zhongshan City (2016-2022)".

[0051] Rhinovirus type B can be the meaning of the term "rhinovirus type B" as recorded in the article "Analysis of Viral Colonies in Bronchoalveolar Lavage Fluid of Patients with Unexplained Fever". The term "influenza B virus" can refer to the meaning of the article "Screening of antiviral activity of Houttuynia cordata and study on the mechanism of action against EV71 virus based on network pharmacology and molecular docking", or it can refer to the meaning of the Baidu Encyclopedia entry "influenza B virus". The term "human immunodeficiency virus type 1" can refer to the meaning of the term "human immunodeficiency virus type 1" as recorded in the article "Characteristics of Molecular Transmission Network and Drug Resistance Analysis of 123 Newly Reported HIV-1 Infections in Guiyang City," or it can refer to the meaning of the term "human immunodeficiency virus type 1" in the Baidu Encyclopedia entry.

[0052] The term "influenza A virus" can refer to the meaning of the word as recorded in the article "Analysis of Infection Results of 13 Respiratory Pathogens in Children in Hohhot Area in 2023," or it can refer to the meaning of the term "influenza A virus" in the Baidu Encyclopedia entry.

[0053] The term "measles virus" can refer to the meaning of the word "measles virus" as recorded in the article "Preparation of Measles Virus Monoclonal Antibody and Its Application in the Detection of Measles-Mumps-Russia Combined Attenuated Live Vaccine," or it can refer to the meaning of the term "measles virus" in the Baidu Encyclopedia entry.

[0054] The term "mumps virus" can refer to the meaning of the word "mumps virus" as recorded in the article "Establishment and Preliminary Validation of Mumps Virus Titer ELISA Detection Method", or it can refer to the meaning of the term "mumps virus" in the Baidu Encyclopedia entry.

[0055] The term "coronavirus" can refer to the meaning of the word as recorded in the article "Analysis of Infection Results of 13 Respiratory Pathogens in Children in Hohhot Area in 2023," or it can refer to the meaning of the term "coronavirus" in the Baidu Encyclopedia entry.

[0056] The term "Coxsackievirus" can refer to the meaning of the word as recorded in the article "A Study on the Composition and Epidemiological Characteristics of Hand-Foot-Mouth Disease Pathogens in Southern Guizhou Province from 2019 to 2024," or it can refer to the meaning of the term "Coxsackievirus" in the Baidu Encyclopedia entry.

[0057] Norovirus can refer to the meaning of the term "norovirus" as recorded in the article "Comparative Study on Different Enrichment and Concentration Methods of Norovirus in Urban Sewage", or it can refer to the meaning of the term "norovirus" in the Baidu Encyclopedia entry.

[0058] Enterovirus 71 can refer to the term "enterovirus (EV71)" as recorded in the Chinese Center for Disease Control and Prevention's "Guidelines for the Diagnosis and Treatment of Enterovirus (EV71) Infection (2008 Edition)," or it can refer to the term "enterovirus 71" as recorded in the Chinese Center for Disease Control and Prevention's "Technical Guidelines for the Use of Enterovirus 71 Inactivated Vaccine."

[0059] The term "Zika virus" can refer to either the meaning recorded in the article "Global Infectious Disease Event Risk Assessment in June 2025" or the meaning of the term "Zika virus" in the Baidu Encyclopedia entry.

[0060] The term "hepatitis B virus" can refer to the meaning of the word as recorded in the article "Global and Chinese Trends in Incidence and Mortality of Hepatitis B Virus-Related Liver Cancer and Age-Period-Cohort Model Analysis from 1992 to 2021," or it can refer to the meaning of the term "hepatitis B virus" in the Baidu Encyclopedia entry.

[0061] The term "Chikungunya virus" can refer to the meaning of the word as recorded in the article "Molecular Epidemiological Monitoring and Genetic Evolution Analysis of Japanese Encephalitis Virus in Four Border Provinces and Regions including Xinjiang," or it can refer to the meaning of the term "Chikungunya virus" in the Baidu Encyclopedia entry.

[0062] The genome size of the target RNA virus is selected from: novel coronavirus 29903 bp, human respiratory syncytial virus type B 15229 bp, human metapneumovirus 13350 bp, human parainfluenza virus type 1 15600 bp, rhinovirus type B 7208 bp, influenza B virus 14522 bp, and human immunodeficiency virus type 1 9181 bp. The genome sizes of other target RNA viruses not listed in this article can be obtained from the NCBI database. For example, the GenBank accession numbers for influenza A virus are OQ350815.1~OQ350822.1, measles virus is AB016162.1, mumps virus is AB000388.2, coronavirus is NC_006213.1, coxsackievirus is AF499643.1, norovirus is JX459908.1, enterovirus 71 is AF135886.1, Zika virus is KU501215.1, hepatitis B virus is AB033556.1, and chikungunya virus is AF369024.2.

[0063] The target RNA virus i is not the same as the baseline RNA virus base; The initial copy number added to the baseline RNA virus base N base Not higher than 10 8 Any value within the range of copies / mL; In practice, the target RNA virus can be selected from any RNA virus, which is routinely determined by those skilled in the art based on practical needs and testing requirements. After identifying the specific target RNA virus, the relative abundance of each target RNA virus can be preset according to its type and quantity, ensuring that the sum of each target RNA virus and its preset relative abundance in the quality control sample equals 100%. This is routinely determined and achieved by those skilled in the art based on the specific RNA virus type and quantity, combined with conventional technical knowledge reported in existing technologies.

[0064] The conventional technical knowledge reported in the prior art includes: 1. Editorial Board of Chinese Journal of Infectious Diseases. Expert consensus on the clinical application of metagenomics second-generation sequencing technology for detecting infectious pathogens in China [with corrections] [J]. Chinese Journal of Infectious Diseases, 2020, 38(11):681-689. DOI:10.3760 / cma.j.cn311365-20200731-00732.

[0065] 2. Expert consensus indicates that metagenomic second-generation sequencing can cover a wide range of pathogens, including viruses, fungi, bacteria, and parasites, regardless of whether the clinical sample culture is successful or not, as long as it contains detectable DNA or RNA.

[0066] 3. Knight, R., Vrbanac, A., Taylor, BC et al. Best practices for analyzing microbiomes. Nat Rev Microbiol 16, 410–422 (2018). https: / / doi.org / 10.1038 / s41579-018-0029-9. This article points out that relative abundance is inherently compositional data. Any effective statistical analysis must be normalized to a constant sum (e.g., 100%) to avoid spurious correlations.

[0067] The initial copy number added to the baseline RNA virus base N base The setting depends on the positive degree of the prepared quality control sample, which includes weak positive, medium positive and strong positive.

[0068] The choice of the baseline RNA virus can be arbitrary. If a weak positive control is to be prepared, it can be based on the description in "Zhang Dong, Zhang Jingjia, Du Juan, et al. Performance confirmation scheme for high-throughput sequencing of pathogen metagenomics [J]. Chinese Journal of Laboratory Medicine, 2022, 45(09): 899-905.DOI:10.3760 / cma.j.cn114452-20220721-00426" that "the minimum detection limit of the virus is not higher than 1000 copies / mL". Generally, the initial added copy number of the baseline virus is set to 2-4 times the minimum detection limit, which can be set within the range of not higher than 4000 copies / mL. If a medium positive control is to be prepared, the initial added copy number of the baseline virus is generally set within the range of 4000~10000 copies / mL. If a strong positive control is to be prepared, the initial added copy number of the baseline virus is generally set within the range of not higher than 10000 copies / mL and not higher than 10000 copies / mL. 8 The range of copies / mL is set; the initial number of copies added is set according to the minimum detection limit of the virus, which can be routinely adjusted and selected by those skilled in the art according to actual needs and practical experience.

[0069] 2) According to the formula ( b1 )and( b2Calculate the initial volume of the pseudovirus particle stock solution corresponding to target RNA virus i. V pR1i and the initial input volume of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. V pR1base : ( b1 ) ( b2 ) formula( b1 )and( b2 )middle, C i The copy number concentration is the pseudovirus particle stock solution corresponding to target RNA virus i. C base The copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base; 3) Calculated according to step 2). V pR1i and V pR1base The pseudovirus particle stock solutions corresponding to each target RNA virus i and the pseudovirus particle stock solutions corresponding to the baseline RNA virus base are mixed separately, and finally protein preservation solution is added to form a sample; in some specific embodiments, the final volume of the protein preservation solution added to form a sample is 1 ml.

[0070] 4) Take 20%-40% of the sample volume and add it to human NC146 cells. Construct a library using RNA pathogen metagenomic sequencing technology, perform sequencing, and conduct bioinformatics analysis to obtain the standardized sequence number of the target RNA virus i aligned to the species. R R1i And the number of sequences aligned to the species after standardization of the baseline RNA virus base. R R1base In some specific embodiments, adding 20%-40% of the sample volume to human NC146 cells means adding 300 μl of sample from 1 ml of sample to 1.0E+05 human NC146 cells.

[0071] In a specific embodiment, the sequence number R R1i It has the conventional technical meaning known to those skilled in the art; for example, it could mean the term "species-specific sequence number" as described in the article "Performance Validation Scheme for High-Throughput Sequencing of Pathogen Metagenomics".

[0072] Library construction, sequencing, and bioinformatics analysis were performed using metagenomic sequencing technology to obtain the sequence number of each target RNA pathogen.R R1i This operation is a routine technical operation well known to those skilled in the art. For specific operation methods, please refer to the method described in the article "Performance Validation Scheme for High-Throughput Sequencing of Pathogen Metagenomics".

[0073] 5) According to the formula ( c Calculate the actual volume of pseudovirus particle stock solution added corresponding to the baseline RNA virus base. V pR2base This allows the value obtained from bioinformatics analysis of the baseline RNA virus to be determined. R R2base Adjust to the range of 0 to 1000; ( c ) Mode( c )middle, R R2base Randomly assign values ​​within the range of 0 to 1000 and R R2base ≠0; Benchmark RNA virus base Corresponding pseudovirus particles and target RNA virus i The corresponding pseudovirus particles each R R2i Satisfy the following formula ( d Conversion relationships: ( d ) formula( d )middle, R R2i Representative RNA virus i The number of valid sequences after adjustment of the corresponding pseudovirus particles; R R2base Representative RNA virus base The corresponding pseudovirus particles were adjusted to have an effective sequence count in the range of 0 to 1000. p pR2i Representative RNA virus i The corresponding preset relative abundance of pseudovirus particle stock solution, p pR2base Representative RNA virus base The preset relative abundance of the corresponding pseudovirus particle stock solution; 6) The adjusted effective sequence number of the pseudovirus particle corresponding to the target RNA virus i, calculated based on step 5). R R2i Using the formula ( e Calculate the actual volume of pseudovirus particle stock solution added for each target RNA virus i.V pR2i : ( e ) 7) The pseudovirus particle stock solution corresponding to the baseline RNA virus base and the pseudovirus particle stock solution corresponding to each target RNA virus i are calculated according to steps 5) and 6). V pR2base and V pR2i The mixture is then added to a protein preservation solution to obtain an RNA-positive quality control sample.

[0074] In some specific embodiments, protein preservation solution was finally added to bring the total volume to 1 mL, resulting in an RNA-positive quality control sample.

[0075] In the practice of quality control sample preparation, the types and relative abundance values ​​of various RNA viruses in the quality control samples can be adjusted and preset according to the samples to be quality controlled, and it can be ensured that the quality control samples prepared with each RNA virus at the preset relative abundance can be obtained by following the preparation steps of the preparation method of the present invention. For example, in some embodiments, the target RNA virus and its preset relative abundance p pRi The following proportions were included: Novel Coronavirus 25%, Human Respiratory Syncytial Virus (HRSV) B 25%, Human Metapneumovirus 15%, Human Parainfluenza Virus 1 10%, Rhinovirus B 10%, Influenza B Virus 7.5%, and Human Immunodeficiency Virus 1 7.5%. The RNA pathogens in the quality control samples were designed in a gradient from high to low abundance to form a continuous relative abundance gradient, which can comprehensively evaluate the detection system's ability to detect pathogens of different abundances.

[0076] In a specific embodiment, the preparation of pseudovirus particles with protein caps wrapped around RNA in step (1) of S1 refers to: using an intracellular expression assembly system constructed with the E. coli phage system, transfecting E. coli, and obtaining pseudovirus particles with protein caps wrapped around RNA through fermentation, lysis and purification processes. Preferably, prior to the mixing step 1), the copy number concentration of the pseudovirus particle stock solution corresponding to the target RNA virus i is determined using digital PCR. C i and the copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. C base Perform absolute quantification; The absolute quantification of the copy number concentration of pseudovirus particle stock solution using digital PCR is a routine operation well known to those skilled in the art. For details, please refer to the method described in the article "Preparation and Application of Quality Control Products of Porcine Reproductive and Respiratory Syndrome Virus MS2 Armored Virus-like Particles" for digital PCR operation.

[0077] Preferably, the pseudovirus particle stock solutions corresponding to each target RNA virus i and their respective relative abundances are as follows: novel coronavirus 25%, human respiratory syncytial virus type B 25%, human metapneumovirus 15%, human parainfluenza virus type 1 10%, rhinovirus type B 10%, influenza B virus 7.5%, and human immunodeficiency virus type 1 7.5%.

[0078] In some embodiments, after preparing pseudovirus particles with protein capsids encapsulating RNA, the pseudovirus particles are collected and purified, and then diluted in a protein preservation solution.

[0079] Preparing pseudovirus particles with protein capsids encapsulating RNA is a routine technical procedure well-known to those skilled in the art. Specifically, refer to the preparation steps described in the article "Preparation and Application of Standard Quality Controls for Sendai Virus Pseudovirus Armored RNA". Purifying the pseudovirus particles is also a routine technical procedure well-known to those skilled in the art. Specifically, refer to the "Purification" steps described in the article "Development of Quality Controls for Type GII Norovirus Armored RNA".

[0080] In other embodiments, the protein preservation solution is MS2 protein preservation solution.

[0081] In a further embodiment, the method for preparing a non-fixed-value composite quality control for high-throughput sequencing of RNA pathogen metagenomics further includes the following step: S2. Preparation of negative quality control: human cell line precipitate free from virus or other exogenous microbial contamination by washing human cell lines 3-5 times.

[0082] The washing process described is a routine technical operation well-known to those skilled in the art; specifically, refer to the "ATCC Animal Cell Culture Guide (2023 Revised Edition)". Contamination and Biosafety The steps described in the "Chapter" are for washing.

[0083] Group 2 Examples, Non-fixed Value Composite Quality Control Products of the Present Invention This set of embodiments provides a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens. All embodiments in this set share the following common feature: they are prepared using any of the preparation methods described in the embodiments of Group 1; the non-fixed-value composite quality control includes: an RNA positive quality control. RNA-positive quality control samples contain the following components in relative abundance: 25% novel coronavirus, 25% human respiratory syncytial virus type B, 15% human metapneumovirus, 10% human parainfluenza virus type 1, 10% rhinovirus type B, 7.5% influenza B virus, and 7.5% human immunodeficiency virus type 1.

[0084] The aforementioned RNA pathogens are of greatest clinical concern, typically causing infections of the respiratory, bloodstream, or reproductive systems. The percentage values ​​involved in this invention are preset values ​​for user reference. This quality control product is a non-fixed-value quality control product, not a standard, requiring users to accumulate target values ​​through continuous testing for more than 20 days using their own detection systems. This invention's non-fixed-value composite quality control product can be used as a final product for market. The core innovation of this invention lies in the preparation method of this non-fixed-value composite quality control product. A characteristic of non-fixed-value quality control products is that the manufacturer does not provide specific values, only indicating the expected range or concentration gradient. The term "non-fixed-value" has the conventional technical meaning commonly understood by those skilled in the art; for example, it can refer to the meaning of "non-fixed-value" in the "3 Discussion" section of "Preparation and Performance Evaluation of Homocysteine ​​Quality Control Products," where it states that "quality control products are divided into fixed-value quality control products and non-fixed-value quality control products based on the presence or absence of measured values."

[0085] In a further embodiment, the non-fixed-value composite quality control material for high-throughput sequencing of RNA pathogen metagenomics further includes: a negative control material; the negative control material includes: a human cell line precipitate that has been washed 3-5 times and is free from viral or other exogenous microbial contamination.

[0086] In a specific embodiment, the human cell line refers to a cell line obtained by immortalizing human cells and then passaged in vitro.

[0087] In a more specific embodiment, the human cell line precipitate contained 1×10⁻⁶ 5 Each cell.

[0088] In some embodiments, the human cell line is a cell line free from viral or other exogenous microbial contamination.

[0089] This invention provides a composite quality control for high-throughput metagenomic sequencing of RNA pathogens and its preparation method. The quality control comprises an RNA positive control (RPC) and a negative control (NC), which can be used to evaluate the detection performance of the entire metagenomic sequencing pipeline for pathogens.

[0090] The key points of the technical solution of this invention are as follows: I. Specifications and Storage Conditions of Quality Control Products Quality control product name, specifications, and storage conditions RNA metagenomics positive control sample 0.5 mL / vial -20℃±5℃ Metagenomic negative cell quality control 1*10 5 Cells / branch -20℃±5℃ II. Composition of Quality Control Products 1. RNA positive control (RPC) • The controlled substances contain a rich variety of RNA viruses, covering important viral pathogens that can cause acute respiratory infections and chronic immune system infections in humans. These viruses can cause respiratory illnesses of varying degrees, ranging from the common cold to severe pneumonia, as well as syndromes that affect human immune function, and have significant clinical application value.

[0091] • It consists of artificially prepared pseudoviruses that mimic RNA viruses and is prepared using an intracellular expression and assembly system constructed using the E. coli phage system.

[0092] • The relative abundance of each RNA virus component of the RPC was set as follows: 25% for novel coronavirus, 25% for human respiratory syncytial virus type B, 15% for human metapneumovirus, 10% for human parainfluenza virus type 1, 10% for rhinovirus type B, 7.5% for influenza B virus, and 7.5% for human immunodeficiency virus type 1.

[0093] • The content of each RNA virus in the quality control samples also adopts a gradient decreasing design, showing a regular decrease from SARS-CoV-2 (25%) to human immunodeficiency virus type I (7.5%). This gradient distribution can effectively verify the sensitivity of the detection system to viruses of different abundances.

[0094] 2. Negative control (NC) • Composed of cell precipitates prepared from human cell lines.

[0095] • Used to simulate the complex nucleic acid background in human samples.

[0096] • Cell lines without a background of respiratory viral infection are preferred.

[0097] • The preferred cell number is 1.0 × 10⁻⁶. 5 Item / piece.

[0098] III. Innovative Aspects of Quality Control Product Preparation Methods 1. The RPC component utilizes an innovative pseudovirus preparation technology, which significantly improves the stability of RNA quality control products.

[0099] 2. The proportions of each component have been precisely calculated and verified, and an innovative gradient decreasing design has been adopted. The nucleic acid content of different pathogens shows regular differences (RNA viruses decrease from 25% to 7.5%), which not only ensures the reliability of the test results, but also comprehensively evaluates the detection system's ability to detect targets at different concentrations.

[0100] 3. By mixing pseudovirus particles with human background cell precipitates, a quality control sample with a fixed ratio is prepared, which can effectively simulate the real situation in clinical samples where RNA viruses are mixed with a large number of human host cells.

[0101] 4. The intra-batch variation of the component proportions was small, and the coefficient of variation (CV) was controlled within an acceptable and reasonable range, showing good homogeneity.

[0102] IV. Technical Effects 1. It can simultaneously evaluate the detection performance of multiple RNA pathogens from different species. 2. Simulate the nucleic acid composition characteristics of real clinical samples 3. Good intra-batch uniformity, with CV values ​​controlled within a reasonable range. 4. Simple storage conditions and convenient transportation The invention will be further described in detail below with specific experimental examples.

[0103] Experimental Example 1. Preparation and Detection of RNA Pathogen Metagenomic Positive Control (RPC) 1. Preparation of RPC: (1) Design and synthesize RNA virus genome sequences (whole genome sequences of each virus), and use the intracellular expression assembly system constructed by the E. coli phage system pET-30a(+) (Sangon Biotech (Shanghai) Co., Ltd., B540185-0001) and pACYCduet1 (Shanghai Zeye Biotechnology Co., Ltd., ZY1236) to transfect E. coli, and obtain a pseudovirus form of viral RNA encapsulated by a protein capsid through fermentation lysis and purification processes.

[0104] (2) Collect and purify pseudovirus particles, and then dilute them in protein preservation solution.

[0105] (3) Extract RNA from pseudovirus particles and perform quantitative detection.

[0106] (4) The RNA copy number concentration was detected using a one-step Hi RT-dPCR kit (product catalog number: 23307, Xinyi Manufacturing Technology (Beijing) Co., Ltd.). The reaction system consisted of a 30 μL reaction volume containing 9 μL of premix A, 3 μL of premix B, 5 μL each of bidirectional primers (10 μM), 2.5 μL of probe (10 μM), and 5.5 μL of RNA template + ddH2O. The PCR reaction program was as follows: the sample was incubated at 60℃ for 60 min for reverse transcription, followed by 40 cycles of incubation at 95℃ for 10 min, 94℃ for 30 s, 60℃ for 1 min, 98℃ for 10 min, and 12℃ for 5 min. The bidirectional primers and probes were conventionally designed and synthesized by those skilled in the art based on the genomic sequence of the target pathogen to be detected and with reference to the following literature: Edwards RL, Takach JE, McAndrew MJ, Menteer J, Lestz RM, Whitman D,Baxter-Lowe LA. Next generation multiplexing for digital PCR using a novelmelt-based hairpin probe design. Front Genet. 2023 Nov 10;14:1272964. doi:10.3389 / fgene.2023.1272964. PMID: 38028620; PMCID: PMC10667681. Wadle S, Lehnert M, Rubenwolf S, Zengerle R, von Stetten F. Real-time PCR probe optimization using design of experiments approach. Biomol DetectQuantif. 2015 Dec 30;7:1-8. doi: 10.1016 / j.bdq.2015.12.002. PMID: 27077046; PMCID: PMC4827641. Qiagen Digital PCR Detection Development Guide (https: / / www.qiagen.com / zh-cn / applications / digital-pcr / beginners / dpcr-guide / setup-and-troubleshooting) In practice, the entire process of digital PCR described above can also be outsourced to commercial biotechnology companies (e.g., NewYi Manufacturing Technology (Beijing) Co., Ltd.), which includes the design and synthesis of bidirectional primers and probes. This is something that can be routinely done by those skilled in the art. Due to space limitations, the primer sequences will not be described in detail here.

[0107] (5) Based on the digital PCR quantification results, the copy number concentration of pseudovirus particles of each pathogen was estimated, and the components were mixed according to the preset ratio. The relative abundance of RNA viruses in each RPC component was set as follows: novel coronavirus 25%, human respiratory syncytial virus type B 25%, human metapneumovirus 15%, human parainfluenza virus type 1 10%, rhinovirus type B 10%, influenza B virus 7.5%, and human immunodeficiency virus type 1 7.5%. The copy number ratio of each pathogen RNA was normalized in RPC according to the copy number of pseudovirus particles of the pathogen, and the target sequence number after normalization was set to 100-5000.

[0108] (6) The prepared RPCs were packaged and stored at -20℃±5℃.

[0109] 2. RPC Operating Procedures: (1) Thaw the RNA metagenomic positive control sample at room temperature for 15 minutes, vortex for 15 seconds, and then centrifuge briefly; (2) Transfer all of the above RPCs to a blank NC146 tube and mix them again by shaking. (3) Take 200 μL of the mixed RPC into a centrifuge tube containing UMSI and wait for extraction; (4) Prepare the lysis reaction solution and use the QIAamp Viral RNA Purification Mini Kit (52906, QIAGENGmbH, USA) to extract and purify RNA; (5) RPC purification, reverse transcription, synthesis of two strands, and purification after two strands; (6) RPC library construction follows the DPC steps; (7) Library purification: RPC library concentration was determined using a Qubit 4.0 fluorescence quantitative quantification instrument; (8) Document Library Computer Reference DPC.

[0110] Part 2, “RPC Operating Procedures,” describes the operational steps for using quality control materials to perform quality control on routine laboratory tests, and is unrelated to the preparation of the quality control materials.

[0111] 3. Evaluation of inter-bottle homogeneity in RPC (1) Randomly select 4 RPCs, test 1 one per day, and monitor continuously for 4 days.

[0112] (2) Based on the results of continuous monitoring, assess the inter-bottle homogeneity of RPC. Record the data volume, host rate, number of detected sequences, and relative abundance of the quality control samples, and calculate the number of sequences, relative abundance, mean, and CV. Relative abundance is the number of single target sequences of the pathogen divided by the total number of target sequences.

[0113] (3) All metagenomic sequencing quality control indicators were qualified. Table 1 shows the data analysis results, and the positive control samples showed that all expected pathogenic microorganisms were detected; Table 2 and... Figure 1 The results showed that the sequencing results (all measured values ​​in Table 2) were basically similar to the preset relative abundance of bacterial communities. The CV (coefficient of variation) values ​​of the four replicate experiments were within the acceptable range, and the intra-batch bottle homogeneity was qualified. It can be used as an RNA positive quality control for metagenomic high-throughput sequencing. Figure 2 A line graph showing the mean of the measured values ​​from four repeated experiments and the preset values ​​shows a very high degree of fit between the two lines, indicating that the relative abundance set by the quality control sample meets expectations, which proves the accuracy of RPC preparation.

[0114]

[0115]

[0116] Experimental Example 2. Preparation and Detection of Negative Controls (NC) 1. Preparation of NC: (1) Human cell lines refer to cell lines that can be passaged in vitro after being immortalized from human cells, preferably cell lines without respiratory tract infection virus background.

[0117] (2) Cell precipitate refers to cryopreserved cells after removing the culture medium and eliminating contamination. Select cell precipitates that have been washed multiple times (3-5 times) and are free from virus or other exogenous microbial contamination. Store at -80 degrees Celsius or lower for a long time.

[0118] (3) The number of cells contained in the cell pellet is consistent with the number of cells obtained from human respiratory tract samples, preferably containing 1×10⁻⁶ cells. 5 Cell count (using a cell counting chamber, repeat the count 3 times to control the cell count in the quality control sample at this level).

[0119] 2. Procedure for using metagenomic negative cell control (DNC / RNC): (1) Take a tube of NC low-speed centrifugation, add 500μL of physiological saline, and set aside for use; (2) Take 300 μL of the NC and DNC that have been added with physiological saline and extract them for library construction according to the DPC operation procedure; (3) Take 200 μL of RNC and extract, reverse transcribe, construct the library and load it into the instrument according to the RPC operation procedure; (4) DNC and RNC both come from NC in (1) above.

[0120] Part 2, "Metagenomic Negative Cell Control (DNC / RNC) Procedures," describes the operational steps for using control products to perform quality control on routine laboratory tests, and is unrelated to the preparation of the control products.

[0121] 3. Evaluation of inter-bottle uniformity in NC Data volume, host ratio, number of detected sequences, and relative abundance of quality control samples are all recorded, and the number of sequences, relative abundance, mean, and CV are calculated. If all metagenomic sequencing quality control indicators are met, and the negative control sample does not detect the expected pathogenic microorganisms present in the positive control sample, thus meeting the requirements for using the negative control sample, the absence of pathogen detection demonstrates specificity. NC does not require evaluation of uniformity and accuracy.

Claims

1. A method for preparing a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens, characterized in that, Includes the following steps: S1. Preparation of RNA positive control samples: (1) Design and synthesize the full-length genome sequence of the target RNA virus and prepare pseudovirus particles with protein capsids encapsulating RNA; (2) Each milliliter of RNA positive control sample was prepared according to the preset relative abundance. p pRi Mix the stock solutions of pseudovirus particles corresponding to each target RNA virus i; The mixing process includes the following steps: 1) According to the formula ( a Calculate the number of copies that need to be added for each target RNA virus i. N i : （ a ） formula( a )middle, N base This represents the initial copy number added to the baseline RNA virus. p pRi The preset relative abundance of target RNA virus i; p pRbase The preset relative abundance representing the baseline RNA virus base; The target RNA virus i is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus, human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The baseline RNA virus is selected from: novel coronavirus, human respiratory syncytial virus type B, human metapneumovirus, human parainfluenza virus type 1, rhinovirus type B, influenza B virus or human immunodeficiency virus type 1, influenza A virus, measles virus, mumps virus, coronavirus, Coxsackie virus, norovirus, enterovirus 71, Zika virus, hepatitis B virus, and chikungunya virus. The target RNA virus i is not the same as the baseline RNA virus base; The initial copy number added to the baseline RNA virus base N base Not higher than 10 8 Any value within the range of copies / mL; 2) According to the formula ( b1 )and( b2 Calculate the initial volume of the pseudovirus particle stock solution corresponding to target RNA virus i. V pR1i and the initial input volume of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. V pR1base : （ b1 ） （ b2 ） formula( b1 )and( b2 )middle, C i The copy number concentration is the pseudovirus particle stock solution corresponding to target RNA virus i. C base The copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base; 3) Calculated according to step 2). V pR1i and V pR1base The pseudovirus particle stock solutions corresponding to each target RNA virus i and the pseudovirus particle stock solutions corresponding to the baseline RNA virus base were mixed separately, and finally protein preservation solution was added to form a sample. 4) Take 20%-40% of the sample volume and add it to human NC146 cells. Construct a library using RNA pathogen metagenomic sequencing technology, perform sequencing, and conduct bioinformatics analysis to obtain the standardized sequence number of the target RNA virus i aligned to the species. R R1i And the number of sequences aligned to the species after standardization of the baseline RNA virus base. R R1base ; 5) According to the formula ( c Calculate the actual volume of pseudovirus particle stock solution added corresponding to the baseline RNA virus base. V pR2base This allows the value obtained from bioinformatics analysis of the baseline RNA virus to be determined. R R2base Adjust to the range of 0 to 1000; （ c ） Mode( c )middle, R R2base Randomly assign values ​​within the range of 0 to 1000 and R R2base ≠0; Benchmark RNA virus base Corresponding pseudovirus particles and target RNA virus i The corresponding pseudovirus particles each R R2i Satisfy the following formula ( d Conversion relationships: （ d ） formula( d )middle, R R2i Representative RNA virus i The number of valid sequences after adjustment of the corresponding pseudovirus particles; R R2base Representative RNA virus base The corresponding pseudovirus particles were adjusted to have an effective sequence count in the range of 0 to 1000. p pR2i Representative RNA virus i The corresponding preset relative abundance of pseudovirus particle stock solution, p pR2base Representative RNA virus base The preset relative abundance of the corresponding pseudovirus particle stock solution; 6) The adjusted effective sequence number of the pseudovirus particle corresponding to the target RNA virus i, calculated based on step 5). R R2i Using the formula ( e Calculate the actual volume of pseudovirus particle stock solution added for each target RNA virus i. V pR2i : （ e ） 7) The pseudovirus particle stock solution corresponding to the baseline RNA virus base and the pseudovirus particle stock solution corresponding to each target RNA virus i are calculated according to steps 5) and 6). V pR2base and V pR2i The mixture is then added to a protein preservation solution to obtain an RNA-positive quality control sample.

2. The method for preparing a non-valued composite quality control for high-throughput metagenomic sequencing of RNA pathogens according to claim 1, characterized in that, In step (1) of S1, the preparation of pseudovirus particles with protein caps encapsulated RNA refers to: using an intracellular expression assembly system constructed with the E. coli phage system, transfecting E. coli, and obtaining pseudovirus particles with protein caps encapsulated RNA through fermentation, lysis and purification processes. And / or, prior to step 1) of the mixing, the copy number concentration of the pseudovirus particle stock solution corresponding to target RNA virus i is determined using digital PCR. C i and the copy number concentration of the pseudovirus particle stock solution corresponding to the baseline RNA virus base. C base Perform absolute quantification; And / or, the pseudovirus particle stock solutions corresponding to each target RNA virus i and their respective relative abundances are as follows: novel coronavirus 25%, human respiratory syncytial virus type B 25%, human metapneumovirus 15%, human parainfluenza virus type 1 10%, rhinovirus type B 10%, influenza B virus 7.5%, and human immunodeficiency virus type 1 7.5%.

3. The method for preparing a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens according to claim 2, characterized in that, After preparing pseudovirus particles with protein capsids encapsulating RNA, the pseudovirus particles were collected and purified, and then diluted in protein preservation solution.

4. The method for preparing a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens according to claim 3, characterized in that, The protein preservation solution is MS2 protein preservation solution.

5. A method for preparing a non-fixed-value composite quality control for high-throughput metagenomic sequencing of RNA pathogens according to any one of claims 1-4, characterized in that, It also includes the following steps: S2. Preparation of negative control: human cell line precipitate free from virus or other exogenous microorganism contamination by washing the human cell line 3-5 times.

6. A non-fixed-value composite quality control product for high-throughput metagenomic sequencing of RNA pathogens, characterized in that, The non-fixed value composite quality control product is prepared by any one of the preparation methods described in claims 1-5; the non-fixed value composite quality control product includes: RNA positive quality control product.

7. A non-fixed-value composite quality control product for high-throughput metagenomic sequencing of RNA pathogens according to claim 6, characterized in that, RNA-positive quality control samples contain the following components in relative abundance: 25% novel coronavirus, 25% human respiratory syncytial virus type B, 15% human metapneumovirus, 10% human parainfluenza virus type 1, 10% rhinovirus type B, 7.5% influenza B virus, and 7.5% human immunodeficiency virus type 1. And / or, the non-fixed value composite quality control product further includes: negative quality control product; the negative quality control product includes: human cell line precipitate that has been washed 3-5 times and is free from viral or other exogenous microbial contamination.

8. A non-fixed-value composite quality control product for high-throughput metagenomic sequencing of RNA pathogens according to claim 7, characterized in that, The human-derived cell line refers to a cell line obtained by immortalizing human-derived cells and allowing for in vitro passage.

9. A non-fixed-value composite quality control product for high-throughput metagenomic sequencing of RNA pathogens according to claim 7, characterized in that, Human cell line precipitate contains 1×10 5 Each cell.

10. A non-valued composite quality control product for high-throughput metagenomic sequencing of RNA pathogens according to any one of claims 7-9, characterized in that, The human cell line is a cell line free from viral or other exogenous microbial contamination.

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