High-throughput detection and information analysis and identification method for human ring virus group

Abstract

The invention provides a high-throughput detection and bioinformation analysis and identification method for a human ring virus group, the method comprises the whole process from reference database construction, sample processing, high-throughput sequencing to bioinformation analysis, and the technical scheme specifically comprises the following steps: step 1, constructing a human ring virus high-quality reference database; 2, performing high-throughput sequencing on the metagenome of the human sample; and step 3, a ring virus group biological information analysis process.

Description

Technical fields:

[0001] This invention relates to the field of biotechnology, and in particular to an interdisciplinary technology combining virology, high-throughput sequencing analysis, and bioinformatics. Specifically, it relates to a high-throughput detection and bioinformatics analysis method for identifying human anellovirus genomes, applicable to anellovirus diversity analysis, host immune status assessment, and viral spectrum analysis in related clinical studies. Background technology:

[0002] With the development of high-throughput sequencing (mNGS) technology, viromics research has gradually become an important means of elucidating human microecology and disease mechanisms. Anelloviridae, a group of viruses widely found in various human sample types such as blood, respiratory tract, and cerebrospinal fluid, has received increasing attention in recent years for clinical immune surveillance and personalized health assessment. However, there is currently no dedicated detection and analysis procedure for the human anellovirome, and related studies mainly use general metaviridical detection frameworks, which face many technical bottlenecks. First, conventional virus detection procedures are prone to problems such as incomplete assembly, unclear species identification, and missing functional annotations when faced with the extremely high genetic variability and structural complexity of anellovirs. Second, existing databases such as RefSeq lag significantly in sequence coverage and classification updates for anellovirs, severely affecting the sensitivity and accuracy of alignment and identification. Third, specific primer detection methods can only cover some known types, making it difficult to achieve systematic detection of the entire anellovirome spectrum and multiple subtypes. Furthermore, current data analysis procedures are fragmented and non-standardized, hindering the replication and validation of results and multi-center dissemination. Therefore, existing technologies have significant shortcomings in terms of detection sensitivity, species annotation, process standardization, and novel virus identification. There is an urgent need for a systematic, standardized, high-throughput, and adaptable method for detecting and analyzing ring viruses to improve the accuracy, completeness, and reproducibility of research. Purpose of the Invention:

[0003] This invention aims to address key technical challenges in current research on the human anelloviridae genome, including missing database information, insensitive detection methods, and non-standardized bioinformatics analysis procedures. Anelloviridae, one of the most abundant viruses in human blood, possesses extremely high genetic diversity and individual specificity, and holds broad potential for immune status monitoring and viromics research. However, existing technologies lack a complete, systematic, and scalable high-throughput detection and analysis scheme for the human anelloviridae genome. Therefore, this invention proposes a high-throughput detection and bioinformatics analysis method for the human anelloviridae genome, aiming to achieve the following objectives:

[0004] (1) Construct a systematic high-quality reference database of human ring viruses, covering comprehensive taxonomic lineage, standardized species nomenclature system and annotation information, to solve the problems of fragmentation, naming confusion and insufficient coverage of existing databases;

[0005] (2) Establish a set of experimental procedures for virus enrichment, library construction and high-throughput sequencing of human blood, respiratory tract and cerebrospinal fluid samples to improve the detection sensitivity and library construction efficiency of ring virus.

[0006] (3) Design a standardized and repeatable bioinformatics analysis process, covering key steps such as raw data quality control, comparison with a high-quality reference database of human ring viruses, abundance quantification, and viral community structure analysis, to ensure the scientific validity, comparability, and shareability of the analysis results.

[0007] This invention forms an integrated technical solution in terms of virus database construction, experimental procedure standardization, and bioinformatics analysis standardization. It can be widely applied in basic scientific research, clinical virus monitoring, and precision medicine, and has significant scientific value and translational prospects. Summary of the Invention:

[0008] This invention provides a method for high-throughput detection and bioinformatics analysis of human anelloviridae, covering the entire process from reference database construction, sample processing, high-throughput sequencing to bioinformatics analysis.

[0009] Therefore, the present invention provides a high-throughput detection and bioinformatics analysis method for human ring virome, the method comprising the following steps:

[0010] Step 1: Construct a high-quality reference database of human ring viruses;

[0011] Step 2: High-throughput sequencing of the human sample metagenomics was performed;

[0012] Step 3: Bioinformatics analysis process for ring virome.

[0013] Step 1 includes the following steps:

[0014] First, a comprehensive, accurately classified, and fully annotated human ringvirus reference database was constructed to provide high-quality standard support for subsequent ringvirus genome detection, bioinformatics analysis, and community structure research. The construction process of this database included key steps such as systematic retrieval of global sequence data, quality control, construction of species taxonomy standards, functional region annotation, development of phylogenetic and species identification processes, standardization and completion of meta-information, and extraction of human-derived sequences.

[0015] The specific steps are as follows:

[0016] (1) Comprehensive acquisition and preliminary cleaning of the ring virus genome sequence;

[0017] (2) Construction of an authoritative reference species system and establishment of an ORF annotation framework;

[0018] (3) ORF1 annotation and manual review of the target sequence;

[0019] (4) Species classification and phylogenetic analysis based on ORF1 sequences;

[0020] (5) Standardization and completion of meta-information and organization of structured data;

[0021] (6) Human samples were spliced ​​together using high-throughput sequencing to supplement the reference dataset;

[0022] Step 2 includes the following steps:

[0023] To achieve highly sensitive detection and omics analysis of the human ring virome across different clinical states and sample types, this invention integrates a standardized metagenomic high-throughput sequencing experimental workflow covering "sample collection – virus enrichment – ​​nucleic acid extraction – library construction and sequencing," ensuring that the obtained data possesses high reproducibility, representativeness, and clinical scalability. The specific steps are as follows:

[0024] (1) Sample collection and preservation;

[0025] (2) Virus enrichment treatment;

[0026] (3) Viral nucleic acid extraction;

[0027] (4) Reverse transcription and double-stranded cDNA synthesis;

[0028] (5) PCR amplification and sample purification;

[0029] (6) Quantitative detection and library construction.

[0030] Step 3 includes the following steps:

[0031] A standardized and reproducible high-throughput bioinformatics analysis workflow for human ring viromes was constructed, covering the complete steps of raw data quality control, comparative analysis, positive identification, quantitative calculation, and expression matrix construction. This provides a stable data foundation and a general analytical framework for subsequent virology and clinical research. The specific steps are as follows:

[0032] (1) Quality control of raw data;

[0033] (2) Identification by comparison with reference database;

[0034] (3) Identification and quantitative calculation of positive lineages;

[0035] (4) Expression matrix output and subsequent extended analysis.

[0036] In one embodiment of the present invention, step 1 further includes the following steps:

[0037] (1) Comprehensive acquisition and preliminary cleaning of the ring virus genome sequence

[0038] Based on the NCBI GenBank and Taxonomy databases, search criteria were set to systematically obtain all nucleic acid sequence records related to ring viruses worldwide, and the Biopython program tool was used for batch parsing.

[0039] (2) Construction of authoritative reference species system and establishment of ORF annotation framework

[0040] We introduced 173 standard species of ring viruses published by the International Committee on Taxonomy of Viruses (ICTV) as classification references, and obtained corresponding reference genomes and annotation information from the NCBI RefSeq database as the basis for core functional annotation. We constructed a complete reference species ORF1 annotation library, covering internationally known virus species, as the core supporting resource for subsequent annotation and comparison.

[0041] (3) ORF1 annotation and manual review of the target sequence

[0042] The target sequences were annotated with ORF1 using the Geneious Prime professional tool platform, and the accuracy and completeness of the annotation were ensured through the following multi-level manual verification and comparison standards: whether the ORF1 start terminus has a typical arginine-rich motif (ARM); whether the annotated sequence has complete start / stop codons and is translatable; whether the length of the ORF1 region is within a reasonable range compared with the reference species; for sequences with low similarity or structural abnormalities, AlphaFold2 was further used to perform structural prediction to verify the biological rationality of its ORF1 protein coding region.

[0043] (4) Species classification and phylogenetic analysis based on ORF1 sequences

[0044] An iterative species and genus classification labeling process was constructed: all complete ORF1 sequences were paired with reference species, their nucleotide or amino acid similarity was calculated, and their classification relationship was labeled based on the species classification threshold: sequences with similarity higher than 69% were classified as known species; sequences with similarity lower than 69% were identified as pseudo-novel species; all PNS sequences and reference species were used to construct an ORF1 phylogenetic tree, and genus-level information was further assigned based on the phylogenetic topology; if a new genus was identified, it was named a pseudo-novel genus.

[0045] (5) Meta-information standardization and completion and structured data organization

[0046] Based on existing literature and metadata standardization rules established in previous studies, the fields in each entry were systematically completed and structured. For records with missing, ambiguous, or non-standard descriptions, the following methods were used to improve them: manual cross-comparison was conducted using the original submission information and published literature; the attributes of "human samples" and "non-human mammalian samples" were clearly marked to ensure the distinguishability of different host sources in subsequent analyses; the sample type field was standardized and classified, and the country and region information was standardized to ISO-3166 encoding to facilitate data statistics and cross-regional comparative studies.

[0047] (6) Human samples were spliced ​​together using high-throughput sequencing to supplement the reference dataset.

[0048] Based on high-quality reference sequences in public databases, metagenomic sequencing data named "human clinical samples from our laboratory" were further introduced to splice, annotate, and supplement the ring virus sequences.

[0049] In one embodiment of the present invention, step 2 further includes the following steps:

[0050] (1) Sample collection and preservation

[0051] The samples involved include human samples such as blood samples (plasma and serum), respiratory samples (pharyngeal swabs, nasopharyngeal swabs) or cerebrospinal fluid samples, all of which were derived from adult populations who were clinically diagnosed as suspected viral infections or healthy controls;

[0052] (2) Virus enrichment treatment

[0053] Pretreatment was performed in a BSL-2 biosafety environment. Samples underwent thawing, mixing, and low-speed and high-speed centrifugation to remove large particles and host cells, yielding a supernatant containing viral particles. The supernatant was then subjected to double purification and concentration via filtration through a 0.22 μm membrane and a 100 kDa ultrafiltration membrane. The volume was adjusted to 170 μL, and a lysis mixture containing enzymes such as Turbo DNase, Benzonase, and RNase was added. The mixture was then digested at 37°C for 30 minutes to maximize the removal of free host nucleic acids, thereby enriching viral particle nucleic acids.

[0054] (3) Viral nucleic acid extraction

[0055] Nucleic acid extraction was performed using the QIAamp Viral RNA Kit from QIAGEN, combined with standardized operating procedures, to achieve efficient recovery of viral RNA and DNA and avoid contamination or bias in downstream analysis.

[0056] (4) Reverse transcription and double-stranded cDNA synthesis

[0057] Using SuperScript TM The IV First-Strand Synthesis system and primer K-8N (5'-GACCATCTAGCGACCTCCACNNNNNNNN-3') with a random tail are used to synthesize the first-strand cDNA; then the Klenow enzyme and the same primer are used to complete the second-strand synthesis to generate double-stranded cDNA, ensuring the integrity and universality of the reverse transcription product.

[0058] (5) PCR amplification and sample purification

[0059] Using random primer K (5'-GACCATCTAGCGACCTCCAC-3') and Premix TM Taq enzyme was used for PCR amplification to increase the abundance of target sequences; the amplification products were purified using the QIAquick PCR Purification Kit to remove reaction system residues and non-specific products.

[0060] (6) Quantitative detection and library construction

[0061] The purified product was processed via Qubit TM The concentration of dsDNA was determined using the dsDNA High Sensitivity Assay Kit, and after dilution to 300 pg / μL, fragments were screened using the AMPure XP magnetic bead method. Library construction was performed using the Illumina Nextera XTDNA Library Prep Kit, and fragment quality was evaluated using the Agilent 2100 Bioanalyzer. Finally, the constructed library was sequenced at paired ends of 150 bp on the Illumina NovaSeq platform to obtain high-quality metagenomic raw data.

[0062] In one embodiment of the present invention, step 3 further includes the following steps:

[0063] (1) Raw data quality control

[0064] Trimmomatic (v0.39) software was used to remove low-quality sequences, adapter contamination sequences and other interfering information from all sequencing data to improve the accuracy and reliability of subsequent alignment and quantitative analysis. To ensure the representativeness and stability of the data analysis, only samples with a sequencing depth of more than 1 million reads were retained for subsequent processes.

[0065] (2) Reference database comparison and identification

[0066] The human ring-ring virus ORF1 lineage reference database (HANVdb ORF1 Lineage Dataset) was used as the sole alignment index for the analysis. Bowtie2 (v2.5.1) software was used for read alignment, and the parameter was set to "--very-sensitive" mode to maximize the sensitivity and accuracy of the alignment.

[0067] (3) Identification and Quantitative Calculation of Positive Lineages

[0068] After comparative analysis, the number of reads for all lineages hitting the reference database in each sample was counted. To avoid false positives, only lineages with a read hit count greater than 10 were retained as positive results. Subsequently, Samtools (v1.18) and Python scripts were used to count the number of reads at the lineage level and calculate the standardized abundance index RPKM (Reads Per Kilobase per Million mapped reads) to generate an expression matrix in a uniform format, facilitating comparative analysis between different samples.

[0069] (4) Expression matrix output and subsequent extended analysis

[0070] The final expression matrix is ​​arranged with lineages as rows and samples as columns. The values ​​in the matrix are the RPKM expression levels of the corresponding lineages. This expression matrix provides a general data foundation for various subsequent analyses, including but not limited to community structure description, correlation analysis with clinical phenotypes or immune status, and viral diversity measurement.

[0071] The embodiments of the present invention are further described in detail below:

[0072] Step 1: Construct a high-quality reference database for human ring viruses (Human Ring Virus ORF1 lineage dataset).

[0073] This invention first constructs a comprehensive, accurately classified, and fully annotated human ring virus reference database to provide high-quality standard support for subsequent ring virus genome detection, bioinformatics analysis, and community structure research. The construction process of this database includes key steps such as systematic retrieval of global sequence data, quality control, construction of species classification standards, functional region annotation, development of phylogenetic and species identification processes, standardization and completion of meta-information, and extraction of human-derived sequences, as follows: (1) Comprehensive acquisition and preliminary cleaning of ring virus genome sequences.

[0074] This invention, based on the NCBI GenBank and Taxonomy databases, uses the search condition taxid=687329 to systematically acquire all nucleic acid sequence records related to ringworm worldwide. As of October 2024, a total of 35,169 raw records were acquired and batch parsed using tools such as Biopython. To ensure database quality, this invention employs the following standards for preliminary cleaning and filtering:

[0075] Remove non-circular viruses (such as contaminated sequences or erroneous annotations); exclude low-quality sequences with incomplete base information (N ratio greater than 10%); remove sequences lacking host information or those obtained from patent applications but without public source records; remove redundant records to ensure the representativeness and refinement of the database.

[0076] (2) Construction of authoritative reference species system and establishment of ORF annotation framework

[0077] To standardize species classification and functional annotation, this invention introduces 173 standard ring virus species published by the International Committee on Taxonomy of Viruses (ICTV) as classification references, and obtains corresponding reference genomes and annotation information, especially the ORF1 region, from the NCBI RefSeq database as the core basis for functional annotation. A complete reference species ORF1 annotation library is then constructed, covering 32 known genera and 173 known virus species internationally, serving as the core supporting resource for subsequent annotation and comparison.

[0078] (3) ORF1 annotation and manual review of the target sequence

[0079] Based on a reference annotation library, this invention utilizes professional tools such as Geneious Prime to perform preliminary ORF1 annotation on target sequences, and ensures the accuracy and completeness of the annotation through the following multi-level manual verification and comparison standards: whether the ORF1 start terminus has a typical arginine-rich motif (ARM); whether the annotated sequence has complete start / stop codons and is translatable; whether the ORF1 region length is within a reasonable range compared to the reference species; for sequences with low similarity or structural abnormalities, AlphaFold2 is further used for structural prediction to verify the biological rationality of their ORF1 protein-coding region.

[0080] (4) Species classification and phylogenetic analysis based on ORF1 sequences

[0081] This invention further constructs an iterative species and genus classification labeling process: all complete ORF1 sequences are paired with 173 reference species, their nucleotide or amino acid similarity is calculated, and their classification relationship is labeled based on a 69% species classification threshold: sequences with similarity higher than 69% are classified as known species; sequences with similarity lower than 69% are identified as pseudo-novel species; all PNS sequences are combined with reference species to construct an ORF1 phylogenetic tree, and genus-level information is further assigned based on the phylogenetic topology; if it is a new genus, it is named a pseudo-novel genus.

[0082] (5) Meta-information standardization and completion and structured data organization

[0083] To enhance the database's applicability and research dissemination value, this invention, based on existing literature and metadata standardization rules established in previous studies, systematically completes and structurally parses fields such as "host information," "sample type," and "country and region of origin" in each entry. For records with missing, ambiguous, or non-standard descriptions, the following methods are used to improve them:

[0084] The original submission information was manually cross-referenced with published literature.

[0085] Clearly label the attributes of "human-derived samples" and "non-human mammalian samples" to ensure the distinguishability of different host sources in subsequent analyses;

[0086] Standardize and categorize sample type fields, such as uniformly describing the source of "blood," "respiratory tract," and "cerebrospinal fluid";

[0087] National and regional information is standardized using ISO-3166 coding to facilitate data statistics and cross-regional comparative studies.

[0088] After the above processing, all high-quality, clearly categorized, and fully functionally annotated ring virus entries have been standardized and accompanied by phylogenetic, annotation, host, and sample information. Based on this, the present invention further screens sequences clearly originating from human hosts, initially constructing a human ring virus database as an important data source for subsequent human clinical research, viral community structure analysis, and studies on their correlation with immune status.

[0089] (6) Human samples were spliced ​​together using high-throughput sequencing to supplement the reference dataset.

[0090] To further improve the accuracy and comprehensiveness of high-throughput detection of human ring virus, this invention, based on high-quality reference sequences in public databases, further incorporates metagenomic sequencing data independently constructed in our laboratory from 6,348 human clinical samples. This data is used to assemble, annotate, and supplement the ring virus sequences. This process significantly enhances the database's coverage of the true viral diversity in human samples.

[0091] First, the raw data of the above samples underwent standardized quality control processing (including low-quality sequence removal and host sequence filtering). Then, an efficient assembly algorithm (such as MEGAHIT) was used to assemble the viral metagenomics. ORF1 sequence annotation was performed through alignment and annotation.

[0092] This invention selects the ORF1 region as the standard region for the classification, identification, and comparison analysis of ring viruses, which has the following unique advantages and scientific rationality:

[0093] ORF1 is the longest and most stable coding region, encoding the most important protein in circoviruses, constituting most of their genome, and its function is highly conserved.

[0094] The international standard for virus classification is based on the fact that the International Committee on Taxonomy of Viruses (ICTV) clearly uses the nucleotide similarity of ORF1 (69% threshold) as the standard for species classification, which is currently the recognized basis for virus classification.

[0095] Significant quantitative advantage: As of October 2024, only 2,630 complete circular genome sequences of digitoviruses were available in public databases, while as many as 20,802 ORF1 sequences were available, indicating that ORF1 has a higher information content and applicability;

[0096] Minimal recombination interference: Literature confirms that ORF1 refers to the recombination cold spot in the circovirus genome, which is less affected by recombination events than other regions, and therefore has higher stability and reliability for alignment analysis;

[0097] High accuracy and robust results: Due to the combination of conservation and diversity of ORF1, it is the optimal region for reading alignment, species identification and relative abundance quantification, which can significantly reduce misidentification and background interference.

[0098] Based on the above criteria, the present invention integrated all high-quality ORF1 sequences screened from public databases with the 3,990 complete ORF1 sequences independently assembled in our laboratory, and performed redundancy removal clustering through CD-HIT (v4.8.1) software at a 95% sequence identity threshold. The longest sequence in each cluster was used as the lineage representative sequence to construct the final human anellovirus ORF1 lineage dataset (a total of 9,059 sequences).

[0099] The sequences and their relevant detailed information are shown in Table 1. The rest of the table has been published on the ScienceDB platform and a dataset DOI has been generated. Dataset DOI: https: / / doi.org / 10.57760 / sciencedb.27295. Dataset access link: https: / / www.scidb.cn / s / YjA7Bf

[0100] All information in Table 1 can be downloaded through the following link: https: / / download.scidb.cn / download?fileId=c463070c28f97dbe038ef3eeac2fb14a&path= / V1 / Table 1-patent.xlsx&shortLink=YjA7Bf&fileName=%E8%A1%A81-patent.xlsx. The Science Data Bank (ScienceDB) is an open and trustworthy general scientific data storage and publishing platform aimed at serving the global open science data sharing cause. The platform provides long-term preservation and DOI persistent identification. Technical support: Computer Network Information Center, Chinese Academy of Sciences, Address: No. 2 Courtyard, Dongsheng South Road, Haidian District, Beijing, Computer Network Information Center, Chinese Academy of Sciences, Official email: sciencedb@cnic.cn

[0101] The data files of Table 1 and Table 2 attached to the present invention

[0102] Table 1 - Sequence Information of Human Anellovirus ORF1 Lineage Dataset (Partial)

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110] This dataset highly represents the genetic diversity of human ringworm viruses and serves as core supporting data for subsequent bioinformatics comparison and analysis. The final integrated reference database includes not only standard sequences from public databases but also complete ORF1 sequences from our real clinical samples, comprehensively ensuring detection sensitivity, comparison accuracy, and classification reliability, and possessing broad value for clinical research applications.

[0111] Step 2: High-throughput sequencing of human sample metagenomics

[0112] To achieve highly sensitive detection and omics analysis of the human ring virome across different clinical states and sample types, this invention integrates a standardized metagenomic high-throughput sequencing workflow covering "sample collection – virus enrichment – ​​nucleic acid extraction – library construction and sequencing," ensuring that the obtained data possesses high reproducibility, representativeness, and clinical scalability. The core workflow is as follows:

[0113] (1) Sample collection and preservation

[0114] The samples involved included human samples such as blood samples (plasma and serum), respiratory samples (pharyngeal swabs, nasopharyngeal swabs), and cerebrospinal fluid samples, all derived from adults clinically diagnosed as suspected viral infections or healthy controls. The sampling process strictly followed clinical-grade aseptic procedures. Blood samples were rapidly separated after vacuum collection and transferred to RNase-free cryovials, while respiratory samples were immediately transferred to virus preservation medium (VTM). All samples were briefly stored at 4°C, then transported within 12 hours and stored long-term at -80°C to ensure the integrity of viral nucleic acid and biosafety.

[0115] (2) Virus enrichment treatment

[0116] Pretreatment was performed in a BSL-2 biosafety environment. Samples underwent thawing, mixing, and low-speed and high-speed centrifugation to remove large particles and host cells, obtaining a supernatant containing viral particles. The supernatant was then double-purified and concentrated using a 0.22 μm filter and a 100 kDa ultrafiltration membrane. The volume was adjusted to 170 μL, and a lysis mixture containing enzymes such as Turbo DNase, Benzonase, and RNase was added. The mixture was then digested at 37°C for 30 minutes to maximize the removal of free host nucleic acids, thereby enriching viral particle nucleic acids.

[0117] (3) Viral nucleic acid extraction

[0118] Nucleic acid extraction was performed using the QIAamp Viral RNA Kit from QIAGEN, combined with standardized operating procedures, to achieve efficient recovery of viral RNA and DNA, avoiding contamination or bias in downstream analysis.

[0119] (4) Reverse transcription and double-stranded cDNA synthesis

[0120] Using SuperScript TM The IV First-Strand Synthesis system and primer K-8N (5'-GACCATCTAGCGACCTCCACNNNNNNNN-3') with a random tail were used to synthesize the first-strand cDNA. The second-strand cDNA was then synthesized using the Klenow enzyme and the same primer, generating double-stranded cDNA, ensuring the integrity and universality of the reverse transcription product.

[0121] (5) PCR amplification and sample purification

[0122] Using random primer K (5'-GACCATCTAGCGACCTCCAC-3') and Premix TM Taq polymerase was used for PCR amplification to increase the abundance of target sequences. The amplification products were purified using the QIAquick PCR Purification Kit to remove reaction residues and non-specific products.

[0123] (6) Quantitative detection and library construction

[0124] The purified product was processed via Qubit TM The concentration of dsDNA was determined using the dsDNA High Sensitivity Assay Kit, and after dilution to 300 pg / μL, fragments were screened using the AMPure XP magnetic bead method. Library construction was performed using the Illumina Nextera XTDNA Library Prep Kit, and fragment quality was evaluated using the Agilent 2100 Bioanalyzer. Finally, the constructed library was sequenced at paired ends (150 bp) on the Illumina NovaSeq platform to obtain high-quality metagenomic raw data.

[0125] Step 3: Ring Virome Bioinformatics Analysis Process

[0126] This invention constructs a standardized and reproducible high-throughput bioinformatics analysis workflow for human ring virome (Anellome), covering the complete steps of raw data quality control, comparative analysis, positive identification, quantitative calculation, and expression matrix construction, providing a stable data foundation and a general analytical framework for subsequent virology and clinical research.

[0127] (1) Raw data quality control

[0128] First, the raw data obtained from high-throughput sequencing underwent quality control processing. This invention uses Trimmomatic (v0.39) software to remove low-quality sequences, adapter contamination sequences, and other interfering information from all sequencing data to improve the accuracy and reliability of subsequent alignment and quantitative analysis. To ensure the representativeness and stability of the data analysis, only samples with a sequencing depth of 1 million reads or more were retained for subsequent processes.

[0129] (2) Reference database comparison and identification

[0130] The human ring virus ORF1 lineage reference database (HANVdb ORF1 LineageDataset) constructed in this invention serves as the sole alignment index for analysis. Bowtie2 (v2.5.1) software is used for read alignment, with the parameter set to "--very-sensitive" mode to maximize the sensitivity and accuracy of the alignment. This database centers on the ORF1 region, the longest coding region in the ring virus genome, occupying a large portion of the sequence length and serving as a crucial basis for species definition by the International Committee on Taxonomy of Viruses (ICTV). Furthermore, the ORF1 region is considered a cold region for gene recombination, with a low probability of recombination; therefore, it possesses high stability and taxonomic authority as an alignment reference region.

[0131] (3) Identification and Quantitative Calculation of Positive Lineages

[0132] After comparative analysis, this invention counts the number of reads for all lineages that hit the reference database in each sample. To avoid false positives, only lineages with a read hit count greater than 10 are retained as positive results. Subsequently, Samtools (v1.18) and Python scripts are used to count the number of reads at the lineage level and calculate the standardized abundance index RPKM (Reads Per Kilobase per Million mapped reads) to generate an expression matrix in a uniform format, facilitating comparative analysis between different samples.

[0133] (4) Expression matrix output and subsequent extended analysis

[0134] The resulting expression matrix is ​​formatted with lineages as rows and samples as columns, with values ​​representing the RPKM expression levels for the corresponding lineages. This expression matrix provides a general data foundation for various subsequent analyses, including but not limited to community structure description, correlation analysis with clinical phenotypes or immune status, and viral diversity measurement. This invention does not limit specific analytical methods; researchers can freely expand upon it according to their respective clinical research goals and experimental designs to achieve multi-dimensional research applications of the human ring virome.

[0135] This analytical workflow is clearly structured, rigorous in its steps, and highly adaptable. It is applicable to metagenomic sequencing data from different sources and of different types, and has good promotional value and practicality in multiple scenarios such as viral ecology research, clinical pathogen identification, and immune function correlation.

[0136] The beneficial effects of this invention are:

[0137] This invention addresses the needs of human anellome detection and analysis by constructing an integrated technical solution covering the entire process from database construction, sample processing, viral nucleic acid extraction, library construction and sequencing to bioinformatics analysis, offering the following significant advantages:

[0138] (1) High-quality reference datasets significantly improve the accuracy of virus identification.

[0139] By integrating authoritative global databases such as NCBI and ICTV, and combining them with over 2,000 high-quality ORF1 sequences generated independently by our team, we have constructed a reference database of human ring viruses covering more than 9,000 lineages. This database boasts advantages such as complete annotation, clear classification, and consistent structure. It can serve as a standardized alignment index for high-precision identification of viral lineages, effectively avoiding identification biases caused by data redundancy or ambiguous classifications, and improving the accuracy and stability of virome analysis.

[0140] (2) Standardized sample processing procedures ensure the quality of viral nucleic acid

[0141] This invention establishes a rigorous process for virus enrichment, nucleic acid extraction and purification for different types of clinical samples (such as plasma, serum, pharyngeal swabs, nasopharyngeal swabs and cerebrospinal fluid, etc.). Combined with a multi-enzyme strategy to remove host nucleic acid, the viral nucleic acid is made purer and more complete, reducing host background interference and providing a reliable guarantee for subsequent high-throughput library construction, sequencing and analysis. At the same time, the unified sample processing process has good reproducibility and scalability, and is suitable for multi-center clinical research environments. (3) The analysis framework based on ORF1 has high versatility and scalability.

[0142] The ORF1 region is the most important structural protein coding region in the circovirus genome, occupying a large portion of the sequence and serving as a key basis for international viral classification. It also exhibits a low recombination rate. This invention explicitly selects ORF1 as the core region for analysis, ensuring the results are authoritative in taxonomy and highly stable in alignment analyses. Furthermore, ORF1 data is abundant; public databases contain far more ORF1 data than complete circular genomes, facilitating the construction of a high-coverage reference library and significantly enhancing the applicability and generalization ability of the method.

[0143] (4) The analysis process is clear, efficient, and highly adaptable, enabling applications in multiple clinical research scenarios.

[0144] The bioinformatics analysis workflow of this invention has been standardized and optimized, covering core steps such as quality control, reference alignment, positive identification, quantitative analysis, and expression matrix generation. It can achieve unified data processing and result output from sequencing data from different sources. The final generated expression matrix can provide researchers with phylogenetic abundance information of the ring virome in different samples, providing a stable data foundation for clinical feature correlation analysis, immune status association, and viral community structure analysis.

[0145] (5) The process is reusable and shareable, which helps in the construction of the virus monitoring system.

[0146] The method of this invention can be rapidly deployed in different research units or medical centers. The technical steps are clear and the cost is controllable. It supports applications such as large-scale population sample virus screening and virome-based immune monitoring research, and has good prospects for practical promotion. It can provide technical support for public health virus monitoring, precision medicine and other fields.

[0147] Key technical points and areas to be protected:

[0148] 1. Construction of a high-quality human ring virus reference database

[0149] This invention constructs a high-quality, classifiable human ringvirus reference database by systematically integrating publicly available ringvirus genome data from global public databases and further supplementing it with ORF1 sequences annotated from over 6,000 human high-throughput sequencing samples accumulated in our laboratory. The ORF1 region is used as the standard annotation reference because it not only covers most of the ringvirus genome and possesses species identification capabilities, but is also a recognized recombination cold spot, exhibiting higher alignment stability and classification reliability. This database forms the core foundation for all subsequent virus detection and analysis processes.

[0150] 2. High-throughput sequencing and data processing workflow for human samples

[0151] This invention establishes a standardized workflow for pretreatment, virus enrichment, nucleic acid extraction, library construction, and high-throughput sequencing of blood and respiratory samples under BSL-2 biosafety conditions. The sequencing data processing workflow includes the following key steps and parameter settings:

[0152] Samples with a total sequencing volume of at least 1,000,000 reads were retained as valid data for subsequent analysis.

[0153] We used Bowtie2 v2.5.1 for the comparison, setting the parameters to --very-sensitive mode to ensure higher comparison sensitivity;

[0154] The human ring virus ORF1 lineage dataset constructed in this invention is used as the alignment index;

[0155] The alignment results were compared using Samtools v1.18 and a Python script to extract the alignment read counts for each ANV lineage in each sample.

[0156] A lineage is considered positive only if the number of reads compared to the number of reads is greater than 10.

[0157] The RPKM (Reads Per Kilobase Per Million mapped reads) value for each lineage is calculated, and the final expression matrix is ​​generated for downstream analysis.

[0158] The above process is highly standardized and repeatable, enabling rapid deployment in different research or hospital environments and ensuring consistency and comparability of data processing.

[0159] 3. Broad application prospects

[0160] The method established in this invention is not only applicable to omics research on ring viruses but also possesses excellent scalability. Researchers can further conduct viral community structure analysis, clinical indicator correlation analysis, immune status association studies, and disease biomarker screening based on the expression matrix results. This approach boasts advantages such as high sensitivity, comprehensive coverage, and high standardization, and can be widely applied in fields such as virology, immunology, infectious diseases, biomarker research, and systems biology, demonstrating significant clinical research and translational application value.

[0161] In summary, the ring virome detection and bioinformatics analysis method proposed in this invention is scientific, universal, and operable. It has significant advantages in terms of the accuracy of virus identification, the degree of process standardization, and the scalability for clinical research. It breaks through the limitations of existing technologies in terms of incomplete databases, inaccurate comparisons, and inconsistent analysis processes, and has broad application value and industrial transformation prospects. Detailed implementation method:

[0162] Example 1: Detection and analysis of ring virome in 10 human blood samples based on the present invention

[0163] To verify the applicability and effectiveness of this invention, this embodiment selected 10 human blood samples (plasma) as research subjects to demonstrate the experimental procedure and data processing of this invention under real sample conditions. This procedure strictly follows the metagenomic sequencing and bioinformatics analysis techniques proposed in this invention, ultimately producing an expression matrix that can be used in subsequent clinical research, community structure analysis, immune status association, and other research scenarios.

[0164] (1) Sample collection and preservation

[0165] All 10 plasma samples collected were derived from suspected cases of viral infection or healthy asymptomatic volunteers with ethical approval. The sample type was peripheral plasma. Blood collection was performed under aseptic conditions by professional medical personnel using vacuum blood collection tubes. Immediately after collection, the plasma was centrifuged to obtain the plasma fraction. To maximize the integrity of the viral nucleic acid, aliquoting was completed within 2 hours of sampling. The plasma was immediately transferred to cryovials free of RNase contamination, briefly stored at 4°C, and then transported to the laboratory within 12 hours for long-term storage at -80°C. To avoid the impact of freeze-thaw cycles on the integrity of the viral nucleic acid, only one thawing process was performed throughout the entire process.

[0166] (2) Virus enrichment and nucleic acid extraction

[0167] Under BSL-2 biosafety conditions, frozen plasma samples were slowly thawed at room temperature, diluted with sterile water, and standardized to a normal volume. These samples were then sequentially filtered through a 0.22 μm membrane and a 100 kDa ultrafiltration tube for viral particle enrichment. Subsequently, an enzyme mixture (containing Turbo DNase, Benzosinase, RNase, and DNase buffer) was added and incubated at 37°C for 30 minutes to digest free host DNA and RNA, minimizing host background signals. The enriched solution obtained from this step provides a high-quality template for viral nucleic acid extraction.

[0168] Viral nucleic acid extraction was performed using the QIAamp Viral RNA Kit (QIAGEN), strictly following the instructions to ensure that both RNA and DNA viruses could be extracted, suitable for capturing ANV double-stranded DNA viruses. The concentration of the extracted nucleic acid was quantified using a quorum analyzer. After confirming that the concentration met the lower limit requirements for library construction, the library construction process commenced.

[0169] (3) Library preparation and high-throughput sequencing

[0170] First, reverse transcription was performed using the SuperScript IV system, and first-strand cDNA was synthesized using K-8N primers. Subsequently, second-strand cDNA was synthesized using Klenow enzyme and K-8N primers to form a double-stranded DNA product. The double-stranded DNA was then randomly amplified by PCR and purified using the QIAquick PCR Purification Kit.

[0171] The purified product was purified using AMPure XP magnetic beads and diluted to the target concentration (300 pg / μL). A library was constructed using the Nextera XT DNA Library Prep Kit, and library quality was assessed using an Agilent 2100 Bioanalyzer to ensure proper fragment distribution and concentration. Afterward, paired-end 150 bp sequencing was performed on an Illumina NovaSeq PE150 platform to obtain raw FASTQ data files. (Library and high-throughput sequencing)

[0172] (4) Sequencing data quality control and positive lineage identification

[0173] Trimmomatic (v0.39) was used to perform quality control on the sequencing data, removing low-quality reads and adapter sequences. Only samples with more than 1,000,000 sequencing reads were retained for subsequent analysis to ensure the statistical stability of virological quantification.

[0174] Clean reads were compared with the reference database (human ringworm ORF1 lineage dataset) constructed in this invention using Bowtie2 (v2.5.1) software in "--very-sensitive" mode. Each read was counted if it successfully matched a reference lineage in the database.

[0175] After the alignment was completed, Samtools (v1.18) was used to process the alignment files, and a custom Python script was used to count the number of reads for each lineage and calculate the RPKM value. For each positive lineage in the sample, a threshold of ≥10 reads was used to ensure the reliability of the quantitative results.

[0176] The final RPKM expression matrix (10×9059) is generated for each sample and lineage.

[0177] The said sequence and its related details are shown in Table 2. The rest of the table has been published on the ScienceDB platform and a dataset DOI has been generated. Dataset DOI: https: / / doi.org / 10.57760 / sciencedb.27295, Dataset access link: https: / / www.scidb.cn / s / YjA7Bf

[0178] All the information in Table 1 can be downloaded through the following link: https: / / download.scidb.cn / download?fileId=20168fe919d1cfc1509ed0edd4005b6b&path= / V1 / Table 2-patent.xlsx&shortLink=YjA7Bf&fileName=%E8%A1%A82-patent.xlsx Table 2 Expression matrix of 10 human blood anellovirus groups (partial)

[0179]

[0180] Based on the high-quality human anellovirus reference database and the standardized sequencing processing workflow constructed by the present invention, this embodiment realizes the efficient, accurate and repeatable identification and quantification of human anellovirus lineages from real clinical samples. Through the experimental operation and analysis of 10 plasma samples, an expression matrix with clear structure and controllable quality is successfully obtained, providing a solid data basis for subsequent various types of virome research and clinical relevance analysis, and fully verifying the technical advantages of the method of the present invention in terms of sensitivity, reliability, scalability and generality.

Claims

1. A high-throughput detection and bioinformatics analysis identification method for human papovavirus group, characterized in that, Comprising the following steps: Step 1, constructing a high-quality reference database of human circovirus; Step 2, high-throughput metagenomic sequencing of human samples; Step 3, circovirus group bioinformatics analysis process.

2. The method of claim 1, It is characterized by, Wherein, Step 1 comprises the following steps: First, a wide coverage, accurate classification, complete annotation of human circovirus reference database is constructed, which provides high-quality standard support for subsequent circovirus group detection, bioinformatics analysis and community structure research, the construction process of the database includes key steps such as systematic retrieval of global sequence data, quality control, construction of species classification standard, functional region annotation, development of phylogenetic and species identification process, standardization of meta-information completion and extraction of human sequences, The specific steps are as follows: (1) Comprehensive acquisition and preliminary cleaning of circovirus genomic sequences; (2) Construction of authoritative reference species system and establishment of ORF annotation framework; (3) ORF1 annotation and manual review of target sequences; (4) Species division and phylogenetic analysis based on ORF1 sequences; (5) Meta-information standardization completion and structured data arrangement; (6) High-throughput sequencing of human samples to supplement the reference dataset; Wherein, step 2 comprises the following steps: In order to realize high sensitivity detection and omics analysis of human circovirus group in different clinical states and sample types, the present application integrates a set of standardized metagenomic high-throughput sequencing experimental process covering "sample collection-virus enrichment-nucleic acid extraction-library construction", which ensures that the obtained data has high repeatability, representativeness and clinical expandability; The specific steps are as follows: (1) Sample collection and preservation; (2) Virus enrichment treatment; (3) Virus nucleic acid extraction; (4) Reverse transcription and double-stranded cDNA synthesis; (5) PCR amplification and sample purification; (6) Quantitative detection and library construction. Wherein, step 3 comprises the following steps: A set of standardized and reproducible high-throughput bioinformatics analysis process of human circovirus group is constructed, which covers the complete steps of raw data quality control, alignment analysis, positive identification, quantitative calculation and expression matrix construction, providing a stable data basis and general analysis framework for subsequent virus group and clinical research, the specific steps are as follows: (1) Raw data quality control; (2) Reference database alignment identification; (3) Positive lineage identification and quantitative calculation; (4) Expression matrix output and subsequent expansion analysis.

3. The method of claim 1, wherein, Wherein, Step 1 further comprises the following steps: (1) Comprehensive acquisition and preliminary cleaning of circovirus genomic sequences Based on NCBI GenBank and Taxonomy database, set the retrieval conditions, systematically obtain all nucleic acid sequence records related to circovirus in the world, use Biopython program tool for batch analysis; (2) Construction of authoritative reference species system and establishment of ORF annotation framework The 173 standard species of circovirus published by the International Committee on Taxonomy of Viruses (ICTV) were introduced as classification references. The corresponding reference genomes and annotation information were obtained from the NCBI RefSeq database as the basis for core functional annotation, and a complete reference species ORF1 annotation library was constructed, covering all known virus species in the world, as a core supporting resource for subsequent annotation and comparison. (3) ORF1 annotation of target sequences and manual review Geneious Prime professional tool platform was used to annotate ORF1 of target sequences, and the following multi-level manual checking and comparison standards were used to ensure the accuracy and integrity of the annotation: whether the ORF1 starting end has a typical arginine-rich motif (ARM); whether the annotated sequence has complete start / stop codons and is translatable; whether the length of the ORF1 region is within a reasonable range; for sequences with low similarity or abnormal structure, AlphaFold2 was used for structure prediction to verify the biological rationality of the ORF1 protein coding region. (4) Species division and phylogenetic analysis based on ORF1 sequences An iterative species and genus classification annotation process was established: all complete ORF1 sequences and reference species were pairwise aligned, the nucleotide or amino acid similarity was calculated, and the species classification threshold was combined to annotate the attribution: sequences with a similarity higher than 69% were classified as known species; sequences with a similarity lower than 69% were determined as potential new species; the ORF1 phylogenetic tree was constructed with all PNS and reference species, and the genus level information was further assigned based on the phylogenetic topology structure, such as new genus or potential new genus. (5) Standardization of meta-information and structured data According to the existing literature and the established meta-data standardization rules in previous studies, the fields in each item were systematically completed and structured, and the records with missing, ambiguous or non-standard descriptions were improved using the following methods: The original submission information and published literature were used for manual cross-comparison; the properties of "human samples" and "non-human mammalian samples" were clearly labeled to ensure the distinguishability of different host sources in subsequent analysis; the sample type field was standardized and classified, and the country and region information was standardized to ISO-3166 code for easy data statistics and cross-regional comparison research. (6) High-throughput sequencing of human samples and supplement to reference data set Based on the high-quality reference sequences in public databases, the "metagenomic sequencing data of human clinical samples in our laboratory" was introduced to splice, annotate and supplement the circovirus sequences.

4. The method of claim 1, wherein, Step 2 further includes the following steps: (1) Sample collection and preservation The samples involved include blood samples (plasma and serum), respiratory samples (throat swab, nasopharyngeal swab), or cerebrospinal fluid samples, etc. Human samples are derived from adult populations diagnosed as suspected viral infection or healthy controls by clinical diagnosis. (2) Virus enrichment treatment ​ Pre-treatment operation was performed in a BSL-2 biosafety environment; the sample was thawed, mixed, and subjected to low-speed and high-speed centrifugation steps to remove large-particle impurities and host cells, and obtain the supernatant containing viral particles. Subsequently, double purification and concentration were performed through 0.22 μm filter membrane filtration and 100 kDa cutoff ultrafiltration membrane; the volume was adjusted to 170 μL after treatment, and a lysis mixture containing Turbo DNase, Benzonase, RNase, and other enzymes was added for digestion at 37°C for 30 minutes to maximize the removal of host free nucleic acids and enrich viral particle nucleic acids; (3) Virus nucleic acid extraction The nucleic acid extraction used the QIAamp Viral RNA Kit kit of QIAGEN Company, combined with a standardized operation process, to achieve efficient recovery of viral RNA and DNA, avoiding contamination or bias to the downstream analysis; (4) Reverse transcription and double-stranded cDNA synthesis SuperScript TM IV First-Strand Synthesis system and primer K-8N (5'-GACCATCTAGCGACCTCCACNNNNNNNN-3') with random tail for first strand cDNA synthesis; followed by Klenow enzyme and the same primer for second strand synthesis to generate double stranded cDNA, ensuring the integrity and universality of the reverse transcription product; (5) PCR amplification and sample purification PCR amplification was performed using random primer K (5'-GACCATCTAGCGACCTCCAC-3') and Premix Ex Taq (Takara) with the target sequence as template. The PCR products were purified by QIAquick PCR Purification Kit to remove the reaction system residues and non-specific products. TM PCR amplification was performed using random primer K (5'-GACCATCTAGCGACCTCCAC-3') and Premix Ex Taq (Takara) with the target sequence as template. The PCR products were purified by QIAquick PCR Purification Kit to remove the reaction system residues and non-specific products. (6) Quantitative detection and library construction After purification, the product was subjected to concentration determination by Qubit TM dsDNA High Sensitivity Assay Kit, diluted to 300 pg / μL, and then subjected to fragment screening by AMPure XP magnetic bead method; library construction was performed using Illumina Nextera XT DNA Library Prep Kit, and fragment quality was evaluated by Agilent 2100 Bioanalyzer; finally, the constructed library was subjected to double-end 150 bp sequencing on an Illumina NovaSeq platform to obtain high-quality metagenomic raw data.

5. The method of claim 1, wherein, Among them, Step 3 further comprises the following steps: (1) Raw data quality control Using Trimmomatic (v0.39) software, all sequencing data was removed from low-quality sequences, adapter contamination sequences and other interference information to improve the accuracy and reliability of subsequent alignment and quantitative analysis. To ensure the representativeness and stability of data analysis, only samples with sequencing depth of more than 1 million reads were retained for subsequent processes. (2) Reference database alignment and identification The human anellovirus ORF1 lineage reference database (HANVdb ORF1 Lineage Dataset) was used as the only alignment index for analysis, and Bowtie2 (v2.5.1) software was used for reads alignment, with the parameter set to "--very-sensitive" mode to maximize the sensitivity and accuracy of alignment; (3) Positive lineage identification and quantitative calculation After alignment analysis, the number of reads for each sample hitting the reference database was counted. To avoid false positive interference, only lineages with more than 10 reads hits were retained as positive results. Subsequently, Samtools (v1.18) and Python scripts were used to count the reads at the lineage level and calculate the standardized abundance index RPKM (Reads Per Kilobase per Million mapped reads), generating a uniform format expression matrix for comparative analysis between different samples. (4) Expression matrix output and subsequent expansion analysis The final expression matrix had lineages as rows, samples as columns, and the values in the matrix were the RPKM expression of the corresponding lineage. This expression matrix provided a general data basis for subsequent multiple analyses, including but not limited to community structure description, correlation analysis with clinical phenotypes or immune status, and virus diversity measurement.

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