WO2021164472A1 - Library construction method based on nanopore sequencing platform, microorganism identification method, and application - Google Patents

Abstract

The present application provides a library construction method based on a nanopore sequencing platform, a microorganism identification method, and an application. The provided construction method comprises: enriching a target gene from a microorganism to obtain an enriched product; and constructing a library on the basis of the enriched product to obtain a sequencing library. The use of a nanopore sequencing platform for sequencing of a sequencing library can achieve one-step broad-spectrum detection of bacteria, fungi, and viruses in a short time. Moreover, because the target gene nucleic acid is enriched, the testing sample amount and cost are reduced.

Description

Method for constructing library based on nanopore sequencing platform, method for identifying microorganisms and application Technical field

The present disclosure relates to the field of gene sequencing, in particular to a method for constructing a library based on a nanopore sequencing platform, a method for identifying microorganisms, and applications.

Background technique

Bacteria, fungi, and viruses are three types of pathogens that cause clinical infections. Cultivation is a common method for clinical bacteria and fungi detection. It will be affected by the natural differences in the growth conditions of bacteria and fungi, which will lead to slow detection speed, which often takes 2-7 days; and the growth of some pathogens will be affected by others. The influence of pathogenic bacteria makes the sensitivity of culture detection low. In addition, different types of bacteria or fungi require different culture methods, and need to predict the type of infection in advance, which limits its application.

Conventional PCR methods can detect nucleic acids in specimens without pre-judging the types of bacterial and fungal infections, and detect bacteria, fungi, and viruses in specimens at one time without distinction. However, conventional PCR methods are limited by PCR technical conditions, and generally can only diagnose 1-15 specific pathogens in a specimen at the same time. The use of antibodies for specific detection of specific pathogens can only target specific pathogens.

The use of gene sequencing technology for pathogen diagnosis is to use a gene sequencer to perform sequence detection on the specimens processed by a certain method of nucleic acid extraction and sequencing library construction, and then compare the obtained gene sequence with the database to determine what the specimen contains The species information of the fungus or/and bacteria. The comprehensiveness of the test (detection of bacteria and fungi at the same time), speed (from specimen to report time), sensitivity (detection of very low pathogens from clinical specimens with complex composition) and convenience (needs of the site environment required to carry out the test) , The minimum sample size requirement) is extremely important for clinical testing.

The overall detection cycle of second-generation metagenomic sequencing is long, often requiring 1 to 3 days. The amount of data required for detection is large, and the detection cost is relatively high. Sequencing equipment and analysis equipment require high requirements and occupy a large area. In order to reduce the cost of a single sample, it is necessary to collect samples for testing, which can only be carried out in professional testing companies or large central laboratories. Based on nanopore metagenomic sequencing analysis, it has the advantages of short sequencing time and excellent sequencing results. However, it may require a large amount of sequencing data, for example, generally 5-10Gb/sample, and the cost of reagents is 5-10 times higher than that of second-generation sequencing, so it is difficult to implement it in clinical practice.

Based on the identification of microorganisms in the sample, further improvements are needed.

Summary of the invention

The present disclosure solves at least one of the problems existing in the prior art to a certain extent, and provides a method for constructing a library based on a nanopore sequencing platform, a method for identifying microorganisms, and applications.

The inventors of the present disclosure creatively researched and designed target gene sites for microbial identification. For example, they designed target gene sites for bacteria, fungi, and viruses; at the same time, they optimized the detection experiment process between different target genes. , To achieve simultaneous detection of bacteria, fungi, viruses, etc. in the sample in one sequencing. Using the target gene locus provided by the present disclosure, it is possible to use the nanopore sequencing platform to increase the proportion of microbial nucleic acid during the sequencing process through a targeted enrichment method, and reduce the amount of data required for detection to 10-50Mb/sample , Which greatly reduces the cost of testing.

In the first aspect of the present disclosure, the present disclosure provides a method for constructing a library based on a nanopore sequencing platform, including: enriching target genes from microorganisms to obtain enriched products, the microorganisms including those selected from At least one of bacteria, fungi, or viruses; a library is constructed based on the enriched product, so as to obtain the sequencing library. The present disclosure provides a method for constructing a library based on a nanopore sequencing platform. By enriching target genes from microorganisms, a library is constructed for the obtained enriched products, for example, referring to the library construction process of the nanopore sequencing platform Build a library to obtain a sequencing library. The obtained sequencing library only contains the enriched target gene nucleic acid from microorganisms. The obtained sequencing library can be used to realize rapid sequencing analysis with the help of the nanopore sequencing platform. The detection time is less than 12 hours from sample to result, which is the fastest It can be completed in 6 hours, and at the same time can realize a one-time broad-spectrum detection of bacteria, fungi, and viruses. And because the target gene nucleic acid is enriched, the amount of data required for detection is reduced to 10-50Mb/sample, which greatly reduces the cost of detection.

According to an embodiment of the present disclosure, the method for constructing a library based on the nanopore sequencing platform described above may further include the following technical features:

According to an embodiment of the present disclosure, the bacterial target genes include universal bacterial target genes and/or highly sensitive bacterial target genes, and the universal bacterial target genes include those selected from the group consisting of 16s rRNA, rpob, gyrB, hsp60, ISR, 23s rRNA At least one, preferably including the target region listed in Table 5 and the 500bp region before and after; the highly sensitive bacterial target gene includes at least one selected from the target gene of the highly sensitive bacteria shown in Table 1, these high The target genes of sensitive bacteria are specifically 16s rRNA, rpob, gyrB, hsp60, ISR, dnaJ, tuf, atpD, rnpB, sodA, inhA, mip, recA, trkA, femA, gap, katG, mabA, gacA and other genes; preferably include Table 7 lists the target regions and the 500bp region before and after. The universal bacterial target gene has strong regional specificity and can be used for the detection of different bacteria. The bacteria listed in Table 1 are clinically important highly sensitive bacteria, and can be used to detect these highly sensitive bacteria by detecting the listed target genes.

According to an embodiment of the present disclosure, the fungal target genes include universal fungal target genes and/or highly sensitive fungal target genes, and the universal fungal target genes include selected from ITS1-4, LSU(D1/2), 18s rRNA, RPB2 At least one of them preferably includes the target region listed in Table 6 and the region of 500 bp before and after; for example, it may be a region of 100 bp to 450 bp before and after, a region of 100 to 400 bp before and after, a region of 100 to 350 bp before and after, and 100 bp before and after. The region of ~300bp, the region of 100~250bp before and after, the region of 100~200bp before and after, the region of 100~150bp before and after, or the region within 100bp before and after, and the region of 50~100bp before and after; the highly sensitive fungal target genes include options From at least one of the target genes of highly sensitive fungi shown in Table 2, these target genes may specifically be RPB1, RPB2, TEF1, BenA, CaM, ND6, MCM7, CAL, TUB2, ACT, ND6 and other genes, preferably including the table The target region listed in 8 and the region of 500 bp before and after; for example, the region of 100 to 450 bp before and after, the region of 100 to 400 bp before and after, the region of 100 to 350 bp before and after, the region of 100 to 300 bp before and after, and the region of 100 to 250 bp before and after A region, a region of 100 to 200 bp before and after, a region of 100 to 150 bp before and after, or a region within 100 bp before and after, and a region of 50 to 100 bp before and after. These target gene regions are highly specific and can be used for the detection of different bacteria.

According to an embodiment of the present disclosure, the viral target genes include multiple viral target genes and/or new coronavirus target genes, and the multiple viral target genes include at least one selected from the viral target genes shown in Table 3, preferably including The target region listed in 9 and the region of 200 bp before and after; for example, a region of 100 to 200 bp before and after, a region of 100 to 150 bp before and after, or a region within 100 bp before and after; the new coronavirus target genes include those selected from Table 4 At least one of the indicated target genes preferably includes the target region listed in Table 10 and the region of 200 bp before and after; for example, it can be a region of 100 to 200 bp before and after, a region of 100 to 150 bp before and after, or within 100 bp before and after Area, the area of 50-100bp before and after.

According to an embodiment of the present disclosure, the bacterial target gene includes a universal bacterial target gene and a highly sensitive bacterial target gene, the fungal target gene includes a universal fungal target gene and a highly sensitive fungal target gene, and the viral target gene includes a multiple viral target Gene and new coronavirus target gene, the method further comprises: enriching the enriched product of universal bacterial target gene, the enriched product of universal fungal target gene, the enriched product of highly sensitive bacterial target gene, and the enriched product of highly sensitive fungal target gene The products, the enriched products of multiple viral target genes and the enriched products of new coronavirus target genes are mixed in a mass ratio of 20-60:5-15:10-25:10-25:10-25. The product library is constructed to obtain the sequencing library. According to the embodiments of the present disclosure, the enriched products of universal bacterial target genes, the enriched products of universal fungal target genes, the enriched products of highly sensitive bacterial target genes, the enriched products of highly sensitive fungal target genes, and the enriched products of multiple viral target genes The enriched product and the enriched product of the new coronavirus target gene can be mixed in a mass ratio of 30-50:6-10:12-20:12-20:12-20.

According to an embodiment of the present disclosure, the method for constructing a library based on a nanopore sequencing platform further includes: performing PCR amplification on the target gene from the microorganism based on the primers in the primer pool, so as to realize the enrichment of the target gene. In order to obtain an enriched product, the primer pool contains at least one primer.

According to the embodiments of the present disclosure, the primers in the primer pool all meet the following conditions: a. The length of the primer is 18-30 bases; b. The melting temperature Tm of the primer is 57-64°C; c. In the primer The GC content is 40-60%; d. The Gibbs free energy ΔG of the 5 bases at the 3'end of the primer is greater than or equal to -9kcal/mol; e. The primer self-complementarity value is less than 8.0, and the 3'end self-complementary parameter of the primer Less than 3.0; f. There is no degenerate base on 3 consecutive bases at the 3'end of the primer; g. The length of the amplified product of the primer is 200 to 1500 bases. In this article, the primer self-complementarity value mentioned is used to characterize the tendency of each primer's own base sequence to form a complementary structure; the 3'end self-complementarity parameter of the primer is to calculate all bases at the 3'end of different primers The tendency of sequences to form complementary structures. The specific trend is evaluated by numerical value. The numerical calculation logic is: 1 point is counted when forming a pair of base complements, the complementation between N bases is -0.25 points, and the non-complementary bases are counted-1 point, forming a gap Complementary (Gap) bases are counted as -2 points. For more detailed calculation methods, please refer to the document Shen, Z., et al., MPprimer: a program for reliable multiplex PCR primer design. BMC Bioinformatics, 2010.11: p.143.

According to an embodiment of the present disclosure, the primer pool includes at least one selected from the following primer pools: a universal bacterial primer pool including the primers listed in Table 5; a universal fungal primer pool, the The universal fungal primer pool includes the primers listed in Table 6; the highly sensitive bacterial primer pool includes the primers listed in Table 7; the highly sensitive fungal primer pool includes the primers listed in Table 7. 8 primers listed; multiple virus primer pool, the multiple virus primer pool includes the primers listed in Table 9; new coronavirus primer pool, the new coronavirus primer pool includes the primers listed in Table 10.

In the second aspect of the present disclosure, the present disclosure provides a sequencing method, including: obtaining a sequencing library based on the method described in any one of the embodiments of the first aspect of the present disclosure;述 Sequencing. Using the nanopore sequencing platform for sequencing, compared with the second-generation sequencing technology, it can be monitored on-site in non-professional laboratories, and detection and data analysis can be performed through laptops and network cloud processes.

In the third aspect of the present disclosure, the present disclosure provides a method for identifying microorganisms, including: obtaining a sequencing library according to any one of the embodiments of the first aspect of the present disclosure based on the nucleic acid of the sample to be tested; and based on the sequencing library Sequencing using a nanopore sequencing platform to obtain sequencing results; comparing the sequencing results with a reference database, and determining the microorganisms in the sample to be tested based on the comparison results. The provided method for identifying microorganisms can be the identification of pathogens, and the identification of pathogens can assist clinical medication. The provided methods for identifying microorganisms can be used to identify the types of bacteria, fungi or viruses in the sample to be tested, can be used as clinical auxiliary drugs, and can also be used for other purposes, such as big data collection, commercial kits or commercial platforms Construction and other non-disease diagnosis purposes.

According to an embodiment of the present disclosure, the method for identifying microorganisms described above may further include the following technical features:

According to an embodiment of the present disclosure, the reference database includes at least one of the following: a general bacterial database containing 16s rRNA, rpob, gyrB, hsp60, 23s rRNA, and ISR gene data; a general fungal database, so The general fungus database contains TS1-4, LSU(D1/2), 18s rRNA and RPB2 gene data; a highly sensitive bacteria database, the highly sensitive bacteria database contains the highly sensitive bacterial target gene data shown in Table 1; a highly sensitive fungus database , The highly sensitive fungus database contains the highly sensitive fungal target gene data shown in Table 2; the multiple virus database, the multiple virus database contains the virus target gene data shown in Table 3; the new coronavirus database, the new coronavirus database contains SARS- Genomic data of CoV-2.

According to an embodiment of the present disclosure, the method for identifying microorganisms described above further includes: comparing the sequencing results with the general bacterial database and the general fungal database, respectively, so as to obtain the first comparison data and the first comparison data. Comparison data; compare the first uncompared data with the highly sensitive bacteria database and the highly sensitive fungus database, respectively, so as to obtain the second comparison data and the second uncompared data; The second uncompared data is compared with the multiple virus database and the new coronavirus database to obtain the third comparison data; based on the first comparison data, the common bacteria and common bacteria contained in the sample are determined For fungi, based on the second comparison data, it is determined that the sample contains highly sensitive bacteria and highly sensitive fungi, and based on the third comparison data, the virus contained in the sample is determined.

According to an embodiment of the present disclosure, the determining the general bacteria and general fungi contained in the sample based on the first comparison data further includes: dividing the first comparison data into first unique comparison data and At least one set of first cross-alignment data, and each set of first cross-alignment data contains multiple alignment sequences; some of the multiple alignment sequences in each set of first cross-alignment data are used as seed sequences, and the remaining part of the group is used for comparison. The sequence is corrected for the seed sequence to obtain a corrected seed sequence; the corrected seed sequence is compared with the optimal alignment data of the general bacterial database and the general fungal database, and the first unique comparison Combine the data to determine the common bacteria and common fungi contained in the sample.

According to an embodiment of the present disclosure, the determining the highly sensitive bacteria and highly sensitive fungi contained in the sample based on the second comparison data further includes: dividing the second comparison data into second unique comparison data And at least one set of second cross-aligned data, each set of second cross-aligned data contains multiple alignment sequences; part of multiple alignment sequences in each set of second cross-aligned data are used as seed sequences, and the remaining part in the group is used The alignment sequence corrects the seed sequence to obtain a corrected seed sequence; the optimal alignment result of the corrected seed sequence with the highly sensitive bacteria database and the highly sensitive fungus database, and the second The two unique comparison data are combined to determine the highly sensitive bacteria and highly sensitive fungi contained in the sample.

According to the embodiments of the present disclosure, based on the determined general bacteria and highly sensitive bacteria in the sample, all bacteria contained in the sample are combined and determined; based on the determined general fungi and highly sensitive fungi in the sample, combined to determine the content contained in the sample All fungi. Generate a list of bacteria or a list of fungi from all the bacteria or all the fungi identified. Take the list of bacteria as an example. If there are crossovers of bacteria or highly sensitive bacteria in the list, compare the genus and species consistency of the crossed bacteria. If the two are the same at the species level, the unique result is determined. If the identification results of the two are the same at the genus level, but the identification results at the species level are inconsistent, the result of the highly sensitive bacteria will be used as the only result. If the two are identified as different , Then both results will be output as the result. According to an embodiment of the present disclosure, the determining the virus contained in the sample based on the third comparison data further includes:

The multiple alignment sequences in the third alignment data that are aligned to the same gene region are used as a group, a part of the alignment sequence in each group is used as a seed sequence, and the remaining alignment sequences in the group are used to align the The seed sequence is corrected to obtain the corrected seed sequence;

Determine the virus contained in the sample based on the optimal comparison result of the corrected seed sequence with the multiple virus database and the new coronavirus database;

Optionally, it further includes: determining the virus present in the sample to be tested based on at least 80% or more of the same base difference between the corrected seed sequence and the multiple virus database and the new coronavirus database Mutation site.

In a fourth aspect of the present disclosure, the present disclosure provides an apparatus for identifying microorganisms, including: a data processing unit that compares the sequencing result of the nucleic acid of the sample to be tested with a reference database for determining the Microorganisms in the sample to be tested. According to an embodiment of the present disclosure, the apparatus for identifying microorganisms further includes: a library construction unit that obtains a sequencing library based on the nucleic acid of the sample to be tested according to the method of any one of the embodiments of the third aspect of the present disclosure Sequencing unit, based on the sequencing library, the sequencing unit uses a nanopore sequencing platform to perform sequencing, so as to obtain the sequencing result.

According to an embodiment of the present disclosure, the device for identifying microorganisms may further include the following technical features:

According to an embodiment of the present disclosure, the reference database includes at least one of the following: a general bacterial database containing 16s rRNA, rpob, gyrB, hsp60, 23s rRNA, and ISR gene data; a general fungal database, so The general fungus database contains TS1-4, LSU(D1/2), 18s rRNA and RPB2 gene data; a highly sensitive bacteria database, which contains the bacterial target gene data shown in Table 1; a highly sensitive fungus database , The highly sensitive fungus database contains the fungal target gene data shown in Table 2; a multiple virus database, the multiple virus database contains the virus target gene data shown in Table 3; a new coronavirus database, the new coronavirus database contains SARS -Genomic data of CoV-2.

According to an embodiment of the present disclosure, the data processing unit further includes: comparing the sequencing results with the general bacterial database and the general fungal database, respectively, so as to obtain first comparison data and first uncompared data Data; compare the first uncompared data with the highly sensitive bacteria database and the highly sensitive fungus database, so as to obtain the second comparison data and the second uncompared data; compare the second The unaligned data is compared with the multiple virus database and the new coronavirus database to obtain the third comparison data; based on the first comparison data, the general bacteria and general fungi contained in the sample are determined, Based on the second comparison data, it is determined that the sample contains highly sensitive bacteria and highly sensitive fungi, and based on the third comparison data, the virus contained in the sample is determined. The mentioned first comparison data refers to the data that can be compared with the general bacteria database and the general fungus database, and the first uncompared data refers to the data that cannot be compared with the general bacteria database and the general fungus database. These unmatched data continue to be compared with the highly sensitive bacteria database and the highly sensitive fungus database. The data that can be compared is used as the second comparison data, and the unmatched data is used as the second uncompared data. These second uncompared data continue to be compared with the multiple virus database and the new coronavirus database, and the data that can be compared is used as the third comparison data.

According to an embodiment of the present disclosure, the determining the general bacteria and general fungi contained in the sample based on the first comparison data further includes: dividing the first comparison data into first unique comparison data and At least one set of first cross-alignment data, and each set of first cross-alignment data contains multiple sequences; some multiple sequences in each set of first cross-alignment data are used as seed sequences, and the remaining sequences in the group are used to compare the seeds The sequence is corrected to obtain a corrected seed sequence; the optimal alignment results of the corrected seed sequence with the general bacterial database and the general fungal database are combined with the first unique alignment data to determine the The general bacteria and general fungi contained in the sample. According to an embodiment of the present disclosure, a random 20%-40% sequence (for example, 30%) in each group of first crossover data can be used as a seed sequence.

According to an embodiment of the present disclosure, the determining that the sample contains highly sensitive bacteria and highly sensitive fungi based on the second comparison data further includes:

Dividing the second comparison data into second unique comparison data and at least one group of second cross comparison data, each group of second cross comparison data contains multiple sequences;

Taking part of multiple sequences in each group of second crossover data as seed sequences, and correcting the seed sequence by using the remaining part of the sequence in the group, so as to obtain a corrected seed sequence;

Combine the corrected seed sequence with the optimal comparison result of the highly sensitive bacteria database and the highly sensitive fungus database, and the second unique comparison data to determine the highly sensitive bacteria contained in the sample and Highly sensitive fungus. According to an embodiment of the present disclosure, a random 20%-40% sequence (for example, 30%) in each set of second crossover data can be used as a seed sequence.

According to an embodiment of the present disclosure, the determining the virus contained in the sample based on the third comparison data further includes: dividing multiple sequences in the third comparison data that are aligned to the same gene region as One group, the partial sequence in each group is used as the seed sequence, and the remaining partial sequences in the group are used to correct the seed sequence to obtain the corrected seed sequence; based on the corrected seed sequence and the multiple virus database and all According to the optimal comparison result of the new coronavirus database, the virus contained in the sample is determined. According to an embodiment of the present disclosure, a random 20%-40% sequence (for example, 30%) in each group can be used as a seed sequence.

According to an embodiment of the present disclosure, further comprising: determining the sample virus to be tested based on at least 80% or more of the same base difference between the corrected seed sequence and the multiple virus database and the new coronavirus database The mutation site.

In the fifth aspect of the present disclosure, the present disclosure provides a kit, including a primer pool, the primer pool includes at least one selected from the following: a universal bacterial primer pool, the universal bacterial primer pool includes table 5 Listed primers; universal fungal primer pool, the universal fungal primer pool includes the primers listed in Table 6; highly sensitive bacterial primer pool, the highly sensitive bacterial primer pool includes the primers listed in Table 7; highly sensitive fungus A primer pool, the highly sensitive fungal primer pool includes the primers listed in Table 8; a multiple virus primer pool, the multiple virus primer pool includes the primers listed in Table 9; a new coronavirus primer pool, the new coronavirus primer pool Include the primers listed in Table 10.

The beneficial effects achieved by the present disclosure are: applying the sequencing method provided by the present disclosure can quickly obtain microbial information in a sample, for example, it can achieve a detection result of a virus in a sample on the same day. And the detection sensitivity is high: it detects low-abundance viruses, bacteria, and fungi, helping early diagnosis and prompting the risk of early infection. The detection range is wide, for example, it can be applied to the detection of the new coronavirus SARS-CoV-2, and it can also detect co-infections caused by other viruses to help quickly determine the diagnosis and treatment plan. It can further detect bacteria, fungi, atypical pathogens, and viruses at one time. The application of this method to identify microorganisms can simultaneously realize the detection of bacteria, fungi, viruses, etc., and the information is more comprehensive. For example, it can realize virus detection and virus mutation monitoring at the same time, and provide rapid and real-time epidemics that can be interpreted and acted upon for epidemic monitoring. Disease information. In addition, the provided method uses the nanopore sequencing platform for sequencing and identification of microorganisms. It is simple and portable, and is suitable for development in laboratories such as hospitals and CDC. The sequencing data can be analyzed in the cloud. Quickly establish and monitor the epidemic.

Description of the drawings

Fig. 1 is a schematic structural diagram of an apparatus for identifying microorganisms according to an embodiment of the present disclosure.

Fig. 2 is the result of mutation analysis on the virus-carrying genome of a patient with new crown infection numbered C1 according to an embodiment of the present disclosure.

Detailed ways

The embodiments of the present disclosure are described in detail below. It should be noted that the described embodiments are exemplary, and are intended to explain the present disclosure, and should not be construed as limiting the present disclosure. At the same time, some terms in this article are explained and explained to facilitate the understanding of those skilled in the art. It should be noted that these explanations and explanations should not be regarded as limiting the scope of protection of the present disclosure.

The terms "first", "second", "third", etc. mentioned in this article are only used for the convenience of description, and cannot be understood as indicating or implying relative importance, nor can they be used exclusively to indicate or imply sequence order. In the description of the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined. In this article, "universal bacteria" refers to some common bacteria, which can usually be distinguished by combining some target genes. These target genes were screened and finally determined to be at least one of 16s rRNA, rpob, gyrB, hsp60, ISR, and 23rRNA. Correspondingly, the general bacterial database refers to a reference database that can be used for the identification of these general bacteria. According to the embodiments of the present disclosure, these general bacterial databases contain data of these general bacterial target genes. Similarly, the universal bacterial primer pool refers to primers that can be used for the amplification or identification of these universal bacteria.

In this article, "highly sensitive bacteria" refers to some common pathogenic bacteria in the clinic. The target genes used to characterize or identify these bacteria are usually different, but they often cause some clinical diseases. The target genes on bacteria have been studied, and target genes that can characterize these bacteria have been found to be used for the identification of these bacteria. What needs to be clarified is that general bacteria and highly sensitive bacteria are not deliberately distinguished, and there may be crossover, that is, some bacteria may belong to both general bacteria and highly sensitive bacteria. When the identified general bacteria and highly sensitive bacteria are consistent at the genus level but not at the species level, the identification results of the highly sensitive bacteria are used as the standard. Correspondingly, the highly sensitive bacteria database refers to a reference database that can be used for the identification of these highly sensitive bacteria. According to the embodiments of the present disclosure, these highly sensitive bacteria databases contain the data of the target genes of these highly sensitive bacteria. Similarly, a highly sensitive bacterial primer pool refers to primers that can be used for the amplification or identification of these highly sensitive bacteria.

In this article, "universal fungi" refers to some common fungi, which can usually be distinguished by combining some target genes. These target genes were screened and finally determined to be at least one of ITS1-4, LSU(D1/2), 18s rRNA, and RPB2. Correspondingly, the general fungal database refers to a reference database that can be used for the identification of these general fungi. According to the embodiments of the present disclosure, these fungal and bacterial libraries contain data on these general fungal target genes. Similarly, the universal fungal primer pool refers to primers that can be used for the amplification or identification of these universal fungi.

In this article, "highly sensitive fungi" refers to some common pathogenic fungi in the clinic. The target genes used to characterize or identify these fungi are usually different, but they often cause some clinical diseases. The target genes on the fungi have been studied, and the target genes that can characterize these fungi have been found and used for the identification of these fungi. It should be noted that general fungi and highly sensitive fungi are not deliberately distinguished, and there may be crossover, that is, some bacteria may belong to both general fungi and highly sensitive fungi. When the identified general fungi and highly sensitive fungi are consistent at the genus level but not at the species level, the identification results of the highly sensitive fungi shall be used as the standard. Correspondingly, a highly sensitive fungus database refers to a reference database that can be used as a reference database for the identification of these highly sensitive fungi. According to the embodiments of the present disclosure, these highly sensitive fungal databases contain data on target genes of these highly sensitive fungi. Similarly, the highly sensitive bacterial primer pool refers to the primers that can be used for the amplification or identification of these highly sensitive fungi.

In this article, when referring to "multiple viruses", it means that it contains at least one virus. Correspondingly, "multiple viral target genes" refer to target genes present on these viruses. In this article, the new coronavirus refers to the SARS-CoV-2 virus. Correspondingly, the multiple virus database refers to a reference database that can be used for the identification of these viruses. According to an embodiment of the present disclosure, the multiple virus database contains data on target genes of these viruses. Similarly, multiple virus primer pools refer to primers that can be used for the amplification or identification of these viruses.

The present disclosure provides a sequencing method, including: enriching target genes from microorganisms to obtain enriched products, the microorganisms including at least one selected from bacteria, fungi, or viruses; based on the enrichment A library of products is constructed to obtain the sequencing library; based on the sequencing library, the sequencing is performed using a nanopore sequencing platform. By enriching the target genes from microorganisms, the obtained enriched products are constructed in accordance with the library construction process of the nanopore sequencing platform to obtain a sequencing library. The obtained sequencing library only contains the enriched target gene nucleic acid from microorganisms. The obtained sequencing library can be used to realize rapid sequencing analysis with the help of the nanopore sequencing platform. The detection time is less than 12 hours from sample to result, which is the fastest It can be completed in 6 hours, and at the same time, it can realize a one-time broad-spectrum detection of bacteria, fungi, and viruses. Moreover, because the target gene nucleic acid is enriched, the amount of data required for detection is reduced to 10-50mb/sample, which greatly reduces the cost of detection. Using the nanopore sequencing platform for sequencing, compared with the second-generation sequencing technology, it can be monitored on-site in non-professional laboratories, and detection and data analysis can be performed through laptops and network cloud processes.

According to an embodiment of the present disclosure, these target genes may be at least one selected from 16s rRNA, rpob, gyrB, hsp60, 23s rRNA, and ISR. These target genes can be used as detection areas for bacteria, and the specific types of bacteria can be determined by comparing the sequencing data of these detection areas with a reference database. According to embodiments of the present disclosure, these target genes may also be at least one of the target genes of the highly sensitive bacteria described in Table 1. These bacteria are clinically important and highly sensitive bacteria, and the specific species of the corresponding bacteria can be determined by detecting the corresponding target genes.

Table 1 Highly sensitive bacteria and their target genes

According to an embodiment of the present disclosure, these target genes may be at least one selected from ITS1-4, LSU(D1/2), 18s rRNA, and RPB2. These target genes can be used as detection areas for fungi, and the specific species of fungi can be determined by comparing the sequencing data of these detection areas with a reference database. According to the embodiments of the present disclosure, these target genes may also be the target genes of the fungi described in Table 2. These bacteria are clinically important and highly sensitive fungi. By detecting the target genes of these fungi, the specific species of the corresponding fungi can be determined.

Table 2 Highly sensitive fungi and their target genes

According to an embodiment of the present disclosure, the viral target genes include multiple viral target genes and/or new coronavirus target genes, and the multiple viral target genes include at least one selected from the viral target genes shown in Table 3; the new coronavirus The viral target genes include at least one selected from the target genes shown in Table 4.

Table 3 Multiple viruses and their target genes

Virus name	Target gene
Boca virus	NP1, VP1-2
Rhinovirus	VP4/VP2, 5’UTR
Human metapneumovirus	N gene, F gene, glycoprotein G, N gene
Respiratory syncytial virus	N gene, P gene

Coronavirus	1a, 1b
Adenovirus	hexon gene
Parainfluenza	H gene
Influenza A virus	M gene, H gene
Influenza B virus	M gene, HA, na, NS
Influenza C virus	M gene
Enterovirus	VP1
Herpes virus	glycoprotein G
Rubella virus	E1

Table 4 New Coronavirus Target Genes

According to an embodiment of the present disclosure, the method for constructing a library based on a nanopore sequencing platform further includes: performing PCR amplification on the target gene from the microorganism based on the primers in the primer pool, so as to realize the enrichment of the target gene. In order to obtain an enriched product, the primer pool contains at least one primer.

According to an embodiment of the present disclosure, the primer pool includes at least one selected from the following primer pools: a universal bacterial primer pool including the primers listed in Table 5; a universal fungal primer pool, the The universal fungal primer pool includes the primers listed in Table 6; the highly sensitive bacterial primer pool includes the primers listed in Table 7; the highly sensitive fungal primer pool includes the primers listed in Table 7. 8 primers listed; multiple virus primer pool, the multiple virus primer pool includes the primers listed in Table 9; new coronavirus primer pool, the new coronavirus primer pool includes the primers listed in Table 10.

According to the embodiments of the present disclosure, the enriched products of universal bacterial target genes, the enriched products of universal fungal target genes, the enriched products of highly sensitive bacteria and highly sensitive fungi target genes, the enriched products of multiple viral target genes, and the new crown The enriched products of viral target genes are mixed in a mass ratio of 20-60:5-15:10-25:10-25:10-25, and a library is constructed on the mixed products to obtain the sequencing library. According to a preferred embodiment of the present disclosure, these enriched products are mixed in a ratio of 30-50:6-10:12-20:12-20:12-20.

The present disclosure also provides an apparatus for identifying microorganisms, as shown in FIG. 1, comprising: a library construction unit, which is based on the sample nucleic acid to be tested and obtains a sequencing library according to the above method; a sequencing unit, the sequencing The unit is based on the sequencing library and uses a nanopore sequencing platform to perform sequencing to obtain the sequencing result; a data processing unit that compares the sequencing result of the nucleic acid of the sample to be tested with a reference database for determining Describe the microorganisms in the sample to be tested. According to an embodiment of the present disclosure, the sequencing unit can be connected to the library building unit, and the data processing unit can be connected to the sequencing unit. In the present disclosure, unless otherwise clearly defined and defined, the term "connected" should be understood in a broad sense, for example, it may be a fixed connection, a detachable connection, or a whole; it may be a mechanical connection or an electrical connection. Connected or can communicate with each other; it can be directly connected or indirectly connected through an intermediary, and it can be the internal communication between two components or the interaction relationship between two components, unless specifically defined otherwise. For those of ordinary skill in the art, the specific meaning of the above-mentioned terms in the present disclosure can be understood according to specific circumstances.

The solutions of the present disclosure will be explained below in conjunction with examples. Those skilled in the art will understand that the following embodiments are only used to illustrate the present disclosure, and should not be regarded as limiting the scope of the present disclosure. Where specific techniques or conditions are not indicated in the examples, the procedures shall be carried out in accordance with the techniques or conditions described in the literature in the field or in accordance with the product specification. The reagents or instruments used without the manufacturer's indication are all conventional products that can be purchased commercially.

Example 1 Construction of target gene design database

Download general bacterial target gene data from existing databases such as NCBI. Filter to remove incomplete gene sequences, incorrectly named sequences that are not part of the target gene, etc. Obtain high-quality bacterial 16s rRNA (ribosomal 16s rRNA subunit), and fungal ITS (internal transcribed spacer).

At the same time, 44493 high-quality bacteria and fungi complete genome data were downloaded from the EnsemblBacteria database. Through the analysis of all genome annotation information, referring to the method of the article, we extracted from the genome database the bacteria identification: rpob (bacterial RNA polymerase β subunit), gyrB (gyrase B subunit), hsp60( Heat shock protein 60), ISR (ribosomal 16s rRNA/23s rRNA intergenic region), atpD, dnaJ, tuf, sodA, rnpB, inhA, IS900, katG, RecA, fumC, icd, mdh, purA; and suitable for fungi Identified LSU, ITS1-4, LSU (D1/2), 18s rRNA, RPB1/2, TEF1, Bena (β-tulbulin), CaM (calmodulin), cyp51A, ND6, MCM7, CAL, TUB2, ACT and other databases.

Finally, filter and optimize the obtained database according to the gene length, gene name, and gene completeness to obtain a high-quality database for each target gene.

Example 2 Target gene conservative and specific region analysis scheme

Using the database constructed in Example 1, using a self-written and integrated analysis process, conservative and specific analysis of the data of each target was performed.

First, use ClustalW/ClustalX and other software to perform multiple sequence alignments, and calculate the conservative data of each alignment site through a statistical process written by yourself. Each target site is analyzed at three levels:

Level one, for the analysis of all the data of a single target site, obtain the "comparison analysis file 1".

Level 2: According to the species information of each data source in the database, use the genus and species name of each species to flatten all the sequences in the database with the species species name, and only keep no more than 5 sequences for the same species. The target gene is flattened out of the database, and all the data in the database is used for analysis to obtain "comparison analysis file 2".

Level three, according to the important pathogen information in Table 1 and Table 2, split each target gene data database into an independent clinically important bacterial database (a total of 60 genera) and a clinically important fungus database (a total of 15 genera), respectively Analyze each independent database to obtain "Comparison Analysis File 3".

Comprehensively compare and analyze the data of files 1, 2, and 3 to evaluate the statistical data of each target gene at the level of all bacteria or fungi, and the conservativeness, specificity, conservative region and specific region of clinically important pathogenic bacteria. For the design of new primers.

Example 3 Design of universal bacterial targeting genes and amplification primers

According to the above analysis results for different target genes, all bacterial targets are counted and classified.

First, statistically analyze the conservative data in the comparison analysis file 1 and the comparison analysis file 2 to determine whether there is a conservative region on the target gene. If present, the target gene can be used for bacterial primer design. The criteria for determining conservative areas are:

The conservative degree of consecutive >15 bases exceeds 80%;

Or in the region of 15-25 bases in length, where more than 90% of the bases have a conservative degree of more than 85%;

Or a contiguous region of >25 bases, in which more than 80% of the bases have a conservative degree of more than 85%.

According to the conservative analysis of each target gene, the application scope of bacterial target genes is divided, and the "target gene evaluation file" is obtained. The final universal bacterial target genes: 16s rRNA, rpob, gyrB, hsp60, ISR, 23s rRNA.

The conservative frequency and variable pattern analysis were performed on the conserved region sites obtained in the "target gene evaluation file", and the "site frequency file" and the "variable pattern file" were obtained respectively. The "site frequency file" records the exact probability of A, T, C, G and deletion at each base site in each conservative region. Based on this file, calculate the maximum probability sequence that may appear in each area and other possible permutation and combination types. The "variable pattern file" records the relationship between variable bases at different positions on each conserved region.

According to the compatible nucleic acid length of the nanopore sequencing method and the results of the above-mentioned "site frequency file" and "variable pattern file", the GC content, TM value, primer length, and expansion of each region on the target gene that can be used for primer design are performed. Increase the length of the product, calculate the GC content of the last 5 bases at the 3 end of the sequence, and the number of consecutive >3 identical base regions. Consider the following factors comprehensively to determine the sequence of each primer site, degenerate and primer combination: 1. Maximize the resolution of the data as much as possible; the primer amplified product is 200-1500 bases, the best 800bp; 2 Reduce the risk of amplification efficiency caused by mutations in conservative regions; according to the results of the "site frequency file", use a similar "shingle" structure to design multiple primers for a single site to improve the amplification efficiency of primers for different types of microorganisms; 3. Consider increasing the specificity of primers as much as possible. According to the results of the "variable pattern file", optimize the selection of the variable combination with the highest frequency, design specific primers, and mix with universal degenerate primers to form a new primer pool to improve the amplification efficiency of primers. 4. Consider the compatibility between different primers, and fix the GC and other key indicators of each primer within a certain range according to the "site frequency file". Improve the uniformity of primer amplification. Through this process, the design and testing of primers on 16s rRNA, rpob, gyrB, hsp60, ISR genes were completed, and a "universal bacterial primer pool" was obtained.

All primers in the designed universal bacterial primer pool meet the following conditions:

The length of the primer is 18-30 bases;

b. The melting temperature Tm of the primer is 57-64°C;

c. The GC content in the primer is 40-60%;

d. The Gibbs free energy ΔG of the 5 bases at the 3'end of the primer is greater than or equal to -9kcal/mol;

e. The primer self-complementarity value is less than 8.0, and the 3'end self-complementarity parameter of the primer is less than 3.0;

f. There is no degenerate base on 3 consecutive bases at the 3'end of the primer;

g. The length of the amplified product of the primer is 300 to 1500 bases.

Specifically, the designed primers are as follows:

Table 5 General bacterial primer pool

Example 4 Universal fungal targeting gene and amplification primer design

Using the same method as in Example 3, detailed analysis was performed on universal fungal target genes and regions suitable for primer amplification on genes. Finally, two target sites of ITS1-4 and LSU (D1/2) were determined, and the primers at the sites were redesigned to obtain a "universal fungal primer pool".

The primers in the provided universal fungal primer pool are as follows:

Table 6 General Fungal Primer Pool

Example 5 Combinations of highly sensitive bacteria and fungi targeting genes and amplification primers

Some target genes do not have universal conserved regions in all bacteria or fungi, and cannot be used for the detection of all bacteria or fungi. They are non-universal target genes. For this type of target gene, according to the content of "Comparison Analysis File 3", using the same method as in Example 3, the highly sensitive bacteria listed in Table 1 and the highly sensitive fungi listed in Table 2 were primed one by one. the design of. Although these non-universal target genes are not conserved in all bacteria or fungi, they are highly conserved within a specific genus, so primers designed based on this genus level can specifically amplify bacteria/fungi of this genus. In this way, adding this primer to the detection scheme can improve the sensitivity of the identification of bacteria/fungi of this genus. In addition, compared with the universal target gene, the non-universal gene has a greater degree of genetic sequence difference between closely related bacteria/fungi, and the bacteria/fungi can be better identified through the sequencing results, which can improve the method for the identification of bacteria/fungi Resolving power. Using the primer matching selection method in Example 3, a set of highly sensitive bacterial primer pool and a set of highly sensitive fungal primer pool were finally designed.

The designed primer pool for highly sensitive bacteria and fungi is shown in Table 7 below:

Table 7 Primer Pool of Highly Sensitive Bacteria

Table 8 Highly sensitive fungus primer pool

Example 6 Multiple bacterial and fungal target gene amplification method and amplification primer combination method

In order to achieve the detection of multiple bacteria and fungi, taking into account the high sensitivity and the wide range of identification, it is necessary to select a primer combination that can be used in an amplification reaction and a suitable amplification method. Based on the foregoing invention, a total of 3 sets of independently amplified primer pools were designed: universal bacterial primer pool, universal fungal primer pool, and highly sensitive bacteria/fungal primer pool.

In order to improve efficiency, the amplification products of multiple different specimens can be mixed and then the sequencing library construction and sequencing can be performed to reduce costs. Therefore, both ends of the amplified products of all primer pools need to carry a specific 24 base "tag sequence". Different specimens carry different tag sequences, and different primer pools in the same specimen carry the same tag sequences. Assign each piece of sequencing data to a specific specimen through the tag sequence.

The tag sequence can be introduced to both ends of the targeted gene by means of amplification. The primers in the universal bacterial primer pool, universal fungal primer pool, and highly sensitive bacteria/fungal primer pool are used to amplify target genes to ensure the sensitivity of amplification and the high efficiency of tag sequence introduction. The enriched products of universal bacterial target genes, the enriched products of universal fungal target genes, and the enriched products of highly sensitive bacteria/fungal target genes are obtained respectively.

Example 7 Design of virus targeted amplification primers

Download the complete reference genome of the virus to be detected from existing databases such as NCBI, and use the scheme in Example 2 to analyze the relatively conservative and variable regions on the virus genome. At the same time, refer to the published PCR identification for each type of virus in the current NCBI PubMed database, and the virus genes selected in the virus nucleic acid detection kit that has been approved by the FDA. After comprehensive analysis, select one or more target genes for the identification of each type of virus. Then filter out the non-complete gene sequences contained in the target genes of each type of virus from the NCBI database, and filter out the wrongly named sequences that do not belong to the target gene of interest, etc., to obtain a high-quality multiple virus database.

In addition, the method mentioned in Example 3 was used to design amplification primers suitable for single-molecule sequencing platforms such as nanopore sequencing to obtain a "multiple virus primer pool".

The primers in the provided multiple virus primer pool are shown in the following table:

Table 9 Multiple virus primer pool

Example 8 Design of highly sensitive and high coverage primers for the novel coronavirus 2019-nCoV (SARS-CoV-2)

From the GISAID database, download the published new coronavirus 2019-nCoV genome data, and use the scheme in Example 2 to confirm the conserved regions on the existing virus genome. Aiming at the conserved regions and simultaneously targeting the 9 genes of rdrp, S, ORF3a, E, M, ORF6, ORF7a, ORF8, and N genes in ORF1a/b on the genome, the "new coronavirus primer pool" was designed to cover the 9094bp gene region on the viral genome. 100% coverage of S, E, M genes related to virulence in the viral genome.

Table 10 New Coronavirus Primer Pool

Example 9 Multiplex virus target gene amplification method and amplification primer combination method

The "multiple virus primer pool" and the "new coronavirus primer pool" choose the same method for amplification. The detailed process includes reverse transcription-cDna amplification, as follows:

1. Reverse transcription

1.1 Transgender system configuration:

Element	Volume (ul)
Random 6 mers	1
dNTP Mixture	1
Nucleic acid sample	8
total capacity	10

Denaturation program: incubate at 65°C for 5 minutes, and cool quickly on ice (the PCR program can be set to 4°C).

1.2 Reverse transcription system configuration:

Element	Volume (ul)
The above-mentioned denatured products	10
Rnase Inhibitor	0.5
5X PrimeScript Ⅱ Buffer	4
PrimeScript II RTase	1
Rnase Free dH2O	4.5
total capacity	20

Reverse transcription program:

Number of cycles	Temperature(℃)	Time (minutes:seconds)
1	30	10:00

1	42	30:00
1	95	5:00
1	4	∞

1.3 Purify the amplified product using magnetic beads

2. cDna amplification

2.1 The first round of amplification system configuration:

2.2 The first round of amplification PCR program:

2.3 Purify the amplified product using magnetic beads. 2.4. The second round of amplification system configuration:

2.5 The second round of amplification system procedures:

Example 10 Hybrid library construction and sequencing of amplified products

In order to ensure that the enriched products obtained by PCR amplification using universal bacterial primer pool, universal fungal primer pool, highly sensitive bacteria/fungal primer pool, virus primer pool, and novel coronavirus primer pool can be fully detected by one sequencing. According to the number of samples, the enriched products obtained from five primer pool amplifications are selected and mixed according to the following proportions in Table 11 to obtain mixed products. The mixed products were constructed using Oxford nanopore technologies' ligation sequencing kit SQK-LSK109 for library construction, and were sequenced using Oxford nanopore technologies' MinION, GridION or PromethION sequencers.

Table 11 Mixing scheme of enriched products

Example 11 Simultaneous detection of 11 types of respiratory viruses and new coronaviruses in specimens

The nucleic acid was extracted from 45 throat swab specimens with clinically suspected novel coronavirus infection, and the “new coronavirus primer pool” provided in the above example was used to amplify 45 specimens, and the “multiple virus primer pool” was used for 16 specimens. For amplification, a different tag sequence is added to each sample. The concentration of the amplified product and the mixing amount of the sample are shown in Table 12 below:

Table 12 Sample mixing volume

The amplified products are built using a library building kit suitable for the nanopore sequencing platform, and then the nanopore sequencing platform is used for sequencing analysis. The sequencing results are compared with the new coronavirus 2019-nCoV detection kit that has been approved by the cFDA as the reference object. Blind sample comparison was performed, and the results are shown in Table 13 below:

Table 13 Comparison results

Based on the diagnostic results of the fluorescence quantitative kit, use the formula PCR and sequencing double positive/(PCR and sequencing double positive + PCR positive but sequencing negative) × 100% detection calculation sensitivity is 100%; use the formula PCR and sequencing double negative/ (PCR and sequencing double negative + PCR positive but sequencing negative) × 100% The negative predictive value is calculated as 100%.

Because the fluorescent quantitative PCR method has fewer cases where PCR is negative but sequencing is positive. Therefore, the above two indicators show that the nanopore sequencing diagnostic program of this application is not weaker than the current fluorescent quantitative PCR method in detection sensitivity.

Mutation analysis capability test

Analysis of virus genome genes contained in 45 specimens. The fragments in the sample that are compared to each target area are grouped, and 30 data in each group are randomly selected as the calibration "seed sequence", and the other 50 sequences in the group are randomly selected each time to use Medaka software (version 0.10.1) Perform data accuracy correction for each "seed sequence". The 30 “seed sequences” after correction are compared with the standard reference genome of the virus. When more than 80% of the "seed sequence" and the reference genome sequence have the same base difference, the gene locus of the tested sample carrying the virus is considered to be mutated.

Using the above process, in the 45 specimens tested this time, a single-base mutation was found in the genome of the infected person with the number C1 carrying the new coronavirus. As shown in Figure 2, the 22,097 bases of the patient’s virus-carrying genome have been mutated from the original G base to the A base.

In Figure 2, the top sequence is the standard reference sequence of the new coronavirus, and the bottom 30 are the corrected "seed sequence". The corrected seed sequence and the virus reference sequence are different at this location, which indicates the location. There is a genetic mutation.

Example 12 Rapid identification of fungal infections in the bloodstream system

Two patients, A and B, in the intensive transplantation department. Both patients A and B were clinically positive for fungal antigens. The clinical diagnosis: community-acquired pneumonia, severe (Pneumocystis infection), and clinical manifestations of infection with lack of immunity. The effect of treatment with drugs against Pneumocystis spp. is not obvious. Patient A sent a blood culture for detection of bloodstream infection on May 6, and the same blood was sent for testing with the primers and methods provided in this disclosure. The blood culture result report was positive on May 12, and after purification and culture, it was identified as C. marneffei by mass spectrometry on May 13, and it took a total of one week for identification; and the method provided in the present disclosure was used for sequencing 8 Hours later, the specimen identification results were obtained on May 7, and 8 sequencing data correctly aligned to C. marneffei were obtained from the fungal test data, and finally determined to be the fungus caused by C. marneffei Sexual bloodstream infection, it takes 1 day in total. In a similar situation, patient B was sent for blood culture at 2 a.m. on May 28, and the blood culture report was positive at 10 a.m. on the 29th. Then, it was reported as blood flow caused by cyanobacteria marneffei at 10 a.m. on the 30th through purification culture. Infection, it takes a total of nearly 3 days; and using the method provided in the present disclosure, due to the severe bloodstream infection of the patient, the proportion of cyanobacteria marneffei in the blood is high, and the blood can be detected 10 minutes after sequencing Produced more than 50 comparisons to the sequencing data of C. marneffei, and reported them to the clinic on the 28th, which took 12 hours in total.

Blood culture is currently the most commonly used clinically, and it is also considered the gold standard for the diagnosis of blood infections. The two clinical cases shown above are serious infections and initial infections. Regardless of the clinical situation, the solutions provided by the present disclosure are consistent with the results of blood culture testing, and at the same time, the time required for testing is greatly reduced.

The detailed content described above is only used as two clinical cases to illustrate the effects of the present disclosure. Using the same method as the above, the inventors analyzed more than one thousand clinical cases, compared and analyzed the results of culture and detection by the primers and methods provided in the present disclosure, and found through comparison that the primers provided in the present disclosure were used And method for detection, the detection accuracy rate is much higher than the detection result of culture; and using the primers and methods provided in the present disclosure for detection, the detection time used is shorter, especially for the detection of fungi, the time is more demonstrated Obviously shorten the advantage.

Example 13 Rapid identification of Mycobacterium tuberculosis infection in the respiratory system

Because Mycobacterium tuberculosis grows very slowly, it takes nearly a month for culture and identification. Therefore, in the past, in clinical diagnosis, GeneXpert nucleic acid detection method (WHO recommended gold standard), T-SPOT antigen detection method or acid-fast staining method was often used for clinical diagnosis. Identification. These methods require 1-8 hours to identify Mycobacterium tuberculosis. However, due to its technical limitations, it can only detect one pathogen of Mycobacterium tuberculosis in a targeted manner. Therefore, in clinical use, it is often necessary for clinicians to pre-judge through clinical symptoms or to screen multiple pathogens one by one. This whole process is time-consuming and laborious, and is easily affected by subjective factors such as doctor's experience. Using the primers and methods provided in the present disclosure, more than 500 specimens of sputum or alveolar lavage fluid of patients with respiratory system infection admitted to the Department of Respiratory Medicine were used to detect and analyze all bacteria and fungi. Tuberculosis was identified in 34 patients’ specimens Mycobacterial infection (Table 14).

For these 34 patients, 27 of them were also re-examined using the gold standard GeneXpert nucleic acid detection method. The results showed that 27 people were positive for Mycobacterium tuberculosis. % Agree.

Table 14 Anastomosis in detection of Mycobacterium tuberculosis

In the description of this specification, descriptions with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" etc. mean specific features described in conjunction with the embodiment or example , Structures, materials, or characteristics are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above-mentioned terms are not necessarily directed to the same embodiment or example. Moreover, the described specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine the different embodiments or examples and the features of the different embodiments or examples described in this specification without contradicting each other.

Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above-mentioned embodiments are exemplary and should not be construed as limiting the present disclosure. Those of ordinary skill in the art can comment on the foregoing within the scope of the present disclosure. The embodiment undergoes changes, modifications, substitutions, and modifications.

Claims (31)

1. A method for constructing a library based on a nanopore sequencing platform, which is characterized in that it comprises:

   Enriching target genes from microorganisms to obtain enriched products, the microorganisms including at least one selected from bacteria, fungi or viruses;

   A library is constructed based on the enriched product, so as to obtain the sequencing library.
2. The method of claim 1, wherein the microorganism is a fungus.
3. The method according to claim 1, wherein the bacterial target gene comprises a universal bacterial target gene and/or a highly sensitive bacterial target gene,

   The universal bacterial target gene includes at least one selected from the group consisting of 16s rRNA, rpob, gyrB, hsp60, ISR, and 23s rRNA;

   The target genes of the highly sensitive bacteria include at least one selected from the target genes on the highly sensitive bacteria shown in Table 1.
4. The method according to claim 3, wherein the universal bacterial target genes include the target regions listed in Table 5 and the regions of 500 bp before and after them.
5. The method according to claim 3, wherein the highly sensitive bacterial target gene includes the target region listed in Table 7 and the region of 500 bp before and after the target region.
6. The method according to claim 1, wherein the fungal target gene comprises a universal fungal target gene and/or a highly sensitive fungal target gene,

   The universal fungal target gene includes at least one selected from ITS1-4, LSU(D1/2), 18s rRNA, and RPB2;

   The target gene of the highly sensitive fungus includes at least one selected from the target genes on the highly sensitive fungus shown in Table 2.
7. The method according to claim 6, wherein the universal fungal target gene includes the target region listed in Table 6 and the region of 500 bp before and after it.
8. The method according to claim 6, wherein the highly sensitive fungal target gene includes the target region listed in Table 8 and the region of 500 bp before and after it.
9. The method according to claim 1, wherein the viral target genes comprise multiple viral target genes and/or new coronavirus target genes,

   The multiple viral target genes include at least one selected from the viral target genes shown in Table 3;

   The new coronavirus target gene includes at least one selected from the target genes shown in Table 4.
10. The method according to claim 9, wherein the multiple viral target genes include the target regions listed in Table 9 and the regions of 200 bp before and after them.
11. The method according to claim 9, wherein the target gene of the new coronavirus comprises the target region listed in Table 10 and the region of 200 bp before and after it.
12. The method according to any one of claims 1 to 11, wherein the bacterial target gene comprises a universal bacterial target gene and a highly sensitive bacterial target gene,

    The fungal target genes include universal fungal target genes and highly sensitive fungal target genes,

    The viral target genes include multiple viral target genes and new coronavirus target genes,

    The method further includes:

    The general bacterial target gene enrichment product, the general fungal target gene enrichment product, the highly sensitive bacterial target gene and the highly sensitive fungal target gene enrichment product, the multiple viral target gene enrichment product and the new coronavirus target gene enrichment product are based on the mass ratio Mixing in a ratio of 20-60:5-15:10-25:10-25:10-25, and building a library of the mixed products to obtain the sequencing library.
13. The method according to claim 1, further comprising:

    The target gene from the microorganism is amplified by PCR based on the primers in the primer pool to achieve the enrichment of the target gene so as to obtain the enriched product, and the primer pool includes at least one primer.
14. The method according to claim 13, wherein the primers in the primer pool all meet the following conditions:

    a. The length of the primer is 18-30 bases;

    b. The melting temperature Tm of the primer is 57-64°C;

    c. The GC content in the primer is 40-60%;

    d. The Gibbs free energy ΔG of the 5 bases at the 3'end of the primer is greater than or equal to -9kcal/mol;

    e. The primer self-complementarity value is less than 8.0, and the 3'end self-complementarity parameter of the primer is less than 3.0;

    f. There is no degenerate base on 3 consecutive bases at the 3'end of the primer;

    g. The length of the amplified product of the primer is 200 to 1500 bases.
15. The method according to claim 13, wherein the primer pool comprises at least one selected from the following primer pools:

    A universal bacterial primer pool, the universal bacterial primer pool includes the primers listed in Table 5;

    A universal fungal primer pool, the universal fungal primer pool includes the primers listed in Table 6;

    A highly sensitive bacterial primer pool, the highly sensitive bacterial primer pool includes the primers listed in Table 7;

    A highly sensitive fungal primer pool, which includes the primers listed in Table 8;

    Multiple virus primer pool, the multiple virus primer pool includes the primers listed in Table 9;

    The new coronavirus primer pool includes the primers listed in Table 10.
16. A sequencing method, characterized in that it comprises:

    Obtain a sequencing library based on the method of any one of claims 1-15;

    Based on the sequencing library, the nanopore sequencing platform is used for sequencing.
17. A method for identifying microorganisms, which is characterized in that it comprises:

    Obtain a sequencing library according to the method of any one of claims 1-15 based on the nucleic acid of the sample to be tested;

    Based on the sequencing library, the nanopore sequencing platform is used to perform sequencing, so as to obtain sequencing results;

    The sequencing result is compared with a reference database, and the microorganisms in the sample to be tested are determined based on the comparison result.
18. The method according to claim 17, wherein the reference database comprises at least one of the following:

    A general bacterial database, which contains 16s rRNA, rpob, gyrB, hsp60, 23s rRNA, and ISR gene data;

    A general fungus database, which contains TS1-4, LSU(D1/2), 18s rRNA and RPB2 gene data;

    A highly sensitive bacteria database, where the highly sensitive bacteria database contains the target gene data of the highly sensitive bacteria shown in Table 1;

    A highly sensitive fungus database, the highly sensitive fungus database containing the highly sensitive fungal target gene data shown in Table 2;

    A multiple virus database, the multiple virus database containing virus target gene data shown in Table 3;

    The new coronavirus database contains the genome data of the SARS-CoV-2 virus.
19. The method according to claim 18, further comprising:

    Comparing the sequencing results with the universal bacterial database and the universal fungus database, respectively, so as to obtain the first comparison data and the first uncompared data;

    Comparing the first uncompared data with the highly sensitive bacteria database and the highly sensitive fungus database respectively, so as to obtain the second comparison data and the second uncompared data;

    Comparing the second uncompared data with the multiple virus database and the new coronavirus database, so as to obtain third comparison data;

    Based on the first comparison data, determine the general bacteria and general fungi contained in the sample, based on the second comparison data, determine that the sample contains highly sensitive bacteria and highly sensitive fungi, based on the third comparison Data to determine the virus contained in the sample.
20. The method of claim 19, wherein:

    The determining the general bacteria and general fungi contained in the sample based on the first comparison data further includes:

    Dividing the first comparison data into first unique comparison data and at least one group of first cross comparison data, each group of first cross comparison data contains multiple sequences;

    Taking part of multiple sequences in each group of first crossover data as seed sequences, and correcting the seed sequence by using the remaining part of the sequence in the group, so as to obtain a corrected seed sequence;

    The calibrated seed sequence is combined with the optimal comparison data of the universal bacteria database and the universal fungus database, and the first unique comparison data to determine the universal bacteria and universal fungi contained in the sample.
21. The method of claim 19, wherein:

    The determining that the sample contains highly sensitive bacteria and highly sensitive fungi based on the second comparison data further includes:

    Dividing the second comparison data into second unique comparison data and at least one group of second cross comparison data, each group of second cross comparison data contains multiple sequences;

    Taking part of multiple sequences in each group of second crossover data as seed sequences, and correcting the seed sequence by using the remaining part of the sequence in the group, so as to obtain a corrected seed sequence;

    Combine the corrected seed sequence with the optimal comparison result of the highly sensitive bacteria database and the highly sensitive fungus database, and the second unique comparison data to determine the highly sensitive bacteria contained in the sample and Highly sensitive fungus.
22. The method of claim 19, wherein:

    The determining the virus contained in the sample based on the third comparison data further includes:

    The multiple sequences that are aligned to the same gene region in the third comparison data are grouped into a group, the partial sequence in each group is used as the seed sequence, and the remaining partial sequences in the group are used to correct the seed sequence, so that Obtain the corrected seed sequence;

    Based on the optimal comparison result of the corrected seed sequence with the multiple virus database and the new coronavirus database, the virus contained in the sample is determined.
23. The method according to claim 22, further comprising: determining based on at least 80% or more of the same base differences between the corrected seed sequence and the multiple virus database and the new coronavirus database The mutation site of the virus in the sample to be tested.
24. A device for identifying microorganisms, which is characterized in that it comprises:

    A library construction unit, based on the nucleic acid of the sample to be tested, to obtain a sequencing library according to the method according to any one of claims 1 to 15;

    A sequencing unit, the sequencing unit uses a nanopore sequencing platform to perform sequencing based on the sequencing library, so as to obtain the sequencing result;

    A data processing unit, which compares the sequencing result of the nucleic acid of the sample to be tested with a reference database, and is used to determine the microorganisms in the sample to be tested.
25. The device according to claim 24, wherein the reference database comprises at least one of the following:

    A general bacterial database, which contains 16s rRNA, rpob, gyrB, hsp60, 23s rRNA, and ISR gene data;

    A general fungus database, which contains TS1-4, LSU(D1/2), 18s rRNA and RPB2 gene data;

    A highly sensitive bacteria database, where the highly sensitive bacteria database contains the target gene data of the highly sensitive bacteria shown in Table 1;

    A highly sensitive fungus database, the highly sensitive fungus database containing the highly sensitive fungal target gene data shown in Table 2;

    A multiple virus database, the multiple virus database containing virus target gene data shown in Table 3;

    The new coronavirus database contains the genome data of the SARS-CoV-2 virus.
26. The device according to claim 24, wherein the data processing unit further comprises:

    Comparing the sequencing results with the universal bacterial database and the universal fungus database, respectively, so as to obtain the first comparison data and the first uncompared data;

    Comparing the first uncompared data with the highly sensitive bacteria database and the highly sensitive fungus database respectively, so as to obtain the second comparison data and the second uncompared data;

    Comparing the second uncompared data with the multiple virus database and the new coronavirus database, so as to obtain third comparison data;

    Based on the first comparison data, determine the general bacteria and general fungi contained in the sample, based on the second comparison data, determine that the sample contains highly sensitive bacteria and highly sensitive fungi, based on the third comparison Data to determine the virus contained in the sample.
27. The device of claim 26, wherein:

    The determining the general bacteria and general fungi contained in the sample based on the first comparison data further includes:

    Dividing the first comparison data into first unique comparison data and at least one group of first cross comparison data, each group of first cross comparison data contains multiple sequences;

    Taking part of multiple sequences in each group of first crossover data as seed sequences, and correcting the seed sequence by using the remaining part of the sequence in the group, so as to obtain a corrected seed sequence;

    Combine the corrected seed sequence with the optimal comparison result of the universal bacteria database and the universal fungus database, and the first unique comparison data to determine the universal bacteria and universal fungi contained in the sample.
28. The device according to claim 26, wherein the determining, based on the second comparison data, the highly sensitive bacteria and the highly sensitive fungi contained in the sample further comprises:

    Dividing the second comparison data into second unique comparison data and at least one group of second cross comparison data, each group of second cross comparison data contains multiple sequences;

    Taking part of multiple sequences in each group of second crossover data as seed sequences, and correcting the seed sequence by using the remaining part of the sequence in the group, so as to obtain a corrected seed sequence;

    Combine the corrected seed sequence with the optimal comparison result of the highly sensitive bacteria database and the highly sensitive fungus database, and the second unique comparison data to determine the highly sensitive bacteria contained in the sample and Highly sensitive fungus.
29. The device of claim 26, wherein the determining the virus contained in the sample based on the third comparison data further comprises:

    The multiple sequences that are aligned to the same gene region in the third comparison data are grouped into a group, the partial sequence in each group is used as the seed sequence, and the remaining partial sequences in the group are used to correct the seed sequence, so that Obtain the corrected seed sequence;

    Based on the optimal comparison result of the corrected seed sequence with the multiple virus database and the new coronavirus database, the virus contained in the sample is determined.
30. The device according to claim 29, further comprising: determining based on at least 80% or more of the same base differences between the corrected seed sequence and the multiple virus database and the new coronavirus database The mutation site of the virus in the sample to be tested.
31. A kit, characterized by comprising a primer pool, the primer pool comprising at least one selected from the following:

    A universal bacterial primer pool, the universal bacterial primer pool includes the primers listed in Table 5;

    A universal fungal primer pool, the universal fungal primer pool includes the primers listed in Table 6;

    A highly sensitive bacterial primer pool, the highly sensitive bacterial primer pool includes the primers listed in Table 7;

    A highly sensitive fungal primer pool, which includes the primers listed in Table 8;

    Multiple virus primer pool, the multiple virus primer pool includes the primers listed in Table 9;

    The new coronavirus primer pool includes the primers listed in Table 10.

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