CN111394486A - Child infectious disease pathogen detection and identification method based on metagenome sequencing - Google Patents
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Abstract
The invention relates to a method for detecting and identifying children infectious disease pathogeny based on metagenome sequencing, which comprises the following steps: extracting DNA of a micro sample after children are infected, and carrying out concentration measurement and quality control on the DNA; establishing a sequencing library of sample DNA, and then carrying out high-throughput sequencing and screening; and comparing the obtained product with a reference database to obtain a sequence with the comparison ratio of more than 70% and without multiple comparison, and then screening pathogenic microorganisms to complete the detection and identification method. The method optimizes the DNA extraction and database construction method aiming at the micro samples of children, and improves the database construction success rate and the effective sequencing data volume of the micro samples; establishes a pathogenic microorganism screening and identifying strategy, effectively eliminates the pollution of laboratories and reagents, and can effectively complete the identification of pathogenic microorganisms.
Description
Technical Field
The invention belongs to the technical field of microbial detection, and particularly relates to a child infectious disease pathogen detection and identification method based on metagenome sequencing.
Background
Infectious diseases are one of the most common diseases in children, and are the focus of pediatric clinical attention. The clinical manifestations of childhood infection are atypical and mostly non-specific, and early identification through clinical manifestations is difficult. On the basis of rapidly and accurately finding out the infection pathogen, a reasonable treatment scheme is selected, and the occurrence and development of diseases can be effectively controlled. Therefore, the early diagnosis and the early treatment of the infectious diseases of the children are significant for reducing the death rate of the children.
The traditional pathogen detection methods include smear microscopy, immunological detection, microbial culture, and molecular detection. However, only one or limited pathogens can be detected by the methods every time, and the culture has the defect of low positive rate, particularly, domestic antibiotics are widely applied, the blood culture positive rate is only 10%, and the cerebrospinal fluid culture positive rate is lower; in addition, the pathogenic culture needs a long time, at least 3 days; the detection rate of bacteria with slow growth speed and harsh culture conditions is lower (for example, the mycobacterium tuberculosis lasts for one month); while immunological detection of the virus exists in the window period; molecular detection requires that the detection range be determined in advance, and specific primers or probes are selected in a targeted manner to detect certain pathogens. The current commonly used auxiliary diagnostic methods comprise blood routine and classification, acute phase reaction proteins such as C-reactive protein, procalcitonin and the like, and have poor specificity and sensitivity.
Metagenomic sequencing (ngs) refers to a technique for sequencing the genome of a population of microorganisms in a particular environment. Because the NGS avoids the defect that most microorganisms cannot be cultured in the traditional method, the method has important significance for the diagnosis of clinical pathogenic microorganisms. In addition, the technology has the characteristics of short detection period (1-2 days), wide detection range, rich results (strain identification, drug resistance detection) and the like. The technology is widely applied to the diagnosis of pathogenic microorganisms infected by central nervous system, respiratory tract and septicemia at present. In the case reported by Charles et al in 2014, as many as 38 traditional pathogenic microorganism detection methods for one immunodeficiency patient are negative, and finally, the detection method progresses to epilepsy and hydrocephalus, and the sequence of 475 leptospira is detected in cerebrospinal fluid by using the mNGS, the medication strategy is changed rapidly, and finally, the disease is cured 25 days after the mNGS is diagnosed. As a first example demonstrating that mNGS can provide effective clinical information, the use of mNGS in the clinic is rapidly opening. Research shows that compared with culture and other methods, the sensitivity of the mNGS reaches 93.7%, and the positive rate is improved by 2.7 times. However, the mNGS is currently used mainly for detection of infectious diseases in adults and has less application in children. The characteristics of the child that samples are difficult to obtain and the sample size is small (e.g., cerebrospinal fluid is usually less than 1ml, blood 1-2ml) present challenges for nucleic acid extraction and library construction of the mNGS. Furthermore, because the mNGS are used to sequence the genomes of all microbial populations, background contamination of laboratories or reagents, and the presence of colonisation in different parts of the human body often complicate the detection of the mNGS. Therefore, interpretation of the outcome of an mNGS, i.e. how to distinguish background contamination, and how to identify the actual pathogenic bacteria from the colonising flora, is critical to the use of an mNGS.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a children infectious disease pathogen detection and identification method based on metagenomic sequencing, establishes an efficient nucleic acid extraction and corresponding library construction method aiming at a children micro sample, and develops a strategy for screening pathogenic bacteria from background and colonizing microorganisms, thereby establishing a children infectious disease pathogen detection and identification method based on metagenomic sequencing. The establishment of the method has important significance for quickly determining the pathogeny of infectious diseases of children, thereby establishing a targeted treatment strategy and reducing the hospitalization time, the medical cost, the antibiotic use days and the mortality of children patients.
The technical scheme adopted by the invention is as follows:
the children infectious disease pathogen detection and identification method based on metagenome sequencing comprises the following steps:
(1) processing the collected sample to be detected to obtain a processed sample;
(2) extracting DNA of the processed sample, and performing concentration measurement and quality control on the obtained DNA to obtain sample DNA;
(3) constructing a sequencing library of the sample DNA to obtain a sample sequencing library;
(4) performing high-throughput sequencing on the sample sequencing library, and then screening sequencing data to obtain a processed sample sequence;
(5) and comparing the processed sample sequence with a reference database to obtain a sequence with a comparison ratio of more than 70% and without multiple comparison, and then screening pathogenic microorganisms to complete the detection and identification method of the child infectious disease pathogen based on metagenomic sequencing.
Further, in the step (1), the method for processing the sample to be detected specifically includes that when the sample to be detected is one of cerebrospinal fluid, alveolar lavage fluid and ascites fluid samples to be detected, 1-2ml of sample to be detected 20000G (G is an international unit of a centrifuge, the rotating speed r/min is changed into a formula of G, RCF is 1.12 x 10 (-5) r (r/min) 2) is centrifuged for 5min, the supernatant is discarded to obtain the processed sample, when the sample to be detected is a whole blood sample, plasma is separated, 1-2ml of whole blood is centrifuged for 10min at 1600G and 4 ℃, the plasma does not touch a white mucous membrane layer, then 16000G and 4 ℃ are centrifuged for 10min, the supernatant is taken as a processed sample, when the sample to be detected is a pharyngeal swab sample, the sample to be detected needs to be vibrated, 1-2m L sterile soaked swab 5-10min is firstly added, and 30s are vibrated every other time, a cotton swab is squeezed, a cotton swab is taken as a treated sample, a crushed PBS is squeezed, the crushed sample is taken as a crushed PBS, the crushed sample is squeezed, the crushed sample is taken as a crushed PBS 3-365 min, the crushed sample is added, the crushed PBS is added, the crushed sample after L-362 m is added, the crushed sample is soaked into the crushed PBS 3-L, the crushed sample, the crushed PBS is added, the crushed sample, the crushed PBS is uniformly mixed, and.
Further, in the step (2), extracting the processed sample DNA from the whole blood sample, wherein a MagMAX free DNA separation kit is used; a Qiagen UCP pathogen small kit is used for extracting the treated sample DNA from the cerebrospinal fluid, the treated alveolar lavage fluid and the treated abdominal water body fluid sample sources, and the treated sample DNA from the pharynx swab sample source and the catheter sample source;
the concentration is measured by a Qubit fluorescence quantitative analyzer, and the quality control is to control the quality of the obtained DNA by electrophoresis.
Further, in the step (3), the kit for preparing the KAPA DNA library is used for constructing the sample DNA sequencing library.
Further, the step of constructing a sequencing library from the sample DNA obtained from the whole blood sample comprises end repair, Adapter connection, purification, amplification and purification; the steps of constructing a sequencing library from sample DNA obtained from body fluid samples such as cerebrospinal fluid, alveolar lavage fluid, ascites and the like, and sample DNA obtained from throat swab samples and catheter samples comprise DNA breaking, end repairing, Adapter connection, fragment selection, purification, amplification and purification.
Further, when the total amount of the sample DNA is more than 60ng, the total amount of the initial DNA required for constructing a sequencing library is 50-100 ng; when the total amount of DNA of the sample is more than 60ng and more than 25ng, the total amount of initial DNA required for constructing a sequencing library is 20-30 ng; when the total amount of 25ng of DNA in the sample is more than 15ng, the total amount of initial DNA required for constructing a sequencing library is 10 ng; when the total amount of the sample DNA is less than 15ng, the total amount of the initial DNA required for constructing a sequencing library is 30 ul; when the total amount of the sample DNA is less than 15ng (the total amount of the sample DNA is far less than that, namely the sample DNA amount is extremely low), the total amount of the initial DNA required for constructing a sequencing library is 30ul +10ng of internal references;
when the total amount of initial DNA required for constructing a sequencing library is more than or equal to 50ng, adding an Adapter with the volume of 2.5 ul; 50ng > 10ng of the total amount of initial DNA required for constructing a sequencing library, and 1.5ul of Adapter is added; 10ng is more than or equal to that the total quantity of initial DNA required for constructing a sequencing library is more than 3ng, and the volume of the added Adapter is 0.5 ul; when the total amount of initial DNA required for constructing a sequencing library is less than or equal to 3ng, adding an Adapter with the volume of 0.2 ul;
for other sample DNA except for whole blood samples, when the genomic DNA is more than 50ng, the number of amplification selection PCR cycles is 7 cycles; 50ng is more than or equal to 10ng of genome DNA, and the number of amplification selection PCR cycles is 9 cycles; when the genome DNA is not less than 10ng, the amplification selection PCR cycle number is 11 cycles;
for sample DNA obtained from a whole blood sample, when the free DNA is more than 30ng, the number of amplification selection PCR cycles is 5 cycles; 30ng is more than or equal to free DNA and more than 5ng, and the number of amplification selection PCR cycles is 7 cycles; 5ng is more than or equal to free DNA and more than 1ng, and the number of amplification selection PCR cycles is 9 cycles; when 1ng is larger than or equal to the genome DNA, the amplification selection PCR cycle number is 11 cycles; the fragment is selected as DNA with the size of screening fragment of 250-450 bp;
the sample DNA comprises genome DNA and free DNA separated from a whole blood sample, and the concentration of the free DNA can be simultaneously detected.
Further, the internal reference is DNA extracted from a healthy human sample.
Further, in step (4), the high throughput sequencing is performed on PE150 sequencing on an Illumina Novaseq platform, the data volume of each sample sequencing library is 10G, each batch of samples must contain negative controls for simultaneous DNA extraction and library building, and sequencing is performed on the same lane.
Further, in the step (4), the screening is to sequentially remove the adaptor sequence, filter the low-quality sequence, delete the sequence with the length less than 40bp from the sequencing data, and remove the sequence aligned to the reference genome GRCh 38;
the removal of the adaptor sequence and the filtration of the low-quality sequence are performed by using software Cutadapt v1.18, and the set parameter is-e 0.2-O10-m 40-q 15, and 15-max-n is 0.1; the sample sequencing library was further filtered using the software Bowtie v2.3.4 before alignment with the human reference genome GRCh 38.
Further, the linker sequence comprises a first read length and a second read length; the first read-length 5 'end linker sequence is shown as SEQ ID NO 1 and GATCGGAAGAGCACACGTCTGAACTCCAGTCACTAATACAGATCTCGTAT, the 3' end linker sequence is shown as SEQ ID NO 2, the sequences ACTGCACTCCAGCCTGGGCGACAGAGCGAGACTCCGTCTCAAAA and SEQ ID NO 3 and the sequence TCGGAAGAGCACACGTCTGAACTCCAGTCACGCAGAA; the second read-long 3' end linker sequences are shown in SEQ ID NO 4 and SEQ ID NO 5, with sequences GGAAAGAGTGTTGGCCGGTGTGTAGATCTCGGTGGTCGCCGTATCATT and TCGGAAGAGCACACGTCTGAACTCCAGTCACGCAGAA, respectively.
Further, in the step (5), the processed sample sequence is compared with a reference database by using a software centrifuge v1.0.3;
the reference database is a reference genomic sequence at the level of microorganisms downloaded from the NCBI genomic database, comprising more than 20000 reference genomic sequences, including more than 12000 bacteria, 7312 viruses, 515 fungi and 168 parasites; the construction method of the reference database comprises the following steps: for each species, sequences at Refseq level are downloaded first, sequences at Complete level are downloaded as a complement if there are less than 200 sequences at Refseq level, sequences at chromosome, scaffold and contig levels are downloaded if there are no sequences at Refseq and Complete level, low complexity fragments in the sequences are tagged with software dutmasker, sequences of less than 150bp are deleted, and then a database is constructed with centrifugev1.0.3;
the screening of pathogenic microorganisms comprises removing background microorganisms and screening permanent planting microorganisms;
the removal of background microorganisms is: (S1) first calculating RPM values of each species detected in the sample and the negative control; (S2) when the microorganism detected in the sample is simultaneously present in the negative control and the ratio of the RPM value of the sample to the RPM value of the negative control is greater than 10, the microorganism is a positive microorganism; when the bacteria, fungi or parasites detected in the sample are not present in the negative control and the RPM value of the sample is greater than 50, the bacteria, fungi or parasites are positive microorganisms; a virus detected in the sample is a positive microorganism when the virus is not present in the negative control and the non-overlapping sequencing reads in the sample are greater than 3; (S3) automatically comparing the positive microorganisms with the background microorganism list using a computer program to remove the positive microorganisms existing in the background microorganism list to obtain a positive microorganism list;
the screening of the planting microorganism is specifically as follows: the microorganism which is detected in the respiratory tract sample and overlaps with the respiratory tract colonization flora list is marked as P3, the microorganism which overlaps with the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2 is marked as P1, and other microorganisms which are detected in the respiratory tract sample and overlap with the positive microorganism list are marked as P2; the microorganism of the positive microorganism list of other samples except the respiratory tract sample, which is overlapped with the microorganisms in the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2, is marked as P1, and the rest microorganisms in the positive microorganism list are marked as P2; the overlapping microorganisms are obtained by automatic comparison of computer programs; the possibility of pathogenic microorganisms is P1 > P2 > P3 in sequence; the respiratory tract sample comprises a pharyngeal swab sample, sputum or alveolar lavage fluid.
RPM (Reads Per Million) value refers to the number of sequencing reads belonging to that species Per million sequencing reads of the microorganism.
Background list of microorganisms: the inventors previously tested a total of 142 negative control samples and generated the background microorganism list by analyzing the microbial composition in the negative control samples, as shown in table 1.
TABLE 1 list of background microorganisms
Note: taxid is the number of the microorganism in the NCBI database.
The inventor arranges the detected data of the respiratory tract samples collected in the earlier work to obtain a respiratory tract colonizing flora list, and the specific content is shown in table 2.
TABLE 2 respiratory tract colonizing flora List
Note: taxid is the number of the microorganism in the NCBI database.
The inventor collects data of all culture positive microorganisms of subsidiary pediatric hospital of the university of 'Redandan' in 2018 earlier, selects the microorganisms with the detection times of 50 th rank, and asks experts of related department principal and task level to review and modify, additionally incorporates 31 microorganisms, and combines the microorganisms to form the common pathogenic microorganism list 1, which is shown in Table 3.
TABLE 3 list of common pathogenic microorganisms 1
Note: taxid is the number of the microorganism in the NCBI database.
The list of common pathogenic microorganisms 2 includes 1449 strains of microorganisms, and details can be queried on the https:// www.kariusdx.com/pathogenlist/3.4 website.
The invention has the beneficial effects that:
the invention provides a children infectious disease pathogen detection and identification method based on metagenome sequencing, which comprises the following specific steps: extracting DNA of a micro sample after children are infected, and carrying out concentration measurement and quality control on the DNA; establishing a sequencing library of sample DNA, and then carrying out high-throughput sequencing and screening; and comparing the obtained product with a reference database to obtain a sequence with the comparison ratio of more than 70% and without multiple comparison, and then screening pathogenic microorganisms to complete the detection and identification method. The method provided by the invention is used for establishing an efficient nucleic acid extraction and corresponding library construction method aiming at a micro-sample of the child, and developing a strategy for screening pathogenic bacteria from background and colonized microorganisms, so that a child infectious disease pathogen detection and identification method based on metagenomic sequencing is established. The establishment of the method disclosed by the invention has important significance for quickly determining the pathogeny of the infectious diseases of children, so that a targeted treatment strategy is formulated, and the hospitalization time, the medical cost, the antibiotic use days and the mortality of children are reduced. The method optimizes the DNA extraction and database construction method aiming at the micro samples of children, and improves the database construction success rate and the effective sequencing data volume of the micro samples; establishes a pathogenic microorganism screening and identifying strategy, effectively eliminates the pollution of laboratories and reagents, and can effectively complete the identification of pathogenic microorganisms.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a graph of sensitivity evaluation of sequencing read sorting software according to this example;
FIG. 2 is a graph showing the evaluation of the positive predictive value of the sequencing read sorting software according to this example;
FIG. 3 is a graph showing the evaluation of the classification error rate of the sequencing read sorting software according to the present example.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
Example 1
The embodiment provides a children infectious disease pathogen detection and identification method based on metagenome sequencing, and the specific treatment method comprises the following steps:
(1) treating collected cerebrospinal fluid: centrifuging 1.5ml of sample to be detected for 5min at 20000G, and discarding the supernatant to obtain a processed sample;
(2) extracting the treated sample DNA by using a Qiagen UCP pathogen small kit; then, a Qubit fluorescence quantitative instrument is used for carrying out concentration determination on the obtained DNA, agarose gel electrophoresis is used for carrying out quality control, and a band of the genome DNA can be obviously observed after the sample DNA is subjected to electrophoresis to obtain the sample DNA;
(3) the steps of constructing the sample sequencing library by using the KAPA DNA library preparation kit comprise DNA breaking, end repairing, Adapter connection, screening of DNA with the fragment size of 250-450bp, purification, amplification and purification; the total amount of sample DNA is 13ng, the total amount of initial DNA required for constructing a sequencing library is 30ul, the volume of the added Adapter is 1.5ul, and the number of amplification selection PCR cycles is 9 cycles; the specific operation is carried out according to the operation steps disclosed by the kit;
(4) performing PE150 sequencing on the sample sequencing library on an Illumina Novaseq platform, wherein the data volume of each sample sequencing library is 10G, each batch of samples must contain negative control for simultaneously performing DNA extraction and library building, and sequencing is performed on the same lane; the sequencing data were then screened: sequentially removing the adaptor sequences from the sample sequencing library, wherein the adaptor sequences comprise a first read length and a second read length; the first read-long 5 'end linker sequence is shown as SEQ ID NO. 1, and the 3' end linker sequence is shown as SEQ ID NO. 2 and SEQ ID NO. 3; the second read-long 3' end connector sequence is shown as SEQ ID NO. 4 and SEQ ID NO. 5, then the low-quality sequence is filtered, the sequence with the length less than 40bp is deleted, and the sequence aligned to the ginseng reference genome GRCh38 is removed, so as to obtain a processed sample sequence;
(5) comparing the processed sample sequence with a reference database to obtain a sequence with an alignment ratio of more than 70% and no multiple alignment, wherein the reference database is a reference genome sequence of a microorganism level downloaded from a NCBI genome database, and comprises more than 20000 reference genome sequences, including more than 12000 bacteria, 7312 viruses, 515 fungi and 168 parasites; then, the pathogenic microorganism is screened: the screening of pathogenic microorganisms comprises removing background microorganisms and screening permanent planting microorganisms;
the removal of background microorganisms is: (S1) first calculating RPM values of each species detected in the sample and the negative control; (S2) the microorganisms detected in the sample are simultaneously present in the negative control, and the ratio of the RPM value of the sample to the RPM value of the negative control is greater than 10, the microorganisms are positive microorganisms; (S3) comparing the positive microorganisms with a background microorganism list, and removing the positive microorganisms existing in the background microorganism list to obtain a positive microorganism list;
the screening of the planting microorganism is specifically as follows: and (3) marking the overlapped microorganisms in the positive microorganism list, the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2 as P1, marking the rest microorganisms in the positive microorganism list as P2, and sequentially marking the possibility of pathogenic microorganisms as P1 > P2 > P3, thus completing the child infectious disease pathogen detection and identification method based on the metagenome sequencing.
Example 2
The embodiment provides a children infectious disease pathogen detection and identification method based on metagenome sequencing, and the specific treatment method comprises the following steps:
(1) processing the collected pharynx swab sample, namely firstly vibrating and extruding, firstly adding 2m L sterile PBS to soak the pharynx swab for 10min, vibrating for 30s every 2min, extruding a pharynx swab cotton stick to fully obtain eluent, and then absorbing 2m L eluent as a processed sample;
(2) extracting DNA of the processed sample by using a Qiagen UCP pathogen small kit, carrying out concentration determination on the obtained DNA by using a Qubit fluorescence quantitative instrument, and carrying out quality control by using electrophoresis to obtain sample DNA;
(3) the steps of constructing the sequencing library of the sample DNA by using the KAPA DNA library preparation kit comprise DNA breaking, end repairing, Adapter connection, screening DNA with the fragment size of 250-450bp, purification, amplification and purification; the total amount of the sample DNA is 20ng, the total amount of the initial DNA required for constructing a sequencing library is 10ng, the volume of the added Adapter is 0.5ul, and the number of amplification selection PCR cycles is 9 cycles; the specific operation is carried out according to the operation steps disclosed by the kit;
(4) performing PE150 sequencing on the sample sequencing library on an Illumina Novaseq platform, wherein the data volume of each sample sequencing library is 10G, each batch of samples must contain negative control for simultaneously performing DNA extraction and library building, and sequencing is performed on the same lane; the sequencing data were then screened: sequentially removing the adaptor sequences from the sample sequencing library, wherein the adaptor sequences comprise a first read length and a second read length; the first read-long 5 'end linker sequence is shown as SEQ ID NO. 1, and the 3' end linker sequence is shown as SEQ ID NO. 2 and SEQ ID NO. 3; the second read-long 3' end linker sequence is shown in SEQ ID NO 4 and SEQ ID NO 5; then filtering the low-quality sequence, deleting the sequence with the length less than 40bp, and removing the sequence aligned to the human reference genome GRCh38 to obtain a processed sample sequence;
(5) comparing the processed sample sequence with a reference database to obtain a sequence with an alignment ratio of more than 70% and no multiple alignment, wherein the reference database is a reference genome sequence of a microorganism level downloaded from a NCBI genome database, and comprises more than 20000 reference genome sequences, including more than 12000 bacteria, 7312 viruses, 515 fungi and 168 parasites; then, the pathogenic microorganism is screened: the screening of pathogenic microorganisms comprises removing background microorganisms and screening permanent planting microorganisms;
the removal of background microorganisms is: (S1) first calculating RPM values of each species detected in the sample and the negative control; (S2) the bacteria, fungi or parasites detected in the sample are not present in the negative control and the RPM value of the sample is greater than 50, said bacteria, fungi or parasites being positive microorganisms; the virus detected in the sample is not present in the negative control, and the non-overlapping sequencing reads in the sample are greater than 3, the virus is a positive microorganism; (S3) comparing the positive microorganisms with a background microorganism list, and removing the positive microorganisms existing in the background microorganism list to obtain a positive microorganism list;
the screening of the planting microorganism is specifically as follows: the microorganism which is overlapped in the positive microorganism list and the respiratory tract colonization flora list detected in the pharynx swab sample is marked as P3, the microorganism which is overlapped in the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2 is marked as P1, the other microorganisms which are remained in the positive microorganism list detected in the pharynx swab sample are marked as P2, and the possibility of pathogenic microorganisms is P1 > P2 > P3 in sequence, thus completing the detection and identification method of the children infectious disease pathogen based on the metagenomic sequencing.
Example 3
The embodiment provides a children infectious disease pathogen detection and identification method based on metagenome sequencing, and the specific treatment method comprises the following steps:
(1) the collected whole blood sample is processed: separating plasma, centrifuging 2ml whole blood at 1600G and 4 deg.C for 10min, separating plasma without touching leucocyte layer, centrifuging at 16000G and 4 deg.C for 10min, and collecting supernatant as processed sample;
(2) extracting DNA of the treated sample: extracting the DNA of a processed sample from a whole blood source, using a MagMAX free DNA separation kit, then using a Qubit fluorescence quantitative instrument to perform concentration determination on the obtained DNA, and using electrophoresis to perform quality control to obtain the sample DNA;
(3) constructing the sample sequencing library using a KAPA DNA library preparation kit: constructing a sequencing library from sample DNA obtained from a whole blood sample, wherein the steps comprise end repair, Adapter connection, purification, amplification and purification; wherein, when the total amount of the sample DNA is 65ng, the total amount of the initial DNA required for constructing a sequencing library is 50-100ng, the volume of the added Adapter is 2.5ul, and the number of amplification selection PCR cycles is 5 cycles; the specific operation is carried out according to the operation steps disclosed by the kit;
(4) performing PE150 sequencing on the sample sequencing library on an Illumina Novaseq platform, wherein the data volume of each sample sequencing library is 10G, each batch of samples must contain negative control for simultaneously performing DNA extraction and library building, and sequencing is performed on the same lane; the sequencing data were then screened: sequentially removing the adaptor sequences from the sample sequencing library, wherein the adaptor sequences comprise a first read length and a second read length; the first read-long 5 'end linker sequence is shown as SEQ ID NO. 1, and the 3' end linker sequence is shown as SEQ ID NO. 2 and SEQ ID NO. 3; the second read-long 3' end linker sequence is shown in SEQ ID NO 4 and SEQ ID NO 5; then filtering the low-quality sequence, deleting the sequence with the length less than 40bp, and removing the sequence aligned to the human reference genome GRCh38 to obtain a processed sample sequence;
(5) comparing the processed sample sequence with a reference database to obtain a sequence with an alignment ratio of more than 70% and no multiple alignment, wherein the reference database is a reference genome sequence of a microorganism level downloaded from a NCBI genome database, and comprises more than 20000 reference genome sequences, including more than 12000 bacteria, 7312 viruses, 515 fungi and 168 parasites; then, the pathogenic microorganism is screened: the screening of pathogenic microorganisms comprises removing background microorganisms and screening permanent planting microorganisms;
the removal of background microorganisms is: (S1) first calculating RPM values of each species detected in the sample and the negative control; (S2) the microorganisms detected in the sample are simultaneously present in the negative control, and the ratio of the RPM value of the sample to the RPM value of the negative control is greater than 10, the microorganisms are positive microorganisms; (S3) comparing the positive microorganisms with a background microorganism list, and removing the positive microorganisms existing in the background microorganism list to obtain a positive microorganism list;
the screening of the planting microorganism is specifically as follows: the microorganism which is overlapped in the obtained positive microorganism list, the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2 is marked as P1, the rest other microorganisms in the positive microorganism list are marked as P2, the possibility of pathogenic microorganisms is P1 > P2 > P3 in sequence, and the child infectious disease pathogen detection and identification method based on the metagenome sequencing is completed.
Examples of the experiments
First, sample DNA extraction scheme optimization
Respectively 10 are provided3And 105Copied mycobacterium smegmatis (gram positive) and salmonella typhimurium (gram negative) are mixed into blood of a healthy person to obtain spike-in samples, four DNA extraction methods are utilized for extraction (shown in table 4), a Qubit fluorescence quantifier is utilized to measure the concentration of extracted DNA, qPCR is carried out by utilizing specific primers of the mycobacterium smegmatis and the salmonella typhimurium, the content of the respective DNA belonging to the mycobacterium smegmatis and the salmonella typhimurium is evaluated according to the Ct value of qPCR amplification, and the efficiency of the four extraction methods is evaluated so as to select the optimal extraction method.
TABLE 4-extracted DNA concentration and qPCR Ct value of spike-in samples by four extraction methods
Note that M L, MagMAX free DNA isolation kit + mechanical lysis, MP, MagMAX free DNA isolation kit + panbacterio, QUCP, Qiagen UCP pathogen minikit, QM, QIAamp DNA microbiome kit, and the DNA concentration units are ng/ul.
As can be seen from Table 4, the qPCR average Ct values of the DNA extracted by the QUCP and QM methods are relatively close to each other and are smaller than those of the two extraction methods, which indicates that the bacterial DNA content obtained by the two extraction methods is the highest, and the DNA concentration obtained by the QM method is low and is not beneficial to the construction of a subsequent sequencing library, so that the QUCP is finally selected as the optimal extraction scheme.
Second, sequencing read length classification software evaluation
Downloading metagenome sequencing benchmark data (30 microorganisms), identifying the types of the microorganisms contained in the benchmark data and corresponding sequencing read length by utilizing kraken2, centrifuge, kaiju and metaplan 2 respectively, and evaluating the sensitivity, positive predicted value and classification error rate of four kinds of software on three levels of family, genus and species respectively by comparing with standard data; the sensitivity of centrifuge was found at the species level with a positive predictive value higher than the other 3 softwares and a classification error rate lower than the other 3 softwares (shown in fig. 1-3).
Reliability verification of macro-gene sequencing method
To verify the reliability of the established macrogene sequencing method, we performed separate verification of sterile zone (including blood, cerebrospinal fluid) and respiratory tract (alveolar lavage fluid) derived samples.
TABLE 5 comparison of results of the macrogene detection and the conventional methods for the detection of samples in the sterile zone
As can be seen from Table 5, for the sample in the sterile zone, the detection result of the traditional method is taken as the gold standard, the metagenome detection sensitivity reaches 91.67%, and the specificity reaches 67.86%. We collected 40 clinical samples (9 sera, 24 whole blood, 7 cerebrospinal fluids), each divided into two, and tested pathogenic microorganisms using the traditional method (culture, qPCR) and metagenomic sequencing, respectively. In 40 samples, 12 samples are positive by the traditional detection method, 20 samples are positive by the metagenome detection, the metagenome detection sensitivity reaches 91.67 percent (11/12), and the specificity reaches 67.86 percent (19/28). After 9 purposely collected positive serum samples are excluded, the metagenome positive rate reaches 38.71% (12/31), while the traditional detection method has a positive rate of only 9.68% (3/31). Metagenome also detects mixed infection in a single traditionally tested negative sample.
For respiratory tract source samples (alveolar lavage fluid), a macro-gene detection result is verified by using an Openarray chip aiming at respiratory tract infection pathogens. The chip contains 33 common respiratory infection pathogens and 3 control assays. From month 9 of 2019 to month 11 of 2019, we included a total of 46 patients in children diagnosed with respiratory infections at the subsidiary pediatric hospital at the university of counterdenier, for a total of 47 alveolar lavage samples. Of these, 30 were males and 16 were females. Also included were 6 patients with congenital immunodeficiency, with a median age of 4 years.
TABLE 6 comparison of the results of the macrogene assays with the Open Array chip
As can be seen from table 6, of the 47 samples, 43 were positive for the macrogene detection, and a total of 71 pathogens were detected in the 43 samples, with the bacteria, viruses and fungi accounting for 66.20%, 28.170% and 5.63%, respectively. The pathogens of the top 5 of the number of tests were mycoplasma pneumoniae (23.94%, 17/71), cytomegalovirus (11.27%, 8/71), streptococcus pneumoniae (11.27%, 8/71), EB virus (7.04%, 5/71), haemophilus influenzae (7.04%, 5/71), respectively. In 46.51% (20/43) of positive samples, more than 1 pathogen was detected, therefore, in order to more accurately evaluate the accuracy of the macrogene detection, we calculated sensitivity and specificity in units of detected pathogens, compared with the detection result of the Open Array chip, the sensitivity of the macrogene detection reaches 82.22% (37/45), and 12 microorganisms are not covered by the Open Array, resulting in 18 cases of Open Array negative and mNGS positive. For these 18 samples, corresponding probes were additionally designed for individual validation, and the detection results of 16 samples were consistent with those of the mNGS. .
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
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Claims (10)
1. The detection and identification method of children infectious disease pathogens based on metagenome sequencing is characterized by comprising the following steps:
(1) processing the collected sample to be detected to obtain a processed sample;
(2) extracting DNA of the processed sample, and performing concentration measurement and quality control on the obtained DNA to obtain sample DNA;
(3) constructing a sequencing library of the sample DNA to obtain a sample sequencing library;
(4) performing high-throughput sequencing on the sample sequencing library, and then screening sequencing data to obtain a processed sample sequence;
(5) and comparing the processed sample sequence with a reference database to obtain a sequence with a comparison ratio of more than 70% and without multiple comparison, and then screening pathogenic microorganisms to complete the detection and identification method of the child infectious disease pathogen based on metagenomic sequencing.
2. The method for detecting and identifying the etiology of infectious diseases in children based on metagenomic sequencing according to claim 1, wherein in the step (1), the method for processing the sample to be tested specifically comprises:
when the sample to be detected is one of cerebrospinal fluid, alveolar lavage fluid and ascites fluid samples to be detected, 1-2ml of sample to be detected needs to be taken for centrifugation for 5min at 20000G, supernatant is discarded, the processed sample is obtained, when the sample to be detected is a whole blood sample, plasma needs to be separated, 1-2ml of whole blood is taken for centrifugation for 10min at 1600G and 4 ℃, plasma does not touch a white blood membrane layer, then centrifugation is carried out for 10min at 16000G and 4 ℃, supernatant is absorbed as the processed sample, when the sample to be detected is a pharyngeal swab sample, vibration extrusion is needed, 1-2m L sterile PBS is firstly added to soak the pharyngeal swab for 5-10min, vibration is carried out for 30s every 1-2min, the pharyngeal swab cotton stick is fully extruded to obtain eluent, then 1-2m L eluent is absorbed as the processed sample, when the sample to be detected is a catheter sample, vibration is carried out after shearing, the catheter sample is firstly sheared, 1-2m L sterile soaking is added to soak for 5-10min, and the catheter sample is uniformly mixed after vibration is carried out for 30s every 1-2min, and then the catheter sample is absorbed as 1-L processing.
3. The method for detecting and identifying the pathogen of infectious diseases in children based on metagenomic sequencing as claimed in claim 1, wherein in the step (2), the processed sample DNA from the whole blood sample is extracted by using a MagMAX free DNA isolation kit; extracting processed sample DNA from cerebrospinal fluid, alveolar lavage fluid and ascites fluid sample sources, and processed sample DNA from a pharynx swab sample source and a catheter sample source, wherein the QIAGEN UCP pathogen small kit is used;
the concentration is measured by a Qubit fluorescence quantitative analyzer, and the quality control is to control the quality of the obtained DNA by electrophoresis.
4. The method for detecting and identifying pathogens of infectious diseases in children according to claim 1, wherein in step (3), the kit for preparing KAPA DNA library is used for constructing the sample DNA sequencing library.
5. The method for detecting and identifying pathogens of infectious diseases in children based on metagenomic sequencing of claim 4, wherein the step of constructing a sequencing library from the sample DNA obtained from the whole blood sample comprises end repair, Adapter ligation, purification, amplification and purification; the steps of constructing a sequencing library from sample DNA obtained from cerebrospinal fluid, alveolar lavage fluid, ascites fluid samples, and sample DNA obtained from throat swab samples and catheter samples include DNA disruption, end repair, Adapter ligation, fragment selection, purification, amplification and purification.
6. The method for detecting and identifying the etiological agent of the infectious disease in children according to claim 5, wherein when the total amount of DNA in the sample is greater than 60ng, the total amount of the initial DNA required for constructing the sequencing library is 50-100 ng; when the total amount of DNA of the sample is more than 60ng and more than 25ng, the total amount of initial DNA required for constructing a sequencing library is 20-30 ng; when the total amount of 25ng of DNA in the sample is more than 15ng, the total amount of initial DNA required for constructing a sequencing library is 10 ng; when the total amount of the sample DNA is less than 15ng, the total amount of the initial DNA required for constructing a sequencing library is 30 ul; when the total amount of sample DNA is less than 15ng, the total amount of initial DNA required for constructing a sequencing library is 30ul +10ng of internal reference;
when the total amount of initial DNA required for constructing a sequencing library is more than or equal to 50ng, adding an Adapter with the volume of 2.5 ul; 50ng > 10ng of the total amount of initial DNA required for constructing a sequencing library, and 1.5ul of Adapter is added; 10ng is more than or equal to that the total quantity of initial DNA required for constructing a sequencing library is more than 3ng, and the volume of the added Adapter is 0.5 ul; when the total amount of initial DNA required for constructing a sequencing library is less than or equal to 3ng, adding an Adapter with the volume of 0.2 ul;
for other sample DNA except for whole blood samples, when the genomic DNA is more than 50ng, the number of amplification selection PCR cycles is 7 cycles; 50ng is more than or equal to 10ng of genome DNA, and the number of amplification selection PCR cycles is 9 cycles; when the genome DNA is not less than 10ng, the amplification selection PCR cycle number is 11 cycles;
for sample DNA obtained from a whole blood sample, when the free DNA is more than 30ng, the number of amplification selection PCR cycles is 5 cycles; 30ng is more than or equal to free DNA and more than 5ng, and the number of amplification selection PCR cycles is 7 cycles; 5ng is more than or equal to free DNA and more than 1ng, and the number of amplification selection PCR cycles is 9 cycles; when 1ng is larger than or equal to the genome DNA, the amplification selection PCR cycle number is 11 cycles;
the fragment was selected as DNA with a screening fragment size of 250-450 bp.
7. The method for detecting and identifying infectious disease pathogens in children based on metagenomic sequencing according to claim 1, wherein in step (4), the high throughput sequencing is PE150 sequencing on Illumina Novaseq platform, and the data volume of each sample sequencing library is 10G.
8. The method for detecting and identifying the pathogen of infectious diseases in children based on metagenomic sequencing as claimed in claim 1, wherein in the step (4), the screening is to remove the linker sequence, filter the low-quality sequence, delete the sequence with the length less than 40bp, and remove the sequence aligned to the reference genome GRCh38 from the sequencing data.
9. The method for detecting and identifying a causative agent of an infectious disease in a child based on metagenomic sequencing of claim 8, wherein the linker sequence comprises a first read and a second read; the first read-long 5 'end linker sequence is shown as SEQ ID NO. 1, and the 3' end linker sequence is shown as SEQ ID NO. 2 and SEQ ID NO. 3; the second read-long 3' end linker sequences are shown in SEQ ID NO 4 and SEQ ID NO 5.
10. The method for detecting and identifying infectious disease pathogens in children based on metagenomic sequencing as claimed in claim 1, wherein in step (5), the reference database is a reference genomic sequence at the level of microorganisms downloaded from NCBI genomic database, and contains more than 20000 reference genomic sequences, including more than 12000 bacteria, 7312 viruses, 515 fungi and 168 parasites;
the screening of pathogenic microorganisms comprises removing background microorganisms and screening permanent planting microorganisms;
the removal of background microorganisms is: (S1) first calculating RPM values of each species detected in the sample and the negative control; (S2) when the microorganism detected in the sample is simultaneously present in the negative control and the ratio of the RPM value of the sample to the RPM value of the negative control is greater than 10, the microorganism is a positive microorganism; when the bacteria, fungi or parasites detected in the sample are not present in the negative control and the RPM value of the sample is greater than 50, the bacteria, fungi or parasites are positive microorganisms; a virus detected in the sample is a positive microorganism when the virus is not present in the negative control and the non-overlapping sequencing reads in the sample are greater than 3; (S3) comparing the positive microorganisms with a background microorganism list, and removing the positive microorganisms existing in the background microorganism list to obtain a positive microorganism list;
the screening of the planting microorganism is specifically as follows: the microorganism which is detected in the respiratory tract sample and overlaps with the respiratory tract colonization flora list is marked as P3, the microorganism which overlaps with the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2 is marked as P1, and other microorganisms which are detected in the respiratory tract sample and overlap with the positive microorganism list are marked as P2; the microorganism of the positive microorganism list of other samples except the respiratory tract sample, which is overlapped with the microorganisms in the common pathogenic microorganism list 1 and the common pathogenic microorganism list 2, is marked as P1, and the rest microorganisms in the positive microorganism list are marked as P2; the possibility of pathogenic microorganisms is P1 > P2 > P3 in this order; the respiratory tract sample comprises a pharyngeal swab sample, sputum or alveolar lavage fluid.
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| CN114107454A (en) * | 2020-08-28 | 2022-03-01 | 上海交通大学医学院附属上海儿童医学中心 | Respiratory tract infection pathogen detection method based on macrogene/macrotranscriptome sequencing |
| CN112410406A (en) * | 2020-11-23 | 2021-02-26 | 深圳基因家科技有限公司 | Method for determining amplification cycle number of library |
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| CN115859174A (en) * | 2023-01-06 | 2023-03-28 | 深圳市儿童医院 | Bacterial meningitis classification model construction method and application of bacterial meningitis classification model in recognition of cerebrospinal fluid metagenome sequencing false positive result |
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