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Application Research Of Metagenomic Sequencing Technology In Pathogen Identification Of Acute Respiratory Infection

Posted on:2021-03-01Degree:MasterType:Thesis
Country:ChinaCandidate:Y F LinFull Text:PDF
GTID:2404330614970444Subject:Public health
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Acute respiratory infection is a common disease that endangers public health.In order to cope with the impact of acute respiratory infection on the economy and society,and to understand its clinical characteristics and pathogenic laws,China has established a sentinel surveillance network for severe acute respiratory infection cases in hospitals to carry out pathogen monitoring and research work.Identifying pathogens is the primary link in the monitoring and prevention of acute respiratory infections.However,pathogen identification of respiratory tract infections poses great difficulties due to the variety of pathogens,tendency of mutations,multiple pathogen co-infections and the continuous emergence of various new infectious pathogens.At present,the commonly used clinical pathogen detection methods mainly include pathogen isolation and culture,immunological detection,molecular biological detection,etc.The pathogen isolation and culture is the "gold standard" for the diagnosis of clinical infectious disease pathogens,but this method takes a long time and has a low positive rate.Immunological detection methods such as colloidal gold and molecular biological detection methods such as PCR can only detect a limited number of known pathogens,and cannot detect rare or new pathogens.The metagenomic sequencing method can directly detect all the microbial nucleic acids in the sample without isolating and cultivating the pathogen in the clinical sample.It can not only simultaneously detect multiple microorganisms present in the sample,but also identify possible infection-related microorganisms that are not easily detected by conventional methods,and is becoming a new method of pathogen detection.Traditional respiratory metagenomic sequencing requires separate extraction of DNA or RNA from the sample to build a sequencing library,which is not only cumbersome,but also difficult to detect RNA and DNA pathogenic microorganisms in the same reaction tube.This study establishes a DNA / RNA co-sequencing method,that is,the total nucleic acid extracted from clinical samples without the removal of DNA is directly subjected to random primer reverse transcription and c DNA second-strand synthesis to construct the DNA library and sequencing,to achieve the purpose of simultaneously detecting different types of microbial sequences in samples.Mocked samples were established by adding 5 different types of pathogens that can cause respiratory infections(RNA virus: influenza A virus,DNA virus: human adenovirus,Gram positive bacteria: Staphylococcus aureus,Gram negative bacteria: Klebsiella pneumoniae,fungus: Aspergillus fumigatus)in throat swabs of healthy people,and gradient dilution of different pathogens was performed to verify the ability of the method to detect single pathogens and multiple pathogens.The results show that for a single pathogen sample,the number of targeted pathogen sequences detected by this method has a certain linear relationship with the original pathogen concentration in the sample and the quantitative PCR detection Ct value.For multiple pathogen samples,five targeted pathogen sequences were detected in five multi-pathogen samples with different dilution gradients,proving that this method can realize the simultaneous detection of multiple types of pathogens in the sample,and also provides a new method for the monitoring of acute respiratory infection pathogens.The next-generation sequencing technology has the advantages of high throughput and high accuracy.The third-generation nanopore sequencing technology has the advantages of longer sequence read length,high portability,and real-time sequencing.In order to evaluate the application scenarios based on DNA/RNA co-sequencing combined with different sequencing technologies,this study selected a sample of alveolar lavage fluid from a patient with acute respiratory tract infection and carried out nanopore third-generation sequencing and BGI next-generation sequencing,respectively.The metagenomic sequencing of the two technologies and the simultaneous pathogen isolation and culture were conducted to analyze whether the detection results of the three methods were consistent and to compare the turnaround time of the three schemes.The pathogen detecting results of nanopore sequencing,BGI next-generation sequencing and pathogen isolation and culture were all Pseudomonas aeruginosa.The turnaround time of the three schemes was about 12 hours,154 hours and 50 hours respectively.The nanopore sequencing scheme detected a P.aeruginosa sequence at the 55 th minute of sequencing,and the turnaround time was the shortest among the three schemes.It is expected to be further applied to the real-time rapid detection of clinical infectious diseases.Among the sequencing results of the BGI next-generation sequencing scheme,P.aeruginosa accounted for the highest proportion of microbial sequences(58.94%),and the scheme also detected microorganisms such as Staphylococcus aureus,Human herpesvirus type 7,Propionibacterium acnes,etc.Compared with the nanopore sequencing scheme,the BGI scheme can obtain more detailed microbial abundance information in the sample,but its turnaround time is longer,which is more advantageous for scenarios such as large-scale respiratory pathogen monitoring without special requirements for the turnaround time.At present,pathogenic monitoring of acute respiratory infection mainly uses quantitative PCR and other methods,and metagenomic sequencing technology has not yet been carried out on a large scale.The current surveillance work is mainly focused on the surveillance of influenza viruses,and information on other pathogens is relatively lacking.In order to verify the application value of metagenomic sequencing technology in the pathogen monitoring of acute respiratory infection,this study was based on the DNA / RNA co-sequencing method and relied on the Beijing SARI case monitoring network to collect SARI samples of 64 death cases and 21 non-death cases from December 2017 to July 2019.Metagenomic sequencing was used to identify possible pathogens in the samples.The sensitivity of metagenomic sequencing technology to influenza A virus detection is 73.33%,the specificity is 95.92%,and the agreement rate is 90.63%.Kappa analysis was performed on the sequencing results and monitoring results.The Kappa value was 0.726,indicating that the metagenomic sequencing method for influenza A virus detection results and SARI influenza monitoring results are highly consistent.At the same time,KI polyomavirus,Ralstonia mannitol,Stenotrophomonas maltophilia and other microorganisms that may be related to infection were also detected in the samples,and found that there may be bacterial-virus co-infection in some samples.Some samples have dominant species with abundance> 50%.Metagenomic sequencing can identify possible infection-related microorganisms and co-infections in the samples that are not easily detected by conventional methods,obtain sample abundance and other information,and is expected to become an important supplement to traditional pathogen detection methods,providing technical support and scientific evidence for the monitoring,traceability,early warning and prevention of SARI pathogens in Beijing.In summary,this study established a DNA / RNA metagenomic co-sequencing method,which can achieve simultaneous detection of different pathogens such as bacteria and viruses in the sample.The method combined with the nanopore real-time sequencing platform can realize the rapid identification of clinically unknown pathogen infections.The method combined with the high-throughput next-generation sequencing platform can be applied to public health pathogen monitoring of large-scale samples,providing technical support and important reference for the identification of acute respiratory infection pathogens.
Keywords/Search Tags:High-throughput sequencing, Metagenomic sequencing, Severe acute respiratory infection, Pathogen detection, Clinical infection
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