scholarly journals The performance of in-house metagenomics next-generation sequencing with Illumina and Nanopore platform to identify pathogens of pulmonary infection from lung biopsy tissues

2021 ◽  
Vol 58 ◽  
pp. 2100340
Author(s):  
Yifan Guo ◽  
Henan Li ◽  
Hui Wang
Keyword(s):  
Next Generation Sequencing ◽  
Lung Biopsy ◽  
Pulmonary Infection ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

2019 ◽  
Author(s):  
Jiahui Wang ◽  
Yelei Han ◽  
Yang Zhou ◽  
Jing Feng
Keyword(s):  
Next Generation Sequencing ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
Fungal Infections ◽  
Next Generation ◽  
Promising Technique ◽  
Infection Diagnosis ◽  
Conventional Tests ◽  
Conventional Test ◽  
Generation Sequencing

Abstract Background. Metagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce. Methods. From July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared. Results. The sensitivity of mNGS in mixed pulmonary infection diagnose was much higher than that of conventional test (97.2％ vs 13.9％; P< 0.01) , but the specificity was the opposite (63.2％ vs 94.7％; P= 0.07) . The positive predictive value of mNGS was 83.3% (95% CI: 68.0-92.5%) , and the negative predictive value was 92.3% (95% CI: 62.1-99.6%) . A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1(1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1(1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected was H uman cytomegalovirus in our study, which was identified in 19(34.5%) cases of mixed pulmonary infection . Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7(12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection. Conclusions. mNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.

scholarly journals Improving Pulmonary Infection Diagnosis with Metagenomic Next Generation Sequencing

2021 ◽  
Vol 10 ◽  
Author(s):  
Yi-Yi Qian ◽  
Hong-Yu Wang ◽  
Yang Zhou ◽  
Hao-Cheng Zhang ◽  
Yi-Min Zhu ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Pathogen Detection ◽  
Pulmonary Infection ◽  
Diagnostic Methods ◽  
Diagnostic Efficiency ◽  
Pulmonary Infections ◽  
Next Generation ◽  
Standard Polymerase Chain Reaction ◽  
Conventional Methods ◽  
Generation Sequencing

Pulmonary infections are among the most common and important infectious diseases due to their high morbidity and mortality, especially in older and immunocompromised individuals. However, due to the limitations in sensitivity and the long turn-around time (TAT) of conventional diagnostic methods, pathogen detection and identification methods for pulmonary infection with greater diagnostic efficiency are urgently needed. In recent years, unbiased metagenomic next generation sequencing (mNGS) has been widely used to detect different types of infectious pathogens, and is especially useful for the detection of rare and newly emergent pathogens, showing better diagnostic performance than traditional methods. There has been limited research exploring the application of mNGS for the diagnosis of pulmonary infections. In this study we evaluated the diagnostic efficiency and clinical impact of mNGS on pulmonary infections. A total of 100 respiratory samples were collected from patients diagnosed with pulmonary infection in Shanghai, China. Conventional methods, including culture and standard polymerase chain reaction (PCR) panel analysis for respiratory tract viruses, and mNGS were used for the pathogen detection in respiratory samples. The difference in the diagnostic yield between conventional methods and mNGS demonstrated that mNGS had higher sensitivity than traditional culture for the detection of pathogenic bacteria and fungi (95% vs 54%; p&lt;0.001). Although mNGS had lower sensitivity than PCR for diagnosing viral infections, it identified 14 viral species that were not detected using conventional methods, including multiple subtypes of human herpesvirus. mNGS detected viruses with a genome coverage &gt;95% and a sequencing depth &gt;100× and provided reliable phylogenetic and epidemiological information. mNGS offered extra benefits, including a shorter TAT. As a complementary approach to conventional methods, mNGS could help improving the identification of respiratory infection agents. We recommend the timely use of mNGS when infection of mixed or rare pathogens is suspected, especially in immunocompromised individuals and or individuals with severe conditions that require urgent treatment.

scholarly journals Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

2019 ◽  
Author(s):  
Jiahui Wang ◽  
Yelei Han ◽  
Jing Feng
Keyword(s):  
Next Generation Sequencing ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
Fungal Infections ◽  
Next Generation ◽  
Promising Technique ◽  
Infection Diagnosis ◽  
Conventional Tests ◽  
Conventional Test ◽  
Generation Sequencing

Abstract Background: Metagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce.Methods: From July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared.Results: The sensitivity of mNGS in mixed pulmonary infection diagnose was much higher than that of conventional test (97.2％ vs 13.9％; P< 0.01) , but the specificity was the opposite (63.2％ vs 94.7％; P= 0.07) . The positive predictive value of mNGS was 83.3% (95% CI: 68.0-92.5%) , and the negative predictive value was 92.3% (95% CI: 62.1-99.6%) . A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1(1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1(1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected was H uman cytomegalovirus in our study, which was identified in 19(34.5%) cases of mixed pulmonary infection . Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7(12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection.Conclusions: mNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.

scholarly journals Mycobacteriummucogenicum and Klebsiellapneumoniae Pulmonary Infection in a Patient Following Cardiac Surgery: A Case Report

2021 ◽  
Vol 14 (2) ◽  
Author(s):  
Zhi-peng Wen ◽  
Chun-li Xu ◽  
Qin Li ◽  
Zhi-chang Zheng ◽  
Ji-hong Yang ◽  
...  
Keyword(s):  
Cardiac Surgery ◽  
Next Generation Sequencing ◽  
Pulmonary Infection ◽  
Case Reports ◽  
Next Generation ◽  
Next Generation Sequencing Technology ◽  
Appropriate Treatment ◽  
Pulmonary Arterial ◽  
Generation Sequencing ◽  
Mycobacterium Mucogenicum

Introduction: Mycobacterium mucogenicum belongs to the rapidly growing mycobacteria, and it is a rare conditional pathogen. Although recent studies suggested that the incidence of M. mucogenicum infection was increased worldwide, there are no case reports of M. mucogenicum and Klebsiella pneumoniae pulmonary infection. Case Presentation: A 32-year-old non-smoking male was diagnosed with congenital atrial septal defect and pulmonary arterial hypertension. After cardiac surgery, lung infections were observed in the patient and then rapidly developed acute respiratory distress syndrome. The cefoperazone and sulbactam, vancomycin, ceftazidime, carbapenem, tigecycline, and micafungin were used for the treatment of pulmonary infection but did not affect. Ultimately, M. mucogenicum and K. pneumoniae were identified as pathogens by using next-generation sequencing. The patient was treated successfully with the administration of clarithromycin, linezolid, tigecycline, and ceftazidime-avibactam. The clinical outcome of this patient was favorable without relapse of infection. Conclusions: This case demonstrates that M. mucogenicum pulmonary infection may result in severe outcomes. The next-generation sequencing technology is important for the identification of M. mucogenicum. Additionally, the clinicians and clinical pharmacists should remain awareness in dealing with M. mucogenicum infection to avoid delaying appropriate treatment.

scholarly journals Application of Metagenomic Next-Generation Sequencing in the Diagnosis of Pulmonary Infectious Pathogens From Bronchoalveolar Lavage Samples

2021 ◽  
Vol 11 ◽  
Author(s):  
Yuqian Chen ◽  
Wei Feng ◽  
Kai Ye ◽  
Li Guo ◽  
Han Xia ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Bronchoalveolar Lavage ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
Diversity Index ◽  
Microbial Culture ◽  
Pulmonary Infections ◽  
Next Generation ◽  
Underlying Diseases ◽  
Generation Sequencing

BackgroundMetagenomic next-generation sequencing (mNGS) is a powerful method for pathogen detection. In this study, we assessed the value of mNGS for bronchoalveolar lavage (BAL) samples in the diagnosis of pulmonary infections.MethodsFrom February 2018 to April 2019, BAL samples were collected from 235 patients with suspected pulmonary infections. mNGS and microbial culture were performed to evaluate the effectiveness of mNGS in pulmonary infection diagnosis.ResultsWe employed mNGS to evaluate the alpha diversity, results suggesting that patients with confirmed pathogens had a lower microbial diversity index compared to that of patients with uncertain pathogens. For the patients admitted to the respiratory intensive care unit (RICU) or on a ventilator, they experienced a lower diversity index than that of the patients in the general ward or not on a ventilator. In addition, mNGS of BAL had a diagnostic sensitivity of 88.89% and a specificity of 14.86% in pulmonary infection, with 21.16% positive predictive value (PPV) and 83.87% negative predictive value (NPV). When rare pathogens were excluded, the sensitivity of mNGS decreased to 73.33%, and the specificity increased to 41.71%. For patients in the simple pulmonary infection group and the immunocompromised group, the main infection types were bacterial infection (58.33%) and mixed-infection (43.18%). Furthermore, mNGS had an advantage over culture in describing polymicrobial ecosystem, demonstrating the microbial distribution and the dominant strains of the respiratory tract in patients with different underlying diseases.ConclusionsThe study indicated that mNGS of BAL samples could provide more accurate diagnostic information in pulmonary infections and demonstrate the changes of respiratory microbiome in different underlying diseases. This method might play an important role in the clinical use of antimicrobial agents in the future.

scholarly journals The Application of Metagenomic Next-Generation Sequencing in Detection of Pathogen in Bronchoalveolar Lavage Fluid and Sputum Samples of Patients with Pulmonary Infection

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Wanghui Shi ◽  
Shanshan Zhu
Keyword(s):  
Next Generation Sequencing ◽  
Bronchoalveolar Lavage ◽  
Pathogen Detection ◽  
Bronchoalveolar Lavage Fluid ◽  
Pulmonary Infection ◽  
Lavage Fluid ◽  
Microbial Culture ◽  
Next Generation ◽  
Two Samples ◽  
Generation Sequencing

Objective. To uncover the application value of metagenomic next-generation sequencing (mNGS) in the detection of pathogen in bronchoalveolar lavage fluid (BALF) and sputum samples. Methods. Totally, 32 patients with pulmonary infection were included. Pathogens in BALF and sputum samples were tested simultaneously by routine microbial culture and mNGS. Main infected pathogens (bacteria, fungi, and viruses) and their distribution in BALF and sputum samples were analyzed. Moreover, the diagnostic performance of mNGS in paired BALF and sputum samples was assessed. Results. The pathogen culture results were positive in 9 patients and negative in 13 patients. No statistical differences were recorded on the sensitivity (78.94% vs. 63.15%, p = 0.283 ) and specificity (62.50% vs. 75.00%, p = 0.375 ) of mNGS diagnosis in bacteria and fungus in two types of samples. As shown in mNGS detection, 10 patients’ two samples were both positive, 13 patients’ two samples were both negative, 7 patients were only positive in BALF samples, and 2 patients’ sputum samples were positive. Main viruses mNGS detected were EB virus, human adenovirus 5, herpes simplex virus type 1, and human cytomegalovirus. Kappa consensus analysis indicated that mNGS showed significant consistency in detecting pathogens in two samples, no matter bacteria ( p < 0.001 ), fungi ( p = 0.026 ), or viruses ( p = 0.008 ). Conclusion. mNGS showed no statistical differences in sensitivity and specificity of pathogen detection in BALF and sputum samples. Under certain conditions, sputum samples might be more suitable for pathogen detection because of invasiveness of BALF samples.

scholarly journals Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

2019 ◽  
Author(s):  
Jiahui Wang ◽  
Yelei Han ◽  
Yang Zhou ◽  
Jing Feng
Keyword(s):  
Next Generation Sequencing ◽  
Human Cytomegalovirus ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
Next Generation ◽  
Promising Technique ◽  
Infection Diagnosis ◽  
Conventional Tests ◽  
Conventional Test ◽  
Generation Sequencing

Abstract Background. Metagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce. Methods. From July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared. Results.The sensitivity of mNGS in mixed pulmonary infection diagnose was much higher than that of conventional test (97.2％ vs 13.9％;P<0.01) , but the specificity was the opposite (63.2％ vs 94.7％;P=0.07) . The positive predictive value of mNGS was 83.3% (95% CI: 68.0-92.5%) , and the negative predictive value was 92.3% (95% CI: 62.1-99.6%) . A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1(1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1(1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected was Human cytomegalovirus in our study, which was identified in 19(34.5%) cases of mixed pulmonary infection. Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7(12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection. Conclusions. mNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity.

scholarly journals Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jiahui Wang ◽  
Yelei Han ◽  
Jing Feng
Keyword(s):  
Next Generation Sequencing ◽  
Human Cytomegalovirus ◽  
Predictive Value ◽  
Pulmonary Infection ◽  
Next Generation ◽  
Promising Technique ◽  
Infection Diagnosis ◽  
Conventional Tests ◽  
Conventional Test ◽  
Generation Sequencing

Abstract Background Metagenomic next-generation sequencing (mNGS) is emerging as a promising technique for pathogens detection. However, reports on the application of mNGS in mixed pulmonary infection remain scarce. Methods From July 2018 to March 2019, 55 cases were enrolled in this retrospective analysis. Cases were classified into mixed pulmonary infection (36 [65.5%]) and non-mixed pulmonary infection (19 [34.5%]) according to primary diagnoses. The performances of mNGS and conventional test on mixed pulmonary infection diagnosis and pathogen identification were compared. Results The sensitivity of mNGS in mixed pulmonary infection diagnosis was much higher than that of conventional test (97.2% vs 13.9%; P < 0.01), but the specificity was the opposite (63.2% vs 94.7%; P = 0.07). The positive predictive value of mNGS was 83.3% (95% CI, 68.0–92.5%), and the negative predictive value was 92.3% (95% CI, 62.1–99.6%). A total of 5 (9.1%) cases were identified as mixed pulmonary infection by both conventional tests and mNGS, however, the pathogens identification results were consistent between these two methods in only 1 (1.8%) case. In summary, the pathogens detected by mNGS in 3 (5.5%) cases were consistent with those by conventional test, and only 1 (1.8%) case was mixed pulmonary infection. According to our data, mNGS had a broader spectrum for pathogen detection than conventional tests. In particular, application of mNGS improved the diagnosis of pulmonary fungal infections. Within the 55 cases, mNGS detected and identified fungi in 31 (56.4%) cases, of which only 10 (18.2%) cases were positive for the same fungi by conventional test. The most common pathogen detected by mNGS was Human cytomegalovirus in our study, which was identified in 19 (34.5%) cases of mixed pulmonary infection. Human cytomegalovirus and Pneumocystis jirovecii, which were detected in 7 (12.7%) cases, were the most common co-pathogens in the group of mixed pulmonary infection. Conclusions mNGS is a promising technique to detect co-pathogens in mixed pulmonary infection, with potential benefits in speed and sensitivity. Trial registration (retrospectively registered): ChiCTR1900023727. Registrated 9 JUNE 2019.

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