Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

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.

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Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

10.21203/rs.2.12006/v2 ◽

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.

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Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

10.21203/rs.2.12006/v1 ◽

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.

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Metagenomic next-generation sequencing for mixed pulmonary infection diagnosis

BMC Pulmonary Medicine ◽

10.1186/s12890-019-1022-4 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 4

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

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.541092 ◽

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.

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Case Report: Metagenomic Next-Generation Sequencing in Diagnosis of Talaromycosis of an Immunocompetent Patient

Frontiers in Medicine ◽

10.3389/fmed.2021.656194 ◽

2021 ◽

Vol 8 ◽

Author(s):

Jiejun Shi ◽

Naibin Yang ◽

Guoqing Qian

Keyword(s):

Next Generation Sequencing ◽

Pathogenic Bacteria ◽

Clinical Decision Making ◽

Fungal Infections ◽

Clinical Manifestations ◽

Whole Body ◽

Recurrent Fever ◽

Next Generation ◽

Generation Sequencing ◽

Immunocompetent Patients

Background: Talaromycosis is a serious fungal infection which is rare in immunocompetent people. Since its clinical manifestations lack specificity, it is easy to escape diagnosis or be misdiagnosed leading to high mortality and poor prognosis. It is necessary to be alert to the disease when broad-spectrum antibiotics do not work well in immunocompetent patients.Case Presentation: A 79-year-old man was admitted to our Infectious Diseases Department for recurrent fever and cough. Before admission he has been treated with piperacillin-tazobactam, moxifloxacin followed by antituberculous agents in other hospitals while his symptoms were not thoroughly eased. During the first hospitalization in another hospital, he has been ordered a series of examination including radionuclide whole body bone imaging, transbronchial needle aspiration for subcarinal nodes. However, the results were negative showing no neoplasm. After being admitted to our hospital, he underwent various routine examinations. The initial diagnosis was bacterial pneumonia, and he was given meropenem injection and tigecycline injection successively, but there were no improvement of symptoms and inflammatory indicators. In the end, the main pathogen Talaromyces marneffei was confirmed using Metagenomic Next-Generation Sequencing (mNGS), and his clinical symptoms gradually relieved after targeted antifungal treatment using voriconazole.Conclusion: When empirical anti-infective treatment is ineffective, it is necessary to consider the possibility of opportunistic fungal infections on immunocompetent patients. mNGS, as a new generation of pathogenic testing methods, can often detect pathogenic bacteria faster than traditional methods, providing important help for clinical decision-making.

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

International Journal of Antimicrobial Agents ◽

10.1016/j.ijantimicag.2021.106421.69 ◽

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

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A Retrospective Paired Comparison Between Untargeted Next Generation Sequencing and Conventional Microbiology Tests With Wisely Chosen Metagenomic Sequencing Positive Criteria

Frontiers in Medicine ◽

10.3389/fmed.2021.686247 ◽

2021 ◽

Vol 8 ◽

Author(s):

Hanyu Qin ◽

Jinmin Peng ◽

Ling Liu ◽

Jing Wu ◽

Lingai Pan ◽

...

Keyword(s):

Next Generation Sequencing ◽

Fungal Infections ◽

Rna Virus ◽

Paired Comparison ◽

Final Analysis ◽

Metagenomic Sequencing ◽

Next Generation ◽

Dna Virus ◽

Virus Identification ◽

Generation Sequencing

Objectives: To evaluate the performance of metagenomic next generation sequencing (mNGS) using adequate criteria for the detection of pathogens in lower respiratory tract (LRT) samples with a paired comparison to conventional microbiology tests (CMT).Methods: One hundred sixty-seven patients were reviewed from four different intensive care units (ICUs) in mainland China during 2018 with both mNGS and CMT results of LRT samples available. The reads per million ratio (RPMsample/RPMnon−template−control ratio) and standardized strictly mapped reads number (SDSMRN) were the two criteria chosen for identifying positive pathogens reported from mNGS. A McNemar test was used for a paired comparison analysis between mNGS and CMT.Results: One hundred forty-nine cases were counted into the final analysis. The RPMsample/RPMNTC ratio criterion performed better with a higher accuracy for bacteria, fungi, and virus than SDSMRN criterion [bacteria (RPMsample/RPMNTC ratio vs. SDSMRN), 65.1 vs. 55.7%; fungi, 75.8 vs. 71.1%; DNA virus, 86.3 vs. 74.5%; RNA virus, 90.9 vs. 81.8%]. The mNGS was also superior in bacteria detection only if an SDSMRN ≥3 was used as a positive criterion with a paired comparison to culture [SDSMRN positive, 92/149 (61.7%); culture positive, 54/149 (36.2%); p < 0.001]; however, it was outperformed with significantly more fungi and DNA virus identification when choosing both criteria for positive outliers [fungi (RPMsample/RPMNTC ratio vs. SDSMRN vs. culture), 23.5 vs. 29.5 vs. 8.7%, p < 0.001; DNA virus (RPMsample/RPMNTC ratio vs. SDSMRN vs. PCR), 14.1 vs. 20.8 vs. 11.8%, p < 0.05].Conclusions: Metagenomic next generation sequencing may contribute to revealing the LRT infection etiology in hospitalized groups of potential fungal infections and in situations with less access to the multiplex PCR of LRT samples from the laboratory by choosing a wise criterion like the RPMsample/RPMNTC ratio.

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Metagenomic Next Generation Sequencing in the Detection of Pathogens in Cerebrospinal Fluid of Patients After Alternative Donor Transplantation: A Feasibility Analysis

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.720132 ◽

2021 ◽

Vol 11 ◽

Author(s):

Binglei Zhang ◽

Jian Zhou ◽

Ruirui Gui ◽

Zhen Li ◽

Yingling Zu ◽

...

Keyword(s):

Cerebrospinal Fluid ◽

Next Generation Sequencing ◽

Viral Infections ◽

Fungal Infections ◽

Clinical Manifestations ◽

Next Generation ◽

Hematopoietic Stem ◽

Cns Infections ◽

Alternative Donor ◽

Generation Sequencing

Central nervous system (CNS) complications can occur in 9%–15% of patients after allogeneic hematopoietic stem cell transplantation (allo-HSCT). The clinical manifestations of the CNS complications are non-specific, with most of them being disturbances of consciousness, convulsions, headaches, fever, and epilepsy, making it difficult to infer the cause of the complications based on clinical manifestations. We retrospectively analyzed the sensitivity and feasibility of metagenomic next generation sequencing (mNGS) in the diagnosis of CNS infections after allo-HSCT. Lumbar punctures were performed on 20 patients with CNS symptoms after receiving alternative donor HSCT(AD-HSCT) at the Affiliated Cancer Hospital of Zhengzhou University from February 2019 to December 2020, and their cerebrospinal fluid (CSF) was collected. The mNGS technique was used to detect pathogens in the CSF. Routine CSF testing, biochemical analyses, G experiments, GM experiments, ink staining, acid-fast staining, and bacterial cultures were carried out, and quantitative PCR (qPCR) tests were used to detect cytomegalovirus (CMV), Epstein-Barr virus (EBV), BK polyomavirus (BKPyV), and human alphaherpesvirus (HHV). A total of 29 tests were performed with 21 of them being positive. Of the five negative patients, three were diagnosed with a posterior reversible encephalopathy syndrome, one as having transplantation-associated thrombotic microangiopathy, and one with transient seizure caused by hypertension. Fifteen patients tested positive, of which four had single infections and eleven had mixed infections. Five cases of fungal infections, six cases of bacterial infections, and 13 cases of viral infections were detected. Among the 13 cases of viral infections, ten cases were CMV(HHV-5); three were BKPyV; two were Torque teno virus (TTV); Two were HHV-1,two were EBV(HHV4), and one each of HpyV5 and HHV-6B. Thirteen patients tested positive for virus while the qPCR detection method of 6 identical specimens were below the minimum detection limit(<1×103 U/ml). The mNGS technique is highly sensitive, and it can be used to diagnose CNS infections after allo-HSCT.

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Rapid Genomic Diagnosis of Fungal Infections in the Age of Next-Generation Sequencing

Journal of Fungi ◽

10.3390/jof7080636 ◽

2021 ◽

Vol 7 (8) ◽

pp. 636

Author(s):

Chi-Ching Tsang ◽

Jade L. L. Teng ◽

Susanna K. P. Lau ◽

Patrick C. Y. Woo

Keyword(s):

Risk Factor ◽

Next Generation Sequencing ◽

Fungal Infections ◽

Laboratory Diagnosis ◽

Clinical Applications ◽

Hiv Positive ◽

Next Generation ◽

The Cost ◽

Next Generation Sequencing Ngs ◽

Generation Sequencing

Next-generation sequencing (NGS) technologies have recently developed beyond the research realm and started to mature into clinical applications. Here, we review the current use of NGS for laboratory diagnosis of fungal infections. Since the first reported case in 2014, >300 cases of fungal infections diagnosed by NGS were described. Pneumocystis jirovecii is the predominant fungus reported, constituting ~25% of the fungi detected. In ~12.5% of the cases, more than one fungus was detected by NGS. For P. jirovecii infections diagnosed by NGS, all 91 patients suffered from pneumonia and only 1 was HIV-positive. This is very different from the general epidemiology of P. jirovecii infections, of which HIV infection is the most important risk factor. The epidemiology of Talaromyces marneffei infection diagnosed by NGS is also different from its general epidemiology, in that only 3/11 patients were HIV-positive. The major advantage of using NGS for laboratory diagnosis is that it can pick up all pathogens, particularly when initial microbiological investigations are unfruitful. When the cost of NGS is further reduced, expertise more widely available and other obstacles overcome, NGS would be a useful tool for laboratory diagnosis of fungal infections, particularly for difficult-to-grow fungi and cases with low fungal loads.

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