Application of metagenomic next-generation sequencing in BALF in patients with pulmonary infection
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PROVIDER: PRJEB54782 | ENA |
REPOSITORIES: ENA
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Project description:BackgroundMetagenomic 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.MethodsFrom 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.ResultsThe 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.ConclusionsmNGS 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.
| S-EPMC6921575 | biostudies-literature
Project description:Clinical application and evaluation of metagenomic next-generation sequencing in pulmonary infection with pleural effusion
| PRJEB50303 | ENA
Project description:BackgroundMetagenomic next-generation sequencing (mNGS) technology has been widely used to diagnose various infections. Based on the most common pathogen profiles, targeted mNGS (tNGS) using multiplex PCR has been developed to detect pathogens with predesigned primers in the panel, significantly improving sensitivity and reducing economic burden on patients. However, there are few studies on summarizing pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China on large scale.MethodsFrom January 2021 to December 2023, bronchoalveolar lavage fluid (BALF) or sputum samples from 546 immunocompetent and immunocompromised patients with suspected community-acquired pneumonia were collected. Pathogen profiles in those patients on whom mNGS was performed were summarized. Additionally, we also evaluated the performance of tNGS in diagnosing pulmonary infections.ResultsCombined with results of mNGS and culture, we found that the most common bacterial pathogens were Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii in both immunocompromised and immunocompetent patients with high detection rates of Staphylococcus aureus and Enterococcus faecium, respectively. For fungal pathogens, Pneumocystis jirovecii was commonly detected in patients, while fungal infections in immunocompetent patients were mainly caused by Candida albicans. Most of viral infections in patients were caused by Human betaherpesvirus 5 and Human gammaherpesvirus 4. It is worth noting that, compared with immunocompetent patients (34.9%, 76/218), more mixed infections were found in immunocompromised patients (37.8%, 14/37). Additionally, taking final comprehensive clinical diagnoses as reference standard, total coincidence rate of BALF tNGS (81.4%, 48/59) was much higher than that of BALF mNGS (40.0%, 112/280).ConclusionsOur findings supplemented and classified the pathogen profiles of pulmonary infections in immunocompetent and immunocompromised patients in Jilin Province of China. Most importantly, our findings can accelerate the development and design of tNGS specifically used for regional pulmonary infections.
| S-EPMC11333343 | biostudies-literature
Project description:Nontuberculous Mycobacteria by Metagenomic Next-Generation Sequencing
| PRJEB43518 | ENA
Project description:Invasive Pulmonary Aspergillosis Diagnosis via Peripheral Blood Metagenomic Next Generation Sequencing
| PRJEB43573 | ENA
Project description:Nocardia Infection Cases Presenting as Pulmonary Mass Were Diagnosed by Metagenomic Next-Generation Sequencing
| PRJEB43516 | ENA
Project description:BackgroundPulmonary cryptococcosis (PC) and mixed pulmonary infection are difficult to be diagnosed due to the non-specificity and their overlapping clinical manifestations. In terms of the clinical diagnosis of PC and mixed pulmonary infection, conventional tests have limitations such as a long detection period, a limited range of pathogens, and low sensitivity. Metagenomics next-generation sequencing (mNGS) is a nascent and powerful method that can detect pathogens without culture, to diagnose known and unexplained infections in reduced time.Case presentationA 43-year-old female was admitted to the hospital after suffering from a cough for one month. At the time of admission, a contrast-enhanced chest CT revealed multiple nodules and plaques in her right lung, as well as the formation of cavities. The blood routine assays showed evidently increased white blood cell count (mainly neutrophils), CRP, and ESR, which suggested she was in the infection phase. The serum CrAg-LFA test showed a positive result. Initially, she was diagnosed with an unexplained pulmonary infection. Bronchoalveolar lavage fluid (BALF) samples were collected for microbial culture, immunological tests and the mNGS. Microbial culture and immunological tests were all negative, while mNGS detected Corynebacterium striatum, Pseudomonas aeruginosa, Streptococcus pneumoniae, and Cryptococcus neoformans. The diagnosis was revised to PC and bacterial pneumonia. Lung infection lesions were healed after she received targeted anti-infection therapy with mezlocillin and fluconazole. In a follow-up after 2 months, the patient's symptoms vanished.ConclusionsHere, we demonstrated that mNGS was capable of accurately distinguishing Cryptococcus from M. tuberculosis in pulmonary infection, and notably mNGS was capable of swiftly and precisely detecting pathogens in mixed bacterial and fungal pulmonary infection. Furthermore, the results of mNGS also have the potential to adjust anti-infective therapies.
| S-EPMC9701064 | biostudies-literature
Project description:Next generation sequence analysis
| PRJNA560769 | ENA
Project description: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.
| S-EPMC7991794 | biostudies-literature