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:Metagenomic next-generation sequencing (mNGS) is increasingly being used to detect pathogens directly from clinical specimens. However, the optimal application of mNGS and subsequent result interpretation can be challenging. In addition, studies reporting the use of mNGS for the diagnosis of invasive fungal infections (IFIs) are rare. We critically evaluated the performance of mNGS in the diagnosis of pulmonary IFIs, by conducting a multicenter retrospective analysis. The methodological strengths of mNGS were recognized, and diagnostic cutoffs were determined. A total of 310 patients with suspected pulmonary IFIs were included in this study. Conventional microbiological tests (CMTs) and mNGS were performed in parallel on the same set of samples. Receiver operating characteristic (ROC) curves were used to evaluate the performance of the logarithm of reads per kilobase per million mapped reads [lg(RPKM)], and read counts were used to predict true-positive pathogens. The majority of the selected patients (86.5%) were immunocompromised. Twenty species of fungi were detected by mNGS, which was more than was achieved with standard culture methods. Peripheral blood lymphocyte and monocyte counts, as well as serum albumin levels, were significantly negatively correlated with fungal infection. In contrast, C-reactive protein and procalcitonin levels showed a significant positive correlation with fungal infection. ROC curves showed that mNGS [and especially lg(RPKM)] was superior to CMTs in its diagnostic performance. The area under the ROC curve value obtained for lg(RPKM) in the bronchoalveolar lavage fluid of patients with suspected pulmonary IFIs, used to predict true-positive pathogens, was 0.967, and the cutoff value calculated from the Youden index was -5.44. In this study, we have evaluated the performance of mNGS-specific indicators that can identify pathogens in patients with IFIs more accurately and rapidly than CMTs, which will have important clinical implications.
| S-EPMC9551268 | biostudies-literature
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:The contribution of the lung microbiota to pneumonia in children of varying severity remains poorly understood. This study utilized metagenomic next-generation sequencing (mNGS) technology to elucidate the characteristics of lung microbiota and their association with disease severity. This retrospective study analyzed bronchoalveolar lavage fluid (BALF) mNGS data of 92 children diagnosed with pneumonia between January 2021 and July 2022. A comparative analysis of the lung microbiota was conducted between the severe pneumonia (SP) (n = 44) and non-severe pneumonia (NSP) (n = 48) groups. Compared to conventional microbiological tests (CMT), mNGS had a higher positivity rate in etiology detection (68% vs 100%). In the NSP group, the predominant type of infection was Mycoplasma pneumoniae single infection, whereas in the SP group, the main type involved a combination of M pneumoniae and bacterial infection. The top 3 identified microbial taxa in both the groups were M pneumoniae, Rothia mucilaginosa, and Schaalia odontolyticus. Although there were no significant differences in the α and β diversity of the lung microbiota between the SP and NSP groups, the abundance of M pneumoniae was higher in the SP group (P = .053). Spearman analysis indicated a highly significant positive correlation between the abundance of Prevotella melaninogenica and M pneumoniae (P < .001). Our analysis identified an association between M pneumoniae infections and disease severity. This study provides a foundation for a better understanding of the pathogenesis of pediatric pneumonia and the relationship between microorganisms.
| S-EPMC11666182 | biostudies-literature
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