Dataset Information

Multicenter Evaluation of the Unyvero Platform for Testing Bronchoalveolar Lavage Fluid.

ABSTRACT: Bronchoalveolar lavage (BAL) culture is a standard, though time-consuming, approach for identifying microorganisms in patients with severe lower respiratory tract (LRT) infections. The sensitivity of BAL culture is relatively low, and prior antimicrobial therapy decreases the sensitivity further, leading to overuse of empirical antibiotics. The Unyvero LRT BAL Application (Curetis GmbH, Germany) is a multiplex molecular panel that detects 19 bacteria, 10 antibiotic resistance markers, and a fungus, Pneumocystis jirovecii, in BAL fluid in ∼4.5 h. Its performance was evaluated using 1,016 prospectively collected and 392 archived specimens from 11 clinical trial sites in the United States. Overall positive and negative percent agreements with culture results for identification of bacteria that grow in routine cultures were 93.4% and 98.3%, respectively, with additional potential pathogens identified by Unyvero in 21.7% of prospectively collected specimens. For detection of P. jirovecii, the positive percent agreement with standard testing was 87.5%. Antibiotic resistance marker results were compared to standard antibiotic susceptibility test results to determine positive predictive values (PPVs). PPVs ranged from 80 to 100%, based on the microorganism and specific resistance marker(s). The Unyvero LRT BAL Application provides accurate detection of common agents of bacterial pneumonia and of P. jirovecii The sensitivity and rapidity of this panel suggest significant clinical value for choosing appropriate antibiotics and for antibiotic stewardship.

SUBMITTER: Klein M

PROVIDER: S-EPMC8106704 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Multicenter Evaluation of the Unyvero Platform for Testing Bronchoalveolar Lavage Fluid.

Klein Matthias M Bacher Johannes J Barth Sandra S Atrzadeh Faranak F Siebenhaller Katja K Ferreira Inês I Beisken Stephan S Posch Andreas E AE Carroll Karen C KC Wunderink Richard G RG Qi Chao C Wu Fann F Hardy Dwight J DJ Patel Robin R Sims Matthew D MD

Journal of clinical microbiology 20210218 3

Bronchoalveolar lavage (BAL) culture is a standard, though time-consuming, approach for identifying microorganisms in patients with severe lower respiratory tract (LRT) infections. The sensitivity of BAL culture is relatively low, and prior antimicrobial therapy decreases the sensitivity further, leading to overuse of empirical antibiotics. The Unyvero LRT BAL Application (Curetis GmbH, Germany) is a multiplex molecular panel that detects 19 bacteria, 10 antibiotic resistance markers, and a fung ...[more]

PMID: 33328178

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Project description:BackgroundIt is now possible to comprehensively characterize the microbiota of the lungs using culture-independent, sequencing-based assays. Several sample types have been used to investigate the lung microbiota, each presenting specific challenges for preparation and analysis of microbial communities. Bronchoalveolar lavage fluid (BALF) enables the identification of microbiota specific to the lower lung but commonly has low bacterial density, increasing the risk of false-positive signal from contaminating DNA. The objectives of this study were to investigate the extent of contamination across a range of sample densities representative of BALF and identify features of contaminants that facilitate their removal from sequence data and aid in the interpretation of BALF sample 16S sequencing data.ResultsUsing three mock communities across a range of densities ranging from 8E+ 02 to 8E+ 09 16S copies/ml, we assessed taxonomic accuracy and precision by 16S rRNA gene sequencing and the proportion of reads arising from contaminants. Sequencing accuracy, precision, and the relative abundance of mock community members decreased with sample input density, with a significant drop-off below 8E+ 05 16S copies/ml. Contaminant OTUs were commonly inversely correlated with sample input density or not reproduced between technical replicates. Removal of taxa with these features or physical concentration of samples prior to sequencing improved both sequencing accuracy and precision for samples between 8E+ 04 and 8E+ 06 16S copies/ml. For the lowest densities, below 8E+ 03 16S copies/ml BALF, accuracy and precision could not be significantly improved using these approaches. Using clinical BALF samples across a large density range, we observed that OTUs with features of contaminants identified in mock communities were also evident in low-density BALF samples.ConclusionRelative abundance data and community composition generated by 16S sequencing of BALF samples across the range of density commonly observed in this sample type should be interpreted in the context of input sample density and may be improved by simple pre- and post-sequencing steps for densities above 8E+ 04 16S copies/ml.

Project description:Genomic profiling of bronchoalveolar lavage (BAL) samples may be useful for tumor profiling and diagnosis in the clinic. Here, we compared tumor-derived mutations detected in BAL samples from subjects with non-small cell lung cancer (NSCLC) to those detected in matched plasma samples. Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) was used to genotype DNA purified from BAL, plasma, and tumor samples from patients with NSCLC. The characteristics of cell-free DNA (cfDNA) isolated from BAL fluid were first characterized to optimize the technical approach. Somatic mutations identified in tumor were then compared with those identified in BAL and plasma, and the potential of BAL cfDNA analysis to distinguish lung cancer patients from risk-matched controls was explored. In total, 200 biofluid and tumor samples from 38 cases and 21 controls undergoing BAL for lung cancer evaluation were profiled. More tumor variants were identified in BAL cfDNA than plasma cfDNA in all stages (P < 0.001) and in stage I to II disease only. Four of 21 controls harbored low levels of cancer-associated driver mutations in BAL cfDNA [mean variant allele frequency (VAF) = 0.5%], suggesting the presence of somatic mutations in nonmalignant airway cells. Finally, using a Random Forest model with leave-one-out cross-validation, an exploratory BAL genomic classifier identified lung cancer with 69% sensitivity and 100% specificity in this cohort and detected more cancers than BAL cytology. Detecting tumor-derived mutations by targeted sequencing of BAL cfDNA is technically feasible and appears to be more sensitive than plasma profiling. Further studies are required to define optimal diagnostic applications and clinical utility.SignificanceHybrid-capture, targeted deep sequencing of lung cancer mutational burden in cell-free BAL fluid identifies more tumor-derived mutations with increased allele frequencies compared with plasma cell-free DNA. See related commentary by Rolfo et al., p. 2826.

Project description:Metagenomic next-generation sequencing (mNGS) has been gradually applied to clinical practice due to its unbiased characteristics of pathogen detection. However, its diagnostic performance and clinical value in suspected pulmonary infection need to be evaluated. We systematically reviewed the clinical data of 246 patients with suspected pulmonary infection from 4 medical institutions between January 2019 and September 2021. The diagnostic performances of mNGS and conventional testing (CT) were systematically analyzed based on bronchoalveolar lavage fluid (BALF). The impacts of mNGS and CT on diagnosis modification and treatment adjustment were also assessed. The positive rates of mNGS and CT were 47.97% and 23.17%, respectively. The sensitivity of mNGS was significantly higher than that of CT (53.49% versus 23.26%, P < 0.01), especially for infections of Mycobacterium tuberculosis (67.86% versus 17.86%, P < 0.01), atypical pathogens (100.00% versus 7.14%, P < 0.01), viruses (92.31% versus 7.69%, P < 0.01), and fungi (78.57% versus 39.29%, P < 0.01). The specificity of mNGS was superior to that of CT, with no statistical difference (90.32% versus 77.42%, P = 0.167). The positive predictive value (PPV) and negative predictive value (NPV) of mNGS were 97.46% and 21.88%, respectively. Diagnosis modification and treatment adjustment were conducted in 32 (32/246, 13.01%) and 23 (23/246, 9.35%) cases, respectively, according to mNGS results only. mNGS significantly improved the diagnosis of suspected pulmonary infection, especially infections of M. tuberculosis, atypical pathogens, viruses, and fungi, and it demonstrated the pathogen distribution of pulmonary infections. It is expected to be a promising microbiological detection and diagnostic method in clinical practice. IMPORTANCE Pulmonary infection is a heterogeneous and complex infectious disease with high morbidity and mortality worldwide. In clinical practice, a considerable proportion of the etiology of pulmonary infection is unclear, microbiological diagnosis being challenging. Metagenomic next-generation sequencing detects all nucleic acids in a sample in an unbiased manner, revealing the microbial community environment and organisms and improving the microbiological detection and diagnosis of infectious diseases in clinical settings. This study is the first multicenter, large-scale retrospective study based entirely on BALF for pathogen detection by mNGS, and it demonstrated the superior performance of mNGS for microbiological detection and diagnosis of suspected pulmonary infection, especially in infections of Mycobacterium tuberculosis, atypical pathogens, viruses, and fungi. It also demonstrated the pathogen distribution of pulmonary infections in the real world, guiding targeted treatment and improving clinical management and prognoses.

Dataset Information

Multicenter Evaluation of the Unyvero Platform for Testing Bronchoalveolar Lavage Fluid.

Publications

Multicenter Evaluation of the Unyvero Platform for Testing Bronchoalveolar Lavage Fluid.

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