Open Forum Infectious Diseases · 2023 · 23 citations · 22 references
Life SciencesInfectious DiseasesMicrobiologyDiagnostic MicrobiologyMedical MicrobiologyMetagenomicsMetagenomic AnalysisPulmonary InfectionsRespiratory InfectionsRespiratory Pathogen DiagnosticsRespiratory Tract InfectionsShotgun MetagenomicsBronchoalveolar Lavage AnalysisClinical Next-generation SequencingMetagenomic DiagnosisMetagenomic DiagnosticsNext-generation Sequencing AssaysNext-generation Sequencing DiagnosisPneumonia DiagnosisRespiratory Infection Diagnosis
Abstract Background Metagenomic next-generation sequencing (mNGS) provides innovative solutions for predicting complex infections. A comprehensive understanding of its strengths and limitations in real-world clinical settings is necessary to ensure that it is not overused or misinterpreted. Methods Two hundred nine cases with suspected pneumonia were recruited to compare the capabilities of 2 available mNGS assays (bronchoalveolar lavage fluid [BALF] mNGS and plasma mNGS) to identify pneumonia-associated DNA/RNA pathogens and predict antibiotic resistance. Results Compared to clinical diagnosis, BALF mNGS demonstrated a high positive percent agreement (95.3%) but a low negative percent agreement (63.1%). Plasma mNGS revealed a low proportion of true negatives (30%) in predicting pulmonary infection. BALF mNGS independently diagnosed 65.6% (61/93) of coinfections and had a remarkable advantage in detecting caustic, rare, or atypical pathogens. Pathogens susceptible to invasive infection or bloodstream transmission, such as Aspergillus spp, Rhizopus spp, Chlamydia psittaci, and human herpesviruses, are prone to be detected by plasma mNGS. BALF mNGS tests provided a positive impact on the diagnosis and treatment of 128 (61.2%) patients. Plasma mNGS, on the other hand, turned out to be more suitable for diagnosing patients who received mechanical ventilation, developed severe pneumonia, or developed sepsis (all P < .01). BALF mNGS was able to identify resistance genes that matched the phenotypic resistance of 69.4% (25/36) of multidrug-resistant pathogens. Conclusions Our data reveal new insights into the advantages and disadvantages of 2 different sequencing modalities in pathogen identification and antibiotic resistance prediction for patients with suspected pneumonia.
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Catherine A. Hogan, Shangxin Yang, Omai B. Garner et al. · Clinical Infectious Diseases · 2020 · 332 citations
Erin H. Graf, Keith E. Simmon, Keith D. Tardif et al. · Journal of Clinical Microbiology · 2016 · 214 citations · Full text