Prospective Evaluation of a Rapid Clinical Metagenomics Test for Bacterial Pneumonia.

Background: The diagnosis of bacterial pathogens in lower respiratory tract infections (LRI) using conventional culture methods remains challenging and time-consuming. Objectives: To evaluate the clinical performance of a rapid nanopore-sequencing based metagenomics test for diagnosis of bacterial pathogens in common LRIs through a large-scale prospective study. Methods: We enrolled 292 hospitalized patients suspected to have LRIs between November 2018 and June 2019 in a single-center, prospective cohort study. Rapid clinical metagenomics test was performed on-site, and the results were compared with those of routine microbiology tests. Results: 171 bronchoalveolar lavage fluid (BAL) and 121 sputum samples were collected from patients with six kinds of LRIs. The turnaround time (from sample registration to result) for the rapid metagenomics test was 6.4 ± 1.4 hours, compared to 94.8 ± 34.9 hours for routine culture. Compared with culture and real-time PCR validation tests, rapid metagenomics achieved 96.6% sensitivity and 88.0% specificity and identified pathogens in 63 out of 161 (39.1%) culture-negative samples. Correlation between enriched anaerobes and lung abscess was observed by Gene Set Enrichment Analysis. Moreover, 38 anaerobic species failed in culture was identified by metagenomics sequencing. The hypothetical impact of metagenomics test proposed antibiotic de-escalation in 34 patients compared to 1 using routine culture. Conclusions: Rapid clinical metagenomics test improved pathogen detection yield in the diagnosis of LRI. Empirical antimicrobial therapy could be de-escalated if rapid metagenomics test results were hypothetically applied to clinical management.

Preliminary assessment of nanopore-based metagenomic sequencing for the diagnosis of prosthetic joint infection.

OBJECTIVES: Pathogen identification is crucial for the diagnosis and management of periprosthetic joint infection (PJI). Although culturing methods are the foundation of pathogen detection in PJI, false-negative results often occur. Oxford nanopore sequencing (ONS) is a promising alternative for detecting pathogens and providing information on their antimicrobial resistance (AMR) profiles, without culturing. METHODS: To evaluate the capability of metagenomic ONS (mONS) in detecting pathogens from PJI samples, both metagenomic next-generation sequencing (mNGS) and mONS were performed in 15 osteoarticular samples from nine consecutive PJI patients according to the modified Musculoskeletal Infection Society (MSIS) criteria. The sequencing data generated from both platforms were then analyzed for pathogen identification and AMR detection using an in-house-developed bioinformatics pipeline. RESULTS: Our results showed that mONS could be applied to detect the causative pathogen and characterize its AMR features in fresh PJI samples. By real-time sequencing and analysis, pathogen identification and AMR detection from the initiation of sequencing were accelerated. CONCLUSION: We showed proof of concept that mONS can function as a rapid, accurate tool in PJI diagnostic microbiology. Despite efforts to reduce host DNA, the high proportion of host DNA was still a limitation of this method that prevented full genome analysis.

Detection of pathogens from resected heart valves of patients with infective endocarditis by next-generation sequencing.

OBJECTIVES: Identification of the underlying pathogens of infective endocarditis (IE) is critical for precision therapy. METHODS: We evaluated a metagenomic method with next-generation sequencing (NGS) for the direct detection of pathogens from the resected valves of 44 IE patients and seven rejected IE patients according to the modified Duke criteria. RESULTS: NGS displayed sensitivity, specificity, positive predictive values and negative predictive values of 97.6%, 85.7%, 97.6%, and 85.7% compared with 46.2%, 100%, 100%, and 12.5% for blood culture and 17.1%, 100%, 100%, and 17.1% for valve culture and 51.4%, 100%, 100%, and 26.1% for valve Gram staining, respectively. CONCLUSIONS: NGS technique had superior sensitivity and shorter turnaround time compared with culture-based methods for identifying causative pathogens of IE. The NGS technology should be considered an essential supplement to culture-based methods, particularly for unculturable or difficult-to-culture microorganisms.

Association of Breast and Ovarian Cancers With Predisposition Genes Identified by Large-Scale Sequencing.

Importance: Since the discovery of BRCA1 and BRCA2, multiple high- and moderate-penetrance genes have been reported as risk factors for hereditary breast cancer, ovarian cancer, or both; however, it is unclear whether these findings represent the complete genetic landscape of these cancers. Systematic investigation of the genetic contributions to breast and ovarian cancers is needed to confirm these findings and explore potentially new associations. Objective: To confirm reported and identify additional predisposition genes for breast or ovarian cancer. Design, Setting, and Participants: In this sample of 11 416 patients with clinical features of breast cancer, ovarian cancer, or both who were referred for genetic testing from 1200 hospitals and clinics across the United States and of 3988 controls who were referred for genetic testing for noncancer conditions between 2014 and 2015, whole-exome sequencing was conducted and gene-phenotype associations were examined. Case-control analyses using the Genome Aggregation Database as a set of reference controls were also conducted. Main Outcomes and Measures: Breast cancer risk associated with pathogenic variants among 625 cancer predisposition genes; association of identified predisposition breast or ovarian cancer genes with the breast cancer subtypes invasive ductal, invasive lobular, hormone receptor-positive, hormone receptor-negative, and male, and with early-onset disease. Results: Of 9639 patients with breast cancer, 3960 (41.1%) were early-onset cases (≤45 years at diagnosis) and 123 (1.3%) were male, with men having an older age at diagnosis than women (mean [SD] age, 61.8 [12.8] vs 48.6 [11.4] years). Of 2051 women with ovarian cancer, 445 (21.7%) received a diagnosis at 45 years or younger. Enrichment of pathogenic variants were identified in 4 non-BRCA genes associated with breast cancer risk: ATM (odds ratio [OR], 2.97; 95% CI, 1.67-5.68), CHEK2 (OR, 2.19; 95% CI, 1.40-3.56), PALB2 (OR, 5.53; 95% CI, 2.24-17.65), and MSH6 (OR, 2.59; 95% CI, 1.35-5.44). Increased risk for ovarian cancer was associated with 4 genes: MSH6 (OR, 4.16; 95% CI, 1.95-9.47), RAD51C (OR, not estimable; false-discovery rate-corrected P = .004), TP53 (OR, 18.50; 95% CI, 2.56-808.10), and ATM (OR, 2.85; 95% CI, 1.30-6.32). Neither the MRN complex genes nor CDKN2A was associated with increased breast or ovarian cancer risk. The findings also do not support previously reported breast cancer associations with the ovarian cancer susceptibility genes BRIP1, RAD51C, and RAD51D, or mismatch repair genes MSH2 and PMS2. Conclusions and Relevance: The results of this large-scale exome sequencing of patients and controls shed light on both well-established and controversial non-BRCA predisposition gene associations with breast or ovarian cancer reported to date and may implicate additional breast or ovarian cancer susceptibility gene candidates involved in DNA repair and genomic maintenance.

Identification of pathogens in culture-negative infective endocarditis cases by metagenomic analysis.

BACKGROUND: Pathogens identification is critical for the proper diagnosis and precise treatment of infective endocarditis (IE). Although blood and valve cultures are the gold standard for IE pathogens detection, many cases are culture-negative, especially in patients who had received long-term antibiotic treatment, and precise diagnosis has therefore become a major challenge in the clinic. Metagenomic sequencing can provide both information on the pathogenic strain and the antibiotic susceptibility profile of patient samples without culturing, offering a powerful method to deal with culture-negative cases. METHODS: To assess the feasibility of a metagenomic approach to detect the causative pathogens in resected valves from IE patients, we employed both next-generation sequencing and Oxford Nanopore Technologies MinION nanopore sequencing for pathogens and antimicrobial resistance detection in seven culture-negative IE patients. Using our in-house developed bioinformatics pipeline, we analyzed the sequencing results generated from both platforms for the direct identification of pathogens from the resected valves of seven clinically culture-negative IE patients according to the modified Duke criteria. RESULTS: Our results showed both metagenomics methods can be applied for the causative pathogen detection in all IE samples. Moreover, we were able to simultaneously characterize respective antimicrobial resistance features. CONCLUSION: Metagenomic methods for IE detection can provide clinicians with valuable information to diagnose and treat IE patients after valve replacement surgery. However, more efforts should be made to optimize protocols for sample processing, sequencing and bioinformatics analysis.

Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions.

PURPOSE: Diagnostic exome sequencing was immediately successful in diagnosing patients in whom traditional technologies were uninformative. Herein, we provide the results from the first 500 probands referred to a clinical laboratory for diagnostic exome sequencing. METHODS: Family-based exome sequencing included whole-exome sequencing followed by family inheritance-based model filtering, comprehensive medical review, familial cosegregation analysis, and analysis of novel genes. RESULTS: A positive or likely positive result in a characterized gene was identified in 30% of patients (152/500). A novel gene finding was identified in 7.5% of patients (31/416). The highest diagnostic rates were observed among patients with ataxia, multiple congenital anomalies, and epilepsy (44, 36, and 35%, respectively). Twenty-three percent of positive findings were within genes characterized within the past 2 years. The diagnostic rate was significantly higher among families undergoing a trio (37%) as compared with a singleton (21%) whole-exome testing strategy. CONCLUSION: Overall, we present results from the largest clinical cohort of diagnostic exome sequencing cases to date. These data demonstrate the utility of family-based exome sequencing and analysis to obtain the highest reported detection rate in an unselected clinical cohort, illustrating the utility of diagnostic exome sequencing as a transformative technology for the molecular diagnosis of genetic disease.