Direct Diagnosis of Echovirus 12 Meningitis Using Metagenomic Next Generation Sequencing.
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ABSTRACT:
SUBMITTER: Morsli M
PROVIDER: S-EPMC8156364 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Current routine real-time PCR methods used for the point-of-care diagnosis of infectious meningitis do not allow for one-shot genotyping of the pathogen, as in the case of deadly Haemophilus influenzae meningitis. Real-time PCR diagnosed H. influenzae meningitis in a 22-year-old male patient, during his hospitalisation following a more than six-metre fall. Using an Oxford Nanopore Technologies real-time sequencing run in parallel to real-time PCR, we detected the H. influenzae genome directly from the cerebrospinal fluid sample in six hours. Furthermore, BLAST analysis of the sequence encoding for a partial DUF417 domain-containing protein diagnosed a non-b serotype, non-typeable H.influenzae belonging to lineage H. influenzae 22.1-21. The Oxford Nanopore metagenomic next-generation sequencing approach could be considered for the point-of-care diagnosis of infectious meningitis, by direct identification of pathogenic genomes and their genotypes/serotypes.
| S-EPMC8069228 | biostudies-literature
Project description:Abstract Background Metagenomic next-generation sequencing (mNGS) of CSF can identify nearly all pathogens in a single test. We previously validated a CSF mNGS assay in a licensed clinical laboratory. To date, the utility of mNGS for infectious disease diagnosis has been described in case reports and small case series, but not in a large-scale clinical trial. Methods The PDAID (“Precision Diagnosis of Acute Infectious Diseases”) study was a 1-year nationwide prospective study across 8 tertiary care hospitals to evaluate the performance and utility of a clinical metagenomic sequencing assay for diagnosis of meningitis, encephalitis, or myelitis from cerebrospinal fluid (CSF) (ClinicalTrials.gov number NCT02910037). We recruited acutely ill hospitalized inpatients lacking a diagnosis at the time of enrollment. CSF samples were processed and analyzed by mNGS testing within 1 week of receipt in the clinical microbiology laboratory, with sequencing results reported in the patient medical record and used to make contemporaneous treatment decisions. Weekly clinical microbial sequencing boards were convened to discuss mNGS results with treating physicians, and clinical impact evaluated by surveys, chart review, and direct clinician feedback. Results A total of 204 patients were enrolled. Patients were severely ill (ICU 48%, average length of stay 26 days, overall 30-day mortality 7.4%). Fifty-nine neurologic infections were diagnosed in 57 patients (27.9%). mNGS identified 15 (25.4%) infections that were missed by all conventional microbiological tests, including emerging and/or uncommon pathogens such as St. Louis encephalitis virus, hepatitis E virus acquired by lung transplant, and Nocardia farcinica. Twelve of the 15 mNGS-only diagnoses (80%) had clinical impact, with 9 of 15 (60%) guiding appropriate treatment. For diagnosis of infections by direct detection CSF testing, mNGS had 79.1% sensitivity and 98.8% specificity, versus 65.1% sensitivity and 99.4% specificity by conventional testing. Conclusion A significant proportion of neurologic infections are missed despite extensive diagnostic testing performed in tertiary care hospitals. Clinical metagenomic CSF testing was found to be useful in increasing the number of diagnosed neurologic infections and providing actionable information for physicians. Disclosures All authors: No reported disclosures.
| S-EPMC6252609 | biostudies-literature
Project description:Importance:Identifying infectious causes of subacute or chronic meningitis can be challenging. Enhanced, unbiased diagnostic approaches are needed. Objective:To present a case series of patients with diagnostically challenging subacute or chronic meningitis using metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) supported by a statistical framework generated from mNGS of control samples from the environment and from patients who were noninfectious. Design, Setting, and Participants:In this case series, mNGS data obtained from the CSF of 94 patients with noninfectious neuroinflammatory disorders and from 24 water and reagent control samples were used to develop and implement a weighted scoring metric based on z scores at the species and genus levels for both nucleotide and protein alignments to prioritize and rank the mNGS results. Total RNA was extracted for mNGS from the CSF of 7 participants with subacute or chronic meningitis who were recruited between September 2013 and March 2017 as part of a multicenter study of mNGS pathogen discovery among patients with suspected neuroinflammatory conditions. The neurologic infections identified by mNGS in these 7 participants represented a diverse array of pathogens. The patients were referred from the University of California, San Francisco Medical Center (n = 2), Zuckerberg San Francisco General Hospital and Trauma Center (n = 2), Cleveland Clinic (n = 1), University of Washington (n = 1), and Kaiser Permanente (n = 1). A weighted z score was used to filter out environmental contaminants and facilitate efficient data triage and analysis. Main Outcomes and Measures:Pathogens identified by mNGS and the ability of a statistical model to prioritize, rank, and simplify mNGS results. Results:The 7 participants ranged in age from 10 to 55 years, and 3 (43%) were female. A parasitic worm (Taenia solium, in 2 participants), a virus (HIV-1), and 4 fungi (Cryptococcus neoformans, Aspergillus oryzae, Histoplasma capsulatum, and Candida dubliniensis) were identified among the 7 participants by using mNGS. Evaluating mNGS data with a weighted z score-based scoring algorithm reduced the reported microbial taxa by a mean of 87% (range, 41%-99%) when taxa with a combined score of 0 or less were removed, effectively separating bona fide pathogen sequences from spurious environmental sequences so that, in each case, the causative pathogen was found within the top 2 scoring microbes identified using the algorithm. Conclusions and Relevance:Diverse microbial pathogens were identified by mNGS in the CSF of patients with diagnostically challenging subacute or chronic meningitis, including a case of subarachnoid neurocysticercosis that defied diagnosis for 1 year, the first reported case of CNS vasculitis caused by Aspergillus oryzae, and the fourth reported case of C dubliniensis meningitis. Prioritizing metagenomic data with a scoring algorithm greatly clarified data interpretation and highlighted the problem of attributing biological significance to organisms present in control samples used for metagenomic sequencing studies.
| S-EPMC5933460 | biostudies-literature
Project description:BackgroundMycoplasma hominis meningitis is a rare postoperative complication of neurosurgery. Accurate and early diagnosis of M. hominis remains challenging because of the limitations of traditional detection methods. Metagenomic next-generation sequencing (mNGS) is an advanced technique with high sensitivity and specificity for identifying infectious pathogens; however, its application in diagnosing M. hominis meningitis has not been widely studied.Case presentationWe report the case of a 61-year-old man who presented with fever and headache after neurosurgical treatment for a cerebral hemorrhage. Empiric antibiotic therapy was ineffective. Traditional culture of pathogens and serological testing yielded negative results, but M. hominis was detected in the cerebrospinal fluid by mNGS. After further verification by polymerase chain reaction (PCR), the patient's clinical treatment was adjusted accordingly. With targeted antibiotic intervention, the patient's symptoms were effectively alleviated, and clinical indicators returned to normal levels. Furthermore, the abundance of M. hominis decreased significantly compared to the initial mNGS reading after targeted treatment, indicating that the infection caused by M. hominis was effectively controlled.ConclusionUsing mNGS, we found that M. hominis may be a candidate causative agent of meningitis. The technique also has the advantage of timeliness and accuracy that traditional cultures cannot achieve. A combination of mNGS with PCR is recommended to identify pathogens in the early stages of infectious diseases to administer targeted clinical medication.
| S-EPMC9380824 | biostudies-literature
Project description:BackgroundTuberculous meningitis (TBM) is a severe form of extrapulmonary tuberculosis and its early diagnosis is very difficult leading to present with severe disability or die. The current study aimed to assess the accuracy of metagenomic next generation sequencing (mNGS) for TBM, and to identify a new test for the early diagnosis of TBM.MethodsWe searched for articles published in Embase, PubMed, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Data up to June 30, 2020 for studies that assessed the efficacy of mNGS for the diagnosis of TBM. Then, the accuracy between mNGS and a composite reference standard (CRS) in these articles was compared using the meta-analysis approach.ResultsFour independent studies with 342 samples comparing mNGS and a CRS were included in this study. The sensitivity of mNGS for TBM diagnosis ranged from 27% to 84%. The combined sensitivity of mNGS was 61%, and the I2 value was 92%. Moreover, the specificity of mNGS for TBM diagnosis ranged from 96% to 100%. The combined specificity of mNGS was 98%, and the I2 value was 74%. The heterogeneity between studies in terms of sensitivity and specificity was significant. The area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) of mNGS for TBM was 0.98.ConclusionsThe sensitivity of mNGS for TBM diagnosis was moderate. Furthermore, the specificity was extremely high, and the AUC of the SROC indicated a very good diagnostic efficacy. mNGS could be used as an early diagnostic method for TBM, however, the results should be treated with caution for the heterogeneity between studies was extremely significant.Systematic review registrationINPLASY202070100.
| S-EPMC7707562 | biostudies-literature
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:Purpose: We assessed the performance of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis and meningitis. Methods: This was a prospective multicenter study. Cerebrospinal fluid samples from patients with viral encephalitis and/or meningitis, tuberculous meningitis, bacterial meningitis, fungal meningitis, and non-central nervous system (CNS) infections were subjected to mNGS. Results: In total, 213 patients with infectious and non-infectious CNS diseases were finally enrolled from November 2016 to May 2019; the mNGS-positive detection rate of definite CNS infections was 57.0%. At a species-specific read number (SSRN) ≥2, mNGS performance in the diagnosis of definite viral encephalitis and/or meningitis was optimal (area under the curve [AUC] = 0.659, 95% confidence interval [CI] = 0.566-0.751); the positivity rate was 42.6%. At a genus-specific read number ≥1, mNGS performance in the diagnosis of tuberculous meningitis (definite or probable) was optimal (AUC=0.619, 95% CI=0.516-0.721); the positivity rate was 27.3%. At SSRNs ≥5 or 10, the diagnostic performance was optimal for definite bacterial meningitis (AUC=0.846, 95% CI = 0.711-0.981); the sensitivity was 73.3%. The sensitivities of mNGS (at SSRN ≥2) in the diagnosis of cryptococcal meningitis and cerebral aspergillosis were 76.92 and 80%, respectively. Conclusion: mNGS of cerebrospinal fluid effectively identifies pathogens causing infectious CNS diseases. mNGS should be used in conjunction with conventional microbiological testing. Trial Registration: Chinese Clinical Trial Registry, ChiCTR1800020442.
| S-EPMC7066979 | biostudies-literature
Project description:Cat-scratch disease (CSD) is an anthropozoonotic infection caused by Bartonella henselae, and it is one of the most common causes of lymph node infections in children and adolescents. B. henselae, belonging to the genus Bartonella, is a common human pathogen of human beings. CSD commonly develops as a result of cat scratches and bites or when injured skin comes into contact with cat saliva. The manifestation of CSD clinically differs for each patient based on their immune system. Individuals who have healthy immune systems generally manifest minimal clinical symptoms and do not necessitate any form of treatment. However, patients who have hypo-immunity require prompt medical attention due to the potential manifestation of severe symptoms that affect multiple systems of the body. Long latency and atypical clinical manifestations are characteristics of CSD. Bartonella isolation and identification are challenging procedures that require specialized equipment. There is no gold standard method for CSD diagnosis, and misdiagnosis and missed diagnosis rates are typically high. We present the case of a middle-aged male patient who developed fever, chills, anal distension, dizziness, and muscle pain for 10 days. The patient had a documented history of cat bites 1 month prior to the onset of symptoms. Following admission, he underwent an examination to determine superficial lymphadenopathy and hypoimmunity. Additionally, he had a fever during the disease. As the patient refused a needle biopsy of lymph nodes, metagenomic next-generation sequencing (mNGS) was employed and B. henselae was detected in the peripheral blood. The patient was diagnosed with CSD and treated with a combination of azithromycin and doxycycline. The fever symptoms were alleviated, and the patient was ultimately discharged. As a result of this case, we suggest that mNGS be used as a crucial supplementary diagnostic tool for individuals with compromised immune systems who may have CSD, especially when conventional diagnostic methods are inconclusive.
| S-EPMC10822884 | biostudies-literature
Project description:Introduction: Scrub typhus is a mite-borne infection widespread in Southeast Asia, with clinical symptoms such as fever, chills, skin rash, eschar at the bite site, and other signs of acute febrile illness. The Rickettsia pathogen (Orientia tsutsugamushi) is always difficult to be diagnosed at an early stage by traditional clinical diagnostic methods, especially for patients without typical eschar. This greatly increases the mortality of patients with scrub typhus. A new approach should be introduced to improve its clinical diagnosis. Methods: During May 2018 to March 2021, 13 samples from 10 patients with suspected scrub typhus were collected. Metagenomic next-generation sequencing (mNGS) and other diagnostic methods (including serology using Weil-Felix reaction and indirect immunofluorescence test (IIFT) for scrub typhus and respiratory tract profile IgM as well as culture for routine bacteria) were used to identify the pathogens in this study. Results: The results of mNGS were all positive, with mapped reads of O. tsutsugamushi ranging from 1 to 460. Eight patients (80%) were diagnosed as scrub typhus. The other two were diagnosed as suspected scrub typhus due to the limited number of reads of the pathogen (one and two, respectively). According to clinical evidences, nine of the 10 patients were finally diagnosed as scrub typhus, except for patient 9 (suspected scrub typhus by mNGS with one specific reads of the pathogen) diagnosed as acute exacerbation of chronic obstructive pulmonary disease. For the five scrub typhus patients without typical eschar, mNGS gave all positive results (4-460 specific reads). For other methods, only Weil-Felix reaction of one patient detected the pathogen. In addition, the respiratory tract profile (IgM) detected various pathogens, but all were confirmed to be false positive. Conclusions: mNGS performed better than conventional clinical methods to early diagnose scrub typhus. This approach can be routinely carried out for early and precise diagnosis in clinical infections, especially for those hard to be identified by traditional diagnostic methods.
| S-EPMC8632043 | biostudies-literature
Project description:Bartonella henselae, the pathogen that causes cat-scratch disease (CSD), is relatively rare in the clinic. CSD usually causes mild clinical manifestations, which self-heal in a matter of weeks. However, in immunocompromised patients, CSD may cause systemic disorders that can lead to critical illness. Due to the diversity of symptom signs and the lack of a golden standard for diagnosis, identifying atypical CSD in a timely manner presents a challenge. Metagenomic next-generation sequencing (mNGS), is a promising technology that has been widely used in the detection of pathogens in clinical infectious diseases in recent years. mNGS can detect multiple pathogens quickly and accurately from any given source. Here, we present a case of atypical CSD, which was diagnosed using mNGS. The patient manifested a fever of unknown infectious origin, and routine antibiotic treatment was ineffective. mNGS was employed to test the patient's peripheral blood, which led to the detection of B. henselae. This was rarely seen in previous CSD reports. We surmised that the patient presented with atypical CSD and thus a targeted therapy was recommended. Crucially, the patient recovered rapidly. Based on this case study findings, we recommend that CSD should be included in the differential diagnosis for fever of unknown origin and that mNGS may be helpful in the diagnosis of CSD.
| S-EPMC9524480 | biostudies-literature