Evaluation of metagenomic and pathogen-targeted next-generation sequencing for diagnosis of meningitis and encephalitis in adults: A multicenter prospective observational cohort study in China

The use of metagenomics to enhance diagnosis of encephalitis

INTRODUCTION

Encephalitis has a broad etiology, including infectious and auto-immune causes. In infectious encephalitis, the breadth of causative organisms results in incomplete testing and low diagnostic yields.Metagenomics sequences all DNA and RNA allowing untargeted detection of all organisms in a single specimen; this is of particular use in diagnosis of encephalitis with a broad etiology.

AREAS COVERED

We review the literature and discuss metagenomics workflows, host depletion and pathogen enrichment methods, bioinformatics analysis and potential analysis of the host transcriptome to aid diagnosis. We discuss the clinical use of metagenomics for diagnosis of neurological infection including time to result, cost, quality assurance, patient cohorts in whom metagenomics adds the most value, recommended specimen types, limitations and review published cases in which metagenomics has been used to diagnose encephalitis.

EXPERT OPINION

There is good evidence for the utility of metagenomics to diagnose infection in encephalitis. Due to infections with rare, unexpected or novel pathogens, metagenomics adds most value to diagnosis in immunocompromised patients and the greatest diagnostic yield is in brain biopsies. Technical advances are needed to reduce the complexity, cost and time to result which will enable wider adoption in clinical laboratories and use as a first-line test.

Metagenomic Next-generation Sequencing in Patients With Infectious Meningoencephalitis: A Comprehensive Systematic Literature Review and Meta-analysis

Background

We aimed to assess the accuracy, clinical efficacy, and limitations of metagenomic next-generation sequencing (mNGS) for diagnosing infectious meningoencephalitis.

Methods

We performed a systematic literature review and meta-analysis of studies that evaluated the performance of mNGS to determine the cause of infectious meningoencephalitis. We explored PubMed, Cumulative Index to Nursing and Allied Health, Embase, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, and Web of Science up to 12 November 2024. To perform a meta-analysis, we calculated the pooled diagnostic odds ratio (DOR) for mNGS and for conventional microbiological tests (CMTs) compared to the clinical diagnosis.

Results

Thirty-four studies met the inclusion criteria, with mNGS-positive rates ranging from 43.5% to 93.5% for infectious meningoencephalitis. The meta-analysis included 23 studies with 1660 patients. The pooled sensitivity was 0.70 (95% confidence interval [CI], .67-.72), and its specificity was 0.93 (95% CI, .92-.94). The DOR for mNGS was 26.7 (95% CI, 10.4-68.8), compared to 12.2 (95% CI, 3.2-47.0) for CMTs. For tuberculosis meningoencephalitis, mNGS demonstrated a pooled sensitivity of 0.67 (95% CI, .61-.72) and specificity of 0.97 (95% CI, .95-.99), with a DOR of 43.5 (95% CI, 7.4-256.6).

Conclusions

Our review indicates that mNGS can be a valuable diagnostic tool for infectious meningoencephalitis, offering high sensitivity and specificity. mNGS's superior DOR compared to that of CMTs highlights its potential for more accurate diagnoses and targeted interventions. Further research is needed to optimize which patients and at what point in the diagnostic process mNGS should be used.

Brain biopsy and metagenomic sequencing enhance aetiological diagnosis of encephalitis

Identifying the aetiology of CNS diseases, regardless of their infectious or non-infectious nature, is often intricate. Next-generation sequencing (NGS) has emerged as a powerful tool for sensitive and unbiased screening of tissue or body fluid specimens. This study aimed to investigate the underlying aetiology of patients with suspected infectious CNS diseases. Between April 2013 and October 2021, we collected brain tissue samples from 33 patients diagnosed with encephalitis or encephalitis-like CNS diseases, obtained via biopsy or autopsy, and underwent metagenomic NGS (mNGS) in conjunction with pathological evaluations. Moreover, we employed PCR-based assays and pathogen-specific immunostaining to corroborate the presence of pathogens within the tissue samples. Among the 33 patients, mNGS elucidated pathogen-specific genomic sequences in 7 cases (21.2%), including halobacteria (archaea), Balamuthia mandrillaris, Epstein-Barr virus, Toxoplasma gondii and herpes simplex virus. Additionally, brain tissue mNGS ruled out known pathogens, identifying 14 cases (42.4%) of non-infectious CNS diseases, which included neoplastic, autoimmune/inflammatory and amyloid angiopathy conditions. The adjustment of therapeutic strategies based on these findings led to improvements in clinical symptoms, imaging outcomes and patient prognosis. Brain biopsy serves as both a direct pathological research target and a valuable source of samples for unbiased high-throughput sequencing. Our study illustrates the reliability of mNGS on brain tissue, which significantly improves the diagnostic rate for suspected encephalitis or encephalitis-like diseases of unknown aetiology. These findings underscore the importance of mNGS in guiding more precise and effective therapeutic interventions for patients in clinical practice.

Pathogenic profiles and lower respiratory tract microbiota in severe pneumonia patients using metagenomic next-generation sequencing

INTRODUCTION

The homeostatic balance of the lung microbiota is important for the maintenance of normal physiological function of the lung, but its role in pathological processes such as severe pneumonia is poorly understood.

METHODS

We screened 34 patients with community-acquired pneumonia (CAP) and 12 patients with hospital-acquired pneumonia (HAP), all of whom were admitted to the respiratory intensive care unit. Clinical samples, including bronchoalveolar lavage fluid (BALF), sputum, peripheral blood, and tissue specimens, were collected along with traditional microbiological test results, routine clinical test data, and clinical treatment information. The pathogenic spectrum of lower respiratory tract pathogens in critically ill respiratory patients was characterized through metagenomic next-generation sequencing (mNGS). Additionally, we analyzed the composition of the commensal microbiota and its correlation with clinical characteristics.

RESULTS

The sensitivity of the mNGS test for pathogens was 92.2% and the specificity 71.4% compared with the clinical diagnosis of the patients. Using mNGS, we detected more fungi and viruses in the lower respiratory tract of CAP-onset severe pneumonia patients, whereas bacterial species were predominant in HAP-onset patients. On the other hand, using mNGS data, commensal microorganisms such as Fusobacterium yohimbe were observed in the lower respiratory tract of patients with HAP rather than those with CAP, and most of these commensal microorganisms were associated with hospitalization or the staying time in ICU, and were significantly and positively correlated with the total length of stay.

CONCLUSION

mNGS can be used to effectively identify pathogenic pathogens or lower respiratory microbiome associated with pulmonary infectious diseases, playing a crucial role in the early and accurate diagnosis of these conditions. Based on the findings of this study, it is possible that a novel set of biomarkers and predictive models could be developed in the future to efficiently identify the cause and prognosis of patients with severe pneumonia.

Diagnosing infectious encephalitis: a narrative review

BACKGROUND

Diagnosing infectious encephalitis can be challenging as it can be caused by a wide range of pathogens, with viruses being the most common cause. In a substantial number of patients, no pathogen is identified despite a clinical diagnosis of infectious encephalitis. Recent advancements in diagnostic testing have introduced new methods to address this diagnostic challenge and improve pathogen detection.

OBJECTIVES

The objective of this study is to provide a comprehensive clinical approach for diagnosing infectious encephalitis and explore novel diagnostic methods.

SOURCES

We searched PubMed to identify relevant literature on diagnosing encephalitis in English up to 1 September 2024, as well as included articles known by the authors.

CONTENT

Clinical characteristics may suggest a specific cause of infectious encephalitis, but are insufficient to guide treatment decisions. Therefore, cerebrospinal fluid (CSF) examination remains the cornerstone of the diagnostic process, with CSF leucocyte count being the most reliable predictor for central nervous system infections. CSF features can be normal, however, in a proportion of patients presenting with infectious encephalitis. A definite diagnosis of infectious encephalitis is established by microbiological or histopathological tests in ∼50% of patients. Additional investigations, including neuroimaging or electroencephalography, can provide evidence for encephalitis or help to identify alternate conditions, although their role is primarily supportive. Emerging diagnostic techniques, including next-generation sequencing metagenomics and unbiased serology (Phage ImmunoPrecipitation Sequencing), have the potential to increase the proportion of patients with a confirmed diagnosis. However, these techniques are not yet practical because of their complex analysis, long turnaround times and high costs.

IMPLICATIONS

Microbiological confirmation is paramount in the diagnosis of infectious encephalitis, but it is currently established in about half of cases. Although novel techniques show promise to increase the proportion of cause-specific diagnoses, they are not yet suitable for routine use. This highlights the ongoing need for advancements in diagnostic methods.

Targeted Next-Generation Sequencing in Pneumonia: Applications in the Detection of Responsible Pathogens, Antimicrobial Resistance, and Virulence

Background

Targeted next-generation sequencing (tNGS) is a high-throughput and cost-effective diagnostic alternative for pneumonia, with the ability to simultaneously detect pathogens, antimicrobial resistance genes, and virulence genes. We aimed to explore the applicability of tNGS in the co-detection of the responsible pathogens, antimicrobial resistance (AMR) genes, and virulence genes in patients with pneumonia.

Methods

A prospective study was conducted among patients with suspected pneumonia at Ruijin Hospital from March 1 to May 31, 2023. Bronchoalveolar lavage fluid (BALF) or sputum samples were collected and sent for tNGS, metagenomic next-generation sequencing (mNGS), and conventional microbiological tests (CMTs).

Results

In total, 67 BALF and 11 sputum samples from 78 patients were included in the analyses. According to the composite reference standards, the accuracy of tNGS in the detection of responsible pathogens was 0.852 (95% confidence interval 0.786-0.918), which resembled that of mNGS and remarkably exceeded that of CMTs. In addition, 81 AMR genes associated with responsible pathogens were reported, and 75.8% (25/33) priority drug-resistant pathogens could be directly identified. A total of 144 virulence genes were detected for four common pathogens. And patients with virulence genes detected were of higher proportions of severe pneumonia (95.0% vs 42.9%, P = 0.009), acute respiratory distress syndrome (55.0% vs 0%, P = 0.022), and neutrophils (82.3% vs 62.2%, P = 0.026) than those not.

Conclusion

In patients with pneumonia, tNGS could detect the responsible pathogens, AMR genes, and virulence genes simultaneously, serving as an efficient and cost-effective tool for the diagnosis, treatment, and severity indication of pneumonia.

Metagenomic next-generation sequencing of cerebrospinal fluid: a diagnostic approach for varicella zoster virus-related encephalitis

Purpose

Varicella zoster virus-related encephalitis (VZV-RE) is a rare and often misdiagnosed condition caused by an infection with the VZV. It leads to meningitis or encephalitis, with patients frequently experiencing poor prognosis. In this study, we used metagenomic next-generation sequencing (mNGS) to rapidly and accurately detect and identify the VZV pathogen directly from cerebrospinal fluid (CSF) samples, aiming to achieve a definitive diagnosis for encephalitis patients.

Methods

In this retrospective study, we analyzed the clinical characteristics and laboratory evaluations of 28 patients at the Harrison International Peace Hospital in Hebei, China, between 2018 and 2024. These patients were diagnosed with neurological disorders using mNGS techniques applied to CSF.

Results

In this cohort of 28 patients, 11 were females and 17 males, with a median age of 65 (IQR: 42.3-70). VZV-RE presented with a range of clinical manifestations, the most common being headaches (81.2%), fever>38°C (42.9%), and vomiting (42.9%). Less frequent symptoms include personality changes (10.7%), speech impairments (21.4%), cranial nerve involvement (21.4%), altered consciousness (17.9%) and convulsions (3.6%). Herpes zoster rash was observed in 35.7% of the cases. Neurological examination revealed nuchal rigidity in only 5 patients. CSF analysis indicated mild pressure and protein levels increase, with all patients having negative bacterial cultures. Abnormal electroencephalogram (EEG) findings were noted in 10.7% (N=3), and encephalorrhagia on Magnetic Resonance Imaging (MRI) was observed in 3.6%. VZV-RE was confirmed through mNGS analysis of CSF within three days of admission. All patients received empiric treatment with acyclovir or valacyclovir, with 21.4% receiving hormonotherapy, and 7.14% receiving immunoglobulin therapy. At the three-month follow-up, 10.7% of the patients had persistent neurologic sequelae, and the mortality rate was 3.6%.

Conclusions

Performing mNGS on CSF offers a rapidly and precisely diagnostic method for identifying causative pathogens in patients with VZV central nervous system (CNS) infections, especially when traditional CNS examination results are negative. Furthermore, the cases reported highlight the positive therapeutic effect of ganciclovir in treating VZV infections.

From Tradition to Innovation: Diverse Molecular Techniques in the Fight Against Infectious Diseases

Infectious diseases impose a significant burden on global health systems due to high morbidity and mortality rates. According to the World Health Organization, millions die from infectious diseases annually, often due to delays in accurate diagnosis. Traditional diagnostic methods in clinical microbiology, primarily culture-based techniques, are time-consuming and may fail with hard-to-culture pathogens. Molecular biology advancements, notably the polymerase chain reaction (PCR), have revolutionized infectious disease diagnostics by allowing rapid and sensitive detection of pathogens' genetic material. PCR has become the gold standard for many infections, particularly highlighted during the COVID-19 pandemic. Following PCR, next-generation sequencing (NGS) has emerged, enabling comprehensive genomic analysis of pathogens, thus facilitating the detection of new strains and antibiotic resistance tracking. Innovative approaches like CRISPR technology are also enhancing diagnostic precision by identifying specific DNA/RNA sequences. However, the implementation of these methods faces challenges, particularly in low- and middle-income countries due to infrastructural and financial constraints. This review will explore the role of molecular diagnostic methods in infectious disease diagnosis, comparing their advantages and limitations, with a focus on PCR and NGS technologies and their future potential.

Molecular diagnostics in cerebrospinal fluid for the diagnosis of central nervous system infections

SUMMARYCentral nervous system (CNS) infections can be caused by various pathogens, including bacteria, viruses, fungi, and parasites. Molecular diagnostic methods are pivotal for identifying the different causative pathogens of these infections in clinical settings. The efficacy and specificity of these methods can vary per pathogen involved, and in a substantial part of patients, no pathogen is identified in the cerebrospinal fluid (CSF). Over recent decades, various molecular methodologies have been developed and applied to patients with CNS infections. This review provides an overview of the accuracy of nucleic acid amplification methods in CSF for a diverse range of pathogens, examines the potential value of multiplex PCR panels, and explores the broad-range bacterial and fungal PCR/sequencing panels. In addition, it evaluates innovative molecular approaches to enhance the diagnosis of CNS infections.

An Investigation into Diagnostic Strategies for Central Nervous System Infections Through the Integration of Metagenomic Next-Generation Sequencing and Conventional Diagnostic Methods

Purpose

The optimal strategy for detecting central nervous system infections (CNSI) in cerebrospinal fluid (CSF) samples remains unclear.

Methods

In a one-year, multicenter retrospective study, we examined the efficacy of metagenomic next-generation sequencing (mNGS) in comparison to conventional pathogen diagnostic techniques for CSF in diagnosing CNSI. We calculated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Youden index for each diagnostic approach. Additionally, receiver operating characteristic (ROC) curves were constructed, and the area under the curve (AUC) was determined to assess the diagnostic performance of each method.

Results

The study included 68 patients, comprising both adults and children, who were suspected of having CNSI. Through the application of comprehensive clinical interpretation (CCI), the sensitivity and specificity of mNGS were found to be 67.6% (95% confidence interval [CI]: 50.85-80.87%) and 45.8% (95% CI: 27.89-64.92%), respectively. In comparison, traditional pathogenic diagnostic methods indicated that the culture method demonstrated a sensitivity of 10.6% (95% CI: 4.63-22.6%) and a specificity of 100% (95% CI: 84.54-100%). Furthermore, the sensitivity and specificity of the peripheral blood nucleated cell count were determined to be 34.0% (95% confidence interval: 22.17-48.33%) and 57.1% (95% confidence interval: 36.54-75.53%), respectively. CSF nucleated cell count demonstrated a sensitivity of 66.0% (95% confidence interval [CI]: 51.67-77.83%) and a specificity of 61.9% (95% CI: 40.87-79.25%). In comparison, the CSF protein content exhibited a sensitivity of 63.8% (95% CI: 49.54-76.03%) and a specificity of 57.1% (95% CI: 36.54-75.53%). When combining mNGS with traditional methodologies, the overall sensitivity increased to 91.3% (95% CI: 79.67-96.56%), although the specificity was reduced to 18.2% (95% CI: 7.31-38.51%). The area under the ROC curve for culture, peripheral blood nucleated cell count, mNGS, CSF nucleated cell count, and CSF protein content were 0.8088, 0.6038, 0.6103, 0.5588, and 0.5588, respectively. The variation in CSF nucleated cell count did not significantly affect the diagnostic efficacy of mNGS.

Conclusion

Currently, both mNGS and traditional diagnostic methods encounter substantial challenges in diagnosing CNSI.

Metagenomic versus targeted next-generation sequencing for detection of microorganisms in bronchoalveolar lavage fluid among renal transplantation recipients

Background

Metagenomic next-generation sequencing (mNGS), which provides untargeted and unbiased pathogens detection, has been extensively applied to improve diagnosis of pulmonary infection. This study aimed to compare the clinical performance between mNGS and targeted NGS (tNGS) for microbial detection and identification in bronchoalveolar lavage fluid (BALF) from kidney transplantation recipients (KTRs).

Methods

BALF samples with microbiological results from mNGS and conventional microbiological test (CMT) were included. For tNGS, samples were extracted, amplified by polymerase chain reaction with pathogen-specific primers, and sequenced on an Illumina Nextseq.

Results

A total of 99 BALF from 99 KTRs, among which 93 were diagnosed as pulmonary infection, were analyzed. Compared with CMT, both mNGS and tNGS showed higher positive rate and sensitivity (p<0.001) for overall, bacterial and fungal detection. Although the positive rate for mNGS and tNGS was comparable, mNGS significantly outperformed tNGS in sensitivity (100% vs. 93.55%, p<0.05), particularly for bacteria and virus (p<0.001). Moreover, the true positive rate for detected microbes of mNGS was superior over that of tNGS (73.97% vs. 63.15%, p<0.05), and the difference was also significant when specific for bacteria (94.59% vs. 64.81%, p<0.001) and fungi (93.85% vs. 72.58%, p<0.01). Additionally, we found that, unlike most microbes such as SARS-CoV-2, Aspergillus, and EBV, which were predominantly detected from recipients who underwent surgery over 3 years, Torque teno virus (TTV) were principally detected from recipients within 1-year post-transplant, and as post-transplantation time increased, the percentage of TTV positivity declined.

Conclusion

Although tNGS was inferior to mNGS owing to lower sensitivity and true positive rate in identifying respiratory pathogens among KTRs, both considerably outperformed CMT.

Use of Metagenomic Next-Generation Sequencing to Identify Pathogens Involved in Central Nervous System Infections

Purpose

Application of metagenomic next-generation sequencing (mNGS) in identifying nosocomial central nervous system (CNS) infections in critical care units remains understudied.

Methods

We conducted a retrospective analysis of microbiological results through both mNGS and routine examination of cerebrospinal fluid (CSF) samples from patients with nosocomial CNS infections. The aim of this study was to assess the clinical diagnostic effect of nosocomial mNGS in this population.

Results

The study included 26 cases of nosocomial CNS infections in total. A total of 69.2% (18/26) of the samples tested positive for mNGS, which is substantially greater than the 7.7% (2/26; p<0.05) detected through conventional techniques. Administration of antibiotics before culture is most likely the cause of the low CSF culture rate. Twenty-five pathogenic strains that were missed by standard testing. Three pathogens that were consistent with the mNGS results were positive by routine tests. Eight cases were negative by mNGS due to low pathogen CSF titres. Compared to traditional testing, mNGS demonstrated 100% sensitivity and 33.3% specificity in diagnosing CNS infections. The thirty-day mortality rate was 26.9% (7/26).

Conclusion

Routine microbiologic testing frequently falls short of detecting all neuroinvasive pathogens. Our research suggests that mNGS offers an alternative means of detecting nosocomial CNS infections. By applying mNGS to CSF samples from patients with meningitis or encephalitis, we were able to improve the ability to diagnose nosocomial neurologic infections.