Performance of metagenomic next-generation sequencing in cerebrospinal fluid for diagnosis of tuberculous meningitis.

Purpose. Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases, while its performance in diagnosis of tuberculous meningitis (TBM) is incompletely characterized. The aim of this study was to assess the performance of mNGS in the diagnosis of TBM, and illustrate the sensitivity and specificity of different methods.Methods. We retrospectively recruited TBM patients between January 2021 and March 2023 to evaluate the performance of mNGS on cerebrospinal fluid (CSF) samples, in comparison with conventional microbiological testing, including culturing of Mycobacterium tuberculosis (MTB), acid-fast bacillus (AFB) stain, reverse transcription PCR and Xpert MTB/RIF.Results. Of the 40 enrolled, 34 participants were diagnosed with TBM, including 15(44.12 %) definite and 19(55.88 %) clinical diagnosis based upon clinical manifestations, CSF parameters, brain imaging, pathogen evidence and treatment response. The mNGS method identified sequences of Mycobacterium tuberculosis complex (MTBC) in 11 CSF samples. In patients with definite TBM, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy of mNGS were 78.57, 100, 100, 66.67 and 85 %, respectively. Compared to conventional diagnostic methods, the sensitivity of mNGS (78.57 %) was higher than AFB (0 %), culturing (0 %), RT-PCR (60 %) and Xpert MTB/RIF (14.29 %).Conclusions. Our study indicates that mNGS of CSF exhibited an overall improved sensitivity over conventional diagnostic methods for TBM and can be considered a front-line CSF test.

Microbiota in adult perianal abscess revealed by metagenomic next-generation sequencing.

The microbiota of perianal abscesses is scarcely investigated. Identifying causative bacteria is essential to develop antibiotic therapy. However, culture-based methods and molecular diagnostics through 16S PCR technology are often hampered by the polymicrobial nature of perianal abscesses. We sought to characterize the microbiota composition of perianal abscesses via metagenomic next-generation sequencing (mNGS). Fourteen patients suffering from perianal abscesses between March 2023 and August 2023 underwent retrospective assessment. Information from medical records was used, including clinical information, laboratory data, and culture and mNGS results. Forty bacterial taxa were identified from perianal abscesses through mNGS, with Bilophila wadsworthia (71.4%), Bacteroides fragilis (57.1%), and Escherichia coli (50.0%) representing the most prevalent species. mNGS identified an increased number of bacterial taxa, with an average of 6.1 compared to a traditional culture-based method which only detected an average of 1.1 in culture-positive perianal abscess patients, predominantly E. coli (75.0%), revealing the polymicrobial nature of perianal abscesses. Our study demonstrates that a more diverse bacterial profile is detected by mNGS in perianal abscesses, and that Bilophila wadsworthia is the most prevalent microorganism, potentially serving as a potential biomarker for perianal abscess.IMPORTANCEAccurately, identifying the bacteria causing perianal abscesses is crucial for effective antibiotic therapy. However, traditional culture-based methods and 16S PCR technology often struggle with the polymicrobial nature of these abscesses. This study employed metagenomic next-generation sequencing (mNGS) to comprehensively analyze the microbiota composition. Results revealed 40 bacterial taxa, with Bilophila wadsworthia (71.4%), Bacteroides fragilis (57.1%), and Escherichia coli (50.0%) being the most prevalent species. Compared to the culture-based approach, mNGS detected a significantly higher number of bacterial taxa (average 6.1 vs 1.1), highlighting the complex nature of perianal abscesses. Notably, Bilophila wadsworthia emerged as a potential biomarker for these abscesses. This research emphasizes the importance of mNGS in understanding perianal abscesses and suggests its potential for improving diagnostic accuracy and guiding targeted antibiotic therapy in the future.

Systemic and cerebrospinal fluid biomarkers for tuberculous meningitis identification and treatment monitoring.

IMPORTANCE: Tuberculous meningitis is a life-threatening infection with high mortality and disability rates. Current diagnostic methods using cerebrospinal fluid (CSF) samples have limited sensitivity and lack predictive biomarkers for evaluating prognosis. This study's findings reveal excessive activation of the immune response during tuberculous meningitis (TBM) infection. Notably, a strong negative correlation was observed between CSF levels of monokine induced by interferon-γ (MIG) and the CSF/blood glucose ratio in TBM patients. MIG also exhibited the highest area under the curve with high sensitivity and specificity. This study suggests that MIG may serve as a novel biomarker for differentiating TBM infection in CSF or serum, potentially leading to improved diagnostic accuracy and better patient outcomes.

Streptococcus suis meningoencephalitis diagnosed with metagenomic next-generation sequencing: A case report with literature review.

Streptococcus suis is a pathogen of emerging zoonotic diseases and meningoencephalitis is the most frequent clinical symptom of S. suis infection in humans. Rapid diagnosis of S. suis meningoencephalitis is critical for the treatment of the disease. While the current routine microbiological tests including bacterial culture and gram staining are poorly sensitive, diagnosis of S. suis meningoencephalitis by metagenomic next-generation sequencing (mNGS) has been rarely reported. Here, we report a 52-year-old female pork food producer with a broken finger developed S. suis meningoencephalitis. After her admission, no pathogenic bacteria were detected through bacterial culture and Gram staining microscopy in the cerebrospinal fluid obtained via lumbar puncture. However, mNGS identified the presence of S. suis in the sample. mNGS is a promising diagnostic tool for rapid diagnosis of rare infectious diseases in the central nervous system.