Metagenomic next-generation sequencing for identification of central nervous system pathogens in HIV-infected patients

Microbiomes detected by cerebrospinal fluid metagenomic next-generation sequencing among patients with and without HIV with suspected central nervous system infection

BACKGROUND

Opportunistic infections in the central nervous system (CNS) can be a serious threat to people living with HIV. Early aetiological diagnosis and targeted treatment are crucial but difficult. Metagenomic next-generation sequencing (mNGS) has significant advantages over traditional detection methods. However, differences in the cerebrospinal fluid (CSF) microbiome profiles of patients living with and without HIV with suspected CNS infections using mNGS and conventional testing methods have not yet been adequately evaluated.

METHODS

We conducted a retrospective cohort study in the first hospital of Changsha between January 2019 and June 2022 to investigate the microbiomes detected using mNGS of the CSF of patients living with and without HIV with suspected CNS infections. The pathogens causing CNS infections were concurrently identified using both mNGS and traditional detection methods. The spectrum of pathogens identified was compared between the two groups.

RESULTS

Overall, 173 patients (140 with and 33 without HIV) with suspected CNS infection were enrolled in our study. In total, 106 (75.7%) patients with and 16 (48.5%) patients without HIV tested positive with mNGS (p = 0.002). Among the enrolled patients, 71 (50.7%) with HIV and five (15.2%) without HIV tested positive for two or more pathogens (p < 0.001). Patients with HIV had significantly higher proportions of fungus (20.7% vs. 3.0%, p = 0.016) and DNA virus (59.3% vs. 21.2%, p < 0.001) than those without HIV. Epstein-Barr virus (33.6%) was the most commonly identified potential pathogen in the CSF of patients living with HIV using mNGS, followed by cytomegalovirus (20.7%) and torque teno virus (13.8%). The top three causative pathogens identified in patients without HIV were Streptococcus (18.2%), Epstein-Barr virus (12.1%), and Mycobacterium tuberculosis (9.1%). In total, 113 patients living with HIV were diagnosed as having CNS infections. The rate of pathogen detection in people living with HIV with a CNS infection was significantly higher with mNGS than with conventional methods (93.8% vs. 15.0%, p < 0.001).

CONCLUSION

CSF microbiome profiles differ between patients living with and without HIV with suspected CNS infection. mNGS is a powerful tool for the diagnosis of CNS infection among people living with HIV, especially in those with mixed infections.

Nanopore targeted sequencing-based diagnosis of central nervous system infections in HIV-infected patients

BACKGROUND

Early and accurate etiological diagnosis is very important for improving the prognosis of central nervous system (CNS) infections in human immunodeficiency virus (HIV)-infected patients. The goal is not easily achieved by conventional microbiological tests. We developed a nanopore targeted sequencing (NTS) platform and evaluated the diagnostic performance for CNS infections in HIV-infected patients, with special focus on cryptococcal meningitis (CM). We compared the CM diagnostic performance of NTS with conventional methods and cryptococcal polymerase chain reaction (PCR).

METHODS

This study included 57 hospitalized HIV-infected patients with suspected CNS infections from September 2018 to March 2022. The diagnosis established during hospitalization includes 27 cases of CM, 13 CNS tuberculosis, 5 toxoplasma encephalitis, 2 cytomegalovirus (CMV) encephalitis and 1 Varicella-zoster virus (VZV) encephalitis. The 2 cases of CMV encephalitis also have co-existing CM. Target-specific PCR amplification was used to enrich pathogen sequences before nanopore sequencing. NTS was performed on stored cerebrospinal fluid (CSF) samples and the results were compared with the diagnosis during hospitalization.

RESULTS

53 (93.0%) of the patients were male. The median CD4 cell count was 25.0 (IQR: 14.0-63.0) cells/uL. The sensitivities of CSF culture, India ink staining, cryptococcal PCR and NTS for CM were 70.4% (95%CI: 51.5 - 84.1%), 76.0% (95%CI: 56.6 - 88.5%), 77.8% (59.2 - 89.4%) and 85.2% (95%CI: 67.5 - 94.1%), respectively. All those methods had 100% specificity for CM. Our NTS platform could identify Cryptococcus at species level. Moreover, NTS was also able to identify all the 5 cases of toxoplasma encephalitis, 2 cases of CMV encephalitis and 1 VZV encephalitis. However, only 1 of 13 CNS tuberculosis cases was diagnosed by NTS, and so did Xpert MTB/RIF assay.

CONCLUSIONS

NTS has a good diagnostic performance for CM in HIV-infected patients and may have the ability of simultaneously detecting other pathogens, including mixed infections. With continuing improving of the NTS platform, it may be a promising alterative microbiological test for assisting with the diagnosis of CNS infections.

Epstein-Barr virus: To be a trigger of autoimmune glial fibrillary acidic protein astrocytopathy?

BACKGROUND

Autoimmune glial fibrillary acidic protein (GFAP) astrocytopathy is a novel autoimmune disease of central nervous system (CNS). It is unclear whether Epstein-Barr virus (EBV) is related to autoimmune GFAP astrocytopathy.

OBJECTIVE

To describe the clinical, laboratory, and imaging characteristics of patients with autoimmune GFAP astrocytopathy.

METHODS

The clinical, laboratory, and imaging findings of patients are presented. The levels of GFAP in CSF were detected by ELISA. T and B cell subsets in CSF were detected by flow cytometry. GFAP-IgG in serum and cerebrospinal fluid (CSF) were tested by cell-based assay (CBA) and tissue-based assay (TBA).

RESULTS

All three patients had fever, cognitive dysfunction, limb weakness, and positive GFAP-IgG with EBV infection in CSF. Enteric glia cells may involve in this disease. Typical imaging findings include the gadolinium enhancement of linear perivascular radial perpendicular to the ventricle, meningeal enhancement (especially in midbrain interpeduncal fossa), longitudinally extensive lesions involving spindle cords, and more T2/Flair-hyperintense lesions in the periventricular white matter at late stage. The patients had poor response to antiviral treatment and strong response to steroid pulse therapy.

CONCLUSION

EBV could induce CNS autoimmune response in autoimmune GFAP astrocytopathy. The detection of GFAP-IgG and EBV may facilitate the early diagnosis in these patients.

Case Report: A case of Chlamydia psittaci infection in an HIV patient

Chlamydia psittaci is the pathogen of psittacosis and infects a wide range of birds and even humans. Human infection occurs most commonly in those with a history of contact with birds or poultry. We describe a case of psittacosis in a human immunodeficiency virus infected patient in Zhejiang Province for the first time. C. psittaci infection was confirmed by nested polymerase chain reaction (PCR) and Real-Time PCR. Phylogenetic analysis revealed that the sequences from the patient's samples clustered with genotype A in the same branch. Our study highlights the possibility of diagnosing psittacosis in patients with a chronic disease such as HIV-infected patients, and should increase awareness and surveillance of psittacosis in China.

Metagenomic next-generation sequencing and proteomics analysis in pediatric viral encephalitis and meningitis

Introduction

Early and accurate identification of pathogens is essential for improved outcomes in patients with viral encephalitis (VE) and/or viral meningitis (VM).

Methods

In our research, Metagenomic next-generation sequencing (mNGS) which can identify viral pathogens unbiasedly was performed on RNA and DNA to identify potential pathogens in cerebrospinal fluid (CSF) samples from 50 pediatric patients with suspected VEs and/or VMs. Then we performed proteomics analysis on the 14 HEV-positive CSF samples and another 12 CSF samples from health controls (HCs). A supervised partial least squaresdiscriminant analysis (PLS-DA) and orthogonal PLS-DA (O-PLS-DA) model was performed using proteomics data.

Results

Ten viruses in 48% patients were identified and the most common pathogen was human enterovirus (HEV) Echo18. 11 proteins overlapping between the top 20 DEPs in terms of P value and FC and the top 20 proteins in PLS-DA VIP lists were acquired.

Discussion

Our result showed mNGS has certain advantages on pathogens identification in VE and VM and our research established a foundation to identify diagnosis biomarker candidates of HEV-positive meningitis based on MS-based proteomics analysis, which could also contribute toward investigating the HEV-specific host response patterns.