Performance of Metagenomic Next-Generation Sequencing for the Diagnosis of Cryptococcal Meningitis in HIV-Negative Patients

Clinical treatment of cryptococcal meningitis: an evidence-based review on the emerging clinical data

Cryptococcal meningitis (CM) is a fatal fungal central nervous system (CNS) infection caused by Cryptococcus infecting the meninges and/or brain parenchyma, with fever, headache, neck stiffness, and visual disturbances as the primary clinical manifestations. Immunocompromised individuals with human immunodeficiency virus (HIV) infection or who have undergone organ transplantation, as well as immunocompetent people can both be susceptible to CM. Without treatment, patients with CM may have a mortality rate of up to 100% after hospital admission. Even after receiving therapy, CM patients may still suffer from problems such as difficulty to cure, poor prognosis, and high mortality. Therefore, timely and effective treatment is essential to improve the mortality and prognosis of CM patients. Currently, the clinical outcomes of CM are frequently unsatisfactory due to limited drug choices, severe adverse reactions, drug resistance, etc. Here, we review the research progress of CM treatment strategies and discuss the suitable options for managing CM, hoping to provide a reference for physicians to select the most appropriate treatment regimens for CM patients.

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

BACKGROUND

Next-generation sequencing (NGS) might aid in the identification of causal pathogens. However, the optimal approaches applied to cerebrospinal fluid (CSF) for detection are unclear, and studies evaluating the application of different NGS workflows for the diagnosis of intracranial infections are limited.

METHODS

In this multicenter, prospective observational cohort study, we described the diagnostic efficacy of pathogen-targeted NGS (ptNGS) and metagenomic NGS (mNGS) compared to that of composite microbiologic assays, for infectious meningitis/encephalitis (M/E).

RESULTS

In total, 152 patients diagnosed with clinically suspected M/E at four tertiary hospitals were enrolled; ptNGS and mNGS were used in parallel for pathogen detection in CSF. Among the 89 patients who were diagnosed with definite infectious M/E, 57 and 39 patients had causal microbial detection via ptNGS and mNGS, respectively. The overall accuracy of ptNGS was 65.1%, with a positive percent agreement (PPA) of 64% and a negative percent agreement (NPA) of 66.7%; and the overall accuracy of mNGS was 47.4%, with a PPA of 43.8% and an NPA of 52.4% after discrepancy analysis. There was a significant difference in the detection efficiency between these two methods both for PPA (sensitivity) and overall accuracy for pathogen detection (P < 0.05).

CONCLUSIONS

NGS tests have provided new information in addition to conventional microbiologic tests. ptNGS seems to have superior performance over mNGS for common causative pathogen detection in CSF for infectious M/E.

Application of metagenomic next-generation sequencing technology in the etiological diagnosis of peritoneal dialysis-associated peritonitis

Pathogens detected by metagenomic next-generation sequencing (mNGS) and the laboratory blood culture flask method were compared to understand the advantages and clinical significance of mNGS assays in the etiological diagnosis of peritoneal dialysis-associated peritonitis (PDAP). The study involved a total of 37 patients from the hospital's peritoneal dialysis centre, six of whom were patients with non-peritoneal dialysis-associated peritonitis. Peritoneal dialysis samples were collected from the 37 patients, who were divided into two groups. One group's samples were cultured using conventional blood culture flasks, and the other samples underwent pathogen testing using mNGS. The results showed that the positive rate of mNGS was 96.77%, while that of the blood culture flask method was 70.97% (p < 0.05). A total of 29 pathogens were detected by mNGS, namely 24 bacteria, one fungus, and four viruses. A total of 10 pathogens were detected using the bacterial blood culture method, namely nine bacteria and one fungus. The final judgment of the PDAP's causative pathogenic microorganism was made by combining the clinical condition, response to therapy, and the whole-genome sequencing findings. For mNGS, the sensitivity was 96.77%, the specificity was 83.33%, the positive predictive value was 96.77%, and the negative predictive value was 83.33%. For the blood culture flask method, the sensitivity was 70.97%, the specificity was 100%, the positive predictive value was 100%, and the negative predictive value was 0%. In conclusion, mNGS had a shorter detection time for diagnosing peritoneal dialysis-related peritonitis pathogens, with a higher positive rate than traditional bacterial cultures, providing significant advantages in diagnosing rare pathogens.

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.

Diagnostic Performance of Metagenomic Next-Generation Sequencing in Central Nervous System Cryptococcosis Using Cerebrospinal Fluid

Purpose

Metagenomic next-generation sequencing (mNGS) has been widely used to diagnose infectious diseases. However, there are few studies on its diagnostic performance in the central nervous system (CNS) cryptococcosis. This study examined the diagnostic efficacy of mNGS in identifying Cryptococcus spp. in cerebrospinal fluid (CSF) samples.

Patients and Methods

From March 2021 to March 2023, 290 patients with suspected CNS infection were recruited from the First Affiliated Hospital, School of Medicine, Zhejiang University, and 74 patients were ultimately included in the study. Lastly, 22 patients with CNS cryptococcosis were included. Of these patients, 25 CSF samples were enrolled. The diagnostic performance of conventional assays [including India ink, cryptococcal antigen (CrAg) testing, and culture] and mNGS was evaluated for CNS cryptococcosis.

Results

In the 25 samples collected, the coincidence rates of mNGS with India ink, CrAg, and culture were 64.0% (16/25), 80.0% (20/25), and 80.0% (20/25), respectively. Without antifungal drug exposure, the coincidence rates were increased to 66.7% (10/15), 100.0% (15/15), and 93.3% (14/15), respectively. The coincidence rates after antifungal therapy were all decreased to 60.0% (6/10), 50.0% (5/10), and 60.0% (6/10), respectively. Moreover, in the 25 samples, the sensitivity of mNGS reached 80.0%, and of India ink, CrAg testing, and culture were 68.0, 100.0, and 60.0%, respectively. The mNGS showed an excellent positive rate (100.0%) in the 15 samples collected without antifungal drug exposure, which was significantly higher than the antifungal drug-exposed group (n = 10) (50.0%) (P = 0.005). The reads of Cryptococcus spp. before antifungal therapy were significantly higher than after it (median, 25,915 vs 2, P = 0.008).

Conclusion

mNGS is an effective tool for diagnosing CNS cryptococcosis using CSF; however, its sensitivity decreases considerably in patients who have been effectively treated with antifungal drugs.

Diagnosis of invasive fungal infections: challenges and recent developments

BACKGROUND

The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow.

MAIN TEXT

A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections.

CONCLUSION

The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms.

Metagenomic next-generation sequencing versus traditional laboratory methods for the diagnosis of central nervous system opportunistic infections in HIV-infected Chinese adults

To evaluate clinical value of metagenomic next-generation sequencing (mNGS) in people living with HIV/AIDS (PLWHA) who had CNS disorders. Cerebrospinal fluid (CSF) samples from 48 PLWHA presenting with CNS disorders were sequenced using mNGS and compared with clinical conventional diagnostic methods. In total, 36/48 ss(75%) patients were diagnosed with pathogen(s) infection by mNGS, and the positive detection proportion by mNGS was higher than that by clinical conventional diagnostic methods (75% vs 52.1%, X² = 5.441, P = 0.020). Thirteen out of 48 patients (27.1%) were detected with 3-7 pathogens by mNGS. Moreover, 77 pathogen strains were detected, of which 94.8% (73/77) by mNGS and 37.0% (30/77) by clinical conventional methods (X² = 54.206, P < 0.001). The sensitivity and specificity of pathogens detection by mNGS were 63.9% (23/36) and 66.7% (8/12), respectively, which were superior to that by clinical conventional methods (23/36 vs 9/25, X² = 4.601, P = 0.032; 8/12 vs 5/23, X² = 5.029, P = 0.009). The application of mNGS was superior for its ability to detect a variety of unknown pathogens and multiple pathogens infection, and relatively higher sensitivity and specificity in diagnosis of CNS disorders in PLWHA.

Pulmonary Cryptococcosis Diagnosed by Metagenomic Next-Generation Sequencing in a Young Patient With Normal Immune Function: A Case Report

Background

Pulmonary cryptococcosis (PC) is a serious opportunistic fungal infection that usually occurs in immunocompromised patients. This disease is often difficult to diagnose in time due to its clinical manifestations and radiological feature similar to other pulmonary infections, as well as the low sensitivity of conventional diagnostic methods. Cryptococcosis in immune-competent patients is rare.

Case Presentation

Here we report a case of PC in an immune-competent patient. Tuberculosis was suspected according to radiological features due to the positive T-lymphocyte spot test and pure protein derivative skin test. To further detect the pathogen, bronchoalveolar lavage fluid (BALF) was collected for metagenomic next-generation sequencing (mNGS). Cryptococcus neoformans (one specific read) was identified by mNGS, indicating the PC of this patient. The following BALF culture and cryptococcal antigen lateral flow assay (CrAg-LFA) test also showed Cryptococcus infection, confirming the mNGS detection. Voriconazole (0.4 g daily) was given orally according to the subsequent susceptibility results. After seven months of treatment, the patient's condition improved.

Conclusion

Metagenomic next-generation sequencing (mNGS) is a better diagnostic tool to help clinicians distinguish pulmonary cryptococcosis from other atypical pulmonary infections.