Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis

Application of metabolomics in diagnostics and differentiation of meningitis: A narrative review with a critical approach to the literature

Due to its high mortality rate associated with various life-threatening sequelae, meningitis poses a vital problem in contemporary medicine. Numerous algorithms, many of which were derived with the aid of artificial intelligence, were brought up in a strive for perfection in predicting the status of sepsis-related survival or exacerbation. This review aims to provide key insights on the contextual utilization of metabolomics. The aim of this the metabolomic approach set of methods can be used to investigate both bacterial and host metabolite sets from both the host and its microbes in several types of specimens - even in one's breath, mainly with use of two methods - Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR). Metabolomics, and has been used to elucidate the mechanisms underlying disease development and metabolic identification changes in a wide range of metabolite contents, leading to improved methods of diagnosis, treatment, and prognosis of meningitis. Mass spectrometry (MS) and Nuclear Magnetic Resonance (NMR) are the main analytical platforms used in metabolomics. Its high sensitivity accounts for the usefulness of metabolomics in studies into meningitis, its sequelae, and concomitant comorbidities. Metabolomics approaches are a double-edged sword, due to not only their flexibility, but also - high complexity, as even minor changes in the multi-step methods can have a massive impact on the results. Information on the differential diagnosis of meningitis act as a background in presenting the merits and drawbacks of the use of metabolomics in context of meningeal infections.

The Worldwide Prevalence of Herpes Simplex Virus Encephalitis and Meningitis: A Systematic Review and Meta-Analysis

Given the relatively high frequency of central nervous system infections and considerable mor- tality and morbidity reported to be caused by herpes simplex viruses among the other viral agents, having a clear knowledge about their epidemiological profile seems necessary. This systematic review and meta-analysis aimed to determine the relative frequency and preva- lence of herpes simplex encephalitis and meningitis in patients tested for viral etiologies. A comprehensive systematic review was performed in PubMed, Scopus, and Web of Science databases, searching for studies on the prevalence and relative frequency of herpes sim- plex virus 1 and herpes simplex virus 2 encephalitis and meningitis. Seventy-one studies were included. Overall, the prevalence of herpes simplex virus encephalitis among patients tested was 8% (95% confidence interval, 6%-11%; I2 = 98%) and the prevalence of herpes simplex virus meningitis among aseptic patients tested was 4% (95% confidence interval, 3%-7%; I2 = 95%), and a significant difference was observed by region. The results of our subgroup analysis for herpes simplex virus encephalitis revealed a prevalence of 8% for pediatric patients and ado- lescents and 12% for adults. The results for herpes simplex virus meningitis showed a prevalence of 4% for pediatric patients and adolescents and 9% for adults. We observed significant differ- ences in the frequency of herpes simplex virus 1 and herpes simplex virus 2 detection rates by region. Having high rates of missed cases due to inadequate, highly sensitive paraclinical tests performed on patients with suspected viral central nervous system infection is one of the pos- sible factors. More studies are needed to detect the possible flaws in the process of diagnosis in different regions.

Temporal pathway analysis of cerebrospinal fluid proteome in herpes simplex encephalitis

OBJECTIVES

We examined the temporal changes of the CSF proteome in patients with herpes simplex encephalitis (HSE) during the course of the disease, in relation to anti-N-methyl-D-aspartate receptor (NMDAR) serostatus, corticosteroid treatment, brain MRI and neurocognitive performance.

METHODS

Patients were retrospectively included from a previous prospective trial with a pre-specified CSF sampling protocol. Mass spectrometry data of the CSF proteome were processed using pathway analysis.

RESULTS

We included 48 patients (110 CSF samples). Samples were grouped based on time of collection relative to hospital admission - T1: ≤ 9 d, T2: 13-28 d, T3: ≥ 68 d. At T1, a strong multi-pathway response was seen including acute phase response, antimicrobial pattern recognition, glycolysis and gluconeogenesis. At T2, most pathways activated at T1 were no longer significantly different from T3. After correction for multiplicity and considering the effect size threshold, 6 proteins were significantly less abundant in anti-NMDAR seropositive patients compared to seronegative: procathepsin H, heparin cofactor 2, complement factor I, protein AMBP, apolipoprotein A1 and polymeric immunoglobulin receptor. No significant differences in individual protein levels were found in relation to corticosteroid treatment, size of brain MRI lesion or neurocognitive performance.

CONCLUSIONS

We show a temporal change in the CSF proteome in HSE patients during the course of the disease. This study provides insight into quantitative and qualitative aspects of the dynamic pathophysiology and pathway activation patterns in HSE and prompts for future studies on the role of apolipoprotein A1 in HSE, which has previously been associated with NMDAR encephalitis.

Cerebrospinal fluid: a target of some fungi and an overview

Meningitis is a potentially life-threatening infection characterised by the inflammation of the leptomeningeal membranes. The estimated annual prevalence of 8.7 million cases globally and the disease is caused by many different viral, bacterial, and fungal pathogens. Although several genera of fungi are capable of causing infections in the central nervous system (CNS), the most significant number of registered cases have, as causal agents, yeasts of the genus Cryptococcus. The relevance of cryptococcal meningitis has changed in the last decades, mainly due to the increase in the number of people living with human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) and medications that impair the immune responses. In this context, coronavirus disease 19 (COVID-19) has also emerged as a risk factor for invasive fungal infections (IFI), including fungal meningitis (FM), due to severe COVID-19 disease is associated with increased pro-inflammatory cytokines, interleukin (IL)-1, IL-6, and tumour necrosis factor-alpha, reduced CD4-interferon-gamma expression, CD4 and CD8 T cells. The gold standard technique for fungal identification is isolating fungi in the culture of the biological material, including cerebrospinal fluid (CSF). However, this methodology has as its main disadvantage the slow or null growth of some fungal species in culture, which makes it difficult to finalise the diagnosis. In conclusions, this article, in the first place, point that it is necessary to accurately identify the etiological agent in order to assist in the choice of the therapeutic regimen for the patients, including the implementation of actions that promote the reduction of the incidence, lethality, and fungal morbidity, which includes what is healthy in the CNS.

Quantitative proteomics on the cerebrospinal fluid of hydrocephalus in neonatal bacterial meningitis

Objective

Hydrocephalus in bacterial meningitis (BM) is a devastating infectious neurological disease and the proteins and pathways involved in its pathophysiology are not fully understood.

Materials and methods

Label-free quantitative (LFQ) proteomics analyses was used to identify differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples from infants with hydrocephalus and bacterial meningitis (HBM group, N = 8), infants with bacterial meningitis (BM group, N = 9); and healthy infants (N group, N = 11). Bioinformatics analysis was subsequently performed to investigate Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enriched signaling pathways of these DEPs. Six proteins (AZU1, COX4I1, EDF1, KRT31, MMP12, and PRG2) were selected for further validation via enzyme-linked immunosorbent assay (ELISA).

Results

Compared with BM group and N group, HBM group had a higher whole CSF protein level (5.6 ± 2.7 vs. 1.7 ± 1.0 vs. 1.2 ± 0.5 g/l) and lower whole CSF glucose level (0.8 ± 0.6 vs. 1.8 ± 0.7 vs. 3.3 ± 0.8 mmol/l) (both P < 0.05). Over 300 DEPs were differentially expressed in HBM group compared with BM group and BM compared with N group, of which 78% were common to both. Cluster analysis indicated that the levels of 226 proteins were increased in BM group compared with N group and were decreased in HBM group compared with BM group. Bioinformatics analysis indicated the involvement of the cell adhesion, immune response and extracellular exosome signaling were significantly enriched in HBM compared with BM group and BM compared with N group. 267 DEPs were identified between HBM group with N group, KEGG analysis indicated that DEPs mainly involved in filament cytoskeleton and immune response. The ELISA results further verified that the expression levels of AZU1 were significantly different from among three groups (both P < 0.05).

Conclusion

This is the first reported characterization of quantitative proteomics from the CSF of infants with HBM. Our study also demonstrated that AZU1 could be a potential biomarker for the diagnosis of hydrocephalus in bacterial meningitis.

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Metabolomic Characterization of Cerebrospinal Fluid from Intracranial Bacterial Infection Pediatric Patients: A Pilot Study

Intracranial bacterial infection remains a major cause of morbidity and mortality in neurosurgical cases. Metabolomic profiling of cerebrospinal fluid (CSF) holds great promise to gain insights into the pathogenesis of central neural system (CNS) bacterial infections. In this pilot study, we analyzed the metabolites in CSF of CNS infection patients and controls in a pseudo-targeted manner, aiming at elucidating the metabolic dysregulation in response to postoperative intracranial bacterial infection of pediatric cases. Untargeted analysis uncovered 597 metabolites, and screened out 206 differential metabolites in case of infection. Targeted verification and pathway analysis filtered out the glycolysis, amino acids metabolism and purine metabolism pathways as potential pathological pathways. These perturbed pathways are involved in the infection-induced oxidative stress and immune response. Characterization of the infection-induced metabolic changes can provide robust biomarkers of CNS bacterial infection for clinical diagnosis, novel pathways for pathological investigation, and new targets for treatment.

Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis

Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae, and treatment options. Here, we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell-, and plasma proteins in the CSF, where, in particular, a large increase of neutrophil-derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multiprotein LASSO regression model resulted in an 18-protein panel of cell- and tissue-associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen-specific host response patterns in CSF from different disease etiologies to support future classification of pathogen type based on host response patterns in meningitis.