Projects / Programmes
Clinical Metagenomics Sequencing for Pathogen Detection in Patients with Central Nervous System Infections
| Code |
Science |
Field |
Subfield |
| 3.01.00 |
Medical sciences |
Microbiology and immunology |
|
| Code |
Science |
Field |
| 3.01 |
Medical and Health Sciences |
Basic medicine |
metagenomics, next-generation sequencing, encephalitis, meningitis, central nervous system infections, bacteria, viruses, unknow aetiology, emerging pathogens
Researchers (15)
Organisations (2)
Abstract
Central nervous system infections impose a heavy burden on health care system as they are associated with high morbidity and mortality. Due to the involvement of vital areas and limited space, central nervous infections are associated with high morbidity and mortality, thus a rapid diagnosis and emergency interventions are necessary to improve outcomes of these patients. The infections are caused by wide variety of organisms including bacteria, parasites, fungi and viruses. The clinical course may be acute, subacute or chronic, depending on the pathogen and immune status of the host. Risk assessment of central nervous system infection in patients is of key importance in predicting likely pathogens, but data are lacking on the epidemiology globally. It is critical to differentiate between immune-mediated and infectious causes of central nervous infections in patients, since immunosuppressive treatment in cases, where the cause is an undiscovered pathogen could be devastating. Because of wide spectrum of possible pathogens, the identification of the aetiological agent requires multiple laboratory tests in addition to clinical and epidemiological information. In spite of hard laboratory labour and various diagnostic approaches used, the aetiology of meningitis/encephalitis is identified in less than 40 % of total cases. The technologies such as metagenomic next-generation sequencing (mNGS) can be attractive tools for broad-based pathogen discovery, filling the gap with unbiased detection of pathogens in clinical samples. This ‘needle-in-a-haystack’ approach involves analysis of millions of sequences derived from nucleic acid present in the clinical specimens to detect sequences corresponding to candidate pathogens. Given the usually low amount of pathogens’ genomic material in clinical samples and a vast proportion of host genome, this diagnostic approach can be expensive and time consuming. Thus, for a successful introduction of a straightforward shotgun metagenomics workflow in microbiological laboratory settings, several questions must be answered first. The aim of the proposed project is to detect unknown or neglected pathogens of central nervous system infections in Slovenia with mNGS, thereby shedding the light on the pathogenesis of meningitis, encephalitis and meningoencephalitis. The study will contribute to the development of guidelines for the diagnosis of central nervous system infections, as we will develop a detailed protocol for the preparation of clinical samples as well as implementation and analysis of metagenomic sequencing for the diagnosis of meningitis, encephalitis or meningoencephalitis. We expect that the results of the proposed project will shorten the hospitalization time and significantly increase the percentage of patients with known aetiology of the disease, which will lead to a targeted treatment and therefore reduce patient mortality.
