Changes in metabolite profiles in the cerebrospinal fluid and in human neuronal cells upon tick-borne encephalitis virus infection
Notice bibliographique
Résumé
Abstract Background Tick-borne encephalitis virus (TBEV) is a significant threat to human health. The virus causes potentially fatal disease of the central nervous system (CNS), for which no treatments are available. TBEV infected individuals display a wide spectrum of neuronal disease, the determinants of which are undefined. Changes to host metabolism and virus-induced immunity have been postulated to contribute to the neuronal damage observed in infected individuals. In this study, we evaluated the cytokine, chemokine, and metabolic alterations in the cerebrospinal fluid (CSF) of symptomatic patients infected with TBEV presenting with meningitis or encephalitis. Our aim was to investigate the host immune and metabolic responses associated with specific TBEV infectious outcomes. Methods CSF samples of patients with meningitis (n = 27) or encephalitis (n = 25) were obtained upon consent from individuals hospitalised with confirmed TBEV infection in Brno. CSF from uninfected control patients was also collected for comparison (n = 12). A multiplex bead-based system was used to measure the levels of pro-inflammatory cytokines and chemokines. Untargeted metabolomics followed by bioinformatics and integrative omics were used to profile the levels of metabolites in the CSF. Human motor neurons (hMNs) were differentiated from induced pluripotent stem cells (iPSCs) and infected with the highly pathogenic TBEV-Hypr strain to profile the role(s) of identified metabolites during the virus lifecycle. Virus infection was quantified via plaque assay. Results Significant differences in proinflammatory cytokines (IFN-α2, TSLP, IL-1α, IL-1β, GM-CSF, IL-12p40, IL-15, and IL-18) and chemokines (IL-8, CCL20, and CXCL11) were detected between neurological-TBEV and control patients. A total of 32 CSF metabolites differed in TBE patients with meningitis and encephalitis. CSF S-Adenosylmethionine (SAM), Fructose 1,6-bisphosphate (FBP1) and Phosphoenolpyruvic acid (PEP) levels were 2.4-fold (range ≥ 2.3-≥3.2) higher in encephalitis patients compared to the meningitis group. CSF urocanic acid levels were significantly lower in patients with encephalitis compared to those with meningitis (p = 0.012209). Follow-up analyses showed fluctuations in the levels of O-phosphoethanolamine, succinic acid, and L-proline in the encephalitis group, and pyruvic acid in the meningitis group. TBEV-infection of hMNs increased the production of SAM, FBP1 and PEP in a time-dependent manner. Depletion of the metabolites with characterised pharmacological inhibitors led to a concentration-dependent attenuation of virus growth, validating the identified changes as key mediators of TBEV infection. Conclusions Our findings reveal that the neurological disease outcome of TBEV infection is associated with specific and dynamic metabolic signatures in the cerebrospinal fluid. We describe a new in vitro model for in-depth studies of TBEV-induced neuropathogenesis, in which the depletion of identified metabolites limits virus infection. Collectively, this reveals new biomarkers that can differentiate and predict TBEV-associated neurological disease. Additionally, we have identified novel therapeutic targets with the potential to significantly improve patient outcomes and deepen our understanding of TBEV pathogenesis.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».