This work compares the metabolic profiles of plasma and the cerebrospinal fluid (CSF) of the patients with high-grade (III and IV) gliomas and the conditionally healthy controls using the wide-range targeted screening of low molecular metabolites by HPLC-MS/MS. The obtained data were analyzed using robust linear regression with Huber’s M-estimates, and a number of metabolites with correlated content in plasma and CSF was identified. The statistical analysis shows a significant correlation of metabolite content in plasma and CSF samples for the majority of metabolites. Several metabolites were shown to have high correlation in the control samples, but not in the glioma patients. This can be due to the specific metabolic processes in the glioma patients or to the damaged integrity of blood-brain barrier. The results of our study may be useful for the understanding of molecular mechanisms underlying the development of gliomas, as well as for the search of potential biomarkers for the minimally invasive diagnostic procedures of gliomas.
Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC–MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.
Metabolomic analysis of patient`s plasma is a promising approach to the study of molecular mechanisms of viral infections, identification of diagnostic and prognostic biomarkers, and improvement of the current therapies. However, metabolomic analysis is often limited to the identification of overrepresented metabolic processes. Information about the genetic regulation of these processes and the molecular mechanisms and roles of viral proteins in the revealed disturbed function of metabolic processes is overlooked. Metabolomic analysis of plasma of COVID-19 patients and the controls using the high-performance liquid chromatography coupled with tandem mass spectrometric detection (LC-MS/MS) was performed. 103 metabolites were shown to differ significantly in the compared groups. Among KEGG metabolic pathways, amino acid metabolism and the biosynthesis of aminoacyl-tRNAs were overrepresented. Using ANDSystem software, the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins was performed. Viral proteins orf8, E, and nsp5 were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins.
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