Your browser doesn't support javascript.
loading
Optimized high-throughput protocols for comprehensive metabolomic and lipidomic profiling of brain sample.
Can Eylem, Cemil; Nemutlu, Emirhan; Dogan, Aysegul; Acik, Vedat; Matyar, Selcuk; Gezercan, Yurdal; Altintas, Suleyman; Okten, Ali Ihsan; Basci Akduman, Nursabah Elif.
Afiliação
  • Can Eylem C; Hacettepe University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey.
  • Nemutlu E; Hacettepe University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey.
  • Dogan A; Hacettepe University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey. Electronic address: ayseguld@hacettepe.edu.tr.
  • Acik V; Department of Neurosurgery, Adana City Training and Research Hospital, Adana, Turkey.
  • Matyar S; Department of Biochemistry, University of Medical Sciences, Adana City Training and Research Hospital, Adana, Turkey.
  • Gezercan Y; Department of Neurosurgery, Adana City Training and Research Hospital, Adana, Turkey.
  • Altintas S; Department of Pathology, Adana City Training and Research Hospital, Adana, Turkey.
  • Okten AI; Department of Neurosurgery, Adana City Training and Research Hospital, Adana, Turkey.
  • Basci Akduman NE; Hacettepe University, Faculty of Pharmacy, Department of Analytical Chemistry, Ankara, Turkey. Electronic address: nbasci@hacettepe.edu.tr.
Talanta ; 282: 126953, 2024 Sep 26.
Article em En | MEDLINE | ID: mdl-39366247
ABSTRACT
Establishing direct causal and functional links between genotype and phenotype requires thoroughly analyzing metabolites and lipids in systems biology. Tissue samples, which provide localized and direct information and contain unique compounds, play a significant role in objectively classifying diseases, predicting prognosis, and deciding personalized therapeutic strategies. Comprehensive metabolomic and lipidomic analyses in tissue samples need efficient sample preparation steps, optimized analysis conditions, and the integration of orthogonal analytical platforms because of the physicochemical diversities of biomolecules. Here, we propose simple, rapid, and robust high-throughput analytical protocols based on the design of experiment (DoE) strategies, with the various parameters systematically tested for comprehensively analyzing the heterogeneous brain samples. The suggested protocols present a systematically DoE-based strategy for performing the most comprehensive analysis for integrated GC-MS and LC-qTOF-MS from brain samples. The five different DoE models, including D-optimal, full factorial, fractional, and Box-Behnken, were applied to increase extraction efficiency for metabolites and lipids and optimize instrumental parameters, including sample preparation and chromatographic parameters. The superior simultaneous extraction of metabolites and lipids from brain samples was achieved by the methanol-water-dichloromethane (213, v/v/v) mixture. For GC-MS based metabolomics analysis, incubation time, temperature, and methoxyamine concentration (10 mg/mL) affected metabolite coverage significantly. For LC-qTOF-MS based metabolomics analysis, the extraction solvent (methanol-water; 21, v/v) and the reconstitution solvent (%0.1 FA in acetonitrile) were superior on the metabolite coverage. On the other hand, the ionic strength and column temperature were critical and significant parameters for high throughput metabolomics and lipidomics studies using LC-qTOF-MS. In conclusion, DoE-based optimization strategies for a three-in-one single-step extraction enabled rapid, comprehensive, high-throughput, and simultaneous analysis of metabolites, lipids, and even proteins from a 10 mg brain sample. Under optimized conditions, 475 lipids and 158 metabolites were identified in brain samples.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Talanta Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Turquia País de publicação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Talanta Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Turquia País de publicação: Holanda