title: Development and optimization of a metabolomic method for analysis of adherent cell cultures.
abstract: In this investigation, a gas chromatography/mass spectrometry (GC/MS)-based metabolomic protocol for adherent cell cultures was developed using statistical design of experiments. Cell disruption, metabolite extraction, and the GC/MS settings were optimized aiming at a gentle, unbiased, sensitive, and high-throughput metabolomic protocol. Due to the heterogeneity of the metabolome and the inherent selectivity of all analytical techniques, development of unbiased protocols is highly complex. Changing one parameter of the protocol may change the response of many groups of metabolites. In this investigation, statistical design of experiments and multivariate analysis also allowed such interaction effects to be taken into account. The protocol was validated with respect to linear range, precision, and limit of detection in a clonal rat insulinoma cell line (INS-1 832/13). The protocol allowed high-throughput profiling of metabolites covering the major metabolic pathways. The majority of metabolites displayed a linear range from a single well in a 96-well plate up to a 10 cm culture dish. The method allowed a total of 47 analyses to be performed in 24h.
authors.affiliation: Department of Clinical Sciences, Lund University Diabetes Centre, Malmö University Hospital, Sweden.
authors.forename: Anders P H
authors.initials: AP
authors.lastname: Danielsson
authors.forename: Thomas
authors.initials: T
authors.lastname: Moritz
authors.forename: Hindrik
authors.initials: H
authors.lastname: Mulder
authors.forename: Peter
authors.initials: P
authors.lastname: Spégel
mesh_terms: D000818:Animals; D002448:Cell Adhesion; D045744:Cell Line, Tumor; D016002:Discriminant Analysis; D008401:Gas Chromatography-Mass Spectrometry / Q000379:methods*; D057166:High-Throughput Screening Assays; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D025341:Principal Component Analysis; D051381:Rats; D013696:Temperature; D013997:Time Factors