Untargeted metabolomics analysis of metabolites from foraging S. coelicolor - Sandblad, Linda; Söderholm, Niklas (Umeå University, 2024)
For untargeted metabolite analysis, agar stubs were punched out from just outside of S. coelicolor colonies on FAM and FAM+G. For each condition, twelve samples were isolated from plates inoculated with S. coelicolor, in addition to two control samples each from sterile plates. The weight of the samples were adjusted to 100 mg before the addition of 1 mL extraction buffer (90/10 v/v methanol:water). Internal standards (13C9-Phenylalanine, 13C3-Caffeine was, D4-Cholic acid, D8-Arachidonic Acid, 13C9-Caffeic Acid) were added to each sample. The sample was shaken at 30 Hz for 3 min in a mixer mill, and proteins were precipitated at +4 °C for 2h on ice. The sample was centrifuged at +4 °C, 14 000 rpm, for 10 min. The supernatant was transferred to a microvial and solvents evaporated. Before analysis, the sample was re-suspended in 10 + 10 µL methanol and water. The set of samples were analyzed in positive mode and negative mode. The chromatographic separation was performed on an Agilent 1290 Infinity UHPLC-system (Agilent Technologies, Waldbronn, Germany). Re-suspended aliquots (2 µL) of the agar extracts were injected onto an Acquity UPLC HSS T3, 2.1 x 50 mm, 1.8 µm C18 column in combination with a 2.1 mm x 5 mm, 1.8 µm VanGuard precolumn (Waters Corporation, Milford, MA, USA) held at 40°C. The gradient elution buffers were A (H2O, 0.1 % formic acid) and B (75/25 acetonitrile:2-propanol, 0.1 % formic acid). The compounds were detected with an Agilent 6550 Q-TOF mass spectrometer equipped with a jet stream electrospray ion source. The settings were kept identical between the modes, except the capillary voltage. The data processing was performed using the Recursive Feature Extraction algorithm within Agilent Masshunter Profinder version B.08.00 (Agilent Technologies Inc., Santa Clara, CA, USA). All multivariate statistical investigations (PCA) were performed using the software package SIMCA®-P+ version 15.0.2 (Umetrics, Umeå, Sweden).
Keywords: Proteomics and metabolomics; Bacteriology; Medical and Health Sciences; Medicin och hälsovetenskap; Biological Sciences; Biologi