Targeted Metabolomics data from Neurospora crassa strains wild type, ∆gna-1, ∆gna-3, and ∆ric8

A metabolomics dataset generated via high-performance liquid chromatography and high-resolution mass spectrometry analysis of the filamentous fungus Neurospora crassa grown in minimal medium containing glucose as the carbon source. A total of 121 polar primary metabolites were detected across four different strains, including wild type. Four additional metabolites were detected but could not be quantified.METHODWe have previously published a paper that describes our metabolomics analysis pipeline in detail [1].Sample CollectionA total of five biological replicates were analyzed for each of the four strains. Strains were inoculated to a density of 1x106 cells/ml in 50 ml of liquid Vogel’s minimal medium (VM) [2] containing 100 mM glucose as the carbon source. Cultures were incubated with shaking in the dark for 16 hours at 30°C, collected using vacuum filtration and flash-frozen.ExtractionTissue was lyophilized for 2 days at -80°C and dried samples were pulverized in a bead mill homogenizer. Samples containing 8-9 mg of tissue were combined with 100 µL of extraction buffer/mg tissue [1]. The samples were then sonicated and vortexed, followed by centrifugation at 16,000xg for 15 min. The supernatant was stored at -80°C.ChromatographyLiquid chromatography was performed using a ZIC-pHILIC column (2.1 x 150 mm, 5 µM) (EMD Millipore) and an I-Class UPLC (Waters). The mobile phases were (A) 5 mM ammonium bicarbonate in water, pH 9.6 and (B) 100% acetonitrile. The gradient was 0 min, 90% B; 1.5 min, 90% B; 16 min, 20% B; 18 min, 20% B; 20 min, 90% B; 28 min, 90% B. Mass spectrometryMass spectrometry was accomplished using a TQ-XS triple quadrupole mass spectrometer (Waters), operated in selected reaction monitoring mode. All gases were nitrogen, except the argon collision gas. Source and desolvation temperatures were 150°C and 500°C, respectively. Desolvation gas was set to 1,000 L/hr, cone gas to 150 L/hr and collision gas to 0.15 mL/min. Capillary voltage was 1 kV in positive ion mode and 2 kV in negative ion mode. A quality control sample, generated by pooling equal aliquots of each sample, was analyzed every 3-5 injections. Data TransformationThe Skyline for Small Molecules software package (accessed 15 Aug 2021) (MacCoss Lab Software) was used for raw data analysis [3]. Default parameters were used for software except where otherwise noted. A transition list containing information on all the targeted metabolites including retention time, ion mass ratios, and collision energy was imported. Raw data was then imported and retention time peaks were standardized for each molecule across all detections. Transition results were applied and data was exported. Each mutant was compared to the wild type strain to derive a relative abundance percentage. Standard error was calculated, and unpaired t-tests were used to determine statistical significance between strains [4]. References:[1] Carrillo AJ, Halilovic L, Hur M, Kirkwood JS, Borkovich KA. 2022. Targeted metabolomics using LC-MS in Neurospora crassa. Curr Protoc 2:e454.[2] Vogel HJ. 1964. Distribution of lysine pathways among fungi: evolutionary implications. Am Nat 98:435–446.[3] Adams KJ, Pratt B, Bose N, Dubois LG, St John-Williams L, Perrott KM, Ky K, Kapahi P, Sharma V, MacCoss MJ, Moseley MA, Colton CA, MacLean BX, Schilling B, Thompson JW, Alzheimer's Disease Metabolomics C. 2020. Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics. J Proteome Res 19:1447-1458.[4] Team RC. 2021. R: A Language and Environment for Statistical Computing., R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.