Thermo xcalibur

HRMS and MS/MS data were processed with Thermo Xcalibur and Compound Discoverer 3.1.1.12 (Thermo Fisher Scientific, CA, USA). For the untargeted metabolomics analysis, customizable processing workflow, including selection of spectra, RT alignment and signal correction, peak detection, and grouping and annotation of compounds, was applied to all the data set and described as follows: After the selection of imported raw files, retention time (RT) alignment was performed from 1 to 12 min as an upper limit with a maximum time shift alignment set at 2 min with 10-ppm mass tolerance. The peak-picking procedure was conducted on a full HRMS data scan between 0 and 1,100 Da, adopting criteria, such as minimum peak intensity (1,000,000), mass tolerance set up at 5 ppm but also by integrating selected isotopes and adducts. Finally, the straight elucidation and the annotation of compounds were performed according to the accurate mass, the potential adducts, and isotopes in correlation with MS/MS fragmentation spectra by comparing with commercial and noncommercial exported or implemented databases (e.g., Dictionary of Natural Products, library mzCloud, Chemspider, Masslist) as well as data from literature.

The separation of B-vitamins and vitamers was performed using a gradient of increasing acetonitrile over a 14 min run time using a reversed-phase Kinetex 2.6 µm F5 100Å LC column 150 × 2.1 mm (Phenomenex, Torrance, CA, USA) on a Vanquish™ UHPLC System (Thermo Fisher Scientific, USA) at a constant flow rate of 0.2 mL/min; the injection volume was 10 µL. Water containing 5% acetic acid and 0.2% HFBA was used as mobile phase A and mobile phase B was acetonitrile. Mass spectrometry was conducted using TSQ Quantiva (Thermo Fisher Scientific) system in positive electrospray ionization (H-ESI) mode. Spray voltage was set to 4000 V, sheath gas 40, auxiliary gas 10, and sweep gas at 1 (all arbitrary units). The ion transfer tube temperature and vaporizer temperature were set at 350·°C. Data was generated by the integrated Thermo Xcalibur™ mass spectrometry data system software (Thermo Xcalibur version 4.1, Thermo Fisher Scientific Inc. US).

The cell pellets collected from 10-I, 50-I, and 50-T were used for proteomic analysis. The digested peptides were labeled using iTRAQ reagents (AB Sciex). The labeled peptides were analyzed on an EASY-nLC 1200 system coupled to a Q-Exactive mass spectrometer (Thermo-Fisher). All raw data were collected using Thermo Xcalibur and analyzed using Sequest HT (Thermo-Fisher). Proteomic data have been deposited to the ProteomeXchange Consortium via the iProx partner repository with the dataset identifier PXD013207. The prediction of transmembrane helices were conducted by TMHMM [76 (link)]. PSORTb [77 (link)] was used to predict the proteins’ subcellular localization, and SignalP [78 (link)] was used to predict the presence of signal peptides.

The raw data obtained by LC-MS analysis were processed with Mascot Distiller 2.4.2 (Matrix Science, UK) to obtain Mascot Generic Files (MGF) containing peptide fragmentation data. For peptide identification and the detection of post-translational modifications, Mascot server 2.4.1 was used. Several Mascot searches were performed with different settings (standard and error-tolerant searches with different combinations of post-translational modifications). Both Mascot Distiller-processed and raw spectra of potentially modified peptides were analyzed manually. MS Product from the Protein Prospector package (http://prospector.ucsf.edu) and Expert GUI [20 (link)] were used for manual assessment of data processed with Mascot Distiller. Raw data were reviewed using Thermo Xcalibur (Thermo, USA). Only modifications that could be assigned to specific positions using MS/MS spectra were considered. Masses of modifications were preferably calculated on the basis of average mass shift of multiple ions in MS/MS spectra. Since the resolution of the Orbitrap analyzer increases with a decrease in m/z, fragment ions of low mass were preferentially used to perform the calculations.

A Selected Reaction Monitoring (SRM) transition library of metabolites was constructed using authentic standards from Sigma-Aldrich (Supplementary Table S1). Standard mixtures were injected periodically throughout the analysis to evaluate the stability of the analytical system as well as to support peak identification. All data were processed by using Thermo Xcalibur software version 3.1 (Thermo Scientific).
Relative quantification was used during method optimization (Supplementary Tables S2–S4). All peak areas obtained from GC-MS/MS analysis were normalized against the ribitol signal.
Absolute quantification was applied to measure intracellular metabolite levels of U. maydis while using different carbon sources (Supplementary Table S5). The extract from U. maydis grown in fully U-¹³C-labeled glucose (Sigma-Aldrich) was used as internal standard. The absolute concentrations of intracellular metabolites in the samples were calculated by using ¹²C/¹³C ratio-based calibration curves.