DOI: 10.20350/digitalcsic/15427
title: LC-MS and LC-MS/MS dataset for the paper ???Cao A, Gesteiro N, Santiago R, Malvar RA and Butr??n A (2023) Maize kernel metabolome involved in resistance to fusarium ear rot and fumonisin contamination. Front. Plant Sci. 14:1160092"

description: [Description of methods used for collection/generation of data] The untargeted metabolomic analysis was conducted by ultra-high-performance liquid chromatography (UHPLC) (Ultimate3000 LC; Thermo Scientific) coupled to a quadrupole-time-of-flight mass spectrometer (QTOF-MS) equipped with an electrospray ionization source (ESI) (Bruker Compact; Bruker Daltonics). Samples (5 ??l injection volume) were separated in an Intensity Solo 2 C18 column (1.7 ??m, 2.1?? 100 mm; Bruker Daltonics) at 35??C. A binary solvent system consisted of 0.1% of formic acid on water (solvent A) and acetonitrile (solvent B) with a 0.4 ml/min flow rate was used with the following gradient conditions: 0 min, 3% B; 4 min, 3% B; 16 min, 25% B; 25min, 80% B; 30 min, 100% B; 32 min, 100% B; return to initial conditions at 33 min (3% B) and maintain until 36 min. The MS acquisition was performed in both negative and positive ionization modes for full scan and auto MS/MS, in a mass scan range of m/z 100-1200. Specific conditions used were: gas flow 9 L/min, nebulizer pressure 38 psi, dry gas 9 L/min, and dry temperature 220??C; capillary and end plate offset were set to 4500 and 500 V, respectively. MS/MS analysis was performed by using different collision energy ramps to cover a range from 15 to 50 eV. The instrument was calibrated externally with a solution of 1mM sodium formate/acetate in 2-propanol:water 50:50 with 0.2% formic acid directly infused to the source. A calibration solution of formate and acetate clusters was injected at the beginning of each run.
description: The present dataset belongs to an untargeted metabolomic study proposed to uncover pathways implicated in resistance to Fusarium ear rot (FER) and fumonisin contamination in the maize kernel and to look for possible biomarkers, using maize inbreds genetically related but with contrasting levels of resistance. The dataset are LC-MS and LC-MS/MS experimental data for untargeted metabolomics of maize immature kernels extracts from eight recombinant inbred lines (RILs) with different level of resistance to FER and fumonisin accumulation at two sampling dates (3 and 10 days) after Fusarium verticillioides inoculation (dat). Spectral data were adquired in a LC-ESI-QTOF mass spectrometer (Bruker Daltonics). MS acquisition was performed in both negative and positive ionization modes for full scan and auto MS/MS, in a mass scan range of m/z 100-1200 with Bruker OTOF Control and DataAnalisys software (Bruker Daltonics). Raw data were converted to .mzML format with ProteoWizard MSConvert tool (Version: 3.0.23163-09bc765). FER and fumonisin resistant RILs are labeled as 1758, 1762, 1766, 1768; susceptible RILs are labeled as 1757, 1759, 1761, 1763. For each combination of RIL and sampling date three biological replicates were analized and can be found inside each RIL MS data .zip file. MS/MS data were obtained from a bulk of the 3 replicates for each RIL-sampling date combination and can be found in the MS/MS data .zip files. Discriminant metabolites between resistant and susceptible RILs were rather found at 10 than 3 dat. Differences for membrane lipid homeostasis, methionine metabolism, and indolacetic acid conjugation seemed highly relevant to distinguish between resistant and susceptible inbreds, confirming the polygenic nature of resistance to FER and fumonisin contamination in the maize kernels. Some specific metabolites such as the polyamine spermidine and/or the alkaloid isoquinoline seemed to be promising indirect selection traits to improve resistance to FER and reduce fumonisin accumulation.
description: BLANK_MS_Negative.zip BLANK_MS_Positive.zip RIL_1757_10d_MS_Negative.zip RIL_1757_10d_MS_Positive.zip RIL_1758_10d_MS_Negative.zip RIL_1758_10d_MS_Positive.zip RIL_1758_3d_MS_Negative.zip RIL_1758_3d_MS_Positive.zip RIL_1759_10d_MS_Negative.zip RIL_1759_10d_MS_Positive.zip RIL_1759_3d_MS_Negative.zip RIL_1759_3d_MS_Positive.zip RIL_1761_10d_MS_Negative.zip RIL_1761_10d_MS_Positive.zip RIL_1761_3d_MS_Negative.zip RIL_1761_3d_MS_Positive.zip RIL_1762_10d_MS_Negative.zip RIL_1762_10d_MS_Positive.zip RIL_1762_3d_MS_Negative.zip RIL_1762_3d_MS_Positive.zip RIL_1763_10d_MS_Negative.zip RIL_1763_10d_MS_Positive.zip RIL_1763_3d_MS_Negative.zip RIL_1763_3d_MS_Positive.zip RIL_1766_10d_MS_Negative.zip RIL_1766_10d_MS_Positive.zip RIL_1766_3d_MS_Negative.zip RIL_1766_3d_MS_Positive.zip RIL_1768_10d_MS_Negative.zip RIL_1768_10d_MS_Positive.zip RIL_1768_3d_MS_Negative.zip RIL_1768_3d_MS_Positive.zip RILs_10d_MSMS_Negative.zip RILs_10d_MSMS_Positive.zip RILs_3d_MSMS_Negative.zip RILs_3d_MSMS_Positive.zip