MetaboLights

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ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/m_MTBLS12296_LC-MS_negative_reverse-phase_metabolite_profiling_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/m_MTBLS12296_LC-MS_positive_reverse-phase_metabolite_profiling_v2_maf.tsvftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/i_Investigation.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/a_MTBLS12296_LC-MS_positive_reverse-phase_metabolite_profiling.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/s_MTBLS12296.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/a_MTBLS12296_LC-MS_negative_reverse-phase_metabolite_profiling.txtftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_QC03.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJD1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJD1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PY3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_QC03.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJ1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJ2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJ2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJD2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_QC02.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_QC02.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PYD3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PY2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJ3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PYD3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PY3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJ3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PY2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJD2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_QC01.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PYD2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_QC01.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PJD3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PY1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJD3.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PYD2.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PY1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/NEG_Hg17SHQ_PYD1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PYD1.rawftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296/FILES/POS_Hg17SHQ_PJ1.rawprimaryOK200phloemleafQuality Controlftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS12296mass spectrometry assayThe pretreatment of LC-MS raw data was performed by Progenesis QI (Waters Corporation, Milford, USA) software, and a 3D data matrix in CSV format was exported. The information in this 3D matrix included: sample information, metabolite name and mass spectral response intensity. Internal standard peaks, as well as any known false positive peaks (including noise, column bleed and derivatized reagent peaks), were removed from the data matrix, deredundant and peak pooled. At the same time, the metabolites were identified by searching Self-built plant-specific metabolite database (MJDBPM). Metabolic features detected at least 80% in any set of samples were retained. After filtering, minimum metabolite values were imputed for specific samples in which the metabolite levels fell below the lower limit of quantitation, and each Metabolic features were normalized by sum. To reduce the errors caused by sample preparation and instrument instability, the response intensity of the sample mass spectrum peaks was normalized by the sum normalization method, and then the normalized data matrix was obtained. Meanwhile, variables with relative standard deviation (RSD) > 30% of QC samples were removed, and log10 processing was performed to obtain the final data matrix for subsequent analysis.Briefly, 100 mg solid sample was added to a 2 mL centrifuge tube and a 6 mm diameter grinding bead was added. Next 800 μL of extraction solution (methanol:water, 4:1, v:v) containing 4 internal standards (0.02 mg/mL L-2-chlorophenylalanine, etc) were used for metabolite extraction. Samples were ground by the Wonbio-96c (Shanghai wanbo biotechnology co., LTD) frozen tissue grinder for 6 min (-10 °C, 50 Hz), followed by low-temperature ultrasonic extraction for 30 min (5 °C, 40 kHz). The samples were left at -20 °C for 30 min, centrifuged for 15 min (4 °C,13,000 x g), and the supernatant was transferred to the injection vial for LC-MS/MS analysis.PopulusThe pretreatment of LC-MS raw data was performed by Progenesis QI (Waters Corporation, Milford, USA) software, and a 3D data matrix in CSV format was exported. The information in this 3D matrix included: sample information, metabolite name and mass spectral response intensity. Internal standard peaks, as well as any known false positive peaks (including noise, column bleed and derivatized reagent peaks), were removed from the data matrix, deredundant and peak pooled. At the same time, the metabolites were identified by searching Self-built plant-specific metabolite database (MJDBPM). Metabolic features detected at least 80% in any set of samples were retained. After filtering, minimum metabolite values were imputed for specific samples in which the metabolite levels fell below the lower limit of quantitation, and each Metabolic features were normalized by sum. To reduce the errors caused by sample preparation and instrument instability, the response intensity of the sample mass spectrum peaks was normalized by the sum normalization method, and then the normalized data matrix was obtained. Meanwhile, variables with relative standard deviation (RSD) > 30% of QC samples were removed, and log10 processing was performed to obtain the final data matrix for subsequent analysis.Feeding by beetle adultshhsunhq@163.comhttps://www.ebi.ac.uk/metabolights/MTBLS12296Male and female adults starved for 24 h were placed on poplars, with one male and one female beetle (Anoplophora glabripennis) on each Populus deltoides ‘Shalinyang’(PdS). The no-insect treatment was used as the control group. After 48 h of feeding, leaves and phloem of PdS were collected, and samples of the control group were collected from the same location. The samples were frozen in liquid nitrogen and stored in a -80 °C refrigerator for subsequent analysis.MetaboLightsPublicMetabolomicsLiquid Chromatography MS - negative - reverse phaseLiquid Chromatography MS - positive - reverse phasebeetlemetabolomic profilingPopulusThe LC-MS/MS analysis of sample was conducted on a Thermo UHPLC-Q Exactive system equipped with an ACQUITY BEH C18 column (100 mm x 2.1 mm i.d., 1.7 μm; Waters, USA) at Majorbio Bio-Pharm Technology Co. Ltd (Shanghai, China).The mobile phases consisted of 0.1% formic acid in water:acetonitrile (2:98, v/v) (solvent A) and 0.1% formic acid in acetonitrile (solvent B). The gradient conditions are as follows: 0.0-0.5 min, mobile phase B was maintained at 2%; 0.5-7.5 min, mobile phase B was increased from 2% to 35%; 7.5-13.0 min, mobile phase B was increased from 35% to 95%; 13.0-14.4 min, mobile phase B was maintained at 95%; 14.4-14.5 min, mobile phase B was decreased from 95% to 2%; 14.5-16.0 min, mobile phase B was maintained at 2%. The flow rate was 0.40 mL/min and the column temperature was 40 °C. The LC-MS/MS analysis of sample was conducted on a Thermo UHPLC-Q Exactive system equipped with an ACQUITY BEH Amide column (100 mm x 2.1 mm i.d., 1.7 μm; Waters, USA) at Majorbio Bio-Pharm Technology Co. Ltd (Shanghai, China). The flow rate was 0.40 mL/min and the column temperature was 40 °C. The injection volume was 3 μL.Transcriptomic and metabolomic data of Populus deltoides ‘Shalinyang’ (PdS) response to feeding of Anoplophora glabripennis adults.beetlemetabolomic profilingPopulusSun Hui-QuanHebei UniversityThe UPLC system was coupled to a Thermo UHPLC-Q Exactive Mass Spectrometer equipped with an electrospray ionization (ESI) source operating in positive mode and negative mode. The optimal conditions were set as followed: source temperature at 400 °C; sheath gas flow rate at 40 arb; Aux gas flow rate at 10 arb; ion-spray voltage floating (ISVF) at -2800 V in negative mode and 3500 V in positive mode, respectively; Normalized collision energy, 20-40-60 V rolling for MS/MS. Full MS resolution was 70000, and MS/MS resolution was 17500. Data acquisition was performed with the Data Dependent Acquisition (DDA) mode. The detection was carried out over a mass range of 70-1050 m/z.falseTranscriptomic and metabolomic data of Populus deltoides ‘Shalinyang’ (PdS) response to feeding of Anoplophora glabripennis adultsPopulus deltoides ‘Shalinyang’ (PdS), a vital species for artificial shelterbelts in the arid regions of northwest China, has shown resistance to the destructive stem-boring beetle Anoplophora glabripennis Motschulsky (Asian longhorned beetle, ALB). However, comprehensive research in this area is still lacking. This study compared PDS leaves and phloem tissues before and after ALB adult feeding, utilizing untargeted metabolomics (LC-MS/MS) and transcriptomics (RNA-Seq) methods. The investigation identified a total of 3,552 metabolites across the 12 samples. Transcriptomic sequencing generated 82.52 Gb of clean data, with an average of 6.88 Gb per sample, and annotated 33,429 expressed genes. These data provide fundamental and valuable information for understanding how the resistant species PdS responds to ALB adult infestation. Furthermore, they can be utilized in future studies to explore the interaction mechanisms between poplar species and ALB and investigate the insect resistance mechanisms of PdS.2026-03-252025-03-07MTBLS12296