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tion_protocol>&lt;p>This project uses the local self-built standard database (in-house database (Shanghai Applied Protein Technology)) of Zhongke New Life to search the database and pass the retention time and molecular mass of the metabolites in the local database (the molecular mass error is within &amp;lt;25 ppm) , secondary fragmentation spectrum, collision energy and other information are matched, the structure of metabolites in biological samples is identified, and the identification results are strictly checked and confirmed manually. The identification level is above Level 2.&lt;/p></metabolite_identification_protocol><repository>MetaboLights</repository><study_status>Public</study_status><ptm_modification></ptm_modification><instrument_platform>Liquid Chromatography MS - negative - reverse phase</instrument_platform><instrument_platform>Liquid Chromatography MS - positive - reverse phase</instrument_platform><chromatography_protocol>&lt;p>The samples were separated by an Agilent 1290 Infinity LC ultra-high performance liquid chromatography system (UHPLC) HILIC column; column temperature 25 °C; flow rate 0.5 mL/min; injection volume 2 μL; mobile phase composition A: water + 25 mM ammonium acetate + 25 mM ammonia, B: acetonitrile; gradient elution program as follows: 0.0-0.5 min, 95% B; 0.5-7.0 min, B linearly changed from 95% to 65%; 7,0-8.0 min, B Linear change from 65% to 40%; 8.0-9.0 min, B maintained at 40%; 9.0-9.1 min, B linearly changed from 40% to 95%; 9.1-12.0 min, B maintained at 95%; samples were placed in a 4 °C autosampler throughout the analysis. In order to avoid the influence caused by the fluctuation of the instrument detection signal, the continuous analysis of the samples is carried out in random order. QC samples are inserted into the sample queue to monitor and evaluate the stability of the system and the reliability of the experimental data.&lt;/p></chromatography_protocol><publication>Combined transcriptome and metabolome analysis reveals the regulatory network of histidine kinase QseC in the two-component system of Glaesserella parasuis.</publication><submitter_name>lvqin he</submitter_name><submitter_affiliation>southwest medical university</submitter_affiliation><organism_part>thallus</organism_part><technology_type>mass spectrometry</technology_type><disease></disease><extraction_protocol>&lt;p>After the sample is slowly thawed at 4 °C, add an appropriate amount of sample to the pre-cooled methanol/acetonitrile/water solution (2:2:1, v/v), and vortex to mix. Ultrasound at low temperature for 30 min, let stand at -20 °C for 10 min, and centrifuge at 14,000 rpm/min at 4 °C for 20 min. Take the supernatant and vacuum dry, add 100 μL of acetonitrile aqueous solution (acetonitrile:water, 1:1, v/v) for reconstitution during mass spectrometry, vortex, centrifuge at 14,000 rpm/min at 4 °C for 15 min, and take the supernatant for sample analysis.&lt;/p></extraction_protocol><organism>Glaesserella parasuis</organism><full_dataset_link>https://www.ebi.ac.uk/metabolights/MTBLS12504</full_dataset_link><author>Yan xuefeng. 425177126@qq.com.</author><author>He lvqin. southwest medical university, luzhou, sichuan, china. 1176044269@qq.com. 18328495366.</author><data_transformation_protocol>&lt;p>The raw data in .wiff / .wiff.scan format was converted to .mzXML format by ProteoWizard, and then XCMS software was used for peak alignment, retention time correction and peak area extraction. The data extracted by XCMS were firstly subjected to metabolite structure identification, data preprocessing, and then to experimental data quality evaluation, and finally to data analysis.&lt;/p></data_transformation_protocol><study_factor>Gene</study_factor><submitter_email>1176044269@qq.com</submitter_email><sample_collection_protocol>&lt;p>SMY1902 and ΔqseC were grown in TSB at 37 °C, with shaking to an OD600 of 0.8. In total 2 mL of bacterial culture were centrifuged at 4000 rpm, and the bacteria were collected in centrifuge tube. After washing the cells 3 times with sterile PBS, and freezing in liquid nitrogen for 1 h and store at -80 °C.&lt;/p></sample_collection_protocol><omics_type>Metabolomics</omics_type><study_design>qseC</study_design><study_design>Transcriptomics</study_design><study_design>Glaesserella parasuis</study_design><study_design>untargeted metabolites</study_design><curator_keywords>qseC</curator_keywords><curator_keywords>Transcriptomics</curator_keywords><curator_keywords>Glaesserella parasuis</curator_keywords><curator_keywords>untargeted metabolites</curator_keywords><mass_spectrometry_protocol>&lt;p>The primary and secondary spectra of the samples were collected using an AB Triple TOF 6600 mass spectrometer. The samples were separated by an Agilent 1290 Infinity LC ultra-high performance liquid chromatography system (UHPLC) and then analyzed by a Triple TOF 6600 mass spectrometer (AB SCIEX) using electrospray ionization (ESI) in positive and negative ion modes, respectively. The ESI source setting parameters are as follows: Nebulizer Gas Auxiliary Heater Gas 1 (Gas1): 60, Auxiliary Heater Gas 2 (Gas2): 60, Curtain Gas (CUR): 30 psi, Ion Source Temperature: 600 °C, Spray Voltage (ISVF) ±5500 V (both positive and negative modes); primary mass-to-charge ratio detection range: 60-1000 Da, secondary product ion mass-to-charge ratio detection range: 25-1000 Da, primary mass-to-charge scanning accumulation time: 0.20 s/spectra, MS MS scan accumulation time 0.05 s/spectra; MS MS was acquired using data-dependent acquisition mode (IDA), and peak intensity value screening mode was used, declustering voltage (DP): ±60 V (both positive and negative modes), collision energy: 35 ± 15 eV, IDA settings are as follows: Dynamically excluded isotope ion range: 4 Da, 10 fragment spectra were collected per scan.&lt;/p></mass_spectrometry_protocol><metabolite_name>5-Hydroxyindole-2-carboxylic acid</metabolite_name><metabolite_name>2-cyano-3-(3,4-dimethoxyphenyl)acrylic acid</metabolite_name><metabolite_name>J147</metabolite_name><metabolite_name>Nicotinamide N-oxide</metabolite_name><metabolite_name>dTMP</metabolite_name></additional><is_claimable>false</is_claimable><name>Combined transcriptome and metabolome analysis reveals the regulatory network of histidine kinase QseC in the two-component system of Glaesserella parasuis</name><description>Glaesserella parasuis is the causative agent of Glässer's disease in pigs, which can lead to polyserositis, arthritis, and meningitis. This study used transcriptome and metabolomics sequencing techniques to investigate the mechanism of action of qseC gene in Glaesserella parasuis. Transmission electron microscopy revealed that the ΔqseC mutant strain exhibited localized dissolution and rupture of the cell wall and membrane. The cytoplasmic wall separation was obvious, and the cytoplasm appeared sparse. These findings suggest an imbalance in membrane homeostasis。Metabolomics analysis identified 819 metabolites, among which 24 metabolites showed significant differences under positive ion mode, including upregulation of Methionine, Prostaglandin F2 α -1-glyceryl ester, and downregulation of Hypoxantine, UDP, and others. There were significant differences in 36 metabolites under negative ion mode. KEGG enrichment analysis revealed abnormalities in pathways related to amino acid synthesis, lipid metabolism, and quorum sensing. Transcriptomic analysis identified 663 differentially expressed genes, including upregulation of membrane synthesis-related genes (such as plsB and wecA) and downregulation of virulence factors (such as hrpA and pilW). This study systematically analyzed the regulatory networks of differentially expressed genes and metabolites by integrating transcriptome and metabolome data. Key genes such as plsB and wecA form a strong association network with metabolites such as methionine and prostaglandin F2α-1-glyceride. KEGG pathway co-enrichment analysis showed that amino acid synthesis (such as cysteine/methionine metabolism) and purine metabolism pathways were co regulated in positive ion mode, while peptidoglycan synthesis and glycerophospholipid metabolism were significantly enriched in negative ion mode. This study constructed a cross-omics regulatory map of “gene-metabolism” mediated by QseC, revealing the global regulatory role of QseC in Glaesserella parasuis, providing a theoretical basis for the development of new prevention and control strategies against Glaesserella parasuis infection.</description><dates><publication>2025-08-11</publication><submission>2025-05-20</submission></dates><accession>MTBLS12504</accession><cross_references><MetaboLights>MTBLC17013</MetaboLights><MetaboLights>MTBLC89640</MetaboLights><MetaboLights>MTBLC183702</MetaboLights><MetaboLights>MTBLC167509</MetaboLights><MetaboLights>MTBLC192601</MetaboLights><ChEBI>CHEBI:17013</ChEBI><ChEBI>CHEBI:89640</ChEBI><ChEBI>CHEBI:183702</ChEBI><ChEBI>CHEBI:167509</ChEBI><ChEBI>CHEBI:192601</ChEBI></cross_references></HashMap>