<HashMap><database>MetaboLights</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Tabular>ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13652/m_MTBLS13652_LC-MS_alternating_reverse-phase_metabolite_profiling_v2_maf.tsv</Tabular><Txt>ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13652/s_MTBLS13652.txt</Txt><Txt>ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13652/i_Investigation.txt</Txt><Txt>ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13652/a_MTBLS13652_LC-MS_alternating_reverse-phase_metabolite_profiling.txt</Txt></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><ftp_download_link>ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS13652</ftp_download_link><organism_part>Serum</organism_part><technology_type>mass spectrometry assay</technology_type><metabolite_identification_protocol>&lt;p>The MRM parameters for each of the targeted analytes were optimized using flow injection analysis, by injecting the standard solutions of the individual analytes, into the ESI source of the mass spectrometer. Several most sensitive transitions were used in the MRM scan mode to optimize the collision energy for each Q1/Q3 pair (Table S2). Among the optimized MRM transitions per analyte, the Q1/Q3 pairs that showed the highest sensitivity and selectivity were selected as “quantifier” for quantitative monitoring. The additional transitions acted as “qualifier” for the purpose of verifying the identity of the target analytes. Analyst (1.7.3, SCIEX) and Biotree Biobud (v2.0.4) were employed for MRM data acquisition.&lt;/p></metabolite_identification_protocol><disease></disease><extraction_protocol>&lt;p>The samples were thawed in ice water bath and was vortexed for 30 s. 50 μL of liquid samples was mixed with 200 μL (ACN:MeOH=1:1, containing internal standards) and were vortexed for 30 s. After sonication in ice-water bath for 15 min, samples were incubated at -40 °C for 1 h. The supernatant was transferred to an autosampler vial for analysis.(Gomez et al. 2020; Hagio, Matsumoto, and Ishizuka 2011)&lt;/p></extraction_protocol><organism>Homo sapiens</organism><data_transformation_protocol>&lt;p>The MRM parameters for each of the targeted analytes were optimized using flow injection analysis, by injecting the standard solutions of the individual analytes, into the ESI source of the mass spectrometer. Several most sensitive transitions were used in the MRM scan mode to optimize the collision energy for each Q1/Q3 pair (Table S2). Among the optimized MRM transitions per analyte, the Q1/Q3 pairs that showed the highest sensitivity and selectivity were selected as “quantifier” for quantitative monitoring. The additional transitions acted as “qualifier” for the purpose of verifying the identity of the target analytes. Analyst (1.7.3, SCIEX) and Biotree Biobud (v2.0.4) were employed for MRM data acquisition.&lt;/p></data_transformation_protocol><study_factor>Treatment</study_factor><metabolights_link>https://www.ebi.ac.uk/metabolights/MTBLS13652</metabolights_link><submitter_email>3277728362@qq.com</submitter_email><sample_collection_protocol>&lt;p>After centrifugation of the collected whole blood, a portion of the serum was aliquoted into cryovials, stored on dry ice, and subsequently subjected to analysis.&lt;/p></sample_collection_protocol><repository>MetaboLights</repository><study_status>Public</study_status><ptm_modification></ptm_modification><omics_type>Metabolomics</omics_type><instrument_platform>Liquid Chromatography MS - alternating - reverse-phase</instrument_platform><study_design>Bile Salt</study_design><study_design>bile acid metabolic process</study_design><study_design>phytosterols</study_design><study_design>Dyslipidemia</study_design><study_design>Gut microbiota (beta diversity)</study_design><study_design>targeted metabolites</study_design><study_design>blood lipids</study_design><chromatography_protocol>&lt;p>The UHPLC separation was carried out using Agilent 1290 UPLC, equipped with a ACQUITY UPLC BEH C18 Column(1.7 μm, 2.1 mm all_fetch_status all_status eb_eye_copy_status eb_eye_entry_counts eb_eye_fetch_status eb_eye_metabolights_compounds.copy eb_eye_metabolights_studies.copy e_fetch_status europe_PMC_metabolights_studies.copy europe_PMC_metabolights_studies.xml studies.copy study.xml tail.xml thomsonreuters_metabolights_studies.copy thomsonreuters_metabolights_studies.xml 150 mm). The mobile phase A was 0.01% formic acid in water, and the mobile phase B was 1 mM ammonium formate in 95% methanol. The column temperature was set at 45 °C. The auto-sampler temperature was set at 6 °C and the injection volume was 2 μL.&lt;/p></chromatography_protocol><publication>Dietary germ oil-derived phytosterols ameliorate hyperlipidemia by suppressing bile salt hydrolase-producing gut microbiota to enrich taurohyodeoxycholic acid.</publication><curator_keywords>Bile Salt</curator_keywords><curator_keywords>bile acid metabolic process</curator_keywords><curator_keywords>phytosterols</curator_keywords><curator_keywords>Dyslipidemia</curator_keywords><curator_keywords>Gut microbiota (beta diversity)</curator_keywords><curator_keywords>targeted metabolites</curator_keywords><curator_keywords>blood lipids</curator_keywords><submitter_affiliation>Southeast university</submitter_affiliation><submitter_name>Jiayue Xia</submitter_name><mass_spectrometry_protocol>&lt;p>Triple Quad 6500+ Mass Spectrometer (SCIEX, USA), equipped with an electrospray ionization interface, was applied for assay development. Typical ion source parameters were: Ion Spray Voltage = +5500/-4500 V, Ion Source Gas 1=50 psi, Ion Source Gas 2=50 psi, Temperature = 450 °C, Curtain Gas=35 psi.&lt;/p></mass_spectrometry_protocol></additional><is_claimable>false</is_claimable><name>Dietary germ oil-derived phytosterols ameliorate hyperlipidemia by suppressing bile salt hydrolase-producing gut microbiota to enrich taurohyodeoxycholic acid_Serum bile acid profile in individuals with borderline elevated cholesterol</name><description>&lt;p>Dyslipidemia is a major cardiovascular risk factor. While dietary phytosterols are known to lower cholesterol, the mechanisms involving the gut-liver axis are not fully understood. By integrating human clinical trials and mechanistic animal models, we demonstrate that phytosterols improve lipid profiles by modulating the gut microbiota-bile acid-farnesoid X receptor (FXR) axis. Phytosterol supplementation suppresses the abundance of bile salt hydrolase-active bacteria, such as Lactobacillus, leading to reduced intestinal enzymatic activity and the accumulation of conjugated bile acids. These bile acids act as intestinal FXR antagonists, downregulating the ileal fibroblast growth factor 15 (FGF15) signaling pathway. This suppression relieves feedback inhibition on hepatic bile acid synthesis, thereby accelerating cholesterol catabolism. Fecal microbiota transplantation validates that these metabolic benefits are gut microbiota dependent. Together, these findings link dietary phytosterols to host lipid metabolism through gut microbial bile acid regulation, providing a mechanistic framework for individualized, food-based strategies to manage dyslipidemia.&lt;/p></description><dates><publication>2026-03-17</publication><submission>2026-01-11</submission></dates><accession>MTBLS13652</accession><cross_references/></HashMap>