Metabolic profiling of Gegen-Qinlian Decoction and its modified formula in gut microbiota from healthy individuals and ulcerative colitis patients with different syndromes using UHPLC-QTOF-MS/MS and an in vitro incubation model.

GQD and MGQD were stable in artificial gastrointestinal fluids but underwent extensive gut microbiota-mediated biotransformation.

• UHPLC-QTOF-MS/MS was used to profile metabolic changes in both artificial gastrointestinal fluids (AGF) and gut microbiota incubation models.
• GQD/MGQD remained stable in AGF with no significant metabolic transformation detected.
• Gut microbiota from healthy individuals (HI), UC patients with spleen deficiency syndrome (UC-SDS), and UC patients with damp-heat syndrome (UC-DHS) were all capable of metabolizing GQD/MGQD constituents.

The three gut microbiota groups metabolized different numbers of GQD and MGQD prototype compounds.

• HI gut microbiota metabolized 52 GQD and 60 MGQD prototype compounds.
• UC-SDS gut microbiota metabolized 39 GQD and 43 MGQD prototype compounds.
• UC-DHS gut microbiota metabolized 35 GQD and 35 MGQD prototype compounds.
• 25 (GQD) and 28 (MGQD) metabolites were common to all three groups.

Healthy individuals demonstrated the highest metabolic capability toward GQD/MGQD, followed by UC-SDS and then UC-DHS patients.

• The HI group showed superior metabolic rates, lower residual compounds, and higher metabolite abundance compared to both UC groups.
• UC-SDS gut microbiota showed intermediate metabolic capability between HI and UC-DHS.
• UC-DHS gut microbiota exhibited the lowest metabolic capability among the three groups.

All three gut microbiota groups exhibited similar core metabolic pathways, predominantly deglycosylation to produce aglycones.

• Deglycosylation was the predominant metabolic pathway across HI, UC-SDS, and UC-DHS groups.
• The addition of two herbs in MGQD did not alter the core metabolic pathways of GQD-sourced constituents.
• The modified formula (MGQD) did inhibit the biotransformation of certain specific constituents.

Glycoside metabolic rates depended on structural features, with flavonoid glycosides metabolized fastest among glycoside types.

• Among glycoside classes, flavonoid glycosides were metabolized fastest, followed by phenylethanoid glycosides and then saponins.
• Among sugar moieties, glucosides were metabolized fastest, followed by glucuronides, xylosides, arabinosides, and apiosides in descending order.
• This structure-dependent metabolic rate pattern was consistent across the different gut microbiota groups studied.

A custom-built MS data analysis workflow was developed to characterize metabolic profiles of complex herbal formulas.

• The workflow characterized metabolized prototype constituents, metabolites, metabolic pathways, and metabolic rates.
• The workflow was described as providing 'a practical analytical workflow for herb-microbiota interaction research.'
• UHPLC-QTOF-MS/MS was employed as the analytical platform for the workflow.