Metabolic profile elucidation after in vitro biotransformation of Herniaria hirsuta by an innovative data analysis strategy for dynamic multiclass experiments

Urinary stone disease is considered as an important healthcare problem. An aqueous extract of the aerial parts of H. hirsuta (Caryophyllaceae) is a widely used herbal medicine. However, little is known about the active compounds and the mechanism of action. [1],[2] Previous phytochemical research on Herniaria species revealed the presence of saponins, flavonoids and coumarins. [2] It is suggested that metabolites of phytochemicals present in H. hirsuta (most likely saponins) are responsible for the beneficial effects.

In vitro gastrointestinal biotransformation followed by automated data analysis was optimized using hederacoside C as a model compound for saponins. Samples were analyzed with UHPLC-PDA-HRMS before, during and after biotransformation.

To analyze the longitudinal LC-MS data, XCMS and EDGE were used to extract significant differential profiles from the raw data. [3],[4] An interactive Shiny app was developed in R to rate the quality of the resulting 10307 features. These ratings were used to train a random forest model. [5] A performance analysis revealed a high capability of the model to correctly predict experts response (AUC 0.93 with 10 fold cross validation). The workflow revealed the biotransformation of hederacoside C. All major metabolites were ranked in the top 100 out of 10307 features.

When subjecting an extract of H. hirsuta to the experimental workflow, herniariasaponin H, the most abundant saponin, showed stepwise elimination of sugar moieties resulting in medicagenic acid. Hepatic biotransformation using S9 fractions of this aglycon resulted in hydroxylated and oxydated metabolites. This insight smooths the path for hepatic biotransformation of the extract.

• References

• 1 Atmani F, Slimani Y. , et al. Effect of aqueous extract from Herniaria hirsuta L. on experimentally nephrolithiasic rats. J Ethnopharmacol 2004; 95 (01) : 87-93
• 2 van Dooren I, Foubert K. , et al. Saponins and Flavonoids from an Infusion of Herniaria hirsuta . Planta Med 2016; 82 (18) : 1576-1583
• 3 Storey JD, Xiao W. , et al. Significance analysis of time course microarray experiments. PNAS 2005; 102 (36) : 12837-12842
• 4 Leek JT, Monsen E. , et al. EDGE: extraction and analysis of differential gene expression. Bioinformatics 2005; 22 (04) : 507-508
• 5 Beirnaert C, Peeters L, Meysman P. , et al. Using expert driven machine learning to enhance dynamic metabolomics data analysis. Metabolites 2019; 9 (03) : 54