Chemicalome and metabolome profiling of polymethoxylated flavonoids in Citri Reticulatae Pericarpium based on an integrated strategy combining background subtraction and modified mass defect filter in a Microsoft Excel Platform.

Detection of metabolites in complex biological matrixes is a great challenge because of the background noise and endogenous components. Herein, we proposed an integrated strategy that combined background subtraction program and modified mass defect filter (MMDF) data mining in a Microsoft Excel platform for chemicalome and metabolome profiling of the polymethoxylated flavonoids (PMFs) in Citri Reticulatae Pericarpium (CRP). The exogenously-sourced ions were firstly filtered out by the developed Visual Basic for Applications (VBA) program incorporated in the Microsoft Office. The novel MMDF strategy was proposed for detecting both target and untarget constituents and metabolites based on narrow, well-defined mass defect ranges. The approach was validated to be powerful, and potentially useful for the metabolite identification of both single compound and homologous compound mixture. We successfully identified 30 and 31 metabolites from rat biosamples after oral administration of nobiletin and tangeretin, respectively. A total of 56 PMFs compounds were chemically characterized and 125 metabolites were captured. This work demonstrated the feasibility of the integrated approach for reliable characterization of the constituents and metabolites in herbal medicines.