Integrating 3D Chromatography With Orbitrap Mass Spectrometry to Profile the Chemical Constituents in JTTZ Formula and Investigate Plasma Pharmacokinetic Changes in Obese Rats

ABSTRACT

Introduction

Chemical profiling and exposure of multicomponent Chinese medicine formula (CMF) are essential for understanding the multitarget treatment mechanism, as they consist of bioactive substances with varying polarities, molecular weights, and charges. However, the chemical composition of CMF is highly intricate, primarily due to the presence of multiple herbs, rendering chemical identification a challenging task.

Objective

Jiangtang Tiaozhi formula (JTTZ), commonly used for early diabetes intervention, was chosen to validate our standardized analytical strategy integrating offline three ‐ dimensional (3D) chromatography–DDA (data‐dependent acquisition) with a precursor ion list (PIL)‐comparative pharmacokinetic study.

Materials and Methods

We have implemented an offline 3D chromatography coupled with data‐dependent MS2 acquisition, including PIL, to obtain comprehensive compound information within JTTZ. We then utilized the MRM quantification approach to determine the pharmacokinetics of the 13 major circulating constituents identified in JTTZ. Finally, the variations in pharmacokinetic parameters between high‐fat diet (HFD) and normal chow diet (NCD) rat models are further illustrated by comparative pharmacokinetics.

Result

Using an offline 3D chromatography platform, 186 compounds were identified in JTTZ, as opposed to the 68 compounds detected with classical one‐dimensional (1D) LC–MS technology. Through the chemical profiling results of the multidimensional chromatography, we found 41 components of JTTZ absorbed in plasma. We then utilized the MRM quantification approach to determine the pharmacokinetics of the 13 major circulating constituents identified in JTTZ. Finally, the variations in pharmacokinetic parameters between HFD and normal chow diet (NCD) rat models are further illustrated by comparative pharmacokinetics. In the HFD group, the T _1/2 values of epiberberine were higher than those in the NCD group.

Conclusion

The results show that the pathological state caused by a HFD changed the plasma pharmacokinetics of jatrorrhizine, mangiferin, and timosaponin BII in JTTZ, providing drug exposure evidence for the involvement of JTTZ in early diabetes intervention. The stepwise pipeline for the “offline 3D chromatography‐DDA acquisition method with PIL‐comparative pharmacokinetic study” in the case study of JTTZ has the potential to reveal the exposure profile of other CMFs, from compound identification to pharmacokinetic analysis.

Short abstract

An offline three‐dimensional chromatography workflow integrating ion‐exchange, HILIC, and reversed‐phase separations was coupled with Q‐Orbitrap mass spectrometry for chemical profiling of the multi‐herb Jiangtang Tiaozhi formula (JTTZ). Data‐dependent acquisition guided by a precursor ion list identified 186 compounds, compared with 68 by conventional 1D LC‐MS. From this chemical library, 41 prototype circulating constituents were characterized in rat plasma, and a validated MRM assay revealed that high‐fat‐diet‐induced obesity significantly altered the pharmacokinetics of jatrorrhizine, mangiferin, and timosaponin BII.

1. Introduction

Chinese medicine formula (CMF) has been widely used for centuries in traditional healthcare systems around the world and is still the main traditional remedies in some Asian countries [1]. Identifying bioactive natural products from CMF is essential for explaining its clinical efficacy and supporting drug development [2, 3]. However, the chemical composition of CMF is highly complex, primarily due to the inclusion of multiple herbal constituents, which makes chemical identification a challenging endeavor [4, 5, 6]. Hence, multidimensional chromatography combined with the reasonable scanning strategy of high‐resolution mass spectrometry was developed for the detection of trace components [7, 8]. Two‐dimensional liquid chromatography (2D‐LC) has emerged as a powerful tool for analyzing TCM formula, offering significantly improved peak capacity and separation power compared to conventional 1D methods [9]. Building on these advances, Subinuer Yasen et al. [10] established an offline HILIC (hydrophilic interaction liquid chromatography) × RP (reversed‐phase) LC–MS approach, which was employed for the comprehensive characterization of triterpenoid saponins in RPJ, leading to the identification of 307 saponins. The technique has been successfully applied to various aspects of TCM analysis, including quality control, fingerprinting, and bioactive compound identification. However, even 2D‐LC may not provide sufficient resolution for the most complex TCM formula. This has led to the development of 3D chromatography approaches [11]. The addition of a third separation dimension can dramatically increase peak capacity and provide a more comprehensive chemical profiling [12]. This approach integrates three distinct separation mechanisms, including reversed‐phase chromatography (RPC), HILIC, and ion‐exchange chromatography (IEC), to facilitate the characterization of chemical constituents in CMF. To further analyze the separated compounds, appropriate data acquisition strategies are essential. The classical methods of acquiring data for nontargeted metabolite analysis are data‐dependent acquisition (DDA) and data‐independent acquisition (DIA) acquisition modes. DIA is superior due to its high coverage and identification reproducibility, but it often results in false‐positive results when the software matches precursor and product ions. To address this limitation, the DDA method plays a crucial role in establishing the correlation between precursor and product ions. This approach involves creating a target list of ions of interest based on prior knowledge, and the incorporation of preferred precursor ion lists (PIL) into DDA workflows has emerged as a powerful strategy [13]. In addition to the PIL‐enhanced strategy, it is crucial to optimize the parameters for DDA experiments to enhance MS/MS coverage and ultimately improve the rate of identification in untargeted methods. Among these parameters, collision energy, ion capillary temperature, spray voltage, and AGC target values are particularly critical, as they directly influence ion fragmentation efficiency and spectral quality [14]. Therefore, our study focused on systematically investigating the impact of these mass spectrometric parameters on constituent identification using an Orbitrap platform.

Notably, the identification of circulating constituents is crucial for understanding the pharmacological effects of traditional Chinese medicine. Only those compounds that enter the blood have the potential to reach target organs and exert therapeutic effects. Therefore, characterizing these constituents helps clarify the treatment mechanisms, and uncover potential active compounds. Based on the identification of circulating constituents, pharmacokinetic parameters (e.g., T _{1 / 2}, T _max, C _max, and AUC_{₀ ‐ t} ) can be calculated to characterize the in vivo behavior of major active compounds [15]. Building on this framework, Yahang Wang et al. [16] employed a pharmacokinetics‐based integrative strategy to demonstrate that multiple bioactive constituents in HQD collectively contribute to its anti‐liver fibrosis effects. In summary, 3D chromatography combined with the PIL‐enhanced DDA method is established, which not only discovers more chemical components in the formula, but also accurately identifies more circulating components and their plasma pharmacokinetic characteristics under the conditions of normal and various diseases.

The Jiangtang Tiaozhi formula, also known as JTTZ, has been used to treat patients with type 2 diabetes, obesity, and hyperlipidemia. It is safe and has shown a significant reduction in HbA1c levels, triglyceride levels, and body weight [17]. JTTZ originated from the classic formula‐Dahuang Huanglian Xiexin decoction, which was described in the Treatise on Febrile Diseases for the treatment of gastric heat syndrome. JTTZ consists of eight Chinese herbs, including Coptidis Rhizoma (Huanglian, HL, Coptis chinensis Franch.), Anemarrhenae Rhizoma (Zhimu, ZM, Anemarrhena asphodeloides Bunge.), Momordica charantia (Kugua, KG, Momordica charantia Linn.), Salvia Miltiorrhizae Radix Et Rhizoma (Danshen, DS, Salvia miltiorrhiza Bunge.), Schisandrae Chinensis Fructus (Wuweizi, WWZ, Schisandra Chinensis (Turcz.) Baill.), Red Yeast Rice (Hongqu, HQ, Monascus purpureus Went.), Aloe (Luhui, LH, Aloe vera (L.) Burm. f.), and Zingiberis Rhizoma (Ganjiang, GJ, Zingiber officinale Rosc.). Only 25 compounds were identified in the previous study using the HPLC method with chemical reference standards [18]. However, these identified compounds did not accurately represent the formula's composition, nor do they facilitate an understanding of the drug absorption process in vivo. For a comprehensive understanding of the chemical components in the JTTZ formula, 3D offline chromatography coupled with PIL data acquisition was applied. This method allows for the deep analysis of the circulating constituents of the JTTZ formula and the pharmacokinetic parameters of its potential active compounds under normal and obese conditions. By conducting comparative studies, we aim to understand the effects of obesity on the pharmacokinetics of the JTTZ formula, offering crucial insights to guide personalized medical interventions. This study seeks to develop a standardized protocol for evaluating the JTTZ formula, encompassing analysis of its chemical composition, circulating constituents, and pharmacokinetic behavior of major compounds.

2. Materials and Methods

2.1. Chemicals and Reagents

Acetonitrile (LC–MS grade), formic acid (FA, LC–MS grade), ammonium formate (AF, LC–MS grade), and methanol (LC–MS grade) were purchased from Thermo Fisher Scientific (Lenexa, KS, USA). Deionized water was obtained through the utilization of a Milli‐Q water purification system (Millipore Ltd. Bedford, MA, USA). Venusil SCX (4.6 mm × 250 mm, 5 μm, Agela), PhenoSphere SAX (4.6 mm × 150 mm, 5 μm, Phenomenex), Hypersil GOLD HILIC (4.6 mm × 250 mm, 5 μm, Thermo Fisher Scientific), Zorbax SB‐C₁₈ (2.1 mm × 100 mm, 1.8 μm, Agilent), InfinityLab Poroshell 120 AQ‐C₁₈ (2.1 mm × 100 mm, 2.7 μm, Agilent), Epic Biphenyl C₁₈ (2.1 mm × 100 mm, 1.8 μm, PerkinElmer), InfinityLab Poroshell 120 EC‐C₁₈ (2.1 mm × 100 mm, 2.7 μm, Agilent), ACQUITY UPLC BEH C₁₈ (2.1 mm × 100 mm, 1.7 μm, Waters), and ACQUITY UPLC HSS T3 (2.1 mm × 100 mm, 1.8 μm, Waters) were used. Coptidis Rhizoma, Anemarrhenae Rhizoma, Momordica charantia , Salvia Miltiorrhizae Radix Et Rhizoma, Schisandrae Chinensis Fructus, Red Yeast Rice, Aloe, and Zingiberis Rhizoma at the weight ratio of 5:10:10:3:2:2:2:2 were purchased from Tongrentang Pharmacy (Beijing, China), which were identified by the Pharmacy Department of the Affiliated Hospital of Changchun University of Chinese Medicine according to the Chinese Pharmacopeia (2020 edition). A total of 38 reference compounds, including aloin A, aloin B, gomisin C, cryptotanshinone, jatrorrhizine, coptisine, berberine, palmatine, epiberberine, berberrubine, neomangiferin, aloesin, timosaponin BII, rutin, quercetin, hesperidin, quercetin 7‐O‐glucoside, 6‐gingerol, protocatechuic acid, salvianolic acid A, schisandrin A, schisandrol, schisanhenol, schisandrol A, diosgenin, tanshinone I, tanshinone IIB, citrinin, timosaponin A1, hexahydrocurcumin, heriguard, 6‐shogaol, 8‐gingerol, 10‐gingerol, and mangiferin, and three internal standard (IS) compounds, such as diphenhydramine, calycosin, and bifendate, were purchased from Shanghai Yuanye Bio‐Technology Co. Ltd. (Shanghai, China). Other reagents were analytical grade.

2.2. JTTZ Extraction and Sample Preparation

Briefly, the eight Traditional Chinese medicines of JTTZ at the weight ratio of 5:10:10:3:2:2:2:2 were boiled in 10‐fold distilled water for 1 h two times to acquire the extraction supernatant. The collected supernatants were filtered, concentrated, and freeze‐dried to obtain JTTZ powder at a yield of 20.77%. The freeze‐dried JTTZ formula powder (200 mg) was weighed out into a 5 mL centrifuge tube and extracted with the aid of ultrasound for 1 h with three different solvent systems, including (A) hydrogen chloride (HCl) in 70% methanol solution (5%, v/v), (B) 70% methanol, and (C) ammonium hydroxide in 70% methanol solution (5%, v/v), to optimize the extraction method. Following centrifugation at 13,000 r/min for 10 min at 25°C, the supernatants underwent evaporation using a vacuum rotary‐evaporator at 35°C and the resulting residue was subsequently dissolved in a 70% methanol solution to achieve a concentration of 10 μg/mL, which was used in establishing the offline 3D chromatography system. Meanwhile, the freeze‐dried powder of each herb sample (0.5 g) was extracted with 70% methanol (25 mL) for 30 min under ultrasonication and centrifuged (13,000 r/min, 10 min, 25°C) to obtain the supernatants. After the evaporation of the supernatants at 35°C, the resulting residue was redissolved in 50% methanol to achieve a concentration of 10 μg/mL. Individual herbal extracts were analyzed by LC–MS to build an in‐house mass spectral library, from which the PIL was subsequently established.

2.3. Methodological Evaluation of 1D Chromatography Conditions for JTTZ Sample

To acquire the better separation in 1D chromatography for JTTZ sample, different detectors (PDA and ELSD detectors), different ion exchange columns (SCX, strong cation exchange; SAX, strong anion exchange), acidic or basic solution pretreatment processes (10% HCl and 10% NH₃ ▪ H₂O), and different mobile phases (15 mM AF, 20 mM AF; 0.05% FA, 0.1% FA) were comparatively investigated. According to the possible compound types of JTTZ, we utilized three types of reference compounds, including flavonoids (RC‐FL, aloin A, aloesin, rutin, quercetin, hesperidin, and quercetin 7‐O‐glucoside), acidic components (RC‐AC, 6‐gingerol, protocatechuic acid, salvianolic acid A, hexahydrocurcumin, schisanhenol, heriguard, 6‐shogaol, 10‐gingerol, and mangiferin), and alkaloids (RC‐AL, berberine, epiberberine, palmatine, and coptisine) to confirm suitable column with better separation.

2.4. Offline 3D‐Chromatography‐Q‐Orbitrap‐MS Analysis

According to the previous report [7], an integrated offline 3D‐chromatography‐Q‐Orbitrap‐MS system was developed, combining IEC, HILIC, and RPC techniques to better resolve the complex multichemicals from the formula. The IEC experiments were performed as 1D separations on an Agilent 1260 HPLC (Agilent, Waldbronn, Germany) equipped with a Venusil SCX chromatography column kept at 35°C at a running rate of 1 mL/min. The mobile phase included a mixture of water (A) and methanol (B) in a consistent ratio of 38% (B) for a total of 10 min. The experiment was carried out for five consecutive runs, each with a 20 μL injection volume. The collection of eluates based on peak detection resulted in the generation of three fractions. Then, these three fractions were dried, at ambient temperature, with a steady flow of N₂ after reconstituting the residues in 1 mL of 70% methanol, the supernatants obtained from centrifugation at 14,000 r/min for 10 min at 25°C were separated in the 2D HILIC method. A combination of 0.1% FA in acetonitrile (B) and water (A) was used as the mobile phase. The flow rate was maintained at 1 mL/min, and a 20 μL injection volume was introduced. The eluent was collected according to the gradient elution program: 0–5 min, 95%–95% (B); 5–7 min, 95%–90% (B); 7–10 min, 90%–90% (B); 10–15 min, 90%–82% (B); 15–20 min, 82%–50% (B).

Zorbax SB‐C₁₈, AQ‐C₁₈, Epic Biphenyl C₁₈, EC‐C₁₈, and ACQUITY UPLC BEH C₁₈ were used to optimize 3D chromatographic separations at 30°C. The mobile phase consisted of a 0.1% FA solution in water (A) and acetonitrile (B), following a gradient program: 0–9 min, 5%–15% (B); 9–18 min, 15%–21% (B); 18–23 min, 21%–21% (B); 23–26 min, 21%–28% (B); 26–33 min, 28%–45% (B); 33–39 min, 45%–95% (B); 39–41 min, 95%–95% (B); 41–42 min, 95%–5% (B); 42–47 min, 5%–5% (B). The flow rate was established at 0.3 mL/min, and the injection was carried out using a volume of 5 μL. By integrating PIL and enabling the IIPO function, a full MS/dd‐MS2 (TopN5) method was established to improve the response of the mass spectrometry signal. The source parameters were configured with the following settings: auxiliary gas temperature maintained at 350°C, capillary temperature maintained at 300°C, auxiliary gas flow rate at eight arbitrary units, and sheath gas flow rate at 35 arbitrary units. Orbitrap analyzer scanned at 70,000 resolution in full‐scan MS1 at m/z 100–1500 and 17,500 in MS2. The AGC targets were configured at 1e⁶ (MS1) and 1e⁵ (MS2), respectively. Meanwhile, maximum injection time (IT) was set to 100 and 50 ms for MS1 and MS2, respectively, and the exclusion time was set to 10 s. The isolation window was 6.0 m/z. High‐energy collision‐induced dissociation was used to trigger the generation of MS2 fragmentation spectra, with the selection of the top 5 ions based on their intensity in the MS1 spectrum. In addition, a mixed normalized collision energy (NCE) value of 20/40/60 eV was used to generate more product ions. Importantly, raw data analysis was conducted using Xcalibur 4.1 software (Thermo Fisher Scientific, Waltham, MA, USA) to obtain the information for molecular formula, adducts, experimental, theoretical, mass error, and MS/MS.

2.5. Identification of Circulating Constituents in Rat Plasma and the Concentration‐Time Curve Analysis of Key Compounds After JTTZ Administration

2.5.1. Animal Model, JTTZ Administration, and Plasma Collection

Fifteen male Sprague–Dawley rats (6 weeks, 180–220 g) were acquired from Beijing Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China) and housed in pathogen‐free conditions with free access to water and feed in a 12‐h shift of light/dark cycle. All animal experiments were fully adhered to the Animal Care and Use Committee of Changchun University of Chinese Medicine (approval number: 2023–123). After the adaptation for 1 week, three rats were used to analyze the chemical constituents of the JTTZ formula in plasma using UPLC–MS/MS after a single‐dose administration of 3 g/kg at 1 h.

Twelve rats were randomly divided into two groups: normal chow diet (NCD, n = 6) group and high‐fat diet group (HFD, 60 kcal% fat, #D12492, Research Diets, New Brunswick, NJ, USA, n = 6). The body weights of these rats were measured every week and the body compositions were analyzed using dual‐energy X‐ray absorptiometry (Shanghai, China) to calculate the ratios of fat and lean mass for the two groups. Biochemical parameters, including total cholesterol (TC), triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), and high‐density lipoprotein cholesterol (HDL‐C), were measured using an automated biochemical analyzer. After the HFD induction for 8 weeks, all rats were orally administrated with JTTZ at a dose of 3 g/kg. Plasma samples were collected from the jugular veins into the EDTA K₂ tubes at 0.25, 0.5, 1, 2, 4, 8, 12, 24, 36, and 48 h to analyze the pharmacodynamic parameters of key compounds in plasma of JTTZ.

2.5.2. Circulating Constituent Identification

Based on a previous study [19], 100 μL of plasma was deproteinized with 300 μL of methanol/acetonitrile (4:1, v/v) containing three IS compounds and centrifuged at 14,000 r/min (4°C, 10 min) to collect the supernatants. The supernatants underwent evaporation using a vacuum rotary‐evaporator at 35°C, which were reconstituted with 100 μL of methanol, and then centrifuged at 14,000 r/min for 10 min at 4°C to acquire plasma sample. The characterization of circulating constituents in the plasma was identified by UPLC‐Q Exactive Orbitrap MS system (Thermo Fisher Scientific). Circulating constituents of JTTZ in plasma were identified by reference standards comparison, Compound Discoverer database, and accurate mass comparison of published literature.

2.5.3. Concentration‐Time Curve Analysis

According to the herb type and compound source, a total of 13 key compounds from JTTZ were selected for the concentration‐time curve analysis. The stock solution (1 mg/mL) of each compound was prepared in methanol and then the mixed stock solution of the 13 compounds was prepared. A series of working solutions were serially diluted with methanol solution (H₂O:MeOH, v/v, 1:1) to seven different concentrations in the range of 0.59–150 ng/mL for berberine, 0.59–150 ng/mL for epiberberine, 0.20–50 ng/mL for berberubine, 0.20–50 ng/mL for coptisine, 0.01–25 ng/mL for jatrotthizine, 0.01–25 ng/mL for palmatine, 3.13–800 ng/mL for mangiferin, 1.56–400 ng/mL for neomangiferin, 3.13–800 ng/mL for timosaponin BII, 3.13–800 ng/mL for aloin A, 1.56–400 ng/mL for aloesin, 0.98–250 ng/mL for gomisin C, and 0.98–250 ng/mL for cryptotanshinone.

The concentration‐time curve analysis for 13 circulating constituents from JTTZ was performed using a UPLC system coupled with a QTRAP6500 (AB Sciex, Framingham, MA, USA). Reverse‐phase UPLC separation was conducted with a Waters HSS T3 C₁₈ column (100 mm × 2.1 mm, 1.7 μm, Waters, Milford, MA, USA). The mobile phase comprised mobile phase A (H₂O with 0.01% FA) and mobile phase B (acetonitrile). The flow rate of the mobile phase was 0.35 mL/min and was maintained at 35°C. In the quantification of these constituents of JTTZ, the gradient separation used was as follows: 0–2 min, 5%–5% (B); 2–10 min, 5%–95% (B); 10–12 min, 95%–95% (B); 12–12.1 min, 95%–5% (B); 12.1–15 min, 5%–5% (B). The optimized mass spectrometer operating parameters were as follows: ion source temperature, 550°C; ion spray voltage, 5.5 kV in positive ion mode, −4.5 kV in negative ion mode; gas 1: 30 psi; gas 2: 30 psi; curtain gas: 30 psi. These 13 compounds were quantified using the multiple reaction monitoring (MRM) mode. The pharmacokinetic parameters including the maximum plasma concentration (C _max), the terminal elimination half‐life (T _1/2), the time corresponding to C _max (T _max), the area under plasma concentration‐time curve (AUC_0‐t ), and the area under plasma concentration‐time curve from 0 to infinity time (AUC_0‐∞) were calculated using the noncompartmental analysis model of WinNonlin v8.1 (Pharsight, CA, USA).

2.6. Method Validation for MRM Analysis

Full validation of the MRM method was performed. The specificity, linearity, lower limits of quantification (LLOQ), accuracy, precision, stability, extraction recovery, and matrix effect of MRM method for all analytes were evaluated to validate the stability, sensitivity, and accuracy of this analytical approach.

2.7. Statistical Analysis

Prism 9.4.0 software (GraphPad, La Jolla, CA, USA) was used for statistical analysis and all data are presented as mean ± standard error. The unpaired two‐tailed Student's t‐test was performed to compare the difference of two groups. p < 0.05 was considered statistically significant.

3. Results and Discussion

3.1. Development of a 3D‐Chromatography Technique

We have developed an offline 3D‐chromatography system to effectively separate the complex chemical components in JTTZ. In the first dimension, IEC was employed to separate compounds based on their surface electric potential. The second dimension utilized HILIC to fractionate hydrophilic components. Finally, RPC coupled with an Orbitrap mass spectrometer was applied as the third dimension to identify all fractions collected from the second dimension.

The “emperor” herb in JTTZ, Coptidis Rhizoma, contains a series of bioactive quaternary ammonium alkaloids that display basic properties [20]. Saponins from the “minister” herbs, Momordica charantia and Anemarrhenae Rhizoma, are neutral, whereas phenolic acids from the “assistant” herb Salvia Miltiorrhizae Radix Et Rhizoma and the “delivering servant” herb Zingiberis Rhizoma are acidic. Given the presence of charged compounds in JTTZ, IEC was selected as the first dimension to separate components according to ionic strength [21].

First, we compared UV detection with evaporative light scattering detection (ELSD) to select a suitable detector (Figure 1A). The UV detector exhibited higher sensitivity and detected more peaks, making it preferable for 1D separation. The UV spectrum of JTTZ showed maximum absorption at 208 nm; however, due to methanol interference below 210 nm, 254 nm was chosen as the detection wavelength. When separating different structural standards, the SCX column displayed eight major peaks, whereas the SAX column showed only three (Figure 1B). Given its superior peak capacity and resolution, the SCX column was selected for the first‐dimension separation of JTTZ.

FIGURE 1.

¹D and ²D separation for preparing sample. (A) Comparison of detectors. (B) Comparison between the strong cation exchange (SCX) and strong anion exchange (SAX) columns by reference standards. (C) Comparison of the SCX columns by samples after different pretreatments. (D) Comparison of the acid additive of ammonium formate (AF), formic acid (FA), and their concentrations. (E) Presentation of the three fractions of the 1D separation on 2D chromatograms. HCl‐treated‐JTTZ, JTTZ with acid treatment; RC‐AC, reference standards of acidic components; RC‐AL, reference standards of alkaloid; RC‐FL, reference standards of flavonoid; NH₃·H₂O‐treated‐JTTZ, JTTZ with alkaline treatment.

After testing various sample pretreatments (including acid and alkali treatment) to improve SCX column resolution, ammonium hydroxide treatment was found to enhance peak capacity (Figure 1C). Additionally, different concentrations of ammonium formate (15 and 20 mM) and formic acid (0.05% and 0.1%) were evaluated as additives, but none significantly improved separation resolution (Figure 1D).

Following 1D SCX chromatography, three main fractions were collected for subsequent 2D separation. When HILIC was applied in normal‐phase mode for the second dimension, only two poorly resolved peaks were obtained for Fraction 1 (Fr.1) and Fraction 2 (Fr.2). Therefore, Fr.1 and Fr.2 were directly subjected to offline 3D chromatography coupled with mass spectrometry to streamline fraction preparation. In contrast, Fraction 3 was successfully separated by HILIC, yielding seven subfractions (Figure 1E). The details of fraction collection for Offline 3D Chromatography were shown in Figure S1. Overall, nine fractions from JTTZ were collected via the offline 3D chromatography system for comprehensive chemical analysis.

3.2. Optimization of ³D Chromatography and Mass Spectrometric Parameters in Data‐Dependent Acquisition Method of the Orbitrap‐MS

To achieve greater MS/MS coverage and enhance identification in JTTZ, the mass spectrometry parameters were optimized for the DDA method. Eleven compounds, including neomangiferin, mangiferin, aloesin, aloin A, berberine, coptisine, palmatine, 6‐gingerol, salvianolic acid A, schisandrol A, and schisanhenol, were chosen as representative constituents of each herb in the JTTZ formula. These compounds were selected as index compounds to investigate the number of diagnostic fragment ions in the MS2 mass spectrum. As previously reported, the ion source parameters, including ion spray voltage, capillary temperature, and collision energy, were optimized to maximize the ionization efficiency [22]. The stepped NCE values of 20/30/40, 20/40/60, 25/35/45, and 30/40/50 eV were compared. Among these, the NCE of 20/40/60 eV yielded appropriate MS2 fragment information for dibenzocyclooctadiene lignans, specifically enabling the detection of the diagnostic product ion at m/z 287.0920 for schisanhenol. Consequently, 20/40/60 eV emerged as the optimal NCE setting. (Figure S2A) of the capillary temperatures tested (250°C, 300°C, 350°C, and 400°C), 300°C was found to be the optimal temperature (Figure S2B). While raising the temperature to 350°C enhances the response of aloin A and mangiferin, it diminishes significantly for coptisine, schisanhenol and schisandrol A. The examination of ionization efficiency at varying spray voltage levels (2.5, 3, 3.5, and 4 kV) indicated that a spray voltage of 4 kV was capable of producing a stable and intense response for 11 compounds (Figure S2C). Following the determination of mass spectrometric parameters, five reverse phase (RP) columns of ³D chromatography were assessed for their ability to identify JTTZ through compound separation and MS/MS coverage. The BEH C₁₈ column outperformed the other columns by acquiring a greater number of peaks from JTTZ and demonstrating superior separation performance compared to the SB‐C₁₈, EC C₁₈, AQ‐C₁₈, and Epic Biphenyl C₁₈ (Figure 2A–C). The orthogonality (A0) between different chromatographic dimensions was evaluated using reference standards (Figure S3 and Table S3). Among the tested columns, the BEH column exhibited superior orthogonality performance. For further optimization of mass spectrum data acquisition rate, a comprehensive assessment of AGC targets and underfill ratios was conducted to determine the MS/MS coverage under different conditions. The optimal combination was identified as an AGC target of 1e⁶ and an underfill ratio of 0.01, resulting in the maximum number of MS/MS spectrum for JTTZ sample (Figure 2D).

FIGURE 2.

Comparison of five chromatographic columns in ³D separations and optimization of automatic gain control (AGC) target values and underfill ratios. A and B exhibit the base peak chromatograms (BPC) of the total extract of JTTZ in both the positive (A) and negative (B) modes obtained by using five columns thereof. C shows the number of peaks resolved by MSDIAL from JTTZ comparing five candidate columns in both the positive (right) and negative (left) ESI modes. Contour plots display the total number of MS/MS scans as a function of AGC target value and underfill ratio (D).

3.3. The Identification of the Constituents in JTTZ Through a Comparison of 1D and 3D Chromatography

We initially develop an in‐house chemical library for each herb using Compound Discoverer software to generate PIL list information for the mass spectrum acquisition method. The chromatogram of each herb at the negative or positive mode was shown in Figure 3A,B. There are a total of 32 compounds identified in Coptidis Rhizoma, including 21 alkaloids. Anemarrhenae Rhizoma contained 34 compounds, including two alkaloids, 10 steroids, four stilbenes, and two terpenoids. Only five characteristic compounds have been identified from Momordica charantia , as there have been few studies on its chemical composition. Salvia Miltiorrhizae Radix Et Rhizoma has 27 compounds, including seven phenylpropanoids and seven terpenoids. Schisandrae Chinensis Fructus has 27 compounds, including three lignans, 15 phenylpropanoids, and three terpenoids. Monascus Purpureus contains nine compounds without monacolin analogs. Monacolin K, a well‐known active compound in Monascus, has not been found, possibly due to the herb decoction. Aloe has 21 compounds, including two phenols and three phenylpropanoids. Lastly, Zingiberis Rhizoma contains 26 compounds, including 15 phenols. All identified compounds from each herb were used to build the PIL list for mass spectrum acquisition. A strategy combining full MS/dd‐MS2 with PIL was adopted to enhance MS/MS acquisition efficiency rate in JTTZ. By incorporating IIPO (if‐idle‐pick‐others) function, we were able to enhance the characterization of target constituents while still obtaining fragmentation data on unknown constituents, leading to the development of the PIL list of JTTZ containing 127 compounds.

FIGURE 3.

Base peak chromatogram (BPC) of eight single herbs in both positive (A) and negative (B) modes. Base peak chromatogram of nine fractions in both positive (C) and negative (D) modes. Comparison of 3D and 1D on the number of compounds identified in different herbs (E). Venn diagram showing the overlap of compounds identified by the 1D and 3D approaches (F). The Y‐axis (A and B) represents different single herbs. The Y‐axis (C and D) represents different fractions. The Y‐axis (E) represents number of identified compounds. DS, Salvia Miltiorrhizae Radix Et Rhizoma; GJ, Zingiberis Rhizoma; HQ, Red Yeast Rice; HL, Coptidis Rhizoma; KG, Momordica charantia; LH, Aloe; WWZ, Schisandrae Chinensis Fructus; ZM, Anemarrhenae Rhizoma. 186 were identified by 3D methods, 68 by 1D methods.

The nine fractions were obtained by using SCX and HILIC techniques. These fractions were then analyzed directly using RPLC‐Orbitrap (Figure 3C,D). A part of the compounds was identified by comparing accurate mass and retention time with a reference spectrum from an in‐house library, while the structure of noncommercial compounds was determined based on GNPS, the MSDIAL public database, and the Compound Discoverer commercial database. A total of 186 compounds were identified using the offline 3D chromatography, while only 68 compounds were identified using the conventional 1D method (Table S1, Figure 3E). Compared to the 25 compounds identified by Yu et al. [18] in JTTZ, our study identified 68 compounds using a conventional 1D method. Furthermore, the 3D method enabled the identification of 186 compounds in JTTZ. In addition, compared with 1D, the 3D chromatography approach enabled the identification of additional compounds that were not detectable in the 1D analysis, thereby expanding the pool of candidate circulating constituents. Notably, several compounds, including berberrubine, coptisine, jatrorrhizine, palmatine, timosaponin BII, and gomisin C, were identified by 3D separation and subsequently confirmed in plasma. This expanded chemical coverage facilitated a more comprehensive characterization of prototype blood‐entering components and provided a rational basis for the subsequent selection of pharmacokinetic analytes. For the three main fractions from offline 3D chromatography, 35 compounds, 38 compounds, and 113 compounds were identified in Fr.1, Fr.2, and Fr.3, respectively (Table S1).

Under mass spectrometric acquisition conditions, DDA is commonly employed; however, it requires analytes to exhibit sufficient signal intensity to trigger MS/MS events. In our preliminary studies, a considerable number of compounds failed to meet the threshold for DDA triggering and were detected only at the MS1 level, while some commonly reported constituents were not even observed at the precursor ion level. This limitation may be attributed to the low abundance of constituents in complex herbal formulas and the severe co‐elution of interfering compounds. Such co‐eluting species not only compete for ionization in the source, thereby suppressing the response of target natural products, but also preferentially trigger DDA events, occupying the limited duty cycle and reducing the opportunity for target compounds to be selected for fragmentation. Multidimensional chromatography provides an effective strategy to address these challenges. Through stepwise enrichment across multiple separation dimensions, the effective concentration of analytes can be increased, while orthogonal separations reduce co‐elution interferences. Consequently, the likelihood of target natural products triggering DDA acquisition is significantly improved.

In the current study, a comparative analysis between the 1D and 3D methods demonstrated that several classical bioactive compounds of Coptidis Rhizoma, including berberrubine, palmatine, coptisine, and jatrorrhizine, were exclusively identified in the 3D workflow, whereas they remained undetected under 1D conditions. An online RPLC × RPLC system was established by Xiaohui Deng [23] and coupled to DAD detection and LTQ‐Orbitrap mass spectrometry. This approach features a high degree of automation and throughput, and it enables the acquisition of abundant fragment ion information. However, it is inherently constrained by limited separation dimensionality and relatively similar separation mechanisms. When different stationary phases are introduced to improve orthogonality, additional considerations regarding mobile phase compatibility become necessary, which may restrict method flexibility. In contrast, offline 3D chromatography allows each separation dimension to be independently optimized using distinct pH conditions and solvent systems, thereby significantly enhancing orthogonality and separation performance. Nevertheless, this approach is more labor‐intensive and time‐consuming, and it may introduce sample loss during multiple handling steps. More importantly, the proposed offline 3D chromatography strategy integrates a PIL, in which compounds are compiled from database matching of individual herbal components. These preannotated compounds are preferentially subjected to DDA, enabling targeted MS/MS spectral collection. As a result, this strategy not only improves the confidence and coverage of compound identification, but also establishes a solid foundation for subsequent pharmacokinetic investigations. Specifically, it facilitates a systematic workflow from chemical profiling to the screening of absorbed prototype compounds in vivo, ultimately supporting downstream pharmacokinetic studies. Twenty‐two compounds were identified using reference standards, and the fragmentation processes of several representative structural types were presented as illustrative examples to support compound identification (Figure S4). The major constituents of Coptidis Rhizoma are isoquinoline alkaloids, which are inherently charged and do not require protonation, resulting in strong MS responses without significant competition for ionization in the source. Berberine and epiberberine are a pair of structural isomers that generate identical fragment ions (m/z 292 and 322), making them indistinguishable based solely on MS/MS spectra. Therefore, they were differentiated by comparison with reference standards based on their retention times (16.29 min for berberine and 19.75 min for epiberberine). Coptisine also produces a characteristic fragment ion at m/z 292. Although its fragment ions are similar to those of berberine‐type alkaloids, structural differences may still exist. Due to the absence of methoxy substitution, coptisine does not generate the typical (M–CH₃) fragment ion. In contrast, palmatine, which contains more methoxy groups, undergoes sequential demethylation to form jatrorrhizine, followed by further loss of H₂O to yield m/z 322. The loss of a methyl group leads to the formation of an ion at m/z 294, which is identical to the characteristic fragment ion generated by berberrubine. These alkaloids share a common fragment ion at m/z 294, which can be considered a diagnostic ion for this class. The major component in Anemarrhenae Rhizoma is mangiferin, a xanthone glycoside derived from neomangiferin through the loss of a glucose moiety. The C–O bond linking the sugar moiety is more susceptible to cleavage, whereas the C–C bond connecting the sugar to the aromatic core is relatively stable. Consequently, instead of preferential glycosidic bond cleavage, fragmentation proceeds via the loss of C₂H₆O₃ to generate an ion at m/z 331, followed by the loss of CH₂O to yield an ion at m/z 301. Gomisin C and schisandrol A are representative lignans from Schisandrae Chinensis Fructus, characterized by multiple methoxy substitutions that undergo sequential demethylation. Gomisin C readily loses a benzoic acid moiety at the C6 position to form a schisandrol B‐type ion, followed by dehydration and demethylation to generate an ion at m/z 371. Further loss of a methoxy group results in an ion at m/z 340, while successive losses of methoxy substituents from the aromatic ring produce a series of fragment ions with a mass difference of 31 Da. Similarly, schisandrol A undergoes dehydration to form a schizandrin A‐type ion, followed by sequential demethylation to generate fragment ions at m/z 384 and 353. Notably, compounds containing a methylenedioxy group (e.g., gomisin C) exhibit distinct fragmentation patterns compared with those bearing only methoxy substituents (e.g., schisandrol A), reflecting differences in their substitution patterns and fragmentation pathways.

3.4. Efficient Identification of Major Circulating Constituents of JTTZ Formula in Rats

Through preliminary exploration and optimization of the UPLC‐Q Exactive Orbitrap MS system, the identification of circulating components of JTTZ was achieved by using Xcalibur. As a result, a total of 41 prototype components occurring in plasma were annotated based on the positive and negative ion chromatograms (Figure 4A,B). This study was focused exclusively on the identification of prototype constituents in plasma, without systematic investigation of their metabolites and the biological interpretation. Circulating compounds were assigned as: HL (8 compounds), ZM (7 compounds), DS (7 compounds), WWZ (6 compounds), LH (5 compounds), HQ (2 compounds), and GJ (6 compounds) (Table S1, # represent). The majority of circulating compounds possess a molecular mass below 600 Da, as larger molecules have reduced membrane diffusion capability [24]. Despite this, saponins demonstrate amphiphilic characteristics due to the variable lipophilicity of the aglycone and the hydrophilicity of sugar moieties. This property enables saponins to form micelles or interact with serum proteins, thereby facilitating their absorption [25]. In the analysis of circulating compounds, four timosaponin compounds were identified, while the five major saponins from KG were absent in circulation. The solubility of saponins decreases as the number of sugar moieties attached to the aglycon skeleton decreases [26, 27]. We hypothesized that the four cucurbitane‐type triterpenes (momordicoside I, karaviloside XI, momordicine II, and momordicoside F2) from KG exhibit lower solubility than timosaponins. With just one sugar group, these four cucurbitane‐type triterpenes demonstrate inadequate gastrointestinal absorption.

FIGURE 4.

A total of 41 circulating components of JTTZ formula in rat plasma were identified by LC–MS analysis. The base peak chromatograms (BPC) of the positive ion (A) and negative ion (B) of JTTZ formula in rat plasma.

3.5. The Establishment of MRM Method and Concentration‐Time Curve Analysis of 13 Circulating Constituents of JTTZ in Rats With Normal Chow or HFD Diets

Previous reviews have summarized that berberine derived from Coptidis Rhizoma exerts antiobesity effects through multiple mechanisms in both preclinical and clinical studies [28]. Given the structural similarity among isoquinoline alkaloids, other analogs may exhibit comparable pharmacological activities. For example, Jatrorrhizine has been summarized in previous reviews as exhibiting antidiabetic activity in cellular and animal models by promoting insulin secretion, improving glucose metabolism, and inhibiting hepatic gluconeogenesis, thereby reducing postprandial hyperglycemia [29].

Mangiferin has been reported to ameliorate type 2 diabetes mellitus by regulating PPARγ and NF‐κB expression and modulating glycerophospholipid and arachidonic acid metabolism [30]. Molecular docking analysis suggested neomangiferin as a sodium‐glucose co‐transporter 2 protein (SGLT‐2) inhibitor, highlighting its promise as a therapeutic candidate in type 2 diabetes treatment [31]. Timosaponin was shown to alleviate inflammation and dyslipidemia in obese rats, with its effects potentially associated with modulation of the Nrf2/HO‐1 and NF‐κB pathways [32]. Gomisin C suppresses early adipogenesis by inhibiting the JAK2–STAT pathway while activating the NRF2–KEAP1 signaling pathway [33]. Cryptotanshinone inhibits adipogenesis by acting as a small‐molecule modulator of the glucagon‐like peptide‐1 receptor (GLP‐1R) [34]. Aloin may contribute to the management of advanced glycation end product (AGE)‐related complications in diseases such as atherosclerosis and diabetes [35]. Aloesin protects against nonalcoholic fatty liver disease (NAFLD) through Nrf2‐mediated mechanisms [36]. Based on the reported pharmacological activities and their potential relevance to metabolic disorders, these compounds were selected for subsequent pharmacokinetic analysis. First, product ion fragments determined from Orbitrap mass spectrometry results were used to develop a multiple reaction monitoring (MRM) quantification method. The optimized declustering potential (DP) and collision energy (CE) for the 13 analytes—aloin A, gomisin C, cryptotanshinone, jatrorrhizine, coptisine, berberine, palmatine, epiberberine, berberrubine, neomangiferin, aloesin, timosaponin BII, and mangiferin—along with three internal standards (diphenhydramine, bifendate, and calycosin) are summarized in Table 1. Chromatographic conditions were systematically optimized to improve separation and detection. Using acetonitrile‐water as the mobile phase enhanced the peak shape of timosaponin BII, while adding 0.01% formic acid improved the peak profiles of alkaloid compounds. Further adjustments to the gradient elution allowed all 13 analytes to be well separated and detected within 15 min. Comparisons between blank rat plasma and spiked samples showed minimal endogenous interference for the target analytes. The calibration curves for all analytes demonstrated excellent linearity, with correlation coefficients (r) greater than 0.99000 over their respective concentration ranges; the corresponding regression equations and lower limits of quantification (LLOQs) are provided in Table 2. As shown in Table 3, accuracy ranged from 85% to 115%, mean extraction recovery varied between 85% and 115%, and matrix effects fell within 70%–115%. Precision, expressed as relative standard deviation (RSD%), was below 15% for all compounds. Stability studies under various conditions—including 4 h at 25°C, three freeze–thaw cycles, storage in the autosampler (15°C), and long‐term storage at −80°C—confirmed that all analytes remained stable in rat plasma (Table S2). Together, these results demonstrate that a reliable and reproducible MRM method for the simultaneous quantification of the 13 analytes has been successfully established.

TABLE 1.

MS/MS detection parameters for 16 compounds.

Analytes	Ion mode	Precursor ion (m/z)	Product ion (m/z)	Declustering potential (V)	Collision energy (V)
Berberine	[M]+	336.2	292.2	50	70
Epiberberine	[M]+	336.2	292.2	50	70
Berberrubine	[M]+	322.0	307.0	101	39
Coptisine	[M]+	320.2	292.1	80	40
Jatrorrhizine	[M]+	338.1	322.1	60	40
Palmatine	[M]+	352.2	336.2	40	39
Mangiferin	[M‐H]+	421.1	331.0	−50	−30
Neomangiferin	[M‐H]+	583.3	331.0	−170	−53
Timosaponin BII	[M‐H]+	919.6	757.4	−220	−61
Aloin A	[M+H]+	419.2	239.3	120	19
Aloesin	[M‐H]+	393.3	273.1	−160	−30
Gomisin C	[M+H]+	537.2	371.1	102	27
Cryptotanshinone	[M+H]+	297.0	268.0	145	33
Diphenhydramine	[M+H]+	256.2	152.0	25	54
Bifendate	[M+H]+	419.0	343.1	86	27
Calycosin	[M+H]+	285.0	270.2	210	32

TABLE 2.

The regression equations, linear range, and LLOQs for 13 compounds.

Analytes	Calibration curves	Range (ng/mL)	R 2	LLOQ (ng/mL)
Berberine	y = 0.16925x + 0.00594	0.59–150	0.99817	0.30
Berberrubine	y = 1.67899x − 0.00258	0.20–50	0.99094	0.02
Epiberberine	y = 0.25743x − 0.00632	0.59–150	0.99728	0.30
Coptisine	y = 2.12087x + 0.00414	0.20–50	0.99556	0.02
Jatrorrhizine	y = 0.56537x + 0.03602	0.01–25	0.99547	0.02
Palmatine	y = 0.48716x + 0.06843	0.01–25	0.99188	0.01
Mangiferin	y = 0.00840x‐0.000303183	3.13–800	0.99062	0.30
Neomangiferin	y = 0.05784x‐0.000725473	1.56–400	0.99415	0.60
Timosaponon BII	y = 2179.07404x + 4990.05966	3.13–800	0.99350	0.20
Aloin A	y = 0.01857x + 0.000303183	3.13–800	0.99681	0.30
Aloesin	y = 0.05396x‐0.000125063	1.56–400	0.99111	0.60
Gomisin C	y = 0.01560x + 0.00430	0.98–250	0.99023	0.50
Cryptotanshinone	y = 9447.77912x + 236.46085	0.98–250	0.99233	0.50

Abbbreviation: LLOQ, lowest limit of quantification.

TABLE 3.

Accuracy, precision, recovery, and matrix effect for the determination of 13 analytes in rat plasma samples.

Analytes	Spiked QC (ng/mL)	Intraday (n = 5)		Interday (n = 15)
		Precision (RSD, %)	Accuracy (%)	Precision (RSD, %)	Accuracy (%)	Recovery (%) (n = 6)	Matrix effect (%) (n = 6)
Berberine	4.69	9.29	106.63	8.25	108.32	92.31 ± 2.76	105.46 ± 4.15
	18.75	8.68	109.84	7.63	112.36	95.48 ± 4.32	103.45 ± 5.14
	75.00	3.23	103.75	5.84	106.23	105.38 ± 8.87	107.18 ± 3.17
Epiberberine	4.69	5.78	110.80	3.25	109.26	105.15 ± 3.16	89.43 ± 10.96
	18.75	6.48	102.18	7.46	105.84	107.34 ± 6.19	93.46 ± 8.41
	75.00	5.83	111.15	8.23	113.25	108.46 ± 3.17	99.47 ± 6.43
Berberrubine	1.56	3.24	107.85	8.52	109.32	92.31 ± 2.76	105.46 ± 4.15
	6.25	6.71	108.32	8.32	113.54	98.48 ± 5.57	104.22 ± 5.56
	25.00	3.25	103.57	6.77	106.32	106.38 ± 7.87	109.18 ± 3.22
Coptisine	1.56	8.74	114.83	3.26	108.65	96.17 ± 8.94	97.58 ± 10.67
	6.25	10.40	109.44	11.32	111.23	97.18 ± 8.49	96.45 ± 9.48
	25.00	3.96	107.56	6.24	109.84	99.18 ± 9.92	95.75 ± 9.48
Jatrorrhizine	0.78	12.23	88.80	14.36	90.26	98.14 ± 8.16	97.43 ± 9.46
	3.13	6.89	105.64	13.25	108.26	104.39 ± 4.36	96.16 ± 5.93
	12.50	1.98	107.51	3.58	111.87	106.76 ± 5.16	99.46 ± 7.56
Palmatine	0.78	14.55	114.24	11.28	112.25	97.46 ± 9.46	108.64 ± 3.48
	3.13	9.91	106.26	7.65	107.25	98.48 ± 8.46	97.52 ± 6.84
	12.50	2.78	114.43	8.20	113.25	105.34 ± 4.16	96.75 ± 7.43
Mangiferin	25.00	3.40	94.75	14.23	103.56	103.14 ± 6.15	97.92 ± 7.46
	100.00	7.93	85.32	10.32	87.68	105.16 ± 4.18	98.83 ± 7.96
	400.00	6.52	102.49	5.69	103.25	111.48 ± 3.74	99.76 ± 7.62
Neomangiferin	12.50	3.65	100.10	2.36	101.85	104.14 ± 8.45	97.46 ± 8.64
	50.00	2.67	109.59	7.56	104.68	105.43 ± 4.18	96.76 ± 5.89
	200.00	7.99	109.66	10.26	109.69	108.13 ± 3.42	99.48 ± 7.91
Timosaponin BII	25.00	3.04	107.04	5.22	104.21	107.15 ± 5.46	97.44 ± 8.49
	100.00	2.15	101.68	6.77	101.58	103.28 ± 8.42	99.57 ± 6.85
	400.00	5.23	85.72	10.38	85.97	104.84 ± 5.17	96.81 ± 7.46
Aloin A	25.00	13.26	102.25	14.28	102.85	97.28 ± 9.84	93.48 ± 7.18
	100.00	8.77	109.43	7.66	107.32	93.08 ± 7.83	96.17 ± 8.43
	400.00	13.63	103.64	8.44	110.58	106.25 ± 6.53	94.46 ± 5.48
Aloesin	12.50	2.11	89.89	6.32	87.26	106.49 ± 6.15	106.46 ± 4.16
	50.00	14.54	95.70	11.22	95.67	107.54 ± 6.48	103.48 ± 8.46
	200.00	8.02	108.27	10.56	109.78	98.43 ± 8.96	98.43 ± 8.96
Gomisin C	7.81	7.58	109.25	7.69	109.91	99.47 ± 9.42	99.18 ± 6.48
	31.25	5.89	111.28	13.85	106.32	103.48 ± 5.16	102.48 ± 5.43
	125.00	7.00	107.12	6.83	107.56	105.29 ± 5.49	96.62 ± 5.81
Cryptotanshinone	7.81	2.46	108.71	3.48	110.78	99.46 ± 9.36	103.78 ± 5.43
	31.25	4.07	86.78	2.65	87.11	93.27 ± 8.74	97.68 ± 6.92
	125.00	8.99	94.63	10.26	94.89	104.49 ± 3.24	96.73 ± 6.31

To further acquire the concentration‐time curves of 13 analytes in the animal models, six rats of each group were fed for 8 weeks. Compared with the NCD group, the body weight of rats in the HFD group showed a substantial increase, with the 34.76% weight gain (Figure S5A). Through the use of dual‐energy X‐ray absorptiometry, the body composition of rats in each group was measured for calculating the ratios of fat and lean mass. As shown in Figure S5B,C, the HFD group had significantly high fat content compared to the NCD group. Meanwhile, the levels of plasma lipids, such as TC and LDL‐C, were increased in the HFD group (Figure S5D). These results indicated that obese rats were induced by HFD after 8 weeks administration. Then, the concentration‐time profiles of 13 analytes in the NCD and HFD rats were established and shown in Figure 5 and relevant pharmacokinetic parameters were summarized in Table 4, after oral administration of JTTZ formula.

FIGURE 5.

The concentration‐time curves of 13 circulating constituents were analyzed in rats with normal chow diet (NCD) and high‐fat diet (HFD) after oral administration of JTTZ formula. Blood concentration‐time curves of six active alkaloids from HL, including berberine, epiberberine, berberubine, coptisine, jatrorrhizine, and palmatine (A), two flavonoids, mangiferin, neomangiferin and one saponin, timosaponin BII (B), two anthraquinones, such as aloin A and aloesin (C), gominsin C (D), and cryptotanshinone (E).

TABLE 4.

Pharmacokinetic parameters for 13 analytes in normal chow diet and high fat diet rats after oral administration of Jiangtang Tiaozhi formula (mean ± SE, n = 6).

Analytes	Group	T 1/2 (h)	T max (h)	C max (ng/mL)	AUC0‐t (h·ng/mL)	AUC0‐∞ (h·ng/mL)
Berberine	NCD	79.56 ± 17.40	0.71 ± 0.14	10.36 ± 7.89	42.70 ± 2.77	133.99 ± 19.09
	HFD	209.23 ± 155.40	6.42 ± 3.98	3.37 ± 0.57	61.82 ± 6.94	379.61 ± 254.29
Epiberberine	NCD	24.18 ± 4.58*	1.33 ± 0.54	166.84 ± 118.58	1575.77 ± 1471.07*	2042.40 ± 1875.86
	HFD	72.33 ± 21.41	7.21 ± 3.78	27.07 ± 4.07	783.88 ± 164.12	2964.47 ± 618.82
Berberrubine	NCD	81.30 ± 13.32	6.00 ± 0.89	3.86 ± 0.19	108.45 ± 2.84	300.39 ± 29.68
	HFD	66.10 ± 16.20	7.67 ± 1.31	5.24 ± 1.05	150.73 ± 21.46	331.03 ± 33.91
Coptisine	NCD	9.92 ± 1.88	1.17 ± 0.58	1.98 ± 0.26	14.64 ± 3.40**	15.91 ± 3.54**
	HFD	14.26 ± 2.55	3.63 ± 1.81	3.62 ± 0.85	59.19 ± 10.10	68.04 ± 11.15
Jatrorrhizine	NCD	11.45 ± 3.65	1.13 ± 0.58	9.00 ± 0.96	67.15 ± 7.77*	94.51 ± 21.82**
	HFD	12.13 ± 3.45	2.71 ± 1.18	14.84 ± 2.80	161.83 ± 33.33	187.55 ± 38.98
Palmatine	NCD	52.74 ± 26.77	1.08 ± 0.59	18.56 ± 2.92	80.15 ± 25.25**	499.30 ± 233.90
	HFD	19.76 ± 3.28	5.71 ± 2.30	34.90 ± 8.23	340.95 ± 52.90	504.25 ± 163.93
Mangiferin	NCD	10.68 ± 2.50	0.63 ± 0.13	177.64 ± 68.60	563.80 ± 136.50*	1033.00 ± 242.77*
	HFD	25.87 ± 8.94	0.38 ± 0.07	308.89 ± 77.45	1371.38 ± 251.12	4219.69 ± 1250.70
Neomangiferin	NCD	0.94 ± 0.26	0.46 ± 0.12	8.34 ± 2.31	5.66 ± 1.55	6.45 ± 2.27
	HFD	22.66 ± 13.32	0.33 ± 0.05	30.43 ± 12.82	39.69 ± 19.64	41.56 ± 19.62
Timosaponin BII	NCD	3.61 ± 1.27	0.29 ± 0.04	17.06 ± 2.53	15.01 ± 2.74*	17.71 ± 3.98 ****
	HFD	27.39 ± 15.69	1.75 ± 1.25	58.66 ± 25.76	138.10 ± 39.12	266.26 ± 15.21
Aloin A	NCD	177.61 ± 129.36	1.63 ± 0.76	29.43 ± 8.79*	184.32 ± 16.20*	951.21 ± 499.86
	HFD	30.97 ± 18.72	6.88 ± 2.11	10.34 ± 5.14	100.40 ± 23.88	147.27 ± 74.04
Aloesin	NCD	9.34 ± 2.73	0.42 ± 0.12	11.31 ± 4.88	26.64 ± 13.59*	47.07 ± 15.05
	HFD	13.26 ± 5.32	4.17 ± 1.71	31.17 ± 6.52	256.78 ± 76.05	286.15 ± 117.78
Gomisin C	NCD	6.66 ± 3.22	2.38 ± 0.74	257.47 ± 56.74	956.16 ± 300.81	1894.47 ± 728.56
	HFD	24.11 ± 8.72	2.83 ± 1.86	209.70 ± 77.28	2856.99 ± 1505.82	3390.45 ± 677.42
Cryptotanshinone	NCD	15.33 ± 3.52	1.42 ± 0.58	5.33 ± 1.02	53.22 ± 6.66	65.42 ± 7.32
	HFD	22.99 ± 5.52	3.50 ± 1.02	3.69 ± 0.45	58.84 ± 6.30	81.61 ± 14.21

Abbreviations: HFD, high fat diet; NCD, normal chow diet.

^* p < 0.05.

^** p < 0.01.

^*** p < 0.001.

^**** p < 0.0001 as compared with the HFD group.

To enhance the safety and efficacy of CMF in clinical application, it is important to investigate the pharmacokinetics of their major active compounds under different disease states. Previous studies have suggested that pathological conditions may lead to alterations in pharmacokinetic parameters [37, 38, 39]. For instance, increased body fat percentage can reduce the oral bioavailability of hydrophilic drugs [40]. In the present study, a similar trend was observed: the relatively hydrophilic compound aloin A, which has two phenol groups, was absorbed quickly (T _max = 1.63 h) and reached a higher C _max (29.43 ng/mL) in the NCD group. This result is consistent with a previous pharmacokinetic study on aloin A [41]. However, the T _max of aloin A in the HFD exceeded fourfold compared to that in the NCD, suggesting that a higher body fat percentage can result in delayed absorption of aloin A in rat plasma. In addition, double peaks were observed for gomisin C and aloesin. The second peak could potentially be attributed to enterohepatic circulation and fractionated gastric emptying [42]. These findings imply that obesity may selectively enhance the absorption of certain components, warranting further investigation into the underlying mechanisms. However, these findings are observational and may not be sufficient to establish a definitive mechanistic explanation, and further studies are warranted to clarify the underlying mechanisms.

Coptidis Rhizoma contains six active alkaloids, including berberine, palmatine, coptisine, epiberberine, and jatrorrhizine, with low bioavailability [43]. This is particularly evident for berberine, a major active constituent, which shows poor gastrointestinal absorption due to its low aqueous solubility, limited intestinal permeability, and extensive first‐pass metabolism [44]. The maximum plasma concentrations (C _max) of the alkaloids in the NCD group ranged from 1.98 to 18.56 ng/mL, which were significantly lower than those in the HFD group, with the exception of epiberberine (166.84 ng/mL). The area under the curve (AUC_0‐t ) values of epiberberine decreased significantly in the HFD group, while an increasing trend was observed for the AUC_0‐t of the other four quaternary ammonium alkaloids (berberine, jatrorrhizine, coptisine, and palmatine) in the HFD group compared to the NCD group. It is speculated that obesity‐induced changes in gastrointestinal physiology, including altered gut motility and pH, may contribute to the observed differences in the absorption of epiberberine. Interestingly, the time to reach maximum concentration (T _max) of all six alkaloids from Coptidis rhizome was lower in the NCD group than in the HFD group, indicating slower absorption of the major active constituents in the HFD group. Dosing based on total body weight in individuals with high body fat could lead to overexposure, increasing the risk of adverse effects. Therefore, adjusting the composition of herbal formulas in relation to patient body‐fat percentage may be crucial for balancing efficacy and safety. This rationale underscores the importance of conducting comparative pharmacokinetic studies on CMF across different pathological states. This study has several limitations that should be acknowledged. First, the offline 3D chromatography workflow is labor‐intensive and time‐consuming, as it requires repeated collection and enrichment of fractionated eluates, which may limit analytical throughput. It should be noted that compound transfer during fraction collection may be accompanied by unavoidable losses, including nonspecific adsorption to tubing, columns, or collection containers, as well as potential chemical instability or degradation during handling. Such effects may result in the underestimation of certain analytes and introduce bias in the overall compound profiling. In addition, except for compounds confirmed by comparison with authentic standards, the present approach cannot provide unequivocal structural confirmation for all annotated compounds, particularly in distinguishing structural isomers. Therefore, the assigned identities should be interpreted with appropriate caution. Second, the present work mainly focused on the identification of absorbed prototype compounds and did not systematically investigate potential metabolites or biotransformation products, thereby providing only a partial view of the in vivo metabolic landscape.

4. Conclusions

With the goal of unraveling the intricate chemical composition of herbs, a new offline 3D chromatography/Q‐Orbitrap‐MS method was developed in this study. Moreover, a strategy of targeted characterization with PIL was utilized to enhance the coverage of targeted constituents while still being able to identify unknown constituents. The 3D method identified 186 components, whereas the 1D method only identified 68 compounds. According to the chemical library built from the 3D method, we identified 41 circulating compounds in NCD rats. The MRM quantification method was developed and successfully utilized to assess the pharmacokinetics of 13 major circulating components in the NCD and the HFD following oral administration of JTTZ. This elucidated the effect of the pathological state of obesity on the pharmacokinetics of the 13 constituents, and the safety and efficacy of JTTZ can be evaluated using this method. Future studies are warranted to further address metabolic profiling and mechanistic validation. This work serves as a guide for the better clinical application of JTTZ in the treatment of obesity.

Funding

This work was supported by the Science and Technology Development Plan Project of Jilin Province (20230402040GH), the National Natural Science Foundation of China (82405364), and the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (ZYYCXTD‐D‐202001).

Ethics Statement

The Ethics Committee of Changchun University of Chinese Medicine has given the approval of this research (No. 2023‐123).

Supporting information

Figure S1: The workflow of fraction collection for offline 3D chromatography.

Figure S2: Optimization of mass spectrometry conditions. (A) Influence of collision energy (from top to bottom: 20/30/40 eV; 20/40/60 eV; 25/35/45 eV; 30/40/50 eV), (B) capillary temperature, and (C) spray voltage on MS2 behaviors of the representative analytes.

Figure S3: Comparison of chromatographic column orthogonality across different dimensions.

Figure S4: Illustration of the major fragmentation pathways of alkaloids, flavonoids, and lignans.

Figure S5: Effects of JTTZ on body weight and body fat in HFD‐fed rats. HFD, rats fed with a high‐fat diet (n = 6); NCD, rats fed with a standard chow diet (n = 6). (A) Body weight gain. (B) Determination of fat content in rats by dual‐energy X‐ray absorptiometry. (C) Fat ratio and lean ratio. (D) TC, TG, HDL‐C, and LDL‐C levels.

Table S1: Compounds identified in Jiangtang Tiaozhi formula by UPLC–MS.

Table S2: The stability of 13 compounds in rat plasma under different storage conditions.

Table S3: Chromatographic column orthogonality across different dimensions.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.