Abstract

   Introduction: Drug dosages and combinations are the main factors that
   affect the efficacy of pleiotropic traditional Chinese medicine (TCM).
   Coptis chinensis Franch. (CF) is a representative TCM with multiple
   effects and is often combined with Tetradium ruticarpum (A. Jussieu) T.
   G. Hartley (TR) to treat cholestasis. The present study assessed the
   influence of CF dose and its combination with TR on the efficacy of CF
   in cholestasis treatment, including their effects on fecal metabolism
   and fecal microorganisms.

   Methods: Rats with α-naphthylisothiocyanate (ANIT, 50 mg/kg)-induced
   cholestasis were administered low (0.3 g/kg) and high (0.6 g/kg) doses
   of CF, as well as CF combined with TR at doses of 0.6 g/kg and
   0.9 g/kg, respectively. The anti-cholestatic effects of these
   treatments were assessed by determining their anti-inflammatory,
   hypolipidemic, and anti-oxidative stress properties. Additionally,
   fecal metabolomics and fecal microorganisms were analyzed.

   Results: Low dose CF had a more potent hypolipidemic effect than high
   dose CF, whereas high dose CF had more potent anti-inflammatory and
   anti-oxidative stress effects. Combination with TR enhanced the
   hypolipidemic effect, but antagonized the anti-inflammatory effect, of
   CF. Analyses of fecal metabolomics and fecal microorganisms showed
   differences in the regulation of lipid- and amino acid
   metabolism-related pathways, including pathways of linoleic acid,
   tyrosine, and arachidonic acid metabolism, and amino acid biosynthesis
   between different doses of CF as well as between different doses of CF
   in combination with TR. These differences may contribute to differences
   in the anti-cholestatic effects of these preparations.

   Conclusion: CF dose influences its anti-cholestatic efficacy. The
   combination with TR had synergistic or antagonistic effects on the
   properties of CF, perhaps by altering fecal metabolism and fecal
   microbial homeostasis.

   Keywords: anti-cholestatic effects, Coptis chinensis Franch., Tetradium
   ruticarpum (A. Jussieu) T. G. Hartley, fecal metabolism, fecal
   microbial diversity

1 Introduction

   The clinical application of Chinese botanical drugs has been found to
   play a vital role in maintaining human health. Coptis chinensis Franch.
   (CF), one of the most commonly used botanical drugs in traditional
   Chinese medicine (TCM), is widely used in the treatment of various
   diseases, such as coronary heart disease, cholestasis, and
   gastroenteritis ([52]Wang et al., 2019). The "Pharmacopoeia of the
   People’s Republic of China,” an official revision of the Chinese
   pharmacopeia, has summarized its efficacy in three main areas: clearing
   heat, eliminating dampness, and detoxification, regarding CF as crucial
   in the treatment of cholestasis ([53]Commission, 2020), a common
   disease characterized by abnormal bile secretion or excretion ([54]Song
   et al., 2022).

   The effects of CF in TCM may depend on its dosage and its combination
   with other botanical drugs ([55]Deng, 2018). For example, the Huanglian
   Jiedu decoction, a combination of CF with Cortex phellodendri
   chinensis, Radix scutellariae, and Fructus gardeniae in a 3:2:2:3
   ratio, showed antipyretic effects by disrupting the JAK2/STAT3 and MAPK
   signaling pathways ([56]Lu et al., 2020a; [57]Li et al., 2021).
   Similarly, the Zhuyu pill, a combination of CF with Tetradium
   ruticarpum (A. Jussieu) T. G. Hartley (TR) in a 1:1 ratio, exhibited a
   significant hypolipidemic effect through the gut-liver axis and the
   NF-κB signaling pathway ([58]Pan et al., 2023; [59]Xu et al., 2023).
   Although CF has shown therapeutic efficacy in various diseases, further
   investigations are required to explore the impact of different dosages
   of CF or combinations with other agents on its effectiveness.
   Therefore, in treating cholestasis, the CF dose and its possible
   combination with other botanical drugs may vary according to specific
   conditions.

   The efficacy of TCM botanical drugs in clearing heat, eliminating
   dampness, and detoxification is frequently assessed by measuring its
   anti-inflammatory, hypolipidemic, and anti-oxidative stress effects,
   respectively ([60]Zhang et al., 2018; [61]Lu et al., 2020b; [62]Shou
   and Shaw, 2023). Because mechanisms involved in the pathology of
   cholestasis include inflammatory reactions, lipid metabolism disorders,
   and increased oxidative stress ([63]Li et al., 2022a; [64]Labiano et
   al., 2022), CF may be effective in treating cholestasis by having
   anti-inflammatory effects, promoting lipid metabolism, and reducing
   oxidative stress. Our previous study ([65]Han et al., 2023a) found that
   CF and TR in a 1:1 ratio could treat cholestasis by regulating lipid
   and bile acid metabolism. It was unclear, however, whether the
   effectiveness of CF in cholestasis was due to its anti-inflammatory
   effects, its enhancement of lipid metabolism, or its resistance to
   oxidative stress. More, the therapeutic efficacy of CF in the treatment
   of cholestasis may be dose dependent or may be altered when combined
   with TR.

   The effects of CF doses, alone or combined with TR, were therefore
   evaluated in a rat model of cholestasis. In addition, the biological
   mechanisms leading to differences in efficacy were analyzed by fecal
   metabolome sequencing and fecal microbial homeostasis. The effects of
   CF dosage and compatibility on its therapeutic efficacy in the
   treatment of cholestasis were analyzed, providing a biological basis
   for the effects of dosage and compatibility on the efficacy of drugs in
   TCM.

2 Materials and methods

2.1 Reagent preparation

   Coptis chinensis Franch. and T. ruticarpum (A. Jussieu) T. G. Hartley
   were purchased from Beijing Tongrentang Co., Ltd. (China).
   Ursodeoxycholic acid (UDCA), α-naphthylisothiocyanate (ANIT), and
   sodium pentobarbital were obtained from Merck Pharmaceuticals, Inc.
   (Germany); and olive oil was from Shanghai Yi En Chemical Technology
   Co.

2.2 Drug preparation and identification of active metabolites

   The characteristics of the botanical drugs used in these four
   combinations are shown in [66]Table 1. The dosage of each medicinal
   plant was based on the dosage range specified in the "Pharmacopoeia of
   the People’s Republic of China.” Each group of botanical drugs was
   prepared according to the decoction method stipulated in the "14th
   Five-Year Plan” of the National Higher Education Materials on TCM.
   Briefly, each group of botanical drugs was mixed separately and
   immersed in 20 times the volume of purified water. Heating was started
   after 30 min and continued for an additional 30 min. The liquid was
   filtered and collected; the above procedure was repeated; and the
   twice-collected liquid was mixed and stored at −20°C.

TABLE 1.

   Characteristics of the botanical drugs in this study.
   Group Chinese name Botanical name[67] ^a Genus family Batch number
   Medicinal parts Origin Weight (g)
   CF_L Huanglian Coptis chinensis Franch Ranunculaceae 220701 Dried root
   Chongqing, China 3
   CF_H Huanglian Coptis chinensis Franch Ranunculaceae 220701 Dried root
   Chongqing, China 6
   CT_L Huanglian Coptis chinensis Franch Ranunculaceae 220701 Dried root
   Chongqing, China 3
   Wuzhuyu Tetradium ruticarpum (A. Jussieu) T. G. Hartley Rutaceae
   220416008 Dried and ripe seed Guizhou, China 3
   CT_H Huanglian Coptis chinensis Franch Ranunculaceae 220701 Dried root
   Chongqing, China 6
   Wuzhuyu Tetradium ruticarpum (A. Jussieu) T. G. Hartley Rutaceae
   220416008 Dried and ripe seed Guizhou, China 3
   [68]Open in a new tab
   ^^a

   The plant name was verified using [69]http://www.theplantlist.org.

   The active metabolites in these herbal decoctions were identified by
   Q-Orbitrap high-resolution LC-MS. Information on the equipment used,
   sample handling procedures, mass spectrometry conditions, and
   chromatographic conditions is included in Supplementary Material 1. The
   decoctions were subjected to high-resolution liquid chromatography,
   with the results collected using CD 3.3 (Compound Discoverer 3.3,
   Thermo Fisher Scientific) and compared with the database (mzCloud,
   [70]https://www.mzcloud.org/) to identify the compounds. Determination
   of the activity of orally administered Chinese botanical drugs requires
   overcoming barriers due to absorption, distribution, metabolism, and
   excretion processes. The active metabolites obtained from the
   comparison were further screened by assessing their oral
   bioavailability (OB) ([71]Xu et al., 2012) and drug-likeness (DL), with
   substances having a DL index ≥0.18 considered highly drug-like ([72]Guo
   et al., 2019). The OB and DL of each active metabolite was assessed
   using the TCMSP database
   ([73]https://old.tcmsp-e.com/molecule.php?qn=2649). Active metabolites
   were screened based on their OB, DL, and comparison with the database
   (mzCloud, [74]https://www.mzcloud.org/), with active metabolites
   regarded as molecules with an OB ≥ 30%, a DL ≥ 0.18, and score of an
   mzCloud best match ≥80.

2.3 Animals and treatments

   Thie animal protocol was approved by the Animal Ethics Committee of
   Chengdu University of Traditional Chinese Medicine (Experimental Animal
   Welfare Ethics Review Certificate No. 2023024), and the animals were
   handled strictly according to internationally recognized animal
   management and rules.

   The rat model, the administration of drugs by gavage, and the
   procedures for anesthesia, blood collection, and extraction of liver
   tissues have been described ([75]Yu et al., 2022a). Briefly, 42 healthy
   male Sprague Dawley rats weighing 250 ± 20 g were purchased from
   Chengdu Da Shuo Experimental Animal Co., Ltd., production license
   number SCXK (CHUAN) 2020-0030. After 6 days of acclimatization feeding,
   the rats were randomly divided into seven groups of six rats each: the
   control group (Control), the model group (Model), the CF low dose group
   (CF_L), the CF high dose group (CF_H), the CF low dose CF plus TR group
   (CT_L), the CF high dose plus TR group (CT_H), and the positive control
   group (UDCA). [76]Figure 1. shows the entire process of model
   construction and drug administration by gavage. Cholestasis in rats was
   induced by intragastric administration of ANIT, at a dose of 50 mg/kg,
   dissolved in olive oil. Intragastric administration of CF and CT was
   determined relative to body surface area. After gavage administration
   on day 17, all rats were fasted for 16 h. After collecting fresh feces
   from each rat on day 18, the rats were anesthetized by intraperitoneal
   injection of sodium pentobarbital 30 mg/kg. Blood samples were
   collected, the rats were sacrificed, and liver tissue samples were
   collected. Feces and liver tissues were frozen and stored at −80°C.

FIGURE 1.

   [77]FIGURE 1
   [78]Open in a new tab

   Animal Experimental Procedures. Cholestasis model construction; gavage
   administration; fecal collection; anesthesia; blood and liver tissue
   collection.

2.4 Liver function assays

   Rat blood samples were centrifuged at 3,500 × g for 15 min at 4°C to
   obtain serum. ALT, AST, ALP, γ-GT, DBIL, TBIL, and TBA concentrations
   in serum were determined using a fully automated biochemical analyzer
   (BS-240VET). Liver tissue samples were fixed with 4% paraformaldehyde,
   washed with water, dehydrated, embedded, and sectioned. The sections
   were stained with HE and examined under a microscope for pathological
   determination.

2.5 Assessments of anti-inflammatory, hypolipidemic, and anti-oxidative
stress effects

   The anti-inflammatory effects of treatment were evaluated by
   determining the levels of expression of TNF-α, IL-1β, IL-6, and IL-10
   mRNAs in rat liver tissue by real-time quantitative PCR (qRT-PCR),
   using qRT-PCR primers ([79]Table 2) based on the mRNA sequences in the
   NCBI database.

TABLE 2.

   qRT-PCR primers used in this study.
   Genes Forward primer (5′–3′) Reverse primer (5′–3′) Product length (bp)
   TNF-α GGT​GCC​TAT​GTC​TCA​GCC​TCT​T GCC​ATA​GAA​CTG​ATG​AGA​GGG​AG 138
   IL-1β GTG​GCT​GTG​GAG​AAG​CTG​TGG CGG​AGC​CTG​TAG​TGC​AGT​TGT​C 147
   IL-6 CCA​CTC​CCA​ACA​GAC​CTG​TCT​A CTG​CAA​GCC​AGT​TTG​GTA​GCA​TC 192
   IL-10 AGC​CTT​ATC​GGA​AAT​GAT​CCA​G GGC​CTT​GTA​GAC​ACC​TTG​GT 229
   [80]Open in a new tab

   The effect of regulating lipid metabolism was evaluated by staining
   liver tissue with oil red O, as well as by measuring TC and TG
   concentrations in blood samples. The serum concentrations of GSH, ROS,
   NO, MDA, and SOD were determined by micro-enzyme assay (cat. no.
   A006-2), enzyme-linked immunosorbent assay (cat. no. YJ206302),
   colorimetry (cat. no. E-BC-K035-S), tribarbituric acid assay (cat. no.
   A003-1), and hydroxylamine assay (cat. no. A001-1), respectively.

2.6 Fecal metabolomics and analysis of microbial diversity

   Metabolites in each group of rats were analyzed by gas
   chromatography-mass spectrometry (GC-MS). The analytical process
   included metabolite extraction and derivatization, detection by GC-MS,
   data pre-processing, and statistical analysis. Additionally, 16S rRNA
   amplicons were sequenced to determine the fecal microbial
   characteristics of rats in each group. This analysis included DNA
   extraction, PCR amplification, library construction and sequencing, and
   bioinformatics analysis. Both tests were performed by Shanghai OE
   Biomedical Technology Co., Ltd., and their methodology and procedure
   have been described ([81]Yu et al., 2021). Further details can be found
   in Supplementary Material 2.

2.7 Statistical analysis

   Differences among multiple groups were assessed by one-way ANOVA or the
   Kruskal Wallis test. All statistical analyses were performed using
   GraphPad Prism 9, with p < 0.05 considered statistically significant.

3 Results

3.1 Active metabolites of drugs in each group

   The active metabolites of medicinal plants observed in each group are
   shown in [82]Figure 2. The primary active metabolites in the CF_L and
   CF_H groups were berberine, glycitein, and arachidonic acid, whereas
   the primary active metabolites in the CT_L and CT_H groups were these
   three metabolites, along with evodiamine, catechin, isorhamnetin,
   obacunone, and quercetin ([83]Table 3).

FIGURE 2.

   [84]FIGURE 2
   [85]Open in a new tab

   Potential active metabolites of each group for botanical drugs. RT:
   Chromatographic retention time.

TABLE 3.

   All active metabolites of the botanical drugs in each group.
   Name Molecular formula RT (min) Score of mzCloud best match OB (%) DL
   Structural formula
   Berberine C[20]H[17]NO[4] 10.78 93.3 36.86 0.78 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx1.jpg
   Glycitein C[16]H[12]O[5] 17.67 97 50.48 0.24 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx2.jpg
   Arachidonic acid C[20]H[32]O[2] 22.03 91.6 45.57 0.20 graphic file with
   name FPHAR_fphar-2024-1372527_wc_tfx3.jpg
   Evodiamine C[19]H[17]N[3]O 16.71 98 86.02 0.64 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx4.jpg
   Catechin C[15]H[14]O[6] 9.04 97 54.83 0.24 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx5.jpg
   Isorhamnetin C[16]H[12]O[7] 13.72 99.7 49.60 0.31 graphic file with
   name FPHAR_fphar-2024-1372527_wc_tfx6.jpg
   Obacunone C[26] H[30]O[7] 15.97 85.6 43.29 0.77 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx7.jpg
   Quercetin C[15]H[10]O[7] 12.92 95.9 46.43 0.28 graphic file with name
   FPHAR_fphar-2024-1372527_wc_tfx8.jpg
   [86]Open in a new tab

   Chemical structural formulas derived from MedChemExpress
   ([87]https://www.medchemexpress.cn/).

3.2 Serum biochemistry and histopathological analysis

   Low and high doses of CF, as well as their combinations with TR,
   exhibited significant anti-cholestatic activity, with a therapeutic
   efficacy similar to that of UDCA ([88]Figures 3A–G). Pathohistological
   examination showed that all groups of botanical drugs reduced the
   inflammation and liver cell necrosis induced by ANIT ([89]Figures
   3H–O). Taken together, these findings indicated that CF and CT had
   significant therapeutic efficacy against cholestasis.

FIGURE 3.

   [90]FIGURE 3
   [91]Open in a new tab

   Liver function assay. Serum biochemical indices (A) ALT, (B) AST, (C)
   ALP, (D) γ-GT, (E) DBIL, (F) TBIL, (G) (TBA), (H) Liver inflammation
   and necrosis score, n = 6, ***/**/*, p < 0.001/p < 0.01/p < 0.05, ns,
   not significant. (I–O) Histopathological examination at 100x and 200x.

3.3 Assessment of anti-inflammatory effects

   CF_L significantly reduced the concentrations of inflammatory factors
   IL-1β and IL-6 in liver tissues of cholestatic rats, showing some
   anti-inflammatory efficacy, whereas CF_H significantly reduced IL-1β,
   TNF-α, IL-6, and increased IL-10 ([92]Figure 4). CF had significant
   anti-inflammatory effects, which were more pronounced at high than low
   CF doses, indicating a quantitative relationship between CF dose and
   anti-inflammatory activity. The addition of TR, however, did not
   enhance the anti-inflammatory effects of both low and high doses of CF.
   Interestingly, CT_H was less effective than CF_L in reducing IL-6 and
   increasing IL-10 concentrations, suggesting an antagonism between the
   anti-inflammatory effects of the two drugs in the treatment of
   cholestasis.

FIGURE 4.

   [93]FIGURE 4
   [94]Open in a new tab

   Levels of inflammatory factors in liver tissue of rats in each group.
   (A) IL-10, (B) IL-1β, (C) TNF-α, (D) IL-6. ***/**/*, p < 0.001/p <
   0.01/p < 0.05, ns, not significant.

3.4 Assessment of hypolipidemic effects

   The effects of treatment on lipid metabolism were determined by
   measuring the levels of lipids in serum and liver samples. Using an
   automatic biochemical analyzer, lipid-related indices ([95]Figures
   5A–D) were detected in the serum of each group of rats. Steatosis was
   assessed by oil red O staining of liver tissue ([96]Figure 5E). The
   results indicated that either CF or CT could significantly reduce the
   accumulation of lipid droplets in the liver tissue of cholestatic rats
   and improve lipid metabolism disorder. CT_L had a significantly more
   substantial hypolipidemic effect than CF_L, suggesting that CF and TR
   had a synergistic hypolipidemic effect in the treatment of cholestasis.

FIGURE 5.

   [97]FIGURE 5
   [98]Open in a new tab

   Assessment of lipid metabolism disorders. (A) TC, (B) TG, (C) LDL-C,
   (D) HDL-C, (E) Liver tissue oil red O staining. ***/**/*, p < 0.001/p <
   0.01/p < 0.05, ns, not significant.

3.5 Assessment of anti-oxidative stress effects

   The anti-oxidative stress effects of treatment were determined by
   measuring serum concentrations of GSH, ROS, SOD, NO, and MDA in these
   rats ([99]Figure 6). CF_L did not show a significant anti-oxidative
   stress effect, whereas CF_H had a highly significant anti-oxidant
   effect, perhaps because only high doses of CF have anti-oxidant stress
   efficacy. The addition of TR, however, did not significantly enhance
   the anti-oxidative stress effect of CF.

FIGURE 6.

   [100]FIGURE 6
   [101]Open in a new tab

   Oxidative stress indicator analysis. (A) GSH, (B) ROS, (C) NO, (D) SOD,
   (E) MDA. ***/**/*, p < 0.001/p < 0.01/p < 0.05, ns, not significant.

3.6 Multivariate statistical analysis of GC-MS results

   The overall distribution among the samples and the stability of the
   whole analysis process were initially determined by unsupervised
   principal component analysis (PCA) ([102]Figures 7B–F). Subsequently,
   supervised orthogonal partial least squares analysis (OPLS-DA) was used
   to differentiate the overall differences in metabolic profiles among
   the groups and to identify the differentially expressed metabolites in
   these groups ([103]Figures 7G–J). The quality of the model was
   evaluated by using seven cycles of interactive validation and 200
   response ordering tests to prevent model overfitting ([104]Figures
   7K–N), with the model parameters shown in [105]Figure 7A. The above
   analyses showed significant metabolic differences between the CF_H and
   CF_L, the CT_L and CF_L, and the CT_H and CF_H groups.

FIGURE 7.

   [106]FIGURE 7
   [107]Open in a new tab

   Multivariate statistical analysis of metabolic profiles. (A) Parameters
   of PCA and OPLS-DA, (B) PCA score plot of all samples, (C–F) PCA
   analysis, (G–J) OLS-DA analysis, (K–N) 200-permutation test.

3.7 Screening of differentially expressed metabolites and pathway enrichment
analysis

   Metabolites differentially expressed by pairs of groups were screened
   by unidimensional and multidimensional analyses. In the OPLS-DA
   analysis, variables important in projection (VIP) were used to measure
   the strength of the influence of the metabolite expression pattern on
   the classification discrimination of each group of samples and to
   screen for significant differences in metabolites. Significant
   differences in the levels of different metabolites between groups were
   verified by t-tests. The criteria for screening were VIP >1 and p <
   0.05, with volcano plots ([108]Figures 8A–D) showing the expression
   trends and numbers of differential metabolites in between group
   comparisons. Comparisons of the Model and Control groups showed that
   617 metabolites were downregulated and 479 upregulated in the former.
   Comparisons of the CF_H and CF_L groups identified 222 metabolites that
   were downregulated and 184 that were upregulated in the former.
   Furthermore, comparisons of the CT_L and CF_L groups found 255
   metabolites downregulated and 307 upregulated in the former, whereas
   comparisons of the CT_H and CF_H groups identified 269 metabolites
   downregulated and 288 upregulated in the former. Cluster statistical
   analyses of between group comparisons screened the top 50
   differentially expressed metabolites ([109]Figures 8E–H). Differences
   in the therapeutic effects on cholestasis produced by different doses
   of CF and by combination with TR may be associated with the
   differential expression of these metabolites.

FIGURE 8.

   [110]FIGURE 8
   [111]Open in a new tab

   Differential metabolites screening and functional enrichment analysis.
   (A–D) Volcano plot of rat fecal metabolites, (E–H) Clustering heat map
   of rat fecal metabolites, (I–L) Differential metabolites KEGG
   enrichment analysis.

   The presence of differentially expressed metabolites was likely due to
   differences in the anti-cholestatic efficacy of various doses of CF and
   their combinations with TR. Pathway enrichment analysis of these
   differentially expressed metabolites may reveal the mechanisms
   underlying these differences in anti-cholestatic metabolic pathways.
   KEGG enrichment analysis identified overlapping pathways in comparisons
   of the Model and Control groups ([112]Figure 8I) and the CF_H and CF_L
   groups. These pathways included those involving ABC transporters,
   steroid biosynthesis, and linoleic acid, arachidonic acid, and tyrosine
   metabolism ([113]Figure 8J). These pathways may be responsible for the
   differences in the anti-inflammatory, hypolipidemic, and anti-oxidative
   stress effects of high and low doses of CF. Differences in the efficacy
   of CT_L and CF_L in treating cholestasis were found to be related to
   differences in the biosynthesis of unsaturated fatty acids, in ABC
   transporters and in CAMP signaling pathway. The difference in efficacy
   of CT_H and CF_H was associated with the modulation of linoleic acid
   metabolism ([114]Figures 8K, L).

3.8 Analysis of the diversity of fecal microorganisms

   Based on the results of amplicon sequence variant (ASV) clustering
   analysis, the number of shared and unique ASVs in the rat groups were
   analyzed and plotted as a flower plot ([115]Figure 9A). Three ASVs were
   shared by the Control, Model, CF_L, CF_H, CT_L and CT_H groups.
   [116]Figure 9B summarizes the relative abundances of each sample at
   different taxonomic levels, including of phylum, class, order, family,
   genus, and species.

FIGURE 9.

   [117]FIGURE 9
   [118]Open in a new tab

   Analysis of fecal microbial diversity. (A) Amplicon Sequence Variant
   (ASVs)-based petal maps. (B) Statistics on the distribution of
   microbial communities in the samples. (C) Specaccum Species
   accumulation curve. (D) ASV diversity index dilution curve. (E) Rank
   abundance curve. (F–J) PCoA analysis. (K–N) NMDS analysis.

   The reasonableness of the sequencing volume of the samples was
   evaluated by alpha diversity analysis, with this evaluation including
   the adequacy of the sampling volume, and the richness and homogeneity
   of the species in each sample ([119]Figures 9C–E). Between-group
   differences in diversity were evaluated by beta diversity analysis,
   including PCoA and NMDS analyses ([120]Figures 9F–N). Fecal microbial
   communities were found to differ significantly in the CF_H and CF_L,
   CT_L and CF_L, and CT_H and CF_H groups. These effects on the
   composition of the gut microbial community and its function may also be
   responsible for the differences in the efficacy of CF in treating
   cholestasis at different doses and after combination with TR.

3.9 Multivariate statistical analysis of fecal microorganisms

   The species of differentially present microorganisms and their
   functions were further clarified by LEfSe and PICRUSt2 analyses.
   [121]Figure 10A shows the significant species with relatively high
   abundance at the phylum, class, order, family, and genus levels, as
   determined by LEfSe analyses. [122]Figures 10B–J show the top 10
   species that differed at the genus level in between-group comparisons.
   Comparisons of the microbiomes obtained from the Model and Control
   groups identified Alloprevotella and Prevotella as being differentially
   expressed in the CF_H and CF_L groups, Prevotella and UCG-005 as being
   differentially expressed in the CT_L and CF_L groups, and Lactobacillus
   and Prevotella being differentially expressed in the CT_H and CT_L
   groups. 16S-based prediction of KEGG function revealed that, in
   treating cholestasis, the difference between CF_H and CF_L may be
   related to the biosynthesis of amino acids, the difference between CT_L
   and CF_L may be related to 2-oxocarboxylic acid metabolism, and the
   difference between CT_H and CF_H may be related to the biosynthesis of
   amino acids.

FIGURE 10.

   [123]FIGURE 10
   [124]Open in a new tab

   Statistical analysis of microbial multivariate variables. (A) LEfSe
   analysis, differential species annotation branch. (B) Histogram of LDA
   value distribution. (C, D, G, H) Top10 species with differential
   abundance at genus level. (E, F, I, J) KEGG function prediction based
   on 16S rRNA gene sequence.

3.10 Correlations between metabolites and microorganisms

   Based on fecal metabolomics and analyses of microbial diversity
   analyses, differentially expressed metabolites and microorganisms were
   subjected to Spearman correlation analyses, thereby assessing the
   relationship between fecal metabolites and genera of fecal microbiota
   ([125]Figure 11). Fecal metabolites were found to strongly correlate
   with fecal microbiota. Differences in the therapeutic effects of
   different doses of CF and different doses of CF paired with TR on
   cholestasis may be due to differences in the regulation of both fecal
   metabolites and fecal microbiota.

FIGURE 11.

   [126]FIGURE 11
   [127]Open in a new tab

   Correlation analysis of fecal metabolites with fecal microbiota genera
   based on the Spearman algorithm. (A) Model vs Control; (B) ZYP_H vs
   Model; (C) CT_L vs CF_L; (D) CT_H vs CF_H. Red is a positive
   correlation, blue is a negative correlation, with darker colors
   indicating a stronger correlation. ***/**/*, p < 0.001/p < 0.01/p <
   0.05.

4 Discussion

   Most Chinese botanical drugs have multiple effects. In specific
   applications, how to control the direction of the effects of Chinese
   herbal medication by adjusting the dosage and selecting the combination
   is a classic problem in Chinese herbal medicine prescription science.
   CF and its commonly used drug combination CT are widely used in
   treating cholestasis ([128]Yu et al., 2022a; [129]Han et al., 2023b).
   ALT and AST directly reflected the damage degree of hepatocytes, and
   ALP and γ-GT were specific and significant markers of cholestasis
   ([130]Han et al., 2019; [131]Berköz et al., 2021); TBIL, DBIL, and TBA
   are the crucial indices of bile markers ([132]Zhao et al., 2017). The
   degree of liver tissue damage and inflammation can be visually assessed
   by pathological histological observation. In the present study, serum
   biochemical indices and histopathological observations of the liver
   showed significant therapeutic effects of both CF and CT on
   cholestasis. On this basis, we investigated the characteristics of the
   therapeutic effects of CF on cholestasis at different doses (CF_L,
   CF_H) and in combination with TR (CT_L, CT_H) through the three
   perspectives of anti-inflammatory effect, hypolipidemic effect, and
   anti-oxidative stress effect, respectively. Levels of IL-6, TNF-α,
   IL-10, and IL-1β in liver tissue reflect the degree of hepatic
   inflammation caused by cholestasis ([133]Wei et al., 2020;
   [134]Gallucci et al., 2022), while serum levels of TC, TG, LDL-C, and
   HDL-C reflect lipid metabolism and oil red O staining visualizes lipid
   accumulation in liver tissue ([135]Sheng et al., 2019). ROS, GSH, SOD,
   MDA, and NO reflect cytotoxicity and hepatic injury caused by the
   accumulation of reactive oxygen species ([136]González et al., 2011;
   [137]Yao et al., 2017). On the dose, the anti-inflammatory,
   hypolipidemic, and anti-oxidative stress effects of CF showed a
   significant quantitative dependence, in which the anti-inflammatory and
   anti-oxidative stress effects were enhanced with increasing dose; on
   the contrary, the hypolipidemic effects were weakened with increasing
   dose. Interestingly, after CF on the combined TR, the two have a
   synergistic effect regarding hypolipidemia and a potential antagonistic
   effect regarding anti-inflammation.

   Gut microorganisms produce a range of metabolites during colonization
   and reproduction that directly and indirectly affect host metabolic and
   immune responses ([138]Coker et al., 2022). Metabolomics technology is
   an important research method to investigate the effect mechanisms of
   Chinese medicines in treating diseases. To analyze the reasons for the
   above differences in efficacy, this study first used fecal metabolome
   sequencing, Model vs Control, CF_H vs CF_L, CT_L vs CF_L, and CT_H vs
   CF_H were screened for significant differential metabolites, and these
   metabolites were analyzed for functional enrichment, respectively.
   Linoleic acid promotes metabolism, regulates the endocrine system, and
   encourages lipid metabolism, among other functions ([139]Spector and
   Kim, 2015). It is also a catalyst for cholesterol metabolism, which
   reduces the levels of cholesterol and lipids in the blood
   ([140]Ebrahimi-Mameghani et al., 2016). Previous studies have shown
   that linoleic acid metabolism is closely related to inflammation and
   oxidative stress ([141]Khazen et al., 2007). When liver injury occurs,
   linoleic acid is released from phospholipids and further produces
   inflammatory mediators, and the expression of linoleic acid is a marker
   of liver injury ([142]Xu et al., 2021). Arachidonic acid plays a
   crucial role in allergy, inflammation, and other organ functional
   responses, and arachidonic acid metabolism can reflect, to some extent,
   the severity of inflammation ([143]Nakaya et al., 2000; [144]Canfora et
   al., 2015). Tyrosine is a significant substrate for endogenous
   peroxidases. The presence of tyrosine and its derivative in vivo and in
   vitro could ameliorate oxidative damage through ferryl heme reduction
   ([145]Lu et al., 2014). Additionally, high levels of tyrosine may
   promote fatty acid synthesis, further promoting liver fat deposition
   ([146]Jin et al., 2016).

   Various previous studies have shown that ecological disturbances in the
   gut microbiota are closely related to the development of cholestasis
   ([147]Tang et al., 2023; [148]Yu et al., 2023), and our preliminary
   study found that the equipotential pairing of CF and TR could have a
   positive intervention effect on cholestasis by interfering with gut
   microbial homeostasis and metabolic homeostasis ([149]Yu et al.,
   2022b). In this study, differential microbial communities were obtained
   by LEfSe analyses of between-group comparisons of Model vs Control,
   CF_H vs CF_L, CT_L vs CF_L, and CT_H vs CF_H, respectively. Prevotella
   is a symbiotic bacterium whose relative abundance has been reported to
   be associated with inflammation ([150]Ning et al., 2020; [151]Wang et
   al., 2020), with an enhanced ability to induce inflammatory mediators
   such as IL-6 and TNF-α ([152]Larsen, 2017). UCG-005 helps promote the
   production of short-chain fatty acids (SCFAs), which helps alleviate
   inflammation and lipid metabolism disorders ([153]Li et al., 2022b;
   [154]Shi et al., 2023). Lactobacillus increase fecal lipid excretion
   and thereby reduce hepatic lipid accumulation by improving the activity
   of bile salt hydrolytic enzymes and the number of unconjugated bile
   acids ([155]Janssen et al., 2017). Prediction of KEGG function in
   differential microorganisms showed that the difference between low-dose
   and high-dose CF for cholestasis was related to amino acid
   biosynthesis, whereas the difference between the therapeutic effects of
   CF and CT for cholestasis was related to 2-Oxocarboxylic acid
   metabolism and amino acid biosynthesis. These were similar to the
   results obtained from fecal metabolomics analyses. Additionally,
   correlation analyses of microorganisms and metabolites showed the
   existence of a relationship between the relative abundance of
   microorganisms and the levels of metabolites.

   The anti-inflammatory, lipid-lowering, and anti-cholestatic effects of
   CF have been reported in many papers ([156]Wang et al., 2019; [157]Hu
   et al., 2022; [158]Lan et al., 2022), and our previous studies have
   confirmed that the combination of CF and TR in the treatment of
   cholestasis is associated with regulating the expression of genes
   related to lipid metabolism ([159]Han et al., 2023a). The effect of the
   combination of CF and TR in the regulation of disorders of lipid
   metabolism has also been demonstrated by other scholars in their
   studies ([160]Zhang et al., 2022; [161]Xu et al., 2023). Amino acid
   metabolism is closely related to oxidative stress, e.g., tryptophan is
   a necessary substrate for melatonin synthesis, while melatonin has a
   significant anti-oxidative stress effect for treating cholestasis
   ([162]Yu et al., 2018). In future studies, we will continue to
   investigate the specific mechanisms by which different dosages and
   combinations of TR alter CF anti-cholestasis by modulating lipid and
   amino acid metabolism.

5 Conclusion

   General, in the treatment of cholestasis, the efficacy of low-dose CF
   was biased towards hypolipidemic, and high-dose CF was biased towards
   anti-inflammatory effects; furthermore, CF and TR had synergistic
   effects on hypolipidemic effects and potential antagonistic effects on
   anti-inflammatory effects. On biological mechanisms, this may be due to
   differences in the dual effects on gut microbiology and metabolic
   homeostasis, of which lipid metabolism and amino acid metabolism are
   critical events. This study elucidates the mechanism of CF in the
   treatment of cholestasis and provides new ideas for the clinical
   application of CF in the treatment of cholestasis.

Acknowledgments