Interaction between a Sulfated Polysaccharide from Sea Cucumber and Gut Microbiota Influences the Fat Metabolism in Rats

Abstract

Due to its significant physiological effects, a sulfated polysaccharide has been considered an important nutrient of sea cucumber, but its metabolism in vivo is still unclear. The present study investigated the metabolism of a sea cucumber sulfated polysaccharide (SCSP) in rats and its influence on the metabolite profiles. The quantification by HPLC-MS/MS revealed that the blood level of SCSP achieved a maximum of 54.0 ± 4.8 μg/mL at 2 h after gavage, almost no SCSP was excreted through urine, and 55.4 ± 29.8% of SCSP was eliminated through feces within 24 h. These results prove the utilization of SCSP by gut microbiota, and a further microbiota sequencing analysis indicated that the SCSP utilization in the gut was positively correlated with Muribaculaceae and Clostridia_UCG-014. In addition, the non-targeted metabolomic analysis demonstrated the significant effects of SCSP administration on the metabolite profiles of blood, urine, and feces. It is worth noting that the SCSP supplement decreased palmitic acid, stearic acid, and oleic acid in blood and urine while increasing stearic acid, linoleic acid, and γ-linolenic acid in feces, suggesting the inhibition of fat absorption and the enhancement of fat excretion by SCSP, respectively. The present study shed light on the metabolism in vivo and the influence on the fat metabolism of SCSP.

1. Introduction

Sea cucumber is valuable seafood, and it has been considered as a functional food and consumed traditionally in Asian countries, especially in China, Japan, and Korea [1]. A sea cucumber sulfated polysaccharide (SCSP) is the critical nutrient in sea cucumber, and it consists of two sulphated polysaccharides, namely fucosylated chondroitin sulphate and fucoidan sulphate [1,2]. The fucosylated chondroitin sulphate has a chondroitin core and a unique sulfated fucose side chain [3]. Fucoidan sulphate from sea cucumber is a linear polysaccharide consisting of α1→3 linked fucose repeating units with various sulfation patterns [3]. SCSP has significant physiological effects such as anticancer [4], anti-bacterial activity [5], hypolipidemic [6], immune regulation [3,7] and anti-inflammation [8]. However, the underlying mechanism of its effects in vivo is still unclear. It has been proved that SCSP cannot be digested by gastrointestinal enzymes or acid liquid [9,10]. Moreover, as a macromolecule, it is difficult for SCSP to travel through intestinal epithelial cells, which could be inferred through the studies on other macromolecules [11]. Thus, more efforts are needed to reveal the action pathway of SCSP after oral supplementation.

Recently, more and more reports have verified that oral administration of indigestible polysaccharides could regulate gut microbiota so as to benefit the host health [12]. Our previous report has revealed that SCSP can effectively prevent diet-induced obesity through modulating the composition of gut microbiota [13]. It has been proposed that indigestible polysaccharides can be metabolized by gut microbiota to produce bioactive metabolites, such as short-chain fatty acids, demonstrating beneficial effects on host health [14]. However, little evidence for the polysaccharide consumption by gut microbiota in vivo has been reported. Sulfated polysaccharides are more resistant to gut microbiota due to their sulfate groups [15,16]. Our previous study found that a part of SCSP could be fermented by fecal microbiota in vitro. But the utilization degree of SCSP by gut microbiota in vivo is still unknown.

Metabolomics have been widely used to analyze what occurs in diseases’ process by identifying potential biomarkers and the related metabolic pathway [17]. However, increasing evidence has suggested that some metabolites produced by gut microbiota have potent functions for host energy metabolism [18,19]. Non-targeted metabolomics are a comprehensive approach for detecting metabolites as much as possible, and it is more robust in characterizing the metabolism profile and finding involved metabolites without targets [20]. Thus, in the present study, nontargeted metabolomics have been applied to monitor the regulation of SCSP on the metabolites in blood, urine, and feces to reveal the underlying action mechanism of SCSP.

The present study aimed to demonstrate the absorption, metabolism, and excretion of sea cucumber polysaccharides in vivo, and to analyze the effects of SCSP administration on the metabolite profiles of blood, urine, and feces, thus revealing the action pathway of sea cucumber polysaccharides in vivo.

2. Materials and Methods

2.1. Materials

The sea cucumber sulfated polysaccharide (SCSP) was extracted from Stichopus japonicus as previously reported [2]. This fraction (SCSP) was characterized in our previous study. It was composed of fucosylated chondroitin sulfate (179.4 kDa) and fucoidan (>670 kDa) with the mass ratio of 1.00:1.07, as evaluated by gel permeation chromatography (GPC). Furthermore, HPLC analyzed after acid hydrolysis and derivatization with PMP demonstrated that the molar ratio of sulfate/uronic acid/fucose (Fuc)/galactosamine (GalN) in SCSP was 7.6:0.8:9.1:1.0. 1-Phenyl-3-methyl-5-pyrazoline (PMP) was purchased from China National Pharmaceutical Group Co., Ltd. (Beijing, China). Trifluoroacetic acid, ammonium acetate, and formic acid were brought from Aladdin reagent Co., Ltd. (Shanghai, China). 1-Methylnicotinamide-d₃ iodide, acetyl-L-carnitine-(N-methyl-d₃), and DL-glutamic acid were purchased from Cambridge Isotope Laboratories Inc. (Cambridge, CA, USA). 12-[(Cyclohexylcarbamoyl) amino] dodecanoic acid and chondroitin sulfate (shark) were both from Sigma-Aldrich Co. (St. Louis, MI, USA).

2.2. Animals

All animal experiments were performed in accordance with the guidelines for care and use of laboratory animals of Dalian Polytechnic University, and the experiment was approved by the Animal Ethics Committee of Dalian Polytechnic University (ID DLPU2018008).

Eighteen male Sprague Dawley (SD) rats (300 ± 20 g) were purchased from Liaoning Changsheng Biotechnology Company (Benxi, China). The rats were kept under standard conditions with a 12 h light–dark cycle, 23 ± 2 °C ambient temperature, and 55 ± 10% relative humidity. The feed was composed of corn, soybean meal, flour, bran, fish flour, salt, calcium hydrogen phosphate, rock flour, multivitamins, multiple trace elements, amino acids, etc., and more details are shown in Supplemental Table S5. The rats were acclimatized in clean cages for a fortnight prior to the experiment and weighed (310 ± 20 g), and then randomly divided into two groups: the Control group (n = 9) and the SCSP group (n = 9, named S1~S9).

To prevent the effects of food on SCSP absorption, the rats were fasted for 12 h before SCSP administration but drank water freely. The rats in the SCSP group were gavaged with 150 mg/kg of the SCSP solution (2 mL), and the Control group were gavaged with the same volume of water. Then, the rats were put into metabolic cages and fed normally after 4 h. Fecal and urine samples were collected at 24 h and 48 h (frozen at −80 °C) to ensure that SCSP was wholly excreted. After 1 day, 150 mg/kg of the SCSP solution was gavaged again. Then, the blood was extracted from the tail of the rats at 0 h, 0.5 h, 1 h, 2 h, 4 h, 6 h, 8 h, and 12 h after administration, and placed in centrifuge tubes containing an EDTA anticoagulant. At 24 h, the rats were anesthetized with ether, and blood samples were collected from the orbital vein and placed in centrifuge tubes containing the EDTA anticoagulant and ordinary centrifuge tubes. The coagulation time of the blood collected at 2 h after gavage from the broken tail of rats using a capillary was measured according to previously described reports [21,22].

2.3. Quantification of SCSP in Plasma, Feces, and Urine

Firstly, SCSP in plasma and feces was isolated. Plasma samples (0.1 mL) were suspended in a mixture of 0.5 mL of 2.6 M trifluoroacetic acid (TFA) and 0.4 mL of water. Dried fecal samples (0.20 g) were dissolved in 4 mL of water, and after centrifugation at 8000 rpm for 10 min, the supernatant (1 mL) was collected and mixed with ethanol (4 mL) and kept at 4 °C overnight. Then, the precipitate was collected after centrifugation (4000 rpm, 10 min).

Quantification of SCSP was conducted as previously described [2]. Briefly, the collected precipitate containing SCSP was redissolved in water (5 mL). After that, 0.5 mL of the solution was mixed with 0.5 mL of 2.6 M TFA. Urine samples (10 mL) were concentrated to 1 mL using a rotary evaporator at 50 °C under a vacuum. Then, a four-fold volume of ethanol was added, and the mixture stood at 4 °C overnight. After that, the precipitate was collected by centrifugation (4000 rpm, 10 min), and dissolved in 1 mL of 1.3 M TFA.

Immediately after the above treatment, the samples were heated at 105 °C for 3 h in sealed tubes for the acid hydrolysis. Then, the resulting solutions were dried with a vacuum concentrator (LaboGene Aps., Lynge, Denmark). Then, 0.5 mL of methanol was added to the solution, which was dried again. This procedure was repeated thrice to remove TFA thoroughly. Then, 100 μL of 1 mg/mL lactose was added as an internal standard, and the mixtures were resolved in a solution composed of 400 μL of ammonia and 400 μL of a 0.3 M PMP methanolic solution. After heating at 70 °C for 30 min in a water bath, the solution was dried with the vacuum concentrator. Thus, the PMP derivatives of hydrolysates of SCSP were prepared for an ESI-MS/MS analysis.

The chromatography separation was carried out on a Shimadzu HPLC system (LC-20ADXR pumps, SIL-20AXP Autosampler, Kyoto, Japan) with a Thermo Scientific (Waltham, MA, USA) Hypersil Gold column (150 × 2.1 mm, 5 μm). A 20 mM ammonium acetate solution and acetonitrile (85:15, v/v) were used as the mobile phase at a flow rate of 0.5 mL/min, and the column temperature was maintained at 30 °C. The ESI-MS/MS analysis was performed on a Q-trap 4000 triple-quadrupole mass spectrometer (AB Sciex, Framingham, MA, USA) in the positive-ion multiple reaction monitoring (MRM) mode. Mass spectrometry analysis parameters are provided in Supplemental Table S4.

2.4. Sequencing Analysis of the Gut Microbiota

Sequencing was carried out on an Illumina MiSeq PE250 platform (Novogene Genomics Technology Co., Ltd., Beijing, China, https://magic.novogene.com (accessed on 1 June 2021)). Briefly, Genomic DNA was isolated from fecal samples by the sodium dodecyl sulfate (SDS) method and assayed using agarose gel electrophoresis. After that, the genomic DNA was amplified with the 341F (5′-CCTACGGGNGGCWGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) primers specific for the V3–V4 region of the 16S rRNA gene. Sequencing libraries were generated using the Ion Plus Fragment Library Kit 48 rxns and assessed on the Qubit@ 2.0 fluorometer (Thermo Scientific, Waltham, MA, USA). Alpha diversity and rarefaction curves were analyzed using QIIME V1.7.0. Venn diagrams were constructed using R software package V3.0.3 and were used to compare and analyze differences in the composition of OTUs in the intestinal flora between groups. A principal coordinate analysis of PCoA and β-diversity was calculated using QIIME software V1.7.0 and presented using Stat, Ggplot2, and WGCNA packages in R software V2.15.3.

2.5. Analysis of Metabolites by UPLC-Q-TOF MS

According to the reported protocols [23], the serum sample (50 μL), the urine sample (150 μL), and the fecal sample (300 mg) were mixed with 200 μL of methanol (−20 °C), 300 μL of water, and 500 μL of a mixture (acetonitrile/methanol/water, 2:2:1, v/v/v), respectively. Then, 10 μL of a mixed internal standard solution containing 20 ng/mL of 12-[(cyclohexylcarbamoyl) amino] dodecanoic acid, 210 ng/mL of 1-methylnicotinamide-d₃ iodide, 51 ng/mL of acetyl-L-carnitine-(N-methyl-d₃), and 3500 ng/mL of DL-glutamic acid (2,4,4-d₃, 98%) was added. The mixture was vortexed for 30 s, and then stored in a refrigerator at −20 °C for 30 min. After that, the mixture was centrifuged at 12,000 g/min for 5 min at 4 °C and the supernatant was collected for a UPLC-Q-TOF MS analysis.

UPLC-Q-TOF MS analyses were performed on AB Sciex Triple TOF 5600 using both positive ion (PI) and negative ion (NI) modes. The chromatography separation was carried out using Waters Xselect @HSS T3 (2.5 μm, 100 mm × 2.1 mm) at a flow rate of 0.4 mL/min, and the column temperature was maintained at 30 °C. For the PI mode, the mobile phase was eluent A (0.1% formic acid in water, v/v) and eluent B (acetonitrile with 0.1% formic acid, v/v). For the NI mode, the mobile phase was eluent A (5 mM ammonium acetate in water) and eluent B (5 mM ammonium acetate in water/acetonitrile = 10:90, v/v). The solvent gradient was set as follows: 0–5 min, 0–20% B; 5–7 min, 20% B; 7–14 min, 20–100% B. The quality Control samples (QC) were prepared by mixing equal (10 μL) amounts of each serum sample. The AB Sciex triple TOF 5600 mass spectrometer was operated with ion source gas 1 of 55 arb, ion source gas 2 of 55 arb, curtain gas of 35 arb, a temperature of 550 °C, and ion spray voltage floating of 5500 V for the PI mode and −4500 V for the NI mode.

The collected raw data were converted to “abf” format and the converted files were imported into MSDIAL. A principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed with SIMCA 14.1 software after exportation. And then the database in MSDIAL was used to identify the metabolites with a VIP value greater than 1.0.

2.6. Statistical Analysis

All data are expressed as means ± standard deviations (SDs). Student’s t-test was used to evaluate the difference between two groups, and three groups were made by one-way ANOVA with Duncan’s test. p < 0.05 was considered to be significantly different. A multiple linear regression analysis was used to investigate the relationship between the utilization of SCSP and bacterial OTUs. Bacterial OUTs with >1% abundance were included in the regression model.

3. Results and Discussion

3.1. Absorption and Exertion of SCSP in Rats

In order to reveal the metabolism of SCSP in rats, SCSP in plasma, feces, and urine of rats after the gavage (46.5 mg) was quantified by HPLC-MS/MS. The method for the quantification of SCSP was validated for sensitivity, recovery, and repeatability (Supplemental Results). The results showed that the blood concentration of SCSP reached the maximum (54.0 ± 4.8 μg/mL) at 2 h (Figure 1A). Since the circulating blood volume of rats is generally about 11 mL, it could be estimated that 1.2% SCSP was in blood circulation at that time. As shown in

Table 1. Excreted amounts and ratios of SCSP in feces and urine.

Sample	Collecting Time (h)	0~24	24~48
Feces (n = 9)	SCSP amount (mg)	27.267 ± 14.662	0.0604 ± 0.083 a
	Excretion ratio (%)	55.42 ± 29.80	0.15 ± 0.17
Urine (n = 3)	SCSP amount (mg)	<0.1 a	<0.1 a
	Excretion ratio (%)	<0.2	<0.2

^a The data were not significantly different from those in Control group.

, SCSP in urine samples collected within 0~24 h and 24~48 h was nearly undetectable, and no more than 0.2% SCSP was excreted through urine as polymers. The same phenomenon has been previously reported [24]. Of note, 55.4 ± 29.8% of SCSP was detected in fecal samples within 24 h although there was great variability among individuals (Figure 1B). However, SCSP was barely detectable in feces after 24 h. From the above results, it could be concluded that the SCSP was mainly eliminated via feces within 24 h. Interestingly, a considerable proportion (~44%) of SCSP disappeared, indicating its degradation by intestinal flora. It has been reported that SCSP could be partially degraded by intestinal flora [25,26,27]. Moreover, the differences of SCSP contents in feces among rat individuals could be contributed to their diversity of intestinal microbiota communities [28]. As shown in Figure 1C, SCSP significantly prolonged coagulation time compared to the Control group (p < 0.01). Nadezhda E. Ustyuzhanina and R.J.C. Fonseca et al. had proved that fucosylated chondroitin sulfate in sea cucumber had an obvious anticoagulant effect by in vitro and in vivo experiments [29,30]. Our experiments also demonstrated the anticoagulant effect of gavaged SCSP, indicating that SCSP could be absorbed into the systemic circulation.

3.2. Relationship between Intestinal Flora and SCSP Utilization

The gut microbiota of the rats were analyzed through multiplex sequencing covering the V3–V4 regions of 16S rRNA, and the differences in the microbiota of the rat individuals were demonstrated. The relative abundances of microbiota at the phylum level (Figure 2A) showed that Bacteroidetes and Firmicutes were the dominant intestinal bacteria in these rats. The composition of Bacteroidetes was further demonstrated as shown in Figure 2B. Muribaculaceae was the most abundant family in Bacteroidetes, with an abundance of 85.2%, followed by Prevotellaceae (~10%) and Bacteroideae (~1%). Furthermore, the relative contributions of 35 dominant genera showed in the heatmap (Figure 2C) revealed that the composition of the intestinal flora varied greatly among individuals. The correlation between Operational Taxonomic Units (OTUs) and the utilization rate of SCSP was demonstrated by a multiple linear regression analysis (Supplemental Table S3) to obtain the regression model y = 35.164x₁ + 38.257x₂ − 0.145, where x₁ and x₂ are from Muribaculaceae and Clostridia_UCG-014, respectively. Thus, the result indicates the two OTUs were both positively correlated with the utilization rate of SCSP (p < 0.05).

SCSP metabolism is a complex process that requires the participation of many gut microbes. It has been reported that some microorganisms such as Bacteroides and Parabacteroides are also involved in the metabolism of SCSP [27]. Different gut microbiota structures could respond to the intake food differently [27,31]. The discrepancy in the SCSP utilization in these rats could be attributed to the great diversity of their microbiota communities. Bacteroidetes, including Muribaculaceae, possess very large numbers of genes encoding carbohydrate-active enzymes, and are considered as the main contributors for polysaccharide utilization [32,33]. Muribaculaceae widely exist in the gut microbiota and a genome analysis indicated their potential capability to degrade complex carbohydrates [34]. Clostridia_UCG-014 has been identified as a member of Clostridiaceae, which possessed some well-studied cellulolytic organisms [35], and it has been considered as one of the major microbial contributors to digest polysaccharides due to its carbohydrate-degrading genes [36]. Then, the present study will suggest some bacteria from Muribaculaceae and Clostridiaceae that are keystone bacteria for SCSP utilization in the gut, affecting SCSP’s outcome, such as anti-obesity and anti-type 2 diabetes [37].

3.3. Regulation of SCSP on Metabolite Profile of Feces

The effect of SCSP administration on the fecal metabolites was investigated through a non-targeted metabolomic analysis using Q-TOF-MS. As shown by PCA (Figure 3A) and OPLS-DA (Supplemental Figure S3), the fecal metabolite profiles of the SCSP group and the Control group separated with each other, indicating SCSP changed the metabolic profiles in the host gut. In total, 95 differential metabolites were identified in feces (

Table 2. Identification results of differential metabolites in feces detected in the positive ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	3-Amino-1,2,4-triazole	C2H4N4	1.37074	↑ (***)
2	Morpholine	C4H9NO	6.33961	↓
3	Diethanolamine	C4H11NO2	1.32672	↓ (**)
4	Dihydrouracil	C4H6N2O2	1.14054	↑ (*)
5	L-proline	C5H9NO2	2.47750	↑ (***)
6	Valine	C5H11NO2	1.17142	↑ (*)
7	Cinnamaldehyde	C9H8O	1.89465	↓ (**)
8	2-Aminobenzimidazole	C7H7N3	1.41216	↑ (***)
9	Hypoxanthine	C5H4N4O	1.58532	↓ (**)
10	Guanine	C5H5N5O	1.22418	↓ (**)
11	His	C6H9N3O2	1.14781	↑ (**)
12	2,8-Quinolinediol	C9H7NO2	2.45795	↑ (**)
13	Metronidazole	C6H9N3O3	3.82603	↑ (*)
14	7,8-Dihydroxycoumarin	C9H6O4	1.67340	↑ (*)
15	5-Butylpyridine-2-carboxylic acid	C10H13NO2	1.14137	↓
16	Metamitron-desamino	C10H9N3O	1.49271	↓
17	Levodopa	C9H11NO4	1.56546	↑
18	2-(4-Isobutylphenyl) propionic acid	C13H18O2	1.45771	↓ (*)
19	Pilocarpine	C11H16N2O2	2.66077	↓ (***)
20	Terbumeton	C10H19N5O	1.10183	↓ (*)
21	Flonicamid	C9H6F3N3O	3.03765	↓ (**)
22	Lumichrome	C12H10N4O2	2.85914	↑ (**)
23	(2Z)-2-Benzylidene-6-methoxy-1-benzofuran-3(2H)-one	C16H12O3	1.40162	↓ (*)
24	Dehydroepiandrosterone	C19H28O2	2.13486	↓
25	Daidzein	C15H10O4	1.41342	↑ (**)
26	Epiandrosterone	C19H30O2	1.03079	↑
27	Jaeschkeanadiol	C15H26O2	1.06159	↓
28	Huperzine A	C15H18N2O	2.14980	↑
29	Graveolide	C15H20O3	1.38494	↑ (**)
30	Baicalein	C15H10O5	1.68694	↓ (**)
31	Galaxolidone	C18H24O2	1.03394	↑ (*)
32	(-)-Eburnamonine	C19H22N2O	1.93955	↑ (***)
33	All-trans-retinoic acid	C20H28O2	1.40410	↑ (*)
34	Methyl 3-(3,4-dihydroxy-5-phenyloxolan-2-yl)-3-hydroxypropanoate	C14H18O6	1.82178	↑
35	5-(4-Hydroxybenzyl)-4-(2-hydroxy-4-methoxyphenyl)-2(5H)-furanone	C18H16O5	1.05768	↓ (**)
36	5-(1,2,4a,5-Tetramethyl-7-oxo-3,4,8,8a-tetrahydro-2H-naphthalen-1-yl)-3-methylpentanoic acid	C20H32O3	1.23648	↓ (***)
37	Hydroquinidine	C20H26N2O2	1.19523	↑ (***)
38	Raclopride	C15H20Cl2N2O3	1.19604	↓ (*)
39	Eicosanoids–bicycloPGE1	C20H32O4	2.81380	↓ (***)
40	Aphidicolin	C20H34O4	1.36684	↓ (*)
41	Melibiose	C12H22O11	2.25455	↓
42	(2E,4E)-12-Hydroxy-13-(hydroxymethyl)-3,5,7-trimethyltetradeca-2,4-dienedioic acid	C18H30O6	1.02162	↓
43	Hirsutine	C22H28N2O3	1.12443	↓ (**)
44	4-(Hydroxymethyl)-1-isopropyl-3-cyclohexen-1-yl beta-d-glucopyranoside	C16H28O7	1.00738	↓
45	3-Methyl-5-(5,5,8a-trimethyl-2-methylene-7-oxodecahydro-1-naphthalenyl) pentyl acetate	C22H36O3	1.69849	↓
46	Deoxycholic acid	C24H40O4	1.00172	↑ (**)
47	(-)-Riboflavin	C17H20N4O6	1.38226	↓ (*)
48	Methyl robustone	C22H18O6	3.32767	↑ (*)
49	Lagochilin	C20H36O5	1.12443	↓ (*)
50	Colladonine	C26H32O5	1.28344	↓ (**)
51	Voacristine	C22H28N2O4	1.24153	↓ (**)
52	Cholic acid	C24H40O5	1.03719	↓
53	Monolinolein	C21H38O4	1.69026	↑ (**)
54	11,12-Methylenedioxykopsinaline	C22H26N2O5	1.80736	↓
55	6-Hydroxy-2,4,4-trimethyl-3-(3-oxobutyl)-2-cyclohexen-1-yl beta-d-glucopyranoside	C19H32O8	1.74942	↓ (***)
56	2-Acetoxy-4-pentadecylbenzoic acid	C24H38O4	1.32797	↓
57	4,6′,7′-Trihydroxy-6-(hydroxymethyl)-2′,5′,5′,8a′-tetramethyl-3′,4′,4a′,5′,6′,7′,8′,8a′-octahydro-2′H,3H-spiro[1-benzofuran-2,1′-naphthalene]-7-carbaldehyde	C23H32O6	4.20631	↑
58	Lovastatin M + Na	C24H36O5	1.20112	↓
59	Irbesartan	C25H28N6O	1.00854	↓
60	Hyocholic acid	C24H40O5	2.79818	↓
61	Beta-peltatin	C22H22O8	3.54980	↑
62	3-[5-Hydroxy-7-methoxy-2,3-dimethyl-6-(3-methylbut-2-enyl)-4-oxo-2,3-dihydrochromen-8-yl] hexanoic acid	C23H32O6	4.08549	↑ (**)
63	5-Hydroxy-5-(2-hydroxy-2-propanyl)-3,8-dimethyl-2-oxo-1,2,4,5,6,7,8,8a-octahydro-6-azulenyl β-d-glucopyranoside	C21H34O9	1.03474	↑
64	6-[3-[(3,4-Dimethoxyphenyl) methyl]-4-methoxy-2-(methoxymethyl) butyl]-4-methoxy-1,3-benzodioxole	C24H32O7	1.05174	↓
65	Prednisolone_tebutate	C27H38O6	1.53337	↓ (*)
66	Lunarine	C25H31N3O4	1.10489	↓
67	Lycoctonine	C25H41NO7	1.02154	↓ (*)
68	NCGC00385237-01-C30H48O4	C30H48O4	1.03038	↓ (*)
69	Petunidin-3-O-beta-glucoside	C22H23O12	1.63603	↑ (*)
70	Emetine	C29H40N2O4	1.08634	↓
71	(2R)-2-Hydroxy-3-(palmitoyloxy) propyl 2-(trimethylammonio)ethyl phosphate	C24H50NO7P	1.13281	↓ (**)
72	1-Linoleoyl-2-hydroxy-sn-glycero-3-PC	C26H50NO7P	1.45727	↓
73	Plasma ID-2759	C26H52NO7P	1.05955	↓ (**)
74	Rhusflavone	C30H22O10	1.18525	↑
75	(1R,2R,3R,3aS,5aS,6R,7R,10R,10aR,10cR)-1,2,6,7-Tetrahydroxy-10a,10c-tetramethyl-4-oxo-6a,7,10,10a,10b,10c-dodecahydro-1H-phenanthro[10,1-bc] furan-10-yl beta-d-glucopyranoside	C25H38O12	2.23274	↓ (*)
76	Pantethine	C22H42N4O8S2	1.16095	↓
77	Cyanidin-3-O-sophoroside	C27H31O16	1.42677	↑ (*)
78	L-Glutathione	C20H32N6O12S2	1.06517	↑ (*)
79	Gitoxin	C41H64O14	3.23925	↑ (**)

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, ** p < 0.01, and *** p < 0.001 vs. the Control group; ↑, increase; ↓, decrease).

and

Table 3. Identification results of differential metabolites in feces detected in the negative ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	Glyceraldehyde	C3H6O3	1.02494	↑ (**)
2	4-Hydroxybenzaldehyde	C7H6O2	1.48141	↓
3	Cis-Muconic acid	C6H6O4	1.90860	↓ (***)
4	Laurilsulfate	C12H26O4S	1.70544	↓
5	γ-Linolenic acid	C18H30O2	1.68250	↑
6	Linoleic acid	C18H32O2	5.62134	↑ (***)
7	Stearic acid	C18H36O2	1.40114	↑ (*)
8	9,10-DiHOME	C18H34O4	1.48835	↓ (*)
9	7,15-Dihydroxyabieta-8,11,13-trien-18-oic acid	C20H28O4	1.11551	↓ (*)
10	5-[2-(Furan-3-yl) ethyl]-8-hydroxy-5,6,8a-trimethyl-3,4,4a,6,7,8-hexahydronaphthalene-1-carboxylic acid	C20H28O4	1.29029	↓
11	Lithochol-11-enic acid	C24H38O3	2.07634	↑ (**)
12	Lithocholic acid	C24H40O3	2.28879	↑ (**)
13	Deoxycholic acid	C24H40O4	4.56029	↓
14	Chenodiol	C24H40O4	5.97657	↓
15	Hyocholic acid	C24H40O5	6.87300	↓
16	Irbesartan	C25H28N6O	1.39312	↑ (*)

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, ** p < 0.01, and *** p < 0.001 vs. the Control group; ↑, increase; ↓, decrease).

), and the related metabolic pathways with -log10 (p) and impact as the horizontal and vertical coordinates are shown in Figure 3B. The metabolic pathway obviously influenced by the SCSP supplement includes biosynthesis of unsaturated fatty acids, pantothenate and CoA biosynthesis, β-alanine metabolism, aminoacyl-tRNA biosynthesis, primary bile acid biosynthesis, riboflavin metabolism, linoleic acid metabolism, purine metabolism, histidine metabolism, retinol metabolism, arginine and proline metabolism, pyrimidine metabolism, tyrosine metabolism, and steroid hormone biosynthesis. Interestingly, the biosynthesis of unsaturated fatty acids and linoleic acid metabolism were both related to lipid metabolism. Of note, stearic acid, linoleic acid, and γ-linolenic acid in these two pathways were enriched by SCSP, indicating the enhancement of lipid metabolism in the guts of rats administrated SCSP.

As we know, diet fat is digested and absorbed in the stomach and the small intestine [38]. More active lipid metabolism in the guts suggests more fat was transported to the gut without being absorbed by the upper digestive tract. Thus, the results in the present study indicate the supplementation of SCSP could inhibit the fat absorption. It has been reported that SCSP could prevent obesity induced by a high-fat diet [13], and the inhibition effect of SCSP against the fat absorption is one of the possible reasons for its anti-obesity activity. Liu et al. reported that the gut microbiota in HFD-fed mice were dominated by Muribaculaceae species, and the untargeted metabolomics analyses of fecal samples show that microbial changes altered the bacteria-derived metabolites, which related to linoleic acid metabolism [39]. Thus, it can be inferred that SCSP could interfere with linoleic acid metabolism by affecting Muribaculaceae to exert anti-obesity effects.

3.4. Regulation of SCSP on Metabolite Profiles of Serum and Urine

To evaluate the physiological effect of single gavage of SCSP, the metabolites in serum and urine of the rats were also determined by UPLC-Q-TOF MS in both positive and negative modes. As shown in

Table 4. Identification results of differential metabolites in serum detected in the positive ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	Glycocyamine	C3H7N3O2	1.84134	↓ (*)
2	3-Formylindole	C9H7NO	3.12390	↑
3	Phosphocholine	C5H15NO4P	2.46685	↓ (***)
4	Phytosphingosine	C18H39NO3	1.55859	↑ (***)
5	Iprovalicarb	C18H28N23	3.53042	↓
6	LysoPC (18:3(9Z,12Z,15Z))	C26H48NOP	1.57622	↓ (***)
7	1-Linoleoyl-2-hydroxy-sn-glycero-3-PC	C26H50NOP	1.33664	↑
8	Isohernandezine	C39H44N27	1.41083	↓
9	(4R,9β,23E)-2-(β-d-Glucopyranosyloxy)-16,20-dihydroxy-9,10,14-trimethyl-1,11,22-trioxo-4,9-cyclo-9,10-secocholesta-2,5,23-trien-25-yl acetate	C38H54O13	1.02230	↑ (***)

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, and *** p < 0.001 vs. the Control group; ↑, increase; ↓, decrease).

,

Table 5. Identification results of differential metabolites in serum detected in the negative ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	Lactic acid	C3H6O3	1.89469	↑ (*)
2	Palmitic Acid	C16H32O2	2.12223	↑ (**)
3	Oleic acid	C18H34O2	1.05400	↑
4	Stearic acid	C18H36O2	1.23960	↑
5	Thymol-β-d-glucoside	C16H24O6	1.62896	↑
6	9,10-DiHOME	C18H34O4	1.19020	↑ (**)
7	Hydroquinidine	C20H26N2O2	1.72053	↑ (***)
8	19S-Methoxytubotaiwine	C21H26N2O3	1.52218	↑

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, ** p < 0.01, and *** p < 0.001 vs. the Control group; ↑, increase).

,

Table 6. Identification results of differential metabolites in urine detected in the positive ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	Pyrrolidine	C4H9N	1.22976	↑ (***)
2	3-Amino-1,2,4-triazole	C2H4N4	3.94189	↑ (**)
3	D-Alanine	C3H7NO2	1.19995	↑ (*)
4	5-Methylcytosine	C5H7N3O	2.25112	↑ (***)
5	2-Benzoxazolinone	C7H5NO2	1.82869	↑
6	3-Methyladenine	C6H7N5	1.69258	↑ (**)
7	7-Methanesulfinylheptanenitrile	C8H15NOS	1.57761	↑ (*)
8	Ethyl-4-dimethylaminobenzoate	C11H15NO2	2.53641	↑ (**)
9	Monuron	C9H11ClN2O	1.31887	↑ (*)
10	Thiabendazole	C10H7N3S	1.43739	↓
11	Cyclo(proline–leucine)	C11H18N2O2	1.25286	↑ (**)
12	Mefenamic acid	C15H15NO2	1.15207	↑
13	Estriol	C18H24O3	1.84057	↑ (**)
14	Daidzein	C15H10O4	1.88659	↓
15	Genistein	C15H10O5	1.82289	↑ (*)
16	Glycitein	C16H12O5	1.03938	↑
17	4′-Methylgenistein	C16H12O5	1.22976	↑ (*)
18	Adenosine 5′-monophosphate	C10H14N5O7P	2.49862	↑
19	Methyl (2E,4E,8E)-7,13-dihydroxy-4,8,12-trimethyltetradeca-2,4,8-trienoate	C18H30O4	1.03817	↑ (*)
20	2-(2,6-Dihydroxy-4-methoxycarbonylbenzoyl)-3-hydroxybenzoic acid	C16H12O8	1.27008	↑

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, ** p < 0.01, and *** p < 0.001 vs. the Control group; ↑, increase; ↓, decrease).

and

Table 7. Identification results of differential metabolites in urine detected in the negative ion mode.

No.	Name	Formula	VIP	SCSP vs. Control
1	Glycolic acid	C2H4O3	1.41701	↑ (***)
2	Catechol	C6H6O2	2.64152	↓
3	5-Methyl-1H-benzotriazole	C7H7N3	1.32223	↓
4	Ortho-aminobenzoic acid	C7H7NO2	1.17925	↓ (*)
5	4-Hydroxyquinoline	C9H7NO	1.07799	↓
6	2-Hydroxyacetanilide	C8H9NO2	1.25584	↑ (*)
7	Divarinol	C9H12O2	1.62192	↑ (***)
8	Allantoin	C4H6N4O3	1.14447	↓
9	Saccharin	C7H5NO3S	1.13550	↑
10	4-Pyridoxic acid	C8H9NO4	2.62819	↓
11	3-Indoxyl sulfate	C8H7NO4S	1.82190	↓
12	Pantothenate	C9H17NO5	1.01748	↑ (*)
13	Daidzein	C15H10O4	2.82778	↑ (***)
14	9-Trans-palmitelaidic acid	C16H30O2	1.01288	↓ (***)
15	Trans-vaccenic acid	C18H34O2	4.77431	↓ (***)
16	Oleic acid	C18H34O2	3.37721	↓ (***)
17	Stearic acid	C18H36O2	2.22722	↓ (***)
18	8-(3-Octyl-2-oxiranyl) octanoic acid	C18H34O3	1.59172	↓ (***)
19	Arachidic acid	C20H40O2	1.36823	↓ (***)

Differential metabolites were analyzed using unpaired two-tailed Student’s t-test with Bonferroni correction (* p < 0.05, and *** p < 0.001 vs. the Control group; ↑, increase; ↓, decrease).

, 17 and 39 differential metabolites were identified in the serum and urine, respectively. The PCA analysis demonstrated a distinction between the serum metabolite profiles of the Control and SCSP groups in both of the positive (Figure 4A) and negative modes (Figure 4B). Moreover, although no significant separation was observed in urine profiles of the Control and SCSP groups detected in the positive mode (Figure 4C), the analysis result determined in the negative mode that an obvious separation was exhibited (Figure 4D). The separation between Control and SCSP groups demonstrated in the negative mode could be attributed to some acidic compounds, such as glycolic acid and arachidic acid. The metabolism pathway analysis in serum and urine metabolites is shown in Supplemental Figure S4. Thus, it can be concluded that single-dose SCSP administration can affect the in vivo metabolism of rats.

Of note, palmitic acid, stearic acid, and oleic acid, which were all increased in the feces of the SCSP group, all decreased in serum and urine of the SCSP group. These long-chain fatty acids (LCFAs) are components of pork fat in the fodder, and they could be absorbed into serum [40]. Thus, the less serum LCFAs in the SCSP group indicated that SCSP could inhibit the LCFAs’ absorption so as to increase fat excretion via feces. It has been reported that the dietary supplementation of SCSP could significantly reduce fat accumulation and lipid levels in high-fat-diet-fed mice [41]. Then, the findings in the present study suggest the inhibition of LCFAs’ absorption plays a role in the anti-obesity and hypolipidemic effects of SCSP. It has been well documented that dietary fibers could prevent the absorption of fat by chelation with their micro-molecular chains [42]. Then, it could be inferred these SCSP micromolecules may bind to fat in the intestine so as to interfere with the fat metabolism in the host.

Taking together all the above results, single gavage of SCSP in vivo could be proposed as follows: a proportion of SCSP could participate in various metabolic reactions of the rats to produce different metabolites, thus benefiting the host health. The other SCSP was not degraded, but they could reduce obesity and hyperlipidemia by inhibiting fat absorption and increasing fat excretion into the feces. This is consistent with the previous research result that SCSP can prevent diet-induced obesity and its associated diseases [13].

4. Conclusions

The present study demonstrated the absorption, the exertion, and the metabolism by gut microbiota of SCSP. As shown by the quantitative analysis of SCSP in blood, urine, and feces, only a small amount of SCSP could be absorbed into the blood while a proportion of SCSP was excreted in the feces, which suggests that a considerable proportion of SCSP was metabolized by gut microbiota and the metabolized amount of SCSP varied among individuals. The SCSP degradation in the intestine was positively correlated with Muribaculaceae and Clostridia_UCG-014, confirming the involvement of these gut bacteria in metabolism of SCSP in the gut. Furthermore, the changes of the metabolites in blood, urine, and feces caused by SCSP administration revealed that SCSP could inhibit the fat absorption by increasing fat excretion. Our findings provide a better understanding of the action mechanism of SCSP in vivo.