In Vitro Digestion and Fermentation of Three Polysaccharide Fractions

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Article Cite This: J. Agric. Food Chem. 2019, 67, 7496−7505

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In Vitro Digestion and Fermentation of Three Polysaccharide Fractions from Laminaria japonica and Their Impact on Lipid Metabolism-Associated Human Gut Microbiota Jie Gao,†,§ Lianzhu Lin,†,§ Zijie Chen,†,§ Yongjian Cai,†,§ Chuqiao Xiao,†,§ Feibai Zhou,†,§ Baoguo Sun,‡,∥ and Mouming Zhao*,†,‡,§,∥ †

School of Food Science and Engineering, South China University of Technology, Guangzhou 510640, China Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology & Business University, Beijing 100048, China § Guangdong Food Green Processing and Nutrition Regulation Technologies Research Center, Guangzhou 510640, China ∥ Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology & Business University, Beijing 100048, China

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ABSTRACT: Our previous study has proved that the three polysaccharide fractions from L. japonica (LP-A4, LP-A6, and LPA8) had significantly different structure characterization. Herein, we conducted in vitro simulated digestion and fermentation to study the digestive mechanism of LP-As. The results of gastrointestinal digestion indicated that LP-A6 and LP-A8 would be easier to trap the enzyme molecules for their denser interconnected macromolecule network compared with LP-A4. Fermentation of LP-As by human gut microbiota, especially for LP-A8, generated a large amount of short-chain fatty acids (SCFAs), which could upregulate the abundance of Firmicutes (Lachnoclostridium and Eubacterium). The high content of sulfate and highly branched sugar residue of LP-A8 might help it be easily used by Firmicutes in gut microbiota of hyperlipidemic patients. Functional analysis revealed that the increased metabolic activities of glycerophospholipid metabolism, ether lipid metabolism, and fatty acid metabolism induced by LP-A8 treatment were closely associated with metabolic syndromes and hyperlipidemia. KEYWORDS: Laminaria japonica polysaccharide fractions, gastrointestinal digestion, gut microbiota, fermentation, lipid metabolism

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INTRODUCTION There is a growing interest in understanding how soluble dietary fiber (polysaccharide) could be digested in the human gastrointestinal tract and affect the intestinal microbiota.1−4 Simulated gastrointestinal digestion is usually used to study the digestive mechanism of functional food because human experiments are expensive, resource intensive, and ethically disputable.5 Reproducibility, controlled conditions, less sample consumption, and easy sampling at the site of interest make in vitro models very suitable for digestive and metabolic mechanism studies of purified polysaccharide fractions. Simulated digestion methods typically include the oral, gastric, and small intestinal phases, and occasionally colon fermentation, taking into account the concentrations of digestive enzymes, pH, digestion time, and salt concentrations.6−9 Evidence is now accumulating to demonstrate that the gut microbiota plays a critical role in the development of diseases associated with lipid metabolism.10−17 Animal models are commonly used to investigate the possible correlation between gut microbiota and lipid metabolism, which are much more convenient and affordable than conducting human trials.9−12 However, human gut microbiota may differ markedly from the animal models, and it is not feasible to perform in vivo studies for the purified polysaccharide fractions. Recently, short chain fatty acids (SCFAs), produced by particular gut microbiota in © 2019 American Chemical Society

colon, are being investigated in different ways to explain the association between gut microbiota and human body. These fatty acids not only serve as energy sources for the gut microbiota but also have impact on lipid and glucose metabolism.18−20 L. japonica is the most widely cultivated and consumed commercial edible brown seaweed around the world. Numerous published papers have demonstrated that polysaccharides from L. japonica have beneficial bioactivities for human health, such as antioxidant, antiallergic, anticancer, antithrombotic, anticoagulant, immunoregulation, and hypolipidemic activities, which are particularly associated with their structural characteristics.21−27 Our previous study suggested that the three polysaccharide fractions of L. japonica, characterized as mannoglucan, fucomannoglucan, and fucogalactan, had notably distinct structural features and bile acidbinding capacity.28 Compared with the other two fractions, LP-A8 exhibited the highest bile acid-binding capacity, which might have correlation with their abundant sulfate, very tiny amounts of uronic acid, and highly branched sugar residue Received: Revised: Accepted: Published: 7496

February 9, 2019 May 23, 2019 May 24, 2019 May 24, 2019 DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

Article

Journal of Agricultural and Food Chemistry

Sigma), 0.625 mL of fresh bile (160 mM), 10 μL of CaCl2(H2O)2 (0.3 mol/L), 38 μL of NaOH (1.0 mol/L), and 0.328 mL of distilled water. The simulated intestinal digestion test was conducted at 37 °C for 2 h and then heated in a boiling bath for 5 min. After simulated digestion, the molecular weight distribution of LPAs was determined by high performance size exclusion chromatography equipped with multiangle laser light scattering and refractive index detector (HPSEC-MALLS-RID). Each sample was replicated three times. Microscopic Observation and Molecular Weight Distribution. The simulated salivary, gastric and intestinal digestion solutions were put on slide glass substrates at room temperature and observed at 400× magnification by optical microscope. The molecular weight distribution of the LP-As after simulated salivary, gastric, and intestinal digestion were measured and compared by using HPSECMALLS-RID according to the previous published method.29 HPSEC-MALLS-RID measurements were conducted on a multiangle laser light scattering detector (MALLS, DAWN HELEOS-II, Wyatt Technology Co., Santa Barbara, CA, USA) with a 2998 PDA detector in a Waters e2695 HPLC system coupled with TSK-GEL G5000PWXL (300 mm × 7.8 mm, i.d.) and TSK-GEL G3000PWXL (300 mm × 7.8 mm, i.d.) columns in series. Bovine serum albumin (BSA, 5 mg/mL) was used to normalize the diodes of the MALLS detector. A dn/dc value of 0.185 mL/g was determined for the BSA in our carrier liquid. NaCl aqueous solution (0.9%) was used as mobile phase at the flow rate of 0.6 mL/min. The simulated digestion solution was filtered by a 0.22 mm membrane and tested at an injection volume of 50 μL and a concentration of 2 mg/mL. The Astra software (Version 6.0.2, Wyatt Tech. Corp. Santa Barbara, CA, USA) was used for data analysis. In Vitro Fermentation. In vitro fermentation of LP-As was performed in triplicate according to the published methods with some modification.1−4,30 Fecal samples were collected from two healthy donors (group NL, normal-lipid control, one female and one male, 45−60 years old, TG 1.52 ± 0.1 mmol/L, TC 5.97 ± 0.49 mmol/L) and two hyperlipidemic patients (group HL, hyper-lipid control, one female and one male, 45−60 years old, TG 8.8 ± 0.28 mmol/L, TC 6.64 ± 1.40 mmol/L) who were eating their regular diets without taking antibiotics for more than 3 months. Fecal samples were tightly sealed in plastic tubes, kept on ice prior to rapidly being stored in −80 °C refrigerator, and used within 7 days of collection. The fecal samples were homogenized with sterilized phosphate-buffered saline, pH 7.4 (feces: PBS buffer = 1:9 (w/v)) and then filtered and pooled to make fecal slurries under anaerobic conditions maintained by Anaero Pack (Mitsubishi Gas Chemical Co., Tokyo, Japan). Then 100 μL of pooled fecal slurry and 400 μL of LP-As (17.5 mg LP-As dissolved in 400 μL of PBS buffer, the final concentration for fermentation was 0.5%, w/v) were inoculated into 3 mL of brain heart infusion (BHI) and incubated in a 37 °C incubator (120 rpm) for 120 h anaerobically (AnaeroPack-Anaero; Mitsubishi Gas Chemical Co., Tokyo, Japan). The preparation of pooled fecal samples for fermentation experiments does not lead to a bacterial community with an aberrant profile and activity compared to that normally prepared from single donors.4,9,30 According to the previously published studies, every step of making fecal slurries should be kept in anaerobic conditions. At the end of the fermentation for each LPAs fraction, two aliquots were collected from each sample for DNA extraction (1 mL) and SCFA analysis (1 mL). SCFA Analysis. SCFA analyses were conducted as previously described.31 One milliliter of each sample with 1% of formic acid was suspended and stored at −20 °C immediately after collection. Once thawed, the sample suspensions were homogenized and then centrifuged for 10 min at 17949 × g. One milliliter of supernatant of each sample was extracted with 1 mL of ethyl acetate for 2 min and then separated by centrifugation for 10 min at 17949 × g. Organic extracts were obtained and stored at −20 °C. Before analysis, 600 μL of organic extracts was transferred into a test tube with 500 μmol/L 4methyl valeric acid as IS. The IS was employed for the correction of injection variability between samples and instrument stability.

such as (1 → 2, 3, 4) linked β-D-ManpA.28 However, limited information is focused on the connection between digestive mechanism and structural characteristics of purified polysaccharide fractions from L. japonica. Thus, the aim of this study was to evaluate how the LP-As digest in the gastrointestinal tract and alter the gut microbiota with SCFA production. Herein, we conducted in vitro simulated digestion and fermentation to study the digestive mechanism of three purified polysaccharide fractions (LP-A4, LP-A6, and LP-A8) from L. japonica. Fermentation of LP-A4, LP-A6, and LP-A8 by human gut microbiota generates large amount of short-chain fatty acids (SCFAs) and leads to the change of gut microbiota community composition, which could change the microbiota composition, uphold health and be a valuable food supplement.

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MATERIALS AND METHODS

Materials. L. japonica, harvested in July 2018 from Weihai (Shandong, China), was washed with tap water and distilled water, then dried at 60 °C in an oven. The dried samples were pulverized to get the powdered material using a 50-mesh screen. Pepsin from porcine gastric mucosa, α-amylase from human saliva, pancreatin, and SCFAs standards including acetic, propionic, butyric, valeric, isobutyric, and isovaleric acids were purchased from Sigma-Aldrich Corp. (St. Louis, USA). All the other reagents used in the present study were of analytical grade. Extraction and Purification of L. Japonica Polysaccharide. The extraction and purification methods used in this study were as described in our previously published paper.24 Briefly, the dried L. japonica powder was extracted with 0.1 mol/L HCl solution. The L. japonica polysaccharide (LP-A) was obtained by freeze-drying of the final polysaccharide solution after precipitation and dialysis. The purification of LP-A was conducted with ion-exchange chromatography, which was monitored with phenol-sulfuric acid reaction.2 The three purified LP-A fractions, LP-A4, LP-A6, and LP-A8, were obtained after dialysis, concentration, and lyophilization, which would be used in the subsequent digestion and fermentation. Simulated Gastrointestinal Digestion. The simulated salivary, gastric, and intestinal fluids were made according to the previously published procedures with some modifications.1 The simulated salivary fluid (SSF) consisted of 15.1 mmol/L KCl, 13.6 mmol/L NaHCO3, 3.7 mmol/L KH2PO4, 0.15 mmol/L MgCl2(H2O)6, 0.06 mmol/L (NH4)2CO3, and 1.1 mmol/L HCl, and 10 mg of LP-As was dissolved in 1 mL of distilled water. The simulated salivary digestion (SSD) tube was a mixture of 5 mL of LPAs solution (10 mg/mL), 3.5 mL of SSF, 0.5 mL of 1500 U/mL salivary alpha-amylase solution (alpha-amylase, 1000−3000 U/mg protein, human saliva Type IX-A, Sigma), 25 μL of CaCl2(H2O)2 (0.3 mol/L), and 0.975 mL of distilled water. The simulated salivary digestion test was conducted at 37 °C for 5 min and then heated in a boiling bath for 5 min. The simulated gastric fluid (SGF) consisted of 47.2 mmol/L NaCl, 25 mmol/L NaHCO3, 8.5 mmol/L HCl, 6.9 mmol/L KCl, 0.9 mmol/ L KH2PO4, 0.5 mmol/L (NH4)2CO3, and 0.1 mmol/L MgCl2(H2O)6. The simulated gastric digestion (SGD) tube was the mixture of 5 mL of salivary chyme from the simulated salivary digestion, 3.75 mL of SGF, 0.8 mL 25000 U/mL porcine pepsin solution (pepsin, 3200− 4500 U/mg protein, porcine gastric mucosa, Sigma), 2.5 μL of CaCl2(H2O)2 (0.3 mol/L), 0.1 mL of HCl (1.0 mol/L), and 0.348 mL of distilled water. The simulated gastric digestion test was conducted at 37 °C for 2 h and then heated in a boiling bath for 5 min. The simulated intestinal fluid (SIF) consisted of 85 mmol/L NaHCO3, 38.4 mmol/L NaCl, 8.4 mmol/L HCl, 6.8 mmol/L KCl, 0.8 mmol/L KH2PO4, and 0.33 mmol/L MgCl2(H2O)6. The simulated intestinal digestion (SID) tube was a mixture of 5 mL of gastric chyme from the simulated gastric digestion, 2.75 mL of SIF, 1.25 mL of pancreatin solution (800 U/mL trypsin, porcine pancreas, 7497

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

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Journal of Agricultural and Food Chemistry

Figure 1. (A) Microscopic observation of the simulated salivary, gastric, and intestinal digestion solutions of LP-As (magnification ×400). (B) HPSEC profile with the static light scattering signals (SLS 90°) of the molecular weight distribution of LP-As before and after simulated salivary (SSD-As), gastric (SGD-As), and intestinal digestion (SID-As). Analysis of the SCFAs was conducted by using Trace GC−MS system coupled with a Trisplus automated sampler, an Ultra GC and a quadrupole DSQ II MS (Thermo Finnigan, San Jose, CA). Separation was conducted with a TR-Wax column (30 m × 0.32 mm × 0.25 μm, Thermo Scientific, Waltham, MA, USA). SCFAs were analyzed under the following conditions: injector temperature at 230 °C, ion source and interface temperature at 250 °C; initial oven temperature at 90 °C, temperature increased to 150 °C at 15 °C/min, to 170 °C at 5 °C/min, and finally to 250 °C at 20 °C/min and maintain for 2 min (total time 14 min). Helium was used as carrier gas at 1 mL/min. The detector was operated in electron impact ionization mode (electron energy 70 eV), scanning the 30−350 m/z range. Identification of the SCFAs was conducted according to the retention time of standard compounds based on the NIST 08 and Wiley7N libraries. Three independent replicate extractions were performed per sample. DNA Extraction. One milliliter fermentation for each LP-As fraction was stored at −80 °C before DNA isolation. Total DNA was

isolated using the PowerMag Soil DNA isolation kit optimized for epMotion (Mo Bio Laboratories, Carlsbad, CA, USA) according to the manufacturer’s instructions. Samples stored at −80 °C were thawed and centrifuged at 13000 rpm for 10 min. Precipitate was homogenized and transferred into the Lysing Matrix E tube for the DNA extraction. 16S rRNA Sequencing. For 16S rRNA sequencing, the V3−V4 region of 16S rRNA gene was amplified by PCR using the universal bacterial primers: 341F(CCTACGGGNGGCWGCAG) and 806R (GGACTACHVGGGTATCTAAT) and then sequenced by using 500 bp paired-end sequencing (Illumina MiSeq). For shotgun metagenomic sequencing, libraries were sequenced by using 50 bp single-read sequencing (Illumina HiSeq).32,33 Sequence Processing and Community Analysis. Sequences were processed with Mothur v.1.39.1 according to the MiSeq SOP using the described 454 standard operating procedure (SOP).34,35 All OTUs were clustered at a cutoff of 0.02 (98% similarity) and classified 7498

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

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Journal of Agricultural and Food Chemistry

Figure 2. Concentrations of acetic (A), propionic (B), isobutyric (C), butyric (D), isovaleric (E), and valeric (F) acids and total SCFAs (G) in fermentation products of LP-As compared to blank group. *P < 0.05, compared with the blank in group HL; #P < 0.05, compared with the blank in group NL. Data represent mean ± SD (n = 3 for each group).

of uronic acids in the molecules of LP-A4 (89.64 ± 2.27%).24 Considering that the ionization of mannuronic acid and glucuronic acid in LP-A4 molecules could be inhibited by the sharply increased concentration of H+ in simulated gastric digestion solution, the intermolecular repulsive force of the macromolecular was weaker, thus stimulated the LP-A4 gathering of precipitation, decreasing the stability of the solution system.42 As presented in Figure 1B, HPSEC profiles with the static light scattering signals (SLS 90°) indicate that there were no significant changes in molecular weight distribution of LP-As after simulated salivary (SSD) and gastric (SGD) digestion. However, the HPSEC profile of LP-A4 in gastric digestion could not be recorded in this experiment because LP-A4 molecules gathered and precipitated in gastric digestion solution revealed by the results of microscopic observation. During the simulated intestinal digestion (SIG), the average Mw of LP-A6 decreased slightly from 1.959 ± 0.06 × 106 g/ mol to 5.244 ± 1.92 × 105 g/mol after 2 h of digestion. The same down-trends could be found in the average Mw of LPA8, which decreased from 1.332 ± 0.32 × 106 g/mol to 1.109 ± 0.60 × 106 g/mol after digestion, but there was no distinct variety in molecular weight distribution of LP-A4 after intestinal digestion. The different digestive characteristics of LP-As might indicate the possible connection between structure feature and digestibility. Compared with LP-A4, LP-A6 and LP-A8 revealed a denser interconnected macro-

using the Ribosomal DNA Project (RDP) database (v9).36 Heat maps and bar plots were created in R using the packages vegan and ggplots.37,38 For PICRUSt, we normalized the OTU results by subsampling to the lowest sequence count (3500 OTUs/sample). This table was input into the QIIME pipeline, which was used to reference the Greengenes 16S rRNA database (v9), the required input for PICRUSt.39 Subsequently, OTUs were normalized by 16S rRNA copy number, and metagenomes were predicted based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) catalogue. 40 HUMAnN was used to predict downstream pathway coverage based on the KEGG Ortholog results.41 Statistical Analysis. The data was presented as mean ± SD (n = 3) and evaluated by one-way analysis of variance (ANOVA) followed by Duncan’s test. All statistical analyses were carried out using R statistical package and SPSS for Windows, Version 17.0 (SPSS Inc., Chicago, IL, USA).

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RESULTS AND DISCUSSION Microscopic Observation and Molecular Weight Distribution. The microscopic observation of the simulated salivary, gastric, and intestinal digestion solutions of LP-As was showed in Figure 1A. The remarkable aggregation of LP-A4 molecules has been observed after simulated gastric digestion for 2 h, compared with LP-A6 and LP-A8. Furthermore, the precipitate formed in gastric digestion disappeared in the next intestinal digestion, which might be due to the changing of pH value. According to our previous study, there is a large amount 7499

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

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Journal of Agricultural and Food Chemistry

Figure 3. Taxonomic composition of gut microbiota. Bar plots show the average relative abundance at the species, genus, family, and order levels in the fermentation products of group NC (normal-lipid control) and group HL (hyper-lipid control) with the treatment of LP-As. Relative abundance at the left end of the horizontal axis is from group NC, and the right end is from group HL.

molecule network with higher content of sulfate and more branched sugar residue, which would be easier to trap the enzyme molecules in pancreatin and expose more cutting site for the enzyme digestion.24 SCFA Production during in Vitro Fermentation. Shortchain fatty acids (SCFA) are the major products of bacterial metabolism in the large intestine and colon, which mainly come from the breakdown of polysaccharide and are beneficial to human health. Acetic acid, propionic acid, butyric acid, and isobutyric acid were the main fermentation products in feces (Figure 2). The fermentation of LP-A8 in group HL (hyper-lipid control) produced significantly higher concentrations of acetic acid (34.46 ± 1.37 mmol/L), butyric acid (22.24 ± 1.07 mmol/L), isobutyric acid (12.73 ± 0.39 mmol/L), valeric acid (1.56 ± 0.26 mmol/L), and total SCFA (78.35 ± 2.44 mmol/ L) compared with the blank (p < 0.05). Furthermore, the concentration of acetic acid (26.60 ± 0.64 mmol/L), propionic acid (14.32 ± 0.87 mmol/L), and total SCFA (58.96 ± 3.47 mmol/L) were notably increased in group NL (normal-lipid control) by the intervention of LP-A8 compared with the blank (p < 0.05). At the same time, the fermentation of LP-A8 in both groups generated more acetic acid, propionic acid, and total SCFA than LP-A4 and LP-A6. Propionic acid in the fermentation of group HL treated with LP-A8 was significantly decreased from 7.64 ± 0.54 mmol/L (blank) to 5.81 ± 0.40 mmol/L (p < 0.05). Significant decreasing was also observed between the blank and LP-A4 or LP-A6 treatment of group NL in the amount of isobutyric acid. In particular, treatment of LPA4 and LP-A6 led to increases in the concentration of butyric acid and isovaleric acid in both group HL and group NL, and also the total SCFAs in group HL, compared with the blank.

Recently, many host metabolic pathways have been found to be linked to dietary fiber and gut microbiota. Numerous published papers have proved that SCFAs, the final fermentation products of the anaerobic intestinal microbiota, are beneficial to the host energy metabolism by upregulating expression of host SCFA receptors and target molecules in metabolic tissues. GPR109A is expressed in adipose tissues and activated adipose tissue macrophages where it regulates lipid homeostasis, which was first identified as a receptor for niacin and is mainly activated by β-hydroxybutryate and butyrate.43,44 Furthermore, SCFAs inhibited isoproterenol-induced lipolysis in a concentration-dependent manner in mouse 3T3-L1derived adipocytes.45 GPR43, also named as FFAR2, has been identified as a receptor of SCFA and is activated by acetate and propionate followed by butyrate.46,47 FFAR2 is expressed in intestinal endocrine L-cells, which could be activated by SCFAs and result in the inhibition of fat accumulation.48 In this study, acetate and butyrate were the most abundant SCFAs in group NL, and their generation was upregulated sharply by LP-A8, which might reveal that LP-A8 has some beneficial effects on the host−lipid metabolism. These data also indicated that fermentation of different kinds of LP-As by human gut microbiota in HL and NL groups promoted the generation of different SCFAs, which might then change the microbiota composition in different rules. Taxonomic Composition of Gut Microbiota. We plotted average relative abundance of microbiota composition in the fermentation products of LP-As in group NL and group HL at order, family, genus, and species levels (Figure 3). Proportions of four frequently detected orders including Gram-negative Bacteroidales (Bacteroidetes phylum) and Enterobacteriales (Proteobacteria phylum) and Gram-positive Clostridiales and Lactobacillales (all from Firmicutes phylum), 7500

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

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Journal of Agricultural and Food Chemistry

Figure 4. Heatmap of KEGG orthologs showing different enrichments of the top 20 abundant orthologs of the gut microbiota in the fermentation products of LP-As in group HL and group NL. The X-axis shows the group names, e.g., LP.A4.HL, representing the fermentation products with the treatment of LP-A4 in group HL. The Y-axis represents the KEGG ortholog ID. Rows show Z-scores calculated for each group.

totaled up to ∼90% of the entire community (Figure 3A). Moreover, there were some differences between group NL and group HL gut microbiota contents. Gram-positive Clostridiales and Lactobacillales were mainly observed in the gut microbiota of hyperlipidemic patients (group HL), while Gram-negative Bacteroidales and Enterobacteriales were the principal orders in the gut microbiota of healthy donors (group NL). The relative abundance of Clostridiales was significantly increased by the treatment of LP-As in group HL (P < 0.01), which was decreased in group NL. In group NL, the relative abundance of Bacteroidales has risen from 28.96% to 48.86% and 47.52% with the intervention of LP-A6 and LP-A8, respectively (P < 0.01). At family and genus levels (Figure 3B,C), Lactococcus (Streptococcaceae family), Flavonif ractor (Ruminococcaceae family), Parabacteroides (Porphyromonadaceae family), Lachnoclostridium (Lachnospiraceae family), and Eubacterium (Eubacteriaceae family) with high abundance were only observed in the gut microbiota of hyperlipidemic patients (group HL) compared with the healthy donors (group NL). The relative abundance of Lachnoclostridium (Lachnospiraceae family, Firmicutes phylum) in group HL could be notably increased by LP-As, whereas the relative abundance of Eubacterium (Eubacteriaceae family, Firmicutes phylum) was only increased by LP-A8 in group HL. Escherichia-Shigella (Enterobacteriaceae family), Bacteroides (Bacteroidaceae family), and Clostridium_sensu_stricto_1 (Clostridiaceae_1 family) were mainly observed in the gut microbiota of healthy donors (group NL), of which the relative abundance of Bacteroides (Bacteroidaceae family) was significantly increased by LP-A6 and LP-A8 (P < 0.01). At species level (Figure 3D), Lactococcus_garvieae (Streptococcaceae family, Firmicutes phylum) was the most prevalent species in group HL, and Clostridium_perf ringens (Clostridiaceae_1 family, Firmicutes phylum) was the most prevalent genus in group NL (Figure 3D). In particular, only the relative abundance of Clostridium_sp (Lachnospiraceae family, Firmicutes phylum) could be significantly increased by LP-As,

especially by LP-A8, in group HL. Meanwhile, the relative abundances of Lactococcus_garvieae, Clostridium_perf ringens, Bacteroides_thetaiotaomicron and Bacteroides_uniformis were decreased by the intervention of LP-As to some extent in both group HL and NL. Firmicutes, including several abundant species such as Faecalibacterium and Eubacterium, have been proved as the dominant producers of butyrate in the large intestine and colon.49 They also include species that convert lactate to butyrate or propionate and may help to stabilize the microbiota by preventing lactate accumulation and excess acidity.50 Evidence also shows that Lachnospiraceae in the feces of six infants was positively associated with a short-chain fatty acid (SCFA)-rich environment.51 The findings from the SCFAs production and taxonomic composition collectively suggest that the notable increasing of butyrate and total SCFAs in group HL by the LP-As treatment could be attributed to higher abundance of Firmicutes compared with the blank. Furthermore, the relative abundances of Lachnospiraceae and Eubacterium in group HL could be significantly increased by LP-A8, compared with the other two fractions, which might have some correlation with the structural feature of LP-A8. The content of abundant sulfate and highly branched sugar residue like (1 → 2, 3, 4) linked β-D-ManpA in the structure feature of LP-A8 might help this kind of macromolecular be easily used by Lachnospiraceae and Eubacterium in human gut microbiota.24 Functional Analysis of Gut Microbiota. PICRUSt was used to assess the functional content of the microbiota according to the 16S data. The top 20 KEGG Orthologs (KOs) with different enrichments identified in this study were shown in Figure 4. Six out of these 20 KOs were enriched in group HL with the treatment of LP-A8, including those KOs associated with membrane transport and structural complex (K02013, K02032, K02035, K02006, and K02003) and metabolism (K00926). The abundances of six orthologs in group NL were increased by the treatment of LP-A6 and LP7501

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

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Journal of Agricultural and Food Chemistry

Figure 5. Heatmap of KEGG pathways showing different enrichments of the top 20 abundant pathways associated with lipid and carbohydrate metabolism of the gut microbiota in the fermentation products of LP-As in group HL and group NL. The X-axis shows the group names, e.g., LP.A4.HL, representing the fermentation products with the treatment of LP-A4 in group HL. The Y-axis represents the KEGG ortholog ID. Rows show Z-scores calculated for each group.

After LP-A8 treatment in group HL, fatty acid biosynthesis and fatty acid elongation of lipid metabolism pathways were reduced, whereas glycerophospholipid metabolism, ether lipid metabolism, and fatty acid metabolism were enriched. The increased metabolic activities of glycerophospholipid metabolism, ether lipid metabolism, and fatty acid metabolism, as well as the decreased fatty acid biosynthesis and fatty acid elongation, are closely associated with metabolic syndromes and hyperlipidemia and may be important for the metabolic improvement induced by LP-A8 treatment. Our previous work has proved that the three LP-As fractions, characterized as mannoglucan, fucomannoglucan, and fucogalactan, had significantly different structure characterizations. The results of this Article indicated that the LP-As could not be entirely digested by gastrointestinal digestion. Furthermore, LP-A6 and LP-A8 would be easier to trap the enzyme molecules in pancreatin and expose more cutting site for the enzyme digestion according to their denser interconnected macromolecule network with more branches, compared with LP-A4. In addition, fermentation of LP-As by human gut microbiota, especially for LP-A8, in both hyperlipid and normal-lipid control groups generated large amount of SCFAs compared with the blank, which might change the microbiota composition and have positive impact on lipid metabolism. The relative abundance of Lachnoclostridium and Eubacterium in group HL, Bacteroides and Clostridium_sensu_stricto_1 in group NL could be notably increased by LP-A6 and LP-A8 (P < 0.01). The findings from the SCFAs production and taxonomic composition collectively suggest that the notable increasing of butyrate and total SCFAs in group HL by the LP-As treatment could be attributed to higher abundance of Firmicutes compared with the blank. Furthermore, the relative abundances of Lachnospiraceae and Eubacterium in group HL could be significantly increased by LP-A8, compared with the other two fractions, which might have some correlation with the structural feature of LP-A8. The content of abundant sulfate and highly branched sugar

A8 compared with blank, which were related to genetic information processing and signal transduction (K03088, K03296, and K02014), metabolism (K00936 and K07636), starch and sucrose metabolism (K05349), and lipid metabolism (K01190). Most of these orthologs, upregulated by LP-A6 and LP-A8, represented enzymes with biosynthetic and genetic information editing and signal transduction functions, while we also identified two orthologs associated with carbohydrate and lipid metabolism, highlighting the potential importance of nutrient acquisition abilities in colonizing a culture environment with LP-As and the positive effects on hyperlipidemia. These findings collectively suggest that the possible beneficial effect of LP-A6 and LP-A8 on carbohydrate and lipid metabolism and the colonization ability of human gut microbiota in culture environment with the intervention of polysaccharide could be attributed to a multitude of biological functions, including membrane transport, structural complex, genetic information processing, and signal transduction. The KEGG pathways correlated with lipid and carbohydrate metabolism of the gut microbiota in the fermentation products of LP-As in group HL and group NL (Figure 5) were further investigated. We identified the top 20 KEGG function terms showing distinct enrichments with or without the treatment of LP-As. The abundance of the top 20 KEGG pathways was changed much more notably in group HL than group NL, which could be attributed to the stable community structure of gut microbiota in the healthy donors.52 Glycolysis/gluconeogenesis, pentose phosphate pathway, and ascorbate and aldarate metabolism of carbohydrate metabolism in both group HL and group NL were decreased following the intervention of LP-As. Galactose metabolism, fructose and mannose metabolism, amino sugar and nucleotide sugar metabolism, and starch and sucrose metabolism of carbohydrate metabolism in group HL were decreased by LP-A6 and LP-A8, which were increased in group NL. 7502

DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505

Article

Journal of Agricultural and Food Chemistry residue like (1 → 2, 3, 4) linked β-D-ManpA in the structure feature of LP-A8 might help this kind of macromolecule be easily used by Lachnospiraceae and Eubacterium in human gut microbiota of hyperlipidemic patients. Functional analysis revealed that the increased metabolic activities of glycerophospholipid metabolism, ether lipid metabolism, and fatty acid metabolism induced by LP-A8 treatment in group HL were closely associated with metabolic syndromes and hyperlipidemia. The present study provides scientific evidence and advances for the potential application of LP-A6 and LP-A8 as an attractive functional food ingredient for hyperlipidemia population. However, physiological functions and exact signaling mechanisms of LP-As in the host peripheral tissues are still unclear, and more research about the regulation of the lipid metabolism by the dietary polysaccharide (LP-As) is required.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jafc.9b00970. Taxonomic composition of gut microbiota was shown with the average relative abundance at the species, genus, family, and order level in the fermentations of group NC (normal-lipid control) and group HL (hyperlipid control) with the treatment of LP-As (PDF)

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AUTHOR INFORMATION

Corresponding Author

*Tel./Fax: +86 20 87113914. E-mail: [email protected]. ORCID

Lianzhu Lin: 0000-0003-4657-1231 Baoguo Sun: 0000-0003-4326-8237 Mouming Zhao: 0000-0003-0221-3838 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This study was funded by the National Natural Science Foundation of China (No. 31871746 and No. 31701539) and Guangzhou Science and Technology Plan Project (Project No. 20160402172).

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DOI: 10.1021/acs.jafc.9b00970 J. Agric. Food Chem. 2019, 67, 7496−7505