Inulin with different degrees of polymerization protects against diet-induced endotoxemia and inflammation in association with gut microbiota regulation in mice

Societal lifestyle changes, especially increased consumption of a high-fat diet lacking dietary fibers, lead to gut microbiota dysbiosis and enhance the incidence of adiposity and chronic inflammatory disease. We aimed to investigate the metabolic effects of inulin with different degrees of polymerization on high-fat diet-fed C57BL/6 J mice and to evaluate whether different health outcomes are related to regulation of the gut microbiota. Short-chain and long-chain inulins exert beneficial effects through alleviating endotoxemia and inflammation. Antiinflammation was associated with a proportional increase in short-chain fatty acid-producing bacteria and an increase in the concentration of short-chain fatty acids. Inulin might decrease endotoxemia by increasing the proportion of Bifidobacterium and Lactobacillus, and their inhibition of endotoxin secretion may also contribute to antiinflammation. Interestingly, the beneficial health effects of long-chain inulin were more pronounced than those of short-chain inulin. Long-chain inulin was more dependent than short-chain inulin on species capable of processing complex polysaccharides, such as Bacteroides. A good understanding of inulin-gut microbiota-host interactions helps to provide a dietary strategy that could target and prevent high-fat diet-induced endotoxemia and inflammation through a prebiotic effect.

Immunomodulation. Transmembrane protein Toll-like receptor 4 (TLR4), interleukin 6 (IL6), interleukin 1β (IL1β), a dendritic cell marker (CD11c) and Ikk kinase ε (IKKε) are highly important proinflammatory indicators, as their abnormal activity is a major feature of inflammation. The mRNA expression of proinflammatory cytokines in epididymal fat tissue was evaluated. Compared to those in the NCD group, TLR4, IL6, IL1β, CD11c and IKKε levels in the HFD group rose 31.49%, 206.19%, 10.79%, 512.62% and 53.10%, respectively (Fig. 3). The five proinflammatory cytokines evaluated in this study were all inhibited to different extents by SC and LC inulin treatment.
Microbial community analysis. Chao 1, one of the most widely used alpha-diversity indexes in ecology, was used to estimate the total number of species. Our results showed that species richness in the HFD group was higher than that in the NCD group (Fig. 5A). Compared with the HFD, SC inulin increased species richness, whereas LC inulin decreased species richness (Fig. 5A). The difference in samples was analyzed by a nonmetric multidimensional scaling (NMDS) model, which revealed obvious separation among the NCD, HFD and two inulin groups (Fig. 5B). One-way analysis of similarity (ANOSIM) analysis showed that the separation was significant among the four groups (see Supplementary Fig. S1). Our results indicated that distinct diet treatments (NCD, HFD, SC and LC) produced distinct gut microbial communities. Furthermore, a Venn graph exhibited the shared and specific Operational taxonomic units (OTUs) among the four groups (Fig. 5C).
Taxonomic profiling suggested that the gut microbiota structure of mice was dominated mainly by the Firmicutes and Bacteroidetes phyla, which comprised more than 90% of the total phyla in the four groups (Fig. 5D). The ratios of Firmicutes to Bacteroidetes were 3.86, 2.72, 6.87 and 2.59 in the NCD, HFD, SC and LC groups, respectively. Furthermore, a high-fat diet significantly decreased the abundance of the Firmicutes phylum (p < 0.01), and this shift was restored by the SC and LC inulin treatments. The dominant families were Erysipelotrichaceae, Lactobacillaceae, Lachnospiraceae, Muribaculaceae, Ruminococcaceae and Rikenellaceae, accounting for more than 75% of the total families (Fig. 5E). The abundances of the Lachnospiraceae and Ruminococcaceae families were significantly stimulated by a high-fat diet (p < 0.01), and the enhancement was reduced by the SC and LC inulin interventions. Additionally, the abundances of the Erysipelotrichaceae and Lactobacillaceae families were decreased by a high-fat diet, and this reduction was increased by the SC and LC inulin supplementations. Notably, compared with SC inulin, LC inulin significantly suppressed the growth of the Lachnospiraceae family.

Discussion
A high-fat diet significantly increased body weight and tissue weight. Some metabolic metrics, such as TG, TC and serum insulin, were also disturbed by a high-fat diet. Notably, a high-fat diet elicited significantly different gut microbial communities compared with those with a normal chow diet. An increased ratio of Firmicutes to Bacteroidetes (F/B) was observed in the HFD group, which was supported by a study showing that the F/B ratio in overweight human adults was lower than that in lean controls 13 . A high-fat diet significantly increased the abundances of the Lachnospiraceae and Ruminococcaceae families (Fig. 5E), which are associated with obesity 14,15 .
Our work exhibited a significant enrichment of Erysipelotrichaceae after fermentable dietary fiber SC and LC inulin supplementation. Previous studies have shown positive correlations between Erysipelotrichaceae levels and complex carbohydrate consumption 16 . For example, Cox et al. reported that dietary fiber hydroxypropyl methylcellulose increased intestinal Erysipelotrichaceae levels 17 . Specifically, our results supported an association between Erysipelotrichaceae abundance and SCFA levels (see Supplementary Fig. S2), which was consistent with a report showing that Erysipelotrichaceae is an SCFA producer and that some species within this www.nature.com/scientificreports www.nature.com/scientificreports/ family are butyrate-producing bacteria 17 . Furthermore, the importance of Erysipelotrichaceae in inflammatory responses is highlighted by reports that its abundance has been found to be significantly increased in systemic inflammation in chronic HIV infection 18 , inflammatory bowel disease 19 and colorectal cancer 20 . The main reason for Erysipelotrichaceae affecting immunity might be because specific taxa of Erysipelotrichaceae are highly immunogenic 21,22 . Data are represented as the mean ± SD (n = 10). # p < 0.05, ## p < 0.01, comparisons between the HFD and NCD groups; *p < 0.05, ** p < 0.01, comparisons among the HFD, SC and LC groups. NCD, normal chow diet; HFD, high-fat diet; SC, high-fat diet plus short-chain inulin; LC, high-fat diet plus long-chain inulin. (2020) 10:978 | https://doi.org/10.1038/s41598-020-58048-w www.nature.com/scientificreports www.nature.com/scientificreports/ The gut microbiota communicates with the host through generated small molecular metabolites. SCFAs, a major class of microbial metabolites, serve as signaling molecules that can directly activate and inhibit endogenous signaling pathways or act as energy resources. SC and LC inulins significantly enhanced the concentrations of acetic acid, propionic acid, butyric acid, isobutyric acid and hexanoic acid in our study. Consistent with the enhancement of SCFA levels, a proportional increase in SCFA-producing bacteria, including the Bifidobacterium, Parasutterella and Allobaculum genera, was observed with SC and LC inulin treatments. Spearman correlation analysis also supported these results that Bifidobacterium, Parasutterella and Allobaculum were all positively correlated with SCFA levels.
SCFAs have broad impacts on a variety of aspects of host health outcomes, and SCFAs facilitate host immunity modulation through several pathways. For example, butyrate downregulated proinflammatory mediators by inhibiting histone deacetylases and dendritic cells 23 . Furthermore, SCFAs were found to exhibit proinflammatory effects by upregulating B cell metabolism, which enhances the systemic generation of IgG and IgA to modulate host immune responses 24 . In general, SCFAs can contribute to antiinflammation and help host defense against pathogens because of their capability to infiltrate into the bloodstream, where they can access G protein-coupled receptors in many tissues or suppress histone deacetylase activity in a variety of cells 25,26 .
Endotoxin refers to lipopolysaccharide (LPS), which is a component of the gram-negative bacterial outer membrane and can enter systemic circulation. In this study, the presence of serum endotoxin, which is known as endotoxemia, was significantly enhanced in the HFD group compared to that in the NCD group. Notably, endotoxemia was significantly alleviated by both SC and LC inulin intervention. The gut microbiota contributes to endotoxin regulation. The abundances of the Bifidobacterium and Lactobacillus genera, which are involved in the reduction in the intestinal endotoxin concentration and improvement in low grade inflammation 27,28 , were decreased by a high-fat diet and increased by inulins in our results. In agreement, Bifidobacterium and Lactobacillus abundances exhibited negative correlations with endotoxin levels (Fig. 6A,C). This result indicated that inulin decreased endotoxemia by increasing the proportion of Bifidobacterium and Lactobacillus. The promotion of these beneficial bacteria might shape environmental conditions (e.g., lowering the pH and increasing the levels of SCFAs) and even further inhibit the growth of some harmful bacteria, such as endotoxin-secreting bacteria.
High-fat diet-induced inflammation was clearly linked to endotoxin secretion 29 . Endotoxin can stimulate the TLR4, an endotoxin receptor found on the surface of many immune cells. TLR4 recruits intracellular adapter molecules to amplify the signal and modulates genes that control the inflammatory response. Leaked endotoxin can trigger adipose inflammation and lead to insulin resistance. Moreover, subcutaneous injections of purified LPS into mice stimulate low-grade inflammation in a manner similar to that of high-fat diet-feeding 30 . This result indicated that inulin modulated immunity through its inhibition of endotoxin secretion. www.nature.com/scientificreports www.nature.com/scientificreports/ SCFAs compared with that of the SC inulin intervention, which was consistent with the report that higher polymerization indicates higher acidification activity than lower polymerization in ex vivo fermentation 32 . Moreover, there was a significant difference in gut microbial communities between the SC and LC groups ( Fig. 5B and see Supplementary Fig. S1). The present study highlights the importance of choosing inulins of proper chain length to achieve good health outcomes.
Further insights into the difference in the gut microbiota showed that SC inulin preferentially stimulated the growth of Bifidobacterium, Faecalibaculum, Oscillibacter, Odoribacter, Blautia, Acetatifactor and Ruminiclostridium, and LC inulin preferentially supported the growth of Bacteroides, Parasutterella and Erysipelatoclostridium. This result was exemplified in previous studies showing that Bifidobacterium specifically utilized SC inulin but not highly polymerized inulin. Bifidobacterium has been reported to possess the enzymatic ability to effectively utilize oligosaccharides, which could be induced by the consumption of galactooligosaccharides and oligofructose 33,34 . Notably, Bacteroides, an LC inulin responder, has a series of enzymes that degrade complex polysaccharides into oligosaccharides and monosaccharides 35 . Moreover, LC inulin increased the abundance of the Muribaculaceae family 2-fold more than the SC group (Fig. 5E). Muribaculaceae is a newly proposed family encompassing OTUs previously classified as Porphyromonadaceae in some databases 36 . The abundance of Muribaculaceae, for which the name family S24-7 was previously used, was reported to be increased by inulins in our previous study 37 , and this family was versatile with respect to complex carbohydrate degradation 36 . This result indicated that LC inulin was more dependent on bacteria capable of processing complex polysaccharides than SC inulin because any fermentable carbohydrates, especially highly polymerized inulin, must be hydrolyzed to simple sugars before utilization by bacteria. In addition to the degrading ability, the ability to adsorb inulins, as well as to benefit from metabolites via cross-feeding, also determines the capacity per organism to benefit from inulin.
In conclusion, we found that SC and LC inulin treatments improved host health by alleviating endotoxemia and inflammation in mice fed a high-fat diet (Fig. 7). Notably, the beneficial health effects from LC inulin were more pronounced than those from SC inulin. LC inulin was more dependent on species with efficient hydrolytic capability than SC inulin, such as Bacteroides. Our study further suggests that the abilities of inulin intervention to enhance the relative abundance of SCFA-producing bacteria and increase the levels of SCFAs play a key role in antiinflammation. Inulin might decrease endotoxemia by increasing the proportion of Bifidobacterium and Lactobacillus, and their inhibition of endotoxin secretion also contributed to antiinflammation.

Materials and Methods
Materials. Male C57BL/6 J mice were purchased from Pengyue Laboratory Animal Company (Jinan, China).
Animal treatment and sample collection. Mice were housed in a temperature-and humidity-controlled laboratory. Approval of this animal experiment was approved by the Animal Protection Ethics Committee of Binzhou Medical University. The ethical approval number of the animal experiments was F-KY-0022-20181101-01. All animal experiments were performed in accordance with Chinese national regulations on the administration of animal experimentation as well as international guidelines on animal experimentation. After one week of acclimatization, mice were randomly divided into four groups (n = 10): the normal chow diet (NCD, 10% fat calories, Research Diets D12450B; Research Diets, Beijing HFK Bioscience Co., Ltd.) group, high-fat diet (HFD, 60% fat calories, Research Diets D12492; Research Diets, Beijing HFK Bioscience Co., Ltd.) group and high-fat diet plus short-chain inulin (SC, 5 g/100 g diet) or long-chain inulin (LC, 5 g/100 g diet) groups. Food intake and body weight were monitored every week. At 10 weeks, fecal samples were collected in individual sterilized cages and immediately frozen in liquid nitrogen. Gut microbiota analysis. Raw data were obtained after data were processed using Cutadapt (V1.9.1, http:// cutadapt.readthedocs.io/en/stable/). Then, chimera sequences were removed to obtain clean reads. OTUs were assigned for sequences with ≥ 97% similarity. OTUs were annotated using the SILVA132 database (http://www. arb-silva.de/). The taxonomic information was obtained, and the community composition was counted at seven taxonomic levels: kingdom, phylum, class, order, family, genus and species. Alpha-diversity was analyzed by Chao 1 (http://scikit-bio.org/docs/latest/generated/generated/skbio.diversity.alpha.chao1.html#skbio.diversity. alpha.chao1) with QIIME software (version 1.9.1). Beta-diversity metrics were calculated by the NMDS model based on Bray-Curtis distance. One-way ANOSIM analysis with multiple pairwise post-tests on all groups at the same time was performed to test whether the difference between the extragroups was greater than that between the intragroups and to assess the significance of the difference in separation. The Chao1, Bray-Curtiss indexes, NMDS and ANOSIM were calculated at OTU level. Differentially abundant genera were analyzed by metastats (https://omictools.com/metastats-tool) with a nonparametric test, followed by the Benjamini and Hochberg false discovery rate approach to filter relevant p-values.
Measurement of SCFAs and serum endotoxin. SCFAs, including acetic acid, propionic acid, butyric acid, isobutyric acid, pentanoic acid, isopentanoic acid and hexanoic acid, were extracted by ether (>99%, Sigma Aldrich), with cyclohexanone as an internal standard. The samples were analyzed by gas chromatography-mass spectrometry (GC-MS, Agilent Technologies Inc., Palo Alto, CA, USA). The apparatus parameters were set according to the method described in our previous study 39 . Additionally, serum endotoxin was measured according to the instructions of the Endotoxin ELISA Kit (Yanbixin Company, Beijing, China). Statistical analysis. Data were analyzed using SPSS (version 12.0, SPSS Inc., Chicago, IL). Differences between the NCD and HFD groups were analyzed using one-way analysis of variance. The HFD, SC and LC groups were analyzed using one-way analysis of variance and post-hoc testing with the Bonferroni-Holm method. Time-series data from the glucose tolerance test were analyzed using two-way analysis of variance and post hoc testing with the Bonferroni-Holm method. Data are represented as the mean ± SD. p values less than 0.05 or 0.01 were considered statistically significant.