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Effects of chitosan oligosaccharide-nisin conjugates formed by Maillard reaction on the intestinal microbiota of high-fat diet-induced obesity mice model

Effects of chitosan oligosaccharide-nisin conjugates formed by Maillard reaction on the... Objectives: The goal of this study was to evaluate the modulatory effect of chitosan oligosaccharide- nisin conjugate (CON-C) on intestinal microbiota of human flora-associated (HFA) mice and also reveal its effect towards the high-fat diet (HFD)-induced obesity. Both Chitosan oligosaccharides and nisin showed great potential in modulating the intestinal microbiota, so it is worth to explore whether the modulation effect of chitosan oligosaccharide could be improved by covalently binding with nisin. Materials and Methods: CON-C was prepared by heating the mixed solution of chitosan oligosaccharide and nisin at 80°C and pH 2.0 for 24h. The structure of CON-C were analyzed by Fourier transform-infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). The CON-C’s anti- obesity effect and modulatory effect toward intestinal microbiota were analyzed using human flora-associated (HFA) mice model. Results: CON-C could alleviated HFD-induced gut dysbiosis, by significantly decreasing the numbers of Bifidobacterium and Lactobacillus/Enterococcus spp., and increasing the numbers of Bacteroides–Prevotella and Clostridium groups. CON-C could also enriched the most differentially expressed genes through KEGG pathways of biosynthesis of amino acids, two-component system, and ATP binding cassette (ABC) transporters. Conclusions: The improved therapeutic effect of CON-C against HFD-induced obesity has been approved, and hence, CON-C has a great potential to be utilized as a functional food ingredient in reducing body weight. Key words: chitosan oligosaccharide; nisin; Maillard reaction; modulatory effect; intestinal microbiota. In human gastrointestinal tract, the vast majority of microbial Introduction residents could form a stable microbial ecosystem, which played Obesity is a global concerned health problem nowadays, which a critical role for human’s health and were also closely associated is strongly associated with metabolic syndromes (Franks and with obesity epidemic (Bäckhed et  al., 2005; Gill et  al., 2006). Mccarthy, 2016). It has been revealed that the imbalance between More recently, the relationship between intestinal flora and intake and energy expenditure and environmental and genetic obesity has increasingly aroused general concerns. The intestinal factors are the essential causes of obesity (Rains et  al., 2011). © The Author(s) 2019. Published by Oxford University Press on behalf of Zhejiang University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 170 Zheng et al., 2019, Vol. 3, No. 3 flora were found significantly different between lean and obese of Academy of the Military Medical Sciences (Beijing, China). individuals (Wang et al., 2014). In a study of high-fat diet (HFD)- Research Diets D12450B 10 kcal% Fat and D12492 60 kcal% Fat induced obesity mice, the gut microbiota were disrupted and were purchased from Research Diets, Inc. (New Brunswick, NJ). All hence lead to inflammation and associated disorders, because other chemicals and reagents were analytical grade. of the increased intestinal permeability (Cani et  al., 2008). it was believed that the goal of weight-loss could be achieved by Preparation of CON-C manipulating microbiota(Wang et al., 2014). The CON-C were prepared by the Maillard reaction between CO Nisin is a small cationic peptide composed of 34 amino acid res- and nisin, according to the methods of Zhu et al. (2008) with some idues, which is produced by Lactococcus lactis subsp. lactis. Lactococcus modifications. Mixtures of CO and nisin in 5:1 ratios (w/w) were lactis is a food grade lactic acid bacterium, generally recognized as dissolved in water at a total concentration of 2%. The sample solu- safe (GRAS), and nisin was also recognized as a food additive in EU tions were stirred on a magnetic stirrer at room temperature for 2 h (Balciunas et  al., 2013). Nisin exhibits a wide spectrum antimicro- to completely dissolve the mixture. The pH values of the solution bial activity against Gram-positive bacteria, including Lactococcus, was adjusted to 2.00 ± 0.01 using HCL. The solution were heated in Streptococcus, Staphylococcus, Micrococcus, and so on (Juneja et  al., a water batch at 80°C for 24 h samples were then taken out of the 2012; Muppalla et  al., 2012). Because of the low molecular weight, water bath, cooled in ice, and freeze dried. high heat-tolerant, excellent water-soluble, no immunogenicity, and no adverse effects on human, nisin showed great advantages and broad Characteristic analysis of CON-C application prospects (Hu et  al., 2017). However, its antibacterial ac- Fourier transform-infrared spectroscopy tivity is often affected by environmental factors, including pH, tempera- Samples were powdered and analysed as KBr pellets (1:99, w/w) ture, and food matrix (Xiao et al., 2011). Nisin can interact with food using Nicolet iS10 Fourier transform-infrared spectroscopy (FT- components, such as proteins, lipids, and pro-metabolic enzymes, which IR) spectrophotometer (Thermo Fisher Scientific). The pellets were lead to the loss of its biological activity. placed in the sample holder. Spectral scanning was taken in the To enhance the stability and prolong the efficacy of nisin, dif- −1 wavelength region between 4000 and 400  cm at a resolution of ferent strategies, such as chemical synthesis, Maillard reaction, and −1 −1 4 cm with scan speed of 2 mm s . complex with saccharides to form nanoparticels, have been developed (Muppalla et  al., 2012; Hu et  al., 2017; Zhu et  al., 2017). Among X-ray diffraction assay them, covalent coupling of carbohydrates through the Maillard-type A D8 ADVANCE X-ray diffraction (XRD) (Bruker-AXS Co., reaction appears to be a promising way (Li et al., 2014). The Maillard Germany) was applied to detect the crystallinity of samples and their reaction, resulting from the initial condensation between amino group patterns based on the wide-angle X-ray diffraction (WAXD) ana- of chitosan and carbonyl moiety of reducing sugars, aldehydes, or ke- lysis. 2θ was scanned from 10° to 80° at a coating time of 2 s with tones, is one of the main reactions taking place in food (Li et al., 2014). an angle step width of 0.05°. Because it does not require additional chemical reagents, Maillard re- action is considered as a green way of modification, and is widely used in the modification of proteins and polysaccharides (Kato, 2002; The antimicrobial of CON-C Oliveira et al., 2014). Muppalla et al. (2012) significantly increased the The antimicrobial properties of CON-C were evaluated according antimicrobial of nisin towards Pseudomonas fluorescens, Escherichia to the reported method with modifications(Song et  al., 2002). coli, Staphylococcus aureus, and Bacillus  cereus by glycating it with Escherichia coli and S. aureus were activated and diluted to the ap- dextran and glucose. propriate concentration with 20 mM phosphate buffer (pH 6.0). The In this study, we select chitosan oligosaccharide (CO) to conju- 4.5  ml of the cell suspension was mixed with 0.5  ml of chitosan gate with nisin via Maillard reaction. CO is a natural cationic poly- oligosaccharide–nisin mixture (CON-M) and CON-C, respectively saccharide and one of the most abundant and renewable natural (The concentration were 0.001%, 0.002%, 0.004%, and 0.005%), resources (Peng et  al., 2013). Because of its unique characteristics and incubated at 37°C for 1 h. Then a 100 µl portion of each treat- of nontoxicity, biocompatibility, biodegradability, and broad anti- ment was surface-plated onto agar plate and incubated at 37°C for microbial spectrum, CO is widely used as food functional ingredient 24 h. Sample-free solution was used as a control. The antimicrobial (Rinaudo, 2006; Kong et al., 2010). Currently, CO has been applied properties of each treatments were compared according to the bac- to deliver drugs, enzymes, and prepare nano-composite particles terial survival rate, which calculated as follows: (Sanyakamdhorn et al., 2013). We then investigated the modulatory effect of chitosan oligosaccharide and nisin conjugates (CON-C) on The bacterial survival rate% ï ò intestinal microbiota. By transplanting faecal microbiota from adult The number of bacteria in each treatment = × 100% human into germ-free mice, we established a relatively stable human The number of bacteria in the control group gut micro-community in recipient mice model, the objective of the present study was to investigate the effects of CON-C on human faecal microbiota, in addition, the abundance of genes enriched in Animals and experimental design various metabolic pathways altered by CON-C in the humanized The anti-obesity effects of CON-C were evaluated according to the re- mouse gut microbiome were investigated. ported method with modifications (Mei et  al., 2017). Firstly, six volun- teers (three females and three males, 25–30 years old), who did not have any history of gastrointestinal disorders and had not been treated with Materials and Methods antibiotics for the previous 6 months, were recruited. Their freshly voided Materials faeces were used to colonize the young adult (6-week old) male mice. Mice Nisin and CO with the deacetylation degree of 90% (5  kDa) then were housed in separate cages within a gnotobiotic isolator under were obtained from Golden Shell (Hangzhou, China). Germ-free 12 h light-dark cycle and with the temperature and humidity controlled C57BL/6J mice were obtained from the Experimental Animal Centre to 22–24°C and 50% ± 10%, respectively. After 7 days with high-fat diet Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 171 (Research Diets D12492 60 kcal% Fat), the mice were then randomly a length less than 100 bp were subsequently filtered out. Finally, a gene divided into five groups with eight in each group: low fat diet group (LFD, catalog containing 255 320 nonredundant genes was constructed. Based Research Diets D12450B 10 kcal% Fat), high-fat diet group (HFD), high- on this reference gene set, we carried out taxonomical assignment and fat diet with nisin group (HFD-N), high-fat diet with CON-M group functional annotation using the NR (Non-Redundant), KEGG (Kyoto (HFD-CON-M), and high-fat diet with CON-C group (HFD-CON-C). Encyclopedia of Genes and Genomes), GO (Gene Ontology), and CAZy Nisin, CON-M, and CON-C were added to the high-fat diet at a final con- (Carbohydrates-Active enzymes) databases of the latest version. centration of nisin at 0.1% (w/w). Sample food and water consumption were measured on a per cage basis three times per week and the averages Taxonomical assignment and functional of food and water consumed were calculated weekly. The body mass of classification each animal was recorded soon after feeding with different diets for the en- The nucleotide sequences of predicted genes were translated into tire period since the start of breeding. Faecal samples were collected from protein sequences using the NCBI Genetic Codes 11. Basic local 0 (CON-C0), 2 (CON-C2), 4 (CON-C4), and 8 weeks (CON-C8) after alignment search tool (BLAST) was employed to conduct the taxo- they were divided into each group. All administrations were conducted for nomical assignment and functional classification of predicted genes eight consecutive weeks. −3 against the corresponding data base with E value ≤1  × 10 . All genes were searched against IMG (v3.4) with N-BLAST using Histopathological evaluation −5 default parameters except that the E value was set to 1  × 10 . Mouse epididymal white adipose tissue (eWAT) and liver were The taxonomical association of a gene was decided by the lowest fixed in 4% neutral buffered formalin and embedded in paraffin. common ancestor of all its taxonomical annotation results. Anti-F4/80 primary antibody (Abcam, British) was used to perform the immunohistochemical staining of paraffin sections (Liu et al., 2017). The representative images of the possible histopathological changes were de- Statistical analysis tected under a high-resolution microscope with photographic facility. Data were analysed by SPSS and expressed as mean ± standard de- viation (SD). Significance was determined at P  <  0.05 by ANOVA Enumeration of bacteria by fluorescent in situ followed by Duncan’s multiple-comparison tests. hybridization The bacterial cells used for hybridization were prepared according to Results and Discussion Zhang et al. (2013). Faecal slurries of mice were collected at different time points and were mixed with autoclaved phosphate-buffered sa- Characterization of CON-C line to yield 10% (w/v) suspensions. The samples were inoculated FT-IR spectra was a useful tool to analysis the derivatives formed with 150 μl of faecal slurry (10%, w/v) with a manual homogenizer by Maillard reaction. Figure 1 showed FTIR spectra of CO, nisin, at 37°C in an anaerobic incubator (10% H , 10% CO , and 80% 2 2 and CON-C. For the nisin, the characteristic absorption bands N ). The 100 µl culture samples were then added to 300 μl filtered −1 −1 around 3288 cm and 2960 cm attributed to axial O–H and N–H paraformaldehyde solution (4%, w/v), and fixed overnight at 4°C. −1 stretching. The peak at 1652 cm which can be attributed to amide Hybridization were performed according to the reported methods −1 − band and the peak at 1449  cm evidenced the presence of COO (Sánchez-Patán et al., 2012). The probes used were Bif164, Lab158, symmetric stretching vibrations (Krivorotova et  al., 2016). For the Bac303, and His150. The bacterial cells were counted using an epi- −1 CO, the characteristic absorption bands around 3444 and 2991 cm fluorescence microscope. At least six random fields were counted on was attributed to –NH, –OH, and –CH– stretching vibration. The each slide, and the bacterial numbers were expressed as log cells −1 characteristic peaks at around 1631, 1526, and 1394  cm were per milliliter ± standard deviation (SD). assigned to amide I, amine II, and amide III absorption bands of Construction of a gut metagenome reference Metagenomic sequencing was conducted using HiSeq4000 and PE150 strategy. DNA from different samples was extracted using the E.Z.N.A. ®Stool DNA Kit (D4015, Omega, Inc.) according to manufacturer’s instructions. The total DNA was eluted in 50 μl of elution buffer and stored at −80°C until measurement in the PCR by LC-Bio Technology Co., Ltd (Hang Zhou, Zhejiang Province, China), and the isolation was confirmed by 1.2% agarose gel electrophoresis. Sequencing libraries were generated using NEB Next Ultra DNA Library Prep Kit for Illumina (NEB) following manufacturer’s recommendations and index codes were added. The library quality was assessed on the Qubit@ 2.0 Fluorometer (Life Technologies, CA) and Agilent Bioanalyzer 2100 system. At last, the library was sequenced on an Illumina MiSeq plat- form and 300 bp paired-end reads were generated. All open reading frames (ORFs) predicted from different samples were merged and aligned to each other using BLAT (Bankevich et al., 2012). Gene pairs with greater than 95% identity (no gap allowed) and aligned reads covering over 90% of the shorter reads were grouped together. The longest ORF in each group was used to represent the group, and the other Figure 1. FT-IR spectra of CO, nisin, and CON-C. ORFs of the group were regarded as redundant sequences. ORFs with Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 172 Zheng et al., 2019, Vol. 3, No. 3 CO, respectively (Umemura and Kawai, 2007). The FTIR spectra of CON-C exhibited significant differences from that of nisin and −1 CO after Maillard reaction. The absorption peaks of 3385 cm re- lated to stretching vibrations of N–H widened and the peak of amide −1 band was slightly shifted to lower wave number 1625 cm , which indicated the formation of the hydrogen bonding between nisin and CO. These results were also consistent with the previous study (Zhu et al., 2015). The packing structures of nisin, CO, and CON-C were deter- mined by XRD technique (Figure 2). The nisin showed a remarkable peak at 31.5°, which corresponded to the characteristic diffrac- tion pattern of sodium chloride (NaCl), a component of Nisaplin (Meira et  al., 2015). For CO, the diffraction peaks at 2θ  =  12.2° and 2θ = 23.5° were observed, which corresponded to the diffrac- tion peaks of (020) and (200) crystal plane (Luo et al., 2013). After Maillard reaction, the peak of CON-C at 12.2° shift to low degree Figure 3. Antimicrobial properties of CON-M and CON-C. and the peak at 23.5° disappeared. Besides all the characteristic crystalline peaks were broader and the crystallinity significantly de- Influence of CON-C on liver histopathology of HFD- creased, indicating that Maillard reaction can reduce the crystallinity induced obesity mice model of the reactants (Li et al., 2013). Obesity is characterized by chronic low-degree inflammation. A pre- vious report indicated that adipose tissue macrophage accumulation The antimicrobial properties of CON-C is directly proportional to measures of adiposity both in mice and As shown in Figure 3, the inhibition of CON-C on E.  coli and humans(Weisberg et  al., 2003). As the eWAT and liver staining re- S.  aureus was significantly higher than that of CON-M: the half- sults (Figure 5) shows, HFD-fed mice showed significantly greater lethal doses of CON-C on E. coli and S. aureus were 45% and 80% microphage accumulation compared with LFD-fed mice, which of the latter. It illustrate that Maillard reaction could efficiently im- is consistent with previous reports(Kanda et  al., 2006). While the prove the antimicrobial properties of both CO and nisin. Similar microphage accumulation in HFD-fed mice was alleviated when to our results, chitosan conjugated with glucose or xylose showed supplemented with CON-C. greater antimicrobial properties (Kanatt et  al., 2008; Zhu et  al., 2013). Influence of CON-C on bacterial populations In general terms, intestinal bacteria could be divided into species Influence of CON-C on body and organ mass of including potentially beneficial or harmful towards the host. Beneficial mice model bacteria mainly include Lactobacillus and Bifidobacterium, which Compared with the other HFD fed mice, the CON-C treated one play important roles in nutrition and prevention of disease, while showed significantly slower body weight gain rate and fewer liver the harmful intestinal bacteria, such as Clostridium, Veillonella, weight gain (Figure 4b and 4c). Considering there were no significant Staphylococcus, occasionally Enterococcus and Escherichia, may differences between all FHD fed mice in water intake and food con- produce potentially harmful substances to the host (Hooper and sumptions (Figure 4a and 4b), which indicating that nisin, CON-M, Gordon, 2001). In this study, we selected Bifidobacterium and and CON-C did not affect the food intakes behaviour of the mice, Lactobacillus/Enterococcus as the representative species of potential the anti-obesity effects of CON-C can hence be confirmed. benefits, and Bacteroides–Prevotella and Clostridium histolyticum as the representative species of potential harm. In consistent with others’ reports (Cani et  al., 2008), the mice fed with LFD diets showed significantly higher amount (P  <  0.05) of Bifidobacterium and Lactobacillus/Enterococcus and lower amount of Bacteroides– Prevotella and C.  histolyticum (Table 1). Recent study indicated that changes in gut microbiota composition are related to the devel- opment of obesity and its associated metabolic disorders (Ridaura et  al., 2013), and obesity-induced gut dysbiosis may impairs intes- tinal integrity (Cani et  al., 2009). In our case, the development of obesity in HFD fed group could partially be explained by the change of bacterial populations caused by the HFD. Among the mice fed with HFD, the one suppled with CON-C had the highest amount of Bifidobacterium and Lactobacillus and lowest amount of Bacteroides–Prevotella and Clostridium histolyticum (Table 1). As our previous results shows, the CON-C had improved antimicrobial properties against E.  coli, and it is possible that the CON-C alleviated the development of obesity induced by HFD, by selectively suppress certain bacterial groups. However, the potential mechanisms of CON-C on the prevention of gut dysbiosis are com- Figure 2. XRD patterns of CO, nisin, and CON-C. plicated and need further clarified. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 173 Figure 4. Effect of nisin, CON-M, and CON-C on the water intake (A), food intake (B), liver weight (C), and body weight (D) of high-fat diet-induced mice. Different letters indicate significant differences (P < 0.05) among different groups. Figure 5. Representative F4/80 immunostaining image of eWAT between LFD (i), HFD (ii), and HFD–CON-C (iii) groups, and liver between LFD (I), HFD (II), and HFD–CON-C (III) groups. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 174 Zheng et al., 2019, Vol. 3, No. 3 −1 Table 1 Time-dependent changes observed in the numbers (log cell ml ) of Bifidobacterium, Lactobacillus/Enterococcus spp., Bacteroides–Prevotella, and Clostridium histolyticum group in the gut of HFA mice model.* Probe type Group Time (week) 1 2 4 8 Bif 164 LFD 7.83 ± 0.02 a, A 8.01 ± 0.02 c, B 8.16 ± 0.01 d, C 8.21 ± 0.02 c, D HFD 7.82 ± 0.01 a, A 7.95 ± 0.02 a, B 8.07 ± 0.02 a, C 8.10 ± 0.01 a, D HFD-N 7.82 ± 0.02 a, A 7.96 ± 0.02 a, B 8.08 ± 0.02 a, C 8.11 ± 0.02 b, D HFD–CON-M 7.83 ± 0.02 a, A 7.95 ± 0.01 a, B 8.08 ± 0.01 a, C 8.10 ± 0.03 c, D HFD–CON-C 7.83 ± 0.01 a, A 7.99 ± 0.02 b, B 8.11 ± 0.01 b, C 8.16 ± 0.02 b, D Lab 158 LFD 7.71 ± 0.01 a, A 7.82 ± 0.02 b, B 8.02 ± 0.02 c, C 8.11 ± 0.01 c, D HFD 7.70 ± 0.02 a, A 7.74 ± 0.01 a, B 7.88 ± 0.01 a, C 8.01 ± 0.01 a, D HFD-N 7.71 ± 0.01 a, A 7.75 ± 0.02 a, B 7.86 ± 0.02 a, C 8.03 ± 0.02 a, D HFD–CON-M 7.70 ± 0.02 a, A 7.75 ± 0.02 a, B 7.89 ± 0.02 a, C 8.03 ± 0.02 a, D HFD–CON-C 7.71 ± 0.02 a, A 7.76 ± 0.02 a, B 7.95 ± 0.03 b, C 8.07 ± 0.02 b, D Bac 303 LFD 7.20 ± 0.01 a, A 7.21 ± 0.02 a, A 7.20 ± 0.02 a, A 7.21 ± 0.02 a, A HFD 7.20 ± 0.01 a, A 7.23 ± 0.03 b, B 7.28 ± 0.02 b, C 7.30 ± 0.02 b, D HFD-N 7.19 ± 0.02 a, A 7.22 ± 0.03 b, B 7.27 ± 0.02 b, C 7.29 ± 0.03 b, D HFD–CON-M 7.20 ± 0.02 a, A 7.23 ± 0.02 b, B 7.28 ± 0.01 b, C 7.30 ± 0.03 b, D HFD–CON-C 7.20 ± 0.02 a, A 7.21 ± 0.02 a, A 7.21 ± 0.01 a, A 7.21 ± 0.02 a, A His 150 LFD 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A HFD 7.01 ± 0.01 a, A 7.04 ± 0.01 b, B 7.07 ± 0.02 b, C 7.11 ± 0.02 b, D HFD-N 7.02 ± 0.02 a, A 7.03 ± 0.02 b, A 7.06 ± 0.03 b, B 7.10 ± 0.02 b, C HFD–CON-M 7.02 ± 0.02 a, A 7.04 ± 0.02 b, A 7.06 ± 0.02 b, B 7.11 ± 0.02 b, C HFD–CON-C 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.03 ± 0.03 a, A 7.03 ± 0.02 a, A *One-way ANOVA and Tukey tests were used to determine significant differences for total bacterial population. Different lowercases indicate significant differ - ences (P < 0.05) for total bacterial (i.e. within column) among different groups. Different capital letters indicate significant differences (P < 0.05) for total bacterial (i.e. within line) among the different time points. Figure 6. Imputed metagenomic differences between CON-C0 and CON-C8. The relative abundance of metabolic pathways encoded in each imputed sample metagenome was analysed using STAMP. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 175 Figure 7. KEGG analysis of differentially expressed genes between CON-C0 and CON-C8. Figure 8. GO analysis of differentially expressed genes between CON-C0 and CON-C8. Influence of CON-C on the humanized mice gut two-component system, and ATP-binding cassette (ABC) trans- porters (Figure 7), and ABC transporters included those predicted to microbiome be involved in sugar, amino acid, and cofactor import. The imputed relative abundances of KEGG pathways in each re- The database of GO provides three types of systematic defin- spective sample were used to predict changes in metabolic func- itions for describing the function of gene products. The structures tion within the microbiomes of different CON-C intervention time of GO functions include molecular function, biological process, (Figure  6). The KEGG pathway demonstrated lipid metabolism, and cellar components, and we selected 10 of the largest GO drug resistance, metabolism of other amino acids, metabolism of terms in each function. GO analysis of CON-C0 and CON-C8 terpenoids and polyketides, transcription and biosynthesis of other showed that the most differentially expressed genes were regu- secondary metabolites accounted for the highest proportion. In the lation of transcription, DNA-templated, transport, phosphorelay meanwhile, the greatest statistical difference between CON-C0 and signal transduction system, metabolic process, and translation CON-C8 were metabolism of terpenoids and polyketides, transcrip- in biological process; cytosol, cellular components, cytoplasm, tion, and biosynthesis of other secondary metabolites. The CON-C plasma membrane, and membrane in cellular components; ATP associated faecal microbiome for 8 weeks was enriched for a binding, transcription factor activity, sequence-specific DNA number of KEGG pathways involved in biosynthesis of amino acids, Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 176 Zheng et al., 2019, Vol. 3, No. 3 binding, protein binding, catalytic activity, and DNA binding in Conclusions molecular functions (Figure 8). In the present study, conjugates based on nisin and CO were pre- CAZy is a special database dedicated to the analysing of the pared using the Maillard reaction. The prepared CON-C showed genomic, structural, and biochemical information of carbohydrate significant protective effect against obesity induced by HFD. By active enzymes, and it covers six major functional categories: glyco- fermentation in vitro with faecal microbiota of HFD-induced side hydrolases (GHs), glycosyltransferase (GTs), polysaccharide obesity mice, it was found that CON-C significantly promote lyases (PLs), carbohydrate esterases (CEs), assisted redox (AAs), the growth of Bifidobacterium and Lactobacillus- Enterococcus and carbohydrate-binding modules (CBMs), which can be further spp., while inhibiting Bacteroides–Prevotella and C.  histolyticum divided into functional subclasses. To investigate if the carbohy- groups. In addition, KEGG and GO pathways showed the most drate utilization of mice gut microbiota increased as a response to significantly enriched differentially expressed genes after CON-C GTP intervention in high-fat diet-induced obesity, we used CAZy to intervention. It suggested CON-C intervention may benefit the sta- search for the key enzyme involved in CAZy level 1.  As the result bility of certain gut microbiota, and affect corresponding meta- showed, GHs, CEs, and PLs were dramatically enriched after GTP bolic pathways, making the contribution to the improvement of intervention, while the abundance of GTs, CBMs, and AAs were less human health. affected, which suggested that the increased capacity for carbohy- drate utilization characterizes high-fat diet-induced changes in the gut microbiota affected by CON-C. Funding The next-generation sequencing platforms provide the opportunity This work was sponsored by Key Research and Development Project of to explore the taxonomic, protein-coding gene, or expression diver- Zhejiang Province (2017C02039). sity nowadays, by applying more comprehensive and less biased meas- urements to the complicated relationship among diet, microbiota, and host, and they have provided a great deal of new information on the Conflict of Interest diversity and composition of human gut microbiota (Zoetendal and The authors declared no conflict of interest. Rajilic-Stojanovic, 2008). With regard to the Maillard reaction prod- ucts (CNMs), it has been reported that the CNMs destabilize the outer References membrane and inhibit the growth of bacterial cells, due to their ex- cellent surfactant properties (Nakamura et  al., 1991).The conjugates Bäckhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A., Gordon, J. I. 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Effects of chitosan oligosaccharide-nisin conjugates formed by Maillard reaction on the intestinal microbiota of high-fat diet-induced obesity mice model

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Oxford University Press
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© The Author(s) 2019. Published by Oxford University Press on behalf of Zhejiang University Press.
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2399-1399
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2399-1402
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10.1093/fqsafe/fyz016
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Abstract

Objectives: The goal of this study was to evaluate the modulatory effect of chitosan oligosaccharide- nisin conjugate (CON-C) on intestinal microbiota of human flora-associated (HFA) mice and also reveal its effect towards the high-fat diet (HFD)-induced obesity. Both Chitosan oligosaccharides and nisin showed great potential in modulating the intestinal microbiota, so it is worth to explore whether the modulation effect of chitosan oligosaccharide could be improved by covalently binding with nisin. Materials and Methods: CON-C was prepared by heating the mixed solution of chitosan oligosaccharide and nisin at 80°C and pH 2.0 for 24h. The structure of CON-C were analyzed by Fourier transform-infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). The CON-C’s anti- obesity effect and modulatory effect toward intestinal microbiota were analyzed using human flora-associated (HFA) mice model. Results: CON-C could alleviated HFD-induced gut dysbiosis, by significantly decreasing the numbers of Bifidobacterium and Lactobacillus/Enterococcus spp., and increasing the numbers of Bacteroides–Prevotella and Clostridium groups. CON-C could also enriched the most differentially expressed genes through KEGG pathways of biosynthesis of amino acids, two-component system, and ATP binding cassette (ABC) transporters. Conclusions: The improved therapeutic effect of CON-C against HFD-induced obesity has been approved, and hence, CON-C has a great potential to be utilized as a functional food ingredient in reducing body weight. Key words: chitosan oligosaccharide; nisin; Maillard reaction; modulatory effect; intestinal microbiota. In human gastrointestinal tract, the vast majority of microbial Introduction residents could form a stable microbial ecosystem, which played Obesity is a global concerned health problem nowadays, which a critical role for human’s health and were also closely associated is strongly associated with metabolic syndromes (Franks and with obesity epidemic (Bäckhed et  al., 2005; Gill et  al., 2006). Mccarthy, 2016). It has been revealed that the imbalance between More recently, the relationship between intestinal flora and intake and energy expenditure and environmental and genetic obesity has increasingly aroused general concerns. The intestinal factors are the essential causes of obesity (Rains et  al., 2011). © The Author(s) 2019. Published by Oxford University Press on behalf of Zhejiang University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 170 Zheng et al., 2019, Vol. 3, No. 3 flora were found significantly different between lean and obese of Academy of the Military Medical Sciences (Beijing, China). individuals (Wang et al., 2014). In a study of high-fat diet (HFD)- Research Diets D12450B 10 kcal% Fat and D12492 60 kcal% Fat induced obesity mice, the gut microbiota were disrupted and were purchased from Research Diets, Inc. (New Brunswick, NJ). All hence lead to inflammation and associated disorders, because other chemicals and reagents were analytical grade. of the increased intestinal permeability (Cani et  al., 2008). it was believed that the goal of weight-loss could be achieved by Preparation of CON-C manipulating microbiota(Wang et al., 2014). The CON-C were prepared by the Maillard reaction between CO Nisin is a small cationic peptide composed of 34 amino acid res- and nisin, according to the methods of Zhu et al. (2008) with some idues, which is produced by Lactococcus lactis subsp. lactis. Lactococcus modifications. Mixtures of CO and nisin in 5:1 ratios (w/w) were lactis is a food grade lactic acid bacterium, generally recognized as dissolved in water at a total concentration of 2%. The sample solu- safe (GRAS), and nisin was also recognized as a food additive in EU tions were stirred on a magnetic stirrer at room temperature for 2 h (Balciunas et  al., 2013). Nisin exhibits a wide spectrum antimicro- to completely dissolve the mixture. The pH values of the solution bial activity against Gram-positive bacteria, including Lactococcus, was adjusted to 2.00 ± 0.01 using HCL. The solution were heated in Streptococcus, Staphylococcus, Micrococcus, and so on (Juneja et  al., a water batch at 80°C for 24 h samples were then taken out of the 2012; Muppalla et  al., 2012). Because of the low molecular weight, water bath, cooled in ice, and freeze dried. high heat-tolerant, excellent water-soluble, no immunogenicity, and no adverse effects on human, nisin showed great advantages and broad Characteristic analysis of CON-C application prospects (Hu et  al., 2017). However, its antibacterial ac- Fourier transform-infrared spectroscopy tivity is often affected by environmental factors, including pH, tempera- Samples were powdered and analysed as KBr pellets (1:99, w/w) ture, and food matrix (Xiao et al., 2011). Nisin can interact with food using Nicolet iS10 Fourier transform-infrared spectroscopy (FT- components, such as proteins, lipids, and pro-metabolic enzymes, which IR) spectrophotometer (Thermo Fisher Scientific). The pellets were lead to the loss of its biological activity. placed in the sample holder. Spectral scanning was taken in the To enhance the stability and prolong the efficacy of nisin, dif- −1 wavelength region between 4000 and 400  cm at a resolution of ferent strategies, such as chemical synthesis, Maillard reaction, and −1 −1 4 cm with scan speed of 2 mm s . complex with saccharides to form nanoparticels, have been developed (Muppalla et  al., 2012; Hu et  al., 2017; Zhu et  al., 2017). Among X-ray diffraction assay them, covalent coupling of carbohydrates through the Maillard-type A D8 ADVANCE X-ray diffraction (XRD) (Bruker-AXS Co., reaction appears to be a promising way (Li et al., 2014). The Maillard Germany) was applied to detect the crystallinity of samples and their reaction, resulting from the initial condensation between amino group patterns based on the wide-angle X-ray diffraction (WAXD) ana- of chitosan and carbonyl moiety of reducing sugars, aldehydes, or ke- lysis. 2θ was scanned from 10° to 80° at a coating time of 2 s with tones, is one of the main reactions taking place in food (Li et al., 2014). an angle step width of 0.05°. Because it does not require additional chemical reagents, Maillard re- action is considered as a green way of modification, and is widely used in the modification of proteins and polysaccharides (Kato, 2002; The antimicrobial of CON-C Oliveira et al., 2014). Muppalla et al. (2012) significantly increased the The antimicrobial properties of CON-C were evaluated according antimicrobial of nisin towards Pseudomonas fluorescens, Escherichia to the reported method with modifications(Song et  al., 2002). coli, Staphylococcus aureus, and Bacillus  cereus by glycating it with Escherichia coli and S. aureus were activated and diluted to the ap- dextran and glucose. propriate concentration with 20 mM phosphate buffer (pH 6.0). The In this study, we select chitosan oligosaccharide (CO) to conju- 4.5  ml of the cell suspension was mixed with 0.5  ml of chitosan gate with nisin via Maillard reaction. CO is a natural cationic poly- oligosaccharide–nisin mixture (CON-M) and CON-C, respectively saccharide and one of the most abundant and renewable natural (The concentration were 0.001%, 0.002%, 0.004%, and 0.005%), resources (Peng et  al., 2013). Because of its unique characteristics and incubated at 37°C for 1 h. Then a 100 µl portion of each treat- of nontoxicity, biocompatibility, biodegradability, and broad anti- ment was surface-plated onto agar plate and incubated at 37°C for microbial spectrum, CO is widely used as food functional ingredient 24 h. Sample-free solution was used as a control. The antimicrobial (Rinaudo, 2006; Kong et al., 2010). Currently, CO has been applied properties of each treatments were compared according to the bac- to deliver drugs, enzymes, and prepare nano-composite particles terial survival rate, which calculated as follows: (Sanyakamdhorn et al., 2013). We then investigated the modulatory effect of chitosan oligosaccharide and nisin conjugates (CON-C) on The bacterial survival rate% ï ò intestinal microbiota. By transplanting faecal microbiota from adult The number of bacteria in each treatment = × 100% human into germ-free mice, we established a relatively stable human The number of bacteria in the control group gut micro-community in recipient mice model, the objective of the present study was to investigate the effects of CON-C on human faecal microbiota, in addition, the abundance of genes enriched in Animals and experimental design various metabolic pathways altered by CON-C in the humanized The anti-obesity effects of CON-C were evaluated according to the re- mouse gut microbiome were investigated. ported method with modifications (Mei et  al., 2017). Firstly, six volun- teers (three females and three males, 25–30 years old), who did not have any history of gastrointestinal disorders and had not been treated with Materials and Methods antibiotics for the previous 6 months, were recruited. Their freshly voided Materials faeces were used to colonize the young adult (6-week old) male mice. Mice Nisin and CO with the deacetylation degree of 90% (5  kDa) then were housed in separate cages within a gnotobiotic isolator under were obtained from Golden Shell (Hangzhou, China). Germ-free 12 h light-dark cycle and with the temperature and humidity controlled C57BL/6J mice were obtained from the Experimental Animal Centre to 22–24°C and 50% ± 10%, respectively. After 7 days with high-fat diet Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 171 (Research Diets D12492 60 kcal% Fat), the mice were then randomly a length less than 100 bp were subsequently filtered out. Finally, a gene divided into five groups with eight in each group: low fat diet group (LFD, catalog containing 255 320 nonredundant genes was constructed. Based Research Diets D12450B 10 kcal% Fat), high-fat diet group (HFD), high- on this reference gene set, we carried out taxonomical assignment and fat diet with nisin group (HFD-N), high-fat diet with CON-M group functional annotation using the NR (Non-Redundant), KEGG (Kyoto (HFD-CON-M), and high-fat diet with CON-C group (HFD-CON-C). Encyclopedia of Genes and Genomes), GO (Gene Ontology), and CAZy Nisin, CON-M, and CON-C were added to the high-fat diet at a final con- (Carbohydrates-Active enzymes) databases of the latest version. centration of nisin at 0.1% (w/w). Sample food and water consumption were measured on a per cage basis three times per week and the averages Taxonomical assignment and functional of food and water consumed were calculated weekly. The body mass of classification each animal was recorded soon after feeding with different diets for the en- The nucleotide sequences of predicted genes were translated into tire period since the start of breeding. Faecal samples were collected from protein sequences using the NCBI Genetic Codes 11. Basic local 0 (CON-C0), 2 (CON-C2), 4 (CON-C4), and 8 weeks (CON-C8) after alignment search tool (BLAST) was employed to conduct the taxo- they were divided into each group. All administrations were conducted for nomical assignment and functional classification of predicted genes eight consecutive weeks. −3 against the corresponding data base with E value ≤1  × 10 . All genes were searched against IMG (v3.4) with N-BLAST using Histopathological evaluation −5 default parameters except that the E value was set to 1  × 10 . Mouse epididymal white adipose tissue (eWAT) and liver were The taxonomical association of a gene was decided by the lowest fixed in 4% neutral buffered formalin and embedded in paraffin. common ancestor of all its taxonomical annotation results. Anti-F4/80 primary antibody (Abcam, British) was used to perform the immunohistochemical staining of paraffin sections (Liu et al., 2017). The representative images of the possible histopathological changes were de- Statistical analysis tected under a high-resolution microscope with photographic facility. Data were analysed by SPSS and expressed as mean ± standard de- viation (SD). Significance was determined at P  <  0.05 by ANOVA Enumeration of bacteria by fluorescent in situ followed by Duncan’s multiple-comparison tests. hybridization The bacterial cells used for hybridization were prepared according to Results and Discussion Zhang et al. (2013). Faecal slurries of mice were collected at different time points and were mixed with autoclaved phosphate-buffered sa- Characterization of CON-C line to yield 10% (w/v) suspensions. The samples were inoculated FT-IR spectra was a useful tool to analysis the derivatives formed with 150 μl of faecal slurry (10%, w/v) with a manual homogenizer by Maillard reaction. Figure 1 showed FTIR spectra of CO, nisin, at 37°C in an anaerobic incubator (10% H , 10% CO , and 80% 2 2 and CON-C. For the nisin, the characteristic absorption bands N ). The 100 µl culture samples were then added to 300 μl filtered −1 −1 around 3288 cm and 2960 cm attributed to axial O–H and N–H paraformaldehyde solution (4%, w/v), and fixed overnight at 4°C. −1 stretching. The peak at 1652 cm which can be attributed to amide Hybridization were performed according to the reported methods −1 − band and the peak at 1449  cm evidenced the presence of COO (Sánchez-Patán et al., 2012). The probes used were Bif164, Lab158, symmetric stretching vibrations (Krivorotova et  al., 2016). For the Bac303, and His150. The bacterial cells were counted using an epi- −1 CO, the characteristic absorption bands around 3444 and 2991 cm fluorescence microscope. At least six random fields were counted on was attributed to –NH, –OH, and –CH– stretching vibration. The each slide, and the bacterial numbers were expressed as log cells −1 characteristic peaks at around 1631, 1526, and 1394  cm were per milliliter ± standard deviation (SD). assigned to amide I, amine II, and amide III absorption bands of Construction of a gut metagenome reference Metagenomic sequencing was conducted using HiSeq4000 and PE150 strategy. DNA from different samples was extracted using the E.Z.N.A. ®Stool DNA Kit (D4015, Omega, Inc.) according to manufacturer’s instructions. The total DNA was eluted in 50 μl of elution buffer and stored at −80°C until measurement in the PCR by LC-Bio Technology Co., Ltd (Hang Zhou, Zhejiang Province, China), and the isolation was confirmed by 1.2% agarose gel electrophoresis. Sequencing libraries were generated using NEB Next Ultra DNA Library Prep Kit for Illumina (NEB) following manufacturer’s recommendations and index codes were added. The library quality was assessed on the Qubit@ 2.0 Fluorometer (Life Technologies, CA) and Agilent Bioanalyzer 2100 system. At last, the library was sequenced on an Illumina MiSeq plat- form and 300 bp paired-end reads were generated. All open reading frames (ORFs) predicted from different samples were merged and aligned to each other using BLAT (Bankevich et al., 2012). Gene pairs with greater than 95% identity (no gap allowed) and aligned reads covering over 90% of the shorter reads were grouped together. The longest ORF in each group was used to represent the group, and the other Figure 1. FT-IR spectra of CO, nisin, and CON-C. ORFs of the group were regarded as redundant sequences. ORFs with Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 172 Zheng et al., 2019, Vol. 3, No. 3 CO, respectively (Umemura and Kawai, 2007). The FTIR spectra of CON-C exhibited significant differences from that of nisin and −1 CO after Maillard reaction. The absorption peaks of 3385 cm re- lated to stretching vibrations of N–H widened and the peak of amide −1 band was slightly shifted to lower wave number 1625 cm , which indicated the formation of the hydrogen bonding between nisin and CO. These results were also consistent with the previous study (Zhu et al., 2015). The packing structures of nisin, CO, and CON-C were deter- mined by XRD technique (Figure 2). The nisin showed a remarkable peak at 31.5°, which corresponded to the characteristic diffrac- tion pattern of sodium chloride (NaCl), a component of Nisaplin (Meira et  al., 2015). For CO, the diffraction peaks at 2θ  =  12.2° and 2θ = 23.5° were observed, which corresponded to the diffrac- tion peaks of (020) and (200) crystal plane (Luo et al., 2013). After Maillard reaction, the peak of CON-C at 12.2° shift to low degree Figure 3. Antimicrobial properties of CON-M and CON-C. and the peak at 23.5° disappeared. Besides all the characteristic crystalline peaks were broader and the crystallinity significantly de- Influence of CON-C on liver histopathology of HFD- creased, indicating that Maillard reaction can reduce the crystallinity induced obesity mice model of the reactants (Li et al., 2013). Obesity is characterized by chronic low-degree inflammation. A pre- vious report indicated that adipose tissue macrophage accumulation The antimicrobial properties of CON-C is directly proportional to measures of adiposity both in mice and As shown in Figure 3, the inhibition of CON-C on E.  coli and humans(Weisberg et  al., 2003). As the eWAT and liver staining re- S.  aureus was significantly higher than that of CON-M: the half- sults (Figure 5) shows, HFD-fed mice showed significantly greater lethal doses of CON-C on E. coli and S. aureus were 45% and 80% microphage accumulation compared with LFD-fed mice, which of the latter. It illustrate that Maillard reaction could efficiently im- is consistent with previous reports(Kanda et  al., 2006). While the prove the antimicrobial properties of both CO and nisin. Similar microphage accumulation in HFD-fed mice was alleviated when to our results, chitosan conjugated with glucose or xylose showed supplemented with CON-C. greater antimicrobial properties (Kanatt et  al., 2008; Zhu et  al., 2013). Influence of CON-C on bacterial populations In general terms, intestinal bacteria could be divided into species Influence of CON-C on body and organ mass of including potentially beneficial or harmful towards the host. Beneficial mice model bacteria mainly include Lactobacillus and Bifidobacterium, which Compared with the other HFD fed mice, the CON-C treated one play important roles in nutrition and prevention of disease, while showed significantly slower body weight gain rate and fewer liver the harmful intestinal bacteria, such as Clostridium, Veillonella, weight gain (Figure 4b and 4c). Considering there were no significant Staphylococcus, occasionally Enterococcus and Escherichia, may differences between all FHD fed mice in water intake and food con- produce potentially harmful substances to the host (Hooper and sumptions (Figure 4a and 4b), which indicating that nisin, CON-M, Gordon, 2001). In this study, we selected Bifidobacterium and and CON-C did not affect the food intakes behaviour of the mice, Lactobacillus/Enterococcus as the representative species of potential the anti-obesity effects of CON-C can hence be confirmed. benefits, and Bacteroides–Prevotella and Clostridium histolyticum as the representative species of potential harm. In consistent with others’ reports (Cani et  al., 2008), the mice fed with LFD diets showed significantly higher amount (P  <  0.05) of Bifidobacterium and Lactobacillus/Enterococcus and lower amount of Bacteroides– Prevotella and C.  histolyticum (Table 1). Recent study indicated that changes in gut microbiota composition are related to the devel- opment of obesity and its associated metabolic disorders (Ridaura et  al., 2013), and obesity-induced gut dysbiosis may impairs intes- tinal integrity (Cani et  al., 2009). In our case, the development of obesity in HFD fed group could partially be explained by the change of bacterial populations caused by the HFD. Among the mice fed with HFD, the one suppled with CON-C had the highest amount of Bifidobacterium and Lactobacillus and lowest amount of Bacteroides–Prevotella and Clostridium histolyticum (Table 1). As our previous results shows, the CON-C had improved antimicrobial properties against E.  coli, and it is possible that the CON-C alleviated the development of obesity induced by HFD, by selectively suppress certain bacterial groups. However, the potential mechanisms of CON-C on the prevention of gut dysbiosis are com- Figure 2. XRD patterns of CO, nisin, and CON-C. plicated and need further clarified. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 173 Figure 4. Effect of nisin, CON-M, and CON-C on the water intake (A), food intake (B), liver weight (C), and body weight (D) of high-fat diet-induced mice. Different letters indicate significant differences (P < 0.05) among different groups. Figure 5. Representative F4/80 immunostaining image of eWAT between LFD (i), HFD (ii), and HFD–CON-C (iii) groups, and liver between LFD (I), HFD (II), and HFD–CON-C (III) groups. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 174 Zheng et al., 2019, Vol. 3, No. 3 −1 Table 1 Time-dependent changes observed in the numbers (log cell ml ) of Bifidobacterium, Lactobacillus/Enterococcus spp., Bacteroides–Prevotella, and Clostridium histolyticum group in the gut of HFA mice model.* Probe type Group Time (week) 1 2 4 8 Bif 164 LFD 7.83 ± 0.02 a, A 8.01 ± 0.02 c, B 8.16 ± 0.01 d, C 8.21 ± 0.02 c, D HFD 7.82 ± 0.01 a, A 7.95 ± 0.02 a, B 8.07 ± 0.02 a, C 8.10 ± 0.01 a, D HFD-N 7.82 ± 0.02 a, A 7.96 ± 0.02 a, B 8.08 ± 0.02 a, C 8.11 ± 0.02 b, D HFD–CON-M 7.83 ± 0.02 a, A 7.95 ± 0.01 a, B 8.08 ± 0.01 a, C 8.10 ± 0.03 c, D HFD–CON-C 7.83 ± 0.01 a, A 7.99 ± 0.02 b, B 8.11 ± 0.01 b, C 8.16 ± 0.02 b, D Lab 158 LFD 7.71 ± 0.01 a, A 7.82 ± 0.02 b, B 8.02 ± 0.02 c, C 8.11 ± 0.01 c, D HFD 7.70 ± 0.02 a, A 7.74 ± 0.01 a, B 7.88 ± 0.01 a, C 8.01 ± 0.01 a, D HFD-N 7.71 ± 0.01 a, A 7.75 ± 0.02 a, B 7.86 ± 0.02 a, C 8.03 ± 0.02 a, D HFD–CON-M 7.70 ± 0.02 a, A 7.75 ± 0.02 a, B 7.89 ± 0.02 a, C 8.03 ± 0.02 a, D HFD–CON-C 7.71 ± 0.02 a, A 7.76 ± 0.02 a, B 7.95 ± 0.03 b, C 8.07 ± 0.02 b, D Bac 303 LFD 7.20 ± 0.01 a, A 7.21 ± 0.02 a, A 7.20 ± 0.02 a, A 7.21 ± 0.02 a, A HFD 7.20 ± 0.01 a, A 7.23 ± 0.03 b, B 7.28 ± 0.02 b, C 7.30 ± 0.02 b, D HFD-N 7.19 ± 0.02 a, A 7.22 ± 0.03 b, B 7.27 ± 0.02 b, C 7.29 ± 0.03 b, D HFD–CON-M 7.20 ± 0.02 a, A 7.23 ± 0.02 b, B 7.28 ± 0.01 b, C 7.30 ± 0.03 b, D HFD–CON-C 7.20 ± 0.02 a, A 7.21 ± 0.02 a, A 7.21 ± 0.01 a, A 7.21 ± 0.02 a, A His 150 LFD 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A HFD 7.01 ± 0.01 a, A 7.04 ± 0.01 b, B 7.07 ± 0.02 b, C 7.11 ± 0.02 b, D HFD-N 7.02 ± 0.02 a, A 7.03 ± 0.02 b, A 7.06 ± 0.03 b, B 7.10 ± 0.02 b, C HFD–CON-M 7.02 ± 0.02 a, A 7.04 ± 0.02 b, A 7.06 ± 0.02 b, B 7.11 ± 0.02 b, C HFD–CON-C 7.02 ± 0.02 a, A 7.02 ± 0.02 a, A 7.03 ± 0.03 a, A 7.03 ± 0.02 a, A *One-way ANOVA and Tukey tests were used to determine significant differences for total bacterial population. Different lowercases indicate significant differ - ences (P < 0.05) for total bacterial (i.e. within column) among different groups. Different capital letters indicate significant differences (P < 0.05) for total bacterial (i.e. within line) among the different time points. Figure 6. Imputed metagenomic differences between CON-C0 and CON-C8. The relative abundance of metabolic pathways encoded in each imputed sample metagenome was analysed using STAMP. Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 CON-C on intestinal microbiota of HFA mice, 2019, Vol. 3, No. 3 175 Figure 7. KEGG analysis of differentially expressed genes between CON-C0 and CON-C8. Figure 8. GO analysis of differentially expressed genes between CON-C0 and CON-C8. Influence of CON-C on the humanized mice gut two-component system, and ATP-binding cassette (ABC) trans- porters (Figure 7), and ABC transporters included those predicted to microbiome be involved in sugar, amino acid, and cofactor import. The imputed relative abundances of KEGG pathways in each re- The database of GO provides three types of systematic defin- spective sample were used to predict changes in metabolic func- itions for describing the function of gene products. The structures tion within the microbiomes of different CON-C intervention time of GO functions include molecular function, biological process, (Figure  6). The KEGG pathway demonstrated lipid metabolism, and cellar components, and we selected 10 of the largest GO drug resistance, metabolism of other amino acids, metabolism of terms in each function. GO analysis of CON-C0 and CON-C8 terpenoids and polyketides, transcription and biosynthesis of other showed that the most differentially expressed genes were regu- secondary metabolites accounted for the highest proportion. In the lation of transcription, DNA-templated, transport, phosphorelay meanwhile, the greatest statistical difference between CON-C0 and signal transduction system, metabolic process, and translation CON-C8 were metabolism of terpenoids and polyketides, transcrip- in biological process; cytosol, cellular components, cytoplasm, tion, and biosynthesis of other secondary metabolites. The CON-C plasma membrane, and membrane in cellular components; ATP associated faecal microbiome for 8 weeks was enriched for a binding, transcription factor activity, sequence-specific DNA number of KEGG pathways involved in biosynthesis of amino acids, Downloaded from https://academic.oup.com/fqs/article-abstract/3/3/169/5566359 by DeepDyve user on 04 December 2019 176 Zheng et al., 2019, Vol. 3, No. 3 binding, protein binding, catalytic activity, and DNA binding in Conclusions molecular functions (Figure 8). In the present study, conjugates based on nisin and CO were pre- CAZy is a special database dedicated to the analysing of the pared using the Maillard reaction. The prepared CON-C showed genomic, structural, and biochemical information of carbohydrate significant protective effect against obesity induced by HFD. By active enzymes, and it covers six major functional categories: glyco- fermentation in vitro with faecal microbiota of HFD-induced side hydrolases (GHs), glycosyltransferase (GTs), polysaccharide obesity mice, it was found that CON-C significantly promote lyases (PLs), carbohydrate esterases (CEs), assisted redox (AAs), the growth of Bifidobacterium and Lactobacillus- Enterococcus and carbohydrate-binding modules (CBMs), which can be further spp., while inhibiting Bacteroides–Prevotella and C.  histolyticum divided into functional subclasses. To investigate if the carbohy- groups. In addition, KEGG and GO pathways showed the most drate utilization of mice gut microbiota increased as a response to significantly enriched differentially expressed genes after CON-C GTP intervention in high-fat diet-induced obesity, we used CAZy to intervention. It suggested CON-C intervention may benefit the sta- search for the key enzyme involved in CAZy level 1.  As the result bility of certain gut microbiota, and affect corresponding meta- showed, GHs, CEs, and PLs were dramatically enriched after GTP bolic pathways, making the contribution to the improvement of intervention, while the abundance of GTs, CBMs, and AAs were less human health. affected, which suggested that the increased capacity for carbohy- drate utilization characterizes high-fat diet-induced changes in the gut microbiota affected by CON-C. Funding The next-generation sequencing platforms provide the opportunity This work was sponsored by Key Research and Development Project of to explore the taxonomic, protein-coding gene, or expression diver- Zhejiang Province (2017C02039). sity nowadays, by applying more comprehensive and less biased meas- urements to the complicated relationship among diet, microbiota, and host, and they have provided a great deal of new information on the Conflict of Interest diversity and composition of human gut microbiota (Zoetendal and The authors declared no conflict of interest. Rajilic-Stojanovic, 2008). With regard to the Maillard reaction prod- ucts (CNMs), it has been reported that the CNMs destabilize the outer References membrane and inhibit the growth of bacterial cells, due to their ex- cellent surfactant properties (Nakamura et  al., 1991).The conjugates Bäckhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A., Gordon, J. I. 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