Wnxiu Co, Fng Liu, Robert W.Li, Yoxin Chin, Yuming Wng,e,Chnghu Xue,e, Qingjun Tng,*

a College of Food Science and Engineering, Ocean University of China, Qingdao 266003, China

b Key Laboratory of Marine Drugs, Ministry of Education, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China

c United States Department of Agriculture, Agriculture Research Service (USDA-ARS), Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA

d Hainan Tropical Ocean University, Sanya 572022, China

e Laboratory for Marine Drugs and Bioproducts, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266003, China

Keywords:

Docosahexaenoic acid

Diet-induced obesity

Insulin resistance

Peptide YY

Gut microbiome

A B S T R A C T

It is unclear how docosahexaenoic acid (DHA) improves insulin resistance via modulating gut microbiome in obese individuals.We used diet-induced obesity (DIO) mice as a model to study the effects of DHA-rich fish oil (DHA-FO) on host metabolic disorders and colonic microbiome.DHA-FO reduced fat deposition,regulated lipid profiles and alleviated insulin resistance in DIO mice.Probably because DHA-FO prevented the permeation of lipopolysaccharide across intestinal epithelial barrier, and promoted peptide YY (PYY)secretion via the mediation of short chain fatty acids receptor (FFAR2) in colon.Furthermore, DHA-FO might regulate PYY expression by reversing microbial dysbiosis, including increasing the abundance of Akkermansia muciniphila and Lactobacillus, and suppressing the growth of Helicobacter.DHA-FO also altered gut microbial function (e.g.“l(fā)inoleic acid metabolism”) associated with PYY expression (r > 0.80, P < 0.05).Herein, DHA-FO enhanced insulin action on glucose metabolism by altering gut microbiome and facilitating colonic PYY expression in DIO mice.

1.Introduction

Chronic consumption of a diet high in sucrose and fat is an important contributing factor for obesity [1].Th e ectopic lipid deposition is always accompanied by insulin resistance, which is characterized by an increase in hepatic glucose output and a reduction in glucose uptake in peripheral tissues (e.g.liver and muscle) [2].The modulation of hepatic glucose output depends on the coordination of gluconeogenesis and glycogen synthesis.The major factor contributing to the impaired glucose uptake is the downregulation of glucose transporter 4 (GLUT4) in white adipose tissue (WAT) and muscle [3].Moreover, systemic inflammation is implicated in the induction of insulin resistance [4].Recently, the gut microbiome has also been proposed to be involved in regulating insulin responses [5].For example, several gut microbial metabolites, such as branchedchain amino acids ( BCAAs) and lipopolysaccharide (LPS), can trigger diet-induced insulin resistance [6,7].In particular, obesity is associated with the leakage of LPS across intestinal epithelial barrier,which is a potent inducer of systemic inflammation [8].

On the contrary, short chain fatty acids (SCFAs), a series of bacterial-derived metabolites, can not only be an energetic substrate but also function as signaling molecules [9].Emerging evidence indicates that SCFAs stimulate the secretion of gut hormones from enteroendocrine cells (e.g., L cells).L cells mainly secret glucagon like peptide-1 (GLP-1) and peptide YY (PYY), which can reduce food intake and affect energy metabolism [10].Increased circulating GLP-1 and PYY levels are also associated with the improvement of glucose homeostasis after metabolic surgery [11].While relatively few studies have investigated the changes of GLP-1 and PYY after nutrition interventions.For instance, inulin and oligofructose modulate the production of incretins, and improve the portal serum levels of GLP-1 and PYY in rats [12,13].In a word, the gastrointestinal system,especially gut microbiome, can be a promising target for potentiating diet-induced insulin action [14].

Dietary lipids can alter the composition of gut microbiome in obese individuals.The intervention of flaxseed oil rich inn-3 polyunsaturated fatty acids (PUFAs) can reduce the ratio of Firmicutes/Bacteroidetes in type 2 diabetes mellitus rats [15].In addition, common beneficial bacteria, such asLactobacillus,Akkermansia muciniphila, andBifidobacteriumare increased by the administration of fish oil, and the difference of gut bacteria can contribute to obesity phenotypic alteration in fish-oil-fed mice compared with lard-fed mice [16].Probably because lard is rich in saturated fatty acids (SFA), while fish oil is rich inn-3 PUFAs, namely docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA).Additionally, fish oil extracted fromCoregonus peledcan facilitate the growth ofBifidobacteriumandAdlercreutzia, thereby improving recurrent obese phenotype in mice [17].In brief, DHA may ameliorate host metabolic disorders in obese individuals through reprograming gut microbiome.However, most of the existing studies have revealed that DHA attenuates diet-induced insulin resistance by preventing chronic inflammation in peripheral tissue [18].For example,recent research suggests that DHA can improve insulin signaling in high-fat diet-fed mice with a focus on the gut-adipose axis [19].Anyway, it remains to be further investigated the mechanisms underlying the beneficial effects of DHA on insulin sensitivity.

This work aimed to reveal whether the fish oil enriched in DHA(> 70%) could prevent diet-induced insulin resistanceviamodulating gut microbiome.We compared primary phenotypical and biochemical indicators between DHA-rich fish oil (DHA-FO) and its industrial raw material, DHA ethyl ester (DHA-EE), in diet-induced obesity (DIO)mice.Then 16S rRNA analysis was conducted to explore the role of gut microbiome played in these beneficial functions.

2.Materials and methods

2.1 Primary materials

The purified DHA-FO and DHA-EE were purchased from Sinomega Biotech Engineering Co., Ltd.(Zhoushan, China).The fatty acid composition of DHA-FO and DHA-EE was given in Table S1.

2.2 Animal care

All the animal studies were approved by the Committee on the Ethics of Animal Experiments of Ocean University of China (approval no.SPXY2015012).The experimental procedures were conformed to guidelines published by the National Institutes of Health (Guide for the Care and Use of Laboratory Animals, 8th edition).Ten-week-old male C57BL/6J mice were purchased from Vital River Laboratory Animal Technology Co., Ltd.(Beijing, China).Mice were housed under standard 12/12 h light/dark cycles at (24 ± 2) °C and fed with a refined diet and waterad libitum.

After the one-week adaptation, the mice were randomly divided into 4 groups (n= 10), namely, Control group, Model group, DHAFO group, and DHA-EE group.As illustrated in Fig.S1A, Control group was fed with a low-sugar low-fat diet (LSLF diet), and Model,DHA-FO, and DHA-EE groups were fed with a high-sugar highfat diet (HSHF diet) for 8 weeks.The composition of LSLF diet and HSHF diet were demonstrated in Fig.S1B.Meanwhile, DHAFO and DHA-EE were respectively given by gavage (1 000 mg/kg body weight, calculated by the dose of DHA), once a day at around 4: 00 p.m.Mice in Control and Model groups were treated with saline during the same period.Body weight and food intake were recorded once every two days.

2.3 Oral glucose tolerance test (OGTT)

OGTT was performed after mice were maintained for 7 weeks.Mice were deprived of food with access to water for 12 h.Then each mouse was gavaged with glucose at a dose of 2 g/kg body weight.Blood samples were then collected from tail vein at time 0, 30, 60, 90,and 120 min.After sampling, all the blood samples were coagulated at room temperature for 30 min and then stored in an ice box.The serum was then separatedviacentrifuging at 7 500 r/min for 15 min.According to the manufacturer’s protocol, the serum levels of glucose were detected with a commercial kit (Biosino Bio-Tech., Beijing, China).

2.4 Sample collection

At the end of the experimental period, all the mice were fasted overnight.Then mice were anesthetized with diethyl ether and killed by cervical dislocation.Blood samples were collected and processed to separate serum as mentioned previously.The liver, WAT(epididymal fat, perirenal fat, subcutaneous fat), cecum, and colon were removed and weighed.The contents in cecum and colon were collected into sterile centrifuge tubes, respectively.Tissue samples were snap frozen in liquid nitrogen.All samples were stored at?80 °C until analysis.

2.5 Histology

Freshly isolated livers (about 20 mg) and epididymal adipose tissues (about 20 mg) were fixed in 4% formaldehyde for one week at room temperature.The tissues were processed in absolute ethyl alcohol for 24 h and embedded in paraffin wax.All the tissues were cut into 5 mm thick slices and then stained with hematoxylin and eosin (H&E).After the staining, all the slices were scanned with a Nikon Eclipse Ti2 microscope (Nikon Instruments, New York, USA).Adipocyte size was calculated with the Adiposoft plugin in ImageJ version 1.53 software.

2.6 Biochemical analyses

The circulating levels of glucose were analyzed as mentioned in section 2.3.The insulin and LPS levels were determined using ELISA kits according to instructions of the manufacturer (Shanghai Elisa Biotech Co.Ltd., China).The concentration of PYY in serum was also measured with an ELISA kit (Gu Yan Biotech Co.Ltd.,Shanghai, China).Similarly, the circulating GLP-1 levels was detected with a commercial kit (Kerunda Biology Co.Ltd, Shenzhen,China).Homeostasis model assessment of insulin resistance (HOMAIR) was calculated according to equation (Fasting glucose level ×Fasting insulin level/22.5) for each mouse.The content of glycogen was detected by a commercial kit purchased from Nanjing Jiancheng Bioengineering Institute (Nanjing, China).

2.7 Total lipid extraction

Total lipids in liver and WAT were extracted using a previously published method [20].Briefly, 0.1 g of tissue was homogenized with 10 mL of chloroform-methanol (2:1,V/V).The homogenate was incubated at 37 °C for 45 min.Then the hepatic lipid sample (1.5 mL)was dried by vacuum concentration.The dry matter was dissolved in 50 μL triton:isopropanol (1 g:9 mL).The contents of triglyceride (TG)and total cholesterol (TC) in liver were detected with commercial kits(Biosino Bio-Tech., Beijing, China).

2.8 Long-chain fatty acids analysis

The fatty acid compositions of liver and WAT tissue samples were determined by GC as a previously published method [21].About 10 mg of total lipid sample was added into a tube containing 1 mL of 10% H2SO4in methanol, and then heated at 70 °C for 45 min.After cooling, 1 mL ofn-hexane was added and fully mixed,and the supernatant was collected after standing for 30 min.The supernatant was evaporated to dryness under vacuum.Then the sample was dissolved in 10 μL ofn-hexane again, and 2 μL of the solution was injected into the gas chromatography (GC) system(Agilent 7890 series).An HPINNOW-AX capillary column(30 m × 0.32 mm × 0.25 μm) was used for the detection.

2.9 SCFAs detection

About 200 mg of cecal content was dissolved in 1 200 μL of ultrapure water and fully homogenized with a vortex.Next, 50 μL of sulfuric acid (50%,V/V) was added to prepare acidified sample.And 2-ethyl butyrate acid solution (1%,V/V) were used as an internal standard.Then the mixture was centrifuged at 5 000gfor 10 min.A volume of 1 μL of the supernatant was injected into a GC system(Agilent 6890 series) with a flame ionization detector (FID).And a DB-FFAP column (30 m × 0.53 mm × 0.25 μm, Agilent) was used according to methods established before [22].

2.10 RNA isolation and quantitative PCR (qPCR)

Total RNA was isolated using Trizol (Invitrogen, Carlsbad,CA) as previously performed [23].Total RNA (2 ng) was reverse transcribed into cDNA using 5X All-In-One RT MasterMix (ABM,Vancouver, Canada) according to the manufacturer’s instruction.The primer sequences were designed as previously described [24-28].Then all the primers were prepared by Shanghai Sangon Gene Company (Qingdao,China).The sequences of primers were provided in Table S2.

2.11 16S rRNA gene analysis

Total DNA from colonic content was extracted using a QiaAmp DNA Stool Mini Kit (Qiagen, cat.no.51604), and DNA integrity was analyzed with BioAnalyzer 2000 (Agilent, Palo Alto, CA).The V3-V4 region of the 16S rRNA gene was chosen for amplification.In brief, a total of 20 ng of DNA was amplified using primers 338F and 806R.Then purified amplicons were pooled and sequenced on an Illumina MiSeq sequencer.

The sequence data were analyzed with Quantitative Insights Into Microbial Ecology 2 program (QIIME2 ver.2019.4 45).The feature table generated in QIIME 2 was used for the calculation ofβ-diversity[Non-metric multidimensional scaling (NMDS)]with vegan package in R (Version 3.6.1).Besides, the composition data analysis (Wilcoxon test based on centred log-ratio) and LASSO regularized regression were conducted on Calypso (cgenome.net:8080/calypso-8.84/faces/univariate.jsp).Then balance analysis was completed with selbal package in R (Version 3.6.1).Network analysis was conducted on Molecular Ecological Network Analysis Pipeline (MENA) (http://ieg4.rccc.ou.edu/MENA/).

Furthermore, Tax4Fun2 was used to predict functional information based on the above-mentioned feature table.Statistical analysis of microbial function data was conducted using STAMP software.Mantel test and Pearson correlation analysis was performed with R package vegan and corrplot, respectively.

2.12 Specific fecal bacteria analysis

Total DNA mentioned in section 2.11 was used for the detection of specific bacteria, namely,A.muciniphila, Helicobacter,andLactobacillus.These taxa were quantified by qPCR as described in section 2.10.The primers were synthesized by Shanghai Sangon Gene Company (Qingdao, China) according to previously published researches[29-31].The sequences of primers were provided in Table S2.

2.13 Statistical analyses

The data are presented as mean ± SEM.Unless otherwise stated,differences between two groups were evaluated byt-test using SPSS 24.0.Significance was accepted at#P< 0.05,##P< 0.01 vs.Control group;*P< 0.05,**P< 0.01 vs.Model group.

3.Results

3.1 DHA-FO prevented insulin resistance in DIO mice

The effects of DHA-FO and DHA-EE were compared on the phenotypical changes in DIO mice.Mice gained significantly more weight when fed the HSHF diet than those fed the LSLF diet(P< 0.05, Fig.S2A).However, all the mice in both DHA-FO and DHA-EE groups did not elicit significant weight loss compared to mice in Model group (Fig.S2A).DHA-FO supplementation caused a considerable decrease in food intake and energy intake of HSHF dietfed mice (P< 0.05, Figs.S2B, S2C).

OGTT was performed to measure insulin sensitivity in DIO mice.As shown in Fig.1A, mice on the HSHF diet exhibited prominent elevated levels of blood glucose compared to mice on the LSLF diet during the OGTT (P< 0.05), whereas DHA-FO administration was able to partially restore the levels comparable to control mice(P< 0.05).When compared with Model group, fasting glucose levels were significantly reduced in DHA-FO group (Fig.1B).In addition,fasting insulin levels were about 5.68% lower in DHA-FO fed mice compared with mice fed a HSHF diet, although the reductions were not statistically significant (Fig.1C).Nevertheless, according to HOMA-IR, DHA-FO might significantly alleviate insulin resistance induced by HSHF diet feeding (Fig.1D).

Fig.1 DHA-FO alleviated insulin resistance in DIO mice (n = 10).(A) Oral glucose tolerance curve and area under the curve.(B) Fasting blood glucose levels.(C)Fasting insulin levels.(D) HOMA-IR.(E) Relative gene expression of PEPCK and G6Pase in liver.(F) Liver glycogen.The data are presented as mean ± SEM.Significance was accepted at #P < 0.05, ##P < 0.01 vs.Control group; *P < 0.05, **P < 0.01 vs.Model group.

Furthermore, the mRNA expression of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6-phosphatase (G6Pase), two key kinases involved in hepatic gluconeogenesis, was decreased in DHA-FO group when compared to Model group (P< 0.05, Fig.1E).Meanwhile, HSHF diet-fed mice showed lower liver glycogen levels than that of LSLF diet-fed mice, whereas these changes were suppressed in DHA-FO fed mice (P< 0.05, Fig.1F).These results suggested that DHA-FO might reduce glucose production in liver.DHA-FO also upregulated the expression of insulin-responsive GLUT4 in WAT (P< 0.05, Fig.S3A), although DHA-FO exerted no significant effect on the expression of GLUT4 in muscle (Fig.S3B).From the above results, DHA-FO could to some extent ameliorate insulin resistance in DIO mice.

3.2 DHA-FO reduced lipid deposition in WAT and liver of DIO mice

HSHF diet-fed mice displayed increased lipid accumulation in WAT (Fig.S4A).But DHA-FO administration successfully reversed the effect of the HSHF diet in terms of epididymal fat and adipocyte size (P< 0.05, Figs.S4A-C).DHA-FO was more effective in decreasing body fat percentage than DHA-EE in DIO mice.Moreover, both DHA-FO and DHA-EE groups displayed a significant reduction in hepatic TG and TC contents (P< 0.05, Fig.S5A), which is in accord with the results of H&E staining (Fig.S5B).Collectively,DHA-FO could reduce body fat depot and repress ectopic lipid deposition in liver.

3.3 DHA-FO altered fatty acid composition in WAT and liver of DIO mice

The fatty acid composition of tissue lipid is associated with insulin resistance.In WAT, eight weeks of HSHF diet feeding increased the levels of 16:0, 18:0 and 20:4n-6 (P< 0.05, Table 1).The liver tissue showed higher levels of 18:0, 20:4n-6 and 23:0 in Model group than those in Control group (P< 0.05, Table 2).HSHF diet also enhanced the ratio ofn-6/n-3 PUFAs.For example, mice in Model group had an elevatedn-6/n-3 PUFAs ratio (Control = 2.36, Model = 4.23;P< 0.05,Table 2) in liver.

Table 1Effects of DHA-FO on fatty acid composition in epididymal fat of DIO mice(n = 10).

Table 2Effects of DHA-FO on fatty acid composition in liver of DIO mice (n = 10).

DHA-FO reversed the proportions of SFA (16:0 and 18:0) in both WAT and liver to control levels (P< 0.05, Table 1 and Table 2).Notably, both DHA-FO and DHA-EE significantly reducedn-6/n-3 PUFAs ratio in liver (Model = 4.23, DHA-FO = 0.71,DHA-EE = 0.97;P< 0.05, Table 2).Besides, arachidonic acid(AA, 20:4n-6) concentration were also decreased by both DHAFO and DHA-EE supplementation (P< 0.01, Table 1 and Table 2).Meanwhile, the mice in DHA-FO and DHA-EE groups had higher levels of DHA (22:6n-3) in WAT and liver than the mice in Model group (P< 0.01, Table 1 and Table 2).

3.4 DHA-FO protected intestinal epithelial barrier in DIO mice

The damage of intestinal epithelial barrier is critical for the development of metabolic disorders in DIO mice.DIO mice showed a significant decrease in the expression ofOccludinandZO-1compared to the control mice (P< 0.05, Fig.2A).DHA-FO supplementation induced increase in the expression of these tight junction proteins(P< 0.05, Fig.2A).Additionally, HSHF diet caused the elevation of circulating LPS level, which is one of the fundamental triggers of insulin resistance in DIO mice (P< 0.05, Fig.2B).DHA-FO effectively lowered the levels of LPS in serum and feces (P< 0.05,Figs.2B, 2C), while DHA-EE did not affect the production and permeation of LPS.Thus, DHA-FO could effectively alleviate increased intestinal permeability induced by HSHF diet feeding.

Fig.2 DHA-FO intestinal epithelial barrier in colon of DIO mice (n = 10).(A) Relative gene expression of Occludin and ZO-1 in colon.(B) The levels of LPS in serum.(C) The concentration of LPS in feces.The data are presented as mean ± SEM.Significance was accepted at #P < 0.05, ##P < 0.01 vs.Control group; *P < 0.05, **P < 0.01 vs.Model group.

3.5 DHA-FO promoted colonic PYY expression via the stimulation of SCFAs in DIO mice

SCFAs are conducive to protecting intestinal epithelial barrier.GC analysis showed that the intervention using DHA-FO and DHAEE improved the synthesis of primary SCFAs (Fig.3A).In particular,DHA-FO effectively promoted the production of acetate and propionate, while DHA-EE specifically increased the concentration of butyrate in cecum of DIO mice (P< 0.01, Fig.3A).HSHF diet feeding decreased the expression of free fatty acid receptor 2(FFAR2), whereas FFAR2 expression was increased three fold in mice fed DHA-FO (P< 0.05, Fig.3B).Although chronic intake of HSHF diet could cause a moderate reduction inGLP-1expression,no significant variation ofGLP-1secretion was observed (Figs.S6A,S6B).However, colonic expression and circulating levels of PYY were notably increased in DHA-FO group compared to Model group(Figs.3B, 3C).Pearson correlation analysis identified the negative association of colonic PYY expression and fasting glucose levels(r< –0.80,P< 0.05, Fig.S7A).Liver glycogen levels also showed a positive correlation with colonic PYY expression (r> 0.60,P< 0.05,Fig.S7B).Besides, circulating PYY levels were significantly correlated with GLUT4 expression in WAT (r> 0.80,P< 0.05, Fig.S7C).

Fig.3 DHA-FO improved PYY expression in DIO mice (n = 10).(A) The concentration of SCFAs in cecal content.(B) Relative gene expression of FFAR2 and PYY in colon.(C) Circulating levels of PYY.The data are presented as mean ± SEM.Significance was accepted at #P < 0.05, ##P < 0.01 vs.Control group; *P < 0.05,**P < 0.01 vs.Model group.

3.6 DHA-FO reprogramed gut microbial structure and composition in DIO mice

16S rRNA analysis revealed thatα-diversity (observed OTUs and Shannon) were not significantly different between all the groups (Fig.4A).NMDS analysis indicated great differences between Control group and Model group.Both DHA-FO and DHA-EE administration caused significant alterations in community structure of DIO mice, whereas these two groups could not be well separated (Fig.4B).

Fig.4 DHA-FO regulated gut microbiome in DIO mice (n = 10).(A) Observed OTUs and Shannon index.(B) NMDS analysis based on Aitchison distance.(C) Relative expression of Akkermansia muciniphila, Helicobacter and Lactobacillus.(D) Boxplot of the proposed balance scores to distinguish individuals from Model and DHA-FO groups.The data are presented as mean ± SEM.Significance was accepted at #P < 0.05, ##P < 0.01 vs.Control group;*P < 0.05, **P < 0.01 vs.Model group.

At the phylum level, the most dominant bacteria were Firmicutes and Bacteroidetes (Fig.S8A).The abundance of Firmicutes and Proteobacteria was higher in Model group than that in Control group,while the relative abundance of Bacteroidetes was reduced.However,none of these changes reached a statistical significance level, neither did the Firmicutes/Bacteroidetes (F/B) ratio (Fig.S8B).

At the genus level, HSHF diet-fed mice had a lower abundance ofClostridium,AkkermansiaandDoreathan LSLF diet-fed mice(Wilcoxon test:P< 0.05 and |fold change| > 2, Table 3).The relative abundance ofHelicobacter, AlistipesandStreptococcuswas decreased in DHA-FO group compared to Model group (Wilcoxon test:P<0.05 and |fold change| > 2, Table 3).Similarly, the relative abundance ofLactobacilluswas significantly increased in DHA-FO and DHAEE groups, especially in DHA-EE group (Table 3).Then qPCR analysis was performed to confirm the abundance ofA.muciniphila,Helicobacter,andLactobacillus(Fig.4C).Notably, DHA-FO could also increase the abundance ofA.muciniphilacompared with Model group (P< 0.05, Fig.4C).

Table 3Differentially abundant taxa between groups identified by Wilcoxon test (n = 10).

Then microbial features associated with obese status and DHA administration were investigated by Selbal analysis.Fig.S9A illustrates that 3 features, namely S24-7 (proposed to be renamed as Muribaculaceae) [32],Parabacteroides, andRuminococcus, could define the global balance between Control and Model groups.This balance had an area under the receiver operating characteristic curve(AUC) of 1 for HSHF diet feeding.Also, 2 features (Blautiaand an unclassified genus in Ruminococcaceae) were enough for describing the difference between Model and DHA-FO groups (AUC = 0.9,Fig.4D).Model group had a much lower balance than DHA-FO group, suggesting that the increase in the relative abundance of the unclassified genus in Ruminococcaceae by DHA-FO played a key role in adjusting obesity-related phenotype (Fig.4D).Similarly,a balance consisting ofBacteroidalesandLactobacillushad high predictive accuracy for DHA-EE treatment (AUC = 0.94, Fig.S9B).In brief, both DHA-FO and DHA-EE could alter the composition of gut microbiome in DIO mice.DHA-FO could promote the growth of several beneficial bacteria.

Since the microbial association also profoundly affects the interaction between host and gut microbiome, it is important to study the relationships between taxa within each group.In present study,this interplay network was constructed on MENA.The network was composed of different modules, and a module is a cluster of taxa that are closely related to each other.As shown in Fig.S10, the global network was clearly different between groups, suggesting that both diet-induced obesity and DHA intervention could obviously affect the microbial topological structure within group.

3.7 DHA-FO modulated gut microbiome related to PYY secretion and insulin resistance in DIO mice

The correlations between gut microbiome and several metabolic indicators were analyzed on Calypso.Notably, microbial features associated with colonic PYY expression were identified using LASSO regularized regression.Fig.5A illustrates a variety of taxa that have significant correlations with PYY expression.The results suggested that the genera (e.g.,Alistipes,Helicobacter, andLactobacillus)regulated by DHA-FO were closely related to the expression of PYY in colon (Fig.5A).Among these features, we also recognized 2 genera(Blautiaand unclassified Ruminococcaceae) that were included in the balance between Model and DHA-FO groups (Fig.5A).

Fig.5 Correlation analysis between the abundance of gut microbiome and insulin resistance-related indicators.(A) LASSO regularized regression investigated the correlation of microbial communities and PYY expression between Model and DHA-FO groups.(B) The association between network of gut microbiome and metabolic indexes in DHA-FO group.Each row and column corresponds to eigengene and module, respectively.Within heatmap, red color means positive correlation and green color means negative correlation between eigengene and module.The numbers in each plot represent the Pearson correlation coefficient (r)and significance (P) in parentheses.The modules (module 12 and 13) with fewer than two members were abandoned.

Moreover, mantel test was performed to evaluate the relevance between metabolic indexes and each module in the network within DHA-FO group.As illustrated in Fig.5B, there were 6 modules(module 1, 4, 6, 7, 8, and 9) closely related to these metabolic indexes.Both module 4 and module 8 showed strong negative correlations with liver glycogen levels.Module 6 was negatively associated with fasting glucose levels (r< -0.80,P< 0.05), while module 7 was positively related to GLUT4 expression in WAT (r> 0.60,P< 0.05).Particularly, module 8 and module 9 had strong correlations with PYY expression and circulating PYY levels, respectively (r> 0.60,P< 0.05).The members of these 2 modules were demonstrated in Table S3.Most of these bacteria belong to Clostridiales, and 2 taxa in module 9 can be assigned to Ruminococcaceae.

In a word, both DHA-FO and DHA-EE partly restored HSHF diet-induced gut microbial dysbiosis.However, only DHA-FO might alleviate insulin resistance through modulating gut microbiome and improving PYY secretion.

3.8 DHA-FO affected gut microbial function in DIO mice

Moreover, 16S rRNA data were submitted for Tax4Fun2 analysis to predict the metagenome functional profiling.HSHF diet feeding induced higher abundances of pathways related to lipid metabolism,such as “Fatty acid metabolism” (ko01212), “Arachidonic acid metabolism” (ko00590) and “Linoleic acid metabolism” (ko00591)(P< 0.05, Table S4).Notably, “Carbon fixation pathways in prokaryotes”(ko00720), a pathway belonging to energy metabolism, was also upregulated in Model group compared to Control group.(P< 0.05,Table S4).Additionally, “Carbon fixation pathways in prokaryotes”(ko00720), “Arachidonic acid metabolism” (ko00590) and “Linoleic acid metabolism” (ko00591) were significantly downregulated by oral administration of DHA-FO in DIO mice (P< 0.05, Fig.6A).

Fig.6 TG-DHA regulated gut microbial function in DIO mice (n = 10).(A) Significantly different KEGG pathways between Model and TG-DHA groups(P< 0.05).(B) Pearson correlation analysis between metabolic indexes and significantly different KEGG pathways (|r| > 0.6,P < 0.05).ko04626: Plant-pathogen interaction, ko00591: Linoleic acid metabolism, ko00720: Carbon fixation pathways in prokaryotes, ko05230: Central carbon metabolism in cancer, ko00590:Arachidonic acid metabolism, ko02040: Flagellar assembly, ko04072: Phospholipase D signaling pathway.

Pearson correlation analysis was performed among a series of metabolic indicators and significantly different KEGG pathways.As shown in Fig.6B, the relative abundance of “Carbon fixation pathways in prokaryotes” (ko00720) was negatively correlated with the levels of LPS in serum (r= -0.96,P< 0.05).Moreover,“Linoleic acid metabolism” (ko00591) had strong correlations with HOMA-IR and colonic expression of PYY and FFAR2, respectively (r> 0.80,P< 0.05).These results indicated that gut microbial functions might be closely related to host insulin resistance.

4.Discussion

In this experiment, DHA-FO was proved to repress energy intake and prevent body fat gain in HSHF diet-fed mice.Dietary energy restriction is one of the most accepted strategies in the management of obesity and insulin resistance.A multitude of researches has discussed whethern-3 PUFA, especially EPA or DHA, can control food intake and ultimately reduce body lipid deposition [33].DHA-FO has been proven to restore fasting insulin levels and HOMA-IR in overweight and obese adults [34].Moreover, DHA-FO suppressed hepatic glucose production and promoted glucose disposal in WAT in the present work.Hepatic glucose production plays a crucial role in the maintenance of normal blood glucose level [3].In summary, DHAFO contributed to regulate glucose homeostasisviaimproving insulin resistance in sensitive tissues.However, the mechanism behind these functions has not yet been completely elucidated.

As expected, DHA-FO and DHA-EE supplementation significantly regulated fatty acid composition in WAT and liver.In this study, the obvious decrease in SFA and the ratio ofn-6/n-3 PUFAs was found in DHA-FO and DHA-EE groups.SFA have been shown to trigger inflammation and insulin resistance in adipose tissue [35].Highn-6/n-3 PUFAs ratio is also implicated in the development of chronic inflammation, becausen-3 PUFAs can compete withn-6 PUFAs for the enzymes that produce inflammatory eicosanoids [36].Additionally, AA (20:4n-6) participates in the induction of hepatic insulin resistance by promoting the proliferation of pro-inflammatory bacteria and enhancing systemic inflammation [37].These alterations in fatty acid profile might partly conduce to the improvement of glucose disposal in DHA-FO treated mice.

Chronic consumption of HSHF diet has been pointed to result in leaky intestinal epithelial barrier [38].Consequently, LPS can enter the systemic circulation and induce chronic inflammation that lead to insulin resistance [14].According to our results, circulating LPS levels were reduced by DHA-FO supplementation, suggesting that DHA-FO might be conducive to maintain intestinal epithelial barrier and gut microbial homeostasis, thus improving insulin sensitivity in peripheral tissues.

SCFAs have been proved to improve tight junction permeability and facilitate epithelial cell proliferation in colon [39].Our data suggested that intervention with DHA-FO enhanced the production of primary SCFAs, especially acetate and propionate.Acetate,propionate and butyrate are responsible for activating FFAR2 [40].Numerous studies demonstrated that FFAR2 is required for promoting the release of GLP-1 and PYY [41,42].In this experiment, DHA-FO specifically promoted PYY secretionviathe mediation of FFAR2.This may because that the release mechanism of GLP-1 is not exactly same with that of PYY.Unlike PYY, GLP-1 is not necessarily dependent on the activation of FFAR2 [43].Anyway, these results suggested the impact of DHA-FO on regulating gut microbiome in DIO mice.

Gut hormones are released in response to nutrients in gut lumen.Thus, their circulating levels are relatively low under fasted state.However, increasing studies have highlighted the intimate connection between fasting PYY levels and metabolic indicators[44,45].Possibly because that L cells predominantly locate in colon where only undigested food residue is concentrated.So gut microbial fermentation may play a dominant role in regulating the endocrine function of L cells.A pilot study has indicated that supplementation with fermentable dietary fiber extracted from oat and barley can reduce weight gain and enhance fasting levels of GLP-1 and PYY [46].

PYY not only reduces insulin release but also improves impaired glucose disposal [47].Although the exact mechanism has not been clarified.Correlation analysis revealed that PYY secretion was closely associated with glucose metabolism in this experiment.Similar to our results, fiber-enriched diets can prolong PYY secretion and decrease the circulating levels of glucose and insulin in healthy young adults [48].Altogether, DHA-FO might alleviate insulin resistance by favorably adjusting PYY secretion.

Normally, the bacteria in gut lumen participate in fiber digestion and produce SCFAs.It can be speculated that DHA-FO might favor the growth of potential probiotics, thereby promoting the proliferation of SCFAs-producing bacteria.Thus, 16S rRNA analysis was performed to explore the effects of DHA-FO and DHA-EE on gut microbiome.The results demonstrated that F/B ratio was not significantly changed between the experimental groups.Accumulating evidence has revealed a significant increase in F/B ratio in obese individuals [49,50],but this change is not confirmed in all studies [51,52].Particularly,F/B ratio of lean mice fed fish oil diet is not decreased compared to obese mice fed lard diet [16].Therefore, the increase of F/B ratio might not be unavoidable in obesity.

At the genus level, HSHF diet feeding caused the reduction in beneficial bacteria (e.g.A.muciniphila) and led to the susceptibility to pathogens infection (e.g.Helicobacter).A.muciniphilais widely reported to ameliorate metabolic syndromes and is also a known acetate producer [53].DHA-FO supplementation altered the expression ofA.muciniphilatowards those of Control group.DHA-FO also effectively inhibited the infection ofHelicobacter, a genus of Gram-negative.In previous research, obese individuals exhibit a higher prevalence ofHelicobacter pyloriinfection than that of lean controls [54].In addition,AlistipesandStreptococcuswere significantly decreased in DHA-FO treated mice.Both of these two bacteria have been reported to positively correlate with body fat content [55,56].Moreover,Lactobacillusferments fibers to pyruvate and lactate through the Embden-Meyerhoff-Parnas pathway [57].Then those products can be further transformed into acetic acid by other bacteria (e.g.A.muciniphila).The reduction ofLactobacillushas been found in DIO mice [58], as was the case in this study.Intriguingly, both two kinds of DHA, especially DHA-EE, could restore the proliferation ofLactobacillusin DIO mice.

Then selbal was used to further identify the microbial features in different groups.This procedure is developed for evaluating whether the balance of two taxonomic groups is related to the response variable of interest.The results turned out that the balance of unclassified Ruminococcaceae andBlautiacould be a microbial signature that can distinguish HSHF diet feeding and DHA-FO administration.Blautiais reported to have a lower relative abundance in high-fat diet-fed group than in low-fat diet-fed group [59].Both Ruminococcaceae andBlautiacontain members that are SCFAs-producing bacteria [60,61].The changes in gut microbial composition might partly explain the elevated release of PYY in mice supplemented with DHA-FO.

Furthermore, LASSO regularized regression analysis revealed that the above-mentioned bacteria (e.g.,LactobacillusandHelicobacter)were all closely related to PYY expression, indicating that these bacteria might collaboratively play roles in ameliorating insulin resistance.The microbial association also contribute to affect host response to exogenous intervention [62].In this experiment, different modules had strong correlations with host phenotype, especially PYY secretion and glucose disposal [63].In short, this study highlighted a beneficial role of DHA-FO in regulating PYY expression, which may be important to link gut microbiome and host metabolism.

The metagenome analysis revealed significant increases in several pathways associated with lipid metabolism and energy metabolism in response to HSHF diet feeding and DHA-FO administration.Interestingly,“Linoleic acid metabolism” seems to be involved in regulating PYY expression and improving insulin resistance in DHAFO group.As reported before, microbial metabolite (10-hydroxy-cis-12-octadecenoic acid) of linoleic acid can stimulate the secretion of gut hormones (GLP-1 and PYY) and attenuate diet-induced obesity [64].In a word, the interplay between gut microbiome and DHA-FO might contribute to the prevention of insulin resistance by targeting gut microbial function.

Recently, dietary intervention aimed at mitigating metabolic disorders have yielded promising results.Intermittent fasting, as a form of periodic caloric deprivation, can alleviate diet-induced obesity by shaping gut microbiome in mice [65].However, this intervention may not be easy to implement due to the prevalence of hyperphagia in obese individuals [66].Our findings suggested that DHA-FO supplementation has a potential to be used in combination with intermittent fasting.DHA-FO might prolong the secretion of PYY,thereby contributing to control appetite and improve insulin resistance in DIO mice during fasting period.

Moreover, many studies also report the role of postprandial PYY in the short-term appetite regulation [67,68].For example, a recent study investigates the effect of soluble fiber dextrin (SFD) on the postprandial release of gut hormones in healthy adults [69].In brief,an increase in PYY levels after the subjects consume a corn20 diet(40 g SFD derived from corn to provide 20 g fiber) was observed.Therefore, we plan to investigate whether DHA-FO can increase satiety after a meal in the future.

5.Conclusions

In conclusion, DHA-FO could ameliorate diet-induced insulin resistance partly through regulating gut microbiome (e.g.A.muciniphilaandLactobacillus) and promoting colonic PYY expression.DHA-FO stimulated PYY production in colon might play an important role in linking diet, gut microbiome, and host metabolism.This study provides a new mechanism underlying the function of DHA in assistant decreasing blood glucose levels in obese individuals.

Conflicts of Interest

The authors declare no conflict of interest.

Acknowledgements

This research was funded by National Key R&D Program of China (grant number 2018YFC0311201), and China Postdoctoral Science Foundation (No.2020M672147).

Appendix A.Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://doi.org/10.1016/j.fshw.2021.07.018.