Evening inulin treatment alleviate anxiety and depression via gut-brain axis: A crucial role for microbiota and amino acids metabolism

Evening inulin treatment alleviate anxiety and depression via gut-brain axis: A crucial role for microbiota and amino acids metabolism | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evening inulin treatment alleviate anxiety and depression via gut-brain axis: A crucial role for microbiota and amino acids metabolism Ping Chen, Fanyang Chen, Tao Hou, Xueqin Hu, Chenxing Xia, Jiaming Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4157149/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Increasing evidence has demonstrated that an imbalance in the microbiota-gut-brain axis exerts an essential effect on the pathophysiology of depressive and anxiety disorders. Our previous research revealed that the timing of inulin administration altered its influence on CUMS-induced anxiety and depression; however, it is still unclear if the gut-brain axis is primarily responsible for these effects. Results Serum metabolomics analysis showed that inulin treatment can alleviate the inflammatory response in CUMS-treated mice and that amino acid metabolic pathways were crucial for its anxiolytic and antidepressant effects. The time of administration seemed to modify the anxiolytic and antidepressant effects of inulin, and inulin intervention in the evening was more pronounced in improving amino acid metabolism and inhibiting the inflammatory response than that of morning inulin treatment. In addition, inulin treatment in the evening significantly reduced serum glucose and insulin levels. The main differential metabolites, including fenofibric acid, 4’-Hydroxyfenoprofen glucuronide and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione may play important roles for the anxiolytic and antidepressant ability of inulin. Fecal microbiota transplantation confirmed that inulin treatment alleviated CUMS-induced anxiety- and depression-like behaviors via gut-brain axis. Conclusions Our results suggest that inulin administration in the evening is more effective in alleviating the inflammatory response and improving amino acid metabolism. This study provides a new potential link between the microbiota-gut-brain axis and chrono-nutrition, which indicates that a more appropriate administration time results in a better intervention effect. Inulin chrono-nutrition microbiota CUMS FMT Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Background Chronic stress is a prevalent health issue in modern society that often leads to various mental disorders, particularly anxiety and depression [ 1 ]. In recent years, increasing evidence has demonstrated that imbalances in the microbiota-gut-brain axis contribute to the pathogenesis of anxiety and depression [ 2 , 3 ]. Certain probiotics and prebiotics have been linked to the alleviation of mood disorders by targeting the microbiota-gut-brain axis [ 4 , 5 ]. The administration time of drugs to reduce depression and anxiety has been shown to affect their therapeutic potential. The host ingesting rhythms govern intestinal microbiota, which exhibits daily variations in composition and function despite not being continuously exposed to sunlight [ 6 , 7 ]. Over the course of a 24-h period, certain microbial species and important compounds generated from microbes experience rhythmed oscillations [ 7 , 8 ]. These results suggested that the timing of consumption might influence how well prebiotics work; however, the impact of different administration times on intervention effectiveness has been overlooked in many studies. In our previous study, we found that the administration time modified the effect of inulin on chronic unpredictable mild stress (CUMS)-induced anxiety and depression [ 9 ]; however, it remains unclear if the gut-brain axis exerts a central role in this process. In this study, a CUMS-induced mouse model and fecal microbiota transplantation (FMT) combined with 16S rRNA sequencing were applied to investigate the influence of microbiota on the anxiolytic and antidepressant ability of inulin, and the results confirmed that the microbiota-gut-brain axis was critical. More importantly, administration time appeared to personalize the effects of inulin on anxiety- and depression-like behaviors. According to our findings, taking inulin in the evening has a more profound effect on alleviating the inflammatory response and improving amino acid metabolism. This study provides a new potential linking between the microbiota-gut-brain axis and chrono-nutrition, which indicates that a more appropriate administration time results in a better intervention effect. Results Inulin treatment alleviated CUMS-induced anxiety- and depression-like behaviors Figure S1 A provided the detail information about the design of the animal experiments. The weekly body weights of the mice were shown in Fig. 1 A. The CUMS treatment resulted in a drop of body weight ( p < 0.05), but this decrease could be restored in part by supplementing inulin in the morning and evening ( p < 0.05) (Fig. 1 B). Both morning and evening inulin supplementation markedly increased the preference of sucrose in CUMS mice ( p < 0.05), however the morning inulin intervention (AMIN) showed more promising results (Fig. 1 C). Mice subjected to CUMS were showed higher propensities to move into the surrounding area, travel shorter distances ( p < 0.05), spend less time at the center part ( p < 0.05), and rearing and explore less ( p < 0.05), as demonstrated in Fig. 1 D-H. Dietary inulin supplementation considerably improved all of these parameters in comparison to the CTRL mice. In addition, the CUMS-treated mice exhibited a noteworthy rise in the number of open arm entries and duration time following inulin administration ( p < 0.05) (Fig. 1 I-K). And inulin supplementation significantly reduced the time spent by mice in the light compartment compared with the CUMS group ( p < 0.05) (Fig. 1 L). Interestingly, only evening inulin administration (PMIN) increased the number of transitions between the light and dark boxes ( p < 0.05) (Fig. 1 M). These findings pointed out that depression- and anxiety-like behaviors could be lessened by inulin supplementation in the morning and evening. Inulin administered in the morning and evening exhibited different effects on inflammation in CUMS-treated mice Chronic stress was attributed positively to behavioral disorders in previous studies [ 10 , 11 ]. It has been shown to increase intestinal permeability and inflammation, damage the gut barrier, and make it easier for exogenous substances to enter the circulation. Therefore, we investigated the inflammatory responses in the gut, serum, and hippocampal tissues of mice. To further investigate the integrity of the intestinal barrier, immunohistochemical staining was employed to detect the expression of the tight junction protein ZO-1. As indicated in Fig. 2 A-B, ZO-1 protein reduced in the CUMS group but went up because of inulin treatment. Similarly, supplementation of inulin in the evening (PMIN) significantly suppressed the CUMS-induced increase in serum LPS levels (Fig. 2 C). Moreover, inulin supplementation significantly downregulated the levels of pro-inflammatory cytokines induced by CUMS, including TNF-α ( p < 0.05), IL-6 ( p < 0.05), and IL-1β ( p < 0.05) (Fig. 2 D-I). In addition, the PMIN group showed lower levels of inflammatory cytokines than the AMIN group. These results indicated that inulin supplementation can enhance tight junction protein expression and diminish inflammatory symptoms and that the effect of inulin intervention was better in the evening. Inulin treatment modulated the gut microbiota composition in CUMS-treated mice 16S rRNA sequencing analysis was carried out on bacteria isolated from the cecum of mice to investigate the implications of stress and inulin intervention on the microbiota of the gut. Neither chronic stress nor inulin intervention changed alpha diversity ( Figure S2 A-D ). Subsequent review of the beta diversity, the samples were generally divided by groups as determined by PCoA and NMDS analyses, implying that the gastrointestinal microbiotas of the various treatment groups differed considerably from one another, with the exception of the IN (AMIN + PMIN) and CTRL groups (Fig. 3 A-B). A Venn diagram revealed that the CTRL, CUMS, and IN groups had identified 1196 OTUs in total, with 136, 84, and 216 distinct OTUs, respectively (Fig. 3 C). Figure 3 D-F and Figure S2 E-F show the average relative abundance profiles of the microbes in all groups. The most prevalent phyla in each group were Firmicutes, Bacteroidota, Actinobacteriota, and Desulfobacteriota, which together accounted for more than 90% of the entire bacterial population (Fig. 3 G). Twenty major genera were detected at the genus level in the three groups with different relative abundances (Fig. 3 H). These genera included Lactobacillus , Dubosiella , Bifidobacterium , and so on. The total number of 37 differences (LDA > 2) within the three groups discovered by the LEfSe analysis; 18 of them were at the level of genera (Fig. 3 I). Compared with other groups, the CUMS group had significantly different relative abundances of Dubosiellea , Enterococcus , and Megamonas . Bifidobacterium , Christensenellaceae_R-7_group , Limosilactobacillus , Rikenella , norank_f_norank_o_Clostridia_UCG-014 , unclassified_f_Eggerthellaceae , and unclassified_o_Peptostreptococcales-Tissierellales were the most abundant genera in the inulin group. Within the CTRL group, the prominent sequences were Colitextribacter , Eubacterium_ruminantium_group , Faecalibacterium , Ligilactobacillus , NK4A214_group , norank_f_Erysipelotrichaceae , norank_f_ Eubacterium_coprostanoligenes_group , and norank_f_norank_o_RF39 . Figure S3 particularly illustrated how the gut microbiota in the various groups varied in terms of both composition and quantity. A summary of these results, the gut microbiota composition was considerably changed by both the CUMS and inulin treatments. Inulin treatment attenuated alterations in serum metabolites and metabolic pathway in CUMS-treated mice Alterations in the composition of gut microbial can influence serum metabolites [ 12 ], and investigation has been done on the effects of inulin on serum metabolites. In the positive and negative ion modes, 1147 recognized metabolites were found overall in the serum samples. Both score plots of partial least squares discriminant analysis (PLS-DA) constructed on the serum metabolites differentiated the CTRL group from the CUMS group, whereas that of the IN group was more similar to the CTRL group (Fig. 4 A), indicating that inulin intervention could modulate the significant changes in the metabolites of CUMS mice. A total of 70 metabolites differed between the CUMS and CTRL groups (VIP > 1, p < 0.05), of which 38 were upregulated and 32 downregulated (Fig. 4 B). When comparing the CUMS and CTRL groups, a total of 29 metabolites exhibited significant differences (Fig. 4 C), with 21 that were higher and 8 that were lower in inulin intervention mice. In addition, 4’-Hydroxyfenoprofen glucuronide, fenofibric acid, and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione were enriched in the serum metabolites of inulin intervention mice. Serum metabolomic pathway analysis was performed based on the differential metabolites. Figure 5 A showed that the enrichment of arginine biosynthesis; alpha-Linolenic acid metabolism; phenylalanine metabolism; pantothenate and CoA biosynthesis; and alanine, aspartate, and glutamate metabolism were significantly different pathways between CUMS and CTRL groups ( p < 0.05). For IN vs. CUMS, phenylalanine metabolism; energy metabolisms; alanine, aspartate, and glutamate metabolism were the significant pathways ( p < 0.05, Fig. 5 B). Moreover, KEGG pathway classification showed that the most significant metabolic pathway affected by inulin intervention was amino acid metabolism (Fig. 5 C). Interestingly, we found that the common pathways enriched in the comparisons of CUMS vs CTRL and IN vs CUMS were phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, and pantothenate and CoA biosynthesis. We also identified 14 shared differential metabolites in CUMS vs CTRL and IN vs CUMS, including valproic acid, 14,15-DiHETrE, risbitin, leucylhydroxyproline, pantothenic Acid, L-Phenylalanine, 2-Carboxy-4-dodecanolide, 4-Hydroxy-6-Methyl-2-Pyrone, 4’-Hydroxyfenoprofen glucuronide, fenofibric acid, 2-Hydroxypentanoic Acid, N6-Methyl-2'-deoxyadenosine, (2-Hydroxyethoxy)acetic acid, and isocitrate (Fig. 5 D, E). Five of these differential metabolites were categorized as carboxylic acids and derivatives, and two were benzene and substituted derivatives ( Table S2 ). Inulin treatment regulated amino acid metabolism in CUMS-treated mice Accumulating evidences suggests that alterations in amino acid content contribute to several mental disorders, including anxiety [ 13 ], depression [ 14 ], and schizophrenia [ 15 ]. Serum metabolomics revealed that the ameliorating effects of inulin on CUMS-induced anxiety- and depression-like behaviors were significantly related to amino acid metabolism. Interestingly, the AMIN and PMIN groups showed significant differences in amino acid levels. As shown in Fig. 6 , the decreased levels of alanine (Fig. 6 A), glutamic acid (Fig. 6 E), tyrosine (Fig. 6 O), tryptophane (Fig. 6 Q), and glycine (Fig. 6 G) in the CUMS mice were attenuated by inulin intervention. Moreover, chronic stress significantly increased the levels of valine (Fig. 6 P) and leucine (Fig. 6 I), whereas inulin treatment restored them to normal levels. Notably, the phenylalanine content (Fig. 6 L) increased after inulin intervention in the morning and decreased after inulin intervention in the evening. Similarly, the increased levels of aspartic acid (Fig. 6 C) in the CUMS mice were reduced by inulin intervention in the morning. Amino acids have been found could influence levels of monoamine neurotransmitters (norepinephrine, 5-HT, and dopamine) [ 16 ], thereby regulating mood and anxiety-like behaviors [ 17 ]. Phenylalanine can be converted to tyrosine, allowing synthesis of neurotransmitters, such as dopamine, epinephrine, and norepinephrine, that regulate nervous system function and maintain psychological balance [ 18 ]. Tryptophan is not only a precursor for the synthesis of serotonin (5-HT), but can also reduce chronic-low inflammation present in schizophrenia, depression and anxiety [ 19 ]. 5-HT is a monoamine neurotransmitter closely related to anxiety and depression. To further examine the effect of inulin on 5-HT synthesis, we determined the serum levels of tryptophan (5-HTP precursor), 5-HTP (5-HT precursor), and 5-HT. Inulin treatment in the morning and evening significantly upregulated the 5-HTP and increased the biosynthesis of 5-HT (Fig. 6 R, S). Notably, compared with the AMIN group, the PMIN group had higher levels of 5-HTP and lower levels of 5-HT. These results further suggested that inulin treatment in the morning and evening involved the regulation of the serotonin metabolic pathway (tryptophan → 5-HTP → 5-HT), and the morning inulin treatment showed higher tryptophan to 5-HT conversion rate. Inulin administration at different times generated different intervention effects on gut microbiota and metabolites in CUMS-treated mice In order to investigate the differences between morning and evening inulin interventions on CUMS-induced behaviors related to anxiety and depression, we compared the gut microbiota composition, metabolites, and metabolic pathways between the two treatment groups and the CUMS group. LEfSe analysis showed that both morning and evening inulin interventions significantly increased the levels of Bifidobacterium , norank_f_norank_o_Clostridia_UCG-014 , and Christensenellaceae_R-7_group in contrast to that in CUMS mice (Fig. 7 A, B). We also analyzed the microbial differences between the AMIN and PMIN groups (Fig. 7 C-H), and the PMIN group exhibited a higher level of Bifidobacterium and norank_f_norank_o_Clostridia_UCG-014 compared with the other groups, whereas the AMIN group showed a significantly elevated relative abundance of Christensenellaceae_R-7_group in comparison to the PMIN group. In addition, compared with the AMIN group, the PMIN group was significantly enriched in uncultured_f_Lachnospiraceae , and unclassified_f_Lachnospiraceae . Conversely, the AMIN group demonstrated a significantly higher level of Faecalibaculum and Coriobacteriaceae_UCG-002 than did the PMIN group. Correlation analysis showed that neuroinflammation and the gut barrier were positively correlated with the abundance of Dubosiella and Enterococcus and negatively correlated with the abundance of Bifidobacterium , norank_f_norank_o_Clostridia_UCG-014 , Christensenellaceae_R-7_group , uncultured_f_Lachnospiraceae , unclassified_f_Lachnospiraceae , Faecalibaculum , and Coriobacteriaceae_ucg-002 . The degree of normal behaviors and neurotransmitter appeared adversely correlated with the abundance of Dubosiella and Enterococcus , and favorably connected with Bifidobacterium , norank_f_norank_o_Clostridia_UCG-014 , Christensenellaceae_R-7_group , uncultured_f_Lachnospiraceae , unclassified_f_Lachnospiraceae , Faecalibaculum , and Coriobacteriaceae_UCG-002 (Fig. 7 I). The metabolites of the morning and evening inulin intervention groups were analyzed separately from those of the CUMS group. Metabolomics analysis found that AMIN vs CUMS and PMIN vs CUMS shared 3 different metabolites, including 4’-Hydroxyfenoprofen glucuronide, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, and trimethylamine N-Oxide (Fig. 8 A-D). The contents of 8 differential metabolites, such as fenofibric acid, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, and 4’-Hydroxyfenoprofen glucuronide, were substantially higher in the AMIN group as opposed to the CUMS group, as presented in Fig. 8 B. In contrast, the contents of 5 differential metabolites significantly decreased. After comparing the PMIN group with CUMS group, the contents of 19 differential metabolites including 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione and 4’-Hydroxyfenoprofen in the PMIN group were significantly increased, and the contents of 15 metabolites significantly decreased (Fig. 8 C). Notably, both the morning and evening inulin treatments significantly elevated the levels of trimethylamine N-Oxide and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione levels. Moreover, chronic stress significantly increased the levels of serum glucose, but significantly reduced them after inulin intervention, which may be related to the low levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in the AMIN and PMIN groups (Fig. 8 E). Correlation analysis of the gut microbes and metabolites showed that trimethylamine N-Oxide, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, PC(20:5/0:0), 4’-Hydroxyfenoprofen glucuronide, valproic acid, fenofibric acid, lysoPC(18:0/0:0), 2-(Hydroxyethoxy)acetic acid, risbitin, 2-Hydroxypentanoic Acid, and stercobilin were negatively correlated with Dubosiella and Enterococcus . Notably, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione was considerably and positively related to Bifidobacterium , norank_f_norank_o_Clostridia_UCG-014 , Christensenellaceae_R-7_group , and Faecalibaculum (Fig. 8 F). We separately compared the effects of morning and evening inulin treatments on the metabolic pathways in CUMS-treated mice. KEGG pathway classification showed that inulin intervention in the evening was more likely to influence amino acid metabolism ( Figure S4 ). Analyses of metabolic pathways using the metabolites that differ in abundance between AMIN vs CUMS and PMIN vs CUMS, indicating that inulin intervention in the morning significantly influenced the citrate cycle (TCA), ether lipid metabolism, glycerophospholipid metabolism, and glyoxylate and dicarboxylate metabolism (Fig. 9 A), whereas inulin intervention in the evening significantly modulated phenylalanine metabolism; glycerophospholipid metabolism; pantothenate and CoA biosynthesis; valine, leucine and isoleucine biosynthesis; and alanine, aspartate and glutamate metabolism (Fig. 9 B). A heatmap of the KEGG metabolic pathways of significantly altered metabolites showed that choline metabolism in cancer, glycerophospholipid metabolism, and central carbon metabolism in cancer were enriched in AMIN vs CUMS and PMIN vs CUMS (Fig. 9 C). We also found that amino acid metabolism, including phenylalanine, tyrosine, and tryptophan biosynthesis, beta-alanine metabolism, and tyrosine metabolism, were affected by evening inulin intervention compared to the morning inulin intervention (Fig. 9 C). Correlation analysis showed that alanine, glutamic acid, phenylalanine, tyrosine, and tryptophane were adversely corresponding to Dubosiella and Enterococcus and favorably connected with Bifidobacterium , Christensenellaceae_R-7_group , uncultured_f_Lachnospiraceae , unclassified_f_Lachnospiraceae , Faecalibaculum , and Coriobacteriaceae_UCG-002 (Fig. 9 D). Notably, gut microorganisms enriched in the PMIN group showed a stronger correlation with amino acids than did the AMIN group, indicating that inulin intervention in the evening was more likely to affect amino acid metabolism. Reconstruction of gut microbiota with inulin rescued the behavioral abnormalities in CUMS-treated mice To verify whether the reduction of anxiety and depression was facilitated by the inulin-associated gut microbiota, fecal microbiota from AMIN and PMIN mice were transplanted into CUMS-treated mice pretreated with an antibiotic cocktail. Behavioral tests were performed after the recolonization period. Figure 10 A showed the weekly body weights of all groups. Transplanting fecal microbiota did not alter the mice's body weight (Fig. 10 B). In comparison to the CUMS-treated mice, mice that acquired inulin mice microbiota (AMIN-CUMS and PMIN-CUMS) exhibited increased sucrose preference (Fig. 10 C). The OFT results showed that the reduction in the central region trajectory (Fig. 10 D), total distance (Fig. 10 E), center part duration time (Fig. 10 F), number of rearing (Fig. 10 G), and number of explorations (Fig. 10 H) in CUMS-treated mice was reversed by fecal microbiota transplantation. The EPM data revealed that the decrease of spontaneous exploration ability observed in CUMS-treated mice was blocked by fecal microbiota treatment (Fig. 10 I-K). Moreover, the center part duration time, the number of explorations in the OFT, and the open arm duration time in the EPM were higher in CUMS-treated mice that received AMIN-derived fecal microbiota than CUMS-treated mice that received PMIN-derived fecal microbiota. The LDT showed that the increased time spent in the light compartment in CUMS-treated mice was decreased by fecal microbiota transplantation (Fig. 10 L). The number of transitions in the LDT was similar between groups (Fig. 10 M). Simultaneously, fecal microbiota transplantation remarkably raised the levels of tryptophan, 5-HTP, and 5-HT in the serum of recipient mice that obtained fecal microbiota from inulin-treated mice (Fig. 10 N-P). These results highlighted that FMT improves CUMS-induced anxiety- and depression-like behaviors. Transplantation of fecal microbiota from mice that received morning and evening inulin interventions presented distinct effects on CUMS-treated mice To further explore the underlying mechanism of the anxiolytic and antidepressant effects of inulin, we measured the inflammatory response in serum, and hippocampus of recipient mice treated with inulin mice microbiota (AMIN-CUMS and PMIN-CUMS), and the expression of ZO-1 in intestine were also investigated. Compared with the CUMS-treated mice, the levels of ZO-1 in the colon tissue were higher in microbiota-depleted mice that got fecal microbiota from inulin-treated mice (Fig. 11 A), and the relative intensity of ZO-1 fluorescence in PMIN-CUMS group was stronger than that in AMIN-CUMS group (Fig. 11 B). Consistent with the results of the inulin intervention groups, serum LPS levels were inhibited by fecal microbiota transplantation (Fig. 11 C). In addition, fecal microbiota transplantation dramatically reduced the expression of IBA-1 in the hippocampus of CUMS mice (Fig. 11 D), and PMIN-CUMS mice showed a significantly lower relative intensity of IBA-1 fluorescence than AMIN-CUMS mice (Fig. 11 E). Moreover, fecal microbiota transplantation significantly decreased the levels of inflammatory cytokines (TNF-α, IL-6, and IL-1β) in serum and hippocampus of mice treated with CUMS (Fig. 11 F-K). Interestingly, recipient mice that acquired fecal microbiota from the evening inulin intervention group (PMIN-CUMS) showed lower levels of inflammatory cytokines than those receiving fecal microbiota from the morning inulin intervention group (AMIN-CUMS). These results indicated that the respective advantages of morning and evening inulin interventions were also reflected in recipient mice transplanted with fecal microbiota. Gut microbiome and serum metabolites of CUMS-treated mice were modified during reconstruction procedure Inulin administration in the morning and evening modulated the composition of gut microbiota and serum metabolites in mice with anxiety- and depression-like behaviors. It was worth exploring whether these characteristic metabolites and microbes could be detected in recipient mice after fecal bacterial transplantation. From the beta diversity, PCoA and NMDS showed that the circles of the inulin intervention group (IN) and fecal microbiota transplantation group (FMT) were clustered (Fig. 12 A-C), indicating the gut microbiome of the recipient mice was similar to that of the donor mice. In addition, the clustering tree also showed that the distance between the AMIN and AMIN-CUMS groups was relatively close, and the distance between the PMIN and PMIN-CUMS groups was relatively close, indicating that the effect of inulin intervention time on intestinal microbes was reflected in the intestinal flora of the recipient mice ( Figure S5 A ). We further analyzed the microorganisms at the genus level in the recipient mice. We found that the gut microbes that were significantly associated with morning and evening inulin interventions were also present in their respective recipient mouse gut microbes (Fig. 12 D, Figure S5 B-K ). For example, the levels of Enterococcus , Dubosiella , and Clostidium_sensu_stricto_1 in recipient mice were significantly lower than those in CUMS-treated mice. Moreover, the lower relative abundances of norank_f_norank_o_Clostridia-UCG-014 , Bifidobacterium , Coribacteriaceae_UCG-002 , Faecalibaculum , uncultured_f_Lachnospiraceae , and unclassified_f_Lachnospiraceae in the CUMS-treated mice were reversed by fecal microbiota transplantation. The dominant bacteria Coribacteriaceae_UCG-002 and Faecalibaculum in the AMIN group were also present in the CUMS-AMIN group, and the dominant bacteria uncultured_f_Lachnospiraceae and unclassified_f_Lachnospiraceae were also present in the CUMS-PMIN group. We also analyzed the serum metabolites of recipient mice. Figure S6 showed the KEGG pathway enrichment for recipient mice (AMIN-CUMS and PMIN-CUMS) compared with CUMS mice. The KEGG pathways related to amino acids, including phenylalanine metabolism; aminoacyl-tRNA biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; valine, leucine and isoleucine degradation; beta-Alanine metabolism; alanine, aspartate and glutamate metabolism; valine, leucine and isoleucine biosynthesis; and tyrosine metabolism, were enriched in the PMIN-CUMS group. The TCA cycle, drug metabolism-cytochrome P450, bile secretion, glucagon signaling pathway, ether lipid metabolism, and glyoxylate and dicarboxylate metabolism were significantly enriched in the AMIN-CUMS group. Notably, the KEGG pathway enrichment heatmaps for AMIN-CUMS vs CUMS and PMIN-CUMS vs CUMS ( Figure S6 C ) were consistent with those of AMIN vs CUMS and PMIN vs CUMS (Fig. 9 C). In addition, we compared differential metabolites between the two groups of recipient mice and CUMS-treated mice. From the VIP chart, it could be observed that there was a significant increase of 4’-Hydroxyfenoprofen glucuronide and fenofibric acid contents in AMIN-CUMS group compared to CUMS group (Fig. 12 E). The low concentrations of these two metabolites in CUMS-treated mice were reversed by inulin intervention. Among the differential metabolites between PMIN-CUMS and CUMS, the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione were highest in the PMIN-CUMS group (Fig. 12 F). Similarly, inulin treatment in the morning and evening significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione as compared with the CUMS group. Because 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione is the M-Ⅰ metabolite of pioglitazone [ 20 ], we also measured the glucose homeostasis in the fecal microbiota transplantation groups. Similarly, fecal microbiota transplantation reduced glucose levels in CUMS-treated mice, and the effect was more pronounced in the PMIN-CUMS group (Fig. 13 A), which may be correlated with PMIN-CUMS having higher levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione. Moreover, CUMS mice showed considerably reduced serum insulin levels compared with control mice, indicating that chronic stress could induce insulin resistance (Fig. 13 B). The level of the phosphorylated insulin receptor (p-IRS-1 ser11001) in the hippocampus was elevated after chronic stress, which was significantly decreased by the transplantation of microbiota from PMIN mice to CUMS mice (Fig. 13 C). These results suggest that evening inulin intervention is effective for improving insulin resistance. Discussion A wide variety of biological systems, such as neurological, gastrointestinal, physiological, and behavioral activities, are influenced by circadian clocks [ 21 ]. Consequently, different prebiotic consumption times may have varying potential benefits for alleviating stress-induced anxiety and depression. According to our previous study, the effects of inulin on anxiety and depression could be altered by the administration time and the dietary patterns [ 9 ]. In this study, the underlying mechanisms of how inulin regulates the microbiota-gut-brain axis and the potential link between the microbiota-gut-brain axis and chrono-nutrition were investigated. The results confirmed that the microbiota-gut-brain axis plays a central role in the anxiolytic property of inulin, and inulin administration in the evening produced a more pronounced effect in alleviating inflammatory response and improving amino acid metabolism. Anxiety and depression have a strong connection with inflammatory response. In this study, inulin intervention in the evening appeared to be more effective in alleviating the inflammatory response, manifested by decreased levels of pro-inflammatory cytokines and LPS and increased expression of ZO-1 compared to inulin intervention in the morning. LPS could be released from the intestine and enter the circulatory system as a result of increased intestinal permeability [ 22 ]. Furthermore, by attaching to Toll-like receptor-4 (TLR4), LPS may lead to the production of pro-inflammatory cytokines [ 23 ]. Indeed, some inflammatory signals can serve as sensors for microbial clocks, with potential roles in coordinating host circadian rhythms, inflammation, and metabolism [ 24 ]. There are diurnal rhythms to pro-inflammatory cytokines, with the morning and evening displaying different inflammatory states [ 25 , 26 ], which could explain why inulin showed different effects on the inflammatory response in CUMS mice at different intervention times. Consistent with our findings, Kalmukova et al. [ 27 ] found that melatonin administration in the evening was more efficient in decreasing pro-inflammatory cytokine levels than morning administration in obese rats. Moreover, compared with the CUMS mice that received fecal microbiota from morning inulin intervention mice (AMIN-CUMS), the mice that received fecal microbiota from evening inulin intervention mice (PMIN-CUMS) also displayed lower levels of TNF-α, IL-1β, and IL-6, indicating that the benefits of evening inulin intervention for reducing inflammation were significantly influenced by gut microbiota. The FMT experiments confirmed that the gut microbes affected by inulin administration feature an indispensable part in relieving anxiety and depression. The microbial community structure in the CUMS group differed significantly from that in the CTRL group, manifested by a significant increase in the relative abundance of Dubosiella and Enterococcus ; however, this trend was reversed after inulin treatment and gut microbiota reconstruction. There are evidences to suggest that following periods of unpredictable chronic mild stress, the relative abundance of Enterococcus in mouse feces becomes higher [ 28 , 29 ]. Enterococcus can produce large amounts of d-lactate in the gut, which may impair brain function. Dubosiella is positively correlated with markers of inflammatory response and glycolipid metabolism disorders [ 30 , 31 ]. In addition, we found that inulin administration significantly increased the levels of Bifidobacterium , norank_f_norank_o_Clostridia_UCG-014 , and Christensenellaceae_R-7_group in the feces of CUMS-treated mice. Furthermore, increases in Bifidobacterium and norank_f_norank_o_Clostridia_UCG-014 were also found in the gut microbes of recipient mice that received the fecal microbiota from inulin-treated mice. Notably, the relative abundances of Bifidobacterium and norank_f_norank_o_Clostridia_UCG-014 were higher in the PMIN and PMIN-CUMS groups. Clinical studies have shown that Bifidobacterium spp. supplementation can relieve symptoms of anxiety and depression [ 32 ]. Pulsatilla chinensis saponins alleviated inflammation in a rat model of ulcerative colitis, which may be ascribed to an increase in beneficial bacteria such as norank_f_norank_o_Clostridia_UCG-014 [ 33 ]. Similarly, long-term consumption of stachyose ameliorated HFD-associated colonic inflammation by increasing the proportion of Christensenellaceae_R-7_group [ 34 ]. Therefore, probiotics that alleviated inflammation via the gut microbiota could also be ideal targets for relieving anxiety and depression. Consistent with these studies, our findings revealed that the increased bacteria in the CUMS group were positively associated with inflammation, whereas the decreased bacteria in the CUMS group were negatively correlated with inflammation. Our results also showed that microbiota abundant in the PMIN and PMIN-CUMS group ( uncultured_f_Lachnospiraceae and unclassified_f_Lachnospiraceae ) were substantially inversely connected with pro-inflammatory cytokines ( p < 0.05), whereas the microbiota enriched in the AMIN and AMIN-CUMS group ( Faecalibaculum and Coriobacteriaceae_UCG-002 ) were not significantly negatively correlations with the pro-inflammatory cytokines. Previous studies have shown that the intestinal microbiota undergoes diurnal oscillations under the control of host feeding time [ 8 , 35 ]. Here, we reported that the intervention time of inulin influenced microbial composition, and the effect of the intestinal microbiome on the inflammatory response was more prominent in the evening inulin intervention group and the FMT group that received PMIN fecal microbiota. Disturbances in amino acids have been implicated in various neuropsychiatric disorders, including anxiety, depression, cognitive impairment, and chronic fatigue syndrome [ 36 , 37 ]. Most amino acids showed a tendency to vary rhythmically over the course of the 24-hour day [ 38 ]. Our current investigation revealed that long-term stress disturbed amino acid metabolism, which was relieved by inulin intervention. Indeed, inulin intervention in the evening had a more prominent influence on amino acid metabolism than in the morning, and this effect was also observed in the FMT experiments. A previous study [ 39 ] showed the gut microbiota significantly influence plasma metabolites, and amino acid metabolites being particularly affected. Notably, the gut microbiota has the ability to facilitate the synthesis and consumption of amino acids, which can be absorbed throughout the digestive tract and then accumulated in the plasma [ 40 ]. The intestinal microbiota exhibited daily cyclical fluctuations, suggesting that the effects of different intervention times on amino acids may be due to different microbes present in the morning and evening. The dominant bacterium in the morning inulin intervention group, Faecalibaculum , a potentially beneficial bacterium that can relieve anxiety- and depression-like behaviors [ 41 ], has a significant positive correlation with tryptophan and 5-HT. Similarly, Deng et al. [ 42 ] discovered a positive correlation between Faecalibacterium and sociability as well as 5-HT pathway components in metformin-treated mice. In terms of the levels of 5-HTP and 5-HT in the inulin intervention and FMT groups, we found that both the AMIN and AMIN-CUMS mice exhibited higher tryptophan to 5-HT conversion rates. The prominent microorganisms in the evening inulin intervention group, uncultured_f_Lachnospiraceae and unclassified_f_Lachnospiraceae , positively correlated with tryptophan, alanine, tyrosine, glycine, and histidine levels. Tyrosine and tryptophan are typical aromatic amino acids that are metabolized by Lachnospiraceae, which is one of the main microbial pathways in the human gut that produces indole-propionic acid, indole, phenol, and p-cresol [ 43 ]. In addition, Lachnospiraceae has been found to be significantly associated with attenuating inflammation in obese [ 44 ] and CUMS mice [ 45 ]. Consistent with previous research, uncultured_f_Lachnospiraceae and unclassified_f_Lachnospiraceae were drastically and poorly associated with pro-inflammatory cytokines. In addition, microbiota, including Escherichia coli , Clostridium spp., Bacteroides spp., and Bifidobacterium spp., can produce enzymes responsible for tryptophan catabolism [ 46 – 48 ]. Furthermore, Bifidobacterium longum has been observed to decrease the concentrations of TNF-α, IL-1β, IL-6 via mediating tryptophan metabolism [ 49 ]. We also found that the amino acids, influenced by inulin intervention in the evening, were substantially negatively associated with pro-inflammatory cytokines ( Figure S7 ). These results suggested that the remission effect of evening inulin intervention on anxiety- and depression-like behaviors may be related to gut microbes reducing inflammation by influencing amino acid metabolism. Moreover, gut microflora directly affect the possibility of drug metabolism of the host [ 39 ]. Within our research, the AMIN and AMIN-CUMS groups showed significantly influenced drug metabolism-cytochrome P450 (CYP) and lipid metabolism compared with the PMIN and PMIN-CUMS groups. Fenofibric acid, an agent for decreasing lipid in the blood, has been shown to be a potent inhibitor of cytochrome CYP 2C [ 50 ]. Indeed, the host gut microbiota may have an effect on the majority of CYP enzymes, which participate in hormone and lipid metabolism, and detoxification [ 51 , 52 ]. Furthermore, CYP are crucial for the regulation of the biological clock and circadian rhythm [ 53 , 54 ]. Fenofibric acid exerts neuroprotective effects against cognitive impairment in Parkinson’s disease [ 55 ]. Moreover, 4’-Hydroxyfenoprofen glucuronide is involved in the synthetic pathway of fenoprofen [ 56 ]. Fenoprofen has been widely used as an anti-inflammatory and analgesic drug [ 57 ]. Similarly, connection investigation on 4’-Hydroxyfenoprofen glucuronide demonstrated a substantial negative relationship to TNF-α and LPS. Notably, fenofibric acid and 4’-Hydroxyfenoprofen glucuronide are organic acids containing phenyl groups. A recent study concluded that the presence of gut microorganisms greatly boosted the levels of certain organic acids containing phenyl groups [ 39 ]. The fenofibric acid showed a positive correlation with the bacteria in the AMIN group ( Faecalibacterium and Coriobacteriaceae_UCG-002), while a negative correlation with the microbiota in the PMIN group ( uncultured_f_Lachnospiraceae and unclassified_f_Lachnospiraceae ). These results suggested that inulin intervention in the evening is more effective at alleviating inflammation and damaging the gut barrier. In addition, inulin intervention in the morning and evening significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in the CUMS-treated mice, accompanied by lower glucose concentrations in both groups. Transplanting the fecal microbiota from evening inulin intervention mice into CUMS-treated mice also significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione; however, this trend was not observed in the other FMT group. 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, a pioglitazone metabolite, is significantly associated with glucose levels. Mood swings, including anxiety, depression, and nervousness, cause the body to release more stress hormones (such as cortisol, thyroid hormones, and adrenal hormones), which can lead to insulin resistance [ 58 , 59 ]. Our findings revealed that evening inulin treatment considerably decreased serum glucose and insulin levels. The expression of p-IRS-1 in the hippocampus was also decreased by the evening inulin intervention. Similarly, Chaihu-shugan, a traditional Chinese medicine, has antidepressant activity and improves glucose tolerance by reducing serum glucose levels in CUMS rats [ 60 ]. In addition, the circadian system affects glucose tolerance by regulating the digestion, absorption, and metabolism of the stomach and intestines according to the time of day [ 61 ]. In this study, the lower levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in CUMS-treated mice were reversed by microbiome recolonization. 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione exhibited a notable negative correlation with Dubosiella and pro-inflammatory cytokines, while displaying a significant positive correlation with Bifidobacterium and norank_f_norank_o_Clostridia_UCG-014 (Figure S7 ). This suggests that the gut bacteria may be a participant in the production of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, which also provides a potential underlying mechanism for effects of inulin. Conclusion In conclusion, the results indicate that the microbiota-gut-brain axis plays a central role in the anxiolytic ability of inulin. Administration time seemed to modify the anxiolytic and antidepressant effects of inulin, and inulin intervention in the evening was more pronounced in improving amino acid metabolism and insulin resistance and inhibiting the inflammatory response. This study provides a new potential linking between the microbiota-gut-brain axis and chrono-nutrition, which may provide novel ideas for precision intervention in mood and behavioral disorders. Methods Animals Male C57BL/6 mice weighing 20 ± 1 g were acquired from Huazhong Agricultural University’s Animal Experiment Center in Wuhan, China. The mice were kept in conventional settings with five mice per cage, 50 ± 2% relative humidity, 23 ± 1°C temperature, 12 h of light and dark, and unrestricted access to food and drink. Before the tests began, all of the mice were given a week to become used to their new surroundings. The ethics committee of the Animal Experiment Center at Huazhong Agricultural University accepted the use of mice in this research, which followed the Chinese Council on Animal Care Guidelines. CUMS procedure The CUMS process was performed as our previous research [ 62 ]. In brief, the procedure comprised the following 9 stressors: water and food deprivation (24 h), 45° cage tilt (24 h), restraint in the box (4 h), day and night reversal (24 h), wet bedding (24 h), tail pinch (3 min, 1 cm from the end of the tail), 45℃ high temperature (5 min), empty cage (no bedding placed, 24 h), shake cage (6 min). The stressors were applied randomly and were not repeated for two consecutive days, and repeated every seven days (Table S1 .). Experimental design The experiments involved in this study were divided into 2 stages: CUMS modeling and inulin treatment, as well as fecal microbiota transplantation (FMT) (Figure S1 ). Stage 1 Sixty mice were randomly assigned to four groups for the CUMS modeling and inulin treatment experiments: a model group (CUMS, n = 30), a morning (7:30–8:00 am) inulin administered group (AMIN, n = 10), an evening (7:30–8:00 pm) inulin administered group (PMIN, n = 10), and a control group not subjected to any stress (CTRL, n = 10). The inulin dose administered was 4 g/kg/day. A weekly measurement of the body weight was made. All of the mice performed a week-long battery of behavioral tests following eight weeks of CUMS. Stage 2 In FMT [ 62 ], 20 mice in the CUMS group split into two groups at random: a recipient group received fresh fecal samples from AMIN group mice (AMIN-CUMS, n = 10 ), and a recipient group received fresh fecal samples from PMIN group mice (PMIN-CUMS, n = 10 ). A combination of 200 mg/kg of ampicillin, 200 mg/kg of metronidazole, 200 mg/kg of neomycin, and 100 mg/kg of vancomycin was gavaged daily for eighteen days to the mice in FMT groups [ 63 ]. Following three days of washout, the recipient mice received 200 µL of the donor's fresh fecal supernatant, which was obtained from either AMIN or PMIN, orally every day for a period of 14 days. After a 14-day period of recolonization, the behavior tests were carried out. Weight was recorded weekly and behavioral tests were taken in the same manner as in stage 1. One day after behavioral testing, the mice were sacrificed and orbital blood samples were taken. The serum, hippocampus, and cecum content were rapidly collected for further investigations. Behavioral testing Testing was done in accordance with the guidelines in our earlier report [ 9 ]. The formula used to compute the sucrose preference (%) in the sucrose preference test (SPT) was sucrose intake (g)/ [sucrose intake (g) + water intake (g)] × 100%. In the open field test (OFT), the distance traveled, number of rearing and explorations, and center part duration time were used to evaluate spontaneous ability of mice. Orientation behavior and exploring abilities of mice in both bright and dark environments were evaluated in the light-dark test (LDT) using the time consumed in the bright chamber and the quantity of transitions. Natural exploratory behavior in a novel environment was measured for the elevated-plus maze test (EPM) using the length time and the quantity of entrances into open arms. Quantitative analysis of serum amino acids With minor adjustments, serum amino acid quantification using ultra-performance liquid chromatography tandem triple quadrupole mass spectrometry (UHPLC-MS/MS) was performed in accordance with previously published procedures [ 64 , 65 ]. A Waters X Bridge Amide column (100 × 2.1 mm, 3.5 µm) was used for the analyses, and 1 µL of injection volume was used. Composition of the mobile phases were water: formic acid (99.9:0.1, v/v) (mobile phase A) and acetonitrile: formic acid (99.9:0.1, v/v) (mobile phase B). The run time was set to 18 min, with a flow rate of 0.25 mL/min. The steps involved in gradient elution were as follows: 92% B for 3 min; decreased to 85% B in 3 min; decreased to 65% B in 3 min; and held at 65% B for 5 min. Within the next 4 min, the gradient returned linearly to the initial condition and was maintained for 10 min for rebalancing. The column oven temperature was adjusted to 40 ℃. IRS: sweep type, positive mode; spray voltage, 5500 V; nebulizer pressure, 50 psi; and capillary temperature, 320℃. ELISA analysis 5-HT, 5-HTP, IL-1β, IL-6, TNF-α, and LPS were determined by ELISA in serum and hippocampus (Shanghai Huding Biological Technology Company, Shanghai, China), in accordance with manufacturer guidelines. In cold PBS containing 1% PMSF, the hippocampus of every mouse was homogenized. The supernatant was extracted following a 15-minute centrifugation process at 4°C and 12,000 rpm. Elabscience's BCA assay kit (E-BC-K318-M) was utilized to quantify the amount of protein. 16S rRNA amplicon and sequencing The sequencing service was provided by Majorbio Bio-Pharm Technology Co., Ltd., Shanghai, China. In brief, the Kruskal-Wallis test was applied to analyze alpha diversity in the study of 16S rRNA sequencing data, and FDR multiple comparisons were then performed. PCoA and NMDS were utilized to display the beta diversity, which was computed using binary Pearson dissimilarity. Circular Packing and River charts were used to illustrate the taxonomic transitions between groups at the phylum and genus levels. To determine whether bacterial groupings had significantly varied levels of abundance from phylum to genus across the different groups, the LEfSe (LDA > 2, p < 0.05) was utilized. Furthermore, the Wilcoxon rank-sum test was employed to examine variations among two groups at the genus level. Metabolomics analysis Using a Waters Acquity UPLC system connected to a Q-Exactive HF-X mass spectrometer with electrospray ionization in both positive and negative ionization modes, untargeted metabolomics of the serum was carried out. Progenesis QI (Waters Corporation, Milford, USA) was used to prepare the raw data files for analysis. The HMDB and Metlin databases were used for matching. The untargeted metabolomics profiling was supplied by Majorbio Bio-pharm Technology Co., Ltd., Shanghai, China. For the metabolomics data, the R package ropls was employed to carry out PLS-DA. According to the VIP derived using the PLS-DA model and the p-value produced by the Student’s-t test, metabolites with VIP > 1 and p < 0.05 were concluded to be substantially distinct metabolites. The KEGG database was utilized for metabolic enrichment and pathway analysis, whereby the differing metabolites of two groups were divided into corresponding biochemical pathways. In accordance with the pathways and functions that they perform, the metabolites were categorized. Statistical analysis Software from GraphPad Prism (version 8.0) and SPSS 25.0 were used for the analyses. Data are represented as mean ± SEM. An ANOVA analysis was performed on all the data, and then the Tukey-Kramer test was conducted. Clustering heat map analysis displayed the distribution of indicators between different groups intuitively according to color. The associations between markers linked to behavior, the gut, metabolism, and the brain were investigated using Spearman's correlation analysis. ImageJ software was used to analyze the relative fluorescence intensity. A threshold of p < 0.05 was established for statistical significance. Abbreviations CUMS Chronic unpredictable mild stress SPT Sucrose preference test OFT Open field test EPM Elevated plus maze test LDT Light-dark box test FMT fecal microbiota transplantation 5-HTP 5-hydroxytryptophan PCoA Principal coordinate analysis NMDS Non-metric multidimensional scaling PLS-DA Partial least squares discriminant analysis LEfSe Linear discriminant analysis effect size VIP Variable importance in the projection LPS Lipopolysaccharides Declarations Acknowledgements Not applicable. Funding This work was supported by the National Natural Science Foundation of China (32372326) and the Fundamental Research Funds for the Central Universities (2662020SPPY004). Author’s contributions C.P. performed the research, analyzed the data, and wrote the main manuscript. C.F.Y, H.T., and H.X.Q. analyzed the data and wrote the manuscript. X.C.X., Z.J.M., and S.S.S. designed the research study, analyzed and interpreted the data. L.C.M. reviewed and edited the manuscript. L.K.K. contributed to the experimental design and drafting and critical revision of the manuscript. The authors read and approved the final manuscript. Availability of data and materials This publication and its additional information files contain all the data generated or processed during this research. The raw Illumina sequence information has been uploaded to the NCBI Sequence Read Archive (SRA) with accession number PRJNA1085102. Ethics approval and consent to participate The ethics committee at Huazhong Agricultural University’s Animal Experiment Center accepted all mouse experimentation protocols (HZAUMO-2022-0131), which followed the Chinese Council on Animal Care Guidelines. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Lupien SJ, McEwen BS, Gunnar MR, et al. Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience. 2009;10:434-445. Heijtza RD, Wang SG, Anuar F, et al. Normal gut microbiota modulates brain development and behavior. Proceedings of the National Academy of Sciences of the United States of America. 2011;108:3047-3052. Siopi E, Chevalier G, Katsimpardi L, et al. Changes in Gut Microbiota by Chronic Stress Impair the Efficacy of Fluoxetine. Cell Reports. 2020;30:3682-3690.e6. Burokas A, Arboleya S, Moloney RD, et al. 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Analytical and Bioanalytical Chemistry. 2016;408:2285-2292. Kıvrak İ, Kıvrak Ş, Harmandar M. Free amino acid profiling in the giant puffball mushroom (Calvatia gigantea) using UPLC–MS/MS. Food Chemistry. 2014;158:88-92. Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Additional file 1: Figure S1. Experimental design. (A) The experimental design of stage 1. (B) The experimental design of stage 2. CUMS: Chronic unpredictable mild stress, FMT: fecal microbiota transplantation, Behavior tests: Sucrose preference test (SPT), open field tests (OFT), light-dark test (LDT), elevated plus-maze test (EPM). Additionalfile2.docx Additional file 2: Figure S2. Inulin intervention changed the alpha diversity and composition of intestinal microbiota. (A) Comparison of chao index, shannon index, sobs index and ace index of gut microbiota in different groups. Percent of microbiota abundance on (B) phylum level, (C) class level, (D) order level, (E) family level, (F) genus level. N = 5 mice/group. Additionalfile3.docx Additional file 3: Figure S3. Boxplots showing differences in relative abundance of sequences according to LEfSe analysis (select the top 50 sequences at genus level). (A) Bifidobacterium , (B) norank_norank_o_Clostridia-UCG-014 , (C) Dubosiella , (D) Ligilactobacillus , (E) Colidextribacter , (F) norank_f_norank_o_RF39 , (G) Christensenellaceae_R-7_group , (H) NK4A214_group , (I) Clostridium_sensu_stricto_1 , (J) Enterococcus , (K) Odoribacter , (L) norank_f_Eubacterim_coprostanoligenes_group . * p < 0.05, ** p < 0.01, *** p < 0.001. CTRL group, n = 5; CUMS group, n = 5; IN group, n = 10. Additionalfile4.docx Additional file 4: Figure S4. Different inulin intervention times produced different influences on the KEGG pathway. Statistical diagram of KEGG pathway classification in (A) AMIN vs CUMS and (B) PMIN vs CUMS. N = 5 mice/group. Additionalfile5.docx Additional file 5: Figure S5. Fecal microbiota transplantation restored the disturbed intestinal flora of CUMS mice. (A) Hierarchical clustering tree on OTU level in FMT-treated mice. Boxplots showing differences in relative abundance of sequences in (B) Dubosiella , (C) norank_f_norank_o_Clostridia_ucg-014 , (D) Bifidobacterium , (E) Clostridium_sensu_stricto_1 , (F) unclassified_f_Lachnospiraceae , (G) uncultured_f_Lachnospiraceae , (H) Odoribacter , (I) Coriobacteriaceae_UCG-002 , (J) Enterococcus , (K) Faecalibaculum in FMT-treated mice (select the top 50 sequences at genus level). N = 5 mice/group. Additionalfile6.docx Additional file 6: Figure S6. The effects of fecal microbiota transplantation on KEGG pathway. Statistical diagram of KEGG pathway classification in (A) AMIN-CUMS vs CUMS and (B) PMIN-CUMS vs CUMS. (C) KEGG pathway enrichment significant heatmap of metabolites in AMIN-CUMS vs CUMS and PMIN-CUMS vs CUMS, * p < 0.05, ** p < 0.01, *** p < 0.001. N = 3 mice/group. Additionalfile7.docx Additional file 7: Figure S7. Spearman correlation between the related indicators of metabolites and gut microbiota. Axis label: red, gut microbiota; yellow, LPS in serum and pro-inflammatory cytokines in the serum and hippocampus; cyan, tryptophan, 5-HTP and 5-HT in the serum; purple, amino acid; black, serum metabolites. Within the heatmap region, red indicates positive correlation and blue indicates negative correlation, * p < 0.05. N = 3 mice/group. Additionalfile8.docx Additional file 8: Table S1. Schedule of CUMS stimulation. Additionalfile9.docx Additional file 9: Table S2. The shared differential metabolites in CUMS vs CTRL and IN vs CUMS. N = 3 mice/group. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4157149","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287954842,"identity":"000e5fa9-6414-42ff-8467-6a4018a7a875","order_by":0,"name":"Ping Chen","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Ping","middleName":"","lastName":"Chen","suffix":""},{"id":287954843,"identity":"36805a11-c870-44e5-92fa-994a4b88c6d5","order_by":1,"name":"Fanyang Chen","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Fanyang","middleName":"","lastName":"Chen","suffix":""},{"id":287954844,"identity":"ec4d00c5-57ad-450b-bb1c-3b325a0b9672","order_by":2,"name":"Tao Hou","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Hou","suffix":""},{"id":287954845,"identity":"00c5f9f9-95bf-4308-8eab-840030f99ad2","order_by":3,"name":"Xueqin Hu","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xueqin","middleName":"","lastName":"Hu","suffix":""},{"id":287954846,"identity":"4369df3a-015e-4006-a802-8ae38513f8b8","order_by":4,"name":"Chenxing Xia","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chenxing","middleName":"","lastName":"Xia","suffix":""},{"id":287954847,"identity":"d4a944c9-6e75-44bc-92b3-2fd2adf3d83c","order_by":5,"name":"Jiaming Zhang","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jiaming","middleName":"","lastName":"Zhang","suffix":""},{"id":287954848,"identity":"8a1592c4-33d4-449f-9233-2287033f7a94","order_by":6,"name":"Shanshan Shen","email":"","orcid":"","institution":"Huazhong University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Shanshan","middleName":"","lastName":"Shen","suffix":""},{"id":287954849,"identity":"647fe514-317c-449e-be82-509524a6ae26","order_by":7,"name":"Chenmei Li","email":"","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chenmei","middleName":"","lastName":"Li","suffix":""},{"id":287954850,"identity":"d70f06a3-c8f4-4498-a9c6-120aca482fb4","order_by":8,"name":"Kaikai Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYBACPmY2BoaEAww8/EDOgQcMByDCPHi0sMG0SDYAtSQQpQUIGUAKDUCKidPCzpb44cEZOxnja4cfAm25Y88/I4Hxwds2Bnlz3A47LJFwI5nH7HaaAVDLM2aJGwnMhnPbGAx3NuDSwt4gkfCBGaglAaTlMBvDjQQ2ad42hgSDAzi1NP9I+FDPYzw7/QNIC4/8jQT23/i1sB0DOuwwj4F0DtgWCQOgLcwEtKRZJJw5ziNxO6fgQILBYQPDMw+bJeeckzDcgEMLP/8x45s/jlXb889O3/zhQ8Vhe7njyQc/vCmzkcdlCxowABGMDUBCgij1o2AUjIJRMAqwAwDSFlq5V9YfXgAAAABJRU5ErkJggg==","orcid":"","institution":"Huazhong Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Kaikai","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2024-03-24 08:44:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4157149/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4157149/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54301088,"identity":"771986c8-4df9-4dd7-9012-9d6bf3eb6015","added_by":"auto","created_at":"2024-04-08 14:29:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1545399,"visible":true,"origin":"","legend":"\u003cp\u003eInulin treatment alleviated CUMS-induced anxiety- and depression-like behaviors. (A) Body weight of mice in CTRL, CUMS, inulin treatment at 7:30-8:00 am and inulin treatment at 7:30-8:00 pm groups. (B) Body weight at 18th week. (C) Sucrose preference of different groups in SPT. (D) Movement locus, (E) total distance, (F) center part duration time, (G) number of rearing, and (H) number of explorations in the OFT. (I) Movement locus, (J) number of entries into the open arms, and (K) open arm duration time in the EPM. (L) Time in light compartment, and (M) number of transitions in the LDT. Values represent as mean ± SEM, n = 8-10. Diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/498919788f4ad892d1c33036.png"},{"id":54301084,"identity":"b28d10fc-8982-4cf5-8b11-45a12e3e0c14","added_by":"auto","created_at":"2024-04-08 14:29:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1988548,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of morning and evening inulin treatment on inflammatory response. (A) Immunofluorescence images of ZO-1 (green) and DAPI (blue) in the colon ((200×, scale bar = 100 μm). (B) Relative intensity of ZO-1 fluorescence of colon in different groups, n = 3. (C) The levels of LPS in serum, n = 6. The levels of (D) TNF-α, (E) IL-6 and (F) IL-1β in serum. The levels of (G) TNF-α, (H) IL-6, and (I) IL-1β in hippocampus, n = 6. Data are represented as mean ± SEM. Different lowercase letters indicate significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/cebcc20c39d89c1c378868e3.png"},{"id":54301090,"identity":"fbaeb5dc-1698-423c-9858-7ee667d1d2dc","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":813882,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of inulin treatment on the biodiversity and composition of the intestinal bacterial population.(A) A score plot for principal coordinate analysis (PCoA) with weighted-unifrac distance metrics. (B) A score plot derived from non-metric multidimensional scaling (NMDS) analysis. (C) Venn diagram of the observed OTUs in different groups.(D), (E), (F) Taxonomic tree in packed circles of different groups. From outside to inside, the circles stand for phylum, class, order, family, and genus. Abundances of intestinal bacteria at (G) phyla level and (H) genus level. (I) LEfSe analysis of intestinal bacteria in different groups. Groups: CTRL, n = 5; CUMS, n = 5; IN, n = 10.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/ff911588500187868538018e.png"},{"id":54301096,"identity":"f1aac290-782f-414a-892e-08da3d96e07f","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":663455,"visible":true,"origin":"","legend":"\u003cp\u003eInulin intervention caused differences in serum metabolites in CUMS-treated mice. (A) Score plots of negative and positive metabolites with partial least squares discriminant analysis (PLS-DA). Heatmap of metabolites with differential abundance in (B) CUMS vs CTRLand (C) IN vs CUMS (VIP \u0026gt; 1, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). CTRL group, n = 3; CUMS group, n = 3; IN group, n = 6.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/9851aaf9d41d678becf3c9df.png"},{"id":54301106,"identity":"750aceed-9fef-4d60-b132-237d24455540","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":628137,"visible":true,"origin":"","legend":"\u003cp\u003eThe differential metabolic pathways and differential metabolites in treatment groups. Analysis of metabolic pathways with the different metabolites in (A) CUMS vs CTRL and (B) IN vs CUMS. (C) KEGG pathway classification of inulin treatment groups. (D) Venn diagram displaying the shared metabolites in CUMS vs CTRL and IN vs CUMS. (E) Boxplots showing the levels of shared metabolites in CUMS vs CTRL and IN vs CUMS. CTRL group, n = 3; CUMS group, n = 3; IN group, n = 6.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/a8632e5ad2486a21354859c4.png"},{"id":54301086,"identity":"60351ea9-5501-45ce-9361-9b1629dc8098","added_by":"auto","created_at":"2024-04-08 14:29:12","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":645799,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of morning and evening inulin administration on amino acid concentrations in the serum. The levels of (A) Alanine acid, (B) Arginine, (C) Aspartic acid, (D) Citrulline, (E) Glutamic acid, (F) Glutamine, (G) Glycine, (H) Histidine, (I) Leucine, (J) Methionine, (K) Ornithine, (L) Phenylalanine, (M) Serine, (N) Threonine, (O) Tyrosine, (P) Valine, (Q) Tryptophane, (R) 5-HTP and (S) 5-HT in serum. 5-HTP: 5-hydroxytryptophan, 5-HT: Serotonin. Values represent as mean ± SEM, n = 5 mice/group. Diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/22e696571d60930815351208.png"},{"id":54301793,"identity":"05371110-30fc-437d-90b5-5ff955cc6eaa","added_by":"auto","created_at":"2024-04-08 14:37:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":624956,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences of gut microbiota between morning and evening inulin intervention in CUMS mice. LDA scores for the microbiome with differential abundant between (A) CUMS and AMIN and (B) CUMS and PMIN (LDA \u0026gt; 2.0). (C-H) Analysis of microbial differences between AMIN group and PMIN group, values represent as mean ± SEM, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. (I) Correlation analysis of the gut microbes, behaviors, neuroinflammation, gut barrier components, and neurotransmitters, cyan denotes optimistic relationship and orange denotes adverse relationship, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. N = 5 mice/group.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/cb122e4aa21e665f180486c1.png"},{"id":54301091,"identity":"42bb4ec7-e68c-48d3-acf0-40aa57cde7c1","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":717404,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences of serum metabolites between morning and evening inulin intervention in CUMS mice. (A) Venn diagram displaying the shared metabolites in AMIN vs CUMS and PMIN vs CUMS, n = 3. Heatmap of metabolites with various abundances in (B) AMIN vs CUMS and (C) PMIN vs CUMS (VIP \u0026gt; 1, \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05), n = 3. (D) Boxplots illustrating the levels of shared metabolites in AMIN vs CUMS and PMIN vs CUMS, n = 3. (E) The levels of glucose in inulin-treated mice, n = 6, values represent as mean ± SEM, diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. (F) Correlation analysis of the gut microbes and metabolites, blue represents optimistic relationship and orange represents passive relationship, n = 3, *\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/e920e8727bf44bbcc14dfdbc.png"},{"id":54301094,"identity":"a79d86d5-8ffa-4c88-bc64-aec626275cf7","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":738103,"visible":true,"origin":"","legend":"\u003cp\u003eInulin intervention in the morning and evening affected different metabolic pathways in CUMS mice. Metabolic pathway analysis conducted with the differentially abundant metabolites in (A) AMIN vs CUMS and (B) PMIN vs CUMS.(C) KEGG pathway enrichment significant heatmap of metabolites in AMIN vs CUMS and PMIN vs CUMS, purple indicates positive correlation and orange indicates negative correlation, n = 3, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. (D) Correlation analysis of the gut microbes and amino acids, blue indicates optimistic correlation and orange indicates passive correlation, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. N = 3 mice/group.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/de25a9ba225d62606553425f.png"},{"id":54301104,"identity":"d840d151-70c8-4a8d-a09a-a28f6e5715f5","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1412911,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of fecal microbiota transplantation on anxiety- and depression-like behaviors in CUMS-treated mice. (A) Body weight of mice exposed to CUMS that underwent fecal microbiota transplantation. (B) Body weight at 18\u003csup\u003eth\u003c/sup\u003e week. (C) Sucrose preference of different groups in SPT. (D) Movement locus, (E) total distance, (F) center part duration time, (G) number of rearing, and (H) number of explorations in the OFT. (I) Movement locus, (J) number of entries into the open arms, (K) open arm duration time in the EPM. (L) Time in light compartment, and (M) number of transitions in the LDT. The levels of (N) Trp, (O) 5-HTP and (P) 5-HT in serum. Trp: Tryptophane, 5-HTP: 5-hydroxytryptophan, 5-HT: Serotonin. Values represent as mean ± SEM, n = 8-10. Diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ns indicates no significant difference.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/9510a16fc2f452360e80165e.png"},{"id":54301108,"identity":"1cfd82f3-59c2-4808-a2ee-0ec4f71c3467","added_by":"auto","created_at":"2024-04-08 14:29:15","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":3177475,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of fecal microbiota transplantation on inflammatory response of CUMS-treated mice. (A) Immunofluorescence images of ZO-1 (green) and DAPI (blue) in the colon (200×, scale bar = 100 μm). (B) Relative intensity of ZO-1 fluorescence of colon in different groups, n = 3. (C) The levels of LPS in serum, n = 6. (D) Immunofluorescence images of IBA-1 (red) and DAPI (blue) in the hippocampus (200×, scale bar = 100 μm). (E) Relative intensity of IBA-1 fluorescence of hippocampus in different groups, n = 3. The levels of (F) TNF-α, (G) IL-6 and (H) IL-1β in serum. The levels of (I) TNF-α, (J) IL-6 and (K) IL-1β in hippocampus, n = 6.Values represent mean ± SEM. Diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/a7d2bb04ccd3b2e21f5a6ed2.png"},{"id":54301103,"identity":"a359e573-900a-42c7-b8f8-cd63362a0c4d","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":766246,"visible":true,"origin":"","legend":"\u003cp\u003eComposition of the gut microbiota and serum metabolites in FMT-treated mice. (A) A score plot for principal coordinate analysis (PCoA) using weighted-unifrac distance metrics, n = 5. (B) A score plot for non-metric multidimensional scaling (NMDS) score plot with pearson, n = 5. (C) Venn diagram of the observed OTUs in various groups, n = 5. (D) Clustering heatmap analysis of the top 50 microorganism, the font marked in red indicates the gut microbes that were significantly associated with morning and evening inulin interventions were also present in AMIN-CUMS and PMIN-CUMS mice, n = 5. VIP plots of the differential metabolites in (E) AMIN-CUMS group vs CUMS group and (F) PMIN-CUMS group vs CUMS group, n = 3.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/4d3845f7e475ec26d60ec408.png"},{"id":54301107,"identity":"d9d0468d-6ec6-4f8f-ae7d-ea07bcbdc15e","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":519302,"visible":true,"origin":"","legend":"\u003cp\u003eRemodeling the gut microbiome induced improvement of systemic glucose homeostasis in CUMS mice. (A) The levels of glucose in FMT-treated mice, n = 6-8. (B) The levels of insulin in FMT-treated mice, n = 6-8. (C) Immunofluorescence images of p-IRS-1(Ser1101) (red) and DAPI (blue) in FMT-treated mice (200×, scale bar = 100 μm), n = 3. Data are represented as mean ± SEM. Diverse alphabetical forms denote significant differences, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"image13.png","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/94c2d1063a25d4d538861212.png"},{"id":54440278,"identity":"b135bcbe-f7fa-4dde-8909-b2ba70b51618","added_by":"auto","created_at":"2024-04-10 14:54:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6077818,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/2fbf3693-ff73-4c80-b70b-7c75f98442b4.pdf"},{"id":54301792,"identity":"be6fa6ed-6816-4dd1-9c88-6247d883bf83","added_by":"auto","created_at":"2024-04-08 14:37:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2334144,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 1: Figure S1. \u003c/strong\u003eExperimental design. (A) The experimental design of stage 1. (B) The experimental design of stage 2. CUMS: Chronic unpredictable mild stress, FMT: fecal microbiota transplantation, Behavior tests: Sucrose preference test (SPT), open field tests (OFT), light-dark test (LDT), elevated plus-maze test (EPM).\u003c/p\u003e","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/24858a154b9c253f60a07c1c.docx"},{"id":54301092,"identity":"a4f0b1ea-4e87-45e6-b794-0cf0ff0c91d5","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2486095,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 2: Figure S2. \u003c/strong\u003eInulin intervention changed the alpha diversity and composition of intestinal microbiota. (A) Comparison of chao index, shannon index, sobs index and ace index of gut microbiota in different groups. Percent of microbiota abundance on (B) phylum level, (C) class level, (D) order level, (E) family level, (F) genus level. N = 5 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/1974593dde63082471e8a68b.docx"},{"id":54301791,"identity":"47ca477c-3fae-4067-97fc-8c979cedc127","added_by":"auto","created_at":"2024-04-08 14:37:13","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1054513,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 3: Figure S3.\u003c/strong\u003e Boxplots showing differences in relative abundance of sequences according to LEfSe analysis (select the top 50 sequences at genus level). (A) \u003cem\u003eBifidobacterium\u003c/em\u003e, (B) \u003cem\u003enorank_norank_o_Clostridia-UCG-014\u003c/em\u003e, (C) \u003cem\u003eDubosiella\u003c/em\u003e, (D) \u003cem\u003eLigilactobacillus\u003c/em\u003e, (E) \u003cem\u003eColidextribacter\u003c/em\u003e, (F) \u003cem\u003enorank_f_norank_o_RF39\u003c/em\u003e, (G) \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, (H) \u003cem\u003eNK4A214_group\u003c/em\u003e, (I) \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, (J) \u003cem\u003eEnterococcus\u003c/em\u003e, (K) \u003cem\u003eOdoribacter\u003c/em\u003e, (L) \u003cem\u003enorank_f_Eubacterim_coprostanoligenes_group\u003c/em\u003e. *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. CTRL group, n = 5; CUMS group, n = 5; IN group, n = 10.\u003c/p\u003e","description":"","filename":"Additionalfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/19c6b76f9af9193b46b914ce.docx"},{"id":54301099,"identity":"6794cc8d-5afb-4154-81dc-48c71d09cdca","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1266905,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 4: Figure S4.\u003c/strong\u003e Different inulin intervention times produced different influences on the KEGG pathway. Statistical diagram of KEGG pathway classification in (A) AMIN vs CUMS and (B) PMIN vs CUMS. N = 5 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile4.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/9a52f8711fbe0b6f701c90f7.docx"},{"id":54301097,"identity":"8f1f54cb-3d09-400c-b1bf-045c501efa78","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1623815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 5: Figure S5. \u003c/strong\u003eFecal microbiota transplantation restored the disturbed intestinal flora of CUMS mice. (A) Hierarchical clustering tree on OTU level in FMT-treated mice. Boxplots showing differences in relative abundance of sequences in (B) \u003cem\u003eDubosiella\u003c/em\u003e, (C) \u003cem\u003enorank_f_norank_o_Clostridia_ucg-014\u003c/em\u003e, (D)\u003cem\u003eBifidobacterium\u003c/em\u003e, (E) \u003cem\u003eClostridium_sensu_stricto_1\u003c/em\u003e, (F) \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e, (G) \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, (H) \u003cem\u003eOdoribacter\u003c/em\u003e, (I) \u003cem\u003eCoriobacteriaceae_UCG-002\u003c/em\u003e, (J) \u003cem\u003eEnterococcus\u003c/em\u003e, (K) \u003cem\u003eFaecalibaculum \u003c/em\u003ein FMT-treated mice (select the top 50 sequences at genus level). N = 5 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile5.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/3104a9e432a4d8917c6065a1.docx"},{"id":54301102,"identity":"ec4aa626-88cb-4949-bb54-e2e11991d14a","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":2087654,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 6: Figure S6. \u003c/strong\u003eThe effects of fecal microbiota transplantation on KEGG pathway. Statistical diagram of KEGG pathway classification in (A) AMIN-CUMS vs CUMS and (B) PMIN-CUMS vs CUMS. (C) KEGG pathway enrichment significant heatmap of metabolites in AMIN-CUMS vs CUMS and PMIN-CUMS vs CUMS, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. N = 3 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile6.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/da292c16b6562fa8ad3c7642.docx"},{"id":54301100,"identity":"50cd3df7-0154-4e8d-994a-b4b579dd4289","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":3353828,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 7: Figure S7. \u003c/strong\u003eSpearman correlation between the related indicators of metabolites and gut microbiota. Axis label: red, gut microbiota; yellow, LPS in serum and pro-inflammatory cytokines in the serum and hippocampus; cyan, tryptophan, 5-HTP and 5-HT in the serum; purple, amino acid; black, serum metabolites. Within the heatmap region, red indicates positive correlation and blue indicates negative correlation, *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05. N = 3 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile7.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/8ca7fc58c59b244d829c3efe.docx"},{"id":54301101,"identity":"5f4bf65c-0f9f-4656-8ea6-cac03b2f8a7b","added_by":"auto","created_at":"2024-04-08 14:29:14","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":16514,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 8: Table S1. \u003c/strong\u003eSchedule of CUMS stimulation.\u003c/p\u003e","description":"","filename":"Additionalfile8.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/d00251aa185f0830feb22e73.docx"},{"id":54301089,"identity":"a81602fa-1732-4f5e-9174-7f5c07ac6f2c","added_by":"auto","created_at":"2024-04-08 14:29:13","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":17930,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional file 9: Table S2. \u003c/strong\u003eThe shared differential metabolites in CUMS vs CTRL and IN vs CUMS. N = 3 mice/group.\u003c/p\u003e","description":"","filename":"Additionalfile9.docx","url":"https://assets-eu.researchsquare.com/files/rs-4157149/v1/eee16858134cd21f86937077.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evening inulin treatment alleviate anxiety and depression via gut-brain axis: A crucial role for microbiota and amino acids metabolism","fulltext":[{"header":"Background","content":"\u003cp\u003eChronic stress is a prevalent health issue in modern society that often leads to various mental disorders, particularly anxiety and depression [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In recent years, increasing evidence has demonstrated that imbalances in the microbiota-gut-brain axis contribute to the pathogenesis of anxiety and depression [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Certain probiotics and prebiotics have been linked to the alleviation of mood disorders by targeting the microbiota-gut-brain axis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe administration time of drugs to reduce depression and anxiety has been shown to affect their therapeutic potential. The host ingesting rhythms govern intestinal microbiota, which exhibits daily variations in composition and function despite not being continuously exposed to sunlight [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Over the course of a 24-h period, certain microbial species and important compounds generated from microbes experience rhythmed oscillations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These results suggested that the timing of consumption might influence how well prebiotics work; however, the impact of different administration times on intervention effectiveness has been overlooked in many studies. In our previous study, we found that the administration time modified the effect of inulin on chronic unpredictable mild stress (CUMS)-induced anxiety and depression [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; however, it remains unclear if the gut-brain axis exerts a central role in this process.\u003c/p\u003e \u003cp\u003eIn this study, a CUMS-induced mouse model and fecal microbiota transplantation (FMT) combined with 16S rRNA sequencing were applied to investigate the influence of microbiota on the anxiolytic and antidepressant ability of inulin, and the results confirmed that the microbiota-gut-brain axis was critical. More importantly, administration time appeared to personalize the effects of inulin on anxiety- and depression-like behaviors. According to our findings, taking inulin in the evening has a more profound effect on alleviating the inflammatory response and improving amino acid metabolism. This study provides a new potential linking between the microbiota-gut-brain axis and chrono-nutrition, which indicates that a more appropriate administration time results in a better intervention effect.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInulin treatment alleviated CUMS-induced anxiety- and depression-like behaviors\u003c/h2\u003e \u003cp\u003e \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA\u003c/b\u003e provided the detail information about the design of the animal experiments. The weekly body weights of the mice were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The CUMS treatment resulted in a drop of body weight (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but this decrease could be restored in part by supplementing inulin in the morning and evening (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Both morning and evening inulin supplementation markedly increased the preference of sucrose in CUMS mice (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), however the morning inulin intervention (AMIN) showed more promising results (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Mice subjected to CUMS were showed higher propensities to move into the surrounding area, travel shorter distances (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), spend less time at the center part (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and rearing and explore less (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-H. Dietary inulin supplementation considerably improved all of these parameters in comparison to the CTRL mice. In addition, the CUMS-treated mice exhibited a noteworthy rise in the number of open arm entries and duration time following inulin administration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eI-K). And inulin supplementation significantly reduced the time spent by mice in the light compartment compared with the CUMS group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eL). Interestingly, only evening inulin administration (PMIN) increased the number of transitions between the light and dark boxes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e1\u003c/span\u003eM). These findings pointed out that depression- and anxiety-like behaviors could be lessened by inulin supplementation in the morning and evening.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInulin administered in the morning and evening exhibited different effects on inflammation in CUMS-treated mice\u003c/h2\u003e \u003cp\u003eChronic stress was attributed positively to behavioral disorders in previous studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It has been shown to increase intestinal permeability and inflammation, damage the gut barrier, and make it easier for exogenous substances to enter the circulation. Therefore, we investigated the inflammatory responses in the gut, serum, and hippocampal tissues of mice. To further investigate the integrity of the intestinal barrier, immunohistochemical staining was employed to detect the expression of the tight junction protein ZO-1. As indicated in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B, ZO-1 protein reduced in the CUMS group but went up because of inulin treatment. Similarly, supplementation of inulin in the evening (PMIN) significantly suppressed the CUMS-induced increase in serum LPS levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Moreover, inulin supplementation significantly downregulated the levels of pro-inflammatory cytokines induced by CUMS, including TNF-α (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), IL-6 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and IL-1β (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-I). In addition, the PMIN group showed lower levels of inflammatory cytokines than the AMIN group. These results indicated that inulin supplementation can enhance tight junction protein expression and diminish inflammatory symptoms and that the effect of inulin intervention was better in the evening.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInulin treatment modulated the gut microbiota composition in CUMS-treated mice\u003c/h2\u003e \u003cp\u003e16S rRNA sequencing analysis was carried out on bacteria isolated from the cecum of mice to investigate the implications of stress and inulin intervention on the microbiota of the gut. Neither chronic stress nor inulin intervention changed alpha diversity (\u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA-D\u003c/b\u003e). Subsequent review of the beta diversity, the samples were generally divided by groups as determined by PCoA and NMDS analyses, implying that the gastrointestinal microbiotas of the various treatment groups differed considerably from one another, with the exception of the IN (AMIN\u0026thinsp;+\u0026thinsp;PMIN) and CTRL groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B). A Venn diagram revealed that the CTRL, CUMS, and IN groups had identified 1196 OTUs in total, with 136, 84, and 216 distinct OTUs, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eD-F and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eE-F show the average relative abundance profiles of the microbes in all groups. The most prevalent phyla in each group were Firmicutes, Bacteroidota, Actinobacteriota, and Desulfobacteriota, which together accounted for more than 90% of the entire bacterial population (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). Twenty major genera were detected at the genus level in the three groups with different relative abundances (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). These genera included \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eDubosiella\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, and so on.\u003c/p\u003e \u003cp\u003eThe total number of 37 differences (LDA\u0026thinsp;\u0026gt;\u0026thinsp;2) within the three groups discovered by the LEfSe analysis; 18 of them were at the level of genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eI). Compared with other groups, the CUMS group had significantly different relative abundances of \u003cem\u003eDubosiellea\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003eMegamonas\u003c/em\u003e. \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, \u003cem\u003eLimosilactobacillus\u003c/em\u003e, \u003cem\u003eRikenella\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, \u003cem\u003eunclassified_f_Eggerthellaceae\u003c/em\u003e, and \u003cem\u003eunclassified_o_Peptostreptococcales-Tissierellales\u003c/em\u003e were the most abundant genera in the inulin group. Within the CTRL group, the prominent sequences were \u003cem\u003eColitextribacter\u003c/em\u003e, \u003cem\u003eEubacterium_ruminantium_group\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eLigilactobacillus\u003c/em\u003e, \u003cem\u003eNK4A214_group\u003c/em\u003e, \u003cem\u003enorank_f_Erysipelotrichaceae\u003c/em\u003e, \u003cem\u003enorank_f_ Eubacterium_coprostanoligenes_group\u003c/em\u003e, and \u003cem\u003enorank_f_norank_o_RF39\u003c/em\u003e. \u003cb\u003eFigure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e\u003c/b\u003e particularly illustrated how the gut microbiota in the various groups varied in terms of both composition and quantity. A summary of these results, the gut microbiota composition was considerably changed by both the CUMS and inulin treatments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eInulin treatment attenuated alterations in serum metabolites and metabolic pathway in CUMS-treated mice\u003c/h2\u003e \u003cp\u003eAlterations in the composition of gut microbial can influence serum metabolites [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and investigation has been done on the effects of inulin on serum metabolites. In the positive and negative ion modes, 1147 recognized metabolites were found overall in the serum samples. Both score plots of partial least squares discriminant analysis (PLS-DA) constructed on the serum metabolites differentiated the CTRL group from the CUMS group, whereas that of the IN group was more similar to the CTRL group (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), indicating that inulin intervention could modulate the significant changes in the metabolites of CUMS mice. A total of 70 metabolites differed between the CUMS and CTRL groups (VIP\u0026thinsp;\u0026gt;\u0026thinsp;1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), of which 38 were upregulated and 32 downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). When comparing the CUMS and CTRL groups, a total of 29 metabolites exhibited significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), with 21 that were higher and 8 that were lower in inulin intervention mice. In addition, 4\u0026rsquo;-Hydroxyfenoprofen glucuronide, fenofibric acid, and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione were enriched in the serum metabolites of inulin intervention mice.\u003c/p\u003e \u003cp\u003eSerum metabolomic pathway analysis was performed based on the differential metabolites. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eA showed that the enrichment of arginine biosynthesis; alpha-Linolenic acid metabolism; phenylalanine metabolism; pantothenate and CoA biosynthesis; and alanine, aspartate, and glutamate metabolism were significantly different pathways between CUMS and CTRL groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For IN vs. CUMS, phenylalanine metabolism; energy metabolisms; alanine, aspartate, and glutamate metabolism were the significant pathways (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Moreover, KEGG pathway classification showed that the most significant metabolic pathway affected by inulin intervention was amino acid metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Interestingly, we found that the common pathways enriched in the comparisons of CUMS vs CTRL and IN vs CUMS were phenylalanine metabolism, alanine, aspartate, and glutamate metabolism, and pantothenate and CoA biosynthesis. We also identified 14 shared differential metabolites in CUMS vs CTRL and IN vs CUMS, including valproic acid, 14,15-DiHETrE, risbitin, leucylhydroxyproline, pantothenic Acid, L-Phenylalanine, 2-Carboxy-4-dodecanolide, 4-Hydroxy-6-Methyl-2-Pyrone, 4\u0026rsquo;-Hydroxyfenoprofen glucuronide, fenofibric acid, 2-Hydroxypentanoic Acid, N6-Methyl-2'-deoxyadenosine, (2-Hydroxyethoxy)acetic acid, and isocitrate (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, E). Five of these differential metabolites were categorized as carboxylic acids and derivatives, and two were benzene and substituted derivatives (\u003cb\u003eTable \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInulin treatment regulated amino acid metabolism in CUMS-treated mice\u003c/h2\u003e \u003cp\u003eAccumulating evidences suggests that alterations in amino acid content contribute to several mental disorders, including anxiety [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], depression [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and schizophrenia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Serum metabolomics revealed that the ameliorating effects of inulin on CUMS-induced anxiety- and depression-like behaviors were significantly related to amino acid metabolism. Interestingly, the AMIN and PMIN groups showed significant differences in amino acid levels. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the decreased levels of alanine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), glutamic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eE), tyrosine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eO), tryptophane (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eQ), and glycine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eG) in the CUMS mice were attenuated by inulin intervention. Moreover, chronic stress significantly increased the levels of valine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eP) and leucine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eI), whereas inulin treatment restored them to normal levels. Notably, the phenylalanine content (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eL) increased after inulin intervention in the morning and decreased after inulin intervention in the evening. Similarly, the increased levels of aspartic acid (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eC) in the CUMS mice were reduced by inulin intervention in the morning. Amino acids have been found could influence levels of monoamine neurotransmitters (norepinephrine, 5-HT, and dopamine) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], thereby regulating mood and anxiety-like behaviors [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Phenylalanine can be converted to tyrosine, allowing synthesis of neurotransmitters, such as dopamine, epinephrine, and norepinephrine, that regulate nervous system function and maintain psychological balance [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Tryptophan is not only a precursor for the synthesis of serotonin (5-HT), but can also reduce chronic-low inflammation present in schizophrenia, depression and anxiety [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. 5-HT is a monoamine neurotransmitter closely related to anxiety and depression. To further examine the effect of inulin on 5-HT synthesis, we determined the serum levels of tryptophan (5-HTP precursor), 5-HTP (5-HT precursor), and 5-HT. Inulin treatment in the morning and evening significantly upregulated the 5-HTP and increased the biosynthesis of 5-HT (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e6\u003c/span\u003eR, S). Notably, compared with the AMIN group, the PMIN group had higher levels of 5-HTP and lower levels of 5-HT. These results further suggested that inulin treatment in the morning and evening involved the regulation of the serotonin metabolic pathway (tryptophan \u0026rarr; 5-HTP \u0026rarr; 5-HT), and the morning inulin treatment showed higher tryptophan to 5-HT conversion rate.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInulin administration at different times generated different intervention effects on gut microbiota and metabolites in CUMS-treated mice\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn order to investigate the differences between morning and evening inulin interventions on CUMS-induced behaviors related to anxiety and depression, we compared the gut microbiota composition, metabolites, and metabolic pathways between the two treatment groups and the CUMS group. LEfSe analysis showed that both morning and evening inulin interventions significantly increased the levels of \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, and \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e in contrast to that in CUMS mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, B). We also analyzed the microbial differences between the AMIN and PMIN groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eC-H), and the PMIN group exhibited a higher level of \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e compared with the other groups, whereas the AMIN group showed a significantly elevated relative abundance of \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e in comparison to the PMIN group. In addition, compared with the AMIN group, the PMIN group was significantly enriched in \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e. Conversely, the AMIN group demonstrated a significantly higher level of \u003cem\u003eFaecalibaculum\u003c/em\u003e and \u003cem\u003eCoriobacteriaceae_UCG-002\u003c/em\u003e than did the PMIN group. Correlation analysis showed that neuroinflammation and the gut barrier were positively correlated with the abundance of \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e and negatively correlated with the abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eFaecalibaculum\u003c/em\u003e, and \u003cem\u003eCoriobacteriaceae_ucg-002\u003c/em\u003e. The degree of normal behaviors and neurotransmitter appeared adversely correlated with the abundance of \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e, and favorably connected with \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eFaecalibaculum\u003c/em\u003e, and \u003cem\u003eCoriobacteriaceae_UCG-002\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e7\u003c/span\u003eI).\u003c/p\u003e \u003cp\u003eThe metabolites of the morning and evening inulin intervention groups were analyzed separately from those of the CUMS group. Metabolomics analysis found that AMIN vs CUMS and PMIN vs CUMS shared 3 different metabolites, including 4\u0026rsquo;-Hydroxyfenoprofen glucuronide, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, and trimethylamine N-Oxide (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-D). The contents of 8 differential metabolites, such as fenofibric acid, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, and 4\u0026rsquo;-Hydroxyfenoprofen glucuronide, were substantially higher in the AMIN group as opposed to the CUMS group, as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003eB. In contrast, the contents of 5 differential metabolites significantly decreased. After comparing the PMIN group with CUMS group, the contents of 19 differential metabolites including 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione and 4\u0026rsquo;-Hydroxyfenoprofen in the PMIN group were significantly increased, and the contents of 15 metabolites significantly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Notably, both the morning and evening inulin treatments significantly elevated the levels of trimethylamine N-Oxide and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione levels. Moreover, chronic stress significantly increased the levels of serum glucose, but significantly reduced them after inulin intervention, which may be related to the low levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in the AMIN and PMIN groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003eE). Correlation analysis of the gut microbes and metabolites showed that trimethylamine N-Oxide, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, PC(20:5/0:0), 4\u0026rsquo;-Hydroxyfenoprofen glucuronide, valproic acid, fenofibric acid, lysoPC(18:0/0:0), 2-(Hydroxyethoxy)acetic acid, risbitin, 2-Hydroxypentanoic Acid, and stercobilin were negatively correlated with \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e. Notably, 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione was considerably and positively related to \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, and \u003cem\u003eFaecalibaculum\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e8\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003eWe separately compared the effects of morning and evening inulin treatments on the metabolic pathways in CUMS-treated mice. KEGG pathway classification showed that inulin intervention in the evening was more likely to influence amino acid metabolism (\u003cb\u003eFigure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e\u003c/b\u003e). Analyses of metabolic pathways using the metabolites that differ in abundance between AMIN vs CUMS and PMIN vs CUMS, indicating that inulin intervention in the morning significantly influenced the citrate cycle (TCA), ether lipid metabolism, glycerophospholipid metabolism, and glyoxylate and dicarboxylate metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eA), whereas inulin intervention in the evening significantly modulated phenylalanine metabolism; glycerophospholipid metabolism; pantothenate and CoA biosynthesis; valine, leucine and isoleucine biosynthesis; and alanine, aspartate and glutamate metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eB). A heatmap of the KEGG metabolic pathways of significantly altered metabolites showed that choline metabolism in cancer, glycerophospholipid metabolism, and central carbon metabolism in cancer were enriched in AMIN vs CUMS and PMIN vs CUMS (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). We also found that amino acid metabolism, including phenylalanine, tyrosine, and tryptophan biosynthesis, beta-alanine metabolism, and tyrosine metabolism, were affected by evening inulin intervention compared to the morning inulin intervention (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). Correlation analysis showed that alanine, glutamic acid, phenylalanine, tyrosine, and tryptophane were adversely corresponding to \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e and favorably connected with \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e, \u003cem\u003eFaecalibaculum\u003c/em\u003e, and \u003cem\u003eCoriobacteriaceae_UCG-002\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eD). Notably, gut microorganisms enriched in the PMIN group showed a stronger correlation with amino acids than did the AMIN group, indicating that inulin intervention in the evening was more likely to affect amino acid metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eReconstruction of gut microbiota with inulin rescued the behavioral abnormalities in CUMS-treated mice\u003c/h2\u003e \u003cp\u003eTo verify whether the reduction of anxiety and depression was facilitated by the inulin-associated gut microbiota, fecal microbiota from AMIN and PMIN mice were transplanted into CUMS-treated mice pretreated with an antibiotic cocktail. Behavioral tests were performed after the recolonization period. Figure\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eA showed the weekly body weights of all groups. Transplanting fecal microbiota did not alter the mice's body weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eB). In comparison to the CUMS-treated mice, mice that acquired inulin mice microbiota (AMIN-CUMS and PMIN-CUMS) exhibited increased sucrose preference (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eC). The OFT results showed that the reduction in the central region trajectory (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eD), total distance (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eE), center part duration time (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eF), number of rearing (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eG), and number of explorations (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eH) in CUMS-treated mice was reversed by fecal microbiota transplantation. The EPM data revealed that the decrease of spontaneous exploration ability observed in CUMS-treated mice was blocked by fecal microbiota treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eI-K). Moreover, the center part duration time, the number of explorations in the OFT, and the open arm duration time in the EPM were higher in CUMS-treated mice that received AMIN-derived fecal microbiota than CUMS-treated mice that received PMIN-derived fecal microbiota. The LDT showed that the increased time spent in the light compartment in CUMS-treated mice was decreased by fecal microbiota transplantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eL). The number of transitions in the LDT was similar between groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eM). Simultaneously, fecal microbiota transplantation remarkably raised the levels of tryptophan, 5-HTP, and 5-HT in the serum of recipient mice that obtained fecal microbiota from inulin-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003eN-P). These results highlighted that FMT improves CUMS-induced anxiety- and depression-like behaviors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTransplantation of fecal microbiota from mice that received morning and evening inulin interventions presented distinct effects on CUMS-treated mice\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further explore the underlying mechanism of the anxiolytic and antidepressant effects of inulin, we measured the inflammatory response in serum, and hippocampus of recipient mice treated with inulin mice microbiota (AMIN-CUMS and PMIN-CUMS), and the expression of ZO-1 in intestine were also investigated. Compared with the CUMS-treated mice, the levels of ZO-1 in the colon tissue were higher in microbiota-depleted mice that got fecal microbiota from inulin-treated mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eA), and the relative intensity of ZO-1 fluorescence in PMIN-CUMS group was stronger than that in AMIN-CUMS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eB). Consistent with the results of the inulin intervention groups, serum LPS levels were inhibited by fecal microbiota transplantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eC). In addition, fecal microbiota transplantation dramatically reduced the expression of IBA-1 in the hippocampus of CUMS mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eD), and PMIN-CUMS mice showed a significantly lower relative intensity of IBA-1 fluorescence than AMIN-CUMS mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eE). Moreover, fecal microbiota transplantation significantly decreased the levels of inflammatory cytokines (TNF-α, IL-6, and IL-1β) in serum and hippocampus of mice treated with CUMS (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e11\u003c/span\u003eF-K). Interestingly, recipient mice that acquired fecal microbiota from the evening inulin intervention group (PMIN-CUMS) showed lower levels of inflammatory cytokines than those receiving fecal microbiota from the morning inulin intervention group (AMIN-CUMS). These results indicated that the respective advantages of morning and evening inulin interventions were also reflected in recipient mice transplanted with fecal microbiota.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eGut microbiome and serum metabolites of CUMS-treated mice were modified during reconstruction procedure\u003c/h2\u003e \u003cp\u003eInulin administration in the morning and evening modulated the composition of gut microbiota and serum metabolites in mice with anxiety- and depression-like behaviors. It was worth exploring whether these characteristic metabolites and microbes could be detected in recipient mice after fecal bacterial transplantation. From the beta diversity, PCoA and NMDS showed that the circles of the inulin intervention group (IN) and fecal microbiota transplantation group (FMT) were clustered (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e12\u003c/span\u003eA-C), indicating the gut microbiome of the recipient mice was similar to that of the donor mice. In addition, the clustering tree also showed that the distance between the AMIN and AMIN-CUMS groups was relatively close, and the distance between the PMIN and PMIN-CUMS groups was relatively close, indicating that the effect of inulin intervention time on intestinal microbes was reflected in the intestinal flora of the recipient mice (\u003cb\u003eFigure \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eA\u003c/b\u003e). We further analyzed the microorganisms at the genus level in the recipient mice. We found that the gut microbes that were significantly associated with morning and evening inulin interventions were also present in their respective recipient mouse gut microbes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e12\u003c/span\u003eD, \u003cb\u003eFigure \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003eB-K\u003c/b\u003e). For example, the levels of \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eDubosiella\u003c/em\u003e, and \u003cem\u003eClostidium_sensu_stricto_1\u003c/em\u003e in recipient mice were significantly lower than those in CUMS-treated mice. Moreover, the lower relative abundances of \u003cem\u003enorank_f_norank_o_Clostridia-UCG-014\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eCoribacteriaceae_UCG-002\u003c/em\u003e, \u003cem\u003eFaecalibaculum\u003c/em\u003e, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e, and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e in the CUMS-treated mice were reversed by fecal microbiota transplantation. The dominant bacteria \u003cem\u003eCoribacteriaceae_UCG-002\u003c/em\u003e and \u003cem\u003eFaecalibaculum\u003c/em\u003e in the AMIN group were also present in the CUMS-AMIN group, and the dominant bacteria \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e were also present in the CUMS-PMIN group.\u003c/p\u003e \u003cp\u003eWe also analyzed the serum metabolites of recipient mice. \u003cb\u003eFigure \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003e\u003c/b\u003e showed the KEGG pathway enrichment for recipient mice (AMIN-CUMS and PMIN-CUMS) compared with CUMS mice. The KEGG pathways related to amino acids, including phenylalanine metabolism; aminoacyl-tRNA biosynthesis; phenylalanine, tyrosine and tryptophan biosynthesis; valine, leucine and isoleucine degradation; beta-Alanine metabolism; alanine, aspartate and glutamate metabolism; valine, leucine and isoleucine biosynthesis; and tyrosine metabolism, were enriched in the PMIN-CUMS group. The TCA cycle, drug metabolism-cytochrome P450, bile secretion, glucagon signaling pathway, ether lipid metabolism, and glyoxylate and dicarboxylate metabolism were significantly enriched in the AMIN-CUMS group. Notably, the KEGG pathway enrichment heatmaps for AMIN-CUMS vs CUMS and PMIN-CUMS vs CUMS (\u003cb\u003eFigure \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003eC\u003c/b\u003e) were consistent with those of AMIN vs CUMS and PMIN vs CUMS (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). In addition, we compared differential metabolites between the two groups of recipient mice and CUMS-treated mice. From the VIP chart, it could be observed that there was a significant increase of 4\u0026rsquo;-Hydroxyfenoprofen glucuronide and fenofibric acid contents in AMIN-CUMS group compared to CUMS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e12\u003c/span\u003eE). The low concentrations of these two metabolites in CUMS-treated mice were reversed by inulin intervention. Among the differential metabolites between PMIN-CUMS and CUMS, the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione were highest in the PMIN-CUMS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e12\u003c/span\u003eF). Similarly, inulin treatment in the morning and evening significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione as compared with the CUMS group.\u003c/p\u003e \u003cp\u003eBecause 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione is the M-Ⅰ metabolite of pioglitazone [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], we also measured the glucose homeostasis in the fecal microbiota transplantation groups. Similarly, fecal microbiota transplantation reduced glucose levels in CUMS-treated mice, and the effect was more pronounced in the PMIN-CUMS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e13\u003c/span\u003eA), which may be correlated with PMIN-CUMS having higher levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione. Moreover, CUMS mice showed considerably reduced serum insulin levels compared with control mice, indicating that chronic stress could induce insulin resistance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e13\u003c/span\u003eB). The level of the phosphorylated insulin receptor (p-IRS-1 ser11001) in the hippocampus was elevated after chronic stress, which was significantly decreased by the transplantation of microbiota from PMIN mice to CUMS mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e13\u003c/span\u003eC). These results suggest that evening inulin intervention is effective for improving insulin resistance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eA wide variety of biological systems, such as neurological, gastrointestinal, physiological, and behavioral activities, are influenced by circadian clocks [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Consequently, different prebiotic consumption times may have varying potential benefits for alleviating stress-induced anxiety and depression. According to our previous study, the effects of inulin on anxiety and depression could be altered by the administration time and the dietary patterns [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In this study, the underlying mechanisms of how inulin regulates the microbiota-gut-brain axis and the potential link between the microbiota-gut-brain axis and chrono-nutrition were investigated. The results confirmed that the microbiota-gut-brain axis plays a central role in the anxiolytic property of inulin, and inulin administration in the evening produced a more pronounced effect in alleviating inflammatory response and improving amino acid metabolism.\u003c/p\u003e \u003cp\u003eAnxiety and depression have a strong connection with inflammatory response. In this study, inulin intervention in the evening appeared to be more effective in alleviating the inflammatory response, manifested by decreased levels of pro-inflammatory cytokines and LPS and increased expression of ZO-1 compared to inulin intervention in the morning. LPS could be released from the intestine and enter the circulatory system as a result of increased intestinal permeability [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Furthermore, by attaching to Toll-like receptor-4 (TLR4), LPS may lead to the production of pro-inflammatory cytokines [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Indeed, some inflammatory signals can serve as sensors for microbial clocks, with potential roles in coordinating host circadian rhythms, inflammation, and metabolism [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. There are diurnal rhythms to pro-inflammatory cytokines, with the morning and evening displaying different inflammatory states [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which could explain why inulin showed different effects on the inflammatory response in CUMS mice at different intervention times. Consistent with our findings, Kalmukova et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found that melatonin administration in the evening was more efficient in decreasing pro-inflammatory cytokine levels than morning administration in obese rats. Moreover, compared with the CUMS mice that received fecal microbiota from morning inulin intervention mice (AMIN-CUMS), the mice that received fecal microbiota from evening inulin intervention mice (PMIN-CUMS) also displayed lower levels of TNF-α, IL-1β, and IL-6, indicating that the benefits of evening inulin intervention for reducing inflammation were significantly influenced by gut microbiota.\u003c/p\u003e \u003cp\u003eThe FMT experiments confirmed that the gut microbes affected by inulin administration feature an indispensable part in relieving anxiety and depression. The microbial community structure in the CUMS group differed significantly from that in the CTRL group, manifested by a significant increase in the relative abundance of \u003cem\u003eDubosiella\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e; however, this trend was reversed after inulin treatment and gut microbiota reconstruction. There are evidences to suggest that following periods of unpredictable chronic mild stress, the relative abundance of \u003cem\u003eEnterococcus\u003c/em\u003e in mouse feces becomes higher [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. \u003cem\u003eEnterococcus\u003c/em\u003e can produce large amounts of d-lactate in the gut, which may impair brain function. \u003cem\u003eDubosiella\u003c/em\u003e is positively correlated with markers of inflammatory response and glycolipid metabolism disorders [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In addition, we found that inulin administration significantly increased the levels of \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e, and \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e in the feces of CUMS-treated mice. Furthermore, increases in \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e were also found in the gut microbes of recipient mice that received the fecal microbiota from inulin-treated mice. Notably, the relative abundances of \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e were higher in the PMIN and PMIN-CUMS groups. Clinical studies have shown that \u003cem\u003eBifidobacterium\u003c/em\u003e spp. supplementation can relieve symptoms of anxiety and depression [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. \u003cem\u003ePulsatilla chinensis\u003c/em\u003e saponins alleviated inflammation in a rat model of ulcerative colitis, which may be ascribed to an increase in beneficial bacteria such as \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Similarly, long-term consumption of stachyose ameliorated HFD-associated colonic inflammation by increasing the proportion of \u003cem\u003eChristensenellaceae_R-7_group\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Therefore, probiotics that alleviated inflammation via the gut microbiota could also be ideal targets for relieving anxiety and depression. Consistent with these studies, our findings revealed that the increased bacteria in the CUMS group were positively associated with inflammation, whereas the decreased bacteria in the CUMS group were negatively correlated with inflammation. Our results also showed that microbiota abundant in the PMIN and PMIN-CUMS group (\u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e) were substantially inversely connected with pro-inflammatory cytokines (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas the microbiota enriched in the AMIN and AMIN-CUMS group (\u003cem\u003eFaecalibaculum\u003c/em\u003e and \u003cem\u003eCoriobacteriaceae_UCG-002\u003c/em\u003e) were not significantly negatively correlations with the pro-inflammatory cytokines. Previous studies have shown that the intestinal microbiota undergoes diurnal oscillations under the control of host feeding time [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Here, we reported that the intervention time of inulin influenced microbial composition, and the effect of the intestinal microbiome on the inflammatory response was more prominent in the evening inulin intervention group and the FMT group that received PMIN fecal microbiota.\u003c/p\u003e \u003cp\u003eDisturbances in amino acids have been implicated in various neuropsychiatric disorders, including anxiety, depression, cognitive impairment, and chronic fatigue syndrome [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Most amino acids showed a tendency to vary rhythmically over the course of the 24-hour day [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our current investigation revealed that long-term stress disturbed amino acid metabolism, which was relieved by inulin intervention. Indeed, inulin intervention in the evening had a more prominent influence on amino acid metabolism than in the morning, and this effect was also observed in the FMT experiments. A previous study [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] showed the gut microbiota significantly influence plasma metabolites, and amino acid metabolites being particularly affected. Notably, the gut microbiota has the ability to facilitate the synthesis and consumption of amino acids, which can be absorbed throughout the digestive tract and then accumulated in the plasma [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The intestinal microbiota exhibited daily cyclical fluctuations, suggesting that the effects of different intervention times on amino acids may be due to different microbes present in the morning and evening. The dominant bacterium in the morning inulin intervention group, \u003cem\u003eFaecalibaculum\u003c/em\u003e, a potentially beneficial bacterium that can relieve anxiety- and depression-like behaviors [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], has a significant positive correlation with tryptophan and 5-HT. Similarly, Deng et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] discovered a positive correlation between \u003cem\u003eFaecalibacterium\u003c/em\u003e and sociability as well as 5-HT pathway components in metformin-treated mice. In terms of the levels of 5-HTP and 5-HT in the inulin intervention and FMT groups, we found that both the AMIN and AMIN-CUMS mice exhibited higher tryptophan to 5-HT conversion rates. The prominent microorganisms in the evening inulin intervention group, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e, positively correlated with tryptophan, alanine, tyrosine, glycine, and histidine levels. Tyrosine and tryptophan are typical aromatic amino acids that are metabolized by Lachnospiraceae, which is one of the main microbial pathways in the human gut that produces indole-propionic acid, indole, phenol, and p-cresol [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In addition, Lachnospiraceae has been found to be significantly associated with attenuating inflammation in obese [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and CUMS mice [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Consistent with previous research, \u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e were drastically and poorly associated with pro-inflammatory cytokines. In addition, microbiota, including \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eClostridium\u003c/em\u003e spp., \u003cem\u003eBacteroides\u003c/em\u003e spp., and \u003cem\u003eBifidobacterium\u003c/em\u003e spp., can produce enzymes responsible for tryptophan catabolism [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Furthermore, \u003cem\u003eBifidobacterium longum\u003c/em\u003e has been observed to decrease the concentrations of TNF-α, IL-1β, IL-6 via mediating tryptophan metabolism [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. We also found that the amino acids, influenced by inulin intervention in the evening, were substantially negatively associated with pro-inflammatory cytokines (\u003cb\u003eFigure \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003e\u003c/b\u003e). These results suggested that the remission effect of evening inulin intervention on anxiety- and depression-like behaviors may be related to gut microbes reducing inflammation by influencing amino acid metabolism.\u003c/p\u003e \u003cp\u003eMoreover, gut microflora directly affect the possibility of drug metabolism of the host [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Within our research, the AMIN and AMIN-CUMS groups showed significantly influenced drug metabolism-cytochrome P450 (CYP) and lipid metabolism compared with the PMIN and PMIN-CUMS groups. Fenofibric acid, an agent for decreasing lipid in the blood, has been shown to be a potent inhibitor of cytochrome CYP 2C [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Indeed, the host gut microbiota may have an effect on the majority of CYP enzymes, which participate in hormone and lipid metabolism, and detoxification [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Furthermore, CYP are crucial for the regulation of the biological clock and circadian rhythm [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Fenofibric acid exerts neuroprotective effects against cognitive impairment in Parkinson\u0026rsquo;s disease [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Moreover, 4\u0026rsquo;-Hydroxyfenoprofen glucuronide is involved in the synthetic pathway of fenoprofen [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Fenoprofen has been widely used as an anti-inflammatory and analgesic drug [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Similarly, connection investigation on 4\u0026rsquo;-Hydroxyfenoprofen glucuronide demonstrated a substantial negative relationship to TNF-α and LPS. Notably, fenofibric acid and 4\u0026rsquo;-Hydroxyfenoprofen glucuronide are organic acids containing phenyl groups. A recent study concluded that the presence of gut microorganisms greatly boosted the levels of certain organic acids containing phenyl groups [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The fenofibric acid showed a positive correlation with the bacteria in the AMIN group (\u003cem\u003eFaecalibacterium\u003c/em\u003e and Coriobacteriaceae_UCG-002), while a negative correlation with the microbiota in the PMIN group (\u003cem\u003euncultured_f_Lachnospiraceae\u003c/em\u003e and \u003cem\u003eunclassified_f_Lachnospiraceae\u003c/em\u003e). These results suggested that inulin intervention in the evening is more effective at alleviating inflammation and damaging the gut barrier.\u003c/p\u003e \u003cp\u003eIn addition, inulin intervention in the morning and evening significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in the CUMS-treated mice, accompanied by lower glucose concentrations in both groups. Transplanting the fecal microbiota from evening inulin intervention mice into CUMS-treated mice also significantly increased the levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione; however, this trend was not observed in the other FMT group. 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, a pioglitazone metabolite, is significantly associated with glucose levels. Mood swings, including anxiety, depression, and nervousness, cause the body to release more stress hormones (such as cortisol, thyroid hormones, and adrenal hormones), which can lead to insulin resistance [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Our findings revealed that evening inulin treatment considerably decreased serum glucose and insulin levels. The expression of p-IRS-1 in the hippocampus was also decreased by the evening inulin intervention. Similarly, Chaihu-shugan, a traditional Chinese medicine, has antidepressant activity and improves glucose tolerance by reducing serum glucose levels in CUMS rats [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In addition, the circadian system affects glucose tolerance by regulating the digestion, absorption, and metabolism of the stomach and intestines according to the time of day [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. In this study, the lower levels of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione in CUMS-treated mice were reversed by microbiome recolonization. 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione exhibited a notable negative correlation with \u003cem\u003eDubosiella\u003c/em\u003e and pro-inflammatory cytokines, while displaying a significant positive correlation with \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003enorank_f_norank_o_Clostridia_UCG-014\u003c/em\u003e (Figure \u003cspan refid=\"MOESM7\" class=\"InternalRef\"\u003eS7\u003c/span\u003e). This suggests that the gut bacteria may be a participant in the production of 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione, which also provides a potential underlying mechanism for effects of inulin.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the results indicate that the microbiota-gut-brain axis plays a central role in the anxiolytic ability of inulin. Administration time seemed to modify the anxiolytic and antidepressant effects of inulin, and inulin intervention in the evening was more pronounced in improving amino acid metabolism and insulin resistance and inhibiting the inflammatory response. This study provides a new potential linking between the microbiota-gut-brain axis and chrono-nutrition, which may provide novel ideas for precision intervention in mood and behavioral disorders.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n\u003ch2\u003eAnimals\u003c/h2\u003e\n\u003cp\u003eMale C57BL/6 mice weighing 20\u0026thinsp;\u0026plusmn;\u0026thinsp;1 g were acquired from Huazhong Agricultural University\u0026rsquo;s Animal Experiment Center in Wuhan, China. The mice were kept in conventional settings with five mice per cage, 50\u0026thinsp;\u0026plusmn;\u0026thinsp;2% relative humidity, 23\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C temperature, 12 h of light and dark, and unrestricted access to food and drink. Before the tests began, all of the mice were given a week to become used to their new surroundings. The ethics committee of the Animal Experiment Center at Huazhong Agricultural University accepted the use of mice in this research, which followed the Chinese Council on Animal Care Guidelines.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eCUMS procedure\u003c/h2\u003e\n\u003cp\u003eThe CUMS process was performed as our previous research [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e]. In brief, the procedure comprised the following 9 stressors: water and food deprivation (24 h), 45\u0026deg; cage tilt (24 h), restraint in the box (4 h), day and night reversal (24 h), wet bedding (24 h), tail pinch (3 min, 1 cm from the end of the tail), 45℃ high temperature (5 min), empty cage (no bedding placed, 24 h), shake cage (6 min). The stressors were applied randomly and were not repeated for two consecutive days, and repeated every seven days (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e.).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eExperimental design\u003c/h2\u003e\n\u003cp\u003eThe experiments involved in this study were divided into 2 stages: CUMS modeling and inulin treatment, as well as fecal microbiota transplantation (FMT) (Figure \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eStage 1\u003c/h2\u003e\n\u003cp\u003eSixty mice were randomly assigned to four groups for the CUMS modeling and inulin treatment experiments: a model group (CUMS, n\u0026thinsp;=\u0026thinsp;30), a morning (7:30\u0026ndash;8:00 am) inulin administered group (AMIN, n\u0026thinsp;=\u0026thinsp;10), an evening (7:30\u0026ndash;8:00 pm) inulin administered group (PMIN, n\u0026thinsp;=\u0026thinsp;10), and a control group not subjected to any stress (CTRL, n\u0026thinsp;=\u0026thinsp;10). The inulin dose administered was 4 g/kg/day. A weekly measurement of the body weight was made. All of the mice performed a week-long battery of behavioral tests following eight weeks of CUMS.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eStage 2\u003c/h2\u003e\n\u003cp\u003eIn FMT [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e], 20 mice in the CUMS group split into two groups at random: a recipient group received fresh fecal samples from AMIN group mice (AMIN-CUMS, \u003cem\u003en\u0026thinsp;=\u0026thinsp;10\u003c/em\u003e), and a recipient group received fresh fecal samples from PMIN group mice (PMIN-CUMS, \u003cem\u003en\u0026thinsp;=\u0026thinsp;10\u003c/em\u003e). A combination of 200 mg/kg of ampicillin, 200 mg/kg of metronidazole, 200 mg/kg of neomycin, and 100 mg/kg of vancomycin was gavaged daily for eighteen days to the mice in FMT groups [\u003cspan class=\"CitationRef\"\u003e63\u003c/span\u003e]. Following three days of washout, the recipient mice received 200 \u0026micro;L of the donor's fresh fecal supernatant, which was obtained from either AMIN or PMIN, orally every day for a period of 14 days. After a 14-day period of recolonization, the behavior tests were carried out. Weight was recorded weekly and behavioral tests were taken in the same manner as in stage 1. One day after behavioral testing, the mice were sacrificed and orbital blood samples were taken. The serum, hippocampus, and cecum content were rapidly collected for further investigations.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eBehavioral testing\u003c/h2\u003e\n\u003cp\u003eTesting was done in accordance with the guidelines in our earlier report [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. The formula used to compute the sucrose preference (%) in the sucrose preference test (SPT) was sucrose intake (g)/ [sucrose intake (g)\u0026thinsp;+\u0026thinsp;water intake (g)] \u0026times; 100%. In the open field test (OFT), the distance traveled, number of rearing and explorations, and center part duration time were used to evaluate spontaneous ability of mice. Orientation behavior and exploring abilities of mice in both bright and dark environments were evaluated in the light-dark test (LDT) using the time consumed in the bright chamber and the quantity of transitions. Natural exploratory behavior in a novel environment was measured for the elevated-plus maze test (EPM) using the length time and the quantity of entrances into open arms.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003eQuantitative analysis of serum amino acids\u003c/h2\u003e\n\u003cp\u003eWith minor adjustments, serum amino acid quantification using ultra-performance liquid chromatography tandem triple quadrupole mass spectrometry (UHPLC-MS/MS) was performed in accordance with previously published procedures [\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e65\u003c/span\u003e]. A Waters X Bridge Amide column (100 \u0026times; 2.1 mm, 3.5 \u0026micro;m) was used for the analyses, and 1 \u0026micro;L of injection volume was used. Composition of the mobile phases were water: formic acid (99.9:0.1, v/v) (mobile phase A) and acetonitrile: formic acid (99.9:0.1, v/v) (mobile phase B). The run time was set to 18 min, with a flow rate of 0.25 mL/min. The steps involved in gradient elution were as follows: 92% B for 3 min; decreased to 85% B in 3 min; decreased to 65% B in 3 min; and held at 65% B for 5 min. Within the next 4 min, the gradient returned linearly to the initial condition and was maintained for 10 min for rebalancing. The column oven temperature was adjusted to 40 ℃. IRS: sweep type, positive mode; spray voltage, 5500 V; nebulizer pressure, 50 psi; and capillary temperature, 320℃.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eELISA analysis\u003c/h2\u003e\n\u003cp\u003e5-HT, 5-HTP, IL-1\u0026beta;, IL-6, TNF-\u0026alpha;, and LPS were determined by ELISA in serum and hippocampus (Shanghai Huding Biological Technology Company, Shanghai, China), in accordance with manufacturer guidelines. In cold PBS containing 1% PMSF, the hippocampus of every mouse was homogenized. The supernatant was extracted following a 15-minute centrifugation process at 4\u0026deg;C and 12,000 rpm. Elabscience's BCA assay kit (E-BC-K318-M) was utilized to quantify the amount of protein.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n\u003ch2\u003e16S rRNA amplicon and sequencing\u003c/h2\u003e\n\u003cp\u003eThe sequencing service was provided by Majorbio Bio-Pharm Technology Co., Ltd., Shanghai, China. In brief, the Kruskal-Wallis test was applied to analyze alpha diversity in the study of 16S rRNA sequencing data, and FDR multiple comparisons were then performed. PCoA and NMDS were utilized to display the beta diversity, which was computed using binary Pearson dissimilarity. Circular Packing and River charts were used to illustrate the taxonomic transitions between groups at the phylum and genus levels. To determine whether bacterial groupings had significantly varied levels of abundance from phylum to genus across the different groups, the LEfSe (LDA\u0026thinsp;\u0026gt;\u0026thinsp;2, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was utilized. Furthermore, the Wilcoxon rank-sum test was employed to examine variations among two groups at the genus level.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n\u003ch2\u003eMetabolomics analysis\u003c/h2\u003e\n\u003cp\u003eUsing a Waters Acquity UPLC system connected to a Q-Exactive HF-X mass spectrometer with electrospray ionization in both positive and negative ionization modes, untargeted metabolomics of the serum was carried out. Progenesis QI (Waters Corporation, Milford, USA) was used to prepare the raw data files for analysis. The HMDB and Metlin databases were used for matching. The untargeted metabolomics profiling was supplied by Majorbio Bio-pharm Technology Co., Ltd., Shanghai, China. For the metabolomics data, the R package ropls was employed to carry out PLS-DA. According to the VIP derived using the PLS-DA model and the p-value produced by the Student\u0026rsquo;s-t test, metabolites with VIP\u0026thinsp;\u0026gt;\u0026thinsp;1 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were concluded to be substantially distinct metabolites. The KEGG database was utilized for metabolic enrichment and pathway analysis, whereby the differing metabolites of two groups were divided into corresponding biochemical pathways. In accordance with the pathways and functions that they perform, the metabolites were categorized.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical analysis\u003c/h2\u003e\n\u003cp\u003eSoftware from GraphPad Prism (version 8.0) and SPSS 25.0 were used for the analyses. Data are represented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. An ANOVA analysis was performed on all the data, and then the Tukey-Kramer test was conducted. Clustering heat map analysis displayed the distribution of indicators between different groups intuitively according to color. The associations between markers linked to behavior, the gut, metabolism, and the brain were investigated using Spearman's correlation analysis. ImageJ software was used to analyze the relative fluorescence intensity. A threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was established for statistical significance.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eCUMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eChronic unpredictable mild stress\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eSucrose preference test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOFT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eOpen field test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eEPM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eElevated plus maze test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLDT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLight-dark box test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eFMT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003efecal microbiota transplantation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e5-HTP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e5-hydroxytryptophan\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePCoA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePrincipal coordinate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNMDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eNon-metric multidimensional scaling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePLS-DA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003ePartial least squares discriminant analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLEfSe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLinear discriminant analysis effect size\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eVIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eVariable importance in the projection\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003eLipopolysaccharides\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (32372326) and the Fundamental Research Funds for the Central Universities (2662020SPPY004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.P. performed the research, analyzed the data, and wrote the main manuscript. C.F.Y, H.T., and H.X.Q. analyzed the data and wrote the manuscript. X.C.X., Z.J.M., and S.S.S. designed the research study, analyzed and interpreted the data. L.C.M. reviewed and edited the manuscript. L.K.K. contributed to the experimental design and drafting and critical revision of the manuscript. The authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis publication and its additional information files contain all the data generated or processed during this research. The raw Illumina sequence information has been uploaded to the NCBI Sequence Read Archive (SRA) with accession number PRJNA1085102.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethics committee at Huazhong Agricultural University\u0026rsquo;s Animal Experiment Center accepted all mouse experimentation protocols (HZAUMO-2022-0131), which followed the Chinese Council on Animal Care Guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLupien SJ, McEwen BS, Gunnar MR, et al. Effects of stress throughout the lifespan on the brain, behaviour and cognition. 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Food Chemistry. 2014;158:88-92.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Inulin, chrono-nutrition, microbiota, CUMS, FMT","lastPublishedDoi":"10.21203/rs.3.rs-4157149/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4157149/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIncreasing evidence has demonstrated that an imbalance in the microbiota-gut-brain axis exerts an essential effect on the pathophysiology of depressive and anxiety disorders. Our previous research revealed that the timing of inulin administration altered its influence on CUMS-induced anxiety and depression; however, it is still unclear if the gut-brain axis is primarily responsible for these effects.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSerum metabolomics analysis showed that inulin treatment can alleviate the inflammatory response in CUMS-treated mice and that amino acid metabolic pathways were crucial for its anxiolytic and antidepressant effects. The time of administration seemed to modify the anxiolytic and antidepressant effects of inulin, and inulin intervention in the evening was more pronounced in improving amino acid metabolism and inhibiting the inflammatory response than that of morning inulin treatment. In addition, inulin treatment in the evening significantly reduced serum glucose and insulin levels. The main differential metabolites, including fenofibric acid, 4\u0026rsquo;-Hydroxyfenoprofen glucuronide and 5-(4-Hydroxybenzyl)thiazolidine-2,4-dione may play important roles for the anxiolytic and antidepressant ability of inulin. Fecal microbiota transplantation confirmed that inulin treatment alleviated CUMS-induced anxiety- and depression-like behaviors via gut-brain axis.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur results suggest that inulin administration in the evening is more effective in alleviating the inflammatory response and improving amino acid metabolism. This study provides a new potential link between the microbiota-gut-brain axis and chrono-nutrition, which indicates that a more appropriate administration time results in a better intervention effect.\u003c/p\u003e","manuscriptTitle":"Evening inulin treatment alleviate anxiety and depression via gut-brain axis: A crucial role for microbiota and amino acids metabolism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 14:29:07","doi":"10.21203/rs.3.rs-4157149/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3d7f59d5-5c52-4766-bb1b-d039f527795c","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-10T14:46:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 14:29:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4157149","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4157149","identity":"rs-4157149","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}