DSS-induced colitis activates the kynurenine pathway in serum and brain by affecting IDO-1 and gut microbiota

To verify the successful induction of IBD in mice, H&E staining of colon tissue was performed. Significant inflammatory infiltration was found in the mucosal layer after 2% DSS treatment, which lead to a higher histological score in the 2% DSS group compared with the Control group (Figures 1A, B). Besides, the expression level of inflammatory cytokines in colon confirmed the inflammation observed in colitis mice. Il-6 mRNA level (proinflammatory cytokine) was significantly increased 8.3 times (Figure 1C), and il-10 (anti-inflammatory cytokines) was significantly decreased by 44.2% in the 2% DSS group compared with the Control group (Figure 1D). Colonic inflammation was associated with epithelial integrity and mucus barrier disruption. Significant reduction of ZO-1 (72.1%) and muc2 (95.4%) was observed in the 2% DSS group (Figures 1E, F), which reflected the damage of mucosal barrier and mucous barrier. Furthermore, colon length and spleen weight were measured as macroscopic evaluations of colonic inflammation. In the 2% DSS group, a 29.4% reduction of colon length was found (Figure 1G), and spleen weight was elevated 3.0 times compared with Control group (Figure 1H). Disease activity index (DAI) values were significantly increased after DSS treatment due to the increased body weight loss, diarrhea and bleeding (Figures 1I, J). Overall, 2% DSS induced significant intestinal inflammation and intestinal barrier damage.

To investigate whether 2% DSS induced colitis affected the metabolism of serum Trp, we detected the levels of Trp and its metabolites (Kyn and Kyna) in serum. The level of serum Trp was decreased by 30.6% in 2% DSS group compared with Control group (Figure 2A). Kyn level in serum was increased 1.3 times (Figure 2B), while Kyna was decreased by 66.9% after DSS treatment (Figure 2C). Moreover, Kyn/Trp ratio and Kyna/Kyn ratio confirmed this effect. Kyn/Trp ratio was significantly elevated 1.8 times in 2% DSS group (Figure 2D), which reflected increased efficiency of Trp metabolism into Kyn. Kyna/Kyn ratio was decreased by 73.2% in 2% DSS treatment group (Figure 2E), indicated the reduction of Kyn metabolism into Kyna. These results indicated that DSS treatment significantly changed the levels of Trp and its metabolites in serum.

The levels of rate-limiting enzymes are the direct factor affecting Trp metabolites. IDO-1 and TDO-2 are the main rate-limiting enzymes that metabolize Trp into Kyn, and KAT2 is rate-limiting enzyme that metabolize Kyn into Kyna (Figure 2F). IDO-1, TDO-2 and KAT2 are all expressed in liver cells. Therefore, we detected the levels of IDO-1, TDO-2 and KAT2 in the liver to explore the causes of Trp metabolite changes. The protein level of IDO-1 in liver did not achieve significance between the two groups (Figures 3A, D), while a significant increase (5.9 times) of IDO-1 mRNA level was observed in 2% DSS group compared with Control group (Figure 3G). TDO-2 decreased by 64.1% and 41.2% respectively in protein level (Figures 3B, E) and mRNA level (Figure 3H) in 2% DSS group compared with Control group. This indicated that the increase in Kyn level was not due to elevated expression of IDO-1 and TDO2. Besides, KAT2 decreased by 28.8% and 67.0% respectively in protein level (Figures 3C, F) and mRNA level (Figure 3I) in 2% DSS group compared with Control group, which suggested that decreased Kyna level might be contributed to reduced KAT2 protein. In brief, the alteration of Trp-Kyn-Kyna pathway in serum was partly regulated by rate-limiting enzymes.

To further confirm the dysregulation of Kyn pathway in IBD patients, we analyzed four NCBI Gene Expression Omnibus (GEO) datasets (GDS1615, GDS4365, GDS3119, GDS3268) containing expression profiles of peripheral blood mononuclear cells and colonic mucosa from IBD patients, and one GEO dataset (GDS3859) containing expression profile of colon tissue from DSS-induced mouse colitis. We found that IDO-1 mRNA levels were significantly higher in peripheral blood mononuclear of UC patients but not CD patients compared with the normal group, which indicated that colitis induced the activation of IDO-1 in immune cells (Figure 4A). In colonic mucosa of UC patients, IDO-1 expression was significantly higher in UC-active/UC-inflamed patients compared with Control or UC-remission/UC-uninflamed patients, which reflected that colitis induced the activation of IDO-1 in colon (Figures 4B–E). Besides, colonic IDO-1 expression was significantly increased after 6 days treatment of DSS compared with normal group in C57BL/6J mice aged 12~14 weeks old (Figure 4F). Collectively, these results demonstrated the increase of IDO-1 in UC patients and colitis mice, indicated upregulation of Kyn pathway.

Subsequently, we explored the effects of DSS-induced colitis on Trp metabolism in the cerebral cortex. Compared with Control group, IDO-1 mRNA level was significantly increased 1.8 times after 2% DSS treatment (Figure 5A), while the level of KAT2 was unchanged in 2% DSS group (Figure 5B). As a result, Kyn level was elevated in 2% DSS group compared with Control group, while Trp and Kyna did not achieve significance in the two groups (Figures 5C–E). This suggested that the level of Kyn and Kyna were under the regulation of IDO-1 and KAT2. Kyn/Trp ratio also showed that the efficiency of Trp metabolism to Kyn was improved (Figure 5F), which was consistent with elevated levels of IDO-1 and Kyn. The Kyna/Kyn ratio did not achieve significance between Control and 2% DSS group (Figure 5G), which reflected Kyn-Kyna pathway was not affected by DSS treatment. The transfer of Kyn from blood to brain is mediated by L-type amino acid transporter 1 (LAT1). We detected SLC3A2 (4F2hc heavy subunit) and SLC7A5 (CD98 light subunit) of LAT1 transporter subunits at the mRNA levels. There was no change in SLC3A2 between two groups (Figure 5H), while SLC7A5 was significantly decreased by 38.8% in 2% DSS group compared with Control group (Figure 5I). Therefore, we inferred that elevated Kyn in the cerebral cortex was mainly derived from IDO-1-mediated local synthesis rather than translocation from the blood.

Previous studies have shown that DSS-induced colitis caused cortical inflammation, as demonstrated by significant elevation of proinflammation cytokines (il-6 and tnf-α) and increased microglial activation in cortical tissue (26). This suggested that the cerebral cortex is a brain target affected by colitis. Furthermore, Kyn administration also induced brain infiltration of proinflammatory monocytes and astrocytic activation (27, 28). Therefore, to further investigate whether Kyn elevation caused by colitis can alter astrocyte and microglia subtypes, we detected the expression levels of astrocyte and microglia markers. In A1-specific markers of astrocyte, H2-D1, H2-T23, GBP2 and CFB mRNA levels were significantly increased by 51.9%, 44.8%, 52.9% and 121.8% (Figures 6A–D), while SerpinG1 was decreased by 24.8% in 2% DSS group compared with Control group (Figure 6E), which indicated the expression of A1-specific markers of astrocyte was elevated in colitis group. In A2-specific markers of astrocyte, EMP1 was decreased by 35.7% in 2% DSS group compared with the Control group (Figure 6F), while there was no significant difference in S100a10 and PTX3 between the two groups (Figures 6G, H). These data suggested that astrocytes in colitis group were driven to an A1 phenotype.

For M1-specific markers of microglia, the mRNA levels of CD80 and CD32 were significantly elevated by 44.3% and 22.9% respectively in 2% DSS group (Figures 7A, B), while the levels of CD16 and CD86 did not achieve significance between 2% DSS group and Control group (Figures 7C, D). For M2-specific markers of microglia, the mRNA levels of TGF-β were significantly increased by 151.0% in 2% DSS group compared with Control group (Figure 7E), while there is no significant difference in YM-1 and CD206 between the two groups (Figures 7F, G). There was no significant change in M1/M2 phenotypes transition of microglia cells. Overall, these results suggested that DSS-induced colitis caused neurotoxic subtype of astrocytes, which may be attributed to increased levels of Kyn in the cerebral cortex.

Several studies have shown that gut microbiota (such as Akkermansia muciniphila and Parabacteroides distasonis) is involved in the regulation of Trp metabolism (29–31). To investigate the characters of the gut flora after 2% DSS treatment, 16S rRNA sequencing was performed with the colon contents. Alpha diversity indices including Shannnon Index, Simpson Index and Pielou’s Evenness did not achieve significance between 2% DSS group and Control group (Figures 8A–C), which reflected unaffected species diversity and evenness. Principal coordinate analysis (PcoA) indicated a lower similarity of sample composition between the two groups (Figure 8D). Furthermore, Venn diagram showed 27 and 16 unique species respectively in Control group and 2% DSS group. And 31 common species were found in both groups (Figure 8E). The relative abundance of 31 common species was shown in the heatmap (Figure 8F), and only 8 common species achieved significance between Control group and 2% DSS group. The abundance of Bacteroides_acidifaciens, Shigella_sonnei, Parabacteroides_distasonis, Bacteroides_vulgatus, Ruminiclostridium_sp_KB18, Burkholderiales_bacterium_YL45 and Lachnospiraceae_bacterium_28-4 were significantly increased, and the abundance of Ileibacterium_valens was significantly decreased in 2% DSS group compared with Control group (Figure 9). These data reflected that DSS-induced colitis altered the diversity and composition of gut flora.

Given the change of Trp metabolism is related to intestinal flora, metabolic functions of the gut microbiota were assessed by PICRUSt2 based on 16S rRNA metagenomics data. Several functional pathways in the microbiome of 2% DSS group were found elevated, including Tryptophan metabolism, NOD-like receptor signaling pathway and MAPK signaling pathway (Figure 10). In addition, species with significant differences in abundance between the Control group and 2% DSS group were significantly associated with rate-limiting enzymes and metabolites of the Trp-Kyn-Kyna pathway (Figure 11), which indicates the regulatory effects of gut flora on Trp metabolism in the serum and cerebral cortex. Specifically, we found that several species were significantly correlated with the levels of IDO-1/TDO-2 in cortex and liver, but not with Kyn, suggested that gut microbiota may affect Kyn by regulating the level of IDO-1. The species involved in this process included: Bacteroides_acidifaciens, Shigella_sonnei, Parabacteroides_distasonis, Ileibacterium_valens, Bacteroides_vulgatus and Burkholderiales_bacterium_YL45. In addition, several species including Parabacteroides_distasonis, Ileibacterium_valens and Burkholderiales_bacterium_YL45 were significantly correlated with both KAT2 in liver and Kyna in serum, indicating that intestinal flora may regulate Kyna level in serum directly or by affecting KAT2.

Male C57BL/6 mice (aged 10 weeks, Vital River Laboratory Animal Technology, Pinghu, China) were used in this study. Animals were kept in specific pathogen-free environment (12h light/12h dark cycle) with regulated temperatures (24 ± 2.0°C) and humidity (55 ± 10%). Water and food were available ad libitum (Jiangsu Xietong Organism, China). Mice were acclimated for one week before the experiments. All animal experimental procedures were approved by the Animal Ethics Committee of Jiangnan University.

The mice were randomly allotted to two groups: Control group and 2% DSS group (n = 7 in each group). The Control group received sterile tap water as drinking water. Experimental colitis was induced by adding 2% DSS (36,000-50,000 Da, MP Biomedicals, Solon, USA) in drinking water for 10 days (from day 1 to day 10). Body weights, diarrhea (stool consistency) and rectal bleeding were daily recorded. All mice were sacrificed after being deeply anesthetized by isoflurane on day 11. Tissues (colon, liver and cerebral cortex), blood and colonic contents were collected. After centrifugation (4°C, 3000 rpm, 15 minutes), serum was separated from the blood.

Colonic tissue (proximal colon to the rectum) was collected and fixed in 4% paraformaldehyde at 4°C. Following embedded in paraffin, the colon was sectioned transversely (5 μm in thickness) and stained with H&E (C0105S, Beyotime, Shanghai, China). The histological changes were recorded under LuxScan 10K/B (CapitalBio, Beijing, China). As described previously, two parameters were used to calculate the histological damage score: tissue damage (score: 0-3) and infiltration of inflammatory cells (score: 0-3) in a double-blind fashion (46). Three sections obtained from each of three sites at 100 μm distance were evaluated, and mice were scored individually with each score representing the mean of nine sections (47).

According to the manufacturer’s instructions, total RNA from colon and cerebral cortex was extracted using Total RNA Extraction Reagent (R401-01, vazyme, Nanjing, China). Then, the total RNA was reverse transcribed into cDNA using HiScript III RT SuperMix for qPCR (R323-01, vazyme, Nanjing, China). PCR was performed using ChamQ Universal SYBR qPCR Master Mix (Q711-00, vazyme, Nanjing, China). Primers used are listed in Table 1. The 2^-ΔΔCt method was used for mRNA quantification. The mRNA expression of target gene was normalized to GAPDH expression.

For extracting total protein, the liver was homogenized in a mixture of RIPA buffer (P0013C, Beyotime, Shanghai, China), 2% phosphatase inhibitor (P1081, Beyotime, Shanghai, China) and 1% phenylmethanesulfonyl fluoride (PMSF, ST506, Beyotime, Shanghai, China). Following centrifugation at 14,000 r/min for 15 minutes at 4°C, supernatants were collected. The level of il-10 (EK0417, Boster, Wuhan, China) in colon was quantified by using commercial ELISA kit according to the manufacturer’s instructions. The detection limit of the kit is 15.6-1000 pg/ml for il-10.

As previously described, body weight loss, stool consistency and bleeding were recorded each day to determine the Disease Activity Index (DAI) (48). The scores were quantified as follows: weight loss: 0 (no loss), 1 (1-5%), 2 (5-10%), 3 (10-20%), and 4 (>20%); stool consistency: 0 (normal), 2 (loose stool), and 4 (diarrhea); and bleeding: 0 (no blood), 1 (Hemoccult positive), 2 (Hemoccult positive and visual pellet bleeding), and 4 (gross bleeding, blood around anus). DAI for each mouse was calculated by adding together the scores for weight loss, stool consistency and fecal blood.

To detect the concentrations of Trp, Kyn and Kyna in serum and cerebral cortex, LC-MS/MS analysis was conducted according to Wang et al. with slight modifications (49). In brief, the analysis was performed using Orbitrap Q-Exactive Plus mass spectrometer (Thermo Fisher Scientific, Bremen, Germany) connected with Vanquish UHPLC System (Thermo Fisher Scientific, Bremen, Germany). Chromatographic separation was achieved on the ACQUITY UPLC BEH C18 column (100 mm × 2.1 mm, 1.7 μm, Waters Corporation, Milford, MA, USA). A linear gradient mobile phase containing 0.1% formic acid water (A) and acetonitrile (B) was programmed as follows: 0–0.5 min, 95% A; 0.5–5 min, 95–20% A; 5–6 min, 20% A; 6–6.1 min, 20–95% A and 6.1–8 min, 95% A (flow rate: 0.4 mL/min). For the electrospray ionization quantitative analysis, the positive ion mode with parallel reaction monitoring was utilized. The detailed MS ionization source conditions included spray voltage at 2800 V; Capillary temperature at 325°C; sheath gas flow rate at 35; aux gas flow rate at 15; sweep gas flow rate at 0; aux gas heater temperature at 350°C. Data were processed by using the Thermo Xcalibur software (Thermo Fisher Scientific, Waltham, MA, USA).

Total protein concentration in liver was determined with a BCA Protein Quantification Kit (E112-02, vazyme, Nanjing, China). After boiling denaturation, total protein (35 μg) was separated by 10%~12% SDS-PAGE, then transferred to PVDF membranes (ISEQ00010, Millipore, Billerica, MA, USA). The membranes were blocked with 5% skim milk for 2 h at room temperature and then incubated (overnight at 4°C) with the following primary antibodies: Rabbit anti-indoleamine 2,3-dioxygenase 1 (IDO-1, 1:1000, 13268-1-AP, Proteintech, Wuhan, China), Rabbit anti-TDO-2 (1:500, 15880-1-AP, Proteintech, Wuhan, China), Rabbit anti-AADAT (KAT2, 1:500, A13090, ABclonal, Wuhan, China) and Rabbit anti-GAPDH (1:8000, ET1601-4, Huabio, Hangzhou, China). Then the HRP conjugated goat anti-rabbit IgG was incubated for 2 h at room temperature. The protein bands were visualized by enhanced chemiluminescence (ECL) reagent (P90720↗, Millipore, USA) and Gel Image System (Bio-Rad, Hercules, CA, USA). Target signals were analyzed by using Image J software (NIH, Bethesda, MA, USA).

IDO-1 gene expression levels of patients with IBD (GDS1615, GDS4365, GDS3119 and GDS3268) and of mouse colitis models (GDS3859) were downloaded from the NCBI GEO database.

The genomic DNA was extracted from the fecal samples by using the PowerSoil DNA Isolation Kit (MOBIO, Carlsbad, CA, USA). The V3~V4 hypervariable regions of bacterial 16S rRNA gene were amplified with the primers 341F (5′-CCTACGGGNGGCWGCAG-3′) and 806R (5′-GGACTACHVGGGTATCTAAT-3′). The target fragments of PCR amplified products were recovered, and then the amplified products of PCR were quantified by fluorescence. The qualified sequencing library was used for Illumina MiSeq pyrosequencing analysis.

Using the SPSS 22.0 software (IBM SPSS Statistics, Armonk, New York, USA), normality was evaluated by the Shapiro-Wilk test. Differences between the two groups were analyzed by independent samples T test and Mann-Whitney U test respectively for parametric values and nonparametric values. Differences among three groups were analyzed by one-way ANOVA with post hoc comparisons of Bonferroni and Kruskal-Wallis test for parametric values and nonparametric values. Values were shown as mean ± SEM. P < 0.05 was considered statistically significant between groups (*P < 0.05, **P < 0.01, ***P < 0.001).