D-Gal (G0500) was purchased from Sigma Aldrich (St Louis, MO, United States). LPS from Escherichia coli O55:B5 (#L2880) was purchased from Sigma Aldrich (St Louis, MO, United States). FICZ (#SML1489) was purchased from Sigma Aldrich (St Louis, MO, United States). Indole-3-lactic acid (#I157602) was purchased from Aladdin (Shanghai, China). Indole-3-acetic acid (#I101074) was purchased from Aladdin (Shanghai, China). 3-Indolepropionic acid (#I103959) was purchased from Aladdin (Shanghai, China).

Hangzhou Ziyuan Experimental Animal Co., Ltd. supplied us with C57BL/6 mice. All of the animals were housed in specific pathogen-free (SPF) conditions at the animal facility of the First Affiliated Hospital of Zhejiang University Medical School. All the animals were grown at a temperature of 22 ± 2°C with a light/dark cycle of 12 h, and fed with standard chow diet. All 60 male 6-to 8-week-old wild-type mice (all on C57BL/6 background and weight from 20 to 22 g) were randomly divided into 6 groups: (1) IAA + D-GalN/Lps (IAAL) group, (2) ILA + D-GalN/Lps (ILAL) group, (3) IPA + D-GalN/Lps (IPAL) group, (4) Ficz +D-GalN/Lps (FiAL) group, (5) Vehicle+D-GalN/Lps (VeAL) group, and (6) Vehicle (Veh) group. IAAL was administered orally in the form of 5 mg/ml IAA with 200 μl volume per mouse daily for 1 week. The IAA stock solution (25 mg/ml, 5) was produced in sterile saline and dissolved by giving NaOH (1 N) and adjusting the pH to 7.2–7.4 with 25% (v/v) HCl. The gavage solution was diluted to a final concentration of 5 mg/ml using sterile saline. ILAL and IPAL were orally administrated with 2.5 mg/ml of ILA and 7.5 mg/ml of IPA with 200 μl volume per mouse per day for 1 week, respectively. ILA stock solution (12.5 mg/ml, 5×) and IPA stock solution (32.5 mg/ml, 5×) were prepared and dissolved in the same way as IAA. The final concentrations of ILA and IPA were 2.5 mg/ml and 7.5 mg/ml, respectively. The dosage of indole derivatives and the method to dissolve was based on the previous studies (Ji et al., 2019; Xiao et al., 2020) and our preliminary study which exhibited good safety and tolerance for mice. FiAL was orally administrated with 5 μg/1 ml of FICZ dissolved in sterile saline, 200 μl per mouse in day 2 and 6. The ALF model was created on day 8 through intraperitoneal injection of 400 mg/kg D-Gal and 50 μg/kg LPS dissolved in sterile saline (10 μl/g total injection volume). On day 8, Veh was administered intraperitoneally with sterile saline (final injection volume: 10 μl/g). The vehicle therapy consisted of daily oral administration of 200 μl of sterile saline. The mice were fasted overnight and sacrificed 6 h after intraperitoneal injection of D-Gal/LPS. The liver and feces were promptly frozen in liquid nitrogen and stored in a refrigerator at −80°C for future use.

The animal and treatment procedures were consistent with the National Institutes of Health’s standard for the care and use of laboratory animals and were approved by the Animal Care Ethics Committee of The First Affiliated Hospital, College of Medicine, Zhejiang University, China.

Serum was collected from the supernatant of the whole blood samples by centrifugation at 3,000 rpm at 4°C for 15 min. Serum was isolated and stored in −80°C refrigerator. Serum ALT and AST transaminases were determined using BS-220 Chemistry Analyzer (Mindray, Shengzhen, China). Hepatic tissue was removed, rinsed in ice-cold phosphate-buffered saline (PBS), and then preserved for 24 h in 4% paraformaldehyde. The 5 m-thick tissue slices were produced for hematoxylin and eosin (H&E) staining, while the remaining sections were embedded in paraffin. Samples were scanned and visualized by an 3DHISTECH Pannoramic 250 FLASH and caseviewer 2.4.¹ The degree of liver histologic injury was measured according to the modified HAI scores (Ishak et al., 1995; Desmet, 2003). Each sample was examined at 40× for five random visual fields.

Terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL) analysis was conducted on paraffin-embedded (5 μm) mouse liver slices treated with Leica AR9640 following antigen retrieval. BrightGreen Apoptosis Detection Kit (Vazyme, Nanjing, China) was used to perform TUNEL staining in accordance with the manufacturer’s instructions. Nucleus was labeled with DAPI. All images were scanned and visualized by 3DHISTECH Pannoramic 250 FLASH and caseviewer 2.4. Each sample was examined at 40× for five random visual fields.

Hepatic tissues’ total RNA was extracted with a Qiagen RNeasy Plus Mini Kit (QIAGEN, Hilden, Germany) and measured by a NanoDrop 2000 spectrophotometer (Thermo Fisher, MA, United States). Following the manufacturer’s instructions, 500 ng of RNA was reverse-transcribed to cDNA using PrimeScript RT Master Mix (Perfect Real Time) (TAKARA, Beijing, China). Quantitative polymerase chain reaction (qPCR) was done using a TB Green® Premix Ex TaqTM (Tli RNaseH Plus) (TAKARA, Beijing, China) kit including forward and reverse primers and cDNA template (100 ng) in an Applied Biosystems VIIA7 instrument (Thermo Fisher Scientific). The amplification protocol was as follows: 95°C for 30 s, 40 cycles of 95°C for 5 s, 60°C for 30 s, and dissociation step. The relative mRNA expression of target genes was standardized utilizing GAPDH as the reference gene and computed using the comparative CT technique. The sequences of RT-qPCR primers are included in Supplementary Table S1 of the Supplementary material.

Serum cytokines were quantified with the LEGENDplex^™ Mouse Inflammation Panel (13-plex) with Filter Plate (Biolegend, CA, United States) according to the protocol provided by the manufacturer with flow cytometry method.

Nuclear extract was extracted with Cryopreserved sample nucleoprotein Extraction Kit (Bio-lab, Beijing, China). Protein concentration was measured by Enhanced BCA Protein Assay Kit (Beyotime, Shanghai, China).

The transcriptive activity of NF-κB (P65) was assessed by NFkB p65 Transcription Factor Assay Kit (Abcam, MA, United States) with nuclear extract. All the experiments were performed according to manufacturer’s protocol.

mRNA molecules were extracted from whole RNA using magnetic beads to which oligo (dT) was coupled. mRNA molecules were fragmented into little fragments using a fragmentation reagent after a certain length of reaction at the correct temperature. Using random hexamer primed reverse transcription, first strand cDNA was synthesized, followed by second strand cDNA synthesis. The end of the generated cDNA was repaired, and then it was 3′ adenylated. These 3′ adenylated cDNA segments were ligated using adapters at their ends. cDNA fragments containing adapters from the previous stage were amplified using a PCR technique. Ampure XP Beads (AGENCOURT) were used to purify PCR products, which were then dissolved in EB solution. On the 2,100 bioanalyzer from Agilent Technologies, the library was verified. The double-stranded PCR products were denatured by heat and then circularized using the splint oligo sequence. As the final library, the single-strand circular DNA (ssCir DNA) was prepared. The library was amplified using phi29 to create DNA nanoballs (DNB) containing over 300 copies of a single molecule. The DNBs were loaded onto the patterned nanoarray, and pair-end 150-base readings were created via combinatorial Probe Anchor Synthesis (cPAS).

Using the CTAB/SDS technique, complete genome DNA was extracted from samples. On 1% agarose gels, DNA concentration and purity were evaluated. Using sterile water, DNA was diluted to 1 ng/l based on its concentration. Using particular primers and barcodes, 16S rRNA genes in various locations (16S V3-V4) were amplified. All PCR mixtures comprised 15 l of Phusion^® High-Fidelity PCR Master Mix (New England Biolabs), 0.2 M of each primer, and 10 ng of target DNA, and cycling conditions included a 1 min initial denaturation at 98°C, 30 cycles at 98°C (10 s), 50°C (30 s), and 72°C (30 s), and a 5 min extension at 72°C. For DNA detection, mix PCR results with an equivalent amount of 1× loading buffer (including SYB green) and run electrophoresis on a 2% agarose gel. The PCR products were combined in identical amounts, and then they were purified using a Qiagen Gel Extraction Kit (Qiagen, Germany). Following the manufacturer’s instructions, NEBNext^® UltraTM IIDNA Library Prep Kit was used to construct sequencing libraries (Cat No. E7645). On the Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2,100 system, the library’s quality was assessed. The library was sequenced on an Illumina NovaSeq device to yield 250 bp paired-end reads.

Data are presented as mean ± SEM. Statistical analysis of non-sequence data between two or multiple groups was performed on GraphPad Prism 9 (CA, United States). Student’s t-test, and one-way analysis of variance (ANOVA) which is followed by Tukey’s or uncorrected Fisher’s LSD multiple comparisons test were used to examine the statistic difference. P values were considered statistically significant at <0.05. The statistical analysis of transcriptome sequence and 16S RNA are listed in the Supplementary material.

Previous studies have highlighted the anti-inflammation and hepatoprotective role of the microbial metabolite indole derivatives in different liver diseases (Ji et al., 2019; Zhao et al., 2019). To investigate the effect of indole derivatives on D-GalN/LPS induced-acute liver injury (ALI), wild-type mice are pretreated with indole derivatives (IAA, ILA, IPA) or vehicle saline for a week, the acute liver injury (ALI) model is established on day eight with D-GalN/LPS injection. 4–5 h after D-GalN/LPS injection, some mice have begun to exhibit an adynamic condition characterized by reduced activity. Unexpectedly, mice pretreated with indole derivatives appeared to exhibit more severe symptoms and left less circulating blood and colon contents for sampling on the sixth hour, contradicting our previous expectations.

To check the severity of ALI in each group. We evaluate the alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels as typical markers of liver injury. Serum ALT and AST levels increased significantly with D-GalN/LPS injection. The pretreatment with indole derivatives (IAA, ILA, IPA) aggravates the acute injury in liver with elevated aminotransferase and decreased AST/ALT ratios (Figure 1A). We then evaluated the histologic injury with hematoxylin and eosin (H&E) staining of each group. The hepatorrhagia is greatly severe and the modified histological activity index (HAI) scores are significant higher in groups pretreated with indole derivatives, which represent a severer tissue injury and hepatocytes damage compared with VeAL group (Figures 1B, C). Of note, indole derivatives (IAA, ILA, IPA) administration along does not exhibit significant toxicity or induce inflammation response to mice in our preliminary experiment (Supplementary Figures 1A, B) and according to other studies (Ji et al., 2019; Xiao et al., 2020). Thus, results of biochemical and histologic analysis indicated that mice in indole derivatives (IAA, ILA, IPA) can sensitize mice to D-GalN/LPS induced-ALF.

In order to get a clearer view of the role of the indole derivatives in the D-GalN/LPS induced-ALF, we chose the IAAL group for further investigation. TNF-α signaling is recognized as the crucial pathogenic and inflammatory factor in D-GalN/LPS induced-ALF (Maes et al., 2016). Thus, we evaluated the expression of TNF-α in liver with RT-qPCR. The relative expression of TNF-α, IL-1β, IL-6, and iNOS mRNA was significantly elevated in IAAL groups compared with VeAL group (Figure 2A). The quantification of serum cytokines TNF-α, IL-1β, IL-6, macrophage recruitment monocyte chemotactic protein-1 (MCP-1) were in consistence with RT-qPCR results (Figure 2B). We also evaluate the degree of hepatocytes apoptosis with terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay. The pretreatment of IAA significantly aggravated cell apoptosis in liver tissue (Figures 2C, D). Taken together, IAA can aggravate D-GalN/LPS induced-liver inflammation and apoptosis.

The aforementioned data already demonstrate the pathogenic function of IAA administration in D-GalN/LPS-induced ALF, however the underlying signaling route remains unknown. To investigate the potential mechanism by which indole derivatives sensitize mice to D-GalN/LPS-induced ALF, an RNA sequence analysis was done to identify potential routes. 419 genes were identified as differentially expressed genes (DEGs) in the comparison between the IAAL and the VeAL using the criterion q ≤ 0.05 and|log2 (fold change)| ≥ 1. 350 DEGs were considerably elevated, whereas 69 DEGs were significantly downregulated (Figure 3A and Supplementary Figure 2A). Using the criteria Q 0.05, KEGG enrichment analysis of DEGs indicated that treatment of IAA substantially altered 28 pathways in VeAL mice. Inflammation, signal transduction, and metabolism made up the majority of the top 10 impacted pathways (Figure 3B). Four routes, including TNF signaling, NF-κB signaling, IL-17 signaling, and retinol metabolism pathway, were identified based on their regular fluctuation tendency, which demonstrated consistency with the progression of liver damage (Figure 3C). By mapping genes from these four major pathways, a protein–protein interaction (PPI) network was built to identify genes involved in ALI aggravation (Figure 3D). These findings showed that the aggravation of the condition might be ascribed to the control of transcriptional expression associated with inflammation, signal transduction, and metabolism.

The results of RNA sequence analysis indicate the possible involvement of TNF signaling, NF-κB signaling, IL-17 signaling pathway in the aggravation of ALI. We first examined the expression levels of IL-17A in the liver. RT-qPCR showed no significant difference in IL-17A expression and serum cytokines assay only indicated a slight increase (about two folds compared with Veh) in IAAL (Supplementary Figure 3). Thus, the IL-17 signaling pathway is unlikely to play an influential role in our study. We next focused on the expression of TNF-α/NF-κB signaling pathway, which is a potent driver for inflammation response. We detect and find a significant elevation in the DNA-binding activity of NF-κB (P65) in IAAL, which is in consistent with our transcriptome results (Figure 4A). Additionally, IAA significantly elevated the expression of several crucial genes in TNF-α/NF-κB signaling including NFkBia and Tnfaip3 and downstream chemokines Cxcl2 and Cxcl3 (Figure 4B). The serum quantification of important downstream product IL-1β, IL-6, and TNF-α (Figure 2B) were significantly increased as above mentioned.

Toll-like receptor 4 (Tlr4)/NF-κB signaling is recognized as the primary pathogenic pathway in D-GalN/LPS induced-ALF activated by LPS administration (Maes et al., 2016). Thus, we hypothesized that IAA pretreatment may promote Tlr4 signaling. However, although D-GalN/LPS treatment significantly enhanced the gene expression of Tlr4 in liver compared with Veh, IAA pretreatment did not significantly alter it (Figure 4C). Nevertheless, we found that another vital toll-like receptor which can promote TNF-α/NF-κB pathway (Piao et al., 2016; Khan et al., 2021), toll-like receptor 2 (Tlr2), was significantly increased in IAAL compared with VeAL (Figure 4D). In addition, we also found that one of the essential co-factors of Tlr2 function, Toll-like receptor 6 (Tlr6; Ozinsky et al., 2000; Janeway and Medzhitov, 2002), exhibit significant increase in IAAL compared with VeAL (Figure 4E), which corroborates the activation of Tlr2 signaling. Taken together, IAA pretreatment may specifically up-regulate Tlr2/NF-κB signaling pathway under the challenge of D-GalN/LPS.

Tlr2 is an important sensor which can engage with bacterial components in gram-positive bacteria (Oliveira-Nascimento et al., 2012). On the other hand, IAA was reported to have the ability to influence microbial ecology (Shen et al., 2022). From this, we performed 16S RNA analyses in both colon and ileum contents to identify possible microbial involvement.

In colon, IAA pretreatment induces a significant shift of the composition of gut microbiota according to the unweighted UniFrac principal component analysis (PCA) analysis (Supplementary Figure 4A). The most altered taxonomic abundance of the microbiome was presented (Supplementary Figure 4B). However, we did not identify meaningful microbiome changes that could be responsible for Tlr2 activation.

As a note, we found encouraging results in the ileum microbiome, which may explain the activation of Tlr2 in the liver. The unweighted UniFrac principal coordinates analysis (PCoA) plot and principal component analysis (PCA) analysis also showed a significant shift in the composition of gut microbiota in IAAL (Figure 5A). The taxonomic abundance of the 10 most abundant microbiome was presented with phylum, family and genus levels (Figure 5B). Specifically, we found that IAA significantly increased the relative abundance of Streptococcus and reduced that of Lactobacillus (Figures 5C, D). The enrichment of gram-positive Streptococcus with underlying pathogenesis and the reduction of beneficial Lactobacillus indicates microbial dysbiosis in the ileum and may contribute to the up-regulation of Tlr2 signaling with IAA pretreatment.

Spearman analysis was performed to identify the underlying correlation between microbial alteration and liver injury. Ten of the richest genera were presented. In consistency with our above findings, the relative abundance of Streptococcus exhibited positive correlation with ALT (r = 0.67)/AST (r = 0.53) levels and the relative abundance of Lactobacillus exhibited negative correlation with ALT (r = −0.55)/AST (r = −0.58) levels (Figure 6). Our findings suggested that the increased Streptococcus and reduced Lactobacillus may at least, partly be responsible for the up-regulation of Tlr2/NF-κB signaling pathway.

We also noticed that previous reports have revealed indole derivatives as important endogenous aryl hydrocarbon receptor (AHR) agonists and the activation of AHR signaling can aggravate APAP induced-ALF (Rothhammer et al., 2016; Schuran et al., 2021; Hezaveh et al., 2022). Thus, we hypothesize that the oral administration of IAA may aggravate the ALI through the activation of AHR signaling. However, we found that though oral administration of IAA and AHR agonist FICZ significantly increase the gene expression of CYP1A1 in liver (Figure 7A), FICZ along induced no significant difference in liver aminotransferase (Figure 7B). As a consequence, the activation of liver AHR signaling has no impact on D-GalN/LPS induced-ALF in our study.