Synbiotics of Lactobacillus suilingensis and inulin alleviates cognitive impairment via regulating gut microbiota indole‐3‐lactic acid metabolism in female AD mice

Abstract

INTRODUCTION

Recent studies have found that gut microbial tryptophan metabolism is altered in Alzheimer's disease (AD) patients. However, the functional consequences of these changes and their therapeutic potential remain unclear.

METHODS

The metagenomic data of 49 preclinical AD patients and 115 healthy controls were analyzed. A synbiotic with targeted metabolic functions was formulated based on in vitro testing, and its effect on AD was evaluated using female 5×FAD mice.

RESULTS

Indole lactic acid (ILA) synthesis was downregulated in AD patients. Synbiotic treatment combining Lactobacillus suilingensis and inulin outperformed probiotic treatment alone in enhancing tryptophan metabolism, and increasing ILA biosynthesis. Increased ILA could reduce Aβ accumulation and significantly alleviate cognitive impairment in female AD mice by inhibiting neuroinflammation through activation of the aryl hydrocarbon receptor (AhR) signaling pathway.

DISCUSSION

This study highlights the therapeutic potential of targeting gut microbial tryptophan metabolism in AD and provides a rationale for future precision strategies aimed at modulating microbiota‐derived metabolic pathways.

Highlights

• Gut metagenomic analysis reveals reduced indole lactic acid (ILA) biosynthesis genes in preclinical AD patients.

• Screening and formulating ILA‐producing synbiotic by using whole‐genome analysis.

• Synbiotic treatment alleviates cognitive impairment and promotes ILA synthesis in female 5×FAD mice.

• ILA alleviates neuroinflammation in female 5×FAD mice by activating aryl hydrocarbon receptor (AhR) in the brain.

• Synbiotic targeting tryptophan metabolism provides a novel approach for Alzheimer's intervention.

1. BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition causing memory loss and cognitive dysfunction, with 416 million people suffering from AD worldwide, of which approximately 316 million are preclinical AD. The prevention and treatment of AD have become major public health issues. ¹ Amyloid‐β (Aβ) deposition, Tau pathology, and neuroinflammation are pathological characteristics of AD, and various hypotheses have revealed the causes of AD based on these characteristics; however, its pathogenesis remains unclear. ² Recent studies have demonstrated that alterations in gut microbiota are closely associated with the pathogenesis of AD, as evidenced by reduced microbial diversity and compositional shifts in AD patients, ³ , ⁴ , ⁵ , ⁶ which lead to distinct profiles of gut microbial metabolites compared to healthy individuals (HC). ⁷ , ⁸ , ⁹ Among these metabolites, tryptophan and its gut microbial catabolites have garnered considerable attention for their critical roles in regulating host metabolism, immune responses, neurodevelopment, and other physiological processes. ¹⁰ , ¹¹ Studies suggest that microbial tryptophan catabolites (MTCs) were changed in AD patients. The levels of indole compounds in feces, such as indole carboxylic acid and 3‐hydroxyethyl indole, were decreased in AD, but indole‐3‐pyruvate acid (IPyA) increased. ¹² In particular, recent studies have discovered that the level of indole lactic acid (ILA) in the plasma of AD patients is significantly lower than that of cognitively normal controls. ¹³ Similar disturbances in tryptophan metabolism have been observed in animal studies, including a marked reduction in gut‐derived indole‐3‐propionic acid (IPA). ¹⁴ , ¹⁵ These findings imply a potential link between altered MTCs and the development of Alzheimer's disease; however, whether such changes contribute to disease progression or represent compensatory responses, as well as whether targeting these alterations could offer therapeutic benefit, remains to be fully elucidated.

The aryl hydrocarbon receptor (AhR) is a ligand‐activated transcription factor widely expressed in the central nervous system and immune cells, playing a pivotal role in regulating inflammation, cell differentiation, and xenobiotic metabolism. ¹⁶ Recent studies show that various MTCs act as exogenous AhR agonists and exert neuroprotective effects in neurodegenerative disease models, including AD. ¹⁷ , ¹⁸ , ¹⁹ For instance, a mixture of indole‐3‐acetic acid (IAA), indole, and IPA suppresses pro‐inflammatory cytokine expression and microglial activation via AhR‐dependent pathways, alleviating neuroinflammation in AD mice. ²⁰ Indole‐3‐carbinol (I3C) enhances neprilysin expression—critical for Aβ degradation—via AhR activation, reducing amyloid pathology and alleviating cognitive deficits. ²¹ ILA could enhance Aβ phagocytosis by microglia and astrocytes through the AhR signaling pathway, decreasing Aβ accumulation. ²² Collectively, these findings highlight the MTCs–AhR axis as a key regulatory mechanism in AD and suggest that boosting AhR‐activating MTCs biosynthesis may offer a novel therapeutic strategy.

Currently, interventions such as probiotics and synbiotics are being explored to modulate microbial metabolism. Certain probiotics, such as Lactobacillus reuteri and Clostridium sporogenes, have been reported to promote the production of beneficial indole metabolites in vivo. ²³ , ²⁴ In particular, members of the Lactobacillus genus have been shown to produce a variety of MTCs, although the production levels vary significantly among strains. ²⁵ , ²⁶ , ²⁷ , ²⁸ Genomic and metabolic screening strategies have emerged as effective tools to identify high‐producing probiotic strains. ²⁴ , ²⁹ , ³⁰ Moreover, the addition of prebiotics may further enhance the metabolic potential of probiotics. ³¹ However, synbiotics targeting the microbial production of tryptophan metabolites have not yet been developed, and their efficacy in AD remains unverified.

Therefore, this study aimed to identify alterations in gut microbial tryptophan metabolism in individuals with preclinical AD, and to develop a targeted synbiotic intervention based on these metabolic differences. We found that the abundance of genes related to ILA biosynthesis was reduced in the gut microbiota of preclinical AD patients. The synbiotic specifically designed to enhance ILA production was able to modulate gut microbial composition and restore tryptophan metabolic function, thereby increasing systemic ILA levels. This, in turn, activated the AhR signaling pathway, reduced neuroinflammation, and ultimately ameliorated cognitive deficits in female AD mice.

2. METHODS

2.1. Human data analysis

The raw data used in this study were obtained from Ferreiro et al., ³² encompassing a total of 164 gut microbiota samples, including 115 samples from HC and 49 samples from patients with mild cognitive impairment. After quality control and host removal, the data underwent further analysis. We utilized MetaWIBELE to structure the gene sets computation and the workflow was shown in (https://github.com/biobakery/metawibele/).We selected parameters (‐d 100‐c 0.95‐aS 0.8) when running the gene clustering step and for other steps we chose the default parameters. After getting sequences of all gene clusters, functional annotation of the generated gene clusters was annotated with eggnog‐mapper software. (https://github.com/eggnogdb/eggnog‐mapper, identity > 40%, query cover > 20%). The sequence of metabolic genes associated with tryptophan microbial pathways were selected from both the NCBI (https://www.ncbi.nlm.nih.gov/) and KEGG websites(https://www.genome.jp/kegg/), and only sequences of bacterial and fungal origin were included in this sequence‐base. Then by Diamand software, we got the all sequences that were matched the gene sequence base from humanized metagenetic data (identity > 40%, query cover > 20%). The non‐redundant (NR) gene abundance profile of metabolizing tryptophan to produce indole derivatives was constructed via the Salmon software (‐c 0.9). Significance analysis of indole derivatives metabolic genes were shown in Table S1 (linear discriminant analysis [LDA] > 2, occurrence rate > 60%). Genes that met the criteria of LDA > 2 and an occurrence rate > 60% were considered as differentially expressed genes between the two‐group human.

2.2. Growth curve analysis

Inulin (Yuanye China), mannooligosaccharide (Yuansen China), and xylooligosaccharide (Macklin China) were additionally added to GAM medium (Haibo China) as carbon sources, and set to 5 g/L and 10 g/L, 20 g/L, 30 g/L, 40 g/L concentration gradient. Add 300 µL of GAM culture medium or culture medium with different carbon sources into the small holes of the growth curve test plate, then add 50 µL of bacterial solution in each small hole, and place the test plate on a fully automatic growth curve analysis instrument (Bioscreen C, Finland). The strains were cultured at 37°C for 48 h in the instrument, during which the absorbance value at 600 nm was measured every 1 h to obtain the growth status of the strain.

2.3. Animals

The B6SJL‐Tg (APPSwFlLon, PSEN1*M146L*L286V) 6799Vas/Mmjax (5xFAD) mouse model carrying five genes related to familial AD was selected for the experiment. The mice were purchased from Jackson Laboratory (USA). This model has three mutated genes related to human amyloid precursor protein (APP) and two mutated genes related to presenilin 1 (PSEN1), which can form amyloid plaque accumulation pathology similar to AD through overexpression of Aβ_1‐42. AD male mice were crossed with wild‐type (WT) female mice (identified non‐AD littermates) to reproduce the offspring (the mice used in the experiment were within three generations of hybridization). Three weeks after the offspring were born, the offspring were marked with ear tags and ear tissues were collected. The offspring mice were genetically analyzed using gel electrophoresis for identification.

RESEARCH IN CONTEXT

1. Systematic review: We searched PubMed for preclinical and clinical studies investigating the relationship between tryptophan metabolism, microbiota‐targeted interventions, and Alzheimer's disease (AD). Evidence indicates that microbial tryptophan metabolism is altered in AD, with reduced levels of beneficial microbial tryptophan catabolites (MTCs). Although several studies have evaluated the effects of probiotic or MTC supplementation on AD, no prior research has focused on synbiotics specifically designed to modulate microbial tryptophan metabolism in AD.

2. Interpretation: Our study identified reduced abundance of indole lactic acid (ILA) biosynthesis‐related genes in the gut microbiota of preclinical AD patients. Based on this finding, we developed a synbiotic that enhances ILA production. Supplementation in female 5×FAD mice increased systemic ILA levels, activated aryl hydrocarbon receptor (AhR) signaling, suppressed neuroinflammation, and improved cognitive function, highlighting a potential therapeutic strategy.

3. Future directions: Further research should assess the broader spectrum of tryptophan metabolites affected by synbiotics, validate findings in male models and human cohorts, and investigate downstream protein‐level changes to understand therapeutic mechanisms better.

Ten 7‐month‐old female WT mice from the same litter were selected as the normal control group (WT, n = 10), and 35 7‐month‐old female AD mice were selected and randomly divided into four groups, namely control group (AD, n = 8), inulin treatment group (AI, n = 8), L sp. AF91 treatment group (AL, n = 9), and synbiotic treatment group (AS, n = 10), inulin was supplemented with drinking water at a concentration of 20 g/L, L sp. AF91 was suspended in phosphate buffered saline (PBS) and formulated to 1×10¹¹CFU/mL, each mouse was orally administered 200 µL every day. Except for the AI and AS groups, the mice in the other groups drank pure water normally. Except for the AL and AS groups, the mice were orally administered 200 µL PBS every day as a control. Mice underwent a 4‐week intervention experiment. During this period, all mice were fed standard feed (AIN‐93 M, Trophic, China), and water containing inulin was replaced twice a week. The body weight and food intake of the mice were measured every 2 days. Weigh and record the amount of water you drink. Behavioral testing was performed at the end of the experiment, and the mice were subsequently sacrificed.

To investigate whether the therapeutic effects of synbiotics on AD mice are mediated by increased ILA and AhR activation, six 7‐month‐old female WT mice from the same litter were selected as the normal control group (WT, n = 6), 24 7‐month‐old female WT mice were selected and randomly divided into four groups, namely control group (AD, n = 6), ILA treatment group (AD+ILA, n = 6), CH223191 treatment group (AD+ CH223191, n = 6), and ILA and CH223191 treatment group (AD+ILA+CH223191, n = 6). Each mouse was orally administered ILA (20 mg/kg/d) or an equal volume of PBS via gavage, and intraperitoneally injected with CH223191 (10 mg/kg/d) or an equivalent volume of corn oil daily. Mice were subjected to a 4‐week intervention, during which they had free access to food and water. Behavioral assessments were conducted after the intervention, followed by euthanasia of the mice.

During the experiment, mice were maintained at a temperature of 22 ± 2°C, a relative humidity of 55 ± 5%, and a 12 h light/12 h dark cycle. Animal experiment‐related operations complied with the Guide for the Care and Use of Laboratory Animals (Eighth Edition, ISBN‐10: 0‐309‐15, 396‐4) and were approved by the Animal Ethics Committee of Northwest A&F University.

Although male animals are more stable in research, sex differences may affect the generalizability of findings. Given the lack of studies on female animals, this study uses female AD mice to explore the effects of synbiotics. Future research can compare male and female animals to investigate potential sex differences and underlying mechanisms.

2.4. Behavioral tests

Barnes maze: The learning and memory abilities of mice were assessed using the Barnes maze. On day 0, Barnes adaptive training was performed, the mice were allowed to adapt to the escape chamber for 60 s. A 180 s learning test was conducted on days 1–4. Regardless of whether the mice could find the target hiding place, they were allowed to adapt to the escape room for another 60 s. After the learning test, remove the escape chamber, place the test animal in the center of the high platform, and explore freely for 180 s. Record the time it takes for the test animal to find the correct hole, the number of probes at the correct hole, and the exploration time and distance in the correct hole quadrant.

Novel object recognition (NOR) test: Use the NOR test to evaluate the short‐term memory ability of mice. The test included an adaptation day, a training day and a test day. On the adaptation day: the mice were placed in an open cube box (length × width × height; 40 × 40 × 40 cm), and the mice were allowed to freely explore for 5 min. On the training day: Place two identical objects on the upper left and lower right of the square box, place the mice in the center of the square box, and explore freely for 5 min. On the test day: Replace one object on a training day with a new object (the new object has a different shape and color from the old object), the mice explore freely for 5 min. During this period, the activity trajectory of mice and their sniffing time for new and old objects are recorded by software. Discrimination index calculation: (New object exploration time—old object exploration time)/(New object exploration time + Old object exploration time) × 100%

Open field test: The open field test is used to evaluate the activity ability of mice. First prepare a cube box (length × width × height; 40 × 40 × 40 cm). At the beginning of the experiment, place the mice in the center of the area. The mice will move freely in the open field for 5 min, during which the software will record the total distance traveled by the mouse.

2.5. Fecal metagenomic analysis

A frozen fecal sample was suspended in a solution containing 250 µL of guanidine thiocyanate, 0.1 M Tris (pH 7.5), and 40 µL of 10% N‐lauroyl sarcosine. Then we introduced 500 µL of 5% N‐lauroyl sarcosine. After an hour of incubation, the mixture underwent vortexing with 500 µL of 0.1 mm glass beads and 500 µL of TENP, followed by centrifugation. The supernatant was then transferred to a new tube, and DNA was precipitated by using isopropanol. Subsequently, on the BGISEQ‐500 platform metagenomic sequencing was achieved. The approach adoptived was polymerase chain reaction (PCR)‐free without size selection, yielding 100 bp paired‐end reads for fecal samples, with the creation of four libraries for each sequencing lane.

2.5.1. Quality Control and Taxonomic Abundance Calculation of Metagenomic Data

We used FASTQC software to filter the raw data, eliminating low‐quality, duplicated, and adapter‐contaminated reads. Following this, we mannered mapment of the high‐quality reads to the mouse reference genome GRCm39 (Genebank assembly accession: GCF_000001635.27) by using bowtie2 with default parameters. The taxonomic landscape(species taxonomic classification and abundance calculatation) was obtained by Kraken2 (default parameter)(https://github.com/DerrickWood/kraken2). Package ‘vegan’ in R software was utilized to perform principal co‐ordinates analysis (PCoA), and computation of Shannon and Simpson indices for species‐level data. We visualized them by package “ggplot2” in R software.

2.5.2. The appraisal of differentially expressed genes

The “edgeR” package was used to identify differentially expressed genes. The raw counts on each gene level were then normalized by the algorithm of trimmed mean of TRM values. An adjusted p of less than 0.05, and log fold change greater than 1 were used to indicate genes that were significantly differentially expressed.

2.5.3. Microbiome functional analysis of ILA pathway

We selected sequences of enzymes related to the production of ILA from the protein database constructed in 2.1 as the protein sequence‐base of metabolizing tryptophan to produce ILA. Subsequently, we employed the same workflow in 2.1 to identify genes involved in differential expression of ILA metabolism within the mouse gene set (LDA > 2, occurrence rate > 90%, average abundance(TRM) > 1000).

2.6. ILA detect

For microbial samples, strains were inoculated into GAM medium supplemented with 20 g/L inulin or regular GAM medium, and the ILA content was measured after 72 h of culture. The sample preparation method is as follows: mix the culture medium after culture, then take 200 µL of the fermentation broth, add 800 µL of chromatography‐grade methanol, mix, and subsequently sonicate for 10 min. After completion of sonication, place the centrifuge tube in a centrifuge at 12,000 rpm for 10 min at 4°C. Then, use a 1 mL sterile syringe to aspirate the supernatant, place it onto a 0.22 µm organic filter, and transfer the liquid into a brown liquid‐phase vial. Finally, store it in a 4°C refrigerator for later use

For serum samples, take 30 µL of mouse serum sample into a 1.5 mL centrifuge tube, add 870 µL of pre‐cooled methanol to precipitate the protein, place it at −20°C for 20 min, and then incubate the sample at 4°C, 13000 r/min. Centrifuge for 10 min, filter the supernatant through a 0.22 µm organic filter, add it to a brown bottle, and place it in a 4°C refrigerator for testing.

For feces samples: weigh mouse feces into a 1.5 mL centrifuge tube, add 1 mL of methanol, vortex and mix for 1 min, then place in a water bath and bathe in a 40°C water bath for 20 min, mixing every 5 min. Then, the sample was placed in a −20°C refrigerator for 20 min to accelerate the precipitation of particulate matter. The sample was then centrifuged at 4°C and 13,000 r/min for 10 min. The supernatant was filtered through a 0.22 µm organic filter membrane, added to a brown bottle, and placed in a 4°C refrigerator for testing.

Chromatographic detection conditions: ZORBAX XDB C18 chromatographic column (4.6 × 250 µm, 5 µm) is used as the separation column; column temperature: 30°C; mobile phase: Phase A: 15 mmoL/L sodium dihydrogen phosphate solution (pH 2.8), B Phase: methanol; flow rate: 1.0 mL/min; injection volume: 10 µL; gradient elution: 0‐12 min, A:B = 42:58, 12–28 min, A:B = 50:50, 28–35 min, A:B = 85:15. The excitation wavelength is 282 nm and the emission wavelength is 352 nm.

2.7. Quantitative real‐time PCR

Total RNA from mouse tissues was extracted using Biozol reagent (LABSELECT, China), and RNA was reversed into cDNA using UEIris RT mix with DNase (US Everbright, China). The cDNA sample was mixed with SYBR mixture (US Everbright, China) according to the ratio described in the instruction manual, and analyzed using a LightCycler 96 (Roche, Switzerland) fluorescence quantitative PCR instrument. The instrument parameters were set according to the instruction manual. Using glyceraldehyde‐3‐phosphate dehydrogenase (GAPDH) as a control, use the ΔΔCt calculation method to calculate the relative expression of the target gene. The primers used in this study are listed in Table S2.

2.8. Hematoxylin and eosin staining and Alcian staining

The procedure of hematoxylin and eosin (H&E) staining followed previous studies. ³³ Paraffin‐embedded tissue sections were dewaxed and rehydrated with xylene and graded ethanol for 5 min each, washed three times with PBS, and stained with hematoxylin. After acidification and washing, it was stained with eosin dye (StatLab) and then dehydrated. Finally, the tissue sections were sealed with neutral gum and observed under a light microscope (Olympus, Tokyo, Japan). And the procedure of Alcian staining followed previous studies. ³⁴ Colonic tissue sections were stained with Alcian‐Blue/Nuclear‐Fast‐Red. The colon tissue sections were bserved atlight microscope (Olympus, Tokyo, Japan). The Image J software was used for quantitative analysis.

2.9. Immunofluorescence staining

The immunofluorescence staining procedure was similar to previous studies. ³⁵ Tissue sections were dewaxed and dehydrated with xylene and graded ethanol. Then, the sections were incubated with β‐amyloid (6E10) mouse monoclonal antibody (lot number SIG‐39320) (1:1000; Biolegend, USA), Iba‐1 rabbit monoclonal antibody (1:1000; abcam, UK). Incubate overnight at 4°C. After incubation, slides were washed with PBS and incubated with secondary antibodies for 20 min. DAPI (4′,6‐diamidino‐2‐phenylindole) is then used to seal the sections. Then, immunofluorescence staining images were obtained using an inverted fluorescence microscope (Olympus, Tokyo, Japan). Positive areas were also quantified by ImageJ.

2.10. Safety test of L. suilingensis AF91‐01CMCA

Serum samples were used for safety testing. The detection of ALB, ALT, BUN, and AST was carried out according to the instructions of the kit (Jiancheng, China), a standard curve was established, and the content was calculated.

2.11. Statistical analysis

Sequencing data were analyzed by Wilcoxon test to determine significant differences between groups. Other data were verified by analysis of variance or unpaired T‐test using Dunnett's test in GraphPad Prism 8.3. Correlation analyzes were established by Pearson linear regression using the software program R (V 3.1.1). Data are reported as mean ± standard error of the mean (SEM), and p < 0.05 was considered statistically significant.

3. RESULTS

3.1. Differences in tryptophan metabolism between preclinical AD and HC

To investigate differences in tryptophan metabolism‐related genes of gut microbiota between preclinical AD patients and HC, the sequencing data of stool samples obtained from the study by Ferreiro et al. were reanalyzed. ³² The cohort consisted of 49 preclinical AD patients (AD) and 115 HC. Based on existing literature, the process of tryptophan metabolism and the key enzymes involved in microbial pathways were summarized, as illustrated in Figure 1A. The gene abundance of key enzymes involved in each step of tryptophan metabolism in stool sample sequencing data was analyzed in this study. The results showed that the gene encoding L‐amino acid oxidase, involved in IPyA synthesis, was enriched in AD. In contrast, the gene for aromatic 2‐oxoacid reductase, which is associated with ILA production, was significantly lower in AD compared to HC (Figure 1B). In the downstream metabolism of ILA, six genes annotated as fldBC enriched in AD, with one enriched in the HC (Figure S1A). Meanwhile, the gene annotated as ArAT, Tam1, and acdA exhibited no significant difference between the two groups (Table S1). During the metabolism of other indole derivatives (Indole, Tryptamine, et al.), no significant difference in the abundance of metabolic genes were observed between HC and AD (Figure S1B–D, Table S1). This result revealed that IPyA was more prone to accumulate in the gut of preclinical AD patients, whereas in HC, IPyA was more likely to be metabolized into ILA.

FIGURE 1.

Differences in tryptophan metabolism in preclinical AD patients, and formulate for ILA‐producing synbiotic. (A) Tryptophan microbial metabolic pathway in the gut. The metabolites are represented in black text, while the enzymes involved in the metabolic process are shown in red text. (B) A total of 154 human samples (49 preclinical AD patients and 115 HC) were analyzed. Plot delineated the notable difference in the abundance of IL4I and fldH sourced from gut microbiota between preclinical Alzheimer's disease patients and healthy controls. The bar chart on the left illustrated gene abundance, while the heatmap on the right displays the distribution of the genes' LDA values (adjusted p‐value < 0.05), as ascertained through linear discriminant analysis. (C) Heatmap described that annotation of genes involved in ILA synthesis in 23 strains, including ArAT, IL4I, Tam1, and fldH. (D) Content of ILA in MRS Culture Medium. Data are presented as the mean ± SEM. n = 3 tube, Statistical analyses were performed using Ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. (E) Radar plot illustrated the oligosaccharide metabolism genes in L. suilingensis AF91‐01CMCA. The "copy number" refers to the annotated count of specific oligosaccharide metabolism genes, while "identity" indicated the percentage of alignment similarity for the specific oligosaccharide metabolism genes. (F) Growth curve of L. suilingensis AF91‐01CMCA in 10 g/L different carbon source medium. Data are presented as the mean ± SEM. n = 3. (G) Growth curves of in different inulin concentrations. Data are presented as the mean ± SEM. n = 3. (H) Content of ILA in GAM and GAM+20 g/L INU Culture Medium. Data are presented as the mean ± SEM. n = 3 tube, Statistical analyses were performed using unpaired T test (two tailed), *p < 0.05, **p < 0.01. acdA, 3‐(aryl)acrylate reductase; AD, Alzheimer's disease; ANOVA, analysis of variance; ArAT, aromatic amino acid aminotransferase; ArAT, aromatic amino acid aminotransferase; fldBC, (R)‐3‐(aryl)lactoyl‐CoA dehydratase; fldH, aromatic 2‐oxoacid reductase; fldH, aromatic 2‐oxoacid reductase; HC, healthy individuals; IA, indole‐3‐acrylate acid; IAA, indole‐3‐acetic acid; IAAld, indole‐3‐acetaldehyde; IL4I, L‐amino acid oxidase; ILA, indole‐3‐lactic acid; INU, inulin; IPA, indole‐3‐propionic acid; IPyA, indole‐3‐pyruvate acid; LDA, linear discriminant analysis; MOS, mannooligosaccharides; SEM, standard error of the mean; Tam1, tryptophan aminotransferase; Tam1, tryptophan aminotransferase; XOS, xylooligosaccharide.

3.2. in vitro selection of high ILA‐producing bacterial strains and synbiotic formulation

To screen for a strain with high ILA production capacity, we analyzed the genomic information of strains in the Cultivated Genome Reference (CGR) database, which was previously formulated. ³⁶ , ³⁷ Initially, all strains (3324 strains) from the CGR2 database (ANI > 97%) were clustered, resulting in 527 representative strains. Functional annotation was performed on these 527 strains, and those containing two enzymes necessary for ILA synthesis were identified using Tam1, ArAT, IL4I, and fldH as screening criteria, yielding 157 strains. These strains were then further filtered based on the species listed in the “List of Microorganisms That Can Be Used in Food” issued by the National Health Commission of China in 2022, resulting in 23 strains (Table S3). Among these, four probiotic strains with high ILA production potential—AF91_01CMCA, AF11_6H, OM09_1A, and AF61_17pH5T—were identified, as they contain the four enzymes required for ILA synthesis (Figure 1C). Further, HPLC analysis revealed that ILA can be detected in the fermentation broth of the four strains (Figure 1D), with Lacticaseibacillus suilingensis AF91‐01CMCA producing higher levels of ILA compared to the other three strains. Considering that carbon sources can promote the growth of strains and enhance their metabolic capabilities, the carbohydrate metabolism genes of L. suilingensis AF91‐01CMCA were analyzed. There were multiple enzymes related to carbohydrate metabolism in L. suilingensis AF91‐01CMCA, among which enzymes were related to the metabolism of inulin, XOS, and MOS (Figure 1E). Growth curve analysis was applied to identify the optimal carbon source of L. suilingensis AF91‐01CMCA. As shown in Figure 1F and Figure S2A‐C, the growth rate of L. suilingensis AF91‐01CMCA with inulin added was higher than MOS and XOS.

Furthermore the growth of L. suilingensis AF91‐01CMCA in a culture medium containing varying concentrations of inulin were analyzed (Figure 1G), results showed that as the inulin concentration increased, the growth curve improved; however, there was no significant difference when 20 g/L, 30 g/L, or 40 g/L concentrations of inulin were added. Finally, the effect of inulin on the ILA‐producing capability of L. suilingensis AF91‐01CMCA were studied (Figure 1H). It was shown that noted a significant enhancement in ILA production in the medium supplemented with 20 g/L inulin compared to the GAM group. Consequently, we formulated a synbiotic combination of inulin and L. suilingensis AF91‐01CMCA for high ILA production.

L. suilingensis AF91‐01CMCA was isolated from healthy human fecal, genetic analysis demonstrated the absence of toxic genes in L. suilingensis AF91‐01CMCA. To evaluate its safety in vivo, a 4‐week animal experiment was conducted. The results revealed that 4‐week supplementation of L. suilingensis AF91‐01CMCA had no significant impact on the liver coefficient, kidney coefficient, indicating no damage to the liver and kidneys (Figure S3A‐B). BUN was used to evaluate the kidney function of mice, while ALB, ALT, and AST were used to assess liver function and liver damage in mice. The results indicated that supplementation with L. suilingensis AF91‐01CMCA had no significant effect on the contents of BUN and ALB in serum, and there were no significant changes in the enzyme activities of AST and ALT in serum. (Figure S3C‐F). These findings support the safety of L. suilingensis AF91‐01CMCA.

3.3. Synbiotic treatment alleviates cognitive impairment in female AD mice

The female 5×FAD animal model was used to assess the effects of synbiotics on AD. The experimental design flow chart is shown in Figure 2A. Throughout the experiment period, the supplementation of prebiotics, probiotics, and synbiotics had no significant impact on the body weight, food intake, and water intake of AD mice (Figure 2B–E). The open field test was employed to evaluate the locomotor activity of mice (Figure 2F), and results showed no significant differences in locomotor activity between the groups. In addition, prebiotic, probiotic, and synbiotic interventions were also performed in WT mice (Figure S4A). Consistent with the findings in AD mice, no significant effects were observed on the body weight, food intake, water intake, or locomotor activity of WT mice (Figure S4B–E). The Barnes maze test and NOR test were conducted to assess the learning and memory of mice. As shown in Figure 2G–I, AD mice exhibited impaired learning and memory abilities. Compared to the AD group, synbiotic treatment significantly improved the exploration time and distance in the target quadrant for AD mice, and is superior to probiotic or prebiotic supplementation alone. Additionally, results from the NOR test showed that the discrimination index of AD mice was significantly lower than that of WT mice (Figure 2J). However, synbiotic treatment also significantly improved the discrimination index of AD mice. In contrast, no significant differences in cognitive abilities were observed in WT mice following any of the three interventions (Figure S4F‐H). These results indicated synbiotic treatment could alleviate the impaired learning and memory abilities of female AD mice. 

FIGURE 2.

Effects of synbiotic supplementation on the cognitive function in female AD mice. (A) Experimental flow diagram. (B) Food intake and (C) water intake during the 4 weeks of treatment. (D) Body weight and (E) body weight gain during the 4 weeks of treatment. (F) Total distance in open field test. (G) Barnes maze area division map. (H) The time radio of target quadrant in Barnes maze test. (I) Total distance in target quadrant in Barnes maze test. (J) Discrimination index in new object recognition test. Data are presented as the mean ± SEM. (B,C) n = 8–10 mice per group, two cages (4‐5 mice / cage); (D–F) n = 8–10 mice per group; (H–J) n = 6–9 mice per group. Statistical analyses were performed using Ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. ns indicates no significant difference. AD, Alzheimer's disease; ANOVA, analysis of variance; SEM, standard error of the mean.

3.4. Synbiotic treatment alleviates neuronal damage, Aβ accumulation, and neuroinflammation in female AD mice

The tissue staining and quantitative real‐time PCR (qRT‐PCR) analysis of brain were performed to further investigate the effects of synbiotics on the pathological changes in female AD mice. H&E staining results showed that AD mice exhibited nuclear pyknosis in the cortex, CA1, and DG areas of the brain compared to the WT (Figure 3A, Figure S5A), which indicates functional abnormalities in the AD mouse brains. However, synbiotic treatment was effective in preventing neuronal cell damage. Additionally, synbiotic treatment was found to counteract the reduction in brain‐derived neurotrophic factor (BDNF) mRNA levels in the cortical region of AD mice (Figure 3C). Immunofluorescence staining of Aβ_1‐42 in mouse brain revealed significant Aβ deposition in the cortex, CA1, and DG area of AD mouse brains (Figure 3B,D, Figure S5B,D, and E). Supplementing with synbiotics significantly reduced the Aβ‐positive area in the cortex, CA1, and DG region. Notably, it is worth noting that the effectiveness of synbiotic surpasses that of probiotics or prebiotics alone. Furthermore, the expression of genes associated with Aβ production was investigated (Figure 3E,F). The mRNA expression levels of APP and beta‐secretase 1 (BACE1) were significantly upregulated in the cortex of AD mice, while synbiotic treatment significantly inhibited these mRNA expression levels, surpassing the effects of probiotics or prebiotics alone.

FIGURE 3.

Effects of synbiotic supplementation on neuronal damage, Aβ accumulation and neuroinflammation in female AD mice. (A) Representative images of H&E staining in the cortex. Scale bars, 100 µm. (B) Representative images of immunofluorescence staining of Aβ and Iba‐1 in the cortex. Scale bars, 200 µm for Aβ; 100 µm for Iba‐1. (C) The mRNA relative expression of BDNF in the hippocampus. (D) The quantification of Aβ accumulation area in the cortex. (E, F) The mRNA relative expression of APP and BACE1 in the hippocampus. (G) The quantification of Iba‐1 positive area in the cortex. (H–J) The mRNA relative expression of TNF‐α, COX‐2, and IL‐1β in the cortex. Data are presented as the mean ± SEM. (C,E,F, H–J) n = 6 mice per group; (D,G) n = 3 slices per group. Statistical analyses were performed using Ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. ns indicates no significant difference. Aβ, amyloid β‐protein; ANOVA, analysis of variance; APP, amyloid precursor protein; BACE1, beta‐secretase 1; BDNF, brain‐derived neurotrophic factor; COX2, cyclooxygenase‐2; Iba‐1, ionized calcium‐binding adapter molecule 1; IL‐1β, interleukin‐1β; SEM, standard error of the mean; TNF‐α, tumor necrosis factor‐alpha.

Neuroinflammation represents another feature of AD pathology. Immunofluorescence staining of Iba‐1 was used to evaluate the status of microglia. The staining results revealed morphological alterations in microglia in the cortex, CA1, and DG areas of AD mouse brains (Figure 3B,G, Figure S5C,F, and G). Specifically, the cell bodies of microglia became enlarged, while their dendrites were shortened, indicating microglial activation. Additionally, there was a significant expansion in the Iba‐1 positive area. Treatment with prebiotics, probiotics, and synbiotics could significantly reduce the proportion of the Iba‐1 positive area, and synbiotics exhibit a more pronounced effect. Subsequently, the mRNA expression levels of inflammatory factors in the cortex regions of mice were evaluated by RT‐PCR (Figure 3H–J). The results showed a significant upregulation of the mRNA expression levels of tumore necrosis factor‐α (TNF‐α), cyclooxygenase‐2 (COX2), and interleukin‐1β (IL‐1β) in AD mice compared to WT. Synbiotic treatment notably decreased the expression levels of these inflammatory factors. In summary, synbiotic treatment could enhance the morphology of neuronal cells in female AD mice, reduce the generation and accumulation of Aβ in the brain, and alleviate neuroinflammation.

3.5. Effects of synbiotic treatment on the gut microbiota structure of female AD mice

To investigate the effects of synbiotic treatment on the gut microbiota of female AD mice, fecal samples were subjected to metagenomic sequencing. As shown in Figure 4A,B, different microbial compositions were observed between WT, AD, and AS groups at the levels of phylum and genus. Compared to AD group, the relative abundance of Verrucomicrob was increased, while Deferribacteres was decreased in the gut microbiota of AS group (Figure 4C,D). Probiotic and prebiotic treatments also altered the gut microbiota structure of AD mice, with prebiotic treatment significantly reducing the levels of phylum Proteobacteria and Deferribacteres (Figure S6A,B). In addition, compared to the AD group, the α and β diversity of gut microbiota in AD mice was significantly decreased by synbiotic treatment, while probiotics and prebiotics treatment had no significant effect on the diversity of gut microbiota (Figure 4E,F, Figure S6C–F). This result demonstrated that synbiotic intervention could significantly alter the composition and structure of the gut microbiota in AD mice. Subsequently, LEfSe analysis was performed to observe the taxonomic changes at the species level. As shown in Figure 4G, Synbiotic treatment increased the relative abundance of Akkermansia muciniphila and Lactiplantibacillus plantarum in the gut microbiota compared to the AD group. Notably, the abundance of Enterococcus faecium and Enterococcus hirae were enriched in the AD group, while treatment with probiotics, prebiotics, and synbiotics significantly reduced their abundance in AD mice (Figure 4G, Figure S7A–C). As L.suilingensis AF91‐01CMCA was a newly isolated species within the Lacticaseibacillus, we conducted an additional comparative analysis of the genome of L.suilingensis AF91‐01CMCA against mouse gut metagenomic data, revealing that the relative abundance of L.suilingensis AF91‐01CMCA significantly increased following synbiotic treatment (Figure 4H). To investigate the relationship between changes in gut microbiota and AD pathological indicators, correlation analysis was performed between the top 30 genera in abundance and behavioral tests and biochemical indicators. Consequently, Akkermansia and Blautia, which increased after synbiotic treatment, exhibited a positive correlation with cognitive function levels and a negative correlation with cortical inflammation levels. The relative abundance of Enterococcus was observed to be significantly decreased in the AS, AL, and WT groups, exhibiting a statistically negative correlation with the Barnes Target Quadrant Exploration Time of the mice (Figure 4I). These results suggest that synbiotics can modulate the composition of the gut microbiota, which is associated with the therapeutic effects of synbiotics in alleviating cognitive impairment in female AD mice.

FIGURE 4.

Effects of synbiotic on the gut microbiota structure of female AD mice. (A) Bar plot illustrated community analysis of gut microbiota in AD, AS, and WT groups at phylum level. (B) Bar plot showed community analysis of gut microbiota in AD, AS, and WT groups at genus level. (C) Difference in the abundance of of Verrucomicrobia in AD, AS, and WT groups. (D) Discrepancy in the abundance of Deferribacteres in AD, AS, and WT groups. (E) Box plot illustrated the alpha‐diversity of gut microbiota in the AD, AS, and WT groups, assessed using the Shannon and Simpson indices. (F) Gut microbiota beta‐ diversity in the AD, AS, and WT groups, assessed by PCoA, incorporating PERMANOVA (permutational multivariate analysis of variance). (G) Plot showed the differential abundance of the indicated species in the gut microbiomes of AS group and AD group, with an adjusted p‐value of less than 0.05. Only species with LDA scores greater than 2 are shown in the plot. (H) The relative abundance of L. suilingensis AF91‐01CMCA in AD, AS, and WT groups. (I) Upper heatmap illustrated the difference in the abundance of the top 30 genera of gut microbiota across the AS, AL, WT, and AD groups. Red indicated enrichment in the AS, AL, or WT groups, while blue signified genera that are enriched in the AD group. Lower heatmap depicted the correlation of the top 30 genera with behavioral and biochemical indicators. Red represented a positive correlation, while purple indicated a negative correlation. The size of each square reflected the absolute value of the correlation coefficient. Data are shown as mean ± SEM. (A–G) n = 8–9 mice per group. (H) n = 6–9 mice per group. (I) n = 8–9 mice per group. Differential analysis at the phylum and genus levels was conducted using the Wilcoxon test method, with significance set at p < 0.05 to identify differences. *p < 0.05, **p < 0.01. ns indicates no significant difference. AD, Alzheimer's disease; AL, L sp. AF91 treatment group; AS, synbiotic treatment group; LDA, linear discriminant analysis; PCoA, principal coordinate analysis; SEM, standard error of the mean; WT, wild‐type.

3.6. Effects of synbiotic treatment on the metabolic function of gut microbiota in female AD mice

To assess the metabolic functions affected by synbiotic treatments, the gene abundance of the gut microbiota was analyzed. The results of beta diversity analysis suggested a remarkable differentiation in the metabolic functions of gut microbiota between the groups of AD and AS (Figure 5A). Gene set enrichment analysis revealed that the treatment of synbiotics resulted in a significant upregulation of glycoprotein‐N‐acetyl galactosamine 3‐beta‐galactosyltransferase (Figure 5B). Furthermore, compared with AD group, some genes were increased in AL group, they were involved in the pathway of glycerol lipid metabolism (K22251: golD), butanoate metabolism (K01574: adc, K01799: maiA), pentose and glucuronate interconversions (K17818: ARD1), and alanine metabolism (K19244: Ala), these genes were also upregulated in WT group (Figure S8A–D). Intriguingly, no upregulated genes were found between the AI group and the AD group (Figure S8E,F). Moreover, in the AL group compared to the AD group, short‐chain fatty acid‐related metabolic activity was increased, while sulfur metabolism and RNA degradation pathways were decreased (Figure S8G). In the AS group, pantothenate and CoA biosynthesis, C5‐branched dibasic acid metabolism, and nitrotoluene degradation were elevated compared to the AD group (Figure 5C). Intriguingly, pantothenate and CoA biosynthesis and C5‐branched dibasic acid metabolism were also elevated in the WT group (Figure 5D). However, inulin treatment might not affect the function of gut microbiota in AD mice.

FIGURE 5.

Effects of synbiotic on the gut microbiota function of female AD mice. (A) Gut microbiota functional beta diversity in AD and AS groups. It was evaluated by using PCoA with statistical analyses including PERMANOVA (permutational multivariate analysis of variance). (B) Volcano plot portrayed the differentially expressed genes derived from gut microbiota between AD and AS groups (The selection criteria: FDR > 0.2 and |log FC | > 1). Dots with blue colors represented up‐regulated genes in AS group, and yellow colors showed up‐regulated genes in AD group. (C) Differential abundance of metabolic pathways in the gut microbiomes of the AS group and AD group, with an adjusted p‐value of less than 0.05. Only metabolism pathways with LDA scores greater than 2 were shown in the plot. (D) The abundance of metabolic pathways (LDA > 2) in gut microbiota of WT group and the AD group (adjusted p‐value < 0.05). (E) Representative image of H&E staining and Alcian staining in the colon. Scale bars, 100 µm. (F) Quantification of the Villus length based on H&E staining using ImageJ software. (G) Quantification of goblet cells area based on Alcian staining using ImageJ software. (H,I) Relative expression of MUC2 and TNF‐α mRNA in the colon. Data are presented as the mean ± SEM. (A) n = 8–10 mice per group; (B–D) 8‐9 mice per group; (F–G) n = 3 slices per group (three quantitative values for each slice); (H,I) n = 6 mice per group. Statistical analyses were performed using Ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. ns indicates no significant difference. AD, Alzheimer's disease; adc, acetoacetate decarboxylase; Ala, alanine dehydrogenase; ANOVA, analysis of variance; ARD1, D‐arabinitol dehydrogenase (NADP+); AS, synbiotic treatment group; FDR, false discovery rate; gold, glycerol dehydrogenase; H&E, hematoxylin and eosin; LDA, linear discriminant analysis; maiA, maleate isomerase; MUC2, mucin 2; PCoA, principal coordinate analysis; SEM, standard error of the mean; TNF‐α, tumor necrosis factor‐α.

3.7. Synbiotic treatment alleviates intestinal barrier dysfunction in female AD mice

H&E staining and Alcian staining were used to observe the effects of synbiotics treatment on intestinal barrier function in female AD mice. H&E staining results showed that the intestinal structure of AD mice was destroyed and the length of intestinal villi was significantly shortened. However, after treatment with probiotics and synbiotics, the intestinal structure was restored and the length of intestinal villi was significantly increased (Figure 5E,F). Alcian staining was employed to evaluate the quantity of goblet cells in the mice intestine. The results shown in Figure 5E and G, the area ratio of goblet cells in the intestine of AD mice was significantly lower than that of WT mice, while treatments of probiotics and synbiotics could significantly increase the area ratio of goblet cells. MUC2 is a mucin secreted by goblet cells and is an important component of the intestinal chemical barrier. The results of RT‐PCR showed that the expression of MUC2 mRNA in the intestine of AD group was significantly decreased compared with WT (Figure 5H). Treatments with either probiotics or synbiotics significantly elevated MUC2 expression. In addition, elevated mRNA expression of TNF‐α was observed in the intestines of AD mice, and all three treatments significantly decreased its levels (Figure 5I). The above results demonstrate that synbiotics significantly enhance the intestinal barrier function in female AD mice.

3.8. Synbiotic affects tryptophan metabolism in gut microbiota and activates AhR signaling pathway

Furthermore, to investigate the effects of synbiotics on ILA production in the gut microbiota, the abundance of genes including ArAT, fldH, IL4I, and Tam1 was analyzed (Figure 6A). Compared with the AD group, synbiotic treatment significantly increased the abundance of most ILA metabolism genes in the AS group. To confirm whether alterations in gene abundance directly influenced ILA content in vivo, ILA contents in fecal and serum samples were detected by HPLC (Figure 6B and C). These experimental findings indicated that both fecal and serum samples from AD mice exhibited significantly lower ILA content than those from WT mice. However, synbiotic treatment substantially increased ILA content in the fecal and serum samples of AD mice. Additionally, research has indicated that ILA serves as an AhR ligand, activating the AhR signaling pathway and inhibiting the NF‐κB signaling pathway, thereby mitigating the inflammatory response. ¹⁴ Consequently, Cyp1a1, Cyp1a2, and IL‐22 were detected by RT‐PCR to evaluate AhR signaling pathway activation. The results revealed that the relative expression levels of Cyp1a1, Cyp1a2, and IL‐22 in the AD group were significantly lower than those in the WT group. However, synbiotic treatment significantly increased the expression of these genes (Figure 6D,F). In order to explore the relationship between ILA content in vivo, AhR signaling pathway activation and biochemical indicators of AD, a correlation analysis was conducted. The results showed that the levels of ILA in fecal may directly increase the ILA content and was positively correlated with ILA content in serum and the expression of intestinal MUC2, but negatively correlated with the expression of intestinal TNF‐α (Figure 6G, Figure S9A,B). In addition, the serum ILA levels was positively correlated with the expression levels of Cyp1a1, Cyp1a2, IL‐22 and BDNF, and negatively correlated with the expression of APP and BACE1 (Figure 6H–M). These results suggest that synbiotic treatment increases ILA synthesis in vivo, and the increased ILA level is associated with AhR signaling pathway activation and the alleviation of AD‐related pathologies.

FIGURE 6.

Synbiotic affect tryptophan metabolism in microbiota and activate AhR signaling pathway. (A) Heatmap illustrated the differentially expressed genes associated with ILA synthesis in the gut microbiota of the AS and WT groups in comparison to the AD group, providing a detailed representation of the abundance of genes, with columns representing the various groups and rows denoting the specific genes. (B) The content of ILA in feces. (C) The content of ILA in serum. (D–F) The mRNA relative expression of Cyp1a1, Cyp1a2, and IL‐22 in the hippocampus. (G) Linear correlation analysis between ILA in serum and ILA in feces. (H‐M) Linear correlation analysis between the mRNA relative expression of Cyp1a1 (H), Cyp1a2 (I), IL‐22 (J), BDNF (K), APP (L), BACE1 (M), and ILA in serum. Data are presented as the mean ± SEM. (A) n = 8–10 mices per group; (B,C) n = 6–8 mices per group; (D–F) n = 5–6 mice per group. Statistical analyses were performed using Ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. AD, Alzheimer's disease; AhR, aryl hydrocarbon receptor; ANOVA, analysis of variance; APP, amyloid precursor protein; ArAT, aromatic amino acid aminotransferase; BACE1, beta‐secretase 1; BDNF, brain‐derived neurotrophic factor; Cyp1a1, cytochrome P450 1A1; Cyp1a2, cytochrome P450 1A2; fldH, aromatic 2‐oxoacid reductase; IL4I, L‐amino acid oxidase; ILA, indole‐3‐lactic acid; IL‐22, interleukin 22; Tam1, tryptophan aminotransferase.

3.9. ILA alleviates cognitive impairment and pathology in female AD mice by activating AHR

AhR is a nuclear receptor, and the activation of its signaling pathway can regulate the expression of various inflammatory factors, thereby influencing inflammatory processes. To investigate whether the therapeutic effects of synbiotics on female AD mice are mediated by increased ILA and AHR activation, in vivo experiments were conducted using ILA supplementation and AHR inhibitors. The experimental design for the animal study is illustrated in Figure 7A. After 4 weeks of intervention, the cognitive function of the mice was assessed using the Barnes maze. As shown in Figure 7B,C the exploration time and distance in the target quadrant of AD mice were significantly lower compared with WT mice. Supplementation with ILA significantly increased the exploration time and distance in the target quadrant of AD mice. However, the beneficial effect of ILA was abolished following AHR signaling inhibition with CH223191. The ILA content in serum was detected by HPLC. The serum ILA content in AD mice was significantly lower than that in WT mice, whereas ILA supplementation significantly increased serum ILA levels in AD mice, with no significant difference observed between the AD+ILA group and AD+ILA+CH2223191 group (Figure 7D). The expression levels of AHR target genes in the cortex were analyzed. The results showed that the relative expression levels of Cyp1a1 and IL‐22 in AD mice were significantly lower than those in WT mice. ILA supplementation significantly upregulated the expression of these target genes, but this effect was abolished following treatment with CH223191 (Figure 7E,F).

FIGURE 7.

ILA alleviates cognitive impairment and pathology in female AD mice by activating AhR. (A) Experimental flow diagram. (B) Total distance in target quadrant in Barnes maze test. (C) The time radio of target quadrant in Barnes maze test. (D) The content of ILA in serum. (E,F) The mRNA relative expression of Cyp1a1, and IL‐22 in the cortex. (G) Representative images of immunofluorescence staining of Aβ and Iba‐1 in the cortex. Scale bars, 100 µm for Aβ; 100 µm for Iba‐1. (H) The quantification of Aβ accumulation area in the cortex. (I) The quantification of Iba‐1 accumulation area in the cortex. (J,K) The mRNA relative expression of IL‐1β, and TNF‐α in the cortex. Data are presented as the mean ± SEM. (B–F) n = 6 mice per group; (H,I) n = 2‐3 mice per group; (J,K) n = 6 mice per group. Statistical analyses were performed using ordinary one‐way ANOVA with Tukey's multiple comparison test. For Tukey's multiple comparison test, *p < 0.05, **p < 0.01. ns indicates no significant difference. AD, Alzheimer's disease; Aβ, amyloid β‐protein; ANOVA, analysis of varianceAhR, aryl hydrocarbon receptor; Cyp1a1, cytochrome P450 1A1; Iba‐1, ionized calcium‐binding adapter molecule 1; IL‐1β, interleukin‐1β; IL‐22, interleukin 22; ILA, indole‐3‐lactic acid; TNF‐α, tumor necrosis factor‐α.

The accumulation of Aβ in the brain was analyzed by immunofluorescence staining. Aβ plaques were observed in the brains of AD mice. ILA supplementation significantly reduced the proportion of Aβ positive areas, but the effect disappeared after using CH223191 to inhibit AHR (Figure 7G,H). Neuroinflammation was evaluated by Iba‐1 immunofluorescence staining and the expression of inflammatory factors. Compared with WT mice, microglia in AD mice exhibited enlarged cell bodies and shortened dendrites, along with a significant increase in the Iba‐1 positive area. ILA supplementation significantly reduced the Iba‐1 positive area and alleviated microglia activation. However, co‐administration of CH223191 with ILA had no significant effect on the Iba‐1 positive area (Figure 7G and I). Additionally, the relative expression levels of TNF‐α and IL‐1β were significantly higher in the brains of AD mice compared to WT mice. Supplementation with ILA significantly reduced the relative expression of these inflammatory factors; however, co‐supplementation with CH223191 had no noticeable effect on their expression (Figure 7J,K).

These results suggest that ILA supplementation can mitigate neuroinflammation, reduce Aβ deposition, and alleviate cognitive impairment in female AD mice, with these effects being AHR‐dependent in the brain.

4. DISCUSSION

Previous studies have shown that tryptophan metabolism is disrupted in AD patients and animal models, with reduced levels of specific MTCs compared to HC. ⁶ , ¹³ However, the causes of this metabolic imbalance and whether targeted modulation of microbial tryptophan metabolism could offer therapeutic benefits remain unclear. In this study, we comprehensively analyzed genes involved in tryptophan microbial metabolism in the gut microbiota of preclinical AD patients and identified a reduced abundance of genes associated with the biosynthesis of ILA compared to HC. We hypothesized that restoring this pathway may help mitigate AD progression. Through gene analysis and in vitro culture testing, we formulated a synbiotic combination L. suilingensis and inulin, which has the ability to produce ILA, and evaluated the safety of synbiotics through genetic analysis and animal experiments. In addition, our findings show that synbiotic supplementation can effectively improve the learning and memory abilities of female 5×FAD mice, alleviating the progression of AD through the ILA/AhR/neuroinflammation pathway.

The progression of AD is frequently accompanied by alteration in the composition of the gut microbiota and damage to the intestinal barrier. ³ , ³⁸ , ³⁹ Previous studies reported that in AD mice, the relative abundance of Akkermansia and Lactobacillaceae was significantly lower than that in WT mice, and supplementing with Akkermansia or Lactobacillus plantarum has been demonstrated to improve AD‐like pathology, such as reducing Aβ accumulation and alleviating learning and memory impairments. ⁴⁰ , ⁴¹ , ⁴² , ⁴³ Additionally, supplementation of prebiotics or probiotics can promote the enrichment of Akkermansia and Lactobacillaceae in the gut of AD mice. ⁴⁴ , ⁴⁵ , ⁴⁶ In this study, synbiotic supplementation changed the gut microbiota structure of AD mice and increased the abundance of Akkermansia and Lactobacillaceae. This change may be one of the mechanisms by which synbiotic alleviates AD symptoms. Furthermore, this study observed an increased abundance of Enterococcus in the gut microbiota of AD mice, which was reduced following synbiotic supplementation. Previous studies have reported that Enterococcus levels are elevated in AD patients compared to HC, which potentially contributes to increased serum inflammatory factors. ⁴⁷ Studies have also shown that Enterococcus supplementation exacerbates neuroinflammation and induces cognitive dysfunction. ⁴⁸ These findings suggest that the reduction in Enterococcus abundance may be one of the mechanisms by which synbiotics alleviate cognitive impairment in AD. In addition, our results indicate that synbiotic supplementation can modulate the metabolic function of gut microbiota, increasing the relative abundance of the glycoprotein‐N‐acetylgalactosamine 3‐beta‐galactosyltransferase in the gut of AD mice. It is reported that this gene is related to the synthesis of mucin, and the elevated mucin levels can promote the growth of mucin‐degrading bacteria such as Akkermansia, and maintain intestinal barrier function. ⁴⁹ , ⁵⁰ , ⁵¹ This finding also partially explains the intestinal barrier protective function of synbiotics and the increase in Akkermansia levels.

Recent studies have focused on tryptophan metabolism in neurodegenerative diseases and revealed an imbalance in tryptophan metabolism in AD patients. ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ , ⁵⁶ Various tryptophan metabolites, including ILA, 5‐hydroxytryptophan, indole‐2‐carboxylic acid, and 3‐(2‐hydroxyethyl) indole, are decreased in AD patients. ¹² , ¹³ This difference in tryptophan metabolism has been attributed to alterations in gut microbiota composition and changes in specific tryptophan‐metabolizing bacterial genera. ¹² , ²⁰ In the present study, a comprehensive analysis of gene abundances related to microbial tryptophan metabolic pathways revealed decreased biosynthesis of ILA in preclinical AD patients, providing a gene‐level explanation for the metabolic imbalance observed in AD. ILA, a microbial metabolite derived from tryptophan, is primarily produced by Lactobacillus species through the degradation of tryptophan. ¹¹ Key genes involved in the biosynthesis of ILA include ARAT, FldH, IL4I, and Tam1, which can serve as predictive markers for assessing the ILA‐producing capacity of bacterial strains. ²⁴ , ²⁹ , ⁵⁷ In this study, the correlation between these biosynthetic genes and ILA production in Lactobacillus was validated. Based on this gene‐guided screening, high ILA‐producing probiotic strains were identified. Furthermore, a precision‐designed synbiotic formulation with enhanced ILA yield was developed by optimizing the available carbon sources.

In addition, previous studies have shown that supplementing probiotics can modulate gut microbiota structure and tryptophan metabolism, increasing the levels of indole compounds in vivo, thus aiding in the prevention and treatment of AD. ¹⁵ , ³⁰ , ⁵⁸ Consistent with these findings, our results demonstrate that synbiotic supplementation regulates microbial tryptophan metabolism in AD mice, increases the abundance of ILA biosynthetic genes and the contents of ILA in vivo. However, the increase in these metabolic genes and ILA contents induced by synbiotic supplementation may also elevate other indole metabolites besides ILA. ⁵⁹ This potential outcome warrants further investigation in future studies, as these metabolites could contribute to the therapeutic effects or have other implications in AD pathology. Besides, synbiotic supplementation can reduce Aβ accumulation, inhibit neuroinflammation, and alleviate cognitive impairment in female AD mice. The protective effect of probiotic supplementation on AD has been reported. ⁶⁰ , ⁶¹ , ⁶² , ⁶³ , ⁶⁴ In AD animal models, supplementing probiotics such as Bifidobacterium breve and Bifidobacterium has shown an ameliorative effect, specifically by reducing neuroinflammation, improving synaptic function, and inhibiting Aβ accumulation. ⁶³ , ⁶⁴ Additionally, recent studies have demonstrated that in male animals, Lactobacillus supplementation can prevent cognitive impairment in AD mice, with this effect being associated with ILA production through Lactobacillus metabolism. ²² However, there remains a scarcity of research on the improving effect of synbiotics with specific metabolic functions on AD. Here, we report the role of synbiotics with the function of regulating tryptophan metabolism in alleviating the progression of AD and is more effective than probiotic supplementation alone. These results provide a reference for future research on synergistic synbiotics in the treatment of AD.

The critical role of AhR in gut‐brain signaling has been well‐established, with numerous gut microbiota metabolites influencing brain health through activation of the AhR signaling pathway. ⁶⁵ , ⁶⁶ Notably, most MTCs, including ILA, have been reported as ligands for AhR. ¹¹ , ⁶⁷ In the brain, AhR is expressed in various cell types such as microglia and astrocytes, it regulates the expression of anti‐inflammatory factors after activation and inhibit the activation of the NF‐κB signaling pathway. ⁶⁸ , ⁶⁹ , ⁷⁰ Research has confirmed that supplementing indole substances can activate AhR signaling pathway in the brain, reduce microglial activation and inhibit neuroinflammation through the AhR/NF‐κB signal pathway. ²⁰ , ⁷¹ Neuroinflammation is an important condition that promotes the development of AD in the early stages. Under inflammatory conditions, Aβ synthesis and accumulation are accelerated, thereby aggravating the deterioration of AD. ⁷² , ⁷³ In this study, synbiotic supplementation activated the AhR signaling pathway, inhibited microglial activation, and alleviated cognitive impairments in female AD mice, potentially through increased ILA contents in the body. Previous studies have reported that ILA facilitates Aβ clearance by enhancing phagocytosis in microglia and astrocytes in male AD mice, and this effect was shown to be AhR‐dependent based on in vitro experiments. ¹⁹ In the present study, ILA administration was also shown to alleviate cognitive deficits in female AD mice and provided in vivo evidence that its beneficial effects are mediated through AhR activation and suppression of neuroinflammation. These findings suggest that AhR‐targeted therapies may benefit both sexes, and the different mechanisms by which AhR contributes to relieving AD symptoms warrant further in‐depth investigation. Additionally, this study focused primarily on the mRNA expression levels of inflammatory factors. Future research should also consider the actual changes in the protein levels of these inflammatory factors in the brain.

In conclusion, this study identifies altered genes in tryptophan metabolism in the gut microbiota of preclinical AD patients, notably a decrease in ILA biosynthesis, suggesting that AD‐related microbial metabolic dysfunction may precede clinical symptom onset. Based on these changes, we designed a targeted synbiotic capable of modulating tryptophan metabolism. Supplementation with synbiotics can modulate the gut microbiota composition in female AD mice, regulate tryptophan metabolism, and enhance ILA synthesis in the body. The resulting increase in circulating ILA levels activates AhR in the brain, which inhibits microglial activation, reduces neuroinflammation, and alleviates cognitive impairments in female AD mice. This study provides new insights into microbiota‐targeted tryptophan metabolic modulation strategies for AD, and offers a methodological reference for the formulation of functionally synergistic synbiotics.

CONFLICT OF INTEREST STATEMENET

All authors declare no competing interests. Author disclosures are available in the Supporting Information.

CONSENT STATEMENT

This study was conducted on mice following a protocol approved by the Experimental Animal Center of Northwest A&F University. As no human subjects were involved, consent was not required.

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Yang C, Sun J, Li L, et al. Synbiotics of Lactobacillus suilingensis and inulin alleviates cognitive impairment via regulating gut microbiota indole‐3‐lactic acid metabolism in female AD mice. Alzheimer's Dement. 2025;21:1‐e70406. 10.1002/alz.70406