The novel synbiotic (Lactiplantibacillus plantarum and galacto-oligosaccharides) ameliorates obesity-related metabolic dysfunction: Arginine as a key mediator signaling molecule

Graphical abstract

Highlights

• •Identified a novel specific synbiotic that ameliorates obesity-related metabolic dysfunction.
• •Arginine is a crucial signal for the synbiotic’s effect, providing new insight into metabolic regulation.
• •Synbiotic intervention effectively improves metabolic indicators in obese individuals.

Abstract

Objective

This study aimed to develop a novel synbiotic composed of Lactiplantibacillus plantarum LLY-606 and galacto-oligosaccharides (GOS) to improve lipid metabolism in obesity.

Design

Through genome-wide analysis using COG and CAZy databases, we identified GOS as a specific growth substrate for Lactiplantibacillus plantarum LLY-606. The efficacy of this synbiotic (LP-GOS) was evaluated in both obese individuals and high-fat diet-induced obese mice.

Results

LP-GOS supplementation reduced visceral fat and waist circumference in humans and attenuated obesity in mice. It also improved gut microbiota composition and increased serum arginine levels. Metabolomic and microbiota analyses suggested that enhanced arginine production plays a key role. This was further confirmed by arginine synthesis inhibition, antibiotic treatment, and CRISPR-Cas9-mediated knockout of the Ass1 gene in Lactiplantibacillus plantarum LLY-606. These interventions demonstrated that LP-GOS improves lipid metabolism through arginine-mediated activation of the AMPK pathway.

Conclusions

LP-GOS effectively alleviates obesity-associated lipid metabolism disorders by enhancing arginine production and activating the AMPK signaling pathway.

Introduction

Obesity has become a global epidemic, presenting substantial health challenges and elevating the risk of numerous chronic diseases [[1], [2], [3]]. Although lifestyle modifications such as increased physical activity can be effective, they often require sustained effort and time. In contrast, pharmacological treatments may offer faster outcomes but are often associated with significant adverse effects. For instance, cardiovascular risks have been reported with medications such as sibutramine, fenfluramine, and dexfenfluramine. Additionally, anti-obesity drugs like rimonabant have been associated with an elevated risk of suicide, while central nervous system stimulants such as methamphetamine carry a high potential for dependence and abuse [4]. Therefore, there is a growing need for innovative, evidence-based strategies to address obesity more effectively.

Recent research has highlighted the critical role of gut microbiota in obesity development [5]. Several studies have indicated that obesity is associated with distinct alterations in gut microbiota composition. Notably, an elevated level of the opportunistic pathogen Enterobacter cloacae has been strongly linked to the onset and exacerbation of obesity, suggesting it may play a more central role in the pathophysiology of metabolic disorders [6]. In contrast, an increased abundance of beneficial bacteria such as Lactiplantibacillus, Bifidobacterium, and Akkermansia has been correlated with weight reduction and improved metabolic profiles [7]. These effects are largely mediated through microbial metabolites such as short-chain fatty acids, bile acids, and amino acids, which influence host metabolism and immune responses [8]. Therefore, targeted modifications to the composition and function of the gut microbiome represent a promising therapeutic approach for preventing obesity [9,10].

Synbiotic—combinations of probiotics and prebiotics—have emerged as a promising strategy for modulating gut microbiota to improve host metabolic health [11]. Studies in both humans and animals have shown that synbiotic can reduce weight gain, improve lipid profiles, and enhance gut barrier function [12,13]. Among potential probiotic candidates, Lactiplantibacillus plantarum, a strain commonly found in the human gut, exhibits strong acid and bile tolerance [14], anti-inflammatory effects [15], and the ability to restore gut microbiota balance and barrier integrity [16,17].

Given the potential of Lactiplantibacillus plantarum LLY-606 to modulate gut microbiota and metabolize specific substrates, the present trial aimed to design a novel synbiotic (LP-GOS) and evaluate its efficacy in alleviating obesity and lipid metabolism disorders in mice and humans, with a focus on mediating role of arginine.

Results

The LP-GOS combination of Lactiplantibacillus plantarum-GOS attenuates metabolic dysfunction in obese mice

Based on genome-wide analysis of Lactiplantibacillus plantarum LLY-606, we identified four carbon sources available to this species. The metabolic pathway is depicted in Supplementary Fig. S1A–1C. Notably, Lactiplantibacillus plantarum LLY-606 demonstrated a faster growth rate when cultured with oligomeric galactose compared to other carbon sources (Supplementary Fig. S1D). Consequently, we selected Lactiplantibacillus plantarum LLY-606 supplemented with GOS as a synbiotic for intervention for obesity management.

To investigate the impact of LP-GOS on HFD-induced obesity, we orally administered Lactiplantibacillus plantarum LLY-606, GOS, and LP-GOS to mice for 8 weeks. Among the groups, LP-GOS treatment resulted in the most pronounced inhibition of weight gain in obese mice (Fig. 1a and Supplementary Fig. 4A). LP-GOS supplementation significantly improved glucose tolerance, insulin sensitivity, fasting serum glucose levels, fasting insulin levels, and other metabolic parameters (Fig. 1B and Supplementary Fig. 6B–E). Moreover, LP-GOS treatment lowered serum leptin, triglycerides (TG), Total cholesterol (TC), and additional metabolic indicators compared to the HFD group (Fig. 1C and Supplementary Fig. 6F–H). The Mouse Respiratory Metabolic Analysis System observed changes in whole energy expenditure (HEAT) exclusively in the LP-GOS group (Fig. 1D–E). Subsequently, we investigated alterations in the hepatic and adipose tissues of obese mice. LP-GOS intervention reduced hepatic lipid accumulation and regulated the expression of lipid synthesis and lipolysis genes in the liver and adipose (Fig. 1G–I, Supplementary Fig. 6I–K). Western blot analysis corroborated these findings, revealing decreased peroxisome proliferator-activated receptor gamma (PPARγ) expression and increased AMP-activated protein kinase (AMPK) phosphorylation in the LP-GOS group (Fig. 1J–K). These findings underscore the potential therapeutic value of LP-GOS in alleviating metabolic dysregulation associated with obesity.

Fig. 1.

The LP-GOS combination of Lactobacillus Plantarum-GOS attenuates metabolic dysfunction in obese mice. (A) Body weight gain. (B) AUC of GTT and ITT. (C) Triglycerides and Total cholesterol (n = 8 mice per group). (D–E) Energy expenditure was determined by an indirect calorimetry system in 24 h (n = 4 mice per group). (F) Relative of Lactobacillus plantarum (n = 6 mice per group, except for HM group n = 5, due to sample degradation). (G) Representative H&E-staining images of the liver sections. Scale bars, 100 μm (n = 3 mice per group). (H) The mRNA levels of lipolysis gene in the liver for each group. (I) The mRNA levels of lipid synthesis gene in the liver for each group (n = 6 mice per group). (J–K) Western blot analysis of liver pparγ and P-AMPK/AMPK related signaling (n = 3 mice per group). All data were presented as mean ± SEM. Significant differences between mean values were determined by one-way ANOVA with Tukey’s multiple comparisons test. Unpaired T-tests was used for comparisons of the Relative abundance of Lactobacillus plantarum.

LP-GOS supplementation alters metabolic capacity in obese patients

Women and men with BMI ≥28 to ≤35 kg/m² aged 18–65 years (n = 60) who were enrolled and underwent randomization to receive either a placebo (n = 30) or synbiotic (n = 30) as a supplement for 3 months. A total of 20 participants were excluded from the final analysis for the following reasons: 12 were lost to follow-up, 4 withdrew due to antibiotic use or non-compliance with the diet/exercise protocol, and 4 were excluded owing to incomplete data collection. Consequently, 40 individuals were included in the safety analysis per-protocol, with more than 95 % adherence. The CONSORT Flow Diagram is depicted in Supplementary Fig. 2. No significant adverse events were observed during the study period. The experimental procedure There were no significant differences in baseline characteristics between the two groups (Supplementary Fig. 3). A summary of the key clinical indicators comparing placebo and synbiotic groups is provided in Supplementary Table 2. Specifically, although there was no significant change in body weight (Fig. 2A), anthropometric variables including BMI, fat mass (Fig. 2B), fat mass (Fig. 2C), fat percentage (Fig. 2D), visceral adipose tissue area (Fig. 2E), waist circumference (Fig. 2F), waist-to-hip ratio (Fig. 2G) and low-density lipoprotein cholesterol (LDL-C) levels were significantly reduced in the synbiotic group after the intervention compared to baseline values. Furthermore, no other anthropometric variables demonstrated statistically significant increases relative to baseline measurements (Supplementary Fig. 4). Furthermore, there was no statistically significant alteration observed in body composition parameters and serum lipid parameters within the placebo group (Supplementary Fig. 5). These findings suggest a potential beneficial effect of LP-GOS on obesity-related parameters, although no significant change in body weight was observed.

Fig. 2.

LP-GOS supplementation alters metabolic capacity in obese patients. (A–H) body composition parameters. (A) Body weight (B) BMI, (C) Fat mass, (D) Fat percentage, (E) Visceral adipose tissue area, (F) Waist, (G) Waist/hip ratio, (H) Low-density lipoprotein cholesterol (LDL-C). All data were presented as mean ± S.E.M. Wilcoxon-tests were used for pairwise comparisons (Placebo group n = 18, Synbiotic group n = 22).

The LP-GOS supplementation modulates the composition of the gut microbiota

We analyzed changes in gut microbiota after synbiotic intervention using 16S rDNA sequencing (V3-V4 regions). PLS-DA revealed significant differences in microbiota composition between the HFD and HS groups (Fig. 3A). At the phylum level, LP-GOS supplementation resulted in an increased abundance of the phyla Thickettsia and Desulfovibrio, while the abundance of the phylum Bacteroidetes decreased (Fig. 3B). Differential microbiota analysis at the OTU level revealed that LP-GOS intervention significantly increased the abundance of OTU109 (Erysipelatoclostridium), OTU281 (Lactobacillus plantarum), OTU333 (Desulfovibrionaceae), and OTU8 (Desulfovibrionaceae). In contrast, the abundance of OTU12 (Desulfovibrionaceae), OTU277 (Butyricimonas), and OTU293 (Muribaculaceae) decreased (Fig. 3C–D). Random Forest analysis identified Lactiplantibacillus plantarum as key biomarkers (Fig. 3E). Further analysis compared placebo and synbiotic groups over a three-month period revealed significant shifts in microbiota composition within the synbiotic group, as confirmed by Venn and PCoA analyses (Fig. 3F–G). Furthermore, Fig. 3H illustrates distinct alterations at both the phylum and genus levels. In the synbiotic group, these changes include a decrease in Firmicutes and an elevated abundance of Lactiplantibacillus, Bifidobacterium, Ruminococcus, and Bacteroidetes. Notably, the marked rise in Lactobacillus abundance suggests successful colonization of Lactiplantibacillus (Fig. 3I). Functional predictions (PICRUSt2) revealed enrichment in the amino acid biosynthesis pathway (Fig. 3J). Collectively, these findings demonstrate that LP-GOS intervention actively restores gut microbiota composition.

Fig. 3.

Impact of LP-GOS on gut microbiota in obese mice and obese patients. (A) The PLSDA analysis were used to test the difference in gut microbiota composition and diversity between groups. (B) The relative abundance of bacteria at the Phylum level. (C) A Z score-scaled heatmap of the relative abundance of bacteria at the OTU level. (D) Differential Analysis of Gut Microbiota by the Wilcoxon rank-sum test (*p < 0.05). (E) The plot of a random forest predicts potential microbial markers. (n = 6 mice per group). (F) Venn diagrams of ASV. (G) The plot of Principal Co-ordinates Analysis (PCoA). (H)Taxonomic distribution of Phylum and Genus. (I) Analysis of differences between Lactobacillus and Bifidobacterium. (J) Prediction of microbiome function by using PICRUST2 (Placebo group n = 18, Synbiotic group n = 22). All data were presented as mean ± S.E.M. Wilcoxon-tests were used for pairwise comparisons.

LP-GOS supplementation alters the composition of serum and fecal metabolites in obese mice

To evaluate the effects of LP-GOS supplementation on serum metabolites in mice, we conducted high-throughput targeted quantification. PLS-DA analysis revealed significant differences in metabolite profiles between the HFD and HS groups (Fig. 4A). Volcano plot highlighted key distinctive metabolites (Fig. 4B). LP-GOS supplementation significantly increased arginine while reducing arachidonic acid (Fig. 4C). Random Forest analysis identified arginine as a potential biomarker in the HS group (Fig. 4D). KEGG enrichment analysis revealed that pathways related to arginine biosynthesis and nitric oxide metabolism were significantly enriched following the intervention(Fig. 4E). Fecal metabolite analysis showed similar trends, with LP-GOS supplementation significantly altering metabolite composition. Consistent with serum results, fecal arginine levels also increased (Fig. 4F). Spearman's correlation analysis demonstrated that elevated arginine was negatively associated with body weight, LEP, LDL, TG, TC, fasting glucose, and fasting insulin levels in mice (Fig. 4G), suggesting a link between higher arginine levels and improved metabolic outcomes.

Fig. 4.

LP-GOS supplementation alters the composition of serum and fecal metabolites in obese mice. (A) The PLSDA analysis were used to test the difference in serum metabolites composition between groups. (B) A volcano plot of the abundance of serum metabolites between groups. (C) The difference in microbial metabolites in serum samples. (*p < 0.05) Differences were examined by Wilcoxon rank-sum test. (D) The plot of a random forest predicts potential markers for microbial metabolites. (E) KEGG pathway enrichment analysis of metabolites. (F) Differences in microbial metabolites in fecal samples. (G) Spearman's correlation analysis was performed to evaluate the relationship between biochemical indices and arginine levels in both serum and fecal samples of mice. (n = 6 mice per group).

Arginine plays an important role in the process of alleviating obesity through LP-GOS

To evaluate the role of arginine in mitigating HFD-induced metabolic impairments, we implemented an experimental design combining HFD with alpha-methyl-DL-aspartic acid (MDLA), an inhibitor of argininosuccinate synthase, followed by LP-GOS supplementation. The experimental timeline is visually represented in Fig. 5A. After an 8-week intervention period, the group receiving MDLA alongside LP-GOS (HS+ASS group) exhibited significantly higher body weight and blood glucose levels compared to the group treated with LP-GOS alone (HS group), although these parameters were still improved relative to the HFD group (Fig. 5B–C). Lipid metabolism was subsequently analyzed. The results demonstrated that LP-GOS supplementation significantly attenuated both lipid accumulation and adipocyte hypertrophy in HFD-fed mice. While this beneficial effect was partially attenuated by concurrent MDLA administration, LP-GOS treatment still maintained significant improvements in lipid metabolism parameters compared to the HFD group (Fig. 5D–G). The mechanism through which Arg enhances energy metabolism involves the Arginine-nitric oxide (NO) pathway, which stimulates the regulation of AMPK activity [18]. Serum measurements showed that MDLA reduced the LP-GOS-induced elevation of arginine and NO levels (Fig. 5H–J). Additionally, LP-GOS supplementation upregulated the phosphorylation of AMPK, an effect that was attenuated by MDLA intervention (Fig. 5K). These findings suggest that the elevated arginine levels induced by LP-GOS supplementation are critical for improving metabolic parameters, potentially through the activation of the arginine–NO–AMPK pathway.

Fig. 5.

Arginine plays an important role in the process of alleviating obesity through LP-GOS. (A) Experimental flow chart of animal treatments. (B) Body weight. (C) Blood glucose (n = 8 mice per group). (D) Representative H&E-staining images of the liver, eWAT and sWAT sections. Scale bars, 100 μm (n = 3 mice per group). (E) Liver mass. (F) eWAT and sWAT mass (n = 8 mice per group). (G) The mRNA levels of lipid metabolism genes in the liver for each group (n = 6 mice per group). (H) The mRNA levels of arginine metabolism genes in the liver for each group (n = 6 mice per group). (I) The level of arginine in serum (n = 6 mice per group). (I) The level of NO in serum (n = 6 mice per group). (K) Western blot analysis of liver P-AMPK/AMPK related signaling (n = 3 mice per group). All data were presented as mean ± SEM. Significant differences between mean values were determined by one-way ANOVA with Tukey’s multiple comparisons test.

Independent promotion of arginine synthesis by LP-GOS in improving obesity

In our previous study, we proposed that LP-GOS mitigates obesity by enhancing arginine production. However, MDLA does not completely eliminate the obesity-alleviating of LP-GOS. This led us to speculate that the gut microbiota might contribute to arginine production. To evaluate this, we eliminated endogenous microbiota in mice via antibiotics and repeated the experiment (Supplementary Fig. 7A). Antibiotic treatment significantly reduced cultivable bacterial loads in fecal samples (Supplementary Fig. 8). Results showed that the Anti+HS group still exhibited significant obesity mitigation, including improvements in body weight, fasting glucose, tissue morphology, lipid metabolism, and arginine synthesis (Supplementary Fig. 7B–G). LP-GOS also increased serum arginine, NO levels, and AMPK phosphorylation, though these effects were partially diminished by MDLA (Supplementary Fig. 7H–K). These findings indicate that LP-GOS can improve obesity-induced lipid metabolism disorders independently of the host gut microbiota.

Building on this foundation, we hypothesize that Lactiplantibacillus plantarum LLY-606 within the LP-GOS formulation possesses the capacity for independent arginine synthesis, thereby contributing to obesity alleviation. This hypothesis is further substantiated by genome-wide functional prediction analysis of Lactiplantibacillus plantarum LLY-606 (Supplementary Fig. 1E–F). To explore if Lactiplantibacillus plantarum LLY-606 in LP-GOS autonomously synthesizes arginine, we used CRISPR/Cas9 to knock down the Ass1 gene in Lactiplantibacillus plantarum LLY-606 (LP-KO), disabling arginine biosynthesis. Repeating the experiment with LP-KO-GOS (Fig. 6A), neither the LP-KO-GOS group (Anti+HS-KO) nor the group receiving both MDLA and LP-KO-GOS (Anti+HASS-KO) showed improvements in obesity-related parameters, including body weight, lipid metabolism, and arginine synthesis (Fig. 6B–H). Moreover, arginine and NO levels in the Anti+HS-KO group were comparable to those in the Anti+HFD group (Fig. 6I–J), and AMPK phosphorylation in the liver remained unaffected (Fig. 6K). This confirms that Lactiplantibacillus plantarum LLY-606 in LP-GOS autonomously synthesizes arginine, playing a critical role in obesity mitigation.

Fig. 6.

Independent Promotion of Arginine Synthesis by LP-GOS in Improving Obesity. (A) Experimental flow chart of animal treatments. (B) Body weight. (C) Blood glucose (n = 8 mice per group). (D) Representative H&E-staining images of the liver, eWAT and sWAT sections. Scale bars, 100 μm (n = 3 mice per group). (E) Liver mass. (F) eWAT and sWAT mass (n = 8 mice per group). (G) The mRNA levels of lipid metabolism genes in the liver for each group (n = 6 mice per group). (H) The mRNA levels of arginine metabolism genes in the liver for each group (n = 6 mice per group). (I) The level of arginine in serum (n = 6 mice per group). (I) The level of NO in serum (n = 6 mice per group). (K) Western blot analysis of liver P-AMPK/AMPK related signaling (n = 3 mice per group). All data were presented as mean ± SEM. Significant differences between mean values were determined by one-way ANOVA with Tukey’s multiple comparisons test.

Methods

Human study

Design, setting, and patients

This was a single-center, randomized, double-blind, placebo-controlled trial. A total of 60 eligible obese patients were enrolled between April 22, 2022, and September 27, 2023. The final follow-up was conducted on February 31, 2024.

Inclusion and exclusion criteria

Inclusion criteria:

• Age 18–65 years old;

• 28 ≤ BMI ≤ 35Kg/m²;

Be willing and able to comply with the protocol during the study and cooperate in completing the tests during the trial. Provide written informed consent prior to entering the study screening and the patient has understood that he/she can withdraw from the study at any time during the study without any loss.

Exclusion criteria

Specifically, Exclusion criteria for the trial included gastrointestinal conditions, autoimmune diseases, pregnancy or lactation, a history of alcohol or tobacco abuse, metabolic disorders, and the use of medications, especially antibiotics.

Interventions

Participants were randomized in a 1:1 ratio to either the synbiotic group (n = 30) or the placebo group (n = 30). Both groups took the assigned supplements for three months, with relevant indicators collected. Participant adherence was monitored through weekly follow-up phone calls, during which trained study personnel conducted verbal confirmation of daily intake of the intervention.

Synbiotic group:

• −Composition: Probiotic powder+galactooligosaccharides
• −Dosage form: 2.5 g per sachet, viable bacteria count > 10^9 CFU/g
• −Administration: One sachet twice daily, taken with warm water (40 °C)

Placebo group:

• −Composition: Maltodextrin
• −Dosage form: 2.5 g per sachet
• −Administration: One sachet twice daily, taken with warm water (40 °C)

Both groups orally administered the supplements for three consecutive months from enrollment. Both the placebo and synbiotic were supplied by Wecare Probiotics Co., Ltd. (Suzhou, China).

Main outcomes and measures

Primary endpoint: Difference in body mass index (BMI) after three months of synbiotic intervention in obese patients.

Secondary endpoints: Changes in body composition (measured by Body270 analyzer) and blood biomarkers (e.g., cholesterol, triglycerides; analyzed by Xijing Hospital Laboratory).

Sample size calculation

Based on prior data showing a 40 %–70 % BMI improvement rate with synbiotic, we hypothesized a 50 % response rate in the treatment group versus 10 % in controls. With a one-year recruitment period, four-month follow-up, one-sided α = 0.05, 80 % power (β = 0.2), and 30 % dropout rate, the required sample size was 78 (39 per arm using block randomization).

The RCT was approved by the Ethics Committee for Clinical Studies of The First Affiliated Hospital of Air Force Medical University. Informed consent was obtained from all participants and the experiments conformed to the principles defined in the WMA Declaration of Helsinki. Sex was not considered in the overall study due to the clinical investigations were applicable to both sexes. The CONSORT 2025 flowchart and CONSORT 2025 editable checklist are detailed in the supplementary materials.

Mice

Six-week-old male C57BL/6J mice were procured from SPF (Beijing) Biotechnology Co., Ltd. They were housed in a standard animal facility. The mice underwent a one-week acclimatization period prior to experimentation. Throughout the experiment, the mice had unrestricted access to food and water. Specifically, obese mice were subjected to a high-fat diet for 4 weeks before identifying and excluding those resistant to obesity prior to treatment. Mouse body weights were measured and recorded weekly throughout the study period. We adhered to the guidelines outlined in the Eighth Edition of the “Guide for the Care and Use of Laboratory Animals” (ISBN-10: 0-309-15396-4). All research procedures were conducted in compliance with applicable ethical regulations for animal research.

Mouse models and treatments

In the first part of the experiment, the control (CON) group was fed with a standard diet (AIN-93M, n = 8) and oral administration saline. Obese mice were divided into four groups (n = 8): High fat diet (HFD) group, High fat diet with Lactiplantibacillus plantarum LLY-606 (HM) group, High fat diet with GOS (HG) group, and High fat diet with synbiotic (HS) group. Specifically: HFD fed a 60 % high-fat diet and oral administration saline, HM fed a 60 % high-fat diet and oral administration 10⁹ CFU/ mL Lactiplantibacillus plantarum LLY-606, HG fed a 60 % high-fat diet added 8 % GOS and oral administration saline), and HS fed a 60 % high-fat diet added 8 % GOS and oral administration 10⁹ CFU/ mL Lactiplantibacillus plantarum LLY-606.

To explore the influence of arginine in the intervention, we selected the alpha-methyl-DL-aspartic acid (MDLA), an inhibitor of arginine succinate synthase (Ass1), which was dissolved in 0.9 % NaCl and administered intraperitoneally to hinder arginine synthesis. Obese mice were divided into three groups (n = 8): HFD group, HS group, and HS intraperitoneal injection of MDLA (HS+ASS) group. The mice were fed as described above. Concurrently, the mice received the following treatments: (1) HFD group and HS group: Intraperitoneal injections of normal saline, administered four times per week; (2) HS+ASS group: intraperitoneal injection of 147 mg/kg MDLA, administered four times per week [34,35].

Antibiotics were administered to mice in their drinking water and replaced with freshly prepared solutions every other day, following a protocol previously described [36]. The antibiotic mixture consisted of 1 g/L Neomycin, 1 g/L Streptomycin, 1 g/L Penicillin, and 0.5 g/L Vancomycin. This treatment was conducted for a duration of 2 weeks. After the treatment, the mice were randomly assigned to one of three groups (n = 8): Antibiotics treatment HFD (Anti+HFD) group, Antibiotics treatment HS (Anti+HS) group and Antibiotics treatment HS+ASS (Anti+HASS) group. The mice were fed and treated as described above.

In the last part of the experiment, antibiotics were treated as described. After the treatment, the mice were randomly assigned to three groups (n = 8): Anti+HFD group, LP-KO-GOS intervention Anti+HFD (Anti+HS-KO) group, LP-KO-GOS and MDLA intervention Anti+HFD (Anti+HASS-KO) group. The mice were fed and treated as described above.

All the treatment continued for 8 weeks until mice were sacrificed, and all the serum and tissue samples were collected and stored at −80 °C.

The specific carbon source was predicted

We obtained genome-wide information for Lactiplantibacillus plantarum LLY-606 (accession numbers: CNS0053740) and functionally predicted all gene sequences using COGNITOR (https://www.ncbi.nlm.nih.gov/COG/). Subsequently, we screened for all genes related to carbohydrate utilization within COG G. Information about CAZy enzymes encoded in the genome was acquired from the CAZy database (https://www.cazy.org), and substrates were predicted using NCBI (https://www.ncbi.nlm.nih.gov) and the EC database (https://www.ebi.ac.uk/). Protein localization prediction was conducted for the glycoside hydrolase proteins obtained (https://www.psort.org/psortb/). We retrieved and analyzed all COG G genes using the BLAST function of the TCDB database to obtain information about carbohydrate transporters. Based on substrate and transporter information and their genomic location, we constructed corresponding metabolic pathways and completed the functional analysis of carbohydrate utilization. Genomic analysis was performed to predict strain-specific prebiotics.

Glucose-tolerance tests and Insulin-tolerance tests

We modified the protocols for glucose tolerance tests (GTT) and insulin tolerance tests (ITT) based on our previous research [37]. For the GTT, mice underwent a 12-hour fast prior to the test. A glucose solution (2 g/kg BW) was injected, and blood glucose levels were measured at 0, 15, 30, 60, and 120 min after the injection. For the ITT, mice fasted for 6 h before the test. Insulin (0.75 U/kg, Sigma Aldrich, USA) was injected, and blood glucose levels were measured at 0, 15, 30, 60, and 120 min after the injection.

Analyses of serum contents

The serum TG, TC, HDL-C, and LDL-C were examined using kits and the serum insulin and leptin were detected using ELISA kits. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as fasting insulin concentration (mU L⁻¹) × fasting glucose concentration (mg dL⁻¹) × 0.05551)/22.5.

Histological staining

The mice tissues were fixed with 4 % (v/v) paraformaldehyde/PBS fixative immediately after mice were sacrificed the mice. The tissues were dehydrated, embedded in paraffin, cut into 5 μm slices with a microtome. The slices were stained with hematoxylin and eosin (H&E) staining. Finally, the images of tissues were observed with an optical microscope (Olympus, Japan).

Indirect calorimetry

The metabolic status of the mice was assessed using indirect calorimetry with a comprehensive laboratory animal monitoring system (CLAMS, Columbus Instruments, Columbus, OH). In this progress, mice were given unrestricted access to food and water. The light and feeding conditions were kept consistent with their home cages. Following the 24-hour acclimation period, oxygen consumption (VO₂) and carbon dioxide production (VCO₂) rates were recorded for 1 min every 5 min over a 24-hour period. This recording started at 2 pm on the first day and ended at 2 pm on the last day. Energy expenditure was determined using the Weir equations.

RNA preparation and RT‐qPCR

The total RNA was acquired from the hepatic and adipose using the TRIZOL Kit. AllinOneStep RT Mixture was used for cDNA synthesis. The mRNA expression was examined using SYBR Green and specific primers (see in supplementary information) in ABI QuantStudio5 real-time system. The relative gene expressions were calculated with the 2^−△△Ct method.

Western blots

The tissue was subjected to protein extraction, followed by quantification using the BCA Protein Assay kit (Thermo, Rockford, USA). Subsequently, the total protein from different tissues was separated through 10 % SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto a polyvinylidene fluoride (PVDF) membrane using a wet transfer apparatus. To prevent non-specific binding, the membranes were blocked with 5 % skimmed milk in TBST for 2 h at room temperature. Incubation with the primary antibody was carried out overnight at 4 °C. This was followed by incubation with HRP-conjugated anti-rabbit secondary antibodies for 1.5 h at room temperature. The blots were visualized using the Champ Chemi 610 Plus system, and densitometry analysis was performed using Image-J software.

Construction of ASS1 knockout strains

Genomic and Plasmid Extraction: Genomic DNA from Lactiplantibacillus plantarum LLY-606 was obtained with the Bacterial Genomic DNA Kit, while plasmid pHSP01 from Escherichia coli was isolated using the Axygen Plasmid Extraction Kit as per the manufacturer's instructions.

Preparation and Transformation of E. coli Competent Cells: E. coli cells were first cultured in LB medium at 37 °C with shaking until the OD600 reached 0.4 to 0.5. Subsequently, the bacterial culture was centrifuged at 4 °C for 10 min at 4500 g, and the supernatant was decanted. The cell pellet was resuspended in a CaCl2 glycerol solution. Following this, 0.1–1.0 µg of plasmid DNA was introduced into the competent cells, and the mixture was incubated on ice for 30 min. The cells were then briefly heat-shocked at 42 °C for 90 s, followed by a 2-minute incubation on ice. To facilitate recovery, 200 μL of LB liquid medium was added, and the cells were subsequently shaken at 37 °C for 1 h. Finally, the transformed cells were streaked on selective agar plates with the corresponding antibiotic resistance and incubated at 37 °C for 24–48 h.

Preparation and Transformation of Lactiplantibacillus plantarum LLY-606 Competent Cells: Lactobacillus plantarum LLY-606 cells were cultured in SGMRS medium, which consists of MRS supplemented with 0.3 M sucrose and 1 % glycine. The static cultivation was conducted at 37 °C until the OD600 reached the range of 0.3–0.5. Following this, the bacterial culture was centrifuged at 4 °C for 10 min at 4500 rpm, and the supernatant was decanted with care. The cell pellet was gently resuspended in pre-chilled SM buffer. Subsequently, 0.1–1 µg of plasmid DNA was introduced into the competent cells and left on ice for 10 min. The cell-DNA mixture was then transferred to pre-chilled electroporation cuvettes and subjected to electroporation at 2.5 kV, 400 Ω, and 25 µF. Following electroporation, SMRS medium was added, and the cells were allowed to recover at 37 °C for 3 h before being streaked onto selective agar plates with the appropriate antibiotic resistance. The plates were then incubated at 37 °C.

Preparation and Transformation of Competent Cells in Lactiplantibacillus plantarum LLY-606 (pLH01): We introduced the auxiliary plasmid pLH01 into Lactobacillus plantarum LLY-606 and selected transformants on chloramphenicol agar plates. These transformants, carrying pLH01, were prepared as previously described to create competent cells. Following this, we added an inducing peptide with the amino acid sequence MAGNSSNFIHKIKQIFTHR to stimulate the expression of RecE/T, with all other steps and procedures remaining the same as previously mentioned.

Plasmid Construction for Gene Knockout: This process entailed modifying the CRISPR/Cas9 editing plasmid pHSP01. The genetic template for this modification was obtained from the genome of Lactiplantibacillus plantarum LLY-606. Specific primers were used to amplify DNA via PCR, yielding three distinct segments: ASS1-up, ASS1-down, and ASS1 gRNA. These segments were then subjected to Overlap PCR with the FX KOD enzyme, allowing them to merge into the ASS1up-down-gRNA fragment. This fragment was seamlessly integrated into the pHSP01 vector after digestion with ApaI and XbaI enzymes. The resulting construct was introduced into competent Escherichia coli cells and streaked onto selective agar plates. The growth of single colonies was confirmed by using the Lcp11-CX-YZ-F and Lcp11-CX-YZ-R primers. The correctly constructed plasmid was named pLdASS1.

Construction of Gene Knockout Strains: The recombined plasmid pLdASS1 was electroporated into competent cells of Lactiplantibacillus plantarum LLY-606 (pLH01). Positive clones were selected on selective agar plates using resistance markers. After PCR validation, the clones obtained were sequenced to confirm the successful generation of a single-gene knockout strain, designated as Lactiplantibacillus plantarum LLY-606 ΔASS1.

16S rRNA microbiome sequencing

The methods in this study have been previously described in detail. [36] Briefly, the microbiome sequencing was performed by Wuhan BGI Testing Co., Ltd., utilizing the Illumina HiSeq2500 platform. The raw data underwent a series of preprocessing steps, including data quality control, paired-end merging, filtering, and removal of chimeras, to generate a feature table. Subsequently, species annotation was performed on the feature table. These operations were conducted using Vsearch (v2.23.0). The SILVA database (138.1) was used as a reference for annotation. A follow-up analysis was analyzed using the OmicStudio tools (https://www.omicstudio.cn/tool; https://meta.bgi.com/).

Metabolism analysis

The HM350 Metabolome kit, developed by Shenzhen BGI Co. Ltd., was used to comprehensively analyze changes in mouse serum metabolites and fecal metabolites. The analysis procedure included sample pretreatment, metabolite detection, data preprocessing, quality control analysis, and target quantification. Chromatographic analysis was conducted with an AB LC-MS QTRAP 6500+ system (SCIEX), using the BEH C18 column (2.1 mm × 10 cm, 1.7 μm, Waters). Mass spectrometry parameters: ESI+/ESI−. LC-MS/MS scanning was performed in MRM (Multi Reaction Monitoring) mode. MultiQuant software (SCIEX, USA) was used for data processing. Default parameters were employed for the automatic identification and integration of each MRM transition (ion pair), with manual inspection aiding the process. A follow-up analysis was analyzed using the OmicStudio tools and MetaboAnalyst 5.0 (https://www.omicstudio.cn/tool & https://www.metaboanalyst.ca/home.xhtml).

Statistical analysis

For human study, analyses were performed using the GraphPad Prism 9.0. The significance level was set to 0.05 for all analyses. The normality of the data was determined by the Shapiro-Wilk test. Wilcoxon-tests were used for pairwise comparisons. Mann-Whitney test was used for unpaired comparisons of the two groups.

For the mouse study, 'n' refers to the individual animals. The number of animal replicates needed was chosen based on similar experiments. Other than for the sequencing data, statistical analyses were performed in GraphPad Prism 9.0. The normality of the data was determined by the Shapiro-Wilk test. If the data fit a normal distribution, an ANOVA with Tukey’s multiple comparison tests was used for parametric analysis of variance between groups; two-tailed unpaired Student’s t-tests were used for comparing 2 groups. Data are presented as the mean ± SEM and the median ± interquartile range unless otherwise noted. p < 0.05 was considered to be statistically significant.

Analysis and data visualization of microbial populations and metabolites were carried out in the Online Analytics Platform, as described above. Differential abundance analysis was performed using the Wilcoxon test. False discovery rate (FDR) for multiple comparisons of sequencing data using Bonferroni test.

Discussion

The primary objective of this study was to evaluate the anti-obesity potential of the synbiotic LP-GOS in HFD-induced obesity. We demonstrated that LP-GOS significantly improved metabolic parameters in both animal and human models, with mechanistic evidence implicating the arginine as a key mediator (see Supplementary Table 1 for a summary of key outcomes across models).

According to the claims of The International Scientific Association for Probiotics and Prebiotics (ISAPP), Synbiotic are defined as synergistic combinations of living microorganisms and substrates, including complementary synbiotic and synergistic synbiotic. Synergistic synbiotic required substrate must be available to the microorganisms in the formulation and the combined effect is better than each component [11]. Through genomic screening and in vitro validation, we identified galacto-oligosaccharides (GOS) as a preferred substrate for Lactiplantibacillus plantarum LLY-606 (Supplementary Fig. 1D). Combined administration of LP-GOS resulted in improved obesity-related outcomes (Fig. 1 and Supplementary Fig. 6), increased gut colonization of Lactiplantibacillus plantarum (Fig. 1F), and modulated microbial composition (Fig. 3).

We assessed the modulatory effects of LP-GOS on individuals with obesity. We found that although there was no significant change in body weight in the synbiotic group, the results showed an improvement in other factors related to obesity (BMI, body fat mass, body fat percentage, Visceral adipose tissue area, and waist) than at baseline (see Supplementary Table 2 for a summary of the key clinical indicators comparing placebo and synbiotic groups). Moreover, there was no discernible difference in the average daily step count between the placebo and synbiotic groups (Supplementary Fig. 3L). This suggests that the ameliorative effects observed in the synbiotic group are not attributable to an increase in physical activity. This is similar to previous studies. Only a decrease in obesity-related indicators was observed in the randomised controlled trial (RCT) of probiotic products, with no significant change in body weight [19,20]. Following LP-GOS supplementation, we observed an increase in Bifidobacterium, Ruminococcus, and Bacteroidetes, accompanied by a notable rise in the abundance of Lactobacillus. Concurrently, there was a decrease in the abundance of Blautia and Streptococcus. Previous studies have shown that Bifidobacterium [21,22] and Ruminococcus [23,24] was recognized for its association with resistance to obesity. The Blautia/Bacteroides ratio was positively correlated with BMI [25] and Streptococcus was positive correlated with obesity [26]. Prediction of microbiome function showed significant enrichment of the amino acid biosynthesis pathway (Fig. 3k). These findings indicate that the deceleration of obesity progression by LP-GOS may be associated with amino acid biosynthesis.

LP-GOS supplementation elevated serum and fecal arginine levels in mice (Fig. 4c and f) and prevented the decline in arginine observed in obese human participants (Supplementary Fig. 4H and Supplementary Fig. 5P). Correlation analyses revealed a negative association between arginine levels and obesity indicators in mice (Fig. 4G). Arginine is a basic semiessential amino acid that can alleviate metabolic abnormalities associated with obesity [27,28]. Our data support the hypothesis that LP-GOS improves metabolic health partially through microbiota-derived arginine.

To further dissect this mechanism, we employed an arginine synthesis inhibitor (MDLA), which attenuated—but did not eliminate—the beneficial effects of LP-GOS (Fig. 5). Notably, LP-GOS continued to reduce weight gain in microbiota-depleted mice, suggesting a possible contribution from Lactiplantibacillus plantarum LLY-606 itself (Supplementary Fig. 7). Genomic analysis revealed that Lactiplantibacillus plantarum LLY-606 encodes the full enzymatic pathway for arginine biosynthesis (Supplementary Fig. 1E–F). CRISPR/Cas9-mediated knockout of Ass1 in Lactiplantibacillus plantarum LLY-606 abolished arginine production and nullified the anti-obesity effects in vivo, confirming that Lactiplantibacillus plantarum LLY-606-derived arginine plays a critical role in the observed phenotype (Fig. 6).

Key strengths of this study lie in our proposal for developing innovative LP-GOS leveraging the properties of Lactiplantibacillus plantarum LLY-606. We focus on elucidating the potential mechanism by which arginine-mediated LP-GOS can alleviate obesity. Previous studies have demonstrated that arginine supplementation can reduce fat mass, improve insulin sensitivity, and attenuate inflammation in both animal models and human subjects [28,29]. For instance, Pai showed that arginine supplementation of rats with T2DM significantly reduced liver inflammatory protein levels, which may consequently reduce tissue damage associated with T2DM [30]. The known mechanisms for these protective effects of arginine involve multiple nitric oxide pathways that modulate AMPK activity, thereby influencing glucose synthesis and lipid metabolism [18,31]. Clinical evidence indicates that high-dose arginine supplementation (3 × 9 g daily over 6 months) elicits significant improvements in insulin metabolism among obese populations, with meta-analyses showing consistent reductions in circulating insulin levels [32]. However, LP-GOS supplementation appears more promising, given that half of dietary arginine undergoes degradation in the small intestine during first-pass metabolism [33]. A recent study also confirms this view, which revealed that the therapeutic effect of Lactiplantibacillus plantarum on NASH is mediated by the arginine that Lactiplantibacillus plantarum produces [27].

Nonetheless, our findings have limitations. A limitation of this study is the absence of a GOS-alone group in some mechanistic analyses, which restricts the ability to fully differentiate the individual effects of GOS versus Lactiplantibacillus plantarum LLY-606 in the synbiotic combination. Meanwhile, although our study demonstrated the biosynthesis of arginine in the gut by Lactiplantibacillus, in adults, arginine is also synthesized via the gut-renal axis [28]. Further research is needed to elucidate how LP-GOS supplementation promotes arginine biosynthesis via the gut-renal axis. Moreover, while our human trial revealed improvements in metabolic indicators such as body fat mass and visceral adipose tissue area, no significant reduction in body weight was observed. This suggests the need for larger, longer-term clinical trials to validate the efficacy of LP-GOS, particularly with respect to body weight control. Future studies should also explore optimal dosing regimens, evaluate sex- or age-related responses, and assess the therapeutic potential of LP-GOS in other metabolic disorders such as insulin resistance, non-alcoholic fatty liver disease, and hyperuricemia.

In conclusion, LP-GOS exerts anti-obesity effects by modulating gut microbiota, enhancing microbial arginine production, and activating metabolic signaling pathways such as AMPK. These findings offer a mechanistic basis for the development of strain-specific synbiotic as a novel nutritional approach to metabolic disorders.

Consent for publication

Written informed consent was obtained from the patient for publication of this case report and accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal on request.

Availability of data and materials

The accession number for the entire mice 16S rRNA sequencing dataset reported in this manuscript is NCBI BioProject (PRJNA1072268). The accession number for the entire human 16S rRNA sequencing dataset reported in this manuscript is NCBI BioProject (PRJNA1072237). Other original data and Image type data is uploaded to figshare (https://figshare.com/s/98642b21e4db15a35303).

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used Chatgpt in order to check the grammar. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication

Compliance with ethics requirements

Ethics approval and consent to participate: The human study was conducted in accordance with the Declaration of Helsinki and registered with Chinese clinical trial Registry (ChiCTR- 2200060837, https://www.chictr.org.cn/). The Institutional Ethics Committees and review Board of The first Affiliated Hospital of Air Force Medical University (KY20222022-F-1) approved this study. The Institutional Ethics Committees and review Board of Northwest A&F University (XN2023-0903) approved this animal study.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following are the Supplementary data to this article: