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Dietary Supplementation with Deinococcus radiodurans Extract Alleviates Obesity and Systemic Inflammation via Gut Microbiota Modulation in Murine and Feline Models

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25 May 2026

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26 May 2026

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Abstract
This study evaluated the efficacy of Deinococcus radiodurans extract (DRE) on weight management, systemic metabolism, and gut microbiota. The extract was administered to high-fat diet-induced obese mice and naturally overweight felines. In mice, a 1.5% extract supplementation mitigated obesity, reduced serum total cholesterol and low-density lipoprotein levels, and ameliorated hepatic steatosis. In the feline model, a 28-day intervention resulted in a 1.9% reduction in body weight, enhanced serum total antioxidant capacity by 16.1%, and reduced the systemic inflammatory marker serum amyloid A by 27.8%. Furthermore, 16S rRNA gene sequencing revealed that the intervention reversed obesity-associated microbial dysbiosis in both models by significantly enriching short-chain fatty acid-producing taxa, notably Oscillibacter and Blautia, while reducing opportunistic pathogens. DRE exerts comprehensive anti-obesity and anti-inflammatory effects by regulating lipid metabolism and reshaping the gut microbiota, highlighting its robust potential as a novel functional nutritional ingredient for metabolic health in companion animals.
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1. Introduction

The number of overweight and obese individuals has increased significantly across the globe in recent years [1]. As a chronic metabolic condition, obesity can lead to serious health issues [2]. The primary cause is often a long-term imbalance where energy intake from food is higher than the energy the body consumes, leading to fat deposition [3,4,5]. Obesity is typically characterized by weight gain, elevated lipid levels, and increased oxidative stress [6]. These factors represent a threat to the long-term health of both humans and companion animals [7,8,9], exacerbating the risk of metabolic comorbidities such as insulin resistance and orthopedic disorders in canine and feline populations [10,11,12].
Current methods for managing weight primarily include changes in lifestyle, the use of certain drugs, or surgery [13,14,15]. While reducing the intake of high-fat foods and increasing exercise can be effective, they are often difficult to maintain. Some drugs are available to reduce nutrient absorption or suppress appetite, but they may cause side effects such as diarrhea or endocrine issues [16,17,18]. Surgical options are expensive and can lead to complications such as inflammation or imbalances in the gut microbiota [19]. Therefore, using safe and effective dietary supplements is a practical way to manage obesity with fewer side effects, as natural bioactive extracts have shown considerable promise in modulating lipid metabolism without adverse pharmacological burdens [20,21,22,23].
The intestinal microbiota is a complex ecosystem that helps regulate the energy balance of the host [24,25,26]. A healthy gut community is important for maintaining overall health [27,28]. Imbalances in these microorganisms can lead to energy disorders and contribute to the development of obesity [29]. Studies have shown that a high-fat diet can reduce microbial diversity and change the structure of the gut community [30,31,32,33]. Conversely, weight management and healthy diets are often linked to an increase in beneficial bacteria and improved species richness [34,35].
Deinococcus radiodurans is a unique extremophilic bacterium distinguished by its extraordinary resilience to ionizing radiation and oxidative stress, traits primarily attributed to its highly efficient DNA repair mechanisms and robust antioxidant systems [36,37,38,39,40,41], including the production of potent carotenoids like deinoxanthin that actively scavenge reactive oxygen species [42]. While the biological properties of the D. radiodurans strain are well-documented, its application as a functional dietary extract remains significantly understudied. Specifically, data regarding the impact of D. radiodurans extract (DRE) on systemic lipid metabolism and host-microbiota interactions is currently limited, representing an area of research that warrants further investigation.
Consequently, the regulatory effects of DRE on weight management, lipid profiles, and the gut microenvironment were investigated using HFD-induced obese mouse and feline models. Through the analysis of growth performance, histopathological shifts in the liver and adipose tissues, and the metabolic output of the gut microbiota, this research provides the theoretical and experimental evidence necessary for the development of D. radiodurans derivatives as functional ingredients. These findings serve as a foundation for utilizing special microbial resources in the formulation of bioactive products targeted at modulating metabolic health and mitigating obesity-related conditions, offering a novel prebiotic strategy for translational application in both laboratory models and companion animal nutrition [43].

2. Materials and Methods

2.1. Culture and Preparation of D. radiodurans

Deinococcus radiodurans (DR) was activated on Tryptone Glucose Yeast (TGY) agar at 28 °C for 36 h. A single colony was then transferred to TGY broth and cultured at 30 °C (220 rpm) until reaching the log phase. This liquid culture served as the seed for solid-state fermentation. The solid substrate, consisting of 60% soybean meal and 40% sunflower meal, was sterilized and cooled before inoculation with the seed culture at a 10% (v/w) ratio.
Fermentation was carried out at 28 °C for 3–5 days. The resulting product was dried, ground through an 80-mesh sieve, and extracted using organic solvents. After concentration and freeze-drying, the final DRE powder was obtained. The moisture content of the final product was maintained below 10%.

2.2. Mice Experimental Design and Sample Collection

Thirty-two C57BL/6J mice (7–8 weeks old, 20 ± 1 g) were acclimated for one week and maintained under a 12 h light/dark cycle at 23–25 °C and 55 ± 5% humidity with free access to food and water. The mice were assigned to four groups: control (CON, n = 6), high-fat diet (HFD, n = 10), HFD supplemented with 0.5% D. radiodurans extract (DRE, n = 8), and HFD supplemented with 1.5% DRE (n = 8). The experimental period lasted 20 weeks, consisting of a 12-week obesity induction phase followed by an 8-week intervention phase where the DRE groups received their respective treatments alongside the HFD.
At weeks 12, 16, and 20, mice were anesthetized to collect blood. A portion of whole blood was collected in EDTA tubes for routine blood analysis. The remaining blood was centrifuged at 3000g for 10 min at 4 °C to separate serum for the measurement of total serum cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), and high-density lipoprotein (HDL-C). Liver and inguinal adipose tissues were excised, weighed, and fixed for pathological observation and Oil Red O staining. Additionally, serum levels of interleukin-6 (IL-6), serum amyloid A (SAA, Eiken LZ-SAA kit), and C-reactive protein (CRP, IDEXX Catalyst CRP kit) were measured to assess systemic inflammation.
Histopathological evaluations were conducted to assess hepatic steatosis and adipose tissue morphology in mice. Tissue samples were collected at both the 16-week and 20-week time points during the experimental period. Following euthanasia, liver and inguinal white adipose tissue (WAT) were excised, rinsed in ice-cold phosphate-buffered saline (PBS), and immediately fixed.
Fecal samples were collected at week 20 of the trial for intestinal microbiota analysis. To minimize inter-individual biological variation and ensure sufficient biomass for subsequent microbial DNA extraction, a 2-by-2 pooling strategy was employed within each group. Specifically, fecal samples from every two mice in the same group were thoroughly mixed and pooled into a single composite sample. Consequently, a total of 12 independent composite samples were subjected to 16S rRNA gene sequencing, including the control group (CON, n = 3 composite samples, derived from 6 mice), the high-fat diet group (HFD, n = 5 composite samples, derived from 10 mice), and the DRE intervention group (HFD + 1.5% DRE, n = 4 composite samples, derived from 8 mice). All composite samples were immediately frozen in liquid nitrogen upon collection and stored at −80 °C until further processing and DNA extraction.
Tissue Fixation and Sectioning: Fresh tissue samples were fixed in 4% paraformaldehyde fixative solution for 24 hours at room temperature to preserve tissue architecture. After fixation, tissues were dehydrated through a graded ethanol series, cleared in xylene, and embedded in paraffin wax. Embedded tissues were sectioned at a thickness of 5 μm using a microtome and mounted onto glass slides for hematoxylin and eosin (H&E) staining.
H&E Staining Procedure: Paraffin-embedded sections were deparaffinized in xylene and rehydrated through a graded ethanol series (100%, 95%, 80%, and 70%) to distilled water. Sections were then stained with Mayer’s hematoxylin solution for 5-8 minutes to visualize nuclei, followed by a 10-minute rinse in running tap water for bluing. Subsequently, sections were counterstained with eosin solution for 2-3 minutes to stain the cytoplasm and extracellular matrix. After staining, sections were dehydrated through graded ethanol, cleared in xylene, and mounted with a resinous mounting medium. Images were captured using a light microscope (Olympus, Japan) equipped with a digital camera. Adipocyte size and morphology were assessed, and at least five fields per sample were analyzed.
Oil Red O Staining Procedure: For the assessment of neutral lipid accumulation in the liver, fresh liver tissue samples were embedded in optimal cutting temperature (OCT) compound and frozen at -80 °C. Frozen sections were cut at a thickness of 8-10 μm using a cryostat and air-dried for 10-15 minutes. Sections were fixed in 4% paraformaldehyde fixative for 15 minutes at room temperature, rinsed with distilled water, and then washed with 60% isopropanol. The fixed sections were stained with freshly prepared Oil Red O working solution for 10-15 minutes at room temperature. Oil Red O stock solution was prepared by dissolving 150 mg of Oil Red O powder in 50 mL of 100% isopropanol, heated to dissolve completely, and filtered to obtain a 3 mg/mL stock solution. The working solution was prepared by mixing 15 mL of stock solution with 10 mL of distilled water, followed by filtration. After staining, sections were differentiated in 60% isopropanol to remove background staining, rinsed briefly in distilled water, and counterstained with Mayer’s hematoxylin for 1-2 minutes to visualize nuclei. Sections were then washed in tap water and mounted in an aqueous mounting medium. Images were captured using a light microscope. The area of Oil Red O-positive lipid droplets was quantified using ImageJ software (National Institutes of Health, USA) and expressed as a percentage of the total field area. At least five random fields per sample were analyzed.

2.3. Cats Experimental Design

Six overweight neutered cats (Body condition score, BCS > 6) characterized by visible adipose accumulation and indistinct ribs were enrolled in a 28-day feeding trial. Each cat received a standardized daily diet (approximately 50 g, adjusted for body weight) supplemented with 1.5% (0.75 g) Deinococcus radiodurans extract (DRE) . Food and water were refreshed daily, and food intake was monitored throughout the study. Body weight, waist circumference, and body condition score (BCS). Fecal consistency was also evaluated at these specific time points using a standard scoring system. Fecal samples were collected at the start (day 0) and end (day 28) of the trial for intestinal microbiota analysis. These clinical metrics were used to assess the safety and overall physical status of the cats during the intervention. On days 0 and 28, blood samples were collected from each cat and centrifuged at 3,500 × g for 15 min at room temperature to obtain serum. Serum biochemical parameters, including total cholesterol (TC) and triglycerides (TG), were measured using an automated biochemical analyzer. To evaluate the systemic redox status, serum levels of superoxide dismutase (SOD), catalase (CAT), total antioxidant capacity (T-AOC), and malondialdehyde (MDA) were determined using specific commercial kits. Additionally, the serum inflammatory response was assessed. The concentrations of SAA, interleukin-6 (IL-6), interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and interleukin-10 (IL-10) were quantified using corresponding enzyme-linked immunosorbent assay (ELISA) kits according to the manufacturer’s protocols.

2.4. Gut Microbial Diversity Analysis

Total genomic DNA was extracted from the fecal samples using the GHFDE100 DNA isolation kit (Zhejiang, China) in accordance with the manufacturer’s instructions. Extracted DNA was stored at −20 °C until further analysis. The quantity and quality of the extracted DNA were determined using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States) and agarose gel electrophoresis, respectively.
The hypervariable V4 region of the bacterial 16S rRNA gene was amplified using the specific primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). Sample-specific paired-end 6-bp barcodes were incorporated into the TrueSeq adaptors for multiplex sequencing. The PCR reactions were performed in a total volume containing 25 μL Phusion High-Fidelity PCR Master Mix (2×), 3 μL (10 μM) of each primer, 10 μL DNA template, 3 μL DMSO, and 6 μL ddH2O. Thermal cycling conditions consisted of an initial denaturation at 98 °C for 30 s, followed by 25 cycles of denaturation at 98 °C for 15 s, annealing at 58 °C for 15 s, and extension at 72 °C for 15 s, with a final extension at 72 °C for 1 min. Negative controls (no template) were included in each PCR run. PCR amplicons were purified using Agencourt AMPure XP Beads (Beckman Coulter, Indianapolis, IN) and quantified using the PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, United States). After the individual quantification step, amplicons were pooled in equal amounts, and paired-end sequencing (2 × 150 bp) was performed on the DNBSEQ-G99 platform (MGI Tech Co., Ltd., Shenzhen, China).
Quality filtering of raw paired-end reads was conducted using Vsearch (v2.22.1) under predefined filtering criteria to retain high-quality clean reads. The filtered reads were subsequently aligned to the SILVA reference database with the UCHIME algorithm for chimera detection and elimination, yielding the final effective tags. Amplicon sequence variants (ASVs) were generated from effective tags using the UNOISE2 denoising algorithm. To reduce noise from low-abundance taxa, ASVs with a mean relative abundance < 0.01% across all samples were removed prior to downstream analysis.
The alpha-diversity indices (Chao1 richness and Shannon diversity) were calculated using QIIME2 (v2024.10) from the ASV table normalized via the total sum scaling (TSS) method and standardized to a total abundance of 100,000 reads per sample. Group-level differences in alpha-diversity were tested via the Kruskal-Wallis test, followed by pairwise comparisons with FDR correction. For beta-diversity, weighted UniFrac distances and Bray-Curtis dissimilarities were calculated and visualized via Principal Coordinate Analysis (PCoA). The statistical significance of microbial community separation among groups was assessed by Permutational Multivariate Analysis of Variance (PERMANOVA) using the R package ‘vegan’[44].

2.5. Statistical Analysis

Data are reported as mean ± standard deviation (SD). Statistical comparisons among groups were performed using one-way analysis of variance (ANOVA) with SPSS 20.0 software. A p-value of less than 0.05 was considered to indicate statistical significance.

3. Results

3.1. Effect of DRE on Growth Performance, Body Weight, and Hematological Parameters in Mice

To evaluate the influence of DRE on the physiological status of obese mice, morphological changes, body weight, and serum lipid parameters were monitored (Figure 1). Mice in the HFD group displayed a noticeably larger body size compared to the CON group after 20 weeks of feeding(Figure 1a). At the 12th week, the body weight of the HFD group was 10.1% higher than that of the CON group, confirming the successful establishment of the high-fat-induced obesity model from a morphological perspective (Figure 1b). Following the initiation of dietary intervention at week 12, DRE treatment mitigated further weight gain in a dose-dependent manner. By the end of the 20th week, the average body weight of mice in the 0.5% DRE group was 1.47 g (4.0%) lower than that of the HFD group. In contrast, the 1.5% DRE group showed a more pronounced reduction in weight gain, with an average weight 2.25 g (6.2%) lower than the HFD group, suggesting that higher concentrations of DRE are more effective in weight management.
The serum lipid analysis further supported the protective role of DRE against metabolic disturbances induced by HFD. Crucially, prior to the dietary intervention at week 12, high-fat intake had already led to significantly elevated levels of total cholesterol (TC) and low-density lipoprotein (LDL) in the HFD group compared to the CON group, which was highly consistent with the characteristics of HFD-induced metabolic syndrome (Figure 1c and Figure 1e). Following the intervention, DRE significantly enhanced the reduction of TC levels. Both DRE-treated groups exhibited decreased TC concentrations, with the 1.5% dose demonstrating superior efficacy, indicating a potential dose-dependent response (Figure 1c). As for TG levels, the 1.5% DRE treatment improved the levels at the end of the experiment, while the 0.5% DRE treatment showed no obvious effect (Figure 1d). DRE also reduced the HFD-induced increase in LDL. Both DRE treatments significantly lowered serum LDL levels, and the 1.5% dose showed a slightly better result than the 0.5% dose (Figure 1e).

3.2. Effect of DRE on Liver Weight, Hepatic Steatosis, and Histopathological Structure in HED-Fed Mice

To assess the protective potential of DRE against HFD-induced liver injury, liver weight, hepatic steatosis and histological alterations were evaluated (Figure 2). Gross measurements indicated that HFD feeding led to an increase in liver weight compared to the CON group (Figure 2a and Figure 2b). Although DRE intervention resulted in a modest reduction in liver mass, with the 1.5% DRE group exhibiting slightly lower average weights than the HFD group, these values remained elevated relative to the CON group.
Histological examination via Oil Red O staining further revealed the impact of DRE on intrahepatic lipid accumulation. By the end of the 20-week feeding period, livers from the CON group showed sparse red staining with clearly defined hepatocyte structures. In contrast, the HFD group exhibited massive accumulation of red lipid droplets and significant macrovesicular steatosis, characterized by enlarged lipid vacuole size (Figure 2d). Quantitative analysis confirmed that the Oil Red O-positive area in the HFD group was significantly higher than that in the CON group (Figure 2e).
Following 8 weeks of dietary intervention, the 1.5% DRE group showed a marked improvement in hepatic steatosis, evidenced by a significant reduction in the size and density of lipid droplets compared to the HFD group. This therapeutic effect was notably superior to that observed in the 0.5% DRE group. Specifically, while the 1.5% DRE dose significantly lowered the lipid-positive area, the 0.5% DRE group failed to demonstrate a substantial improvement, with the positive area even showing a slight increase at week 20 (Figure 2e). Furthermore, H&E staining corroborated these findings; 1.5% DRE effectively mitigated the disruption of hepatic cords and cellular swelling induced by the HFD (Figure 2c). Collectively, these data suggested that DRE exerted a dose-dependent protective effect against HFD-induced lipid deposition and histological damage in the liver.

3.3. Effect of DRE on Fat Accumulation in Mice

H&E staining of adipose tissue sections was performed to evaluate the impact of DRE on lipid storage and cellular architecture (Figure 3). In the CON group, the adipose tissue structure remained distinct, with adipocytes appearing small, uniform in size, and arranged in an orderly fashion without observable lesions. Conversely, prolonged HFD feeding resulted in a dramatic expansion of adipocyte volume. The cells in the HFD group exhibited pronounced hypertrophy and a crowded arrangement, indicating significant pathological changes associated with excessive lipid accumulation.
Following the dietary intervention, DRE effectively mitigated these morphological alterations. Compared with the HFD group, adipocytes in the 1.5% DRE-treated group were significantly smaller and more regularly arranged, nearly resembling the physiological state of the CON group. This suppressive effect on adipocyte hypertrophy was markedly superior to that observed in the 0.5% DRE group, where the reduction in cell size was less prominent. Notably, the restorative effect of DRE was more evident at Week 20 than at Week 16, suggesting that DRE alleviates HFD-induced adipocyte expansion in a dose-dependent and time-cumulative manner. These results indicated that the addition of DRE to a high-fat diet can effectively inhibit fat accumulation and attenuate the degeneration of adipose tissue structure.

3.4. Effect of DRE on the Gut Microbial Diversity in Mice

To investigate whether the mitigation of HFD-induced obesity by DRE is associated with structural modulations of the gut microbiota, 16S rRNA gene sequencing was performed on fecal samples from the CON, HFD, and HFD+1.5%DRE groups.
Alpha diversity was evaluated to assess the species richness and evenness within the microbial communities. The results indicated that the high-fat diet (HFD) led to a decreasing trend in microbiota richness and diversity (Figure 4a). However, the intervention with 1.5% DRE partially alleviated this phenomenon, prompting the diversity metrics to rebound towards the levels observed in the CON group. Although the Chao1 and Shannon indices did not reach statistical significance (Kruskal-Wallis P = 0.357 and P = 0.2272, respectively) due to individual variance among the samples, the Simpson index exhibited marginal significance (P = 0.0546). This reflects a potential regulatory effect of the DRE intervention on the distribution of microbial dominance.
Beta diversity was subsequently assessed using Principal Coordinate Analysis (PCoA) based on Bray-Curtis dissimilarities to evaluate the overall microbial community structure among the experimental groups (Figure 4b). The PERMANOVA results revealed a highly significant difference in the microbial community architecture across the groups (R2 = 0.4015, P= 0.001). The PCoA plot demonstrated a complete separation between the CON group and the HFD group along the PC1 axis, which accounted for 31.7% of the total variation. This substantial shift indicates that the high-fat diet profoundly altered the composition of the murine gut microbiota. Although the HFD+1.5%DRE group did not show a statistically significant spatial separation from the HFD group, it displayed a distinct orientational trend of shifting back towards the CON group.
Taxonomic profiling was conducted to characterize the specific compositional shifts within the gut microbiome (Figure 4c). At the phylum level, the relative abundance analysis revealed that the murine gut microbiota was primarily dominated by Bacteroidota and Firmicutes across all groups. At the genus level, the community landscape was primarily characterized by variations in the relative abundances of taxa such as Muribaculaceae, Mucispirillum, Bacteroides, and the Lachnospiraceae group.
To further elucidate the specific bacterial genera driving these community shifts, a differential abundance analysis was performed using the ANCOM-BC2 method (CLR + Kruskal + Wilcoxon) and visualized via a heatmap and distinct centered log-ratio (CLR) abundance box plots (Figure 4d, Figure 5). In the upper hierarchical cluster, a subset of bacterial genera exhibited a negligible presence under normal physiological conditions in the CON group but was robustly enriched under the pressure of a high-fat diet (HFD). Strikingly, the addition of 1.5% DRE effectively halted or attenuated this pathogenic expansion, forcing these taxa to revert toward the low-abundance characteristics of the CON group. Specifically, Alloprevotella and Phascolarctobacterium, which were heavily overgrown in the HFD group, experienced a severe contraction upon DRE administration, thus exhibiting a near-complete regression to the CON baseline. Similarly, the HFD-induced overgrowths of Paraprevotella and the Lachnospiraceae_UCG-006 clade were noticeably mitigated in the HFD+1.5%DRE group, representing a clear transitional trajectory of converging back toward the healthy control structure.
Conversely, the lower hierarchical cluster was predominantly populated by key endogenous core genera that maintained a high baseline abundance in the CON group but suffered severe depletion and wash-out under the HFD regime. In this cluster block, the DRE intervention exerted a highly visible rescue effect, prompting these depleted functional taxa to rebound and shift back toward the positive values of the CON group. For instance, the genus A2, which plummeted into a low-abundance abyss in the HFD group, was successfully restored to a median baseline by DRE. Furthermore, Ureaplasma completely reversed its HFD-suppressed state, rebounding into a positive abundance range within the HFD+1.5%DRE group. A broader spectrum of functional taxa, including Monoglobus, the Clostridium_methylpentosum_group, UCG-005, Peptococcus, Odoribacter, Tyzzerella, and distinct clades within the class Clostridia (specifically the Clostridia_vadinBB60_group and Clostridia_UCG-014), all displayed a perceptible mitigation of their HFD-induced depletion, demonstrating a generalized capacity of DRE to rescue core commensal microbes from high-fat diet-induced suppression. Overall, these results demonstrate that DRE supplementation effectively mitigates high-fat diet-induced microbial deviations in mice. By selectively suppressing obesity-associated taxa and restoring key endogenous commensals toward the CON baseline, DRE successfully drives the dysbiotic microecology to reconstitute a healthier profile associated with metabolic homeostasis.

3.5. Effect of DRE on Growth Performance and Physical Appearance in Overweight Cats

To evaluate the safety and efficacy of DRE, the clinical status and growth performance of six overweight cats were monitored for 28 days. All cats remained healthy and showed normal appetite, water intake, and voluntary activity. Daily food intake and consumption rate did not change obviously during the trial. This showed that DRE supplementation was safe and did not negatively affect the feeding behavior of the cats.
The effects of DRE on body composition and morphology are shown in Figure 4. After the 28-day intervention, the cats showed a stable decrease in body weight. The body condition score (BCS) also improved and gradually moved toward the ideal range (Figure 6a). The average weight dropped from 5.19 kg at day 0 to 5.09 kg at day 28, representing a reduction of about 1.9% (Figure 6b). Consistent with the weight loss, the average waistline decreased over the 28 days (Figure 4c). Furthermore, muscle condition scores (MCS) were maintained at healthy levels (above 3) for all cats during the weight loss process. Concurrently, the fecal scores remained stable throughout the trial, indicating normal digestive function and tolerance to the supplement . Overall, these results showed that DRE provided safe and effective body management for overweight cats.

3.6. Effect of DRE on Serum Antioxidant Capacity and Inflammatory Status in Overweight Cats

Serum samples were evaluated to determine the impact of DRE on the systemic antioxidant defense and inflammatory levels (Figure 6).
After the 28-day intervention, the antioxidant status showed a differential response (Figure 7). The activities of key antioxidant enzymes, SOD and CAT, showed slight upward trends, increasing by 7.4% and 5.1%, respectively. These changes did not reach statistical significance (P = 0.137 and P = 0.76). However, the total antioxidant capacity (T-AOC) increased significantly by 16.1% (P = 0.026). This suggested that non-enzymatic antioxidants played a major role in the overall antioxidant defense. The concentration of MDA slightly decreased from 0.72 nmol/mL to 0.67 nmol/mL without statistical difference (P = 0.141), indicating that the oxidative stress risk remained stable and well-controlled.
Furthermore, the core inflammatory markers were analyzed. The SAA level significantly decreased by 27.8% (P = 0.021), indicating a clear reduction in systemic inflammation. The pro-inflammatory cytokines IL-6 and TNF-α showed downward trends, which was consistent with the decrease in SAA, although the changes were not significant. Meanwhile, IFN-γ levels increased by 20% (P = 0.046), suggesting a moderate activation of the immune system that might help with metabolic regulation. The anti-inflammatory cytokine IL-10 also showed a slight increase. Overall, the intervention effectively enhanced the comprehensive antioxidant reserve and alleviated the chronic inflammatory state in the subjects

3.7. Effect of DRE on the Gut Microbial Diversity in Overweight Cats

To evaluate the modulatory effect of DRE on the intestinal microecology of overweight cats, 16S rRNA gene sequencing was performed on fecal samples collected before (D0) and after a 28-day intervention (D28).
Alpha-diversity indices were calculated to assess microbial richness and evenness within the feline gut (Figure 8a). Following the 28-day DRE intervention, the Chao1 index exhibited a statistically significant increase (Wilcoxon test, p = 0.0411), indicating that the treatment effectively enriched the total number of microbial species in overweight cats. Although the Shannon and Simpson indices showed numerical upward trends, the differences did not reach statistical significance (p = 0.3939 and p = 0.4848, respectively). These results demonstrate that DRE primarily enhances gut microbial diversity by promoting species richness.
Beta-diversity was assessed using Principal Coordinate Analysis (PCoA) based on Bray-Curtis dissimilarities to visualize the overall microbial community structure (Figure 8b). The PERMANOVA test indicated that the macroscopic community architecture did not undergo a statistically significant global shift between D0 and D28 (R² = 0.1022, P=0.317). This suggests that while DRE intervention selectively enriched specific microbial taxa, it maintained the fundamental stability of the feline gut ecosystem without causing drastic structural disruptions.
At the phylum level, the feline gut microbiota was predominantly composed of Firmicutes and Bacteroidota across both time points (Figure 8c). Following the 28-day intervention, a noticeable remodeling of these dominant phyla was observed. The relative abundance of Bacteroidota increased, accompanied by a concurrent reduction in Firmicutes. Consequently, this shift led to a substantial decrease in the Firmicutes/Bacteroidota (F/B) ratio, a widely recognized microbiological hallmark associated with the mitigation of the obesity phenotype. Additionally, the relative abundance of Fusobacteriota exhibited a moderate expansion in the D28 group compared to the baseline.
To further elucidate the specific bacterial shifts driving these ecological changes, a heatmap analysis was conducted at the genus level (Figure 8d). Taxonomic profiling revealed that DRE supplementation significantly enriched a consortium of short-chain fatty acid (SCFA)-producing bacteria. Specifically, the relative abundances of Bacteroides, Blautia, Cetobacterium, Sutterella, and Collinsella were notably elevated at D28. Consistent with the biomarker discovery, the genus Oscillibacter (belonging to the family Oscillospiraceae) also demonstrated a prominently higher abundance following the intervention.
In striking contrast, DRE treatment effectively reduced the relative abundance of several opportunistic pathogens known to induce gut dysbiosis, including Campylobacter, Peptostreptococcus, and Escherichia-Shigella. Furthermore, the abundance of Megamonas—a conditionally commensal genus frequently correlated with hepatic fat accumulation and increased body mass—was markedly suppressed at D28 compared to D0. Collectively, these taxonomic shifts demonstrate that DRE alleviates the overweight phenotype by specifically promoting beneficial SCFA-associated microbiota while concurrently inhibiting obesity-related and potentially pathogenic taxa.

4. Discussion

Obesity arises from a chronic energy imbalance where caloric intake consistently exceeds expenditure, leading to systemic metabolic dysfunction and excessive lipid deposition [3,45,46,47]. In this study, the high-fat diet (HFD) group in mice successfully established a robust obesity model, demonstrated by a 10.1% increase in body weight compared to the control group within 12 weeks. Dietary intervention with DRE dose-dependently mitigated further weight gain. While the 0.5% dose had a moderate impact, the 1.5% DRE group showed a more significant reduction, maintaining an average weight 6.2% lower than the HFD group by the end of the 20-week trial. These findings were mirrored in the feline model, where overweight cats exhibited a stable 1.9% downward trend in body weight and a shift toward the ideal body condition score (BCS) range of 4–6 [48]. The consistent reduction in abdominal volume and waistlines across different animal models suggests that DRE could regulate lipid metabolism across mammalian species [43,49].
The liver and adipose tissues are the primary sites for lipid processing, and their structural integrity is a critical indicator of metabolic health [50,51]. In HFD-fed mice, severe hepatic steatosis was confirmed by massive macrovesicular lipid accumulation, with the Oil Red O-positive area reaching 67.5%. Intervention with 1.5% DRE dramatically improved this pathological state, reducing the lipid-positive area to 10.5% and effectively mitigating cellular swelling and the disruption of hepatic cords. Simultaneously, 1.5% DRE inhibited the expansion of adipocytes in white adipose tissue [52]. Adipocytes in the 1.5% DRE-treated group were significantly smaller and more regularly arranged than those in the HFD group, nearly resembling the physiological state of the control group. The observation that this restorative effect was more evident at week 20 than at week 16 suggested that DRE alleviates adipocyte hypertrophy in a dose-dependent and time-cumulative manner [53]. Furthermore, systemic metabolic health was supported by the serum lipid analysis in mice, where 1.5% DRE significantly reduced TC and LDL levels compared to the HFD baseline. These data indicate that DRE exerts a comprehensive protective effect against the structural and metabolic disturbances induced by high-fat intake.
Oxidative stress and chronic low-grade inflammation are hallmark features of obesity, as lipid peroxidation and pro-inflammatory cytokine release often lead to progressive tissue damage and insulin resistance [6,54]. In the feline model, DRE intervention significantly increased the T-AOC by 16.1%. While the increases in SOD and CAT activities did not reach statistical significance, the overall upward trend in these enzymes, combined with a marginal reduction in MDA levels, suggested a strengthened antioxidant defense system. Crucially, this antioxidant improvement was accompanied by a marked alleviation of systemic inflammation. The significant 27.8% reduction in SAA, alongside downward trends in typical pro-inflammatory cytokines (IL-6 and TNF-α), indicated a profound amelioration of the chronic inflammatory state. Also the moderate increase in IFN-γ suggested a properly regulated immune activation, which might assist in metabolic regulation and lipid clearance during the weight loss process. This improvement in the antioxidant reservoir might protect the intestinal environment from the oxidative stress typically associated with an overweight status [55,56].
The gut microbiota is a critical regulator of host energy homeostasis, and its diversity is frequently compromised in obese individuals [57,58]. In the present study, both HFD-induced obese mice and overweight cats exhibited a distinct decline in microbial richness and altered community composition. However, DRE supplementation consistently reversed this dysbiosis. In mice, DRE intervention restored alpha-diversity metrics and induced a significant taxonomic shift, characterized by the enrichment of several SCFA-associated genera, including Phascolarctobacterium, Odoribacter, and Alloprevotella [59,60]. As primary degraders of complex polysaccharides, these taxa ferment dietary fibers into SCFAs [61], playing vital roles in maintaining intestinal barrier integrity and modulating host lipid metabolism [26,62,63,64,65].
These findings were further corroborated in the feline model. DRE intervention in overweight cats significantly increased the Chao1 index, suggesting that the extract effectively promoted the recovery of species richness. Furthermore, the relative abundance of the Bacteroidota phylum increased, which supported the improved body condition scores observed in the overweight cats [66]. Taxonomic profiling revealed that DRE enriched specific beneficial taxa, notably the genus Oscillibacter. Recent large-scale microbiome cohorts have identified Oscillospira and its related taxa within this family as robust biomarkers for leanness and lower body mass index (BMI) [67,68]. Heatmap analysis also showed higher abundances of Bacteroides, Phascolarctobacterium, and Blautia. Members of Oscillospiraceae and Blautia are widely recognized as vital contributors to the SCFA pool in the mammalian gut [69,70]. Specifically, taxa within Oscillospiraceae are potent producers of butyrate [71]. Beyond SCFA production, previous metagenomic studies suggested that Oscillospiraceae members can degrade host glycans, which requires the host to expend additional energy to regenerate intestinal mucins [72,73]. This increased energy expenditure provided a potential metabolic mechanism for the weight reduction observed in the feline and murine models. Meanwhile, the genus Blautia is highly efficient at producing acetate, which serves as an essential precursor to further promote butyrate synthesis via microbial cross-feeding networks [74]
These enriched SCFAs, particularly butyrate, sustain host health by strengthening the intestinal mucosal barrier and suppressing systemic inflammation [68,75]. In contrast, DRE reduced the abundance of opportunistic pathogens such as Campylobacter, Peptostreptococcus, and Escherichia-Shigella which cause gut dysbiosis and mucosal inflammation. DRE concurrently reduced the relative abundance of Megamonas, a conditionally commensal genus positively correlated with BMI, waist circumference, and hepatic fat accumulation. By reducing the burden of these pro-inflammatory taxa and promoting the expansion of SCFA-producers, DRE improved the overall gut microbial environment [65]. These consistent microbial changes were in alignment with the decreased SAA and increased T-AOC reported earlier, suggesting a strong mechanistic link between gut microbiota remodeling and systemic health improvement during weight management.

5. Conclusions

In conclusion, the present study demonstrates that Deinococcus radiodurans extract (DRE) serves as a potent and effective functional intervention for mitigating obesity and improving systemic metabolic health across both murine and feline models. In HFD-induced obese mice, DRE supplementation significantly reduced weight gain, regulated serum lipid profiles, and alleviated pathological lipid deposition in the liver and adipose tissues. In overweight companion cats, the intervention successfully promoted weight reduction, enhanced systemic antioxidant capacity (T-AOC), and suppressed chronic inflammation (SAA). Crucially, these metabolic improvements were tightly coupled with a conserved remodeling of the gut microbiota across species. DRE consistently restored microbial richness and optimized the ecological structure by significantly enriching key short-chain fatty acid (SCFA)-producing taxa—including Oscillibacter, Blautia, Phascolarctobacterium, and Odoribacter—while concurrently suppressing pro-inflammatory opportunistic pathogens. Overall, these findings highlight the therapeutic potential of DRE as a promising natural prebiotic ingredient for weight management and metabolic health restoration in both laboratory settings and companion animal practice.

Author Contributions

Author Contributions: Conceptualization, L.L. and Y.H.; methodology, W.H., Y.W., C.H., C.S., and Y.T.; software, W.H. and Y.W.; validation, W.H., Y.W., and C.S.; formal analysis, W.H., Y.W., and C.S.; investigation, W.H., Y.W., C.H., C.S., Y.T., S.Y., and M.H.; resources, L.L., Y.H., C.H., S.Y., and M.H.; data curation, W.H., Y.W., and C.S.; writing—original draft preparation, W.H., and Y.W.; writing—review and editing, L.L., Y.H., C.H., S.Y., and M.H.; visualization, W.H. and Y.W.; supervision, L.L. and Y.H.; project administration, L.L., Y.H., and C.H.; funding acquisition, L.L. and Y.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

All animal experiments were approved by the Animal Ethics Committee of Zhejiang A&F University (Approval No. ZAFUAC2025010).

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to commercial confidentiality and privacy restrictions.

Acknowledgments

We thank Zhejiang Kefeng Biotechnology Co., Ltd. for providing technical support in the fermentation processes. During the preparation of this manuscript, the authors used Gemini for the purposes of language editing and polishing. We explicitly state that all experimental images and data were derived from actual experiments. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
ANCOM-BC2 Analysis of Compositions of Microbiomes with Bias Correction 2
BCS Body Condition Score
DR Deinococcus radiodurans
DRE Deinococcus radiodurans Extract
F/B Firmicutes / Bacteroidota ratio
H&E Hematoxylin and Eosin
HDL-C High-Density Lipoprotein Cholesterol
HFD High-Fat Diet
IL-6 Interleukin-6
IL-10 Interleukin-10
IFN-γ Interferon-gamma
LDL Low-density lipoprotein
LDL-C Low-Density Lipoprotein Cholesterol
MCS Muscle condition scores
MDA Malondialdehyde
PCoA Principal Coordinate Analysis
PERMANOVA Permutational Multivariate Analysis of Variance
SAA Serum Amyloid A
SCFA Short-Chain Fatty Acid
TC Total Cholesterol
TG Triglyceride
TNF-α Tumor Necrosis Factor α
T-AOC Total Antioxidant Capacity
WAT White Adipose Tissue

References

  1. Abad-Jiménez Z, Vezza T: Obesity: A Global Health Challenge Demanding Urgent Action. Biomedicines 2025, 13(2). [CrossRef]
  2. Koliaki C, Dalamaga M, Liatis S: Update on the Obesity Epidemic: After the Sudden Rise, Is the Upward Trajectory Beginning to Flatten? Current Obesity Reports 2023, 12(4):514–527. [CrossRef]
  3. Kong Y, Yang H, Nie R, Zhang X, Zuo F, Zhang H, Nian X: Obesity: pathophysiology and therapeutic interventions. Molecular biomedicine 2025, 6(1):25. [CrossRef]
  4. Spiegelman BM, Flier JS: Obesity and the Regulation of Energy Balance. Cell 2001, 104(4):531–543. [CrossRef]
  5. Bray GA, Popkin BM: Dietary fat intake does affect obesity!123. The American Journal of Clinical Nutrition 1998, 68(6):1157–1173. [CrossRef]
  6. Olivares-Vicente M, Herranz-Lopez M: The Interplay Between Oxidative Stress and Lipid Composition in Obesity-Induced Inflammation: Antioxidants as Therapeutic Agents in Metabolic Diseases. Int J Mol Sci 2025, 26(17). [CrossRef]
  7. Montoya M, Péron F, Hookey T, Morrison J, German AJ, Gaillard V, Flanagan J: Overweight and obese body condition in ∼4.9 million dogs and ∼1.3 million cats seen at primary practices across the USA: Prevalences by life stage from early growth to senior. Preventive Veterinary Medicine 2025, 235:106398. [CrossRef]
  8. Martins TO, Ramos RC, Possidonio G, Bosculo MRM, Oliveira PL, Costa LR, Zamboni VAG, Marques MG, de Almeida BFM: Feline obesity causes hematological and biochemical changes and oxidative stress - a pilot study. Vet Res Commun 2023, 47(1):167–177. [CrossRef]
  9. Quinn R, Quain A: Overweight and Obesity in Dogs and Cats: An Exploration of Animal Welfare and Behaviour Impacts, and Recommendations for Management in Veterinary Primary Care. Animals (Basel) 2026, 16(8). [CrossRef]
  10. Zoran DL: Obesity in Dogs and Cats: A Metabolic and Endocrine Disorder. Veterinary Clinics: Small Animal Practice 2010, 40(2):221–239. [CrossRef]
  11. Saavedra C, Pérez C, Oyarzún C, Torres-Arévalo Á: Overweight and obesity in domestic cats: epidemiological risk factors and associated pathologies. Journal of Feline Medicine and Surgery 2024, 26(11):1098612X241285519. [CrossRef]
  12. Haddad KK: How Successful Are Veterinary Weight Management Plans for Canine Patients Experiencing Poor Welfare Due to Being Overweight and Obese? Animals (Basel) 2024, 14(5).
  13. Aremu SO, Akute B, Aremu DO, Zando C, Aremu ED, Nwachukwu OJ, Omosebi MO, Akute VO, Oluwole ST, Barkhadle AA et al.: Dietary strategies for preventing and managing obesity through evidence-based nutritional interventions. Discover Public Health 2025, 22(1):424. [CrossRef]
  14. Valladares AC, Astudillo MA, Drinnon AR, Dowlatshahi S, Kansara A, Shakil J, Patham B: Medical Management of Obesity: Current Trends and Future Perspectives. Methodist DeBakey cardiovascular journal 2025, 21(2):62–73. [CrossRef]
  15. Srivastava G, Campbell SL, Hill CR, Stanley TL, Lawson EA, Apovian CM, Almandoz JP, Leggio L, Lakdawalla DN, Dar M et al.: Novel strategies for medical management of obesity: mechanisms, clinical implications, and societal impacts—a report from the 25th Annual Harvard Nutrition Obesity Symposium. The American Journal of Clinical Nutrition 2025, 122(3):866–885. [CrossRef]
  16. Khera R, Murad MH, Chandar AK, Dulai PS, Wang Z, Prokop LJ, Loomba R, Camilleri M, Singh S: Association of Pharmacological Treatments for Obesity With Weight Loss and Adverse Events: A Systematic Review and Meta-analysis. Jama 2016, 315(22):2424–2434. [CrossRef]
  17. Siebenhofer A, Winterholer S, Jeitler K, Horvath K, Berghold A, Krenn C, Semlitsch T: Long-term effects of weight-reducing drugs in people with hypertension. The Cochrane database of systematic reviews 2021, 1(1):Cd007654. [CrossRef]
  18. Derosa G, Maffioli P: Anti-obesity drugs: a review about their effects and their safety. Expert opinion on drug safety 2012, 11(3):459–471. [CrossRef]
  19. Askari A, Jambulingam P, Gurprashad R, Al-Taan O, Adil T, Munasinghe A, Jain V, Rashid F, Whitelaw D: The surgical management of obesity. Clinical Medicine 2023, 23(4):330–336. [CrossRef]
  20. Soldan M, Argalasova L, Hadvinova L, Galileo B, Babjakova J: The Effect of Dietary Types on Gut Microbiota Composition and Development of Non-Communicable Diseases: A Narrative Review. Nutrients 2024, 16(18). [CrossRef]
  21. Kakafoni G, Zvintzou E, Kyroglou S, Giannatou K, Mparnia V, Vareltzis P, Kypreos KE: Effect of a Novel Lavender Extract on Plasma Lipid and Lipoprotein Metabolism, Glucose Tolerance and Adipose Tissue Metabolic Activation: A Preclinical Safety and Efficacy Study. Nutrients 2024, 17(1). [CrossRef]
  22. Ullah H, Dacrema M, Buccato DG, Fayed MAA, De Lellis LF, Morone MV, Di Minno A, Baldi A, Daglia M: A Narrative Review on Plant Extracts for Metabolic Syndrome: Efficacy, Safety, and Technological Advances. Nutrients 2025, 17(5). [CrossRef]
  23. Templeman JR, Hogan K, Blanchard A, Marinangeli CPF, Camara A, Verbrugghe A, Shoveller AK: Effect of raw and encapsulated policosanol on lipid profiles, blood biochemistry, activity, energy expenditure and macronutrient metabolism of adult cats. Journal of Feline Medicine and Surgery 2021, 24:177 – 184. [CrossRef]
  24. iang Z, Mei L, Li Y, Guo Y, Yang B, Huang Z, Li Y: Enzymatic Regulation of the Gut Microbiota: Mechanisms and Implications for Host Health. Biomolecules 2024, 14(12). [CrossRef]
  25. Jyoti, Dey P: Mechanisms and implications of the gut microbial modulation of intestinal metabolic processes. npj Metabolic Health and Disease 2025, 3(1):24. [CrossRef]
  26. Lin D, Medeiros DM: The microbiome as a major function of the gastrointestinal tract and its implication in micronutrient metabolism and chronic diseases. Nutrition Research 2023, 112:30–45. [CrossRef]
  27. Aziz T, Hussain N, Hameed Z, Lin L: Elucidating the role of diet in maintaining gut health to reduce the risk of obesity, cardiovascular and other age-related inflammatory diseases: recent challenges and future recommendations. Gut microbes 2024, 16(1):2297864. [CrossRef]
  28. Midya S, Banerjee A, Pathak S, Duttaroy AK: Gut Microbiota and Its Importance in Health and Disease. In: Microbiota and Dietary Mediators in Colon Cancer Prevention and Treatment. Edited by Pathak S, Banerjee A, Duttaroy AK. Singapore: Springer Nature Singapore; 2024: 1–19.
  29. Shen Y, Fan N, Ma SX, Cheng X, Yang X, Wang G: Gut Microbiota Dysbiosis: Pathogenesis, Diseases, Prevention, and Therapy. MedComm 2025, 6(5):e70168. [CrossRef]
  30. Shen Y, Sun D, Chen K, Jiang J, Shao D, Yang L, Sun C, Liu D, Ke Y, Wu C et al.: High-fat and low-fiber diet elevates the gut resistome: a comparative metagenomic study. NPJ biofilms and microbiomes 2025, 11(1):156. [CrossRef]
  31. Chassaing B, Gewirtz AT: Gut Microbiota, Low-grade Inflammation, and Metabolic Syndrome. Toxicologic Pathology 2014, 42(1):49–53. [CrossRef]
  32. Chen J, Xiao Y, Li D, Zhang S, Wu Y, Zhang Q, Bai W: New insights into the mechanisms of high-fat diet mediated gut microbiota in chronic diseases. iMeta 2023, 2(1):e69. [CrossRef]
  33. Jo JK, Seo SH, Park SE, Kim HW, Kim EJ, Kim JS, Pyo JY, Cho KM, Kwon SJ, Park DH et al.: Gut Microbiome and Metabolome Profiles Associated with High-Fat Diet in Mice. Metabolites 2021, 11(8). [CrossRef]
  34. Mamun MAA, Rakib A, Mandal M, Singh UP: Impact of a High-Fat Diet on the Gut Microbiome: A Comprehensive Study of Microbial and Metabolite Shifts During Obesity. Cells 2025, 14(6). [CrossRef]
  35. Khavandegar A, Heidarzadeh A, Angoorani P, Hasani-Ranjbar S, Ejtahed H-S, Larijani B, Qorbani M: Adherence to the Mediterranean diet can beneficially affect the gut microbiota composition: a systematic review. BMC Medical Genomics 2024, 17(1):91. [CrossRef]
  36. Liu F, Li N, Zhang Y: The radioresistant and survival mechanisms of Deinococcus radiodurans. Radiation Medicine and Protection 2023, 4(2):70–79. [CrossRef]
  37. Cox MM, Battista JR: Deinococcus radiodurans — the consummate survivor. Nature Reviews Microbiology 2005, 3(11):882–892. [CrossRef]
  38. Slade D, Radman M: Oxidative Stress Resistance in Deinococcus radiodurans. Microbiology and Molecular Biology Reviews 2011, 75(1):133–191. [CrossRef]
  39. Qi H-z, Wang W-z, He J-y, Ma Y, Xiao F-z, He S-y: Antioxidative system of Deinococcus radiodurans. Research in Microbiology 2020, 171(2):45–54. [CrossRef]
  40. Tian B, Sun Z, Shen S, Wang H, Jiao J, Wang L, Hu Y, Hua Y: Effects of carotenoids from Deinococcus radiodurans on protein oxidation. Letters in Applied Microbiology 2009, 49(6):689–694. [CrossRef]
  41. Dong X, Tian B, Dai S, Li T, Guo L, Tan Z, Jiao Z, Jin Q, Wang Y, Hua Y: Expression of PprI from Deinococcus radiodurans Improves Lactic Acid Production and Stress Tolerance in Lactococcus lactis. PLOS ONE 2015, 10(11):e0142918. [CrossRef]
  42. Han JM, Lim J, Kim WS, Yoo BG, Jung JH, Lim S, Byun EB: Deinoxanthin-Enriched Extracellular Vesicles from Deinococcus radiodurans Drive IL-10-Dependent Tolerogenic Programming of Dendritic Cells. Antioxidants (Basel) 2025, 14(9). [CrossRef]
  43. Langhi C, Vallier M, Bron A, Otero YF, Maura M, Le Joubioux F, Blomberg N, Giera M, Guigas B, Maugard T et al.: A polyphenol-rich plant extract prevents hypercholesterolemia and modulates gut microbiota in western diet-fed mice. Frontiers in Cardiovascular Medicine 2024, Volume 11 - 2024. [CrossRef]
  44. Wang Y, Chen Z, Hua C, Mao J, Geng W, Feng X, Ye S, Song S, Wang H, Wang X et al.: Cross-sectional analysis of feline gut microbiota reveals differences across age-defined groups under varying environments. Frontiers in Veterinary Science 2026, 13. [CrossRef]
  45. Theodorakis N, Nikolaou M: The Human Energy Balance: Uncovering the Hidden Variables of Obesity. Diseases (Basel, Switzerland) 2025, 13(2). [CrossRef]
  46. Torres-Carot V, Suárez-González A, Lobato-Foulques C: The energy balance hypothesis of obesity: do the laws of thermodynamics explain excessive adiposity? European Journal of Clinical Nutrition 2022, 76(10):1374–1379. [CrossRef]
  47. Nelson VLB, Ballou LM, Lin RZ: Energy balancing by fat Pik3ca. Adipocyte 2015, 4(1):70–74. [CrossRef]
  48. Taylor S, Roberts G, Evans M, German AJ: Recording of body weight and body condition score of cats in electronic health records from UK veterinary practices. Journal of Feline Medicine and Surgery 2022, 24(10):e380–e393. [CrossRef]
  49. Zhang Q, Li Y, Han Y, Zhou W, Li X, Sun J, Bai W: Lactiplantibacillus plantarum FEED8 Biosynthesis of Pyranoanthocyanin (Cyanidin-3-glucoside-4-vinylcatechol) Improves Oxidative Stress and Inflammation of the Gut Microbiome in Cadmium-Exposed Mice. Journal of Agricultural and Food Chemistry 2025, 73(12):7187–7201. [CrossRef]
  50. Zhao Y, Zhao M-F, Jiang S, Wu J, Liu J, Yuan X-W, Shen D, Zhang J-Z, Zhou N, He J et al.: Liver governs adipose remodelling via extracellular vesicles in response to lipid overload. Nature Communications 2020, 11(1):719. [CrossRef]
  51. Duwaerts CC, Maher JJ: Macronutrients and the Adipose-Liver Axis in Obesity and Fatty Liver. Cellular and Molecular Gastroenterology and Hepatology 2019, 7(4):749–761. [CrossRef]
  52. Li Q, Spalding KL: The regulation of adipocyte growth in white adipose tissue. Frontiers in Cell and Developmental Biology 2022, Volume 10 - 2022.
  53. Yang Z-H, Chen F-Z, Zhang Y-X, Ou M-Y, Tan P-C, Xu X-W, Li Q-F, Zhou S-B: Therapeutic targeting of white adipose tissue metabolic dysfunction in obesity: mechanisms and opportunities. MedComm 2024, 5(6):e560. [CrossRef]
  54. Patil BS, Patil JK, Chaudhari HS, Patil BS: Oxidative Stress, Inflammation, and Obesity: Insights into Mechanism and Therapeutic Targets. Proceedings 2025, 119(1):6. [CrossRef]
  55. Riaz Rajoka MS, Thirumdas R, Mehwish HM, Umair M, Khurshid M, Hayat HF, Phimolsiripol Y, Pallarés N, Martí-Quijal FJ, Barba FJ: Role of Food Antioxidants in Modulating Gut Microbial Communities: Novel Understandings in Intestinal Oxidative Stress Damage and Their Impact on Host Health. Antioxidants 2021, 10(10):1563. [CrossRef]
  56. Li L, Guo Z, Zhao Y, Liang C, Zheng W, Tian W, Chen Y, Cheng Y, Zhu F, Xiang X: The impact of oxidative stress on abnormal lipid metabolism-mediated disease development. Archives of biochemistry and biophysics 2025, 766:110348. [CrossRef]
  57. Yang Q, Wu Z: Gut Probiotics and Health of Dogs and Cats: Benefits, Applications, and Underlying Mechanisms. Microorganisms 2023, 11(10). [CrossRef]
  58. Wang W, Dong H, Chang X, Chen Q, Wang L, Chen S, Chen L, Wang R, Ge S, Wang P et al.: Bifidobacterium lactis and Lactobacillus plantarum Enhance Immune Function and Antioxidant Capacity in Cats through Modulation of the Gut Microbiota. Antioxidants (Basel) 2024, 13(7). [CrossRef]
  59. Gomez-Arango LF, Barrett HL, McIntyre HD, Callaway LK, Morrison M, Dekker Nitert M: Increased Systolic and Diastolic Blood Pressure Is Associated With Altered Gut Microbiota Composition and Butyrate Production in Early Pregnancy. Hypertension 2016, 68(4):974–981. [CrossRef]
  60. Watanabe Y, Nagai F, Morotomi M: Characterization of Phascolarctobacterium succinatutens sp. nov., an Asaccharolytic, Succinate-Utilizing Bacterium Isolated from Human Feces. Applied and Environmental Microbiology 2012, 78(2):511–518. [CrossRef]
  61. Koh A, De Vadder F, Kovatcheva-Datchary P, Bäckhed F: From Dietary Fiber to Host Physiology: Short-Chain Fatty Acids as Key Bacterial Metabolites. Cell 2016, 165(6):1332–1345. [CrossRef]
  62. De Vadder F, Kovatcheva-Datchary P, Goncalves D, Vinera J, Zitoun C, Duchampt A, Bäckhed F, Mithieux G: Microbiota-Generated Metabolites Promote Metabolic Benefits via Gut-Brain Neural Circuits. Cell 2014, 156(1):84–96. [CrossRef]
  63. Canfora EE, Jocken JW, Blaak EE: Short-chain fatty acids in control of body weight and insulin sensitivity. Nature Reviews Endocrinology 2015, 11(10):577–591. [CrossRef]
  64. Portincasa P, Khalil M, Mahdi L, Perniola V, Idone V, Graziani A, Baffy G, Di Ciaula A: Metabolic Dysfunction–Associated Steatotic Liver Disease: From Pathogenesis to Current Therapeutic Options. In: International Journal of Molecular Sciences. vol. 25; 2024: 5640. [CrossRef]
  65. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI: An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444(7122):1027–1031. [CrossRef]
  66. Chen YR, Zheng HM, Zhang GX, Chen FL, Chen LD, Yang ZC: High Oscillospira abundance indicates constipation and low BMI in the Guangdong Gut Microbiome Project. Sci Rep 2020, 10(1):9364. [CrossRef]
  67. Konikoff T, Gophna U: Oscillospira: a Central, Enigmatic Component of the Human Gut Microbiota. Trends in Microbiology 2016, 24(7):523–524. [CrossRef]
  68. Sankarganesh P, Bhunia A, Ganesh Kumar A, Babu AS, Gopukumar ST, Lokesh E: Short-chain fatty acids (SCFAs) in gut health: Implications for drug metabolism and therapeutics. Medicine in Microecology 2025, 25:100139. [CrossRef]
  69. Barcenilla A, Pryde Susan E, Martin Jennifer C, Duncan Sylvia H, Stewart Colin S, Henderson C, Flint Harry J: Phylogenetic Relationships of Butyrate-Producing Bacteria from the Human Gut. Applied and Environmental Microbiology 2000, 66(4):1654–1661. [CrossRef]
  70. Louis P, Flint HJ: Diversity, metabolism and microbial ecology of butyrate-producing bacteria from the human large intestine. FEMS Microbiology Letters 2009, 294(1):1–8. [CrossRef]
  71. Van den Abbeele P, Ghyselinck J, Marzorati M, Koch AM, Lambert W, Michiels J, Chalvon-Demersay T: The Effect of Amino Acids on Production of SCFA and bCFA by Members of the Porcine Colonic Microbiota. Microorganisms 2022, 10(4). [CrossRef]
  72. Pereira FC, Wasmund K, Cobankovic I, Jehmlich N, Herbold CW, Lee KS, Sziranyi B, Vesely C, Decker T, Stocker R et al.: Rational design of a microbial consortium of mucosal sugar utilizers reduces Clostridiodes difficile colonization. Nature Communications 2020, 11(1):5104. [CrossRef]
  73. Salazar-Jaramillo L, de la Cuesta-Zuluaga J, Chica Luis A, Cadavid M, Ley Ruth E, Reyes A, Escobar Juan S: Gut microbiome diversity within Clostridia is negatively associated with human obesity. mSystems 2024, 9(8):e00627–00624. [CrossRef]
  74. Liu X, Mao B, Gu J, Wu J, Cui S, Wang G, Zhao J, Zhang H, Chen W: Blautia-a new functional genus with potential probiotic properties? Gut Microbes 2021, 13(1):1–21. [CrossRef]
  75. Facchin S, Bertin L, Bonazzi E, Lorenzon G, De Barba C, Barberio B, Zingone F, Maniero D, Scarpa M, Ruffolo C et al.: Short-Chain Fatty Acids and Human Health: From Metabolic Pathways to Current Therapeutic Implications. Life (Basel) 2024, 14(5). [CrossRef]
Figure 1. Effects of DRE on the growth performance and hematological parameters of mice. (a) Physical appearance of mice from different groups. (b) Body weight changes over 20 weeks. The red triangle indicates the initiation of dietary intervention at week 12. (c) Serum total cholesterol (TC) concentration at weeks 12, 16, and 20. (d) Serum triglyceride (TG) concentration at weeks 12, 16, and 20. (e) Serum low-density lipoprotein (LDL) concentration at weeks 12, 16, and 20. All data are expressed as the mean ± SD. The horizontal lines with asterisks indicate statistical significance between the connected groups (*P < 0.05, **P < 0.01).
Figure 1. Effects of DRE on the growth performance and hematological parameters of mice. (a) Physical appearance of mice from different groups. (b) Body weight changes over 20 weeks. The red triangle indicates the initiation of dietary intervention at week 12. (c) Serum total cholesterol (TC) concentration at weeks 12, 16, and 20. (d) Serum triglyceride (TG) concentration at weeks 12, 16, and 20. (e) Serum low-density lipoprotein (LDL) concentration at weeks 12, 16, and 20. All data are expressed as the mean ± SD. The horizontal lines with asterisks indicate statistical significance between the connected groups (*P < 0.05, **P < 0.01).
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Figure 2. Effects of DRE on hepatic morphology, lipid accumulation, and histological structure in mice. (a) Gross morphology of the liver. (b) Liver weight. (c) H&E staining of liver sections at Week 16 and Week 20. (d) Representative images of Oil Red O staining in liver tissues. (e) Quantitative analysis of Oil Red O-positive area (%). All data are expressed as the mean ± SD. *P < 0.05 and **P < 0.01.
Figure 2. Effects of DRE on hepatic morphology, lipid accumulation, and histological structure in mice. (a) Gross morphology of the liver. (b) Liver weight. (c) H&E staining of liver sections at Week 16 and Week 20. (d) Representative images of Oil Red O staining in liver tissues. (e) Quantitative analysis of Oil Red O-positive area (%). All data are expressed as the mean ± SD. *P < 0.05 and **P < 0.01.
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Figure 3. Effect of DRE on the morphology of adipose tissue in mice.
Figure 3. Effect of DRE on the morphology of adipose tissue in mice.
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Figure 4. Effects of DRE on gut microbiota in mice. (a) Alpha-diversity analysis including Shannon, Simpson, and Chao1 indices. (b) Principal Coordinate Analysis (PCoA) illustrating the separation of CON, HFD, and HFD+1.5%DRE microbial communities. (c) Relative abundance of gut microbiota at the phylum level. (s) Heatmap of the main genus showing the structural shifts in microbial composition.
Figure 4. Effects of DRE on gut microbiota in mice. (a) Alpha-diversity analysis including Shannon, Simpson, and Chao1 indices. (b) Principal Coordinate Analysis (PCoA) illustrating the separation of CON, HFD, and HFD+1.5%DRE microbial communities. (c) Relative abundance of gut microbiota at the phylum level. (s) Heatmap of the main genus showing the structural shifts in microbial composition.
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Figure 5. Comparative analysis of fecal microbiota composition in mice. Individual panels illustrate the specific taxonomic shifts identified via ANCOM-BC2 analysis among the CON, HFD, and HFD+1.5%DRE groups. Box plots represent the median (horizontal line) and the first and third quartiles (box limits), with whiskers extending to 1.5 times the interquartile range. Individual data points are superimposed as overlaid jitter points.
Figure 5. Comparative analysis of fecal microbiota composition in mice. Individual panels illustrate the specific taxonomic shifts identified via ANCOM-BC2 analysis among the CON, HFD, and HFD+1.5%DRE groups. Box plots represent the median (horizontal line) and the first and third quartiles (box limits), with whiskers extending to 1.5 times the interquartile range. Individual data points are superimposed as overlaid jitter points.
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Figure 6. Effects of DRE supplementation on the physical and clinical parameters of overweight cats during a 28-day intervention. (a) Body condition score (BCS). (b) Body weight (kg). (c) Waistline (cm). Data are expressed as the mean ± SD (n = 6).
Figure 6. Effects of DRE supplementation on the physical and clinical parameters of overweight cats during a 28-day intervention. (a) Body condition score (BCS). (b) Body weight (kg). (c) Waistline (cm). Data are expressed as the mean ± SD (n = 6).
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Figure 7. Effects of DRE on serum antioxidant capacity and inflammatory status in overweight cats. (a) Superoxide dismutase (SOD) activity. (b) Catalase (CAT) activity. (c) Total antioxidant capacity (T-AOC). (d) Malondialdehyde (MDA) concentration. (e) Serum amyloid A (SAA) concentration. (f) Tumor necrosis factor-alpha (TNF-α) concentration. (g) Interferon-gamma (IFN-γ) concentration. (g) Interleukin-10 (IL-10) concentration. (i) Interleukin-6 (IL-6) concentration. All data are expressed as the mean ± SD (n = 6). *P < 0.05 versus Day 0; NS indicates no significant difference (P > 0.05).
Figure 7. Effects of DRE on serum antioxidant capacity and inflammatory status in overweight cats. (a) Superoxide dismutase (SOD) activity. (b) Catalase (CAT) activity. (c) Total antioxidant capacity (T-AOC). (d) Malondialdehyde (MDA) concentration. (e) Serum amyloid A (SAA) concentration. (f) Tumor necrosis factor-alpha (TNF-α) concentration. (g) Interferon-gamma (IFN-γ) concentration. (g) Interleukin-10 (IL-10) concentration. (i) Interleukin-6 (IL-6) concentration. All data are expressed as the mean ± SD (n = 6). *P < 0.05 versus Day 0; NS indicates no significant difference (P > 0.05).
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Figure 8. Effects of DRE on gut microbiota in overweight cats. (a) Alpha-diversity analysis including Shannon, Simpson, and Chao1 indices. (b) Principal Coordinate Analysis (PCoA) illustrating the separation of D0 and D28 microbial communities. (c) Relative abundance of gut microbiota at the phylum level. (d) Heatmap of the main genus showing the structural shifts in microbial composition.
Figure 8. Effects of DRE on gut microbiota in overweight cats. (a) Alpha-diversity analysis including Shannon, Simpson, and Chao1 indices. (b) Principal Coordinate Analysis (PCoA) illustrating the separation of D0 and D28 microbial communities. (c) Relative abundance of gut microbiota at the phylum level. (d) Heatmap of the main genus showing the structural shifts in microbial composition.
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