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. 2025 Feb 20;17(1):2467193. doi: 10.1080/19490976.2025.2467193

Roseburia hominis improves host metabolism in diet-induced obesity

Wenli Huang a,b,c, Wenyi Zhu a,b,c, Yu Lin a,b,c, Francis K L Chan a,b,d, Zhilu Xu a,b,c,✉, Siew C Ng a,b,c,d,✉
PMCID: PMC11845086  PMID: 39976263

ABSTRACT

Next-generation live biotherapeutics are promising to aid the treatment of obesity and metabolic diseases. Here, we reported a novel anti-obesity probiotic candidate, Roseburia hominis, that was depleted in stool samples of obese subjects compared with lean controls, and its abundance was negatively correlated with body mass index and serum triglycerides. Supplementation of R. hominis prevented body weight gain and disorders of glucose and lipid metabolism, prevented fatty liver, inhibited white adipose tissue expansion and brown adipose tissue whitening in mice fed with high-fat diet, and boosted the abundance of lean-related species. The effects of R. hominis could be partially attributed to the production of nicotinamide riboside and upregulation of the Sirtuin1/mTOR signaling pathway. These results indicated that R. hominis is a promising candidate for the development of next-generation live biotherapeutics for the prevention of obesity and metabolic diseases.

KEYWORDS: Intestinal microbiology, Obesity, probiotics

Introduction

Obesity is a pressing global public health issue with at least 2.8 million people dying each year attributed to its consequences.1 Obesity could also cause life-threatening complications, including different kinds of cancer, stroke, and sleep apnea.2–4 The incidence of overweight or obesity has been rapidly increasing for the past few decades, where people are adopting a Westernized lifestyle.5 Environmental factors have also been implicated, including changes in the gut microbiota, to play a role in the development of metabolic disorders. Numerous studies have reported that obese individuals have abnormal gut microbiota.6,7 Obesity was associated with notable alterations in microbiome composition, individual taxa, and function, whereas such microbiome associations were modest for type 2 diabetes.8 Transplantation of fecal samples from obese humans to mouse models could lead to weight gain in mice, suggesting that the gut microbiota may play a causative role in obesity.9 Although the exact mechanism linking gut microbiota to obesity is far from being very well understood, it’s well established that gut microbiota can increase energy production from diet, contribute to low-grade inflammation, and regulate fatty acid composition.

Conventional non-pharmacological interventions based on diet and exercise showed limited success in achieving sustained weight loss,10 while treatment by medications or bariatric surgery is limited by high cost or potential surgical-related complications.11 Our previous work has shown that modulation of gut microbiota through fecal microbiota transplantation (FMT) holds a tremendous therapeutic potential to treat the growing obesity epidemic, especially when combined with diet and exercise.12 However, the application of FMT is limited by several obstacles, including a lack of dedicated centers, difficulties with donor recruitment, and complexities related to regulation and safety monitoring.13 Growing evidence supports that probiotics and symbiotics exert some beneficial role in human health.14 One of the gut bacteria, Akkermansia muciniphila, has been demonstrated as a promising next-generation live biotherapeutics to counter obesity and metabolic diseases.15,16 In our recent systematic review of microbiota in obesity and metabolic diseases, we found a consistent depletion of the bacterial genus Roseburia in patients with obesity and metabolic disorders in the eastern population.17,18 In a cross-sectional study of the Chinese population from two different geographic regions, we found that R. hominis was depleted in subjects with obesity, with or without type 2 diabetes, compared with lean healthy control subjects.19 The depletion of R. hominis was further confirmed by a study containing 2262 Chinese individuals using metagenomics sequencing.20 Here, we investigated the impact of R. hominis on body weight, metabolic profile, and gut microbiota in a diet-induced obese mouse model, and the underlying mechanism of R. hominis on the improvement of metabolic health.

Materials and methods

Study participants

The stool samples of 100 subjects from the Hong Kong cohort (43 lean controls and 57 obese subjects) were used to verify the abundance of R. hominis. The age of all the subjects in this study was 18–70 years. Lean healthy controls were recruited from the general population and were included if they had a body mass index (BMI) greater than or equal to 18.5 Kg/m2 and less than 23 Kg/m2. Subjects with obesity were included if their BMI greater than or equal to 28 Kg/m2. Patients were excluded if they had cancer, severe gastrointestinal diseases, active infection, acquired immunodeficiency syndrome, known history of organ dysfunction or failure, abdominal surgery, or autoimmune diseases. We collected subjects’ stool samples and performed metagenomics sequencing. This study was approved by the Ethics Committee of the Chinese University of Hong Kong (No: 2014.026).

A total of 275 healthy controls and 222 individuals with obesity or type 2 diabetes from the MetaCardis project21were included to validate our findings from the in-house cohort. The MetaCardis project is a public European cohort aimed at investigating the microbiome characteristics associated with the spectrum of cardiometabolic diseases.

Fecal whole DNA extraction

The fecal samples from human subjects were fresh-frozen in the −80 freezer. The whole DNA of fecal samples was extracted using Maxwell RSC PureFood GMO and Authentication Kit. Briefly, fecal pellet was added to 1 mL of CTAB buffer and vortexed for 30 seconds, then the sample was heated at 95°C for 5 minutes. The samples were vortexed thoroughly with beads at a maximum speed for 15 minutes. 40 μL of proteinase K and 20 μL of RNase A were added to the sample and the mixture was incubated at 70°C for 10 minutes. The supernatant was then obtained by centrifuging at 13,000 g for 5 minutes and was added to the Maxwell RSC machine for DNA extraction. The extracted DNA concentration was measured using the Qubit® dsDNA Assay Kit in Qubit® 2.0 Fluorometer (Life Technologies, CA, USA).

Quantitative polymerase chain reaction (qPCR)

To quantify the specific bacteria in human stool samples, qPCR was conducted to detect the level of R. hominis by using the fecal genomic DNA in 10 µl of SYBR Green qPCR Master Mix (Takara, Japan). Bacteria quantitation was calculated relative to the universal 16s gene. Total RNA was extracted from the mice tissue and cells through the Trizol method using RNAiso Plus (Takara, Japan) according to protocol. The reverse transcription of RNA into DNA complement was conducted using PrimeScript™ RT Master Mix (Takara, Japan). The amplification and qPCR were performed using TB Green® Premix Ex Taq™ (Takara, Japan). All reactions were performed in triplicate and analyzed on QuantStudio TM 7 Flex System (ThermoFisher Scientific, USA). Sequences of primers used in this study are available in Table S1.

Animal experiment

5 weeks-old male C57BL/6 wild-type mice were housed in the animal facility under standard conditions, with free access to water and a normal chow diet (ND). Mice were co-housed for 4 weeks with the exchange of beddings to homogenize the baseline microbiota. After co-housing, mice were randomly divided into different groups (five mice per group). Mice were fed with a high-fat diet (40% fat, HFD), and orally challenged with 109 colony forming units of R. hominis (HFD-RH) or phosphate-buffered saline (HFD-PBS). Another group were fed with ND and orally administrated with PBS (ND-PBS). The body weight of mice was recorded weekly. BMI was calculated to assess mice obesity.22 The 72-hour food consumption was measured at baseline and endpoint. The fecal samples of mice were collected at baseline and week 11 and immediately frozen using liquid nitrogen. The mice were euthanized at 11 weeks and analyzed. All animal procedures were approved by the Animal Experimentation Ethics Committee of the Chinese University of Hong Kong.

Preparation of bacteria suspension and supernatant

Type strain R. hominis A2–183 (DSM 16,839) was obtained from the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures. Under anaerobic conditions, type stains were cultured in a modified YCFA medium supplemented with 0.2% each of glucose, maltose, and cellobiose overnight.23 The resulting culture was centrifuged at 4500rpm for 15 min. The supernatant was collected. The precipitate was resuspended using PBS.

Oral glucose tolerance test and insulin resistance index

After 10 weeks of treatment, the mice were fasted for 8 hours and given an oral gavage of D-glucose at a dose of 2 grams per Kg body weight. Plasma was collected before and 15 min, 30 min, 60 min, 90 min and 120 min after oral glucose gavage from the tip of the tail vein. Blood glucose was determined with a glucose meter (Sinocare, China) at each timepoint. Plasma insulin was determined using the high-sensitive mouse insulin ELISA kit (IMD, Hong Kong, China) according to the manufacturer’s protocol. Insulin resistance index was calculated by the area under the curve of both blood glucose and plasma insulin before and 120 min after oral glucose gavage.

Tissue sampling

At the end of the experiment, the mice were anesthetized, and the blood was collected from the heart. Afterwards, mice were immediately sacrificed for cervical dislocation. Liver, white and brown adipose tissues were dissected and measured. A section of the tissues was immersed in liquid nitrogen and stored at −80°C for further analysis. Another part of the tissues was fixed in 4% paraformaldehyde or placed in a sucrose solution for histological analysis.

Biochemical measurements

The triglycerides (TG), total cholesterol (TC), high- and low-density lipoprotein cholesterol, aspartate aminotransferase (AST), alanine transaminase (ALT) in mouse serum and hepatic triglycerides were determined via metabolism kits (Nanjing Jiancheng Bioengineering Institute, China) and measured using spectrophotometer according to the manufacturer’s instructions. Nicotinamide adenine dinucleotide (NAD+) level was determined using NAD+/NADH assay Kit (Beyotime, China). The NAD+ levels in liver tissues were adjusted with tissue weight. The NAD+ levels in cells were adjusted with cellular protein concentration.

Histological analysis

At room temperature, tissue samples were fixed in 4% paraformaldehyde for 24 hours, processed to dehydration, paraffin section, and stained with hematoxylin-eosin (H&E). A section of liver and white adipose tissue was processed to frozen section, rewarmed, dried and stained with 0.5% Oil Red O working solution (Sigma-Aldrich, Germany). L-02 cells were washed with pre-cooled PBS at 4°C and fixed in 4% paraformaldehyde for 10 min, and incubated with Oil Red O dye for 15 min at 25°C. The stained tissues and cells were scanned under a light microscope (Olympus, Japan) and images were obtained using imaging software.

Metagenomics profiling

For the fecal microbiota analysis, mice fecal DNA was extracted by Maxwell RSC PureFood GMO and Authentication Kit as mentioned above. DNA libraries were analyzed for size distribution using the Agilent2100 Bioanalyzer (Agilent, USA) and were sequenced on an Illumina HiSeq platform. Raw sequence reads were trimmed using Trimmomatic to remove adapters and low-quality regions (v-0.36). Host reads were removed using KneadData (C57BL). Paired-end reads were concatenated. High-quality reads were used to obtain species-level taxonomic profiling by Kraken2. Principal coordinate analysis (PCoA) was conducted using R packages phyloseq and vegan. Linear discriminant analysis (LDA) effect size (LEFSe) was used to determine the taxa between the two groups, taxa with LDA > 2 and adjusted p < 0.05 were shown. Functional pathways were predicted using HUMAnN3. The difference in proportions between the groups is shown with 95% confidence intervals. Only pathways with p value < 0.05 (Welch’s t-test, FDR adjusted) were shown.

Metabolomic profiling

Mice serum and conditioned culture medium were subjected to untargeted or targeted metabolomic profiling. Untargeted metabolomics analysis was performed using an LC-ESI-MS/MS system (UPLC, ExionLC AD, https://sciex.com.cn/; MS, QTRAP® System, https://sciex.com/). Targeted metabolomic analysis was based on triple quadrupole ultra-high-performance liquid chromatography tandem mass spectrometry coupled to Sciex QTrap 6500+ mass spectrometer (AB Sciex LLC, Framingham, MA, USA). Metabolomic data was analyzed using the R package Metabo AnalystR20. Significantly regulated metabolites between groups were determined by VIP ≥ 1 and absolute Log2 (Fold change) ≥1.

Cell culture and treatment

The human liver cell-line L-02 was cultured in a medium containing 1% double antibiotic streptomycin and penicillin (Logan, UT, USA), 10% fetal bovine serum and 89% Dulbecco’s modified eagle medium (Thermo Fisher Scientific, USA). Cells were incubated at 37°C with 5% CO2 and 95% moist air. Cells were cultured with a medium containing 5 mg/100 ml palmitic acid (PA) and simultaneously treated with: heat-killed (65°C, 30 minutes) R. hominis, R. hominis conditioned medium (RHCM) and RHCM treated with proteinase K. Nicotinamide riboside (Selleck, USA) and E×527(20uM, MedchemExpress, Sweden) were diluted in culture medium to intervene cells for 24 hours.

RNA sequencing (RNA-Seq)

Total RNA was extracted from the cells treated with PA plus RHCM or PA plus YCFA through the Trizol method using RNAiso Plus (Takara, Japan) according to the manuscript protocol. Messenger RNA (mRNA) was purified, and a sequencing library was constructed by Novogene (Beijing, China). Raw sequence reads were trimmed using Trimmomatic to remove adapters and low-quality regions (Trimmomatic-0.36). High-quality sequencing reads were mapped to the reference genome of GRCh38. STAR-2.7.3a was used to align genes. SAMtools-1.13 and HTseq were used to sort and count high throughput reads. Differentially expressed genes were screened using DESeq in R. Genes with adjusted P-value < 0.05 and |log2(Fold Change) |>1 were considered as differentially expressed and then mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database (http://www.kegg.jp/kegg/pathway.html).

Statistical analysis

All statistical tests were performed using R Project v4.1.2 or GraphPad Software Version 8.0.1 (La Jolla, CA, USA). Data are presented as percentage (%), median (P25–P75) or mean ± SE. Two groups comparison was made using t test or Mann-Whitney U test. Multiple group comparisons were made by one-way analysis of variance (ANOVA). Two-way repeated measures ANOVA was conducted to compared repeated measure data. Chi-square test was used to analyze categorical data. Correlation analysis was conducted by Spearman correlation test. p < 0.05 was considered statistically significant. The data with a superscript symbol (* Model group vs Blank group, # Intervention group vs model group) are significantly different (*p < 0.05; **p < 0.01; ***p < 0.001).

Results

R. hominis was depleted in subjects with obesity

In our previous study, we found that R. hominis were depleted in patients with obesity.19 Such depletion was further confirmed by qPCR with species-specific primers (Figure 1(a,b)). Table S2 showed the basic character characteristics of subjects recruited in this study. We further validated this finding in the MetaCardis cohort21 and found that the relative abundance of R. hominis was depleted in metabolically compromised subjects than in lean controls (Figure 1c). The prevalence of R. hominis was also lower in subjects with obesity compared with lean controls (Figure 1d). Moreover, the relative abundance of R. hominis negatively correlated with BMI and TG in our cohort (Figure 1(e,f)) and was negatively correlated with BMI, TG, and waist circumference in the MetaCardis cohort (Figure 1g).

Figure 1.

Figure 1.

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The prevalence and relative abundance of R. hominis in obesity patients. (a) Log10 transferred relative abundance of R. hominis in obese and lean subjects detected by metagenomics sequencing and (b) qPCR in the Hong Kong cohort (N = 100, obese 53, lean 47). (c) Log10 transferred relative abundance of R. hominis in untreated metabolically subjects and lean subjects detected by metagenomics sequencing. (d)The prevalence of R. hominis in the Hong Kong cohort (N = 100, obese 53, lean 47). (e) Correlation between R. hominis and BMI in Hong Kong cohort; (f) Correlation between R. hominis and TG in Hong Kong cohort. (g) Correlation between R. hominis and metabolism parameters in the published dataset.

R.hominis prevented body weight gain and improved glucose and lipid metabolism in mice fed with HFD

We next assessed whether supplementation of R hominis could prevent diet-induced obesity in mice. The body weight and weight gain in the HFD-RH group were significantly lower than those in the HFD-PBS group at week 11 (Figure 2(a–d)). The BMI of mice in the HFD-RH group was also remarkably lower than those in the HFD-PBS group (Figure 2e). Mice in the HFD-RH group exhibited lower food consumption within a 72- hour period compared to those in the HFD-PBS group, although this difference did not reach statistical significance (Figure 2f). Mice in the HFD-RH group demonstrated higher insulin sensitivity and lower insulin resistance compared with mice in the HFD-PBS group (Figure 2(g–i)). Notably, the TC and TG levels of mice in the HFD-RH group were substantially lower than those in the HFD-PBS group (Figure 2(j,k)). Fecal samples from the HFD-RH group had 8.24% and 8.56% more calories at week 4 and week 11, respectively, compared with the HFD-PBS group. This indicated that R. hominis inhibited energy absorption from food and thereby contributed to the prevention of diet-induced obesity.

Figure 2.

Figure 2.

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R. hominis prevented body weight gain and metabolic disorder in hfd-induced obese mice. (a) Body weight of mice treated during 11 weeks by oral gavage live R. hominis in PBS and fed with HFD. (b) Body weight in grams after 11 weeks of treatment. (c) Body weight gain of mice treated during 11 weeks by oral gavage live R. hominis in PBS and fed with HFD. (d) Body weight gain in grams after 11 weeks of treatment. (e) BMI of mice. (f) Food consumption of mice for 72 hours. (g-h) Plasma insulin and mean area under the curve after glucose administration during glucose tolerance test. (I) Insulin resistance index. (j-k) Serum total cholesterol and triglycerides levels in mice after 11 weeks of intervention. Data are presented as the mean ± SEM. * 0.01 < p < 0.05, ** 0.001 < p < 0.01, *** p < 0.001 for ND-PBS versus HFD-PBS comparisons and # 0.01 < p < 0.05, ## 0.001 < p < 0.01, ### p < 0.001 for HFD-PBS versus HFD-RH comparisons. “ns” indicates not significant (p > 0.05).

R. hominis mitigated hepatic steatosis and aberrant adipose tissue morphology in mice fed with HFD

The liver weight in the HFD-RH group were lower than that in the HFD-PBS group at week 11, although the results did not reach statistical significance (Supplementary Figure S1A-B). Administration of R. hominis mitigated the lipid accumulation and distorted tissue structure in the liver induced by HFD (Figure 3(a,b)). The same changes were observed for hepatic TG, hepatic steatosis, and inflammation scores, as well as serum levels of ASL and ALT (Figure 3(c–g)). These results indicated that the administration of R. hominis exerted a protective effect against HFD-induced liver injury.

Figure 3.

Figure 3.

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R. hominis reduced lipid accumulation and inhibited structural disorder of metabolic tissues in mice fed with HFD. (a) H & E and oil red O-stained pictures of liver tissue. (b) Lipid droplet area in oil red O-stained slides of mice liver; (c) Hepatic TG level. (d-e) the steatosis and inflammation score for the liver of nd-fed or hfd-fed mice gavaged with R. hominis or PBS control. (f-g) AST and ALT levels in mouse serum. (h-k) H&E-staining, adipocyte diameter, adipocyte diameter distribution, and the distribution of large adipocytes (>80 μm) in white adipose tissue. (l-m) h&e-staining, lipid droplet area in brown adipose tissue. (N) Relative expression of genes related to energy metabolism and mitochondrial function in the brown adipose tissue. Data are presented as the mean ± SEM.* 0.01 < p < 0.05, ** 0.001 < p < 0.01, *** p < 0.001 for ND-PBS versus HFD-PBS comparisons and # 0.01 < p < 0.05, 0.001 < p < 0.01, p < 0.001 for HFD-PBS versus HFD-RH comparisons. “ns” indicates not significant (p > 0.05).

Furthermore, supplementing live R. hominis to HFD-fed mice resulted in a significant decrease in the weight of white adipose tissue and the ratio of white adipose tissue weight to body weight, compared to HFD-fed mice without intervention (Supplementary Figure S1C-D). The adipocytes in the white adipose tissue of mice in the HFD-RH group had a markedly smaller diameter, suggesting reduced lipid accumulation (Figure 3(h,i)). Moreover, R. hominis intervention led to an increased proportion of small adipocytes and a decreased proportion of large adipocytes in white adipose tissue (Figure 3(j,k)). Supplementing with R. hominis in HFD-fed mice also restored the morphology of brown adipocytes and inhibited brown adipose tissue whitening, as evidenced by the decreased surface area occupied by lipid droplets (Figure 3(l,m)). The genes involved in energy metabolism, such as cell death-inducing Cidea, Dio2, UCP1, and PGC1α, were upregulated in the brown adipose tissue of mice intervened with live R. hominis as indicated by qPCR, although statistical significance was reached only for Cidea (Figure 3n).

R. hominis supplementation improved intestinal microbiota composition and metabolome in mice fed with HFD

At week 11, the Shannon index showed an increased trend in the HFD-RH group compared with the HFD-PBS group (Figure 4a). Beta-diversity based on Jensen-Shannon divergence distance presented significant separate clusters for the HFD-RH group, compared with the HFD-PBS group (Figure 4b). We observed significant enrichment of certain species with positive effects on obesity, such as Faecalibacterium prausnitzii, Dysosmobacter welbionis, Parabacteroides goldsteinii, and Lactobacillus johnsonii24–27 in RH-treated mice (Figure 4(c,d)). In contrast, pathogenic bacteria, such as Olsenella uli,28 were depleted in mice treated with R. hominis (Figure 4d). Correlation analysis indicated that the relative abundance of beneficial bacteria was negatively associated with the body weight gain, BMI, TG, TC, ALT, and AST of mice, however, the relative abundance of pathogenic bacteria exhibited a positive association with these indices (Figure 4e). The abundance of R. hominis of mice in the HFD-RH group significantly increased at week 11, compared to the baseline (Supplementary Figure S2A-B). Functional predictions identified 59 differentially present metaCyc pathways between HFD-PBS and HFD-RH groups. Gluconeogenesis-related pathways, such as the gluconeogenesis III pathway, were depleted, while pathways that promote energy metabolism, such as TCA cycle IV and lipid IVA biosynthesis, were enriched (Supplementary Figure S2C).

Figure 4.

Figure 4.

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R. hominis supplementation restored the composition of mouse intestinal microbiota. (a) Analysis of alpha diversity (Shannon index) of gut microbiota OUT at various taxonomic ranks. (b) PCoA of beta diversity of gut microbiota based on JSD distance. (c) LDA effect size at the genus and (d) species level between HFD-RH and HFD-PBS group by LEfSe. Taxa with LDA > 2 and adjusted p < 0.05 were shown. (e) Correlation between basic characteristics and differential species in mice between HFD-PBS and HFD-RH groups.

R.Hominis prevented pa-induced lipid accumulation in L-02 cells by metabolizing NAD+ precursors

We next examined by which mechanism R. hominis contributed to obesity prevention in a human normal liver cell-line L-02 treated with PA. We found that RHCM, but not heat-killed R. hominis, could significantly prevent lipid accumulation induced by PA (Figure 5(a,b), Supplementary Figure S3A-B). RHCM also significantly suppressed the level of intercellular TG level (Figure 5c). Proteinase K did not abolish the preventive effect of RHCM on lipid accumulation (Supplementary Figure S3C-D), indicating that the functional metabolites in RHCM were non-protein molecules.

Figure 5.

Figure 5.

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The conditional medium of Roseburia hominis (RHCM) prevented pa-induced lipid accumulation in L-02 cells by the secretion of nicotinamide riboside. (a-b) Oil red O-stained pictures and relative oil red O area of pa-induced cells with intervening with RHCM. (c) Intercellular TG level after intervention of PA with vehicle CM or RHCM. (d)Relative oil red O area of pa-induced cells intervening with five different fractions of RHCM. (e) The relative abundance of nicotinamide riboside in the different fractions of RHCM and (f) mice serum. (g)The absolute level of nicotinamide riboside in RHCM. (h-i) Oil red O-stained pictures and relative oil red O area of pa-induced cells with intervening with nicotinamide riboside. Data are presented as the mean ± SEM. * 0.01 < p < 0.05, ** 0.001 < p < 0.01, *** p < 0.001 for PA group versus Blank control comparisons and # 0.01 < p < 0.05, ## 0.001 < p < 0.01, ### p < 0.001 for RHCM group versus PA group comparisons. “ns” indicates not significant (p > 0.05).

To further determine the molecular weight range of target metabolites involved in preventing lipid accumulation in cells, we separated RHCM into different molecular weight fractions using ultrafiltration tubes with 100, 50, 30, 10, and 3 KD molecular weight cutoff membranes. RHCM with all molecular weight cutoffs could prevent lipid accumulation in L-02 cells, with the fraction less than 3KD showing the strongest effect (Figure 5d). Metabolomics profiling showed that nicotinamide riboside was the only metabolite enriched in all fractions of RHCM (Supplementary Figure S3E-J). Moreover, the abundance of nicotinamide riboside was highest in the fraction less than 3KD and was almost undetectable in the vehicle medium (Figure 5e). As shown in Figure 5f, the relative concentration of nicotinamide riboside in the mice serum of the HFD-RH group was higher than that in the mice of the HFD-PBS group, although there was no significant difference. Targeted metabolomics confirmed that RHCM contained a higher nicotinamide riboside content (Figure 5g). The treatment of nicotinamide riboside (7.5ug/ml) prevented lipid accumulation induced by PA (Figure 5h,i).

R. hominis and nicotinamide riboside prevented lipid accumulation through NAD+ and upregulation of SIRT1/mTOR signaling pathway

RNA-seq was performed on cell models treated with PA and RHCM or YCFA to assess the impact on the host cell transcriptome. We identified 1981 differential genes between the vehicle and RHCM groups (Figure 6(a,b)). KEGG enrichment analysis indicated that the intervention of RHCM significantly upregulated several pathways that associated with energy metabolism and oxidative stress, such as mTOR signaling pathway, Thermogenesis, Oxidative phosphorylation, Insulin signaling pathway, FoxO signaling pathway and Fatty acid metabolism (Figure 6c).

Figure 6.

Figure 6.

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The preventive effect of R. hominis and nicotinamide riboside are dependent on NAD+ and upregulation of the SIRT1/mTOR signaling pathway. (a-c) RNA-Seq analysis of cells treated with PA plus vehicle medium or RHCM. (d-e) the NAD+ level of cells treated with PA and RHCM or nicotinamide riboside. (f-g) the mRNA level of SIRT1 in cells treated with RHCM or nicotinamide riboside. (h-i) the mRNA level of mTOR in cells treated with RHCM or nicotinamide riboside. (j-l) the expression of NAD+/SIRT1/mTOR in the liver of mice in ND-PBS, HFD-PBS, and HFD-RH group. (m-p) Oil red O-stained pictures and relative oil red O area of pa-induced cells intervening with RHCM or nicotinamide riboside plus EX527. Data are presented as the mean ± SEM. * 0.01 < p < 0.05, ** 0.001 < p < 0.01, *** p < 0.001 for model group versus normal control group comparisons and # 0.01 < p < 0.05, ## 0.001 < p < 0.01, ### p < 0.001 for intervention group versus model group comparisons.

As nicotinamide riboside is a precursor of NAD+, we assessed whether RHCM could promote the production of NAD+. As expected, both treatment with RHCM, and nicotinamide riboside, restored the level of NAD+, which was inhibited by PA (Figure 6(d,e)). Next, we checked the expression of SIRT1, the NAD+ dependent deacetylase, and a known regulator of mTOR, in cells treated with RHCM. We found that treatment of both RHCM and nicotinamide riboside could restore the expression of SIRT1, which was suppressed by PA (Figure 6(f,g)).

Moreover, the treatment of both RHCM and nicotinamide riboside could also upregulate the mTOR pathway that was suppressed by PA (Figure 6(h,i)), which was consistent with RNA-seq results. We further confirmed the regulation of this pathway by R. hominis in the mice fed with HFD. We found that the liver of mice fed with HFD showed a significant reduction in NAD+ level and suppression of SIRT1 and mTOR pathways, compared with mice fed with ND (Figure 6(j–l)). The supplementation of R. hominis significantly restored the reduction of NAD + level and SIRT1 and mTOR expression in mice liver (Figure 6(j–l)).

Additionally, the inhibition of SIRT1 by E×527 partially abolished the protective effect of RHCM and nicotinamide riboside on lipid accumulation in L-02 cells (Figure 6(m–p)). All together, these results suggested that R. hominis and nicotinamide riboside could contribute to anti-lipid accumulation by activating NAD+/SIRT1 pathway.R

Discussion

In this study, we report that R. hominis was inversely associated with BMI and TG in obese subjects with type 2 diabetes. We demonstrated that the administration of live R. hominis was associated with a reduction in body weight gain and improvements in glucose and lipid metabolism, as well as a reduction in hepatic steatosis and inflammation in mice fed a HFD. These effects may be partially attributed to the production of nicotinamide riboside and the regulation of gut microbiota. This study highlights the potential role R. hominis as live biotherapeutics for obesity and its related metabolic disorders.

We observed a significant reduction in the abundance of R. hominis in individuals with obesity. In addition, the relative abundance of R. hominis was inversely correlated with BMI and triglyceride levels. Depletion of R. hominis was repeatedly reported in Asian populations.19,20 In addition to cross-sectional studies, we also found that R. hominis was significantly increased in patients receiving FMT and lifestyle intervention and was associated with decrease in serum low-density lipoprotein following FMT.12 Previous studies have revealed that R. hominis could improve and regulate innate immunity via its immunomodulatory properties effect,29 and alleviate neuroinflammation by producing butyrate.30 Butyrate, a member of short-chain fatty acids, has been proven to exert health-promoting effects in metabolic diseases, such as obesity, type 2 diabetes, atherosclerosis, and nonalcoholic fatty liver disease.31–34 Study also reported R. hominis alleviated alcoholic fatty liver disease by improving the gut ecosystem and preventing leaky gut.35

We showed that long-term administration of live R. hominis was associated with a significant reduction in body weight gain, serum TG and TC levels, as well as hepatic steatosis and inflammation in mice fed a HFD. This protective effect was further confirmed by a reduction in serum AST and ALT levels. The decrease in serum lipid levels primarily occurs due to two main factors: the reduction of lipid absorption and the increase of lipid metabolism.36 The reduction of body weight, serum TG, and TC levels can be partially explained by R. hominis inhibited caloric absorption from food. The evaluation of histological scores according to the Grading system by Liang et al.37 discovered that R. hominis supplementation significantly inhibited hepatic steatosis and inflammation. The liver plays a central role in fatty acid metabolism, with approximately 20% of dietary fat being transported to the liver through the bloodstream.38 Fat overload and insulin resistance are indeed two significant factors that can contribute to the development of fatty liver.39,40 R. hominis contributed to the prevention effect in the fatty liver by inhibiting caloric absorption from food. In addition, R. hominis ameliorated insulin resistance in mice through upregulation of insulin receptor substrate (IRS)1 and IRS2, which are generated in the liver and serve as key mediators of insulin signaling by binding to the insulin receptor and transmitting signals downstream.41 Upon activation by insulin, IRS1 and IRS2 activate various signaling pathways that regulate glucose and lipid metabolism in the liver.42

In addition to the liver, we also observed that supplementation with live R. hominis inhibited adipocyte hypertrophy in white adipose tissue and the whitening of brown adipose tissue caused by HFD. Adipose tissue in mammals is primarily categorized into two types: white adipose tissue, responsible for lipid storage and utilization,43 and brown adipose tissue, primarily involved in thermoregulation.44 Under normal conditions, white adipose tissue undergoes healthy expansion in response to energy excess, characterized by adipocyte hyperplasia without an increase in adipocyte size.43 However, prolonged caloric overload can lead to unhealthy white adipose tissue expansion, characterized by hypertrophic adipocytes and ectopic fat accumulation. In this study, the intervention of RH may inhibit the expansion of adipocyte size by inhibiting lipid absorption and accumulation. Brown adipose tissue whitening, induced by HFD feeding, involves the conversion of brown adipocytes into white-like unilocular cells.45 It is associated with mitochondrial dysfunction and impaired thermogenesis in the brown adipose tissue. Consistently, we found that R. hominis supplementation led to upregulation of thermogenesis associated genes, such as UCP1, PGC1α, Dio2, and Cidea. UCP1, known as the uncoupling protein 1, is a thermogenic protein predominantly found in brown adipose tissue. It plays a critical role in facilitating adaptive thermogenesis, a process that generates heat without shivering.46 PGC1α is a key marker involved in mitochondrial biogenesis and plays a crucial role in regulating the activity of brown adipose tissue in response to environmental stimuli, including dietary factor.47 Dio2 is a specific brown adipose tissue marker and is essential for optimal thermogenesis in brown adipocytes.48 Cidea is not expressed in white adipose tissue but is highly expressed in brown and Brite adipocytes in mice and improves the metabolic profile through the expansion of adipose tissue.49 These findings suggest that R. hominis enhanced the thermogenic activity of brown adipose tissue and counteracted the negative effects of HFD on brown and white adipose tissue function. These findings reinforce the potential of R. hominis as a therapeutic strategy for ameliorating liver dysfunction associated with high-fat diet-induced obesity.

Additionally, we also showed that long-term supplementation of R. hominis did not negatively affect metabolic health and survival rate of mice fed with a normal chow diet, thus highlighting its potential as a safe intervention for metabolic health in a clinical setting.

We found that R. hominis could prevent lipid accumulation via metabolism of NAD+ precursors. Nicotinamide riboside is a derivative of vitamin B, and a precursor of NAD+, a critical coenzyme that involved in energy generation and DNA repair.50 Supplementation of nicotinamide riboside rapidly boosts the NAD+ level in human blood through direct or indirect pathways.51 Previous studies showed that the supplementation of nicotinamide riboside could attenuate age-associated metabolic and functional changes in hematopoietic stem cells.52 Nicotinamide riboside could ameliorate hepatic metaflammation by modulating NOD-like receptor thermal protein domain associated protein 3 inflammasome in a rodent model of type 2 diabetes53 and promote the regeneration of liver function.54 In humans, nicotinamide riboside recipients showed increased brain NAD levels and decreased levels of inflammatory cytokines in serum in patients with Parkinson’s disease.55

We showed that the expression of SIRT1 was suppressed by long-term HFD in mice as well as liver cells treated with PA. Supplementation of live R. hominis led to upregulation of SIRT1 in mice liver. Similarly, treatment with RHCM activated of SIRT1/mTOR signaling pathway. Inhibition of SIRT1 with E×527 suppressed the protective effect of RHCM and nicotinamide riboside on lipid accumulation. The mTOR signaling pathway is essential in multiple diseases, such as bone diseases,56 liver diseases,57 and tumor.58 In metabolic diseases, mTOR contributes to the regulation of adipogenesis, lipid metabolism, thermogenesis, and adipokine synthesis and/or secretion.59 Nicotinamide riboside/NAD+ is the activator of SIRT1, a positive regulator of liver X receptor proteins involved in cholesterol metabolism, lipid metabolism, glucose homeostasis, and immune response.60–62 The increase of NAD+ could activate SIRT1 to improve metabolic disease.63 Our data suggested that R. hominis protects against diet-induced metabolic disorders by upregulation of SIRT1/mTOR signaling pathway. However, it is worth noting that mice receiving live R. hominis had lower food consumption as well as more remaining calories in stool, compared with mice in the HFD-PBS group. This indicated that R. hominis led to lower energy absorption from food and thereby contributed to the prevention of diet-induced obesity.

R. hominis affected gut microbiota composition and boosted the abundance of species associated with human metabolic health. R. hominis resulted in the accumulation of beneficial bacteria, including P. goldsteinii, L. johnsonii, F. prausnitzii, and D. welbionis, meanwhile depleting pathogenic bacteria Olsenella genus. P. goldsteinii was depleted in subjects with obesity and the intervention of P. goldsteinii reduced obesity and metabolic disorder in mice.64 L. johnsonii was a probiotic candidate that with the ability to alleviate gut inflammation, improve gut environment in obese mice.25 F. prausnitzii was frequently reported to be depleted in the gut of subjects with obesity in previous studies, and its supplementation reduced blood glucose and improved glucose tolerance.26,27 D. welbionis was a novel next-generation probiotic candidate that has a positive effect on obesity.24 Olsenella genus was a well-characterized pathogen that was involved in endodontic infections in humans.28 This modulatory effect may be due to the production of butyrate. When butyrate is transported into colonocytes, oxygen consumption increases dramatically, providing an anaerobic microenvironment for anaerobic microbiomes and boosting their growth.65 This microenvironment also inhibits the proliferation of facultative anaerobic bacteria associated with colonic dysbiosis.65,66 Therefore, the regulation of the gut microbiota by R. hominis could partly explain its beneficial effect in obesity prevention.

There are several limitations for the current study. Firstly, the majority of human subjects with obesity in this study had type 2 diabetes and were on diabetic medication. This could potentially contribute to the differences between microbiota from lean and obese subjects. Secondly, the animal experiment was conducted solely under specific-pathogen-free conditions. Mono-association of R. hominis in germ-free mice is needed to gain a deeper understanding of the impact of R. hominis on host health. Thirdly, the effect of nicotinamide ribose was examined in an in vitro system only. Therefore, while R. hominis shows potential as a live biotherapeutic for obesity and related metabolic disorders, further investigation is warranted to clarify the mechanisms involved.

Despite these limitations, our study provides compelling evidence supporting the association of R. hominis as a biomarker for a lean state and its potential contribution to the improvement of obesity. The utilization of R. hominis and related products in human obesity bears promising prospects for future research and applications.

Together, our findings suggested that R. hominis protects against diet-induced metabolic disorders partially by metabolizing NAD+ precursors and upregulation of SIRT1/mTOR signaling pathway. R. hominis is a promising candidate for the development of next-generation live biotherapeutics for the treatment of obesity and metabolic diseases.

Supplementary Material

Supplemental Material
KGMI_A_2467193_SM3448.docx (6.5MB, docx)

Funding Statement

This work was supported by InnoHK, The Government of Hong Kong, Special Administrative Region of the People’s Republic of China, Centre for Gut Microbiota Research, Faculty of Medicine, The Chinese University of Hong Kong, and National Natural Science Foundation (NSFC) of China (82400998).

Disclosure statement

SCN has received research grants through her affiliated institutions from Olympus, Ferring, and Abbvie. SCN is a scientific co-founder and shareholder of GenieBiome Ltd. SCN receives patent royalties through her affiliated institutions. FKLC is a Board Member of CUHK Medical Centre. He is a co-founder, non-executive Board Chairman and shareholder of GenieBiome Ltd. He receives patent royalties through his affiliated institutions. He has received fees as an advisor and honoraria as a speaker for Eisai Co. Ltd., AstraZeneca, Pfizer Inc., Takeda Pharmaceutical Co., and Takeda (China) Holdings Co. Ltd. SCN has served as an advisory board member for Pfizer, Ferring, Janssen, and Abbvie and received honoraria as a speaker for Ferring, Tillotts, Menarini, Janssen, Abbvie, and Takeda. XZ, FKLC, SCN are named inventors of patent applications held by the CUHK and MagIC that cover the therapeutic and diagnostic use of microbiome.

Abbreviations

FMT

fecal microbiota transplantation

BMI

body mass index

ND

normal chow diet

HFD

high-fat diet

PBS

phosphate-buffered saline

TG

triglycerides

TC

total cholesterol

AST

aspartate aminotransferase

ALT

alanine transaminase

NAD+

nicotinamide adenine dinucleotide

H&E

hematoxylin-eosin

PCoA

principal coordinate analysis

LDA

linear discriminant analysis

LEFSe

LDA effect size

PA

palmitic acid

RHCM

R. hominis conditioned medium

KEGG

kyoto encyclopedia of genes and genomes

ANOVA

one-way analysis of variance

IRS1/2

insulin receptor substrate 1/2.

Data availability statement

The data underlying this article will be shared on reasonable request to the corresponding author.

Author contributions

Conceptualization: SCN, ZLX, KLC; Methodology: WLH, WYZ, YL; Investigation: WLH, ZLX; Visualization: WLH, YL; Supervision: SCN, ZLX; Writing – original draft: WLH; Writing – review & editing: SCN, ZLX

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2025.2467193

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