Abstract
Tobacco smoking is positively correlated with non-alcoholic fatty liver disease (NAFLD)1,2,3,4,5, but the underlying mechanism for this association is unclear. Here we report that nicotine accumulates in the intestine during tobacco smoking and activates intestinal AMPKα. We identify the gut bacterium Bacteroides xylanisolvens as an effective nicotine degrader. Colonization of B. xylanisolvens reduces intestinal nicotine concentrations in nicotine-exposed mice, and it improves nicotine-exacerbated NAFLD progression. Mechanistically, AMPKα promotes the phosphorylation of sphingomyelin phosphodiesterase 3 (SMPD3), stabilizing the latter and therefore increasing intestinal ceramide formation, which contributes to NAFLD progression to non-alcoholic steatohepatitis (NASH). Our results establish a role for intestinal nicotine accumulation in NAFLD progression and reveal an endogenous bacterium in the human intestine with the ability to metabolize nicotine. These findings suggest a possible route to reduce tobacco smoking-exacerbated NAFLD progression.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
$199.00 per year
only $3.90 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
All of the data supporting the findings of this study are included in the Article and Supplementary Tables 1–7. The metagenomic and phosphoproteomic data were uploaded to a public database (China National Microbiology Data Center (NMDC), under accession numbers NMDC10018157 and NMDC10018158, respectively). The following public databases were used in this study: NCBI reference database and Metaquery database. Source data are provided with this paper.
References
Okamoto, M. et al. Cigarette smoking is a risk factor for the onset of fatty liver disease in nondrinkers: a longitudinal cohort study. PLoS ONE 13, e0195147 (2018).
Ou, H., Fu, Y., Liao, W., Zheng, C. & Wu, X. Association between smoking and liver fibrosis among patients with nonalcoholic fatty liver disease. Can. J. Gastroenterol. Hepatol. 2019, 6028952 (2019).
Jung, H. S. et al. Smoking and the risk of non-alcoholic fatty liver disease: a cohort study. Am. J. Gastroenterol. 114, 453–463 (2019).
Takenaka, H. et al. Non-alcoholic fatty liver disease is strongly associated with smoking status and is improved by smoking cessation in Japanese males: a retrospective study. Kobe J. Med. Sci. 66, E102–E112 (2020).
Yuan, S. et al. Lifestyle and metabolic factors for nonalcoholic fatty liver disease: Mendelian randomization study. Eur. J. Epidemiol. 37, 723–733 (2022).
WHO Report on the Global Tobacco Epidemic 2008: The MPOWER Package 14 (WHO, 2008).
WHO Global Report on Trends in Prevalence of Tobacco Smoking 2000–2025, Second Edition 21 (WHO, 2018).
Holford, T. R. et al. Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964-2012. JAMA 311, 164–171 (2014).
Xue, S., Schlosburg, J. E. & Janda, K. D. A new strategy for smoking cessation: characterization of a bacterial enzyme for the degradation of nicotine. JACS 137, 10136–10139 (2015).
Dulchavsky, M., Clark, C. T., Bardwell, J. C. A. & Stull, F. A cytochrome c is the natural electron acceptor for nicotine oxidoreductase. Nat. Chem. Biol. 17, 344–350 (2021).
Tripathi, A. et al. The gut-liver axis and the intersection with the microbiome. Nat. Rev. Gastroenterol. Hepatol. 15, 397–411 (2018).
Lindell, G. et al. Acute effects of smoking during modified sham feeding in duodenal ulcer patients. An analysis of nicotine, acid secretion, gastrin, catecholamines, epidermal growth factor, prostaglandin E2, and bile acids. Scand. J. Gastroenterol. 28, 487–494 (1993).
Han, X. J. et al. Stimulation of α7 nicotinic acetylcholine receptor by nicotine suppresses decidual M1 macrophage polarization against inflammation in lipopolysaccharide-induced preeclampsia-like mouse model. Front. Immunol. 12, 642071 (2021).
Sousa, M. V. et al. Smoking accelerates renal cystic disease and worsens cardiac phenotype in Pkd1-deficient mice. Sci. Rep. 11, 14443 (2021).
Wu, X. X. et al. Nicotine promotes atherosclerosis via ROS-NLRP3-mediated endothelial cell pyroptosis. Cell Death Dis. 9, 171 (2018).
Fluhr, L. et al. Gut microbiota modulates weight gain in mice after discontinued smoke exposure. Nature 600, 713–719 (2021).
Wang, S. N., Liu, Z., Tang, H. Z., Meng, J. & Xu, P. Characterization of environmentally friendly nicotine degradation by Pseudomonas putida biotype A strain S16. Microbiology 153, 1556–1565 (2007).
Tang, H. Z. et al. A novel gene, encoding 6-hydroxy-3-suceinoylpyridine hydroxylase, involved in nicotine degradation by Pseudomonas putida strain S16. Appl. Environ. Microbiol. 74, 1567–1574 (2008).
Wang, C. et al. Nicotine accelerates atherosclerosis in apolipoprotein E-deficient mice by activating α7 nicotinic acetylcholine receptor on mast cells. Arterioscler. Thromb. Vasc. Biol. 37, 53–65 (2017).
Liu, R., Kurose, T. & Matsukura, S. Oral nicotine administration decreases tumor necrosis factor-alpha expression in fat tissues in obese rats. Metabolism 50, 79–85 (2001).
Wu, Y. et al. Activation of AMPKα2 in adipocytes is essential for nicotine-induced insulin resistance in vivo. Nat. Med. 21, 373–382 (2015).
Garcia, D. & Shaw, R. J. AMPK: mechanisms of cellular energy sensing and restoration of metabolic balance. Mol. Cell 66, 789–800 (2017).
Marra, F. Lipotoxicity and the gut-liver axis in NASH pathogenesis. J. Hepatol. 68, 280–295 (2018).
Xue, Y. et al. GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy. Mol. Cell. Proteomics 7, 1598–1608 (2008).
Filosto, S., Ashfaq, M., Chung, S., Fry, W. & Goldkorn, T. Neutral sphingomyelinase 2 activity and protein stability are modulated by phosphorylation of five conserved serines. J. Biol. Chem. 287, 514–522 (2012).
Wu, Q. et al. Suppressing the intestinal farnesoid X receptor/sphingomyelin phosphodiesterase 3 axis decreases atherosclerosis. J. Clin. Invest. 131, e142865 (2021).
Lindell, G., Lunell, E. & Graffner, H. Transdermally administered nicotine accumulates in gastric juice. Eur. J. Clin. Pharmacol. 51, 315–318 (1996).
Mu, Y. et al. Bacterial catabolism of nicotine: catabolic strains, pathways and modules. Environ. Res. 183, 109258 (2020).
Gunasekaran, M. Direct evidence that sunbirds’ gut microbiota degrades floral nectar’s toxic alkaloids. Front. Microbiol. 12, 639808 (2021).
Agostoni, C. et al. Scientific opinion on the safety of ‘heat-treated milk products fermented with Bacteroides xylanisolvens DSM 23964’ as a novel food EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA). EFSA J. 13, 3956 (2015).
Lavrynenko, O. et al. Ceramide ratios are affected by cigarette smoke but not heat-not-burn or e-vapor aerosols across four independent mouse studies. Life Sci. 263, 118753 (2020).
Tippetts, T. S. et al. Cigarette smoke increases cardiomyocyte ceramide accumulation and inhibits mitochondrial respiration. BMC Cardiovasc. Disord. 14, 165 (2014).
Zhou, Y. J. et al. Screening for compensated advanced chronic liver disease using refined Baveno VI elastography cutoffs in Asian patients with nonalcoholic fatty liver disease. Aliment. Pharmacol. Ther. 54, 470–480 (2021).
Kleiner, D. E. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41, 1313–1321 (2005).
Lloyd-Jones, D. M. et al. Framingham risk score and prediction of lifetime risk for coronary heart disease. Am. J. Cardiol. 94, 20–24 (2004).
Hippisley-Cox, J., Coupland, C. & Brindle, P. Development and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort study. BMJ 357, j2099 (2017).
Everard, A. et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl Acad. Sci. USA 110, 9066–9071 (2013).
Wu, Q. et al. Intestinal hypoxia-inducible factor 2α regulates lactate levels to shape the gut microbiome and alter thermogenesis. Cell Metab. 33, 1988–2003 (2021).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Truong, D. T. et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902–903 (2015).
Dhariwal, A. et al. MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 45, W180–W188 (2017).
Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011).
Liu, C. et al. Enlightening the taxonomy darkness of human gut microbiomes with a cultured biobank. Microbiome 9, 119 (2021).
Despres, J. et al. Unraveling the pectinolytic function of Bacteroides xylanisolvens using a RNA-seq approach and mutagenesis. BMC Genom. 17, 147 (2016).
Apsunde, T. D. & Trudell, M. L. Microwave-assisted iridium-catalyzed synthesis of nicotine and anabasine derivatives. Synthesis 45, 2120–2124 (2013).
Dye, F. S. et al. Characterisation of proguanylin expressing cells in the intestine evidence for constitutive luminal secretion. Sci. Rep. 9, 15574 (2019).
Xuan, Q. H. et al. Development of a high coverage pseudotargeted lipidomics method based on ultra-high performance liquid chromatography-mass spectrometry. Anal. Chem. 90, 7608–7616 (2018).
Ren, L. L. et al. TiO2 with tandem fractionation (TAFT): an approach for rapid, deep, reproducible, and high-throughput phosphoproteome analysis. J. Proteome Res. 17, 710–721 (2018).
Liu, P. et al. Cell-cycle-regulated activation of Akt kinase by phosphorylation at its carboxyl terminus. Nature 508, 541–545 (2014).
Waterhouse, A. et al. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 46, W296–W303 (2018).
Acknowledgements
This work was supported by the National Natural Science Foundation of the People’s Republic of China (nos 91857115 and 31925021), the National Key Research and Development Program of China (no. 2018YFA0800700), the National Natural Science Foundation of the People’s Republic of China (nos 82130022, 81921001, 92057103, 31872820 and 82070588), the National Cancer Institute Intramural Research Program, the National Key Research and Development Program of China (no. 2022ZD0213000) and the Innovative Research Team of High-Level Local Universities in Shanghai and a Key Laboratory Program of the Education Commission of Shanghai Municipality (ZDSYS14005). We thank the members of the CHESS-MAFLD consortium for their coordination and platform support for this study.
Author information
Authors and Affiliations
Contributions
C.J. conceptualized and designed the study. B.C., L.S., G.Z., Z.S., K.W., L.Y., F.X., P.W., Y.D., Q.N., Q.W., Z.Z., J.X., J.L., Y. Luo., J.C., K.W.K., R.Z., Y.X. and M.-H.Z. performed the experiments and analysed the data. C.J., F.J.G., C.Y., Y. Li and M.-H.Z. supervised the study. B.C., L.S., G.Z. and C.J. wrote the manuscript with input from all of the authors. All of the authors edited the manuscript and approved the final manuscript.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature thanks William Holland, Paul Kenny, Herbert Tilg and Peter Turnbaugh for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Gut microbiota composition differences between smokers with high nicotine and low nicotine levels.
a, Quantification of the nicotine concentrations in lung, ileum content, ileum tissue, brain, liver, eWAT and serum samples obtained from s.c. injection mouse model for two weeks (SPF, n = 8 mice/group). b, Top 10 species of gut bacteria in humans that show high correlation with the known nicotine-degrading enzyme, nicA. These species were identified by MetaQuery. c–i, 30 smokers who were further divided into the HN (high nicotine, n = 16) and LN (low nicotine, n = 14) groups according to their ileal nicotine levels. Ileal nicotine concentrations in HN and LN groups. The data did not obey the normal distribution determined by the Shapiro normality test; thus, the median was used as a break point, and divided into two groups (c). α-diversity of the gut microbiota between the LN and HN individuals, as indicated by the ACE (d), Chao1 (e) and Shannon indices (f). Partial least squares discriminant analysis (PLS-DA) using the Bray-Curtis distance (g). Taxonomic cladograms were generated by LefSe of metagenomic analysis data. The blue colour indicates enriched taxa in the LN group, and the red colour indicates enriched taxa in the HN group. The size of each circle is proportional to the taxon’s abundance (h, i). Data are the means ± s.e.m. b, Correlations were assessed by nonparametric Spearman’s test. c–f, Two-tailed Student’s t-test.
Extended Data Fig. 2 Identification of B. xylanisolvens as a nicotine degrader.
a, Growth curves of B. xylanisolvens with or without nicotine in culture medium (n = 3/group). b, Nicotine concentration in B. xylanisolvens in vitro cultivation compared with control (BHI medium with nicotine supplementation, n = 5/group). c, 1H NMR spectrum (top) and 13C NMR spectrum (bottom) of HPB. d, Production of HPB in B. xylanisolvens in vitro supplementation compared with control (BHI medium with nicotine supplementation, n = 5/group). e, Nicotine and HPB concentrations in ileal tissues of the smoking exposure mouse model for two weeks (SPF, n = 6 mice/group). f, Nicotine and HPB concentration in ileal tissues of the subcutaneous injection mouse model for two weeks (SPF, n = 6 mice/group). g, Structural comparison of the SWISS-MODEL50-predicted B. xylanisolvens NicX and predicted Pseudomonas putida NicA. The Root-Mean-Square-Deviation (RMSD) of 242 aligned residues is 1.323 Å. h, Nonlinear regression for nicotine degradation catalysed by purified NicX. The reaction mixture contained 1 mM FMN, 25 mM Tris-HCl (pH 7.6), 20 ng NicX, and nicotine at different concentrations at 37 °C, n = 3/group. i, Schematic diagram illustrating the workflow for nicX gene deletion in B. xylanisolvens. The diagram was created using BioRender. j, Production of HPB in E. coli and E. coli + nicX in vitro cultivation (LB medium with nicotine supplementation, n = 5/group). k, Production of HPB in B. xylanisolvens and B. xylanisolvens-ΔnicX in vitro cultivation in culture medium (BHI medium with nicotine supplementation, n = 5/group). l, Growth curves of WT and nicX-KO B. xylanisolvens. (n = 3/group). Data are the means ± s.e.m. a, b, l, Two-tailed Student’s t-test. d, j, k, Two-tailed Mann-Whitney U-test. e, f, for Nicotine, one-way ANOVA with Dunnett’s T3 post hoc test; for HPB, Kruskal-Wallis test with Dunn’s test. Experiments in a, b, d, h, j, k, l were performed three times independently.
Extended Data Fig. 3 B. xylanisolvens transplantation alleviates nicotine-accelerated NASH.
HFHCD-fed SPF mice were treated with PBS, B. xylanisolvens colonization, nicotine water, nicotine water plus B. xylanisolvens colonization, and nicotine water plus nicX knock-out B. xylanisolvens colonization for 20 weeks (n = 6 mice/group). a, Faecal B. xylanisolvens abundance analyses of mice by qPCR. b, Ileal nicotine concentrations. c, Body weight gain. d, Body mass composition. e, Liver weights. f, Liver weight–to–body weight ratios. g, h, Serum ALT (g) and AST (h) levels. i, Hepatic TG content. j, Serum TG content. k, Hepatic CE content. l, Serum CE content. m, Serum NEFA content. n–r, Histology scores of hepatic steatosis (n), lobular inflammation (o), ballooning (p), NAFLD activity (q), and fibrosis stage (r). s–u, Relative mRNA levels of genes related to hepatic lipid metabolism (s), inflammation (t) and fibrosis (u). Data are the means ± s.e.m. c, e–i, k–m, One-way ANOVA with Tukey’s post hoc test. a, b, j, One-way ANOVA with Dunnett’s T3 post hoc test. d, n–u, Kruskal-Wallis test with Dunn’s test.
Extended Data Fig. 4 Nicotine-induced activation of intestinal AMPKα.
a, b, Activation of the AMPKα in ileal organoids after treatment with nicotine at different concentrations for 4 h (n = 3 independent experiments). c, Western blot analysis indicated that ileal AMPKα was activated in the nicotine drinking mouse model (SPF, n = 6 mice/group). d, e, Western blot analysis indicated that ileal AMPKα was activated in the smoking mouse model (d) and the subcutaneous injection mouse model (e) (SPF, n = 3 mice/group). f, Western blot analysis of ileal primary enterocytes isolated from WT, Prkaa1ΔIE and Prkaa2ΔIE mice (SPF) and then cultured with or without nicotine (1 μg ml−1) treatment for 4 h. Experiments were performed with n = 4 mice/group. g, Western blot analysis showing ileal AMPK signalling in the nicotine drinking mouse model transplanted with Control or B. xylanisolvens (SPF, n = 6 mice/group). h, i, Western blot analysis showing ileal AMPK signalling in the nicotine drinking mouse model transplanted with E. coli or nicX knock-in E. coli (h); and WT or nicX knock-out B. xylanisolvens (i) (SPF, n = 6 mice/group). j, Western blot analysis showing AMPK signalling in SW480 cells incubated with nicotine (1 μg ml−1) or HPB (1 μg ml−1) for 4 h. This result is representative of 3 independent experiments. In c–e, g–i, mice were supplied nicotine plus HFHCD for two weeks. Data are the means ± s.e.m. (b).
Extended Data Fig. 5 Intestinal AMPKα1 deficiency improves NASH via decreasing ceramide generation.
Eight-week-old male Prkaa1fl/fl and Prkaa1ΔIE mice were administered a HFHCD plus nicotine water for 20 weeks (SPF, n = 8 mice/group). a, Liver weight. b–e, Serum TG (b), hepatic CE (c), serum CE (d) and serum NEFA (e) contents. f–j, Histology scores of hepatic steatosis (f), lobular inflammation (g), ballooning (h), NAFLD activity (i), and fibrosis stage (j). k-m, Relative mRNA levels of genes related to hepatic lipid metabolism (k), inflammation (l) and fibrosis (m). n, o, Eight-week-old male Prkaa1fl/fl (WT) and Prkaa1ΔIE (KO) mice were administered a HFHCD plus nicotine water for 20 weeks (SPF, Prkaa1fl/fl, n = 12 mice; Prkaa1ΔIE, n = 11 mice). PLS-DA analysis of lipid metabolites in the ileum (n). Random forest analysis showing the top 10 lipid metabolites that lead to differences in the ileal lipid profiles (o). p, A schematic diagram illustrating the workflow of phosphorylated proteomics. Created with BioRender. q, Volcano map of phosphorylated proteomics analysis from ileal epithelia of Prkaa1fl/fl (WT) and Prkaa1ΔIE (KO) mice (n = 5 mice/group) administered a HFHCD plus nicotine water for 20 weeks. Relative fold change (log2) of phosphorylated sites abundance was determined by comparing KO versus WT, and P values (–log10) were calculated by two-tailed t-test. Data are the means ± s.e.m. a–e, Two-tailed Student’s t-test. f–m, Two-tailed Mann- Whitney U-test.
Extended Data Fig. 6 AMPKα phosphorylates SMPD3 protein which became more stable by escaping from ubiquitination degradation.
a, Effect of nicotine (1 μg ml−1) treatment on Smpd3 mRNA levels in ileal organoids (n = 3/group). b, PRKAA1-WT or PRKAA1-KD (kinase domain mutant) was introduced into SW480 cells, and the cells were then treated with vehicle or nicotine (1 μg ml−1) for 12 h. c, GPS2.0 predicts potential kinases and phosphorylation sites for SMPD3. d, The S208/209 peptide of SMPD3 satisfied the AMPK substrate motif and was conserved in different species (data from NCBI database). e, Mass spectrometry analysis of the phosphorylation at Ser209 on SMPD3. f, HFHCD-fed Prkaa1fl/fl and Prkaa1ΔIE mice (SPF) were treated with nicotine water for 2 weeks, and organoids were then isolated and cultured for 7 days and treated with nicotine (1 μg ml−1) for the last 3 days. Western blot analysis showing the stability of SMPD3 after the administration of CHX. g, Mass spectrometry analysis of the ubiquitination at Lys103 on SMPD3. h, The Lys63 ubiquitination of SMPD3 in SW480 cells transfected with SMPD3-flag (WT and K103R) with or without nicotine treatment. i, The SMPD3 ubiquitination in SW480 cells transfected with SMPD3-flag (WT, S209A or S209A/K103R) and treated with or without nicotine. j, Phosphorylation level (S209) of SMPD3 was detected by anti-p-SPMD3 (S209) antibody in SW480 cells transfected with SMPD3-flag (WT or S209A) and treated with or without nicotine. k, Ubiquitination level (K103) of SMPD3 was detected by anti-ubi-SMPD3 (K103) antibody in SW480 cells transfected with SMPD3-flag (WT or K103R) and treated with or without nicotine. For e, g-k, nicotine (1 μg ml−1) treatment for 24 h. Data are the means ± s.e.m. Experiments in a, b, e–k were performed three times independently. a, One-way ANOVA with Tukey’s post hoc test.
Extended Data Fig. 7 Interaction between p-AMPKα and SMPD3 in intestinal ceramide production.
a-c, HFHCD-fed SPF mice were treated with nicotine water or nicotine water plus 10 mg/kg GW4869 (by daily gavage) for 2 weeks, and ileal organoids were then isolated and cultured for 7 days and treated with GW4869 (10 μM) and nicotine (1 μg ml−1) for the last 3 days before the detection of ceramide production and secretion (n = 5 mice/group). a, nSMase activity. b, Ceramide profiles in isolated organoids. c, Ceramide profiles in the supernatant of isolated organoids. d-f, HFHCD-fed Prkaa1fl/fl and Prkaa1ΔIE mice (SPF) were treated with nicotine water for 2 weeks, and organoids were then isolated and infected with LV (lentivirus)-Ctrl or LV-Smpd3, the infected organoids were plated and cultured for 7 days and treated with nicotine (1 μg ml−1) for the last 3 days before the detection of ceramide production and secretion. Western blot analysis for verifying SMPD3 overexpression. (n = 3 mice/group) (d). Ceramide profiles in isolated organoids. (n = 8 mice/group) (e). Ceramide profiles in the supernatant of isolated organoids. (n = 8 mice/group) (f). g, HFHCD-fed WT mice were transplanted with PBS, B. xylanisolvens colonization, nicotine water, nicotine water plus B. xylanisolvens colonization, and nicotine water plus nicX knock-out B. xylanisolvens colonization for 20 weeks (SPF, n = 6 mice/group), and ileal tissues were collected for ceramide profile analysis. Data are the means ± s.e.m. a, b, Two-tailed Student’s t-test. c, Two-tailed Mann-Whitney U-test. f, One-way ANOVA with Tukey’s post hoc test. e, g, Kruskal-Wallis test with Dunn’s test.
Extended Data Fig. 8 Ceramide supplementation eliminates the beneficial effects derived from intestinal AMPKα1 deficiency.
Eight-week-old male Prkaa1fl/fl and Prkaa1ΔIE mice were treated with or without 10 mg/kg ceramide (d18:1/16:0) by daily i.p. injection under HFHCD plus nicotine water treatment for 20 weeks (SPF, Prkaa1fl/fl, n = 8 mice; Prkaa1ΔIE, n = 7 mice; Prkaa1ΔIE + Ceramide, n = 8 mice). a, Ileal ceramide profiles. b, Liver weights. c, Liver weight–to–body weight ratios. d, e, Serum ALT (d) and AST (e) levels. f–j, Hepatic TG (f), serum TG (g), hepatic CE (h), serum CE (i) and serum NEFA (j) contents. k, Representative H&E staining (upper), Oil Red O staining (middle) and Sirius Red staining (lower) of liver sections (n = 4 mice/group, 3 images/mouse). Scale bar, 100 µm. l–p, Histology scores of steatosis (l), lobular inflammation (m), hepatocyte ballooning (n), NAFLD activity (o) and fibrosis stage (p). q–s, Relative mRNA levels of genes related to hepatic lipid metabolism (q), inflammation (r) and fibrosis (s). Data are the means ± s.e.m. d–g, i, One-way ANOVA with Tukey’s post hoc test. h, One-way ANOVA with Dunnett’s T3 post hoc test. a–c, j, l–s, Kruskal-Wallis test with Dunn’s test.
Extended Data Fig. 9 Inhibition of SMPD3 ameliorates nicotine-induced NASH.
Eight-week-old male SPF mice were randomly grouped and administered vehicle or 10 mg/kg GW4869 by daily gavage under HFHCD plus nicotine water treatment for 20 weeks (Nicotine, n = 5 mice; Nicotine + GW4869, n = 7 mice). a, Ileal ceramide profiles. b, Liver weights. c, Liver weight–to–body weight ratios. d, e, Serum ALT (d) and AST (e) levels. f-j, Hepatic TG (f), serum TG (g), hepatic CE (h), serum CE (i) and serum NEFA (j) contents. k, Representative H&E staining (left), Oil Red O staining (middle) and Sirius Red staining (right) of liver sections (n = 3 mice/group, 3 images/mouse). Scale bar, 100 µm. l–p, Histology scores of steatosis (l), lobular inflammation (m), hepatocyte ballooning (n), NAFLD activity (o) and fibrosis stage (p). q–s, Relative mRNA levels of genes related to hepatic lipid metabolism (q), inflammation (r) and fibrosis (s). Data are the means ± s.e.m. b, e, g–j, r, Two-tailed Student’s t-test. a, c, d, f, l-q, s, Two-tailed Mann-Whitney U-test.
Extended Data Fig. 10 B. xylanisolvens-mediated nicotine degradation negatively correlates with clinical NASH.
In 41 smokers with NAFLD, NAFL n = 11, borderline NASH n = 16, definite NASH n = 14. a–c, Relative abundances of B. xylanisolvens associated with steatosis score (a), ballooning score (b), and lobular inflammation (c) in smokers with NAFLD. In 42 non-smokers with NAFLD, including NAFL (n = 11), borderline NASH (n = 14), and definite NASH (n = 17). d, Bacterial taxonomic profiling of the gut microbiota from non-smokers with different NAFLD stages at the species level. e, Relative abundances of B. xylanisolvens associated with different NAFLD stages in non-smokers with NAFLD. f-h, Relative abundances of B. xylanisolvens associated with steatosis score (f), ballooning score (g), and lobular inflammation (h) in non-smokers with NAFLD. i, j, Correlative analysis of B. xylanisolvens with ALT (i) and AST (j). Correlations between variables were assessed by linear regression analysis. Linear correction index R square and P values were calculated. k, Summary diagram illustrating the role of microbial nicotine degradation in ceramide modulation and NAFL-NASH progression. Created with BioRender. Data are the means ± s.e.m. a–c, e–h, Kruskal-Wallis test with Dunn’s test.
Supplementary information
Supplementary Figure 1
Uncropped gels for Figs. 1–4 and Extended Data Figs.1–10.
Supplementary Tables 1–7
This file includes Supplementary Tables 1–7 and their accompanying legends
Source data
Rights and permissions
About this article
Cite this article
Chen, B., Sun, L., Zeng, G. et al. Gut bacteria alleviate smoking-related NASH by degrading gut nicotine. Nature 610, 562–568 (2022). https://doi.org/10.1038/s41586-022-05299-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-022-05299-4
This article is cited by
-
Longitudinal multi-omics analysis uncovers the altered landscape of gut microbiota and plasma metabolome in response to high altitude
Microbiome (2024)
-
Characteristics of gut microbiota in patients with asthenozoospermia: a Chinese pilot study
BMC Microbiology (2024)
-
Phosphorylation: new star of pathogenesis and treatment in steatotic liver disease
Lipids in Health and Disease (2024)
-
Gut microbial metabolites reveal diet-dependent metabolic changes induced by nicotine administration
Scientific Reports (2024)
-
Progress in gut microbiota-host interaction
Science China Life Sciences (2024)
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.