Molecular characterization of the fecal microbiota in patients with nonalcoholic steatohepatitis--a longitudinal study

Vincent Wai-Sun Wong, Chi-Hang Tse, Tommy Tsan-Yuk Lam, Grace Lai-Hung Wong, Angel Mei-Ling Chim, Winnie Chiu-Wing Chu, David Ka-Wai Yeung, Patrick Tik-Wan Law, Hoi-Shan Kwan, Jun Yu, Joseph Jao-Yiu Sung, Henry Lik-Yuen Chan, Vincent Wai-Sun Wong, Chi-Hang Tse, Tommy Tsan-Yuk Lam, Grace Lai-Hung Wong, Angel Mei-Ling Chim, Winnie Chiu-Wing Chu, David Ka-Wai Yeung, Patrick Tik-Wan Law, Hoi-Shan Kwan, Jun Yu, Joseph Jao-Yiu Sung, Henry Lik-Yuen Chan

Abstract

Background: The human gut microbiota has profound influence on host metabolism and immunity. This study characterized the fecal microbiota in patients with nonalcoholic steatohepatitis (NASH). The relationship between microbiota changes and changes in hepatic steatosis was also studied.

Methods: Fecal microbiota of histology-proven NASH patients and healthy controls was analyzed by 16S ribosomal RNA pyrosequencing. NASH patients were from a previously reported randomized trial on probiotic treatment. Proton-magnetic resonance spectroscopy was performed to monitor changes in intrahepatic triglyceride content (IHTG).

Results: A total of 420,344 16S sequences with acceptable quality were obtained from 16 NASH patients and 22 controls. NASH patients had lower fecal abundance of Faecalibacterium and Anaerosporobacter but higher abundance of Parabacteroides and Allisonella. Partial least-square discriminant analysis yielded a model of 10 genera that discriminated NASH patients from controls. At month 6, 6 of 7 patients in the probiotic group and 4 of 9 patients in the usual care group had improvement in IHTG (P=0.15). Improvement in IHTG was associated with a reduction in the abundance of Firmicutes (R(2)=0.4820, P=0.0028) and increase in Bacteroidetes (R(2)=0.4366, P=0.0053). This was accompanied by corresponding changes at the class, order and genus levels. In contrast, bacterial biodiversity did not differ between NASH patients and controls, and did not change with probiotic treatment.

Conclusions: NASH patients have fecal dysbiosis, and changes in microbiota correlate with improvement in hepatic steatosis. Further studies are required to investigate the mechanism underlying the interaction between gut microbes and the liver.

Conflict of interest statement

Competing Interests: Vincent Wai-Sun Wong has been an advisory board member of Roche, Novartis, Gilead and Otsuka, and received paid lecture fees from Roche, Novartis, Abbott Diagnostics and Echosens. Grace Lai-Hung Wong has been an advisory board member of Otsuka, and received paid lecture fees from Echosens and Otsuka. Henry Lik-Yuen Chan has been consultant for Abbott, Bristol-Myers Squibb, Merck, Novartis and Roche, and received paid lecture fees from Abbott, Bristol-Myers Squibb, Echosens, Gilead, Glaxo-Smith-Kline, Merck, Novartis and Roche.This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1. Genus level Bray-Curtis dissimilarity between…
Figure 1. Genus level Bray-Curtis dissimilarity between fecal samples.
Footnote: C, controls; P0, baseline samples of NASH patients; P6, month 6 samples of NASH patients; Uc, usual care group; Tx, probiotic treatment group.
Figure 2. Relative abundance of bacterial phyla.
Figure 2. Relative abundance of bacterial phyla.
(A) Controls (N = 22), (B) NASH patients at baseline (N = 16), (C) NASH patients at month 6 of usual care (N = 9), and (D) NASH patients at month 6 of probiotic treatment (N = 7).
Figure 3. Abundance of bacterial clades that…
Figure 3. Abundance of bacterial clades that differed between controls and NASH patients.
Footnote: Relative abundance is shown in percentage. C, controls; P, NASH patients; Uc, usual care group at month 6; Tx, probiotic treatment group at month 6. *

Figure 4. Firmicutes phylogeny and principal component…

Figure 4. Firmicutes phylogeny and principal component analysis (PCA) plot based on Unifrac distances between…

Figure 4. Firmicutes phylogeny and principal component analysis (PCA) plot based on Unifrac distances between the Firmicutes sequences in control and NASH subjects.
(A) The Firmicutes phylogeny was reconstructed from the OTU representative sequences in the control and NASH samples, and their relative abundance was indicated by gradient color from red to blue. (B) PCA plot of controls and NASH patients. The percentage of variation explained by each principal component was indicated in the parenthesis.

Figure 5. Score plots of PLS-DA distinguishing…

Figure 5. Score plots of PLS-DA distinguishing between the microbial community data of controls and…

Figure 5. Score plots of PLS-DA distinguishing between the microbial community data of controls and NASH patients.
(A and B) OTU level, (C and D) genus level.

Figure 6. Abundance of Lactobacillus and Bifidobacterium…

Figure 6. Abundance of Lactobacillus and Bifidobacterium .

Lactobacillus and Bifidobacterium were the two bacterial genera…
Figure 6. Abundance of Lactobacillus and Bifidobacterium.
Lactobacillus and Bifidobacterium were the two bacterial genera contained in the probiotics used in this study. ‘C’, ‘P’, ‘Uc’ and ‘Tx’ refer to controls, NASH patients at baseline, NASH patient at 6 months after usual care and treatment of probiotic, respectively. There is no significant difference between each pair of study groups.

Figure 7. Correlation between the changes in…

Figure 7. Correlation between the changes in intrahepatic triglyceride content and fecal bacterial abundance in…

Figure 7. Correlation between the changes in intrahepatic triglyceride content and fecal bacterial abundance in 16 NASH patients over 6 months.
Footnote: The x-axis and y-axis represents changes of intrahepatic triglyceride content and abundance of the indicated bacterial groups in 6 months, respectively. Solid and dashed lines are linear regression fits and 95% confidence bands, respectively.
All figures (7)
Figure 4. Firmicutes phylogeny and principal component…
Figure 4. Firmicutes phylogeny and principal component analysis (PCA) plot based on Unifrac distances between the Firmicutes sequences in control and NASH subjects.
(A) The Firmicutes phylogeny was reconstructed from the OTU representative sequences in the control and NASH samples, and their relative abundance was indicated by gradient color from red to blue. (B) PCA plot of controls and NASH patients. The percentage of variation explained by each principal component was indicated in the parenthesis.
Figure 5. Score plots of PLS-DA distinguishing…
Figure 5. Score plots of PLS-DA distinguishing between the microbial community data of controls and NASH patients.
(A and B) OTU level, (C and D) genus level.
Figure 6. Abundance of Lactobacillus and Bifidobacterium…
Figure 6. Abundance of Lactobacillus and Bifidobacterium.
Lactobacillus and Bifidobacterium were the two bacterial genera contained in the probiotics used in this study. ‘C’, ‘P’, ‘Uc’ and ‘Tx’ refer to controls, NASH patients at baseline, NASH patient at 6 months after usual care and treatment of probiotic, respectively. There is no significant difference between each pair of study groups.
Figure 7. Correlation between the changes in…
Figure 7. Correlation between the changes in intrahepatic triglyceride content and fecal bacterial abundance in 16 NASH patients over 6 months.
Footnote: The x-axis and y-axis represents changes of intrahepatic triglyceride content and abundance of the indicated bacterial groups in 6 months, respectively. Solid and dashed lines are linear regression fits and 95% confidence bands, respectively.

References

    1. Wong VW, Chu WC, Wong GL, Chan RS, Chim AM, et al. (2012) Prevalence of non-alcoholic fatty liver disease and advanced fibrosis in Hong Kong Chinese: a population study using proton-magnetic resonance spectroscopy and transient elastography. Gut 61: 409–415.
    1. Xu C, Yu C, Xu L, Miao M, Li Y (2010) High serum uric acid increases the risk for nonalcoholic Fatty liver disease: a prospective observational study. PLoS One 5: e11578.
    1. Ascha MS, Hanouneh IA, Lopez R, Tamimi TA, Feldstein AF, et al. (2010) The incidence and risk factors of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis. Hepatology 51: 1972–1978.
    1. Bhala N, Angulo P, van der Poorten D, Lee E, Hui JM, et al. (2011) The natural history of nonalcoholic fatty liver disease with advanced fibrosis or cirrhosis: an international collaborative study. Hepatology 54: 1208–1216.
    1. Wong VW, Wong GL, Choi PC, Chan AW, Li MK, et al. (2010) Disease progression of non-alcoholic fatty liver disease: a prospective study with paired liver biopsies at 3 years. Gut 59: 969–974.
    1. Targher G, Day CP, Bonora E (2010) Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. N Engl J Med 363: 1341–1350.
    1. Wong VW, Wong GL, Yip GW, Lo AO, Limquiaco J, et al. (2011) Coronary artery disease and cardiovascular outcomes in patients with non-alcoholic fatty liver disease. Gut 60: 1721–1727.
    1. Miele L, Valenza V, La Torre G, Montalto M, Cammarota G, et al. (2009) Increased intestinal permeability and tight junction alterations in nonalcoholic fatty liver disease. Hepatology 49: 1877–1887.
    1. Harte AL, da Silva NF, Creely SJ, McGee KC, Billyard T, et al. (2010) Elevated endotoxin levels in non-alcoholic fatty liver disease. J Inflamm (Lond) 7: 15.
    1. Verdam FJ, Rensen SS, Driessen A, Greve JW, Buurman WA (2011) Novel evidence for chronic exposure to endotoxin in human nonalcoholic steatohepatitis. J Clin Gastroenterol 45: 149–152.
    1. Spruss A, Kanuri G, Wagnerberger S, Haub S, Bischoff SC, et al. (2009) Toll-like receptor 4 is involved in the development of fructose-induced hepatic steatosis in mice. Hepatology 50: 1094–1104.
    1. Wagnerberger S, Spruss A, Kanuri G, Volynets V, Stahl C, et al. (2012) Toll-like receptors 1–9 are elevated in livers with fructose-induced hepatic steatosis. Br J Nutr 107: 1727–1738.
    1. Li Z, Yang S, Lin H, Huang J, Watkins PA, et al. (2003) Probiotics and antibodies to TNF inhibit inflammatory activity and improve nonalcoholic fatty liver disease. Hepatology 37: 343–350.
    1. Ma X, Hua J, Li Z (2008) Probiotics improve high fat diet-induced hepatic steatosis and insulin resistance by increasing hepatic NKT cells. J Hepatol 49: 821–830.
    1. Aller R, De Luis DA, Izaola O, Conde R, Gonzalez Sagrado M, et al. (2011) Effect of a probiotic on liver aminotransferases in nonalcoholic fatty liver disease patients: a double blind randomized clinical trial. Eur Rev Med Pharmacol Sci 15: 1090–1095.
    1. Malaguarnera M, Vacante M, Antic T, Giordano M, Chisari G, et al. (2012) Bifidobacterium longum with fructo-oligosaccharides in patients with non alcoholic steatohepatitis. Dig Dis Sci 57: 545–553.
    1. Wong VW, Won GL, Chim AM, Chu WC, Yeung DK, et al. (2013) Treatment of nonalcoholic steatohepatitis with probiotics. A proof-of-concept study. Ann Hepatol 12: 256–262.
    1. Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, et al. (2006) Metagenomic analysis of the human distal gut microbiome. Science 312: 1355–1359.
    1. Ley RE, Turnbaugh PJ, Klein S, Gordon JI (2006) Microbial ecology: human gut microbes associated with obesity. Nature 444: 1022–1023.
    1. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, et al. (2009) A core gut microbiome in obese and lean twins. Nature 457: 480–484.
    1. Qin J, Li Y, Cai Z, Li S, Zhu J, et al. (2012) A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490: 55–60.
    1. Larsen N, Vogensen FK, van den Berg FW, Nielsen DS, Andreasen AS, et al. (2010) Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLoS One 5: e9085.
    1. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, et al. (2004) The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci U S A 101: 15718–15723.
    1. Spencer MD, Hamp TJ, Reid RW, Fischer LM, Zeisel SH, et al. (2011) Association between composition of the human gastrointestinal microbiome and development of fatty liver with choline deficiency. Gastroenterology 140: 976–986.
    1. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, et al. (2012) The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 55: 2005–2023.
    1. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, et al. (2005) Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41: 1313–1321.
    1. Wong VW, Wong GL, Tsang SW, Fan T, Chu WC, et al. (2011) High prevalence of colorectal neoplasm in patients with non-alcoholic steatohepatitis. Gut 60: 829–836.
    1. Liu Z, Lozupone C, Hamady M, Bushman FD, Knight R (2007) Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res 35: e120.
    1. Andersson AF, Lindberg M, Jakobsson H, Backhed F, Nyren P, et al. (2008) Comparative analysis of human gut microbiota by barcoded pyrosequencing. PLoS One 3: e2836.
    1. Cole JR, Wang Q, Cardenas E, Fish J, Chai B, et al. (2009) The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37: D141–145.
    1. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73: 5261–5267.
    1. Xia J, Wishart DS (2011) Web-based inference of biological patterns, functions and pathways from metabolomic data using MetaboAnalyst. Nat Protoc 6: 743–760.
    1. Nawrocki EP, Kolbe DL, Eddy SR (2009) Infernal 1.0: inference of RNA alignments. Bioinformatics 25: 1335–1337.
    1. Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS One 5: e9490.
    1. Hamady M, Lozupone C, Knight R (2010) Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4: 17–27.
    1. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, et al. (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444: 1027–1031.
    1. Saulnier DM, Riehle K, Mistretta TA, Diaz MA, Mandal D, et al. (2011) Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome. Gastroenterology 141: 1782–1791.
    1. Rajilic-Stojanovic M, Biagi E, Heilig HG, Kajander K, Kekkonen RA, et al. (2011) Global and deep molecular analysis of microbiota signatures in fecal samples from patients with irritable bowel syndrome. Gastroenterology 141: 1792–1801.
    1. de Wit N, Derrien M, Bosch-Vermeulen H, Oosterink E, Keshtkar S, et al. (2012) Saturated fat stimulates obesity and hepatic steatosis and affects gut microbiota composition by an enhanced overflow of dietary fat to the distal intestine. Am J Physiol Gastrointest Liver Physiol 303: G589–599.
    1. Serino M, Luche E, Gres S, Baylac A, Berge M, et al. (2012) Metabolic adaptation to a high-fat diet is associated with a change in the gut microbiota. Gut 61: 543–553.
    1. Zhu L, Baker SS, Gill C, Liu W, Alkhouri R, et al. (2013) Characterization of gut microbiomes in nonalcoholic steatohepatitis (NASH) patients: A connection between endogenous alcohol and NASH. Hepatology 57: 601–609.
    1. Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermudez-Humaran LG, et al. (2008) Faecalibacterium prausnitzii is an anti-inflammatory commensal bacterium identified by gut microbiota analysis of Crohn disease patients. Proc Natl Acad Sci U S A 105: 16731–16736.
    1. Nardone G, Compare D, Liguori E, Di Mauro V, Rocco A, et al. (2010) Protective effects of Lactobacillus paracasei F19 in a rat model of oxidative and metabolic hepatic injury. Am J Physiol Gastrointest Liver Physiol 299: G669–676.
    1. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464: 59–65.

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