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Bifidobacteria metabolize lactulose to optimize gut metabolites and prevent systemic infection in patients with liver disease

Nature Microbiology volume 8, pages 2033–2049 (2023)Cite this article

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Abstract

Progression of chronic liver disease is precipitated by hepatocyte loss, inflammation and fibrosis. This process results in the loss of critical hepatic functions, increasing morbidity and the risk of infection. Medical interventions that treat complications of hepatic failure, including antibiotic administration for systemic infections and lactulose treatment for hepatic encephalopathy, can impact gut microbiome composition and metabolite production. Here, using shotgun metagenomic sequencing and targeted metabolomic analyses on 847 faecal samples from 262 patients with acute or chronic liver disease, we demonstrate that patients hospitalized for liver disease have reduced microbiome diversity and a paucity of bioactive metabolites, including short-chain fatty acids and bile acid derivatives, that impact immune defences and epithelial barrier integrity. We find that patients treated with the orally administered but non-absorbable disaccharide lactulose have increased densities of intestinal bifidobacteria and reduced incidence of systemic infections and mortality. Bifidobacteria metabolize lactulose, produce high concentrations of acetate and acidify the gut lumen in humans and mice, which, in combination, can reduce the growth of antibiotic-resistant bacteria such as vancomycin-resistant Enterococcus faecium in vitro. Our studies suggest that lactulose and bifidobacteria serve as a synbiotic to reduce rates of infection in patients with severe liver disease.

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Fig. 1: Faecal samples from hospitalized patients with liver disease display a wide range of microbiome and metabolomic profiles.
Fig. 2: Lactulose use is associated with increased bifidobacteria species abundance and reduced VRE abundance in the absence of systemic antibiotic use.
Fig. 3: Lactulose-mediated bifidobacteria expansion is associated with significant changes in bioactive faecal metabolites.
Fig. 4: Lactulose-mediated bifidobacteria expansion is associated with exclusion of antibiotic-resistant Enterococcus species.
Fig. 5: Bifidobacteria expansion and associated metabolite production are associated with decreased incidence of systemic infection and prolonged survival.

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Data availability

In keeping with the Health Insurance Portability and Accountability Act (HIPAA) and the University of Chicago institutional review board policy, clinical data that we obtained through the CRI are stored on secure, encrypted and password-protected servers and is not all publicly available. Select, non-identifiable clinical data are available on the data repository https://github.com/DFI-Bioinformatics/DFILiverDiseaseMicrobiome. Metagenomic information is publicly available on NCBI under BioProject ID PRJNA912122 (liver disease patient cohort and murine 16S data) and BioProject ID PRJNA838648 (healthy donor cohort). Quantitative faecal metabolomic information paired to faecal metagenomic information is publicly available on NCBI under BioProject ID PRJNA912122 (liver disease cohort) and BioProject ID PRJNA838648 (healthy donor cohort). Raw data files are publicly available on MassIVE repository under dataset IDs MSV000092750 and MSV000092751(both liver disease and healthy donor cohorts). In addition to the repositories specified above, all raw data included in the paper are publicly available at https://github.com/DFI-Bioinformatics/DFILiverDiseaseMicrobiome. Source data are provided with this paper.

Code availability

All code used for data analysis is publicly available at https://github.com/DFI-Bioinformatics/DFILiverDiseaseMicrobiome.

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Acknowledgements

We acknowledge the staff in the Duchossois Family Institute (DFI) metagenomics and metabolomics core facilities for technical assistance. We are grateful to all members of the DFI for enthusiastic discussions that guided this study. We also acknowledge the University of Chicago CRI for assistance with medical data extraction and the University of Chicago GRAF for their care of animals used in this study and guidance with performing gnotobiotic experiments. Funding: T32DK007074 (M.A.O.), U01AA026975 (T.G.C.), R35GM146969 (S.H.L.), Searle Scholars Program (S.H.L) and Duchossois Family Institute.

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Authors and Affiliations

  1. Department of Medicine, Section of Gastroenterology, Hepatology, and Nutrition, University of Chicago, Chicago, IL, USA

    Matthew A. Odenwald, Alan L. Hutchison, K. Gautham Reddy, Sonali Paul, Anjana Pillai, Helen S. Te, Mary E. Rinella, Michael R. Charlton & Andrew I. Aronsohn

  2. Duchossois Family Institute, University of Chicago, Chicago, IL, USA

    Huaiying Lin, Nicholas P. Dylla, Cody G. Cole, Jake D. Mostad, Téa E. Pappas, Ramanujam Ramaswamy, Emerald Adler, Jaye Boissiere, Maryam Khalid, Jackelyn Cantoral, Fidel Haro, Rita A. Oliveira, Emily Waligurski, Samuel H. Light, Anitha Sundararajan, Ashley M. Sidebottom & Eric G. Pamer

  3. Department of Medicine, Section of Infectious Diseases and Global Health, University of Chicago, Chicago, IL, USA

    Christopher Lehmann & Eric G. Pamer

  4. Department of Microbiology, University of Chicago, Chicago, IL, USA

    Cody G. Cole, Emily Waligurski & Eric G. Pamer

  5. Department of Pathology, University of Chicago, Chicago, IL, USA

    Angelica Moran & Kathleen G. Beavis

  6. Department of Medicine, Division of Pulmonary and Critical Care Medicine, Cook County Health, Chicago, IL, USA

    Matthew R. Stutz

  7. Section of Cardiology, Department of Medicine, University of Chicago, Chicago, IL, USA

    Mark Dela Cruz

  8. Division of Digestive and Liver Diseases, UT Southwestern Medical Center, Dallas, TX, USA

    Thomas G. Cotter

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Contributions

Conception or design of the work: M.A.O., C.L., A.M., M.R.S., M.D.C., R.A.O., T.G.C., S.H.L., K.G.R., S.P., A.P., H.S.T., M.E.R., M.R.C., E.G.P. and A.I.A. Data collection: M.A.O., H.L., N.P.D., C.G.C., J.D.M., T.E.P., R.R., E.A., J.B., M.K., J.C., F.H., E.W., K.G.B., A.S. and A.M.S. Data analysis and interpretation: M.A.O., H.L., C.L., N.P.D., C.G.C., J.D.M., T.E.P., R.R., A.M., A.L.H., M.R.S., M.D.C., R.A.O., T.G.C., A.S., A.M.S., E.G.P. and A.I.A. Drafting the article: M.A.O., H.L. and E.G.P. All authors provided critical revision of the article and approved of the final version of the paper to be published.

Corresponding authors

Correspondence to Matthew A. Odenwald or Eric G. Pamer.

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Nature Microbiology thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Fecal samples from patients with liver disease display a wide range of metabolomic profiles that correlates with metagenomic alpha-diversity.

Initial samples from each patient with full metabolomic profiling (n = 237) and healthy donors (n = 22) were arranged in order of increasing alpha-diversity as measured by inverse Simpson from left-to-right and shown in the top panel. One third of samples were grouped into low, medium, or high alpha-diversity based on inverse Simpson tertiles. Eighty-two metabolites were analyzed qualitatively for each sample, and the relative concentrations are represented in the pseudocolored heat map. For each compound, a Kruskal-Wallis test was run between the low diversity (n = 79), medium diversity (n = 79), high diversity (n = 79), and healthy donor (n = 22) groups. Statistics were adjusted for multiple comparisons using the Benjamini-Hochberg procedure and are color-coded in the far-right column.

Source data

Extended Data Fig. 2 The Bifidobacteria expanded cluster has a distinct short chain fatty acid and bile acid profile.

(A) A taxonomic UMAP (taxUMAP) was generated using 847 samples from 262 patients with liver disease. Each sample is represented by a single point that is colored based on the most abundant taxon as indicated. Samples with no taxa reaching ≥5% relative abundance were not considered to have a most abundant taxa and were labeled as “other.” (B – G) Samples within the taxUMAP were pseudocolored based on the indicated (B-D) SCFA or (E-G) BA concentrations. (H-R) All 847 stool samples were grouped by most abundant taxon as shown in Panel A. Graphs show the indicated (H-J) SCFA or (K-R) BA concentrations. Each individual point represents a single stool sample with the following sample sizes: n = 223 (Enterococcus), 142 (Bacteroidetes), 118 (Bifidobacterium), 91 (Lactobacillaceae), 75 (Lachnospiraceae), 57 (Proteobacteria), 44 (Streptococcus), 17 (Erysipelotrichaceae), 13 (Staphylococcus), 8 (Actinobacteria), 8 (Oscillospiraceae), and 51 (Others). Median and interquartile range are indicated by the horizontal line and box, respectively. The lower vertical line depicts Q1 – 1.5*IQR and the upper vertical line depicts Q3 + 1.5*IQR. Statistical comparisons between individual groups were analyzed using a two-tailed Wilcoxon rank sum test. Individual groups were compared to the Bifidobacteria dominated group, the unique cluster in this patient cohort. P-values are adjusted for multiple comparisons using the Benjamini-Hochberg procedure and represented as follows: *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001.

Source data

Extended Data Fig. 3 In the absence of lactulose, Bifidobacteria expansion is associated with modest fecal metabolite changes.

(A) Volcano plot (log2fold change vs. log10p-value) of qualitative metabolites comparing samples with low ( < 10%) vs. high ( ≥ 10%) Bifidobacteria abundance without lactulose exposure. P-values were calculated using a two-tailed Wilcoxon rank sum test and are corrected for multiple comparisons using the Benjamini-Hochberg procedure. Values with log2 fold-change > 1 (corresponding to a 2-fold change with a p-value < 0.05) were considered significant. (B) select SCFA and BA were quantified. Units for SCFA are mM, and units for BA derivatives are in μg/mL. (C) BA conversion from conjugated-primary BA to primary BA and then to secondary BAs was tested for each sample. Each point represents a molar ratio for an individual sample. For all comparisons (A-C), there is one sample per patient that was chosen based on the highest relative abundance of Bifidobacteria, and sample size was n = 79 (no lactulose exposure <10% Bifidobacteria) and n = 24 (no lactulose exposure with ≥10% Bifidobacteria). For panels B and C, each point represents a single sample. Median and interquartile range are indicated by the horizontal line and box, respectively. The lower vertical line depicts Q1 – 1.5*IQR and the upper vertical line depicts Q3 + 1.5*IQR. Statistical comparisons between individual groups were analyzed using a two-tailed Wilcoxon rank sum test. P-values are adjusted for multiple comparisons using the Benjamini-Hochberg procedure and represented as follows: *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001. For both panels B and C, Samples were grouped by whether they had expanded Bifidobacteria in the absence of recent lactulose exposure. Median and interquartile range are indicated by the line and box, respectively. The lower vertical line depicts Q1 – 1.5*IQR and the upper vertical line depicts Q3 + 1.5*IQR. CA: cholic acid; GCA: glycocholic acid; DCA: deoxycholic acid.

Source data

Extended Data Fig. 4 B. longum acidifies pH, produces acetate, and efficiently hydrolyzes conjugated primary bile acids.

B. longum was grown in regular media (blue) or media supplemented with 50 mM lactulose (red) or sucrose (green). (A) pH before and after 24 h of growth (n = 3 for 0 h; n = 6 for 24 h). (B) SCFA concentrations after 24 h of growth. n = 6 all conditions. (C and D) Supernatant BA quantified after 24 h B. longum growth in media containing 10μg/ml (C) TCA or (D) GCA. n = 4 all conditions. (B-D) *, p < 0.05, two-tailed t-test corrected for multiple comparisons. Plots representative of three independent experiments with ≥3 technical replicates. TCA: taurocholic acid, GCA: glycocholic acid, CA: cholic acid, CDCA: chenodeoxycholic acid, DCA: deoxycholic acid, and LCA: lithocholic acid. (E) Ex-GF mouse B. longum monocolonization experimental design. (F) Stool lactulose in GF mice receiving drinking containing 0, 10, 20, or 40 g/L lactulose or in SPF mice with water containing either 0 or 20 g/L lactulose. n = 1 for each condition. (G) Stool water content of GF mice receiving water with 0 or 20 g/L lactulose. n = 3 for each group. *, p < 0.05, two-tailed t-test. (H) Fecal quantitative 16 S metagenomics from ex-GF mice colonized with B. longum +/- lactulose in drinking water. n = 4 for each group except for day 1 in the water-treated group (one mouse did not produce a stool sample). n = 3 for the lactulose-treated group after day 1 (one mouse did not produce stool samples). (I – K) SCFA concentrations before and 10-days after Bifidobacteria inoculation. Each dot represents one sample from each mouse. Bar represents the median. *, p < 0.05, two tailed t-test comparing water to lactulose-treated mice at a time point. (L) Primary, (M) conjugated primary, and (N) secondary BA were measured. Each dot represents one sample from each mouse. Bar represents the median. *, p < 0.05, t-test comparing to time 0 for a given lactulose exposure.

Source data

Extended Data Fig. 5 Lactulose promotes Bifidobacteria expansion and favorable metabolomic profile in mice colonized with complex bacterial consortia.

(A) Schematic indicating timing of consortia gavage, lactulose administration (20 g/L in drinking water), and stool collection in ex-germ-free mice. 16 S: metagenomics; Metab.: targeted, quantitative metabolomics. For CON.1, n = 3 mice total (pre- and post-lactulose samples taken); CON.2, n = 6 mice (3 without lactulose, 3 with lactulose); and CON.3, n = 8 mice (4 without lactulose, 4 with lactulose). (B) 16 S metagenomics from stool samples without (left facet within each consortia) and with (right facet within each consortia) lactulose exposure is shown as relative abundance. Concentrations of acetate and taurocholic acid are shown in units of mM below each paired sample. (C) Bifidobacteria relative abundance, acetate concentration (mM), and taurocholic acid concentrations (μg/ml) were measured and compared between mice that were and were not exposed to lactulose. Each dot represents a single stool sample from an individual mouse, and the bar represents the median. *, p < 0.05 by one-tailed t-test comparing water to lactulose-treated mice for each consortium.

Source data

Extended Data Fig. 6 Bifidobacterium longum supernatant inhibits VRE growth in vitro.

(A) Schematic of experimental design for VRE growth in B. longum conditioned media (CM). B. longum was grown in BHIS for 24-hours prior to collecting and filtering the supernatant. VRE growing at steady state was then diluted to a low density (OD600 = 0.05) prior to inoculating in various dilutions of B. longum conditioned media in fresh BHIS. (B) VRE growth curves in 100%, 50%, 12.5%, and 0% CM with the pH of the 4 concentrations of CM in BHIS shown in the right portion of this panel. (C) The pH of neutral BHIS was acidified from 7.2 to 5.8 using HCl, and the pH of B. longum CM was neutralized from 5.8 to 7.2 with NaOH prior to VRE inoculation. Growth curves for VRE in each of these 4 conditions are shown. (D) VRE was inoculated into either neutral (top panels) or acidified (bottom panels) BHIS containing 0 mM (blue), 30 mM (green), 100 mM (orange), or 300 mM (red) of the indicated SCFA. (E) VRE was grown in minimal media containing either no additive (blue) or 50 mM lactulose, and OD600 was measured over time. (F) VRE was grown in BHIS with or without 50 mM lactulose, and OD600 was measured over time. All growth curves are depicted with mean +/- standard deviation for technical replicates for each group. Plots are representative of three independent experiments done in at least triplicate, each of which was reproduced on each experimental replicate.

Source data

Extended Data Fig. 7 Bifidobacteria expansion and associated metabolite production are associated with decreased incidence of spontaneous bacterial peritonitis (SBP).

(A) Flow diagram depicting number of samples and number of patients that were filtered out at each step of analysis for SBP. (B) Taxonomic relative abundance by shotgun metagenomics of stool samples paired to ascites samples is plotted in order of decreasing Bifidobacteria abundance from left to right. Underneath each stool sample is the clinical diagnosis associated with an ascites sample (SBP (red) or not SBP (green)). (C) Volcano plot of normalized metabolite concentrations. P-values were calculated using a two-tailed Wilcoxon rank sum test and are corrected for multiple comparisons using the Benjamini-Hochberg procedure. Values with log2 fold-change > 1 (corresponding to a 2-fold change with a p-value < 0.05) were considered significant. (D and E) Quantitative levels for butyrate, propionate, lithocholic acid, and alloisolithocholic acid were compared from samples associated and not associated with SBP. Units for SCFA are mM, and units for BA derivatives are in μg/mL. Each point represents a single sample. Median and interquartile range are indicated by the horizontal line and box, respectively. The lower vertical line depicts Q1 – 1.5*IQR and the upper vertical line depicts Q3 + 1.5*IQR. Statistical comparisons between individual groups were analyzed using a two-tailed Wilcoxon rank sum test. There were 101 ascites-adjacent samples not associated with SBP and 21 associated with SBP.

Source data

Extended Data Fig. 8 Bifidobacteria expansion and associated metabolite production are associated with decreased incidence of bacteremia.

(A) Flow diagram depicting number of samples and number of patients that were filtered out at each step of analysis for bacteremia. (B) Taxonomic relative abundance by shotgun metagenomics of stool samples paired to blood cultures is plotted in order of decreasing Bifidobacteria abundance from left to right. Underneath each stool sample is the clinical diagnosis associated with a given blood culture (bacteremia (red) or no bacteremia (green)). (C) Volcano plot of normalized metabolite concentrations. P-values were calculated using a two-tailed Wilcoxon rank sum test and are corrected for multiple comparisons using the Benjamini-Hochberg procedure. Values with log2 fold-change > 1 (corresponding to a 2-fold change with a p-value < 0.05) were considered significant. (D and E) Quantitative levels for butyrate, propionate, lithocholic acid, and alloisolithocholic acid were compared from samples associated and not associated with SBP. Units for SCFA are mM, and units for BA derivatives are in μg/mL. Each point represents a single sample. Median and interquartile range are indicated by the horizontal line and box, respectively. The lower vertical line depicts Q1 – 1.5*IQR and the upper vertical line depicts Q3 + 1.5*IQR. Statistical comparisons between individual groups were analyzed using a two-tailed Wilcoxon rank sum test. There were 227 blood culture-adjacent samples not associated with SBP and 19 associated with bacteremia.

Source data

Extended Data Table 1 Patient demographics and baseline disease characteristics stratified by initial sample alpha-diversity
Full size table
Extended Data Table 2 Patient demographics and baseline disease characteristics stratified by initial sample Bifidobacteria expansion in response to lactulose
Full size table

Supplementary information

Source data

Source Data Fig. 1

. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used to generate relative abundance plots in a). Tab name: Quant Metab and Clin Info. Data description: quantitative metabolomic information, alpha-diversity and alpha-diversity categories for all samples.

Source Data Fig. 2. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used to generate relative abundance plots in a). Tab name: Quant Metab and Clin Info. Data description: contains information regarding vanA gene coding (RPKM), medication exposures and disease chronicity used to generate heat maps in a.

Source Data Fig. 3. Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) medication exposures that were used to determine if samples were obtained after lactulose, (2) bifidobacteria relative abundance and (3) quantitative metabolite levels. Tab name: Qual Metab. Data description: contains relative metabolite levels for all samples in the study (used in a).

Source Data Fig. 4. Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) medication exposures that were used to determine if samples were obtained after lactulose and (2) bifidobacteria, Enterococcus and Proteobacteria relative abundances. Tab name: Fig. 4b. Data description: raw data used to generate growth curves. Tab name: Fig. 4d. Data description: c.f.u. counts for each condition shown.

Source Data Fig. 5. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used to perform LEfSe analysis). Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) infection status, (2) quantitative metabolites, (3) alpha-diversity, (4) lactulose exposure and bifidobacteria abundance, and /5) survival time after consent (up to 90 days).

Source Data Extended Data Fig. 1. Tab name: Qual Metab. Data description: contains relative metabolite levels for all samples in the study.

Source Data Extended Data Fig. 2. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used to generate taxUMAP and determine most abundant taxa). Tab name: Quant Metab and Clin Info. Data description: contains information regarding quantitative metabolites.

Source Data Extended Data Fig. 3. Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) medication exposures that were used to determine if samples were obtained after lactulose, (2) bifidobacteria relative abundance and (3) quantitative metabolite levels. Tab name: Qual Metab. Data description: contains relative metabolite levels for all samples in the study (used in a).

Source Data Extended Data Fig. 4. Tab name: Fig E4A. Data description: measured pH values for each sample. Tab name: Fig E4B. Data description: measured SCFA levels for each sample. Tab name: Fig E4CD. Data description: measure BA levels for each sample. Tab name: Fig E4F. Data description: stool lactulose content for each sample. Tab name: Fig E4G. Data description: stool water content for each sample. Tab name: Fig E4IJK. Data description: stool SCFA concentrations for each sample. Tab name: Fig E4LMN. Data description: stool BA concentrations for each sample.

Source Data Extended Data Fig. 5. Tab name: Fig E5C. Data description: stool bifidobacteria, acetate and taurocholic acid levels for each sample.

Source Data Extended Data Fig. 6. Tab name: Fig E6B. Data description: raw values for growth curves shown. Tab name: Fig E6C. Data description: raw values for growth curves shown. Tab name: Fig E6D. Data description: raw values for growth curves shown. Tab name: Fig E6E. Data description: raw values for growth curves shown. Tab name: Fig E6F. Data description: raw values for growth curves shown.

Source Data Extended Data Fig. 7. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used for relative abundance plots). Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) infection status and (2) quantitative metabolites. Tab name: Qual Metab. Data description: contains relative metabolite levels for all samples in the study used to generate c.

Source Data Extended Data Fig. 8. Tab name: Metaphlan4. Data description: metagenomic information for all samples (used for relative abundance plots). Tab name: Quant Metab and Clin Info. Data description: contains information regarding (1) infection status and (2) quantitative metabolites. Tab name: Qual Metab. Data description: contains relative metabolite levels for all samples in the study used to generate c.

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Odenwald, M.A., Lin, H., Lehmann, C. et al. Bifidobacteria metabolize lactulose to optimize gut metabolites and prevent systemic infection in patients with liver disease. Nat Microbiol 8, 2033–2049 (2023). https://doi.org/10.1038/s41564-023-01493-w

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