CoChat
Sign Up
Cited by 518Gut microbiota and healthDrug Transport and Resistance MechanismsSteroid Chemistry and Biochemistry

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

Taxonomic profiling and populational patterns of bacterial bile salt hydrolase (BSH) genes based on worldwide human gut microbiome

Open access
Song, Ziwei, Cai, Yuanyuan, Lao, Xingzhen, Wang, Xue, Lin, Xiaoxuan, Cui, Yingyun, Kalavagunta, Praveen Kumar, Liao, Jun, Jin, Liang, Shang, Jing, Li, Jing·2019·Microbiome
DOI 10.1186/s40168-019-0628-3PMC PMC6345003

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: Bile salt hydrolase plays an important role in bile acid-mediated signaling pathways, which regulate lipid absorption, glucose metabolism, and energy homeostasis. Several reports suggest that changes in the composition of bile acids are found in many diseases caused by dysbacteriosis. RESULTS: Here, we present the taxonomic identification of bile salt hydrolase (BSH) in human microbiota and elucidate the abundance and activity differences of various bacterial BSH among 11 different populations from six continents. For the first time, we revealed that bile salt hydrolase protein sequences (BSHs) are distributed in 591 intestinal bacterial strains within 117 genera in human microbiota, and 27.52% of these bacterial strains containing BSH paralogs. Significant variations are observed in BSH distribution patterns among different populations. Based on phylogenetic analysis, we reclassified these BSHs into eight phylotypes and investigated the abundance patterns of these phylotypes among different populations. From the inspection of enzyme activity among different BSH phylotypes, BSH-T3 showed the highest enzyme activity and is only found in Lactobaclillus. The phylotypes of BSH-T5 and BSH-T6 mainly from Bacteroides with high percentage of paralogs exhibit different enzyme activity and deconjugation activity. Furthermore, we found that there were significant differences between healthy individuals and patients with atherosclerosis and diabetes in some phylotypes of BSHs though the correlations were pleiotropic. CONCLUSION: This study revealed the taxonomic and abundance profiling of BSH in human gut microbiome and provided a phylogenetic-based system to assess BSHs activity by classifying the target sequence into specific phylotype. Furthermore, the present work disclosed the variation patterns of BSHs among different populations of geographical regions and health/disease cohorts, which is essential to understand the role of BSH in the development and progression of related diseases.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s40168-019-0628-3

Cites

85 of 85 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 1 Comparison of known representative BSHs. a Secondary structure comparison. b Topological diagram. c 3D structure comparison of four BSHs that have reported their active site residues. Here, the red frames in the secondary structures, the red stars in the topological diagram, and the red chains in 3D structures both show the reported active site residues in four BSH
Fig. 1 Comparison of known representative BSHs. a Secondary structure comparison. b Topological diagram. c 3D structure comparison of four BSHs that have reported their active site residues. Here, the red frames in the secondary structures, the red stars in the topological diagram, and the red chains in 3D structures both show the reported active site residues in four BSHCC BY · PubMed Central
Fig. 2 Taxonomic characterization of BSHs obtained from the HMP. a Taxonomic identification of BSHs in different main genera, i.e., containing more than five BSHs. b Quantity of BSHs containing bacteria stains at the phylum and genus level, respectively. c The proportion of strains expressing BSHs among all strains from the HMP database. d The proportion of different paralogs in all BSHs from the HMP database. e Density distribution of BSHs between and within genera in the HMP database. Details are shown in Additional file 2: Table S2
Fig. 2 Taxonomic characterization of BSHs obtained from the HMP. a Taxonomic identification of BSHs in different main genera, i.e., containing more than five BSHs. b Quantity of BSHs containing bacteria stains at the phylum and genus level, respectively. c The proportion of strains expressing BSHs among all strains from the HMP database. d The proportion of different paralogs in all BSHs from the HMP database. e Density distribution of BSHs between and within genera in the HMP database. Details are shown in Additional file 2: Table S2CC BY · PubMed Central
Fig. 3 Effects of multiple factors on relative abundance of BSHs. a Relative abundance (RA) of BSHs in different genders among nine populations. b Correlation between BSHs RA and age in eight populations. c Correlation between BSHs RA and BMI in seven populations. d The cumulative RA and genera distribution of BSHs in different populations. e The multivariable-adjusted analysis of cumulative RA of BSHs against individual conditions including four factors. pa values were calculated by nonparametric univariate method (Mann-Whitney U test) corrected for false discovery rate. pb values were calculated by multivariable-adjusted analyses using linear regression model for target factor with remaining three factors. Here, the 11 populations form six continents include Africa: HZ; Asia: CN, JP, and KR; Europe: DK, SE, AT, and FR; Oceania: AU; North America (N-America): US; South America (S-America): PE. Note that the datasets of KR and AU have no individual information of gender, age, and BMI, and the dataset of HZ has no individual information of BMI, while the dataset of US has no individual information of age and BMI. Thus, the above datasets were excluded in related analysis. Details are shown in Additional file 2: Table S3, S4
Fig. 3 Effects of multiple factors on relative abundance of BSHs. a Relative abundance (RA) of BSHs in different genders among nine populations. b Correlation between BSHs RA and age in eight populations. c Correlation between BSHs RA and BMI in seven populations. d The cumulative RA and genera distribution of BSHs in different populations. e The multivariable-adjusted analysis of cumulative RA of BSHs against individual conditions including four factors. pa values were calculated by nonparametric univariate method (Mann-Whitney U test) corrected for false discovery rate. pb values were calculated by multivariable-adjusted analyses using linear regression model for target factor with remaining three factors. Here, the 11 populations form six continents include Africa: HZ; Asia: CN, JP, and KR; Europe: DK, SE, AT, and FR; Oceania: AU; North America (N-America): US; South America (S-America): PE. Note that the datasets of KR and AU have no individual information of gender, age, and BMI, and the dataset of HZ has no individual information of BMI, while the dataset of US has no individual information of age and BMI. Thus, the above datasets were excluded in related analysis. Details are shown in Additional file 2: Table S3, S4CC BY · PubMed Central
Fig. 4 Taxonomic characterization and populational patterns of reclassified BSHs. The left panel shows the phylogenetic tree of BSHs in 11 populations from six continents, include Africa: HZ; Asia: CN, JP, and KR; Europe: DK, SE, AT, and FR; Oceania: AU; North America (N-America): US; South America (S-America): PE. Different colors represent the eight reclassified BSH phylotypes. The highlighted sequences with “id” were selected for molecular docking and enzyme activity experiments. The pies in the middle panel showed the percentage of genera in each phylotype of BSHs (for genera in group “others,” please refer to Additional file 2: Table S5). Bar plots in the right panel indicate the relative abundance (RA) of each BSH phylotypes in different populations. Details are shown in Additional file 2: Table S4–S6
Fig. 4 Taxonomic characterization and populational patterns of reclassified BSHs. The left panel shows the phylogenetic tree of BSHs in 11 populations from six continents, include Africa: HZ; Asia: CN, JP, and KR; Europe: DK, SE, AT, and FR; Oceania: AU; North America (N-America): US; South America (S-America): PE. Different colors represent the eight reclassified BSH phylotypes. The highlighted sequences with “id” were selected for molecular docking and enzyme activity experiments. The pies in the middle panel showed the percentage of genera in each phylotype of BSHs (for genera in group “others,” please refer to Additional file 2: Table S5). Bar plots in the right panel indicate the relative abundance (RA) of each BSH phylotypes in different populations. Details are shown in Additional file 2: Table S4–S6CC BY · PubMed Central
Fig. 5 Molecular docking and enzyme activity comparison. The results of molecular docking and kinetic reaction of eight BSH phylotypes with a glycocholic acid (GCA), b glycochenodeoxycholic acid (GCDCA), c glycine deoxycholic acid (GDCA), d taurocholic acid (TCA), e taurochenodeoxycholic acid (TCDCA), f taurodeoxycholic acid (TDCA), and g tauroursodeoxycholic acid (TUDCA). The left panel shows the binding energy (BD energy) of each BSH, and molecular docking predicted binding models of BSH-T3 with different bile acids. The middle panel showed the eight BSHs in the kinetic reaction with different bile acids. The right panel compares the deconjugation (the proportion of product bile acid of specific substrate) in light green bar when the substrate concentration is 0.1 mM, and specific activity (the activity of an enzyme per milligram of total protein, using the highest enzyme activity as 100%) of eight BSHs with different bile salts (final concentration of all bile salts was 20 mM) in light purple bar when the substrate concentration is 20 mM. Data were analyzed with student’s t test corrected by false discovery rate. *p < 0.05, **p < 0.01, and ***p < 0.05, versus the BSH which shown the highest enzyme activity for the specific bile salt, i.e., BSH-T3 showed the highest enzyme activity when the substrates were TCDCA and TDCA, for TCA, it is BSH-T1. Details are shown in Additional file 2: Table S7–S9
Fig. 5 Molecular docking and enzyme activity comparison. The results of molecular docking and kinetic reaction of eight BSH phylotypes with a glycocholic acid (GCA), b glycochenodeoxycholic acid (GCDCA), c glycine deoxycholic acid (GDCA), d taurocholic acid (TCA), e taurochenodeoxycholic acid (TCDCA), f taurodeoxycholic acid (TDCA), and g tauroursodeoxycholic acid (TUDCA). The left panel shows the binding energy (BD energy) of each BSH, and molecular docking predicted binding models of BSH-T3 with different bile acids. The middle panel showed the eight BSHs in the kinetic reaction with different bile acids. The right panel compares the deconjugation (the proportion of product bile acid of specific substrate) in light green bar when the substrate concentration is 0.1 mM, and specific activity (the activity of an enzyme per milligram of total protein, using the highest enzyme activity as 100%) of eight BSHs with different bile salts (final concentration of all bile salts was 20 mM) in light purple bar when the substrate concentration is 20 mM. Data were analyzed with student’s t test corrected by false discovery rate. *p < 0.05, **p < 0.01, and ***p < 0.05, versus the BSH which shown the highest enzyme activity for the specific bile salt, i.e., BSH-T3 showed the highest enzyme activity when the substrates were TCDCA and TDCA, for TCA, it is BSH-T1. Details are shown in Additional file 2: Table S7–S9CC BY · PubMed Central
Fig. 6 The relative abundance of BSHs among case-control cohorts. a The relative abundance (RA) of BSH in the gut microbiome of healthy people and patients with type 2 diabetes (T2D) and the average RA of different BSH phylotypes in healthy people and patients. b The relative abundance (RA) of BSH in the gut microbiome of healthy people and patients with atherosclerosis (AS) and the average RA of different BSH phylotypes in healthy people and patients. pc values were calculated by the chi-squared test, pu values were calculated by the Mann-Whitney U test, and p values in each type were followed by false discovery rate correction. The populations from CN and CN2 are independent cases. Details are shown in Additional file 2: Table S3
Fig. 6 The relative abundance of BSHs among case-control cohorts. a The relative abundance (RA) of BSH in the gut microbiome of healthy people and patients with type 2 diabetes (T2D) and the average RA of different BSH phylotypes in healthy people and patients. b The relative abundance (RA) of BSH in the gut microbiome of healthy people and patients with atherosclerosis (AS) and the average RA of different BSH phylotypes in healthy people and patients. pc values were calculated by the chi-squared test, pu values were calculated by the Mann-Whitney U test, and p values in each type were followed by false discovery rate correction. The populations from CN and CN2 are independent cases. Details are shown in Additional file 2: Table S3CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 85 references

Research works printed but not linked: 2

  1. National Center for Biotechnology Information, U.S. https://www.ncbi.nlm.nih.gov . Accessed 17 Oct 2018.
  2. Haeusler RA, Astiarraga B, Camastra S, Accili D, Ferrannini E. Human insulin resistance is associated with increased plasma levels of 12a-hydroxylated bile acids. Diabetes. 2013;62:4184–91. · DOI · Paper page

Cited by

Sorted by citations

Items 101–200 of 518

Related

See all

Metadata

Authors
Song, Z., Cai, Y., Lao, X., Wang, X., Lin, X., Cui, Y., Kalavagunta, P. K., Liao, J., Jin, L., Shang, J., & Li, J.
Affiliations
China Pharmaceutical University (CN)
Corresponding author
  • Jin, Liang
  • Shang, Jing
  • Li, Jing
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2019-01-23
Volume
7
Issue
1
Pages
9-9
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/s40168-019-0628-3
PMC
PMC6345003
OpenAlex
W2952656298
Cited by
505
References
85
Citations by year
2026: 56 · 2025: 88 · 2024: 109 · 2023: 78 · 2022: 77 · 2021: 58 · 2020: 32 · 2019: 6
FWCI
14.31
Type
journal article
Language
en
Open access
Licence
Locations
  • Microbiome (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
National Natural Science Foundation of China (31670495)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
  • Physical Sciences › Chemistry › Organic Chemistry › Steroid Chemistry and Biochemistry
Keywords
bile salt hydrolase, human gut microbiome, bile acid deconjugation, Lactobacillus, Bacteroides, population variation, atherosclerosis, diabetes mellitus, dysbiosis, bile acid signaling
MeSH terms
Gastrointestinal Microbiome, Amidohydrolases, Amino Acid Sequence, Bacteria, Bile Acids and Salts, Humans, Phylogeny, Protein Structure, Secondary, Enzyme Assays, Molecular Docking Simulation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review