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Research article
Jason M. Ridlon
Corresponding Author
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Background: Berberine (BBR) is a plant-based nutraceutical that has been used for millennia to treat diarrheal infections and in contemporary medicine to improve patient lipid profiles. Reduction in lipids, particularly cholesterol, is achieved partly through up-regulation of bile acid synthesis and excretion into the gastrointestinal tract (GI). The efficacy of BBR is also thought to be dependent on structural and functional alterations of the gut microbiome. However, knowledge of the effects of BBR on gut microbiome communities is currently lacking. Distinguishing indirect effects of BBR on bacteria through altered bile acid profiles is particularly important in understanding how dietary nutraceuticals alter the microbiome.
Methods: Germfree mice were colonized with a defined minimal gut bacterial consortium capable of functional bile acid metabolism (Bacteroides vulgatus, Bacteroides uniformis, Parabacteroides distasonis, Bilophila wadsworthia, Clostridium hylemonae, Clostridium hiranonis, Blautia producta; B4PC2). Multi-omics (bile acid metabolomics, 16S rDNA sequencing, cecal metatranscriptomics) were performed in order to provide a simple in vivo model from which to identify network-based correlations between bile acids and bacterial transcripts in the presence and absence of dietary BBR.
Results: Significant alterations in network topology and connectivity in function were observed, despite similarity in gut microbial alpha diversity (P = 0.30) and beta-diversity (P = 0.123) between control and BBR treatment. BBR increased cecal bile acid concentrations, (P < 0.05), most notably deoxycholic acid (DCA) (P <0.001). Overall, analysis of transcriptomes and correlation networks indicates both bacterial species-specific responses to BBR, as well as functional commonalities among species, such as up-regulation of Na+/H+ antiporter, cell wall synthesis/repair, carbohydrate metabolism and amino acid metabolism. Bile acid concentrations in the GI tract increased significantly during BBR treatment and developed extensive correlation networks with expressed genes in the B4PC2 community.
Conclusions: This work has important implications for interpreting the effects of BBR on structure and function of the complex gut microbiome, which may lead to targeted pharmaceutical interventions aimed to achieve the positive physiological effects previously observed with BBR supplementation.
Keywords
Berberine, bile acids, gnotobiotic mice, gut bacteria, network analysis, nutraceutical, RNA-Seq
Figure 1
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This is a list of supplementary files associated with this preprint. Click to download.
- CopyofSupplementaryDataset4FoldChangeStatistics.xlsx
- NC3RsARRIVEGuidelinesChecklistPWPagenumbers.pdf
- S1.pdf
Figure S1. Profile of liver bile acids from control and berberine treated mice.
- S2.pdf
Figure S2. Profile of three most abundant liver bile acids from control and berberine treated mice.
- S3.pdf
Figure S3. Serum bile acid profile in control and berberine treated mice.
- S4.pdf
Figure S4. Profile of cecal bile acids between control and berberine treated mice not represented in Figure 1. Significance determined by student t test. * P < 0.05.
- S5.pdf
Figure S5: 16S rDNA profile of human gut bacterial consortium in cecal samples of gnotobiotic fed control diet versus berberine. A. Relative abundance of bacterial families in control mice (C1-C6) and berberine treatment (B1-B6) B. Non-metric multidimensional scaling (NMDS) plot of beta diversity based on Bray-Curtis index. ANOSIM test results: R = 0.141, P = 0.123, 999 permutations.
- S6.pdf
Figure S6. Shannon Index comparison between control mice and berberine treatment. The rarified 23,900 MiSeq dataset was used. Mann-Whitney test P = 0.309.
- SupplementaryDataset2RNASeqControlData.xlsx
- SupplementaryDataset3RNASeqBerberineData.xlsx
- SupplementaryDatasetCorrelationNetworks.xlsx
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View the published article at BMC Microbiology.
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Editorial decision: Accept
On 23 Oct, 2020
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On 20 Oct, 2020
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On 19 Oct, 2020
Editor invited
On 19 Oct, 2020
Version 2
Posted 14 Sep, 2020
No comments provided
Editorial decision: Minor revision
On 14 Oct, 2020
Editor assigned
On 08 Sep, 2020
Submission checks complete
On 07 Sep, 2020
Editor invited
On 07 Sep, 2020
No comments provided
Review #3 received
Received 31 Aug, 2020
Editorial decision: Major revision
On 31 Aug, 2020
Reviewer #3 agreed
On 06 Aug, 2020
Review #1 received
Received 27 Jul, 2020
Review #2 received
Received 24 Jul, 2020
Reviewer #2 agreed
On 08 Jul, 2020
Reviewer #1 agreed
On 28 Jun, 2020
Reviewers invited
Invitations sent on 22 Jun, 2020
Editor assigned
On 19 Jun, 2020
Submission checks complete
On 18 Jun, 2020
Editor invited
On 18 Jun, 2020
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Subject Areas
General Microbiology
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See the published version of this preprint at BMC Microbiology.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Jason M. Ridlon
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BMC Microbiology.
No community comments so far
Editorial decision: Accept
On 23 Oct, 2020
Editor assigned
On 20 Oct, 2020
Submission checks complete
On 19 Oct, 2020
Editor invited
On 19 Oct, 2020
Version 2
Posted 14 Sep, 2020
No comments provided
Editorial decision: Minor revision
On 14 Oct, 2020
Editor assigned
On 08 Sep, 2020
Submission checks complete
On 07 Sep, 2020
Editor invited
On 07 Sep, 2020
No comments provided
Review #3 received
Received 31 Aug, 2020
Editorial decision: Major revision
On 31 Aug, 2020
Reviewer #3 agreed
On 06 Aug, 2020
Review #1 received
Received 27 Jul, 2020
Review #2 received
Received 24 Jul, 2020
Reviewer #2 agreed
On 08 Jul, 2020
Reviewer #1 agreed
On 28 Jun, 2020
Reviewers invited
Invitations sent on 22 Jun, 2020
Editor assigned
On 19 Jun, 2020
Submission checks complete
On 18 Jun, 2020
Editor invited
On 18 Jun, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
General Microbiology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BMC Microbiology.
Background: Berberine (BBR) is a plant-based nutraceutical that has been used for millennia to treat diarrheal infections and in contemporary medicine to improve patient lipid profiles. Reduction in lipids, particularly cholesterol, is achieved partly through up-regulation of bile acid synthesis and excretion into the gastrointestinal tract (GI). The efficacy of BBR is also thought to be dependent on structural and functional alterations of the gut microbiome. However, knowledge of the effects of BBR on gut microbiome communities is currently lacking. Distinguishing indirect effects of BBR on bacteria through altered bile acid profiles is particularly important in understanding how dietary nutraceuticals alter the microbiome.
Methods: Germfree mice were colonized with a defined minimal gut bacterial consortium capable of functional bile acid metabolism (Bacteroides vulgatus, Bacteroides uniformis, Parabacteroides distasonis, Bilophila wadsworthia, Clostridium hylemonae, Clostridium hiranonis, Blautia producta; B4PC2). Multi-omics (bile acid metabolomics, 16S rDNA sequencing, cecal metatranscriptomics) were performed in order to provide a simple in vivo model from which to identify network-based correlations between bile acids and bacterial transcripts in the presence and absence of dietary BBR.
Results: Significant alterations in network topology and connectivity in function were observed, despite similarity in gut microbial alpha diversity (P = 0.30) and beta-diversity (P = 0.123) between control and BBR treatment. BBR increased cecal bile acid concentrations, (P < 0.05), most notably deoxycholic acid (DCA) (P <0.001). Overall, analysis of transcriptomes and correlation networks indicates both bacterial species-specific responses to BBR, as well as functional commonalities among species, such as up-regulation of Na+/H+ antiporter, cell wall synthesis/repair, carbohydrate metabolism and amino acid metabolism. Bile acid concentrations in the GI tract increased significantly during BBR treatment and developed extensive correlation networks with expressed genes in the B4PC2 community.
Conclusions: This work has important implications for interpreting the effects of BBR on structure and function of the complex gut microbiome, which may lead to targeted pharmaceutical interventions aimed to achieve the positive physiological effects previously observed with BBR supplementation.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
This is a list of supplementary files associated with this preprint. Click to download.
- CopyofSupplementaryDataset4FoldChangeStatistics.xlsx
- NC3RsARRIVEGuidelinesChecklistPWPagenumbers.pdf
- S1.pdf
Figure S1. Profile of liver bile acids from control and berberine treated mice.
- S2.pdf
Figure S2. Profile of three most abundant liver bile acids from control and berberine treated mice.
- S3.pdf
Figure S3. Serum bile acid profile in control and berberine treated mice.
- S4.pdf
Figure S4. Profile of cecal bile acids between control and berberine treated mice not represented in Figure 1. Significance determined by student t test. * P < 0.05.
- S5.pdf
Figure S5: 16S rDNA profile of human gut bacterial consortium in cecal samples of gnotobiotic fed control diet versus berberine. A. Relative abundance of bacterial families in control mice (C1-C6) and berberine treatment (B1-B6) B. Non-metric multidimensional scaling (NMDS) plot of beta diversity based on Bray-Curtis index. ANOSIM test results: R = 0.141, P = 0.123, 999 permutations.
- S6.pdf
Figure S6. Shannon Index comparison between control mice and berberine treatment. The rarified 23,900 MiSeq dataset was used. Mann-Whitney test P = 0.309.
- SupplementaryDataset2RNASeqControlData.xlsx
- SupplementaryDataset3RNASeqBerberineData.xlsx
- SupplementaryDatasetCorrelationNetworks.xlsx
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