David Shen, MD, PhD
Division of Gastroenterology Perelman School of Medicine University of Pennsylvania
MICROBIOME PROGRAM
PennCHOP MICROBIOME PROGRAM Physiologic implications of - - PowerPoint PPT Presentation
PennCHOP MICROBIOME PROGRAM Physiologic implications of co-metabolism between the gut microbiome and its host David Shen, MD, PhD Division of Gastroenterology Perelman School of Medicine University of Pennsylvania Atherosclerosis
Division of Gastroenterology Perelman School of Medicine University of Pennsylvania
MICROBIOME PROGRAM
Liver is first portal that emerges from intestinal mucosal surface: Receives approximately 75% of blood supply from splanchnic circulation Potential liver diseases/processes affected by gut microbiome
Urea Bile Acids
Biotransformation and alteration of receptor- ligand interactions via FXR and TGR5 Hydrolysis into ammonia and its use by both the host and the gut microbiota as a source of nitrogen
Bile Salt Hydrolase (Deconjugation) 7α-Dehydroxylation
sensitive to the toxic effects of bile than Gram-negative bacteria (MacConkey agar contains bile)
multifactorial with membrane effects, DNA damage, oxidative stress, alterations in RNA structure, and protein denaturation
in bacteria that inhabit the intestinal tract of mammals, enhance colonization efficiency
Schaap FG, et al. Nat Rev Gastroenterol Hepatol. 2014;11:55-67.
Erlinger S. 2017
7α-Hydroxy-4-cholesten-3-one (C4): intermediate in the biochemical synthesis of bile acids from cholesterol
group):
Friedman, Li, Shen, et al. Gastroenterology 2018
Bacterial Taxonomic Associations with Bile Acid Synthesis-Specific Effects of Obeticholic Acid (10 mg/day): A general increase in Gram-positive bacteria and decrease in Gram-negative bacteria Plasma C4
Bacterial Taxonomic Associations with Bile Acid Synthesis-Specific Effects of Obeticholic Acid (10 mg/day): A general increase in Gram-positive bacteria and decrease in Gram-negative bacteria
Table 1: GEE model identified 15 species significantly associated with C4 change over time Phylum Species P value of C4 FDR of C4 OCA Response Gram Firmicutes Streptococcus_thermophilus 1.87e-07 2.30e-05 Increase pos Actinobacteria Bifidobacterium_breve 4.46e-04 0.023 Increase pos Firmicutes Streptococcus_salivarius 0.001 0.023 Decrease pos Firmicutes Lactobacillus_casei_paracasei 0.001 0.03 Increase pos Firmicutes Lachnospiraceae_bacterium_5_1_63FAA 0.001 0.03 Increase pos Bacteroidetes Alistipes_putredinis 0.003 0.053 Decrease neg Firmicutes Lactococcus_lactis 0.01 0.172 Increase pos Bacteroidetes Bacteroidales_bacterium_ph8 0.022 0.316 Decrease neg Firmicutes Subdoligranulum_unclassified 0.024 0.316 Equivocal pos Firmicutes Dorea_longicatena 0.026 0.316 Increase pos Actinobacteria Bifidobacterium_longum 0.03 0.316 Increase pos Firmicutes Dialister_invisus 0.031 0.316 Decrease pos Bacteroidetes Bacteroides_plebeius 0.037 0.347 Decrease neg Firmicutes Ruminococcus_obeum 0.045 0.389 Decrease pos Bacteroidetes Paraprevotella_unclassified 0.049 0.389 Decrease neg
(time effect FDR <0.05)
Uniref 90 Genomic Pathway Analysis
135 pathways with significant association with time
(Repeated Measure ANOVA, FDR <0.01)
* * *
Lactococcus lactis Streptococcus Thermophillus Lactobacillus casei/paracasei
Blue=Physiologically relevant concentrations in the human small intestine
GCDCA (uM) GCA (uM)
Physiologically-relevant concentration of OCA* in the human small intestine (1-40 mM**)
*Unconjugated OCA equivalents (i.e., summation of unconjugated OCA, glyco-OCA, and tauro-OCA) **Concentrations based on estimates of: calculation of OCA dose distributed in small intestine; simulated steady-state total OCA concentrations by physiological compartment for 10 mg OCA daily administration1.
1From Intercept Pharmaceuticals.
Dlugosz A. et al. Sci Rep. 2015;5:8508
Streptococcus spp. accounts for 19% of 454-pyrosequencing reads in the human small intestine
Pereira and Berry. Environ Microbiol 2017
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
P r
i ma l Sma l l I n t e st i n e ( P SI )
T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
T
a l p r
i ma l sma l l i n t e st i n a l
T
a l Bile Acids Endogenous Bile Acids Primary Bile Acids Secondary Bile Acids
Concentration (nM)
*** ** *** ** *** ** *
600,000 500,000 400,000 300,000 20 , 100,000
T
a l d i st a l sma l l i n t e st i n a l
20 , T
a l
T
a l f e c a l
2, T
a l
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
P r
i ma l Sma l l I n t e st i n e ( P SI )
T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP ! NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
T
a l p r
i ma l sma l l i n t e st i n a l
T
a l 20 ,
* ***
T
a l d i st a l sma l l i n t e st i n a l bile acid levels Concentration (nM)
600,000 500,000 400,000 300,000 20 , 100,000 T
a l Bile Acids Endogenous Bile Acids Primary Bile Acids Secondary Bile Acids
T
a l f e c a l
2, T
a l
OCA treatment inhibits endogenous luminal bile acid levels and leads to an increase in Gram-positive bacteria specifically in the small intestine of mice
*p<0.05 **p<0.01 ***p<0.001
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
P r
i ma l Sma l l I n t e st i n e ( P SI )
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 2 5 , n M
9 5NP 9 6NP NP 2NP 2R1 9 7 NP 9 8 NP 9 8 R1 9 9 NP
T
a l p r
i ma l sma l l i n t e st i n a l
T
a l 20 ,
T
a l d i st a l sma l l i n t e st i n a l
20 , T
a l
T
a l f e c a l bile acid levels Concentration (nmol/g stool)
6,000 5,000 4,000 3,000 2, 1,000 7,000 T
a l Bile Acids Endogenous Bile Acids Primary Bile Acids Secondary Bile Acids
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R 1 9 7 NP 9 8 NP 9 8 R 1 9 9 NP
P r
i ma l Sma l l I n t e st i n e ( P SI )
d T T T T 66NP 67 NP 63NP 65NP 9 3NP
> 25, n M
9 5NP 9 6NP NP 2NP 2R 1 9 7 NP 9 8 NP 9 8 R 1 9 9 NP
C MC OC
T
a l 20 ,
20 , T
a l
2, T
a l
Proximal SI Distal SI Feces Control Methylcellulose OCA
OCA treatment inhibits endogenous luminal bile acid levels and leads to an increase in Gram-positive bacteria specifically in the small intestine of mice
Control Methylcellulose OCA
A robust taxonomic signature for FXR activation in the human gut microbiome: An opportunity for precision medicine
leads to a significant induction of bile acid sensitive Gram-positive bacterial taxa in the human small intestine whose signature can be detected in the stool
effects of FXR agonists in humans and its association with diet—a glimpse into the dynamics of the human small intestinal microbiota
dynamic biomarker of FXR (OCA) function for precision medicine
intestine might provide novel opportunities to “engineer” the gut microbial composition
Urea CO2 + NH3
Urease
Urea Cycle
Amino Acid Pool Dietary Protein Intake
Renal Urea Excretion
The Gut Microbiome and Host Nitrogen Balance
15-30% 74% 18% 4%
Urea Cycle
Fate of NH3 from colonic urea hydrolysis: 1) Excreted in feces 2) Used by gut bacteria to synthesize amino acids, proteins, and other small molecules 3) Absorbed by host and utilized in liver for protein or urea synthesis
assembled in 1970s and standardized by NCI in 1978
commensal bacteria
inducing immune tolerance
Altered Schaedler’s Flora (ASF) Method of Host Preparation
A
Day post transfer
Germfree + ASF Prepared + ASF
B
Cho and Blaser. Nature Rev. Genet. 2012
ASF suppresses the return of Bacteroidetes
Day
ASF permits the selective return
Day
Fecal Urease Activity After Inoculation Fecal Ammonia Levels After Inoculation
*p<0.05, **p<0.001
Host Urea + H2O Ammonia + CO2
Bacterial Urease
Survival benefit of ASF in TAA model of hepatic injury
Control (no TAA) Prepared + Normal Microbiota (TAA) Prepared + ASF (TAA)
20 40 60 80 100
% Spontaneous alternation
ns
*
ASF improves performance in the Y-maze neurobehavior test
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 50 100
Time Post-FMT (wks) Percent survival Control (TAA) Prepared + ASF (TAA)
p < 0.05 Start of TAA Time Post-Transplantation (wks) *p<0.05, ANOVA p=0.04
properly prepared host reduces fecal urease activity and fecal ammonia production long-term and reduces morbidity and mortality in a murine model of liver disease
host with a defined gut microbiota can lead to durable metabolic changes with therapeutic utility
and impact on host physiology and metabolism
pathways carries therapeutic potential for diseases
Biomarker Therapeutics
Disease diagnosis/staging (e.g. liver disease) Drug response (e.g. OCA) Diet, prebiotics, probiotics, synbiotics Antimicrobials Microbial transfer (FMT, ASF) Drug targets Therapeutic modifications Host physiologic response Drug ADME
*Co-Principal Investigators
DNA sequencing, data analysis, and mathematical modeling Frederic D. Bushman, PhD (Penn) Hongzhe Li, PhD (Penn) Rob Knight, PhD (U of C, Boulder)
Patient/subject recruitment and phenotyping, dietary assessment, sample collection and processing *Gary D. Wu, MD (Penn) James D. Lewis, MD (Penn) Robert Baldassano, MD (CHOP)
Jun Chen, Sam Minot, Serena Dollive, Eric Chen, Meenakshi Bewtra, Christian Hoffmann, Ying-Yu Chen, Sue
Judith Kelsen, Colleen Judge, Christel Chehoud, David Shen, Rohini Sinha, David Metz, Tatiana Esipova, Susan Parrott, Elliot Friedman, Josie Ni, Sarah Smith, Lillian Chau, Andrew Lin
Gary L. Lichtenstein, MD (Penn) Charlene Compher, PhD, RD (Penn) Anthony Otley, MD (Dalhousie) Anne Griffiths, MD (Toronto) Metabolomics Michael Bennett, PhD (CHOP) Marc Yudkoff, MD (CHOP) Biological Oxymetry Sergei Vinogradov, PhD (Penn) Stephen Thom, MD (Univ. of Maryland)
MICROBIOME PROGRAM
PennCHOP
NIH K08 DK106457 AGA Microbiome Junior Investigator Research Award Center for Molecular Studies in Digestive and Liver Diseases (P30 DK050306) The Joint Penn-CHOP Center for Digestive, Liver, and Pancreatic Medicine