Gut Microbiome: Toxicant Perturbation and Stability Syed Hashsham - PowerPoint PPT Presentation

Gut Microbiome: Toxicant Perturbation and Stability Syed Hashsham Department of Civil and Environmental Engineering Center for Microbial Ecology Risk e-Learning Webinar Series The Interplay Between Environmental Exposures and Infectious Agents October 31, 2016 Superfund Research Program Environmental Microbial and Mammalian Biomolecular Responses to AhR Ligands

Outline A. Gut Microbiome • Background and Objective • Treg/Th17 system, TCDD, and SFB • Hypothesis and Experimental Details • Results B. Key Challenges Ahead • Communication channels • Predictive capabilities • Markers/Gut chips • Interventions C. Summary

Gut Microbiome: Diseases & Interventions DISEASES ORGANS Allergies Brain Asthma Mouth Host Anxiety Heart Autism Kidney Autoimmune Liver Cardiovascular Immune System Crohn ’ s Colon Depression Tissue IBD Muscle Gut Microbiome Mood Disorder Migraine INTERVENTIONS Commensals Multiple Sclerosis Fecal Transplant ENVRIONMENAL Keystone Species NAFLD Psychobiotics EXPOSURE Opportunistic Pathogens Obesity Pre- and Probiotics Toxicants Pathobionts Parkinson's Antibiotics Pathogens Spinal Cord Injury Food Habits Stroke CRISPR Type 2 Diabetes Phage

Objective: Characterize the effect of specific gut microbiome members on Treg/Th17 System with and without TCDD Treg/Th17 (Host) Segmented Filamentous Bacteria (SFB) 2,3,7,8-TCDD Bacteroides fragilis (Toxicant) (Key Gut Members)

With TCDD, AhR promotes Treg and suppresses Th17 Naïve T cells IL-6 IL-6 Th17 Treg aids in antimicrobial Th17 Treg modulates and response; abrogates ROR γ t also causes Foxp3 + autoimmune inflammation & disease autoimmune disease Aryl hydrocarbon Receptor (AhR) IL-17 IL-22 IL-10 2,3,7,8-TCDD

Why Segmented Filamentous Bacteria (SFB)? • Obligate symbiont • No genes for amino acids, vitamins/cofactors, nucleic acids • Extensive auxotroph • Host-specific SFB in humans? Candidatus Savagella | Environmental Microbiology 14 (6): 1462-2920 | 2012 2015 SFB cultivation is now possible using TC7 cell lines (BioTechniques, 59 (2):94–98, 2015 Dig Dis Sci. 60(10): 2953-62 SFB in patients by qPCR. Less in IBD constipated, and more in IBD diarrhea. 2013 Yin et al., ISME Journal 251 humans: majority colonized between ages 2 to 3 2013 Hans Jonsson 2009 Snel et al. Ivanov et al., Cell : 2009

Gut Clostridia B. fragilis Segmented Filamentous Bacteria (SFB) SFB Polysaccharide A Short Chain Fatty Acids Lamina propria Butyrate Dendritic cells Naïve T cells IL-6 IL-6 microRNAs Th17 Treg ROR γ t Foxp3 + Aryl Hydrocarbon Receptor (AhR) IL-21R IL-10 Nos2 IL-21 Host TCDD

Hypothesis TCDD exposure disrupts the Treg /Th17 system and specific gut microbial members are capable of preventing this disruption.

Two Possibilities! TCDD impacts the gut microbiome which then impacts host TCDD Clostridia B. fragilis SFB SCFA PSA TCDD impacts the host which then impacts the gut microbiome

Experimental Details C57BL6 Gnotobiotic Key measurements Traditional TCDD: 30 µ g/kg every 4 d TCDD: 0.01 to 30 µ g/kg every 4 d • mRNA expression of ileal 56 d study 30 d study immunology genes (nCounter: 4 per group 120 d study (90 d + 30 d recovery) 547 Immunology gene targets) 8 per group • T-cells in blood/spleen (Flow • GF cytometry) • SFB Cage separation • microRNA expression in ileum • B. fragilis • B. fragilis + SFB (nCounter: 600 mouse microRNAs) Tim Zacharewski ’ s Lab UM Germ-Free Facility Fecal pellets, ilium, cecum, blood • High Throughput (Wafergen) or qPCR Fecal pellets, cecum

Ileum Gnotobiotic C57BL6: Gene Expression With TCDD Compared to GF Up-regulation Up-regulation Down-regulation Down-regulation Compared to GF, SFB has With TCDD, SFB has more more Up-regulated genes. Down-regulated genes.

Spleen Gnotobiotic C57BL6: Treg p =0.35 Colonization cd36 TGF- β p<0.0001 TCDD 1400 TCDD 7000 Vehicle + T re g c e lls in s p le e n 2 5 1200 6000 Normalized count 1000 5000 2 0 800 4000 1 5 600 3000 % C D 4 400 2000 1 0 200 1000 G F B + S F B G F B B + S F B S F B B S F B 0 0 Vehicle TCDD GF Vehicle B B+SFB TCDD SFB Parametric two-way ANOVA

Gnotobiotic C57BL6: Th17 Spleen Ciita was similar! p = 0.0004 IL1- β Colonization 80 1600 + T h 1 7 c e lls in s p le e n Vehicle 2 .0 p = 0.0196 TCDD 70 1400 Normalized count Normalized count 1 .5 60 1200 TCDD 50 1000 1 .0 40 800 0 .5 30 600 % C D 4 20 400 0 .0 10 G F B S F B + B S F B G F B S F B + B S F B 200 0 0 Vehicle TCDD GF GF B B B+SFB B+SFB SFB SFB Parametric two-way ANOVA

Gnotobiotic C57BL6: B. fragilis and SFB B. fragilis SFB S F B 1 6 S rR N A g e n e c o p ie s p e r m g ile u m B . fra g ilis rp lB g e n e p e r m g c a e c u m 6 ´ 1 0 6 2 0 0 0 5 ´ 1 0 6 4 ´ 1 0 6 1 5 0 0 p=0.029 p=0.038 3 ´ 1 0 6 2 ´ 1 0 6 1 0 0 0 1 ´ 1 0 6 5 0 0 4 ´ 1 0 4 1 ´ 1 0 4 0 V e h T C D D V e h T C D D

Traditional C57BL6: Dose Response & Recovery Day 38 90 120

Overall Interaction of TCDD, B. fragilis , and SFB Decrease in Clostridia Gut B. fragilis Segmented Filamentous Bacteria (SFB) Increase in B. fragilis & SFB SFB Polysaccharide A Clostridia Butyrate Lamina propria Dendritic cells (Expected change in SFB (Expected change in B. was an INCREASE) fragilis & Clostridia was a Naïve DECREASE) T cells IL-6 IL-6 Th17 Treg ROR γ t Foxp3 + AhR IL-21R IL-10 Nos2 IL1- β Host TCDD TCDD

Traditional C57BL6: Increase in Antimicrobial Resistance Genes amphenicol : yidY 25 MDR : acrF, mdtE, acrR, tolC beta lactamase : ampC, blaCMY2 other : bacA 20 tetracycline : tet(32) sulfonamide : folA 15 Fold difference 10 5 0 0.3 1 3 10 30 RT-30 -5 µ g/kg TCDD (LS and RS groups)

B. Key Challenges Ahead Identity 1. Who is there? 2. Who is doing what and how? Activity 3. Can we predict gut behavior? Quantitatively? Prediction 4. How do we know when something is wrong? Diagnosis 5. How to stop or encourage key members? Intervention

2. Who is doing what and how? microRNA expression in SFB-associated mice is much greater than Germ-free or B. fragilis - associated groups! Ivanov et al., Cell : 2009 Spatial resolution More sensitive to work with 1-10 µl blood At all molecular levels MicroRNAs may alter the gut microbiota through fecal Ileum microRNAs, affecting growth and other cellular processes ( Liu et al., 2016 ).

3. Can we predict the gut behavior – quantitatively? MDSINE Perturbation Response Envelope Gut Disruption Index Time series Resistance: Biomass Maximum deviation VRE vs. E. faecium Perturbation from the pre- perturbed Halpin et al, Am. J. equilibrium Response Infection Control 44 Generalized Lota (2016) 830-6 Volterra Model Resilience: Inverse of time taken to return to equilibrium Trajectories Interactions Stability 1 Disease-specific Keystone-ness Time Bucci et al. Genome Biology Deterministic 17:121, 2016 Probabilistic Hashsham et al., Fernandez et al., AEM, 2000

4a. How do we know when something is wrong? Markers Carbohydrates Functions, Guilds Acetyl-CoA Functional Gene Diversity Butyrate producers Primer Coverage Roseburia intestinalis Faecalibacterium prausnitzii …. Butyryl-CoA Fish et al., Front. Microbiol. 4: 291 2013 Butyryl-CoA acetate transferase Butyrate kinase BUT BUK Vital et al., mBio, 2014 Butyrate

4b. How do we know when something is wrong? Gut Chips Illumina Amplification-based qPCR or Low- Hybridization-based Arrays High Throughput Sequencing density Chips HuMiChip (500 functional genes, 180,000 probes) Numerous but most Fluidigm (24 primer sets) HuGChip (66 families, 4000 probes) focused on 16S rRNA GULDA (Gut Low Density IBS/IBD Chip (300 bacteria, 54 probes) gene based Array): 31 targets

5. How to stop, encourage, or manage them?

Summary 1. TCDD and SFB/ B. fragilis interact through AhR in a predictable manner in terms of immune cell response. Such interactions may establish the basis for intervention. 2. Measuring smaller effects of toxicants on gut microbiome members through the host may be difficult. 3. Gut member activity, mode of communication with the host, quantitative predictive models, and markers of healthy/sick gut microbiome are some of the key challenges ahead in gut microbiome research.

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Acknowledgements Research Supported by National Institutes of Environmental Health Sciences (2P42ES004911) Co-PIs & Collaborators James Tiedje, Norb Kaminski, Tim Zacharewski, Gerben Zylstra, James Cole, Benli Chai, and Brad Upham Robert Stedtfeld, Maggie Williams, Robert Crawford, Tiffany Stedtfeld, Shao Xiangwen, Prianca Bhaduri, and Kelly Fader Gnotobiotic study was conducted at the University of Michigan ’ s Germ-Free facility with Dr. Kathryn Eaton. SFB source: Candidatus Arthromitus SFB-mouse-Japan was provided by Dr. Tomomi Kuwahara under MTA.