How Mycobiome/Bacteriome Work Together Personal Story!!!

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Cooperative Evolutionary Strategies: Personal Story!!! How Mycobiome/Bacteriome Work • In 1974 my PHD advisor handed me a paper showing that rabbits treated with antibiotics or anti-inflammatory steroids Together developed the fungal infection candidiasis • It made me realize that not only could fungi in the environment negatively impact our health, but fungal species also inhabit the mammalian body, alongside diverse commensal bacteria. • When one microbial community is knocked out, another can Mahmoud A Ghannoum, Ph.D., MBA, FIDSA cause illness. Professor and Director, Center for Medical Mycology, Case Western Reserve University • If the communities are undisturbed, however, the fungal Cleveland, OH inhabitants appear to be harmless or perhaps even beneficial. This realization happened 42 Years Ago!!!

Researching the Mycobiome • As of November 2015, only 269 of more than 6,000 Web of Science search results for the term “microbiome” even mention “fungus”

• The scientific search engine returns only 55 papers pertaining to the Opined: “mycobiome” - That future human microbiome studies should be expanded beyond bacteria to include fungi, viruses, and other microbes in the same samples. - Such studies will allow a better understanding of the role of these communities in health and disease Ghannoum & Mukherjee (2010). Microbe 5(11) The Scientist. 02.2016. 35

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The Human Mycobiome Time for a New Perspective Regarding the Role of Fungi in Health and Disease ORAL CAVITY LUNGS GASTRO- SKIN INTESTINAL • Historically, fungi were considered passive colonizers of the microbial community that could become pathogenic

• Alternaria • Candida • Aspergillus • Cryptococcus as the result of a change in the environment. • Aspergillus • Candida • Debaryomyces • Aureobasidium • Cladosporium • Aspergillus • Epidermophyton • Candida • Penicillium • Candida • Recent profiling of the “Mycobiome” is providing a new • Malassezia • Cladosporium • Cryptococcus • Cladosporium • Cryptococcus • Cryptococcus • Microsporum perspective showing that: • Fusarium • Fusarium • Rhodotorula • Gibberella • Penicillium • Trichophyton • Glomus • Pneumocystis • Aspergillus - Fungi have a complex, multifaceted role in • Pichia • Mucor • Chrysosporium • Saccharomyces • Saccharomyces • Epicoccum humans, and are active participants in directly • Teratosphaeria • Leptosphaerulina • Penicillium *Potentially pathogenic lineages • Phoma influencing health and disease. • Saccharomyces • Ustilago - Fungi cooperate with bacteria!! • Early surveys have revealed several pathogenic species that may increase one’s risk of disease when the healthy microbiome is disrupted. - It is not bacteria or fungi alone. They work together in • Candida and Aspergillus species are among the most common members of the the sandbox!!! human mycobiome. • When the balance of a microbial community is disrupted, fungal species can flourish and cause disease The Scientist. 02.2016. 37

Mycobiome and Crohn’s Disease (CD) • Dysbiosis of the intestinal flora plays a key role in modulating CD-associated inflammatory processes. • Until recently, the only study focusing on the mycobiome and CD was conducted by Illiev et al. Mycobiome: using a dextran sodium sulfate (DSS)-induced colitis mouse model showing: “A Tale of Two Partners” • The gut is colonized with 10 fungal species dominated by C. tropicalis (65%), A Tale of Two Cities addresses the fundamentally • Fungi and NOT bacteria is responsible for dual nature of humanity aggravating the severity and inflammation of CD

With apologies to Mr. Dickens Iliev, I. D. et al. Science 336, 1314–1317 (2012)

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Characterization of the Mycobiome and Bacteriome in Crohn’s PCA Clustering Analysis: Crohn’s (CD, Red), non-Crohn’s Patients and Healthy Relatives in Multiplex Families Relatives (NCR, Blue), and non-Crohn’s unrelated (NCU, Green) (A) Bacteriome (B) Mycobiome Subjects Demographics Clinical Details of CD Patients A1 (<=16 yr) 0 Variable CD NCRNCU Total Age Category A2 (17-40 yr) 8 Families 9 9 4 13 A3 (>= 40 yr) 12 L1 (Terminal Individuals 20 28 21 69 11 Ileum) Female 12 13 13 38 L2 (Colon) 2 Male 8 15 8 31 Location L3 (Ileum- 6 Age (mean, yrs) 44.5 48.4 41.3 45.1 Colon) L4 (Upper GI 0 Tract) CD – Crohn’s disease patients B1 3 NCR – Non-Crohn’s, Related individuals (Nonstenotic) NCU – Non-Crohn’s, Unrelated individuals Behavior B2 (Stenotic) 4 B3 12 (Penetrating) Disease Active 3 Status Remission 8

5/15/2017 Crohn's Disease Study (France)

Abundance of Bacterial and Fungal Phyla in Participants Richness of Microbiota

Bacteriome Mycobiome

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Abundance of Bacterial Taxa Abundance of Fungal Taxa

P ≤ .002 P ≤ .001 P = .007 Oscillospira Saccharomyces spp S. cerevisiae P = .0018 Prevotella

Candida spp. P = .034 Faecalibacterium C. tropicalis Faecalibacterium P = .025 prausnitzii P = .2 P = .01

Anti–Saccharomyces cerevisiae antibodies (ASCA) P = .001 Abundance of Candida spp. ASCA is widely used in diagnosis of Crohn’s P = .001 CD NCR P-value Species disease, and it is Mean SD Mean SD Candida tropicalis 10.41% 18.59% 1.01% 1.65% 0.005 detected in 50-60% of Candida glabrata 2.29% 10.23% 1.88% 10.80% 0.892 CD patients. Candida albicans 0.52% 1.36% 0.67% 2.03% 0.778 Candida parapsilosis 0.34% 1.39% 0.01% 0.03% 0.17 Candida tartarivorans 0.18% 0.81% 0.00% 0.00% 0.202 Candida dubliniensis 0.06% 0.29% 0.00% 0.02% 0.23 Candida temnochilae 0.06% 0.21% 0.05% 0.21% 0.864 • ASCA level in CD group was significantly higher than levels Candida zeylanoides 0.01% 0.04% 1.38% 7.83% 0.439 in both NCR and NCU groups. • No significant difference in ASCA level between the NCR and NCU groups (P > .05). • Importantly, ASCA level was correlated with abundance

5/15/2017 Crohn's Disease Study (France) of C. tropicalis.

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Fungal-Fungal Genera Correlations Significant Correlations of C. tropicalis with Bacterial Species in CD Patients

Bacterial Taxon Pearson Correlation P-value CD NCR Alkalimonas amylolytica .701 .001 Aquamonas haywardensis .743 .000 Enterobacter hormaechei .808 .000 Enterobacter ludwigii .725 .000 Enterobacter pyrinus .687 .001 Erwinia chrysanthemi .577 .008 Erwinia dispersa .733 .000 Erwinia soli .491 .028 Erwinia toletana .757 .000 Escherichia coli* .569 .009 Pantoea agglomerans .697 .001 Profftia tarda .575 .008 Serratia marcescens* .651 .002 - 13 Different bacterial species significantly correlated with C. tropicalis Number of genera = 28 Number of genera = 33 - * Significantly increased in CD patients Associations among fungal genera in: Red circles: negative associations, while blue circles positive associations.

Confocal Microscopy (A) CT (B) CT + EC Confocal Analysis

Side-view EC

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CT+SM Thickness (µm) Thickness (C) CT + SM (D) CT + EC + SM CT+EC

CT CT CT+EC CT+SM CT+EC+SM EC SM CT EC

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Increase in β-D-Glucan Production in Mixed Species Biofilm CT + EC

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Does Mixed Species Biofilm Impact Host mBio 7(5):e01250-16. doi:10.1128/mBio.01250-16. Immunity RESEARCH ARTICLE Microarray Analyses of Epithelial Cells Bacteriome and Mycobiome Interactions Underscore Microbial Dysbiosis in Familial Crohn’s Disease Exposed to CT, SM and EC Hoarau, G., Mukherjee, P., Gower-Rousseau, C., Hager, Chandra, J., Retuerto, M., Neut, C., Vermeire, S., • Caco-2 cells were exposed to organisms (CT, Clemente, J., Colombel, J.F., Fujioka, H., Poulain, D., Sendid, B., and Ghannoum, M. SM, EC) • RNA was isolated, analyzed by microarray (Affymetrix Core) • 71 pathways were significantly altered • 8 pathways (inflammation-related)

Microarray Results - Caco-2 exposed to Microbes

Production of nitric oxide and ROS TNFR1

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Red – increased, Green – decreased in Caco-2 cells Red – increased, Green – decreased in Caco-2 cells Microarray Results - Caco-2 exposed to Microarray Results - Caco-2 exposed to Microbes Microbes

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Autophagy Effect of Biofilm on Caco-2 Cells: In vitro Testing

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DSS Model using C57BL/6 Mice: in vivo Contribution of CT, EC and SM to the 0 3 -1 1 -1 6 0 3 -1 1 -1 6 8 0 0 p = 0.0250 4 0 0 0 pathogenesis of Crohn’s disease p = 0.0329

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L I (DSS) were added to the drinking water for 6 I 2 0 0 1 0 0 0 0 0 days; D S S D S S + C E S D S S D S S + C E S • Then mice were orally gavaged with CT, EC and SM for three times during DSS treatment. 0 3 -1 1 -1 6

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Fluorescent Microscopy of Distal Colon Sections IF N -y p g /m l IL -3 3

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*IL-33 interacts with the IL1RL1 and IL1RAP receptors to produce type 2 cytokines by way of activation of the NF-κB and MAP Kinase signaling pathways

Does Antifungal Treatment Make a Difference? in vivo DSS Model using Dectin1-/- Mice Metabolomic Analysis of Mixed Species IF N -y

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N 2 0 BF003 Medium M_03 T 0 BF004 C. tropicalis C_01 BF005 C. tropicalis C_02 Q 0 -5 0 0 0 O P S O I P Q O O P + P + I BF006 C. tropicalis C_03 S P P le O in O + + o t le in P z a P O BF007 E. coli E_01 l O o t a t e a P a n s l P z t g y c l a s e o i n l BF008 E. coli E_02 n c N h a y c u u e g o N i if l n c h t F V u lu e BF009 E. coli E_03 n if V A t F n BF010 S. marcescene S_01 A BF011 S. marcescene S_02 BF012 S. marcescene S_03 BF013 C. tropicalis + E. coli CE_01 BF014 C. tropicalis + E. coli CE_02 BF015 C. tropicalis + E. coli CE_03 BF016 C. tropicalis + S. marcescene CS_01 BF017 C. tropicalis + S. marcescene CS_02 BF018 C. tropicalis + S. marcescene CS_03 BF019 C. tropicalis + E. coli + S. marcescene CES_01 BF020 C. tropicalis + E. coli + S. marcescene CES_02 BF021 C. tropicalis + E. coli + S. marcescene CES_03

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Metabolite Profile PCA Loading Plot of Culture Medium

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OPLS-DA Analysis of CES vs Others Results of Analysis (High in CES)

Score Plot S-Plot High in CES Extracted 12 compounds (high in CES by OPLS-DA) from the list of all metabolites *p(corr)[1]>0.5, p[1]>0 P < 0.005, Student’s t-test

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100 E S 50 CE *p(corr)=y, Reproducibility CS *p[1]=x, Fold-changing 0 CES Compounds List P value (CES vs Others) * N-Acetylserine 1.60556E-06 3-Phenyllactic acid 3.0117E-06 * Threitol 3.83155E-06 5-Oxoproline 7.76024E-06

4-Hydroxyproline 6.97087E-05 Expansion Glutaric acid 7.58895E-05 Student’s t-test 2-Hydroxyisocaproic acid 0.000182724 Indol-3-acetic acid 0.004743121 P < 0.005 4-Hydroxyphenyllactic acid 0.091129605 *Derivatization during sample preparation Glyceraldehyde 0.283403873 Trimethylsilyl: 2TMS, 3TMS, 4TMS, 2TMS(2) 3-Hydroxyisobutyric acid 0.488709156 Methoxym: meto Dihydrouracil 0.828002993 (Please cut “TMS” and “meto” from the name when you check their functions.)

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Healthy Mycobiome and Bacteriome Fungal and Bacterial Interactions: A Proposed Model

Cooperative Evolution of Fungi and Bacteria: A Strategy that is beneficial to both • Microbial communities, in their yearning to survive within the host, developed cooperative evolutionary strategies that culminate in the creation of robust biofilms • Fungi: Gaining virulence factors (filamnetation, increased SAP secretion) thereby enhancing their ability to invade the host. • Bacteria: Develop antibacterial tolerance afforded by living under the protective Fungal matrix umbrella. • Microbe-induced production of mucolytic enzymes (lead to barrier dysfunction, Resulting in tissue damage and lesion formation). - Ruminococcus gnavus and C. albicans: produce mucolytic enzymes that can Degrade the protective mucin layer of the gut epithelium, contributing to lesion formation

• The Host: this interkingdom cooperation impacts the host immune system: - Under the influence of enteric pathogens and immunomodulatory components of fungal biofilms, levels of proinflammatory cytokines increase, causing oxidative damage and apoptotic cell death. “The Wild-Type”

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Collaborators • Center for Medical Mycology (Case , UH): Center for Medical Mycology: - Pranab Mukherjee • Inserm, Université Lille France: Boualem Sendid - Maurcio Retuerto Gautier Hoarau - Jyotsna Chandra Daniel Poulain - Chris Hager - Yan Sun Icahn School of Medicine • Division Gastroenterology & at Mount Sinai Jean-Frederic Colombel Liver Disease: - Fabio Cominelli - Theresa Pizarro - Alex Rodriguez

Funding: - NIH/NIDCR - INSERM - DDRCC: Pilot study