Interactions between Cryptosporidium parvum and the Intestinal Ecosystem Thesis by Olga Douvropoulou In Partial Fulfillment of the Requirements For the Degree of Master of Science King Abdullah University of Science and Technology Thuwal, Kingdom of Saudi Arabia April, 2017 2 EXAMINATION COMMITTEE PAGE The thesis of Olga Douvropoulou is approved by the examination committee. Committee Chairperson: Professor Arnab Pain Committee Co-Chair: Professor Giovanni Widmer Committee Members: Professor Takashi Gojobori, Professor Peiying Hong 3 © April, 2017 Olga Douvropoulou All Rights Reserved 4 ABSTRACT Interactions between Cryptosporidium parvum and the Intestinal Ecosystem Olga Douvropoulou Cryptosporidium parvum is an apicomplexan protozoan parasite commonly causing diarrhea, particularly in infants in developing countries. The research challenges faced in the development of therapies against Cryptosporidium slow down the process of drug discovery. However, advancement of knowledge towards the interactions of the intestinal ecosystem and the parasite could provide alternative approaches to tackle the disease. Under this perspective, the primary focus of this work was to study interactions between Cryptosporidium parvum and the intestinal ecosystem in a mouse model. Mice were treated with antibiotics with different activity spectra and the resulted perturbation of the native gut microbiota was identified by microbiome studies. In particular, 16S amplicon sequencing and Whole Genome Sequencing (WGS) were used to determine the bacterial composition and the genetic repertoire of the fecal microbial communities in the mouse gut. Following alteration of the microbial communities of mice by application of antibiotic treatment, Cryptosporidium parasites were propagated in mice with perturbed microbiota and the severity of the infection was quantified. This approach enabled the prediction of the functional capacity of the microbial communities in the mouse gut and led to the identification of bacterial taxa that positively or negatively correlate in abundance with Cryptosporidium proliferation. 5 ACKNOWLEDGEMENTS I would like to express my deepest gratitude to my committee chair, Prof Arnab Pain for giving me the chance to work on a project of particular interest to me and for his genuine and continuous interest in the progression of my research. Prof Pain has been a constant source of motivation, knowledge and guidance throughout my thesis. I am truly thankful to my secondary supervisor, Prof Giovanni Widmer for accepting me as a visiting student and supporting me to develop my skills in microbiome analysis. He showed great care in explaining new concepts to me and providing ideas on how to proceed with the research I was involved in. My appreciation also goes to Prof Gillian Beamer and Kevin Huynh for their assistance with my work in Dr Widmer’s lab. I would like to particularly thank Dr Fathia Ben Rached for her continuous support in all aspects, as well as Dr David Ngugi and Raeece Ghazzali for their insightful comments and valuable help in the Bioinformatic analysis part of the thesis as well as for conducting the WGS analysis. I am grateful to have been working together with Abhinay Ramaprasad, Dr Amit Subudhi, Christopher Beaudoin, Chongwei Bi, Dr Hifzur Ansari, Dr Malak Haidar, Qingtian Guan, Sharif Hala, Dr Tobias Mourier and Dr Zineb Rchiad in Prof Pain’s laboratory and I have really enjoyed spending time with them inside and outside of the lab. Special thanks to my committee members, Prof Takashi Gojobori and Prof Peiying Hong for taking their precious time to review this thesis. My great thanks go to KAUST which provided me with an ideal research environment. I would also like to express my gratitude to my friends and family for their encouragement and support in all aspects. 6 TABLE OF CONTENTS EXAMINATION COMMITTEE PAGE .............................................................. 2 COPYRIGHT PAGE .............................................................................................. 3 ABSTRACT .............................................................................................................. 4 ACKNOWLEDGEMENTS ................................................................................... 5 TABLE OF CONTENTS ........................................................................................ 6 LIST OF ABBREVIATIONS ................................................................................. 8 LIST OF ILLUSTRATIONS .................................................................................. 9 LIST OF TABLES ................................................................................................... 10 Chapter 1: Introduction ……………………………………………………….… 11 1.1 Cryptosporidium Background, Transmission and Life Cycle…………. 11 1.2 Current Challenges and Therapeutic Approaches to cryptosporidiosis... 14 1.3 Alternative Treatment Approaches based on Interactions between Cryptosporidium and the Gut Micro- Environment...................................... 15 1.4 Research Questions and Objectives......................................................... 20 1.5 Significance of the Study......................................................................... 21 Chapter 2: Experimental Design…………………………………….…………... 22 2.1 Animal Experiments………………………………...………………...... 22 2.2 Purification of Cryptosporidium parvum oocysts ………………........... 23 2.3 Cryptosporidium detection in feces….……………………………….... 25 2.3.1 Detection of Cryptosporidium parvum in fresh feces…………........... 25 2.3.2 Flow cytometric detection of Cryptosporidium parvum in overnight- collected feces.................................................................................................. 26 2.3.2.1 Flow cytometric Analysis (FCM) ...................................................... 28 2.4 Antibiotic Treatment................................................................................. 29 2.5 Fecal Microbiome Analysis…………………......……………………… 30 2.5.1 DNA extraction ………………………………………………………. 30 2.5.2 Library Preparation ………………………………..…….…………… 31 2.5.2.1 Preparation of Illumina 16S amplicon libraries…………………….. 31 2.5.2.2 Preparation of WGS libraries………………………………………. 33 2.5.3 Quality control of 16S rRNA gene amplicon sequences……...……… 34 2.5.4 Sequence Data Analysis………………………………………………. 34 2.5.5 Alpha and Beta Diversity…………………………………...…………. 37 Chapter 3: Results………………………………………...……………………. 39 3.1 Effect of bacitracin and vancomycin on oocyst output of mice infected with Cryptosporidium parvum………………………………...…………... 39 3.2 Influence of bacitracin and vancomycin on the gut microbial community composition of mice …………………………………...……. 42 3.3 Influence of bacitracin and vancomycin on the alpha diversity of the mouse fecal microbial communities ……………………….……………… 45 3.4 Influence of bacitracin and vancomycin on the beta diversity of the mouse fecal microbial communities ………………………………….…… 48 3.5 Differentially abundant bacterial taxa between mouse fecal microbial 7 communities of treated and control groups …………………….……….… 49 3.6 Influence of bacitracin and vancomycin on the functional potential of the mouse fecal microbial communities…………………………………… 50 Chapter 4: Discussion ……………………………………………………………. 61 4.1 Cross-Talk between Commensal Microorganisms and Cryptosporidium parvum………………………...…………………………………….……… 61 4.2 Modulation of oocyst output in mice infected with Cryptosporidium parvum according to antibiotic treatment………...………………………. 62 4.3 Analysis of the association between differentially abundant gut bacterial genera and species in treated or control groups of mice infected with Cryptosporidium parvum and the severity of cryptosporidiosis….…. 63 4.4 Analysis of the alpha and beta diversity metrics in treated or control groups of mice infected with Cryptosporidium parvum…………...……… 66 4.5 Impact of antibiotic treatment on the functional potential of the mouse fecal microbial communities……………………………………….……… 67 4.6 Concluding Remarks and Recommendations for Future Research……. 68 BIBLIOGRAPHY ………………………………………………………………… 70 SUPPLEMENTARY INFORMATION…………………………………………. 76 8 LIST OF ABBREVIATIONS ACE Abundance-based Coverage Estimator AIDS Acquired Immune Deficiency Syndrome AR Antibiotic Resistance BIOM Biological Observation Matrix BLAT Blast-Like Alignment Tool CARD Comprehensive Antibiotic Resistance Database CD-1 Cluster of differentiation 1 DEXp Dexamethasone-phosphate DNA Deoxyribonucleic acid FCM Flow cytometry FCS/PBS Fetal Calf Serum in Phosphate Buffered Saline FL1 Fluorescence detector 1 FSC Forward-side scatter g Grams IBEC Institutional Biosafety and Ethics Committee IgG Immunoglobulin G KAUST King Abdullah University of Science and Technology KEGG Kyoto Encyclopedia of Genes and Genomes Kg Kilogram Mb Mega base pairs MG-RAST MetaGenome Rapid Annotation using Subsystem Technology Platform ORF Open Reading Frame OTU Operational Taxonomic Unit PCA Principal component analysis PCR Polymerase Chain Reaction poly(I:C) Polyinosinic:polycytidylic acid QUAST Quality Assessment Tool RGI Resistance Gene Identifier Rpm Revolutions per minute rRNA Ribosomal ribonucleic acid SPAdes St. Petersburg genome assembler SOP Standard Operating Procedure 16S Svedberg units USA United States of America WGS Whole Genome Sequencing 9 LIST OF ILLUSTRATIONS Figure 1.1 Magnitude of Cryptosporidium’s effects on child mortality. Adapted by Kotloff, K. L. et al. Lancet 382, 209-222 (2013) ...........................................................................12 Figure 1.2