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BIOCHEMICAL IDENTIFICATION AND FUNCTIONAL CHARACTERIZATION OF MICRORNA-TARGET INTERACTIONS IN GROWTH CONTROL AND CANCER TRANSFORMATION HONG XIN (B.Sc (Hons.), NUS A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY INSTITUTE OF MOLECULAR AND CELL BIOLOGY NATIONAL UNIVERSITY OF SINGAPORE 2013 I DECLARATION I hereby declare that the thesis is my original work and it has been written by me in its entirety I have duly acknowledged all the sources of information which have been used in the thesis This thesis has also not been submitted for any degree in any university previously _ Hong Xin 4th March 2013 II ACKNOWLEDGEMENTS I am deeply grateful to my PhD mentor, Professor Stephen Michel Cohen, for his rigorous PhD training, great vision on science and directionality of projects His broad scope of scientific interests, inspiring ideas, critical thinking, deep penetrance of scientific investigations and many other outstanding scientific qualities have been so much beneficial throughout my PhD and will continuously be influential on my future career I would like to thank my thesis committee members, Professor Ng Huck Hui, Dr José R Dinneny, and Professor Toshie Kai for their valuable comments and constructive advice My sincere thanks to all the past and current members of the Cohen lab, especially Dr Thomas Sandman, Ms Lim Sing fee, Dr Jishy Varghese, Dr Chen Yawen, Dr Zhang Wei and Dr Ge Wanzhong for creating a nice working environment, providing numerous kind help whenever needed, and teaching me how to be a good scientists during daily communications I would like to express my heartfelt appreciation to my collaborators Dr Molly Hammell, Mr Nguyen Thanh Hung, Dr Zhang Rui, Dr Mathijs Voorhoeve, and Dr Hector Herranz Without them, my PhD projects would not be accomplished so smoothly Thanks also go to Dr Wang Songyu, Vinayaka, Na Chen, Dr Wang Xin Gang for the friendships Last but not least, I dedicated this thesis to my beloved wife JingJing, my parents, and my son Xavier and my daughter-to-be-born for their love, support, and encouragement throughout my PhD They have been always one huge motivation in my scientific career III TABLE OF CONTENT SUMMARY VI LIST OF TABLES VIII LIST OF FIGURES IX LIST OF SYMBOLS AND ABBREVIATIONS XI LIST OF PUBLICATIONS XII CHAPTER 1 INTRODUCTION 1 1.1 THE DISCOVERY OF ANIMAL MICRORNAS 1 1.2 MICRORNA BIOGENESIS 2 1.2.1 microRNA transcription 2 1.2.2 miRNA maturation 2 1.2.3 RISC effector loading 3 1.2.4 Argonaute proteins as RISC effectors 3 1.3 MECHANISMS OF MIRNA ACTION 4 1.3.1 Mechanism of miRNA action 4 1.3.2 Effects on target mRNA level 5 1.3.2.1 1.3.2.2 Direct mRNA cleavage Repression by mRNA destabilization 1.3.3 Effect on protein translation 7 1.4 IDENTIFICATION AND VALIDATION OF MIRNA TARGETS 8 1.4.1 Identification of miRNA targets 8 1.4.1.1 Computational prediction 1.4.1.2 Target identification based on genome-wide expression profiling 11 1.4.1.3 Biochemical purification of miRNP complex coupled to high throughput platforms 13 1.4.2 Experimental validation of microRNA targets 15 1.4.2.1 Target reporter assay in vitro and in vivo 15 1.4.2.2 Measuring target level in microRNA overexpressed and/or depleted cells 17 1.4.2.3 Genetic and functional interactions between a microRNA and its targets 18 1.5 GENETIC MANIPULATIONS OF MIRNA ACTIVITIES IN CELLS AND ORGANISMS 19 1.5.1 Genetic knockouts 19 1.5.2 Application of miRNA sponges 21 1.6 MIRNA DYSREGULATION IN CANCER CELLS 23 1.6.1 Genomic copy number alterations of miRNAs in cancer 24 1.6.2 Change in transcriptional regulations of miRNAs in cancer 25 1.6.3 miRNAs dysregulate many downstream signaling pathways critically involved in cancer initiation and progression 25 CHAPTER 2 MATERIALS AND METHODS 33 2.1 DROSOPHILAGENETICS 33 2.2 IMMUNOSTAINING 33 2.3 SDS-PAGE AND IMMUNOBLOT ANALYSIS 34 2.4 IMMUNOPURIFICATION OF MIRNP COMPLEX FROM DROSOPHILAS2 CELLS 34 2.5 UTR REPORTER CONSTRUCTS AND LUCIFERASE REPORTER ASSAYS 35 2.6 MIRNA AND MRNA QUANTITATIVE REAL TIME PCR 36 2.7 EXPRESSION PROFILING 37 2.8 MIRNA TARGET SITE PREDICTION 38 2.9 STATISTICAL ANALYSIS 39 2.10 MAMMALIAN CELL CULTURE 39 2.11 SOFT AGAR COLONY FORMATION ASSAY 40 2.12 CANCER PATIENT SURVIVAL ANALYSIS 40 IV CHAPTER 3 BIOCHEMICAL PURIFICATION OF MIRNA-‐RISC COMPLEX COUPLED TO HIGH-‐THROUGHPUT MICROARRAY PROFILING IDENTIFIES A DISTINCT SET OF MIRNA TARGETS IN DROSOPHILAS2 CELLS 41 3.1 INTRODUCTION 41 3.2 EXPERIMENTAL ASSESSMENT OF AN IMPROVED AGO1 IMMUNOPURIFICATION PROTOCOL 43 3.3 EXPRESSION PROFILING OF MRNAS ASSOCIATED WITH AGO1 IDENTIFIED HUNDREDS OF IP-ENRICHED TRANSCRIPTS 46 3.4 EXPERIMENTAL VALIDATION OF TARGET ENRICHMENT IN AGO1 IP 50 3.5 EXPERIMENTAL VALIDATION OF SELECTED MIR-184 TARGETS IDENTIFIED BY AGO1 IP 55 3.6 SEED TYPE ENRICHMENT OF THE TARGET SITES IN AGO1 IP-ENRICHED TRANSCRIPTS 60 3.7 OTHER CONTEXTUAL FEATURES ENRICHED IN AGO1 IP-ENRICHED TRANSCRIPTS 61 3.8 COMPARISON OF TARGETS IDENTIFIED BY AGO1 IP AND AGO1 DEPLETION 67 3.9 FUNCTIONAL CLUSTERING SUGGESTS DISTINCT BIOLOGICAL FUNCTIONS IN THE TWO TARGET GROUPS 78 3.10 GENOME-WIDE ANALYSIS SHOWS MIRNA TARGETS WITH DISTINCT STRUCTURAL AND MOLECULAR PROPERTIES 80 3.11 DISCUSSION 83 CHAPTER 4 FUNCTIONAL CHARACTERIZATION OF BANTAM-‐SOCS36E INTERACTION LEADS TO IDENTIFICATION OF SOCS PROTEIN FAMILIES AS ONCOGENIC COOPERATING FACTORS IN EGFR/RASV12-‐DRIVEN TUMORIGENESIS 86 4.1 INTRODUCTION 86 4.2 DEPLETION OF BANTAM BY MICRORNA SPONGE PRODUCES EGFR-LIKE PHENOTYPES 88 4.3 IDENTIFICATION OF SOCS36E AS A BANTAM TARGET 91 4.4 SOCS36E IS A NEGATIVE GROWTH REGULATOR 94 4.5 SOCS36E IS A NEGATIVE FEEDBACK REGULATOR OF EGFR SIGNALING 97 4.6 SOCS36E BEHAVES AS A TUMOR SUPPRESSOR UNDER CONDITIONS OF ELEVATED EGFR ACTIVITY 100 4.7 HUMAN SOCS5 BEHAVES AS A CANDIDATE TUMOR SUPPRESSOR IN AN EGFR/RASDEPENDENT CELLULAR TRANSFORMATION ASSAY 103 4.8 SOCS5 EXPRESSION IS DOWNREGULATED IN BREAST CANCER AND ASSOCIATED WITH METASTATIC-FREE SURVIVAL 106 4.9 DISCUSSION 110 CHAPTER 5 CONCLUSION AND FUTURE WORK 114 V SUMMARY microRNAs are a class of non-coding RNAs of 21 to 23 nucleotides in length They are endogenously expressed in the majority of eukaryotes MicroRNAs form proteinRNA complexes with the RNA-induced silencing complex (RISC) and bind to either 3’UTR or coding regions of messenger RNAs, causing destabilization of mRNA and/or inhibition of protein translation Animal microRNAs recognize their mRNA target via imperfect base pairing The 5’ position from 2-8nt, the so called “seed region”, is critical for microRNAs to repress their targets Each miRNA is predicted to regulate up to hundreds of genes and more than 65% of the animal genome could be potentially targeted by miRNAs miRNAs play important roles in diverse biological processes, including growth, differentiation, neurogenesis, apoptosis and metabolism Misregulation of miRNAs is correlated with various types of human pathologies including cancer and directly contribute to disease initiation and progression (representative reviews in (Iorio and Croce, 2012; Mendell and Olson, 2012; Rottiers and Naar, 2012)) My PhD project is focused on identification and functional characterizations of miRNA-target interactions involved in growth control and cancer transformation I used biochemical immunoprecipitation against Drosophila Ago1 (Ago1-IP) to isolate and purify Ago1/miRNA/mRNA complex and utilized microarray profiling to identify mRNAs enriched in Ago1-IP in Drosophila S2 cells Hundreds of potential miRNA targets associated with Ago1 in Drosophila S2 cells were identified by Ago1-IP Computational analysis using the IP-enriched target sets and Ago1 RNAi-upregulated target sets suggested the existence of two distinct sets of microRNA targets that exhibit substantial differences in molecular and structural properties My study further VI revealed a genome-wide correlation between binding site accessibility and the 3’UTR length of mRNA targets, suggesting an unprecedented complexity of miRNA-target interactions One target that I identified from the Ago1-IP is Socs36E, which contains a binding site for the growth regulatory microRNA, bantam Genetic and functional analysis suggested Socs36E is a negative growth regulator and contributes to bantam’s loss-offunction phenotype in the Drosophila wing Mechanistically, Socs36E negatively regulates EGFR activity while EGFR signaling also controls Socs36E expression, forming a negative feedback regulatory loop Socs36E acts as a “brake” to repress excessive EGFR signaling and when the “brake” is removed, EGFR overexpression leads to uncontrolled tumorous overgrowth and neoplastic transformation Using an in vitro cancer transformation model of primary human fibroblast cells, I further demonstrated one of the human orthologs of Socs36E, SOCS5, is a potential cooperating tumor suppressor of RasV12/EGF-driven cancer transformation SOCS5 is downregulated in breast cancer samples and associated with ErBB/ER/PR status Lower SOCS5 expression correlates with poorer metastatic-free survival in breast cancer patients, suggesting SOCS5 can be a potential biomarker with prognostic value Taken together, through characterization of miRNA-target interactions involved in developmental growth control, my collaborators and I have identified the SOCS protein family, as oncogenic cooperation factors of EGFR/Ras/MAPK- mediated cancer transformation in both Drosophila and human VII LIST OF TABLES Table 1 1 A comparison of different computational prediction programs 32 Table 3 1 List of microRNA seed families expressed in Drosoiphila S2 cells 50 Table 3 2 The non-‐redundant set of validated miRNA target pairs 54 Table 3 3 Predicted miR-‐184 targets enriched in Ago1 IP 58 Table 3 4 Summary of IP target validation 59 Table 3 5 Analysis of enrichment for stable hybridization binding energy, MFE, ΔGhybrid 64 Table 3 6 Analysis of enrichment for miRNA binding site openness for IP-‐enriched trascripts using non-‐IP enriched transcripts 64 Table 3 7 Analysis of enrichment for miRNA binding site openness for IP-‐enriched transcripts using all S2 cells transcripts as controls 65 Table 3 8 Analysis of miRNA binding site openness and flanking region openness in Ago1 IP-‐ enriched group 66 Table 3 9 Analysis of enrichment for stable hybridization binding energy (MFE) in Ago1 RNAi-‐ upregulated group 73 Table 3 10 Analysis of enrichment for miRNA binding site openness for Ago1 RNAi-‐upregulated transcripts as compared to all detectable S2 cell transcripts 76 Table 3 11 Analysis of miRNA binding site openness and flanking region openness in Ago1 RNAi upregulated group 78 Table 3 12 Gene ontology analysis of Ago1 IP-‐enriched transcripts and transcripts upregulated by Ago1 RNAi 79 Table 3 13 Genome-‐wide comparisons of upstream, downstream, and site openness (accessibility) of all predicted miRNA sites as a function of UTR length 83 Table 4 1 Listing of Log2 median-‐centered SOCS5 expression levels for each indicated dataset 110 VIII LIST OF FIGURES Figure 1 1 microRNA biogenesis and action 27 Figure 1 2 Argonaute domain organization 28 Figure 1 3 Ago/GW182 as effector complex in miRNA-‐mediated gene silencing 28 Figure 1 5 Schematic representation of ends-‐out gene targeting by homologous recombination 30 Figure 1 6 miRNA sponge design 31 Figure 1 7 The general workflow for small RNA sequencing by NGS platforms ERROR! BOOKMARK NOT DEFINED Figure 3 1 The general workflow of an improved Ago1 immunopurification protocol 45 Figure 3 2 A representative immunoblot of Ago1 IP on transgenic S2 cells expressing a Flag/HA epitope tagged Ago1 (+) or control S2 cells (-‐) 46 Figure 3 3 miRNAs and validated known targets are enriched in Ago1 immunopurified RNA complex 46 Figure 3 4 Number of transcripts enriched in Ago1 IP and the mean abundance of transcripts 48 Figure 3 5 Validation of selected IP-‐enriched genes by independent IP-‐Q-‐PCR 49 Figure 3 6 Comparison of IP results with experimentally validated miRNA targets 52 Figure 3 7 Effect of miR-‐184 depletion on the recovery of predicted mir-‐184 targets by IP 53 Figure 3 8 Effect of miR-‐184 depletion on the expression level of mir-‐184 targets for IP-‐enriched Vs non IP-‐enriched sets 56 Figure 3 9 Luciferase assay validation on selected IP-‐enriched mir-‐184 targets 57 Figure 3 10 miRNA target seed type enrichment analysis in Ago1 IP-‐enriched transcripts 61 Figure 3 11 Graphic representation of miRNA binding site openness and flanking region openness as shown in Table 3.8 67 Figure 3 12 A comparative analysis on Ago1 IP-‐enriched transcripts Vs Ago1 RNAi-‐upregulated transcripts 70 Figure 3 13 Comparison of seed type enrichment of targets identified by Ago1 IP and Ago1 depletion 71 Figure 3 14 Comparison of binding site energy of targets identified by Ago1 IP and Ago1 depletion 72 Figure 3 15 Differences in UTR length and miRNA site density distributions between Ago1 IP-‐ enriched group and Ago1 RNAi-‐upregulated group 74 IX Figure 3 16 Assessment of miRNA site openness, upstream openness and downstream openness for the Ago1 RNAi upregulated set vs all S2 RNAs with sites 75 Figure 3 17 Fold enrichment for the optimal upstream windows (35nt) and downstream windows (50nt) in IP-‐enriched and Ago1 RNAi upregulated sets 77 Figure 3 18 UTR length versus site density and structural openness in DrosophilamRNAs 82 Figure 4 1 bantam microRNA sponge design and validation 90 Figure 4 2 bantam depletion by microRNA sponge resembled the effect of EGFR depletion in the wing 91 Figure 4 3 Socs36E is a direct bantam target 93 Figure 4 4 bantam regulates Socs36E level in vivo 94 Figure 4 5 Socs36E mutant flies are slightly bigger in size 96 Figure 4 6 Socs36E is a negative growth regulator that genetically interacts with bantam 97 Figure 4 7 Socs36E represses EGFR/MAPK signaling 98 Figure 4 8 EGFR also regulates Socs36E expression, thus forming a negative feedback loop 99 Figure 4 9 Depletion of Socs36E in EGFR overexpressing wing discs caused dramatic tissue overgrown 102 Figure 4 10 Depletion of Soce36E in EGFR overexpressing wing lead to neoplastic transformation 103 Figure 4 11 Depletion of SOCS5 enhanced soft agar colony formation in primary human fibroblast cells 105 Figure 4 12 SOCS5 mutation rates and mRNA expression in cancer 108 Figure 4 13 SOCS5 expression is associated with metastatic-‐free survival in breast cancer patients 109 X allow a higher resolution of genome-wide target site identification and mapping Our S2 cell Ago1 IP-enriched target list could provide useful information for further functional validation of individual miRNA-target pairs using Drosophila genetics and biochemical tools In the second part of my thesis, I made use of the Ago1 IP-enriched target list to identify Socs36E as a functionally important bantam target involved in growth control I showed that bantam directly targets Socs36E by regulating its 3’UTR region and regulates Soc36E protein level in vivo Co-depletion of bantam and Socs36E partially rescued the reduction in wing size in bantam loss-of-function mutants, suggesting bantam-Socs36E interaction is important for tissue growth control We further demonstrated that Socs36E and EGFR form a negative feedback loop and Socs36E acts as a “brake” to repress excessive EGFR signaling The importance of this feedback control was demonstrated in the wing: once the “brake” is removed by Socs36E depletion, EGFR overexpression leads to uncontrolled tumorous overgrowth and neoplastic transformation We further uncovered the SOCS protein family as evolutionarily conserved oncogenic cooperating factors of EGFR/RasV12- mediated cancer transformation in both Drosophila and human One of the human orthologs of Socs36E, SOCS5, is a potential cooperating tumor suppressor of RasV12 -driven human cancer transformation The clinical relevance of SOCS5 in human cancer is demonstrated that SOCS5 is downregulated in breast cancer samples and associated with ErBB/ER/PR status Lower SOCS5 expression correlates with poor metastaticfree survival in breast cancer patients It might be interesting in the future to investigate whether other family members of SOCS proteins act in a similar manner to SOCS5 or they are functionally distinct If 115 there are well-annotated clinical samples available, it could be quite interesting to analyse whether SOCS5 level correlates with 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As shown in Fig 1.2, Ago are large proteins about 100kDa comprising a single variable N-terminal domain and three conserved C-terminal domains, including the PAZ, MID and PIWI domains (Vaucheret,
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