CHARACTERISATION, DIVERSITY AND EXPRESSION PATTERNS OF MUCIN AND MUCIN-LIKE GENES IN SEA ANEMONES

Alaa Abdulgader Haridi Bachelor of Biology, Master of Plant Protection

Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Earth, Environment and Biological Sciences

Science and Engineering Faculty

Queensland University of Technology

2018

Keywords

Actinia tenebrosa, Actinaria, Air exposure, Anthozoan, Aulactinia veratra, Cnidarians, De novo assembly, Gel-forming mucins, Glycoproteins, Mucus, Mucin, Mucin-like, Mucin gene diversity, Mucin genes expression, Mucin5B-like, Mucin1- like, Mucin4-like, quantitative real-time PCR, RNA-sequences, Sea anemone, Transcriptome, Transmembrane-mucins, Trefoil peptide

Characterisation, diversity and expression patterns of mucin and mucin-like genes in sea anemones i

Abstract

The waratah sea anemone, Actinia tenebrosa, inhabits the intertidal zone of

Australia and New Zealand. This environment exposes A. tenebrosa to a myriad of abiotic and biotic challenges including heat, desiccation and pathogenic microorganisms. Actinia tenebrosa is thought to respond to some abiotic and biotic challenges by producing a thick covering of protective mucus. The proteinaceous scaffold that supports this protective mucus covering, are mucin glycoproteins, which are encoded by a range of mucin genes. Earlier research into cnidarians generated explanations of the significance of mucus in cnidarian immunity, but little research has been undertaken to investigate the mucin gene repertoire of cnidarians and no studies have evaluated mucin gene expression patterns under environmental challenges. As a consequence, the first objective of this research project was to use RNA-sequencing,

De novo assembly and annotation to identify the mucin and mucin-like genes present in a range of cnidarian species. Using this approach, we were able to identify a range of gel-forming and transmembrane mucin genes in A. tenebrosa, including full-length mucins (mucin1-like and mucin4-like), as well as partial-length mucins (mucin5B- like, mucin6-like and mucin3A-like), a range of mucin-like genes, and mucin associated genes. The domain structure of the identified full-length mucin genes was found to be similar to that of the homologous genes in other species, and the majority of the mucin genes were found to be present in the other cnidarian species examined.

The second objective of this research was to investigate the expression of the mucin genes under an environmental challenge. Specifically, we examined genome wide patterns of gene expression in two intertidal sea anemones, Aulactinia veratra and A. tenebrosa under an aerial exposure treatment to test the hypothesis that mucin

Characterisation, diversity and expression patterns of mucin and mucin-like genes in sea anemones ii

genes will have significantly higher expression under this treatment. Mucin4-like and mucin5B-like were up-regulated in response to the three hours of aerial exposure in A. veratra, but none of the identified mucin genes were differentially expressed in A. tenebrosa. These findings indicate that mucin genes are not expressed in the same way in these two intertidal anemone species under aerial exposure treatments.

The results from this research demonstrate that there is a diverse repertoire of mucin genes in cnidarians and that the majority of these genes are widespread across this phylum. The expression patterns of these mucin genes were varied across the two test species and, in many cases, did not conform to our hypothesis, with the exception of mucin4-like and mucin5B-like in A. veratra. These findings establish a baseline from which future research can extend our understanding of mucin genes and proteins in phylum Cnidaria. The discovery of a diverse range of mucin genes in sea anemone species provided a basic reference for future mucin studies in cnidarians, but also could lead to research into their application in the pharmacological, clinical and cosmetic industries.

Characterisation, diversity and expression patterns of mucin and mucin-like genes in sea anemones iii

Table of Contents

Keywords ...... i Abstract ...... ii Table of Contents ...... iv List of Figures ...... vii List of Tables ...... x List of Abbreviations ...... xi Statement of Original Authorship ...... xii Acknowledgements ...... xiii Chapter 1: Introduction ...... 1 1.1 Background, knowledge gap and research problem ...... 1 1.2 Research aim ...... 2 1.3 Research objectives ...... 2 1.4 Research methods ...... 3 1.5 Research significance ...... 3 Chapter 2: Literature review ...... 5 2.1 Overview ...... 5 2.2 Mucus ...... 5 2.3 Mucin ...... 6 2.4 Actinia tenebrosa and Aulactinia veratra ...... 12 2.5 Conclusion ...... 15 Chapter 3: General methods ...... 19 3.1 Overview ...... 19 3.2 Sample collection and maintenance ...... 19 3.3 RNA isolation ...... 20 3.4 Library preparation, RNA-Sequencing and quality control ...... 20 3.5 Transcriptome assembly using the De Novo assembler and assessment...... 21 3.6 Transcriptome functional annotation and gene ontology ...... 21 3.7 Mucin and mucin-like candidate identification ...... 21 3.8 Read mapping and differential gene expression analysis ...... 22 3.9 Gene set enrichment analysis (GSEA) ...... 22 Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa ...... 23 4.1 Introduction ...... 24 4.2 Materials and methods ...... 25

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4.3 Results ...... 27 4.4 Discussion ...... 39 4.5 Conclusion ...... 42 Chapter 5: The expression of mucin-like genes using qRT-PCR ...... 43 5.1 Introduction ...... 43 5.2 Materials and methods ...... 44 5.3 Results ...... 46 5.4 Discussion ...... 47 Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA-sequencing ...... 51 6.1 Introduction ...... 52 6.2 Materials and methods ...... 53 6.3 Results ...... 54 6.4 Discussion ...... 62 6.5 Conclusion ...... 64 Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA-sequencing ...... 65 7.1 Introduction ...... 66 7.2 Materials and methods ...... 67 7.3 Results ...... 68 7.4 Discussion ...... 73 7.5 Conclusion ...... 74 Chapter 8: General discussion and conclusion ...... 75 8.1 Overview ...... 75 8.2 Summary of the results ...... 75 8.3 Significance of the results ...... 78 8.4 Research gaps and future direction ...... 79 8.5 Conclusion ...... 81 Chapter 9: Bibliography ...... 83 Appendices ...... 97 Appendix 1 | The table below shows the functional conserved MUC domains found in the structures of A. tenebrosa identified mucin1-like and mucin4-like, including the definition for each protein domain...... 97 appendix 2 | This table below shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like, mucin4-like and mucin- like from the red A. tenebrosa colourmorph...... 99 Appendix 3 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like, mucin4-like and mucin- like from the green A. tenebrosa colourmorph...... 100

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Appendix 4 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like and mucin4-like from the blue A. tenebrosa colourmorph...... 101 Appendix 5 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like and mucin4-like from the brown A. tenebrosa colourmorph...... 102 Appendix 6 | Domain structure organisations of the excluded partial identified mucin5B-like, mucin6-like and mucin3A-like from the red, green, blue and brown A. tenebrosa colourmorphs. A) Partial mucin5B-like structure representing the N-terminus domains; B) Partial mucin5B-like structure representing the C-terminus domains; C) Partial mucin6-like structure with lack of N and C terminuses; D) and E) Partial mucin3A-like structures with lack of N and C terminuses...... 103 Appendix 7 | This table shows mucin1-like information across cnidarian tested species, generated from blasting A. tenebrosa mucin1-like against cnidarian species. It was found that the A. tenebrosa mucin1-like presented as a full-length sequence in all cnidarian tested species, with differential in the identical percent, amino acid sequence length and presence of N terminus signal peptide and C terminus domains. The √ refers to presence, while × refers to absence...... 104 Appendix 8 | The following table shows mucin4-like information across cnidarian tested species, generated from blasting A. tenebrosa mucin4-like against cnidarian species. It was found that the A. tenebrosa mucin4-like presented as a full-length sequence in all cnidarian tested species, with differential in the identical percent, amino acid sequence length and presence of N terminus signal peptide and C terminus domain collections. The √ refers to presence, while × refers to absence...... 105 Appendix 9 | The table below shows the identified mucin-associated molecules (trefoils) from the four A. tenebrosa colourmorphs, including their blast hit results, their protein domains definitions and their availability in other cnidarian species, that are examined in this study. 107

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List of Figures

Figure 1 | The general structure for all mucins indicating the main regions; first, the distinctive terminal regions (N and C), and second, the large central region (PTS) ...... 8 Figure 2 | A) Actinia tenebrosa fully submerged at high tide, B) A. tenebrosa fully exposed at low tide and, C) The distribution of A. tenebrosa and Aulactinia veratra in Australia and New Zealand, D) A. veratra fully submerged at high tide (edited and reproduced from Muller, 2014)...... 12 Figure 3 | The figure shows the sea anemone A. veratra at low tide, A) An individual of A. veratra between colonies of A. tenebrosa (Image by PGL, 2014); B) A. veratra covered with coarse sand and shell grit (Image from Silva, 2013)...... 13 Figure 4 | A) The body plan of the model cnidarian, Hydra vulgaris B) the two germ layers of H. vulgaris, the ectoderm and endoderm; gland cells which produce mucus are coloured blue. (Image from Technau and Steele, 2011) ...... 14 Figure 5 | The figure shows the sea anemone species A. tenebrosa in four colourmorph. A) Green and brown A. tenebrosa at low tide; B) Blue A. tenebrosa fully submerged in water; C) Blue A. tenbebrosa at high tide and D) Red A. tenebrosa fully submerged in water (Images by PGL, 2014, 2015)...... 26 Figure 6 | WEGO plots show gene ontology classification in the whole set of red A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC...... 30 Figure 7 | WEGO plots show gene ontology classification in the whole set of green A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC...... 30 Figure 8 | WEGO plots show gene ontology classification in the whole set of blue A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC...... 31 Figure 9 | WEGO plots show gene ontology classification in the whole set of brown A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC...... 31 Figure 10 | The protein domain architectures of A. tenebrosa mucin1-like, mucin4-like and mucin-like candidates based on SMART visualisation. A) Mucin1-like shows the full protein structure of MUC1 including the N-terminus indicated by signal peptide, one SEA domain followed by transmembrane domain on the C-terminus. B, C, and D) Mucin4-like sequences show the domain structure of MUC4 which is indicated by the NIDO, AMOP and VWD domains, additional domains on the N-terminus presented in the N-terminus in

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sequence B, and additional single SEA domain presented in the C- terminus in sequence C. E and F) Mucin-like candidate structures were lacking in the complete collection of MUC4 domains (NIDO, AMOP and VWD) and so they identified only as mucin-like sequences. Varied numbers and sizes of low complexity regions presented among the candidate sequences...... 34 Figure 11 | The figure shows mucin1-like protein domain architectures from the tested cnidarian species based on SMART visualisation. The protein domain structures of MUC1, including a single SEA domain followed by a transmembrane domain on the C-terminus, presented in all tested cnidarian species. The N-terminus indicated by the signal peptide was absent in mucin1-like of some species. The number and size of the low complexity regions were varied among the mucin1-like of cnidarian species...... 37 Figure 12 | The figure shows protein domain architectures for mucin4-like genes across the tested cnidarian species based on SMART visualisation. The MUC4 domain structure, including NIDO, AMOP and VWD domains, were presented in the majority of species. A. tenebrosa mucin4-like additional domains in the N-terminus were presented only in mucin4-like of A. elegantissima, A. buddemeieri, A. pallida and O. faveolata, while, the additional single SEA domain in the C-terminus presented only in the C-terminus of A. elegantissima, N. annamensis and C. polypus. The N-terminus indicated by the signal peptide was absent in some sequences...... 38 Figure 13 | The protein domain architectures of the trefoil genes based on SMART visualisation ...... 39 Figure 14 | Agarose gel electrophorsis image of the PCR (annealing temperature 55-58⁰C) showing complete failure with no amplicons for any of the seven products. The gel was run with 1kb ladder from Bioline...... 46 Figure 15 | Agarose gel electrophorsis image of the PCR (annealing temperature 52⁰C) showing the seven primers amplified a product in this PCR reaction. Most primers amplified multiple products; In particular, primer set 1, 3, 4 and 7. The gel was run with 1kb ladder from Bioline...... 47 Figure 16 | Aulactinia veratra, water sample fully submerged in water (immersed as a control) and air sample (3 hours of exposure to air) ...... 53 Figure 17 | WEGO plots show gene ontology classification results for the whole set of A. veratra transcripts; they show the highest numbers of GO terms were under BP, followed by MF, and later CC ...... 55 Figure 18 | Hierarchically clustered heat map showing the RNA-sequence expression levels of 5686 differentially expressed contigs across the water and air samples based on (FC ≥2 and FDR of ≤ 0.001). The log2-transformed median-centred FPKM was the expression values. The up-regulation and down-regulation contigs are indicated by the yellow and purple colour intensities, respectively. The similarity of expression patterns across the samples is represented by the three

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levels of clustering as indicated by the blue, red and green coloured bars. These three levels correspond to the sub-clusters shown in Figure 19...... 57 Figure 19 | Cluster plots show the contigs with similar expression patterns across the two samples (air and water) resulting into three sub- clusters. The grey lines show the expression of the contigs, which was measured in log2-transformed median-centred FPKM, while the blue lines show the expression profile for each cluster...... 58 Figure 20 | The bars show over and under-represented genes among the three gene ontology categories in air and water samples based on FDR <0.01 ...... 59 Figure 21 | Actinia tenebrosa air sample (3 hours of air exposure), and water sample fully submerged in water (immersed as a control) ...... 67 Figure 22 | Actinia tenebrosa during a three-hour aerial exposure experiment. A) The species at the beginning of the exposure experiment with drawn tentacles and oral disc totally closed. B and C) The species during the first hours of exposure with the oral disc gradually opening; a thin layer of mucus was observed. D, E and F) show the species during the second hour, clearly indicating the amount of mucus and the open oral disc. G and H) An obvious amount of mucus covered the oral disc and surrounded the whole body...... 70 Figure 23 | Hierarchically clustered heat map showing the RNA-sequences expression levels of 1701 differentially expressed contigs across the water and air samples based on (FC ≥2 and FDR of ≤ 0.001). The log2-transformed median-centred FPKM was the expression values. The up-regulation and down-regulation contigs are indicated by the yellow and purple coloured intensities respectively. The similarity between contig expression patterns across the samples is represented by the two level of clustering indicated by green and red coloured bars; these two levels correspond to the sub-clusters shown in Figure 24...... 71 Figure 24 | Cluster plots show the contigs with similar expression patterns across the two samples (air and water), resulting in two sub-clusters. The grey lines show the contigs’ expression, which was measured in log2-transformed median-centred FPKM, while the blue lines show the expression profile for each cluster...... 72

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List of Tables

Table 1 | This table shows the controlled water conditions of the50L marine tanks, which reflects the natural conditions of the sea anemones...... 20 Table 2 | The assembly statistic metrics generated from the four A. tenebrosa transcriptomes...... 28 Table 3 | Total number of contigs that received BLASTx and BLASTp hits across the four A. tenebrosa colourmorphs ...... 29 Table 4 | List of full-length identified mucin and mucin-like candidates generated from the four A. tenebrosa colourmorph transcriptomes...... 32 Table 5 | Table shows the massive diversity of A. tenebrosa mucin1-like and mucin4-like candidates across cnidarian tested species. Mucin4-like shows higher presence across the species than mucin1-like ...... 36 Table 6 | List of seven primers designed to test the expression of mucin genes from A. veratra...... 45 Table 7 | Assembly statistics metrics generated from A. veratra transcriptomes (Air and water treatment reads were merged to a single file, then assembled) using Trinity de novo assembler...... 54 Table 8 | List of 28 over-represented genes generated from the aerial exposure sample based on (FDR<0.01), GO terms in bold refer to the ontologies enriched by mucin5B-like and mucin4-like...... 60 Table 9 | List of 7 under-represented genes generated from the aerial exposure sample based on (FDR<0.01) ...... 60 Table 10 | List of 42 over-represented genes generated from the water sample based on (FDR<0.01) ...... 61 Table 11 | List of 29 under-represented genes generated from the water sample based on (FDR<0.01) ...... 62 Table 12 | The assembly statistic metrics generated from A. tenebrosa transcriptomes (Air and water treatment reads were merged to a single file then assembled) using Trinity de novo assembler...... 68

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List of Abbreviations

RNA Ribo nucleic acid

mRNA Messenger RNA

NR Non-redundant

GO Gene ontology

ORF Open reading frame

SMART Simple modular architecture research tool

Pfam Protein families

BLAST Basic local alignment search tool

NCBI National centre of biotechnology information

QC Quality control/check

CEGMA Core eukaryotic genes mapping approach

DGE Different gene expression

VNTR Variable numbers of tandemly repeated

RSEM RNA-Seq by Expectation-Maximization

WEGO Web Gene Ontology Annotation Plot

GSEA Gene set enrichment analysis

FDR False discovery rate

CEGs Core eukaryotic genes

CC Cellular component

MF Molecular function

BP Biological process

CSR Cellular stress response

PGL Physiology Genomics Lab at QUT

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Statement of Original Authorship

The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

Signature: QUT verified signature

25/10/2018 Date: ______

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Acknowledgements

I would like to thank the following people for their support and encouragement during my research journey:

My supervisor, Dr Peter Prentis for his supervision, advice, guidance and patience.

The Physiological Genomics Lab group, for their help in completing the research experiments.

Karyn Gonano, for her help to improve my writing throughout my thesis.

My parents for their support and encouragement during my PhD journey.

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Chapter 1: Introduction

1.1 BACKGROUND, KNOWLEDGE GAP AND RESEARCH PROBLEM

Mucin gene products are a significant source of natural products used in the biomedical and cosmetic industries (Authimoolam and Dziubla, 2016; Aso et al., 2003; Kim, 2012). In fact, both of these industries encourage the search for new sources of mucin proteins with potential therapeutic or cosmetic applications. To date, despite a number of studies reporting the ubiquitous distribution of mucin protein encoding genes across metazoan taxa, little is known about the repertoire of mucin genes in cnidarians.

Genomic studies have indicated that cnidarians are an excellent alternative model to Drosophila and C. elegans for genomic research particularly that aimed at understanding the core Eumetazoa gene set (Yum et al., 2014; Putnam et al., 2007; Galliot and Schmid, 2003). This is largely attributed to the fact that cnidarian genomes are complex, with a core gene set, exon-intron structure and gene synteny more similar to those of vertebrates than some other models (Galliot and Schmid, 2003; Rabinowitz et al., 2016; Wood-Charlson and Weis, 2009; Miller et al., 2005; Technau et al., 2005). Cnidarian species can provide powerful insights into gene families in Eumetazoa, including the mucin gene family, which control the production and formation of mucus.

Actinia tenebrosa and other intertidal anemone species are suitable candidate species for the study of mucin genes in phylum Cnidaria because they are abundant along the Australian coastline. The majority of these species are also found with a thick covering of mucus at low tide. These species are thought to depend on mucus to protect themselves against pathogens, desiccation and other intertidal environmental challenges during periods of aerial exposure at low tide.

The role of this mucosal covering in intertidal anemones is currently unknown, but it is likely to be atleast superficially similar to that reported for other cnidarian species, including corals and the sea anemone, Nematostella vectensis and Bunodosoma caissarum. In coral, mucus has been hypothesised to help protect and

Chapter 1: Introduction 1

defend against pathogens and aid in feeding (Jatkar, 2009), whereas in N. vectensis and B. caissarum mucus is produced when the animal is stressed (Stefanik et al., 2013; Amado et al., 2011). To date, no studies we are aware of, have attempted to understand the diversity and distribution of mucins in cnidarian species, examined their domain structure to determine their similarity to previously identified mucins, or investigated the expression of mucin genes in response to stress. This is a large knowledge gap which we will examine in this thesis by identifying the mucin gene family, characterising their diversity in this phylum and investigating the effect of stress on mucin gene expression.

Research into the mucin gene diversity present in cnidarians, as well as understanding their diversity and expression, is key to expanding our understanding of the mucin gene family in eumetazoans.

1.2 RESEARCH AIM

The overall aim of this research project was to identity the mucin and mucin-like genes in cnidarian species, analyse their domain organisation and examine their expression in response to environmental stress in intertidal sea anemones.

1.3 RESEARCH OBJECTIVES

Therefore the specific objectives of this research project were to:

1. Sequence and assemble four sea anemone transcriptomes to identify and characterize the mucin and mucin-like genes present in these species; then to investigate their protein structures and diversity across other cnidarian species, in order to highlight the repertoire of the mucin gene family in cnidarians.

2. Examine the expression profile of mucin genes in Aulactinia veratra using quantitative real-time PCR in response to aerial stress.

3. Examine the expression profile of A. veratra mucin genes using RNA-sequencing in response to aerial exposure.

4. Examine the expression profile of A. tenebrosa mucin genes using RNA- sequencing in response to aerial exposure.

Chapter 1: Introduction 2

1.4 RESEARCH METHODS

To achieve the research aims and fill the knowledge gaps identified above, next generation sequencing techniques were selected as an appropriate approach. This technique enabled the research to be performed in faster way compared to traditional technologies. Research outcomes

The knowledge gap of this research was filled by achieving the four research objectives. From the first objective, the transmembrane and gel-forming mucins were identified in A. tenebrosa. The identified mucin protein domain organisation were similar to mucin sequences in other taxa. Mucins identified in Actinia tenebrosa were found to be present in a wide variety of other cnidarian species. In the second objective, mucin expression was examined, but the qPCR method was not well suited for this experiment.

From the third and fourth objectives, mucin expression was examined in two intertidal anemone species, A. tenebrosa and A. veratra. The results showed dissimilar patterns of mucin gene expression under the same experiment conditions across the two species. Mucin genes were differentially expressed in A. veratra, while no mucin genes were differentially expressed in A. tenebrosa.

1.5 RESEARCH SIGNIFICANCE

1. This research has characterised a range of mucin and mucin-like genes in cnidarians to establish a reference point for future research into the mucin gene family in cnidarians.

2. Investigating the response of mucin genes under aerial exposure in sea anemones has demonstrated that these genes are not expressed in the same way even for ecologically similar sea anemone species.

3. The identification of new mucin genes can be used to inform future research that aims to find and develop natural products from mucins for pharmacological, clinical and cosmetic applications.

Chapter 1: Introduction 3

0 4

Chapter 2: Literature review

2.1 OVERVIEW

Mucus is one of the first lines of defence in most metazoan taxa. It provides protection by creating a viscous colloid covering from the gel-forming characteristics of the mucin proteins it contains. This review of the literature illustrates background information about the mucus and its main component, mucin proteins. Important knowledge gaps about mucins in Cnidaria are highlighted. The review then focuses on the sea anemone species A. tenebrosa as an excellent cnidarian species for investigating the mucin genes in this phylum.

2.2 MUCUS

Mucus is a complex combination of secreted substances (Bythell and Wild, 2011) found in a wide variety of organisms, where it is used to coat moist surfaces both internally and externally (Bansil and Turner, 2006; Reddy, Trus and Nauwynck, 2017). Epithelial cells are the dominant cells that produce mucus (Koch et al., 2017). Mucus is a viscous colloid made up of a combination of water, antiseptic enzymes, proteins, inorganic salts, immunoglobins (Bansil and Turner, 2006), lipids, ions, glycoproteins and other exudates secreted by epithelial mucocytes (Bythell and Wild, 2011; Brown and Bythell, 2005; Karakoç et al., 2016). It is the mixture of components in mucus and in particular the mucin glycoproteins that enables mucus to provide a protective function (Pearson et al., 2011). This protective function includes providing a barrier against infectious agents like bacteria and viruses; protecting against desiccation, chemical enzymes, mechanical damage; and playing a protective role in wound healing (Stabili et al., 2014; Reddy, Trus and Nauwynck, 2017). The mucus glycoproteins are also responsible for the hydration and mucoadhesive properties of mucus (Bansil et al., 2013; Karakoç et al., 2016) and provide mucus with its viscoelasticity (Sperandio et al., 2013), and lubricity to protect and clean the epithelial surface (Bythell and Wild, 2011; Portal et al., 2017; Coppin et al., 2017). These glycoproteins are called mucins (Karakoç et al., 2016; Perez-Vilar and Mabolo, 2007). Despite mucin being an essential component of mucus, little is known about its protein

Chapter 2: Literature review 5

structure outside of vertebrates. In fact, we do not even know which mucin genes are present in most cnidarian species or their patterns of expression under periods of environmental stress.

The mucus in cnidarian species is thought to play an essential role in the biological processes of locomotion, structural support, navigation, heterotrophic feeding, protection against environmental stresses, preservation of tissue hydration, and defence against predators and pathogens (Stabili et al., 2015; Amado et al., 2011). Previous studies on the mucus of coral species have highlighted the differing functional roles of mucus, such as pathogen defence, feeding, protection against UV radiation and in protection against sedimentation (Jatkar et al., 2010; Bythell and Wild, 2011). In H. vulgaris the mucosal surface prevents contact between bacterial cells and the epithelial surface (Fraune et al., 2015), but studies like this in cnidarian species are uncommon and consequently our understanding of mucin diversity and the role of mucus in this phylum is limited. We address this research gap in this thesis by investigating and analysing the mucin and mucin-like genes present in A. tenebrosa, as well as those present in other species from this phylum.

2.3 Mucin

2.3.1 What is mucin? Mucins are a part of the glycoprotein family and the main proteinaceous component of mucus (Wang et al., 2017; Fahy and Dickey, 2010). Most mucins form a thick mucus layer, while others form a glycocalyx coating (Lang, 2007; Toribara et al., 1993), which is secreted by goblet cells (Sperandio et al., 2013) and/or mucosal gland cells (Gipson et al., 2014). To date, twenty-one mucin genes have been identified in humans and are usually referred to as MUC genes (Lee et al., 2016; Zaretsky and Wreschner, 2013). The current mucin classification is based on a global classification system developed by the scientific community, but there are a number of mucin groups classified as mucin-like. These mucin-like proteins have been difficult to classify, hence they were placed into a mucin-like group. Mucin classification largely takes into account the presence of a PTS domain to identify the mucin, but Rose and Voynow (2006) suggested that tandem repeats of this PTS should be taken into account when the gene is identified. For example, when a gene with PTS domain has no tandem

Chapter 2: Literature review 6

repeats, it should be defined as mucin-like. However, MUC14, MUC15 and MUC18, are already identified as mucin genes, although they consist of a PTS domain but have no tandem repeats (Meezaman et al., 1994). This uncertainty should be taken into account when identifying mucin genes and classifying them as mucin or mucin-like.

2.3.2 Mucin structure Mucins usually comprise a 15-20% polypeptide component and over 70% of carbohydrates, especially the o-linked glycans in mucus (Gendler et al., 1995; Offner and Troxler, 2000). A small ratio of N-glycan has also been identified in mucin proteins (Kaur et al., 2013; Yu et al., 2008; Asker et al., 1998). Each mucin glycoprotein has two distinctive regions; first is the amino- and carboxyl-terminus (N and C terminus) regions, and the second is the large central region (Figure 1). The amino- and carboxy-terminus regions are very sparsely o-glycosylated, but rich in cysteines. The central region of the mucin structure is characterised by amino acids which are rich in proline (P), threonine (T) and serine (S) residues (Ratcliffe, 2016; Arike and Hansson, 2016; Keeley and Mecham, 2013; Chakaborty et al., 2010; Lang 2007). These PTS residues are the hallmark of all mucin proteins (Xu et al., 2016; Chaturvedi et al., 2008) and are made up of more than 40% threonine and serine and about 5% proline residues (Arike and Hansson, 2016). These hallmark PTS residues are highly O-glycosylated, play an important functional role in forming defensive mucus gel (Arike and Hansson, 2016; Keeley and Mecham, 2013; Zaretsky and Wreschner, 2013), and are used to identify mucin protein sequences (Arike and Hansson, 2016; Corfield, 2014; Hansson, 2012). These domains are highly variable tandem repeat sequences and are sometimes also referred to as VNTR domains (Bythell and Wild, 2011; Ratcliffe, 2016; Arike and Hansson, 2016). As a result, mucin genes vary widely in the number of their PTS domains, their length, and the sequence of amino acids in these domains (Karakoç et al., 2016; Gendler and Spicer, 1995). The variation in PTS/VNTR domains across a mucin protein can make it difficult to use these domains to classify specific mucin types.

Chapter 2: Literature review 7

Figure 1 | The general structure for all mucins indicating the main regions; first, the distinctive terminal regions (N and C), and second, the large central region (PTS)

2.3.3 Mucin classification The most common molecular classification of mucin proteins is based on domain structures that can be used to categorize mucin proteins into two subgroups: secreted and membrane-bound mucins (Coppin et al., 2017; Desseyn et al., 2000).

The secreted mucins are divided into gel-forming mucins and non-oligomeric (soluble) mucins (Lee et al., 2016; Zaretsky and Wreschner, 2013; Corfield, 2014). The gel-forming mucins are the largest secreted group of mucins (Portal et al., 2017; Thornton and Sheehan, 2004; Thornton et al., 2008), are very large in size and form the protective gel layer, which aids in epithelial surface protection (Kesimer et al., 2009). The composition of gel-forming mucins includes MUC2, MUC5AC, MUC5B, MUC6, and MUC19. The non-oligomeric mucins comprise MUC7 and MUC9, which are soluble (Lee et al., 2016). The domain architecture of gel-forming mucins contains a signal peptide on the N-terminus, cysteine-rich von Willebrand factor type D (VWD) and type C (VWC) domains, and a central PTS/VNTR domain (Lang, 2007). The C- terminus of gel-forming mucins includes other cysteine-rich domains and the cysteine knot domain (Zaretsky and Wreschner, 2013). The number of the cysteine-rich domains varies among the gel-forming mucins (Zaretsky and Wreschner, 2013).

The transmembrane-bound mucins (Lang et al., 2007) comprise MUC1, MUC3A, MUC3B, MUC11, MUC12, MUC13, MUC14, MUC15, MUC16, MUC17, MUC18, MUC20 and MUC21 (Zaretsky and Wreschner, 2013). Based on the classification of Arike and Hansson, 2016, transmembrane-mucin types can be grouped into a SEA transmembrane-mucin group, which have a SEA domain, and a NIDO-AMOP-VWD transmembrane-mucin group. The SEA group includes: MUC1, MUC3A, MUC3B, MUC12, MUC13, MUC16 and MUC17, while the NIDO-AMOP-

Chapter 2: Literature review 8

VWD group includes only MUC4. The domain architecture of transmembrane mucins contains a signal peptide on the N-terminus and a central PTS/VNTR domain (Lang, 2007). The C-terminus of all transmembrane mucins, with the exception of MUC4, contains a sea urchin sperm protein enterokinase agrin (SEA) domain, epidermal growth factor-like domains, a transmembrane domain, and a cytoplasmic tail (Lang, 2007; Zaretsky and Wreschner, 2013). Some of the transmembrane mucins such as MUC16 include more than one SEA domain. The majority of transmembrane mucins also include one or more EGF domains, except MUC1 and MUC16 (Lang, 2007; Zaretsky and Wreschner, 2013). The C-terminus of MUC4 contains a nidogen-like domain (NIDO), an adhesion-associated domain (AMOP), and VWD domains (Van- Putten and Strijbis, 2017).

2.3.4 Mucin associated molecules Early studies that investigated the production and secretion of mucus, identified mucin as the major proteinaceous component of mucus with less than one percent being comprised of other proteins. These associated proteins include an essential protein in the biosynthesis and packaging of mucin called the trefoil peptide (Wang et al., 2012). The trefoil peptide is a protein family consisting of several proteins with similar functions (Sands and Podolsky, 1996), known as TFF1, TFF2, and TFF3 or as integumentary mucins type C.1, A.1 and B.1. Trefoil proteins are produced by goblet cells (Ogata and Podolsky, 1997) and increase the viscosity of mucus (Wright, 1997). Often trefoil proteins are co-expressed with mucin genes (Lang et al., 2004; Sasaki et al., 2007; Thornton et al., 2008). For example, TFF1 is expressed with MUC5AC, and TFF2 is expressed with MUC6 (Aamann et al., 2014). Overall, this trefoil family are similar to the mucins in terms of secretion, stimulation response within the cell (Gouyer et al., 2011), mucosal protection, healing (Taupin and Podolsky, 2003), and repair (Aamann et al., 2014). In cnidarians, the integumentary mucin type C.1 was found to be up-regulated in Acropora corals during development stages where it is found as a component of extra cellular matrix proteins (Hemond et al., 2014). In Acropora millepora the trefoil protein was also highly up-regulated during development particularly at the post-settlement stage (Hayward et al., 2011). Little else is known about the expression of integumentary mucins in cnidarian species.

Chapter 2: Literature review 9

2.3.5 The significance and function of mucins Mucins play roles in a number of important biological functions. Their general structure and biochemical properties protect cell surfaces, and their specific molecular structures regulate the local molecular microenvironment near the cell surface (Hollingsworth et al., 2004). The specific molecular composition and higher-order structures of mucins contribute to the secretion of hydrochloric acid (HCl) from gastric glands while protecting the epithelium from acid in the stomach. Mucins can also relay information about the condition of the external environment to epithelial cells through signal transduction, which occurs via membrane-associated mucins (Chambers et al., 1994). Thus, mucins can also serve as cell-surface receptors, transmitting signals in response to external stimuli that then lead to coordinated cellular responses (Hollingsworth et al., 2004). They can act as ligands for adhesion molecules, growth factors, lectins, chemokines and cytokines (Fong et al., 2000). Mucins can bind water and thus determine the state of hydration in an individual organism. Additionally, they act as a protective barrier; block the passage of bacteria, large molecules and other infectious organisms (Pelaseyed et al., 2014). Mucins have negatively charged oligosaccharides and so can retain positively charged particles when required (Becher et al., 2009). Mucins also play roles in several other biological functions, including the regulation of gene expression, cell proliferation, cell differentiation, embryogenesis, immunity and apoptosis. Mucins also play a role in carcinogenesis (Becher et al., 2009) and they are involved in the innate immune system (Møller et al., 2017; Bryne et al., 1995). Consequently, it can be seen that mucins are multifunctional proteins and likely undertake multiple roles in cnidarian species.

2.3.6 The evolution of mucin genes in phylum Cnidaria The evolutionary history of mucin genes across vertebrate and invertebrate species indicates that gel-forming mucins probably evolved earlier than transmembrane-mucins (Zaretsky and Wreschner, 2013). Research in cnidarians has shown that at least a single gel-forming mucin exists in many cnidarian species, including N. vectensis (Lang et al., 2007), the jellyfish Aurelia aurita (Uzawa et al., 2009), the coral A. digitifera (Takeuchi et al., 2016) and another anemone species Calliactis polypus (Stewart et al., 2017). The limited presence of mucin genes in cnidarians may represent gene loss, or may be the result of limited investigation of this

Chapter 2: Literature review 10

group and may not be representative of the mucin genes present in this phylum. Therefore, to determine the diversity of mucin genes present in cnidarians and their distribution across other cnidarian species, further studies are required, like those proposed here on the sea anemone species Actinia tenebrosa and Aulactinia veratra.

2.3.7 Sources and applications of mucin proteins The physical and structural properties of the mucin glycoproteins make their application potentially useful in a range of industries. In the medical industry, mucins can have applied uses as diagnostic markers (Rachagani et al., 2009). In the pharmaceutical industry, mucins have potential applications as drug delivery systems, because they are natural barriers to drug delivery and reduce drug permeation (Authimoolam and Dziubla, 2016). The adhesive property of mucins can be utilised in drug delivery systems, such as in the design of encapsulated microspheres, or in nanoparticle-based delivery systems (Authimoolam and Dziubla, 2016). Due to the adhesive properties of mucin, these proteins can have applications in the immobilization of nanomaterials or change the manner of particulate transfer (Ensign et al., 2012; Lai et al., 2009). Mucin encapsulation can be used to increase the residence time of drugs in the gastrointestinal tract. For example, if the use of mucoadhesive polymers, such as poly vinyl pyrrolidine, carboxymethyl cellulose or chitosan, in conjunction with mucin increases the residence time of drugs and this can enhance the chance of drug absorption (Larhed et al., 1998; Larhed et al., 1997; Patil and Sawant, 2008).

Marine organisms are known to be natural sources of mucin proteins. In other organisms where mucin is present, for instance the snail, the mucins have been used as an effective moisturiser in the cosmetic industry. In other cases the mucin has been used in creating effective wound healing agents (Adikwu and Alozie, 2007), as antibaterial agents, and as an insulin absorbing enhancer (Kim, 2012). Mucins from other marine species may also have interesting applications but more research needs to examine the diversity of mucin proteins in these organisms. Recently, it has been reported that qniumucin from jellyfish A. aurita is a more effective moisturiser than hyaluronic acid (Kim, 2012). Recent research by Stabili et al., (2015) on the sea anemone A. equina, indicated that its mucus has significant amounts of pharmaceutical and bioactive compounds. The mucus of other anemones has only been examined

Chapter 2: Literature review 11

superficially; therefore, investigating the diversity of mucin glycoproteins in intertidal sea anemones may identify mucins with applications in the pharmacological, clinical and cosmetic industries.

2.4 ACTINIA TENEBROSA AND AULACTINIA VERATRA

2.4.1 Taxonomy, habitat and distribution Actinia tenebrosa and Aulactinia veratra are common species of sea anemone species known as the waratah anemone and green shore anemone, respectively (Farquhar, 1898; Silva, 2013). These species belong to phylum Cnidaria, within class Anthozoa and order Actinaria (Loh, 2011; Silva, 2013). Both species are native to Australian and New Zealand coasts (Loh, 2011; Ottaway, 1979; Silva, 2013; Edmands and Fautin, 1991) and are found in the intertidal zone attached to rocky or other hard substrates (Loh, 2011; Silva, 2013) ( Figure 2). In the intertidal zone, Aulactinia veratra can be found as individuals among colonies of Actinia tenebrosa (Figure 3/A), but Aulactinia veratra is also found to be covered with coarse sand and shell grit (Figure 3/B) (Silva, 2013). Actinia tenebrosa and Aulactinia veratra occur in the mid intertidal zone and are exposed to air during the tidal cycle. To cope with this periodic exposure they produce large quantities of mucus as an external covering.

Figure 2 | A) Actinia tenebrosa fully submerged at high tide, B) A. tenebrosa fully exposed at low tide and, C) The distribution of A. tenebrosa and Aulactinia veratra in Australia and New Zealand, D) A. veratra fully submerged at high tide (edited and reproduced from Muller, 2014).

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Figure 3 | The figure shows the sea anemone A. veratra at low tide, A) An individual of A. veratra between colonies of A. tenebrosa (Image by PGL, 2014); B) A. veratra covered with coarse sand and shell grit (Image from Silva, 2013).

2.4.2 Morphology, physiology and reproduction behaviour Sea anemones are radially symmetrical animals, with tissues that develop from two germ layers, an inner endoderm and an outer ectoderm that are separated by a mesoglea (a jelly-like non-cellular matrix) (Figure 3; Frazao et al., 2012). The body of both species are shaped like a tubular column that is bright red to brown through to green in colour for Actinia tenebrosa, commonly green for Aulactinia veratra, and is similar to other sea anemone species from the same genus, such as Actinia equina (Haylor et al., 1984). A. tenebrosa ranges in size from 1.5 to 10 cm in length and from 1 to 5 cm in diameter on average (Loh, 2011), while A. veratra size up to 6 cm in length. This species is viviparous, brooding its young internally, where they are protected from digestive enzymes by a thick mucosal covering (Berry and Corfield,

Chapter 2: Literature review 13

2014). Reproduction in this species is both sexual and asexual (Voynow and Rubin, 2009; Silva, 2013). Studies have suggested that mucus plays a role in cnidarian communication, and our lab has preliminary evidence that mucus-associated chemicals are involved in intraspecific aggressive behaviours of A. tenebrosa (Pavasovic and Prentis, unpublished data). The secreted proteins involved in cnidarian communication are unlikely to involve mucin proteins directly, but this has yet to be examined in detail.

Figure 4 | A) The body plan of the model cnidarian, Hydra vulgaris B) the two germ layers of H. vulgaris, the ectoderm and endoderm; gland cells which produce mucus are coloured blue. (Image from Technau and Steele, 2011)

2.4.3 Immune system The immune system of cnidarians is similar to that of other invertebrate species, and consists of an innate immune system only (Jatkar, 2009). Cnidarian species depend on mucus secretion as a part of this immune system (Rosa et al., 2016). Antimicrobial peptides that are a component of mucus secretions (Otero-Gonzalez et al., 2010), pattern recognition receptors and the glycocalyx work together as a physicochemical barrier to microorganisms. In cnidarians, particularly order Actiniaria, the mucus is also known to possess cytotoxic and hemolytic activity (Stabili et al., 2015), which helps sea anemones protect from microbial pathogens (Clare, 1995). The mucus of both species examined here has not been examined in detail; nor have the mucin genes of this species.

Chapter 2: Literature review 14

2.4.4 Molecular techniques used in gene family evolution Research aimed at unederstanding the diversity of mucin and mucin-like genes in sea anemones has lagged, because genomic resources are not developed for most cnidarian species. Next generation sequencing platforms such as Illumina and Ion Torrent have recently been used to rapidly characterise transcriptome sequences from a number of non-model organisms (Chiara et al., 2013; Li et al., 2013; Hook et al., 2014; Schunter et al., 2014). These massive datasets allow precise and accurate de novo assembly and annotation of transcriptomes. Analysis of high quality transcriptome datasets derived from Illumina reads have shown that the evolution of new genes occurs primarily through gene duplication and can lead to large increases in gene copy number in specific lineages. In molluscs, for example, this has been observed in Crassostrea gigas, where tyrosinase genes have been extensively duplicated (26 copies) when compared to Homo sapiens (2 copies) and Caenorhabditis elegans (1 copy) (Zhang et al., 2012). While some lineage specific expansions appear random, many also seem to have an adaptive basis. More research is required, however, to determine the diversity and of the mucin gene family in cnidarians.

2.5 CONCLUSION

Previous cnidarian studies on gene family evolution have investigated different genes, but none of have included mucins. Mucins are a family of high-molecular weight, heavily glycosylated proteins produced by epithelial tissues in most metazoan organisms. These proteins contain many clustered oligosaccharides linked to tandem repeat peptide domains of threonine, serine and proline. In fact, the genes that encode these mucin proteins are poorly understood outside of vertebrates. In particular, we know little about the diversity, domain structure or expression of mucin genes in cnidarian species. The role of mucins is well understood in a number of vertebrates, but in cnidarians and particularly in sea anemones their role is still obscure. To date, no studies have used molecular approaches to look at this gene in cnidarians. In intertidal sea anemone species regularly exposed to several environment stresses during low tide mucin production could be induced by gene expression changes. Therefore, understanding this responses will provide a useful insight into how these

Chapter 2: Literature review 15

organisms tolerate stress which is currently unknown. The sea anemones Actinia tenebrosa and Aulactinia veratra are particularly suitable candidates for the study of mucin and mucin-like genes because these species are abundant along the Australian coastline, and are easily recognised and collected. In addition, studies on mucins in this two species have not yet been undertaken. In this thesis, the aim is to characterize the spectrum of mucin and mucin-like genes in A. tenebrosa, describe their structure and diversity across other cnidarians, as well as examine their expression profile in response to aerial exposure in both A. tenebrosa and A. veratra. This research will characterise the diversity of mucin and mucin-like genes in sea anemones to establish a background information for future mucin research in cnidarians or other metazoans.

Chapter 2: Literature review 16

Chapter 2: Literature review 17

Chapter 3: General methods

3.1 OVERVIEW

To identify mucins and other genes involved in mucus production in A. tenebrosa, we generated multiple transcriptomes using next generation sequencing and de novo transcriptome assembly methods. Thw datasets were then investigated and potential mucin transcript sequences were identified. The expression patterns of the identified mucin genes were interrogated using the widely adopted RNA-sequencing technology (Hafner et al., 2008) following an aerial exposure treatment. RNA- sequencing technology presented as the optimal method to analyse the expression of the target genes in this research, as the qRT-PCR method failed to work in this study system. Mucin sequence structures were analysed and the diversity of mucin genes across cnidarians was examined in detail.

3.2 SAMPLE COLLECTION AND MAINTENANCE

The sea anemone species investigated in this research were collected during low tide from Point Cartwright, Queensland, Australia (26°32'9.83"S, 153° 5'45.12"E). Each individual sea anemone was collected by gently removing the base from the substrate surface, and then stored individually in 50ml plastic containers filled with seawater and transported to the marine laboratory at the Queensland University of Technology. In this facility, they were housed in 50L aquarium glass tanks under controlled conditions that reflected their natural environment (Table1). To maintain the species, water quality was checked daily using a Multi 3430 IDS multi-parameter portable probe and chemical kit. Animals were fed with prawn once a week, but this was suspended > 48hrs before aerial exposure experiments commenced. Sea anemone species were maintained for 1 to 2 weeks, as an acclimation period before the experiments were taken.

Chapter 3: General methods 19

Table 1 | This table shows the controlled water conditions of the50L marine tanks, which reflects the natural conditions of the sea anemones.

Condition Range

Temperature (⁰C) 20 – 25

Salinity (ppt) 34 – 38

PH 8.0 – 8.5

Ammonia/Ammonium (mg/L) 0 – 0.075

Nitrate (mg/L) 0 – 5.0

3.3 RNA ISOLATION

Individual live sea anemones were frozen in liquid nitrogen and stored at −80°C until RNA extraction. The individuals were then homogenised in liquid nitrogen and total RNA was extracted from the whole organisms using a Trizol/chloroform RNA extraction protocol (van der Burg et al., 2016). RNA quality and integrity were tested using a bioanalyzer 2100 RNA nano chip following the protocol of Stewart et al., (2017).

3.4 LIBRARY PREPARATION, RNA-SEQUENCING AND QUALITY CONTROL

One library preparation was undertaken using an Illumina True-Seq stranded mRNA sample preparation kit (Illumina) and following the manufacturer’s instructions. Sequencing was performed on the Illumina NextSeq 500 platform using 150 bp paired-end reads. Raw sequence reads were converted to FastQ files, and non- biological sequences as well as low quality reads (Q < 20) were removed using Trimmomatic (Frischkorn et al., 2014; Bolger, Lohse, and Usadel, 2014; van der Burg et al., 2016). The high quality sequence reads with thresholds of Q > 20 were used for assembly and other downstream analyses.

Chapter 3: General methods 20

3.5 TRANSCRIPTOME ASSEMBLY USING THE DE NOVO ASSEMBLER AND ASSESSMENT

Trinity v2.0.6 short read de novo assembler was used to assemble high quality reads using default settings (Grabherr et al., 2011). CD- Hit v.4.6.1 (Fu et al., 2012; Li and Godzik, 2006) was used to remove redundant and chimeric sequences from all assembled contigs (Stewart et al., 2017). In addition, CEGMA v.2.5 (Parra et al., 2007) was used to assess the assembly completeness by determining the percentage of full- length sequences corresponding to 248 highly conserved eukaryotic proteins (van der Burg et al., 2016).

3.6 TRANSCRIPTOME FUNCTIONAL ANNOTATION AND GENE ONTOLOGY

Transcriptome annotation was conducted using the Trinotate pipeline V3.0 Ghaffari et al., (2014), which is available at (https://trinotate.github.io/). Specifically, contigs were annotated using BLAST+ v.2.2.31 software (E value1 × 10−5) (Altschul et al., 1990) against the Swiss-Prot and TrEMBL (Uniref90) databases using sequence identity (Suzek et al., 2014; UniProt Consortium, 2014). Gene Ontology (GO) terms were assigned to contigs that received BLAST hits and had functional annotation information. The distribution of GO terms across Molecular Function (MF), Biological Process (BP) and Cellular Component (CC) categories were visualised in WEGO (Ye et al., 2006) as per Ali et al. (2015).

3.7 MUCIN AND MUCIN-LIKE CANDIDATE IDENTIFICATION

Potential mucin and mucin-like candidates were identified by filtering the annotation results which were generated in Trinotate. Specifically, BLASTx and BLASTp results were filtered using the keywords ‘mucin’ and ‘mucin-like’. This meant sequences with significant BLAST hits to mucin and mucin-like genes in other species were selected as candidate mucin and mucin-like genes. Then, as a validation step, the open reading frames were predicted for the selected mucin and mucin-like sequences using ORF finder, and assessed if the predicted peptides were full length sequences (presence of start and stop codons; similar length to homologous mucin proteins). Domain architectures of the selected mucin and mucin-like sequences were

Chapter 3: General methods 21

investigated using the SMART database (Simple Modular Architecture Research Tool) (Letunic et al., 2014) to determine if candidate mucin proteins included ‘Signal peptides’ ‘Transmembrane domains’ ‘SEA’ ‘VWD’ ‘NIDO’ and ‘AMOP’ domains. Detection of these functional domains helped to classify mucin sequences into secreted or transmembrane mucin types. Only full-length mucin and mucin-like sequences were included as candidates for extensive downstream analysis.

3.8 READ MAPPING AND DIFFERENTIAL GENE EXPRESSION ANALYSIS

BOWTIE2 software v.2.2.5 was used to map reads back to the reference assembly (Langmead et al., 2012) for both species in which differential gene expression analysis was undertaken. Transcript abundance was estimated using RSEM v1.2.19 (Li B et al., 2011). Fragments per kilobase of transcript per millions (FPKM) was calculated for all transcripts (Mortazavi et al., 2008). Differential gene expression (DGEs) analysis was performed using the EdgeR Bioconductor package (Robinson et al., 2010) in the trinity pipeline following the scripts at (https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Differential-Expression). The gene list with statistically significant differential expression based on a false discovery rate (FDR) of <0.001 and log fold change (FC) ≥ 2 were then clustered using hierarchical clustering to produce a heatmap at (https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Differential-Expression). The list of differentially expressed genes was filtered to find if any of the mucin candidates were in this list.

3.9 GENE SET ENRICHMENT ANALYSIS (GSEA)

Gene set enrichment analysis was conducted on the list of DGEs using trinity scripts at (https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Differential- Expression). The results were filtered to determine if specific ontologies were over or under represented in comparison to the overall assembly based on FDR of <0.01.

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Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa

The sea anemone A. tenebrosa and other sea anemone species at high tide (Image by PGL, 2014, 2016)

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 23

4.1 INTRODUCTION

Mucins are classified into two groups: the secreted and transmembrane mucins (Coppin et al., 2017; Desseyn et al., 2000). The secreted gel-forming group include: MUC2, MUC5AC, MUC5B, MUC6, and MUC19 (Lee et al., 2016), while the transmembrane group include: MUC1, MUC3A, MUC3B, MUC12, MUC13, MUC16, MUC17 and MUC4 (Zaretsky and Wreschner, 2013). The protein structures of mucins consist of two regions, the distinctive N and C terminuses and the central PTS region. The PTS region is used to identify mucin proteins, but it is not conserved across mucin sequences, which makes it difficult to use for identifying specific mucin groups (Karakoç et al., 2016; Gendler and Spicer, 1995).

The protein structural domains of the gel-forming mucin group consist of conserved VWD domains and a cysteine knot domain, which can be used to identify the gel-forming mucins (Zaretsky and Wreschner, 2013). However, the protein structural domains of the second transmembrane group consist of SEA domain or NIDO, AMOP and VWD domains (Lang, 2007). These conserved domains can be used to identify the transmembrane mucins. These two mucin groups have been comprehensively studied in many phyla, but only limited study has occurred in phylum Cnidaria.

Cnidaria is a sister phylum to superphylum Bilateria, but the body plan of cnidarians has only two germ layers (Knack, 2011). Despite their simple body plans, cnidarians can cope in stressful environments well, and many species are particularly common in the intertidal zone. Previous studies on coral species have reported that mucus has a functional role in protecting the tissue surface (Jatkar et al., 2010). From this study there was an indication that cnidarian mucus may include a range of mucin types, but this has not been examined in detail. This study hypothesised that the sea anemone species, such as Actinia tenebrosa and other cnidarian species have a diverse range of mucin gene families, as these species depend on mucus to survive and protect themselves under the stresses they endure in the intertidal zone. The sea anemone species Actinia tenebrosa, is as an excellent species to investigate the study hypothesis, as it is widespread in Australia, easily identified and collected (Ottaway, 1979; Loh, 2011). Additionally, A. tenebrosa produce abundant mucus as they are one of the few anemone groups that are fully exposed during low tide (Fautin et al., 2008).

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 24

To date, the presence of mucin genes in Cnidaria has been reported for the sea anemone N. vectensis (Lang et al., 2007), and for the coral A. digitifera (Takeuchi et al., 2016). Although these studies identified the presence of mucin genes in this phylum, they provided a limited view of the mucin repertoire as a whole. Furthermore, the study of mucin domain structure in this phylum is almost non-existent, and should be investigated in order to understand the similarity of cnidarian mucin proteins to previously reported mucins in other taxa.

Therefore the first study of my thesis aimed to identify mucin and mucin-like genes in A. tenebrosa, analyse their domain structure and investigate their presence and absence in different cnidarian species. The bioinformatic techniques were selected to identify and analyse new mucin gene sequences. This information will be used to identify the repertoire of the mucin and mucin-like genes in phylum Cnidaria.

4.2 MATERIALS AND METHODS

4.2.1 Animal collections Four colourmorphs of A. tenebrosa (Figure 5; red n=1, green n=1, blue n=1 and brown n=1) were collected from Point Cartwright in November 2014 and February 2015 and housed in the marine laboratory, as detailed in (Chapter 3).

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 25

Figure 5 | The figure shows the sea anemone species A. tenebrosa in four colourmorph. A) Green and brown A. tenebrosa at low tide; B) Blue A. tenebrosa fully submerged in water; C) Blue A. tenbebrosa at high tide and D) Red A. tenebrosa fully submerged in water (Images by PGL, 2014, 2015).

4.2.2 RNA isolation, sequencing and quality control Methods detailed in Chapter 3. The raw RNA sequence reads were deposited at the NCBI under the accession numbers: SRR3216075, SRR3206038, SRR3207346, and SRR3207346 for the red, green, brown and blue colourmorphs, respectively.

4.2.3 Assembly, annotation and Gene Ontology (GO) The four sets of clean reads (red n=1, green n=1, blue n=1 and brown n=1) were assembled individually using the Trinity de novo assembly software (Grabherr et al., 2011). Detailed methods for assembly, annotation and gene ontology can be found in Chapter 3.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 26

4.2.4 Mucin and mucin-like candidate identification and protein domain analysis Transcripts identified as potential mucin and mucin-like genes were identified following the steps outlined in Chapter 3. ORF finder (Letunic et al., 2014) was used to predict the amino acid sequence of candidate mucin genes and the SMART domain database to visualise the functional domains as detailed in Chapter 3.

4.2.5 Diversity of mucin and mucin-like genes To investigate the diversity of the selected A. tenebrosa mucin and mucin-like candidates in other cnidarians species, A. tenebrosa mucin candidates were blasted against other cnidarians species using the local BLAST searches with an E-value of 1×10−5. The tested cnidarians species that showed homologous sequences with A. tenebrosa mucin candidates that contained a mucin domain were included in further analysis.

The tested datasets included: Aulactinia veratra, Anthopleura buddemeieri, C. polypus, Nemanthus annamensis, Anthopleura elegantissima, Telmatactis sp and Aiptasia pallida (Van der burg et al., 2016), as well as other publicly available cnidarian genome datasets for N. vectensis, A. digitifera, and Hydra magnipapilatta.

4.3 RESULTS

4.3.1 Sequencing and assembly statistical summary Overall 152,136,760; 179,309,262; 175,687,690 and 201,995,450 sequence reads were generated from the red, green, blue, and brown colourmorphs, respectively. Reads from the four samples were assembled into 111,882; 105,145; 87,137 and 122,362 contigs for the red, green, blue, and brown colourmorphs, respectively (for more assembly statistic metrics see Table 2). All assemblies were largely complete (> 96 % for all colourmorphs) and contained a high proportion of full-length transcripts (> 92 % for all colourmorphs) (Table 2).

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 27

Table 2 | The assembly statistic metrics generated from the four A. tenebrosa transcriptomes.

Quality metrics Red Green Blue Brown

Total reads 152,136,760 179,309,262 175,687,690 201,995,450

Total assembled base pairs 88,116,072 86,177,706 83,348,231 98,585,782

Number of transcripts 111,882 105,145 87,137 122,362

N50 1,478 bp 1609 bp 1,770 bp 1,600 bp

Average contig length 787.58 bp 819.6 bp 956.52 bp 805.69 bp

Maximum length 30,441 bp 30457 bp 31384 bp 32,195 bp

CEGMA

Full length sequences (%) 92.3 96.8 97.98 95.6

CEGs (%) 96.4 98.4 98.79 98.4

4.3.2 Annotation and gene ontology The total number of assembled contigs and significant BLAST hits with a stringency of 1E×10−5 from the red, green, blue and brown colourmorphs is shown in Table 3. High levels of BLAST success were found for both the BLASTx and BLASTp searches.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 28

Table 3 | Total number of contigs that received BLASTx and BLASTp hits across the four A. tenebrosa colourmorphs

Colourmorphs BLASTx hit BLASTp hit

Red 46,904 38,274

Green 47,370 27,471

Blue 46,334 29,250

Brown 64,883 37,026

GO terms were assigned to 27,172, 23,348, 22,733, and 24,968 contigs from the red, green, blue and brown colourmorphs respectively. GO terms from each A. tenebrosa colourmorph were then individually analysed in WEGO and showed the total assigned gene distribution under each GO category. The highest numbers of GO terms were assigned under BP, followed by MF and CC category. In the BP category, the cellular process and metabolic processes were the most commonly assigned GO terms. Binding and catalytic activity were the top assigned GO terms under the MF category. The greatest number of GO terms assigned under the CC category included: cell, cell part and organelle. Figures 6, 7, 8 and 9 are show WEGO plots.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 29

Figure 6 | WEGO plots show gene ontology classification in the whole set of red A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC.

Figure 7 | WEGO plots show gene ontology classification in the whole set of green A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 30

Figure 8 | WEGO plots show gene ontology classification in the whole set of blue A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC.

Figure 9 | WEGO plots show gene ontology classification in the whole set of brown A. tenebrosa transcripts; thy also show the number and percent of contigs assigned to GO terms from BP, followed by MF, and later CC.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 31

4.3.3 Mucin and mucin-like gene diversity A number of partial (no full-length) and complete (full-length) mucin and mucin- like contigs were identified in the four datasets. The complete contigs included: 4 mucin and 15 mucin-like sequences and these were selected for downstream analysis (Table 4). Most mucin and mucin-like candidates had multiple isoforms ranging from one to eight. The partial mucin and mucin-like contigs were excluded from downstream analysis in this study, but are briefly discussed in the discussion section.

Table 4 | List of full-length identified mucin and mucin-like candidates generated from the four A. tenebrosa colourmorph transcriptomes.

Colourmorphs Total identified mucins Total identified mucin-like

Red 1 4

Green 1 5

Blue 1 3

Brown 1 3

The gene ontology results show that four potential mucin candidates from the red, green, blue and brown A. tenebrosa colourmorphs had the same four GO terms included: GO:0016324 (Apical plasma membrane), GO:0005737(Cytoplasm), GO:0016021 (integral component of membrane), and GO:0005634 (Nucleus). The 15 potential mucin-like candidates from the four A. tenebrosa colourmorphs had the same three GO terms assigned and included: GO:0016021 (integral component of membrane), GO:0005509 (calcium ion binding), and GO:0007160 (cell-matrix adhesion).

4.3.4 Mucin and mucin-like candidate domain structure analysis The structures of the selected mucin and mucin-like candidates from the four A. tenebrosa colourmorphs were analysed based on the amino acid level and the candidates were then identified as mucin1-like, mucin4-like and mucin-like.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 32

4.3.4.1 Mucin1-like All A. tenebrosa colourmorphs had sequence with high similarity to mucin1-like (transmembrane-bound type). Predicted protein sequences encoded by these genes were found to contain a signal peptide in the N-terminus followed by two low complexity regions (PTS rich), followed by one SEA domain motif and one transmembrane domain in the carboxyl C-terminus (Figure 10/A). BLASTx and BLASTp hits, pfam domain structures, and sequence length for this gene from the four A. tenebrosa colourmorphs are shown in Appendices 2, 3, 4 and 5.

4.3.4.2 Mucin4-like and mucin-like Ten candidate mucin genes from the four colourmorphs were annotated as mucin4-like (transmembrane-bound type). These candidates had domain structures that consisted of NIDO, AMOP, and VWD domains that are part of the conserved architecture of MUC4. The N-terminus and C-terminus of the MUC4 proteins contained a signal peptide and transmembrane domain, respectively. Some mucin4- like proteins contained additional domains in the N-terminus (CUB, ZP, FN3), while others had an additional SEA domain in the C-terminus (Figure 10/B, 10/C and 10/D). The length of the PTS rich low complexity regions among mucin4-like candidates was highly variable. The other five mucin-like candidates annotated as mucin-like in the Acropora genus, and structurally they were lacking in the complete collection of MUC4 domains (NIDO, AMOP and VWD); therefore, they identified as mucin-like sequences in downstream analysis (Figures 10/E and 10/F). BLASTx and BLASTp hits, pfam domain structures, and sequence length for this gene from the four A. tenebrosa colourmorphs are shown in Appendices 2, 3, 4 and 5.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 33

Figure 10 | The protein domain architectures of A. tenebrosa mucin1-like, mucin4-like and mucin-like candidates based on SMART visualisation. A) Mucin1-like shows the full protein structure of MUC1 including the N-terminus indicated by signal peptide, one SEA domain followed by transmembrane domain on the C-terminus. B, C, and D) Mucin4-like sequences show the domain structure of MUC4 which is indicated by the NIDO, AMOP and VWD domains, additional domains on the N-terminus presented in the N-terminus in sequence B, and additional single SEA domain presented in the C- terminus in sequence C. E and F) Mucin-like candidate structures were lacking in the complete collection of MUC4 domains (NIDO, AMOP and VWD) and so they identified only as mucin-like sequences. Varied numbers and sizes of low complexity regions presented among the candidate sequences.

4.3.5 The diversity of mucin1-like, mucin4-like and mucin-like domain structures among cnidarian species The majority of A. tenebrosa mucin1-like, mucin4-like and mucin-like candidates were present in all other cnidarian species examined (one match from each species).

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 34

4.3.5.1 Mucin1-like The domain architecture of the mucin1-like was conserved across the majority of cnidarian species, with the exception in A. buddemeieri, N. vectensis, Telmatactis sp and H. magnipappillata (Table 5, Figure 11, Appendix 7).

4.3.5.2 Mucin4-like and mucin-like The mucin4-like domain architecture was conserved across the majority of species (NIDO, AMOP, and VWD), with the exception of N. vectensis, H. magnipappillata and H. vulgaris (Table 5, Appendix 8). The additional domains CUB, ZP, FN3 found in the N-terminus of two mucin4-like candidates from A. tenebrosa, were conserved in A. buddemeieri, O. faveolata, A. elegantissima and A. pallida, (Figure 12). The SEA domain which was in a different mucin 4-like candidate was conserved in the C-terminus of mucin4-like of N. annamensis, C. polypus and A. elegantissima (Figure 12).

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 35

Table 5 | Table shows the massive diversity of A. tenebrosa mucin1-like and mucin4-like candidates across cnidarian tested species. Mucin4-like shows higher presence across the species than mucin1-like

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 36

Figure 11 | The figure shows mucin1-like protein domain architectures from the tested cnidarian species based on SMART visualisation. The protein domain structures of MUC1, including a single SEA domain followed by a transmembrane domain on the C- terminus, presented in all tested cnidarian species. The N-terminus indicated by the signal peptide was absent in mucin1-like of some species. The number and size of the low complexity regions were varied among the mucin1-like of cnidarian species.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 37

Figure 12 | The figure shows protein domain architectures for mucin4-like genes across the tested cnidarian species based on SMART visualisation. The MUC4 domain structure, including NIDO, AMOP and VWD domains, were presented in the majority of species. A. tenebrosa mucin4-like additional domains in the N-terminus were presented only in mucin4-like of A. elegantissima, A. buddemeieri, A. pallida and O. faveolata, while, the additional single SEA domain in the C-terminus presented only in the C-terminus of A. elegantissima, N. annamensis and C. polypus. The N-terminus indicated by the signal peptide was absent in some sequences.

4.3.6 Mucin associated gene identification Integumentary mucin C.1, integumentary mucin A.1, Trefoil factor 2 (TFF2) and Trefoil factor1 (TFF1) were identified in A. tenebrosa (Figure 13). BLAST hit results, domain architecture and their diversity in other cnidarian species is shown in Appendix 9.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 38

Figure 13 | The protein domain architectures of the trefoil genes based on SMART visualisation

4.4 DISCUSSION

This study identified and characterized the domain structure of mucin1-like and mucin4-like genes in A. tenebrosa, and investigated their diversity across other cnidarian species.

4.4.1 The domain structure of A. tenebrosa identified mucin genes Blasting A. tenebrosa transcriptomes to other non-redundant protein sequences revealed that a number of mucin genes found in this species had homologs in vertebrate species. This finding is supported by Miller et al., (2007); Putnam et al., (2007) who reported that sea anemone (cnidarians in general) genomes are more similar to vertebrates than are those of flies or nematodes. Full-length transmembrane-mucins, mucin1-like and mucin4-like genes identified in A. tenebrosa, and this provides preliminary evidence that the membrane-bound mucins, such as mucin4-like and mucin1-like are not restricted to vertebrates. The previously identified domain architectures for MUC1 and MUC4 were conserved in the A. tenebrosa mucin1-like and mucin4-like. These mucin genes and proteins were found to be conserved across cnidarian species indicating that the diversity of mucins previously reported for this phylum was an under estimate (Lang et al., 2007).

4.4.2 The diversity of the transmembrane mucin: mucin1-like across cnidarians The diversity of mucin1-like domains was analysed in cnidarian species and the amino acid sequence length was found to vary across the tested species. The N- terminus part, including the signal peptide of mucin1-like protein, was diverse in amino acid size and presence across the tested species. The N-terminus of C. polypus, A. veratra and A. elegantissima lacked a signal peptide. The one SEA domain followed

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 39

by a transmembrane domain on the C-terminus was present in the C-terminus in the majority of species, but with variation in its size and position in the protein. Since the mucin1-like was conserved across cnidarian species, it appears mucin1-like is widely distributed in this phylum. These results suggest that mucin1-like is an important gene in this phylum. The function of MUC1 is to protect the epithelial surface (Brayman et al., 2004), and this function is probably the same in cnidarian species.

4.4.3 The diversity of the transmembrane mucin: mucin4-like across cnidarians The mucin4-like gene showed high diversity among cnidarian species examined, particularly variation in sequence length. This protein consists of the conserved domain structure including: NIDO, AMOP, and VWD. This MUC4 domain structure is conserved across most species examined and helped to identify this gene. The size and position of the conserved domains: NIDO, AMOP, and VWD varied among cnidarian species. The N-terminus signal peptide and C-terminus transmembrane domain also varied across the species.

An additional SEA domain, in the C-terminus of A. tenebrosa, N. annamensis, C. polypus and A. elegantissima, needs to be highlighted, as in most previous evolutionary studies the SEA domain is found in all transmembrane-bound mucins except in MUC4. Zaretsky and Wreschner (2013) proposed that MUC4 originated from a SEA domain-containing ancestor, as did all other transmembrane-bound mucins, but that the SEA domain was lost during evolution. The presence of the SEA domain in cnidarian mucin4-like, could confirm the hypothesis proposed by Zaretsky and Wreschner (2013). The additional N-terminus CUB, ZP and FN3 domains on the N-terminus that occurred in mucin4-like of A. tenebrosa, A. buddemeieri, O. faveolata, A. elegantissima and A. pallida were previously recognised in an extracellular matrix protein of corals (Takeuchi et al., 2016; Ramos-Silva et al., 2013). In the role of this protein in A. tenebrosa, is still unclear, but they may act as an associated molecule in the mucus layer. The ZP domain is common to several different extracellular proteins, not only mucin. For instance, in N. vectensis the ZP domain is found in other extracellular proteins that have roles as a structural component of the oocyte coat and could contribute to the polymerization of the jelly matrix (Levitan et al., 2015). The ZP domain also plays a role during fertilization, preimplantation and oogenesis in mammals (Levitan et al., 2015). This may indicate an important extracellular or

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 40

reproductive function of the transmembrane-type mucin4-like protein in cnidarian species.

4.4.4 Partial mucin genes Partial sequences of gel-type mucins including mucin5B-like, mucin6-like and transmembrane-type mucin3A-like were identified in A. tenebrosa. The domain structure of mucin5B-like was similar to the canonical sequence of this gene, consisting of a signal peptide, cysteine-rich VWD domains and a cysteine knot domain (Appendix 6/A, and 6/B). These mucin5B domain structures were found to be the same across other cnidarian taxa, indicating that this domain structure is highly conserved in this group. The identified mucin6-like and mucin3A-like were too incomplete to determine if their domain structure was conserved across species (Appendix 6/C, 6/D, 6/E).

4.4.5 Mucin associated genes: Trefoils peptide Trefoil peptides (TFF1, TFF2), referred to as integumentary mucin A.1 and integumentary mucin C.1, were identified in the sea anemone A. tenebrosa and also in the other cnidarian species examined. The amino acid sequence structure for the candidates consists of trefoil motifs and they are believed to play a role in the maintenance of mucosal membranes. In cnidarians, integumentary mucin C.1 was found to be up-regulated in the developmental stage in Caribbean Acropora corals (Hemond et al., 2014), as well as in A. millepora (Hayward et al., 2011). Interestingly, in A. tenebrosa, trefoils were identified as TFF1 and TFF2, similar to trefoils in mammals, and also as domain components for the integumentary mucin A.1, C.1 in the X. laevis. These trefoils were identified as full-length in our study for the first time in sea anemones. Recently we have confirmed the presence of both of these integumentary mucin proteins in the mucous covering of A. tenebrosa. The fact that these mucins are widely distributed in cnidarians and found in their mucous covering suggests that they may be important in mucous production and other protective functions.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 41

4.5 CONCLUSION

I have carried out the first study examining the mucin gene family in cnidarians. The study found that cnidarians have a diverse repertoire of mucin genes. Most of these genes were highly conserved and likely retain similar functions to homologous genes that have been studied in other species. Integumentary mucin proteins were identified in all cnidarian species tested, indicating that these trefoil domain proteins may play an important role in mucous secretions in this phylum. Overall, this study has established a reference for future mucin research in phylum Cnidaria.

Chapter 4: Identification, diversity and domain structure analysis of mucin and mucin-like genes in sea anemone Actinia tenebrosa 42

Chapter 5: The expression of mucin-like genes using qRT-PCR

5.1 INTRODUCTION

Sea anemones undergo larval dispersal and are largely sedentary in their post larval developmental stages (Orr et al., 1982). As a consequence, these organisms need to possess mechanisms to survive and cope in dynamic and changing environmental conditions. Nowhere is this truer than in the intertidal zone, the area between the low tide and high tide marks, where organisms are exposed to dramatic fluctuations in a number of environmental variables such as temperature, pH, salinity, dissolved oxygen and the availability of food. Physiological adaptations such as the extensive duplication of heatshock protein 70 and inhibition of apoptosis proteins in the Pacific oyster (Crassostrea gigas) (Zhang et al., 2012) have been proposed to allow intertidal species to withstand the extreme environmental fluctuations present in the intertidal zone. While this recent research has started to illuminate how intertidal species persist in such a stressful environment, relatively little research has been carried out in this area for cnidarian species.

Aulactinia veratra is an intertidal sea anemone with a broad distribution ranging from southern Queensland to Western Australia. Across its range A. veratra spans multiple environmental gradients, including clines in water temperature and abrupt changes in salinity. The environmental conditions encountered by A. veratra also change on a temporal scale. For example, dramatic changes in temperature, pH, salinity and aerial exposure occur over a tidal cycle in the intertidal zone. Consequently, A. veratra must possess some remarkable physiological adaptations to cope with such dramatic changes over very short time periods. The production of large amounts of mucus has been proposed as one potential adaptation to aerial exposure in this environment, but gene expression patterns of mucin genes have not been examined in this species in response to temporal and spatial environmental stresses.

As a first step toward understanding the expression patterns of mucin genes in A. veratra, we use quantitative reverse transcriptase polymerase chain reaction (PCR) to study their expression. This technique is an accurate and powerful technique for

Chapter 5: The expression of mucin-like genes using qRT-PCR 43

measuring gene expression and can be used with experiments to test patterns of mucin gene expression across a tidal cycle.

5.2 MATERIALS AND METHODS

5.2.1 Sample collection, air exposure experiment design and candidates selection Two A. veratra individuals were collected from the same location, as explained in Chapter 3, and then the air exposure experiment was undertaken. The first A. veratra individual was aerially exposed for three hours before RNA extraction, while the second sample was kept immersed in the tank as a control. Seven A. veratra mucin transcripts representing mucin4-like, mucin1-like, and mucin5B-like and four mucin- like genes (identified previously) were selected as candidates for this study.

5.2.2 RNA extraction and cDNA synthesis Total RNA was extracted from the A. veratra individuals using the steps and protocol detailed in Chapter 3. Complementary DNA (cDNA) was synthesized by reverse RNA transcription using SensiFAST cDNA synthesis protocol (Bioline, Australia, Cat # BIO-65054) (Ali et al., 2015). The reaction was made of 1μg of RNA template, 4 μl of 5xTransAmp Buffer, 1 μl of Reverse Transcriptase to a total of 6 μL.

5.2.3 Primer design and PCR amplification The primers were designed in primer design tool (Ye et al., 2012) using the default settings with the following modifications: the PCR product size was adjusted as 150 for the Min and 250 for the Max; Primer melting temperatures (Tm) as 58 for the Min, 60.0 for the Opt, 62.0 for the Max and 2 for the Max Tm difference. Then under the advance parameters, the primer size was adjusted as 18 for the Min, 22 for the Max, and 3 for the Max Poly-X (Table 6). The PCR amplification was made of 12.5 μL of MyFi mix, 2μL of each primer (1 μl forward and 1 μl reverse), 7.5 μL of H2O, 2 μL of MgCl2, and 1μL of cDNA to a total of 25 μL. PCR amplification conditions were: 5 min at 96⁰C, followed by 30 cycles of 30 sec at 96⁰C, 30 sec at 50⁰C, 30 sec at 72⁰C, then a final extension of 5 min at 72⁰C. PCR products were

Chapter 5: The expression of mucin-like genes using qRT-PCR 44

analysed by 3% agarose gel as per (Surm et al., 2015). PCR was tested at multiple temperatures to try and optimise PCR conditions.

Table 6 | List of seven primers designed to test the expression of mucin genes from A. veratra.

Sample Transcript ID Gene Forward primer Reverse primer PCR product number size (bp)

1 TR62800|c0_g2_i1 Mucin GGCATGGTAACA CAACTCTGTCCTG 221 5B-like GGAGCACT GCGAAGT

2 TR71694|c4_g1_i1 Mucin GGCTTGTATGCG AGCACACGAAGG 229 4-like AGAAGGGT AACGACAT

3 TR75184|c1_g1_i1 Mucin- ACGTTCCGCTGG AAACCGGGCAGC 163 like ACACTAAG AAATGAAC

4 TR57942|c0_g2_i1 Mucin- ATCGTGGGTCAA ACGTAAACTGTGG 225 like GCTCGATG TGGCAGT

5 TR69677|c0_g5_i2 Mucin CCCAACGCTCCC CGGAACATCCAG 180 1-like AGAAGAAT CACCAAAC

6 TR65757|c0_g2_i1 Mucin- TACTGTCAAACCC CATGCACGCTGCA 177 like ACTCGGC TTTCACT

7 TR71902|c0_g1_i1 Mucin- TCTGAGCAGTTGC GCCAGATGGAGC 242 like AGCCTAC GGTCTTTA

Chapter 5: The expression of mucin-like genes using qRT-PCR 45

5.3 RESULTS

The seven mucin candidates selected in this experiment were found to give highly variable results under all annealing conditions. The first four PCR attempts resulted in complete failure with no amplicons for any of the products (annealing temperature 55-58⁰C; see Figure 14 for representative gel picture). Following this the annealing temperature was dropped to 52⁰C in an attempt to improve amplification success. All primers amplified a product in this PCR reaction, but most primers amplified multiple products (Figure 15). In particular, primer set 1, 3, 4 and 7 all produced many multiple bands and multiple rounds of PCR optimization could not improve this result. Therefore this experiment was terminated and replaced with a genome-wide approach to test mucin gene expression in this species.

Figure 14 | Agarose gel electrophorsis image of the PCR (annealing temperature 55-58⁰C) showing complete failure with no amplicons for any of the seven products. The gel was run with 1kb ladder from Bioline.

Chapter 5: The expression of mucin-like genes using qRT-PCR 46

Figure 15 | Agarose gel electrophorsis image of the PCR (annealing temperature 52⁰C) showing the seven primers amplified a product in this PCR reaction. Most primers amplified multiple products; In particular, primer set 1, 3, 4 and 7. The gel was run with 1kb ladder from Bioline.

5.4 DISCUSSION

This experiment aimed to analyse the expression of A. veratra mucin genes in response to three hours of aerial exposure using the qRT-PCR. The outcome of this experiment showed that this procedure was unsuccessful for the primer sets designed. Previous studies using PCR have reported a number of factors that can influence the success of PCR reactions. These include; factors relating to PCR conditions and the design of the primers (Andreson et al., 2008; Beasley et al., 1999; Cobb and CIarkson 1994; Innis et al., 2012; Yuryev et al., 2004; Yuryev et al., 2002). These factors were considered in this study, in order to prevent or improve upon potential negative PCR results, but at each attempt, the PCR reaction produced no amplification or the amplification of multiple products.

Overall, the outcome of this study was not surprising for the following probable reasons: the mucin genes are composed of multiple low complexity regions that make primer design and PCR difficult. According to Thermo Fisher Scientific, (n.d.) low

Chapter 5: The expression of mucin-like genes using qRT-PCR 47

complexity regions affect PCR efficiency by quickly depleting PCR primers before PCR products can be generated. Another reason is that the conserved areas of the mucin genes outside of these low complexity regions are comprised of domains that are present in a wide variety of proteins (EGF domains, SEA domains, etc.). The wide distribution of these domains may have caused mispriming and the amplification of multiple products in PCR reactions. As no previous cnidarian studies have attempted to analyse mucin genes using PCR, we remain unsure as to the exact reasons behind the failure of our PCR reactions. In conclusion, qPCR may not be the best method to examine the expression of mucin genes in intertidal sea anemones such as A. veratra. I propose that RNA-Seq experiments may be a better way to examine the expression of mucin genes in these species.

Chapter 5: The expression of mucin-like genes using qRT-PCR 48

Chapter 5: The expression of mucin-like genes using qRT-PCR 49

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing

The sea anemone A. veratra at high tide (Image by PGL, 2014)

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing 51

6.1 INTRODUCTION

Early in this research, the mucin4-like and mucin1-like genes were identified and characterised in A. veratra, which is what makes it a perfect candidate for examining mucin gene expression, still obscure in sea anemones. Previously, mucin expression has been examined in the waratah A. tenebrosa and it was found that none of mucin1-like and mucin4-like was responsive to air exposure. This reinforced the need to examine the mucin in A. veratra under the same experimental conditions in order to understand the significance of the mucin genes when the species was exposed at low tide, and to generate further understanding about mucin in sea anemones. This study hypothesised that the mucin genes identified in A. veratra would have significantly high expression in response to aerial exposure. The aim of this current study is to investigate and analyse the expression of the A. veratra mucins under air exposure, the kind of stress that the species are used to being exposed to, in their real environment.

To date, sea anemone molecular studies have suggested the potential role of the mucin genes in wound healing and in the development stages in N. vectensis (DuBuc et al., 2014; Levitan et al., 2015). None of these studies has examined the response of mucin genes, in particular, not in the green snakelock A. veratra. What the molecular response of the mucin genes is under aerial exposure stress is still unknown.

This current study addressed this question by examining and analysing the response of A. veratra mucin genes in response to an experiment involving three hours of aerial exposure. The high-throughput next-generation sequencing technology and bioinformatics analyses were used to complete this study. It was found that the A. veratra mucin genes were up-regulated in response to air exposure. The data generated from this study could be used in conjunction with future mucin gene studies of sea anemones and other cnidarians to compare A. veratra mucin gene expression results across time, and to extend our understanding of mucin stress response in this phylum.

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing 52

6.2 MATERIALS AND METHODS

6.2.1 Sample collection and air exposure experiment design Two samples of A. veratra were collected from Port Cartwright, Queensland, Australia, in February 2016 and maintained, as detailed in Chapter 3. The first A. veratra individual was aerially exposed for three hours before RNA extraction, while the second sample was kept immersed in the tank as a control. In this study, the air exposed sample was named (Air) and the control sample, named (Water) (Figure 16)

Figure 16 | Aulactinia veratra, water sample fully submerged in water (immersed as a control) and air sample (3 hours of exposure to air)

6.2.2 RNA extraction, library preparation, sequencing, assembly and quality assessment RNA extraction, library preparation, sequencing, assembly and quality assessment for the A. veratra air and water samples were conducted as per Chapter 3 and Chapter 7. The raw RNA sequence reads were deposited in NCBI under the accession number SRR3205707 for the water sample and SRR3205708 for the air sample.

6.2.3 Functional annotation and gene ontology Functional annotation was conducted using the Trinotate pipeline V3.0 (Ghaffari et al., 2014) as detailed in Chapter 3.

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing 53

6.2.4 Differential gene expression and gene enrichment analysis Analysis of differential expression between the air and water treatments was conducted as explained in Chapter 3.

6.2.5 Aulactinia veratra mucin genes differential expressed identification The A. veratra mucins (earlier identified in Chapter 4) were searched for in the list of significantly differentially expressed contigs for consideration as candidates in this study.

6.3 RESULTS

6.3.1 Transcriptome sequencing and assembly statistical summary A total of 69,513,111 clean reads were assembled into 118,019 contigs. The assembly was highly complete and contained a high proportion of full-length transcripts (98.4 %) (Table 7 shows more assembly statistics metrics).

Table 7 | Assembly statistics metrics generated from A. veratra transcriptomes (Air and water treatment reads were merged to a single file, then assembled) using Trinity de novo assembler.

Assembly statistics Bp

Total assembled base pairs 88,375,948

Number of transcripts 118,019

N50 1,407 bp

Maximum length 30,277 bp

Average contigs length 748.83 bp

CEGMA

Full length (%) 95.6

Full length and partial (%) 98.4

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6.3.2 Functional annotation and gene ontology Overall 47,513 contigs returned significant BLASTx hits with a stringency of 1E×10−5, and gene ontology terms were assigned to 35,574 contigs. The distribution of GO terms showed that the highest number of GO terms was assigned to BP, then MF and finally the least terms were assigned to CC. In the BP category, cellular process (20,728 gene) (74.5%), metabolic process (14,716 genes) (52.9%) and biological regulation (12,237 genes) (44%) were the most commonly assigned GO terms. Binding (18,438 genes) (66.3%) and catalytic activity (11,099 genes) (39.9%) were the top assigned GO terms under the MF category. The greatest number of GO terms assigned under the CC category were; cell (22,942 genes) (82.4%), cell part (22,940 genes) (82.4%) and organelle (15,978 genes) (57.4%) (Figure17).

Figure 17 | WEGO plots show gene ontology classification results for the whole set of A. veratra transcripts; they show the highest numbers of GO terms were under BP, followed by MF, and later CC

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6.3.3 The effect of air exposure on mucus production in A. veratra At the beginning of the experiment, the A. veratra oral disc and tentacles were completely closed. Then, during the first hour, the oral disc opened slightly while the tentacles were still drawn, and there was some mucus production. During the second hour, there was a clear increase of mucus covering the oral disc. During the third hour, mucus production increased again.

6.3.4 Comparative different gene expression profiles, and cluster analysis across water and air treatments Overall 5686 differentially expressed sequences were found in A. veratra across water and air treatments. The 5685 sequences included 3243 genes significantly up- regulated in the water treatment, while the remaining 2443 genes were up-regulated in the air treatment. The expression level across the two samples based on (FC ≥2 and FDR of ≤ 0.001) is shown in a hierarchically clustered heat map (Figure 18). Contigs with up-regulation are indicated in yellow, the contigs with down-regulation indicated, in purple. The contigs expression pattern similarity across the samples is indicated by the three generated sub-cultures, as shown in Figure 19.

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Figure 18 | Hierarchically clustered heat map showing the RNA-sequence expression levels of 5686 differentially expressed contigs across the water and air samples based on (FC ≥2 and FDR of ≤ 0.001). The log2-transformed median-centred FPKM was the expression values. The up-regulation and down-regulation contigs are indicated by the yellow and purple colour intensities, respectively. The similarity of expression patterns across the samples is represented by the three levels of clustering as indicated by the blue, red and green coloured bars. These three levels correspond to the sub-clusters shown in Figure 19.

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing 57

Figure 19 | Cluster plots show the contigs with similar expression patterns across the two samples (air and water) resulting into three sub-clusters. The grey lines show the expression of the contigs, which was measured in log2-transformed median-centred FPKM, while the blue lines show the expression profile for each cluster.

6.3.5 Aulactinia veratra mucin genes differentially expressed across water and air treatments From our candidate mucin gene list mucin5B-like, mucin4-like and mucin-like genes were differentially expressed. Specifically, the mucin5B-like and mucin4-like were differentially expressed under the aerial exposure treatment, while the mucin-like was differentially expressed in the water treatment.

6.3.6 Gene set enrichment and functional analysis Functional enrichment analysis was performed on the differentially expressed contigs, and it revealed a number of over-represented GO terms in the air and water treatments. The enrichment results based on FDR <0.01 identified 42 statistically over- represented and 29 under- represented genes in the water sample; while in the

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air sample, 28 were over- represented and 7 were under- represented genes. The highest number of over-represented genes in the water and air samples was under the BP category, followed by CC in the water treatment and MF in the air treatment sections, with the lowest being the CC in the air treatment option, and MF in the water sample (Figure 20). The set of over-represented genes in the air treatment (Table 8) included genes that were not over-represented in the water treatment (Table 10). Specifically, the majority of the gene ontology terms under the BP in the air treatment belonged to the defence and immune response functions. Additionally, genes belonging to ‘binding’, ‘transport’, and ‘developments’ were over-represented in response to air exposure (Table 8). On other hand, a group of extracellular genes constituted the majority of over-represented genes under the CC category in the water treatment (Table 10). However, the under-represented genes in the air treatment included those which referred to cellular activities or to the receptor pathway and activity (Table 9). This result showed a reduction in the gene activity inside the cell when the animal body was exposed to environmental stress. In contrast, the majority of under-represented genes in the water treatment were rich in receptor activity, signal transduction and transporter genes (Table 11).

Among the over represented genes from the air treatment, the extracellular region ontology was enriched by mucin5B-like, while the calcium ion binding ontology was enriched by the mucin4-like.

Figure 20 | The bars show over and under-represented genes among the three gene ontology categories in air and water samples based on FDR <0.01

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Table 8 | List of 28 over-represented genes generated from the aerial exposure sample based on (FDR<0.01), GO terms in bold refer to the ontologies enriched by mucin5B-like and mucin4-like.

Gene Gene ontology terms FDR ontology <0.01 category CC Kinesin complex 2.00E-07 MF Microtubule motor activity 3.07E-05 BP Immune response 0.001111 MF Inositol 1,4,5 trisphosphate binding 0.001434 BP Immune system process 0.001434 BP Innate immune response 0.001434 MF RNA-directed DNA polymerase activity 0.001434 MF Motor activity 0.001785 CC Extrinsic component of endoplasmic reticulum membrane 0.001992 BP Defence response to bacterium 0.002612 CC Microtubule associated complex 0.002612 BP Defence response to bacterium, incompatible interaction 0.003185 BP Defence response 0.003266 MF Carbohydrate binding 0.003266 BP Response to salicylic acid 0.003266 MF Calcium ion binding 0.003266 BP Defence response, incompatible interaction 0.003266 BP Defence response to other organism 0.003712 BP Response to bacterium 0.003935 CC Extracellular region 0.004379 BP DNA integration 0.005257 BP Thick ascending limb development 0.006159 BP Metanephric thick ascending limb development 0.006159 MF Store-operated calcium channel activity 0.007007 CC Basolateral plasma membrane 0.00727 BP Distal convoluted tubule development 0.00727 BP Metanephric distal convoluted tubule development 0.00727 MF DNA polymerase activity 0.009396

Table 9 | List of 7 under-represented genes generated from the aerial exposure sample based on (FDR<0.01)

Gene Gene ontology terms FDR ontology <0.01 category CC Intracellular organelle 0.000166 CC Intracellular part 0.000262 BP G-protein coupled receptor signalling pathway 0.000348 CC Cell part 0.000561 BP Cellular metabolic process 0.000561 MF G-protein coupled receptor activity 0.001476 CC Intracellular membrane-bounded organelle 0.00206

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Table 10 | List of 42 over-represented genes generated from the water sample based on (FDR<0.01)

Gene Gene ontology terms FDR ontology <0.01 category CC Extracellular region part 2.37E-17 CC Proteinaceous extracellular matrix 3.84E-15 CC Extracellular matrix 3.84E-15 CC Collagen trimer 1.78E-12 CC Ribosome 1.22E-08 MF Structural constituent of ribosome 3.35E-08 MF Structural molecule activity 2.17E-07 CC Extracellular space 3.31E-07 BP Translation 4.30E-07 BP Positive regulation of protein binding 1.16E-06 CC Extracellular region 3.61E-06 BP Ossification involved in bone remodelling 7.93E-06 BP Establishment of planar polarity involved in neural tube closure 7.93E-06 BP Collagen catabolic process 1.44E-05 BP Multicellular organismal catabolic process 1.78E-05 CC Extracellular vesicular exosome 1.78E-05 BP Ossification 1.78E-05 CC Extracellular organelle 1.78E-05 CC Extracellular membrane-bounded organelle 1.78E-05 BP Positive regulation of binding 1.83E-05 BP Establishment of planar polarity of embryonic epithelium 1.87E-05 BP Collagen metabolic process 4.48E-05 BP Regulation of osteoblast proliferation 7.55E-05 MF Chitin binding 0.000101 BP Multicellular organismal macromolecule metabolic process 0.000105 BP Regulation of protein binding 0.000106 BP Positive regulation of osteoblast proliferation 0.000112 BP Multicellular organismal metabolic process 0.000112 CC Ribonucleoprotein complex 0.00021 BP Cochlea morphogenesis 0.000532 BP Wnt signalling pathway, planar cell polarity pathway 0.000536 BP Regulation of establishment of planar polarity 0.001047 CC Myosin II complex 0.001815 BP Non-canonical Wnt signalling pathway 0.002429 BP Inner ear receptor stereocilium organization 0.00288 BP Regulation of binding 0.00426 BP Positive regulation of necrotic cell death 0.005312 BP Leukocyte migration 0.005666 CC Basement membrane 0.005864 BP Extracellular matrix organization 0.007413 CC Extracellular matrix part 0.007942 BP Extracellular structure organization 0.007977

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Table 11 | List of 29 under-represented genes generated from the water sample based on (FDR<0.01)

Gene Gene ontology terms FDR ontology <0.01 category CC Membrane part 0 MF G-protein coupled receptor activity 0 CC Integral component of membrane 0 MF Signal transducer activity 0 BP G-protein coupled receptor signalling pathway 2.67E-07 MF Signalling receptor activity 9.37E-07 CC Intrinsic component of membrane 9.37E-07 MF Transmembrane signalling receptor activity 1.50E-06 CC Membrane 1.60E-05 MF Molecular transducer activity 0.000147 CC Cell part 0.000678 BP Single-organism process 0.000723 MF Receptor activity 0.001242 BP Biological regulation 0.001992 CC Plasma membrane 0.0022 BP Transmembrane transport 0.002207 MF Transporter activity 0.002232 MF Transmembrane transporter activity 0.002339 BP Macromolecule modification 0.002657 BP Regulation of biological process 0.004064 BP Single-organism transport 0.005079 CC Plasma membrane part 0.005321 BP Cellular protein modification process 0.005321 BP Protein modification process 0.005321 BP Single-organism localization 0.007192 BP Establishment of localization 0.007643 BP Ion transport 0.008041 BP Regulation of metabolic process 0.008041 MF Neurotransmitter receptor activity 0.008041

6.4 DISCUSSION

This study reported that A. veratra mucin4-like and mucin5B-like genes were differentially expressed in response to air exposure; and a single mucin-like gene was differentially expressed in the water treatment.

6.4.1 Mucin expression The identified partial mucin5B-like and full-length mucin4-like genes were the only responsive mucins to the three hours of air exposure, indicating that they may play an important role when the animal is out of the water and confronting conditions of stress such as air exposure. Early in this research, full-length mucin1-like and

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mucin4-like were identified in A. veratra, but in this air experiment, mucin1-like showed no significant change in expression, while only mucin4-like and the partial mucin5B-like sequence showed changes in expression. From this data we hypothesise that mucin5B-like and mucin4-like are the mucins that respond to this type of stress in the sea anemone A. veratra, while mucin1-like does not.

In a previous study, a change in mucin5B-like expression was observed during development of the sea anemone species N. vectensis (Levitan et al., 2015). This expression data indicates that mucin5B-like may have different roles across ecologically divergent sea anemone species such as A. veratra and N. vectensis, or that it undertakes multiple roles in different metabolic and developmental processes.

The function of the mucin-like gene that was differently expressed in the water treatment is not clearly understood, but it may have a protective under submerged conditions. For example in fish natural mucus secretions occur to safeguard the skin against pathogen invasion (Nigam et al., 2012). The expression of the mucin-like in the water sample could also be interpreted as mechanism to increase mucus production for a similar role as that observed in fish.

6.4.2 Genes functionally associated with stress response Most of the over-represented genes under the aerial treatment were related to defence and immune response functions. This indicated that the response to air exposure in A. veratra induces stress related genes, which has been observed in a number of invertebrate species under environmental stress (Zhang et al., 2012). An earlier study on N. vectensis identified three different groups of genes related to stress- response in sea anemones, including genes belonging to wound healing, genes belonging to immune response and genes belonging to chemical stresses (Reitzel et al., 2008). Barshis et al., (2013) examined genome wide patterns of gene expression in Acropora hyacinthus under thermal stress and found genes belonging to these classes to induced in thermally sensitive individuals. Overall, this data indicates that aerial exposure in A. veratra is stressful and that the induction of stress response genes may serve a protective role during this time.

The gene expression data from A. veratra is indicative of the cellular stress response (CSR), a universal cellular defence mechanism, which is initiated in response

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to changes in the extracellular environment (Kültz, 2005). Depending on the duration and severity of stress, cells either reinstate the process of cellular homeostasis to the previous state or take on a distorted state in the new and changed environment (Booth and Bilodeau-Bourgeois, 2009). The response includes control of the cell cycle, DNA and chromatin stabilization and repair, removal of damaged proteins, protein chaperoning and repair, as well as various metabolism functions (Kültz, 2003). Consequently, the induction of stress response genes seen in A. veratra may be associated with the CSR and allow cells of this animal to re-establish normal function when returned to water.

6.5 CONCLUSION

This investigation of mucin genes expression in A. vertara provided a first look at how mucin genes in the intertidal species respond to aireal exposure during low tide. Overall, the experiment has shown that the expression of A. veratra mucin4-like and mucin5B-like genes are induced by aireal exposure. This indicates that they may have an important role in defence against environmental stresses. The study data contributed to our understanding of mucin4-like and mucin5B-like genes and genes related to stress in sea anemones. Future research can extend this data by examining mucin gene expression in phylum Cnidaria.

Chapter 6: The influence of aerial exposure on Aulactinia veratra mucin gene expression using the RNA- sequencing 64

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing

The sea anemone A. tenebrosa at high tide (Image by PGL, 2016)

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing 65

7.1 INTRODUCTION

Previous studies in cnidarians have examined the response of genes to different environmental stresses. These studies have included the following stresses: temperature in Montastraea faveolata, A. pallida (Black et al., 1995) and Porites astreoides larvae (Olsen et al., 2013); thermal stress in A. millepora (Bellantuono et al., 2012); sunlight stress in A. tenebrosa (Muller, 2016); and air exposure in Palythoa caribaeorum (Rosa et al., 2016); and Veretillum cynomorium (Teixeira et al., 2013). In fact these studies have investigated the influence of several environmental stress factors on different stress response genes in cnidarians but no studies have examined the expression of mucin genes under any stress treatment. This deficiency highlights the need to study the expression of mucin genes under simulated environmental stresses in cnidarians, such as intertidal sea anemones.

Actinia tenebrosa is an intertidal sea anemone species exposed to several stress factors such as high and/or low temperature, ultra violet light, desiccation, food limitation and aerial exposure (Rosa et al., 2016; Shick and Dykens, 1984; Freites et al., 2002; Berger and Emucinin-likeet, 2007; Kumar et al., 2011; Teixeiraet et al., 2013). This species is regularly found attached to rocks and often directly exposed during low tides (Farquhar, 1898; Ottaway, 1978; Ottaway, 1973). During aerial exposure this species produces large quantities of mucus as an external covering a mechanism thought to provide protection against direct exposure (Muller, 2016). Consequently, this study set out to examine if mucin genes previously identified in A. tenebrosa are upregulated in response to aerial exposure. To test this idea I undertook a RNA sequencing experiment to examine the expression levels of mucin genes under this experimental treatment.

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing 66

7.2 MATERIALS AND METHODS

7.2.1 Sample collection and air exposure experiment design Two samples of A. tenebrosa were collected from Port Cartwright, Queensland, Australia, in February 2016 and maintained, as detailed in Chapter 3. The first A. tenebrosa individual was aerially exposed for three hours before RNA extraction, while the second sample was kept immersed in the tank as a control. In this study, the air exposed sample was named (Air) and the control sample, named (Water) (Figure 21).

Figure 21 | Actinia tenebrosa air sample (3 hours of air exposure), and water sample fully submerged in water (immersed as a control)

7.2.2 RNA extraction, library preparation, sequencing and quality assessment RNA extraction, library preparation, sequencing and quality assessment for the A. tenebrosa air and water samples were conducted as per Chapter 3. The raw RNA sequence reads were deposited in NCBI under the accession number SRR3216075 for the water sample and SRR3193648 for the air sample.

7.2.3 Transcriptome assembly, functional annotation and Gene ontology Assembly and functional annotation was conducted using the Trinotate pipeline V3.0 (Ghaffari et al., 2014) as detailed in Chapter 3.

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7.2.4 Differential gene expression and enrichment analysis Analysis of differential expression between the air and water treatments was conducted as explained in Chapter 3.

7.2.5 Identification of Actinia tenebrosa mucin genes differentially expressed The A. tenebrosa mucins (early identified in Chapter 4) were searched in the list of significantly differentially expressed contigs, and then selected as candidates for this study.

7.3 RESULTS

7.3.1 Transcriptome sequencing, assembly statistical summary and annotation Overall 152,136,760 sequence reads were retained after trimming and low quality sequences were removed. These reads assembled into 111,882 contigs. The transcriptome assembly was largely complete (96.4%), and contained a high proportion of full-length transcripts (92.3%). For further assembly statistic metrics, see Table 12 below. Of the 111,882 assembled contigs 46,904 (BLASTx success) and 38,274 (BLASTp success) returned significant BLAST hits. GO terms were assigned to 27,172 contigs. The distribution of GO terms under each GO category is shown in Chapter 4, in the ‘Results’ section, 4.3.2.

Table 12 | The assembly statistic metrics generated from A. tenebrosa transcriptomes (Air and water treatment reads were merged to a single file then assembled) using Trinity de novo assembler.

Quality metrics Bp

Total reads 152,136,760

Total assembled base pairs 88,116,072

Number of transcripts 111,882

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing 68

N50 1,478 bp

Average length of contigs 787.58 bp

Maximum length 30,441 bp

CEGMA

Full length sequences (%) 92.3

CEGs (%) 96.4

7.3.2 The effect of air exposure on mucus production in A. tenebrosa An A. tenebrosa sample was exposed to air for three consecutive hours before the RNA was extracted. At the beginning of the experiment, the A. tenebrosa oral disc and tentacles were completely closed (Figure 22A). Then, during the first hour, the oral disc opened slightly while the tentacles were still drawn, and mucus production increased (Figure 22B). After one hour, the tentacles were still retracted around the oral disc and covered with a mucus layer (Figure 22C). During the second hour (Figures 22D, 22E and 22F) there was a clear increase in the amount of mucus covering the oral disc. In the third hour (Figures 22G and 22H) there was an increase in mucus on the whole body.

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Figure 22 | Actinia tenebrosa during a three-hour aerial exposure experiment. A) The species at the beginning of the exposure experiment with drawn tentacles and oral disc totally closed. B and C) The species during the first hours of exposure with the oral disc gradually opening; a thin layer of mucus was observed. D, E and F) show the species during the second hour, clearly indicating the amount of mucus and the open oral disc. G and H) An obvious amount of mucus covered the oral disc and surrounded the whole body.

7.3.3 Different gene expression profiles and clusters analysis across water and air treatments Overall 1701 differentially expressed sequences were found in A. tenebrosa across water and air treatments. The 1701 sequences included 878 genes which were

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significantly up-regulated in the water treatment, while the remaining 823 genes were up-regulated in the air treatment. The expression level across the two samples based on (FC ≥2 and FDR of ≤ 0.001) is shown in the hierarchically clustered heat map (Figure 23) where contigs with up-regulation are indicated in yellow, while the contigs with down-regulation are indicated in purple. The similarity between the contigs expression patterns across the samples is indicated by the two sub-clusters generated, as shown in Figure 24.

Figure 23 | Hierarchically clustered heat map showing the RNA-sequences expression levels of 1701 differentially expressed contigs across the water and air samples based on (FC ≥2 and FDR of ≤ 0.001). The log2-transformed median-centred FPKM was the expression values. The up-regulation and down-regulation contigs are indicated by the yellow and purple coloured intensities respectively. The similarity between contig expression patterns across the samples is represented by the two level of clustering indicated by green and red coloured bars; these two levels correspond to the sub-clusters shown in Figure 24.

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing 71

Figure 24 | Cluster plots show the contigs with similar expression patterns across the two samples (air and water), resulting in two sub-clusters. The grey lines show the contigs’ expression, which was measured in log2-transformed median-centred FPKM, while the blue lines show the expression profile for each cluster.

7.3.4 Actinia tenebrosa mucin genes differentially expressed across water and air treatments Overall, none of the full-length identified mucins; mucin4-like and mucin1-like were differentially expressed in response to the aerial exposure. The mucin6-like and one mucin-like sequence were differently expressed across the treatments. The mucin6-like sequence was up-regulated in the aerially exposed treatment, while the mucin-like sequence was upregulated in the water treatment.

7.3.5 Gene set enrichment and functional analysis Functional enrichment analysis was performed on the list of differentially expressed contigs and it revealed no over or under represented GO terms in the air and water treatments based on FDR of <0.01.

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7.4 DISCUSSION

This study examined the responses of identified A. tenebrosa mucin genes to air exposure and demonstrated their lack of expression. The functional annotation statistically generated a zero number of enriched/depleted genes across the air and water treatments. There are several possible reasons for this outcome.

The first explanation for the above outcome is that the mucin genes have a heavy molecular weight of glycosylated proteins and are large in size, which makes them difficult to study (Portal et al., 2017). These molecular features make synthesis very complex (Thai et al., 2015). In addition to its range, the original A. tenebrosa mucin molecular weight may be affected during assembly, which in turn may lead to a lack of mucin expression. Perez-vilar and Mabolo (2007) said that the mucin gene molecular weight increase when the mucin disulfied-linked is assembled.

The second explanation for the lack of mucin expression is that the three hours of aerial exposure may need to be increased or decreased. A long expression time, such as the three hours, may decrease the mucin expression, especially if the amount of mucus in the gland cell diminishes over time. However, the three hours of air exposure may not be enough time for full mucus secretion and so not stimulate the mucin expression. These observations are supported by Bansial et al., (1995), who claimed that the properties of mucus as a viscous fluid are different from those it has when the mucus is a viscous gel. The three hours of aerial exposure may not be adequate for the mucus fluid to become a gel, or the three hours may be longer than the mucus requires for becoming a gel. If the exposure time is the reason for lack of mucin gene expression, then future research will need to analyse the mucin gene expression at the end of each hour of the three hours of exposure.

The third explanation for what may also influence mucin gene expression is that, during the three hours of air exposure treatment, the animal was exposed to the air at the temperature of the laboratory, where there was no sun light/heat or any other factor that could challenge the animal and alter the mucin expression. Normally, the animal in the intertidal environment is exposed to air, sun light/heat, humidity and additional factors such as bacteria interaction and tissue injury. All these factors may act as strong stimulators and so alter the cellular interaction response, mucus secretion and so, mucin synthesis/expression. This opinion is supported by the Davidovich et al. (2011) study, as they confirmed that mucin synthesis is influenced by change in humidity and

Chapter 7: The influence of aerial exposure on Actinia tenebrosa mucin gene expression using the RNA- sequencing 73

by high temperature conditions. Additional studies that confirm our interpretation (Bythell and Wild, 2011; Krupp, 1984; Wild et al., 2004, 2005) have demonstrated that coral mucus increased during air exposure at low tide. Further coral study also confirmed that increases in the sea surface temperature led to an increase in mucus producing cells (Bythell and Wild, 2011; Piggot et al., 2009). A fourth explanation for the lack of expression of mucin genes is that the synthesis of mucin in the sea anemone A. tenebrosa might be related to infections just like the mucin in vertebrates.

Overall, since the mucin genes were identified in A. tenebrosa (Chapter 4), their lack expression in this study may not indicate their absence, but it indicates that the aerial exposure stress did not stimulate the expression of the mucin genes. This study is one of the first studies to focus on the mucin genes’ responses to air exposure in cnidarians and particularly in the sea anemone A. tenebrosa, which makes it difficult to formulate the reasons behind the results found.

7.5 CONCLUSION

This study investigated the response of A. tenebrosa mucin genes to three hours of aerial desiccation. The experiment showed increased mucus secretion during the three hours of aerial exposure. No mucin genes, however, were differentially expressed under this treatment. These results may indicate that A. tenebrosa mucins might not be stimulated by air exposure stress. Overall, the study result provides background data for future research in other cnidarian species.

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Chapter 8: General discussion and conclusion

8.1 OVERVIEW

The overall aim of this research project was to identity mucin and mucin-like genes examine their diversity in cnidarians and analyse their expression in sea anemones. With respect to the first objective, presented in Chapter four, the mucin candidates in Actinia tenebrosa were identified, and then their protein domain structures and diversity across cnidarians analysed. This objective was a fundamental step in detecting the repertoire of this gene family in cnidarians. Regarding the second, third and fourth objectives presented in Chapters five, six and seven respectively, the expression of mucin genes was investigated in the sea anemone species A. tenebrosa and A. veratra using qRT-PCR and RNA-sequencing. While qRT-PCR experiment failed, the RNAseq research project was successful in its objectives. The information generated by this thesis provides useful information for the future study of mucin genes in phylum Cnidaria. In this chapter, the results generated from the four objectives and their significance are summarised and discussed in the overall context of the thesis objectives. It concludes with suggestions for the direction of future studies of mucin genes and proteins in sea anemone and cnidarian species.

8.2 SUMMARY OF THE RESULTS

This thesis focussed on exploring the mucin repertoire in A. tenebrosa, as intertidal sea anemones have not been the focus of previous studies have not investigated mucins in this group of species. To date, studies have reported a significant role of mucus in cnidarian species (Jatkar, 2009; Stefanik et al., 2013), but none of these studies have provided molecular information about the genes encoding mucin proteins that support and make up mucus. Consequently, this current research has focused on addressing this knowledge gap.

Chapter 8: General discussion and conclusion 75

The first objective (Chapter 4), identified and characterised the mucin sequences from A. tenebrosa, described their functional domain protein structure and investigated their presence/absence across other cnidarian species. Four transcriptomes from four A. tenebrosa individuals were sequenced, assembled and annotated. A number of full- length and partial-length mucin sequences were identified from the four individuals. Specifically, the full-length mucins included, mucin1-like and mucin4-like, while the partial-length mucins included, mucin5B-like, mucin6-like and mucin3A-like. A group of trefoil proteins associated with the mucin genes in the mucus secretion was also identified in A. tenebrosa. In terms of protein domain structures, mucin1-like and mucin4-like were similar to known domain structure of MUC1 and MUC4. Most mucins were widely distributed as they were found in most of the cnidarian species tested. These findings indicated that species from phylum Cnidaria have a diverse repertoire of mucin genes present in their genomes.

The second objective of this research (Chapter 5) I aimed to analyse the expression of mucin genes identified in A. veratra under aerial exposure using qRT- PCR. The primers for these mucin genes were designed, but the result revealed no PCR products from them. The structure of these mucin candidates has several low complexity regions and widely distributed domains, and this may have been a reason for the failure of the qRT-PCR method in this experiment. Low complexity regions are found in most mucins of the other tested cnidarian species as well, not only A. veratra. Therefore, this research examined the expression of A. tenebrosa and A. veratra identified mucins using only next generation sequencing, which is a widely used alternative method (Hafner et al., 2008).

The third objective of this research (Chapter 6) examined the expression of the identified mucin genes of A. veratra under an aerial exposure treatment. I observed that mucin5B-like and mucin4-like genes were significantly upregulated in response to air exposure stress in A. veratra, while another mucin-like was significantly upregulated in the control sample. I observed that the number of gene ontologies related to stress response was significantly enriched in the air sample. These findings indicated that the expression of A. veratra mucin5B-like, mucin4-like and a group of stress response genes responded to air exposure. This indicates that mucin5B-like and

Chapter 8: General discussion and conclusion 76

mucin4-like may have a role in the production of mucus and protection of this sea anemone during aerial exposure.

In Chapter seven of the current research, I examined the expression of mucin genes in A. tenebrosa, under a treatment of aerial exposure. The gene expression experiment was conducted using a differential gene expression analyses across the samples. It was found that neither the mucin1-like or mucin4-like genes were significantly differentially expressed in response to air exposure stress. These findings indicate that aerial exposure did not stimulate the expression of A. tenebrosa mucin genes, which may suggest that mucins do not play a significant role when the species is stressed by air exposure.

In comparing the mucin responses to air exposure across A. veratra (Chapter 6) and A. tenebrosa (Chapter 7), it was found that only A. veratra mucins were responsive to air exposure, while A. tenebrosa mucins showed no response. Although the two species are intertidal zone species and both of them were exposed to the same experimental conditions, the expression of their mucin genes was varied. These results might suggest that the sea anemone A. veratra is more sensitive to intertidal environmental stresses than A. tenebrosa, and that the sea anemone A. tenebrosa is more tolerant of intertidal environmental stresses than A. veratra. There are a number of reasons for thinking this. Firstly, from my own lab observation, the A. veratra species showed more aggressive behaviour than A. tenebrosa individuals in the aquarium tank in terms of space, possibly due to the fact that A. veratra show greater spacing in their real environment, lying deeply between rocks and covered with sand and shell grit to protect themselves. Secondly, during the three hour aerial exposure experiment, A. veratra showed more mucus production than the A. tenebrosa possibly because A. tenebrosa are usually more exposed to environmental stress. Additionally, during the air exposure treatment, no sand or shell grit was on A. veratra and mucus production was the only mechanism to protect itself and respond to stress. I believe this may be why the A. veratra mucins were immediately responsive to air exposure, while A. tenebrosa mucins might have needed a longer time or other stimulation to respond. Additionally, it’s possible that the variation in gene response could be cause of a technical error during the experimental or during assembly.

Chapter 8: General discussion and conclusion 77

8.3 SIGNIFICANCE OF THE RESULTS

The findings from this research confidently filled the research gaps and provided a valuable understanding about mucins in this group. This research has identified and investigated for the first time the mucin domain structures in A. tenebrosa and their diversity across other cnidarians. No previous molecular studies in cnidarians have focused on identified and described mucin protein domain structures or on their diversity across this phylum. Therefore, these newly identified and described mucin genes from the A. tenebrosa will serve as a genomic reference for future mucin studies across cnidarians. Additionally, identifying the diversity of mucin genes across other tested cnidarian species is preliminary evidence of the potentially significant role of mucin genes within this phylum. These findings will support future molecular research which aims to investigate and better understand the role and significance of mucin genes and proteins in phylum Cnidaria.

In this research, mucin gene expression was analysed for the first time in the sea anemone A. tenebrosa, as previous sea anemone (Muller, 2016), and cnidarian (Bellantuono et al., 2012; Black et al., 1995; Rosa et al., 2016) studies analysed the expression of different genes, but not mucins, under environmental stress. Furthermore, air exposure treatment was selected in this current study to analyse mucin expression. Understanding the mucin response under an aerial exposure treatment will help researchers to understand its potential significant role in protecting this species during low tides. The different patterns of mucin gene expression between the species indicate that not all intertidal species respond to the same stress in a similar way. This is significant as I entered this research project with the assumption that they would. These differences in expression may be related to differences in the ecology and life history of the species, something that will need to be taken into account in examinations of cnidarian species. Future mucin gene studies in cnidarians can use these findings as baseline for future comparison so as to provide a greater understanding of mucin gene expression in cnidarians in general.

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8.4 RESEARCH GAPS AND FUTURE DIRECTION

8.4.1 Objective 1 To achieve the first objective (Chapter 4) of the current thesis, the RNA was isolated from the whole A. tenebrosa organism, and numbers of full-length and partial mucins were identified. While these results were conclusive, one question that remains to be answered is which tissue expresses the mucin genes s. A good starting point to answer this question, would be to use single cell sequencing in future research. Identifying which tissue or cell type produces each mucin will help to better understand the significant role and response of each identified mucin in A. tenebrosa.

Future research could also isolate and purify the mucin proteinss from A. tenebrosa, to analyse their biochemical composition, and investigate their cell protection capability in vitro. This method could be scaled up for the pharmaceutical, food and cosmetic industry if these proteins were found to have commercial uses.

Additionally concerning this objective, the trefoil peptide family was identified as co-expressed/associated proteins with the mucin in mucus production. Since mucus productions is known to consist of mucins and a range of other mucin related/associated proteins, not only trefoils, it is suggested that future studies isolate and analyse the mucus components of A. tenebrosa. Analysing A. tenebrosa mucus might help to identify other potential mucin associated proteins.

8.4.2 Objective 2 In regard to the second objective, qRT-PCR was used to analyse the expression of A. veratra mucin candidates. Negative PCR results were generated from this PCR, even though several attempts were conducted. These result could be expected, as it is believed that the low complexity regions cause problems in PCR. Future studies of cnidarian mucins are therefore recommended to use RNA-seq, unless they are able to filter out the low complexity regions as in Dozmorov et al. (2015).

Chapter 8: General discussion and conclusion 79

8.4.3 Objective 3 In regards to the third objective (Chapter 6), the sea anemone A. veratra mucins were also investigated under aerial exposure treatment, which provided mucin results limited to sea anemones. To establish greater insight into the mucin expression patterns within whole cnidarians, future studies could investigate and compare more cnidarian species, not only sea anemones. Doing this would provide a comprehensive view of the expression patterns of these mucin genes. Future studies could also extend the aerial exposure duration beyond three hours and/or investigate mucin expression under different environmental stresses. Together, these methods of monitoring mucin gene expression will provide a holistic analysis of mucin expression during stress in sea anemones and cnidarians.

8.4.4 Objective 4 In relation to the fourth objective (Chapter 7), the sea anemone A. tenebrosa, was stressed under three hours of aerial exposure, in order to analyse the pattern of its mucin expression. This experiment was conducted with only one individual A. tenebrosa, and the expression patterns of its mucins were examined under aerial exposure for stress at laboratory room temperature. Future research could improve my experiments through a number of modifications. First, they could use a number of biological replications to avoid any potential technical errors which may affect the mucin expression results, and to give a more precise estimation of gene expression. Second, the laboratory aerial exposure experiment could be conducted under field conditions, where the animal is naturally stressed by aerial exposure. More realistic outcomes could then be determined. Additionally, the mucins could be investigated using other types of stresses: for example, physiochemical, thermal factors, UV, injury and pathogenic infection. These other stress factors might stimulate greater mucin gene expression when compared to air exposure stress. These modifications would subsequently provide a deeper understanding of mucin expression patterns in A. tenebrosa.

Chapter 8: General discussion and conclusion 80

While this project was restricted in terms of time and budget, it does establish a successful fundamental step for exploring and studying the mucin in the sea anemone A. tenebrosa and other cnidarians.

8.5 CONCLUSION

This research provides evidence that the sea anemone A. tenebrosa and other cnidarians have a diverse repertoire of mucin genes, which was not previously established in this phylum. The expression patterns of the identified mucin genes in A. tenebrosa and A. veratra in response to air exposure varied across the two species. Overall, this research project has successfully identified and characterised a range of mucin genes in A. tenebrosa and other cnidarian species. The domain structure of the mucin proteins found that they were consisted of conserved domains found in the homologous proteins in vertebrate species. Importantly, the current research provided results of the first investigation into mucin gene expression in the sea anemones A. tenebrosa and A. veratra, and indicates a potential significant role of these genes in response to air stress at low tide. Ultimately, the data provided by this research opens up an avenue for future studies of mucin genes in phylum Cnidaria. In conclusion, important background information about mucin genes in phylum Cnidaria is now clearer. Future molecular research can extend and build on these outcomes and generate a greater understanding of mucin genes in other cnidarians.

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Chapter 8: General discussion and conclusion 82

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Appendices

APPENDIX 1 | The table below shows the functional conserved MUC domains found in the structures of A. tenebrosa identified mucin1-like and mucin4-like, including the definition for each protein domain.

Pfam domains Definition

SEA Sea urchin sperm protein, Enterokinase, Agrin.

VWC Von Willebrand factor type C domain

VWD Von Willebrand factor type D domain

CT C-terminus cystine knot-like domain (CT-CK).

NIDO Nidogen-like

AMOP Adhesion-associated domain

TM Transmembrane helix region/domain

TIL Trypsin inhibitor like

ZP Zona pellucida domain

CUB CUB domain

FN3 Fibronectin type 3 domain

EGF_CA Calcium-binding EGF-like domain

EGF Epidermal growth factor-like domain

LC Low compositional complexity region

SP Signal peptide

Appendices 97

Appendices 98

APPENDIX 2 | This table below shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1- like, mucin4-like and mucin-like from the red A. tenebrosa colourmorph.

Contigs number Mucin BLASTx BLASTp Transcript Amino BLASTx and length(bp) acid length BLASTp hit Description Description

TR50731|c0_g1 Mucin1-like Non Mucin-1 2040 448 Non

MUC1_MESAU

TR63507|c0_g3 Mucin4-like Mucin-like Non 5591 1355 MLP_ACRMI protein Non

TR63465|c2_g2 Mucin-like Mucin-like Non 6067 962 MLP_ACRMI protein Non

TR61953|c2_g3 Mucin-like Mucin-like Non 2523 716 MLP_ACRMI protein Non

TR63556|c1_g3 Mucin-like Mucin-like Non 1234 314 MLP_ACRMI protein Non

Appendices 99

APPENDIX 3 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like, mucin4- like and mucin-like from the green A. tenebrosa colourmorph.

Contigs number Mucin BLASTx BLASTp Transcript Amino BLASTx and length(bp) acid length BLASTp hit Description Description

TR49398|c1_g2 Mucin1-like Non Mucin-1 2007 454 Non

MUC1_MESAU

TR43324|c0_g1 Mucin4-like Mucin-like Mucin-like 7750 1324 MLP_ACRMI protein protein MLP_ACRMI

TR50363|c3_g2 Mucin4-like Mucin-like Mucin-like 7483 2257 MLP_ACRMI protein protein MLP_ACRMI

TR50175|c7_g4 Mucin4-like Mucin-like Mucin-like 4762 1345 MLP_ACRMI protein protein MLP_ACRMI

TR50236|c3_g4 Mucin-like Mucin-like Mucin-like 4688 962 MLP_ACRMI protein protein MLP_ACRMI

TR45099|c4_g13 Mucin-like Mucin-like Non 5515 931 MLP_ACRMI protein Non

Appendices 100

APPENDIX 4 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like and mucin4-like from the blue A. tenebrosa colourmorph.

Contigs number Mucin BLASTx BLASTp Transcript Amino BLASTx and length(bp) acid length BLASTp hit Description Description

TR24970|c9_g2 Mucin1-like Non Mucin-1 1977 454 Non

MUC1_MESAU

TR26748|c2_g1 Mucin4-like Mucin-like Mucin-like 5873 1332 MLP_ACRMI protein protein MLP_ACRMI

TR24768|c4_g2 Mucin4-like Mucin-like Mucin-like 5594 1353 MLP_ACRMI protein protein MLP_ACRMI

TR20060|c1_g1 Mucin4-like Mucin-like Mucin-like 7551 2269 MLP_ACRMI protein protein MLP_ACRMI

Appendices 101

APPENDIX 5 | This table shows the contig number, blastx and blastp description and hit, amino acid, and transcript length (bp) for the identified mucin1-like and mucin4-like from the brown A. tenebrosa colourmorph.

Contigs number Mucin BLASTx BLASTp Transcript Amino acid BLASTx and length(bp) length BLASTp hit Description Description

TR57482|c19_g3 Mucin1-like Non Mucin-1 2063 454 MUC1_MESAU

TR56459|c5_g1 Mucin4-like Mucin-like Mucin-like 7734 1324 MLP_ACRMI protein protein MLP_ACRMI

TR58560|c7_g11 Mucin4-like Mucin-like Mucin-like 7487 2099 MLP_ACRMI protein protein MLP_ACRMI

TR59496|c2_g1 Mucin4-like Mucin-like Mucin-like 7470 2268 MLP_ACRMI protein protein MLP_ACRMI

Appendices 102

APPENDIX 6 | Domain structure organisations of the excluded partial identified mucin5B-like, mucin6-like and mucin3A-like from the red, green, blue and brown A. tenebrosa colourmorphs. A) Partial mucin5B-like structure representing the N- terminus domains; B) Partial mucin5B-like structure representing the C-terminus domains; C) Partial mucin6-like structure with lack of N and C terminuses; D) and E) Partial mucin3A-like structures with lack of N and C terminuses.

Appendices 103

APPENDIX 7 | This table shows mucin1-like information across cnidarian tested species, generated from blasting A. tenebrosa mucin1-like against cnidarian species. It was found that the A. tenebrosa mucin1-like presented as a full-length sequence in all cnidarian tested species, with differential in the identical percent, amino acid sequence length and presence of N terminus signal peptide and C terminus domains. The √ refers to presence, while × refers to absence.

Cnidarian Sequence full Identical Amino acid N-terminus signal C-terminus SEA and species length % length peptide TM domains

A. veratra √ 61.42% 316 × √

A. pallida √ 43% 387 √ √

C. polypus √ 44.86% 200 × √

N. annamensis √ 45.23% 200 √ √

A. elegantissima √ 71.69% 321 × √

A. digitifera √ 33% 449 √ √

O. faveolata √ 36% 548 √ √

Appendices 104

APPENDIX 8 | The following table shows mucin4-like information across cnidarian tested species, generated from blasting A. tenebrosa mucin4-like against cnidarian species. It was found that the A. tenebrosa mucin4-like presented as a full-length sequence in all cnidarian tested species, with differential in the identical percent, amino acid sequence length and presence of N terminus signal peptide and C terminus domain collections. The √ refers to presence, while × refers to absence.

Cnidarian Sequence full Identical % Amino acid N-terminus C-terminus NIDO- species length length signal peptide AMOP-VWD

domains

A. veratra √ 65.36% 1345 × √

A. pallida √ 40% 2321 √ √

C. polypus √ 48.89% 1398 × √

N. annamensis √ 44.42% 2257 √ √

A. elegantissima √ 72.55% 2286 √ √

A. elegantissima × 74.64% 2164 √ √

A. digitifera √ 40% 1306 × √

O. faveolata √ 45% 1416 × √

Appendices 105

Telmatactis sp √ 40.52% 1456 √ √

A. buddemeieri √ 66.48% 2171 × √

Appendices 106

APPENDIX 9 | The table below shows the identified mucin-associated molecules (trefoils) from the four A. tenebrosa colourmorphs, including their blast hit results, their protein domains definitions and their availability in other cnidarian species, that are examined in this study.

Proteins BLAST hit genus Domain definitions Presence in other cnidarian tested species

Trefoil factor1 Homo and Mus P or trefoil or TFF domain √

Trefoil factor2 Homo and Sus P or trefoil or TFF domain √

Integumentary mucin C.1 Xenopus P or trefoil or TFF domain √

Integumentary mucin A.1 Xenopus P or trefoil or TFF domain √

Appendices 107

Appendices 108

Appendices 109

Appendices 110