Comprehensive Molecular Surveillance of Norovirus and Adenovirus in Australasia

Home , Norovirus

Jennifer Hoi Yin Lun

A thesis submitted in fulfilment of the requirements for the degree of

Doctor of Philosophy

(Virology)

School of Biotechnology and Biomolecular Sciences

Faculty of Science

The University of New South Wales

August 2018

Thesis/Dissertation Sheet

Abstract:

Viruses are responsible for more than 50% of all health-care associated gastroenteritis. Of those, norovirus is the leading cause of viral gastroenteritis and adenovirus can cause a wide range of clinical diseases, including gastroenteritis, respiratory illnesses and conjunctivitis. Therefore, molecular surveillance of these viruses is essential to identify prevalent strains that are linked to epidemics.

In this thesis, two molecular epidemiological studies of norovirus were performed to characterise strains within Australia and New Zealand, between 2014 and 2017, by using both clinical and wastewater samples (Chapters 3 and 4). In chapter three, we identified a decline in the prevalence of the recent pandemic variant Sydney 2012 which was concomitant with the emergence of several novel recombinant viruses in both nations. Interestingly, two of these recombinants contained the GII.4 Sydney capsid which we hypothesised may have provided a higher epidemiological fitness to these noroviruses. In chapter 4, we sought to explore the potential mechanisms that could facilitate such a change. Analysis of full-length GII.4 Sydney 2012 capsid sequences revealed positive selection in residue 373 of epitope A in all three recombinant GII.4 Sydney 2012 strains. In addition, amino acid reversion to the predecessor New Orleans 2009 variant was observed in GII.P16/GII.4 Sydney 2012 capsid, an event likely to have facilitated the GII.4 Sydney capsid persistence observed.

In chapter 5, we investigated the diversity of adenovirus within the Australian population also using wastewater and clinical samples. We successfully sequenced a total of 20 serotypes and identified F-41 as the most prevalent serotype (average of 68.5%) in the Australian population during 2016-2017. Collectively in chapters 3-5 we showed that NGS of wastewater samples provides a more informative summary of viruses that cause asymptomatic and symptomatic infections and not just the latter which is commonly reported from clinical samples.

In summary, this is the first Australian study to assess population-level epidemiology of norovirus and adenovirus, highlighting the benefits of using both clinical and environmental samples for surveillance of viruses circulating within the population. A better understanding of the viral strains’ distribution will enhance the development of a successful vaccine.

Declaration relating to disposition of project thesis/dissertation

I hereby grant to the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or in part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all property rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstracts International (this is applicable to doctoral theses only).

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‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

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‘ I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.

I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International.

I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'

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INCLUSION OF PUBLICATIONS STATEMENT UNSW is supportive of candidates publishing their research results during their candidature as detailed in the UNSW Thesis Examination Procedure. Publications can be used in their thesis in lieu of a Chapter if: • The student contributed greater than 50% of the content in the publication and is the “primary author”, ie. the student was responsible primarily for the planning, execution and preparation of the work for publication • The student has approval to include the publication in their thesis in lieu of a Chapter from their supervisor and Postgraduate Coordinator. • The publication is not subject to any obligations or contractual agreements with a third party that would constrain its inclusion in the thesis

Please indicate whether this thesis contains published material or not. This thesis contains no publications, either published or submitted for publication (if this ☐ box is checked, you may delete all the material on page 2) Some of the work described in this thesis has been published and it has been documented in the relevant Chapters with acknowledgement (if this box is checked, you may delete all ☐ the material on page 2)

This thesis has publications (either published or submitted for publication) incorporated ☒ into it in lieu of a chapter and the details are presented below

CANDIDATE’S DECLARATION I declare that: • I have complied with the Thesis Examination Procedure • where I have used a publication in lieu of a Chapter, the listed publication(s) below meet(s) the requirements to be included in the thesis. Name Signature Date (dd/mm/yy)

Postgraduate Coordinator’s Declaration (to be filled in where publications are used in lieu of Chapters) I declare that: • the information below is accurate • where listed publication(s) have been used in lieu of Chapter(s), their use complies with the Thesis Examination Procedure • the minimum requirements for the format of the thesis have been met. PGC’s Name PGC’s Signature Date (dd/mm/yy)

For each publication incorporated into the thesis in lieu of a Chapter, provide all of the requested details and signatures required

Details of publication #1: Full title: Emerging recombinant noroviruses identified by clinical and waste water screening Authors: Lun JH, Hewitt J, Sitabkhan A, Eden JS, Enosi Tuipulotu D, Netzler NE, Morrell L, Merif J, Jones R, Huang B, Warrilow D, Ressler KA, Ferson MJ, Dwyer DE, Kok J, Rawlinson WD, Deere W, Crosbie ND and White PA Journal or book name: Emerging microbes & infections Volume/page numbers: 7(1): 50 Date accepted/ published: 29/03/2018 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work First author. >50% contribution. Conceived and designed experiments, performed the experiments, contributed reagents/materials/analysis tools, analysed the data and wrote the paper. Location of the work in the thesis and/or how the work is incorporated in the thesis: Chapter 4 (pages 49-71) Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy)

Details of publication #2: Full title: Recombinant GII.P16/GII.4 Sydney 2012 was the dominant norovirus identified in Australia and New Zealand in 2017 Authors: Lun JH, Hewitt J, Yan GYH, Enosi Tuipulotu D, Rawlinson WD and White PA Journal or book name: Viruses Volume/page numbers: 10 (10):548 Date accepted/ published: 09/10/2018 Status Published x Accepted and In In progress press (submitted) The Candidate’s Contribution to the Work First author. >50% contribution. Conceived and designed experiments, performed the experiments, contributed reagents/materials/analysis tools, analysed the data and wrote the paper. Location of the work in the thesis and/or how the work is incorporated in the thesis: Chapter 4 (pages 49-71) Primary Supervisor’s Declaration I declare that: • the information above is accurate • this has been discussed with the PGC and it is agreed that this publication can be included in this thesis in lieu of a Chapter • All of the co-authors of the publication have reviewed the above information and have agreed to its veracity by signing a ‘Co-Author Authorisation’ form. Supervisor’s name Supervisor’s signature Date (dd/mm/yy)

Abstract

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Acknowledgements

To my supervisor, Pete, thank you for being a great mentor for the past four years. I have learnt so much from you, and I am very grateful for all the advice and support you’ve given me throughout my PhD. Also, thanks for all the lunches and conferences, they were great fun! Thanks for everything. To my co-supervisor, JS, thank you for taking time out of your day to teach me and answer all my questions. Thanks for all the bioinformatics you’ve taught me and thank you for all the coffees. To Nat and Dan, thank you so much for all your help and support for the past years, and for always being there, even little things like having a chat, coffee breaks and lunches. You two made this PhD so much more enjoyable, and I am so glad we did our PhD together. You guys were there from the beginning and I hope we will continue to be friends in the future. To Andy and Kunlee, you were there from the very beginning (Honours) and I want to thank you for your patience and everything you’ve taught me. To Alefiya, thanks for being my MS2 buddy, it was enjoyable doing endless plaque assays with you. To Elise, thank you for the coffee chats and all the advice you’ve given me. To Alice, Tulio and Grace, I want to thank you for all the chats and making the lab so enjoyable and fun.

To my wonderful family, I’m so grateful for your endless love and support. Mum and Dad, thank you for supporting me 100% and for all the encouragements you’ve given me throughout. Emmie, thanks for always being there for me and for listening when I needed someone to talk to. To all my friends, thanks for being so supportive and simply being there. Thank you.

This work would not have been possible without the help of many others. To all the co-authors, thank you for all your contributions and this would not have been possible without all your support. I would also like to thank Bill Rawlinson and Juan Merif from Prince of Wales Hospital, and Richard Jones and Irena Serafimovska from the Douglass Hanly Moir diagnostic laboratory, for their generous provision of norovirus and adenovirus samples. I would like to thank Sydney Water Corporation for sample provision. I would like to thank Nick Crosbie, from Melbourne Water Corporation, for all his support throughout my PhD and partnering with WaterRA to provide me with a top-up scholarship. Being part of WaterRA provided me with many opportunities that were invaluable, and I want to thank Carolyn Bellamy, from WaterRA, for all the support she has given me throughout my PhD.

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Publications during time of candidature

Research articles

Lun JH, Ressler KA, Ferson MJ and White PA (2017) Norovirus and cruise ships. Microbiology Australia 38(4): 187-190.

Lun JH, Hewitt J, Sitabkhan A, Eden JS, Enosi Tuipulotu D, Netzler NE, Morrell L, Merif J, Jones R, Huang B, Warrilow D, Ressler KA, Ferson MJ, Dwyer DE, Kok J, Rawlinson WD, Deere W, Crosbie ND and White PA (2018) Emerging recombinant noroviruses identified by clinical and waste water screening. Emerging microbes & infections 7(1): 50.

Lun JH, Hewitt J, Yan GYH, Enosi Tuipulotu D, Rawlinson WD and White PA (2018) Recombinant GII. P16/GII. 4 Sydney 2012 was the dominant norovirus identified in Australia and New Zealand in 2017. Viruses, 10(10): 548.

Chan MCW, Hu Y, Chen H, Podkolzin AT, Zaytseva EV, Komano J, Sakon N, Poovorawan Y, Vongpunsawad S, Thanusuwannasak T, Hewitt J, Croucher D, Collins N, Vinje J, Pang XL, Lee BE, de Graaf M, van Beek J, Vennema H, Koopmans MPG, Niendorf S, Poljsak-Prijatelj M, Steyer A, White PA, Lun JH, Mans J, Hung TN, Kwok K, Cheung K, Lee N and Chan PKS (2017) Global spread of norovirus GII. 17 Kawasaki 308, 2014–2016. Emerging infectious diseases 23(8): 1350.

Jones BJ, Flint J, Collins J, White PA, Lun JH, & Durrheim, DN (2018) Gastroenteritis outbreak at a health function caused by an emerging recombinant strain of Norovirus GII. P16/GII. 4 Sydney 2012, Australia. Epidemiology & infection 146(8): 970-971.

Enosi Tuipulotu D, Netzler NE, Lun JH, Mackenzie JM and White PA (2017) RNA sequencing of murine norovirus-infected cells reveals transcriptional alteration of genes important to viral recognition and antigen presentation. Frontiers in immunology 8:959.

Netzler NE, Enosi Tuipulotu D, Eltahla AA, Lun JH, Ferla S, Brancale A, Urakova N, Frese M, Strive T, Mackenzie JM and White PA (2017) Broad-spectrum non-nucleoside inhibitors for caliciviruses. Antiviral research 146:65-75.

Enosi Tuipulotu D, Netzler NE, Lun JH, Mackenzie JM and White PA (2018) TLR7 agonists display potent antiviral effects against norovirus infection via innate stimulation. Antimicrobial agents and chemotherapy AAC-02417.

Fumian TM, Enosi Tuipulotu D, Netzler NE, Lun JH, Russo AG, Yan GYH and White PA (2018) Potential therapeutic agents for feline calicivirus infection. Viruses 10(8).

Fumian TM, Fioretti JM, Lun JH, dos Santos IA, White PA, Miagostovich MP (2019) Detection of norovirus epidemic genotypes in raw sewage using next generation sequencing. Environment International 123:282-91.

Submitted for publication

Lun JH, Crosbie ND and White PA (submitted) Genetic Diversity and Quantification of Adenoviruses in Wastewater from Sydney and Melbourne, Australia. Science of the Total Environment.

Conference publications

Yan GJ, Lun JH, Enosi Tuipulotu D, Morrell L and White PA. Emergence of Norovirus Recombinant strain GII.P16/GII.4 Sydney 2012 in New South Wales, 2017. The Australian Society of Microbiology, Molecular Microbiology Meeting, 2018.

Lun JH, Eden JS, Beatson P, Cox P, Crosbie ND, Deere W and White PA. The diversity of norovirus and adenovirus in wastewater. The Australia’s International Water Conference and Exhibition (OzWater 17’), 2017.

Lun JH, Sitabkhan A, Eden JS, Enosi Tuipulotu D, Netzler NE, Morrell L, Jones R, Ressler KA, Ferson MJ, Dwyer DE, Kok J, Rawlinson WD, Deere D, Crosbie ND and White PA. Comprehensive Molecular Epidemiological Study of Norovirus with Multiple Sample Types. The 9th Australasian Virology Society Meeting, 2017.

Lun JH and White PA. Increased gastroenteritis outbreaks caused by new noroviruses displaced the pandemic Sydney 2012 variant in Australia 2016. The 6th International Calicivirus Conference, 2016.

Netzler NE, Eltahla AA, Enosi Tuipulotu D, Lun JH, Urakova N, Frese M, Strive T, Mackenzie JM and White PA. Broad-spectrum non-nucleoside inhibitors for Caliciviruses. The 6th International Calicivirus Conference, 2016.

Lun JH, Sitabkhan A, Netzler NE and White PA. Molecular Epidemiological of Norovirus in NSW, Australia with the incorporation of a bacteriophage BioSphere as process Control. The 8th Australasian Virology Society Meeting, 2015.

Netzler NE, Enosi Tuipulotu D, Eltahla AA, Lun JH, Urakova N, Frese M, Strive T, Kelly AG and White PA. Non-Nucleoside Polymerase Inhibitors for Caliciviruses. The 8th Australasian Virology Society Meeting, 2015.

Table of Contents

1 General introduction part I: norovirus ...... 1

1.1 Acute gastroenteritis ...... 1

1.2 Background and history of norovirus ...... 1

1.3 Norovirus classification ...... 3

1.4 Structure and genome organisation ...... 4 1.4.1 ORF1 encoding non-structural proteins ...... 5 1.4.2 ORF2 and ORF3 encoding structural proteins ...... 6

1.5 Infectivity and transmission ...... 7

1.6 Norovirus and cruise ships ...... 7

1.7 Clinical manifestation and pathogenesis ...... 9

1.8 Molecular epidemiology ...... 10

1.9 Childhood infections ...... 13

1.10 Evolution of noroviruses ...... 13

1.11 Host susceptibility ...... 14

1.12 Prevention and control ...... 15

2 General introduction part II: adenovirus ...... 17

2.1 Background and history ...... 17

2.2 Structure and genome organisation ...... 17

2.3 Classification ...... 18

2.4 Transmission and infectivity ...... 20

2.5 Clinical manifestation and pathogenesis ...... 21

2.6 Prevention and control ...... 21

2.7 Environmental occurrence and persistence ...... 22

Viral contamination in water matrices ...... 24

Viral detection in environmental matrices using next generation sequencing ...... 24

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Aims and outline of thesis ...... 26

3 Emerging recombinant noroviruses identified by clinical and wastewater screening ...... 28

3.1 Abstract ...... 29

3.2 Introduction ...... 30

3.3 Materials and methods ...... 33 3.3.1 Ethics statement ...... 33 3.3.2 Clinical specimen collection and outbreak identification ...... 33 3.3.3 Wastewater sample collection ...... 33 3.3.4 Viral concentration and RNA extraction ...... 33 3.3.5 MS2 process control ...... 34 3.3.6 RT-PCR of norovirus RNA from clinical and wastewater samples ...... 34 3.3.7 Full-length norovirus genome sequencing preparation ...... 35 3.3.8 Nextera XT library preparation for NGS ...... 35 3.3.9 Norovirus phylogenetic analysis ...... 35 3.3.10 NGS data analysis ...... 35 3.3.11 Identification of recombination breakpoints ...... 36

3.4 Results ...... 37 3.4.1 Other emerging noroviruses ...... 43 3.4.2 Genogroup I norovirus ...... 44 3.4.3 Outbreak settings in Australia and New Zealand ...... 44 3.4.4 Recombinant breakpoint identification in norovirus full length genomes ...... 46 3.4.5 Norovirus capsid genotype diversity in Australian wastewater samples ...... 48

3.5 Discussion ...... 50

4 Recombinant GII.P16/GII.4 Sydney 2012 was the dominant norovirus identified in Australia and New Zealand in 2017 ...... 54

4.1 Abstract ...... 55

4.2 Introduction ...... 56

4.3 Materials and methods ...... 58 4.3.1 Collection of clinical specimens ...... 58 4.3.2 Collection of wastewater samples ...... 58

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4.3.3 Viral concentration and RNA extraction ...... 58 4.3.4 Reverse Transcription PCR (RT-PCR) amplification and sequencing ...... 58 4.3.5 Norovirus phylogenetic analysis ...... 59 4.3.6 NGS data analysis ...... 59 4.3.7 Analysis of amino acid variation within GII.4 capsid sequences ...... 59 4.3.8 Molecular adaptation analysis of the norovirus GII.4 capsid ...... 60

4.4 Results ...... 61 4.4.1 Gastroenteritis outbreak increase in 2017 ...... 61 4.4.2 Outbreak settings ...... 61 4.4.3 Circulating GI noroviruses ...... 62 4.4.4 Circulating GII noroviruses ...... 65 4.4.5 Antigenic variation within the GII.4 capsids ...... 69 4.4.6 Norovirus GII genotype distribution in wastewater samples ...... 71

4.5 Discussion ...... 74

5 Genetic diversity and quantification of adenoviruses identified in wastewater from Sydney and Melbourne, Australia ...... 77

5.1 Abstract ...... 78

5.2 Introduction ...... 79 5.2.1 Viral transmission through contaminated water ...... 79 5.2.2 Adenovirus ...... 79 5.2.3 Norovirus ...... 80 5.2.4 Quantification of enteric viruses in wastewater ...... 80 5.2.5 AdV surveillance at a population level using NGS ...... 81 5.2.6 Aims ...... 82

5.3 Material and methods ...... 83 5.3.1 Wastewater sample collection ...... 83 5.3.2 Clinical sample collection ...... 83 5.3.3 Viral concentration and nucleic acid extraction ...... 83 5.3.4 MS2 process control ...... 83 5.3.5 NGS amplicon preparation ...... 84 5.3.6 Quantification of AdV DNA and norovirus RNA levels in wastewater ...... 84 5.3.7 Nextera library preparation ...... 85 5.3.8 NGS data analysis ...... 85

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5.4 Results ...... 86 5.4.1 Quantitative analysis of AdV and norovirus in wastewater samples ...... 86 5.4.2 Genetic diversity of AdV in wastewater samples ...... 89 5.4.3 Genetic diversity of AdV in clinical specimens collected in Sydney ...... 91 5.4.4 Comparison of genetic diversity in clinical and wastewater samples ...... 92

5.5 Discussion ...... 93

6 General Discussion ...... 97

7 References ...... 109

8 Appendix ...... 139

8.1 Ethics approval forms ...... 139

List of Figures Figure 1-1. Phylogenetic analysis of norovirus genogroups...... 4 Figure 1-2. Genome organisation of norovirus...... 5 Figure 1-3. Timeline of pandemic norovirus GII.4 variants emergence...... 12 Figure 2-1. Structure of AdV...... 18 Figure 2-2. Phylogenetic analysis of AdV serogroups and serotypes...... 19 Figure 3-1. Phylogenetic analysis of ORF1/ORF2 overlap region of GII norovirus...... 39 Figure 3-2. Phylogenetic analysis of ORF1/ORF2 overlap region of GI norovirus...... 40 Figure 3-3. Yearly and monthly distributions of norovirus genotypes identified in the Oceania region, compared with institutional outbreaks reported to NSW Ministry of Health between July 2014 to December 2016...... 42 Figure 3-4. Norovirus outbreak settings identified in Australia and New Zealand between July 2014 and December 2016...... 45 Figure 3-5. Simplot analysis of novel norovirus recombinant strains...... 47 Figure 3-6. Norovirus genotype distribution in wastewater samples collected from Sydney and Melbourne, 2016...... 48 Figure 4-1. The number of gastroenteritis and norovirus outbreaks reported in the Oceania region, 2017...... 61 Figure 4-2. Phylogenetic analysis of polymerase (RdRp) and capsid (VP1) regions of GI noroviruses...... 63 Figure 4-3. Monthly distribution of norovirus genotypes identified in the Oceania region in 2017...... 64 Figure 4-4. Phylogenetic analysis of polymerase (RdRp) and capsid (VP1) regions of GII norovirus...... 67 Figure 4-5. Phylogenetic analysis of GII.4 full-length capsid sequences...... 68 Figure 4-6. Capsid residue variation and antigenic variation within the full-length capsid of GII.4 recombinant viruses...... 70 Figure 4-7. Norovirus genotype distribution in wastewater samples collected from Sydney and Melbourne, 2017...... 72 Figure 5-1. AdV DNA levels detected in wastewater samples collected from Sydney and Melbourne...... 87 Figure 5-2. Norovirus GII RNA levels detected in wastewater samples collected from Sydney and Melbourne...... 88

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Figure 5-3. AdV genotypic distribution in wastewater samples collected from Sydney and Melbourne, 2016 to 2017...... 90 Figure 5-4. Genotype distribution of adenovirus identified in clinical samples...... 92

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List of Tables

Table 1-1. Cruise ship arrivals in Sydney and number of reported acute gastroenteritis (AGE) cases...... 8 Table 2-1. AdV serotypes and associated clinical diseases.199-205 ...... 20 Table 3-1. Total number of norovirus genotypes identified in Australia and New Zealand from July 2014 to December 2016...... 38 Table 3-2. Full-length genome sequences of novel noroviruses identified in this study and their reported outbreak dates...... 44

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Abbreviations aa Amino acid

AdV Adenovirus

AGE Acute gastroenteritis bp Base pair ct Cycle threshold

DNA Deoxyribonucleic acid

G Genogroup kb Kilo base kDa Kilo dalton

NGS Next Generation Sequencing nm nanometre

NS Non-structural nt Nucleotide

ORF Open reading frame

PCR Polymerase chain reaction qRT-PCR Quantitative reverse transcription PCR

RdRp RNA-dependent RNA polymerase

RNA Ribonucleic acid

VLP Virus-like particles

WWTP Wastewater treatment plant

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Chapter 1: General introduction – norovirus

1 General introduction part I: norovirus

1.1 Acute gastroenteritis Acute gastroenteritis (AGE) is the fifth most cause of mortality, the second most common cause of morbidity worldwide, and is estimated to cause 1.3 million deaths each year.1, 2 AGE is characterised by the inflammation of the gastrointestinal tract, resulting in a sudden onset of diarrhoeal disease with associated symptoms such as vomiting, nausea, fever and abdominal pain. Despite improved sanitation and prevention strategies around the globe, diarrhoeal disease remains a significant health burden across people of all ages in both developed and developing countries.3, 4

Aetiological agents of gastroenteritis include viruses, bacteria and parasites. Viruses such as norovirus, rotavirus, astrovirus, enteric adenovirus (mainly serotype 40 and 41) and sapovirus cause more than 50% of all health-care associated gastroenteritis.5 Salmonella, Shigella and Campylobacter species are the common causative agents of bacterial gastroenteritis, and parasitic cases are generally caused by Giardia lamblia, Cryptosporidium parvum and Dientamoeba fragilis.6

Prior to 2006, rotavirus was the leading cause of viral gastroenteritis, with the majority of children in developed countries experiencing an episode of rotavirus gastroenteritis by the age of five.7 This resulted in an estimated 600,000 deaths each year between 1986 to 2000.7 Due to this significant health burden, the World Health Organisation (WHO) prioritised the development of rotavirus vaccines in the late 1990,8 including Rotarix® and RotaTeq®, which were subsequently released in the United States and Australia in 2006. Rotavirus vaccinations have led to a 67-75% reduction in infections in Europe, the United States and Australia, and a decline in hospitalisations related to rotavirus-associated acute gastroenteritis.9-11 Following the success of the rotavirus vaccine, norovirus has now replaced rotavirus as one of the most prominent aetiological agents of viral gastroenteritis in certain countries with available vaccines.12

1.2 Background and history of norovirus Norovirus is the leading cause of viral gastroenteritis in all age groups around the world, estimated to cause 12-24% of clinical acute gastroenteritis cases, 11-17% of hospital cases and approximately 70,000 to 200,000 deaths annually.13, 14 In the United States alone, norovirus

Chapter 1: General introduction – norovirus causes an average of 19-21 million cases, 56,000-71,000 hospital admissions and 570-800 deaths per year.15 Norovirus infection is generally self-limiting, but morbidity and mortality rates are especially high in vulnerable populations including young children, the elderly and immunocompromised individuals. Norovirus is the only known human enteric pathogen that can cause pandemics of gastroenteritis,16 with outbreaks commonly occurring in closed or semi- closed institutional settings such as nursing homes, hospital wards, childcare centres, cruise ships and military camps.17-19 Outbreaks are difficult to control and can lead to huge economic losses due to closures of hospital wards, businesses, and time off work. These losses have been estimated to cost USD $4.2 billion in direct health care and USD $60.3 billion in societal cost worldwide annually.1

The first recorded reference of norovirus-like illness was in 1929 by Zahorsky, who described the “hyperemesis hemis” or “winter vomiting disease”, characterised by a sudden onset of vomiting and diarrhoea.20 The occurrence of this illness also peaked during the winter season, hence its name. Following on from Zahorsky’s study, a number of gastroenteritis epidemics were reported, mainly affecting children, however no aetiological agents were ever identified for these outbreaks.21, 22

In October 1968, the first reported outbreak of norovirus was identified in an elementary school in Norwalk, Ohio.23 Fifty percent of the students and teachers (n=232) within the school developed acute gastroenteritis within two days, followed by a secondary attack rate of 32% among family contacts. The secondary attacks developed over a five-day period, with an average incubation time of 48 hours. The clinical symptoms associated with the illness included vomiting, nausea, abdominal pain and many individuals experienced diarrhoea.23 Despite the similar symptoms observed, all attempts to cultivate and characterise the aetiological agent in cell culture or within animals were unsuccessful.24-26 However, in 1972, Albert Kapikian discovered viral-like particles in the faecal matter collected from the 1968 Norwalk outbreak with the use of immune-electron microscopy.27 The particles were 27-32 nm in diameter, and represent the prototype virus of the genus Norovirus, termed Norwalk virus. This was the first time a virus was identified as an aetiological agent of gastroenteritis.

Due to the inability to propagate norovirus in cell culture or animal models, knowledge on the virus replication and pathogenesis remained unknown until decades later. The cloning and sequencing of the Norwalk virus genome in 1990 helped us gain a greater understanding of the molecular epidemiology of norovirus and greatly aided the development of specific

Chapter 1: General introduction – norovirus diagnostic assays.28 Despite numerous accounts of norovirus-associated outbreaks, it was not until 1996 when norovirus was first recognised as a cause of gastroenteritis pandemics.29

1.3 Norovirus classification Norovirus, formerly known as Norwalk-like viruses, constitutes a genus within the Caliciviridae family. The family is divided into five genera: Lagovirus, Nebovirus, Norovirus, Sapovirus and Vesivirus. Of those genera, only viruses from the Norovirus and Sapovirus can infect humans. Sapovirus infections mostly occur in young children and cause a milder form of gastroenteritis compared to norovirus infection.

Like other RNA viruses, the Norovirus genus is genetically very diverse and can be further classified into seven genogroups (GI-GVII) based on their VP1 amino acid sequence, which differ by around 45% at the nucleotide level (Figure 1-1).30 Genogroups can be further subdivided into genotypes, which vary by ~15%, based on their full-length capsid sequences. Any norovirus genogroup and genotype is designated with a Roman numeral followed by a number. For example, a virus classified under genogroup II, genotype 4 would be termed GII.4.30 Of all the genogroups identified, only GI, GII and GIV are responsible for human infections with GII associated with majority (~90%) of all norovirus infections, followed by GI (~10%). GIV infections in human are rare but can also infect cats and dogs.

To date, nine genotypes have been identified in GI, 25 genotypes in GII and two within GIV.31, 32 Despite the discovery of more than 36 genotypes, GII.4 viruses are responsible for 65- 80% of all norovirus infections. 16, 33 The term “variant” is used for individual viruses within the pandemic GII.4 lineage.30 In addition to infecting humans, noroviruses from a range of genogroups can infect a wide range of animals, including porcine (GII), bovine (GIII), feline (GIV), murine (GV) and canine (GIV, GVI and GVII).34-38

Noroviruses were initially classified into genogroups and genotypes based on the complete VP1 amino acid diversity, but as genetic recombination frequently occurs at the ORF1/ORF2 overlapping region a dual nomenclature system was proposed. This consisted of genotyping both the RNA-dependent RNA polymerase (RdRp), encoded by the NS7 region at the 3’ end of ORF1 and the VP1 amino acid sequence.30 The dual nomenclature system includes information on genogroup, genotype and for GII.4 strains, the variant type. If only the capsid genotype is known, the strain will be written, for example, as GII.4 Sydney 2012. However, if

Chapter 1: General introduction – norovirus both RdRp and capsid sequences are known, the strain nomenclature is shown, for example, as GII.P12/GII.3.

G G

I I I .

. 4 4 G

A I I

p . w 4

Genogroup VI O

G d O r I o

Genogroup II I r a

. l o n canine

4 e Genogroup IV r g a Genogroup III

S n G e

n y 1 8

human, porcine I I d A 4 s

. G 6 2 human, feline, 8 4 n B 8 7 6

G Q 7 bovine B e 0 5 7

4 0 2 Genogroup VII

U r y 8 6 9 0

G i 4 3 9 0 s 4 7 1 3 7 J 4 canine 5 5

II t 1 F 9 1 1 1 X 5 7

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Figure 1-1. Phylogenetic analysis of norovirus genogroups. Norovirus full-length VP1 amino acid sequences were used for phylogenetic analysis, representing all seven genogroups.32 Sequences were obtained from the NCBI public database. Sequence alignment was performed using MUSCLE. A maximum-likelihood phylogenetic tree was produced using MEGA 7 software39 with bootstrapping test of 1,000 replicates, based on the General Time Reversible model. The bootstrap percentage values are shown at each branch point for values ≥75%. The number of substitutions per site is indicated by the scale bar.

1.4 Structure and genome organisation Norovirus is a small icosahedral virion with a diameter ranging between 27-35 nm in size.27, 40 Its T=3 icosahedral symmetry is composed of 90 dimers of the major capsid protein (VP1).41 It contains a positive-sense, single-stranded, polyadenylated RNA genome of approximately 7.5 kb,42 which is organised into three open reading frames (ORFs), encoding both

Chapter 1: General introduction – norovirus structural and non-structural proteins (Figure 1-2).43, 44 The 5’ end of the genome is covalently attached to a virus-encoded protein called VPg and the 3’ end contains a polyadenylated tail (Figure 1-2).

Figure 1-2. Genome organisation of norovirus. (A) The norovirus genome contains ORFs, with a 19 bp overlap region between the 3’ end of ORF1 and 5’ end of ORF2. This genome organisation is based on the human norovirus GII strain Sydney 2012 (GenBank accession number JX459908). ORF1 encodes a large polyprotein that undergoes proteolytic cleavage to form non-structural proteins NS1 -NS7.45 ORF2 and ORF3 encodes for the major capsid protein VP1 and VP2, respectively. Other features include the protein VPg (NS5) covalently attached at the 5’ end of the genomic RNA and a poly (A) tail at the 3’ end. (B) The capsid structure of Norwalk virus, with a T-3 icosahedral symmetry composed of 90 dimers of VP1 subunits. The shell (S), protruding (P)1 and P2 domains are shown in blue, red and yellow, respectively. The ribbon representative of the Norwalk virus VP1 dimer is shown in the box (pdb:1IHM), where the S, P1 and P2 domains are coloured the same way. The interior shell of the viral particle is formed by the N-terminal and the S domain, whilst the P1 and P2 domains are exposed, protruding out from the vial capsid structure. Schematic is modified and adapted from 46.

1.4.1 ORF1 encoding non-structural proteins ORF1 is over 5 kb in length, making up the first two-thirds of the genome (Figure 1-2). It encodes a large polyprotein that is cleaved by the viral protease (NS6) into six non-structural

Chapter 1: General introduction – norovirus viral proteins (NS1-7).47 NS1/2 encodes an N-terminal protein, which is the membrane anchor in the replication complex, NS3 is an NTPase which is responsible for nucleotide triphosphate activity and NS4 is a helicase (p20) that is proposed to inhibit cellular protein secretion.47 The exact functions of the NS1-4 are not known, but the NS5-7 proteins are well described. NS5 is the VPg, a viral protein genome linked protein that recruits translational machinery and acts as a protein primer for replication. NS6 is a protease responsible for the cleavage of the viral polyprotein, as well as inhibiting the translation of host proteins.

Lastly, NS7 is the RdRp, which is essential for viral replication and transcription.47 The norovirus RdRp, like other RNA polymerases, lacks a proof-reading mechanism to correct mis- incorporated nucleotides during the process of replication.48 Therefore, the RdRp fidelity is generally 100 times less than viral DNA polymerases, which possess a 3’ to 5’ exonuclease for proof-reading.49 This low fidelity allows the viral RNA population to quickly evolve in response to host immunity.50 This highlights the important role the RdRp plays in norovirus fitness and evolution.

1.4.2 ORF2 and ORF3 encoding structural proteins ORF2 and ORF3 encode the VP1 and VP2 proteins, respectively. VP1 (60 kDa), the major capsid protein, is divided into three distinct structural domains. The N-terminal forms the internal portion of the capsid along with the conserved shell (S domain). A flexible hinge connects the S-domain to a protruding stem (P1 domain) which then leads to the hypervariable protruding P2 domain (Figure 1-2B) that forms the external surface of the viral capsid.51 The P2 domain comprises a number of motifs that are involved in host cell binding and antigenicity of the virus.52, 53 These motifs are termed epitopes A to E.54 Of those, epitopes A, D and E are the most important antigenic regions of the P domain. For example, in GII.4 variants aa variation within these epitopes can evade host neutralising antibodies and thus results in a selective advantage allowing the emergence of viruses with pandemic potential.55-57

VP2 (25 kDa) is a small protein with an undefined function. It has been termed a minor capsid protein, as one study demonstrated that it supported viral capsid assembly,58 although other studies have suggested it plays a role in the recruitment of genome RNA into the capsid for assembly.59

Chapter 1: General introduction – norovirus

1.5 Infectivity and transmission Norovirus can infect people of all ages and has a high attack rate due to its low infectious dose; 10-100 virions are sufficient to infect a healthy individual, and also because of high levels of viral shedding in infected individuals.60 Furthermore, the viral particles are extremely stable in the environment and are resistant to freezing, heating to 60°C, chlorine and acid. The virion is less susceptible than other viruses to commonly used disinfectants, such as alcohol and quaternary ammoniums.61

Norovirus is commonly transmitted person-to-person via the faecal-oral route. It can also be transmitted through aerosol spread, ingestion of contaminated food and water, and incidental hand contact with contaminated surfaces.62 Norovirus is ranked the most common aetiological agent of food-related gastroenteritis in Australia (39.5%),63 with a total of 1.55 million cases between 2006 to 2010.64 Despite this, only ~5% of all norovirus-related outbreaks are foodborne, causing around 50 of the 800 institutional outbreaks per year in New South Wales (NSW), Australia (personal communication; unpublished data, Public Health Unit). Airborne transmission of norovirus from vomitus aerosols has also been reported in restaurants.65 However, foodborne outbreaks of norovirus-associated gastroenteritis are often due to infected food handlers not sanitising their hands prior food preparation, or the consumption of contaminated food and water, in particular oysters and salad ingredients which are not cooked.66 Norovirus GI and GII are frequently found in shellfish contamination, owing to the fact they are filter feeders in aquatic environments that can be contaminated by human sewage.67

1.6 Norovirus and cruise ships Norovirus is notorious for causing outbreaks on cruise ships all over the world, affecting thousands of passengers per year, leading to considerable economic losses for the $40 billion industry.68-72 The cruise ship industry has an important economic benefit to Australia, with an estimated tourist income of $1.74 billion annually.73 Since 2007, the number of cruise ship arrivals into Sydney has tripled and their destinations abroad have doubled, with an average of 200 cruise ships berthing in Sydney each year, peaking at 320 in 2016 (Table 1-1). Despite the strict sanitation measures on ships, around 5.3% (yearly range 3.1%–9.0%) of ships arriving in Sydney have reported outbreaks of gastroenteritis (unpublished data, Public Health Unit, SESLHD), with norovirus commonly identified as aetiological agent (Table 1-1). A recent

Chapter 1: General introduction – norovirus investigation in the United States, from 2008 to 2014, showed that norovirus was responsible for 97% (92/95) of acute gastroenteritis on cruise ships.74

Table 1-1. Cruise ship arrivals in Sydney and number of reported acute gastroenteritis (AGE) cases.

AGE AGE AGE other Total AGE Total no. of unknown norovirus cause outbreaks arrivals cause Arrival Year 2007 3 (3.0%) 0 6 (6.0%) 9 (9.0%) 99 2008 6 (5.9%) 0 0 6 (5.9%) 102 2009 1 (0.9%) 0 4 (3.7%) 5 (4.6%) 109 2010 3 (2.2%) 0 4 (2.9%) 7 (5.1%) 136 2011 2 (1.0%) 0 5 (2.6%) 7 (3.7%) 191 2012 6 (2.8%) 0 8 (3.7%) 14 (6.5%) 214 2013 4 (1.6%) 1 (0.4%) 12 (4.8%) 17 (6.8%) 250 2014 7 (2.6%) 1 (0.4%) 6 (2.2%) 14 (5.2%) 268 2015 4 (1.4%) 0 5 (1.8%) 9 (3.2%) 278 2016 4 (1.3%) 1 (0.3%) 5 (1.6%) 10 (3.1%) 320 Total 40 3 55 98 1967

To prevent norovirus outbreaks on cruise ships and help eliminate the risk of person-to- person spread associated with buffet style meals, several cruise ship companies have rolled out dine-in restaurants with designated wait-staff. Hand washing and the use of hand sanitisers is another strategy for outbreak prevention on ships.75, 76 In Australia, on-board gastroenteritis outbreaks that involve more than three percent of the ship’s passengers and crew are required to be reported to the Australian Department of Agriculture and Water Resources (DAWR) under the Biosecurity Act 2015 (Commonwealth). Following this notification, DAWR Biosecurity Officers inform the state or territory health authority, with subsequent implementation of prevention and control procedures. Among other things, these include: cleaning of infected cabins and more frequent laundering of linen, disinfection in common areas, deployment of external public health sanitation squads and delayed boarding of new passengers to allow additional sanitation activities. Two major classes of disinfectant are used on board cruise ships to ensure inactivation of virions, hydrogen peroxide and chlorine-based sanitisers, and they can be used for decontamination of both non-food contact and food-contact surfaces.

Cruise ships are also commonly susceptible to subsequent outbreaks once an initial outbreak has struck. A study in Europe of 13 ships over a 28-week period showed each ship had between 1 and 12 outbreaks (mean = 3.46).77 In the case of cruise ship norovirus outbreaks, great debate surrounds whether the outbreak originates from embarking passengers, or if the

Chapter 1: General introduction – norovirus virus was already on board from the previous outbreak. After the first infection is introduced on to a ship, an outbreak is likely to ensue through person-to-person transmission. With the regular changing of passengers, noroviruses on board that fail to be removed could repeatedly infect a new susceptible population. A number of risk factors for repeated outbreaks have been identified: these include possible contact between boarding and disembarking passenger groups, inappropriate cleaning for norovirus elimination, and passengers refusing to be isolated to prevent further transmission of the virus.78 In conclusion, cruise ships have been touted as sentinel surveillance settings for new norovirus strains, with pandemics ensuing soon after the number of cruise ship outbreaks increase.77

1.7 Clinical manifestation and pathogenesis The clinical symptoms of norovirus include nausea, vomiting, diarrhoea, abdominal cramps, fever, chills, myalgias, headache, and a sore throat.79 The incubation period of norovirus infection is between 24-48 hours, with clinical symptoms lasting three to five days.80 However, more vulnerable populations, such as children, elderly and immunocompromised individuals, can experience severe and persistent symptoms such as chronic diarrhoea, dehydration, weight loss, malnutrition, renal failure, and even death (largely through dehydration).81-83 During the acute and symptomatic phase of norovirus infections, 108 to 1010 norovirus virions can be found in one gram of stool.84, 85 Also, prolonged viral shedding is observed in infected individuals, with virus RNA detected up to 8 weeks after symptoms have resolved.84 This provides an opportunity for the virus to infect other hosts.

In the 1970s, the pathogenicity of norovirus was observed in human volunteers who were challenged with Norwalk virus (GI.1).86 Subjects developed AGE symptoms and infection was confirmed by measuring viral genomes in stool. Histopathological examination of jejunum biopsies showed broadening and blunting of the villi,86, 87 pale and enlarged mitochondria, increased cytoplasmic vacuolisation and intercellular oedema.24 Volunteers, who were exposed to high titre of Norwalk virus, were susceptible to infections with a GII.1 strain (Hawaii virus), suggesting that immunity to one strain is unlikely to provide cross-genogroup protection.88 Though other studies have shown short-term (<6 months) immunity against norovirus strains, long term immunity (>6 months) has not been demonstrated with re-exposure of the same strain.88, 89

Chapter 1: General introduction – norovirus

1.8 Molecular epidemiology Norovirus is a major aetiological agent of viral gastroenteritis worldwide with infections occurring throughout the year, but it is most prevalent during winter months in temperate climates.90 It was not until the 1990s that norovirus was recognised as a leading cause of epidemic gastroenteritis.29, 91 Despite the characterisation of numerous genotypes, outbreaks caused by norovirus GII.4 are the most common, accounting for 65-80% of all norovirus infections.16, 33, 92 In order to evade population immunity, new GII.4 pandemic variants emerge every 3-5 years replacing previously dominant GII.4 strains.52, 93 A pandemic variant is defined as a pandemic norovirus with >5% amino acid divergence within its capsid sequence from the previous pandemic virus.94 To date, six distinct GII.4 variants have been associated with pandemics of AGE (Figure 1-3).

During 1995-1996, the GII.4 US 95/96 strain was found to be the aetiological agent responsible for increased norovirus outbreaks around the globe, including Australia,95 Europe and the United States.96 This strain was the first reported GII.4 pandemic variant which dominated for several years until the emergence of a new GII.4 variant.42 The GII.4 variant, Farmington Hills, replaced the US 95/96 variant in 2002 and was responsible for almost 80% of the norovirus AGE outbreaks in the United States and Europe.97, 98 Since then, new GII.4 variants have emerged and become dominant every 2-5 years. In 2004, the Farmington Hills variant was replaced by the GII.4 variant, Hunter virus, which led to an increase of AGE outbreaks in Australia,99 Europe 100 and Asia.101 Following this, two new variants, Yerseke 2006a and Den Haag 2006b, were identified between 2006-2007. Of those, the Yerseke 2006a strain was found to be the most predominant worldwide in 2006, with a lower prevalence in Asian countries.16 The 2006a strain evolved from the previous 2004 Hunter virus, whereas the 2006b was a likely descendent of the 2002 Farmington Hills virus.16 Interestingly, the 2006b strain did not dominate until 2007, which led to a rise in global norovirus activity and it remained as the main circulating GII.4 variant until 2010.100, 102-104 In 2009, a new GII.4 strain, New Orleans, was found to be the major cause of gastroenteritis epidemics and persisted for three years before the arrival of another novel variant, Sydney 2012, in late 2012.105, 106

The Sydney 2012 variant (GII.Pe/GII.4 Sydney 2012) is a recombinant virus, which contains the ORF1 from GII.Pe Osaka 2007 strain, with the ORF2 and ORF3 derived from the GII.4 Apeldoorn 2008 strain.105 Since then, no definitive pandemic variants have emerged, and the Sydney variant remained as one of the most predominant strains globally.107, 108 Other GII.4

Chapter 1: General introduction – norovirus variants associated with epidemics, but not full pandemics, were localised in specific geographical regions including; Japan 2001, Henry 2001, Asia 2003, Yerseke 2006a, Osaka 2007 and Apeldoorn 2008.16, 109-111

A few non-GII.4 strains have emerged as an important cause of norovirus infections including the GII.17 Kawasaki strain. This strain was associated with a sudden increase of gastroenteritis in Southeast Asia in the 2014/2015 winter seasons.112-116 Interestingly, this trend was not observed in North America, Europe or Australia, where a low prevalence of GII.17 infections was reported.108, 117, 118

Chapter 1: General introduction - norovirus

Asia Yerseke Den Haag Apeldoorn Melbourne Epidemic varitants: 2003 2006a 2006b 2008 2016

Pandemic variants: 9.1% 9.2% 4.9% 13.2% 11.3% 5.4% 20%

1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018

US 1995/96 Farmington Hills 2002 Hunter 2004 Den Haag 2006b New Orleans 2009 Sydney 2012 GII.P16/GII.2 GII.P16/GII.4 Sydney 2012 Noel et al., 1999, Widdowson et al., 2004 Bull et al., 2006 Eden et al., 2010 Yen et al., 2011 Eden et al., 2013, Niendorf et al., 2017 Matsushima et al., 2016 White et al., 2002 van Beek et al., 2013 Lun et al., 2018

Figure 1-3. Timeline of pandemic norovirus GII.4 variants emergence. Norovirus GII.4 is responsible for 65-80% of all norovirus infections. Six pandemic variants have emerged within this GII.4 lineage since the mid-1990s. The arrows depict the year of pandemic emergence with references listed below. The first pandemic variant was identified as US 1995/96,29 followed by Farmington Hills in 2002,42 Hunter in 2004,99 Den Haag 2006b in 2007,102 New Orleans in 2009119 and Sydney in 2012.105 The pandemic variants are named based on the location and year of when it was first isolated. The percentages shown above the timeline display the percentage of divergence with its predecessor variant. GII.P16/GII.2 and GII.P16/GII.4 Sydney 2012 are recombinant noroviruses where GII.P indicates the polymerase genotype (GII.P16), followed by its capsid genotype (GII.2 or GII.4 Sydney 2012). Epidemic strains were also identified, indicated by the dashed arrows, where cases/outbreaks were localised in specific geographical locations; Asia 2003, Yerseke 2006a, Apeldoorn 2008 and Melbourne 2016.

Chapter 1: General introduction - norovirus

1.9 Childhood infections Although GII.4 norovirus is responsible for majority of human norovirus infections, GII.3 strains also play a major role in childhood norovirus infections.120 It has been identified as one of the major capsid genotypes most frequently associated with infected children for the past two decades.121 These GII.3 strains are often recombinants, where the GII.3 capsid genotype is commonly associated with a GII.P21 ORF1, formerly termed GII.Pb. Since its identification in 2002, recombinant GII.P21/GII.3 virus is one of the most prevalent noroviruses around the globe.120, 122 Unlike GII.4 viruses, where a novel strain emerges and displaces the predecessor, GII.P21/GII.3 viruses continue to cause childhood infections worldwide.122, 123 The ORF1 GII.P21 lineage has also recombined with other capsid genotypes, including GII.1, GII.2 and GII.4.124 Therefore, surveillance of GII.3 viruses is important for the identification of new GII.3 recombinant strains and the development of effective prevention and control strategies.

1.10 Evolution of noroviruses Similar to other single-stranded RNA viruses, norovirus continuously undergoes both antigenic shift (recombination) and antigenic drift, to generate new strains that can evade population host immunity. Antigenic drift (nucleotide substitution) is a mechanism where the virus accumulates mutations within genes encoding antigenic proteins (reviewed in 43, 125). Variations in the aa sequence of these antigenic proteins can lead to viral escape of herd immunity.54, 56 Like influenza virus, where a single amino acid change of the HA1 glycoprotein can allow viral immune escape,126 changes within the norovirus capsid protein, VP1, also enable immune evasion.93 Amino acid changes mostly occur within the P2 domain, where antibody binding sites are located. The aforementioned P2 epitopes A-E have been shown to be blockade epitopes by using a range of serology assays, but mostly using surrogate neutralisation assays.57 Specifically, four sites (294, 368, 373, 376) within the P2 domain have been identified that undergo positive selection within GII.4 pandemic variants between 2007 and 2012.93 GII.4 viruses have been shown to have a higher viral fitness compared to other genotypes, which explains its dominance and ability to cause epidemics and pandemics.127

Antigenic shift, or RNA recombination, is another major driving force of viral evolution. Recombination occurs when there is an exchange of genetic material between two co-infecting viruses, resulting in the formation of a new virus.94 Majority of the recombinants occur naturally and is generated when a host is infected with more than one viruses, where the polymerase partially replicate two viruses, resulting in a recombinant virus. A recombinant can be detected

Chapter 1: General introduction - norovirus using phylogenetic analyses, where the different regions of the virus cluster into two or more classification groups.128, 129 Other detection methods include using programs such as SimPlot,130 which determine recombination by comparison of genetic similarity to potential parental strains, and 3SEQ, that test each triplet of sequence for the identification of recombination breakpoints.131 Norovirus recombination mostly occurs at the ORF1/ORF2 overlap,94 which separates the non-structural and structural regions of genome. Therefore, recombination at this region allows for exchanges between the viral capsid132 and non-structural genes, which enables the emergence of novel recombinants containing components from two different noroviruses.133

The first naturally occurring recombinant was identified in 1997, namely Snow Mountain virus.134 One of the most common norovirus recombinants is GII.P21/GII.3 (formerly GII.Pb/GII.3) which emerged between 2000-2001 and caused hundreds of outbreaks in Australia, Asia and Europe.101 The GII.Pb/GII.3 recombinant is commonly associated with childhood infections and more severe symptoms are generally observed in younger individuals.108, 123, 135 Interestingly, they have a more stable evolutionary rate compared to GII.4 strains127 and the GII.Pb/GII.3 recombinant continue to cause childhood infections today. However, more recently there was evidence for the replacement of this older strain with GII.P12/GII.3 strains in children.102

1.11 Host susceptibility Norovirus binding has been shown to be linked with Histo-Blood Group Antigen (HBGA) expression and antigen secretion, whereby different HBGA genotypes affect the susceptibility of host cells to norovirus infection.136-138 It has been speculated that the first step of infection is initiated by the attachment of norovirus to the HBGAs.139, 140 There are three major types of HBGAs, including the ABO, Lewis antigens and the secretor H antigen. The ABO and Lewis antigens are carbohydrates that are commonly found in the intestinal epithelial cells, and their biosynthesis is regulated by fucosyltransferase enzymes, such as FUT2 and FUT3. Although FUT2 specifically regulates them in the intestinal epithelial cells. These enzymes regulate the biosynthesis of the carbohydrates by adding a fucose residue to the disaccharide of H antigen.141 The FUT2 gene shows a high level of polymorphism and as a result, 80% of the human population carry the FUT2 enzyme and are classified as secretors.

Chapter 1: General introduction - norovirus

Studies have demonstrated secretors are significantly more susceptible to norovirus infections with certain strains.142 However, GII.4 strains have been shown to infect any individuals despite their ABO or Lewis phenotype or secretor status.142 The remaining 20% are called non-secretors as they lack an active FUT2 enzyme and thus display no H antigen secretion.143 Thorven et al. showed host susceptibility to norovirus is associated with FUT2 gene encoded secretions of α-1,2-linked fucose on HBGAs.144 Individuals lacking a FUT3 gene are known as ‘Lewis negative’, and they represent 10-30% of the population.141 The combination of polymorphisms between the ABO, FUT2 and FUT3 loci helps generate population groups with distinct epithelial glycosylation patterns,145 and different norovirus strains have different specificities depending on the host genetics. In contrast, some noroviruses can infect any individual regardless of secretor status, Lewis or ABO phenotype.142

Norovirus genogroups and genotypes have different HBGA binding affinities, thus epidemics can result if a certain blood group is more prevalent within the location. For example, previous studies have shown blood group B individuals have a relatively lower incidence of norovirus GI infections compared to other blood groups.146, 147 Whilst another study showed individuals with blood group O are more susceptible to norovirus infections than other blood groups.148 GI.1 Norwalk virus-like particles (VLPs) have shown to have a higher binding affinity to gastrointestinal epithelial cells of H-antigen secretor individuals compared to non- secretors.146, 149-151 Other studies have found the host susceptibility to infection did not correlate with the blood group or secretor status.152-155 In addition, studies have shown non-secretor individuals had a significantly lower antibody titre in response to norovirus infection, therefore it was proposed that they are likely to be more resistant to norovirus infection compared to secretors regardless of blood group.146, 156, 157

In summary, norovirus infections may affect all individuals due to the various HBGA binding profiles found in GI and GII viruses, which can influence the evolution of human norovirus.43, 158 Current evidence shows that a non-secretor status is more protective against norovirus infections, and thus asymptomatic or reduced disease severity is common within these individuals.

1.12 Prevention and control Norovirus infections are generally self-limiting but is recognised as a major public health concern due to its ability to cause more severe and chronic gastroenteritis in vulnerable

Chapter 1: General introduction - norovirus populations. Due to the lack of vaccines or antiviral treatments available for norovirus- associated gastroenteritis,159, 160 a number of strategies have been employed by the healthcare professionals to manage norovirus infections, in particular during the case of an outbreak 161-163. The first line of defence is infection control to prevent vulnerable populations immunocompromised individuals from being infected,164 followed by the isolation of infected patient once an infection has occurred.165 Nonetheless, the main prevention strategies focus on sanitation, isolation of infected individuals and environmental disinfection.17 For severe cases, oral rehydration with electrolytes (e.g. bismuth subsalicylate) and intravenous fluids can be administered to relieve gastrointestinal symptoms.166

There are currently no vaccines available for norovirus infection, however, two virus-like particle (VLP)-based vaccines are currently in development. VLPs are non-infectious particles that do not contain any viral genetic material. The first vaccine candidate, currently under early stages of human clinical trials, is a nasal spray containing monovalent GI.1 VLPs. This was first developed by LigoCyte Pharmaceuticals but was then taken over by Takeda in 2002. The vaccine induced a moderate level of protection, where 69% of volunteers who received a placebo developed gastroenteritis compared to 37% of vaccine recipients.149 Despite the advantages of intranasal vaccine delivery, the nasal delivery device experienced malfunctioned.149 Thus, Takeda pursued a vaccine that can be injected intra-muscularly and is currently in Phase IIb clinical trials.

The second vaccine candidate is a bivalent vaccine that offers protection against both GI.1 and GII.4 noroviruses. The vaccine was developed by Takeda and can be injected intra- muscularly.167 This vaccine contains both GI.1 and GII.4 VLPs and is used adjuvanted with 3-O- desacyl-4ʹ-monophosphoryl lipid A (MPL) and alum.167, 168 This bivalent vaccine was less effective when compared with nasal vaccine previously mentioned, where 54% of vaccine recipients developed gastroenteritis when challenged with live norovirus, compared to 62.5% of placebo recipients.167 However, when challenged with a GII.4 virus, more placebo recipients (41.7%) reported gastroenteritis symptoms compared to vaccine recipients (20%).

Norovirus vaccines are all in early to mid-stage development and further research and clinical trials are required to identify their efficacy as a preventative measure against norovirus infections.

Chapter 2: General introduction - adenovirus

2 General introduction part II: adenovirus

2.1 Background and history Adenovirus (AdV) is abundant within the human population worldwide, and is responsible for 5-10% of all febrile illness in young children.169 The first AdV strains were isolated in 1953 from lymph nodes, hence its name “adeno”, from the Greek word for glands.170 In the following year it was determined that AdVs are responsible for acute respiratory infections that can persist in lymphoid tissues, which are the two main clinical properties of AdV infection. Today, AdV have been shown to cause various human diseases, including gastroenteritis, respiratory tract infections, conjunctivitis and in rare cases acute haemorrhagic cystitis, meningitis and pneumonia.171

AdVs are a family of viruses that affect mostly children under the age of five. Recent studies have shown AdV was responsible for 6-20% of lower respiratory tract infections in hospitalised children172-175 and 10-23% admitted had AGE.176 AdV infections are generally not life-threatening and are usually asymptomatic, but more severe outcomes can be observed in vulnerable groups (such as infants, elderly and immunocompromised individuals). Outbreaks of AdV commonly occur in childcare centres, schools, camps and other health care settings.177-181

2.2 Structure and genome organisation AdVs are non-enveloped, double-stranded DNA viruses with an icosahedral capsid, approximately 90-100 nm in diameter (Figure 2-1). The viral capsid is composed of 252 capsomers; of those 240 have a six-fold symmetry (hexons) and the remaining 12 have a five- fold symmetry (pentons), which produce the particle corners.182 A fibre-like projection protrudes from each of the 12 vertices and is responsible for host receptor binding.183 The DNA genome is approximately 35 kb in length and encodes for more than 30 structural and non-structural proteins in total.184

Chapter 2: General introduction - adenovirus

A B

CORE CAPSID PROTEIN PROTEIN V II (hexon) VII III (penton) DNA IIIa X IV (ﬁbre) terminal VI VIII IX

Figure 2-1. Structure of AdV. (A) A schematic of AdV virion, showing the various protein components and its orientation as well as the viral DNA genome. The core and capsid proteins are indicated in the legend. Not all components will be present in a single virion. Diagram adapted from (B) Cryo-EM structure of AdV virus (serotype D-26), with colour coded structural components.185 View is down the icosahedral three-fold axis. Image adapted from 186.

2.3 Classification AdV belongs to the Mastadenovirus genus within the Adenoviridae family. Other genera within the family include Atadenovirus, Aviadenovirus, Ichtadenovirus and Siadenovirus. Of those, only members of Mastadenovirus can cause human infections. Seven species (A-G) have been identified within the Mastadenovirus genus, and can be further classified into 68 serotypes (Figure 2-2).171 Originally, the AdV species were classified into serotypes based on haemagglutination and serum neutralisation.187, 188 Traditional serological methods and pathogenicity were used to differentiate the 51 AdV serotypes.189 However, for serotypes 52- 68, genomic sequencing and phylogenetic analysis of the hexon gene are now required for differentiation.189

Chapter 2: General introduction - adenovirus

Serogroup D 8-10, 13, 15, 17, 19, HAdV 56 22-24, 26-27, 30, 32-33, HAdV 10 36, 37, 38, 39, 42-49, 51

HAdV 26

HAdV 9

HAdV 19 HAdV 53 HAdV 36

HAdV 46 HAdV 38 HAdV 58 HAdV 48

HAdV 13

Serogroup C 1, 2, 5, 6 HAdV 5

HAdV 1 HAdV 4 HAdV 2 Serogroup G 52 HAdV 52 Serogroup E 4

HAdV 12 HAdV 55

HAdV 8 HAdV 14 HAdV 31 HAdV 40

Serogroup A HAdV 3 12, 18, 31 HAdV 41 HAdV 50

Serogroup F 16 HAdV 40, 41

Serogroup B 3, 7, 11, 14, 16, 21, 34-35, 50 0.06

Figure 2-2. Phylogenetic analysis of AdV serogroups and serotypes. Full-length AdV hexon gene sequences were used for phylogenetic analysis, representing six serogroups (A-G). Sequence alignment was performed using MUSCLE. A maximum-likelihood phylogenetic tree was produced using MEGA 7 software39 with bootstrapping test of 1,000 replicates, based on the General Time Reversible model. The number of substitutions per site is indicated by the scale bar.

In recent years, multiple AdV receptors have been identified, where different serogroups have affinity to various tissues. The various tissue tropism of the different serotypes is still unknown, though the fibre proteins from serogroups A, C and F have been shown to interact with the host cellular protein coxsackie adenovirus receptor (CAR).190 As suggested by

Chapter 2: General introduction - adenovirus the name it also binds to coxsackie viruses. Other AdVs use alternative cellular receptors such as CD46, desmoglein 2, sialic acid, or heparan sulfate.191

Five of the seven AdV serogroups, particularly serogroup D, have a range of tissue tropisms (Table 2-1). Serogroup D has been shown to grow in ocular, respiratory and gastrointestinal tract (GIT) tissues.192 AdV F-40 and F-41 are most commonly associated with gastroenteritis, however, other serotypes such as A-12, A-31, D-65, D-67 and G-52, have also been identified to cause AGE.193, 194 Respiratory infections are most commonly caused by serotypes B-1, serogroup C and E.195 Serotypes within serogroup D (8, 19, and 37) are commonly associated with adenoviral keratoconjunctivitis, which is a major cause of ocular morbidity,195- 197 and also by AdV E-4, C-5, B-3, B-7, B-11 and B-14.198 This demonstrates that despite certain serotypes more likely to replicate in specific tissues, the same clinical manifestation can be caused by infection from a range of other AdV serotypes (Table 2-1). This is of major public health concern as there are currently no vaccines available for AdV and there is no systematic surveillance or typing of AdV in Australia.

Table 2-1. AdV serotypes and associated clinical diseases.199-205 AdV serogroups Serotypes Type of infection A 12, 18, 31 gastrointestinal, respiratory, urinary B 3, 7, 11, 14, 16, 21, 34, 35, 50 keratoconjunctivitis, gastrointestinal, respiratory, urinary C 1, 2, 5, 6 respiratory, gastrointestinal, hepatitis, urinary D 8-10, 13, 15, 17, 19, 20, 22-30, 32-33, 36-39, 42-49, 51 gastrointestinal, keratoconjunctivitis E 4 keratoconjunctivitis, respiratory F 40, 41 gastrointestinal G 52 gastrointestinal

2.4 Transmission and infectivity AdV infections can be transmitted through the inhalation of aerosolised droplets, direct conjunctival inoculation, faecal-oral route (mainly through contaminated water),206-209 fomites, environmental surfaces or airflow filters.210, 211

Human AdVs are resistant to gastric and biliary secretions and they have a high tropism for the gastrointestinal tract; thus, they are commonly detected in faeces at high level.212 Non- symptomatic individuals can continuously shed AdV viral particles in the environment for weeks in their faeces, especially when serogroups B and C are the causative agent.169, 213, 214 In addition, AdVs are occasionally found in the urine of AdV-infected immunocompromised individuals,215- 217 though this is perhaps an insignificant route of transmission. Due to its non-enveloped viral

Chapter 2: General introduction - adenovirus structure, AdVs are more resistant to lipid disinfectants, resulting in a prolonged survival in their external environment.218, 219 The combination of the factors listed above enables a large amount of AdVs to persist in the environment and cause outbreaks affecting hundreds of people.

2.5 Clinical manifestation and pathogenesis The incubation period of AdV infections range from two days to two weeks, depending on the serotype and the tissue(s) infected.220, 221 For gastroenteritis, the incubation period ranges between 3-10 days, and once symptoms initiate, diarrhoea can last up to two weeks, which is much longer compared to that of other viral gastroenteritis.222 Respiratory infections of AdV generally last from one to seven days, with symptoms such as fever, cough and sore throat, usually lasting a few days to a week.223 However, prolonged symptoms can be experienced in more severe infections, including pneumonia, which can last between two to four weeks. Conjunctivitis can persist from several days to a week, however more severe keratoconjunctivitis can last for several weeks.224

A high level of infectious particles (105 – 106 virions /mL) are usually found in the sputum or oral secretions of AdV infected individuals.225 Although many serotypes of AdV are found in the stool from patients with diarrhoea, only enteric AdV (F-40, F-41 and A-31) have been shown to be causative agents of gastroenteritis.202, 222 Previous studies have shown the presence of non-enteric adenoviral particles in the faeces of both healthy individuals and those with gastroenteritis, however, enteric AdVs are exclusively found in patients with gastroenteritis.

AdV infection is commonly asymptomatic. For example, 50% of healthy children have been shown to carry non-enteric AdV; whilst enteric AdVs are rarely present in healthy individuals.226 Enteric AdV levels can be as high as 1 ´ 1011 virions/g of stool in infected individuals, which is approximately eight times higher compared to the non-enteric serotypes found in the stool samples. This demonstrates the predilection of enteric AdVs (F-40, F-41, A-31, A-12) to replicate in the gastrointestinal tract. In contrast, non-enteric adenoviral particles (C-1, C-2, B-3, C-5), were reported to be excreted intermittently, although they can persist for months.169

2.6 Prevention and control There are currently no publicly available vaccines or antivirals against AdV infections. Although, a live oral enteric-coated vaccine against serotypes E-4 and B-7 was released in the United States in 1971 for personnel within the military.227 However, the vaccine production was

Chapter 2: General introduction - adenovirus halted in 1999 which subsequently resulted in outbreaks of AdV serotype E-4 and B-7 in training camps, with several fatalities reported.228 Furthermore, serotype B-14 emerged and became the predominant serotype to cause respiratory infections in United States military training sites,229, 230 this highlighted the continual need for a vaccine. In 2011, another live oral AdV vaccine against serotype E-4 and B-7 was approved for use in the United States military personnel aged between 17 to 50 years. A 100-fold decrease in AdV infections caused by serotype E-4, B-7 and B-14 was observed231 following the reintroduction of AdV vaccine. These results suggested that the emergence of AdV B-14 was due to the discontinuation of the first vaccine, since cross- reactive antibodies to AdV B-14 were developed following immunisation to AdV E-4 and B-7. This demonstrates the importance of selecting prevalent serotypes for the development of a successful vaccine. Therefore, to detect the predominant circulating strains, molecular epidemiolocal surveillance needs to be conducted at a population scale.

With the lack of publicly available antiviral and vaccine candidates for AdV infections, good hygiene practices are essential to prevent AdV outbreaks. AdV are resistant to many commonly used lipid-based disinfectants, and therefore can maintain infectivity for prolonged periods within environmental settings. To prevent healthcare-associated outbreaks, strict infection control practices need to be followed. These include the use of chlorine or formaldehyde as disinfectants,232 the use of alcohol-based hand gels233 or the inactivation of infected substances and materials by heating to 56°C for 30 mins or 60°C for 2 mins.232 Once an outbreak occurs, proper disinfection of the surrounding environment is critical to prevent another outbreak occurrence.

2.7 Environmental occurrence and persistence AdVs are commonly detected in wastewater, river water, drinking water and swimming pools.234-236 They are frequently detected in wastewater due to their resistance to ultraviolet (UV) light and thus can persist in the external environment for longer periods compared to other viruses.233 In addition, AdVs have been shown to persist in groundwater longer than F-specific RNA bacteriophages and can remain infectious in source waters used for drinking and recreational uses.237 This may lead to outbreaks of gastroenteritis, conjunctivitis or respiratory illness238-240 to the wider community, particularly if water sources are contaminated as hundreds of people could be affected. Several serotypes of AdV (F-41, A-12, F-40, C-2, B-3) have been frequently detected in wastewater and sludge around the globe.241-243 Despite the treatment of

Chapter 2: General introduction - adenovirus wastewater before it is discharged into rivers/oceans or re-used, enteric viruses have been detected in water matrices worldwide.244-248

Furthermore, high concentrations of AdV are detected in primary and secondary treated effluent and chlorinated effluent from wastewater treatment plants,249 with an average concentration of more than 106 genome copies/L.249, 250 This highlights that any surface water that has been contaminated with wastewater is likely not suitable for recreational activities.239

Viral contamination and detection in environmental matrices

Viral contamination in water matrices

Waterborne diseases is a global burden worldwide, with an estimated 2.2 million deaths per year, and cases of diarrhoeal, gastrointestinal and systemic illnesses every day.251, 252 Of those, 1.4 millions deaths are children.252 Infections can occur by the ingestion or contact with contaminated water by infectious agents, such as bacteria, viruses and protozoa.253 Culture dependent methods are widely used for the detection of pathogens in water, however, these methods are very time consuming and have a low sensitivity.254, 255 Bacterial levels are commonly used to measure pathogen contamination in water matrices, and amongst those, E. coli is extensively used as its detection is relatively easy and inexpensive. However, the use of bacteria to determine potential water contamination does not provide information on their host of origin, and levels do not correlate with the levels of other pathogens in the water, such as viruses and protozoa. Therefore, water that is considered pathogen free by monitoring only for bacteria may be contaminated with viruses or protozoa,256 and for accurate pathogen detection, it is essential to be able to detect viruses in water matrices.

Viral detection in environmental matrices using next generation sequencing

Next generation sequencing (NGS) technology allows the simultaneous sequencing of large amounts of genetic material. NGS has advanced and revolutionised pathogen genomic sequencing and genetic studies with increased turnaround times and outputs, generating more data at much lower cost per base sequenced.257 Owing to the availability and cost effectiveness of NGS, it is now used for full length viral genome sequencing, viral discovery and to study viral genetic diversity in clinical and environmental samples.

Despite the large number of molecular epidemiological studies of human viruses, the majority have been conducted with clinical specimens, or data obtained from hospitals, health institutes or diagnostic laboratories. Norovirus- and AdV-associated gastroenteritis is generally self-limiting and does not require hospitalisation or special medical attention. Therefore, the clinical data is only a partial representation of the total number of gastroenteritis viruses circulating in the human population and favours those who are symptomatic. A limited number of studies have examined the correlation in genotypic diversity of viruses between clinical samples and sewage networks.219, 247 Of those studies, the majority do not quantify the number of viruses and first-generation Sanger sequencing technologies were used to measure viral

Viral contamination and detection in environmental matrices diversity.242, 258-262 With the use of NGS, we can efficiently determine the composition of viral populations and monitor circulating genotypes within the wastewater systems.

Aims and outline of thesis

Norovirus and AdV are significant human pathogens that affect individuals in both developed and developing countries with substantial health and economic burdens on society. Infections from these viruses impact greatly on the most vulnerable populations within the community, including the elderly, children and immunocompromised individuals. Since the first identification of norovirus GII.4 epidemic strain in the mid-1990s, five other GII.4 variants have been associated with pandemic outbreaks of acute gastroenteritis and have been responsible for 65-80% of all infections. To develop a successful vaccine or antiviral, it is crucial to understand the mechanism of norovirus evolution, as well as the circulating strains within the population.

The multi-tropism nature of AdV, its resistance to disinfectants, and its ability to cause outbreaks showcase the importance for the development of vaccines or antivirals to combat this virus. Apart from the release of AdV serotype E-4 and B-7 vaccine for the U.S. military personnel, there are currently no vaccines or antivirals available for the remaining populations worldwide. For the development of effective vaccines or antivirals, the circulating serotypes of AdV must be understood at a population level.

Therefore, the overall aims of this thesis are to identify circulating and emerging strains of norovirus and AdV at a population level. In addition, the mechanisms of GII.4 norovirus evolution were investigated to understand factors that enable its persistence and contribute to their higher virological fitness.

In chapter three, a molecular epidemiological study was performed to investigate epidemics of norovirus-associated acute gastroenteritis in Australia and New Zealand between July 2014 and December 2016. RT-PCR, sequencing and phylogenetic analyses were used to determine the emergence of new recombinant strains or variants within the population. In addition, NGS technologies were used on complex wastewater samples to identify the genetic diversity of norovirus GII strains, including both symptomatic and asymptomatic cases. The results between clinical and wastewater samples were compared to see if any correlation could be observed.

In chapter four, the evolutionary dynamics of norovirus GII.4 viruses were explored. Recombination events between the most recent pandemic GII.4 variant (GII.4 Sydney 2012), its predecessor (GII.4 New Orleans 2009) and other non-GII.4 strains resulted in the emergence of novel GII.4 recombinant viruses in 2017. The evolution of the GII.4 viral capsid was investigated

Aims and outline of thesis as the majority of the recombinant strains maintain the GII.4 Sydney 2012 capsid. Furthermore, sudden increases of gastroenteritis cases were observed in mid-2017 in both Australia and New Zealand. Therefore, the molecular epidemiology of norovirus was analysed within the Oceania region to identify the prevalent circulating strains responsible for the increase in gastroenteritis outbreaks.

In chapter five, the RNA and DNA levels of norovirus and AdV, respectively, in wastewater were quantified. Understanding the quantity of enteric viruses in wastewater samples, can aid in determining the risks involved in the event of water contamination. In addition, the genetic diversity of AdV was characterised in both wastewater and clinical samples to better understand the circulating serogroups and serotypes at a population level.

Chapter 3: Norovirus molecular epidemiology 2014-16

3 Emerging recombinant noroviruses identified by clinical and wastewater screening

Text and figures included in this chapter are taken from the following publication:

Declaration

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations. This work is under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Jennifer Hoi Yin Lun [Candidate]

Authors contributions: Conceived and designed the experiments – JHL, PAW; Performed the experiments – JHL, JH, AS, DET, LM, BH ; Analysed the data – JHL, PAW; Contributed reagents/materials/analysis tools – JHL, JH, AS, JSE, DET, NEN, LM, JM, RJ, BH, DW, KAR, MJF, DED, JK, WDR, DD, NDC, PAW; Wrote the paper – JHL, PAW.

Chapter 3: Norovirus molecular epidemiology 2014-16

3.1 Abstract Norovirus is estimated to cause 677 million annual cases of gastroenteritis worldwide, resulting in 210,000 deaths. As viral gastroenteritis is generally self-limiting, clinical samples for epidemiological studies only partially represent circulating noroviruses in the population and is biased towards severe symptomatic cases and large outbreaks. Since infected individuals from both symptomatic and asymptomatic cases shed viruses into the sewerage system at a high concentration, wastewater samples are useful for the molecular epidemiological analysis of norovirus genotypes at a population level. Using Illumina MiSeq and Sanger sequencing, we surveyed circulating norovirus within Australia and New Zealand, from July 2014 to December 2016. Importantly, norovirus genomic diversity during 2016 was compared between clinical and wastewater samples to identify potential pandemic variants, novel recombinant viruses and the timing of their emergence. Whilst the GII.4 Sydney 2012 variant was prominent in 2014 and 2015, its prevalence significantly decreased in both clinical and wastewater samples over 2016. This was concomitant with the emergence of multiple norovirus strains, including two GII.4 Sydney 2012 recombinant viruses, GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P16/GII.4 Sydney 2012, along with three other emerging strains; GII.17, GII.P12/GII.3 and GII.P16/GII.2. This is unusual, as a single GII.4 pandemic variant is generally responsible for 65–80% of all human norovirus infections at any one time and predominates until it is replaced by a new pandemic variant. In summary, this study demonstrates the combined use of clinical and wastewater samples provides a more complete picture of norovirus circulating in the population.

Chapter 3: Norovirus molecular epidemiology 2014-16

3.2 Introduction Next generation sequencing (NGS) is a new and rapidly evolving technology that facilitates the simultaneous sequencing of large amounts of genetic material. Over the past decade, NGS has advanced and revolutionised pathogen genomic sequencing, with increased turn-around times and outputs, generating more data at much lower per base costs. Due to the availability and cost-effectiveness of NGS, it can be used as a tool to study viral genetic diversity in wastewater.219

Molecular epidemiological studies of norovirus are usually performed with clinical samples collected from patients presenting at medical facilities. However, this is not representative of the whole norovirus population and is biased towards severe symptomatic cases, thus offering only a narrow picture of the complete viral diversity. Community norovirus infection and prolonged shedding results in high levels of norovirus in wastewater,260, 263 making wastewater a useful medium for population-based, epidemiological scale, enteric virus surveillance.

Norovirus is a leading cause of acute viral gastroenteritis (AGE) among people of all age groups.264 Norovirus-associated outbreaks commonly occur in closed environments; including nursing homes, hospitals, childcare centres and cruise ships.265 Institutional outbreaks of viral gastroenteritis are difficult to control and have significant global economic burden to public health care systems (USD $4.2 billion) and communities (USD $60.3 billion) each year.1

Norovirus is transmitted from person-to-person, mainly through the faecal-oral route. It is highly infectious,266 and transmission is aided by its stability in the external environment. Clinical symptoms of norovirus infection include diarrhoea, vomiting, nausea, headaches, chills and abdominal cramps, usually lasting two to four days.267 Severe and persistent symptoms can be experienced in vulnerable populations, including children, immunocompromised individuals and the elderly.82

Norovirus is a non-enveloped, 27–35 nm virion which contains a positive sense, single- stranded RNA genome of approximately 7,500 nt. The Norovirus genus is classified within the Caliciviridae family, and can be divided into seven genogroups (GI-GVII), and further separated into more than 40 genotypes, based on the amino acid sequence of the full-length capsid region.30 GI, GII and GIV have been shown to infect humans, however, viruses from GII genotype 4 (GII.4) are responsible for pandemics and 65–80% of all norovirus infections globally.16, 33

Chapter 3: Norovirus molecular epidemiology 2014-16

Norovirus GII.4 evolution is driven through the generation of genetic variants, by antigenic drift and shift (recombination), leading to the emergence of novel and potential pandemic viruses approximately every 2-3 years.93 Amino acid divergence in the P2 protruding domain of the capsid (VP1) contributes to the emergence of these viruses through escape from herd immunity.93, 268 Another important mechanism driving the evolution and emergence of norovirus is recombination, with the breakpoint usually found at the ORF1/ORF2 overlap region, which separates the non-structural and structural regions of the genome.269

Six distinct norovirus GII.4 variants have been associated with pandemics of AGE over the past two decades.269, 270 Pandemic variants are distinguished based on the complete full-length capsid amino acid sequences, where more than 5% amino acid divergence is considered indicative of a new pandemic variant. GII.4 pandemic variants are named based on the location first identified, followed by the year. The GII.4 pandemic variants include: US 1995/96,91 Farmington Hills 2002,271 Hunter virus 2004,99 Den Haag 2006b33, New Orleans in 2009.119 and in early 2012, Sydney 2012. The GII.4 Sydney 2012 variant was first identified in March 2012 in Australia,105, 106 and originated through recombination between the GII.4 Osaka 2007 variant and GII.4 Apeldoorn 2008.93

Despite the predominance of norovirus GII.4, several non-GII.4 strains are also an important cause of norovirus infections. In the 2014/2015 winter in Southeast Asia, a sudden increase in gastroenteritis was observed, as the GII.17 Kawasaki strain emerged.116, 272 Despite this increase of GII.17 in Asian countries, this trend was not observed in North America or Europe, with only a low reported prevalence of GII.17 infections.117, 118 Norovirus GII.3 appears to play a major role in childhood infections and has been the capsid genotype most frequently associated with children for the past few decades.121 These strains are often recombinants, in particular the GII.3 capsid is often associated with a GII.P21 ORF1 (GII.P21/GII.3),121 formerly termed GII.Pb/GII.3.123

Continuous surveillance of circulating norovirus genotypes in the community is essential to better understand the evolution and diversity of norovirus. Only through early identification of potential pandemic variants can sufficient warning be provided to public health sectors to implement infection control measures. These include isolation of infected individuals, community health warnings and education for robust hygiene and de-contamination practices. Therefore, we examined the molecular epidemiology of circulating norovirus from clinical samples collected in Australia and New Zealand from July 2014 to December 2016, to monitor

Chapter 3: Norovirus molecular epidemiology 2014-16 current epidemic strains, to identify emerging pandemic variants, and to characterise recombinant viruses. Using NGS (Illumina MiSeq platform), the diversity of norovirus in wastewater was monitored at a city-based population scale in both Sydney and Melbourne, Australia. The changing patterns of prevalent strain emergence were compared to those found in clinical samples with a particular focus on the timings of viral emergence. This study highlights the importance of multiple sample types for a more complete understanding of the norovirus diversity at a population level and establishes the relationship between clinical and wastewater findings.

Chapter 3: Norovirus molecular epidemiology 2014-16

3.3 Materials and methods

3.3.1 Ethics statement UNSW Human Research Ethics Advisory Panel (HREAP) reviewed and approved the ethics application for this study (HC16826 and HC17459) (Appendix 8.1).

3.3.2 Clinical specimen collection and outbreak identification All samples were collected between July 2014 and December 2016. For Australia, clinical specimens were collected as part of routine diagnostic services requested by clinicians or public health agencies. A total of 285 norovirus positive clinical samples (New South Wales (NSW)=270, Australian Capital Territory (ACT)=10, Queensland (QLD)=5) were collected from public and private laboratories. Samples were collected from sporadic gastroenteritis cases and outbreaks. For New Zealand (NZ), clinical samples were collected as part of the New Zealand Ministry of Health norovirus outbreak surveillance program. Samples were referred to the Norovirus Reference Laboratory at the Institute of Environmental Science and Research by diagnostic community or hospital laboratory or directly through public health agencies. At least one sample from each gastroenteritis outbreak that was positive for norovirus (n=497) was genotyped. An outbreak is defined when two or more cases are linked by time, location or food sources, and confirmed to be the same genotype. All other samples are categorised as sporadic gastroenteritis cases.

3.3.3 Wastewater sample collection Influents of Bondi and Malabar wastewater treatment plants (WWTPs) from Sydney, Australia (250 mL) and Western Treatment Plants in Werribee, Melbourne (1 L) (population capacities of 296,350, 1,667,460 and 2,400,000 respectively), were collected each month from January to December 2016. All samples were delivered to University of New South Wales (UNSW) on the day of collection and stored at -80°C upon arrival.

3.3.4 Viral concentration and RNA extraction For clinical samples collected in Australia, 20% (v/v) suspensions in water were prepared. Viral RNA extraction was performed using QIAamp Viral RNA mini kit (Qiagen, Hilden, Germany) following manufacturer’s instructions.33 For clinical samples collected in New Zealand, 20% (v/v) suspensions were prepared and clarified with chloroform as previously described.273

Chapter 3: Norovirus molecular epidemiology 2014-16

Viral RNA extraction was performed using the Roche Viral Nucleic Acid Extraction Kit (Roche, Basel, Switzerland) in accordance to the manufacturer’s instructions.

Wastewater samples (12 mL) were centrifuged at 9,400× g at room temperature for 15 mins to remove debris. The supernatant was ultra-centrifuged at 186,000× g at 4°C for 1.5 hrs to concentrate virus and the pellet resuspended in 100 µL of PBS. Viral RNA extraction was performed using QIAamp Viral RNA mini kit (Qiagen).33

3.3.5 MS2 process control MS2 bacteriophage was used as extraction and process control for Australian clinical and wastewater samples. MS2 is a useful control for virus recovery when spiked into clinical and environmental samples to validate all downstream processes including viral RNA nucleic acid extraction, reverse transcription and PCR amplification.274 MS2 was prepared as 20 µL frozen aliquots with a concentration of 2.6 ´ 105 ± 1.6 ´105 viral genome copies and spiked into clinical and wastewater samples prior viral concentration. The virus recovery is considered validated if the cycle threshold (ct) value generated is 16.26 ± 1.6 (n=40).

3.3.6 RT-PCR of norovirus RNA from clinical and wastewater samples For Australian clinical samples, norovirus detection was first performed using reverse transcription polymerase chain reaction (RT-PCR) targeting the 5’ end of capsid gene (region C) of norovirus GI and GII, as described previously.93 Sequence from the 5’ end of norovirus capsid gene allows differentiation of genogroups and genotypes, and the primers used have previously been shown to be able to amplify and distinguish a wide range of genotypes.275, 276 For the detection of potential recombinant norovirus GII strains in Australia, a 575 bp region spanning the ORF1/ORF2 overlap was amplified.108 Full-length norovirus genomes from three samples collected from NSW were amplified as described in Eden et al.105 For New Zealand samples, a norovirus GI and GII duplex RT-qPCR followed by either a norovirus GI or GII RT-PCR that spanned the norovirus region B (within ORF1) and region C, across the ORF1/2 overlap, was used for genotyping as described previously.273 PCR products were purified and sequenced as previously described.273

To assess antigenic variation within the capsids of circulating strains, the full-length capsid gene sequences of representative GII.2, GII.3 and GII.4 strains were amplified.105

Chapter 3: Norovirus molecular epidemiology 2014-16

In preparation for MiSeq sequencing of wastewater amplicons, a second-round PCR was performed to attach Illumina sequencing adapters, this was carried out in accordance to the manufacturer’s protocol. With the addition of Illumina overhang adapters, the final amplicon size is 373 bp. All PCR amplicons were cleaned up using Agencourt™ AMPure XP beads (Beckman Coulter, California, United States).

3.3.7 Full-length norovirus genome sequencing preparation For the norovirus full-length genome sequencing of six Queensland samples, a second method was used. RNA was extracted from a 10% (v/v) faecal suspension using QIAamp viral RNA extraction kit (Qiagen). DNase Heat&Run (ArcticZymes, Tromsø, Norway) was used to remove host and other contaminating DNA. First strand cDNA was prepared using Protoscript II kit (New England Biolabs, Massachusetts, USA) followed by second strand DNA synthesis using a cocktail of Escherichia coli DNA ligase, DNA polymerase I and RNase H (NEB).

3.3.8 Nextera XT library preparation for NGS Illumina libraries were prepared using the Nextera XT DNA sample preparation kit and quantified using the Quant-iT PicoGreen dsDNA assay kit. The fragment sizes were evaluated using Tape Station D1000 (Agilent Technologies, California, USA). Libraries generated from wastewater and three NSW strains, were submitted to Ramaciotti Centre for Genomics (UNSW) for paired end sequencing on the Illumina MiSeq platform using a v2 300 cycle kit (2 × 150 bp). For the six Queensland strains, libraries were sequenced using the v2 mid-output kit on a NextSeq 500 machine in the Public Health Virology Laboratory, Queensland.

3.3.9 Norovirus phylogenetic analysis Phylogenetic analyses of the partial polymerase (172 bp) and capsid regions (282 bp) were used to determine norovirus GII genotypes identified in clinical samples. For GI genotypes, 172 bp and 223 bp of partial polymerase and capsid regions were used for phylogenetic analysis. Polymerase and capsid sequences were aligned separately using MUSCLE and compared to known reference sequences using maximum likelihood phylogenetic analysis,277 and confirmed with an online genotyping tool (NoroNet).278

3.3.10 NGS data analysis Sequences were removed if they did not range between 200-320 bp. The paired end sequences were merged and aligned to norovirus reference sequences. A minimum of two

Chapter 3: Norovirus molecular epidemiology 2014-16 representative reference sequences of each norovirus genotype were used. The parameters were as default for the Geneious mapper, v 9.0.5 (Geneious software R9, Biomatters, Auckland, New Zealand) and medium sensitivity was used for reference mapping and virus identification. The number of reads aligned to each reference genotype was used to quantify the abundance of each respective genotype within wastewater samples. The proportion representation of each genotype was then calculated by dividing the number of reads attributed to the genotype over the total number of sequencing reads.

3.3.11 Identification of recombination breakpoints Assembly of the reads generated from nine norovirus full-length genome sequencing was performed using Geneious software R9, by mapping reads to norovirus reference sequences. The full-length genome consensus sequences were then analysed using SimPlot (v3.5) to identify recombination breakpoints.130

Chapter 3: Norovirus molecular epidemiology 2014-16

3.4 Results The prevalence of circulating norovirus GI and GII genotypes in Australia and New Zealand were determined in this study, which included a total of 782 norovirus-positive specimens. Of these 285 norovirus-positive samples were collected from Australia (NSW, ACT and QLD), of which 238 were associated with sporadic cases and 47 were linked to outbreaks. In New Zealand, 497 laboratory-confirmed norovirus outbreaks, where representative samples were successfully genotyped, were included in this study (Table 3-1). Polymerase and capsid genotypes were determined by phylogenetic analysis of sequences using the maximum-likelihood method277 and confirmed using database searches (Table 3-1). To compare the identified norovirus sequences, a subset of 89 Australian (GI=11, GII=78) and 104 New Zealand (GI=33, GII=71) representative sequences were selected for phylogenetic tree construction (Figure 3-1 and Figure 3-2). All sequences were submitted to GenBank database, accession numbers MG585752-MG585937.

Chapter 3: Norovirus molecular epidemiology 2014-16

Table 3-1. Total number of norovirus genotypes identified in Australia and New Zealand from July 2014 to December 2016. Genotype No. of outbreak cases No. of sporadic cases Polymerase Capsid NZ (%) AUS 1 (%) AUS 2 (%) Undetermined GI.3 - - 2 (0.8) Undetermined GI.6 - 1 (2.1) 3 (1.3) Undetermined GI.9 1 (0.2) - - GI.P1 GI.1 2 (0.4) - 1 (0.4) GI.P2 GI.2 21 (4.2) - 1 (0.4) GI.P3 GI.3 22 (4.4) - 5 (2.1) GI.P5 GI.5 2 (0.4) - - GI.Pb GI.6 8 (1.6) - - GI.P6 GI.6 7 (1.4) 3 (6.4) - GI.P7 GI.7 1 (0.2) - - GI.P9 GI.9 3 (0.6) - - Undetermined GII.2 - - 2 (0.8) GII.Pe GII.2 - - 1 (0.4) GII.P2 GII.2 17 (3.4) - 2 (0.8) GII.P16 GII.2 27 (5.4) 4 (8.5) 41 (17.2) GII.P21 GII.3 11 (2.2) 1 (2.1) 4 (1.7) GII.P12 GII.3 37 (7.4) 2 (4.3) 21 (8.8) Undetermined GII.3 2 (0.4) - - Undetermined GII.4 Sydney 2012 6 (1.2) - - GII.P16 GII.4 Sydney 2012 20 (4.0) 12 (25.5) 25 (10.5) GII.Pe GII.4 Sydney 2012 180 (36.2) 18 (38.3) 60 (25.2) GII.P4 NO 2009 GII.4 Sydney 2012 39 (7.8) 4 (8.5) 38 (16.0) Undetermined GII.6 2 (0.4) - - GII.P7 GII.6 31 (6.2) 1 (2.1) 15 (6.3) Undetermined GII.7 5 (1.0) - - GII.P7 GII.7 5 (1.0) - 2 (0.8) GII.P8 GII.8 2 (0.4) - - GII.P3 GII.13 1 (0.2) - - GII.P16 GII.13 2 (0.4) - 4 (1.7) GII.P21 GII.13 - - 1 (0.4) GII.P7 GII.14 1 (0.2) - 1 (0.4) GII.P17 GII.17 27 (5.4) 1 (2.1) 9 (3.8) ND GII.20 1 (0.2) - - GII.P7 ND 1 (0.2) - - Mixed infection Mixed infection 8 (1.6) - - Undetermined Undetermined 5 (1.0) - - Total 497 47 238 1 AUS outbreak samples include NSW (n=37), ACT (n=7) and QLD (n=3) 2 AUS acute gastroenteritis samples include NSW (n=233), ACT (n=3) and QLD (n=2) NZ: New Zealand, AUS: Australia, NSW: New South Wales, ACT: Australian Capital Territory, QLD: Queensland

Chapter 3: Norovirus molecular epidemiology 2014-16

A B 99 GII.Pe (n=29) GII.4 (n=64) 82

Key 97 New Zealand (NZ) GII.P4 New Orleans 2009 (n=20) GII.20 AB542917 New South Wales (NSW) GII.Pj AY682552 Queensland (QLD) NZ15053/Jan/15 GII.P17 KC597139.1 1978 NZ15311/Apr/15 GII.P4 AY032605 MD145 1987 NSW005L/Dec/16 GII.P4 X86557 Lordsdale GII.3 AB385626 73 GII.P12 AF504671 NZ14968/Jul/14 NZ161033/Nov/16 NZ15219/Mar/15 NSW841C/Aug/14 87 NSW477U/Dec/14 NZ15391/Jun/15 NSW585N/May/15 NZ15438/Jul/15 98 87 NZ161033/Nov/16 NZ15819/Nov/15 NSW841C/Aug/14 NSW4540/Oct/16 QLD002/Sep/16 NZ16288/May/16 GII.P12 (n=15) NZ15438/Jul/15 GII.3 (n=22) NZ161015/Nov/16 NZ15819/Nov/15 NSW721P/Sep/16 82 NSW4540/Oct/16 QLD002/Sep/16 NSW0965/Jun/16 NZ16958/Nov/16 NSW721P/Sep/16 NZ16913/Oct/16 NZ16288/May/16 NSW604K/Nov/16 NZ161015/Nov/16 NSW0965/Jun/16 NZ15391/Jun/15 NSW4602/Oct/16 NSW4602/Oct/16 GII.P1 U07611 NZ16913/Oct/16 98 GII.Pc AY134748 NZ16958/Nov/16 GII.Pc JX846925 NSW604K/Nov/16 GII.Pm EU921353 GII.22 AB083780 GII.Pg GQ845370 NSW6242/Oct/16 NSW8996/May/15 QLD007/Sep/16 GII.P21 AY919139 NSW5641/Oct/16 GII.P21 AY682549 NSW5362/Nov/16 GII.P21 AY845056 NSW447T/Oct/16 95 NSW477U/Dec/14 NSW2083/Nov/16 NSW585N/May/15 GII.P21 (n=8) NZ16912/Oct/16 75 NZ15219/Mar/15 NZ161044/Dec/16 NZ14968/Jul/14 NZ161058/Dec/16 GII.P21 EU921389 NSW0101/Jun/16 82 NSW005L/Dec/16 NSW7280/Aug/16 NZ15053/Jan/15 86 QLD004/Sep/16 NZ15311/Apr/15 NSW2648/Oct/16 GII.2 (n=23) GII.Pf AY682550 NSW506P/Aug/14 93 GII.P2 DQ456824 NSW603H/Oct/16 NSW506P/Aug/14 74 NSW146N/Apr/15 GII.P2 X81879 NZ15483/Jul/15 NSW902G/Oct/16 NSW902G/Oct/16 NZ141569/Dec/14 GII.P2 (n=7) NZ141569/Dec/14 91 NZ15331/May/15 NZ15794/Nov/15 NZ15483/Jul/15 99 NZ16044/Jan/16 NZ15794/Nov/15 NZ15331/May/15 NZ16044/Jan/16 GII.2 AY682552 GII.Pg DQ379714 79 NSW2272/Mar/15 90 GII.Pa AB190457 GII.5 AJ277607 GII.Pa AF190817 GII.10 AY237415 GII.Pa AY588132 GII.1 U07611 GII.Ph AB089882 86 GII.12 AJ277618 92 GII.Pn GQ856469 GII.16 AY682551 91 GII.Pn HM635128 GII.18 AY823304 SW GII.P22 AB212306 76 GII.11 AB074893 SW 90 GII.P22 AB083780 GII.19 AY823306 SW GII.P22 AB233471 GII.21 EU019230 GII.P5 AF397156 NZ141032/Jul/14 NSW8990/Aug/14 91 NZ141049/Jul/14 92 GII.P16 (n=37) NSW294Q/Oct/14 GII.13 AY113106 GII.13 (n=7) 99 NSW8996/May/15 NSW329E/Oct/16 GII.P13 EF529741 NSW762N/Dec/16 GII.P13 EU921354 99 NZ16749/Aug/16 97 GII.P3 U02030 GII.17 LC037415 Kawasaki308 GII.P3 U22498 NSW6963/Dec/16 72 NSW9428/Jul/16 GII.P17 (n=13) NZ15877/Dec/15 96 GII.P18 AY823305 SW NZ15581/Sep/15 89 GII.P11 AB074893 SW NZ16149/Mar/16 GII.P11 AB126320 SW NZ16120/Mar/16 NZ161073/Dec/16 GII.17 (n=13) 82 GII.P8 AB039780 GII.P8 JF802498 NSW8772/Oct/16 NZ141199/Sep/14 GII.P8 (n=3) NZ15806/Nov/15 97 NZ15021/Dec/14 NZ141497/Nov/14 88 NZ15528/Jul/15 NZ14990/Jul/14 94 GII.P15 AB360387 GII.17 AB983218 Kawasaki323 GII.P15 GQ856474 GII.17 KJ156329 13-BH-1 NSW1339/Oct/16 NSW543Q/Jun/15 0.1 NZ15253/Mar/15 GII.6 HM633213 84 NZ141456/Nov/14 NSW534D/Jan/15 99 76 NSW458M/Dec/15 NSW223F/Jan/15 NZ15430/Jul/15 GII.P7 (n=6) NZ141246/Sep/14 NSW600H/Apr/15 NSW1339/Oct/16 GII.P7 AB258331 99 NSW0142/Jul/16 GII.P7 AB039776 NSW3258/Oct/16 GII.6 (n=12) 99 GII.P20 EU275779 NSW2620/Nov/16 GII.P20 EU424333 85 NZ161076/Dec/16 GII.P6 JX989075 NSW2111/Dec/16 GII.P6 AB039778 NZ15256/Apr/15 73 76 NZ141456/Nov/14 NZ15224/Mar/15 97 NSW223F/Jan/15 NSW922S/Dec/14 NZ15253/Mar/15 NZ141246/Sep/14 83 87 NSW0142/Jul/16 NSW600H/Apr/15 GII.14 (n=2) NSW3258/Oct/16 GII.P6 (n=11) GII.14 AY130761 NSW2111/Dec/16 84 GII.9 AY038599 NZ161076/Dec/16 94 GII.8 AB039780 NSW922S/Dec/14 NZ141199/Sep/14 GII.8 (n=3) NZ15224/Mar/15 NZ15021/Dec/14 86 NZ15256/Apr/15 NZ15528/Jul/15 NSW2620/Nov/16 GII.15 AY130762 NZ15430/Jul/15 97 GII.7 AJ277608 71 NSW458M/Dec/15 GII.7 (n=3) NSW534D/Jan/15 0.05

Figure 3-1. Phylogenetic analysis of ORF1/ORF2 overlap region of GII norovirus. Representative norovirus GII strains isolated in clinical samples (n = 149/686) were analysed phylogenetically. Strains analysed are denoted with a bullet (•) and colour coded to show sample origin (pink = NSW, blue = NZ, green = QLD). Sample names contain the geographical location and time of collection. Reference strains were downloaded from GenBank and are labelled with their genotype and accession number. (A) Phylogenetic analysis of 172 bp of the 3’ end of the polymerase gene of norovirus GII viruses. (B) Phylogenetic analysis of 282 bp from the 5’ end of the capsid gene of norovirus GII viruses. The scale bar indicates the number of nucleotide substitutions per site. Sequence alignments were performed using the MUSCLE algorithm. Maximum likelihood phylogenetic trees were produced with MEGA 7 software39 and bootstrap tests (1,000 replicates) based on the Kimura 2-parameter model.279 The bootstrap percentage values are shown at each branch point for values ≥70%.

Chapter 3: Norovirus molecular epidemiology 2014-16

NSW4789/Oct/16 NZ141421/Oct/14 A B NZ15458/Jul/15 NZ141421/Oct/14 NZ16956/Nov/16 NZ15458/Jul/15 NZ16709/Aug/16 72 NSW3104/May/17 NSW0654/Sep/16 NSW9045/May/17 94 GI.6a AJ277615 NZ16956/Nov/16 NSW3104/May/17 NZ16709/Aug/16 NSW9045/May/17 GI.6 (n=15) NZ16706/Aug/16 GI.Pb (n=12) NZ161048/Dec/16 NZ161048/Dec/16 91 NZ16706/Aug/16 88 NSW3747/Oct/16 94 NSW5956/Sep/16 NSW5956/Sep/16 NSW3747/Oct/16 99 NSW4789/Oct/16 NZ141085/Aug/14 NSW0654/Sep/16 81 GI.6b AF093797 GI.Pb JQ388274 95 NZ141380/Oct/14 NZ16865/Oct/16 NZ141397/Oct/14 NZ16129/Mar/16 NZ15506/Jul/15 98 NZ15072/Jan/15 94 NZ15714/Oct/15 GI.P2 KF306212 GI.5 (n=2) 78 GI.5a AJ277614 NZ141140/Aug/14 GI.5b AB039774 NZ141218/Sep/14 GI.P2 (n=10) 99 NSW095G/Nov/16 NZ141236/Sep/14 96 NZ16949/Oct/16 GI.1 (n=2) 93 NZ141536/Nov/14 GI.1 M87661 NZ15094/Feb/15 GI.4 AB042808 NZ15734/Oct/15 NSW757Y/Aug/14 NSW757Y/Aug/14 NZ141236/Sep/14 99 NZ16949/Oct/16 99 99 NZ141140/Aug/14 NSW095G/Nov/16 GI.P1 (n=2) GI.2 L07418 GI.P1 KF429765 NZ141536/Nov/14 NZ141085/Aug/14 NZ15734/Oct/15 99 NZ141397/Oct/14 GI.2 (n=10) 99 GI.P6 (n=3) NZ16129/Mar/16 NZ141380/Oct/14 NZ141218/Sep/14 GI.P6 AF093797 NZ15072/Jan/15 GI.P4 JN603273 NZ15094/Feb/15 98 GI.P5 AF414406 NZ16865/Oct/16 99 NZ15506/Jul/15 GI.P5 (n=2) GI.8 AF538679 NZ15714/Oct/15 91 NSW1928/Sep/16 99 NZ141160/Aug/14 GI.3d EF547396 100 NZ14975/Jul/14 96 GI.P9 (n=2) GI.3c AB187514 GI.P9 GU296356 GI.3a U04469 GI.P7 JN603265 NSW6658/Jan/17 GI.P8 GU299761 NSW6667/Jan/17 79 91 NSW088O/Feb/17 NSW088O/Feb/17 99 NSW6668/Jan/17 NSW6668/Jan/17 71 NSW9896/May/17 NSW9896/May/17 70 NSW6658/Jan/17 NZ15623/Sep/15 99 NSW6667/Jan/17 GI.3b AF145709 GI.P3 JN603244 NSW168V/Dec/15 NSW1928/Sep/16 NSW460C/Jan/16 GI.3 (n=21) NZ15623/Sep/15 NSW794J/Jan/17 NZ16360/Jun/16 99 NSW219K/Dec/15 90 0.1 NZ16235/Apr/16 NZ16071/Feb/16 NZ16472/Jul/16 GI.P3 (n=21) NZ16391/Jun/16 NSW521B/Dec/15 NZ16715/Aug/16 NZ16075/Feb/16 NZ16330/May/16 93 NSW219K/Dec/15 NZ16360/Jun/16 NSW460C/Jan/16 NSW521B/Dec/15 NSW168V/Dec/15 NZ15034/Jan/15 NZ15034/Jan/15 NZ16472/Jul/16 NZ16071/Feb/16 NZ16075/Feb/16 NZ16330/May/16 NZ16235/Apr/16 NZ16391/Jun/16 GI.7c AJ844469 NZ16715/Aug/16 99 GI.7a AJ277609 NSW794J/Jan/17 Key GI.7b JN899243 99 GI.9 HQ637267 New Zealand (NZ) NZ141160/Aug/14 GI.9 (n=2) New South Wales (NSW) NZ14975/Jul/14 0.1 Figure 3-2. Phylogenetic analysis of ORF1/ORF2 overlap region of GI norovirus. Representative norovirus GI strains isolated in clinical samples (n = 52/83) are shown in this phylogenetic analysis. Strains analysed in this study are denoted with a bullet (•) and colour coded to show sample origin (pink = NSW, blue = NZ). All sample names contain the geographical location and time collection.

Chapter 3: Norovirus molecular epidemiology 2014-16

Reference strains were downloaded from GenBank and are labelled with their genotype and accession number. (A) Phylogenetic analysis of 172 bp of the 3’ end of the polymerase gene of norovirus GI viruses. (B) Phylogenetic analysis of 223 bp of the 5’ end of the capsid gene of norovirus GI viruses. The scale bar indicates the number of nucleotide substitutions per site. Sequence alignments were performed using the MUSCLE algorithm. Maximum likelihood phylogenetic trees were produced with MEGA 7 software39 and bootstrap tests (1,000 replicates), based on the Kimura 2-parameter model.279 The bootstrap percentage values are shown at each branch point for values ≥70%. Norovirus GII.4 distribution in Australia and New Zealand

A decline in the prevalence of GII.Pe/GII.4 Sydney 2012 was observed over the study period in both Australia and New Zealand (Figure 3-3). Specifically, in Australia in 2014 (July to December), the Sydney 2012 variant represented 74.0% of all noroviruses, which decreased to 37.5% in 2015 and only accounted for 10.8% of noroviruses in 2016 (Table 3-1, Figure 3-3A). This was also observed in New Zealand, with the Sydney 2012 variant responsible for 56.7% of norovirus outbreaks from July to December 2014, 46.6% in 2015 and 16.0% in 2016 (Table 3-1, Figure 3-3B).

Chapter 3: Norovirus molecular epidemiology 2014-16

A Australia B New Zealand GII.Pe/GII.4 Sydney 2012

) 100 100 GII.P4 NO 2009/GII.4 Sydney 2012 % ( GII.P16/GII.4 Sydney 2012 s

e f

p GII.P16/GII.2

o 75 75 y GII.P7/GII.7 t

n GII.P12/GII.3 o

o GII.P8/GII.8 i n

t GII.P17/GII.17 e u g 50 50 GII.P3/GII.13

b GII.P21/GII.3 i s

r GII.P21/GII.13 u t GII.P16/GII.13 r s i i v GI GII.P7/GII.14 D o 25 25 r mixed infec�ons

o GII.P2/GII.2 n GII.Pe/GII.2 not determined 0 0 GII.P7/GII.6 others 2014 2015 2016 2014 2015 2016 Year Year C Oceania Region 70 s

k 60 a e r

b 50 t u

o 40 / s e

s 30 a c

o 20

. o 10 N 0 J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D 2014 2015 2016 Time (month/year) D NSW Ministry of Health 110 100 l d 90 a e t n

r 80 o i o t

p 70 u e t r i

t 60 s s k n 50 i a

f e

r 40 o

b . t

o 30 u N o 20 10 0 J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D 2014 2015 2016 Time (month/year)

Figure 3-3. Yearly and monthly distributions of norovirus genotypes identified in the Oceania region, compared with institutional outbreaks reported to NSW Ministry of Health between July 2014 to December 2016. (A) The prevalence of norovirus genotypes identified in Australia during the study period. A total of 238 individual norovirus cases and 47 outbreaks were sequenced and genotyped from Australia (NSW, ACT and QLD). (B) All samples collected, sequenced and genotyped from New Zealand represented viruses from 497 separate outbreaks. Samples with unknown capsid genotypes and mixed GI/GII infections were excluded in this analysis (n = 14). (C) The monthly norovirus genotypic distribution for Australia and New Zealand combined throughout the study period (2014-2016) was examined. Different genotypes and GII.4 variants are colour coded as per the legends. All norovirus GI viruses identified are grouped together under GI (dark grey), and others include all GII viruses identified (GII.P2/GII.2, GII.Pe/GII.2, GII.P7/GII.6, GII.P7/GII.7, GII.P16/GII.13, GII.P21/GII.13) that are not indicated in the legends. (D) The monthly number of institutional outbreaks reported to the NSW Ministry of Health.

Chapter 3: Norovirus molecular epidemiology 2014-16

Whilst the GII.Pe/GII.4 Sydney 2012 variant itself exhibited a rapid decline over the study’s time frame, viruses with a Sydney GII.4 capsid remained prevalent throughout 2016, representing 47.2% and 45.5% of the total norovirus population in Australia and New Zealand, respectively (Figure 3-3C). This was resultant of the two newly emerged GII.4 Sydney derived recombinant forms. The first recombinant, GII.P16/GII.4 Sydney 2012, was initially identified in 2015 in Australia, and accounted for 14.6% and 15.9% of norovirus identified in 2015 and 2016, respectively. It was the third most predominant norovirus in circulation in 2016 (Figure 3-3A). Although, this recombinant first emerged in August 2015 in New Zealand, the next outbreak associated with GII.P16/GII.4 Sydney 2012 was not identified until April 2016 and accounted for only 10.2% of outbreaks in 2016 (Figure 3-3B). The second Sydney recombinant detected, GII.P4 New Orleans 2009/GII.4 Sydney 2012 (GII.P4 NO 2009/GII.4 Sydney 2012) emerged in Australia in May 2015 and represented 8.3% of cases, which increased to 20.5% in 2016 (Figure 3-3A).

Similarly, in New Zealand, the GII.4 NO 2009/Sydney 2012 strain, emerged in February 2013 (with two outbreaks),108 was the predominant (36/187, 19.3%) norovirus detected in outbreaks in 2016. Of these 35 outbreaks, 23 were identified in nursing homes or hospital wards between July and September 2016. The second most frequently detected norovirus was the GII.Pe/GII.4 Sydney 2012 variant (30/187, 16.0%) (Figure 3-3B). The emergence of these new viruses was accompanied by an increase in institutional outbreaks of gastroenteritis reported to the NSW Ministry of Health, particularly in the winter period (June-August) of 2016 (Figure 3-3D).

3.4.1 Other emerging noroviruses The GII.17 Kawasaki strain was first identified in June 2015 in Australia (Table 3-2) and accounted for 2.1% of 2015 norovirus cases and 4.6% in 2016, including one outbreak (Table 3-1, Figure 3-3A). In New Zealand, the GII.17 strain was identified in April 2014 and was responsible for 1.7% (n=3) of all outbreaks that year, followed by 3.4% in 2015 and 10.2% in 2016 (Table 3-1, Figure 3-3B).

In addition to the GII.4 Sydney recombinants, a novel GII.P16/GII.2 recombinant emerged in Australia in April 2015 (Table 3-2). Its prevalence steadily increased in 2016, accounting for 23.6% of all noroviruses detected that year, including three outbreaks (Table 3-1, Figure 3-3A). In New Zealand, this recombinant was first identified from an outbreak in March 2016, and that year the strain accounted for 13.9% of all norovirus outbreaks (Table 3-1, Figure 3-3B).

Chapter 3: Norovirus molecular epidemiology 2014-16

Table 3-2. Full-length genome sequences of novel noroviruses identified in this study and their reported outbreak dates.

Genotype Sample ID of full GenBank Date of Sequence Australia New Zealand (polymerase/capsid) length sequences accession no. collection length (bp) First case First outbreak Outbreak setting First outbreak Outbreak setting GII.P17/GII.17 NSW9428 KY905330 Jul 2016 7491 Jun 2015 Jul 2016 residential Jul 2014 nursing home GII.P17/GII.17 NSW543Q KY905332 Jun 2015 7533 GII.Pe/GII.4 Sydney 2012 QLDB101 KY905333 Sep 2016 7497 Mar 2012 Apr 2012 hospital Feb 2012 nursing home GII.P4 NO 2009/GII.4 Sydney 20121 NSW789Z KY905331 Aug 2016 7546 May 2015 Aug 2016 cruise ship Oct 2014 nursing home GII.P16/GII.4 Sydney 20121 QLDB309 KY905335 Sep 2016 7529 Jul 2015 Jul 2016 cruise ship Aug 2015 nursing home GII.P12/GII.31 QLDB207 KY905334 Sep 2016 7498 Aug 2014 Jun 2016 residential Apr 2015 commercial food operator GII.P16/GII.21 QLDB411 KY905336 Sep 2016 7527 GII.P16/GII.2 QLDB512 KY905337 Sep 2016 7522 Apr 2015 Aug 2016 residential Mar 2016 school/college GII.P16/GII.2 QLDB614 KY905338 Oct 2016 7522 1 Sequences selected for Simplot analysis in Figure 3-5

The GII.P21/GII.3 recombinant, often associated with childhood infections, was seen in Australia in both 2014 (4.0%) and 2015 (4.2%), however, it only accounted for one case in 2016 (Figure 3-3A). This trend was also observed in New Zealand, where it accounted for 7.6% of all outbreaks in 2014/15, (of which 63.6% were associated with child-care facilities) but had disappeared by June 2015 (Figure 3-3B). In Australia, concomitant with the GII.P21/GII.3 decline, a second emerging virus (GII.P12/GII.3) was identified in 2016 (11.3% of cases) and was largely associated with childhood infections (20/22 cases). However, these cases were not associated with any norovirus outbreaks. This virus was also identified in New Zealand in 2015 (9.7% of outbreaks) and 2016 (10.2% of outbreaks). In contrast, only one third of those outbreaks occurred in childcare centres, with the majority in long-term care facilities (48.6%).

3.4.2 Genogroup I norovirus In Australia, GI accounted for only 5.5% of all norovirus cases, with four different GI capsid genotypes identified. Norovirus GI.3 (n=7/16) and GI.6 (n=7/16) were the most common, followed by GI.2 (n=1/16) and GI.1 (n=1/16) (Table 3-1, Figure 3-2). In comparison, norovirus GI was more prevalent in New Zealand and accounted for 13.3% of the 497 norovirus-associated outbreaks. A total of six wildtype GI strains were identified; GI.P3/GI.3 as the most prevalent (22/66, 33.3%), followed by GI.P2/GI.2 (21/66, 31.8%) and GI.P6/GI.6 (7/66, 10.6%) (Table 3-1). A recombinant strain, GI.Pb/GI.6, was also identified in four outbreaks (Table 3-1).

3.4.3 Outbreak settings in Australia and New Zealand A total of 544 norovirus-associated AGE outbreaks were identified during the study period. In Australia norovirus GI (all GI.6) and GII were responsible for four and 43 outbreaks, respectively (NSW=37 outbreaks, ACT=7, QLD=3) (Table 3-1, Figure 3-3A), whilst in New Zealand, norovirus GI and GII were responsible for 66 and 426 outbreaks, respectively, with the genogroup of five outbreaks not determined (Table 3-1, Figure 3-3B). In New Zealand, GI

Chapter 3: Norovirus molecular epidemiology 2014-16 outbreaks were caused by GI.P3/GI.3 (33.3%), followed by GI.P2/GI.2 (31.8%) and GI.Pb/GI.6 (12.1%).

The pandemic Sydney 2012 variant was the most commonly detected outbreak virus in both Australia (18/47, 38.3%) and New Zealand (180/497, 36.2%), across the 2.5-year study period. In Australia, the second most prevalent outbreak strain was the new GII.P16/GII.4 Sydney 2012 recombinant (23.4%), whereas GII.P4 NO 2009/GII.4 Sydney 2012 was the second most common outbreak virus in New Zealand (7.8%) (Table 3-1).

The majority of outbreaks were reported in nursing homes in both Australia (55.3%) and New Zealand (57.3%) (Figure 3-4). In Australia, hospitals wards were the second most common setting for reported norovirus outbreaks (12/47, 25.5%), followed by cruise ships (5/47, 10.6%) and private homes (2/47, 4.3%) (Figure 3-4A). As majority of the outbreaks occurred in nursing homes and hospital wards, the average age distribution identified in outbreaks was 78, ranged between 3 to 101. In New Zealand, a wider range of outbreak settings were identified, with the childcare centres the second most common setting (64/497, 12.9%), followed by commercial food operators (48/497, 9.7%) (Figure 3-4B). Eight (1.6%) outbreaks were identified as mixed GI and GII genotypes infection, all detected in New Zealand.

A 55.3% Nursing home 57.3% B 25.5% Hospital ward 6.0% 10.6% Cruise ship 0.4% 4.3% Private home 2.6% 2.1% Commercial food operator 9.7% 0% Childcare centre 12.9% 0% Prison 0.4% 0% School/college and camp 4.6% 0% Social event 3.0% Australia 0% Other 1.6% New Zealand n=47 2.1% Unknown 1.4% n=497

Figure 3-4. Norovirus outbreak settings identified in Australia and New Zealand between July 2014 and December 2016. The setting for norovirus outbreaks was compared between Australia and New Zealand during the study period. A total of 47 and 497 outbreaks were identified in Australia and New Zealand, respectively. An outbreak is defined as two or more cases linked by location and time.

Chapter 3: Norovirus molecular epidemiology 2014-16

3.4.4 Recombinant breakpoint identification in norovirus full length genomes To further characterise clinically important strains, nine norovirus full-length genomes of representative viruses were analysed using Simplot to identify recombination breakpoints (Figure 3-5). The majority consensus sequence of norovirus assembled reads were used for each virus with coverage ranging between 8.2 × 106–10.4 × 106. This analysis revealed that both GII.17 viruses were shown to be wild-type viruses with between 99.5% and 99.7% identity to the prototype GII.17 Kawasaki-323 sequence. The other five viruses analysed were either intra- genotypic (GII.Pe/GII.4 Sydney 2012 and GII.P4 NO/GII.4 Sydney 2012), or inter-genotypic (GII.P16/GII.4 Sydney 2012, GII.P16/GII.2 and GII.P12/GII.3) recombinants with breakpoints identified at the ORF1/ORF2 overlap between nucleotide positions 5023 and 5101 (Figure 3-5).

Chapter 3: Norovirus molecular epidemiology 2014-16

(A) Query: QLDB309/Sep/16 (GII.P16/GII.4 Sydney 2012) (B) Query: QLDB411/Sep/16 (GII.P16/GII.2) ORF1 ORF3 ORF1 ORF3 ORF2 ORF2 100 100 GII.4 Syd 2012 GII.2 90 GII.16 90 GII.16 80 80 (%)

70 70 60 60 50 50 40 40 30 30 20 20 Seuqence identty (%) Sequence identty 10 10 0 5066 0 5062 0 1000 2000 3000 4000 5000 6000 7000 0 1000 2000 3000 4000 5000 6000 7000 Positon (nt) Positon (nt)

(C) Query: NSW789Z/Aug/16 (GII.P4 New Orleans 2009/GII.4 Sydney 2012) (D) Query: QLDB207/Sep/16 (GII.P12/GII.3) ORF1 ORF3 ORF1 ORF3 ORF2 ORF2 100 100 GII.4 Syd 2012 GII.3 90 GII.4 NO 2009 90 GII.12 80 80 (%)

y 70 70 60 60 50 50 40 40 30 30 20 20 Sequence identty (%) Sequence identt 10 10 5101 5023 0 0 0 1000 2000 3000 4000 5000 6000 7000 0 1000 2000 3000 4000 5000 6000 7000 Positon (nt) Positon (nt)

Figure 3-5. Simplot analysis of novel norovirus recombinant strains. Representative sequences of emerging viruses were subjected to full-length genome sequencing and analysed using Simplot for the identification of recombination breakpoints. For all recombinant strains, a single breakpoint was identified at the ORF1/ORF2 overlap region. (A) Simplot for recombinant strain GII.P16/GII.4 Sydney 2012 (QLDB309/Sep/16, GenBank accession number KY905335) with a breakpoint identified at nucleotide position 5066. (B) Simplot for recombinant strain GII.P16/GII.2 (QLD411/Sep/16, GenBank accession number KY905336) with a breakpoint identified at nucleotide position 5062. (C) Simplot for recombinant GII.P4 New Orleans 2009/GII.4 Sydney 2012 (NSW789Z/Aug/16 (GenBank accession number KY905331) with a single breakpoint identified at nucleotide position 5101. (D) Simplot for recombinant GII.P12/GII.3 (QLDB207/Sep/16, GenBank accession number KY905334 with a breakpoint at nucleotide position was 5023. The breakpoint positions are shown by red lines. Each analysis used a window size of 300 nt and a step size of 5 nt. The reference strains used are as follows: GII.4 Syd 2012 for NSW0514/2012/AU (GenBank accession number JX459908), GII.4 NO 2009 for NSW001P/2008/AU (GenBank accession number GQ845367), GII.3 for HK71/1978/CHN (GenBank accession number JX846924), GII.12 for 04-179/2005/JP (GenBank accession number AB220922), GII.16 for Neustrelitz260/2000/DE (GenBank accession number AY772730), GII.2 for KL109/1978/MYS (GenBank accession number JX846925).

Chapter 3: Norovirus molecular epidemiology 2014-16

3.4.5 Norovirus capsid genotype diversity in Australian wastewater samples This study aimed to capture a complete picture of norovirus diversity at a population level, with the use of NGS technologies on wastewater samples from two major Australian cities, Sydney and Melbourne. Norovirus PCR amplicons (306 bp) were generated monthly for 2016 from Malabar, Melbourne and Bondi wastewater samples, and subjected to Illumina MiSeq sequencing. The time period for wastewater collection is shorter compared to clinical sample collection, which spanned from July 2014 to Dec 2016. An average of 588,775 reads (range 105,082 to 1,452,622) were generated from each collection point. All raw data were submitted to Sequence Read Archive (SRA) database, accession no. PRJNA417367. Reads were merged and assembled to known reference strains using Geneious and their relative abundance determine based on mapped read counts. A total of eighteen norovirus capsid genotypes were identified across all three sites, and the dominant variants included GII.4, GII.17, GII.2, GII.13, GII.3 and GII.1 (Figure 3-6).

Bondi Malabar Melbourne A (capacity 296 350) (capacity 1 667 460) (capacity 2 400 000)

) 100 100 100 % (

s GII.1

e f 75 GII.2

p 75 75 o y

t GII.3 n o

o GII.4 i n t e 50 50 50 GII.5 u g

b i

s GII.6 r u t

r GII.7 s i

i 25 25 25 v GII.8 D o r GII.10 o n 0 0 0 GII.11 J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D GII.12 Time (month) Time (month) Time (month) GII.13

GII.14 4.9%

B 6.1% 8.4% 5.3% 6% 5.6% GII.16 10.8% 5.6% GII.17 16.2% GII.20 8.5% GII.21 GII.22 52.2% 43.5% 18.4% 46.4% 26.5% 9.7%

12%

No. of reads: 79 567 No. of reads: 231 909 No. of reads: 122 529 (5.1% of total reads) (12.8% of total reads) (6.2% of total reads)

Figure 3-6. Norovirus genotype distribution in wastewater samples collected from Sydney and Melbourne, 2016. Norovirus genotypic distribution was determined in wastewater samples by capsid amplicon sequencing using Next Generation Sequencing (NGS) technology. Samples were sequenced on the MiSeq platform and Geneious was used for merging and mapping of the reads to the reference sequences. Capsid genotypes are labelled in different colours as indicated by the legends. (A) The genotype distribution of norovirus capsids identified in two wastewater treatment plants in Sydney (Bondi and Malabar) and one in Melbourne, Australia. The Y-axis represents the percentage norovirus distribution in each sample, and the time is indicated on the X-axis. (B) To further investigate the less predominant capsid genotypes, the three most predominant capsid genotypes (GII.2, GII.4 and GII.17) across all sites, were removed and the distribution of the remaining genotypes plotted as pie charts. The number of reads attributed to non-GII.2, GII.4 and GII.17 are listed below the pie chart.

Chapter 3: Norovirus molecular epidemiology 2014-16

Interestingly, a decline in the proportion of GII.17 as a percentage of total reads was observed from early 2016. From its peak of 68.6% of the total WWTP norovirus population in January (average of all three sites), it decreased to 16.6% by April and accounted for only 4.1% in August 2016 (Figure 3-6). This reduction was accompanied by an overall increase in the GII.4 population from March (53.4%), which was steady until the emergence of the GII.2 norovirus strain (Figure 3-6). An increase of GII.2 was observed in all three sites from May 2016 onwards. In Malabar, GII.2 steadily increased from May (4.0%), July (42.5%), September (80.8%) to December (99.9%), replacing GII.4 as the predominant strain identified (Figure 3-6A). Similarly, GII.2 strains accounted for less than 3% in the first months of 2016 in Melbourne, increased to 32.1% in June and 98.3% in December. This GII.2 increase was also observed in Bondi; 2.5% in April, 56.7% in August and 99.7% in November (Figure 3-6A).

Chapter 3: Norovirus molecular epidemiology 2014-16

3.5 Discussion In order to design effective control strategies such as vaccines, it is important to understand the prevalence and diversity of current and emerging noroviruses. The genotypes of circulating norovirus strains were determined in Australia and New Zealand between July 2014 and December 2016 in clinical samples. However, as people infected with norovirus would not necessarily seek medical advice this can create a bias towards severe symptomatic cases and therefore does not fully represent circulating noroviruses within a population, with less pathogenic strains perhaps under-represented. The application of NGS to monitor norovirus population diversity in wastewater can provide a better understanding of norovirus epidemiological data at the population scale by screening wastewater produced from many thousands or millions of people. Moreover, the comparison of clinical and wastewater data allows a more complete representation of norovirus epidemiology at a city-based population level.

Sequencing and phylogenetic analysis of the polymerase and capsid overlapping regions revealed the Sydney pandemic variant (GII.Pe/GII.4 Sydney 2012) remained the predominant strain in the Oceania region in 2014 (65.4% of norovirus outbreaks and cases) and 2015 (42.1%). The Sydney 2012 variant emerged in 2012 and over the ensuing four years herd immunity in the population is likely to have accumulated against the virus. This could account for the sudden decline of GII.4 Sydney pandemic variant in 2016 (only 13.4% of norovirus cases), concomitant with the emergence of five new viruses including two novel GII.4 Sydney 2012 recombinants, GII.P12/GII.3, GII.P16/GII.2 and GII.17. The emergence of new viruses is likely to be responsible for the increase of institutional gastroenteritis outbreaks reported to the NSW Ministry of Health between July and November 2016.

The maintenance of the GII.4 Sydney 2012 capsid in the population was facilitated by two separate recombination events, resulting in the emergence of the intra-genotypic GII.P4 NO 2009/GII.4 Sydney 2012 and the inter-genotypic GII.16/GII.4 Sydney 2012 recombinant viruses. These two recombination events likely provided the viruses a selective advantage to evade host immunity directed towards the GII.Pe encoded non-structural region of the Sydney variant (GII.Pe/GII.4 Sydney 2012). The GII.P4 NO 2009/GII.4 Sydney 2012 virus arose though an unusual recombination event between a pandemic variant and its pandemic predecessor.280 In Europe, this strain was identified in late 2012 in the UK and Denmark.281, 282 However, this strain was first identified in early 2013 in New Zealand (data not shown) and May 2015 in Australia, but

Chapter 3: Norovirus molecular epidemiology 2014-16 remained at low prevalence throughout 2015. It was not until 2016 when it became a major cause (19.6%) of gastroenteritis within the Oceania region. This timing is consistent with a study by Bruggink et al. in Victoria, Australia, who showed this recombinant emerged in Melbourne in August 2015, but did not cause a significant increase of gastroenteritis until June 2016.283

Another GII.4 recombinant, GII.P16/GII.4 Sydney 2012, emerged in mid-2015, and circulated in 2016, where it was then responsible for 12.5% of noroviruses identified in the Oceania region. This increase in strain activity was also observed in France between 2016 and 2017, where it was responsible for 24% of all norovirus outbreaks identified.284 In addition, this strain became predominant in the USA, the UK285 and South Korea286 in 2017.

GII.17 was found to be the cause of increased gastroenteritis in Southeast Asian countries during winter of 2014,113, 272, 287 but did not cause epidemics in other countries and only circulated at low prevalence. This is consistent with our findings where it accounted for less than 2.5% of norovirus cases in 2014/15 and only 4.6% of all noroviruses identified in Australia in 2016.115, 117, 118 However, surprisingly, across all three WWTP sites in Sydney and Melbourne higher viral prevalence was observed with an average of 68.7% of all reads were attributed to GII.17 in the early months of 2016. These findings suggest GII.17 could be less virulent compared to other genotypes which results in an underestimation of prevalence when only clinical samples are used for norovirus epidemiological studies.

A third recombinant virus, GII.P16/GII.2, circulated at a low prevalence (two cases in 2013108 and a single case in 2015) until June 2016 where it was responsible for 18.8% of all sporadic and outbreak cases identified in the Oceania region. This sudden increase of GII.P16/GII.2 was also observed in Germany, France, and China. In Germany, it was found to be the most predominant strain between September and December 2016, accounting for 47.7% of acute gastroenteritis cases and 42% of outbreaks.288 In France, GII.P16/GII.2 was responsible for 14% of outbreaks identified during the winter seasons of 2016 and 2017.284 Similarly, this increase of GII.P16/GII.2 was observed in China, where it was first detected in August 2016 and caused 79% (44/56) outbreaks identified in November and December 2016.289 Analysis of the VP1 full-length capsid sequences revealed no amino acid changes to account for the rapid predominance through antigenic variation. Therefore, amino acid substitutions in the GII.P16 polymerase have been proposed as a possible cause of the GII.P16/GII.2 emergence through changes in polymerase function.290

Chapter 3: Norovirus molecular epidemiology 2014-16

Norovirus GII.P21/GII.3 has been a major cause of childhood gastroenteritis since 2002.123, 291 In addition to the other emerging viruses detected, a novel GII.P12/GII.3 recombinant was identified in 2015 and 2016 in New Zealand and Australia, respectively. This recombinant was found to be associated with childhood infections, and likely replaced the GII.P21/GII.3 recombinant childhood strain, as its prevalence declined rapidly from May 2015 onwards. The majority (90%) of Australian patients infected with GII.P12/GII.3 strain were under 12 years old, suggesting this virus has a predilection for infecting children. In 2016, this recombinant was detected at a prevalence of 8.1% in clinical samples compared to 0.57% of genotypes identified in wastewater samples. We hypothesise that this is because children have lower norovirus immunity, and infection would elicit more severe symptoms upon their first norovirus exposure. Therefore, children are more likely to visit a hospital or general practitioner for medical advice compared to adults. This is not without precedence, for example children with respiratory syncytial virus infection results in more severe outcomes and are present for medical intervention far more than adults.292 Therefore, the use of clinical samples for surveillance could create bias towards viruses from children and selection viruses that induce symptoms, thus skewing genotypic distribution patterns.

Wastewater is an ideal source for molecular epidemiological studies because infected individuals excrete high levels of virus and continue to shed for up to eight weeks, even after symptom resolution.293 In the present study, NGS was used to examine the genetic diversity, prevalence and temporal dynamics of GII noroviruses present in complex wastewater samples. The findings were compared with norovirus results obtained from clinical samples in Australia for 2016. A high level of norovirus genotypic diversity was identified in wastewater samples from Sydney and Melbourne, with 18 of 22 capsid genotypes detected (GII.1-8, 10-14, 16, 17, 20-22), compared to 12 capsid genotypes detected in clinical samples. Amongst the four genotypes not identified, two were not expected (GII.18 and GII.19) as these only infect pigs.127 The predominant GII genotype identified in wastewater varied throughout the year; GII.17 was predominant in summer 2016 (January/February), which was slowly replaced by strains with a GII.4 capsid. From May 2016, GII.4 prevalence declined and the prevalence of GII.2 strains increased. This data correlated with an increase in GII.2 positive clinical samples, suggesting that wastewater samples could augment clinical samples for norovirus surveillance. The increased abundance of GII.2 in wastewater was observed two months prior increased GII.2 detection in clinical samples, signifying its use as a predictive model, which could be used as warning of impending epidemics leading to peaks of season.

Chapter 3: Norovirus molecular epidemiology 2014-16

To date, only a handful of studies have examined the genotypic diversity of viruses in wastewater, in which most used traditional Sanger sequencing/cloning methods,258, 262, 294 with only two employing NGS technologies.295, 296 Studies by Kazama et al.,295 and Prevost et al.,296 applied second generation sequencing technologies (pyrosequencing) to characterise norovirus diversity in wastewater, which was then compared to the diversity found in clinical samples. A French study also identified a total of 16 norovirus GII genotypes of which GII.4 (86% Sydney 2012 variant) was the most prevalent in both sample types between May 2013 and May 2014.296 In contrast to our study, Prevost et al.296 found a strikingly different distribution of norovirus diversity between wastewater and clinical samples. For example, GII.4 was the predominant genotype identified in clinical samples throughout the year but only predominant in spring and winter in wastewater samples.

In this study, we used 181 clinical samples collected over 2016 and matched the genotypes found to monthly genotype data from wastewater samples in three WWTPs. Kazama et al. also compared the norovirus diversity between wastewater and clinical samples in a shorter timeframe, between November 2012 and March 2013.295 A relatively low number of clinical samples (n=96) was used for correlation purposes, which only identified three GII genotypes (GII.4, GII.5 and GII.14) and a single GI virus (GI.6).295 In total, nine norovirus GII genotypes were identified in the wastewater samples, with GII.14 as the most predominant (average of 36.2% of GII viruses identified), followed by GII.4 (21.5%). However, similar to our findings, GII.17 viruses were only detected in wastewater samples, and were not identified in clinical samples.295 Further work is needed to determine the effectiveness of using wastewater for norovirus molecular surveillance, but the initial studies show promising results.

In 2016, an unusual co-circulation of six prevalent norovirus strains was documented, this included four novel recombinant viruses, the GII.17 Kawasaki virus and the Sydney 2012 variant. Sequencing of both clinical and wastewater samples demonstrated that both norovirus genotype diversity and the temporal dynamics of when certain viruses emerged coincided. The use of next generation sequencing technologies for monitoring norovirus diversity in wastewater samples provided a more complete picture of norovirus epidemiology at a population level to identify noroviruses associated more with asymptomatic infections, whilst complementing data obtained from clinical studies.

Chapter 4: Recombinant noroviruses in 2017

4 Recombinant GII.P16/GII.4 Sydney 2012 was the dominant norovirus identified in Australia and New Zealand in 2017

Text and figures included in this chapter are taken from the following publication:

Lun JH, Hewitt J, Yan GYH, Enosi Tuipulotu D, Rawlinson WD and White PA (2018) Recombinant GII.P16/GII.4 Sydney 2012 was the dominant norovirus identified in Australia and New Zealand in 2017. Viruses 10(10): 548.

Declaration I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Jennifer Hoi Yin Lun [Candidate]

Authors contributions: Conceived and designed the experiments – JHL, PAW; Performed the experiments – JHL, JH, GYHY, DET; Analysed the data – JHL, PAW; Contributed reagents/materials/analysis tools – JHL, JH, GJHY, DET, EDR, PAW; Wrote the paper – JHL, PAW.

Chapter 4: Recombinant noroviruses in 2017

4.1 Abstract For the past two decades, norovirus pandemic variants have emerged every 3–5 years and dominate until they are replaced by alternate strains. However, this scenario changed in 2016 with the co-circulation of six prevalent viruses, three of which possessed the pandemic GII.4 Sydney 2012 capsid. An increased number of institutional gastroenteritis outbreaks were reported within the Oceania region in mid-2017. This study identified emerging noroviruses circulating in Australia and New Zealand in 2017 to assess the changing dynamics of the virus infection. RT-PCR-based methods, next generation sequencing, and phylogenetic analyses were used to genotype noroviruses from both clinical and wastewater samples. Antigenic changes were observed between the capsid of pandemic Sydney 2012 variant and the two new Sydney recombinant viruses. The combination of these antigenic changes and the acquisition of a new ORF1 through recombination could both facilitate their ongoing persistence in the population. Overall, an increased prevalence of GII.P16/GII.4 Sydney 2012 viruses was observed in 2017, replacing the GII.P16/GII.2 recombinant that dominated in the region at the end of 2016. This shift in strain dominance was also observed in wastewater samples, demonstrating the reliability of wastewater as a molecular surveillance tool.

Chapter 4: Recombinant noroviruses in 2017

4.2 Introduction Acute gastroenteritis (AGE) is the second leading human infectious disease and results in 1.4 million deaths worldwide each year.2, 3 Norovirus is now the leading cause of viral AGE in all age groups globally13 and is estimated to cause 677 million cases each year accounting for ~210,000 deaths.1 Despite the self-limiting nature of the disease, severe and prolonged symptoms can be observed in children, the elderly and in immunocompromised individuals. 16 Norovirus is highly transmissible due to (i) the low infectious dose,60 (ii) virus stability within the environment and (iii) continued virus shedding after symptoms have resolved. Therefore, outbreaks of norovirus-associated gastroenteritis frequently occur in semi-closed environments including hospitals, aged-care facilities, childcare centres and cruise ships.

Norovirus is a genus of genetically diverse single-stranded, RNA viruses within the Caliciviridae family. Based on full-length amino acid capsid (VP1) sequences, norovirus can be tentatively divided into seven genogroups (GI-GVII) and more than 40 genotypes.297 The viruses GI, GII and GIV are associated with human infections, however, GII viruses are responsible for the majority of human norovirus infections.

Recombination (antigenic shift) and antigenic drift are the two main mechanisms that drive norovirus evolution.54 Antigenic drift is caused by amino acid changes within the capsid protein (VP1), primarily within the protruding domain (P2), which enables the virus to escape from population host immunity.298 The capsid of GII.4 noroviruses continuously undergo epochal evolution, resulting in the emergence of new pandemic variants approximately every 3-5 years.16, 29, 33, 93, 99 Recombination usually occurs near the ORF1/ORF2 overlap, which enables the exchange of the entire structural or non-structural regions,128 leading to the creation of novel viruses, some of which also have pandemic potential.105

For the past two decades, the pandemic GII.4 variants usually account for 60-80% of all norovirus infections, and dominate until another variant emerges.16 However, a change in norovirus molecular epidemiology has been observed over the past three years. In 2016, we saw a decline of the pandemic Sydney 2012 variant, concomitant with the emergence of two novel GII.4 recombinant viruses, both of which retained the Sydney 2012 capsid, but acquired new non-structural regions (GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P16/GII.4 Sydney 2012).299 The emergence of GII.P4 New Orleans 2009/GII.4 Sydney 2012 was first detected in 2013 and was created through a recombination event between the Sydney 2012 pandemic

Chapter 4: Recombinant noroviruses in 2017 variant with its pandemic predecessor GII.4 New Orleans 2009 variant.280 Following its identification, this recombinant virus was also identified in Australia, New Zealand,283, 299 Denmark,281 England,282 and South Africa.300 The other novel GII.4 recombinant, GII.P16/GII.4 Sydney 2012, was first identified in the Oceania region in mid-2015 and was found circulating at a low prevalence in South Korea, Germany and Japan in 2016.286, 288, 299, 301 In mid-late 2016, an increase of a third novel recombinant, GII.P16/GII.2, was observed in Australia and New Zealand.299 This virus was also detected around the globe in 2016, including Japan,302 the United States,107 China (51% of outbreaks)289 and Europe,284, 288 where it was responsible for 14-42% of all norovirus outbreaks.

Therefore, continuous surveillance of circulating norovirus strains at a population level is essential for early identification of novel viruses which may have pandemic potential. In this study, we compared the noroviruses which were circulating in Australia and New Zealand in 2017, assessed the changing dynamics of epidemic variants, and identified emergent norovirus variants which arose from recombination and antigenic variation. Molecular epidemiology of norovirus is commonly conducted using clinical samples collected from symptomatic patients, which is not representative of all circulating noroviruses in a population. Consequently, the second aim of this study was to compare the norovirus GII genotype distribution between wastewater and clinical samples.

Chapter 4: Recombinant noroviruses in 2017

4.3 Materials and methods

4.3.1 Collection of clinical specimens All norovirus-positive clinical specimens were collected as part of routine diagnostic services or norovirus surveillance between January and December 2017. Multiplex reverse transcription polymerase chain reaction (RT-PCR) and norovirus lateral flow enzyme immunoassay (EIA) were used during the routine diagnostic services for norovirus detection. The study was approved by the University of New South Wales (UNSW) Human Research Ethics Advisory Panel (HREAP) (HC12221, HC16826 and HC17459). For Australia, 243 specimens were collected via the New South Wales (NSW) Ministry of Health from gastroenteritis institutional outbreaks and sporadic cases. For New Zealand, representative specimens from 238 separate norovirus outbreaks in 2017 were collected. All norovirus sequences generated from clinical specimens were submitted to GenBank, accession numbers MK280856-MK280983.

4.3.2 Collection of wastewater samples Monthly influent samples (250 mL) were collected from Bondi and Malabar wastewater treatment plants (WWTP) between January and December 2017. Melbourne samples were collected from Werribee, western WWTP, between May and December 2017. All samples were stored at -80°C on the day of collection.

4.3.3 Viral concentration and RNA extraction Stool suspensions (10-20% in water) were prepared from clinical specimens, followed by viral RNA extraction as described previously.33,273 Ultracentrifugation was used to concentrate viruses in wastewater samples prior to viral RNA extraction, as described in.299 Frozen aliquots of MS2 bacteriophage, with a concentration of 2.6 × 106 ± 1.6 x 105 genome copies/20 µL, were used as process control to validate RNA extraction and RT-PCR amplification.299

4.3.4 Reverse Transcription PCR (RT-PCR) amplification and sequencing For Australian clinical specimens, a norovirus GI and GII duplex RT-PCR was performed targeting the 5’ end of capsid gene for norovirus genotyping,93 along with a norovirus GI or GII RT-PCR targeting the ORF1/ORF2 overlap for the identification of potential recombinants.108, 273 For New Zealand clinical specimens, RT-PCR was conducted targeting the region B of the RdRp, region C of the capsid, and across the ORF1/ORF2 overlap.273 All RT-PCR products were Sanger sequenced and genotyped using phylogenetic analysis.299

Chapter 4: Recombinant noroviruses in 2017

For wastewater samples, the 5’ end of norovirus GII capsid was amplified, followed by a second round PCR for the addition of universal sequencing adapters, following the manufacturer’s protocol (Illumina, San Diego, CA, USA). PCR amplicons were purified using AMPure XP beads (Beckman Coulter, Brea, CA, USA) prior to next generation sequencing (NGS) library preparation. NGS libraries were prepared and sequenced on the Illumina MiSeq platform, as described previously.299 Library fragment sizes were evaluated on a Tape Station D1000 (Agilent Technologies, Santa Clara, CA, USA) prior to sequencing. Full-length capsid genes of representative GII.4 were amplified, as described previously,105 and Sanger sequenced.

4.3.5 Norovirus phylogenetic analysis Partial polymerase (GI-171 bp, GII-172 bp) and partial capsid (GI-295 bp, GII-282 bp) sequences were used for phylogenetic analyses to determine genotype of norovirus - positive samples and confirmed using an online genotyping tool (http://www.rivm.nl/mpf/norovirus/typingtool).30 MUSCLE was used to align the GI and GII sequences and phylogenetic trees were constructed using the maximum likelihood method.277

4.3.6 NGS data analysis The software package Geneious, v 9.1.7 (Biomatters, Auckland, New Zealand) was used to analyse MiSeq data. Raw data were filtered to retain sequencing reads between 200 to 400 nt in length. Paired-end sequences were merged and mapped to a list of GII references (n=88) using Geneious mapper with medium sensitivity and default parameters. The proportion of each GII genotype was calculated, as described in 299. Subsequently, all GII.4 reads were mapped to GII.4 variant sequences (n=3) to determine the abundance of individual GII.4 variants in the population.

4.3.7 Analysis of amino acid variation within GII.4 capsid sequences Full length GII.4 capsid (VP1) protein sequences were aligned and compared with reference sequences obtained from GenBank. Variable informative sites were analysed and determined by the website DIVEIN (http://indra.mullins.microbiol.washington.edu/DIVEIN/).303 Informative sites are identified when the same amino acid mutation at the same position is shared by at least two strains.

Chapter 4: Recombinant noroviruses in 2017

4.3.8 Molecular adaptation analysis of the norovirus GII.4 capsid To investigate the likelihood of positive selection within the GII.4 capsid, 42 representative sequences were retrospectively selected between the period 2014 to 2017 and compared to reference sequences obtained from NCBI. The web server (http://datamonkey.org/)304 was used to identify potential positive and negative selection within the capsid coding sequence. The three codon-based methods used were Mixed Effect Model of Evolution (MEME), Fixed Effects Likelihood (FEL) and Fast, Unconstrained Bayesian AppRoximation (FUBAR).93 The significance threshold was set to p value of 0.1 for both MEME and FEL, and posterior possibility of 0.9 for FUBAR.

Chapter 4: Recombinant noroviruses in 2017

4.4 Results

4.4.1 Gastroenteritis outbreak increase in 2017 In August 2017, a sudden increase of gastroenteritis outbreaks was reported to the NSW Ministry of Health, Australia and peaked in September 2017 (n=175 outbreaks). This represented a 4.8-fold and 2.7-fold increase compared to the average number of monthly outbreaks detected in 2015 and 2016, respectively (Figure 4-1A).299 Additionally, a rise in norovirus outbreaks was also observed in New Zealand, with the peak occurring in October 2017 (n=42 outbreaks) (Figure 4-1B). This was the highest number of norovirus outbreaks recorded in New Zealand since the emergence of the Sydney 2012 pandemic strain (Figure 4-1B), and a 2.7- fold rise when compared to the previous two years. Therefore, we aimed to determine if the increased norovirus outbreaks were caused by the emergence of a novel norovirus.

(A) NSW Ministry of Health, Australia (B) New Zealand (C) NSW, Australia 200 25 40 Aged care facility Hospital Norovirus outbreaks investgated 6.8% Childcare centre 9.1% Others 20 150 30 4.5% Accommodaton facility 2.3% Commerical food operator 2.3% 27.3% Cruise ship/airplane 15 2.3% School/college and camps Social event 100 20 Private home 10 45.4% 50 10 5 Number of norovirus outbreaks Number of gastroenterits outbreaks 0 0 0 J F M A M J J A S O N D J F M A M J J A S O N D n=44 2017 2017 Time (month/year) Time (month/year)

Figure 4-1. The number of gastroenteritis and norovirus outbreaks reported in the Oceania region, 2017. (A) The monthly number of institutional gastroenteritis outbreaks reported to the NSW Ministry of Health department in 2017 (highlighted in grey), and the number of norovirus- associated outbreaks investigated in this study (highlighted in yellow); (B) The number of norovirus outbreaks reported to New Zealand Ministry of Health from January 2015 to December 2017. The outbreak settings are categorised as indicated by the legend. (C) A total of 44 norovirus outbreaks were identified in NSW, Australia, throughout this study period. The outbreak settings are represented by different colours in the legend.

4.4.2 Outbreak settings A total of 282 norovirus outbreaks (Australia = 44 and New Zealand = 238) were investigated from samples collected, during 2017. Of those, GI was identified as the aetiological agent in 52 outbreaks (18.4%), whilst GII was the causative agent in 228 outbreaks (80.9%). The remaining two outbreaks identified in New Zealand were caused by a mix of GI and GII noroviruses. In Australia, most outbreaks occurred in aged care facilities (45.4%), followed by

Chapter 4: Recombinant noroviruses in 2017 hospitals (27.3%), accommodation facilities (9.1%), cruise ships/airplanes (6.8%) and social events (4.5%), with the remaining detected in three other settings (Figure 4-1C). Aged care facilities were also identified as the most common outbreak setting in New Zealand (63.5%), followed by childcare centres (12.2%), hospitals (10.9%), commercial food operators (5.0%), school/colleges (2.9%) and others (Figure 4-1B).

4.4.3 Circulating GI noroviruses GI represented 9.1% (n=22/243) of all noroviruses sequenced in Australia and phylogenetic analysis identified a total of five capsid genotypes (Figure 4-2). GI norovirus was found to be more prevalent in New Zealand than Australia, where it was responsible for 21.4% (n=51/238) of all norovirus outbreaks, with six GI capsid genotypes identified (Figure 4-2). From the 73 norovirus GI strains isolated from Australia and New Zealand, ten GI genotypes were identified, of which GI.P3/GI.3 (30.1%, 22/73) was the most predominant, followed by GI.Pb/GI.6 (21.9%, 16/73) and GI.Pd/GI.3 (20.5%, 15/73) (Figure 4-3A).

Chapter 4: Recombinant noroviruses in 2017

Figure 4-2. Phylogenetic analysis of polymerase (RdRp) and capsid (VP1) regions of GI noroviruses. Representative norovirus GI strains isolated in this study (n=29), from both NSW, Australia and New Zealand, are shown in this phylogenetic analysis. They are denoted with a coloured bullet (•), where Australian samples are represented in purple and New Zealand samples in orange. All samples are labelled with their geographical location and time of strain isolation. Reference strains were obtained from the GenBank database, labelled with their genotype and accession number. (A) Maximum likelihood phylogeny derived from partial 3’ end of polymerase gene (171 bp) of GI noroviruses. (B) Maximum likelihood phylogeny derived from partial 5’ end of capsid gene (295 bp) of GI noroviruses. Sequence alignments were performed with MUSCLE algorithm. Maximum likelihood phylogenetic trees were produced using MEGA 5 software (https://www.megasoftware.net/) with bootstrapping test of 1,000 replicates, based on the Kimura 2-parameter model. The bootstrap percentage values are shown at each branch point for values ≥70%. The number of substitutions per site is indicated by the scale bar.

Chapter 4: Recombinant noroviruses in 2017

(A) Australia and New Zealand (GI) GI.P1/GI.1 10 GI.P2/GI.2 GI.Pd/GI.3 8 GI.P3/GI.3 GI.P4/GI.4 6 GI.P5/GI.5 GI.Pb/GI.6 4 GI.P6/GI.6 GI.P7/GI.7 2 GI.P8/GI.8 ND

Number of GI cases/outbreaks 0 J F M A M J J A S O N D GII.Pe/GII.2 Time (month) GII.P2/GII.2 GII.P16/GII.2 (B) New South Wales, Australia (GII) (C) New Zealand (GII) GII.P12/GII.3 GII.P16/GII.3 100 100 GII.P21/GII.3 GII.Pe/GII.4 Syd 2012 80 80 GII.4 NO/GII.4 Syd 2012 GII.P16/GII.4 Syd 2012 GII.P7/GII.6 60 60 GII.P7/GII.7 GII.P8/GII.8 40 GII.P2/GII.13 40 GII.P16/GII.13 GII.P21/GII.13 20 20 GII.P7/GII.14 GII.P15/GII.15 Norovirus GII distribution (%) Norovirus GII distribution (%) Norovirus GII.P17/GII.17 0 0 Mixed GI/GII J F M A M J J A S O N D J F M A M J J A S O N D ND Time (month) Time (month)

Figure 4-3. Monthly distribution of norovirus genotypes identified in the Oceania region in 2017. (A) The number of GI norovirus genotypes identified in the Oceania region (Australia and New Zealand) during the study period. A total of 73 samples were collected and identified as GI norovirus, 52 cases were linked to outbreaks and the remaining were sporadic cases (n=21). Both polymerase and capsid were sequenced to determine its genotype, with each genotype denoted by different colours as indicated in the legend. The ND represents samples that had incomplete genotyping results where only the capsid or the polymerase region was determined. (B) The monthly genotype distribution of GII noroviruses identified in New South Wales, Australia, throughout the study was examined. A total of 220 GII cases were identified in this study, where 44 were linked to outbreaks and the remaining were considered sporadic cases. Different genotypes are indicated by different colours, labelled in the legend. (C) All samples collected from New Zealand were of outbreak samples and a total of 184 GII outbreaks were investigated in 2017. The monthly genotype distribution of GII noroviruses are shown.

Chapter 4: Recombinant noroviruses in 2017

4.4.4 Circulating GII noroviruses Norovirus GII was identified as the most predominant genogroup, responsible for 84.8% (n=408/481) of all cases/outbreaks investigated in 2017 from Australia and New Zealand (Figure 4-3B, Figure 4-3C and Figure 4-4). Based on the phylogenetic analyses (Figure 4-4), interestingly, the GII.4 capsid sequences segregated into three different clusters, allowing differentiation of the GII.4 capsid containing viruses (Figure 4-4B and Figure 4-5). In January 2017, the recombinant GII.P16/GII.2 was dominant in New Zealand (37.5%) and Australia (33.3%); however, its prevalence slowly declined, which was concomitant with the increase of the recombinant GII.P16/GII.4 Sydney 2012 in the region (Figure 4-3B and Figure 4-3C). In 2017, the GII.P16/GII.4 Sydney 2012 recombinant was the dominant strain responsible for 56.8% (n=138/243) and 42.9% (n=102/238) of all cases/outbreaks identified in both Australia and New Zealand, respectively. In Australia, the prevalence of GII.P16/GII.4 Sydney 2012 reached to 75.0% of total cases/outbreaks in May and then to 84.2% by August 2017 (Figure 4-3B), whilst in New Zealand, the virus caused >60% of norovirus GII outbreaks between June and December (Figure 4-3B).

Chapter 4: Recombinant noroviruses in 2017

Figure 4-4. Phylogenetic analysis of polymerase (RdRp) and capsid (VP1) regions of GII norovirus. Representative norovirus GII strains isolated in this study (n=92), from both NSW, Australia and New Zealand, are shown in this phylogenetic analysis. They are denoted with a coloured bullet (•), where Australian samples are represented in purple and New Zealand samples in orange. All samples are labelled with their geographical location and time of strain isolation. Reference strains were obtained from the GenBank database, labelled with their genotype and accession number. (A) Maximum likelihood phylogeny derived from partial 3’ end of polymerase gene (172 bp) of GII noroviruses. (B) Maximum phylogeny derived from partial 5’ end of capsid gene (282 bp) of GII noroviruses. Sequence alignments were performed with MUSCLE algorithm. Maximum likelihood phylogenetic trees were produced using MEGA 5 software with bootstrapping test of 1,000 replicates, based on the Kimura 2-parameter model. The bootstrap percentage values are shown at each branch point for values ≥70%. The number of substitutions per site is indicated by the scale bar.

Chapter 4: Recombinant noroviruses in 2017

NSW17N124/Jun/17 99 80 NSW17N137/Jun/17 99 NSW2811/Sep/17 89 NSW5099/Mar/17 NSW17N121/Apr/17 NSW859T/Nov/15 NSW17N48/Oct/17 NSW5282/Aug/17 NSW624J/Feb/15 93 NSW180D/Feb/16 NSW799Y/Jul/15 NSW8482/Aug/16 NSW656Y/Dec/14 NSW559W/Aug/14 84 NSW272P/Oct/14 99 99 NSW1208/Mar/15 72 94 NSW068X/Aug/14 NSW804E/Sep/14 100 NSW843R/Oct/14 86 96 NSW800A/Dec/14 2012 Sydney GII.Pe/GII.4 JX459908 GII.4/Sydney NSW0514/2012/AUS 100 NSW707E/Dec/15 NSW6027/Jun/16 NSW682S/Jul/15 - GII.4 Sydney 100 NSW015D/Jul/14 NSW4490/Jul/14 100 NSW4644/May/15 95 NSW2530/Jun/16 NSW9405/Jun/17 100 NSW8193/Sep/16 99 NSW8065/Sep/16 100 NSW094P/Jun/15 NSW762O/Jul/15 NSW17N133/Jul/17 91 MG002634 BNE5/2017/AU* NSW34272/Sep/17 NSW17N122/Aug/17 100 MG002632 BNE3/2017/AU* NSW3842/Aug/17 NSW4768/Sep/17 100 NSW417P/Oct/15 NSW206B/Jan/16 99 NSW8531/Jul/16 95 NSW0344/Jul/16 NSW1580/Mar/16 NSW0297/Jul/16

NSW772S/Jun/16 2012 Sydney Orleans 2009/GII.4 New GII.P4 95 NSW012/Aug/16 100 NSW775Q/Nov/14 NSW776R/Nov/14 KF378731 Norovirus PA13/2013/ITA NSW3704/Dec/17 96 99 NSW9983/May/17 74 NSW17N100/Sep/17 99 NSW17N128/Mar/17 NSW6351/Apr/17 NSW8653/Dec/15 96 NSW3648/Jul/16 LC175468 GII.P16 GII.4 Sydney2012/Kawasaki194/2016/JP GII.P16/GII.4 Sydney 2012 Sydney GII.P16/GII.4 98 NSW9639/Aug/16 GU445325 GII.4/New Orleans1805/2009/USA

0.01

Figure 4-5. Phylogenetic analysis of GII.4 full-length capsid sequences. Representative full-length GII.4 capsid sequences were selected between 2013 to 2017 and compared to prototype GII.4 pandemic variants and GII.4 recombinant viruses. Sample sequences are denoted by the sample location, sample ID and date of collection. Prototype sequences of each GII.4 pandemic variant and GII.4 recombinant viruses are indicated in bold. Reference sequences were obtained from GenBank, labelled with its accession number and country of isolation. The GII.Pe/GII.4 Sydney 2012 sequences are denoted with a red triangle, GII.P4 New Orleans 2009/GII.4 Sydney 2012 with a yellow circle and the GII.P16/GII.4 Sydney 2012 sequences with a green diamond. The asterisks (*) denote sequences obtained from the Bruggink et al. 2018 study. Sequence alignments were performed with MUSCLE algorithm. Maximum likelihood phylogenetic trees were produced using MEGA 5 software with bootstrapping test of 1,000 replicates, based on the Kimura 2-parameter model. The bootstrap percentage values are shown at each branch point for values ≥70%. The scale bar indicates the number of substitutions per site. The GenBank accession numbers for viruses sequenced are MK213510-MK213547.

Chapter 4: Recombinant noroviruses in 2017

In Australia, the second most predominant GII identified was the pandemic Sydney 2012 variant (10.8%, n=24/221), followed by the recombinant GII.P4 New Orleans 2009/GII.4 Sydney 2012 (6.8%, n=15/221), GII.P16/GII.2 (6.3%, n=14/221) and GII.P7/GII.6 (5.0%, n=11/221) (Figure 4-3B and Figure 4-4). However, in New Zealand, GII.P16/GII.2 was found to be the second most predominant GII virus identified (9.1%, n=17/187), followed by GII.Pe/GII.4 Sydney 2012, GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P7/GII.6, each accounted for 7.0% of GII outbreaks (n=13/187) (Figure 4-3C and Figure 4-4).

4.4.5 Antigenic variation within the GII.4 capsids The multiple recombination events of the Sydney 2012 pandemic variant is unusual and has facilitated viruses with this capsid to persist around the globe. Full-length GII.4 amino acid capsid consensus sequences of the three Sydney 2012 viruses were examined to identify antigenic variation and evidence of positive selection, especially within putative antigenic sites and histo-blood group antigen (HBGA) binding pocket (epitopes A-E). Representative capsid sequences of GII.Pe/GII.4 Sydney 2012 (n=20), GII.P4 New Orleans 2009/GII.4 Sydney 2012 (n=13) and GII.P16/GII.4 Sydney 2012 (n=9), were used to generated consensus sequences. Compared to the original pandemic Sydney capsid, the consensus sequences of the contemporary Sydney 2012 viruses varied at a number of residues (Figure 4-6). Firstly, the consensus sequence of GII.Pe/GII.4 Sydney 2012 varied at seven residues, including residues 297, 372 and 373 in epitope A, residue 310 in the NERK motif, and residues located in the P2 domain (309) and P1 domain (414 and 540) (Figure 4-6). Secondly, the GII.P4 New Orleans 2009/GII.4 Sydney 2012 capsid consensus sequence varied at 11 residues, in which six were located within the main antigenic epitopes; epitope A (297, 372 and 373), B (333), C (340) and D (393). The remaining changes were observed in P1 domain (residue 229, 460, 494, 539) and NERK motif (310) (Figure 4-6). Finally, the GII.P16/GII.4 Sydney 2012 recombinant strain varied at ten residues located in; epitope A (373), epitope B (333), epitope D (393), NERK motif (310), shell domain (119, 145, 174), P1 domain (539, 540) and P2 domain (377) (Figure 4-6). Of all variable sites identified, residue 373 was found to be under positive selection by all three codon- based methods (MEME, FEL and FUBAR).

Chapter 4: Recombinant noroviruses in 2017

A Epitope C Epitope A

Epitope D

Epitope E

B A B C A A A D Genotype (polymerase/capsid) 119 145 174 229 297 309 310 333 340 359 368 372 373 377 393 414 460 494 539 540 GII.4 New Orleans 2009 I I S V R N S V T S A D N T S H Y S A L GII.Pe/GII.4 Sydney 2012 V V P V R N D V T A E D R A G H Y S A V GII.Pe/GII.4 Sydney 2012 1 V V P V H S N V T A E N H A G P Y S A L GII.P4 NO 2009/GII.4 Syd 2012 2 V V P I H N N M A A E S N A S H H P V V GII.P16/GII.4 Sydney 2012 3 I I S V R N N M T A E D H A S H Y S V V Shell P1 P2 P1

Figure 4-6. Capsid residue variation and antigenic variation within the full-length capsid of GII.4 recombinant viruses. Full-length capsid sequence of novel GII.4 recombinant viruses were collected between July 2014 and December 2017. Consensus sequences of contemporary GII.Pe/GII.4 Sydney 20121 (n=20), GII.4 New Orleans 2009/GII.4 Sydney 20122 (n=13) and GII.P16/GII.4 Sydney 20123 (n=9) were generated and compared to pandemic variants (New Orleans 2009 and Sydney 2012) for the identification of antigenic variations, especially within the P2 protruding domain. (A) Characterised blockade antibody epitopes are highlighted in the different colours; epitope A (red), epitope B (orange), epitope C (yellow), epitope D (green) and epitope E (purple). The residues within the P2 domain, especially those within epitope A, which differed from the pandemic Sydney 2012 variant. (B) Antigenic variations observed between full length capsid sequences of pandemic Sydney variant and the new Sydney 2012 recombinants. Labelled boxes above the antigenic sites indicate sites within known blockade epitopes A-E that are important determinants of viral antigenicity. The A-D epitopes identified in the GII.4 capsid are coloured; epitope A (red), epitope B (orange), epitope C (yellow) and epitope D (green). The numbers across the top panel indicate the amino acid position within the VP1 sequence, hypervariable sites with ≥3 amino acids substitutions across all sequences are shaded in grey. Residues that vary from the GII.4 New Orleans 2009 sequence over time are indicated by shades of blue. The bottom panel indicates the shell, P1 and P2 domains of the capsid. The prototype of each pandemic/recombinant variants are indicated in the lightest shade of orange.

Chapter 4: Recombinant noroviruses in 2017

4.4.6 Norovirus GII genotype distribution in wastewater samples The use of wastewater samples for viral surveillance can overall enhance norovirus surveillance at a population scale.295, 299 Partial GII norovirus capsid regions were amplified from monthly samples collected from three WWTP sites from Sydney and Melbourne and sequenced on the Illumina MiSeq platform. A total of 4,892,127 reads were generated from 32 wastewater samples, with an average of 152,879 reads per sample. All raw data were submitted to Sequence Read Archive (SRA) database, accession no. PRJNA508844. Across the three sites, 16 capsid genotypes were identified; the dominant capsid genotypes included GII.4 (52.6%), GII.2 (24.5%), GII.3 (9.8%), GII.17 (5.8%) and GII.13 (5.5%) (Figure 4-7). Sequences that did not map to existing genotypes were excluded from this study.

Chapter 4: Recombinant noroviruses in 2017

(A) Bondi WWTP (B) Malabar WWTP (C) Melbourne WWTP GII.1 100 100 100 GII.2 GII.3 GII.Pe/GII.4 Syd 2012 80 80 80 GII.P4 NO/GII.4 Syd 2012 GII.P16/GII.4 Syd 2012 Other GII.4 60 60 60 GII.5 GII.6 Not sampled GII.8 40 40 40 GII.12 GII.13 GII.14 20 20 20 GII.15 GII.16 GII.17

Norovirus genotype distribu�on (%) Norovirus 0 0 0 GII.20 GII.21 J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D GII.22 Time (month) Time (month) Time (month)

Figure 4-7. Norovirus genotype distribution in wastewater samples collected from Sydney and Melbourne, 2017. The norovirus GII capsid genotypic distribution was determined in wastewater samples by amplicon sequencing using NGS technology. After amplification of the desired region (capsid), a second round PCR was performed for the addition of adapters prior to NGS library preparation. Libraries were sequenced on the MiSeq platform and an average of 152,879 reads was generated for each sample. Geneious was used for merging and mapping of the reads to the norovirus GII reference sequences. (A) The monthly genotype distribution of norovirus GII viruses in wastewater samples collected from Bondi WWTP in Sydney, Australia. (B) Norovirus GII genotypic diversity was examined in wastewater samples collected monthly from Malabar WWTP in Sydney, Australia. (C) The monthly norovirus GII genotype diversity was also examined in Melbourne, all samples were collected from western wastewater treatment plant. Samples were not collected between January and April 2017. The y-axis represents the percentage of norovirus genotype distribution in each sample, and the time is indicated on the x-axis. Norovirus GII capsid genotype and GII.4 recombinants are labelled in different colours as indicated by the legend.

Chapter 4: Recombinant noroviruses in 2017

GII.2 was found to be the predominant capsid genotype at the Bondi and Malabar WWTPs in January (33.1% and 39.1% of reads, respectively) and February (37.4% and 36.4%, respectively). However, a steady decline of GII.2 was observed for the remainder of the year at both sites, accompanied by an increase of GII.4 viruses around March 2017 (Figure 4-7A and Figure 4-7B). Subtle but distinct differences can be found between the three GII.4 Sydney capsid sequences, which enabled the inference of polymerase genotype. At the Bondi WWTP an increase in GII.P16/GII.4 Sydney 2012 recombinant was observed; 25.6% in February, 41.3% in May, 41.9% in July and reached its highest levels in November 2017 (50.7%) (Figure 4-7A). At the Malabar WWTP an average of 23.8% of GII.P16/GII.4 reads were seen in the first three months of 2017, then 39.1% in July, 43.3% in September and 36.8% in December (Figure 4-7B). This virus was the most predominant GII strain from July to December and accounted for an average of 37.5% of the monthly genotype distribution for 2017 in Sydney (Figure 4-7A and Figure 4-7B).

For the Melbourne WWTP, GII.4 was the dominant capsid genotype between May and December 2017 (average of 60.9% of monthly reads) (Figure 4-7C). Surprisingly the recombinant GII.P16/GII.4 Sydney 2012 was not the predominant strain in Melbourne, with a monthly average of 19.1% of reads across 2017. Of the three GII.4 recombinants, GII.P4 New Orleans 2009/GII.4 Sydney 2012 was the most prevalent virus in wastewater samples, constituting 34.1% of reads in May, 45.5% in August, 25.7% in November. GII.2 viruses were identified as another dominant genotype throughout the study period in Melbourne, accounting for a monthly average of 19.1% (Figure 4-7C).

Chapter 4: Recombinant noroviruses in 2017

4.5 Discussion A total of six pandemic norovirus variants have emerged in the past two decades, all of which may be classified within the GII.4 lineage93 with the most recent emerging in 2012, namely Sydney 2012 (GII.Pe/GII.4 Sydney 2012).105,106 Recently Sydney 2012 has undergone recombination with both its predecessor pandemic strain (New Orleans 2009) and a GII.P16 virus to create two new strains (GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P16/GII.4 Sydney 2012), with reported potential to evade population immunity and cause outbreaks.107, 284, 285, 299, 305

In the winter months of 2017, an increase in gastroenteritis outbreaks was observed in Australia and New Zealand when compared to the previous two years (Figure 4-1). This increase is consistent with the study by Bruggink et al., 2018 in Victoria, Australia, where the number of outbreaks in 2017 doubled in July (n=22) compared to May 2017 (n=11).306 Overall, this data suggested the continued dominance of GII.P16/GII.2 or the emergence of a novel norovirus. Therefore, we genotyped circulating noroviruses within the Oceania region in 2017. The prevalence of GII.P16/GII.2 diminished in early 2017 and was replaced by GII.P16/GII.4 Sydney 2012, which was the dominant virus in both Australia (57.0%) and New Zealand (43.2%) for the rest of the year. This replacement suggests that a GII.4 capsid is one essential requirement for norovirus persistence within the population. A previous study by Parra et al. showed non-GII.4 viruses were genetically more static,127 and only minor divergence was observed within the GII.2 capsid sequence over 40 years.290 This lack of variance in GII.2 antigenic domains could explain their short-lived duration. In contrast, GII.4 viruses have the highest rate of evolution compared to other genotypes, signifying its ability to facilitate the emergence of new variants, and as shown in this study, its ability to replace GII.2 as a dominant strain.125, 127

The GII.P16/GII.4 Sydney 2012 recombinant retained the original Sydney 2012 capsid, albeit with slight modifications. Based on the increased circulation of this strain, the change in the non-structural region may also have contributed to immune escape and conferred higher virological fitness.285,307 This is supported by the cocirculation and increased prevalence of GII.P16/GII.4 Sydney 2012 and GII.P16/GII.2 viruses in 2016/17, both of which possess the GII.P16 polymerase.299 Indeed GII.P16/GII.2 could represent the “stepping stone” precursor to GII.P16/GII.4 Sydney 2012 virus. This hypothesis is supported by Tohma et al., who showed the polymerase of GII.P16/GII.4 Sydney 2012 was derived from the GII.P16/GII.2 virus.290 In addition, alterations within the non-structural genes allow viral persistence through escape of the

Chapter 4: Recombinant noroviruses in 2017 cytotoxic T lymphocyte response of the host, which has been demonstrated for both hepatitis C virus and human immunodeficiency virus infections,308, 309 although this is not well studied for norovirus.310

No definitive pandemic variant has emerged since 2012; instead, two new recombinants have maintained a GII.4 Sydney 2012 capsid.280, 301 This suggests that antigenic drift, where point mutations occurred within the capsid P2 domain, may have contributed to immune escape.54 Therefore, consensus GII.4 capsid sequences collected in Oceania between 2014 to 2017 were used to identify potential sites of antigenic drift and positive selection within Sydney 2012 capsids. Of the blockade epitopes (A-E), epitope A is believed to be one of the most important determinants of antigenic change57 and associated with the loss of blockade antibody binding, and the emergence of new GII.4 variants.57, 311 In this study, significant positive selection was detected at residue 373 of epitope A in all three recombinant GII.4 Sydney 2012 strains, consistent with previous findings.93, 307

Epitope D contains the histo-blood group antigen (HBGA) carbohydrate binding sites,133, 298 and changes in residue 393 showed loss of human monoclonal antibody binding and modulation in Lewis A and B binding 57, 298, 311 and therefore, affect attachment and entry of the virus. Within epitope D, amino acid reversion to sequence found in the New Orleans 2009 capsid at residue 393 (epitope D), was identified in both the GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P16/GII.4 Sydney 2012 recombinant viruses. Additionally, residues 119, 145 and 174 within shell domain of GII.P16/GII.4 Sydney 2012 also reverted to residues found in the previous pandemic variant, New Orleans 2009. Even though antigenic reversion is commonly identified in viruses,312-315 the benefits are not well understood. However, previous studies proposed reversion is a result of immune escape316 and it can limit the antigenic repertoire.317

Additional antigenic changes were also observed after 2014, with all three strains with the Sydney 2012 capsid possessing an asparagine (N) amino acid at residue 310, opposed to the aspartic acid (D) found in the original in Sydney 2012 variant. Residue 310 is located within the NERK motif, which regulates capsid structural conformation, and thus antigenic changes may result in less or inaccessible epitopes.307 This persistence of Sydney 2012 capsid was probably enhanced by the sudden emergence of multiple recombinant noroviruses, with different ORF1 regions, but all containing the Sydney 2012 capsid. This acquisition of a novel non-structural region together with the observed capsid amino acid changes likely increased the epidemiological fitness of the recombinant viruses through immune escape. Therefore, the

Chapter 4: Recombinant noroviruses in 2017 combination of both recombination and antigenic variation influenced the continued circulation of the GII.4 Sydney capsid.

Consistent with our clinical data, a high abundance of GII.P16/GII.4 Sydney 2012 was detected in wastewater collected from Sydney and a switch in strain predominance was observed in March (Bondi) and April (Malabar), where GII.P16/GII.4 Sydney 2012 capsid replaced the previously dominant GII.2 capsid genotype. In contrast to Sydney wastewater, no change in capsid genotype dominance was observed in Melbourne WWTP, and GII.4 viruses were maintained as the dominant capsid genotype throughout the study period. This could be due to the lack of sampling in the early months of 2017, where the switch was observed in Bondi and Malabar WWTP. Furthermore, the recombinant GII.P4 New Orleans 2009/GII.4 Sydney 2012 was identified as the dominant GII virus in Melbourne WWTP. This result correlated with the study performed by Bruggink et al., in Victoria, Australia, where GII.P4 New Orleans 2009/GII.4 Sydney 2012 was responsible for 69% of all outbreaks investigated between January and September 2017,306 demonstrating the usefulness of wastewater samples for norovirus surveillance.

Molecular epidemiological surveillance of norovirus is essential to identify new circulating recombinants and emerging strains at a population level, particularly when outbreak activity escalates. Moreover, knowledge of circulating noroviruses is useful for effective vaccine design. Norovirus surveillance in Australia and New Zealand, 2017, showed an increase of GII.P16/GII.4 Sydney 2012 viruses, concomitant with the decrease of the 2016 prevalent strain GII.P16/GII.2. Our study highlights the importance of norovirus recombination together with antigenic capsid changes for the emergence of new epidemic strains. With the use of NGS technologies, the switch in GII norovirus dominance was also observed in wastewater at a population level in Sydney and the dominant New Orleans 2009/GII.4 Sydney 2012 strain also was identified in Melbourne. This highlights the reliability of wastewater as a norovirus surveillance tool.

Chapter 5: Genetic diversity of adenovirus

5 Genetic diversity and quantification of adenoviruses identified in wastewater from Sydney and Melbourne, Australia

Text and figures included in this chapter have been taken from the following manuscript which has been submitted for publication to Science of the Total Environment:

Lun JH, Crosbie ND and White PA (submitted) Genetic diversity and quantification of adenoviruses in wastewater from Sydney and Melbourne, Australia. Science of the Total Environment.

Declaration

I certify that this publication was a direct result of my research towards this PhD, and that reproduction in this thesis does not breach copyright regulations.

Jennifer Hoi Yin Lun [Candidate]

Authors contributions: Conceived and designed the experiments – JHL, PAW; Performed the experiments – JHL; Analysed the data – JHL, PAW; Contributed reagents/materials/analysis tools – JHL, NHC, PAW; Wrote the paper – JHL, NDC, PAW.

Chapter 5: Genetic diversity of adenovirus

5.1 Abstract Adenoviruses (AdV) are DNA viruses that can cause a wide range of clinical diseases, including gastroenteritis, respiratory illnesses, conjunctivitis, and in more severe cases hepatitis, pancreatitis and disseminated diseases. AdV infections are generally asymptomatic or self- limiting but can cause adverse outcomes within vulnerable populations. Since most of AdV serotypes replicate within the human gastrointestinal tract, high levels of AdV DNA are excreted into wastewater systems. In this study, we identified the genetic diversity of AdV at a population level using wastewater samples collected from Sydney and Melbourne from 2016 - 2017, using next generation sequencing (NGS) technologies. In addition, AdV and norovirus genomes were quantified using quantitative polymerase chain reaction (qPCR) based methods to better understand the health risks involved if wastewater contamination occurs.

An average of 1.8 ´ 107 genome copies of AdV DNA was detected in one litre of wastewater collected in Sydney and Melbourne, over the two-year study period. For a comparison with a common cause of viral gastroenteritis, norovirus GII RNA levels were also quantified, and an average of 1.6 ´ 107 genome copies/L was measured across all sites. A total of six major groups (A-F) of AdV were identified in wastewater samples using MiSeq, which included 19 different serotypes. Of those, the most prevalent was F41 (83.5%), followed by F40 (11.0%) and A31 (3.7%). In contrast, five groups of AdV (A-D, F) were identified in clinical samples with F41 as the most dominant serotype, which accounted for 52.5% of gastroenteritis cases. The next most prevalent were C1 and C2 (each responsible for 15.0%), and B3 was the fourth most common serotype (7.5%).

This study demonstrated the practicability of using amplicon based NGS sequencing to identify AdV diversity and quantify AdV and norovirus genome levels in environmental water samples, as well as broadening our current understanding of circulating enteric viruses in the Australian population.

Chapter 5: Genetic diversity of adenovirus

5.2 Introduction

5.2.1 Viral transmission through contaminated water Enteric viruses are of major concern due to their low infectious dose, high viral shedding in patients, and stability in external environments.318 Viral water contamination can occur when human and animal waste enter waterways without proper, or insufficient, treatment for pathogen removal. This can pose a significant public health risk to swimmers and recreational users and has the potential to infect many people when drinking water sources are contaminated.319 Furthermore, food contamination can also occur from irrigation with contaminated water.

Acute gastroenteritis (AGE) is the second leading cause of death in children under the age of five, resulting in approximately 1.3 million annual deaths.2 Symptoms of AGE include diarrheal, vomiting, abdominal pain, myalgia, nausea, chills and fever. Despite improved food safety and hygiene practises, AGE continues to have a significant health impact on people of all ages, in both developed and developing countries. Even though viral gastroenteritis is generally self-limiting, severe dehydration can lead to death in more vulnerable individuals, including infants, elderly and immunocompromised individuals.16, 216, 320 Outbreaks of viral gastroenteritis are difficult to control and commonly occur in hospital wards, cruise ships, childcare centres and elder-care facilities.321, 322 The societal cost of norovirus infections alone are estimated to be around USD$60.3 billion per year globally.1

Viruses commonly associated with waterborne disease outbreaks include norovirus, adenovirus (AdV), rotavirus (RoV), hepatitis A virus (HAV), hepatitis E virus (HEV) and enterovirus.323 These enteric viruses are transmitted through the faecal-oral route and can affect the gastrointestinal tract or the liver. Noroviruses are the leading cause of viral gastroenteritis, accounting for approximately 50% of global gastroenteritis cases,320 and enteric AdV causes up to 15% of all AGE,324, 325 whilst HAV and HEV together are responsible for 4.1% of viral hepatitis mortality.326, 327

5.2.2 Adenovirus AdVs are non-enveloped, double-stranded icosahedral DNA viruses, approximately 90- 100 nm in diameter, with fibre projections on each of the 12 vertices.183 The genome is approximately 30-35 kilobases in length and encodes for more than 30 structural and non- structural proteins.184 AdV belongs to one of five genera within the Adenoviridae family, genus

Chapter 5: Genetic diversity of adenovirus

Mastadenovirus. Within the genus, seven known serogroups have been identified (A-G) which can be further classified into 67 serotypes.171

In addition to gastroenteritis, AdV can cause a wide range of clinical diseases, including respiratory illness, conjunctivitis, hepatitis and pneumonia.171 This is because many AdV serogroups, in particular serogroup D, have a wider tissue tropism. Of all seven serogroups, AdV serogroups A, F and G have selective tropism for the gastrointestinal (GI) tract and are rarely found to infect other tissues.195, 205, 328 Whilst, serogroups B, C and E are more commonly associated with respiratory illnesses,195 but can also cause gastroenteritis.329, 330 Serogroup D viruses mainly cause conjunctivitis.195-197

5.2.3 Norovirus

Norovirus is the leading cause of viral gastroenteritis worldwide and is responsible for approximately 210,000 deaths per year.1 It is a single-stranded, RNA virus belonging to the Caliciviridae family. It can be further divided into six genogroups and more than 40 genotypes.30 Of those, only genogroup (G) I, GII and GIV are associate with human infections where the majority are caused by genogroup II (GII).16 The virus is transmitted via the faecal-oral route, with a reported infectious dose of less than 100.60 The incubation period ranges from between 12 to 48 hours.14 Similar to AdV, norovirus is also stable in external environments and is resistant to biodegradation in water where it can remain infectious in groundwater for two months.331-333

5.2.4 Quantification of enteric viruses in wastewater The quantification of pathogenic viruses in wastewater is important to understand the viral burden and possible risks involved in the case of viral contamination of water sources. It is also key to measure the DNA levels of AdV present in wastewater, as viral contamination can pose a public health risk and affect hundreds of people. In addition to AdV, norovirus is also one of the most commonly identified enteric viruses in wastewater,334-336 thus measuring its concentration can provide a better understanding of viral contamination risk in water systems. In addition, knowledge on enteric virus levels can help determine the necessary treatments required for proper removal of pathogenic viruses in recycled water. In contrast, bacterial indicators such as total coliform, faecal coliforms, E. coli and enterococci, are commonly used to detect faecal contamination. These bacteria are prevalent in the intestine and faeces of warm- blooded animals and thus presence suggest faecal contamination, even though the bacteria are not usually pathogenic.

Chapter 5: Genetic diversity of adenovirus

Despite the number of studies performed to measure the DNA levels of AdV in wastewater, several issues were identified. Firstly, the concentration of total virus measured by previous studies varied considerably, ranging from 6.3 x 104 genome copies/L219 to 6.5 x 107 genome copies/L.337 This was also observed for norovirus GII RNA levels, whose concentration ranged from 6.8 x 103 genome copies/L296 to 6 x 107 genome copies/L.258 Secondly, the measurement unit used has not always been standardised between studies; units used include PCR detectable units (PDU)/L260, 262, 263 and RT-PCR or PCR units/L,259 rather than genome copies/litre. This prevents any direct comparison between these studies. Thirdly, the majority of the studies do not have a process control, unlike this thesis, to ensure all steps performed in the quantification assay are validated, including concentration and extraction processes.219, 242, 338 Therefore, there is a need for better methods and controls for enteric virus quantification within the wastewater systems, which this thesis has addressed.

5.2.5 AdV surveillance at a population level using NGS Despite the large number of molecular epidemiological studies on human enteric viruses, the majority have been conducted with clinical samples from patients presenting with gastroenteritis or hepatitis. AdV-associated gastroenteritis is generally asymptomatic or self- limiting, and usually does not require hospitalisation or special medical attention.339 Therefore, clinical data is only inclusive of symptomatic/more severe cases, neglecting asymptomatic/mild cases and is not representative of all AdV viruses in the population.

During both acute and symptomatic phases of infection, high levels of virions can be found in stools of infected individuals and viral particles continue to be shed for months after symptoms have subsided.340, 341 Additionally, enteric viruses are very stable in external environments and resistant to degradation.43, 342 The combination of these two factors leads to high levels of enteric viruses in wastewater and as such represents a useful source to comprehensively study the molecular epidemiology of virus populations infecting individuals within the community.

To-date only a limited number of studies have examined the correlation between genotypic diversity of AdV between wastewater and clinical samples.219, 247 Of those studies, the majority do not quantify the total number of viruses, and older Sanger sequencing technologies have been used to measure viral diversity.242, 260, 343 These traditional cloning and Sanger sequencing methods are biased towards the strains that are more prevalent in the given sample, and do not give an accurate overall picture of the genetic diversity in wastewater systems.344

Chapter 5: Genetic diversity of adenovirus

With the advance of next generation sequencing technology (NGS), AdV genotype diversity can be determined and monitored in complex wastewater samples for a more comprehensive understanding of viral molecular epidemiology at the population scale.

5.2.6 Aims The aim of this study was to quantify concentrations and diversity of enteric viruses in three wastewater treatment plants in Sydney and Melbourne, Australia. With the use of molecular methods, the AdV DNA and norovirus RNA levels were quantified and compared to better understand viral levels within the wastewater systems. Furthermore, using NGS technologies, the diversity of AdV was determined in wastewater representing millions of people, i.e. at a population level. The diversity of AdV identified in wastewater was then compared to those found in clinical AdV data from New South Wales (NSW) to determine if the groups and serotypes identified between the two sample types were similar.

Chapter 5: Genetic diversity of adenovirus

5.3 Material and methods

5.3.1 Wastewater sample collection Monthly influent samples (250 mL) were collected from wastewater treatment plants (WWTP) in Sydney (Bondi and Malabar) between January 2016 and June 2017, with a population capacity of 296,350 and 1,667,460, respectively. For Melbourne (Western Treatment Plant), influent samples (1L) were collected from January to December 2016 (population capacity 2,400,000). All samples were delivered to the University of New South Wales (UNSW) on the day of collection, aliquoted and stored at -80°C upon arrival.

5.3.2 Clinical sample collection AdV-positive clinical samples (n=40) were collected from Prince of Wales Hospital throughout the two-year study period (January 2016 to December 2017). Multiplex polymerase chain reaction (PCR) was used during routine diagnosis for AdV detection. This study was approved by the UNSW Human Research Ethics Advisory Panel (HREAP), ethics approval number HC17459.

5.3.3 Viral concentration and nucleic acid extraction Wastewater samples (12 mL) were centrifuged at 9,400 x g at room temperature for 15 min to remove debris. The supernatant was ultracentrifuged at 186,000 x g at 4°C for 1.5 hrs for viral concentration. The supernatant was then carefully removed, and the pellet was resuspended in 100 µL of PBS.

For clinical samples, a 20% (v/v) suspension in water was prepared as described previously.33 Viral nucleic acid from clinical and wastewater samples were extracted using the QIAamp Viral RNA mini kit and eluted in a final volume of 60 µL.

5.3.4 MS2 process control MS2 bacteriophage was used as extraction and process control for wastewater samples to validate all downstream processes including viral concentration, viral nucleic acid extraction, reverse transcription and PCR amplification. MS2 was prepared as 20 µL frozen aliquots with a concentration of 2.6 × 105 ± 1.6 × 105 genome copies of viruses and added to samples prior ultracentrifugation, which then produced a cycle threshold (ct) value of 16.26 ± 1.6 when spiked into clinical and wastewater samples (n=40).

Chapter 5: Genetic diversity of adenovirus

5.3.5 NGS amplicon preparation For the detection and quantification of AdV in wastewater samples, extracted DNA was subjected to a nested, quantitative polymerase chain reaction (qPCR). First, PCR was used to amplify AdV DNA from extracted nucleic acid using primers (hex1deg/hex2deg)345 targeting a 301 bp of the hypervariable hexon gene of AdV. Amplification of this gene allows for the discrimination of more than 54 serotypes of AdV (34). A 50 µL PCR mix was prepared for each sample, containing 5 × Platinum Taq DNA polymerase (Invitrogen, Carlsbad, CA, USA), 2 × reaction mix (Invitrogen), 500 nmol/L of each primer and 8 µL of extracted nucleic acid. PCR conditions were 95°C for 30 sec and 15 cycles of 95°C for 15 sec, 55°C for 30 sec and 72°C for 1 min; followed by a final extension of 72°C for 7 min. For amplicon NGS sequencing, a second round PCR was used to add overhang adapters to both ends of the purified amplicons. The primers nehex3deg and nehex4deg345 were used to generate a 107 bp region of the hexon gene, but with the addition of Illumina overhang adapters. The conditions of the second round PCR were the same as first round with the number of cycles increased to 25.

5.3.6 Quantification of AdV DNA and norovirus RNA levels in wastewater For the quantification of AdV DNA levels in wastewater samples collected from the three WWTP sites, monthly viral loads were determined using qPCR with reference to standard curves, but without the addition of adapters for the nested round PCR. The viral nucleic acid levels were defined as the number of AdV genome copies per litre of wastewater.

For the quantification of norovirus GII RNA levels, a 311 bp region of the 5’ end of norovirus GII capsid was amplified from purified nucleic acid with a real-time, one-step nested reverse transcription (RT) PCR approach. Eight microliters of extracted nucleic acid was added to a total of 50 µL PCR reaction mix (SuperScript III One-step RT-PCR System with Platinum Taq high fidelity; Invitrogen), 500 nmol/L of the outer primers for norovirus GII (G2F1/G2R1)346 and 0.4 µL of SuperScript III reverse transcriptase enzyme (Invitrogen). Cycling conditions included a 30 min reverse transcription step at 50°C; reverse transcription inactivation at 95°C for 2 min; 15 cycles of 95°C for 15 sec, 57°C for 30 sec, and 68°C for 1 min; followed by a final extension of 68°C for 5 min. The second round PCR was prepared by adding 2 µL of first round product to 23 µL of reaction mix from SuperScript III One-step RT-PCR System with Platinum Taq (Invitrogen),

0.2 mM dNTP mix, 2 mM MgSO4 and 200 nmol/L of each of the second-round primers (G2F3/G2SKR).276

Chapter 5: Genetic diversity of adenovirus

5.3.7 Nextera library preparation All PCR products were cleaned up using Agencourt AMPure XP beads (Beckman Coulter, CA, USA), and libraries were prepared and quantified using the Nextera DNA sample preparation kit (Illumina) and Quant-iT PicoGreen dsDNA assay kit (Thermo Fisher, Massachusetts, USA), respectively. The quality of fragment sizes were evaluated using Tape Station D1000 (Agilent Technologies, Santa Clara, California, United States). Samples were submitted to the Ramaciotti Centre for Genomics at UNSW, Sydney, Australia, for paired-end sequencing on the Illumina MiSeq platform using a v2 300 cycle kit (2 × 150 bp).

5.3.8 NGS data analysis Sequencing data were analysed using the platform Geneious, version 9.347 FastQC application on BaseSpace (Illumina) was used to measure the quality of the reads, and only sequences with phred score above 28 were selected. Sequences were also removed if they did not range between 200 to 320 base pairs. The paired-end sequences were merged, and primer/adapter sequences were trimmed to avoid false read mapping. AdV hexon gene reference sequences were collected from NCBI database and imported into Geneious program. The trimmed sequences were then aligned to AdV reference sequence lists independently. The default parameters for the Geneious read mapper were utilised; medium sensitivity was used for reference mapping and virus type identification. The number of reads aligned to each reference genotype were recorded to be used for viral diversity in wastewater samples.

Chapter 5: Genetic diversity of adenovirus

5.4 Results

5.4.1 Quantitative analysis of AdV and norovirus in wastewater samples A total of 68 monthly wastewater samples were collected from three wastewater treatment plants over the study period (January 2016 to December 2017). Using qPCR, DNA levels were measured and expressed as genome copies per litre. In the Bondi WWTP, the highest AdV DNA levels were observed in the summer season between January and March of both 2016 (average of 4.0 ´ 107 genome copies/L) and 2017 (average of 4.9 ´ 107 genome copies/L) (Figure 5-1A). DNA levels were the lowest at the Bondi WWTP in July 2016, with 6.4 ´ 104 genome copies of AdV DNA/L. Over the two-year period, the monthly average of AdV DNA detected in 2016 (1.1 ´ 107 genome copies/L) was 1.8-fold lower compared to 2017 (2.0 ´ 107 genome copies/L) (Figure 5-1A). The highest AdV DNA levels detected at the Malabar site were in December 2016 (5.2 ´ 107 genome copies/L), followed by December of the following year (5.1 ´ 107 genome copies/L) (Figure 5-1B). The lowest detected level was in May 2016, with 3.8 ´ 104 genome copies/L (Figure 5-1B). For the Melbourne site, AdV DNA levels were not measured between January and April in 2017. For the remaining months, the highest detected DNA levels were in July 2017 (2.4 ´ 107 genome copies/L), and the lowest DNA were in September 2016 (1.3 ´ 106) (Figure 5-1C). Across the three sites, Malabar exhibited the highest monthly average AdV DNA levels compared to the other two sites, with an average of 2.3 x 107 genome copies/L (ranged from 3.8 x 104 to 5.4 x 107genome copies/L). Bondi averaged 1.5 × 107 genome copies/L each month (range from 6.4 × 104 to 7.8 × 107), whilst Melbourne averaged 8.6 × 106 genome copies/L (range from 1.3 × 106 to 2.4 × 107) (Figure 5-1).

Chapter 5: Genetic diversity of adenovirus

Figure 5-1. AdV DNA levels detected in wastewater samples collected from Sydney and Melbourne. The AdV DNA levels were measured in all three wastewater treatment plants; Bondi, Malabar and Melbourne Western treatment plant. Viruses in 12 mL of wastewater were concentrated with ultracentrifugation and viral nucleic acid was subsequently extracted. The purified nucleic acid was then subjected to nested PCR for the detection of AdV DNA in the samples. The AdV DNA level was quantified using standard curves with known genome copies of adenovirus DNA, represented in genome copies per litre. The AdV DNA level measured in each site are represented by different colours; Bondi shown in orange, Malabar in aqua and Melbourne in green. The shaded grey boxes represent the four seasons of the year, as indicated by the legend.

Norovirus GII RNA levels were measured using qRT-PCR. The highest norovirus levels at the Bondi WWTP were detected in October 2016 (2.6 ´ 108 genome copies/L), and the lowest were detected in August 2016 (1.8 ´ 105 genome copies/L) (Figure 5-2A). In Malabar, the highest levels of norovirus GII RNA were seen in September 2016 (1.2 ´ 108), followed by October (9.2 ´ 107) and November (6.9 ´ 107) of the same year. In contrast to the Bondi WWTP, the highest

Chapter 5: Genetic diversity of adenovirus norovirus RNA levels were measured in Malabar site were in October 2016 (9.7 ´ 107), followed by August of the following year (3.6 ´ 107 genome copies/L) (Figure 5-2B). The lowest RNA levels detected were in January 2016 and July 2017, both with 1.9 ´ 105 genome copies/L (Figure 5-2B). Between the three sites, Melbourne WWTP had the highest monthly average norovirus GII RNA levels at 1.8 × 107 viral genomes/L (range from 4.1 × 104 to 9.7 x 107 genome copies/L), followed by Bondi (1.6 × 107, range 1.8 × 105 to 2.6 × 108 genome copies/L) and Malabar (1.5 × 107, ranged between 1.1 × 105 and 1.2 × 108) (Figure 5-2).

Figure 5-2. Norovirus GII RNA levels detected in wastewater samples collected from Sydney and Melbourne. The norovirus RNA levels were measured in all three wastewater treatment plants; Bondi, Malabar and Melbourne Western treatment plant. Viruses in 12 mL of wastewater were concentrated with ultracentrifugation and viral nucleic acid was subsequently extracted. The purified nucleic acid was then subjected to nested RT-PCR, targeting the capsid, for the detection of norovirus GII RNA in the samples. The norovirus RNA level was quantified using standard curves. The norovirus GII RNA is shown in genome copies per litre. The norovirus RNA level measured in each site are represented by different colours; Bondi in orange, Malabar in

Chapter 5: Genetic diversity of adenovirus aqua and Melbourne in green. The shaded boxes indicate the different seasons of the year, as indicated in the legend.

In order to determine if norovirus RNA levels vary with seasonality changes, average RNA levels were calculated for each season. The season with the highest viral load measured across all three sites was in Spring 2016; Bondi (9.4 ´ 107 genome copies/L), Malabar (9.4 ´ 107) and Melbourne (3.9 ´ 107) (Figure 5-2). Across all three sites, the average norovirus GII RNA level in spring 2016 was 12-fold higher compared to winter and summer of 2016, and it was 10-fold higher compared to autumn in 2016. However, there was no distinct seasonality changes observed in norovirus RNA levels detected in 2017.

5.4.2 Genetic diversity of AdV in wastewater samples This study aimed to identify AdV serotypes circulating in the population by applying NGS technologies to wastewater samples collected from Sydney and Melbourne WWTPs. Viral nucleic acid was extracted and the hexon region of AdV amplified using PCR prior to Illumina MiSeq sequencing. An average of 2.1 × 105 reads (range 9.8 × 103 to 3.8 × 105), 2.2 × 105 (range 7.9 × 104 to 6.9 × 105) and 1.9 × 105 (range 3.0 × 104 to 4.9 × 105) were generated from Bondi, Melbourne and Malabar each month, respectively. All raw data were submitted to Sequence Read Archive (SRA) database, accession no. PRJNA509980. Next generation sequencing results revealed AdV DNA belonging to six major serogroups (A-F), which further categorised into 19 serotypes; AdV-A (12, 18, 31), AdV-B (3, 16), AdV-C (1, 2, 5, 6), AdV-D (8, 17, 19, 23, 36, 51, 58), AdV-E (4) and AdV-F (40, 41) (Figure 5-3).

Chapter 5: Genetic diversity of adenovirus

(A) Bondi (capacity 296,350) 100

75 Serogroup A 50 AdV12 AdV18 AdV31

Distribu�on of Distribu�on 25 AdV genotypes (%) AdV genotypes Serogroup B AdV03 0 J F M A M J J A S O N D J F M A M J J A S O N D AdV16 2016 2017 Time (month/year) Serogroup C (B) Malabar (capacity 1,667,460) AdV01 100 AdV02 AdV05 AdV06 75 Serogroup D 50 AdV08 AdV17 AdV19

Distribu�on of Distribu�on 25 AdV23

AdV genotypes (%) AdV genotypes AdV36 AdV51 0 AdV58 J F M A M J J A S O N D J F M A M J J A S O N D 2016 2017 Serogroup E Time (month/year) AdV04 (C) Melbourne (capacity 2,400,000) 100 Serogoup F AdV40 AdV41 75

Not 50 sampled

Distribu�on of Distribu�on 25 AdV genotypes (%) AdV genotypes

0 J F M A M J J A S O N D J F M A M J J A S O N D 2016 2017 Time (month/year)

Figure 5-3. AdV genotypic distribution in wastewater samples collected from Sydney and Melbourne, 2016 to 2017. Wastewater samples were concentrated using ultracentrifugation methods, followed by viral nucleic acid extraction. A nested PCR was used to amplify the hexon gene of adenovirus and attachment of overhang adapters. Libraries were generated, and amplicons were sequenced on Illumina MiSeq platform. The adenovirus diversity in wastewater was identified by mapping the reads to adenovirus reference sequences, obtained from GenBank. The distribution of adenovirus genotype was calculated by dividing the number of read attributed to the serotype over the total number of reads generated for that month. The relative abundance of adenovirus serotypes are labelled in different colours, as indicated by the legend.

Chapter 5: Genetic diversity of adenovirus

Despite the large number of serotypes identified, the most commonly represented serogroup was AdV-F, with a relative abundance of more than 94.5% of total reads, followed by AdV-A (4.7% of all reads). Specifically, AdV-F41 accounted for an average of 77.7% in Bondi (range from 1.3% to 99.8%), 79.3% in Malabar (range 21.9% to 99.5%) and 68.2% in Melbourne (range 14.8% to 99.5%) (Figure 5-3). Of the three serotypes identified within the AdV-A serogroup, A31 was found to be the next dominant serotype identified in both Bondi and Malabar sites with an average of 10.0% of reads per month, which ranged from 0 to 61.6% (Figure 5-3A and Figure 5-3B). This was followed by AdV-A12, which accounted for 4.1% and 7.8% of monthly reads in Bondi and Malabar, respectively. In contrast to Sydney, the second most prevalent serotype identified in Melbourne was AdV-F40, which accounted for an average of 9.4% of reads per month (ranged between 2.0% and 91.2%) (Figure 5-3C). This was followed by AdV-A31 as the third most prevalent serotype in Melbourne and accounted for 5.4% of monthly reads (Figure 5-3C). The most predominant serotype detected over the two-year study period across all sites was AdV-F41, which accounted for 83.5% of all reads, followed by AdV- F40 (11.0%) and AdV-A31 (3.7%).

5.4.3 Genetic diversity of AdV in clinical specimens collected in Sydney The genetic diversity of AdV was also determined in clinical specimens to gain a better understanding in the AdV serotypes found in patients presenting with gastroenteritis. AdV positive specimens (n=40) were collected from hospitals and diagnostic laboratories in New South Wales between 2016 and 2017. All AdV sequences were submitted to GenBank, accession number MK296427-MK296466. Five of the seven major serogroups of AdV were identified, which included a total of seven serotypes; A31, B3, C1, C2, C30, D19 and F41. Throughout the study period, AdV-F41 was identified as the most predominant serotype in patients and accounted for 52.5% of AdV detected (n=21/40) in 2016/17. Serogroup C was the second most predominant serogroup, responsible for 35.0% of AdV infections (n=14/40). Based on hexon region sequence, three serotypes were identified within serogroup C (Figure 5-3), C1, C2 and C30. Throughout the study period, C1 and C2 were each responsible for 15% of AdV gastroenteritis cases, B3 was responsible for 7.5%, C30 5.0%, A31 and D19 each accounted for 2.5% of all cases identified (Figure 5-4).

Chapter 5: Genetic diversity of adenovirus

Serogroup A AdV31 (2.5%) Serogroup B AdV03 (7.5%) Serogroup C AdV01 (15.0%) AdV02 (15.0%) AdV30 (5.0%) Serogroup D AdV19 (2.5%) Serogroup F n=40 AdV41 (52.5%)

Figure 5-4. Genotype distribution of adenovirus identified in clinical samples. AdV positive stool samples were collected from hospitals and diagnostic laboratories between 2016 to 2017. Specimens were collected from patients presenting with gastroenteritis symptoms. Viral nucleic acid was extracted, followed by hexon gene amplification using PCR and sequenced using the Sanger approach. Phylogenetic analysis was used for AdV serotype identification, with serotypes represented by different colours as indicated in the legend.

5.4.4 Comparison of genetic diversity in clinical and wastewater samples Serotype prevalence found in wastewater and clinical samples were compared to determine if the AdV genetic diversity correlated between the two samples. In wastewater samples, a higher number of serotypes were identified (n=19 of 68), compared to the AdV serotypes (n=7) identified in clinical specimens collected from patients with gastroenteritis (Figure 5-3 and Figure 5-4). AdV-F41 was the most predominant serotype identified in both clinical and wastewater samples and accounted for 83.5% of reads from all three WWTPs throughout the study period and was also responsible for 52.5% of the AdV-associated gastroenteritis cases (Figure 5-3 and Figure 5-4). In wastewater samples, F40 was the second leading AdV serotype identified, and accounted for 11.0% of all reads, however, it did not correlate with clinical data, where it was not detected. In comparison, AdV-C was responsible for 35% of all cases and identified as the second most dominant serogroup identified in clinical specimens. Of those, serotypes C1 and C2 each caused 15% of all cases investigated. The third most prevalent serotype (3.7% of reads) identified in wastewater was A31, but this serotype only accounted for 2.5% of all gastrointestinal illness investigated.

Chapter 5: Genetic diversity of adenovirus

5.5 Discussion The combination of low infectious does, high viral shedding and stability in external environment enables the persistence of enteric viruses within a population, and they represent a major public health concern. Viruses are one of the most important aetiological agents for gastroenteritis, but most viral gastroenteritis cases and outbreaks remain unreported.348 Therefore, this limits our understanding of viral gastroenteritis incidence, as well as circulating viral strains within a population. The use of wastewater can overcome this issue as it is inclusive of all individuals within the sewerage catchment area and enables a non-biased identification of viral genetic diversity within the community.

The present study uses qPCR and NGS technologies to determine the quantity and genetic diversity of AdV in wastewater collected from Sydney and Melbourne WWTPs. MS2 bacteriophage has been widely used for enteric virus recovery in many studies.349, 350 To ensure all steps of the methodology were validated, MS2 bacteriophage was used as a process control, in the form of a frozen sphere, thus allowing a standardised amount of virus to be encapsulated. The benefit of this control enables verification of all downstream applications including; viral concentration, viral extraction, reverse transcription (for all RNA viruses) and PCR amplification. Both clinical and wastewater samples were spiked with a single MS2 BioSphere to ensure all downstream processes were validated. In addition, amplicon based NGS sequencing was used, targeting the hexon gene of AdV, thus there were no reads attributed to the control MS2 bacteriophage. All samples obtained a ct value of 16.26 ± 1.6, which confirmed the number of MS2 genome copies spiked into the sample is similar to the number of genome copies obtained. Therefore, this can ensure the efficacy of all downstream applications.

The concentration of infectious AdV can be determined using cell-culture methods, however, the use of different host cell lines in these infectivity assays is biased due to the tropism of different serotypes.219 Furthermore, cell culture is time-consuming and expensive, and thus molecular methods, such as PCR, are commonly used for viral quantification. AdV are generally effectively removed in secondary treatment, with 1-4 Log reduction in infectious viruses,242, 250 but in some cases wastewater can contaminate surface water and subsequent human exposure can occur through recreational activities. Therefore, it is important to quantify AdV circulating in the WWTP and such data may eventually be used to estimate the public health risks involved in water contamination events. The AdV DNA levels were determined in three WWTP in Sydney (Bondi, Malabar) and Melbourne (Western). An average of 1.8 × 107 genome

Chapter 5: Genetic diversity of adenovirus copies of AdV DNA was found per litre of wastewater across all three WWTPs in Australia and ranged between 1.0 × 105 and 7.8 × 107 (Figure 5-1). This was similar to the AdV load found in other countries, including Brazil (ranged between 1.7 × 105 to 2.3 × 107 genome copies/L),242, 351 New Zealand (1.9 × 104 to 4.6 × 106 genome copies/L),352 Spain (range 2.1 × 106 to 1.2 × 108)250 and Japan (average of 2.2 × 106/L).353 However, compared to the present study lower concentrations of AdV levels were detected in the United Kingdom (1 × 104 to 6 × 105 genome copies/L)354 and the United States (102 to 104 genome copies/L).355 The difference in AdV DNA levels can be attributed to many reasons including; the methodology used, the source of the wastewater (residential versus industrial), population size and the capacity of the WWTP. No distinct seasonality was observed with either high or low AdV DNA levels throughout the study period, which further supports the non-seasonality nature of AdV infections.354, 356 Furthermore, the quantification of AdV can provide more information for the infectious risk assessment in the event of water contamination.

The cultivation of norovirus has been unsuccessful until recently,357 but the method has not been applied to measuring infectious noroviruses in wastewater. In this thesis, qRT-PCR was used to quantify norovirus GII RNA levels in wastewater collected in Sydney and Melbourne, Australia. The quantification of norovirus genomes represents both infectious and non- infectious viruses, and therefore the methods used capture the total viral levels. In comparison to AdV viral load, the overall average monthly norovirus RNA level was 0.8 log lower, averaged across all sites and timepoints used in this thesis. An average of 1.6 × 107 genome copies/L was detected per month across all three WWTPs, with levels ranging between 1.8 × 105 and 2.6 × 108. This is similar to a previous study by da Silva et al. in France, where an average of 6 × 107 genome copies of norovirus GII was detected per litre of influent wastewater.258 However, other

3 296 studies have detected lower concentrations of norovirus RNA, with an average of 6.8 × 10 and 3.4 × 105 242 genome copies of norovirus GII RNA per litre of wastewater.

Katayama et al. found a difference in norovirus GI and GII RNA levels in wastewater collected in summer compared to winter, where winter samples showed a reduction of between 0.02 log and 0.05 log in virus levels, respectively.259 In contrast to this study, no significant difference was noted between the norovirus viral levels detected in winter and summer in the current study, however, an increase in viral load was observed during Spring in Australia (between September and November of 2016) across all sites in the current study. This is consistent with the seasonal peak in institution outbreaks caused by norovirus in Australia,

Chapter 5: Genetic diversity of adenovirus which is between August and November.299 Despite the increase in norovirus RNA levels during Spring 2016 across all three sites, this was not observed in 2017, thus it is difficult to identify if there is a consistent yearly seasonality change in norovirus RNA levels. In the United Kingdom (UK), Farkes et al. detected the highest norovirus GII RNA levels in November 2016.354 Even though high norovirus RNA levels were detected in both the UK and Australia, there is a seasonality difference between the countries; summer in Australia and winter in UK. Therefore, this demonstrates the continual surveillance and quantification will need to be performed for a more comprehensive temporal analysis of enteric viral levels in wastewater around the globe.

The majority of AdV infections are asymptomatic,358 therefore reliance on clinical specimens to understand the full picture of circulating serotypes within the population is likely not sufficient, as only symptomatic individuals seek medical attention. Asymptomatic infections are not a burden to the infected individual as they are not exhibiting any symptoms. However, it can be problematic to those that are more vulnerable as viral particles are also shed from asymptomatic individuals. In addition, a high viral load of AdV is shed into the wastewater system and it is always detected in wastewater.359-361 Therefore, using NGS technologies, the genetic diversity of AdV in WWTP samples was examined for a better representation of all circulating AdV serotypes within the community. Primers used bind to the hexon gene of adenoviruses, which is a conserved yet diverse region of the virus, allowing the detection of all serotypes with no biased. Overall, AdV serotypes F-41, A-31, A-12 and F-40 were most commonly represented (Figure 5-3), collectively making up more than 90% of the AdV population detected (Figure 5-3). Serotypes identified in this study were similar to others that have examined the AdV diversity in wastewater.219, 344 Serotype F-41 and F-40 are commonly associated with gastroenteritis and not surprisingly, F-41 was represented in more than 50% of the monthly AdV population across all three wastewater sites throughout 2016 and 2017, which is consistent with previous studies.219, 360 Interestingly, despite its ability to cause gastroenteritis F-40 was less commonly detected in wastewater compared to F-41, this lower prevalence (11.0%) was also observed in other studies.362 Not surprisingly, serotype A, and in particular A- 12 and A-31, was identified as the second most common group within the circulating population, this is because serotypes A-12 and A-31 are also associated with gastrointestinal infections and urinary infections, respectively. Serotype A-31 is a significant AdV pathogen as it can cause gastroenteritis, in particular infants,329, 363, 364 as well as disseminated diseases in children after liver and hematopoietic stem cell transplantation.365 Serotype A-12 has also been associated

Chapter 5: Genetic diversity of adenovirus with meningoencephalitis.366, 367 This highlights the importance of subgroup F and A in a clinical setting, as well as its high prevalence in wastewater samples.

The genetic diversity of AdV observed in WWTP samples was compared with clinical (n=40) symptomatic cases (gastroenteritis infections), collected within the same time-frame of the study, to enhance our understanding of difference between circulating clinical cases and AdV within the population. This analysis could help to confirm AdV serotypes that are associated with more severe cases, as only symptomatic individuals usually present to the medical facilities. The most common cause of AdV-associated gastroenteritis was serotype F-41, which accounted for 52.5% of all cases investigated (Figure 5-4). Based on other AdV studies using clinical specimens for surveillance, serogroup F is commonly associated with AdV acute gastroenteritis cases,356, 368, 369 which correspond to the high detected level in WWTPs. Interestingly, 35% of all clinical cases were identified as serogroup C AdV. AdV serogroup C often cause mild respiratory infection, and they can be associated with more severe disease such as intussusception, pneumonia and myocarditis in children under the age of one.370, 371 Even though serogroup C AdVs were associated with respiratory illnesses, previous studies have demonstrated their high prevalence in adenovirus positive clinical specimens.372, 373 This could be due to its lower stability to persist in external environment compared to other AdV serogroups, and it may be shed at lower levels compared to serogroup F. Further work will need to be performed to better understand why serogroup C is less prevalent in wastewater samples. However, the use of both clinical and wastewater sample will enhance the molecular surveillance of adenovirus, identifying strains in both symptomatic and asymptomatic patients.

In conclusion, we demonstrated routine surveillance of enteric viruses in water samples is a useful tool for monitoring the prevalence of enteric viral genotypes and serotypes. Using NGS technology, the identification and diversity of AdV in complex environmental samples were achieved, and results are consistent with previous data on AdV serotypes identified in the water environment. Future studies can be performed to monitor other pathogenic enteric viruses circulating in water matrices.

Chapter 6: General discussion

6 General Discussion

There is an estimated 1.7 to 5 billion cases of diarrhoeal disease across the world each year.14 These cases also result in approximately 1.7 million deaths, the majority of which occur in young children from developing countries.57 Infections with norovirus and AdV pose a serious health and economic burden around the globe and together these viruses account for 33% of all acute gastroenteritis cases across the world.13, 374 Norovirus-associated acute gastroenteritis is responsible for approximately 200,000 deaths per year.1 Furthermore, the burden of AdV- related illnesses is often underestimated, as the majority of AdV related illnesses are asymptomatic. AdV can cause a range of diseases such as respiratory tract infections, conjunctivitis, acute haemorrhagic cystitis and meningitis.220 Recent studies have demonstrated AdV was the aetiological agent in 6-20% of children admitted to hospital presenting with lower respiratory infections,172-175 and responsible for 10-23% of all children admitted with acute gastroenteritis globally.176, 375 Therefore overall, AdV poses a large health burden on the globe, particular in paediatric settings.

Since 1996, six pandemics of norovirus-associated gastroenteritis have been identified in which all variants emerged from the GII.4 lineage.93 In general, GII.4 variants account for 62-80% of all norovirus cases worldwide.16 The predominance of GII.4 variants has resulted in hundreds of millions of infections globally and outbreaks impacting the most vulnerable populations in the community, including the elderly, children and immune-compromised individuals.

In comparison, AdV has a wide cellular tropism that enables it to cause numerous clinical illnesses, unlike other viruses with specific tropism (e.g. norovirus), and therefore specific AdV subgroups and serotypes are commonly associated with specific diseases. For example, subgroup F (40 and 41) primarily cause gastroenteritis,222 whilst subgroup C (1, 2, 5 and 6) cause mainly respiratory illnesses.213 AdV can persist in external environments for months,218, 219 and this fact, together with their enteric nature, means they are commonly found in various water matrices and can potentially infect hundreds of individuals through waterborne outbreaks.207, 244, 376

Despite the high morbidity and mortality associated with norovirus and AdV infections, there are currently no preventative vaccines or antivirals available. GII.4 norovirus and AdV B-7 are more divergent and pathogenic compared to other genotypes and serotypes.52, 105, 174, 377 An essential part of successful vaccine or antiviral development is the identification of circulating

Chapter 6: General discussion norovirus and AdV strains within the population. Therefore, molecular epidemiological surveillance of both norovirus and AdV is essential to understand the most prevalent strains/serotypes in circulation within the population.

However, the current standards in clinical surveillance neglect mild or asymptomatic infections and in addition the identification of enteric viruses is not enforced in all medical facilities. This is problematic since high viral load and prolonged shedding of norovirus and AdV is observed in not only in symptomatic214, 341, 375, 378, 379 but also asymptomatic individuals.85, 380 Consequently, a more accurate picture of the strains circulating in the community can be obtained through the study of viruses in wastewater.

Therefore, this thesis aimed to;

(i) Identify the circulating noroviruses within the Australian and New Zealand population to detect emerging and/or recombinant viruses. This can help understand their prevalence within the Oceania region. (ii) Describe the evolutionary mechanisms that contribute to the higher epidemiological fitness of GII.4 variants and their predominance as a causative agent of norovirus-associated acute gastroenteritis. (iii) Quantify norovirus and AdV levels in wastewater. This will provide a more robust assessment of a populations’ risk of virus infection following sewage contamination of water reservoirs. (iv) Identify the genetic diversity of norovirus and AdV in wastewater and compare this to the diversity found in clinical data. This will help determine if there are similar trends in viral diversity between the two sample types and establish if wastewater can be used as a useful surveillance tool.

Chapter 6: General discussion

Emergence of novel noroviruses, concomitant with a decline of GII.4 Sydney pandemic variant in the Oceania region between 2014 and 2017

A successful norovirus vaccine must induce broad protective immunity against various circulating genotypes to provide the widest coverage against the antigenically diverse norovirus. Furthermore, future norovirus vaccines, in particular, needs to be updated on a regular basis due to continued viral evolution and subsequent escape from population immunity.127 For this reason it is imperative to characterise circulating norovirus strains, recombinants and emerging epidemic/pandemic variants using molecular epidemiological surveillance around the globe, as they will ultimately benefit the efficacy of the norovirus vaccine.

In this thesis, two comprehensive molecular epidemiological studies were performed to characterise the norovirus strains circulating in both Australia (NSW, ACT and QLD) and New Zealand between 2014 and 2017 (Chapters 3 and 4). Using RT-PCR, sequencing and phylogenetic analysis of the partial capsid gene, GII.4 Sydney 2012 was identified as the dominant cause of three consecutive winter epidemics of acute gastroenteritis across NSW, Australia and New Zealand between July 2014 and December 2016. This was not surprising as the pandemic usually represents the predominant norovirus identified in all norovirus cases globally.16, 108 However, a slight decline in the prevalence of the Sydney pandemic variant was observed over the 2.5-year period (from 64.7% in 2014 to 46.4% in 2016) (Figure 3-3). Closer inspection of the combined analysis on both non-structural (RdRp) and structural (capsid) regions revealed that the GII.4 Sydney pandemic variant (GII.Pe/GII.4 Sydney 2012) was only responsible for 45.0% and 13.2% of infections identified in 2015 and 2016, respectively (Figure 3-3). The remaining GII.4 Sydney 2012 sequences did not contain a GII.Pe polymerase; one cluster recombined with its predecessor GII.4 New Orleans 2009, and the other cluster with a GII.P16 virus.

In 2016, the rapid decrease in the Sydney pandemic variant prevalence, from 51.3% in 2015 to 46.6%, was concomitant with the emergence of five novel noroviruses. This resulted in the co-circulation of six noroviruses; the Sydney pandemic variant, two Sydney 2012 recombinant viruses (GII.P4 New Orleans 2009/GII.4 Sydney 2012 and GII.P16/GII.4 Sydney 2012), GII.P17/GII.17, and another two recombinant viruses (GII.P16/GII.2 and GII.P12/GII.3) (Figure 3-3). This co-dominance of multiple viruses continued into 2017 (Chapter 4). However, a sudden increase in recombinant GII.P16/GII.4 Sydney 2012 was observed in the early months of 2017 (Figure 4-3). This was the first observation of a GII.4 variant that recombined with two

Chapter 6: General discussion viruses; a predecessor strain and a GII.P16 virus, whilst maintaining its capsid. This is indicative of the importance of recombination in norovirus evolution, as the GII.4 Sydney recombinants continued to cause epidemics, even into 2018.

As well as detection in Australia and New Zealand, the GII.P4 New Orleans 2009/GII.4 Sydney 2012 recombinant was also detected in the United States,280 Denmark,281 United Kingdom282 and Africa300 between 2012 to 2014, when the Sydney 2012 pandemic variant largely predominated. In this study, this variant maintained a low to very low prevalence and did not cause any significant outbreaks or epidemics until 2016 (Chapter 3). Following its emergence in the Oceania region, a rise in GII.P4 New Orleans 2009/GII.4 Sydney 2012 was also observed in Denmark between 2016 and 2017, where it was responsible for 28% of all outbreaks identified.284 This emergence was also observed in the United States, where it was responsible for 7.2% of all norovirus outbreaks investigated.107 The prevalence of recombinant GII.P16/GII.4 Sydney 2012 increased in Oceania from 2016 (Figure 3-3C and Figure 4-3) and this is in line with a study from France, which showed that this variant caused 24% of all norovirus outbreaks identified between 2016 and 2017.284 Furthermore, its predominance was also observed around the globe.107, 285, 286 The co-circulation of two recombinant viruses, both containing the GII.4 Sydney capsid, demonstrates the exchange of non-structural region can assist the persistence of the GII.4 Sydney 2012 capsid sequence in the norovirus population. The acquisition of a new RdRp could affect its replication activity125 and the exchange of GII.P16 RdRp may have increased its viral fitness, but additional work is needed to determine this.286

In this study, GII.P17/GII.17 noroviruses were identified in sporadic cases, as well as in water matrices around the globe,300, 381-386 however, it was rarely reported as the predominant genotype in clinical norovirus-associated gastroenteritis cases. In the winter of 2014 and 2015, an unexpected increase in GII.P17/GII.17 was observed in south-east Asian countries, where it was responsible for 51.2-69.6% of all norovirus infections, replacing the previous dominant GII.4 Sydney 2012 variant.114, 116, 387, 388 In comparison the GII.P17/GII.17 variant was identified within Oceania in 2014, however it remained at low prevalence and did not dominate until 2016 (Figure 3-3). Similarly, in Italy, GII.P17/GII.17 was increasingly reported as a prevalent cause of norovirus infections, from as few as <10% of cases in 2013-14, to over 40% of cases in 2016.389 This increased occurrence in 2016 was also observed in other countries around the globe.107, 115, 390

It is unclear why there was a much higher rate of norovirus GII.17 infections in southeast Asian countries compared to other parts of the world. One hypothesis is that the

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GII.P17/GII.17 genotype replaced the GII.4 Sydney variant in Asia due to its polymerase, which was reported in one study to have a higher error rate compared to GII.4 pandemic strains.387 This higher error rate could enable the GII.17 viruses to maintain viral fitness and thus escape host immunity. In addition, residue substitutions on the antigenic epitopes of the GII.17 capsid were speculated to be due to the acquisition the new RdRp. Interestingly, the persistence of GII.17 in Australia and New Zealand lasted until late 2016, where it was replaced by novel recombinant GII.P16/GII.2.289, 391, 392 This virus circulated at a low prevalence prior to mid 2016,108 but was responsible for nearly 20% of all norovirus sporadic cases analysed and numerous outbreaks in 2016 (Figure 3-3). This sudden increase was not only noted in the Oceania region, but was also observed around the globe.284, 285, 288, 289, 393-395 The later decline of GII.17 is likely to be due to herd immunity within the population.

Genotype GII.3 noroviruses are commonly associated with childhood infections, in particular recombinant GII.P21/GII.3.108, 135, 396, 397 Between 2014 and 2015, this genotype was responsible for an average of 4-11% of all norovirus infections in the Oceania region. In 2016, a new recombinant, GII.P12/GII.3, was also found to be associated with childhood infections where >90% of the patients infected with this strain were under the age of 12 (Figure 3-3). This suggests a strain predilection towards childhood infections. This recombinant GII.P12/GII.3 strain was also identified as the dominant GII.3 noroviruses isolated from children in China and Thailand between 2015 and 2016.398, 399 The acquisition of new ORF1, which encodes the GII.P21 RdRp (formally GII.Pb) to GII.P12, perhaps resulted in a higher mutation rate for the polymerase which subsequently increased genetic diversity.400

Our knowledge gained from this study demonstrated a co-circulation of six noroviruses within the Australian population. If the pattern of multiple co-circulating strains continues, then the composition of a norovirus vaccine will likely require multiple virus strains, including GII.3 strain as it commonly infect children, for better protection and efficacy.

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Mechanisms for the persistence of GII.4 Sydney capsid within the population

Recombination

Recombination within the norovirus genome at the ORF1/ORF2 overlapping region is a mechanism for the generation of genetically diverse strains, enabling norovirus to continually evolve and cause outbreaks. This thesis shows the importance of recombination in the emergence of both inter-genotypic and intra-genotypic recombinants (Chapter 3 and 4). This thesis also highlights that the current methods used to identify true viral recombination events, and genotyping methods which involve sequencing of the partial capsid (Region C) are not sufficient for full strain identification (Chapter 3).

Previous studies have shown that exchange of the RdRp (usually through recombination) can alter replication fidelity, influencing both viral fitness and transmission.125, 401 One example is the recombination event that allowed a GII.3 virus to acquire a GII.P12 ORF1, which subsequently allowed this new variant to cause more infections, as the population became immune naive.310 In 2016, the emergence of two GII.4 recombinant strains was reported, the strains are referred to as; GII.P4 New Orleans 2009/GII.4 Sydney 2012 (GenBank accession number KY905331) and GII.P16/GII.4 Sydney 2012 (GenBank accession number KY905335) (Table 3.2).

Simplot analysis of the full-length genome sequences of these strains showed that both contained a GII.4 Sydney 2012 ORF2/3 region, but had unique ORF1 regions, i.e. GII.P16 and GII.P4 New Orleans 2009 (Figure 3-5). Intra-genotypic recombination is commonly observed, particularly in more recent times (2007 to 2008) for viruses within the GII.4 lineage.105 It should be noted, the GII.P4 New Orleans 2009/GII.4 Sydney 2012 recombination event represents the most important recombination event between a pandemic variant and its predecessor, in terms of epidemiological fitness. Work in this thesis demonstrates that these new recombinants that maintained the GII.4 Sydney 2012 capsid (n=3), and which had subsequently acquired a new ORF1 region, likely had a genetic and selective advantage for continued human infection. These strains also likely had an increased ability to evade host immunity, as population immunity was directed towards the previous GII.Pe non-structural region.125, 401

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Antigenic variation within the capsid

The emergence of two new recombinant viruses that comprised of the same Sydney pandemic variant capsid (VP1) sequence, is unusual since population immunity has been shown to be commonly targeted towards the capsid region of norovirus. Hence, antigenic variations within the viral capsid are frequently observed among the GII.4 variants.93 In addition, it is very uncommon for three of the six co-dominant viruses to all contain the same capsid.

To further analyse this unusual phenomenon, the full-length sequences of strains representing the three GII.4 Sydney capsids (n=20) were analysed for antigenic variation, with a focus on the putative five antigenic sites and HBGA binding pockets (termed motifs A-E) (Figure 4-6). When compared to the original Sydney 2012 pandemic sequence, amino acid (aa) variations were observed in all three recombinants and the majority of changes were located within the main antigenic epitopes (Figure 4-6). In particular, positive selection was identified at residue 373 of epitope A in all three recombinant GII.4 Sydney strains, consistent with the study of Eden et al., 2013.105

Of all the blockades epitopes, epitope A is one of the most important determinants of antigenic changes that has been associated with the emergence of new GII.4 variants and the loss of blockade antibody binding.57, 311 Furthermore, the amino acid sequence of GII.P16/GII.4 Sydney 2012 capsid showed aa reversion, where the sequence resembled that of the GII.4 New Orleans 2009 pandemic variant (Figure 4-6). Therefore, the combination of both recombination and antigenic variation has both influenced the evolutionary persistence of GII.4 Sydney capsid. This also further demonstrates that antigenic variation within the GII.4 Sydney capsid allows for viral escape from herd immunity.

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Quantification of enteric viruses in complex wastewater samples

Inadequate discharge of sewage can lead to contamination of aquatic environments. Human enteric viruses present in sewage are of particular concern owing to their stability in external water environments, low infectious dose and high viral shedding.

Therefore, it is useful to quantify both norovirus RNA and AdV DNA levels in wastewater to predict the risk of infection to the population in an event of water contamination by viruses. Previous studies have been performed to quantify enteric virus levels in wastewater, however, several experimental and study design factors prevent the direct comparison between these reports. These include: a non-standardised unit of measurement,259, 262, 263, 402 and a lack of process controls for the validation of the methods used.219, 242, 338 Due to the above issues, the level of viruses detected can vary significantly between studies and thus accurate total virus quantification for AdV and norovirus still remain elusive.219, 258, 296, 337

In this study, norovirus GII RNA and AdV DNA genome copies were quantified in Australian wastewater (Chapter 5). In conjunction with this, MS2 bacteriophage was used as a process control to ensure all steps (viral extraction, reverse transcription and PCR amplification and quantification) were validated. Across the three wastewater treatment plants in Sydney and Melbourne, a monthly average of 1.1 ´ 107 and 1.6 ´ 107 genome copies/L was determined for norovirus GII RNA and AdV DNA, respectively (Figure 5-1 and Figure 5-2) which correlates with concentrations of these viruses found in previous studies.236, 403 In an Italian study, AdV was identified to have the highest concentration in wastewater, compared to other viruses, with levels up to 9.8 ´ 108 genome copies/L, whereas norovirus was detected at a concentration of 9.9 ´ 105 genome copies/L.404 A slightly lower concentration of norovirus was detected in Japan where up to 1.3 ´ 106 genome copies of GII RNA was detected per litre.295 The correlation seen in this study with other studies, strongly suggests PCR based methodology could be a standardised technique used for quantification of enteric viruses in wastewater. Quantification of viral genome levels within the wastewater system is important and can assist in measuring the risk of viral infection in the general public following water contamination events.

This study presents the first quantitative investigation of AdV in Australian wastewater samples, and it represents a significant advancement in the quantification of enteric viruses in wastewater. Furthermore, the quantification of norovirus GII RNA and AdV DNA levels was performed in conjunction with the use of process internal controls, and thus the data obtained

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Chapter 6: General discussion from this study is much more reliable compared to other data in the literature, where no process control was used. However, (RT-) PCR quantification of viral genomes does not provide an estimate on the number of infectious viruses present, and thus further work will be needed for direct extrapolation of actual numbers of infectious virus, from PCR based data. This advance will further enhance understanding into real human health risks.

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Genetic diversity of norovirus and AdV in wastewater samples

Wastewater represents the effluence of an entire population, where human waste from millions of individuals is deposited into a collection system, i.e. a wastewater treatment plant. Thus, viruses identified in wastewater represent both viruses transmitted within the population,405 viral pathogens transmitted through contaminated food and water.219, 295, 406 Consequently, the genetic diversity of norovirus and AdV was determined in wastewater sites in Sydney and Melbourne, Australia using NGS technologies (Chapter 3-5).

For norovirus, a total of 19 of 22 genotypes were identified throughout a two-year study period. In early 2016, a high prevalence of GII.17 was observed in wastewater samples (Figure 3-6). Similar to the results in thesis, surveillance of norovirus in South African wastewater also showed the emergence of GII.17 in 2015-2016.407 This dominance of GII.17 was also observed in sewage, oysters and wastewater samples from Japan using pyrosequencing.295 However, GII.17 noroviruses had a much lower prevalence in clinical samples compared to wastewater samples, suggesting that GII.17 infections may be more asymptomatic. In addition, this increase in GII.17 prevalence in Australia and New Zealand also correlated with the increase of GII.17 viruses around the globe, suggesting that the use of clinical data does not provide a complete picture of norovirus strains that are circulating within the population of major cities. This thesis demonstrated the capability to detect and identify viruses in complex wastewater samples using amplicon-based Sanger and NGS sequencing. Furthermore, this thesis shows the reliability of using wastewater samples for molecular epidemiological surveillance.

Norovirus of the GII.4 and GII.2 capsid lineages are recognised as common genotypes worldwide.105, 290 However, we observed that the dominance of GII.4 viruses was eroded from mid-2016 followed by an increase in GII.2 viruses in Australian WWTP (Figure 3-6). This fluctuation of GII.4 and GII.2 viruses coincide with the trend found in Australian clinical samples and was consistent with other studies worldwide, where GII.P16/GII.2 viruses became prevalent.284, 288, 393, 394

A switch in norovirus genotype dominance was observed in wastewater samples collected in 2017, where GII.2 viruses dominated at the beginning of the year and were then replaced by GII.4 capsid containing viruses in March 2017 (Figure 4-7). This corresponded with our clinical data (Figure 4-3) and further exemplifies the reliability of viral surveillance through wastewater screening (Chapter 3 and 4).

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AdV are commonly found in aquatic environments around the world355, 362, 408, 409 and there is potential for real-time and continued surveillance of circulating AdV through molecular analysis of wastewater. Using NGS, the genetic diversity of AdV was also identified in wastewater collected from Sydney and Melbourne, Australia (Chapter 5). From this analysis a total of 19 serotypes were identified, representing six different species (Figure 5-3). This is consistent with a study that examined the diversity of AdV in wastewater collected in Luxembourg, which revealed eight serotypes of AdV (1, 2, 3, 6, 12, 31, 40 and 4), all of which were identified in this thesis.219 A more recent study by Iaconelli et al. also showed similar results, with a total of 19 AdV types detected.410

This thesis is the first identification of AdV serotypes in Australian wastewater, and the distribution and abundance of each serotype are in agreement with published literature.219, 344 The most commonly represented serotypes in this thesis are F-41 (83.5%), F40 (11.0%) and A- 31 (3.7%) (Figure 5-3). This was not surprising as the site of replication is in the intestinal tract, and thus they are frequently shed into the wastewater system.364, 411 This highlights that the combined use of both clinical and wastewater samples can enhance the identification of circulating AdV serotypes in a population.

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Conclusions and future directions

This study highlights the complexity of norovirus evolution and the vital role that both recombination and antigenic capsid variation play in the emergence of new noroviruses. Importantly we have shown that over the timeframe of this study, the GII.4 Sydney pandemic variant appears to have an increased capacity for evolutionary changes in response to population immunity, higher replication and mutation rates, as well as an ability to recombine with co-circulating strains.

To develop a successful vaccine, the continual surveillance of norovirus around the globe is required to identify circulating strains within a population. Most norovirus epidemiological analyses have been conducted using clinical samples collected from hospitals and thus only represent the circulating strains within symptomatic individuals. In this thesis, we have demonstrated that wastewater can be used for enteric virus surveillance within a population and thus is inclusive of both symptomatic and asymptomatic cases. Furthermore, we detected similar changes in norovirus strain dominance from both clinical and wastewater samples, illustrating that the latter could be used to enhance or replace clinical norovirus surveillance for an entire population.

This is the first Australian study to identify and quantify the diversity of norovirus and AdV in wastewater samples. The use of NGS in wastewater monitoring can enhance our current understanding of circulating viruses in the population and has implications for a more complete identification of both asymptomatic and symptomatic viruses. This work has important implications for human health in which the surveillance of enteric pathogens in wastewater system can be used to identify circulating epidemic and pandemic viruses, as well as emerging viruses. Data generated in this thesis can also be used to assess the risk of contamination in water matrices such as drinking water reservoirs, or recreational waters used by the wider population.

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Appendix

8 Appendix

8.1 Ethics approval forms

Human Research Ethics Advisory Panel (HREAP) Executive UNSW Australia UNSW Sydney NSW Australia 2052 E: [email protected]

21-Nov-2016

Dear Professor Peter White, Project Title The study of norovirus molecular epidemiology in Australia HC No HC16826 Re HC16826 Notification of Ethics Approval – Negligible Risk Project Approval Period 21-Nov-2016 - 20-Nov-2021

Thank you for submitting the above research project to the UNSW Human Research Ethics Advisory Panel (HREAP) Executive for ethical review. This project was considered by the HREAP Executive at its meeting on 22-Nov-2016.

I am pleased to advise you that the HREAP Executive has granted ethical approval of this project, subject to the following conditions being met:

Conditions of Approval Specific to Project: N/A

Conditions of Approval - All Projects:

The Chief Investigator will comply with the declarations agreed to in the Negligible Risk Research Application Form.

The Chief Investigator will immediately report anything that may warrant review of ethical approval of the project.

The Chief Investigator will report to the UNSW HREAP Executive annually in the specified format and notify the UNSW HREAP Executive when the project is completed.

A copy of this ethical approval letter must be submitted to all Investigators and sites prior to commencing the project.

The UNSW HREC/HREAP Terms of Reference, Standard Operating Procedures, membership and standard forms are available from https://research.unsw.edu.au/forms-faqs-procedures-guidelines

Should you require any further information, please contact the Human Ethics Office at: [email protected]

The UNSW HREAP Executive wishes you every continued success in your research.

Kind Regards

139

Appendix

25-Jul-2017

Dear Professor Peter White,

Project Title The study of norovirus molecular epidemiology in Australia HC No HC17459 Re HC17459 Notification of Ethics Approval Approval Period 25-Jul-2017 - 24-Jul-2022

Thank you for submitting the above research project to the HREAP Executive for ethical review. This project was considered by the HREAP Executive at its meeting on 18-Jul-2017.

I am pleased to advise you that the HREAP Executive has granted ethical approval of this research project. The following condition(s) must be met before data collection commences:

Conditions of Approval: N/A

Conditions of Approval - All Projects:

The Chief Investigator will immediately report anything that might warrant review of ethical approval of the project. The Chief Investigator will seek approval from the HREAP Executive for any modifications to the protocol or other project documents. The Chief Investigator will notify the HREAP Executive immediately of any protocol deviation or adverse events or safety events related to the project. The Chief Investigator will report to the HREAP Executive annually in the specified format and notify the HREAP Executive when the project is completed at all sites. The Chief Investigator will notify the HREAP Executive if the project is discontinued before the expected completion date, with reasons provided. The Chief Investigator will notify the HREAP Executive of his or her inability to continue as Coordinating Chief Investigator including the name of and contact information for a replacement.

The HREAP Executive Terms of Reference, Standard Operating Procedures, membership and standard forms are available from https://research.unsw.edu.au/research-ethics-and-compliance-support-recs.

If you would like any assistance, or further information, please contact the ethics office on: P: +61 2 9385 6222, + 61 2 9385 7257 or + 61 2 9385 7007 E: [email protected]

Kind Regards,

140