The Effective Contribution of Viral Respiratory Infection to Wheezing Illness

in Hospitalised Young Children

Chisha Teza Sikazwe

BSc (Biomedical Sciences and Molecular biology)

Master of Infectious Diseases

This thesis is presented for the degree of Doctor of Philosophy in Microbiology of

The University of Western Australia

School of Biomedical Sciences

2018

ii

iii

Thesis declaration

I, Chisha Teza Sikazwe, certify that:

This thesis has been substantially accomplished during enrolment in the degree.

This thesis does not contain material which has been accepted for the award of any

other degree or diploma in my name, in any university or other tertiary institution.

No part of this work will, in the future, be used in a submission in my name, for an y

other degree or diploma in any university or other tertiary institution without the

prior approval of The University of Western Australia and where applicable, any

partner institution responsible for the joint-award of this degree.

This thesis does not contain any material previously published or written by another

person, except where due reference has been made in the text.

The work(s) are not in any way a violation or infringement of any copyright,

trademark, patent, or other rights whatsoever of any person.

Technical assistance was kindly provided by Tom Chung for Cytokine multiplex bead

experiment that is described in Chapter seven of this thesis.

This thesis contains only sole-authored work, some of which has been published

and/or prepared for publication under sole authorship.

XChisha Teza Sikazwe

Date: 25.06.2018

iv

Abstract

Respiratory tract infections are a leading cause of morbidity and mortality worldwide. Our

emerging understanding of the importance of acute lower respiratory viral infe ction in

early childhood predisposing to chronic inflammatory respiratory disease, coupled with the

complex interplay between virus and host underscores the need for investigations to

understand the clinical manifestation and the interplay between the magnitude of

infection and the corresponding host response. Rhinoviruses, specifically RV -C have been

identified as an important contributor to wheezing illness in paediatric medicine. Though,

little is known about its contribution to infection. Thus, this the sis aims to improve

understanding of the underlying pathophysiological mechanisms in the context of RV -C

wheezing illness through the development of a reliable method of quantifying RV -C load

and characterisation of the host response following infection.

RV-C was the most common virus detected in preschool aged children hospitalised with an

acute asthma exacerbation (Chapter 6). This was also apparent in preschool aged non-

asthmatic children hospitalised with a wheezing illness (chapter 7). Interestingly, i n young

infants under the age of two years hospitalised (Chapter 5) with a wheezing illness, RSV

rather than RV-C was found to be the most common virus detected. Viral load studies

revealed that both RSV and RV-C replicate to significantly higher levels in hospitalised

patients than in non-respiratory disease controls. In asthmatics and non-asthmatic

patients, RV-C induced respiratory wheeze appears to be driven by a Th2 response that is

independent of viral load. The magnitude of the host immune response is more apparent

in children with asthma compared to those without asthma. In addition, RV-C infection in

pre-school aged children with wheeze appears to induce a selective increase in neutrophil

chemokines and a significant increase in neutrophil numbers with a simultaneous increase

in illness severity.

v

The findings in this thesis extend the existing knowledge on RV-C mediated wheezing

illness and demonstrate that magnitude of replication does not significantly contribute to

disease outcome. Conversely, it appears that the host immune response for which in part

is driven by a pro-inflammatory, neutrophilic inflammation may play a substantial role in

severity of disease. Host directed therapy targeting neutrophil pathways may prove to be

beneficial in young children infected with RV-C.

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Table of contents

Thesis declaration ......................................................................................................... iii

Abstract........................................................................................................................ iv

List of Figures................................................................................................................. x

List of Tables ................................................................................................................ xii

Acknowledgments....................................................................................................... xiii

AUTHORSHIP DECLARATION: SOLE AUTHOR PUBLICATIONS .................................... xv

Peer reviewed papers and Conference presentations .................................................... xvi

List of Abbreviations................................................................................................... xvii

1 Literature review .................................................................................................... 2

1.1 Introduction ............................................................................................ 3

1.1.1 Respiratory syncytial virus ........................................................................ 6

1.1.2 Rhinoviruses ............................................................................................ 6

1.1.3 Human Metapneumovirus ........................................................................ 8

1.1.4 Influenza virus ......................................................................................... 8

1.1.5 Parainfluenza virus ................................................................................... 9

1.1.6 Adenovirus ............................................................................................ 10

1.1.7 Human Coronaviruses ............................................................................ 10

1.2 Laboratory Diagnosis of Respiratory Infections ................................................... 11

1.2.1 Upper and Lower airway samples............................................................ 12

1.2.2 Virus isolation by cell culture .................................................................. 13

1.2.3 Direct detection of respiratory viruses by immunofluorescence ................ 14

1.2.4 Nucleic Acid Tests .................................................................................. 15

1.3 Viral kinetics of acute respiratory tract infections................................................ 19

1.4 Viral respiratory infection and asthma................................................................ 20

1.5 Innate immune response to viral respiratory infection ........................................ 23

vii

1.6 Aims of Project ................................................................................................. 26

2 Materials and Methods ......................................................................................... 27

2.1 Sample collection .............................................................................................. 27

2.2 Nucleic acid extraction and viral detection.......................................................... 28

2.3 Design of primers and probes ............................................................................ 29

2.4 Production and quantification of transcribed RNA standards ............................... 31

2.5 Quantitative Real time PCR (Viral load)............................................................... 32

2.6 Digital Droplet PCR ............................................................................................ 33

2.7 PCR reagents .................................................................................................... 34

2.8 Gel Electrophoresis ........................................................................................... 34

2.9 Thermocyclers .................................................................................................. 34

2.10 Computational analysis ..................................................................................... 35

2.11 Multiplex immunoassay..................................................................................... 35

2.12 Quality Control ................................................................................................. 36

2.13 Statistical Analysis ............................................................................................. 36

2.14 Ethics Approval ................................................................................................. 36

3 The design and development of quantitative detection assays for the common

causative viral pathogens of acute lower respiratory tract infection ................................ 38

3.1 Introduction ..................................................................................................... 39

3.2 Samples............................................................................................................ 41

3.3 Results ............................................................................................................. 41

3.4 Discussion......................................................................................................... 55

4 The development of a reliable PCR assay to measure RV-C load in clinical samples ... 61

4.1 Introduction ..................................................................................................... 62

4.2 Samples............................................................................................................ 64

4.3 Results ............................................................................................................. 66

4.4 Discussion......................................................................................................... 75

5. The Quantitative Detection of Respiratory Syncytial Virus in Hospitalized Young South

African Children ........................................................................................................... 78

5.1 Introduction ..................................................................................................... 79

5.2 Samples............................................................................................................ 81

5.3 Results ............................................................................................................. 82

5.3.1 Baseline characteristics .......................................................................... 82

5.3.2 RSV infection and clinical outcome .......................................................... 84

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5.3.3 RSV disease and HIV infection ................................................................. 87

5.3.4 RSV load .................................................................................................... 88

5.4 Discussion......................................................................................................... 91

6 Determinants of acute asthma exacerbation severity following RV-C infection ......... 95

6.1 Introduction ..................................................................................................... 96

6.2 Samples............................................................................................................ 97

6.3 Results ............................................................................................................. 99

6.3.1 Study participants characteristics ............................................................ 99

6.3.2 Virus Detection ...................................................................................... 99

6.3.3 RV-C load..............................................................................................101

6.3.4 Surrogate markers of inflammation........................................................104

6.3.5 Performance of RV-C load, neutrophils and eosinophils in predicting the

severity AAE ........................................................................................................108

6.4 Discussion........................................................................................................109

7. Cytokine profiles in nasal secretions of patients hospitalised with Rhinovirus Species C

associated respiratory wheeze .....................................................................................115

7.1 Introduction ....................................................................................................116

7.2 Samples...........................................................................................................117

7.3 Results ............................................................................................................119

7.3.1 Virus Detections....................................................................................119

7.3.2 Nasal cytokine profiles of wheezing patients following RV-C infection ......124

7.3.3 Relationships between cytokines, RV-C load and clinical outcomes ..........132

7.4 Discussion........................................................................................................135

8. General Discussion and Conclusions......................................................................142

8.1 Introduction .........................................................................................143

8.2 Epidemiology of respiratory viruses in young children under the age of five

years 145

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8.3 Reliable methods of accurately determining viral load in RV-C infected

patients 148

8.4 Viral Determinants of severity of RV-C induced wheezing illness ..............150

8.6 Conclusion .......................................................................................................154

Bibliography ...............................................................................................................156

Appendices .................................................................................................................176

Appendix 1 ..........................................................................................................176

Appendix 2 .................................................................................................................181

Published work completed during PhD .........................................................................181

x

List of Figures

Figure 4.3-1 A BioEdit sequence alignment of primer and probe regions that were targeted

by assays one to four. Sequences of forward primer region (left box), probe region (center

box) and reverse primer region (right box). Identical bases at the same position are

represented by dots whereas capitalized bases indicate mismatches between sequences.

................................................................................................................................... 66

Figure 4.3-2 the algorithm for the determination of RV-C viral load in clinical samples ..... 72

Figure 4.3-3: Box plots of RV-C load in samples from young children presenting to the

Emergency Department with acute wheeze. .................................................................. 74

Figure 5.3-1: Viruses detected in NPAs collected from ALRI cases and NRD controls. RV

(RV-A, RV-B, RV-C), HCoV (OC43, 229E, HKU-1, NL63), HPIV (PIV I-IV), IFV (A/H1N1, A/H3N2,

B and C) ....................................................................................................................... 84

Figure 5.3-2: The distribution of RSV positive and RSV-negative ALRI cases by age. RSV

disease was more prevalent in children within their first year of life. Peak hospitalization

rate was observed in the 0-2 month age group. ............................................................ 86

Figure 5.3-3: Distribution of respiratory viruses detected in HIV infected ALRI patients .... 87

Figure 5.3-4: A box plot comparing RSV load between ALRI cases and NRD controls......... 88

Figure 5.3-5 A box plot comparing RSV load by subtype and clinical diagnosis.................. 89

Figure 5.3-6: A box plot comparing RSV loads in ALRI cases with a viral co-infection [n=12;

RSV with either hAdV (75%, n=9), hCoV (17%, n=2) or RV (8%, n=1)] versus sole RSV

infection (n=15). .......................................................................................................... 90

Figure 6.3-1 A bar graph comparing the frequency (%) of viruses detected in cases and

controls. Rhinovirus-C (RV-C), Rhinovirus-A (RV-A), parainfluenza virus (PIV), respiratory

syncytial virus (RSV), human adenovirus (hAdV), Influenza viruses (IFV), human corona

virus (hCoV) Rhinovirus-B (RV-B) and human metapneumovirus (hMPV) ........................100

Fig 6.3-2: Box plot summarising RV-C load in children hospitalised with an acute asthma

exacerbation (cases) and otherwise healthy individuals with a non-respiratory disease

(controls). Median RV-C load of AAE cases was 2.6 log10 copies/mL higher than that of the

non-respiratory disease control group . ........................................................................102

Figure 6.3-3: A boxplot of RV-C loads for cases(n=21) stratified by disease severity and

controls (n=2). Groups were compared using the Mann-Whitney U test,. median viral load

between the two severity groups did not differ significantly. .........................................103

Figure 6.3-4 Surrogate markers of asthma exacerbation in acute samples from patients

infected with RV-C stratified by illness severity. A) Absolute neutrophil peripheral blood

counts B) absolute eosinophils peripheral blood counts C) Total serum IgE levels counts.

Mann- Whitney U or Kruksall-Wallis test were used for testing on the apporpriate group of

subjects. All data are expressed as box and whisker plots. *:p=0.05 (severe vs non-severe)

** p

xi

Figure 7.3-2: RV detection rates stratified by species. RV-C was the predominant species

detected in children hospitalised with respiratory wheeze ............................................120

Figure 7.3-3- A comparison of virus detection rates between patients with classified with

asthma compared to those not classified with asthma. .................................................121

Figure 7.3-4: Area under the curve analysis of RV-C load to predict hospitalisation. RV-C

load was poor predictor of hospitalisation with an AUC of 0.5 (95%CI, 0.24-0.74) ...........122

Figure 7.3-5 Levels of IL-4 (a) and IL-13 (b) in nasal secretions of non-respiratory disease

controls, RV-C infected patients with asthma and without asthma. IL-4 and IL-13 were both

significantly elevated in the asthmatic group but IL-13 levels did not differ significantly in

the non asthmatic group compared to controls.* p

xii

List of Tables Table 1-1: Seasonal and clinical profiles of the commonly detected viruses associated with

acute respiratory tract infection....................................................................................... i

Table 4.3-1 A comparison of RNA transcript concentration and Cq values for the different

RV-C assays.................................................................................................................. 68

Table 4.3-2 the performance of the individual PCR assays for the detection of matched RV -

C RNA transcript........................................................................................................... 69

Table 4.3-3 Intra and Inter assay variability of the four RV-C qRT-PCR assays (Assay 1-4) .. 70

Table 4.3-4 Variation in calculated copy number yield (%) of transcripts 1-4 compared to

the number of probe mismatches ................................................................................. 71

Table 5.3-1 Demographic and clinical details of study participants .................................. 83

Table 6.3-1 Baseline characteristics of children with acute asthma exacerbation (AAE) and

controls ....................................................................................................................... 99

Table 6.3-2: A statistical summary of the risk of being diagnosed with acute asthma

exacerbation follwoing respiratory virus detection........................................................101

Table 7.3-1 Summary of clinical and demographic data of hospitalised children with RV -C

respiratory wheeze .....................................................................................................123

Table 7.3-2 nasal cytokine levels of healthy non-respiratory disease controls, RV-C

infected patients with asthma and without asthma. ....................................................130

Table 7.3-3: An illustration of the relationship between RV-C load and inflammatory

mediator production in the nasal secretions of children with asthma .............................133

Table 7.3-4: An illustration of the relationship between RV-C load and inflammatory

mediator production in the nasal secretions of children without asthma ........................133

Table 7.3-5: Association between cytokine production and hospitalisation of children

hospitalised following RV-C infection............................................................................134

Table 0-1 The performance of the individual PCR assays for the detection of matched RV -C

RNA transcript ............................................................................................................176

Table 0-2 A comparison of RNA transcript concentration and Cq values for the different RV-

C assays ......................................................................................................................177

Table 0-3 Intra and Inter assay variability of the four RV-C qRT-PCR assays (Assay 1-4) ....178

Table 0-4 The RV-C load determinations for patients enrolled in the PREVIEW study. Clinical

samples were tested in triplicate and mean viral load calculated. ..................................179

xiii

Acknowledgments

First and foremost, I want to thank Prof. David Smith, A/Prof. Allison Imrie, Dr. Glenys

Chidlow and Dr. Gerald Harnett. It has been an honour to be your Ph.D. student. You all

have taught me, both consciously and unconsciously, how good research is conducted. I

appreciate all your contributions of time, ideas, and funding to make my Ph.D. experience

productive and stimulating. The joy and enthusiasm you all had for this research was

contagious and motivational for me, even during tough times. I am also thankful for the

excellent example you have provided as successful leaders in your respective fields. Special

thanks to Robyn Thompson for her countless efforts to ensure I had access to everything

(conferences, meetings and training courses) and everyone I needed to accomplish my

objectives.

I would like to thank all the members of the PathWest Molecular Diagnostics Laboratory

for accommodating me into your busy laboratory. You have been a source of friendships as

well as good advice. Many thanks to our collaborators at the Telethon Kids Institute,

especially Professor Peter Le Souef, Dr. Ingrid Laing and Dr Kim Khoo. I would also like to

thank Dr. Abha Chopra at the Institute of Immunology and Infectious diseases for providing

access to their digital PCR instrument.

Last but not the least, I want to thank my partner Emma, my family and my closest friend’s

you guys have been amazing during this time. Mum you have been my biggest supporter

from the get go. Dad thank you for your wise words, my brothers Kapembwa and

Kamando, you are the best brothers and friends one could ever ask for. Jarrad, thank you

for your friendship during this phase it was one where we learnt a lot from each other and

I will forever cherish the times spent at coffee. My dearest Emma, thank you for being so

patient and supportive during this time.

xiv

I gratefully acknowledge the funding sources that made my Ph.D. work possible. I was

funded by University of Western Australia Postgraduate award and University of Western

Australia Top-up Scholarship. Material, consumables and software were made available by

PathWest Laboratory Medicine WA. This research was supported by an Australian

Government Research Training Program (RTP) Scholarship.

xv

AUTHORSHIP DECLARATION: SOLE AUTHOR PUBLICATIONS

This thesis contains the following sole-authored work that has been published and/or prepared for publication.

Deta ils of the work: Comparison of Droplet Digital RT-PCR to qPCR for the quantitative detection of Respiratory

Syncytia l Virus Chisha T. Sikazwe, Angela Fonceca, Avram Levy, Glenys R. Chidlow, Al lison Imrie, Mark Everard,

David W. Smith. RSV16: 10th International Respiratory syncytial vi rus symposium, Sept 2016, Patagonia,

Argentina. Location in thesis: Chapter Three

Deta ils of the work: Reliable quantification of rhinovirus species C using real-time PCR. Sikazwe CT, Chidlow GR,

Imrie A, Smith DW. J Vi rol Methods. 2016 May 20;235:65-72. doi :10.1016/j.jvi romet.2016.05.014. [Epub ahead

of print] PMID: 27216896. Location in thesis: Chapter Four

Deta ils of the work: The Quantitative Detection of Respiratory Syncytial Virus in Hospitalized Young South

African Children Chisha T. Sikazwe, Al icia A. Annamalay, Glenys R. Chidlow, Salome Abbott, Siew -Kim Khoo,

Joelene Bizzintino, Robin Green, Allison Imrie, Peter LeSouëf, David W. Smith. Submitted to Influenza and other

Respiratory vi ruses. Location in thesis: Chapter Five

Deta ils of the work: Sikazwe CT, Chidlow GR, Imrie A, Smith DW. Determinants of acute asthma exacerbation

severity following RV-C infection. Location in thesis: Chapter Six

Deta ils of the work: Sikazwe CT, Chidlow GR, Imrie A, Smith DW. Cytokine profiles in nasal secretions of

patients hospitalised with Rhinovirus Species C associated respiratory wheeze, Cytokine. (In preparation).

Location in thesis: Chapter Seven

XChisha Teza Sikazwe

Date:

XAllison Imrie

Co-ordinating Supervisor

Date:

25/06/2018

25/06/2018

xvi

Peer reviewed papers and Conference presentations

1 Rachael Lappan; Kara Imbrogno; Chisha Sikazwe; Denise Anderson; Danny Mok;

Harvey Coates; Shyan Vijayasekaran; Paul Bumbak; Christopher Blyth; Sarra Jamieson;

Christopher Peacock A microbiome case-control study on recurrent acute otitis media

identified potentially protective bacterial genera. Microbiome, (In submission)

2 Bjerregaard, A., Laing, I.A., Backer, V., Fally, M., Khoo, S.-K., Chidlow, G., Sikazwe, C.,

Smith, D.W., Le Souëf, P. and Porsbjerg, C. (2016) Clinical characteristics of eosinophilic

asthma exacerbations. Respirology, 22: 295–300. doi: 10.1111/resp.12905.

3 Bjerregaard, A., Laing, I.A., Backer, V., Fally, M., Khoo, S.-K., Chidlow, G., Sikazwe, C.,

Smith, D.W., Le Souëf, P. and Porsbjerg, C. (2017)-High fractional exhaled nitric oxide

and sputum eosinophils are associated with an increased risk of future virus-induced

exacerbations – a prospective cohort study. Clinical and Experimental Allergy

4 The Quantitative Detection of Respiratory Syncytial Virus in Hospitalized Young South

African Children Chisha T. Sikazwe, Alicia A. Annamalay, Glenys R. Chidlow, Salome

Abbott, Siew-Kim Khoo, Joelene Bizzintino, Robin Green, Allison Imrie, Peter LeSouëf,

David W. Smith. Submitted to Influenza and other Respiratory viruses (in submission)

5 Reliable quantification of rhinovirus species C using real -time PCR. Sikazwe CT,

Chidlow GR, Imrie A, Smith DW. J Virol Methods. 2016 May 20;235:65-72.

doi:10.1016/j.jviromet.2016.05.014. [Epub ahead of print] PMID: 27216896

6 Respiratory viruses in young South African children with acute lower respiratory

infections and interactions with HIV. Annamalay AA, Abbott S, Sikazwe CT, Khoo SK,

Bizzintino J, Zhang G, Laing I, Chidlow GR, Smith DW, Gern J, Goldblatt J, Lehmann D,

Green RJ, Le Souëf PN. J Clin Virol. 2016 Aug;81:58-63. doi: 10.1016/j.jcv.2016.06.002.

Epub 2016 Jun 4. PMID: 27317881

7 Comparison of Droplet Digital RT-PCR to qPCR for the quantitative detection of

Respiratory Syncytial Virus Chisha T. Sikazwe, Angela Fonceca, Avram Levy, Glenys R.

Chidlow, Allison Imrie, Mark Everard, David W. Smith. RSV16: 10th International

Respiratory syncytial virus symposium, Sept 2016, Patagonia, Argentina.

8 Reliable Quantification of Rhinovirus Species C using a Taqman Real -time PCR Based

Approach Chisha T Sikazwe · Glenys R. Chidlow · Allison Imrie · David W. Smith. 1st

International Meeting for Respiratory Pathogens, Sep 2015 Singapore.

9 The Relationship between RSV Load and Clinical Disease in South African Children

Chisha T Sikazwe, Glenys R. Chidlow, Allison Imrie, David W Smith. 9th International

Symposium on Respiratory syncytial virus Nov 2014, Cape Town, South Africa

xvii

List of Abbreviations

Abbreviation Definition

µ Micro

µL Microlitre

µM Micromolar

AAE Acute Asthma Exacerbation

ALF Australian Lung Foundation

ARTI Acute Respiratory Tract Infection

BAL Bronchoalveolar Lavage

BHQ Black Hole Quencher

BLAST Basic Local Alignment Search Tool

bp Base Pair

cDNA Complementary DNA

CFT Complement Fixation Test

CMV Cytomegalovirus

COPD Chronic Obstructive Pulmonary Disease

CPE Cytopathic Effect

Cq Cycle Quantification Value

Ct Cycle Threshold

xviii

CXCL- Chemokine Ligand

ddPCR Digital Droplet PCR

DNA Deoxyribonucleic Acid

EIA Enzyme Immunoassay

GINA Global Initiative For Asthma

HAdV Human Adenovirus

HBoV Human Bocavirus

HCoV Human Coronavirus

HMPV Human Metapneumovirus

HPIV Human Parainfluenza virus

GAPDH Glyceraldehyde 3-phosphate dehydrogenase

IF Immunofluorescence

IFAV Influenza A Virus

IFBV Influenza B Virus

IFN- Interferon

IL- Interleukin

LNA Locked Nucleic Acid

LRTI Lower Respiratory Tract Infection

MERS-CoV Middle Eastern Respiratory Syndrome Coronavirus

xix

MGB Minor Groove Binding

mL Milliliter

NA Nasal Aspirate

NAT Nucleic Acid Test

NPA Nasopharyngeal Aspirate

NPS Nasopharyngeal swab

NT Neutralisation Test

NW Nasal Wash

PCR Polymerase Chain Reaction

PMH Princess Margaret Hospital

PWLM PathWest Laboratory Medicine WA

qPCR Quantitative Real Time PCR

RNA Ribonucleic Acid

RSV Respiratory Syncytial Virus

RT-ddPCR Reverse Transcription Digital Droplet PCR

RT-PCR Reverse Transcription PCR

RT-qPCR Reverse Transcription Quantitative Real Time PCR

RV Rhinovirus

SARS-CoV Severe Acute Respiratory Syndrome Coronavirus

xx

Th T Helper Cells

TKI Telethon Kids Institute

TLR Toll Like Receptors

TNF- Tumor Necrosis Factor

URTI Upper Respiratory Tract Infection

UTR Untranslated Region

UWA The University Of Western Australia

VL Viral Load

WHO World Health Organisation

α Alpha

β Beta

2

1 Literature review

1.1 Introduction

Acute respiratory tract infections (ARTIs) contribute substantially to the global burden of

illness from communicable pathogens. ARTIs are a leading cause of morbidity and mortality

accounting for approximately four million deaths per year globally (Bryce et al., 2005).

Children under the age of five years, adults over the age of sixty-five, individuals with an

underlying chronic condition and immunocompromised individuals are population groups

in whom poor outcomes occur following infection (Falsey et al., 2003; Graham and Gibb,

2002; Nair et al., 2011a; Nair et al., 2010; Nair et al., 2013). Estimates of the global burden

of acute respiratory illness indicate that there are vast differences between developed and

developing countries. According to recent reports, ARTIs are the leading cause of childhood

death in developing countries (Nair et al., 2011b). Pneumonia alone accounts for 1.4

million childhood deaths per year in these regions. Conversely, in developed nations

deaths due to ARTIs represent a negligible percentage of total deaths, accounting for less

than two percent of deaths but are predominantly responsible for absenteeism and

enormous financial costs to the healthcare system (Denny Jr., 2001). Reports from the US

estimate that direct financial costs of ARTIs to the healthcare system approach $40 billion

annually. Similarly, in Europe the expenditure on patients with ARTI is over €15 billion. The

direct and indirect cost of ARTIs to the Australian health care system is estimated to be up

to AUD 600 million each year (The Australian Lung Foundation, 2007).

All groups of microbes are capable of establishing an infection in the respiratory tract.

However, viruses predominate as aetiologic agents of ARTIs and can contribute to

respiratory disease either directly through frank infection or indirectly by exacerbating

pre-existing illness (Bafadhel et al., 2011; Bandi et al., 2003; Busse, Lemanske, and Gern,

2010; Hosseini et al., 2015) and increasing the risk of secondary bacterial infection

(Bellinghausen et al., 2016; Ewijk et al., 2007). Influenza virus (IFV), respiratory syncytial

4

virus (RSV), rhinovirus (RV), human metapneumovirus (hMPV), human parainfluenza virus

(hPIV) and human adenovirus (hAdV) are the most prevalent viruses in hospitalised

patients and are all linked to ALRI (Lukšić et al., 2013). The distribution of these viruses is

influenced by season, geographic region and age group (Lukšić et al., 2013). They are at

least 6 families and more than 150 viruses that are associated with ARTI. The clinical and

seasonal profiles of the most common types are listed in Table 1.

Table 1-1: Seasonal and clinical profiles of the commonly detected viruses associated with acute respiratory tract infection

Virus

Incubation period (days)

Seasonality Clinical manifestations Laboratory diagnostic method

Respiratory syncytial virus (RSV) 2-8 Winter bronchiolitis, pneumonia Virus isolation in cell culture, RT-PCR, IF, EIA,

Human metapneumovirus (HMPV) 2-8 Winter to spring bronchiolitis, pneumonia RT-PCR, IF

Rhinovirus (RV) 2 All year round coryza, COPD and asthma exacerbation, bronchiolitis, pneumonia

RT-PCR, NT and Virus isolation in cell culture (for some types)

Coronavirus (HCoV) 2 All year round coryza, pneumonia (rarely in non-SARS or MERS infection)

RT-PCR,ELISA,HA,IF

Influenza virus (IFV) 2-8 Winter Virus isolation in cell culture, RT-PCR, CFT, HI,IF, EIA,NT

Human parainfluenza viruses (HPIV) 2-8 Autumn to winter coryza, croup, bronchitis, bronchiolitis, and pneumonia

Virus isolation in cell culture, RT-PCR, CFT, HI,IF, EIA,NT

Adenovirus (AdV) 5-7 All year round pneumonia, bronchitis, pharyngitis, tonsillitis, and pharyngoconjunctival

fever

RT-PCR, HI, IF,EIA and NT

Human bocavirus (HBoV) 5-7 All year round Coryza, bronchiolitis, pneumonia

RT-PCR

Abbreviations: RT-PCR; reverse transcription PCR, IF; immunofluorescence, EIA; enzyme immunoassay, HA; haemagglutination, NT; neutralisation test, HI; haemagglutination inhibition, CFT; complement fixation

test.

1.1.1 Respiratory syncytial virus

RSV is a member of the paramyxoviridae family and has a single strand negative sense

enveloped RNA genome. RSV genome encodes two non-structural proteins and nine

structural proteins. The attachment (G) and fusion (F) glycoproteins are the

immunodominant antigens of RSV and are essential in infectivity and antigenicity (Fodha et

al., 2007). RSV is considered to be serologically monotypic, but consists of two genetic

subgroups, RSV-A and RSV-B (Papadopoulos et al., 2004). RSV A is more prevalent than RSV

B but there is no consensus on which of the subtypes is more pathogenic.

RSV accounts for 40-50% of all viral infections requiring hospitalisation in young infants

(Nair et al., 2011b). Virtually all children are exposed to RSV before the age of 3 years

(Henderson et al., 2005). Acute bronchiolitis is the typical syndrome associated with RSV

infection in young infants and is characterised by a predominantly neutrophilic pattern of

inflammation and mucus in the airways, which often results in some degree of pulmonary

obstruction. Young infants are predisposed to severe acute bronchiolitis because of the

small diameter of their airways. Congenital heart disease, prematurity, bronchopulmonary

dysplasia or cystic fibrosis are all risk factors for severe infection and possibly death

(PREVENT, 1997).

1.1.2 Rhinoviruses

Rhinoviruses (RVs) are non-enveloped positive sense single stranded RNA viruses

belonging to the family Picornaviridae. They are genetically and antigenically diverse

consisting of three species (A, B and C). Historically, extensive cross neutralisation test

were utilised for the classification of RV-A and B isolates into 100 serotypes but these

isolates (types) are now assigned solely on genomic sequence (McIntyre, Knowles, and

7

Simmonds, 2013). In 2006, utilisation of molecular techniques led to the discovery of RV-C,

which had been entirely unrecognised using traditional rhinovirus detection techniques

(Arden et al., 2006). Cell lines that were conventionally used to isolate rhinovirus are not

permissive to RV-C infection and as a result preclude serotype assignment. Sequence

typing has revealed that RV-C is genetically more diverse than the other two species and

currently consists of 65 distinct genotypes (McIntyre et al., 2013).

Historically, RV-A and RV-B serotypes were stratified into two groups (major and minor) on

the basis of cellular receptor utilisation (intracellular adhesion molecule [major] or low-

density lipoprotein receptor [minor]) whereas the RV-C receptor remained unidentified

until recently. A recent report has shown that the human cadherin-related family member

3 (CDHR3), a member of the cadherin family of transmembrane proteins, facilitates RV -C

attachment and replication (Bochkov et al., 2015). This receptor is highly expressed in the

lower respiratory tract but its biological function remains unknown. A single nucleotide

polymorphism in CDHR3 gene is associated with RV-C wheezing illness in infancy and has

been shown to be risk factor for asthma inception (Bonnelykke et al., 2014).

The spectrum of disease exhibited by RVs range from asymptomatic infections, mild upper

respiratory infections (common cold) to severe or fatal lower respiratory tract infections

(pneumonia and bronchiolitis). RV infection is also associated with the exacerbation of

chronic respiratory conditions such as asthma, cystic fibrosis and other chronic obstructive

pulmonary disorders (Blomqvist et al., 2002; Çalışkan et al., 2013; Camargo et al., 2012;

Choi et al., 2015). In addition, RV induced wheeze in early childhood is associated with an

increased risk of developing asthma later on in life (Jackson et al., 2008a). Recent studies

have also revealed that RV-C species are more closely associated with asthma exacerbation

and illness requiring hospitalization than the other RV species, suggesting that RV-C may be

more pathogenic than RV-A and RV-B (Bizzintino et al., 2011a; Cox et al., 2013). Host and

8

viral factors associated with RV-C pathogenesis and illness severity are yet to be

completely elucidated.

1.1.3 Human Metapneumovirus

HMPV is classified as a negative sense single stranded RNA virus belonging to the

Paramyxoviridae family. Sequence analysis of the fusion (F) and attachment (G) genes has

identified two genotypes namely A and B. Both genotypes may co-circulate but only one

genotype is dominant during an epidemic (Tsukagoshi et al., 2013a; van den Hoogen et al.,

2002).

HMPV is associated with hospitalisation in young children, the elderly and individuals w ith

an underlying chronic condition. It is distributed worldwide and mimics the seasonal

distribution of influenza and RSV in that infection rates tend to peak in winter and early

spring (Kahn, 2003). Much like other respiratory viruses the spectrum of clinical disease

ranges from a mild upper respiratory tract infection to severe pneumonia. Observational

studies report that elderly people infected with hMPV display more severe clinical

symptoms compared to younger patients and those elderly infected with RSV or Influenza

virus (Falsey et al., 2003; Widmer et al., 2012).

1.1.4 Influenza virus

The influenza viruses are a major causative agent of ARTI in both children and adults,

Infection can cause mild to severe illness, and can occasionally lead to death (Pretorius et

al., 2016). Influenza accounts for a substantial burden of ARTI and current estimates

suggest that it is responsible for approximately five million severe cases and between

291,000-646,000 deaths per annum (Iuliano et al., 2018). Three Influenza types (type A,

type B and type C) are known to infect humans. Only the influenza A/H1N1, A/H3N2 and

influenza B viruses are considered as being significant contributors to seasonal influenza.

9

Influenza C virus infection is seasonal but has limited genetic diversity and is not thought to

cause epidemics (Nicholson, Wood, and Zambon, 2003).

Genomes of influenza A and B viruses are composed of eight single-stranded negative

sense RNA segments whereas the influenza C virus is composed of seven segments of

single stranded negative sense (Nicholson et al., 2003).

The genomes of influenza viruses specifically the Influenza A virus (IFAV) regularly undergo

changes under immune pressure. The genes encoding surface glycoproteins

haemagglutinin and neuraminidase may undergo subtle genetic changes (antigenic drift) or

abrupt major changes (antigenic shift).

Influenza therapeutics comes in the form of vaccines and anti -viral compounds. Vaccines

are recommended for annual boosting especially in high risk groups (Fiore, Bridges, and

Cox, 2009; Matsushita et al., 2017). Most Influenza antiviral compounds inhibit viral

replication and release, and can be utilised for treatment and prophylaxis (Dobson et al.,

2015; Jefferson et al., 2014b).However, adverse events reported from use of these

compounds suggested that they should be administered judiciously(Jefferson et al.,

2014a).

1.1.5 Parainfluenza virus

Human parainfluenza viruses (HPIV), of which they are four types (HPIV1-4) are negative

sense RNA viruses of the Paramyxoviridae family. HPIVs typically cause mild, self-limited

upper respiratory tract infections in adults, but can result in severe, life -threatening LRTIs

in immunocompromised patients (Guzmán-Suarez et al., 2012). HPIVs 1-3 are a common

cause of croup syndrome and are among the most commonly detected viruses in

hospitalised young infants after RSV. HPIV-4 is known to cause mild upper respiratory tract

10

infections (Tsukagoshi et al., 2013b). However, due to a lack of epidemiological data on

HPIV-4 the extent of its pathogenicity is largely unknown.

1.1.6 Adenovirus

Human Adenoviruses (HAdV) are a major cause of viral disease in both children and adults

(Lynch, Fishbein, and Echavarria, 2011). HAdV have linear double-stranded DNA genomes

and are classified into seven species (HAdV A to G) and a total of 55 types based on a

combination of serological characteristics and phylogenetic analysis (Robinson et al., 2011).

Certain species are known to cause respiratory illnesses including, acute febrile pharyngitis

(HAdV-B and -C; types 1,3,5,7), pharyngoconjunctival fever (HAdV-B; types 3,7,14), acute

respiratory tract infections (HAdV-B and -E; types 3,4,7,14,21), pneumonia (HAdV-B, -C,

and -E; serotypes 1-4 and 7), pertussis-like syndrome (HAdV-C; type 5) (Demian et al.,

2014). PCR is the method of choice in detecting adenoviruses.

1.1.7 Human Coronaviruses

Human coronaviruses (HCoVs) are enveloped viruses with a single-strand positive sense

RNA genome. Coronaviruses possess the largest known genomes among any of the RNA

viruses (Lau et al., 2013). Six species of HCoVs are known to infect humans; they are

classified into four genera based on proteomic analysis (Lau et al., 2013). HCoV-229E and

HCoV-NL63 belong to the Alphacoronavirus genus, HCoV-OC43 and HCoV-HKU1 belong to

lineage A Betacoronavirus, while severe acute respiratory syndrome associated

coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV)

belong to lineages B and C Betacoronavirus, respectively (Annan et al., 2013). HCoV-OC43,

HCoV-229E, hCoV-HKU1 and hCoV-NL63 are commonly associated with self-limiting mild

upper respiratory tract infections but on some occasions may be causative agents of

severe LRTIs especially in young infants, the elderly, and individuals with compromised

11

immunity (Lu et al., 2012). HCoVs are detected frequently with other respiratory viruses;

the significance of this phenomenon in relation to illness severity is unclear.

In the last decade SARS-CoV and MERS-CoV have been responsible for epidemics around

the world (Cheng et al., 2007). SARS-CoV was identified as the causative agent of the SARS

global epidemic from 2002 to 2003. MERS-CoV was initially reported in Saudi Arabia in

2012 (Zaki et al., 2012). Since then it has caused illness in people in countries with links to

the Arabian Peninsula (de Groot et al., 2013). Both MERS-CoV and SARS-CoV are emerging

zoonotic pathogens that crossed the species barrier with case fatality rates of 35% and

10% respectively (To et al., 2013). Bats appear to be the natural reservoir of both MERS-

CoV and SARS-CoV, transmission to humans occurs via dromedary camels and civets (live

market animals) respectively (Dijkman et al., 2013; Hu et al., 2015; Pfefferle et al., 2009;

Yusof et al., 2015). Nucleic acid tests are the method of choice for the laboratory diagnosis

of HCoVs (Gaunt et al., 2010) and MERS-CoV(Feikin et al., 2015).

1.2 Laboratory Diagnosis of Respiratory Infections

Laboratory diagnostic methods are the cornerstone in accurately attributing pathogen to

clinical presentation. Early detection of the aetiologic agent is pertinent for providing

optimal clinical management, which may include patient isolation, determining

appropriate therapy and/or cessation of inappropriate therapeutic interventions. In

addition, diagnostics are also essential for outbreak detection and response, and public

health surveillance. Characteristics of the ideal diagnostic test include being accurate

(between tests and laboratories), high throughput, cost-effective, suitable for a wide

spectrum of clinical samples, excellent sensitivity and specificity. Current diagnostic tests

fulfil some, but not all of these ideal characteristics.

12

They are several methods that are available for the identification of the aetiologic agent

from patients with an ARTI. The traditional laboratory diagnostic methods such as virus

isolation in cell culture and serology tests perform well but have some inherent limitations

in aspects of sensitivity and/or specificity. Molecular based diagnostic techniques such as

PCR have led to clinicians and scientists re-evaluating the role of certain viruses in disease

outcome. PCR based tests are a relatively new tool in the laboratory diagnostics. These

tests allow for rapid screening of clinical samples for multiple aetiologies with the added

benefit of excellent sensitivity and specificity. Further, these diagnostic approaches

facilitate further understanding of the viral kinetics in respiratory infections as well as the

ability to identify respiratory viruses that have been entirely missed by traditional

diagnostic approaches.

1.2.1 Upper and Lower airway samples

A variety of specimens have been used for directly sampling the respiratory tract including

nasal swabs (NS), nasopharyngeal swabs (NPS), nasal washings (NW), nasal aspirates (NA),

nasopharyngeal aspirates (NPA), sputum, bronchoalveolar lavage (BAL) or biopsies. The

technique utilised to collect a sample is based on clinical presentation and the method to

be utilised to identify the pathogen.

NWs are conventionally used on children and are not well tolerated in adults. NW can be

unpleasant to the patient, in addition, NW can be technically demanding, as the technique

requires the use of a solution such as saline. A NS is commonly taken from the mid-inferior

portion of the inferior turbinates for optimal virus recovery. Though this collection

technique maximises virus recovery, it causes some discomfort to the patient.

Nonetheless, both sampling techniques are suitable for detection of virus by cell culture.

NPA is especially useful for virus culture, antigen detection, and polymerase chain reaction

(PCR) based assays and is collected using a mucus trap, attached to a disposable suction

13

catheter. This technique requires a skilled operator, so it may be unsuitable for widespread

clinical practice. Studies that have compared NS and NPA sampling techniques for

detection by PCR report that the overall sensitivity of nasal swabs was inferior to that of

NPAs, but the authors noted that obtaining a NPA was invasive, uncomfortable and

significantly more distressful than a nasal swab (Heikkinen et al., 2002; Lambert et al.,

2008). With the recent development of flocked nasal swabs and advanced molecular

techniques, the sensitivities have increased to a level comparable to NPAs with the added

advantage of the flocked nasal swab being less painful and more convenient than NPAs, as

no supplementary tools are required (Ortiz de la Tabla et al., 2010). Sputum samples are

more representative of lower respiratory tract and are collected non-invasively. Despite

the aforementioned advantages of sputum collection, practical reasons preclude the

effective collection of sputum from infants and children (Abdullahi et al., 2008; Grant et al.,

2012). Children have difficulty producing sufficient sputum for laboratory evaluation

compared to adults and are more inclined to swallow the specimen than expectorate it

(Grant et al., 2012). Further the viscosity of sputum and the likely presence of

contaminating bacteria as well as the toxic effects sputum can have on cell culture

preclude its widespread use for viral diagnostic purposes (Falsey, Formica, and Walsh,

2012). BAL and lung biopsy specimen are collected directly from lower respiratory tract

sites. Previous studies on MERS-CoV have shown that quantification cycle (Cq) values were

lower in lower respiratory tract samples compared to upper respiratory tract samples and

more accurately reflect the apparent viral kinetics in the lower respiratory tract. However,

these specimen types are usually collected from the severely ill (Falsey et al., 2012) and too

few of these specimens would be available to conduct proper population level studies.

1.2.2 Virus isolation in cell culture

14

Historically, virus isolation by cell culture was the diagnostic method used to screen

respiratory samples for the presence of viruses. Virus isolation in cell culture is regarded as

the "gold standard" to which all other detection methods have been compared since the

isolation of virus in cell culture indicates the presence of an infectious, viable, and

replication competent virus, an occurrence which is unachievable using other detection

techniques (Leland and Ginocchio, 2007). This method is labour intensive, and often

requires prolonged incubation periods (3-14 days) to provide results, limiting its use in the

acute management of patients. A broad range of respiratory viruses can be grown by using

at least 4 cell lines, which includes human epithelial cell lines (HEp-2, A-549, HeLa),

human fibroblast cell lines (HLF, HELF, MCR-5, WI-38) and primary monkey kidney cells

(Denny Jr., 2001). For most respiratory virus applications, the presence of virus is

commonly detected by a characteristic cytopathic effect (CPE) under light microscopy. The

combination of conventional cell culture and commercial viral -antigen detection systems

can be used to accelerate diagnostic turn-around times, since viral antigens are detected in

the cell monolayer by immunofluorescence, usually before a distinct CPE is observable

(Terletskaia-Ladwig et al., 2008). In recent times, more rapid and powerful tools to detect

the presence of virus in clinical samples collected from patients following ARTI have

gradually superseded virus culture techniques.

1.2.3 Direct detection of respiratory viruses by immunofluorescence

Laboratory diagnosis can be performed by direct detection of virus in clinical specimen.

Direct antigen tests assist in the diagnosis of respiratory infection by providing evidence of

the antigen in respiratory specimen. These tests are instrumental in informing pertinent

therapeutic decisions in a short time frame (Gomez et al., 2016). Direct and indirect

immunofluorescence are the two sub-forms of the immunofluorescence test. The direct

test is composed of a virus specific monoclonal antibody that is conjugated directly to

15

fluorescent dye. If the virus is present in the clinical sample the monoclonal antibody

attaches to the targeted viral antigen and the conjugated fluorescent dye can be visualised

under a fluorescent microscope. In the indirect method, two antibodies are used, a specific

primary monoclonal antibody that attaches to the viral antigen and a secondary antibody

labelled with a fluorescent dye to bind to the primary monoclonal antibody. The indirect

method is more sensitive than the direct method because of the signal amplification from

multiple secondary antibodies binding to a single primary antibody.

Antigen detection methods such as the enzyme immunoassay (EIA) are performed by

adding patient specimen onto a surface that is pre-coated with an antibody that captures

the virus specific antigen if present in the specimen. EIA is a highly sensitive assay and

utilises an enzyme system to produce a colour reaction that can be quantified.

1.2.4 Nucleic Acid Tests

Diagnostic laboratories detect respiratory viruses in clinical samples by using molecular

techniques to detect virus genome. PCR based methods are the most favourable and the

most widely used approach for rapid and accurate respiratory virus detection from clinical

specimens. The advent of nucleic acid based tests has led to the identification of viruses

that were entirely missed using conventional diagnostic techniques. Most respiratory

viruses have their genetic information primarily stored in the form of RNA, with the

notable exception of HAdV and HBoV. Amplification of an RNA target requires a reverse

transcription (RT) step in order to convert RNA to cDNA followed by conventional PCR (RT-

PCR). DNA targets do not require an RT step. The repetition of three successive reactions

is the basis of PCR:

1. Denaturation of double stranded DNA (dsDNA) into si ngle stranded DNA (ssDNA)

between 94 and 95⁰C

16

2. Annealing of 2 synthetic oligonucleotides (primers) to each ssDNA at each termini at a

variable temperature ranging from 37-72⁰C

3. Synthesis of new DNA strands; the PCR method util izes a thermostable DNA polymerase

to add nucleotides at the 3' of end of the primers at 68 - 72⁰C.

These three steps entail a single PCR cycle, since each synthesized DNA strand becomes a

template for amplification there is an exponential increase in amplicon at the end of each

cycle. The length of the PCR product is equivalent to that of the two primers plus the

distance separating the two primers. Several variations of PCR are applicable to the

diagnosis of respiratory viral infection including nested PCR, real -time PCR (qPCR) and

multiplex qPCR.

1.2.4.1 Real time PCR (qPCR)

Utilisation of modern molecular techniques has enabled detection of viral nucleic acid

during the exponential phase of the reaction rather than waiting for the endpoint of the

reaction to register detection. The fundamental principle of qPCR is based on the detection

and quantification of fluorescent reporter molecules whose signal can be registered in

each cycle of the PCR. The cycle number when the fluorescence becomes detectable is

referred to as the cycle threshold/quantification value (Ct/Cq), and is proportional to the

logarithm of the initial amount in the clinical sample. Unlike conventional PCR, qPCR does

not require any post PCR amplification manipulations thereby minimizing any issues

related to contamination. However, similar to conventional PCR is the addition of a reverse

transcription step when screening clinical samples for respiratory viruses with an RNA

genome.

A DNA binding fluorescent dye, such as SYBR green represents the simplest method to

detect amplified product using qPCR, given that this dye binds to any double stranded DNA

17

in the reaction. A shortfall of SYBR green chemistry is its lack of sequence specific DNA

binding activity. So this type of chemistry will also bind to non-specific products that the

qPCR reaction may generate and may lead to false positive results. Sequence specific

hydrolysis probes are alternative detection chemistry and mitigate the problem of false

positive results because fluorescence signal is only detected when the probe binds to the

target area. Sequence specific hydrolysis probes are the most widely used and published

detection chemistry available for qPCR. These probes are beneficial because they are

designed to increase both the sensitivity and specificity of the assay. qPCR provides

excellent sensitivity and a wide dynamic range and for this reason can be utilised to

measure viral load in clinical samples.

Viral load determination may increase current understanding of host viral interactions

(Quinn, 2011) and may help predict disease progression (Jartti et al., 2013). Viral load

determination from clinical samples is performed by interpolating the cycle quantification

value (Cq) into a standard curve. The standard curve is constructed by standards of target

nucleic acid that encompass a wide range (5-9 logs) of known concentrations. It is

important to note that there is inherent variability in construction of a standard curve

between batches. As such it is imperative that the reference standards used are scrutinised

thoroughly for precision and reproducibility during the validation process , in order to

understand the limitations of the assays and to provide valid standards for RNA

quantification.

Specimen collection is an important source of variability that may obscure real changes

and consequently unreliable quantification results. The reliability of any PCR-based

quantification experiment can be improved by including an invariant endogenous control

(mRNA that is stably expressed and is not affected by experimental conditions) in the

experiment to correct for sample to sample variation that may arise.

18

1.2.4.2 Multiplex PCR

Multiplex PCR refers to the use of multiple sequence specific primers and probes to detect

multiple targets in a single reaction tube. This type of assay is efficient and economical but

requires substantial assay optimization to ensure optimal amplification of the different

targets if present. The availability of multiplex PCR makes the detection of co-infections

feasible (Franz et al., 2010). Multiplex PCR is an important tool in the diagnostic laboratory

when screening for potential etiologic contributions to disease.

1.2.4.3 Droplet digital PCR

Droplet digital PCR (ddPCR) is a relatively new approach that improves on qPCR by making

external standards unnecessary in viral quantification. In a similar approach to qPCR,

ddPCR involves the detection of template sequence with either a SYBR green or hydrolysis

probe reaction chemistry but quantification is conducted differently. It involves the

generation of a large library of emulsion based droplets (~20,000), also termed partitions

(Markey, Mohr, and Day, 2010). These partitions are generated from sample-reagent

mixtures and are distributed in such a way that there may be either one or zero template

molecules in the each partition (Mojtahedi, Fouquier d'Herouel, and Huang, 2014). This is

the fundamental principle underpinning digital PCR. Further, and in contrast to qPCR the

thermal cycling is performed to endpoint (Markey et al., 2010). The total initial number of

template is obtained by tallying partitions in which the template is detected compared to

the number of partitions in which the reaction is unreactive (Markey et al., 2010). A

Poisson correction is applied to the final copy number to compensate for the possibility

that more than one template molecule may be present in some partitions. ddPCR is highly

sensitive, reproducible, provides enhanced accuracy and precision thus lending itself to a

number of favourable applications such as low copy target detection, quantitative

detection of minor genotypes. Moreover, ddPCR does not rely on factors such as

19

amplification efficiency and arbitrarily assigned threshold values and therefore reduces the

amount of bias in the sample resulting in confident quantification (Hall Sedlak and Jerome,

2014; Huggett et al., 2013).

Recent work from a study comparing ddPCR to qPCR for quantitative detection of

cytomegalovirus (CMV) demonstrated that ddPCR is equivalent for the accurate

quantification of CMV load in clinical samples over a wide dynamic range (Hayden et al.,

2013). Recent work that evaluated ddPCR for influenza vaccine development has

demonstrated a high throughput ddPCR method for very precise and accurate influenza

virus titre quantification (Palatnik de Sousa et al., 2015). The authors also noted several key

issues that are determinants of variability in qPCR were circumvented with the ddPCR

approach.

1.3 Viral kinetics in acute respiratory tract infections

Viral kinetic studies have improved our understanding of the interplay between host and

virus in human immunodeficiency virus (HIV), CMV, hepatitis B and C infections.

Experimental human infection studies on RSV and IFAV have shown the unique ways in

which viral kinetics modulate illness severity and disease course (Bagga et al., 2013;

DeVincenzo et al., 2010; El Saleeby et al., 2011). In addition, viral load studies have shed

light on critical treatment time points used in order to minimise the risk of severe illness.

The recent discovery of novel respiratory pathogens has stimulated investigations into viral

load as a surrogate marker of disease severity in hospitalised patients. For ex ample,

evidence from a recent study conducted in France reports that a high hMPV viral load is an

important predictor of disease severity in young children (Roussy et al., 2014). Indeed,

previous RSV studies indicate that high viral load is associated with symptom severity

(DeVincenzo et al., 2010; El Saleeby et al., 2011; Houben et al., 2010) . Furthermore, a

20

reduction in RSV and influenza viral loads in patients as a consequence of antiviral therapy

has been found to be associated with improved clinical outcomes (Boivin, Coulombe, and

Wat, 2003; Shadman and Wald, 2011). This paradigm of direct virus damage to host tissue

shaping clinical outcome has been supported further by investigations on SARS-CoV and

MERS-CoV (Feikin et al., 2015; Hung et al., 2004; Min et al., 2016). In RV infection, evidence

in the published literature suggests that viral load is predictive of the severity of clinical

illness, given that individuals with a lower respiratory tract infection harbour higher viral

loads that those with an upper respiratory tract infection (Utokaparch et al., 2011). This

finding is further supported by an Italian study that reported that an abundant RV viral

load (>106copies/mL) in the absence of other viral pathogens is strongly associated with

LRTI (Piralla et al., 2012). However, other studies have not reproduced these findings (Jartti

et al., 2008) and thus the relevance of RV viral load in lower respiratory tract infections is

not yet completely understood.

1.4 Viral respiratory infection and asthma

Asthma is one of the most common chronic respiratory inflammatory conditions and a

substantial contributor to morbidity worldwide (GINA, 2017). It is characterised by airway

inflammation, remodelling, reversible airway blockage, and increased airway smooth

muscle tone (Zhao et al., 2002). It can be difficult to diagnose asthma with certainty in

children aged between 0-5 years because there are no standardised diagnostic criteria for

asthma (GINA, 2017). In addition, respiratory infections predominant in childhood such as

bronchiolitis share many clinical features with exacerbations of asthma, including

wheezing, shortness of breath and respiratory distress (Sigurs et al., 2000). Diagnosis of

asthma in children may involve the individual’s history of recurrent wheeze, family history

of atopy and objective investigations that support the diagnosis. Several stimuli can trigger

21

exacerbations of asthma symptoms in young children including smoking, viral infections,

air pollution and environmental allergens (Pelaia, Vatrella, and Maselli, 2012; Riccio et al.,

2012; Saraya et al., 2014; Sykes et al., 2014). The advent of molecular methods has shown

that respiratory viruses are present more commonly in acute asthma than previously

acknowledged, and are detected in up to 85% of asthma exacerbations (Saraya et al.,

2014). RV and RSV are the predominant viruses that appear to be involved with these

exacerbations (Saraya et al., 2014; Sigurs et al., 2000; Soto-Quiros et al., 2012). It is still

not yet clear if infection causes long term changes in the airways which subsequently

increase the risk of developing asthma. An alternative hypothesis is that severe RSV and/or

RV disease (bronchiolitis) may be an early marker of a predisposition for childhood asthma

(Miller et al., 2011; Moore, Stokes, and Hartert, 2013; Moore et al., 2007). The children at

high risk of developing asthma are those who wheeze and develop allergic sensitization

before the age of 2 years (Jackson et al., 2008a; Sigurs et al., 2010; Sigurs et al., 2000). Long

term prospective studies have linked severe RSV disease in young infants to subsequent

recurrent wheeze and asthma in susceptible children (Sigurs et al., 2010). However other

studies do not confirm the association between medically attended RSV disease and

subsequent asthma development (Poorisrisak et al., 2010).

RV infection in young infants is an independent risk factor for subsequent wheeze and

childhood asthma (Jackson et al., 2008a). Several reports have shown that RVs are the

most common virus detected in hospitalised young children with exacerbations of asthma,

suggesting an etiologic role (Liu et al., 2016; Luchsinger et al., 2014; Message and Johnston,

2002; Miller et al., 2011). Children classified as asthmatic are more likely to have poor

outcomes following RV infection compared to normal individuals (Corne et al., 2002). RV-C

appears to be the most commonly detected species in hospitalised asthmatic children with

some studies suggesting that it is also the most pathogenic (Bizzintino et al., 2011a; Cox et

al., 2013; Liu et al., 2016). However, determinants of RV-C associated asthma severity are

22

yet to be clearly defined, and the contribution of RV-C in asthma exacerbation severity is

still not clear.

23

1.5 Innate immune response to viral respiratory infection

In response to infection, germ line encoded receptors (pattern recognition receptors,

PRRs) that are resident on sentinel cells of the immune system sense conserved pathogen-

associated molecular patterns (PAMPs) on microbes (Gommerman and Ng, 2013; Kim and

Lee, 2014; Malmgaard, 2004; Scagnolari et al., 2009). There are three known PRR families

and they include toll-like receptors (TLRs), retinoic acid inducible gene 1 (RIG-1)-like RNA

helicases (RLHs) and nucleotide-binding oligomerization domain (NOD) like receptors

(NLRs). Signalling downstream of each PRR family results in the activation of important

pathways that regulate the expression of chemokines, pro-inflammatory cytokines, type 1

interferon (type 1 IFN) and antimicrobial peptides (Thompson and Locarnini, 2007). RLHs,

TLR 3, 7, 8 and 9 identify viral nucleic acid and induce innate type 1 IFN responses with or

without the production of pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, IL-12, IL-18).

Type 1 IFN is known to block viral replication at an early step in replication and to be very

important for the induction of an anti-viral state against common respiratory viruses

(Scagnolari et al., 2009). Type I IFN deficient mice are more prone to delayed viral

clearance and severe disease following viral challenge. Further, impaired IFN response to

viral infection has been postulated as a pathogenic mechanism for poor outcomes in

asthmatic patients (Baraldo et al., 2012) and MERS-CoV infection (Faure et al., 2014). In

animal models of hMPV infection it has been shown that a TLR 4 mediated inflammatory

response does not facilitate an adaptive immune response important for viral clearance

and protection against reinfection but predicts the progression of clinical disease

(Velayutham et al., 2013). In RSV infection, PRRs correlate with viral load and there is an

increased pulmonary expression of PRRs compared to healthy controls or infants with RV

or hBoV infection (Scagnolari et al., 2009).

24

Different viral infections can elicit different inflammatory responses, and these

inflammatory responses can generally be grouped into T-helper 1 (Th1) and T-helper 2

(Th2) responses. These inflammatory responses are classified based on the type of

chemokines and cytokines produced. Th1 responses are characterised by production of

IFN-γ, IL-1β, IL-2, IL-12, IL-18, and TNF-α. The Th1 response is pro-inflammatory and is

important in the generation of immune responses necessary for the control and clearance

of intracellular pathogens, thus it is the most suitable response to viral infection. The Th2

response on the other hand is characterised by secretion of IL-4, IL-5, IL-6, IL-9, IL-10, and

IL-13. This type of response is involved in antibody production (including IgE) and

eosinophilic inflammation. This response is strongly associated with atopy and protection

against parasitic infection. It has also been demonstrated that Th2 inflammation counter

regulates Th1 mediated responses (Gill et al., 2010). Respiratory viral infections provoke

differing inflammatory profiles. For instance, IFAV can induce the overproduction of Th1

inflammatory mediators and this is associated with poor clinical outcomes. Dysregulated

secretion of TNF-α and IL-1β maybe critical for pathogenicity and may also hinder the

development of an effective adaptive immune response following infection (Han et al.,

2014). In RSV disease, sequential increases of IFN-γ coincide with improved clinical

outcomes and provide support for the protective role of IFN-γ following infection

(Bermejo-Martin et al., 2007a). Conversely, severe acute viral respiratory infection in

infants is associated with augmented Th2 responses (Bermejo-Martin et al., 2007b). In

addition, individuals with an underlying Th2 bias, such as those with an allergic pulmonary

condition, are more likely to have poor clinical outcomes compared with those without an

underlying Th2 bias (Gern et al., 2000; Mahmutovic Persson et al., 2016; Monick et al.,

2007).

Many types of cells have been implicated in the pathogenesis of ARTI and of note is the

quick and robust pulmonary and systemic neutrophil response following infection

25

(Nagarkar et al., 2009; Sugamata et al., 2012). This robust neutrophil response correlates

with disease severity and is mediated primarily by IL-8 (Cortjens et al., 2016). Neutrophilia

is a common response to both bacterial and viral infections. While there are clear

protective roles for neutrophils against bacterial infection, the evidence for an anti-viral

role is less clear. The role of neutrophils has been investigated in RSV infection and they

are believed to play a role in pathogenesis (Cortjens et al., 2016; Linden, 2001;

Mahmutovic Persson et al., 2016). The role of neutrophils in influenza mouse models is

reported to be both protective and pathogenic. Some papers suggest neutrophils can

reduce viral load by phagocytosis of infected cells and trapping of free virus in neutrophil

extracellular traps. However, other reports have demonstrated that neutrophil

myeloperoxidase facilitates acute respiratory distress syndrome following influenza

infection and that mice lacking myeloperoxidase were more competent in reducing viral

load (Sugamata et al., 2012). Neutrophil involvement has also been demonstrated in RV-

induced asthma exacerbations and high counts are observed in the airways of individuals

following fatal exacerbations (Fahy, 2009; Fahy et al., 1995; Linden, 2001). In a RV mouse

model, IL-8 knock-out mice infected with RV showed significantly reduced neutrophil

responses, and demonstrated reduced airway hyper-responsiveness (Nagarkar et al.,

2009). Functional neutrophil activity has been demonstrated to be enhanced in the airways

of asthmatics, particularly during exacerbations, and correlates with reductions in lung

function and increases in symptom score (Proud, 2011). However, the precise contribution

of neutrophils to asthma has yet to be established.

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1.6 Aims of Project

The general aim of this thesis was to develop reliable quantitative PCR (viral load) assays to

investigate the contribution of certain respiratory viruses to clinical outcome of young

children hospitalised with an acute viral respiratory tract infection.

The specific aims were as follows:

To develop and validate the use of reliable in-house qPCR (viral load) assays for

different respiratory viruses including IFAV, hMPV, RSV-A&B, and RV-C.- Chapter 3

and 4 (RV-C only)

To compare the analytical performance of real time qPCR to digital PCR in the

quantitative measurement of RSV load in clinical samples - Chapter 3

To examine the contribution of RSV to clinical disease in young infants in a high HIV

prevalence setting- Chapter 5

To investigate the contribution of RV-C to disease severity in young children

presenting to emergency department with acute asthma exacerbations - Chapter

6.

To understand the interplay between RV-C infection and the innate immune

response in young children hospitalised with a RV-C associated wheezing illness -

Chapter 7

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2 Materials and Methods

2.1 Sample collection

Clinical specimens included flocked nasal swabs, per nasal aspirates, sputum and

nasopharyngeal aspirates samples. Swabs were placed in virus transport medium (VTM)

which contains Hanks balanced salt solution, with 50mg gentamicin, 0.1% bovine serum

albumin, 0.1% sodium bicarbonate and 8mM HEPES buffer).

Nasopharyngeal aspirates (NPAs) were collected from 105 ALRI cases and 53 controls from

Pretoria, South Africa between July 2011 and November 2012 (Chapter 5). Children 0-2

years of age hospitalized with an ALRI at the Steve Biko Academic Hospital or Tshwane

District Hospital in Pretoria were enrolled as cases. A diagnosis of pneumonia (respiratory

distress and either chest X-ray changes (e.g. consolidation or effusion), or auscultatory

findings (e.g. crepitations or bronchial breathing) or bronchiolitis (respiratory distress and

at least one of the following; wheeze, chest X-ray changes (e.g. hyperinflation) or

Hoovers’s sign (inward movement of the lower rib cage during inspiration) was determined

by the clinician in charge. Fifty-three age-matched children presenting to the same

hospitals with a non-respiratory illness over the same period were enrolled as controls

(NRD controls). The study protocol was approved by the University of Western Australia

Human Ethics Committee and the University of Pretoria Ethics Committee. Written

informed consent from parent/guardian was obtained prior to participation. NPAs were

stored at -80°C in Pretoria, South Africa until transfer on dry ice to Telethon Kids Institute,

Perth, Australia for processing and long term storage. An aliquot of each sample was

transported on dry ice to PathWest Laboratory Medicine WA, Perth, Australia.

For Chapter 6, flocked nasal swabs were collected from young children presenting with an

acute asthma exacerbation as part of the MAVRIC (Mechanisms of Acute Viral Respiratory

28

Infection in Children) study carried out at Princess Margaret Hospital in Perth, Western

Australia. Flocked nasal swab specimens were also collected from children with no

evidence of respiratory disease. These children were selected to match the acute asthma

exacerbation cases for age, and season of birth. An aliquot of each sample was

transported on dry ice to PathWest Laboratory Medicine WA, Perth, Australia and stored

at -80oC until further use.

Study participants for the cytokine study (Chapter 7) had a flocked swab sample collected

upon inpatient admission. These samples were placed on ice and transported to the

PathWest laboratory as soon as practically possible for storage in -80oC freezer.

2.2 Nucleic acid extraction and viral detection

Total nucleic acids were extracted from 200µL of respiratory specimen using the MagMAX

viral RNA isolation kit (Thermo-Fisher Scientific, Australia) according to the manufacturer’s

instructions. All automated liquid transfer procedures utilised the CAS 1200 instrument

and conductive tips (Corbett Life Science. Australia)

An in-house multiplex respiratory pathogen assay was used to screen study samples for

respiratory pathogens such as influenza A, B and C viruses (FLUAV, FLUBV,FLUCV),

parainfluenza virus I-IV (PIV), RSV-A & B, Coronaviruses (hCoV- HKU1, -NL63, -OC-43, -

229E), human metapneumovirus (hMPV), and human adenoviruses (hAdV) (Chidlow et al.,

2009). Every multiplex PCR run performed included positive (PCR, inhibition and extraction

positive controls) and negative controls (method blanks interspersed by 5 test samples).

Nucleic acid extracts were stored at -80oC. A few minor adjustments were made to the

multiplex PCR real-time assay (Chidlow et al., 2009). Adjustments included the addition of

a 2.5 µM ROX reference dye (ThermoFisher), which was to be used for the 1:10 dilution of

amplicon generated from the enrichment PCR assays. Further, extra primer pairs were

29

included to screen for hMPV (Chidlow et al., 2009). The primer pairs reported by Lee and

colleagues (Lee et al., 2007) were used for RV identification and genotyping. Respective

monoplex quantitative PCR assays were used to confirm any discordant results obtained

from the respiratory multiplex PCR assay. Thermal cycling programmes for the enrichment

PCR assays and the real time multiplex PCR assay were adopted from (Chidlow et al.,

2009).

2.3 Design of primers and probes

Assay oligonucleotides were designed using primer express v3.0 software (primers and

MGB probes) (ThermoFisher Scientific, Australia or the Exiqon microRNA PCR online

service (LNA probes).Primers were synthesised by Integrated DNA Technologies (IDT,

Australia), MGB probes were synthesized by Applied Biosystems (ThermoFisher Scientific,

Australia) and Locked Nucleic Acid (LNA) probes were synthesized by Sigma-Aldrich (Sigma-

Aldrich, Australia). The primers and probes used in the multiplex PCR to screen initially for

viral nucleic acid in respiratory samples were as previously described (Chidlow, 2013;

Chidlow et al., 2009).

Viral load from clinical samples was determined by real-time PCR targeting specific regions

of nucleoprotein gene of RSV (A&B) and HMPV, the matrix gene of IFAV and the

5’untranslated region (UTR) of RV-C (Table 2.1). These sequences were used because they

are highly conserved across all the respective strains investigated. Table 2.1 lists primers

and probes details for IFAV, RSV (A&B), HMPV, RV-C and Glyceraldehyde-3-phosphate

dehydrogenase (GAPDH) assay

30

Table 2.1: Primers and probes used in quantitative real-time PCR assays

aLNA bases are underlined.

Target Target region Oligonucleotide sequence (Position) a

HMPV F (Forward Primer) Nucleoprotein gene 5’-ATCATCAGGYAAYATYCCACAAA-3’ (420 - 442)

HMPV R (Reverse Primer ) 5’- TATTAARGCACCTACACATAATAA-3’ (518 -542)

HMPV (Probe) 5’-FAM-CCTGCGTGGCTGCC-MGBNFQ-3’ (481- 497)

RSV-A F (Forward Primer) Nucleoprotein gene 5’CAACTTCTGTCATCCAGCAAA3’(1117 -1137)

RSV-A R (Reverse Primer) 5’TGCACATCATAATTAGGAGTATCAAT3’ (1166-1191)

RSV-A Probe 5’-FAM-CACCATCCAACGGAGC`3’-BHQ-1 (1140 – 1155)

RSV-B F (Forward Primer) Nucleoprotein gene 5’ATTCAACGTAGTACAGGAGATAATA3’ (1141 - 1165)

RSV-B R (Reverse Primer ) 5’CCACATAGTTTGTTTAGGTGTTT’ (1193 -1214)

RSV-B Probe 5’-FAM-TGACACTCCCAATTAT3’-BHQ-1 (1167 – 1182)

IFAV (Forward Primer) Matrix gene 5’CTTCTAACCGAGGTCGAAACGTA3’ (7-29)

IFAV (Reverse Primer ) 5’-GGTGACAGGATTGGTCTTGTCTTTA--3’ (137-161)

IFAV (Probe) 5’FAM-TCAGGCCCCCTCAAAGCCGAG3’-BHQ-1 (49-69)

RV-C IrlonS (Forward Primer) 5’UTR 5’-GCACTTCTGTTTCCCC-3’ (165 - 180)

RV-C EntA (Reverse Primer) 5’- GCATTCAGGGGCCGGAG-3’ (461 -445)

RV-C Probe 1 5’-FAM-CCTGCGTGGCTGCC-MGBNFQ-3’ (358 - 371)

RV-C Probe 2 5’-FAM-CCCGCGTGGCTGCC3’-BHQ-1 (359 - 372)

RV -C Probe 3 5’-FAM-CCCGCGTGGTGCCC-MGBNFQ-3’ (354 - 367)

RV -C Probe 4 5’ -FAM-CCTGCGTGGTGCCC3’-BHQ-1 (354 – 367)

GAPDH (forward) GAPDH mRNA 5’GAAGGTGAAGGTCGGAGTC3’ (7-25)

GAPDH (reverse) 5’AAATCCCATCACCATCTTC3’ (213-231)

GAPDH probe 5’-FAM-GGCTGAGAACGGGAAGCTTG-MGBNFQ

31

2.4 Production and quantification of transcribed RNA

standards Nucleotide sequences matching a segment of the 5' UTR of RV-C2 [EF077280.1], RV-C6

[EF582387], RV-C51 [JF317015],RV-C25 [JF317013], RSV A [KJ627348]&B [KU950585] NP gene,

HMPV NP gene [AHV79765], IFAV matrix gene [CY056296] were incorporated into individual

plasmid constructs manufactured by Integrated DNA Technologies (IDT,