Comparative Genomic Analysis of Mobile Genetic Elements in Histophilus Somni Isolates from Feedlot Cattle

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2020-08-25 Comparative genomic analysis of mobile genetic elements in Histophilus somni isolates from feedlot cattle

Mostafa Nazari Zanjani, Mohammad

Mostafa Nazari Zanjani, M. (2020). Comparative genomic analysis of mobile genetic elements in Histophilus somni isolates from feedlot cattle (Unpublished master's thesis). University of Calgary, Calgary, AB. http://hdl.handle.net/1880/112445 master thesis

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Comparative genomic analysis of mobile genetic elements in Histophilus somni

isolates from feedlot cattle

Mohammad Mostafa Nazari Zanjani

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF MASTER OF SCIENCE

GRADUATE PROGRAM IN VETERINARY MEDICAL SCIENCES

CALGARY, ALBERTA

AUGUST, 2020

Organisms, including bacteria, are defined by the genes they possess. This genomic pool determines whether a bacterial species can survive or compete in a changing environment. Bacteria can acquire new genomic content through de novo mutations or through external genomic reservoirs via horizontal gene transfer. Horizontal gene transfer (HGT) is the exchange of genetic material through mobile genetic elements

(MGE) between cells which have no parent-offspring relationship. The conjugation pathway is one of the main routes of HGT in bacteria and is in part mediated by plasmids or integrative and conjugative elements (ICE). ICEs can provide new genes through HGT which confer new phenotypic traits such as resistance to antibiotics and heavy metals, biofilm-formation and metabolic alterations. In this study, an ICE was identified in Histophilus somni, a Gram-negative bacterium that is one of the major bacteria involved in bovine respiratory disease (BRD). The ICE and other mobile genetic elements were identified through analysis of whole-genome sequences (WGS) of H. somni isolates collected from tissue samples from Canadian and American feedlot cattle mortalities. A variety of antimicrobial resistance genes were located within ICE sequences. AMR genes tet(H), Sul2/folP, APH(3”)-Ib,

APH(6)-Id, and APH(3’’)-Ia, were identified. These genes may provide phenotypic resistance for the antimicrobial classes: tetracyclines, sulfonamides, phenicols and aminoglycosides. Plasmids were not identified in WGS files. No AMR genes were

ii found on the chromosome other than those within ICE sequences. The ICEs in

Canadian and American H. somni isolates exhibited similar genome assembly and genome content. The similarity of the ICE in Canadian and American H. somni isolates indicates that they may have moved between the two countries during import and export of cattle. The ICEs of H. somni were identified as members of the

ICEHin1056 ICE-family. ICEs of the ICEHin1056 ICE-family have been identified in four bacterial species; two human-specific species, Haemophilus influenzae, and

Haemophilus parainfluenzae, and the animal pathogens, H. somni, Actinobacillus pleuropneumoniae, M. haemolytica, and P. multocida.

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Preface

This study used whole genome sequences to examine the genome of H. somni isolates collected from Canadian and American feedlot cattle. The American database containing WGS assembly and annotation was published by the United

States Department of Agriculture (USDA), Genetics, Breeding, and Animal Health

Research Unit, Clay Centre, USA. The American WGS record, assembly and annotation, was used without modification for comparative genomics to identify and compare mobile genetic elements and antimicrobial resistance genes.

Canadian WGS data used in this study were provided by the Vaccine and Infectious

Disease Organization–International Vaccine Centre (VIDO-InterVac), Saskatoon,

Canada. All post sequencing procedures including bioinformatics, assembly, annotation, dataset creation, and comparative genomics conducted on Canadian

WGS were completed in this study.

Acknowledgements

I would like to thank my supervisor, Dr. Karen Liljebjelke for guiding me through my MSc. Thank you for your patience and for encouraging me to pursue my academic career. You were a great supervisor, teacher, mentor and friend during the past two years, and I cannot express my gratitude enough for all your kind support.

I also want to take the opportunity to thank my graduate committee members: Dr.

Anthony B. Schryvers, and Dr. Tim McAllister. The novelty and great outcomes of the current research project are results of your constant support and the fruit of your valuable time dedicated to me. I would like to express my deepest appreciation to

Dr. Rahat Zaheer who was great motivator and a model of hard work and critical thinking.

I would like to thank my dear friends, who just like me came from different parts of the world, but all shared one heart of kindness, care and support: lab mates Fernando

Guardado, Mai Farghaly, friends Jamyang Namgyal, Karma Phuntsho, sources of peace and dedication Ana Perez Contreras, Shahnas Najimudeen, Catalina Barboza and Sabrina Marsha, and last but not least to my dear friend and colleague Lindsay

Roger who showed me the beautiful culture of Canada.

Dedication

To my love Pegah Peikazadi, my best and closest friend.

Disclaimer

This thesis was copy-edited for grammar and clarity by the graduate supervisor, Dr.

Karen Liljebjelke. Intellectual revisions, technical and scientific recommendations were provided by Dr. Tim A. McAllister, and Dr. Antony B. Schryvers.

vii

Table of Contents Abstract ...... ii Preface ...... iv Acknowledgements ...... v Dedication ...... vi Disclaimer ...... vii List of abbreviations ...... xii Chapter one: General introduction ...... 1 1.1 Feedlot Cattle ...... 1 1.1.1 Nature and description of feedlot ...... 1 1.1.2 General overview of beef cattle production system in Canada ...... 1 1.1.3 Feedlot production in Alberta ...... 2 1.1.4 Management of diseases in feedlot cattle ...... 2 1.2 Bovine Respiratory Disease ...... 3 1.2.1 Significance of the disease ...... 3 1.2.2 BRD is a multi-factorial disease initiated by stress ...... 4 1.2.3 Viruses involved in BRD ...... 5 1.2.4 Major BRD-associated bacteria ...... 5 1.2.5 Role of Histophilus somni in BRD ...... 7 1.2.6 Pathophysiology of BRD-associated bacteria ...... 9 1.3 BRD management ...... 10 1.3.1 Vaccination ...... 10 1.3.2 Use of antimicrobials to prevent, control and treat BRD ...... 11 1.3.3 Antimicrobials licensed for BRD in cattle ...... 11 Table 1. Antimicrobials licenced for use in feedlot Cattle ...... 13 1.3.4 Recent regulations of antimicrobial usage in livestock in Canada and US ...... 14 1.3.5 Advantages and disadvantages of AMR phenotype assays ...... 16 1.4 Role of horizontal gene transfer in dissemination of AMR ...... 20 1.4.1 Horizontal gene transfer in bacteria ...... 20 1.4.2 Integrative conjugative elements (ICE) ...... 21 1.4.3 ICE life cycle ...... 21 Figure 1: Schematic of an integrative and conjugative element life cycle ...... 27 1.4.4 ICE in BRD-associated bacteria and their cargo genes ...... 27

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1.5 Conclusion ...... 28 1.6 Objectives, specific aims and methods ...... 29 Chapter two: Creation of a binformatics dataset and identification of antibiotic resistance genes in the genome of Histophilus somni strains ...... 33 2.1 Draft Genome Sequences of 12 Histophilus somni Strains Isolated from Feedlot Cattle in Alberta, Canada ...... 33 2.1.1 Authors and affiliations ...... 33 2.1.2 Background ...... 34 2.1.3 Announcement ...... 34 2.1.4 Data availability ...... 36 Chapter three: In silico analysis of the WGS of a multidrug-resistant Histophilus somni strain collected from feedlot cattle in Alberta, Canada ...... 38 3.1 Authors and affiliations ...... 38 3.2 Introduction ...... 39 3.3 Methods ...... 39 3.4 Results ...... 42 3.5 Discussion...... 47 3.6 Conclusion ...... 54 Table 3: Summary of identified AMR genes in the sequence of ICE in H. somni UOC-KLM-ATR-014 . 56 Chapter four: The integrative and conjugative element of H. somni ...... 57 4. An integrative and conjugative element (ICE) conferring multi-drug resistance and copper tolerance in Histophilus somni from feedlot cattle in Alberta ...... 57 4.1 Authors and affiliations ...... 57 4. 2 Introduction ...... 58 4. 3 Materials and Methods ...... 59 4.3.1 Whole-genome sequence raw data files ...... 59 Table 4. Summary of H. somni sequences and associated metadata used in this study...... 61 4.3.2 Assembly and annotation of draft whole genome sequences...... 62 4.2.3 Identification of mobile genetic elements ...... 63 4.3.4 Characterization of ICEs ...... 63 4.3.5 Comparative genomic analysis of ICEs in Canadian and American H. somni isolates ..... 64 4.3.6 Comparison of H. somni ICE and P. multocida and M. haemolytica ICEs ...... 65 4.3.7 Identification of H. somni ICE family ...... 65 4.3.8 Antimicrobial resistance and metal tolerance genes of ICEs among members of the ICEHin1056 family ...... 65

4.3.9 H. somni ICE host range prediction ...... 66 Table 5: Bacteria containing similar ICE ...... 67 4.4 Results ...... 68 4.4.1 Identification of mobile genetic elements in H. somni WGS ...... 68 Table 6. Summary of ICEs, IMEs and prophages integrated into H. somni chromosomes ...... 69 4.4.2 Identification of H. somni ICE family ...... 70 Figure 2: Results of a MultipleGeneBlast alignment used to identify the most homologous ICEs .... 71 Figure 3. Whole-genome sequence alignment using Mauve to examine gene arrangement and compare coding modules between ICEs...... 72 4.4.3 Genomic structure of H. somni ICE ...... 73 Table 7: Genomic characteristics of H. somni ICE ...... 74 Table 8: Integrative and conjugative machinery complex (ICMC genes) identified in H. somni ICE sequences...... 75 Figure 4. A circular map of Canadian H. somni strain ...... 76 Figure 5. Simplified map of ICE identified in H. somni UOC-KLM-ATR-014. Genes with similar function are assembled close to each other ...... 77 Figure 6. Sequence map illustrating ICE integration into a tRNA-Leu at a palindromic sequence site ...... 77 4.4.4 Gene-arrangement in ICEs of BRD-associated bacteria ...... 79 4.4.6 Identification of cargo genes of ICEHin1056 ICE family members ...... 80 4.4.7 Host range prediction for the H. somni ICE ...... 81 4.5 Discussion...... 82 Chapter five: General discussion and future research ...... 86 5. 1 General Discussion ...... 86 Figure7: Graphic abstract: Histophilus somni strains, collected from Canadian and American feedlot cattle ...... 89 5.2 Future work ...... 91 5.3 Conclusion ...... 94 6. References ...... 96 7. Appendix ...... 139 Appendix Table 1. Comparative assessment between the type and pool of coding virulence factors (VF) carrying by Haemophilus spp and Histophilus spp ...... 139 Appendix Figure 1: The graph is showing the Phred score of one of the Canadian WGS. The minimum phred quality score (Q-score) of sequences were 32. Phred scores range from 4 to about 60, with higher values corresponding to higher quality...... 148

Appendix Figure 2: The FastQC assessment of a Canadian WGS ...... 149 Appendix Figure 3: The circular map of UOC-KLM-ATR-014, showing three prophages and one integrative and conjugative element (ICE) inserted on its genome...... 150 Appendix Figure 4: The circular map if ICE integrated in the chromosome...... 151 Appendix Figure 5: Genomic islands identified on the genome of UOC-KLM-ATR-014 A) The circular map of the KLM-014 made by IslandViwer_4. Numbers on the map are showing the size of the genome. Red bars are identified genomic islands which were included one ICE (highlighted portion), two IME and three prophages...... 152 Appendix Table 2: The genome content of ICE and its coding products ...... 154 Appendix Figure 6: The protein homology of the AMR gene floR ...... 155 Appendix Figure 7. A detailed map of the ICE of (a Canadian-KLM-014) H. somni...... 155 Appendix Figure 8. Genome arrangement and size-similarities in ICEs of BRD-associated bacteria . 155 Figure 9: The simplified bioinformatic workflow of this study to identify and classifying ICEs ...... 155

List of abbreviations

BRD Bovine respiratory disease

ICE Integrative conjugative element

IME Integrative mobilizable element

ARG Antimicrobial resistance gene

AMR Antimicrobial resistance

MGE Mobile genetic element

HGT Horizontal gene transfer bp Basepair nt Nucleotide

AA Amino acid

GPD Gross domestic product

Int Integrase/recombinase

ICMC Integrative and conjugative machinery complex

DRs Direct repeats

MIA Medically important antimicrobial

xii

WHO World Health Organization

CNS Central nervous system

IgBP Immunoglobulin binding protein

OmpA Outer membrane protein

FHA Filamentous hemagglutinin

LPS Lipopolysaccharide

VF Virulence factor

USDA United States Department of Agriculture

VIDO-InterVac Vaccine and Infectious Disease Organization–International

Vaccine Centre

T4SS Type IV secretion system

FDA Food and Drug Administration

IS Insertion sequence

WGS Whole-genome sequence

GI Genomic island

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Chapter one: General introduction

1.1 Feedlot Cattle

1.1.1 Nature and description of feedlot

Alberta Agriculture and Forestry defines a feedlot as “Any land enclosed by a fence or other means which is used or intended for use to feed cattle in confinement” [1].

A feedlot is an intensive feeding operation where beef cattle or other livestock are held for the purpose of weight gain through consumption of energy-rich diets before slaughter. The primary purpose of this system is to boost growth and weight gain, and increase intramuscular deposition of fat via reducing energy expenditure used by foraging. [2].

1.1.2 General overview of beef cattle production system in Canada

Beef cattle production starts with calves born in spring. Animals weigh between 300 and 400 Lb are weaned prior to transport to a feedlot. Most calves are purchased from auction markets and are transported in livestock trucks to feedlots. The timing of calving results in the majority of calves placed in feedlots in fall, with a smaller portion arriving during winter [3,4]. After settling into the feedlot the diet of newly arrived animals changes from forage to grain, with grain accounting for the majority of the finishing diet. This diet promotes weight gain and produces tender and marbled beef. Animals are ready for market at 1100-1600 pounds, depending on their breed [5–7].

1.1.3 Feedlot production in Alberta

Canada produces approximately 2% of the global supply of beef, accounting for 7% of beef exports worldwide. Canada is the 12th place beef producer worldwide, generating around 3.08 billion pounds annually. Between 2014 and 2018 beef production contributed $18 billion to Canada’s gross domestic product (GPD) on average [8]. Almost half of beef cattle producers are located in western Canada

(41%), and Alberta has more feedlots than all other provinces combined. Out of 150 feedlots in Alberta surveyed by “Canfax” in 2018, 115 held <10,000 head capacity,

23 held 10,000-20,000 and 12 finishes >20,000 (35% of the total Albert feedlot cattle) [9].

1.1.4 Management of diseases in feedlot cattle

A compromised immune system due to various stressors is the most common reason why respiratory infections and other diseases develop in feedlot cattle. Opportunistic pathogens responsible for BRD are usually the first cause of morbidity and mortality after cattle arrive at feedlots. Metabolic diseases such as acidosis and liver abscesses

2 are common problems caused by high grain finishing diets and occur later in the feeding cycle. Environmental and management factors influence other health problems such as foot-rot and digital dermatitis, which lead to lameness and subsequent loss of productivity and decrease in weight gain [10–13].

1.2 Bovine Respiratory Disease

1.2.1 Significance of the disease

Bovine respiratory disease (BRD) is a disease of the lower respiratory tract and one the most common and costly infectious diseases in North America feedlot cattle [14].

The term BRD is used to categorize any undifferentiated respiratory disease with clinical signs such as fever, cough, running-nose, and other indications of respiratory disease [15]. In US feedlots BRD accounts for 70-80% of morbidity and 40-50% of mortality [16,17]. The economic toll of the disease on the US beef production is estimated to be a loss of more than $1 billion annually [18], with some studies estimating losses up to $4 billion per year [19]. The economic impact of the disease arises from increased labour, cost of prevention and treatment, loss of productivity and reduction of meat quality. Due to similarities in beef production practices in

Canada and the US the per capita economic losses of BRD are expected to be similar in Canadian beef production.

1.2.2 BRD is a multi-factorial disease initiated by stress

Controlling BRD among newly received animals presents a great challenge due to the high rate of morbidity and mortality in feedlot cattle. Most mortalities related to

BRD in cattle occur shortly after or within the first 45 d after arrival at feedlots

[20,21]. Animals are exposed to different stresses before arrival at feedlots such as weaning, handling, transport and comingling. Many cattle are transported a considerable distance prior to arrival at a feedlot. Within the first 24 hours after arrival calves undergo a variety of management practices referred to as processing.

Processing procedures include ear tagging, vaccination against bovine respiratory disease (BRD) pathogens and clostridial diseases, deworming, medication with antimicrobials, and induction of abortion in heifers [22]. The objective of these procedures is to prevent disease and prepare calves for the intensive feedlot system.

Shipment to the feedlot and processing practices can be a source of considerable stress for cattle. Research suggests that the stress of shipping compromises the immune system of cattle and enables viruses and bacteria to cause respiratory infections [23–25].

A management practice known as preconditioning has the goal of preparing calves for transition to the feedlot environment and minimizing stressors. Preconditioning practices includes vaccination, deworming, castration, dehorning, soft weaning, and

4 eating from bunks which allows calves to develop immunity and adapt before entering feedlots. Studies have shown that preconditioned calves have less morbidity compared to conventionally managed calves [26]. Factors such as age, weather conditions and genetics also influence the development and severity of BRD

[27,28].

1.2.3 Viruses involved in BRD

An ineffective immune system permits viruses to invade cells and cause infection, damaging respiratory mucosa and the mucociliary escalator and destroying the integrity of the respiratory cellular (physical) barriers. Compromised cellular barriers then allow bacterial invasion of the lower respiratory tract. The major BRD- associated viruses in North America are bovine herpesvirus 1, Parainfluenza virus

3, bovine respiratory syncytial virus, and bovine viral diarrhea virus [29,30].

1.2.4 Major BRD-associated bacteria

Most of the BRD-associated bacteria are commensal species colonizing the upper respiratory tract and present in healthy animals. Upon disruption of the innate immune barriers, bacteria may overgrow or invade the lower respiratory tracts.

Major BRD-associated bacteria are Mycoplasma bovis and three members of the

Pasteurellaceae family: Mannheimia haemolytica, Pasteurella multocida, and

Histophilus somni [31].

M. haemolytica is the bacterium most commonly recovered from BRD diagnostic samples. This opportunistic pathogen causes acute lung infections with characteristic fibrinous pneumonia. This bacterium is part of the healthy flora of cattle, but possesses virulence factors such as adhesion, capsular polysaccharide, and fimbriae which enable M. haemolytica to attach to and colonize the respiratory tract. The bacterium uses sialoglycoprotease, neuraminidase, transferrin-binding proteins, leukotoxins, lipopolysaccharide (LPS) and lipoproteins to survive in the lung and avoid the hosts innate and acquired mucosal and systemic immune defences [32]. P. multocida, another opportunist pathogen associated with BRD, has fewer virulence factors which mediate adherence and growth on the respiratory epithelium than M. haemolytica. The pathogenesis of this bacterium is mainly associated with LPS and virulence factors involved in iron acquisition. Adhesins responsible for adherence of the bacterium to cell surfaces include type IV fimbriae, OmpA (outer membrane protein), neuraminidase and filamentous hemagglutinin (FHA). These adhesins increase pathogenicity of the organisms [33–35].

H. somni is a Gram-negative opportunistic pathogen, and part of the commensal mucosal flora of cattle and sheep. In addition to its association with BRD this

6 bacterium is also associated with other clinical manefestations including pneumonia, septicemia, myocarditis, abortion, thrombotic meningitis, encephalomyelitis, and synovitis. H. somni can induce the expression of immunoglobulin binding proteins

(IgBPs) and causes endothelial cell apoptosis. H. somni uses phase variation (turning on and off expression of surface proteins) and antigen variation (altering the proteins or carbohydrates on bacteria surface membrane lipooligosaccharide (LOS)) to escape host phagocytosis [36]. Lipooligosaccharide is the major component of the outer membrane structure of Gram-negative bacteria [37,38].

1.2.5 Role of Histophilus somni in BRD

Histophilus somni is a Gram-negative member of the Pasteurellaceae family and is commonly isolated from diagnostic samples collected from cattle with BRD. H. somni can cause a multi-systemic disease known as histophilosis. Clinical signs of histophilsis include polyarthritis, pleuritis (inflammation of the membranes that surround the lungs and line the chest cavity), pericarditis (inflammation of the pericardium), and myocarditis (inflammation of the heart muscle). H. somni may also invade the vascular endothelium leading to septic vasculitis with thrombosis.

Vascular lesions occurring in the CNS may lead to ischemia, infarction and parenchymal lesions known as thromboembolic meningoencephalitis (TME) which can lead to sudden death with or without neurologic signs. Otitis (inflammation of

7 the ear) and conjunctivitis (inflammation of the mucosa of the eye and eyelid) are less frequent clinical symptoms of histophilosis. In many cases of histophilosis, clinical signs associated with the pulmonary system are the most common manifestation of infection [37,39–41]. BRD and histophilosis are world-wide problems and occur in North America, Brazil, Africa and Europe [42–44].

A variety of management practices are used to control, prevent or treat BRD or histophilosis in feedlot cattle. These include preconditioning practices, vaccination and administration of antimicrobials [45–48]. These management practices control and reduce BRD-associated morbidity and mortality in herds [26]. Vaccines against

BRD associated viruses and bacteria have not been shown to provide complete and lasting protection against infection in field conditions [49–52].

Because the efficacy of vaccination is variable (discussed in section 1.3.1), the administration of antibiotics (discussed in section 1.3.2) is the most common and frequent method used for control, prevention and treatment of BRD and histophilosis in feedlost. Decreasing susceptibility of BRD bacterial pathogens to antimicrobials has been reported in recent studies conducted in North America feedlot cattle [53–

55].

1.2.6 Pathophysiology of BRD-associated bacteria

The BRD-associated bacteria are commensal organisms inhabiting the upper respiratory tract of healthy cattle [56]. These bacteria are innocuous until the homeostasis of the respiratory tract becomes disturbed. Influencing elements such as stress or viral infection are the primary disruptors of homeostasis. The BRD- associated bacteria H. somni and P. multocida have been observed inhabiting polymicrobial biofilms [57]. Biofilms create a stable environment for bacteria to co- exist with their host by protecting the organisms against harmful agents such as immune cells antibodies or antimicrobials. Bacteria in biofilms down-regulate production of virulence factors. Stressors and viral infection can disturb the microenvironment of the biofilms, and bacteria may be sloughed from the biofilm and enter a planktonic (free-living) form. Bacteria in a planktonic form quickly convert to virulent phenotypes through overexpression of virulence factors.

Dispersal of bacteria from biofilms is a mechanism that commensal BRD-associated bacteria may use to revert to pathogenic states, move to the lower respiratory tract

(usually by inhalation) and colonize epithelial tissue [58–60]. Inhalation of aerosolized bacteria in cattle with a weakened immune system has been demonstrated as a way for M. haemolytica to reach the lower lung and initiate infection[61].

Once established in the lung, bacteria trigger inflammatory responses. The inflammation is the result of the activity of bacterial virulence factors, chemotactic attraction of immune cells, and host responses. Endotoxin released by bacterial LPS is a potent stimulator of inflammatory cytokines and incites pulmonary inflammation. The inflammation of lung tissue leads to lung injury, and bronchopneumonia, which produces the classic signs of BRD including pneumonic lesions, fever, depression, anorexia, nasal discharge, and pus in the respiratory tract

[62,63].

1.3 BRD management

1.3.1 Vaccination

Vaccination against combinations of BRD-associated viral and bacterial pathogens is routine practice in North America feedlots. More than 80% of vaccines licensed for cattle in Canada are to prevention of BRD [64]. Commercial vaccines are available in modified live, killed, or combination formulations against viral and bacterial BRD-associated pathogens. Despite positive reports about efficiency of vaccines for boosting antibodies against viral agents [65,66] to date, vaccination has shown limited and inconsistent protection against BRD-associated bacteria [67,68].

Two main reasons suggested for ineffectiveness of vaccination are 1) immune- protection may not be achieved immediately after injection, as it takes some time for

10 immunity to be established and 2) the immune system of animals in feedlots are not working well enough to produce enough antibody for immunity [69].

1.3.2 Use of antimicrobials to prevent, control and treat BRD

The use of antimicrobials for the prevention, control, and treatment of BRD in North

America feedlot cattle is common. Preventative and disease control uses are known as prophylaxis and metaphylaxis. Prophylaxis is a preventive action using medication in an individual animal that is perceived to be at high risk of developing

BRD. When multiple cattle considered at high-risk of developing respiratory disease receive antimicrobials upon arrival at the feedlot this treatment is known as metaphylaxis. The goal of metaphylaxis is to control and stop the spread of the disease. Both prophylaxis and metaphylaxis have been shown to reduce morbidities and mortalities caused by BRD. It is believed that treatment reduces or eradicates

BRD bacteria preventing proliferation and colonization of the lower respiratory tract. Antimicrobials may also be used to treat clinical illness in individual animals at feedlots. This is known as therapeutic use of antimicrobials [70–72].

1.3.3 Antimicrobials licensed for BRD in cattle

The major antimicrobials licensed for prevention, control and treatment of BRD, liver abscesses and foot-rot in feedlot cattle are listed in Table 1 [73–75].

Antimicrobials licensed for BRD belonging to different classes are penicillin and ceftiofur (β-Lactam), tulathromycin and tilmicosin (macrolide), oxytetracycline, and chlortetracycline (tetracyclines), and enrofloxacin and danofloxacin (quinolones).

Table 1. Antimicrobials licenced for use in feedlot Cattle Generic name Antibiotic class Trade name Year of Route of Purpose Disease approval administration Oxytetracycline 200 mg/ml Tetracycline LA-200 1980 Injection/ Feed P/M/T* BRD/Foot rot Penicillin Penicillin Dual-Pen 1984 Injection T General Tylosin Macrolide Tylan 1985 Injection/ Feed P Liver abscesses Ampicillin trihydrate Penicillin Polyflex 1985 Injection/Feed P/M/T General Tilmicosin Macrolide Micotil 1992 Injection/ Feed P/M/T BRD Florfenicol Amphenicol Nuflor 1996 Injection P/M/T BRD/Foot rot Ceftiofur sodium Cephalosporin Naxcel 1998 Injection T BRD Spectinomycin Aminocyclitol Trobicin 1998 Injection T BRD Enrofloxacin Fluoroquinolone Baytril100 1998 Injection T BRD Danofloxacin Fluoroquinolone Advocin 2002 Injection T BRD Ceftiofur crystalline Cephalosporin Excede 2003 Injection T BRD Oxytetracycline 300mg/ml Tetracycline Tetradure 2003 Injection/Feed P/M/T BRD Tulathromycin Macrolide Draxxin 2005 Injection P/M/T BRD Virginiamycin streptogramin Virginiamycin 2007 Feed P Liver abscesses Ceftiofur hydrochloride Cephalosporin Excenel 2008 Injection T BRD Gamithromycin Macrolide Zactran 2011 Injection T BRD Tildipirosin Macrolide Zuprevo 2012 Injection T BRD *P: Prophylaxis, M: Metaphylaxis, T: therapeutics

1.3.4 Recent regulations of antimicrobial usage in livestock in Canada and US

Canada is actively engaged in global efforts to fight AMR and has committed multisectoral support to the implementation of the World Health Organization’s

(WHO) Global Action Plan on AMR (https://www.who.int/antimicrobial- resistance/global-action-plan/en/), and to develop and implement its domestic plan to address the issue of AMR development and spread in humans, livestock and the environment [76].

As part of this pan-Canadian plan known as “Responsible use of Medically

Important Antimicrobials in Animals” [77], as of December 1st, 2018, all medically important antimicrobial (MIAs) for veterinary use are under new regulations enacted by the public health office of the Canadian government. As described by this statutory law, all MIAs must be sold and used only under prescription with the establishment of a veterinarian-client relationship. This regulation is intended to preserve effectiveness of current medicines and minimize development and spread of AMR. Some of the fundamental parts of this law are as follows:

i) Removal of growth promotion claims from MIA drug labels. This action

intendsto reduce the use of antimicrobials as growth promotants in food

animals and restrict usage to prevention and treatment purposes. The

regulation aims to prevent off-label use for the purpose of growth

promotion.

ii) Labelling of all MIAs administered in-food or in-water with a responsible

use statement. This is intended to give the public more information about

antibiotic usage and health-related controversies, and to generate increased

scrutiny regarding AMR development and health risks.

iii) Adding a “Pr” indication that the MIA drug is a prescription-only

medicine, to prevent sale and administration without veterinary oversight.

These regulations apply to food animal producers and companion animal owners and stipulate that they cannot give or sell a Pr drug in any form to someone else. This framework is intended to reduce the unregulated use of antimicrobials and to provide records of antimicrobial usage in animals.

Similar regulations for antimicrobial usage have recently been enacted by the Food and Drug Administration (FDA) in the US. The plan known as “Supporting

Antimicrobial Stewardship in Veterinary Settings” is a five-year plan which began in September 2018 [78]. As in Canada, all MIAs will be moved from over-the- counter to prescription status. This regulation eliminates the use of antimicrobials with importance in human-medicine (MIA) in food-producing animals for production purposes (growth promotion). However, these drugs still can be used under the supervision of a veterinarian for other purposes.

1.3.5 Advantages and disadvantages of AMR phenotype assays

Antimicrobial resistance is a global economic concern in human and animal health.

Resistant bacteria can survive and grow despite antimicrobial therapy and reduce available treatment options increasing the rate of morbidity and mortality [79,80].

For example it is estimated that 2 million people in the US each year suffer from the consequences of resistant bacterial infections with a cost to the health care system of $20 billion annually [81,82].

Antimicrobial susceptibility testing (AST) is a term referring to traditional microbiological methods for assessing phenotypic resistance of bacteria used in diagnostic laboratories. Most AST assays are culture-based which relies on growing colonies of bacteria as a fundamental part of the assay [83–85]. The general practice of AST is as follows: bacteria are sampled from patients or environments and put on selective or non-selective culture media such as agar (solid) or broth (liquid) media.

The goal is to grow the purest colonies as possible. The colonies are then challenged by direct exposure to antimicrobials. The ability of bacteria to resist and survive the presence of antimicrobials is recorded as resistant or susceptible phenotype.

Diagnosticians use two references for interpretation of assay results: Clinical and

Laboratory Standards Institute (CLSI) (https://clsi.org/standards/), or the European

Committee on AST (EUCAST) (https://eucast.org/). However, susceptibility

16 standards are not available for all combinations of bacteria and antimicrobials, and some bacteria may not be culturable.

The advantages of these assays are relatively low cost and reproducibility. These assays do not require extensive training or complex equipment and the results are easy to understand and interpret. The main disadvantage is the time required to perform the assay which is 36-48 hours. This is a serious limitation when assaying slow-growing bacteria such as Mycobacterium tuberculosis. Culture-required assays can also fail to produce results in cases where multiple bacteria cause co-infection.

In these cases, the bacteria cultured are assumed responsible, however several reports indicate that the bacteria detected in culture may not be responsible for clinical signs [86,87].

A commonly used molecular technique used often in diagnostic laboratories is the polymerase chain reaction (PCR) assay. PCR was developed in the 1980s and has revolutionized diagnostics in many respects. Both an advantage and disadvantage of the PCR assay is its high sensitivity. PCR assay reliability depends on multiple factors; optimal primer design, %GC content of the target template, and presence of adequate mineral and salt in the PCR reaction. The PCR primers, forward and reverse, require near 100% identity to the complementary target DNA, making their binding sensitive to the presence of single nucleotide polymorphisms within the target sequence. To ensure the results of PCR are producing the expected data, a

17 thorough validation process should always be performed to evaluate the specificity

(number of false-positive results) and sensitivity (number of false-negative results) of the assay. Designing primers to ensure that they have both high specificity and high sensitivity is not an easy task. This limitation makes PCR assays well-suited to detect the presence or absence of (resistance) genes, but it is a less appropriate method for detection of point mutations within target genes. As a result of this limitation, PCR assays are often performed prior to culture-based antimicrobial susceptibility testing of isolates [88–91].

There are other culture-independent methods used for antimicrobial susceptibility testing such as matrix-assisted laser desorption-ionization time of flight mass spectrometry (MALDI–TOF-MS) [92], fluorescence in situ hybridization (FISH)

[93], and microfluidics-based techniques [94]. Despite differences in the technology these methods use a common molecular detection method for identification and classification. The culture-independent methods can provide results in 30 minutes to

24 h. Despite the time savings these techniques the equipment needed for these platforms is expensive. The maintenance, training and required-per-run-calibration

(MALDI–TOF-MS) make this equipment too costly for many laboratories [95].

Other issues such as unspecific and random results (FISH) [93], the complexity of equipment, and difficult to interpretant outcomes (microfluidics-based techniques) also create barriers to use of these assays [96].

Molecular methods are used because they can provide speed and accuracy in detecting AMR genes, but they are often followed by traditional phenotypic assays so that sensitivity values can be provided.

1.3.5 Antibiotic-resistance in BRD-associated bacteria

Despite regulatory laws in Canada and worldwide aimed at reducing the use of antimicrobials in food-animals, antimicrobials are still commonly used to prevent, control and treat liver abscesses and BRD in feedlot cattle [13,62]. Antimicrobials are effective in reducing clinical signs of BRD and subsequently improving the productivity of cattle in feedlots. However, increasing occurrence of multi-drug resistance (MDR) has been reported in BRD-associated bacteria and may make antibiotic treatment less effective [97]. Recent studies have recorded a decrease in susceptibility to multiple antimicrobials in M. haemolytica, P. multocida, and H. somni [55]. A recent study conducted in Alberta feedlot cattle showed more than sixty-percent of M. haemolytica, and P. multocida isolates from cattle with (n =210) and without (n=107) clinical signs of BRD had a high frequency of resistance

(>70%) to the antimicrobials most commonly used for metaphylaxis, oxytetracycline and tulathromycin [98]. A similar study performed in feedlot cattle in the US showed similar rates of resistance to the same antimicrobials in the same

BRD bacteria. This study found that M. haemolytica isolates collected from the

19 lower respiratory tract of newly arrived (< 2 weeks) feedlot cattle had resistance to tulathromycin between 4 and 90% [99]. Failure of antimicrobial therapy for BRD in North American feedlot cattle would have severe economic consequences and undesirable health outcomes for the animals.

1.4 Role of horizontal gene transfer in dissemination of AMR

1.4.1 Horizontal gene transfer in bacteria

Horizontal gene transfer (HGT) is the exchange of genetic material through mobile genetic elements (MGE) between two cells with no parent-offspring relationship

[100,101]. HGT contributes to genome plasticity, adaptation and evolution in bacteria. Bacterial cells can acquire and donate new genes and subsequently develop new phenotypes via HGT of MGE. The new phenotype may enable adaptation to hostile environments and increase survival [102]. Prokaryotic cells employ three general mechanisms for HGT: 1) Transduction, the transfer of DNA between cells by bacteriophages [103], 2) Transformation, the uptake of exogenous DNA from the environment [104], and 3) Conjugation, the transfer of DNA from a donor to a recipient via physical contact through a mating apparatus [105]. Plasmids and integrative and conjugative elements (ICE) are major conjugative MGEs in bacteria.

Acquisition of new traits such as antibiotic resistance, heavy metal tolerance, virulence factors, ability to make biofilms, and genes encoding new metabolic

20 capabilities have been reported to be transferred between various bacterial species by ICEs [106,107].

1.4.2 Integrative conjugative elements (ICE)

ICEs are a conjugative type of mobile genetic element (MGE). They can move horizontally between two cells autonomously. ICEs are integrated into a bacterial host chromosome and propagate passively during chromosomal replication and cell division. Expression of ICE genes leads to excision of the element from the host chromosome followed by horizontal transfer to an appropriate recipient cell and subsequent reintegration into the new host chromosome. The horizontal movement is mediated by a series of specific genes encoded on the ICE. The structural genes are needed for integration, excision, transfer, and genome regulation and together comprise the integration and conjugation machinery complex (ICMC) of ICEs

[108,109].

1.4.3 ICE life cycle

The ICE life cycle is summarized in figure 1. Under normal conditions, most ICEs integrate into the host chromosome, and their genes are not actively expressed. In this phase, the ICE propagates by cell division of the host through vertical transmission. Upon exposure to an external stressor which may be life-threatening

21 to the host cell (specific cellular conditions), or perhaps stochastically, the ICMC genes of the ICE are expressed and initiate HGT [108]. Excision from the host chromosome and reintegration into the recipient chromosome can be described in four steps.

i) Integration into the chromosome:

All ICEs encode for an integrase/recombinase enzyme (Int). The Int gene and its accessory genes are required for both integration and excision of ICEs. The insertion site of the ICE on the host chromosome has been shown to have a regulatory role in determining the transfer frequency of the element. Most of the identified Int in ICEs are members of the tyrosine recombinase family and are site-specific double- stranded DNA recombinases. These type of recombinases are very energy efficient and do not require high-energy compounds such as ATP for activity [110–112]. The presence of tyrosine recombinase on the ICE means that before integration into the host chromosome, the ICE must be double-stranded (ds). The integrase promotes the recombination between identical sequences on the host chromosome (known as attB) and the ICE (known as attP) [113]. Most of these integrases direct ICE into tRNA genes. tRNA genes are distributed in multiple copies throughout the genome, which makes them suitable targets for integration because mobile elements can integrate into the genome with low risk of compromising the integrity of protein-coding genes

22 and crippling a crucial function of the cell [114]. Most bacterial species have different alleles (motifs) for specific tRNA, but ICEs tend to integrate into only one of these motifs. The reason for this molecular behavior is the preferential nature of integrases to recombine with the conserved sequences of attB and attP sites. Two exceptions are ICEclc B13 identified in Pseudomonas knackmussii str. B13 [115–

117], which can insert into either allele of tRNA-Gly genes, and PAPI-1 reported in

Pseudomonas aeruginosa that can integrate into either gene (allele) of tRNA-Lys

[118]. Not all characterized ICEs use tyrosine-recombinase integrases. For example, the ICE reported from Streptococcus agalactiae, uses a DDE transposase. This ICE integrates into a promotor of an RNA polymerase factor [119]. Another example is the ICE identified in Clostridium difficile which uses a serine recombinase that is not site-specific in terms of integration [120,121].

ii) Excision from the host chromosome:

To transfer to a new host, the integrated ICE must excise from the host chromosome and form an extrachromosomal double-stranded (ds) circular DNA molecule.

Excision of ICE is also mediated by Int activities but proceeds in the reverse direction of insertion through the recombination of the left and right attachment sites sequences attR and attL. Attachment sites are residues of the normal (tRNA) gene that have been interrupted by the ICE DNA sequence [122]. Int-mediated excision

23 requires small DNA-binding accessory proteins known as recombination directionality factors (RDF). RDFs are small positively charged DNA binding proteins that bias the DNA Int-mediate recombinase activity toward excision rather than integration. Mutations within RDF coding regions reduce the excision frequency of ICE [123,124]. For example, members of the SXT ICE family, found in Vibrio cholerae, do not need RDF for excision, but their excision frequency in the presence of RDFs increases 1000-fold [125]. This finding is an indication that RDFs have a greater impact on the frequency of excision than the initiation of excision.

iii) Maintenance of the excised ICE:

There is always a chance for loss of integrity of the extrachromosomal ICE. If the host goes through chromosome replication or cell division, the ICE may not be transmitted to progeny. Two significant mechanisms preventing the loss of ICE after excision are ICE-encoded homologous soj proteins or the function of toxin-antitoxin pairs [126–129]. During excision of the ICE from the chromosome genes for these two functional units are upregulated to preserve the vulnerable ICE. Sporulation initiation inhibitor protein (soj) is a DNA replication regulator which has been reported as a gene necessary for plasmid maintenance [128,130] and proper chromosome partitioning in bacteria [131]. Expression of this protein occurs only when ICE are excised and circularized. The precise action of soj proteins remains to

24 be determined. It is proposed that soj proteins are involved in segregation of bacterial chromosomes. A study using ICE in Pseudomonas aeruginosa showed that with lack of soj proteins (in soj protein mutated strains), ICE is lost from all cells [118]. Toxin– antitoxin (TA) systems are pairs of genes linked together and found in almost all bacterial species. They function in DNA maintenance and bacterial survival and organisms have them in multiple copies on their chromosome. In mobile genetic elements such as plasmid and ICEs, their role is to ensure that only progenies which inherit the mobile genetic element survive. TA systems encode for a toxin protein which is capable of killing the cell, and a corresponding antitoxin that deactivates the toxin protein. TA system biological function is associated with genome stabilization [132], stress tolerance [133], protection against phage-induce mutation

[134] and ICE maintenance [126]. The TA gene pair recognized in ICE maintenance while the element is excided from the chromosome are mosA and mosT. Presence of TA pair mosA and mosT on ICE in Vibrio cholerae caused the loss of ICE to be reduced by 10-fold, and a mutation of TA genes (deletion of 8 genes) increased the number of colonies that lacked the ICE on their genome compared to wild types.

The presence of ICE in mutants was one cell in every 104 while in wild type this rate was one cell in every 107 [135].

iv) Conjugative transfer:

Because many of the proteins involved in DNA transfer are similar between ICE and plasmids, the model of conjugative transfer by ICE is also relevant to the transfer of plasmids. A relaxase needs to covalently bind to dsDNA and nick it at the origin of transfer (oriT) to initiate conjugal transfer. The nicked DNA then undergoes rolling circle replication [136,137]. The relaxase remains attached to the single-stranded

DNA (ssDNA), while with the assistance of coupling protein, the ssDNA translocates to the mating pore to be transferred to the recipient. Most of the identified oriT sequences are located upstream of the gene coding for relaxase and can be identified by their characteristic inverted repeat sequence [138]. After the ssDNA is transferred to the recipient cell, it serves as a template for host cell DNA polymerase to reconstruct the dsDNA circular molecule of the ICE. Some ICEs may undertake a replicative transition form, which goes through a replication process that generates multiple copies before insertion into the recipient chromosome [139,140].

In most of the identified ICEs in Gram-negative bacteria, the conjugal apparatus that provides the physical connection between the host and recipient is an ICE-encoded secretion system. In silico analysis has identified that the secretion system is a type

IV secretion system (T4SS). Little is known about the conjugative system in Gram- positive bacteria nor the secretion system they may employ. In Gram-positive

26 bacteria, genes proposed to have a secretion function are not related to T4SS genes

[141,142].

Figure 1: Schematic of an integrative and conjugative element life cycle

1.4.4 ICE in BRD-associated bacteria and their cargo genes

ICEs usually carry a variety of genes that have no function in the life cycle of ICE, neither in integration nor conjugation. These genes are known as accessory or cargo genes and in some instances provide phenotypic advantages to the host. Genes for antimicrobial resistance are the most common examples of cargo genes reported in

ICEs [113]. ICEpmu1 reported in P. multocida, and ICEMh1, identified in M.

27 haemolytica harbor 12 and five antimicrobial-resistant genes, respectively

[143,144]. Although, the role and presence of ICE in antibiotic-resistant H. somni has not been previously described and the genome of H. somni and mobile genetic elements associated with its chromosome have not been characterized [145].

1.5 Conclusion

Several studies in feedlot cattle have shown an increase in the pathogenicity profile of H. somni in Canada over time. A significant increase in antimicrobial resistance has been documented [55,97,98,146]. Despite comparative genomic and molecular studies on other members of the Pasteurellaceae family little is known about the H. somni genome nor any MGEs that it may contain. A study conducted a decade ago compared the genome of two strains of H. somni, 2336 and 129Pt, and is one of the few studies to describe any mobile genetic elements in H. somni [145]. My thesis examined the whole genomes of 19 strains of H. somni collected from Canadian and

American feedlot cattle. This study used WGS of American cattle isolates of H. somni published by USDA for comparative genomics, MGE identification and identification of AMR genes and virulence factors. The American H. somni WGS were compared to Canadian H. somni WGS. All post-sequencing procedures required to create a bioinformatics dataset were completed in this study. The

28 completed dataset was used for post sequencing bioinformatics. Chapter 2 describes the methods used for creating and publishing the Canadian dataset of H. somni WGS.

A full description of methods is contained in the first published manuscript. The second part of the chapter consists of a methods paper draft intended to be submitted as a manuscript. This manuscript demonstrates how to extract information regarding antimicrobial resistance genes through free accessible bioinformatics pipelines. By employing comparative genomic analysis this research identified and characterized a variety of different mobile genetic elements including ICEs present in the genome of H. somni. Details of the structure and function of the ICE, the arrangement and structure of ICMC genes, the gene content of ICE (core and cargo genes), similarity and differences between Ice and previously identified ICEs, and the family of ICE identified in H. somni are discussed in chapter 3.

1.6 Objectives, specific aims and methods

The objectives and goals of this study as follows:

i) Creation of a bioinformatics dataset of Canadian isolates of H. somni using

whole-genome sequences. The aim was to provide informative, and detail-

rich datasets of H. somni genomes which could be used as a public

resource. To have a well-organized dataset, the following steps were taken:

➢ A complete bioinformatics dataset of 12 Canadian H. somni strains was

created which included raw whole-genome sequences (FASTQ files), and

their associated meta-data, assembled and annotated whole genome

sequences.

➢ The number of ambiguous and hypothetical proteins on the genome was

minimized, and annotation improved by using functional and structural

bioinformatics including protein modelling, protein-domain identification,

protein-family categorization and biochemical pathway assessment.

➢ The final version of multi-layered in silico analysis was submitted to

several bioinformatics databases for publication in order to make them

fully accessible for public use.

ii) Mobile genetic elements identification and classification

The Canadian dataset created as the first objective contained 12 Canadian

isolates and the 7 American isolate WGS published by USDA were used

for identification MGEs in the genome of H. somni. To satisfy the specific

aims of this objective, the following steps were taken:

➢ The WGS were examined to determine if plasmids were present in the

genome.

➢ Other mobile genetic elements in the genomes of H. somni were identified

such as ICEs, IMEs, prophages, and transposable elements.

➢ Comparative genomics was used to classify types of MGEs identified.

iii) Annotate and characterize the genes present in identified ICEs

To examine the ICEs, the following steps were taken:

➢ The core (structural) genes of the ICE and the specific subtypes

responsible for independent horizontal movement were identified.

➢ The integration position (recombination motif), and the gene in which

ICEs were inserted into the chromosome of H. somni were identified.

➢ The gene arrangements of the ICEs - the genomic synteny - was

compared to previously identified ICEs present in the WGS of other

related bacterial species.

➢ The family of the ICE in H. somni was identified and both the sequence

and synteny of the ICE sequences were compared to other members

within the ICE-family to determine relatedness.

31 iv) Identification of cargo genes present in the ICEs

The following steps ere taken to identify and classify cargo genes in the

ICEs identified in Canadian and American H. somni strains:

➢ The presence of genes encoding potential virulence factors was

determined

➢ Antimicrobial resistance, and metal tolerance genes were identified.

➢ The biochemical pathways of all ICE-coding genes were assessed to

determine if these genes might support alternative biochemical

pathways (potential virulence genes).

Chapter two: Creation of a binformatics dataset and identification of antibiotic resistance genes in the genome of Histophilus somni strains

2.1 Draft Genome Sequences of 12 Histophilus somni Strains Isolated from Feedlot Cattle in Alberta, Canada

The manuscript has been published in “Microbiology Resource Announcement”.

DOI: 10.1128/MRA.00864-19.

2.1.1 Authors and affiliations

Mohammad Mostafa Nazari,a Krishna Bhatt,a Andrew Potter,b Karen Liljebjelkea a) Faculty of Veterinary Medicine, University of Calgary, Department of

Ecosystem and Public Health, University of Calgary, AB, Canada. b) Vaccine and Infectious Disease Organization-International Vaccine Centre,

University of Saskatchewan, Saskatoon, SK, Canada.

2.1.2 Background

Histophilus somni is a Gram-negative opportunistic pathogen associated with respiratory disease in cattle. Here, we report the draft genome sequences of 12

Histophilus somni strains isolated from feedlot cattle in Alberta, Canada, which were diagnosed with respiratory disease.

2.1.3 Announcement

Histophilus somni, formerly Haemophilus somnus, is a member of the family

Pasteurellaceae. Histophilus somni, along with two other members of

Pasteurellaceae (Pasteurella multocida and Mannheimia haemolytica), is associated with bovine respiratory disease (BRD) complex [147]. An opportunistic pathogen, H. somni is also responsible for a multisystemic disease called histophilosis in cattle, sheep, and goats [148–150]. A better understanding of the genome of H. somni, including antimicrobial resistance and horizontal gene transfer, is needed to understand BRD in feedlot cattle. The raw FASTQ files of 12 H. somni whole-genome sequences were obtained from the Vaccine and Infectious Disease

Organization–International Vaccine Centre (VIDO-InterVac), Saskatoon, Canada.

These short-read whole genomes were previously aligned against a reference genome for the detection of single nucleotide polymorphisms and insertion and deletion sites [151], as well as for prediction of protein-coding regions [152]. For

34 this work, the genomes were assembled de novo and annotated using the methods described below, and this information was deposited in NCBI GenBank.

These genome sequences originate from six H. somni strains isolated from the heart and lung tissue and synovial fluid of feedlot calves between 2012 and 2013 and from six H. somni strains isolated from feedlot cattle lung tissue in the 1980s [151]. Amies transport medium with charcoal was used to collect and transport samples [151].

Isolates were cultured on tryptic soy agar with 5% sheep blood and incubated for 36 to 48 h at 37°C in a 5% CO2 atmosphere [151–153]. Genomic DNA was extracted with a Genomic-tip (Qiagen, Toronto, Ontario, Canada), as previously described

[151]. Genomic DNA libraries were prepared using a Nextera XT library prep kit

(Illumina, San Diego, CA, USA), and whole-genome sequencing was done using the

Illumina MiSeq 500 platform, with a paired-end 2 × 150-bp read type, as previously described [151]. FastQC v1.0.0

(https://www.bioinformatics.babraham.ac.uk/projects/fastqc) and QUAST v5.0.2

(http://quast.sourceforge.net/quast) were used for quality assessment and trimming of sequenced files before and after assembly, respectively [154,155]. Default parameters were used for all in silico software, unless otherwise specified. Quality control and DNA trimming of the raw FASTQ files included removing low-quality base pairs at each read terminal (quality [Q] score, <20), as well as reads of less than

50 nucleotide base pairs, that were >10% Ns, and those with a >15-bp overlapping

35 sequence with the Illumina adaptors. FASTQ files with a Q score of at least 98% were used for further in silico analysis (appendix figures 1 and 2). The genomes were assembled de novo using SPAdes v3.13.0 (http://cab.spbu.ru/software/spades/)

[156]. The final annotation of sequences was performed using the NCBI Prokaryotic

Genome Annotation Pipeline (PGAP)

(https://www.ncbi.nlm.nih.gov/genome/annotation_prok/) with default thresholds

[157].

2.1.4 Data availability

The genome sequences and associated data for 12 H. somni strains were deposited in NCBI GenBank, the European Nucleotide Archive (ENA), and the DNA Data

Bank of Japan (DDBJ), under the accession numbers provided in Table 2.

Table 2. Characteristics of and accession numbers for H. somni genomes.

NCBI GenBank Average European DNA Data G+C length of Total number Genome Number of RNA genes Number Isolate Accession BioSample BioProject SRA Nucleotide Bank of content MGE# raw reads of reads Size (bp) of Genes Number ID ID Archive Japan (%) (bp) rRNA tRNA ncRNA* NZ_SKBV0 SAMN11042 PRJNA525 SRR9761 SRX65187 KLM-01 SRP216147 36.9 150 387,096,900 2,361,113 5 48 4 2,283 - 0000000 644 156 912 14 NZ_SMNW SAMN11094 PRJNA526 SRR9761 SRX65329 KLM-03 SRP216148 37.3 150 459,494,700 2,229,261 4 44 4 2,078 + 00000000 176 281 918 89 NZ_SNRV0 SAMN11132 PRJNA527 SRR9776 SRX65396 KLM-04 SRP216160 37.4 150 408,072,300 2,271,789 4 44 4 2,151 + 0000000 143 266 588 41 NZ_SOYZ0 SAMN11191 PRJNA528 SRR9824 SRX658159 KLM-06 SRP216238 36.9 150 411,876,300 2,363,734 5 48 4 2,286 + 0000000 546 478 922 7 NZ_SPKI00 SAMN11264 PRJNA529 SRR9824 SRX658160 KLM-07 SRP216239 37.1 150 457,396,500 2,092,744 4 44 4 1,909 - 000000 820 326 930 5 NZ_SSCM0 SAMN11360 PRJNA531 SRR9824 SRX658160 KLM-08 SRP216240 37.2 150 420,674,400 2,149,571 7 44 4 1,990 - 0000000 228 494 931 6 NZ_SSCN00 SAMN11360 PRJNA531 SRR9824 SRX658163 KLM-09 SRP216242 37.1 150 296,814,900 2,079,435 4 42 4 1,900 - 000000 446 503 960 5 NZ_SSCQ00 SAMN11360 PRJNA531 SRR9825 SRX658181 KLM-10 SRP216251 36.7 150 413,164,800 2,233,495 4 46 4 2,119 - 000000 900 509 144 3 NZ_SSCO00 SAMN11360 PRJNA531 SRR9825 SRX658182 KLM-11 SRP216252 37.1 150 3741,13,800 2,090,388 4 44 4 1,906 - 000000 902 510 155 4 NZ_SSCP00 SAMN11360 PRJNA531 SRR9825 SRX658215 KLM-12 SRP216254 37.2 150 435,419,400 2,128,480 4 45 4 1,974 + 000000 904 512 483 2 NZ_SSCR00 SAMN11372 PRJNA531 SRR9825 SRX658219 KLM-13 SRP216256 37.0 150 429,169,200 2,406,339 4 47 4 2,339 - 000000 139 670 531 9 NZ_SUKB0 SAMN11475 PRJNA534 SRR9825 SRX658224 KLM-14 SRP216257 37.2 150 424,964,700 2,228,888 4 44 4 2,073 + 0000000 348 002 577 5 *non-coding RNA, # Mobile Genetic Element

Chapter three: In silico analysis of the WGS of a multidrug-resistant

Histophilus somni strain collected from feedlot cattle in Alberta, Canada

The draft manuscript is prepared for submission to the journal of global antimicrobial resistance.

3.1 Authors and affiliations

Mohammad Mostafa Nazaria, Timothy McAllisterb, Rahat Zaheerb Karen

Liljebjelkea aFaculty of Veterinary Medicine, University of Calgary, Department of Ecosystem and Public Health, University of Calgary, AB, Canada. b Lethbridge Research Centre, Agriculture and Agri-Food Canada, Lethbridge,

AB, Canada

3.2 Introduction

Bovine respiratory disease (BRD) is one of the most prevalent and costly infectious diseases in North America feedlot cattle. Histophilus somni is one of the major bacterial contributors to BRD, and can also produce a lethal multisystemic infectious syndrome, known as histophilosis [158]. Antimicrobials are used to prevent or treat histophilosis and BRD in Canada and the USA. Recently, multi-drug resistance

(MDR) in BRD pathogens and an increase in treatment failures have been reported in North America. In this study, we describe the genomic characteristics of an MDR

H. somni strain (UOC-KLM-ATR-014) isolated from diagnostic samples from a cow with BRD in a feedlot in Alberta, Canada. On the chromosome of this isolate, an

ICE was identified carrying six antimicrobial genes (ARGs), one metal tolerance gene, and a potential virulence gene. The ICE in H. somni was closely related to

ICEs present in Pasteruella multocida, Mannheimia haemolytica, Haemophilus influenzae, and Haemophilus parainfluenzae, and other members of the

Pasteurellaceae family.

3.3 Methods

Histophilus somni strain UOC-KLM-ATR-014, was used for this study. The strain belongs to a dataset made from 12 whole-genome sequences of H. somni isolates collected from Alberta feedlot cattle with BRD [159]. The bacterial strain was

39 isolated from tissue samples (lung/heart) from a feedlot cow which died from BRD.

Genomic DNA was extracted from bacterial cells using a Genomic-Tip DNA extraction kit (Qiagen Canada, Toronto, Ontario) as per manufacturer instructions.

Concentration and purity of extracted DNA were assessed using an ND-1000

UV/Vis Nanodrop spectrophotometer (ThermoScientific, Waltham, USA). Genomic

DNA libraries were prepared using a Nextera XT library preparation kit (Illumina,

San Diego, CA, USA) according to manufacturer instructions. Whole-genome sequencing (WGS) was completed using the Illumina MiSeq 500 platform (Illumina,

San Diego, USA), with a paired-end 2 × 150-bp read type at Cofactor Genomics, St.

Louis, Missouri, USA. Default parameters were used for all in silico software unless otherwise specified. The online tools FastQC v 1.0.0

(https://www.bioinformatics.babraham.ac.uk/projects/fastqc), and QUAST v 5.0.2

(https://cab.spbru.ru) were used for quality assessment of reads before and after assembly, respectively. The tool Trimmomatic v 0.39

(http://www.usadellab.org/cms/?page=trimmomatic) was used for Illumina sequence trimming and adapter clipping. The genome was assembled de novo using

SOAPdenovo v 2.0 (https://github.com/aquaskyline/SOAPdenovo2) and sequences were annotated using the NCBI prokaryotic genome annotation pipeline

(https://www.ncbi.nlm.nih.gov/genome/annotation_prok/).

Antimicrobial-resistant genes were identified using the annotation tools of the comprehensive antibiotic resistance database (CARD) (https://card.mcmaster.ca/).

The nucleotide and protein (amino acid) sequences of identified AMR coding genes were examined individually using the online tools NCBI BLASTn

(https://blast.ncbi.nlm.nih.gov/Blast.cgi) and UniProt (https://www.uniprot.org/), respectively. Initial identification of potential AMR genes was followed by a verification step employing the protein structure modelling tool in the

SWISS_MODEL pipeline (https://swissmodel.expasy.org/). The refence protein for each of the potential AMR genes extracted from the protein data bank

(https://www.rcsb.org/) was used to model the protein encoded by the potential

AMR genes present in the ICE. The goal of protein modelling was to identify potential changes in residues compared to the reference proteins. Potential virulence factors were identified and classified using the online tool VFanalyzer

(http://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi?func=VFanalyzer). The genome was probed for plasmid-associated gene sequences using the tool Recycler

(https://github.com/Shamir-Lab/Recycler). Prophages and mobile genetics elements

(MGE) including integrative and conjugative elements (ICE) were identified in the

WGS using Virsorter (https://github.com/simroux/VirSorter) and VRprofile

(https://tool-mml.sjtu.edu.cn/STEP/STEP_VR.html), respectively. The assembled draft genome of the strain was visualized using the tool CGView - Circular Genome

Viewer (http://wishart.biology.ualberta.ca/cgview/) and results of CGView were assessed using IslandViewer 4 (https://www.pathogenomics.sfu.ca/islandviewer) with the goal to visualize the relative positioning of identified MGEs within the genome.

The family of the identified ICE was determined using MultiGeneBlast v 1.1.13

(http://multigeneblast.sourceforge.net/usage.html) to assess the ICE genomic architecture and for comparison of synteny to the genomic arrangements of previously reported ICEs extracted from the repository of the ICEberg database

(https://db-mml.sjtu.edu.cn/ICEberg/). The tool MAUVE v 2.4.0

(https://darlinglab.org/mauve/mauve.html) was used to align and visualize the genetic sequences of similar ICEs.

3.4 Results

The assembled draft genome of bacterial strain “UOC-KLM-ATR-014”, assigned

NCBI reference sequence number NZ_CP042993.1 was 2183545 bp in length, with a GC content of 37.4% (https://www.ncbi.nlm.nih.gov/nuccore/NZ_CP042993.1).

The draft genome contained 2053 genes (protein coding sequences), and 68 RNA genes (16 rRNA, 48 tRNA, and four ncRNA). The genome harboured 59 genes for potential virulence factors: two coding for adhesions, five coding for type IV pili, thirty-three associated with endotoxin activity, three coding for exopolysaccharides

(immune system evasion), fifteen genes associated with iron-uptake (iron transport locus, and heme biosynthesis), and a gene located on the identified ICE which was identified as a protein involved in hemoglobin and hemoglobin-haptoglobin binding

– a heme utilization protein. A comparison of virulence genes identified in

Haemophilus spp, and Histophilus spp, genomes is provided in Appendix Table 1.

Three prophages and one ICE were found integrated into the chromosome of the study strain of H. somni (appendix figure 3). No plasmid sequences were identified in the whole genome sequence of H. somni isolates in the database used in this study.

Prophages on the chromosome were identified as Mannheimia haemolytica bacteriophage vB_MhS_1152AP2 (Mannheimia spp. virus) and two copies of

Haemophilus spp. specific virus, PHAGE_Haemop_SuMu_NC_019455. The H. somni ICE (GenBank accession number MN401320.1) had a length of 72914 bp and a GC content slightly higher than the host (41.8% versus 39%). The ICE was integrated into a tRNA Leu gene, in nucleotide position 687500…760413 (appendix figure 4) (https://www.ncbi.nlm.nih.gov/nuccore/MN401320.1). The ICE encoded for 79 proteins, including a heavy metal tolerance gene (multi-copper oxidase) and six ARGs: tet(H), floR, Sul2/folP, APH (3'')-Ib, APH (6)-Id, and APH (3')-Ia. The summary of methods used to identify and predict the function of AMR genes are shown in Table 3. All AMR genes were found in the ICE sequence (appendix figure

5). The AMR genes may confer phenotypic resistance to tetracyclines, phenicols,

43 sulphonamides, and aminoglycosides. The resistance to different classes of antimicrobials potentially conferred by these ARGs is described in the context of feedlot production in the sections below.

1. Tetracycline efflux MFS transporter tetHR

The AMR gene tet(H) confers resistance to tetracycline class antimicrobials. The antimicrobials oxytetracycline and chlortetracycline are presently commonly used in treatment of feedlot cattle. The frequency of use of these antimicrobials in terms of total tons of antimicrobials used in US feedlot cattle is reported to be 17.4% and

20.6% respectively [160]. In Canadian feedlots the frequency of resistance to tetracycline class antimicrobials among H. somni isolates appears to be rising, with tetracycline resistance reported to be %70 in 2017 [98] as compared to a resistance frequency of %50 reported in 2009 [53].

2. Chloramphenicol/florfenicol efflux MFS transporter floR

The florfenicol/chloramphenicol resistance gene floR was located within the ICE sequence of the H. somni strain. Florfenicol is a fluorinated structural analogue of thiamphenicol. Both florfenicol and chloramphenicol are approved for exclusive veterinary use [161]. The phenicol class antimicrobial florfenicol is one the most frequently used drugs for treatment of BRD in calves in the US (%54 of total

44 antimicrobial use by weight) and Canada [162]. The phenicols are used only for individual animal treatment. Florfenicol-resistant H. somni declined by nine percent between years 2000 to 2009. Forfenicol resistance represented only 1.6% of total antimicrobial resistance reported in 2017 [53,98]. The protein structure encoded by the floR gene identified within the ICE was modelled. The modelled protein structure showed that this gene sequence may not produce a functional protein because the protein did not have high-level identity of 3D structural alignment when compared with the structure of a reference protein (z-score of -4). When using the I-

Tasser pipeline a Z-score = 0 indicates good agreement, and a Z-score >1 indicates a confident alignment between the reference protein structure and modelled protein structure of similar size. Scores of (Z = -4.0) or below are an indication of protein models with low identity to reference proteins [163]. Gene mutations such as base pair deletions or frameshift might account for changes in the reading frame of the potential floR gene identified in the ICE sequence. Changes in the coding sequence of the potential were floR gene were confirmed via pair-wise alignment of the sequences of the potential floR gene identified in the ICE and the reference floR gene. The pair-wise alignment verified the result of protein modelling by showing various gaps and misplaced amino acids in the floR located within the ICE

(Appendix figure 6). No floR genes were identified within the ICE sequences in

American origin H. somni strains. The AMR gene, “elongation factor Tu (EF-Tu)”

45 was identified within American origin H. somni ICE but not within Canadian origin

H. somni ICE. The product of this gene provides resistance to the elfamycin-type antimicrobials pulvomycin and efrotomycin, which are currently used as growth- promotants in US feedlots [164,165]. The use of elfamycin-type antimicrobials is not common in Canada.

3. Sulfonamide-resistance dihydropteroate synthase sul2

The sulfonamide resistance gene sul2 was identified within the Canadian ICE sequences [166]. Trimethoprim-sulfadoxine and sulfamethazine, sulfonamide-class antimicrobials, are licensed for BRD treatment [167]. The frequency of resistance to sulfamethazine is reported to be higher in H. somni (81.8%) than found in P. multocida (78.2%) or M. haemolytica (76.1%) [146].

4. Aminoglycoside O-phosphotransferase APH(3'')-Ib, APH(6)-Id, and

APH(3')-Ia

The genes APH(3”)-Ib, APH(6)-Id, and APH(3’’)-Ia encode for aminoglycoside O- phosphotransferase enzymes which confer aminoglycoside drug resistance

[168,169]. Aminoglycosides were frequently used in the 1970s in feedlot cattle for treatment and control of BRD [170]. The use of this class of antimicrobials was discontinued in feedlot cattle after the Academy of Veterinary Consultants (AVC)

46 released a position statement in 1993 [171]. Use of this group of antimicrobials in veterinary medicine has declined since the 70s due to resistance, especially to older drugs in the class, and due to problems with renal toxicity. Aminoglycosides remain important for treatment of serious Gram-negative infections in animals such as enteritis caused by E. coli and Salmonella spp [172,173].

3.5 Discussion

The occurrence of antimicrobial resistant bacterial infections that are difficult to treat are increasing worldwide and have the potential for causing a global health crisis.

The World Economic Forum global risks report 2019 has declared that antimicrobial resistance is one of the greatest threats to human health [174]. Because the incidence of antimicrobial resistant infections is increasing worldwide the potential for untreatable infections may become reality. It is estimated that in Europe 25,000 people die each year due to multidrug-resistant (MDR) bacterial infections, and the cost to the European Union economy is estimated €1.5 billion annually [175]. In the

United States more than two million people are diagnosed with resistant bacterial infections annually, with 23,000 deaths as a direct result [176]. Adding to the complicated problem of AMR in human and animal health the lack of development of new antimicrobial drugs and improvement/modification of current drugs.

Increasing antimicrobial resistance is a serious problem in both human and animal

47 medicine. Antimicrobials are important tools in food animal production.

Antimicrobials are used predominantly for prevention and treatment of food animal disease, but are also used for the purpose of growth promotion [177]. Due to the variety of uses of antimicrobials in food animals, these uses are under increasing scrutiny because of the potential for creation and dissemination of AMR to humans and the environment. The mechanisms of AMR development and dissemination in bacteria is complex. The development of AMR in bacterial populations is based on

Darwinian selection of microorganisms with enhanced microbial fitness (chance of survival) which acquire and express AMR genes when exposed to antimicrobials.

What makes bacterial genetics unique is that they can both share AMR genes with their progeny (vertical transfer) and exchange them with other strains (horizontal transfer) [178–180]. Acquisition of foreign DNA material through pathways of horizontal gene transfer (HGT) is one the most important mechanisms for sharing

AMR genes between bacteria [181,182]. Mobile genetic elements carrying AMR genes can be shared across bacterial species or strains. Horizontal movement of

MGEs between the BRD-associated bacteria P. multocida and M. haemolytica has been hypothesized to be responsible for resistance gene transmission among BRD pathogens [144,183].

The ICE identified in H. somni were found to be carrying AMR genes for antimicrobials which are not commonly used in feedlot cattle. The floR gene coding

48 for chloramphenicol/florfenicol resistance, and three genes coding for aminoglycoside-altering enzymes, APH(3'')-Ib, APH(6)-Id, and APH(3')-Ia were identified within the H. somni ICE sequence, but these antimicrobials are not commonly used in feedlot cattle in Canada.

Linkage between sulfonamide, streptomycin (aminoglycoside) and chloramphenicol resistance genes in P. multocida and M. haemolytica has been reported [184], and another study identified linkage between tetracycline and sulfonamide resistance genes in P. multocida [185]. This study did not identify plasmids in the WGS of H. somni strains, but linkage of a similar group of AMR genes was identified in ICE present in the strains. It is possible that an AMR-bearing plasmid was purged from H. somni at some time and the AMR genes were captured by ICE through recombination events.

Plasmids are circular double stranded extrachromosomal DNA molecules which can replicate independently using the host cell resources. The acquisition of a plasmid by a bacterium may come with a fitness cost (ability to replicate and survive in a competitive environment) [186,187]. Because of fitness cost plasmids encoding advantageous traits such as antimicrobial resistance may be purged from the bacterial population in the absence of positive selection pressure. The effects of positive selection on the population may lead to beneficial plasmid genes moving

49 into the bacterial chromosome via recombination events resulting in the elimination of a more costly plasmid [188–190].

A plasmid in P. multocida and M. haemolytica has been reported which carries a similar group of AMR genes to the linked AMR genes identified in the H. somni

ICE described in this study. A similar plasmid has not been found in H. somni.

Movement of plasmids between P. multocida, M. haemolytica and H. somni is theoretically possible because these organisms are closely related and are cohabitants of biofilms in the upper respiratory tract of cattle. There are no WGS of

P. multocida and M. haemolytica strains carrying AMR plasmids (2001) available, so conducting comparative genomics between ICE identified in H. somni and the

AMR plasmids identified in other BRD pathogens. Due to the poor quality of H. somni WGS published 12 years ago it was not possible to investigate the presence of AMR plasmids nor the acquisition and evolution of ICE in H. somni.

Use of comparative genomics determined that the ICE found in H. somni belonged to the ICEHin1056 ICE-family. The ICEHin1056 family has eight members identified to-date, six from strains of Haemophilus influenzae, one found in a strain of Haemophilus parainfluenzae, and one identified in Actinobacillus pleuropneumoniae [191–193]. H. influenzae and H. parainfluenzae are Gram- negative inhabitants of the human upper respiratory tract. Similar to the BRD pathogens in cattle, when the immune system is compromised these bacteria can

50 infiltrate the disrupted mucosal barrier and spread to other organs leading to clinical signs such as meningitis, and epiglottitis [194]. H. influenzae is responsible for almost 12% of community-acquired pneumonias and the treatment guideline established for management of this infectious problem by the American Thoracic

Society and the Infectious Disease Society of America [195]. Third-generation cephalosporins such as ceftriaxone, and cefotaxime, and cefuroxime are primary choices for treatment of H. influenzae and H. parainfluenzae infections [194].

Amoxicillin-clavulanate, cephalosporins (beta-lactams), macrolide antimicrobials azithromycin and clarithromycin, vancomycin and fluoroquinolones are the empirical antimicrobial choices recommended by the Infectious Disease Society of

America for treatment of meningitis caused by H. influenzae [195]. The American

Thoracic Society and the Infectious Disease Society of America recommend azithromycin (macrolide), clarithromycin (macrolide), and doxycycline

(tetracycline) if no antimicrobial therapy had been administered in the past 3 months.

If antimicrobial therapy had been administered in the past 3 months the treatment recommendations are levofloxacin, gatifloxacin, gemifloxacin, or moxifloxacin, all fluoroquinolones as single agents or in combination with macrolide-β-lactam therapy [196,197].

A. pleuropneumoniae is a Gram-negative bacteria, and the causative agent of porcine pleuropneumonia, one of the most deadly respiratory diseases in pigs worldwide

[198,199]. Similar to vaccines against H. somni and other BRD-associated bacteria, vaccines against A. pleuropneumoniae do not provide strong and lasting immunity

[200,201]. Antimicrobials such as trimethoprim/sulfonamide, cephalosporins, amoxicillin-clavulanic acid, fluoroquinolones, and tetracycline are most commonly used for treatment of A. pleuropneumoniae infections. Increasing resistance to these antimicrobials is reported in A. pleuropneumoniae strains [202–204].

The ICE reported from H. influenzae, H. parainfluenzae and A. pleuropneumoniae are named ICEHin1056 ICEHpaT3T1, ICEHpa8f, ICEHin299, ICEhinR2866,

ICEHinB, ICEHin86-28NP, and ICEApl1. Each of these ICE carry only a tet

B tetracycline-resistant gene in their DNA sequence. Other AMR genes coding for resistance to β-lactamases, fluoroquinolone and elfamycin (EF-Tu mutants conferring resistance to Pulvomycin) are located on the chromosome of these bacteria outside of the ICE-sequence. Unlike the other ICEHin1056 ICE-members which harbor only tetB, the ICE of H. somni carries multiple AMR genes: tet(H),

Sul2/folP, APH(3”)-Ib, APH(6)-Id, and APH(3’’)-Ia.

Of interest, the ICEs identified in H. somni isolates from Canadian and American cattle carry a multicopper oxidase family protein type 3 gene. Copper is required for a variety of cellular processes, tissue growth and development, bone and wool growth, pigmentation, and healthy nerve fiber in animals. Copper is included in multi-mineral supplements used in feedlot cattle. The recommendation for copper in

52 beef cattle feed is 10 mg/kg; however, amounts used in feed are reported to be almost twice the nutritional requirement [205–207]. Excessive minerals are excreted from the animal body via manure and urine, and once in the environment might create selection pressure for bacteria to acquire tolerance to minerals. The mechanism by which copper may inhibit or kill bacteria is summarized as follows. Copper ions are an essential micro-nutrient for bacteria but an excess can interfere with normal cell function by generating reactive oxygen species which disrupt the cell membrane integrity. A damaged membrane in turn may lead to DNA damage [208]. The ability of copper to inhibit growth and potentially kill bacteria makes it useful as a nonspecific antimicrobial or disinfecting agent [209].

The multicopper oxidase family protein type 3 gene located in the H. somni ICE sequence codes for an oxidoreductase which aids in copper detoxification. This protein oxidizes toxic copper ions (Cu(I)) which are capable of disrupting the cell membrane and damaging cellular integrity to (Cu(II)) which is less active [210].

Because of the presence of excess copper in the feed this gene may provide tolerance against toxic levels of copper and provide a phenotypic advantage for survival of H. somni in the feedlot cattle environment.

Also identified within the H. somni ICE sequence was the potential virulence factor heme utilization protein, which is a conserved heme utilization operon initially identified in free-living E.coli [211]. The genes encoded within this heme utilization

53 operon enable active uptake and utilization of heme as an iron source in many pathogenic microorganisms, and enable multiplication and survival within hosts they invade [212]. In addition to the heme utilization protein, other virulence factors involved in iron-uptake, biosynthesis and transfer were identified outside of the ICE- sequence on the H. somni chromosome. These include transferrin-binding proteins tbpA, and tbpB, ferrochelatase hemH, delta-aminolevulinic acid dehydratase hemB, and porphobilinogen deaminase hemC [213,214].

3.6 Conclusion

This research identified a sophisticated mobile genetic element classified as an ICE carrying antimicrobial resistance genes for multiple classes of antimicrobials. Some of the AMR genes confer resistance to antimicrobials frequently used in feedlot cattle. In addition, the ICE was found to carry a multi-copper oxidase gene which may improve survival of H. somni in the feedlot environment. The ICE was found to carry multiple genes for proteins involved in heme acquisition and utilization.

These genes may be considered virulence genes if they increase bacterial survival and pathogenicity.

The presence of this diverse collection of genes in the accessory regions of the H. somni ICE can be explained as the result of selection pressures on the bacterial population in the feedlot environment. The ICEs identified in H. somni in this study

54 have multiple-drug resistance genes. The presence of the large ICE in bacterial strains indicates phenotypic advantages for bacterial survival outweigh the fitness cost of having a large mobile genetic element on the chromosome. These ICE can be maintained in the H. somni population through both vertical and horizontal transmission and have the potential to be horizontally transferred from H. somni to other closely related bacterial species in the Pasteurellaceae family. Both vertical and horizontal transfer will result in dissemination of AMR among BRD pathogens.

The presence of multi-drug resistance conferring mobile genetic elements in BRD pathogens poses a serious threat to the efficacy of antibiotic treatment of BRD in feedlot cattle.

Table 3: Summary of identified AMR genes in the sequence of ICE in H. somni UOC-KLM-ATR-014 In silico assessment* Resistance phenotype Protein Resistance BLAST - UniProt – Gene name modelling - (antimicrobial class) NCBI Protein data mechanism SWISS- database bank MODEL tet(H) Tetracycline + + + Antibiotic efflux Antibiotic target Sul2/folP Sulfonamide + + + replacement floR Chloramphenicol/Florfenicol + - - Antibiotic efflux APH (3'')- Aminoglycoside + + + Antibiotic inactivation Ib APH (6)-Id Aminoglycoside + + + Antibiotic inactivation APH (3')-Ia Aminoglycoside + + + Antibiotic inactivation * The nucleotide sequences of AMR genes were assessed using NCBI BLASTn followed by BLAST UniProt Protein Data Bank to assesses NCBI database search results. Protein modelling was used to compare ICE AMR proteins against the modelled reference proteins.

Chapter four: The integrative and conjugative element of H. somni

4. An integrative and conjugative element (ICE) conferring multi-drug resistance and copper tolerance in Histophilus somni from feedlot cattle in

Alberta

The manuscript draft is intended for submitted to the journal Infection, Genetics, and

Evolution.

4.1 Authors and affiliations

Mohammad Mostafa Nazari Zanjani a, Tim A. McAllister b, Anthony B. Schryvers c, Rahat Zaheer b, Karen Liljebjelke a

a) Faculty of Veterinary Medicine, University of Calgary, Department of

Ecosystem and Public Health, University of Calgary, AB, Canada.

b) Lethbridge Research Centre, Agriculture and Agri-Food Canada, Lethbridge,

AB, Canada.

c) Department of Microbiology, Immunology and Infectious Diseases,

University of Calgary, Calgary, AB, Canada

4. 2 Introduction

Bovine respiratory disease (BRD) is one of the most economically significant diseases in feedlot cattle. This respiratory disease complex is a result of three codependent factors: i) environmental stress such as shipment and sudden change in diet which weakens the immune system, ii) infection with viral BRD pathogens and iii) secondary bacterial infection with BRD-associated bacterial pathogens [215].

The most commonly isolated bacteria in clinical cases of BRD are three members of the Pasteurellaceae family, Pasteurella multocida, Mannheimia haemolytica, and

Histophilus somni [18].

Management of BRD includes the use of vaccines against viral and bacterial respiratory pathogens, and antimicrobials for prophylaxis/metaphylaxis or therapeutic purposes. Antimicrobials are commonly used for prevention and treatment of BRD and may be administrated to high risk cattle upon arrival at the feedlot. A decreased susceptibility of BRD-associated bacteria to commonly prescribed antibiotics may decrease efficacy of antibiotics used for prevention, control and treatment of BRD in feedlot cattle [55]. In P. multocida, and M. haemolytica multi-drug resistance (MDR) to antimicrobials used to control and treat

BRD has been associated with a type of mobile genetic elements (MGE) known as integrative and conjugative elements (ICE) [143,144]. ICEs are a conjugative type of mobile genetic element which can move horizontally between two cells that have

58 no parent-offspring relationship. ICE movement is independent of the host cell due to specific genomic modules located in the ICE sequence and expressed by the ICE.

These genomic modules comprise the integration and conjugation machinery complex (ICMC) of the ICE [109]. ICMC genes are involved in four main steps which enable the ICE to move from the host chromosome to the recipient genome.

These steps are i) Excision from the host chromosome, ii) Maintenance of the excised ICE as a circular intermediate, iii) Conjugative transfer, and iv) reintegration into the recipient chromosome [108,113]. ICEs may carry genes with no function in ICMC process. These genes are known as accessory or cargo genes and may encode for virulence factors, metal-tolerance, antimicrobial resistance or alternative biochemical pathways [113]. To-date, MGEs conferring MDR have not been identified in H. somni, although there are reports that resistance to antimicrobials has been increasing [97,98,216].

4. 3 Materials and Methods

4.3.1 Whole-genome sequence raw data files

A total of nineteen H. somni whole-genome sequences were used in this study (Table

4). The dataset contained of H. somni genomes from isolates collected from feedlot cattle in Canada (n=12), and the USA (n=7). The Canadian WGS data files were obtained from the Vaccine and Infectious Disease Organization-International

Vaccine Centre (VIDO-InterVac), Saskatoon, Sk, Canada [159]. The American

WGS were extracted from publicly accessible bioinformatics databases submitted by the Genetics, Breeding, and Animal Health Research Unit, USDA-ARS-

USMARC, Clay Center, the US [217].

Table 4. Summary of H. somni sequences and associated metadata used in this study.

NCBI Country Source of Date of Sequencing DNA Number Number of coding Strain name %GC accession no of origin isolate collection platform length (bp) of Genes regions (CD) UOC-KLM-ATR-01 NZ_CP042983.1 Aug-2012 36.9 2110695 1958 1890 UOC-KLM-ATR-03 NZ_CP042984.1 Oct-2012 37.3 2183498 2046 1978 UOC-KLM-ATR-04 NZ_CP043001.1 Aug-2012 37.4 2183401 2050 1982 UOC-KLM-ATR-06 NZ_CP042985.1 Sep-2012 36.9 2110633 1930 1862 UOC-KLM-ATR-07 NZ_CP042986.1 Sep-1983 37.1 2110618 1927 1859 UOC-KLM-ATR-08 NZ_CP042987.1 Alberta, Sep-2012 Illumina 37.2 2110729 1962 1894 Heart/Lung UOC-KLM-ATR-09 NZ_CP042988.1 Canada Aug-2012 MiSeq 500 37.1 2110643 1933 1865 UOC-KLM-ATR-010 NZ_CP042989.1 1983 36.7 2110625 1927 1859 UOC-KLM-ATR-011 NZ_CP042990.1 1983 37.1 2110646 1931 1863 UOC-KLM-ATR-012 NZ_CP042991.1 1983 37.2 2110678 1935 1867 UOC-KLM-ATR-013 NZ_CP042992.1 1983 37.0 2110694 1959 1891 UOC-EPH-KLM-014 NZ_CP042993.1 Sep-2012 37.2 2183545 2053 1985 USMARC-63250 NZ_CP018802.1 Bodily fluid 37.2 2110642 1924 1856 USMARC-63255 NZ_CP018803.1 Mucus 37.4 2183391 2011 1943 USMARC-63368 NZ_CP018804.1 Bodily fluid 37.4 2183505 2012 1944 Kansas, USMARC-63369 NZ_CP018805.1 Mucus Oct-2013 PacBio P6 37.4 2183439 2008 1940 USA USMARC-63370 NZ_CP018806.1 Bodily fluid 37.4 2183418 2012 1944 USMARC-63373 NZ_CP018807.1 Mucus 37.2 2110610 1925 1857 USMARC-63374 NZ_CP018808.1 Mucus 37.4 2183430 2011 1943

4.3.2 Assembly and annotation of draft whole genome sequences

Default parameters were used for all in silico software unless otherwise specified.

The American WGS were used as extracted from databases. The following bioinformatics tools and methods were used for quality control, assembly, scaffolding and annotation of the WGS from Canadian isolates. FastQC v 1.0.0 and

QUAST v 5.0.2 were used for quality assessment of sequences, before and after assembly, respectively [155,218]. Trimmomatic v 0.38 was used for sequence trimming and adapter clipping [219]. In the trimming process the following types of reads were removed: low-quality reads (quality [Q] score, <20), reads with less than

50 nucleotide bp or with more than 10% N, and sequencing-reads with a >15-bp overlap with the Illumina adaptors. The outcome of trimming was that the FASTQ files had at least 98% of reads with a ≥ Q score 30 [220]. The trimmed WGS files were assembled de novo, and were then put into scaffolds using SPAdes v 3.13.0 and MeDuSa: a multi-draft based scaffolder [221,222]. Before annotation using the

NCBI prokaryotic genome annotation pipeline (PGAP) [157], contigs with less than

200 nucleotides (nt) were removed from the assembly files as a quality control step

[223].

4.2.3 Identification of mobile genetic elements

The annotated files of 19 draft WGS were used to search for and categorize the type of conjugative MGEs and transposable elements. The tool Islandviewer 4 was used to screen the WGS for genomic islands (GI) [224]. Tools of the "CGView - Circular

Genome Viewer" were used to visualize any diversity of the %GC content in the chromosome of all strains [225]. Genomic islands larger than 10 Kb nucleotides with a unique %GC content compared to the rest of the genome were selected and extracted for further analysis.

ICEs were identified in the selected GIs using ICEfinder- an in silico tool of ICEberg

2.0 database [226]. In silico tools of the VRprofile pipeline [227] were used to verify the results of ICEfinder, and to search for integrative and mobilizable element

(IME), another type of conjugative MGEs [109].

To search for plasmids in WGS files, PlasmidSPAdes and Recycler, were used before and after the assembly, respectively [228, 229]. Prophages and bacteriophages were searched for and categorized using VirSorter on assembled

WGS files [230].

4.3.4 Characterization of ICEs

The integration sites of ICEs were identified by using direct repeats (DRs) via pairwise nucleotide sequence alignment of the first and last 500 base-pairs (bp) of

63 the surrounding nucleotides of mobile genetic element using BLASTn [231]. The

ICMC genes in the ICE sequence were identified and classified by assessing coding proteins and their biochemical functions via the BLASTp service of Uniprot: a pipeline of Protein Data Bank, and by using the Kyoto Encyclopedia of Genes and

Genomes (KEGG), respectively [232, 233].

Comparative protein homology modeling using “I-TASSER” was used to query the function of hypothetical proteins in the ICE. Tools of the Swiss-model pipeline were used to assess the structure of the modeled protein [234, 235].

The origin of transfer (oriT) of ICEs was assessed using oriT finder [236]. The type and category of the secretion systems of ICEs were classified using the TXSScan pipeline [237].

4.3.5 Comparative genomic analysis of ICEs in Canadian and American

H. somni isolates

The gene arrangement in Canadian and American ICEs were compared using the

Easyfig visualizer [238]. To determine the phylogenetic relationship of the ICMC genes of ICEs, Clustal Omega v 1.2.4 was used to produce multiple sequence alignments, and MRBAYES: Bayesian inference v 3.2, was employed to interpret the results [239, 240].

4.3.6 Comparison of H. somni ICE and P. multocida and M. haemolytica

ICEs

The evolutionary relationship (phylogenetics) of ICMC genes in ICEs of H. somni,

ICEpmu1 in P. multocida, and ICEmh1 in M. haemolytica were examined. ICE sequences were extracted from the ICEberg database 2.0. To make the multiple sequence alignment and to interpret results, Clustal Omega and MRBAYES were used.

4.3.7 Identification of H. somni ICE family

The repository of ICEberg 2.0 was used to create a shortlist of the ICEs identified in different species of bacteria most homologous to the novel ICE in H. somni.

MultiGeneBlast v 1.1.13 was used to assess the identity of the homologs between multigene modules of ICEs [241]. The arrangements of genes in homologous ICEs were compared and visualized using Mauve: the whole genome alignment tool v

2.4.0 [242].

4.3.8 Antimicrobial resistance and metal tolerance genes of ICEs among members of the ICEHin1056 family

Whole-genome sequence of P. multocida and M. haemolytica strains carrying

ICEpmu1, and ICEmh1, and WGS of bacterial species harbouring ICEs of the

ICEHin1056 family were used for comparative analysis (Table 5). Antimicrobial resistance genes were searched for using the built-in annotation tools of the comprehensive antibiotic resistance database (CARD) [243]. Vfanalyzer: an automatic pipeline of virulence factor database was used to identify potential virulence factors carried by ICEs [244]. Metal-tolerance genes were manually identified in using annotation files.

4.3.9 H. somni ICE host range prediction

The host range of the H. somni ICE was predicted using BLASTn optimized for highly similar sequences (megablast) at the integration site of the ICE in the chromosomal tRNAleu gene. Bacterial characteristics similar to those of H. somni were considered when filtering the search results. Gram-positive bacteria, viruses and Archaea were not included in the BLAST result.

Table 5: Bacteria containing similar ICE NCBI genome

Bacterial strain Name of ICE accession number ICE family

Pasteurella multocida 36950 ICEPmu1 CP003022.1 Unclassified

Mannheimia haemolytica 42548 ICEMh1 CP005383.1 Unclassified

Haemophilus influenzae 1056 ICEHin1056 AJ627386.1 ICEHin1056

Haemophilus influenzae 86- ICEHin86-

028NP 28NP CP000057.2 ICEHin1056

Haemophilus influenzae 10810 ICEHinB FQ312006.1 ICEHin1056

Haemophilus influenzae R2866 ICEhinR2866 CP002277.1 ICEHin1056

Haemophilus influenzae 299 ICEHin299 AM884334.1 ICEHin1056

Haemophilus influenzae 8f ICEHpa8f AM884335.1 ICEHin1056

Haemophilus parainfluenzae

T3T1 ICEHpaT3T1 FQ312002.1 ICEHin1056

Actinobacillus pleuropneumoniae serovar 8 ICEApl1 NZ_LN908249 ICEHin1056

4.4 Results

4.4.1 Identification of mobile genetic elements in H. somni WGS

Results of sequence analysis using PlasmidSpades and Recycler showed that all

Canadian and American H. somni WGS were free of known plasmids. The conjugative MGEs and transposable elements identified in Canadian and American

H. somni strain WGS are summarized in Table 6. A variable number of genomic islands (variable %GC) were recognized in all strains, and consisted of ICE, IME, or prophage sequences.

ICEs were found in three of 12 Canadian isolates, and five of seven American strains. The ICE identified in Canadian and American isolates were highly similar in gene arrangement, gene content and nucleotide size. One Canadian ICE was submitted to the NCBI GenBank under the accession number of MN401320.1. The detailed genomic content of the ICE is shown in appendix Figure 7.

IMEs were also identified in all ICE-positive strains and were subsequently named after their co-existing ICEs. All IMEs lacked genes for the relaxosome complex, secretion system, and were devoid of cargo (accessory) genes. The most prevalent prophage and bacteriophage identified in Canadian H. somni strains was

Mannheimia haemolytica bacteriophage vB_MhS_1152AP2 (Mannheimia spp.

Virus), and in American strains was a Haemophilus spp. specific virus, Haemophilus phage SuMu_NC_019455.

Table 6. Summary of ICEs, IMEs and prophages integrated into H. somni chromosomes Mobile genetic elements Integrative and conjugative Integrative and mobilizable element Genomic element Prophage Country (IME) Strain name islands (ICE) of origin (no.) Copy Name of element Copy number Name of element Copy number number

UOC-KLM-ATR-01 4 -* - - - 4 UOC-KLM-ATR-03 5 ICEHsKLM-03 1 IMEHsKLM-03 1 3 UOC-KLM-ATR-04 5 ICEHsKLM-04 1 IMEHsKLM-04 1 3 UOC-KLM-ATR-06 5 - - - - 5 UOC-KLM-ATR-07 5 - - - - 5 UOC-KLM-ATR-08 4 - - - - 4 Canada UOC-KLM-ATR-09 5 - - - - 5 UOC-KLM-ATR-010 7 - - - - 7 UOC-KLM-ATR-011 6 - - - - 6 UOC-KLM-ATR-012 7 - - - - 6 UOC-KLM-ATR-013 5 - - - - 5 UOC-EPH-KLM-014 6 ICEHsKLM-014 1 IMEHsKLM-014 (A &B) 2 3 USMARC-63250 4 - - - - 4 USMARC-63255 5 ICEHs-63255 1 IMEHs-63255 1 3 USMARC-63368 5 ICEHs-63368 1 IMEHs-63368 1 3 USMARC-63369 USA 5 ICEHs-63369 1 IMEHs-63369 1 3 USMARC-63370 6 ICEHs-63370 1 IMEHs-63370 (A & B) 2 3 USMARC-63373 7 - - - - 7 USMARC-63374 4 ICEHs-63374 1 IMEHs-63374 1 2 * none detected

4.4.2 Identification of H. somni ICE family

MultipleGeneBlast identified (total score < 50) the following bacterial strain genomes which harbour the most homologous ICEs to the novel ICE in H. somni:

P. multocida 36950, M. haemolytica M42548, Haemophilus parainfluenzae T3T1,

Haemophilus influenzae R2866, Haemophilus influenzae 10810 genome, and

Haemophilus influenzae 86-028NP (Fig.2). All these strains carry ICE which are members of the ICEHin1056 family. The results of using Mauve showed that the

ICE sequence in H. somni has the most similar gene organization, nucleotide order, and sequence similarity to the members of the ICEHin1056 family (Fig. 3). Based on similarity of sequence arrangement, positioning of ICMC genes on the ICE of H. somni and homologous ICE identified by MultipleGeneBlast, the novel ICE of H. somni was classified as a member of the ICEHin1056 family. ICE in the

ICEHin1056 family and the H. somni ICE use the same type of ICMC genes. These clusters of genes are essential for the mobile genetic element to start and finish independent horizontal movement (excision, conjugation, maintenance, and integration). The use of Mauve demonstrated that the location of ICMC gene clusters in the H. somni ICE is highly similar to many ICE in the ICEHin1056 ICE family.

Figure 2: Results of a MultipleGeneBlast alignment used to identify the most homologous ICEs to the novel ICE in H. somni. Arrow colors represent gene homology in the NCBI Blastn alignment. White arrows represent genes with no matches for the query. Arrows with the same color have high sequence homology and gene synteny. Total score is a composition of the number of BLAST hits matching threshold default = 250 hits/gene, and the number of contiguous gene pairs with conserved synteny. Cumulative BLAST bit score represents similar gene content to the queried H. somni ICE sequence. Total score >100 indicates high similarity, and <50 indicates lack of significant homology. 71

H. somni ATR-014

H. Influezaea 86-028

H. Influezaea 10810

H. Influezaea R2866

H. Paranfluezaea T3T1

M. Haemolytica

P. multocida Figure 3. Whole-genome sequence alignment using Mauve to examine gene arrangement and compare coding modules between ICEs. Mauve identified conserved segments free of genome rearrangements. These regions are called Locally Collinear Blocks (LCBs). LCBs with similar colors represent sections of genome with similar nucleotide order, length and gene arrangement which have identical transcription direction and are coding for products with a similar cellular function. Mauve was used to classify the H. somni ICE family. Red: integrase/recombinase, Yellow: AMR genes, Green, Violet and Blue: chromosomal excision, ICE maintenance and mating pore formation, Pink: metal-tolerance gene. Numbers refer to ICE size bp.

4.4.3 Genomic structure of H. somni ICE

The genomic characteristics of the novel ICE in H. somni are summarized in Table

7. The unique function of each category of ICMC gene is summarized in Table 8.

Whole data related to the Canadian ICE of H. somni are provided in Appendix Table

2. ICE are considered to be DNA dervied from sources outside of the genome and differ in %GC content from other regions of the chromosome. The GC content of the ICE sequence was ~ %42, higher than the host chromosome GC content of ~

%37. The relative location of the ICE in the draft WGS genome is shown in Figure

4. A detailed map of the ICE sequence is provided in Appendix Figure 7. Genes with similar biochemical functions were found to be located close to each other on the

ICE sequence (Fig. 5, Appendix Table 2).

The integration site (CAA) used by the ICE was in a tRNA-Leu gene. All ICE identifed had an identical 21-nucleotide direct repeat as follows:

[CGTGTCGGTTCGAGTCCGACC] (Figure 6).

Table 7: Genomic characteristics of H. somni ICE ICE location Country Length Coding gene *DR length Insertion tRNA gene location ICE name %GC interval on of origin (Kbp) number (bp) site motif on chromosome chromosome ICEHsKLM-03 72921 40.96 76 687450...687535 687506...760427 21 - ICEHsKLM-04 Canada 72912 41 79 identical 687439...687524 687495...760407 ICEHsKLM-014 72918 41.82 79 CGTGTCG 687445...687530 687500...760418 tRNA-Leu ICEHs-63255 72907 41.81 81 GTTCGAG (CAA) 686759...686844 686814...759720 ICEHs-63368 72908 41.81 82 687708...687793 687763...760670 The US ICEHs-63369 72905 41.8 81 TCCGACC 687423..687508 687478...760384 ICEHs-63370 72904 41.8 81 686924..687009 686979..759884 * DR: Direct repeats; bp: base pair

Table 8: Integrative and conjugative machinery complex (ICMC genes) identified in H. somni ICE sequences.

Process Gene Product Mating pore ICE maintenance after Integration Conjugation formation excision traI Relaxase - - + - traD T4CP* - + + - traG Conjugal transfer protein - + + - xerC Tyrosine recombinase + - - - xerD Site specific tyrosine recombinase + - - - ssb Single strand DNA binding protein + - + - parA ParA family protein + + dnaB Replicative DNA helicase + - - + parB Chromosome partitioning protein + - - + Cluster of genes for T4SS** - + + -

* type IV coupling protein, ** type IV secretion system

Figure 4. A circular map of Canadian H. somni strain UOC-KLM-ATR-014 made using CG-View. a) Relative location of ICE on H. somni chromosome with higher %GC content shown as black bar. b) Inset showing ICE sequence. Size of ICE is ~72 Kbp. The ICE encodes 79 genes and is integrated in a tRNA-leu gene (red arrows). Numbers on figure refer to size of the chromosome.

Figure 5. Simplified map of ICE identified in H. somni UOC-KLM-ATR-014. Genes with similar function are assembled close to each other. Colors indicate gene function: horizontal movement regulation, Hypothetical protein, Maintaining ICE cellular homeostasis, Antimicrobial resistance gene, Metal-tolerance gene, Mpf structure, conjugal transfer and T4SS, FloR antimicrobial resistance gene. The first and second rows of numbers refer to size of ICE and location on the H. somni chromosome, respectively.

Figure 6. Sequence map illustrating ICE integration into a tRNA-Leu at a palindromic sequence site. The first row shows the tRNA- Leu gene nucleotide sequence, the middle row shows the translated amino-acid sequence, and the bottom row depicts the complementary nucleotide sequence of tRNA-Leu.

The average size of ICEs in H. somni was 75 Kbp (kilo base-pairs). The genes necessary for the independent horizontal movement; ICMCs and a complete cluster of genes encoding the structure of a type IV secretion system (T4SS) were identified in all ICE sequences examined. The same type of ICMC-genes were found in

Canadian and American H. somni strains. The integrase/recombinase genes xerD and xerC belong to the site-specific tyrosine recombinase family. Accessory genes of the integrase/recombinase complex were also identified as: a) ParA family protein, b) replicative DNA helicase (dnaB), and c) chromosome partitioning protein

(ParB). The accessory genes, ParA and ParB encode soj proteins which function in preventing the loss of ICE after excision through inhibition of chromosome replication. These accessory genes were located immediately after the left-hand short DRs (attL). Also identified were the genes for relaxase traI and for single- strand DNA binding protein ssb.

The components of the mating pore formation (Mpf) are responsible for making a physical connection between two cells during horizontal exchange of mobile genetic elements. The Mpf components identified in the H. somni ICE were; a complete

(type IV) secretion system, type IV coupling protein (traD), and conjugal transfer protein (traG). The T4SS gene cluster had a nucleotide similarity of at >95% with the MpfG family which is found in members of the ICEHin1056 family. The oriT of the ICE sequences were located between the eight bp length inverted repeat

78 sequences ACCTTTCC and GGAAAGGT which were located in a 423 nc group,

500 nucleotides upstream of the relaxase.

The ICE of most Canadian and American H. somni strains were found to have identical ICMC genes. However the American strain USDA-ARS-USMARC-63374 was found to have a different direction of gene transcrition for many genes which may reflect an error in WGS chromosome assembly or annotation by the genome publisher.

4.4.4 Gene-arrangement in ICEs of BRD-associated bacteria

Genomic comparison of the gene-arrangement of ICEs from H. somni, P. multocida, and M. haemolytica demonstrated that despite having highly similar ICMC genes their arrangement varied. The ICE of H. somni had the most similar gene- arrangement to ICEHin1056 ICE family members which were not BRD pathogens.

When comparing ICE of P. multocida and M. haemolytica to ICE of H. somni it was discovered that the ICMC genes were located in different positions. The ICEs of the three BRD-associated bacteria also have a different assortment of cargo genes, and despite some similarity their accessory genes are different (appendix figure 8). ICEs in P. multocida and M. haemolytica were carrying different combinations of antimicrobial resistant genes. One ICE in a P. multocida strain was harboring 11

ARGs conferring resistance to streptomycin/spectinomycin (aadA25), streptomycin

(strA and strB), gentamicin (aadB), kanamycin/neomycin (aphA1), tetracycline

[tetR-tet (H)], chloramphenicol/florfenicol (floR), sulphonamides (sul2), tilmicosin/clindamycin (erm), or tilmicosin/tulathromycin (msrE, mphE) [42]. ICE reported from M. haemolytica strains were found to be carrying only five AMR genes. These genes may provide the following resistance for its host: streptomycin

(strA and strB), kanamycin/neomycin (aphA1), tetracycline (tetH), and sulphonamides (sul2).

The AMR genes carried by the ICE of H. somni strains were; tetH, floR, Sul2/folP,

APH(3”)-Ib, APH(6)-Id, and APH(3’)-Ia. These genes may provide resistance to tetracyclines, phenicols, sulphonamides, and aminoglycosides. In ICEs from

American H. somni strains an “elongation factor Tu (EF-Tu)” was identified, and the phenicol resistance gene (floR) was not identified. The EF-Tu gene confers resistance against elfamycin antibiotics such as pulvomycin and efrotomycin [245].

4.4.6 Identification of cargo genes of ICEHin1056 ICE family members

According to the ICEberg 2.0 repository of integrative and conjugative elements database, members of the ICEHin1056 family have been identified in four bacterial species, with six ICEs found in Haemophilus influenzae, one identified in

Haemophilus parainfluenzae, and one in Actinobacillus pleuropneumoniae. The only cargo genes identified in these ICE was the antimicrobial resistance gene tetB.

The tetracycline gene tetH was found in the H. somni ICE. Both genes may confer phenotypic resistance to tetracyclines. No cargo genes coding for potential virulence factors or metal tolerance were found in ICEHin1056 family members other than H. somni ICE.

4.4.7 Host range prediction for the H. somni ICE

In silico prediction of host range based on the homology of insertion sequences at the tRNA gene recombination site suggested that the H. somni ICE may move between H. somni isolates more frequently than the rest of bacterial species based on % BLAST similarity of integration sequences. The insertion site sequence of other organisms had a BLAST sequence similarity between 85-99%. P. multocida

M. haemolytica, H. influenzae, and H. parainfluenzae, all members of the

Pasteurellaceae family had insertion site sequence similarity of between 85-99%, with P. multocida having highest insertion site sequence similarity (99%).

Comparison of the insertion site sequence homology predicted that the ICE has a low probability of being able to move from H. somni to Actinobacillus pleuropneumonia and Escherichia coli with BLAST sequence similarity scores of only 80-85%. The likelihood of the ICE being able to move to Salmonella enterica serovar Typhimurium and Yersinia pseudotuberculosis is also low, with BLAST sequence similarity scores around 75%.

4.5 Discussion

Organisms, including bacteria, are defined by their genome. The ability of bacteria to evolve and adapt to harsh environments, such as selection pressure from antimicrobials, is due to the dynamic nature of their genetic repertoires. Bacteria possess the unique ability to quickly acquire new genes which confer advantageous traits through pathways of horizontal gene transfer. A variety of mobile genetic elements are known agents of horizontal gene transfer in bacteria. In this study a large MGE called an integrative and conjugative element (ICE) belonging to the

ICEHin1056 family was identified as integrated in the chromosome of H. somni strains isolated from Canadian and American feedlot cattle. This large mobile genetic element is carrying multiple antimicrobial resistance genes. Interestingly, H. somni strains lacking an ICE did not have any AMR genes located on their chromosomes.

The autonomous horizontal movement of ICEs is due to the gene products of the

ICMC gene cluster present on the ICE. In this study the ICE identified in both

Canadian and American H. somni strains possessed a complete and highly similar set of ICMC genes. These genes were found to be homologous to the ICMC genes found in other ICEHin1056 family members, and to the ICEs found in P. multocida and M. haemolytica. All H. somni ICE in had similar genes which are involved in the cycle of integration, maintenance, excision, and conjugal transfer.

It was found that all H. somni examined had identical 21-nc direct repeats, and that they were integrated into a tRNA Leu gene (CAA) at the DNA leading strand. Other members of the ICEHin1056 family and the ICEs reported in P. multocida and M. haemolytica also integrate at a tRNA-leu site. One difference among members of the

ICEHin1056 ICE family is that the DRs differ in size (66-nc), and the ICEs integrate into the lagging DNA strand into a different motif (allele) of the tRNA-Leu gene:

TAA instead of CAA. Similarly, the integration site of the H. somni ICE and the

ICEs in P. multocida and M. haemolytica is in a tRNA-Leu (CAA) in the leading strand, with a 21-pb DRs, but the DRs sequence is different

(GGTCGGACTCGAACCGACACG).

The H. somni ICE possesses genes for production of an Mpf structure which the ICE uses to move from the donor to the recipient in a process called conjugal transfer. A total of eighteen genes composed the T4SS structure in the H. somni ICEs and in other ICEs of the ICEHin1056 family. The T4SS identified in the H. somni ICE belonged to the MpfG family, as did the T4SS identified in P. multocida and M. haemolytica. Although they are in the same family, the T4SS genes found in the P. multocida and M. haemolytica ICEs have a more complex form and are encoded by a total of 21 genes compared to the 18 genes comprising the T4SS found in ICEs of

H. somni. It is unknown what if any biological differences in this may produce in conjugal transfer of ICE found in H. somni, P multocida and M. haemolytica. The

ICMC genes are homologous and belong to the same Mpf family in ICEs of H. somni, P. multocida, and M. haemolytica, but the gene-arrangement of ICEs in H. somni was most similar to other members of the ICEHin1056 family. The ICEs identified in P. multocida and M. haemolytica have very different gene arrangements, and this study identified them as belonging to an as-yet unclassified group of ICEs.

ICE members of the ICEhin1056 family reported in H. influenzae, H. parainfluenzae, and A. pleuropneumoniae and the ICE of H. somni, have strong homology as shown by Mauve and MultiGeneBlast alignments. The ICE in these bacteria may have a common ancestor. The ICE in these bacteria retained the HGT- required-modules but have different cargo genes including different antimicrobial resistance genes. This may be the result of different selection pressures experienced by these bacteria.

For example, the β-lactamases, and fluoroquinolone class antimicrobials such as amoxicillin-clavulanic, and levofloxacin, gatifloxacin, gemifloxacinare are choices for treatment of H. influenzae and H. parainfluenzae infections. β-lactamase and fluoroquinolone-AMR-genes have been located on the chromosome of H. influenzae and H. parainfluenzae which may account for their absence in the ICE they carry

[246, 247]. It is not energy-efficient for organisms to retain two or more copies of genes with a similar function, so these genes may have been lost from the ICE

84 sequence. No antimicrobial resistance genes were found on the chromosome of H. somni but multiple antimicrobial genes were located on the ICE.

It has been suggested that prohibiting the use of antibiotics for growth-promotion in animals, banning or restricting the use of antimicrobials important to human medicine in veterinary medicine, and investing more in alternative-to-antibiotics therapeutic approaches might be helpful to reduce the pressure for selection of AMR in bacteria and reduce AMR dissemination. It is my opinion that high-throughput screening of WGS from environmental, commensal and pathogenic bacteria for

AMR genes and markers for MGEs, and the establishment of a real-time bioinformatics data bank accessible to researchers and diagnosticians would provide valuable surveillance data for molecular epidemiological modelling of AMR which could be used for informing public health policy.

Chapter five: General discussion and future research

5. 1 General Discussion

The rate of morbidity and mortality associated with BRD in feedlot cattle is considerable worldwide [248]. Approximately 75% of feedlot morbidity, and 90% of all feedlot deaths have been attributed to BRD [17,249,250]. To mitigate the economic and animal welfare impacts of BRD, a variety of preventive and therapeutic protocols are used, but the most common and frequent response to BRD is the use of antimicrobials [62]. The frequency of antimicrobial usage may have led to the increasing frequency of antimicrobial resistance in BRD-associated bacteria of the Pasteurellaceae family; Mannheimia haemolytica, Pasteurella multocida, and

Histophilus somni [54,55,149].

Although the mechanisms of acquisition and dissemination of antimicrobial resistance (AMR) in bacteria are complex, it is accepted that exposure of organism to drugs creates selection pressure for development of resistance [180]. A bacteria carrying AMR genes may exchange those genes through horizontal gene transfer, enabling susceptible strains to quickly become resistant [158]. Previous research on the genome of P. multocida and M. haemolytica showed that an integrative conjugative element (ICE) is one of the mechanisms responsible for transmitting multiple drug-resistance genes in these organisms [143,144]. A study conducted a decade ago speculated about the possibility of MGEs in the genome of H. somni,

86 however the authors did not identify a connection between AMR or other virulence genes and a MGE. That study's overall goal was to compare the genome of two strains and identify their genome similarities and differences [145]. No subsequent studies examining the genome of H. somni have been published.

H. somni is one of the pathogens associated with BRD in feedlot cattle and is responsible for a multi-systemic infectious disease known as histophilosis. Multiple recent reports have noted that H. somni is becoming less susceptible to the antimicrobials most commonly used in feedlot cattle.

A comparative genomic analysis of H. somni WGS was conducted for this study.

The main goal was to determine if AMR genes are associated with MGEs in the genome of H. somni are affiliated with mobile genetic elements (MGE) (Figure 7).

Datasets were created using WGS of H. somni isolates collected from Canadian and

American feedlot cattle. The MGEs associated with AMR genes in H. somni were identified as a type of ICE. The novel ICE identified in H. somni was carrying six different AMR genes, a possible virulence factor, and one gene for heavy metal- tolerance (multi-copper oxidase). Interestingly, H. somni strains without an ICE did not have any AMR or metal-tolerance genes located on their chromosomes.

The ICE found in H. somni were identified as a member of the ICEHin1056 ICE family. Most of the members this ICE family have been identified in Haemophilus influenzae and Haemophilus parainfluenzae which are human pathogens. An ICE

87 was identified in an isolate of Actinobacillus pleuropneumoniae, a bacterium associated with swine. This is the only other bacterium associated with livestock that has been identified as a carrier of this ICE family.

The ICEs of H. somni, P. multocida, and M. haemolytica were aligned and compared to those in H. somni to assess gene assembly (synteny) and sequence homology.

Results showed that the ICE in these three bacteria are encoding similar core/ICMC gene necessary for independent horizontal movement; however, the genome arrangement and genomic content (genes) were different. The complements of AMR genes within the ICEs were also different.

The host range was predicted in silico for the H. somni ICE using the sequence of the ICE integration site in the tRNA leucine gene of the chromosome. Results suggested that the element may be able to move horizontally to different bacterial species based on the degree of homology of the insertion site sequence in P. multocida, M. haemolytica, H. influenzae, and H. parainfluenzae. This prediction would have to be tested in vitro using mating assays. The possibility that the MDR- conferring ICE of H. somni may be able to transfer horizontally to other closely related bacteria has important implications for the use of antimicrobials to control and treat BRD in feedlot cattle.

Figure 7. Graphic illustration of workflow. The whole-genome sequences of 19 H.somni strains (12 from Alberta Canada, 7 from Kansas, USA) were used. American WGS files were extracted from bioinformatics databases and used without modification for further in silico assessments. Canadian WGS files were assembled and annotated for this study. The genomes of H. somni strains were analyzed to identify mobile genetic elements (MGE) including bacteriophages, transposons, integrative conjugative elements (ICE) and integrative and mobilizable elements (IME). Virulence genes, antimicrobial-resistance genes, and metal-tolerance genes were identified and classified. The function of ICE genes was predicted using protein configuration and biochemical pathway analysis. The characteristics of ICEs were assessed, and the ICE family was determined. Genes required for horizontal movement were identified. The host range was predicted in silico by comparing integration site sequence similarity in related bacteria.

Despite new regulation of veterinary antimicrobial use, antimicrobial resistance remains a serious global health concern. Reduction of antimicrobial use for purposes of growth promotion in food-animals may help reduce antimicrobial resistance.

Residues of antimicrobials used in human and veterinary medicine may remain in the environment and serve as selection pressure for dissemination of antimicrobial resistance. The dissemination of AMR genes through horizontal transfer of ICEs may create a reservoir of AMR which remains even when no antimicrobials are being used [251]. ICEs may transfer AMR genes to co-living bacteria in their niche or move their genomic traits to organisms living in the greater environment [252].

Restriction of antimicrobial use may provide only a partial solution for AMR development but it might not address the complex molecular mechanisms of AMR development and dissemination. Examining the molecular mechanisms of AMR development and dissemination would provide more insight for development of better management practices, creation of new diagnostics tools, and provide better advice for antimicrobial therapy to health practitioners.

This study identified multiple AMR genes present within an ICE on the chromosome of H. somni. Traditional antimicrobial susceptibility testing (AST) would assess the resistance phenotype of the strain but would not provide information about the linkage of AMR genes in a transmissible mobile genetic element. Discovery of this

MDR conferring mobile genetic element was only possible using WGS analysis.

The addition of in silico WGS examination to traditional diagnostic methods would generate meaningful AMR epidemiology data. The use of in silico and sequence- based methods would provide deeper and more accurate insight into the molecular mechanisms of AMR development and dissemination.

5.2 Future research

Whole genome sequencing is a relatively new technology but has improved a lot since first introduced. The cost of the sequencing and decreased, and now is comparable to conventional AST methods. Despite advancements in computational biology, however, the inherent limitation of in silico methods is still that these techniques do not predict phenotypes. The data in this study, generated using bioinformatic analysis, is being confirmed using molecular biological and microbiological methods in vitro. The creation of a dataset of H. somni WGS and its submission to searchable online databases will serve as a resource for further research on the genome of H. somni.

Among the interesting data derived from the WGS dataset was the identification of a large sophisticated ICE containing multiple AMR genes, potential virulence factors and a metal-tolerance gene. The complexity of this molecular-genomic between an ICE and AMR could not be recognized without using whole-genome sequencing.

There is ongoing research into the use of bacteriophage therapy to replace antimicrobials. The logic of bacteriophage therapy is based on the ability of the virus to interrupt a DNA sequence causing a targeted mutation. Data from this study showed that the ICE is encoding genes which allow the element to move between cells and transmit AMR genes. Disruption of ICMC genes of the ICE would cripple the element and would halt the AMR dissemination due to inability to transfer. In case of bacteriophage therapy, data presented in this thesis may help to target one of those ICMC genes for mutation by bacteriophage and subsequently stop the horizontal transmission of AMR.

In this study extra steps and novel methods such as protein modeling and functional annotation using the biochemical pathways assessment of genes were used to annotate and map the genome of H. somni strains as completely as possible

(Appendix figure 9). The process of annotation of the H. somni genome using prediction of the gene product function was successful, however, I used a variety of un-linked bioinformatics pipelines to perform this task. For future work, I suggest writing and developing a unified bioinformatics pipeline to perform these steps on raw WGS to predict the function of a gene and its associated biochemical pathway.

Such a bioinformatics program would be helpful for complete annotation of genomes.

The accurate annotation of novel or never before sequenced bacterial WGS is difficult without reference genomes for comparison. At the time of this study there were only two WGS accessible from online bioinformatics databases, one of which was partial (in-complete_129PT). Prior to this study there had been no reports of

ICE in H. somni which carry AMR genes in their sequences, nor was a complete map of an H. somni ICE available. This is the first comparison of the genomes of

Canadian and American H. somni isolates collected from feedlot cattle. This study provides a wide variety of information about the genome of H. somni and information about the potential for horizontal transmission of AMR between H. somni strains. The information generated has been made available for future studies and adds to the scientific knowledge of microbiology, bacteriology and genomics.

The limited number of WGS available can not provide information about the genomic evolution of the bacteria, the ICE, or the acquisition of AMR genes by the

ICE over time. More WGS of BRD-associated pathogens will enable monitoring the transmission dynamics of AMR carried by ICE and other MGEs. This investment can be justified by the economic importance of increasing AMR in BRD pathogens.

Overall, the benefits of WGS outweigh the cost of sequencing. WGS datasets published to public bioinformatics databases serve as a resource for researchers and diagnosticians regardless of where they are located. Countries which are struggling

93 with economic distress or researchers living where have restricted access to sequencing facilities can use freely available processed WGS data and contribute to science, their country and to humanity. Public access WGS databases are good strategy that benefits the world and all societies should take advantage of and contribute to this valuable resource.

5.3 Conclusion

This study answered many important questions about AMR in H. somni, but also raised questions about the evolutionary origin of the ICE in H. somni. More WGS and genomics and bioinformatics research will be needed to further investigate these topics. As shown in this study whole-genome sequencing provides useful information for inferring the evolutionary path of a newly identified ICE. However, due to the lack of available whole genome sequences, or meta-data like phenotype assessments, at this point it is impossible to reach a confident and precise conclusion about the common ancestor of the H. somni ICE. I suggest a study be performed over a long period to continuously research the development and changes on the genomes of BRD-associated bacteria.

This study demonstrated the influential role of horizontal gene exchange by ICEs and their ability to disseminate physically linked AMR genes. This ICE may have the ability to trans-conjugate from one bacterial species to another and they may be

94 able to move from animal-pathogen to free-living bacteria in the environment.

Prediction of the ICE host range hinted that it may ultimately be able to transmit

AMR and virulence genes to closely related human pathogens [252,253].

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7. Appendix

Appendix Table 1. Comparison of genes encoding virulence factors (VF) in Haemophilus spp. and Histophilus spp.

Haemophilus spp. Histophilus spp.

H. influenzae H. influenzae H. H. influenzae H. influenzae 86-028NP PittEE H. somni H. somni H. somni ducreyi PittGG Rd KW20 (non- (nontypeable 129PT 2336 KLM-014 35000HP (nontypeable) (serotype d) typeable) )

Type of genome (chromosome/plasmid), GenBank accession number, and genome size nucleotide base-pair (bp)

chromoso me chromosome chromosome chromosome chromosome chromosome chromosome chromosome NC_0029 NZ- NC_007146 NC_009566 NC_009567 NC_000907 NC_008309 NC_010519 40 CP042993 (1914490 bp) (1813033 bp) (1887192 bp) (1830138 bp) (2007700 bp) (2263857 bp) (1698955 (2183545 bp) bp) Virulence Gene CD locus tag numbers extracted from genome dataset factor name

Category of virulence factor genes: Adherence CGSHiGG_1 hifA ------0025 CGSHiGG_1 hifB ------Haemagglu- 0030 tinating pili CGSHiGG_1 hifC ------0035 CGSHiGG_1 hifD ------0040

139

CGSHiGG_1 hifE ------0045 Haemophilus adhesion and hap - NTHI0354 ------penetration (Hap) H. influenzae CGSHiGG_0 serotype a hia/hsf - - - HI1731a - - - 2400 and f CGSHiEE_0 hmw1A - NTHI1983 - - - - - high- 3650 molecular- CGSHiEE_0 hmw1B - NTHI1984 - - - - - weight 3645 protein 1 CGSHiEE_0 hmw1C HD1895 NTHI1985 - - - - - 3640 CGSHiEE_0 hmw2A - NTHI1450 - - - - - high- 5600 molecular- CGSHiEE_0 hmw2B - NTHI1449 - - - - - weight 5605 protein 2 CGSHiEE_0 hmw2C - NTHI1448 - - - - - 5610 Peptidoglyca CGSHiEE_0 CGSHiGG_0 FWK62_RS0 n O- oapA HD0651 NTHI0448 HI0330 HS_1287 HSM_0331 1380 4450 2935 Acetylation HD0045, CGSHiEE_0 FWK62_RS0 P5 protein ompP5 NTHI1332 HI1164 HS_1035 HSM_1513 HD0046 6225 4665 flp1 HD1312 ------flp2 HD1311 ------flp3 HD1310 ------flpB HD1309 ------The tad locus flpC HD1308 ------rcpA HD1307 ------rcpB HD1306 ------flpD HD1305 ------tadA HD1304 ------140

tadB HD1303 ------tadC HD1302 ------tadD HD1301 ------tadE HD1300 ------tadF HD1299 ------tadG HD1298 ------CGSHiEE_0 CGSHiGG_0 FWK62_RS0 pilA HD1123 NTHI0409 HI0299 HS_0250 HSM_0123 1560 4310 1385 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 pilB HD1124 NTHI0408 HI0298 HS_1430 HSM_0217 1565 4305 1875 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 pilC HD1125 NTHI0407 HI0297 HS_0457 HSM_0755 Type IV pili 1570 4300 7945 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 pilD HD1126 NTHI0406 HI0296 HS_0458 HSM_0756 1575 4295 7940 comE/p CGSHiEE_0 CGSHiGG_0 FWK62_RS0 HD0434 NTHI0560 HI0435 HS_1112 HSM_1067 ilQ 0815 5395 6745 Category of the following VF gens Endotoxin CGSHiEE_0 CGSHiGG_0 FWK62_RS0 kdsB HD0334 NTHI0068 HI0058 HS_0658 HSM_0998 3010 2800 7075 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpxK HD0217 NTHI0069 HI0059 HS_0656 HSM_0996 3005 2805 7085 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 msbA HD1630 NTHI0072 HI0060 HS_1021 HSM_1499 3000 2810 4735 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 msbB HD0404 NTHI0296 HI0199 HS_1202 HSM_0361 Lipooligos- 2255 3610 3135 CGSHiEE_0 accharide lgtC HD1090 NTHI0365 - HI0258 HS_0636 1770 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 orfM HD1348 NTHI0366 HI0260 HS_0125 HSM_2010 1765 4080 0695 CGSHiEE_0 CGSHiGG_0 kdkA HD1101 NTHI0367 HI0260.1 1760 4085 opsX/rf CGSHiGG_0 FWK62_RS0 HD0445 NTHI0368 - HI0261 HS_1611 HSM_0399 aC 4090 9800

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CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpt6 - NTHI0383 HI0275 HS_0234 HSM_0102 1675 4175 1285 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 galE HD0829 NTHI0471 HI0351 HS_0789 HSM_1256 1245 4565 6070 CGSHiEE_0 CGSHiGG_0 NTHI0472, 7715, 4570, lic3A - HI0352 - - - NTHI1034 CGSHiEE_0 CGSHiGG_0 1240 7845 CGSHiGG_0 waaQ HD1202 NTHI0649 HI0523 - - - 5865 CGSHiEE_0 CGSHiGG_0 HSM_0978, FWK62_RS0 lic2A HD0472 NTHI0677 HI0550 HS_0637 0225 6005 HSM_0977 7180 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 kdtA HD0454 NTHI0772 HI0652 HS_1590 HSM_0421 8940 6540 9690 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lgtF HD1201 NTHI0773 HI0653 HS_0291 HSM_0164 8935 6545 1610 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpxH HD1938 NTHI0892 HI0735 HS_0498 HSM_1773 8445 7140 3355 yhxB/m CGSHiEE_0 CGSHiGG_0 HS_1118, FWK62_RS1 HD1507 NTHI0899 HI0740 HSM_1832 anB 8405 7190 HS_1670 0135 CGSHiEE_0 CGSHiGG_0 lex2A - NTHI0910* - - - - 8335 7260 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lex2B HD1721 NTHI0913 HS_0638 HSM_0979 8330 7265 7170 CGSHiEE_0 CGSHiGG_0 lpsA - NTHI0926 HI0765 - - - 8265 7320 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 galU HD1431 NTHI0976 HI0812 HS_1117 HSM_1063 8000 7555 6765 CGSHiEE_0 - - - HI0867 - - - 7700 CGSHiEE_0 CGSHiGG_0 kfiC - - HI0868 - - - 7695 7875 CGSHiEE_0 CGSHiGG_0 orfE - - HI0869 - - - 7690 7880 orfO - - HI0870 - - -

142

CGSHiEE_0 CGSHiGG_0 siaA HD0686 - HI0871 - HSM_1426 - 7675 7890 wbaP/rf CGSHiEE_0 CGSHiGG_0 - - HI0872 - - - bP 7670 7895 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 rffG HD0687 NTHI1037 HI0873 HS_0707 HSM_1118 7665 7900 6475 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpxD HD1189 NTHI1082 HI0915 HS_0978 HSM_1456 7440 8135 4985 CGSHiGG_0 yhbX HD0371 NTHI1180 - HI1005 - - - 8625 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpxB HD0846 NTHI1220 HI1060 HS_1358 HSM_0257 6780 8930 2245 CGSHiEE_0 FWK62_RS0 lpxA HD1187 NTHI1222 - HI1061 HS_1359 HSM_0256 6775 2240 CGSHiEE_0 CGSHiGG_0 - HD1598 NTHI1224 HI1064 - - - 6765 8950 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 rfaF HD0653 NTHI1272 HI1105 HS_1612 HSM_0398 6535 9175 9805 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 rfaD HD1890 NTHI1278 HI1114 HS_1613 HSM_0397 6480 9225 9810 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 lpxC HD0816 NTHI1312 HI1144 HS_0364 HSM_0634 6325 9380 8425 gmhA/l CGSHiEE_0 CGSHiGG_0 FWK62_RS0 HD1228 NTHI1350 HI1181 HS_1238 HSM_0840 pcA 6140 9600 7565 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 neuA HD0685 NTHI1891 HI1279 HS_0706 HSM_1117 4135 1585 6480 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 rfaE HD1182 NTHI1607 HI1526 HS_0576 HSM_0925 5200 0330 7370 CGSHiGG_0 FWK62_RS0 htrB HD1106 NTHI1606 HI1527 HS_0575 HSM_0924 0325 7375 CGSHiGG_0 CGSHiEE_0 0280, FWK62_RS0 licA HD1021* NTHI1597 HI1537 HS_1461 HSM_0542 5255 CGSHiGG_0 8705 0115

143

CGSHiGG_0 CGSHiEE_0 0275, FWK62_RS0 licB - NTHI1596 HI1538 HS_1460 HSM_0543 5260 CGSHiGG_0 8700 0110 CGSHiGG_0 CGSHiEE_0 0270, FWK62_RS0 licC - NTHI1595 HI1539 HS_1459 HSM_0544 5265 CGSHiGG_0 8695 0105 CGSHiGG_0 0265, licD - NTHI1594 - HI1540 HS_1458 HSM_0545 - CGSHiGG_0 0100 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 kdsA HD0857 NTHI1576 HI1557 HS_0946 HSM_1421 5365 0170 5165 CGSHiGG_0 FWK62_RS0 lgtA HD0466 NTHI1474 - HI1578 HS_0636a* HSM_0975 0020 7185 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 kpsF HD1168 NTHI1981 HI1678 HS_0918 HSM_1396 3670 2125 5280 CGSHiEE_0 CGSHiGG_0 lsgF HD0886 NTHI2002 HI1695 - - - 3560 2215 CGSHiEE_0 lsgE HD0885 NTHI2003 HI1696 - - - 3555 CGSHiEE_0 CGSHiGG_0 lsgD HD0883 NTHI2004 HI1697 - - - 3550 2230 CGSHiEE_0 CGSHiGG_0 lsgC - NTHI2005 HI1698 - - - 3545 2235 CGSHiGG_0 FWK62_RS0 lsgB - NTHI2006 HI1699 - HSM_1794 2245 9945 CGSHiEE_0 CGSHiGG_0 lsgA HD0882 NTHI2007 HI1700 - - - 3530 2250 CGSHiEE_0 CGSHiGG_0 wecA HD1844 NTHI2025 HI1716 - - - 3450 2330 Category of the following VF gens: Immune evasion Exopolysacc mrsA/g CGSHiEE_0 FWK62_RS0 HD0201 NTHI1664 HI1463 HS_0730 HSM_1197 haride lmM 4920 6360

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CGSHiEE_0 CGSHiGG_0 galU HD1431 NTHI0976 HI0812 HS_1117 HSM_1063 - 8000 7555 CGSHiEE_0 CGSHiGG_0 galE HD0829 NTHI0471 HI0351 HS_0789 HSM_1256 - 1245 4565 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 pgi HD0418 NTHI1475 HI1576 HS_0938 HSM_1413 5470 0035 5205 CGSHiEE_0 manA HD0765 HI1710* HS_0605 HSM_0956 3480* CGSHiEE_0 CGSHiGG_0 HS_1118, HSM_1062, FWK62_RS0 manB HD1507 NTHI0899 HI0740 8405 7190 HS_1670 HSM_1832 6770 immunoglob CGSHiEE_0 ulin A1 iga1 - NTHI1164 HI0990 - - - 7015 protease Outer HD1435, CGSHiEE_0 CGSHiGG_0 membrane ompP2 NTHI0225 HI0139 - - - HD1433 2590 3275 proteins Category of the following VF gens: Iron uptake CGSHiEE_0 CGSHiGG_0 FWK62_RS0 hitA - NTHI0177 HI0097 HS_0783 HSM_1250 2810 3025 6100 Haemophilus FWK62_RS0 iron transport hitB - NTHI0179 - - HI0098 HS_0782 HSM_1249 6105 locus CGSHiEE_0 FWK62_RS0 hitC - NTHI0180 - HI0099 HS_0781 HSM_1248 2795 6110 FWK62_RS0 hemA - - - - - HS_0810 HSM_1279 5875 FWK62_RS0 hemB - - - - - HS_0548 HSM_1661 4105 FWK62_RS0 hemC - - - - - HS_0044 HSM_1937 Heme 0330 biosynthesis FWK62_RS0 hemD HD1742 - - - - HS_0045 HSM_1938 0335 FWK62_RS0 hemE - - - - - HS_1540 HSM_0564 9460 FWK62_RS0 hemG - - - - - HS_1569 HSM_0443 9570

145

CGSHiEE_0 hemH - NTHI1329 - HI1160 HS_1047 HSM_1531 6240 FWK62_RS0 hemL - - - - HS_1229 HSM_0850 7485 CGSHiEE_0 CGSHiGG_1 FWK62_RS0 hemM HD1629 NTHI1435 HI1607 HS_0998 HSM_1476 5685 0085 4885 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 hemN HD1668 NTHI0594 HI0463 HS_0472 HSM_0771 0675 5555 0690 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 hemX HD1741 NTHI0858 HI0603m HS_0046 HSM_1939 1990 6950 0340 CGSHiEE_0 CGSHiGG_0 FWK62_RS0 hemY HD1740 NTHI0857 HI0602 HS_0047 HSM_1940 1985 6945 0345 FWK62_RS0 hemR - NTHI0202 HI0113 HS_0728 HSM_1176 6370 CGSHiEE_0 hxuA - NTHI0371 HI0264 - - - Heme/Hemo 1735 pexin- CGSHiEE_0 CGSHiGG_0 hxuB - NTHI0370 HI0263 - - - binding 1740 4100 complex CGSHiEE_0 CGSHiGG_0 FWK62_036 hxuC - NTHI0369 HI0262 - - 1745 4095 00* hgpA ------CGSHiEE_0 CGSHiGG_0 Hemoglobin hgpB - NTHI0782 HI0661 - - - 0010 6590 and CGSHiGG_0 hemoglobin- hgpC - NTHI0840 - HI0712 - - - 6875 haptoglobin binding hgpD - NTHI0736 ------CGSHiEE_0 CGSHiGG_0 proteins ------(Hgps) 8890 6430 FWK62_RS0 hgbA HD2025 - - - HI1565m HS_0720 HSM_1168 6400 Transferrin- CGSHiEE_0 binding tbpA - NTHI1168 - HI0994 HS_0449 HSM_0750 - 6995 protein 1 Transferrin- CGSHiEE_0 CGSHiGG_0 binding tbpB - NTHI1169 HI0995 HS_0448 HSM_0749 - 6990 8580 protein 2 146

Category of virulence factor genes: Toxin Cytolethal cdtA HD0902 ------distending cdtB HD0903 ------toxin cdtC HD0904 ------hhdA HD1327 ------Hemolysin hhdB HD1326 ------* encoded by ICE as a cargo gene, highlighted in the table

147

Appendix Figure 1: The graph demonstrates quality assessment of WGS using the Phred score. In this example the minimum phred quality score (Q-score) of sequences was 32. The Phred scores range from 4 to 60, with higher values corresponding to higher quality of sequence.

Phred Probability of an error in Accuracy of quality sequencing_ wrong base sequencing score placement in sequencing 10 1 in 10 90% 20 1 in 100 99% 30 1 in 1,000 99.9% 40 1 in 10,000 99.99% 50 1 in 100,000 99.999%

148

Appendix Figure 2: This graph of the FastQC assessment of a WGS demonstrates that the despite using a short-reads sequencing platform, the extensive genome coverage (150x) and using a paired-end approach increases the quality score of reads and that creation of contigs was acceptable with minimum gaps.

149

Appendix Figure 3: The circular map of UOC-KLM-ATR-014 shows the relative location of three prophages and one integrative and conjugative element (ICE) inserted in the genome. Numbers on the circle refer to the size of the genome. Secretion system types are labelled T3,4,6,7SS. Kbp: Kilo base-pair.

150

Appendix Figure 4: The circular map showing the relative location of an ICE integrated in the H. somni chromosome. The ICE is integrated in a tRNA-Leu (CAA) gene, codes for 79 genes, has a %GC content higher than the host (42%), and is located between 687500…760413 nc in strain UOC-KLM-ATR-014. A) Whole circularized draft genome, and B) inset showing where the ICE is integrated. Numbers on maps refer to the nucleotide location on the genome.

151

Appendix Figure 5: Circular map showing the relative locations of A genomic islands identified on the chromosome of H. somni strain UOC-KLM-ATR-014. A) The

circular map of the draft genome created using IslandViewer 4. Numbers on the map show the size of the genome. Red bars indicate identified genomic islands. An ICE is contained within the grey highlighted area. Also shown are two IME and three prophages. Orange dots indicate virulence and AMR genes. Five orange dots indicating virulence elements are located outside of the ICE. These

genes are involved in biofilm formation and quorum sensing as annotated using the KEGG database. As shown in inset B) all AMR genes and the metal-

Higher %GC content tolerance gene (red dot) are located within the ICE sequence. compared to host

Integrative and conjugative element (ICE) Integrative and mobilizable element (IME) 152

Prophage

Metal tolerance gene, multicopper oxidase family protein B

AMR genes: tet(H), Sul2/folP, APH (3'')-Ib, APH

(6)-Id, and APH (3')-Ia.

Integrative and conjugative

element (ICE)

153

Appendix Table 2: The gene content and gene products of H. somni ICE sequences Size of the gene # Location on chromosome Product of the gene *F/R Name of the gene (bp)

1 687628..688452 family protein 825 F ParA

2 688464..689825 replicative DNA helicase 1362 F dnaB

3 689834..691483 chromosome partitioning protein 1650 F ParB

4 691476..692033 DUF2857 domain-containing protein 558 F

5 692192..693382 hypothetical protein 1191 F

TIGR03761 family integrating conjugative 6 693561..694319 759 F element protein

7 694328..694813 DUF3158 family protein 486 F

8 695170..695622 single-stranded DNA-binding protein 453 F Ssb

9 695932..696120 hypothetical protein 189 F

10 696161..696463 ISL3 family transposase 303 F

11 696463..697773 tetracycline efflux MFS transporter Tet(H) 1311 F tet(H)

12 697869..699071 TetR family transcriptional regulator 1203 R TetR(H)

13 699163..699786 hypothetical protein 624 F

14 699789..700307 hypothetical protein 519 R

154

alcohol dehydrogenase catalytic domain- 15 700356..700535 180 R containing protein

16 700624..700779 multicopper oxidase family protein 156 F Mco

17 700869..702416 DUF411 domain-containing protein 1548 R Mco-regulatory

18 702430..702885 hypothetical protein 456 R

19 703067..703387 aldo/keto reductase 321 R

20 703386..704153 hypothetical protein 768 F

21 704692..705402 hypothetical protein 711 R

22 705498..705782 hemophilus-specific protein 285 F

23 705879..706397 DNA topoisomerase III 519 F

24 706557..708608 DUF3577 domain-containing protein 2052 F

25 709426..709857 hypothetical protein 432 F

26 709963..710643 heme utilization protein 681 F

27 710669..711076 hypothetical protein 408 F

28 711156..711518 hypothetical protein 363 F

29 711631..711891 lipoprotein 261 F

TIGR03759 family integrating conjugative 30 712050..712679 630 F element protein

31 712679..713452 lytic murein transglycosylase 774 F

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integrating conjugative element protein- 32 713431..714201 771 F Mpf structure PFL_4695family type IV conjugative transfer system coupling 33 714204..714710 507 F traD protein

34 714710..716911 hemophilus-specific protein 2202 F Mpf structure

TIGR03747 family integrating conjugative Mpf structure 35 716904..717257 354 F element membrane protein

36 717254..717949 hypothetical protein 696 F

37 717981..718364 hypothetical protein 384 R

TIGR03758 family integrating conjugative Mpf structure 38 718551..718877 327 F element protein

39 718874..719110 DUF2976 domain-containing protein 237 F Mpf structure

40 719125..719514 TIGR03750 family conjugal transfer protein 390 F Mpf structure

TIGR03746 family integrating conjugative Mpf structure 41 719537..719902 366 F element protein TIGR03749 family integrating conjugative Mpf structure 42 719906..720550 645 F element protein TIGR03752 family integrating conjugative Mpf structure 43 720550..721434 885 F element protein TIGR03751 family conjugal transfer Mpf structure 44 721446..722900 1455 F lipoprotein

45 722913..723311 conjugative transfer ATPase 399 F Mpf structure

46 723314..726151 TraC 2838 F Mpf structure

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47 726151..726579 hemophilus-specific protein 429 F Mpf structure

48 726569..726886 conjugal transfer protein 318 F TraG

49 726897..728369 hypothetical protein 1473 F

50 728415..728756 hypothetical protein 342 R

51 728777..729247 hypothetical protein 471 R

integrating conjugative element protein- Mpf structure 52 729463..729891 429 R PFL_4711family TIGR03756 family integrating conjugative Mpf structure 53 729912..731924 2013 R element protein TIGR03757 family integrating conjugative Mpf structure 54 731942..732883 942 R element protein

55 732880..733323 hypothetical protein 444 R

56 733697..734050 hemophilus-specific protein 354 F Mpf structure

57 734122..734367 hypothetical protein 246 F

58 734466..734861 hypothetical protein 396 F

59 734939..735781 hemophilus-specific protein 843 F Mpf structure

60 735897..736304 DUF1738 domain-containing protein 408 F Mpf structure

61 736549..737523 DUF1281 C domain-containing protein 975 F Mpf structure

62 737663..738409 SAM-dependent DNA methyltransferase 747 F

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63 738482..739279 relaxase-conjugal transfer nickase/helicase 798 F TraI

64 739707..741686 site-specific integrase-Tyrosine recombinase 1980 F XerD

65 741842..742606 IS91-like element ISVsa3 family transposase 765 F

66 743670..745163 LysR family transcriptional regulator 1494 R

chloramphenicol/florfenicol efflux MFS 67 745275..745580 306 R floR transporter FloR

68 745608..746822 DUF3363 domain-containing protein 1215 R

69 747099..747983 hypothetical protein 885 R

70 748304..748528 IS91 family transposase 225 R

sulfonamide-resistant dihydropteroate synthase 71 748611..749903 1293 R sul2 Sul2

72 750066..750911 aminoglycoside O-phosphotransferase 846 F aph(3'')-Ib

73 751080..751883 aminoglycoside O-phosphotransferase 804 F APH(6)-Id

74 751883..752719 aminoglycoside O-phosphotransferase 837 F APH(3')-Ia

75 753055..753870 mobilization protein A 816 F

76 754787..755797 tyrosine-type recombinase/integrase- 1011 F XerC

77 757146..758045 Mu DNA-binding domain 900 R

78 758195..758632 PBECR4 domain-containing protein 438 F

79 759364..759942 family protein 579 R ParA

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Genes with similar function are highlighted with the same color. Size of the genes is presented as base-pair (bp). Color key: Blue: horizontal movement regulation, Black: potential virulence factor, Yellow: maintaining ICE cellular homeostasis, Green: antimicrobial resistance gene, Purple: Metal-tolerance gene, Red: mating pore forming (Mpf) structure and functionality, Grey: hypothetical protein. *F: Forward, R: Reverse.

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a b

Appendix Figure 6: The homology of the AMR gene floR protein structure is shown. a) shows the floR protein structure and b) shows the protein modelled from the reference floR gene. The floR protein from the ICE sequence has a more irregular 3D form compared to the reference protein. The pairwise amino acid sequence alignment shows that the ICE-encoded floR protein is missing amino acid residues, c) gaps in the green bar indicate missing amino acids. Numbers indicate position of amino acids in the protein sequence.

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Appendix Figure 7. An annotated circularized map of the ICE of the Canadian H. somni strain KLM-014. Numbers refer to size of the ICE (bp). Arrows represent direction of gene transcription (forward, and reverse).

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Appendix Figure 8. Comparison of genome arrangement and size- similarities in ICEs from BRD- associated bacteria. Genes carried by the ICE are represented as arrows. The direction of gene transcription (forward and reverse) is represented by the direction of the arrows. The shaded areas between ICEs represent sequence similarity with darker shades indicating higher homology. A) ICEs of H. somni had similar genome arrangement, except the ICE illustrated in B) strain USDA-ARS- A USMARC-63374. C) ICE of M. haemolytica and D) ICE from P. multocida showing a very different genome arrangement compared to ICEs of H. somni.

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PGA

B Appendix Figure 9. Illustration of bioinformatic workflow used in this study for identifying and classifying ICEs and their genes. A) the pipeline for initial work on WGS, and B) tools used identify MGEs and ICE. * the NCBI prokaryotic genome annotation pipeline.

the comprehensive

antimicrobial resistance AMR database (CARD) 163