Development of Diagnostic Assays for Melioidosis, Tularemia, Plague And

Home , Bubonic plague, Melioidosis, Plague (disease), Tularemia, Yersinia enterocolitica

University of Nevada, Reno

Development of Diagnostic Assays for

Melioidosis, Tularemia, Plague and COVID19

A dissertation submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Cellular and Molecular Biology

Derrick Hau

Dr. David P. AuCoin / Dissertation Advisor

December 2020 THE GRADUATE• SCHOOL

We recommend that the dissertation prepared under our supervision by

entitled

be accepted in partial fulfillment of the requirements for the degree of

Advisor

Committee Member

Graduate School Representative

David W. Zeh, Ph.D., Dean Graduate School

December 2020 i

Abstract

Infectious diseases are caused by pathogenic organisms which can be spread throughout communities by direct and indirect contact. Burkholderia pseudomallei,

Francisella tularenisis, and Yersinia pestis are the causative agents of melioidosis, tularemia and plague, respectively. These bacteria pertain to the United States of

America Federal Select Agent Program as they are associated with high mortality rates, lack of medical interventions and are potential agents of bioterrorism. The novel coronavirus disease (COVID-19) has resulted in a global pandemic due to the highly infectious nature and elevated virulence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Proper diagnosis of these infections is warranted to administer appropriate medical care and minimize further spreading. Current practices of diagnosing melioidosis, tularemia, plague and COVID-19 are inadequate due to limited resources and the untimely nature of the techniques. Commonly, diagnosing an infectious disease is by the direct detection of the causative agent. Isolation by bacterial culture is the gold standard for melioidosis, tularemia and plague infections; detection of

SAR-CoV-2 nucleic acid by real-time polymerase chain reaction (RT-PCR) is the gold standard for diagnosing COVID-19. These techniques, however, can often be time consuming and require laboratory equipment and trained individuals not readily available in low-technology settings. The present dissertation outlines the development of alternative diagnostic assays for melioidosis, tularemia, plague, and COVID-19 as three sections: (I) Diagnostic Target Identification, (II) Immunoassay Development, (III)

Evaluation of Immunoassays

First, the identifications of circulating B. pseudomallei and F. tularensis proteins in clinical specimens were performed using a multi-armed approach to determine putative biomarkers of melioidosis and tularemia. The approach consisted of three methods for identifying circulating bacterial proteins resulting in a comprehensive methodology for determining potential biomarkers. The three methods were (i) In vivo Microbial Antigen

Discovery (InMAD), (ii) patient serological markers and (iii) protein profiling by mass spectrometry. Converging results from the three analyses yielded putative targets to evaluate as biomarker of melioidosis or tularemia. The B. pseudomallei target list consisted of seven proteins: BPSS1531, BPSL2298, BPSL1504, BPSS0311,

BPSL3092, BPSL1445, and BPSL3319. The F. tularensis target list consisted of five proteins: FTT1357/1712, FTT0308, FTT0928c, FTT0954c and FTT1349/1704. Upon validation, protein targets can be used to develop alternative assays for the diagnosing melioidosis and tularemia.

Second, immunoassays were developed for the detection of two Y. pestis proteins suggested as biomarkers of plague: low-calcium response V (LcrV) and capsular fraction-1 (F1). A total of twenty-two high affinity monoclonal antibodies (mAbs) were isolated from BALB/c mice immunized with recombinant LcrV, F1 and LcrV-F1 fusion protein via hybridoma technology. mAbs were characterized by Western blots, enzyme- linked immunosorbent assays (ELISA), and surface plasmon resonance. Antigen- capture ELISAs and lateral flow immunoassays (LFI) were developed using the mAbs and optimized for analytical sensitivity. Prototype LFIs were evaluated to detect LcrV and

F1 in surrogate clinical specimens. A multiplexed LFI detecting both LcrV and F1 was assessed against a panel of Y. pestis isolates, clinical near neighbors and other bacterial

Select Agents indicating high assay specificity. The immunoassays developed can be

iii

used to evaluate clinical samples, further determining the diagnostic power of the LcrV and F1 proteins in clinical samples.

Third, the capsular polysaccharide (CPS) of B. pseudomallei has been identified as a biomarker of melioidosis. Previous studies indicate CPS is filtered through the kidneys and excreted in urine during an infection. The Active Melioidosis Detect Plus (AMD+TM) is an updated version of the point-of-care, rapid diagnostic tool developed through a collaboration between the Diagnostics Discovery Laboratory and InBios International Inc

(Seattle, WA). The AMD+TM LFI was used to evaluate twenty melioidosis urine samples which includes temporal sets collected from two patients receiving treatment. CPS was detected in 80% of the melioidosis urine samples by the AMD+TM LFI. Additionally, three isolates of B. pseudomallei (K96243, 1026b, Bp82) were assessed to determine concentrations of CPS in cultures grown in vitro. Results suggest a large concentration of CPS is produced in vitro, with quantifiable amounts by ELISA within hours of inoculation. This suggests the detection of CPS in bacterial culture may be an alternative method for diagnosing melioidosis with the sensitivity of bacterial culture, and specificity and timeliness of an immunoassay.

Lastly, the COVID-19 pandemic has led to over 46 million infections and 1.2 million deaths worldwide. SARS-CoV-2 is highly infectious and more virulent than other known coronaviruses. Diagnoses by RT-PCR and contact tracing have been essential for minimizing the spread of infection, however additional countermeasures including vaccines and therapeutics are warranted. Viral neutralization is associated with blocking the receptor-binding domain of the spike protein (RBD). A cohort study examining antibody titers against RBD in individuals who have recovered from acute COVID-19

suggest low and waning titers within months post-recovery. As accounts of reinfections have been documented, low titers may further indicate minimal protective immunity for those who have previously been infected. Additionally, two individuals had 4-fold to 8- fold increases in IgG response ninety days after enrollment and may suggest reinfection.

Further evaluation of patient history will elucidate the possibilities of re-exposure and assess IgG response to RBD as a retroactive method of diagnosing COVID-19 reinfections.

Acknowledgements

I would like to express my gratitude to my advisor, Dr. David AuCoin. I am grateful for the opportunity to pursue a graduate degree in his laboratory as well as for the mentorship I have acquired over the past several years. I would also like to acknowledge my committee members: Dr. Thomas Kozel, Dr. Cyprian Rossetto, Dr. Paul Brett, and

Dr. David Quilici. I am thankful for your knowledge and support throughout the course of this work.

I would like to share my appreciate for all past and present members of the Diagnostic

Discovery Laboratory and the Molecular Microbiology and Immunology department. I am thankful for everyone’s contributions to my academic growth and for keeping a vibrant work environment.

I would like to thank my family and friends for their love and endless support. And lastly, a special shoutout to Spam, the best pup who has stuck by my side throughout the entire process.

Table of Contents

PAGE

Abstract...... i

Acknowledgements………...... v

Table of Contents…………………...... vi

List of Tables..…………...…………………...... ix

List of Figures.…………...…………………...... xi

Chapter 1: Introduction...... 1

1.1 Overview

1.2 Melioidosis

1.3 Tularemia

1.4 Plague

1.5 COVID19

Chapter 2: Multi-armed Approach for Identifying Circulating Bacterial Proteins in

Melioidosis and Tularemia Patient Samples...... 12

2.1 Abstract

2.2 Background

2.3 Methods

2.4 Results

vii

2.5 Discussion

2.6 Figures and Tables

Chapter 3. Development of a dual antigen lateral flow immunoassay for detecting Yersinia pestis………………………….…………………………………………………………………68

3.1 Abstract

3.2 Background

3.3 Methods

3.4 Results

3.5 Discussion

3.6 Figures and Tables

Chapter 4. Detection and Quantitation of Capsular Polysaccharide (CPS) in Clinical

Melioidosis Samples and Laboratory-grown Burkholderia pseudomallei Isolates……..112

4.1 Abstract

4.2 Introduction

4.3 Materials and Methods

4.4 Results

4.5 Discussion

4.6 Figures and Tables

Chapter 5. Temporal Profile of Immunoglobulin G Titers against SARS-CoV-2 RBD in

Recovered Patients of Northern Nevada…………………………………………………...135

4.1 Abstract

4.2 Introduction

viii

4.3 Methods

4.4 Results

4.5 Discussion

4.6 Figures

Chapter 6: Conclusion……………………...... …………………………………………143

Literature Cited……………………………………………………………………………...... 146

List of Tables

Chapter 2: Multi-armed Approach for Identifying Circulating Bacterial Proteins in Melioidosis and Tularemia Patients

Table 1 Summary of melioidosis samples evaluated for circulating 44 Burkholderia pseudomallei proteins

Table 2 Burkholderia pseudomallei protein hits by NAPPA array probed 46 with InMAD immune sera

Table 3 Burkholderia pseudomallei protein hits by NAPPA probed with 47 melioidosis patient sera

Table 4 Summary of melioidosis samples evaluated for circulating 48 Francisella tularensis proteins

Table 5 Francisella tularensis protein hits by NAPPA array probed with 49 InMAD immune sera

Table 6 Francisella tularensis protein hits by NAPPA probed with tularemia 50 patient sera

Table 7 Proteins to be evaluated by validation studies as biomarkers of 51 melioidosis and tularemia

Table S1 List of Burkholderia pseudomallei proteins identified by data- 52 dependent acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS).

Table S2 List of Burkholderia pseudomallei protein hits by data-independent 57 acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS).

Table S3 List of Francisella tularensis proteins identified by data-dependent 67 acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS).

Chapter 3. Development of a dual antigen lateral flow immunoassay for detecting Yersinia pestis

Table 1 Monoclonal antibody (mAb) library against Y. pestis LcrV and F1 100 antigens

Table 2 Affinity and kinetics analysis of Y. pestis mAbs by surface plasmon 101 resonance

Table 3 Assay sensitivity of the top 4 mAb pairs (LcrV or F1) by lateral flow 102 immunoassay

Table 4 Limit of detection of enzyme-linked immunosorbent assays using 103 recombinant LcrV and F1 antigens in buffer

Table S1 Primers for cloning LcrV and F1 genes 108

Table S2 Preliminary assay sensitivities of top mAb pairs by LFI for LcrV 109

Table S3 Preliminary assay sensitivities of top mAb pairs by LFI for F1 110

Chapter 4. Detection and Quantitation of Capsular Polysaccharide (CPS) in Clinical Melioidosis Samples and Laboratory-grown Burkholderia pseudomallei Isolates

Table 1 Growth of Burkholderia pseudomallei isolates (K96243, 1026b, 129 and Bp82) in Luria-Bertani (LB) broth.

Table 2 Summary of melioidosis patient samples collected by the Menzies 130 School of Health Research

Table 3 Summary of AMD+ LFI testing and CPS quantitation by ELISA of 131 melioidosis patient urine samples

Table S1 Concentrations of capsular polysaccharide (CPS) in supernatant 132 fraction of Burkholderia pseudomallei cultures

Table S2 Concentrations of capsular polysaccharide (CPS) in cellular 133 fraction of Burkholderia pseudomallei cultures.

List of Figures

Chapter 2: Multi-armed Approach for Identifying Circulating Bacterial Proteins in Melioidosis and Tularemia Patients

Figure 1 Strategy for circulating bacterial protein discovery. 38

Figure 2 Western blot analysis of InMAD immune sera against Burkholderia 39 pseudomallei Bp82 lysate.

Figure 3 Analysis of 53 complete Burkholderia pseudomallei isolate 40 genomes to identify core and unique genes

Figure 4 Venn diagram of the potential biomarkers of melioidosis 41

Figure 5 Western blot analysis of InMAD immune sera against Francisella 42 tularensis LVS lysate

Figure 6 Venn diagram of the potential biomarkers of tularemia 43

Chapter 3. Development of a dual antigen lateral flow immunoassay for detecting Yersinia pestis

Figure 1 Western blot analysis of anti-LcrV monoclonal antibodies (mAbs) 96 against Yersinia pestis Harbin-35 lysate.

Figure 2 Western blot analysis of anti-F1 monoclonal antibodies (mAbs) 97 against Yersinia pestis Harbin-35 lysate.

Figure 3 Sensitivity of Yersinia pestis lateral flow immunoassays (LFI) using 98 recombinant LcrV and F1.

Figure 4 Specificity testing of dual Yersinia pestis lateral flow immunoassay 99 (LFI) against clinically relevant bacterial panel.

Figure S1 LFI prototypes were tested against Y. pestis Harbin-35 lysate for 104 the detection of LcrV

Figure S2 Limit of detection of the LcrV LFI prototype in six pools of 105 surrogate clinical samples

Figure S3 Limit of detection of the F1 LFI prototype in six pools of surrogate 106 clinical samples

xii

Figure S4 Antigen-capture ELISAs were performed to determine the limits of 107 detection

Chapter 4. Detection and Quantitation of Capsular Polysaccharide (CPS) in Clinical Melioidosis Samples and Laboratory-grown Burkholderia pseudomallei Isolates

Figure 1 Quantitation of capsular polysaccharide (CPS) in Burkholderia 126 pseudomallei cultures

Figure 2 Active Melioidosis Detect TM plus (AMD+) lateral flow immunoassay 127 (LFI) used to evaluate melioidosis patient urine samples collected at the Menzies School of Health Research in Darwin, Australian.

Chapter 5. Temporal Profile of Immunoglobulin G Titers against SARS-CoV-2 RBD in Recovered Patients of Northern Nevada

Figure 1 Temporal changes of anti-receptor-binding domain (RBD) titers in 142 Northern Nevada patients recovered from an acute SARS-CoV-2 infection

Chapter 1. Introduction

1.1 Overview

The following chapters outline the developmental procedure for constructing novel diagnostic assays for infectious diseases. The process is broken down into three stages:

I. Diagnostic Target Identification (Chapter 2)

II. Immunoassay Development (Chapter 3)

III. Evaluation of Immunoassays (Chapters 4 & 5)

The work put forth ensues the development of diagnostic assays for melioidosis, tularemia, plague, and COVID-19, each within different stages of development. Here in chapter 1, general background is provided for each infectious disease investigated in the subsequent chapters.

1.2 Melioidosis

Burkholderia pseudomallei, a Gram-negative saprophyte, is the causative agent of melioidosis. The word melioidosis comes from the Greek melis meaning “distemper”, oid indicating “resemblance”, and the suffix osis implying disease [1]. The infection was first described by Alfred Whitmore and C. S. Krishnaswami in 1912 with a patient who experienced long-lasting fever and abscess formation at the site of morphine injections

[2]. Glanders, caused by Burkholderia mallei, was initially suspected; however, the individual did have close contact with horses making the diagnosis unlikely. Further evaluation found the bacterium responsible for infection to be motile, a key feature discrediting B. mallei [2]. Whitmore coined the new etiological agent B. pseudomallei due to its glanders-like clinical manifestation [2].

Epidemiology

Melioidosis is considered one of the most neglected tropical diseases in the world. B. pseudomallei is endemic to Southeast Asia and northern Australia; however recent studies suggest South Asia bears a larger burden than is actually reported [3]. The model also estimated 165,000 melioidosis infections worldwide with a case fatality rate of 54% in 2015 [3]. Prevalence of melioidosis in Thailand averages 3.9 - 4.4 cases per

100,000 individuals, with higher prevalence in the northeastern and eastern providences

(12.6-14.9 cases per 100,000) [4-7]. Two hospitals in these regions with higher prevalence estimate an economic setback associated with melioidosis to be between

$150,000 - $450,000 per year [8]. In comparison, the prevalence in northern Australia averaged 19.6 cases per 100,000 individuals [9]. This would suggest a large economic setback in Australia as prevalence is greater and advancements in medical standards are further along compared to that available in Thailand.

Clinical Features

The complexity and severity of melioidosis is demonstrated by a broad range of disease outcomes [10, 11]. The incubation period for melioidosis can range between 1 to 21 days, with short times correlating to high inoculum [12]. Melioidosis presents with a multitude of clinical manifestations dependent on the route of infection and infection foci.

Common routes of infection include cutaneous, ingestion, and inhalation [13]. Cutaneous infections result in the development of skin ulcers, while inhalation results in pneumonia

[14-16]. Interestingly, ingestion leads to more bacteremia as opposed to pneumonia [17,

18]. Risk factors for melioidosis include diabetes mellitus, chronic liver or kidney disease, alcohol abuse, long-term steroid use, hematologic malignancy, neutropenia or neutrophil dysfunction, chronic lung disease, thalassemia, and forms of immunosuppression [13].

Bacterial isolation remains the gold standard for diagnosing melioidosis [12]. The low bioburden associated with melioidosis results in low sensitivity for such method [4].

Furthermore, diagnosing an infection is vital for administering proper medical intervention as B. pseudomallei is intrinsically resistant to many antibiotics including some considered last-resort treatments for other bacterial infections [19]. The recommended treatment for melioidosis consists of an extensive two-phase regiment for complete eradication of the bacterium [13, 20-23]. Presently, there is no approved vaccine for melioidosis.

Global Significance

B. pseudomallei is classified as a Category B bioterrorism agent, though no accounts of malicious use have been documented. The ease of spread, highly virulent nature, and lack of medical countermeasures warrant concerns for malevolent distribution of B. pseudomallei. Near neighbor B. mallei has been used as an agent of bioterrorism by infecting enemy cavalry during the American Civil War, World War I and World War II

[24, 25]. Dissemination of B. pseudomallei would not only be catastrophic on a public health standpoint, but also affect ecological systems as the bacterium can persist in the environment as well as infect a large array of hosts.

1.3 Tularemia

Francisella tularensis is a facultative intracellular pathogen and the causative agent of tularemia. In 1911, McCoy and Chapin discovered ground squirrels exhibiting plague-like lesions in Tulare County, California [26]. Difficulties presented in isolating bacteria, suggesting these squirrels were not infected with Yersinia pestis, the causative agent of plague. The etiological agent was isolated in 1912 and determined to be a nonmotile

Gram-negative coccobacillus, in which McCoy and Chapin named Bacterium tularense after Tulare County [27]. Large numbers of B. tularense were found in diseased animals and staining with carbol fuchsin or aniline gentian violet indicated a clear coating surrounding the bacterium which suggested a capsule [27]. Interesting, this capsule was not observed around bacteria found in intracellularly [27]. In 1927, the bacterium was identified to be transmissible via Dermacentor andersoni, a member of the tick family

Ixodidae [28]. Dr. Edward Francis’s contributions resulted in diagnosing over 14,000 cases of tularemia. To honor his work, the organism was renamed Francisella tularensis in 1959 [29, 30].

Epidemiology

F. tularensis is one of the most pathogenic organisms as the infectious dose has been reported as few as 10 colony forming units [31]. Tularemia is a rare disease in the United

States of America with only about 200 cases reported annually [32]. Most cases are in the northern hemisphere, with Finland, Sweden, Spain and Turkey reporting an accumulative 2,000 cases annually [33]. Recent studies have identified F. tularensis in

Australia [34-37]. There are four subspecies of F. tularensis: tularensis holarctica, novicida, and mediasiatica [38]. F. tularensis subsp. tularensis (type A) are prominent in the United States of America and the most virulent among the subspecies [39]. F. tularensis subsp. holartica type B are ubiquitously found in the northern hemisphere and generally less lethal in humans and animals [40]. Subspecies tularensis and holarctica are responsible for the majority of human infections, however infections caused by subspecies novicida in immunosuppressed individuals have been determined [40, 41].

As a zoonotic disease, tularemia infects mammals, birds, reptiles and fish and is associated with arthropod transmission via ticks, flies and mosquitos [42, 43]. Ecological factors for promoting bacterial maintenance is poorly understood, but rabbits and hares are considered important hosts for F. tularensis [44]. Persistence of F. tularensis in water sources have been suggested due to formation of biofilms and/or an intracellular lifecycle in free-living amoebas [45-47].

Clinical Features

Tularemia is a febrile illness which presents with nonspecific clinical symptoms. The average incubation period is between 3 to 5 days but can extent upwards of 21 days

[48]. The most common route of infection is subcutaneous via arthropod transmission resulting in ulceroglandular tularemia. This form of tularemia accounts for about 90% of all reported cases and noted by the development of an ulcer at the infection site [49].

Other routes include ingestion of infected animals and inhalation of infectious droplets.

Typhoidal and pneumonic tularemia present with flu-like symptoms including fever, exhaustion, shortness of breath, and weight loss [50]. Pneumonic tularemia is the most serious form and has a mortality rate of 60% when left untreated [51]. The gold standard for diagnosing tularemia is bacterial culture, however the fastidious nature of F. tularensis results in low assay sensitivity [52]. Alternativity, detection of anti- lipopolysaccharide (LPS) antibodies can be used to diagnose tularemia [53]. F. tularensis remains susceptible to aminoglycosides (i.e. streptomycin and gentamicin) and are recommended as the first-line treatment options [54]. All isolates of F. tularensis have been identified to be inherent resistance to beta-lactams and azithromycin [54].

Mortality rates drop to 1-3% when effective treatment is administered [55]. Alas, there is currently no approved vaccine for tularemia.

Global Significance

Low infectious dose, rapid disease progression, and lack of medical countermeasures contribute to F. tularensis being classified as a Category A bioterrorism agent. At the time of the Helsinki Accords, the United States of America had stockpiled upwards of

450 kg of dry-powder F. tularensis with unknown amounts from the Soviet bioweapons program [51]. Estimates from the World Health Organization indicated 50 kg released by aerosolization over a metropolitan area would result in 5 million tularemia infections [56].

An economic burden of $5.4 billion dollars per 100,000 persons exposed was projected in 1997 [57]. Though no account of malevolent dissemination of F. tularensis is recorded, modern concerns are present due to the accessibility of the etiological agent.

1.4 Plague

Yersinia pestis, a Gram-negative coccobacillus, is the causative agent of plague. The bacterium was identified by Alexandre Yersin and Shibasaburo Kitasato in 1894 during an outbreak in Hong Kong, later to be marked as the beginning of the third plague pandemic in written history [58, 59]. The bacterium was isolated and determined the etiological agent by Koch’s postulates. Yersin continued his research at the Pasteur

Institute in Paris, France and found the bacterium to be transmissible by fleas [60]. By

1897, Yersin developed anti-serum for patients in Hong Kong reducing mortality rates to

9% [61, 62]. Yersin’s key finding and his emphasis on studying buboes lead to the nomenclature change from Pasteurella pestis to Yersinia pestis in 1970 [63].

Epidemiology

Y. pestis is present in all geographical regions besides Oceania [64]. Plague is a zoonosis commonly associated with small mammals and their fleas. Over 200 species of mammals and 150 species of fleas can be naturally infected by Y. pestis [65]

Transmission to humans is commonly through flea bites, contact with animal excretions, and inhalation of aerosolized droplets [66, 67]. The Y. pestis lifecycle is comprised of two stages associated with either the flea or the mammalian host [68]. The bacterium is equipped with three plasmids encoding for several virulence factors including a capsule and type III secretion system, of which are temperature sensitive and upregulated within the mammalian host [69]. Interestingly, human infections do not play a long-term role in the persistence of Y. pestis in a community [70]. Madagascar accounts for most plague cases reported and ranged between 200-700 infections annually between 2010 - 2015

[71]. Notably, the 2017 plague season resulted in 2,417 infections with a case fatality rate of 8.6% [72]. This outbreak was highlighted by an increased number of pneumonic infections suggesting human-to-human transmission [73]. Fortunately, the 2017 outbreak was generally contained due to proper measures in place for the annual plague season

[74].

Clinical Features

Plague is a febrile illness with varying clinical presentations dependent on the form of infection: bubonic, pneumonic, or septicemic. Bubonic plague is the most common form and associated with inflammation of the lymph nodes and formation of bacterial filled swellings called buboes. Though considered the least severe form of infection, bubonic plague has a mortality rate of 40-70% when left untreated and can progress into a secondary infection [75]. Pneumonic and septicemic plague present with flu-like symptoms and have extremely short incubation periods (1-3 days) [76]. The rapid

progress of pneumonic and septicemic plague result in a narrow window in which antibiotic therapy is effective [77]. Without medical intervention, these forms of plague are nearly always fatal [75]. The gold standard for diagnosing plague is bacterial isolation [78]. Bubonic plague is easily detected by the identification of buboes.

Pneumonic and septicemic plague are much more difficult to differentiate based on clinical presentation. Patients exhibiting plague-like symptoms in endemic regions are precautionarily put on antibiotic treatments to mitigate disease onset [79]. Doxycycline and gentamicin are the recommended antibiotic for treating plague, however streptomycin and ciprofloxacin are also approved treatment options [80-82]. No approved vaccine is available for the prevention of plague.

Global Significance

There have been three major plague pandemics documented in written history resulting in about 200 million deaths collectively: Justinian Plague of 541, Black Death of 1347, and the Third Plague Pandemic in 1894 [70]. Each outbreak has been associated with independent emergences of Y. pestis from rodent populations into human populations

[83, 84]. Wet climates have been associated with accelerated spreading of communicable diseases as rodent populations are driven into populate environments such as cities and town [85, 86]. Y. pestis is classified as a Category A bioterror agent as the dissemination would be catastrophic to a community. Accounts of weaponizing the bacterium have been documents in medieval siege warfare as well as dissemination of plague-infected fleas during World War II [87]. The United States of America and

Soviet Union bioweapons programs had both investigated the utility of Y. pestis as a weapon of mass destruction [88]. Furthermore, drug-resistant strains of Y. pestis have been isolated in patients, indicating resistance via transferable plasmids [89, 90]. The

imminent threat of Y. pestis on national security and public health remains as the bacterium is ubiquitously present around the world and susceptible to genetic engineering.

1.5 COVID19

Coronavirus disease 2019 (COVID19) is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has resulted in a pandemic signified by pneumonia with multiorgan dysfunction [91]. SARS-CoV-2 is an enveloped, positive- sense RNA virus pertaining to the Coronavirus family highlighted by crown-like spikes on the surface [92]. The first accounts of COVID19 originated in Wuhan City, China in

December 2019 [93]. The rapid transmission around the world can be attributed to the highly infectious nature along with the ease of modern transportation [94].

Epidemiology

As of November 2, 2020, over 46 million COVID19 cases have been reported worldwide with 1.2 million associated deaths [95]. The initial outbreak of COVID19 began in the

Hubei providence in central China and has then emerged in all continents besides

Antarctica [95]. The first cluster of infections included 27 individuals who presented with symptoms aligning with viral pneumonia and found to be linked to the Huanan Seafood

Wholesale Market [96, 97]. Prior to the COVID19 outbreak, six other coronaviruses were identified to circulate in humans. Four of the six coronaviruses (HCoV-OC43, HCoV-

229E, HCoV-NL63, HCoV-HKU1) cause only mild respiratory disease typically designated as the common cold [98]. More notable are severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East Respiratory Syndrome coronavirus

(MERS-CoV) which have caused outbreaks in 2003 and 2015, respectively. Compared

to COVID19, the SARS-CoV and MERS-CoV outbreaks had greater case fatality rates,

9% and 36% respectively. However the increased infectivity of SARS-CoV-2 has attributed to wider spreading of the disease and a larger case count [99, 100].

Comparatively, the total number of deaths from SARS-CoV-2 exceeds SARS-CoV by

143-fold and MERS-CoV by 2247-fold [95, 99].

Clinical Features

Clinical manifestations are highly variable among those infected with SARS-CoV-2 [94].

The incubation period for COVID19 ranges between 2.1 to 11.1 days, averaging 6.4 days [101]. Most individuals experience mild symptoms including fever, fatigue, dry cough, and loss of smell [102, 103]. More severe cases may result in hospitalization, ventilator use, or potentially intubation [104]. Disease severity may increase in those with co-morbidities such as diabetes, chronic kidney diseases, hypertension, and other cardiovascular diseases [105]. Increasing age is also a factor for heightened disease severity [106]. Current methods of diagnosing COVID19 are real-time polymerase chain reaction, antigen tests, or serodiagnosis [107]. Presently, there are no approved treatments or vaccines available for COVID19 infections.

Global Significance

Within eleven months, 46 million COVID19 infections have been reported with a case fatality rate of 2.6% worldwide. Several cases of reinfections have been identified which may indicate poor protective immunity in those recovered from an infection [108-110].

Some individuals may not experience any symptoms or clinical manifestations, and provide a means for silently spreading the disease [111]. More research is warranted to

determine effective countermeasure for COVID19. SARS-CoV-2 will remain a threat to public health as the virus is highly infectious and minimal countermeasures in place.

Chapter 2. Multi-armed Approach for Identifying Circulating Bacterial Proteins in

Melioidosis and Tularemia Patient Samples

Derrick Hau1, Kathryn J. Pflughoeft1, Emily E. Hannah1, Sujata G. Pandit1, Haley

DeMers1, Heather R. Green1, Peter N. Thorkildson1, Shilpa Sharma1, Teerapat Nualnoi1,

D. Mitchell Magee2, Lusheng Song2, Joshua LaBaer2, Rebekah J. Woosley3, David R.

Quilici3, Mark Mayo4, Bart J. Currie4, Yasemin Oszurecki5, Jason W. Sahl6, Paul Keim6, and David P. AuCoin1*

1 Department of Microbiology and Immunology, University of Nevada Reno School of

Medicine Reno, Nevada, United States of America

2 Biodesign Institute, Arizona State University, Tempe, Arizona, United States of America

3 Mick Hitchcock, Ph.D. Nevada Proteomics Center, University of Nevada, Reno, Nevada,

United States of America

4 Royal Darwin Hospital Campus, Menzies School of Health Research, Darwin, Northern

Territory, Australia

5 Hacettepe University, Faculty of Medicine, Ankara, Turkey

7 Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona

*Corresponding author

Email: [email protected]

2.1 Abstract

The detection of pathogen-associated macromolecules in clinical samples is a powerful alternative to more traditional gold standards of diagnosing infectious diseases.

Burkholderia pseudomallei and Francisella tularensis are the causative agents of melioidosis and tularemia, respectively. These facultative, intracellular bacteria are categorized as Tier 1 Select Agents by the United States Federal Government as they have the capacity for large-scale dissemination, elevated rates of mortality and morbidity, and have minimal medical countermeasures in place. B. pseudomallei is prevalent in tropical regions and is intrinsically resistant to many first-line antibiotics. F. tularensis is ubiquitously found in the northern hemisphere and has an infection dose as few as 10 colony forming units. Current gold standard for diagnosing these infections is blood culture, however this method is inadequate and timely. The multifaceted display of clinical presentations of melioidosis and tularemia further emphasize the need for specific, yet rapid diagnostics. Detection of shed or cell-surface associated biomarkers can be rapid and accommodate for proper administration of therapeutics. To further characterize viable bacterial targets present during an infection, a multi-armed approach was utilized in which clinical melioidosis and tularemia samples were analyzed by direct and indirect platforms. First, the In vivo Microbial Antigen Discovery (InMAD) platform utilized syngeneic CD1 mice to indirectly detected bacterial proteins in clinical samples in conjunction with a high-density nucleic acid protein array (HD-NAPPA). Secondly, patient serology was evaluated on the HD-NAPPA to determine generated antibody response in the host as these proteins may be shed targets from these intracellular pathogens. Third, direct protein profiling by liquid chromatography with tandem mass spectrometry (LC-MS/MS) would depict proteins in an unbiased proteomic methodology.

Converging data from each approach resulted in multiple targets of interest to be

evaluated as biomarkers of melioidosis and tularemia. Upon validation, putative targets may be used to develop diagnostic assay to improve current medical standards for melioidosis and tularemia.

Keywords

Burkholderia pseudomallei, Francisella tularensis, melioidosis, tularemia, diagnostics, biomarkers, InMAD, proteomics

2.2 Background

The Select Agent Program is comprised of pathogens and toxins which pose a severe threat to public health and national security. Burkholderia pseudomallei (Bp) and

Francisella tularensis (Ft), are categorized as Tier 1 Select Agents as they are highly infectious and associated with elevated mortality rates. The ease of dissemination and lack of approved vaccines for B. pseudomallei and F. tularensis further signify the necessity for additional medical countermeasures as malevolent distribution of either pathogens can lead to mass casualty.

Melioidosis is a neglected tropical disease caused by the bacterium B. pseudomallei.

The Gram-negative bacillus is a motile saprophyte ubiquitously found in Southeast Asia and northern Australia. Estimations based on environmental suitability and reported cases predict 165,000 infections annually resulting in 89,000 deaths with a larger region of endemicity than commonly reported [3]. Melioidosis infections have a high rate of incidence with co-morbidities such as diabetes, excessive alcohol intake and respiratory diseases; however, B. pseudomallei can also infect healthy individuals [13]. The early diagnosis of an infection is vital for administering therapy within an effective treatment window as B. pseudomallei is intrinsically resistant to many first-line antimicrobial agents including penicillin and cephalosporins [19]. Ceftazidime and meropenem are the recommended to treat an infection, though case fatality rates of 20-40% are still observed with administering these effective antibiotics [112-114]. Coined as the ‘great imitator’, melioidosis presents with nonspecific symptoms ranging from febrile illness to abscesses formation and organ dysfunction dependent on infection foci [115]. The multitude of clinical presentations often leads to misdiagnoses [116]. The gold standard

for diagnosing melioidosis is blood culture, however, this method can take upwards of seven days and sensitivity is approximately 60% due to low bioburden [117, 118].

Tularemia, caused by F. tularensis, is a zoonotic disease contracted by humans through contact with infected animals and arthropod vectors such as ticks and mosquitos [119].

The Gram-negative, rod-shaped coccobacillus is an intracellular pathogen endemic to the United States of America, Europe, and Asia. There are four subspecies of F. tularensis: tularensis (Type A), holarctica (Type B), novicidia, and mediasiatica [38].

These subspecies are genetically divergent from one another resulting in varying degrees of virulence in humans and animals [40]. Type A isolates found in the United

States of America are the most pathogenic subspecies causing lethal pulmonary infections and have an extremely low infectious dose with few as 10 colony forming units

[31, 39]. Type B isolates are found ubiquitously in the northern hemisphere and generally less lethal to humans and animals [40]. The live vaccine strain (LVS) was derived from a Type B isolate S15 obtained by the USA from Russian [120]. Though considered the best vaccine candidate for its protection against Type A isolates, residual virulence has been observed as the method of attenuation is poorly understood [51, 121,

122]. F. tularensis subspecies novicida has only shown to cause infection in severely immunocompromised patients [41], and little is known about F. tularensis subspecies mediasiatica, and therefore studies are generally focused on Type A and B strains.

Different routes of infection lead to a variety of clinical presentations; of which, ulceroglandular development is most common (90%) due to arthropod transmission [49].

F. tularensis remains susceptible to streptomycin and gentamicin; however, the low number of cases often lead to a diagnosis of tularemia to be overlooked [54]. The gold

standard for diagnosis is bacterial culture, but the fastidious nature of the bacterium yields low sensitivity and specificity for such technique [52].

Alternative methods of diagnosing melioidosis and tularemia are warranted to improve sensitivity and specificity as well as accommodate for earlier administration of effective treatments. Immunoassays and polymerase chain reactions (PCR) are powerful techniques to detect trace amounts of pathogen-derived proteins, carbohydrates, or nucleic acids in complex specimens such as sera, urine, bodily fluids, or biopsies. The detection of pathogen-derived macromolecules is an alternative for diagnosing active infections with a shorter turnaround time compared to bacterial culture. The caveat of such diagnostic method is identifying viable targets to detect for in the infected individual. Qualities to consider when defining a good biomarker are being in detectable concentration ranges and high specificity to distinguish between pathogens.

In vivo Microbial Antigen Discovery (InMAD) utilizes the adaptive immune response to identify circulating antigens in infected samples [123]. The InMAD process indirectly detects for circulating pathogen-derived macromolecules via the generation of antibodies against clinical specimens using naïve mice. First, specimens are filtered to removed whole cells and represents a sample containing only circulating macromolecules (host and microbial). The filtered sample is used to immunize naïve mice to elicit an immune response. The mice generate antibodies against circulating antigenic targets in the infected sample and can be used to probe bacterial lysates or protein arrays for target identification. Biomarkers have been discovered using the InMAD platform for melioidosis, tularemia, aspergillosis and Lyme disease using various animal models of infection (mouse, guinea pig and macaque) [123-125]. Previous InMAD studies for

melioidosis and tularemia resulted in the identification and validation of circulating carbohydrates [123, 126-128]. B. pseudomallei capsular polysaccharide (CPS) has been demonstrated to be shed by the bacterium and filtered through the kidney into urine

[128, 129]. F. tularensis lipopolysaccharide (LPS) has been detected in quantifiable concentrations in tularemia patient serum [E.E. Hannah, unpublished data]. The use of human samples to identify potential biomarkers via the InMAD platform may further suggest additional targets as microbial profiles may vary in different hosts.

The InMAD approach, however, is biased towards detecting targets which are immunogenic [123]. Alternate methods are required to identify targets which will not necessarily elicit a humoral response. Advancements in liquid chromatography with tandem mass spectrometry (LC-MS/MS) allows for a proteomic-based analysis with the power of computational learning [130, 131]. Technologies utilizing LC-MS/MS are more readily accessible than before and permit for high-throughput protein profiling with deep coverage [132]. Direct analyses of melioidosis and tularemia patient samples via LC-

MS/MS may serve as an unbiased strategy for discovering bacterial proteins present in clinical specimens.

A multi-armed approach was performed to identify circulating bacterial proteins during melioidosis and tularemia infections. Samples were collected from melioidosis patients in

Darwin, Australia and from tularemia patients in Ankara, Turkey. The first approach identified bacterial antigens via the InMAD platform. The integration of high-density nucleic acid programmable protein arrays (HD-NAPPA) allowed for identifying proteins in which an antibody response was generated in the InMAD immune sera. The HD-NAPPA was then probed with patient sera samples to determine serological targets. As B.

pseudomallei and F. tularensis are facultative intracellular pathogens, a humoral response elicited by the host may indicate shed protein accessible by the immune system. The clinical specimens were also directly analyzed for proteins present in the complex sample through LC-MS/MS. Criteria were set for each method to determine potential biomarkers of melioidosis and tularemia. These targets may serve useful in the development of novel assays for diagnosing melioidosis and tularemia, and further understanding these infectious diseases.

2.3 Methods

Ethics statement

Studies on human subjects were approved by the University of Nevada, Reno Institutional

Review Board (IRB).

The use of laboratory animals in this study was approved by the University of Nevada,

Reno Institutional Animal Care and Use Committee (protocol number 00024). All work with mice were performed at the University of Nevada, Reno in conjunction with the Office of

Lab Animal Medicine, which adheres to the National Institutes of Health Office of

Laboratory Animal Welfare (OLAW) policies and laws (assurance number A3500-01).

Bacterial cultures

Select agent exempt strains of Burkholderia pseudomallei and Francisella tularensis were grown at biosafety level 2 (BSL2). The bacterial cultures were grown at in vivo-like conditions and were used in downstream applications (i.e. Western blots, InMAD). B. pseudomallei Bp82 (NR-49094, BEI Resources, Manassas, VA) was grown in minimal salt media (M9) supplemented with glucose, casamino acids, thiamine and adenine as previously described [133]. F. tularensis LVS (NR-646, BEI Resources) was grown in brain heart infusion (BHI) broth containing cysteine [134]. Cultures were grown by shaking at

37°C for 24 hours. Cell density was determined by spectrometry using 600 nm wavelength

(OD600).

Melioidosis and Tularemia Samples

Clinical melioidosis samples were collected at the Royal Darwin Hospital Campus in

Darwin, Australia through a collaboration with Menzies School of Health Research.

Individuals were confirmed melioidosis positive by bacterial culture. Urine and serum

samples were collected during patient visits, and the presence in samples of capsular polysaccharide (CPS) was determined using the Active Melioidosis Detection Rapid Test

(AMDTM) lateral flow immunoassay (LFI) provided by InBios International (Seattle, Wa).

Tularemia samples were acquired from collaborators at the Hacettepe University in

Ankara, Turkey. Urine and sera samples were archived from patients diagnosed with tularemia by either PCR or serology. Numerous samples from individual patients were collected for temporal and paired analyses.

Sample Handling and Inactivation

Clinical specimens for melioidosis and tularemia were received by the University of

Nevada, Reno at biosafety level 3 (BSL3). Sample were processed through 0.22 μm filtered via syringe filter units (MilliporeSigma, Burlington, MA) or Spin-X centrifuge tube filters (Corning Costar, Corning, NY) to render specimens void of viable bacteria.

Melioidosis and tularemia sera samples were diluted 1:1 in PBS to decrease sample viscosity prior to filtration. Urine samples were filtered undiluted. Sample sterility was confirmed by back plate under the approved Memorandum of Understanding and

Agreement (MOUA) filed with the UNR Institutional Biosafety Committee. Filtered samples were processed at BSL2 for downstream applications.

Patient serum samples were depleted of the top abundant proteins using the Human 14

Multiple Affinity Removal Columns (Agilent, Santa Clara, CA). Depleted serum and urine were concentrated using the Amicon Ultra centrifuge filters 3,000 MWCO

(MilliporeSigma).

Generation of InMAD Immune Sera

All animal work was performed in a BSL2 laboratory in the animal facility located at the

University of Nevada, Reno. Naïve CD1 mice, 6 – 8 weeks old, (Charles River

Laboratories, Inc.), were immunized with melioidosis or tularemia clinical specimens.

Emulsions of clinical specimen with Alhydrogel adjuvant 2% (Invivogen, San Diego, CA) or Titermax Gold Liquid Adjuvant (TiterMax, Norcross GA) were used to immunize mice via subcutaneous injection. Each sample was used to immunize four animals which were housed together. The number of animals was selected to account for variability in the immune response, human error, and for any unforeseeable causes (i.e. death of animal).

InMAD immune serum was collected from mice via retro-orbital survival bleeds at pre- immune, 4 weeks, and 6 weeks. Final bleeds were collected via cardiac sticks at 8 weeks following euthanasia by isoflurane overdose. Immunizations with heat-inactivated B. pseudomallei Bp82 and F. tularensis LVS were used to generate positive control sera.

Western blot

A standard Western blot procedure was performed using semidry blotting. 6x reducing

Laemmli loading buffer was added to bacterial lysates. The reduced sample was then boiled for 10 minutes. Samples were separated on 4-15% SDS gel, and proteins were transferred to a nitrocellulose membrane (Bio-Rad Laboratories, Hercules, CA). Blots were blocked overnight with 5% milking in tris buffered saline containing 0.1% Tween-20

(blocking buffer). Pre-immune and InMAD immune sera were diluted into blocking buffer and probed in the Miniblotter Instrument (Interchim, Montluçon, France). Horseradish peroxidase (HRP) labeled secondary goat anti-mouse Ig (SouthernBiotech, Birmingham,

AL) followed as a detection module. Signal was developed using SuperSignal™ West

Femto Maximum Sensitivity Substrate (ThermoFisher Scientific, Grand Island, NY) and imaged using a ChemiDoc XRS imaging system (Bio-Rad Laboratories).

Nucleic Acid Programmable Protein Array (NAPPA)

InMAD immune serum and patient sera were used to probe high-density nucleic acid programmable protein arrays (HD-NAPPA) to identify reactive protein targets. HD-

NAPPA fabrication, assaying data analyses were performed at the Biodesign Institute at

Arizona State University (Tempe, AZ). 53 whole B. pseudomallei genomes were annotated to identify the core genome of B. pseudomallei [135]. A total of 3,167 genes were cloned into pANT7_cGST, a cell-free expression vector containing a terminal GST tag, and used in the production of a core genome protein array for B. pseudomallei. The

B. pseudomallei NAPPA arrays were ran in two steps to accommodate for the number of genes. A condensed array was printed and express with multiple proteins per spot.

Positives spots from the first array were then reprinted in a deconvoluted array with individual genes printed and expressed in individual wells [136]. Genes for the F. tularensis arrays can be found at https://dnasu.org/DNASU/ [137]. The entire F. tularensis ORF collection was subcloned into the pJFT7_nHalo_DC(r4) expression vector and printed as 1,443 individual spots on the HD-NAPPA.

The HD-NAPPA arrays were fabricated and assayed as previously described [138].

Arrays were blocked with SuperBlock (Thermo Fisher Scientific), then filled with human cell-free expression system (In Vitro Transcription and Translation coupled system

(IVTT); Thermo Fisher Scientific) and a custom micro-reactor device was used for the protein expression. After sealing the wells with a polystyrene membrane under 200 PSI pressure, the arrays incubated in the reactor for 2 h at 30 °C for expression and for 0.5 h at 15 °C for protein capture, followed by blocking with 5% skim milk in phosphate buffered saline with 0.2% tween 20 (PBST) for 30 mins.

InMAD immune sera (see section Generation of InMAD Immune Sera) or patient sera were diluted in 5% skim milk in PBST. Arrays were incubated overnight (14-16 hours) at

4°C with gentle shaking. The arrays were washed and detected by Alexa Fluro® 647- conjugated goat anti-mouse IgG or anti-human IgG (Jackson ImmunoResearch Labs,

West Grove, PA) and Cy3 labeled Goat anti-mouse IgM or anti-human IgA (Jackson

ImmunoResearch Labs). The arrays were rinsed, dried, and imaged using the

PowerScanner (Tecan Systems Inc, San Jose, CA). The resulting images were quantified with the ArrayPro Analyzer Software (Media Cybernetics, Inc, Rockville, MD).

Signal cutoff was determined as 1.4 for InMAD immune serum and 2.0 for patient serum.

Criteria for a potential biomarker for the InMAD NAPPA was target hits with specificity greater than 95%. Criteria for patient NAPPA were specificity greater than 95% and sensitivity greater than 15%.

Sample preparation for Mass Spectrometry

Clinical samples were digested using an in-solution protocol for LC-MS/MS analysis

[139]. Up to 20 μL of samples were digested in a single reaction. 20 μL of acetonitrile

(ACN) was added to the sample and incubated at room temperature (RT) for 20 minutes.

40 μL of 10mM dithiothreitol (DTT) in 25mM ammonium bicarbonate (ABC) was added to the sample and incubated at 60°C for 10 minutes. 20 μL of 55mM iodoacetamide (IA) in 25mM ABC was added and incubated at RT for 35 minutes. 20 μL of 5 ng/μL trypsin in 25mM ABC was added and incubated at 37°C for 4 hours to digest upwards of 5 μg of total protein.

Reactions containing peptides were purified using Pierce C18 Spin Columns

(ThermoFisher Scientific, Waltham, MA) as per manufacturer’s protocol. Columns were

prepared using 50% methanol, then equilibrated with 5% ACN, 0.5% trifluoroacestic acid

(TFA) in ddH2O (binding/wash buffer). 4x sample buffer (20% CAN, 2% TFA in ddH2O) was added to the digested sample then loaded onto the C18 spin column. The column was washed with binding/wash buffer. Peptides were then eluted from the column with

70% ACN, 0.1% TFA in ddH2O. Samples were concentrated using a speed vac and resuspended in 0.1% formic acid (FA) in ddH2O.

Liquid Chromatography

Liquid chromatography was performed on an UltiMate 3000 RSLC nano system (Thermo

Fisher Scientific) on a self-packed ReproSil-Pur C18 column (100 um x 35 cm). The gradient used consisting of solvent B from 2-90% (Solvent A - 0.1% FA in ddH2O,

Solvent B -0.1% Formic Acid in ACN) at 50°C using a digital Pico View nanospray source (New Objectives, Woburn, MA) that was modified with a custom-built column heater and an ABIRD background suppressor (ESI Source Solutions, Woburn, MA). The column was a self-packed Pico-Frit (New Objectives, Woburn, MA) using a 15μm tip with

40 cm of 1.9 um ReproSil-Pur 120 C18-AQ (Dr. Maisch GmbH, Germany) at 9,000 psi using a nano LC column packing kit (nanoLCMS, Gold River, CA).

Data-dependent acquisition Mass Spectrometry (DDA-MS/MS)

Mass spectral analysis was performed using an Orbitrap Fusion mass spectrometer

(ThermoFisher Scientific). The MS1 precursor selection range was from 400-1500 m/z at a resolution of 120K and an automatic gain control (AGC) target of 2.0 x 105 with a maximum injection time of 100 ms. Quadrupole isolation at 0.7 Th for MS2 analysis using CID fragmentation in the linear ion trap with a collision energy of 35%. The AGC was set to 4.0 x 103 with a maximum injection time of 150 ms. The instrument was

operated in a top speed data-dependent mode with a most intense precursor priority with dynamic exclusion set to an exclusion duration of 60s with a 10ppm tolerance. The data was then analyzed using Sequest version v.27, rev. 11 (ThermoFisher Scientific) and

Scaffold Q+ (Proteome Software, Portland, OR.). Criteria for a potential biomarker was at least 2 peptides identified with cross-correlation (Xcorr) value greater than 1.8

Data-independent acquisition Mass Spectrometry (DIA-MS/MS)

Mass spectral analysis was performed using an Orbitrap Fusion mass spectrometer

(Thermo Fisher Scientific). Six gas phase fractions (GPF) of the B. pseudomallei Bp82 spiked in normal human urine were used to generate a reference library. The GPF acquisition used 4 m/z precursor isolation windows in a staggered pattern (GPF1 398.4-

502.5 m/z, GPF2 498.5-602.5 m/z, GPF3 598.5-702.6 m/z, GPF4 698.6-802.6 m/z,

GPF5 798.6-902.7 m/z, GPF6 898.7-1002.7 m/z). Patient samples were run on an identical gradient as the GPFs using a staggered window scheme (4 m/z Exploris 480,

24 m/z Fusion) over a mass range of 385-1015 m/z. An empirically corrected library which combines the GPF and the deep neural network Prosit were used to generate predicted fragments and retention times using ScaffoldDIA (Proteome Software). Each sample was run in triplicate and evaluated against normal human urine. Criteria of a potential biomarker is at least 2 peptides identified.

2.4 Results

Identification of B. pseudomallei proteins in clinical melioidosis specimens

Serum and urine from melioidosis patients were collected at the Royal Darwin Hospital

Campus in Darwin, Australia. Blood cultures were performed upon being admitted to the hospital to confirm a diagnosis. Sample collection occurred throughout the treatment phase and individual samples were assessed for the presence of B. pseudomallei CPS by AMDTM LFI (Table 1). The detection of B. pseudomallei CPS is indicative of the presence of bacteria and a signal of an active infection. Clinical specimens were evaluated for circulating B. pseudomallei proteins through a multi-armed approach to determine additional putative biomarkers of infection (Figure 1).

CD1 mice were immunized with either 1:1 diluted, undepleted serum, 1:10 diluted sera, depleted sera, or 5-10x concentrated urine in stable emulsions. The aluminum hydroxide emulsions were preferred over previously described methods as the injection were quickly absorbed when administered subcutaneously [123]. Mice immunized with 1:10 diluted sera and depleted sera did not generate a strong response by Western blot against B. pseudomallei Bp82 lysate (data not shown). Emulsions made with Titermax

Gold Liquid were not as readily absorbed into the mice and resulted in uncertainty about dosaging.

A total of 30 melioidosis patient samples were used to generate InMAD immune sera to identify B. pseudomallei proteins. Western blots analyses of whole-cell B. pseudomallei

Bp82 lysates were probed with the 8-week InMAD immune sera. A representative

Western blot of mice immunized with serum and urine collected from a single patient showed reactivity to the bacterial lysate (Figure 2). The generated InMAD immune sera

showed differing levels of reactivity suggesting mouse to mouse variability even when the same samples were injected between different mice (Figure 2, lanes 1-8 and 9-16).

Strong reactive bands at around 72 kDa were observed in the mice immunized with both serum and urine from this individual patient. Pre-immune sera collected from naïve mice were not reactive to the B. pseudomallei Bp82 lysate (Figure 2, odd lanes).

To identify B. pseudomallei protein targets in which the InMAD immune sera are reactive to, HD-NAPPAs were produced using a set of genes which were annotated as the B. pseudomallei core genome. A total of 3,167 genes were selected and included in the protein array. Genomic analyses of the B. pseudomallei genomes has been previously described and a workflow on selecting included genes can be found in Figure 3 [135]. B. pseudomallei arrays were initially screened in a condensed format consisting of two protein targets per spot. Positive spots on the condensed array were deconvoluted to assay individual reactive proteins. A list of proteins that were positive when probed with

InMAD immune sera can be found in Table 2. The protein list includes two flagella- associated proteins (BPSL3319 and BPSL0267) as well as 14 targets annotated as hypothetical proteins.

B. pseudomallei is a facultative intracellular pathogen, with the capacity to move cell-to- cell via actin-based motility. As an alternative method to identify putative biomarkers, serology from twenty melioidosis patients were evaluated on the HD-NAPPA array.

Targets in which the patient had generated antibodies to suggest these proteins were accessible by the immune response due to shedding or secretion. 27 proteins were identified with ≥95% sensitivity and ≥15% specificity for either IgG or IgA (Table 3).

Included in the results, BPSL0999, BPSL3222, BPSS0476, BPSL2698, and BPSL2522

were previously identified as serological markers [140-143]. The list also included

BPSS0001, BPSL1161, BPSL1827, and BPSL2355 which are annotated as hypothetical proteins.

Mass spectrometry analyses of melioidosis samples were performed using two acquisition methods: data-dependent acquisition (DDA) and data-independent acquisition (DIA). In addition to the thirty melioidosis samples used to generate InMAD immune sera, an additional ten (totaling forty) specimens were evaluated using a DDA methodology. This method identifies proteins by aligning peptide hits to the SWISS-

PROT database [144]. The DDA method resulted in the identification of 152

Burkholderia protein in serum and/or urine which met the criteria of a target hit (Table

S1). Though the DDA method is a traditional platform for discovery proteomics, it is inherently biased towards proteins with greater abundance. Only peptides which met a minimum ion abundance threshold are further fragmented for analysis. Circulating bacterial proteins are likely to be in low abundant proteins compared to host proteins and may not be identified due not exceed the threshold for MS2 analysis.

A pilot study using a DIA method was evaluated to identify B. pseudomallei proteins in melioidosis patient urine. The DIA assay was designed and fabricated at the Proteomics

Center at the University of Nevada, Reno through establishing a spectral library database [145]. This library database was developed using B. pseudomallei Bp82 lysate spiked into normal human urine. A total of 488 B. pseudomallei proteins were included in protein database which represents less than 10% of all annotated proteins in B. pseudomallei [146]. Five urine samples (390-9, 423-1, 434-1, 438-1, 461-2) were evaluated using the DIA assay, resulting in 385 hits that met the criteria as a potential

protein hit (Table S2). The lack of an ion abundance threshold resulted in a greater number of protein hits which met criteria due to deeper coverage; however, this approach is limited to proteins represented in the spectral database.

A Venn diagram displaying protein targets which met criteria set for each approach is shown in Figure 4. The 33 proteins listed in the mass spectrometry section are the overlapping protein hits between DIA and DDA. Proteins previously identified as virulence factors, BPSL3319 (flagellin) and BPSS1531 (type III secretion system effector protein BipC), were potential targets determined by both InMAD and mass spectrometry.

Of the targets that overlapped by patient serology and mass spectrometry, two were outer membrane protein A homologues as well as the chaperone protein GroES. A lipase chaperone protein along with two hypothetical proteins were identified by both

InMAD and patient serology, suggesting these targets to be highly immunogenic.

Identification of F. tularensis proteins in clinical tularemia specimens

Samples from patients infected with F. tularensis were obtained from an archived collection at Hacettepe University in Ankara, Turkey. Patients were confirmed tularemia positive by either RT-PCR or serodiagnosis (Table 4). Patient #1-14 were confirmed by

RT-PCR which would indicate an active infection due to the presence of bacterial nucleic acid. Patients #15-21 were confirmed positive by serodiagnosis. The retroactive nature of serodiagnosis may not necessarily represent an active infection. Serum was collected from all 21 patient and paired urine samples from patients #15-21. These samples were analyzed using the multi-armed approach (Figure 1).

Western blots analyses of whole-cell F. tularensis LVS lysates were probed with InMAD immune sera to determine reactivity. Mice immunized with sera collected from two patients who were diagnosed with tularemia by serodiagnosis (#18 and #19) resulted in reactivity to the bacterial lysate (Figure 5). Though these patients were diagnosed by serology, the presence of LPS in these samples was confirmed in a parallel study indicating an active infection (data not shown). This gives confidence in InMAD immune sera to be reactive to F. tularensis proteins. The “ladder” banding pattern in lanes 2, 4,

10, and 12 is likely antibodies against the F. tularensis LPS, a biomarker identified in previous InMAD studies using mouse model of tularemia infection [123, 147]. Variability in antibody generation were observed in the InMAD immune sera as show by a variety of reactive bands in mice immunized with the same clinical specimen.

HD-NAPPA for tularemia was probed with InMAD immune serum to identify individual F. tularensis proteins. A total of 1,443 genes were subcloned from the whole genome ORF collection and assayed on the HD-NAPPA. A list of proteins reactive by the tularemia

InMAD immune sera can be found in Table 5. Redundancies in the F. tularensis genome resulted in duplicate spots on the array. Notably, two spots were present for proteins associated with the Francisella Pathogenicity Island (FPI) [148]. Though the duplicate wells did not react identically, both spots containing either intercellular growth locus subunit C (IglC) or subunit G (IglG) met the criteria as a potential target. Additionally, transposase, encoded by the ISFtu2 genomic element, resulted in positivity in two independent spots on the array. This redundant genomic element has been evaluated as a diagnostic target by RT-PCR [149].

The twenty-one tularemia patient serum samples were also used to probe the HD-

NAPPA to identify antibodies present during a tularemia infection. Along with F. tularensis LPS, 25 protein targets were identified with ≥95% sensitivity and ≥15% specificity for either human IgG or IgA (Table 6). FTT0975, FTT0106c, FTT0077,

FTT0472, FTT1539, FTT1116, FTT1529, FTT0879, FTT1349 were previously identified to elicit an IgG or IgM antibody response in tularemia patients [150, 151]. The development of serological assays against four of the proteins listed above have been described [151, 152]. FTT1589c, FTT1679, FTT0721c, and FTT1269c may serve as additional IgG serological targets for tularemia. Interestingly, most targets reactive by human IgA in the present study have not been previously identified, with the exceptions of FTT0879 and FTT1349/1712. 19 of the 21 patients were positive for anti-LPS IgG, but only two were positive for anti-LPS IgA.

Tularemia sera and urine were evaluated by LC-MS/MS only using the DDA method.

The criteria used to evaluate the tularemia samples was less stringent (Xcorr ≥ 1.4) as the total number of protein hits was low. To enrich the data as a discovery approach, the cutoff was lowered, and lesser weight was put on the mass spectrometry results for determining putative biomarkers. Only thirty-four Fransicella proteins met the adjusted criteria set (Table S3). A comparison of F. tularensis hits by the different approaches is shown in Figure 6. Despite lowering the criteria, only two proteins (FTT0699 and

FTT0721c) identified by mass spectrometry overlapped with either the InMAD or patient serology approaches. In addition to LPS, nine proteins (FTT1349/1704, FTT1357/1712,

FTT0879, FTT0954c, FTT0151, FTT0677c, FTT1042, FTT0052, FTT1073c) were identified by InMAD immune sera and patient serology and may represent highly immunogenic antigens.

2.5 Discussion

The InMAD process had previously identified B. pseudomallei CPS and F. tularensis

LPS as viable biomarkers of melioidosis and tularemia; however, the previous study used samples collected from a mouse model of infections which may be inadequate for identifying all circulating antigens in human infections. A multi-armed proteomic approach was utilized to identify additional bacterial proteins in clinical specimens. This methodology represents an encompassing workflow to identify circulating bacterial proteins accounting for various assay biases. The InMAD approach identifies antigenic proteins using a naïve CD1 mice to amplify an indirect detection modality. The patient serological approach identifies targets which were accessible by the host immune system. Since B. pseudomallei and F. tularensis are intracellular pathogens, targets identified by this approach may signify these proteins to be shed and circulating during an infection. The mass spectrometry approach determined protein content in an unbiased methodology, specifically including those not necessarily immunogenic or include in the HD-NAPPA. Discovery mass spectrometry may not have the analytical sensitivity as the above approaches, however assessing protein targets in an unbiased methodology is warranted to determine all possible circulating bacterial proteins. Two mass spectrometry acquisition methods were evaluated to determine an optimal methodology for unbiased profiling to identify bacterial proteins in clinical samples.

InMAD immune sera generated from melioidosis and tularemia specimens demonstrated reactivity against bacterial lysates by Western blot. The integration of the HD-NAPPA allowed for a high-throughput analysis on an individual protein level. HD-NAPPA arrays have previously been used to identify serological markers in other infectious diseases, including tuberculosis, Lyme Disease, and 25 different viruses [125, 136, 138]. The

present study is the first B. pseudomallei protein array with the capacity of screening over 3,000 proteins in a single run. The HD-NAPPA platform was used to identified targets in both murine InMAD immune serum and human patient serology. Each sample type was evaluated using two secondary modules to detect different immunoglobulin subclasses (murine – IgG & IgM; human – IgG & IgA). Expressed genes reactive by human IgG in melioidosis patient resulted in a majority of proteins which were previously identified [140-143]. Interestingly, the IgA response in patient sera suggested six additional serology markers which can be evaluated: BPSS1348, BPSL3153,

BPSS1740, BPSL3092, BPSL3335, and BPSL2983. BPSL2522 (OmpA) was previously identified as a IgG serological marker is suggested to also elicit an IgA response [140-

143]. The identification of novel IgA markers may be valuable as inhalation and ingestion are common routes of contracting melioidosis. The B. pseudomallei HD-NAPPA is currently being used to determine temporal changes in host antibody response during treatment for melioidosis and may further give insight on disease progression and dynamics of the host immune response.

Duplication of protein targets on the F. tularensis HD-NAPPA give confidence to the data collected from the arrays when probed with either InMAD immune sera or tularemia patient sera. These duplications on the HD-NAPPA are due to redundancies in the F. tularensis genome and may further justify the importance of these targets. The detection of murine IgM in InMAD immune sera resulted in a greater number of potential targets by

HD-NAPPA compared to targets identified by murine IgG. The generated IgM response in InMAD immune sera should be evaluated using earlier timepoint (4 or 6 weeks) as

IgM levels are known to wane quickly as the immune response matures towards an IgG response. The previous InMAD study found 8 weeks postimmunization was optimal for

detecting murine IgG response against bacterial proteins by the InMAD process [123].

Further optimization of InMAD immune serum time points may result in a greater number of potential hits by HD-NAPPA. Like melioidosis patient serology, the tularemia patient

IgA analysis resulted in several protein targets which have not been previously identified.

Notably, the IglC and IglG proteins encoded within the FPI were shown to elicit an IgA response in the infected individuals. IglC, a hemolysin-coregulated protein (hcp) homologue, modulates the phagosome biosynthesis and is essential for bacterial survival within the macrophage [148]. The function of IglG yet is unknown, however IglG is suggested to be essential for translocating other effector proteins, including IglC and intercellular growth locus subunit F [153]. Due to the infectious nature of F. tularensis via the inhalation route, these targets may serve valuable as diagnostic and therapeutic targets for tularemia.

Mass spectrometry can be a powerful method for profiling total protein content; however, traditional DDA discovery mass spectrometry often miss lower abundant proteins as ion abundance thresholds are not met. As F. tularensis is an intracellular pathogen, the abundance of F. tularensis proteins in clinical specimens may be scarce as suggested by the minimal hits identified by mass spectrometry [154]. Little is known about antigenemia during a tularemia infection. Results in the present study indicate few proteins were in detectable concentrations by the mass spectrometry and more weight should be put on the other arms of the discovery approach for tularemia. The fabrication and optimization of a DIA assay for F. tularensis may help improved in data collect by mass spectrometry.

A comparison of DDA and DIA methods for discovery of circulating B. pseudomallei proteins in patient samples was conducted. DIA is a newer approach which analyzes total protein content using overlapping windows, removing the ion abundance component associated with traditional tandem mass spectrometry. A spectral library of human and B. pseudomallei proteins was produced using bacterial lysates spiked into normal human urine to simulate all possible protein present. Urine was selected for the analysis as the total protein concentrations are much lower than that of serum and collection volumes can be much greater. Additionally, urine is suggested to have more

B. pseudomallei antigens during a melioidosis infection, however this may be attributed to the accumulation of CPS in the sample type [129, 155]. The DDA method processes peptide matches against the SWISS-PROT database and resulted in more confident protein hits with fewer forced protein matches made. On the other hand, the DIA method resulted in much deeper coverage of B. pseudomallei proteins. Though the DIA method resulted in better protein coverage, the method is inherently limited as a discovery approach due to database constraints. The establishment of a spectral library is required for the DIA approach, as the DDA approach may utilize an in silico-based library. Further optimize is warranted to expand on the discovery capacity of the DIA method.

Candidate biomarkers for validation were selected based on converging data and other metrics such as localization, low levels of homology, and protein function. Table 7 summarized the seven B. pseudomallei proteins and five F. tularemia proteins chosen for further analysis. Of the twelve proteins selected, eleven had high SignalP-5.0 scores suggesting secretion or translocation into extracellular space. Though BPSS0311 did not have a high SignalP-5.0 score, however good sequence coverage via DIA mass spectrometry suggests the 297kD protein to be present in melioidosis urine. Secretion

system proteins (BPSL1531, FTT1349/1704, FTT1357/1712) were selected as these complexes are associated with virulence and have been extensively studied in other organisms. BPSL3092 is putative bacteriocin classified as part of a hemolysin export system and is just upstream from a type VI secretion system [156]. Detection of

BPSL1445 (lipoprotein) and BPSL3319 (flagellin) by the multi-armed approach further suggest these protein as diagnostic markers as they have been identified as upregulated during an infection and also elicit serological responses [140, 157]. Previous work isolating hybridoma cell lines from mice immunized with heat-killed B. pseudomallei yielded a monoclonal antibody reactive to BPSL2298, phasin-like protein (data not shown). This may indicate BPSL2298 is shed into extracellular spaces or in high abundance compared to other protein in the whole-cell lysate. The remaining protein targets selected may have been annotated as hypothetical proteins or have irrelevant functions, however they should not be discredited as potential biomarkers of infection.

This present study outlines a workflow to determine putative protein biomarkers of infection using clinical samples from melioidosis and tularemia patients. Further evaluation of protein targets will need to be performed to validate them as biomarkers of infection. Directed assays, including immunoblot analysis and targeted mass spectrometry, will be performed for validation studies. In addition to diagnostic purposes, the data collected in this study may serve useful for vaccine studies, understanding host- microbe interactions, and bacterial pathogenesis. The multi-armed approach is also being used to evaluate anthrax samples and will further support the methodology for biomarker discovery.

Approach Criteria as a putative target InMAD Signal cutoff = 1.4 Specificity > 95% Patient Serology Signal cutoff = 2.0 Specificity > 95% Sensitivity > 15% Mass Spectrometry Xcorr cutoff = 1.8 (B. pseudomallei) Xcorr cutoff = 1.4 (F. tularensis) ≥ 2 peptides identified.

Figure 1. Strategy for circulating bacterial protein discovery. Clinical specimens (urine and serum) were collected from melioidosis and tularemia patients. Samples were analyzed by three approaches: InMAD, Patient Serology, and Mass spectrometry. An indirect approach coined In vivo microbial antigen discovery (InMAD) combines filtered clinical samples rendered bacterium free with aluminum hydroxide adjuvant and used to immunize CD1 mice. The mice illicit an immune response against antigens in the clinical specimen including secreted/shed bacterial proteins. The reactive InMAD immune serum is then used to probe bacterial nucleic acid programmable protein arrays (NAPPA). Patient serum was also used to probe the NAPPA directly. Patient serum and urine were directly analyzed for protein content by liquid chromatography with tandem mass spectrometry (LC-MS/MS).

Figure 2. Western blot analysis of InMAD immune sera against Burkholderia pseudomallei Bp82 lysate. Odd-numbered lanes are pre-bleed negative controls (1:100). Even-numbered lanes are terminal bleeds 8-weeks post-immunization (1:10). Clinical specimens used to generate InMAD immune sera were serum (Lanes 1-8) and urine (Lanes 9-16) collected from Patient 440 at the same time. Image taken with 120 second exposure time.

Figure 3. Analysis of 53 complete Burkholderia pseudomallei isolate genomes to identify core and unique genes to include on the nucleic acid programmable proteome array (NAPPA) for melioidosis

*Identified by both DIA and DDA methods

Figure 4. Venn diagram of the potential biomarkers which met the criteria of each arm of the approach for melioidosis. Proteins listed in Mass Spectrometry represent targets identified by both DIA and DDA settings. A comprehensive list of individual proteins identified by mass spectrometry can be found in Tables S1 and S2.

Figure 5. Western blot analysis of InMAD immune sera against Francisella tularensis LVS lysate. Odd-numbered lanes are pre-bleed negative controls. Even-numbered lanes are terminal bleeds 8-weeks post-immunization. Serum collected from two different patients were used to generate InMAD immune Patient 18 (Lanes 1-8) and Patient 19 (Lanes 9-16). Image taken with 180 second exposure time.

Figure 6. Venn diagram of the potential biomarkers which met the criteria of each arm of the shed protein discovery approach for tularemia.

Table 1. Summary of melioidosis samples evaluated for circulating Burkholderia pseudomallei proteins

Sample Sample AMD LFI Patient InMAD DDA MS DIA MS ID Type Results NAPPA 304-2 Urine - ✓ 309-12 Serum + ✓ ✓ ✓ 309-4 Serum + ✓ ✓ ✓ 341-2 Serum + ✓ ✓ ✓ 362-7 Serum + ✓ ✓ ✓ 362-15 Serum - ✓ 375-5 Serum + ✓ ✓ ✓ 372-12 Serum - ✓ 372-13 Serum - ✓ 372-14 Serum - ✓ 390-33 Urine + ✓ ✓ 390-4 Serum + ✓ ✓ ✓ 390-9 Urine + ✓ ✓ ✓ 391-20 Urine + ✓ ✓ 391-23 Urine + ✓ ✓ 400-12 Urine - ✓ 412-1 Urine + ✓ ✓ 412-7 Serum - ✓ 422-1 Urine + ✓ ✓ 422-5 Serum ND ✓ 423-1 Urine + ✓ ✓ ✓ 423-12 Urine + ✓ 423-3 Urine + ✓ 423-5 Serum + ✓ ✓ ✓ 423-9 Urine + ✓ 430-10 Urine + ✓ ✓ 430-15 Serum + ✓ ✓ ✓ 430-16 Serum + ✓ ✓ ✓ 430-17 Serum + ✓ ✓ ✓

430-18 Urine + ✓ ✓ 430-26 Urine + ✓ ✓ 430-9 Urine + ✓ ✓ 432-15 Urine - ✓ 432-4 Serum + ✓ 432-5 Urine + ✓ ✓ 432-7 Urine - ✓ 433-4 Urine + ✓ ✓ 434-1 Urine + ✓ ✓ ✓ 438-1 Urine - ✓ ✓ 439-2 Urine + ✓ ✓ 439-6 Serum + ✓ ✓ ✓ 440-2 Urine + ✓ ✓ 440-3 Serum - ✓ ✓ ✓ 444-5 Serum - ✓ ✓ ✓ 444-6 Urine - ✓ 461-2 Urine - ✓ ✓ 547-5 Urine + ✓ ✓

Table 2. Burkholderia pseudomallei protein hits by NAPPA array probed with InMAD immune sera. Percentage of InMAD immune sera reactive to protein spots by either IgM or IgG antibodies. Cutoff set to 1.4; specificity > 95%; n=89. Locus Tag Protein name IgM IgG BPSL2234 hypothetical protein 8% 7% BPSS1740 lipase chaperone lipB 6% 4% AQ15_RS04020 hypothetical protein 4% 2% BPSL0248 transporter protein 0% 6% BPSS0957 hypothetical protein 1% 4% BPSS1236 sugar transporter ATP-binding protein 1% 4% BPSL2501 hypothetical protein 1% 3% BPSL0076 ribonuclease P protein component 1% 3% BPSL0323 methyl-accepting chemotaxis protein 2% 2% BPSS2275 hypothetical protein 2% 2% BPSL0909 NOL1/NOP2/Sun family protein 0% 3% BPSL0677 DNA binding protein 0% 3% BPSL3319 flagellin FliC 0% 3% BPSL1181 alanyl-tRNA synthetase 1% 2% BPSL2884 hypothetical protein 1% 2% BPSL2436 RNA polymerase sigma factor RpoE 1% 2% BPSL0693 hypothetical protein 1% 2% BPSS2260 hypothetical protein 1% 2% BPSL2355 hypothetical protein 1% 2% BPSL0366 8-amino-7-oxononanoate synthase bioF 3% 0% BPSL3384 aminotransferase 2% 1% BPSL2861 4-hydroxybenzoate octaprenyltransferase 2% 1% BPSL3284 secreted substrate binding protein 2% 1% BPSS1531 translocator protein BipC (T3SS-3) 2% 1% BPSL0245 ATPase 2% 0% BPSL0267 flagella synthesis protein 2% 0% type VI secretion system-associated BPSS0175 2% 0% protein TagK-3 (T6SS-4) tagK-3 BPSS0597 hypothetical protein 2% 0% BPSS0798 hypothetical protein 2% 0% phenylacetic acid degradation protein BPSL3044 2% 0% PaaI paaI BPSS0837 hypothetical protein 0% 2% BPSL2220 hypothetical protein 0% 2% BPSS0831 hypothetical protein 0% 2% BPSL3011 dephospho-CoA kinase coaE 0% 2% BPSL1286 hypothetical protein 0% 2%

Table 3. Burkholderia pseudomallei protein hits by NAPPA probed with melioidosis patient sera. Percentage of InMAD immune sera reactive to protein spots by either human IgG or IgA antibodies. Cutoff value set to 2.0; specificity > 95%; sensitivity > 15%; n=20

Locus Tag Protein Name IgG IgA BPSL1449 lysM domain protein 35% 0% BPSS0001 hypothetical protein 30% 15% BPSL2355 hypothetical protein 30% 0% BPSL1381 peptidase 25% 0% BPSL0999 membrane protein 20% 0% BPSL0697 periplasmic cytochrome c protein 20% 0% BPSL2995 signal recognition particle protein 20% 10% BPSL1286 hypothetical protein 20% 0% BPSL2404 periplasmic ligand binding lipoprotein 15% 0% BPSL0993 hypothetical protein 15% 5% BPSL3222 50S ribosomal protein L7/L12 rplL 15% 0% BPSL0774 two-component system sensor kinase 15% 0% BPSL2712 hydrolase 15% 0% BPSL1161 hypothetical protein 15% 10% BPSL2246 peptidyl-prolyl cis-trans isomerase B ppiB 15% 0% BPSL0027 flagellar motor switch protein FliM 15% 10% BPSS1228 cation transporter 15% 0% BPSL1827 hypothetical protein 15% 0% BPSS0476 co-chaperone GroS 15% 0% BPSL2698 co-chaperone GroES1 15% 0% BPSS1348 efflux transporter outer membrane subunit 10% 30% BPSL2522 outer membrane protein A ompA 10% 25% BPSL3153 sulfur carrier protein ThiS 5% 25% BPSS1740 lipase chaperone lipB 5% 20% BPSL3092 bacteriocin secretion protein 0% 35% BPSL3335 lipoprotein 0% 15% acetyl-CoA carboxylase biotin carboxyl BPSL2983 0% 15% carrier protein subunit accB CPS Capsular polysaccharide 30% 30%

Table 4. Summary of melioidosis samples evaluated for circulating Francisella tularensis proteins

Patient ID Serum sample Urine sample Diagnosis 1 ✓ PCR 2 ✓ PCR 3 ✓ PCR 4 ✓ PCR 5 ✓ PCR 6 ✓ PCR 7 ✓ PCR 8 ✓ PCR 9 ✓ PCR 10 ✓ PCR 11 ✓ PCR 12 ✓ PCR 13 ✓ PCR 14 ✓ Serology 15 ✓ ✓ Serology 16 ✓ ✓ Serology 17 ✓ ✓ Serology 18 ✓ ✓ Serology 19 ✓ ✓ Serology 20 ✓ ✓ Serology 21 ✓ ✓ Serology

Table 5. Francisella tularensis protein hits by NAPPA array probed with InMAD immune sera. Percentage of InMAD immune sera reactive to protein spots by either IgM or IgG antibodies. Cutoff set to 1.4; specificity > 95%; n = 83. Locus Tag Protein name IgM IgG FTT1712 Intercellular growth locus subunit C 23% 2% FTT0799 glycosyl transferases group 1 family protein 22% 0% FTT0879 superoxide dismuate 16% 1% FTT0954c hypothetical protein 13% 2% FTT0699 polynucleotide phosphorylase 8% 6% FTT1357 Intercellular growth locus subunit C 12% 0% FTT0151 16S rRNA-processing protein RimM 11% 1% FTT1704 Intercellular growth locus subunit G 11% 1% isftu2 transposase 8% 2% FTT0183c 30S ribosomal protein S1 7% 2% FTT1402c hypothetical protein 6% 4% FTT1349 Intercellular growth locus subunit G 8% 0% BZ14_968 putative ferredoxin 8% 0% FTT0677c hypothetical protein 8% 0% FTT0307 glutamyl-tRNA synthetase 2% 5% FTT1042 C32 tRNA thiolase 6% 1% FTT0052 histidyl-tRNA synthetase 6% 0% FTT0845 hypothetical protein 5% 0% FTT1073c hypothetical protein 5% 0% FTT1761 hypothetical protein 2% 2% FTT0461 RNA-binding protein 1% 4% FTT1257 HlyD family secretion protein 0% 5% FTT0518 50S ribosomal protein L11 methyltransferase 4% 0% FTT1202 LysR family transcriptional regulator 4% 0% FTT1647c diyroorotate dehydrogenase 2% 1% isftu2 transposase 2% 1% FTT0924 hypothetical protein 1% 2% FTT0220c hypothetical protein 1% 2% FTT0209c periplasmic solute binding family protein 1% 2% FTT0115 nucleoside permease NUP family protein 1% 2% FTT0469 dimethyladenosine transferase 1% 2% FTT0859c hypothetical protein 1% 2% LPS Lipopolysaccharide 5% 4%

Table 6. Francisella tularensis protein hits by NAPPA probed with tularemia patient sera. Percentage of InMAD immune sera reactive to protein spots by either human IgG or IgA antibodies. Cutoff value set to 2.0; specificity > 95%; sensitivity > 15%; n=21

Locus Tag Protein Name IgG IgA FTT0975 hypothetical protein 57% 5% FTT0106c RND efflux transporter 48% 0% dihydrolipoamide succinyltransferase FTT0077 component of 2-oxoglutarate dehydrogenase 62% 14% complex acetyl-CoA carboxylase, biotin carboxyl FTT0472 81% 0% carrier protein FTT1589c hypothetical protein 24% 10% FTT1539c hypothetical protein 24% 0% FTT1116c preprotein translocase family protein 24% 0% FTT1679 30S ribosomal protein S20 19% 0% FTT1529 acyl-CoA dehydrogenase 19% 0% FTT0721c peroxidase/catalase 19% 0% FTT1269c molecular chaperone DnaK 29% 0% FTT1712 Intercellular growth locus subunit C 10% 33% FTT1357 Intercellular growth locus subunit C 10% 43% FTT1092c pseudo 19% 24% FTT0879 superoxide dismuate 10% 38% FTT1042 C32 tRNA thiolase 10% 38% FTT1349 Intercellular growth locus subunit G 19% 33% FTT1109 choloylglycine hydrolase family protein 10% 33% FTT0287c hypothetical protein 5% 33% FTT0954c hypothetical protein 10% 33% FTT1704 Intercellular growth locus subunit G 10% 33% FTT0677c hypothetical protein 10% 33% FTT0151 16S rRNA-processing protein RimM 10% 33% FTT0052 histidyl-tRNA synthetase 5% 33% FTT1073c hypothetical protein 10% 29% LPS Lipopolysaccharide 90% 10%

Table 7. Proteins to be evaluated by validation studies as biomarkers of melioidosis and tularemia

Protein SignalP- InMAD Patient Locus Tag LC-MS/MS Description 5.0 Score NAPPA NAPPA

Melioidosis

translocator 0.97 BPSS1531 protein BipC ✓ (other) (T3SS-3) phasin-like 0.99 BPSL2298 ✓ protein (other) subfamily M23B 0.98 BPSL1504 ✓ unassigned (Sec/SPII) peptidase multifunctional polyketide- 0.65 BPSS0311 ✓ peptide (other) syntase bacteriocin 0.98 BPSL3092 secretion ✓ ✓ (other) protein 0.98 BPSL1445 lipoprotein ✓ (Sec/SPII) 0.95 BPSL3319 flagellin ✓ ✓ (other)

Tularemia

FTT1357/ Intercellular 0.97 ✓ ✓ 1712 growth locus C (other) Uncharacterize 0.97 FTT0308 ✓ d protein (Sec/SPI) β-glucosidase- 1.00 FTT0928c related ✓ ✓ (other) glycosidase hypothetical 0.95 FTT0954c ✓ ✓ protein (other) FTT1349/ Intercellular 0.94 ✓ ✓ 1704 growth locus G (other)

Table S1. List of Burkholderia pseudomallei proteins identified by data-dependent acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS). Each hit is an individual peptide with a Xcorr score ≥ 1.8.

Locus Tag/ Protein Description # of hits Gene ID BPSL3053 indole-3-glycerol phosphate synthase 19 BPSL2545 5-methyltetrahydropteroyltriglutamate-- homocysteine S- 12 methyltransferase BPSL1015 porphobilinogen deaminase 11 BPSL0893 elongation factor G 11 BPSL2938 leucyl-tRNA synthetase 10 BPSL1290 thiamine biosynthesis protein ThiC 10 BPSL3362 glycine dehydrogenase 9 BPSL0906 isoleucyl-tRNA synthetase 9 BPSL3290 S-adenosyl-L-homocysteine hydrolase 7 BPSL1006 argininosuccinate lyase 7 BPSS1705 3-isopropylmalate dehydrogenase 7 BPSL0383 arginyl-tRNA synthetase 6 aroA 3-phosphoshikimate 1-carboxyvinyltransferase 6 BPSS1355 choline dehydrogenase 6 fabV enoyl-[acyl-carrier-protein] reductase 6 BPSL3311 transcriptional activator FlhD 6 BPSL1358 phosphoglucosamine mutase 6 BPSL2252 DNA mismatch repair protein MutS 6 BPSL1324 phosphoenolpyruvate carboxykinase 6 BPSL0965 leucyl aminopeptidase 6 rlmN 23S rRNA (adenine(2503)-C(2))-methyltransferase 6 BPSL2826 molecular chaperone DnaJ 5 BPSL2827 molecular chaperone DnaK 5 BPSS0040 GTP cyclohydrolase I 5 BPSL0687 glycerol kinase 5 BPSL1513 4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase 5 BPSL3027 UDP-N-acetylmuramoyl-L-alanyl-D-glutamate synthetase 5 BPSL2403 non-hemolytic phospholipase C 5 BPSL2896 bifunctional phosphoribosylaminoimidazolecarboxamide 5 formyltransferase/IMP cyclohydrolase BPSL3220 DNA-directed RNA polymerase subunit beta' 5 BPSL3016 preprotein translocase subunit SecA 5 ttcA tRNA 2-thiocytidine(32) synthetase 5 BPSL0969 dihydroxy-acid dehydratase 5 BPSL2824 3-methyl-2-oxobutanoate hydroxymethyltransferase 5

BPSL0644 aspartyl-tRNA synthetase 4 BPSL3398 ATP synthase F0F1 subunit alpha 4 BPSS1354 betaine aldehyde dehydrogenase 4 BPSL0364 biotin synthase 4 BPSS1960 thymidine phosphorylase 4 BPSL0276 flagellar basal body L-ring protein 4 BPSL0122 methionyl-tRNA formyltransferase 4 glnD PII uridylyl-transferase 4 BPSL1514 histidyl-tRNA synthetase 4 BPSL2739 homogentisate 1,2-dioxygenase 4 lifO lipase chaperone 4 BPSL2281 lysyl-tRNA synthetase 4 BPSL0197 homoserine O-acetyltransferase 4 BPSL0674 (dimethylallyl)adenosine tRNA methylthiotransferase 4 BPSL0003 5-methylaminomethyl-2-thiouridine methyltransferase 4 BPSL2818 phosphoribosylaminoimidazole synthetase 4 pvdA l-ornithine 5-monooxygenase 4 BPSL2600 seryl-tRNA synthetase 4 BPSS0006 L-threonine 3-dehydrogenase 4 rbsA sugar ABC transporter ATP-binding protein 4 BPSL2905 anhydro-N-acetylmuramic acid kinase 3 BPSL3169 shikimate kinase 3 BPSL2385 succinylglutamate desuccinylase 3 BPSS1353 transcriptional regulator BetI 3 BPSL0366 8-amino-7-oxononanoate synthase 3 BPSS1532 translocator protein BipB (T3SS-3) 3 BPSS1534 type III secretion system export apparatus protein BsaZ (T3SS-3) 3 BPSL2304 bifunctional 5,10-methylene-tetrahydrofolate dehydrogenase/ 3 5,10-methylene-tetrahydrofolate cyclohydrolase BPSL0189 aspartyl/glutamyl-tRNA amidotransferase subunit B 3 BPSL2127 GMP synthase 3 BPSL1163 coproporphyrinogen III oxidase 3 BPSL0799 phosphoribosylaminoimidazole-succinocarboxamide synthase 3 BPSL0203 ATP-dependent protease ATP-binding subunit HslU 3 htpX zinc metalloprotease 3 BPSL2431 GTP-binding protein LepA 3 BPSL0998 methionyl-tRNA synthetase 3 msbA lipid A export permease/ATP-binding protein 3 BPSL0868 UDP-N-acetylenolpyruvoylglucosamine reductase 3 BPSL3024 UDP-N-acetylmuramate--L-alanine ligase 3

BPSL0912 quinolinate synthetase 3 BPSL2426 pyridoxine 5'-phosphate synthase 3 plsX phosphate acyltransferase 3 BPSL1366 polyphosphate kinase 3 BPSL3002 gamma-glutamyl kinase 3 BPSL1538 ribosomal protein S12 methylthiotransferase 3 rlmD 23S rRNA (uracil(1939)-C(5))-methyltransferase 3 tal transaldolase 3 BPSL1945 threonyl-tRNA synthetase 3 BPSL2490 tRNA (guanine-N(1)-)-methyltransferase 3 BPSL3052 anthranilate phosphoribosyltransferase 3 BPSL2656 UreD-family accessory protein 3 BPSL0373 bifunctional isocitrate dehydrogenase kinase/phosphatase 2 acsA acetyl-CoA synthetase 2 BPSL2009 alanyl-tRNA synthetase 2 apt adenine phosphoribosyltransferase 2 BPSL1743 arginine deiminase 2 BPSL1962 chorismate synthase 2 BPSL2387 succinylglutamic semialdehyde dehydrogenase 2 BPSL3396 ATP synthase F0F1 subunit beta 2 BPSL3274 hypothetical protein 2 BPSS0890 hypothetical protein 2 BPSL0365 dithiobiotin synthetase 2 BPSS1531 translocator protein BipC (T3SS-3) 2 BPSL1165 hypothetical protein 2 BPSL0877 hypothetical protein 2 BPSL3301 chemotaxis-specific methylesterase 2 cheD chemoreceptor glutamine deamidase 2 BPSL2497 D-amino acid dehydrogenase small subunit 2 BPSL2941 dihydrodipicolinate reductase 2 BPSL3023 D-alanine--D-alanine ligase 2 erpA iron-sulfur cluster insertion protein 2 BPSL2442 3-oxoacyl-ACP synthase 2 fdhD formate dehydrogenase accessory sulfurtransferase 2 BPSL3022 cell division protein FtsQ 2 BPSL2076 glycogen branching enzyme 2 glgC glucose-1-phosphate adenylyltransferase 2 BPSL2614 bifunctional glucokinase/RpiR family transcriptional regulator 2 BPSL0313 bifunctional glmU protein 2

BPSL2835 bifunctional glutamine-synthetase 2 adenylyltransferase/deadenyltransferase BPSL2197 glutamyl-tRNA synthetase 2 BPSL0297 glutathione reductase 2 BPSL2698 co-chaperonin GroES 2 BPSL2623 glutamate-1-semialdehyde aminotransferase 2 hutI imidazolonepropionase 2 BPSS1512 deubiquitinase TssM 2 iolG inositol 2-dehydrogenase 2 BPSL2865 catalase-peroxidase 2 BPSL0971 prolipoprotein diacylglyceryl transferase 2 BPSL0414 lipoyl synthase 2 lptD LPS-assembly protein 2 BPSL2147 UDP-N-acetylglucosamine acyltransferase 2 BPSS1722 malate dehydrogenase 2 BPSL2815 tRNA delta(2)-isopentenylpyrophosphate transferase 2 BPSL0080 tRNA modification GTPase TrmE 2 mnmG tRNA uridine-5-carboxymethylaminomethyl(34) synthesis enzyme 2 BPSL0786 molybdenum cofactor biosynthesis protein MoaC 2 BPSL2975 monofunctional biosynthetic peptidoglycan transglycosylase 2 BPSL2481 oligoribonuclease 2 BPSL0991 pantoate--beta-alanine ligase 2 BPSL1941 phenylalanyl-tRNA synthetase subunit alpha 2 pncB nicotinate phosphoribosyltransferase 2 BPSL1362 phosphate transporter ATP-binding protein 2 BPSL1866 dihydroorotate dehydrogenase 2 2 BPSL0632 7-cyano-7-deazaguanine reductase 2 BPSL3212 50S ribosomal protein L4 2 BPSL1461 50S ribosomal protein L9 2 BPSL3221 DNA-directed RNA polymerase subunit beta 2 BPSL2899 Holliday junction DNA helicase RuvB 2 BPSL1858 alkanesulfonate monooxygenase 2 BPSL0779 succinyl-CoA synthetase subunit beta 2 BPSS1697 tryptophan synthase subunit alpha 2 BPSL2158 elongation factor Ts 2 tyrS tyrosyl-tRNA synthetase 2 BPSL3163 glycerol-3-phosphate transporter ATP-binding subunit 2 BPSS0356 excinuclease ABC subunit B 2 BPSL2420 excinuclease ABC subunit C 2 BPSL1980 valyl-tRNA synthetase 2

ybeY rRNA maturation Rnase 2 yidC membrane protein insertase 2

Table S2. List of Burkholderia pseudomallei protein hits by data-independent acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS). Hits were made against a custom B. pseudomallei database.

Locus Tag/ Protein Description # of hits GeneID BPSS1356 regulatory protein 148 BPSS0306 multifunctional polyketide-peptide syntase 129 BPSS0311 multifunctional polyketide-peptide syntase 118 BPSL1087 heat shock protein 90 103 BPSS0487 hypothetical protein 94 BPSL2827 molecular chaperone DnaK 85 BPSL2952 glyceraldehyde 3-phosphate dehydrogenase 1 81 BPSL1743 arginine deiminase 77 BPSS1172 non-ribosomal peptide synthase/polyketide synthase 76 BPSL3396 ATP synthase F0F1 subunit beta 75 BPSS1726 aconitate hydratase 73 BPSL2515 30S ribosomal protein S1 73 BPSL3221 DNA-directed RNA polymerase subunit beta 72 BPSL3215 elongation factor Tu 69 BPSL1484 ClpB heat-shock protein 68 BPSL2298 phasin-like protein 65 BPSS1722 malate dehydrogenase 61 BPSL3216 elongation factor G 58 BPSL3220 DNA-directed RNA polymerase subunit beta' 56 BPSL3290 S-adenosyl-L-homocysteine hydrolase 56 BPSL3041 PacL 56 BPSS0307 gamma-aminobutyraldehyde dehydrogenase 55 BPSS1171 non-ribosomal peptide synthase/polyketide synthase 55 BPSS0304 hypothetical protein 52 BPSL2270 phosphopyruvate hydratase 49 BPSS0372 fumarate hydratase 49 BPSS0355 aromatic amino acid aminotransferase 47 BPSL3398 ATP synthase F0F1 subunit alpha 46 BPSS1955 bifunctional enoyl-CoA hydratase/phosphate acetyltransferase 46 BPSS0299 fatty-acid CoA ligase 45 BPSL0893 elongation factor G 45 BPSS2288 heat shock protein 20 44 BPSL0779 succinyl-CoA synthetase subunit beta 43 BPSL3224 50S ribosomal protein L1 43 BPSS0486 non-ribosomal peptide synthetase 43

BPSL1445 lipoprotein 42 BPSL2096 hydroperoxide reductase 42 BPSL2192 malate synthase 42 BPSL3187 DNA-directed RNA polymerase subunit alpha 41 BPSL3152 thiazole synthase 40 BPSS0839 hypothetical protein 40 BPSL3016 preprotein translocase subunit SecA 39 BPSL0004 DNA-binding protein HU-alpha 39 BPSS1954 polymerase 39 BPSL3106 type VI secretion system protein TssC-1 39 BPSL0965 leucyl aminopeptidase 38 BPSS1847 lipoprotein 38 BPSL1744 ornithine carbamoyltransferase 38 BPSL1955 succinyl-CoA:3-ketoacid-coenzyme A transferase subunit A 36 BPSS0309 peptide synthase regulatory protein 36 BPSL3151 thiamine-phosphate pyrophosphorylase 35 BPSL3101 type VI secretion system protein TssH-1 35 BPSL0638 hypothetical protein 35 BPSL2865 catalase-peroxidase 34 BPSS1715 type II citrate synthase 34 BPSS1486 hypothetical protein 34 BPSL1550 betaine aldehyde dehydrogenase 34 BPSL1721 argininosuccinate synthase 33 BPSL2500 electron transfer flavoprotein subunit beta 33 BPSS1169 hypothetical protein 33 BPSL3212 50S ribosomal protein L4 33 BPSL1536 acetyacetyl-CoA reductase 32 BPSL2698 co-chaperonin GroES 32 BPSL2748 oxidoreductase 31 BPSL2422 elongation factor P 31 BPSL0692 gamma-glutamyltransferase 2 30 BPSL0793 branched-chain amino acid aminotransferase 30 BPSL2522 outer membrane protein a 30 BPSL2953 transketolase 30 BPSL2188 isocitrate lyase 30 BPSL1560 hypothetical protein 30 BPSL2305 oligopeptidase A 29 BPSL2158 elongation factor Ts 29 BPSL0854 pyridoxamine 5'-phosphate oxidase 29 BPSL3286 dienelactone hydrolase 29

BPSL1405 ATP-dependent protease 29 BPSL2987 thiol peroxidase 28 BPSL0644 aspartyl-tRNA synthetase 28 BPSL1552 outer membrane protein 27 BPSS0913 methionine gamma-lyase 27 BPSL1323 heat shock protein 27 BPSL2983 acetyl-CoA carboxylase biotin carboxyl carrier protein subunit 27 BPSL1322 heat shock protein 26 BPSL2094 osmolarity response regulator 26 BPSS1484 hypothetical protein 26 BPSS1170 non-ribosomal peptide synthase/polyketide synthase 26 BPSS0880 transcription elongation factor 26 BPSL2390 bifunctional N-succinyldiaminopimelate- 25 aminotransferase/acetylornithine transaminase BPSL3188 30S ribosomal protein S4 25 BPSS0308 hypothetical protein 24 BPSL0896 isocitrate dehydrogenase 24 BPSL3202 50S ribosomal protein L24 24 BPSS1173 non-ribosomal peptide/polyketide synthase 24 BPSL2627 6,7-dimethyl-8-ribityllumazine synthase 23 BPSL0853 cyclopropane-fatty-acyl-phospholipid synthase 23 BPSL2433 peptidase 23 BPSS1916 acetoacetyl-CoA reductase 23 BPSL2129 inosine 5'-monophosphate dehydrogenase 23 BPSL3223 50S ribosomal protein L10 23 BPSL3107 type VI secretion system protein TssB-1 23 BPSL1265 hypothetical protein 23 BPSL1907 dihydrolipoamide dehydrogenase 22 BPSS1140 universal stress family protein 22 BPSL3108 type VI secretion system-associated protein TagM-1 22 BPSL0875 adenylate kinase 22 BPSL3399 ATP synthase F0F1 subunit delta 22 BPSL3395 ATP synthase F0F1 subunit epsilon 22 BPSL2648 protein-L-isoaspartate O-methyltransferase 21 BPSS0840 zinc-binding dehydrogenase 21 BPSL1359 phosphate transport system, substrate-binding exported 21 periplasmic protein BPSL2097 hypothetical protein 21 BPSL1909 2-oxoglutarate dehydrogenase E1 21 BPSL1518 RNA-binding protein Hfq 21 BPSL1549 hypothetical protein 21

BPSL0521 ribose-phosphate pyrophosphokinase 21 BPSL1164 phosphoribosylamine--glycine ligase 21 BPSL1207 polynucleotide phosphorylase 21 BPSS1680 histone-like protein 20 BPSS1174 non-ribosomal peptide/polyketide synthase 20 BPSL1954 succinyl-CoA:3-ketoacid-coenzyme A transferase subunit B 20 BPSL2924 glutamate/aspartate periplasmic binding protein 20 BPSL1763 exported chitinase 20 BPSL0798 fructose-1,6-bisphosphate aldolase 20 BPSL1027 nitrogen regulatory protein P-II 2 20 BPSS0302 fatty acid biosynthesis-related CoA ligase 20 BPSL2151 outer membrane protein 20 BPSS0767 hypothetical protein 19 BPSS1561 carboxypeptidase 19 BPSS1944 alcohol dehydrogenase 19 BPSL3388 periplasmic amino acid binding transport protein 19 BPSS0225 hypothetical protein 18 BPSL2544 aminopeptidase 18 BPSL2733 LysR family transcriptional regulator 18 BPSL1351 carbamoyl phosphate synthase large subunit 18 BPSS1956 acetate kinase 18 BPSL2204 enoyl-ACP reductase 18 BPSL0796 phosphoglycerate kinase 18 BPSL2931 KHG/KDPG aldolase 18 BPSL1402 trigger factor 17 BPSL0408 penicillin-binding protein 6 17 BPSL3208 50S ribosomal protein L22 17 BPSL2863 ferritin 17 BPSS1183 non-ribosomally encoded peptide/polyketide synthase 17 BPSL1514 histidyl-tRNA synthetase 17 BPSS0303 diaminopimelate decarboxylase 17 BPSL2423 sigma-54 interacting response regulator protein 17 BPSL1723 hypothetical protein 16 BPSL1919 transcription elongation factor NusA 16 BPSS0864 aldo/keto reductase 16 BPSS1485 hypothetical protein 16 BPSL1918 translation initiation factor IF-2 15 BPSL2499 electron transfer flavoprotein subunit alpha 15 BPSL2605 thioredoxin reductase 15 BPSL3181 cytochrome C 15

BPSS0484 HhqD 15 BPSL3306 chemotaxis two-component sensor kinase CheA 15 BPSL2138 hypothetical protein 15 BPSL1198 ketol-acid reductoisomerase 15 BPSL1290 thiamine biosynthesis protein ThiC 15 BPSL3397 ATP synthase F0F1 subunit gamma 15 BPSL0969 dihydroxy-acid dehydratase 15 BPSL2917 heat shock Hsp20-like protein 15 BPSL2260 tryptophanyl-tRNA synthetase 15 BPSL0371 acetyl-CoA acetyltransferase 14 BPSL1535 acetyl-CoA acetyltransferase 14 BPSS1076 hypothetical protein 14 BPSL1497 thioredoxin 1 14 BPSS2284 hypothetical protein 14 BPSL3196 30S ribosomal protein S5 14 BPSL1217 NADH dehydrogenase subunit G 14 BPSS1953 ATP synthase F0F1 subunit beta 14 BPSL0124 M48 family peptidase 14 BPSS1098 hypothetical protein 14 BPSL0118 DNA topoisomerase III 14 BPSL1404 ATP-dependent protease ATP-binding subunit ClpX 14 BPSL0349 hypothetical protein 14 BPSS0890 hypothetical protein 14 BPSL3058 thiol:disulfide interchange protein DsbC 14 BPSL0906 isoleucyl-tRNA synthetase 14 BPSL3203 50S ribosomal protein L14 14 BPSL3400 ATP synthase F0F1 subunit B 14 BPSL0437 glutathione synthetase 14 BPSL1769 cobalamin biosynthesis-like protein 14 BPSL1478 threonine synthase 14 BPSL2628 transcription antitermination protein NusB 13 BPSL2925 glutamate dehydrogenase 13 BPSL2272 CTP synthetase 13 BPSL2928 adenylosuccinate lyase 13 BPSS0836 universal stress protein 13 BPSS1924 hypothetical protein 13 BPSL1510 nucleoside diphosphate kinase 13 BPSL2693 hypothetical protein 13 BPSL3225 50S ribosomal protein L11 13 BPSL0410 hypothetical protein 13

BPSS2169 MoaA/NifB/PqqE family protein 13 BPSL2679 epimerase/dehydratase 13 BPSL0383 arginyl-tRNA synthetase 13 BPSL2732 aminotransferase 13 BPSL1095 transaldolase B 13 BPSL2258 dihydrodipicolinate synthase 13 BPSL0849 transcription regulator AsnC 13 BPSL2734 D-lactate dehydrogenase 13 BPSS1114 FtsH-2 protease 13 BPSS1203 aspartate carbamoyltransferase 12 BPSL2520 hypothetical protein 12 BPSL3209 30S ribosomal protein S19 12 BPSL0203 ATP-dependent protease ATP-binding subunit HslU 12 BPSS0032 universal stress-related protein 12 BPSS0837 hypothetical protein 12 BPSS0482 HhqB 12 BPSL3051 anthranilate synthase component II 12 BPSL2127 GMP synthase 12 BPSL2356 anaerobic ribonucleoside triphosphate reductase 12 BPSL2911 50S ribosomal protein L13 12 BPSL2344 histidine ammonia-lyase 12 BPSL0453 cytochrome c oxidase 12 BPSL3121 cytochrome c1 12 BPSL0443 phosphoglyceromutase 12 BPSL3053 indole-3-glycerol phosphate synthase 12 BPSL2600 seryl-tRNA synthetase 12 BPSL1980 valyl-tRNA synthetase 12 BPSL0999 OmpA family transmembrane protein 12 BPSL3389 trifunctional transcriptional regulator/proline 12 dehydrogenase/pyrroline-5-carboxylate dehydrogenase BPSL2758 serine hydroxymethyltransferase 12 BPSL1908 dihydrolipoamide succinyltransferase 12 BPSL2874 hypothetical protein 12 BPSL3391 uroporphyrinogen decarboxylase 12 BPSL3194 50S ribosomal protein L15 11 BPSS0276 aerotaxis receptor 11 BPSL2992 ribonucleotide-diphosphate reductase subunit alpha 11 BPSL2990 histone H1-like protein 11 BPSL0916 50S ribosomal protein L28 11 BPSL2765 OmpA family lipoprotein 11

BPSL1209 triosephosphate isomerase 11 BPSL1213 NADH dehydrogenase subunit C 11 BPSL3160 hypothetical protein 11 BPSL1797 ABC transporter membrane protein 11 BPSL0989 ParA family ATPase 11 BPSL2831 ferrochelatase 11 BPSL0379 short chain dehydrogenase 11 BPSL2535 transferase 11 BPSL1458 30S ribosomal protein S6 11 BPSL1506 hypothetical protein 11 BPSL1940 phenylalanyl-tRNA synthetase subunit beta 11 BPSS0514 acetyl-CoA hydrolase/transferase 11 BPSL2932 phosphogluconate dehydratase 11 BPSS0280 succinate-semialdehyde dehydrogenase 11 BPSS1723 lyase 11 BPSL2557 cold shock-like protein 11 BPSL2197 glutamyl-tRNA synthetase 11 BPSL1356 FtsH endopeptidase 11 BPSL2271 2-dehydro-3-deoxyphosphooctonate aldolase 11 BPSL2489 50S ribosomal protein L19 10 BPSL2301 pyruvate dehydrogenase subunit E1 10 BPSS1766 sulfurtransferase (cyanide detoxification) 10 BPSL2829 heat shock protein GrpE 10 BPSL2984 acetyl-CoA carboxylase biotin carboxylase subunit 10 BPSL3207 30S ribosomal protein S3 10 BPSL3183 delta-aminolevulinic acid dehydratase 10 BPSL1981 UTP-glucose-1-phosphate uridylyltransferase 10 BPSL1013 phosphoenolpyruvate carboxylase 10 BPSL1745 carbamate kinase 10 BPSS2287 hypothetical protein 10 BPSL1711 carbamoyl transferase 10 BPSL1555 putrescine-binding periplasmic protein 10 BPSS0619 methylmalonate-semialdehyde dehydrogenase 10 BPSL2963 orotidine 5'-phosphate decarboxylase 10 BPSS1107 hypothetical protein 10 BPSL1273 hypothetical protein 10 BPSL1416 phosphoribosylformylglycinamidine synthase 10 BPSL0903 deoxyuridine 5'-triphosphate nucleotidohydrolase 10 BPSL3206 50S ribosomal protein L16 10 BPSL2942 outer membrane protein 10

BPSS2043 hypothetical protein 10 BPSS1102 hypothetical protein 10 BPSL0880 superoxide dismutase 9 BPSS0300 malonyl CoA-ACP transacylase 9 BPSL3234 phenylacetic acid degradation NADH oxidoreductase PaaE 9 BPSL2140 phosphoenolpyruvate synthase 9 BPSL0856 thioredoxin protein 9 BPSL3154 thiamine biosynthesis oxidoreductase ThiO 9 BPSL1495 transcription termination factor Rho 9 BPSL1215 NADH dehydrogenase subunit E 9 BPSL1349 carbamoyl phosphate synthase small subunit 9 BPSL2611 maltose-binding protein 9 BPSL2438 3-oxoacyl-ACP synthase 9 BPSL0547 single-stranded DNA-binding protein 9 BPSL0137 hypothetical protein 9 BPSL0186 rod shape-determining protein MreB 9 BPSS1095 heat-shock chaperone protein 9 BPSL1513 4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase 8 BPSL3015 bifunctional ornithine acetyltransferase/N-acetylglutamate 8 synthase BPSL0212 S-adenosylmethionine synthetase 8 BPSS1466 aldehyde dehydrogenase 8 BPSL3217 30S ribosomal protein S7 8 BPSL1188 TetR family transcriptional regulator 8 BPSS0721 enoyl-ACP reductase 8 BPSL3226 transcription antitermination protein NusG 8 BPSL2989 lipoprotein 8 BPSS1046 hypothetical protein 8 BPSL3210 50S ribosomal protein L2 8 BPSS0005 2-amino-3-ketobutyrate CoA ligase 8 BPSL0298 argininosuccinate synthase 8 BPSS1704 aspartate-semialdehyde dehydrogenase 8 BPSL2147 UDP-N-acetylglucosamine acyltransferase 8 BPSS1846 hypothetical protein 8 BPSS0882 hypothetical protein 8 BPSL1860 3-hydroxyisobutyryl-CoA hydrolase 8 BPSL2361 hypothetical protein 8 BPSL0532 PTS system, EIIA component 8 BPSL0384 hypothetical protein 8 BPSL2697 molecular chaperone GroEL 7

BPSS1182 acyl carrier protein 7 BPSL3190 30S ribosomal protein S13 7 BPSL1622 hypothetical protein 7 BPSS2134 hypothetical protein 7 BPSL3281 HNS-like transcriptional regulator 7 BPSL2439 acyl carrier protein 7 BPSS1861 hypothetical protein 7 BPSL3422 adenylate cyclase 7 BPSL2009 alanyl-tRNA synthetase 7 BPSL2998 prolyl-tRNA synthetase 7 BPSL3105 type VI secretion system protein TssD-1 7 BPSL0099 glyoxalase/bleomycin resistance protein/dioxygenase 7 superfamily protein BPSS1762 1-deoxy-D-xylulose-5-phosphate synthase 7 BPSS2273 2-oxoisovalerate dehydrogenase subunit alpha 7 BPSL1720 argininosuccinate lyase 7 BPSL3301 chemotaxis-specific methylesterase 7 BPSL1385 hypothetical protein 7 BPSL2441 ACP S-malonyltransferase 6 BPSL3199 30S ribosomal protein S8 6 BPSL3213 50S ribosomal protein L3 6 BPSL3360 glycine cleavage system aminomethyltransferase T 6 BPSL3211 50S ribosomal protein L23 6 BPSL0074 DNA polymerase III subunit beta 6 BPSL0919 4-hydroxy-3-methylbut-2-enyl diphosphate reductase 6 BPSL2116 allantoicase 6 BPSL2300 dihydrolipoamide acetyltransferase 6 BPSL1542 cystathionine beta-lyase 6 BPSS0031 anaerobic growth regulatory protein 6 BPSL2686 dTDP-glucose 4,6-dehydratase 6 BPSL1961 electron transport protein 6 BPSL0079 hypothetical protein 6 BPSL3057 peptidase 6 BPSL3050 anthranilate synthase component I 6 BPSL1083 aminotransferase 6 BPSL2599 hypothetical protein 5 BPSL0520 50S ribosomal protein L25 5 BPSS1813 non-ribosomal peptide synthase related protein 5 BPSL2666 phosphoglucomutase 5 BPSS0310 hypothetical protein 5

BPSL3253 oxidoreductase 5 BPSL1960 short chain dehydrogenase 5 BPSL2612 glucose-6-phosphate 1-dehydrogenase 5 BPSL3070 aminopeptidase 5 BPSL3144 ABC transporter ATP-binding subunit 5 BPSS0354 3-hydroxybutyrate dehydrogenase 4 BPSL2342 urocanate hydratase 4 BPSL2920 hypothetical protein 4 BPSL0780 succinyl-CoA synthetase subunit alpha 4 BPSS1915 metallo-beta-lactamase 4 BPSS1542 chaperone protein BsaR (T3SS-3) 4 BPSL2995 signal recognition particle protein 4 BPSL3319 flagellin 4 BPSL1911 GTP-binding protein 4 BPSS0507 aminotransferase class-V 4 BPSL0927 CDP-6-deoxy-delta-3,4-glucoseen reductase 4 BPSL1206 30S ribosomal protein S15 3 BPSL2691 bifunctional pyrimidine regulatory protein PyrR uracil 3 phosphoribosyltransferase BPSL2896 bifunctional phosphoribosylaminoimidazolecarboxamide 3 formyltransferase/IMP cyclohydrolase BPSL3305 chemotaxis protein CheW 3 BPSL3232 phenylacetic acid degradation protein PaaC 3 BPSL2988 sugar kinase 3 BPSL2749 hypothetical protein 3 BPSS1918 alcohol dehydrogenase 3 BPSS0463 hypothetical protein 3 BPSL0446 preprotein translocase subunit SecB 2 BPSL2650 omega amino acid--pyruvate transaminase 2 BPSL0116 D-isomer specific 2-hydroxyacid dehydrogenase 2 BPSL2157 uridylate kinase 2 BPSL3042 beta-ketoadipyl CoA thiolase 2 BPSS0275 beta-ketoadipyl CoA thiolase 2 BPSL1226 hypothetical protein 2 BPSL1969 FAD-binding reductase 2 BPSS1749 6-phosphogluconate dehydrogenase 2

Table S3. List of Francisella tularensis proteins identified by data-dependent acquisition (DDA) liquid chromatography tandem mass spectrometry (LC-MS/MS). Each hit is an individual peptide with a Xcorr score ≥ 1.4.

Locus Tag Protein Description # of hits FTT0618c tRNA-2-methylthio-N(6)-dimethylallyladenosine synthase 21 FTT0527 AAA domain protein 7 FTT0188 Cell division protein FtsZ 7 FTT0108c CCA-adding enzyme 6 FTT1328c Putative D-lactate dehydrogenase, Fe-S protein, FAD/FMN- 4 containing FTT0154 Tyrosine recombinase XerD 4 FTT0932 Uncharacterized protein (ROK family protein) 4 FTT0137 Elongation factor Tu 4 FTT1241 Serine hydroxymethyltransferase 4 FTT1318c Cytosol aminopeptidase 4 FTT0790 exopolysaccharide biosynthesis polyprenyl 4 glycosylphosphotransferase family protein FTT0325 50S ribosomal protein L3 4 FTT0299 Valine--tRNA ligase 3 FTT0145 DNA-directed RNA polymerase subunit beta 3 FTT1570c beta-hydroxyacyl-(acyl-carrier-protein) dehydratase FabZ 3 FTT0337 50S ribosomal protein L5 3 FTT1230 ACT domain protein 3 FTT1291 major facilitator superfamily (MFS) transport protein 3 FTT0699 Polyribonucleotide nucleotidyltransferase 3 FTT1508c RelA/SpoT family protein 3 FTT0426 amino acid kinase family protein 3 FTT0769 Protein translocase subunit SecA 2 FTT1509c hypothetical protein CH65_1928 2 FTT0070c Major Facilitator Superfamily protein 2 FTT1404 sporulation related domain protein 2 FTT0308 hypothetical protein CH65_159 2 FTT0629 tRNA dimethylallyltransferase 2 FTT0926 Glutathione synthetase 2 FTT1367c phosphoglycerate kinase family protein 2 FTT0422 UDP-N-acetylmuramoyl-tripeptide--D-alanyl-D-alanine ligase 2 FTT0602c DUF3573 domain-containing protein 2 FTT1310c ATP-dependent metalloprotease 2 FTT0721c Catalase-peroxidase 2 FTT1769c ATP-dependent chaperone protein ClpB 2

Chapter 3. Development of a dual antigen lateral flow immunoassay for detecting

Yersinia pestis

Derrick Hau1, Brian Wade1, Chris Lovejoy1, Sujata G. Pandit1, Dana E. Reed1, Haley L.

DeMers1, Heather R. Green1, Emily E. Hannah1, Megan E. McLarty1, Cameron J. Creek1,

Chonnikarn Chokapirat1, Jose Arias-Umana1, Garett F. Cecchini1, Teerapat Nualnoi1,

Marcellene A. Gates-Hollingsworth1, Peter N. Thorkildson1, Kathryn J. Pflughoeft1, David

P. AuCoin1*

1Department of Microbiology and Immunology, University of Nevada Reno, School of

Medicine, Nevada, United States of America

*Corresponding author

Email: [email protected]

3.1 Abstract

Background:

Yersinia pestis is the causative agent of plague, a zoonosis associated with small mammals. Plague is a severe disease, especially in the pneumonic and septicemic forms, where fatality rates approach 100% if left untreated. Y. pestis was responsible for over 200 million deaths in Europe during the second great pandemic in the 14th century.

The bacterium is primarily transmitted via flea bite or through direct contact with an infected host. Most recently, the 2017 plague outbreak in Madagascar resulted in more than 2,400 cases and was highlighted by an increased number of pneumonic infections.

Plague remains endemic in Africa, Asia, and the Americas. For patients infected with Y. pestis, an accurate and timely diagnosis is critical to ensure that therapy is administered during an effective treatment window. Standard diagnostics for plague include laboratory-based assays such as bacterial culturing and serodiagnostic tests. Point-of- care rapid diagnostic tests (RDT) are utilized in some endemic areas; however, the assays are unable to detect all virulent strains of Y. pestis.

Methods:

The goal of this study was to develop a sensitive rapid plague diagnostic that can detect all virulent strains of Y. pestis. To meet this goal, twenty-two monoclonal antibodies

(mAbs) were produced against two Y. pestis antigens, low-calcium response V (LcrV) and capsular fraction-1 (F1), each shown to be detectable during an infection. mAbs were utilized to develop antigen-capture lateral flow immunoassays (LFI) and enzyme- linked immunosorbent assays for the detection of each antigen. A dual antigen LFI prototype comprised of two test lines was evaluated for the detect of both antigens in Y pestis lysates.

Results:

The LFIs developed for the detection of LcrV and F1 had limits of detection of roughly 1-

2 ng/mL in surrogate clinical samples (normal human sera spiked with recombinant protein). The optimized antigen-capture ELISA assays resulted in limits of detection of

74 pg/mL for LcrV and 61 pg/mL for F1 in buffer. The dual antigen LFI prototype could detect both antigens in Y. pestis lysates. The dual format was also evaluated for specificity using a panel of clinical near-neighbors and other Tier 1 bacterial Select

Agents. The resulting rapid diagnostic assay may be useful for differentiating plague from other infections presenting with nonspecific clinical symptoms.

Conclusions:

LcrV is expressed by all virulent Y. pestis strains, but homologs produced by other Yersinia species can hinder assay specificity. F1 is specific to Y. pestis but is not expressed by all virulent strains. Utilizing highly reactive mAbs, a dual-antigen detection (multiplexed) lateral flow immunoassay (LFI) was developed to capitalize on the strengths of each target.

Keywords

Yersinia pestis, plague, diagnostics, point-of-care, LcrV, F1, lateral flow immunoassay,

ELISA

3.2 Background

Plague is a febrile illness caused by Yersinia pestis, a Gram-negative, nonmotile coccobacillus. The bacterium was responsible for the Black Death, which devastated over a third of Europe’s population between 1347-1353 [158]. The Centers for Disease Control and Prevention (CDC) classifies Y. pestis as a Tier 1 Select Agent due to its high infectivity, threat to public health, and potential as a biothreat. The spread of Y. pestis is facilitated by small mammals and fleas. The bacterium is transmitted to humans through flea bites, contact with animal excretions, or inhalation of aerosolized droplets. The different routes of infection lead to three forms of plague: bubonic, pneumonic, and septicemic. Bubonic plague is easily diagnosed by the inflammation of lymph nodes resulting in the formation of painful swellings called buboes. Bubonic plague is the least fatal of the three forms, with a 40-70% case fatality rate (CFR) when left untreated; however, bubonic plague may develop into a more serious form of the infection [75].

Pneumonic and septicemic plague present with nonspecific flu-like symptoms, leading to death in as few as three days post-exposure [76]. The CFR for pneumonic and septicemic infections near 100% when left untreated [75]. Time is a critical factor for treating plague as effective therapeutics must be administered within 20 hours from the onset of symptoms to ensure the best chance for patient survival [77].

Y. pestis is a zoonotic bacterium found in all geographical regions besides Oceania, with

Madagascar and the Democratic Republic of Congo being the primary hot spots for annual plague outbreaks [64, 159]. Madagascar had accounted for 74% of all cases reported to the World Health Organization (WHO) between 2010 and 2015 [71]. During this time period, 200-700 cases were reported annually, mainly in the form of bubonic plague which is rarely transmissible human-to-human [73, 88]. During the 2017 plague season,

Madagascar reported a total of 2,417 cases of plague with a CFR of 8.6% [72].

Identification of the initial cluster of infections allowed for a proper response to prevent a larger epidemic [74]. This outbreak not only marked an increase in overall cases, but more importantly, an increased percentage of pneumonic infections (70% of total infections) [73,

74]. The increase in pneumonic infections may, in part, be attributed to human-to-human transmission that occurred via infectious droplets [66, 67]. This along with high mortality rates of pneumonic infections warrant the need for development of additional countermeasures for plague.

The gold standard for diagnosing plague is bacterial culture [78]. The use of serodiagnosis can improve the time for diagnosis but is hindered by the capacity to detect active infections [78, 160, 161]. These methods can be time consuming and require specialized laboratories and trained technicians. Advancements in rapid diagnostic tests (RDT) such as lateral flow immunoassays (LFI) have made the detection of Y. pestis more feasible in low-technology settings and are instrumental in controlling plague outbreaks in endemic regions. A comparative study on various diagnostic methods has deemed an LFI to be an ideal platform for diagnosing plague [162]. LFIs are rapid, membrane-based immunoassays using antibodies linked to gold-nanoparticles for visual detection.

Temperature stable reagent and user-friendly protocols make LFIs ideal for resource limited settings. The current LFI used in Madagascar detects for the capsular fraction-1

(F1) antigen and has a sensitivity of 100% and specificity ranging between 59-71%, dependent on the form of infection and testing matrix [163-165]. Of concern however, is that F1- strains have been identified in clinical settings as well as in the laboratory settings

[163, 166]. For the current project, development of a multiplexed RDT allows for detection

of multiple analytes hopefully strengthening the diagnostic power of the point-of-care assay.

Y. pestis is a facultative anaerobe equipped with several virulence factors to allow survival within macrophages and in extracellular spaces [167]. Genes encoding virulence factors are dispersed throughout the genome, including on three plasmids (pCD1, pPCP1, pMT1)

[168]. Current LFIs used to diagnose plague detect for F1, a protein encoded by the caf1 gene on pMT1, a plasmid unique to Y. pestis [162, 169, 170]. The 15.5 kDa F1 antigen polymerize to form a filament capsule surrounding the bacterium, protecting it from phagocytosis [171]. Expression of F1 is temperature-induced at 37°C. The protein is known to be shed during an infection, making it a viable candidate biomarker for diagnosing plague [172-174]. Though attenuated in its ability to cause bubonic plague, F1- isolates remain highly virulent by the inhalation route leading to pneumonic infections [170,

175].

The pCD1 plasmid carries genes encoding a type-III secretion system (T3SS) and its related effector proteins [176]. The pCD1 plasmid is found in clinically relevant neighbors

Y. pseudotuberculosis and Y. enterocolitica and is important for virulence [177]. The T3SS is associated with a low-calcium response crucial for pathogenicity of Yersinia species

[176]. Low-calcium response V (LcrV) is a multifunctional protein serving as the needle tip of the T3SS to translocate Yersinia outer proteins into host cells [178]. LcrV is also translocated during the process and suppresses the host inflammatory response by upregulating interleukin 10 via Toll-like receptor 2 [179]. Mutations in lcrV lead to avirulence in mice due to the inability to translocate effector proteins [180, 181]. Though

LcrV is displayed on the surface of the bacterium and translocated via the T3SS, the

antigen has also been reported to be shed into growth media in vitro [182]. Studies conducted using models of infection indicate that LcrV is detectable in serum and bronchoalveolar lavage fluid (BALF) in mice displaying symptoms of bubonic and pneumonic plague [183]. Since LcrV is essential for pathogenicity and appears to be shed during infection, it may serve as an important alternative biomarker for the diagnosis of plague [184-186].

While Y. pestis remains susceptible to many antibiotics, a growing number of resistant strains have been reported; and the ease of transferring resistance via plasmids is well established [89, 90, 187]. Furthermore, there is no FDA-approved vaccine for plague. Its short incubation period, high mortality rates, and potential for mass infection through aerosolization warrant the development of novel countermeasures for the infection. In this study, immunoassays were developed for the detection of LcrV and F1 for potential diagnosis of plague infections. Hybridoma cell lines producing monoclonal antibodies

(mAbs) against LcrV and F1 antigens were produced. The resulting mAbs were evaluated for affinity and kinetics and used to develop sensitive immunoassay prototypes. mAb pairs were evaluated to develop LFIs and enzyme-linked immunosorbent (ELISA) assays for the detection of LcrV and F1. Surrogate clinical samples (antigens spiked into normal human sera) were used to determine the analytical sensitivity or limit of detection (LOD) for the LFI prototypes. Pathogenic near neighbors and other Tier 1 bacterial Select Agents were used to begin to evaluate specificity of the LFI. The overall goal is for these prototypes to eventually be validated in samples collected from plague patients followed by FDA approval.

3.3 Methods

Monoclonal antibody (mAb) production

The use of animals in this study was to produce reagents (mAbs) for the development of immunoassay assays. All animal work and husbandry were located in the animal facility at the University of Nevada, Reno. Twenty Female CD1 mice, 6 – 8 weeks old (Charles

River Laboratories, Inc.), were immunized with either recombinant F1/LcrV fusion protein

(F1-V), LcrV, or F1 (Biodefense and Emerging Infections Research Resources Repository

[BEI Resources], Manassas, VA). Subcutaneous injections of recombinant F1-V, LcrV, or

F1 in emulsions of Titermax Gold Liquid Adjuvant (TiterMax, Norcross GA) were performed with subsequent boosts at weeks 4 and 8. Immunizations of recombinant F1 were also performed using Freund’s complete adjuvant (MilliporeSigma, Billerica, MA) via intraperitoneal injection with subsequent boosts using Freund’s incomplete adjuvant

(MilliporeSigma) at weeks 4, 8 and 12 . Each immunization scheme consisted of five animals caged together. The number of animals was selected to account or variability in the immune response, human error, and for any unforeseeable causes (i.e. death of animal). Sera samples were collected via submandibular or retro-orbital survival bleeds and titers were screened by indirect ELISA. A final boost of recombinant protein without adjuvant was administered intravenously three days prior to splenectomy. Euthanasia was performed by CO2 asphyxiation and final bleeds were performed via cardiac sticks.

Splenocytes from all mice were harvested and hybridoma cell lines were produced by standard technique using the P3X63Ag8.653 fusion partner [188]. Splenocytes from mice with the highest titers against the target antigen were prioritized to produce hybridoma cell lines (data not shown). Remaining splenocytes were frozen down and stored in liquid nitrogen. mAbs were purified from hybridoma supernatant by protein A affinity chromatography.

Indirect enzyme-linked immunosorbent assay (ELISA)

Microtiter plates (96-wells) were coated with recombinant protein (LcrV or F1) in phosphate buffered saline (PBS) overnight at room temperature. Plates were washed with

PBS containing 0.05% Tween-20 (PBS-T) then blocked for 90 minutes at 37°C with PBS-

T containing 5% non-fat milk (blocking buffer). Primary antibodies (mouse sera or purified mAbs) were diluted in blocking buffer and serial two-fold dilutions were performed across plates. Primary antibodies were incubated for 90 minutes at room temperature. Plates were washed with blocking buffer then incubated with horseradish peroxidase (HRP) labeled goat anti-mouse IgG antibody (SouthernBiotech, Birmingham, AL) for 60 minutes at room temperature. Isolated mAbs were also analyzed using IgG subclass specific

(IgG3, IgG1, IgG2a, IgG2b) goat anti-mouse secondary antibodies (SouthernBiotech) for further characterization. Plates were washed with PBS-T and incubated with tetramethylbenzidine (TMB) substrate (Kirkegaard & Perry Laboratories, Inc.,

Gaithersburg, MD) for 30 minutes at room temperature. An equal volume of 1M phosphoric acid (H3PO4) was used to stop the reaction, and colorimetric data was read at an optical density of 450nm (OD450).

Bacterial lysate preparation

At biosafety level 2 (BSL2), a glycerol stock of Y. pestis Harbin-35 (BEI Resources) was streaked onto a brain-heart infusion (BHI) agar plate and incubated at 28°C for 48 hours.

An individual colony was picked, inoculated into tryptic soy broth (TSB), and grown overnight at 37°C shaking in 5% CO2. Larger cultures were inoculated from the starter culture and grown for 48 hours at 37°C shaking in 5% CO2. Bacterial cells were pelleted by centrifugation and resuspended in PBS. Cells were heat-inactivated at 80°C for 2 hours. Bacterial supernatant was 0.2 μm filtered. Bacterial cell lysate and supernatant

were backplated onto BHI agar and incubated at 37°C for at least 72 hours to ensure no viable cells were present.

Additionally, bacterial lysates for Y. pestis KIM D19, Y. pestis A12 Derivative 6, Y. pseudotuberculosis IP2666, Y. enterocolitica WA, Francisella tularensis B38, F. tularensis

LVS, Bacillus anthracis Ames-35, Burkholderia pseudomallei K96243, B. pseudomallei

1026B, and B. pseudomallei Bp82 were prepared as per instructed (BEI Resources).

Bacterial lysates were heat inactivated and separated by cells and supernatant. B. pseudomallei strains K96243 and 1026B were propagated at biosafety level 3 (BSL2) and confirmed nonviable before removal to (BSL2) by a validated protocol. Y. pestis KIM D19,

Y. pestis A12 Derivative 6, Y. pseudotuberculosis IP2666, Y. enterocolitica WA,

Francisella tularensis B38, F. tularensis LVS, Bacillus anthracis Ames-35, and B. pseudomallei Bp82 lysates were propagated at BSL2 as per protocol above. Inactivated bacterial cells were resuspended in PBS to an optimal density at 600nm (OD600) of 0.5.

Recombinant LcrV and F1 cloning and expression

Genes encoding LcrV and F1 were cloned into Escherichia coli, expressed and purified.

The F1 encoding gene (caf1) and lcrV were amplified by polymerase chain reaction (PCR) from the Y. pestis Harbin-35 lysate, using primers shown in Supplemental Table 1. The caf1 gene was void of the first 63 base pairs which encodes for a cleaved signal peptide

[189]. Each gene was cloned into the pQE-30 Xa Vector (Qiagen, Hilden, Germany) by

Gibson Assembly (New England Biolabs (NEB), Ipswich, MA). Plasmids were sequence verified and transformed into E. coli M15 for protein expression. E. coli containing expression plasmids were grown at 37°C to an optimal density at OD600 of 0.6 before inducing protein expression by the addition of isopropyl ß-D-1-thiogalactopyranoside

(IPTG) at an end concentration of 1mM. Induced cultures were grown at 37°C for 12-16 hours. Bacterial cell pellets were collected by centrifugation then lysed with BugBuster

10X Protein Extraction Reagent (MilliporeSigma) and sonication. The soluble fraction for both were purified using Protino Ni-TED resin (Macherey-Nagel, Duren, Germany).

Western blot

A standard Western blot procedure was performed using semidry blotting. 6x reducing or non-reducing Laemmli loading buffer was added to bacterial lysate. The reduced sample was then boiled for 10 minutes. Samples were separated on a 10% SDS gel, and proteins were transferred to a nitrocellulose membrane (Bio-Rad Laboratories, Hercules, CA).

HRP-labeled LcrV mAbs were used to probe the membrane directly. Unlabeled F1 mAbs were used to probe the membrane, followed by an HRP-labeled goat anti-mouse Ig for detection. Signal was developed using SuperSignal™ West Femto Maximum Sensitivity

Substrate (ThermoFisher Scientific, Grand Island, NY) and imaged using a ChemiDoc

XRS imaging system (Bio-Rad Laboratories).

Lateral flow immunoassay (LFI)

Lateral flow immunoassays were initially constructed using Fusion-5 matrix membrane

(GE Healthcare, Piscataway, NJ), FF120HP nitrocellulose membrane (GE Healthcare) and C083 cellulose fiber sample pad strips (MilliporeSigma). FF120HP membranes were striped with unlabeled antibodies using the BioDot XYZ platform (BioDot, Irvine, CA).

Purified Y. pestis mAbs were striped at 1mg/mL and served as the test line. Unlabeled goat anti-mouse Ig (SouthernBiotech) were striped serving as the control line. All mAbs were conjugated to 40nm colloidal gold particles (DCN Diagnostics, Carlsbad, CA), blocked with bovine serum albumin and concentrated to an optical density of ten at 540nm.

Colloidal gold conjugated mAbs were spotted roughly 8mm from the top of the Fusion-5 matrix membrane prior to running the assay and served as the detection antibody. Initial screening was done using all possible mAb pairs for LcrV and F1. A single concentration of recombinant protein (100 ng/mL) was used to evaluate mAb pairing. 40uL of sample was loaded onto the sample pad then placed in a well containing 150uL of chase buffer only. Each prototype was run in parallel with chase buffer only, as a negative control. Test line intensity was read promptly after 20 minutes using the ESE Lateral Flow Reader

(Qiagen). Top performing pairs were then down selected using a concentration of 1 ng/mL of recombinant protein.

Top LFI prototypes were optimized for testing using human sera. Recombinant protein

(LcrV or F1) was spiked into six lots of pooled normal human sera ([NHS], Bioreclamation

IVT, Westbury NY & Innovative Research, Novi MI) and evaluated for signal intensity and non-specific background signal. LFI components optimized include conjugate release pads, nitrocellulose membranes, wicking pads, chase buffers, striping concentrations, gold conjugate diluents and sample pre-treatment steps. The final prototypes were constructed using UniSart CN140 nitrocellulose membrane (Sartorius, Germany),

CFSP203000 absorbent pad, and conjugate pad grade 8951 (Ahlstrom, Finland). F127 and 10G surfactants were added to the gold diluent for the LcrV and F1 prototypes respectively to help with the release of the conjugate from the conjugate pad. Mouse IgG was added to the human serum samples as a pretreatment step to prevent human anti- mouse antibody (HAMA) interference [190].

Antigen-capture enzyme-linked immunosorbent assay (ELISA)

The top eight performing mAbs ranked by LFI testing were screened to develop antigen- capture ELISAs. Microtiter plates were coated overnight with 1 µg/mL capture mAb. After blocking, recombinant protein (F1 or LcrV) was diluted into blocking buffer and serial two- fold dilutions were performed across plates. Detection antibody at 0.1 µg/mL was incubated for 60 minutes at room temperature. HRP labeling of mAbs was performed using EZ-Link Plus Activated Peroxidase (ThermoFisher Scientific). Plates were washed with PBS-T and incubated with TMB substrate for 30 minutes at room temperature. An equal volume of 1M H3PO4 was used to stop the reaction, and colorimetric data was read at OD450.

Checkerboard ELISAs were performed using the top 2 mAb pairs to optimize concentrations of capture and detection mAbs. Optimization was performed using two-fold serial dilutions of either the capture or detection mAbs in independent experiments. The capture mAbs was first optimized by using concentrations ranging from 0.078 – 10 µg/mL with 1 μg/mL detection mAb. Capture mAb concentrations were chosen based on signal intensity and minimal background. The selected capture mAb concentrations were used to optimize the detection mAbs from a range of 0.0078 – 1 µg/mL. The optimized ELISA conditions (shown in Table 3) were selected based on the lowest LOD defined as the concentration at two-fold background signal.

Surface plasmon resonance (SPR)

SPR experiments were conducted on the Biacore X100 instrument using the His Capture format (GE Healthcare). A CM5 chip surface was prepared using the His Capture Kit as per manufacturer’s recommendation. For each cycle, his-tagged recombinant protein

(LcrV or F1) diluted into HBS-EP+ buffer (GE Healthcare) was immobilized onto the anti-

His capture surface. LcrV was immobilized at a concentration of 5 µg/mL and F1 was immobilized at a concentration of 1 µg/mL. Antigen capture was performed at 5 µL/second for 60 seconds followed by 120 second stabilization. These conditions were established for optimal kinetic analyses of each mAb. Full kinetic analyses were performed by injecting each purified mAb for 7 cycles at a concentrations range of 0.5 – 50 µg/mL over the LcrV or F1 surface for 120 seconds followed by a dissociation period of 240 seconds at 30

µL/second. The anti-His capture surface was regenerated between each cycle using

10mM glycine pH1.5 (GE Healthcare) for 30 seconds at 10 µL/second. Binding kinetics and affinity were evaluated using a bivalent model on the Biacore X100 Evaluation

Software (GE Healthcare).

3.4 Results

Hybridoma production and mAb reactivity

In order to develop antigen-capture immunoassays for the detection of LcrV and F1, a large panel of mAbs were isolated and evaluated to determine the best conditions for optimal specificity and analytical sensitivity. Titermax Gold Liquid and Freund’s adjuvants were used for the immunization strategy to drive the immune response resulting in IgG antibodies [191, 192]. Twenty-two total hybridoma cell lines that produce mAbs against Y. pestis LcrV or F1 were isolated (Table 1). mAb reactivity was confirmed by indirect ELISA to recombinant F1 or LcrV proteins. Subclass specific secondary antibodies were used to characterize mAbs by class, and all antibodies were determined to be members of the

IgG1, IgG2b, or IgG2a subclass (Table 1). These antibody subclasses are preferred over the IgG3 subclass in the development of antigen-capture immunoassays as the IgG3 subclass can self-associate resulting in increased background signal and potential false positive reactions [193].

Western blot analysis probing Y. pestis Harbin-35 lysate determined mAb reactivity against native protein. High density bands were detected at the correct molecular weight of the monomeric LcrV protein (Figure 1A). Reactivity is observed at higher molecular weights, indicating that both monomeric and multimeric forms are present in bacterial culture. mAbs 4E8 and 5D3 had limited reactivity to the non-reduced native protein as well as the multimeric forms suggesting reactivity to linear epitopes more available in reducing conditions (Figure 1B). mAbs isolated against F1 showed differing levels of reactivity to the monomeric F1 antigen in the reduced Western blot (Figure 2A). The non-reduced

Western blot analysis showed reactivity of the F1 mAbs against the assembled F1 capsule which resulted in an expected laddering pattern (Figure 2B) [194]. Reducing conditions

disrupt protein-protein interactions, disassembling the F1 capsule. mAb 3A2 was isolated from a mouse immunized with the F1-V fusion protein and showed preferential reactivity to the monomeric structure and had low reactivity to the assembled capsule. Inversely, mAbs 9B7 and 12F5 showed limited reactivity to the reduced bacterial lysate and were more reactive against higher molecular weights present in the non-reduced lysate (Figure

2B). The epitopes of mAbs 9B7 and 12F5 may only be available in the F1 capsule made of 3 or more subunits.

Binding affinity and kinetics by surface plasmon resonance (SPR)

Characterization of the mAbs in each library included analysis of binding affinity and kinetics by SPR. Experiments were performed in triplicate and evaluated using a bivalent binding model. The association rate (ka), dissociation rate (kd), and equilibrium dissociation constant (KD; KD = kd/ka) are reported in Table 2. LcrV mAbs displayed a narrow range of equilibrium dissociation constants (0.3 – 4.5 nM). F1 mAbs had a larger range of 0.002 –

250 nM. Interestingly, mAbs 2B2 and 3A2 were isolated from mice immunized with the

F1-V fusion protein. 2B2 displayed a high affinity to recombinant LcrV (KD = 2.6 nM); however, 3A2 displayed the poorest affinity to recombinant F1 (KD = 250 nM).

Lateral flow immunoassay (LFI) development and optimization

The constructed library of mAbs were evaluated as capture and detection components for the development of LFI prototypes. mAb pairs were quantitatively ranked based on the signal intensity at the test line when running a 100 ng/mL of recombinant protein sample

(LcrV or F1) in chase buffer minus nonspecific signal when run with chase buffer only

(Supplemental Table 2 and 3). Though LFIs are generally evaluated by visual detection, the use of a lateral flow reader provides a standardized measure to minimize human

variability and error. The top pairs were then down selected for their performance with 1 ng/mL recombinant protein and no nonspecific binding (Table 3).

Testing complex matrices such as human sera often lead to assay signal loss and nonspecific binding described as matrix effects [195]. In order to account for interference of the matrix on downstream applications, the top LFI prototypes were further optimized for assaying human serum. An LOD was defined as the minimum concentration at which a positive signal is observed in spiked pooled normal human sera (NHS). A positive signal was defined as an intensity reading greater than 20 mm*mV using the Qiagen ESE Lateral

Flow Reader. Visual LOD is estimated to have an intensity between 15-30 mm*mV among various LFIs developed in our laboratory. Due to sample variability, difference in assay performance was observed between each lot of pool human serum. Six different pools of

NHS were used to optimize each LFI prototype for nonspecific background signal. Then the pools were spiked with recombinant protein and used to determine the LOD of the LFI prototypes to account for possible matrix effects on signal intensity. The top performing pair (capture/detection) against native LcrV was 8F10/2B2; however, due to consistent nonspecific reactivity when assaying NHS, the next top performing pair (8F10/6F10) was further evaluated (Supplemental Figure 1). The top pair for F1 detection was 11C7/3F2.

The LOD of LcrV was 2ng/mL and the LOD of F1 was 1ng/mL in lot NHS207 spiked with recombinant protein (Figure 3). Despite high analytical sensitivity to each antigen, differences of assay signal were observed between the six pools of NHS (Supplemental

Figures 2 & 3). The aggregate LOD was determined as the lowest concentration which consistently resulted in positive LFIs among the pools of NHS. The LcrV and F1 prototypes have LODs of about 1 ng/mL. Detection of both antigens in pooled NHS #28614 appeared to have an increased LOD suggesting effects due to the clinical matrix.

Generation of a multiplexed LcrV/F1 assay

In order to detect potentially all pathogenic isolates of Y. pestis, a multiplexed LFI was developed. The multiplexed prototype was constructed with two test lines, one specific for

LcrV and one for F1 using the mAb pairs described above. The specificity of the dual LFI prototype was tested using bacterial lysates from Select Agent exempt strains of Y. pestis, clinically relevant near neighbors, and other Tier 1 bacterial Select Agents (Figure 4). Cell lysates were adjusted to an OD600 of 0.5 to normalize bacterial counts of both live and dead cells. Y. pestis Harbin-35 and KIM19 strains were positive for LcrV and F1. Y. pestis

A12 Derivative 6, an LcrV- strain, was positive only for F1. Y. pseudotuberculosis IP2666 lysate was positive for LcrV, but Y. enterocolitica was negative for LcrV. Additionally, all other Tier 1 bacterial Select Agents were negative for LcrV and F1.

Antigen-capture enzyme-linked immunosorbent assay (ELISA) development and optimization

The top eight mAbs for each antigen ranked by LFI were analyzed to develop a sensitive quantitative antigen-capture ELISA for the detection of Y. pestis. ELISAs were initially evaluated using 1 mg/mL capture mAb and 0.1mg/mL detection mAb to rank pairs

(Supplemental Figure 4). The two mAb pairs with the highest sensitivity for each antigen were optimized for capture and detection conditions by checkerboard ELISAs (Table 4).

LcrV was detected as low as 74 pg/mL by 6E5/8F10 and F1 was detected down to 61 pg/mL by 11B8/3F2. The LODs for each assay was determined using recombinant protein spiked into buffer and reported in Table 4. Though these assays will need to be validated using specimen matrices (blood, sputum, aspirates), the LODs of the developed ELISAs in buffer are 10-fold greater in analytical sensitivity compared to a commercially available

assay and comprised of two mAb pairs ensuring consistency compared assays using polyclonal antibodies [162, 196]. Furthermore, the described ELISAs are well within the clinical concentrations observed for F1 and can be powerful tools to investigate the presence and concentration of both LcrV and F1 in plague patient samples [197].

3.5 Discussion

The quick progression of plague infections warrants the need for sensitive, specific, and rapid diagnostic tools. Though most infections lead to bubonic plague, the more severe forms of the infection present with nonspecific clinical presentations that can be challenging to distinguish from many other diseases. Commercially available LFIs have been developed for the detection of the F1 antigen [162]. F1 encapsulates the bacteria and is shed in copious amounts; however, the growing number of F1- isolates makes the biomarker inadequate for diagnosing all plague infections [170]. To combat the potential of widespread infections, an RDT capable of detecting all pathogenic strains of Y. pestis is imperative. Through the isolation of a library of mAbs reactive to F1, as well as LcrV, we have developed assays for the detection of an expanded array of Y. pestis isolates which may prove to be useful on multiple fronts.

The success of Y. pestis as a pathogen may be attributed to its genetic diversity.

Widespread pandemics have been traced to three global biovars of Y. pestis (antiqua, medievalis, and orientalis), however, the lcrV genes among these biovars are conserved

[198]. Polymorphisms in lcrV have been observed in the biovar microtus [199]. These polymorphisms resulted in varied abilities to form multimers and result in avirulence in humans [198]. In addition to polymorphisms in lcrV, various isoforms of the F1 antigen exist due to point mutations [200, 201]. The NT1 isoform (Ala48 Phe117) is most common and is expressed by the three global strains responsible for human infections [200].

Moreover, the adaptive immune response elicited by the NT1 isoform are cross-reactive to the NT2 (Ser48 Phe117) and NT3 (Ala48 Val117) isoforms [202]. The Harbin-35 and KIM

D19 are strains included within biovar medievalis and maintain the three plasmids associated with virulence (pCD1, pPCP1, pMT1), but are attenuated due to the deletion

of the pgm locus, a segment of the chromosome that includes a pathogenicity island [203].

The pgm locus encodes for various iron-regulated proteins necessary for bubonic and pneumonic plague infections [204]. Unlike most laboratory strains Harbin-35 and KIM D19 maintain the pCD1 plasmid and LcrV expression. The A12 D6 strain is included within the biovar orientalis and is lacking the pCD1 plasmid. mAbs isolated in this study show reactivity to Y. pestis Harbin-35, KIM D19, and A12 D6 native proteins which suggest mAb reactivity is against most if not all human pathogenic strains of Y. pestis (Figures 1-2 & 4).

However, further characterization of the mAbs isolated should be performed to confirm cross-reactivity among all pathogenic Y. pestis strains.

Binding affinity and kinetics derived from SPR demonstrate the mAbs produced in this study possess high affinity to their targets (Table 3). In general, higher affinity mAbs are preferred in immunoassays to achieve the greatest analytical sensitivity which should result in improved clinical sensitivity; however, the mAb pairs which performed well in LFI and ELISA formats did not necessarily have the highest affinity or superior kinetics. Initial screening of LcrV mAbs by ELISA indicated that the pairing of high affinity mAbs 8F7 and

8F10 resulted in LODs 10 to 20-fold less sensitive than 8F10 and either 6E5 or 6F10, mAbs with lower degrees of affinity (Table 2; Supplemental Figure 4). Likewise, the mAbs used in the optimized F1 ELISAs (10D9, 11B8, and 11C7) were ranked among the middle for binding affinity (KD). Additionally, mAb 12B6 had binding affinity over 2 logs greater (KD

= 0.002 nM) than the rest but did not perform well in the antigen-capture format. Overall, the mAbs used to develop the sandwich assays all displayed dissociation constants less than 10 nM. These results exemplify that in addition to having high affinity, mAbs used in antigen-capture immunoassays require pairing synergy.

Interestingly, the top performing mAb pairs in the LFI format were not the same as the

ELISA. Though both LFIs and ELISAs are antigen-capture immunoassays, there are stark differences in the assay formats. Notably, ELISAs reach binding equilibrium with long incubation periods, minimize nonspecific binding with several wash steps, and are more sensitive due to enzymatic signal amplification. However, the ELISA format is less accessible in low-technology settings such as in the field or in developing countries due to laboratory equipment requirements and storage of temperature-sensitive reagents. In contrast, LFIs utilize capillary flow to apply reagents systematically without intermediate washing steps, are self-contained within a single dipstick, and produce results in less than

20 minutes by the colorimetric sensing of gold-nanoparticle aggregates, optimal for visual detection by the human eye.

The immunoassay prototypes developed in this study had great analytical sensitivity.

Levels of F1 in patient serum can range from 4 – 50,000 ng/mL [197]. Concentrations of soluble LcrV in human samples have yet to be determined, but a mouse model of infection indicates serum concentrations of LcrV are between 6 – 26.5 ng/mL 48 hours post- inhalational exposure [183]. The LcrV and F1 immunoassays developed in this study have

LODs well within the clinically relevant reported ranges. The ELISAs developed in this study would be useful in quantifying LcrV and F1 in plague patient samples to further validate each diagnostic target. Additionally, the ELISA format may also be important in outbreak settings to allow for high throughput screening of patient samples.

In each of the three forms of plague, Y. pestis can quickly invade the bloodstream and be detected within days of exposure. This would make serum an ideal matrix to assay for bubonic, pneumonic, and septicemic plague, but a caveat of using serum as a sample is

that matrix effects, or interference at the test line is possible. Matrix effects were evident in testing both the LcrV and F1 LFIs; however, the LODs remained at the lower end of the clinical range. The LOD results for both the LcrV and F1 prototypes were 1 ng/mL. This is an improvement compared to commercially available LFIs detecting for F1 in human serum (3 - 4 ng/mL) [78, 162]. Additionally, the optimized LFI prototypes were able to run up to 50 μL of undiluted human sera with a minimal degree of pre-treatment. The tested assay protocol includes a sample preparation step in which mouse IgG was added to prevent HAMA interference. However, mouse IgG could be integrated into the sample pad upon prior to finalization of the LFI. The ability to test undiluted sera minimizes sample handling procedures and improves assay sensitivity, key aspects for successful point-of- care assays.

Plague remains a modern threat to public health, and LFIs are ideal tools for detecting and limiting the spread of infections. In addition to the risk of naturally occurring plague,

Y. pestis has been used as a biological weapon. The use of Y. pestis in medieval siege warfare has been well documented, and in modern times, plague-infected fleas were disbursed by the Japanese army in China during World War II [87]. Several countries, including the United States of America and the former Soviet Union, have investigated the utility of Y. pestis as a bioweapon [88]. Further investigation of Y. pestis as a biological weapon is no longer permit under the treaty signed at the Biological Weapons Convention in 1972. Nonetheless, countermeasures against Y. pestis are warranted in defense of nefarious actions. The dissemination of an F1- strain may occur in the event that the bacterium is used as an agent of bioterrorism as the F1 antigen is heavily regarded as a diagnostic markers and vaccine candidate [205-210]. The multiplexing of assays detecting for LcrV and F1 increases the diagnostic ability of a Y. pestis RDT, as it may be capable

of detecting all pathogenic Y. pestis strains including those found to be F1 deficient. The dual assay shows high specificity to Y. pestis without cross-reacting with other Tier 1

Select Agents with similar symptoms. More specificity testing needs to be performed using these prototypes with an increased panel of microbes known to present similar symptoms.

The prompt and proper detection of all pathogenic Y. pestis is critical for minimizing casualties during a potential bioterrorism act or naturally occurring outbreak. Further evaluation on clinical samples collected from plague patients is needed to fully validate this multiplexed LFI.

While the immunoassay prototypes developed in this study were designed with patient samples in mind, a secondary use would be to evaluate animal populations and vectors for the presence of Y. pestis. As a zoonotic disease, proper plague surveillance requires the monitoring of natural animal reservoirs and associated vectors. Current methods of surveying wild populations include serological testing of sentinel animals, such as coyotes, which prey on smaller mammals [211]. Though coyotes do not present with symptoms, they do elicit an immune response to Y. pestis antigens. The downside of serological surveillance is the persistence of antibodies long after exposure, meaning that a positive response may not be indicative of current active infections. Though expression of LcrV and F1 are regulated by temperature, leaky expression of LcrV at 26°C has been observed

[69]. This leaky expression may allow for detection of Y. pestis in vectors such as fleas.

High-throughput screening of small mammals and vectors could be conducted using an

LFI in the field to gain more data regarding the prevalence of Y. pestis in these reservoir populations.

In addition to use in a diagnostic assay, exogenous antibodies have shown to be effective in protecting from and treating plague infections when administered pre- and post- exposure. In a mouse model of pneumonic plague, F1 specific IgG mAbs were able to confer protection when administered prophylactically [212]. Additionally, three human mAbs (one against F1, two against LcrV) isolated by naïve human phage displayed Fab libraries demonstrate some protection for bubonic plague [213]. LcrV and F1 mAb cocktails do have synergy when administered together [214]. LcrV subunits form pentamers at the tip of the T3SS at the cell surface [178, 215]. LcrV in this pentametric structure is associated with immunosuppression properties and have shown to elicit a more protective response in vaccine studies [179, 216]. Several of the isolated LcrV mAbs show reactivity to high molecular weight bands by Western blot analysis (Figure 1). This reactivity may be due to multimerization of LcrV suggesting some mAbs may bind and potentially inhibit LcrV functions in vivo. Testing the therapeutic potential of this large panel of Y. pestis mAbs in an animal model of infection may results in the development of an additional treatment option for plague patients.

List of abbreviations mAbs – monoclonal antibodies

LOD – limit of detection

RDT - rapid diagnostic test

LcrV – low-calcium response V

F1 – fraction 1 capsular antigen

NHS – normal human serum

LFI – later flow immunoassay

ELISA – enzyme-linked immunosorbent assay

BSL2 – biosafety level 2

BSL3 – biosafety level 3

Declarations

Ethics approval and consent to participate

The use of Normal Human Serum has been reviewed by the Institutional Review Board at the University of Nevada, Reno (OHRP #IRB00000215). Normal Human Serum acquired from a commercial source has been classified as exempt human subject research

(exemption 4) as i) no specimens will be collected specifically for this study and ii) there are no subject identifiers. As a consequence, the use of clinical samples in this project does not meet the criteria of human subject research as per 45 CFR 46 of the HHS regulations.

The use of laboratory animals in this study was approved by the University of Nevada,

Reno Institutional Animal Care and Use Committee (protocol number 00024). All work with animals at the University of Nevada, Reno was performed in conjunction with the Office

of Lab Animal Medicine, which adheres to the National Institutes of Health Office of

Laboratory Animal Welfare (OLAW) policies and laws (assurance number A3500-01).

Consent to publish

Not Applicable

Availability of data and materials

All datas generated for this study are included in the manuscript and/or the Supplementary

Files.

Competing Interests

The goal is to transition these prototypes into an FDA approved diagnostic for plague through the MCDC contract # MCDC OTA W15QKN-16-9-1002.

Funding

Funding from the Naval Research Laboratory contract ND0173-16-C-2003 supported the generation of mAbs and ELISA development. Funds from a Defense Threat Reduction

Agency (DTRA) contract HDTRA114-AMD2-CBA-01-1-0107 expanded the library of mAbs and allowed for the development and optimization of LFIs.

Authors Contribution

DH, BW, CL, SGP, DER, MAG, PNT, KJP, and DPA designed the experiments and wrote the manuscript. DH, BW, CL, SGP, DER, HLD, HRG, EEH, MM, CJC, CC, JAU, GFC, TN conducted the experiments. All authors read the manuscript.

Acknowledgements

We would like to acknowledge the guidance provided through the DCN Dx Custom Lateral

Flow training for suggestions for optimizing LFI’s.

Figure 1. Western blot analysis of anti-LcrV monoclonal antibodies (mAbs) against Yersinia pestis Harbin-35 lysate. mAb (1 µg/mL) reactivity was assessed against (A) reduced and (B) non-reduced bacterial lysate.

Figure 2. Western blot analysis of anti-F1 monoclonal antibodies (mAbs) against Yersinia pestis Harbin-35 lysate. mAb (1 µg/mL) reactivity was assessed against (A) reduced and (B) non-reduced bacterial lysate.

Figure 3. Sensitivity of Yersinia pestis lateral flow immunoassays (LFI) using recombinant LcrV and F1. LFI prototypes were tested with recombinant (A) LcrV and (B) F1 spiked into pools of normal human serum. Assay signal was evaluated and quantitated by optical density using a Qiagen ESE reader. Intensity ≥ 20 mm*mV scores as positive.

# Bacteria 1 Yersinia pestis Harbin-35 2 Yersinia pestis KIM19 3 Yersinia pestis A12 Derivative 6 4 Yersinia pseudotuberculosis IP2666 5 Yersinia enterocolitica WA 6 Francisella tularensis B38 7 Francisella tularensis LVS 8 Bacillus anthracis Ames-35 9 Burkholderia pseudomallei K96243 10 Burkholderia pseudomallei 1026B 11 Burkholderia pseudomallei Bp82 12 PBS control

Figure 4. Specificity testing of dual Yersinia pestis lateral flow immunoassay (LFI) against clinically relevant bacterial panel. The dual LFI prototype containing test lines specific for LcrV (8F10/6F10) and F1 (11C7/3F2) was tested against a panel of bacterial lysates; lysates were normalized to an OD600 = 0.5 in PBS.

100

Table 1. Monoclonal antibody (mAb) library against Y. pestis LcrV and F1 antigens

Antigen mAb Immunization Subclass LcrV 2B2 F1-V IgG2a 4E8 LcrV IgG2a 5D3 LcrV IgG1 6E5 LcrV IgG1 6F10 LcrV IgG1 8F3 LcrV IgG1 8F7 LcrV IgG2a 8F10 LcrV IgG1 F1 3A2 F1-V IgG2a 3F2 F1 IgG1 4E5 F1 IgG2a 4F12 F1 IgG1 5E10 F1 IgG2a 9B7 F1 IgG1 10D9 F1 IgG1 10E3 F1 IgG1 11B8 F1 IgG2a 11C7 F1 IgG1 12B6 F1 IgG2a 12E10 F1 IgG2a 12F5 F1 IgG2b 15C4 F1 IgG2a

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Table 2. Affinity and kinetics analysis of Y. pestis mAbs by surface plasmon resonance

3 -3 ka x 10 kd x 10 KD Antigen mAb (M-1s-1) (s-1) (nM) LcrV 2B2 52 0.14 2.6 4E8 210 0.78 3.7 5D3 65 0.22 3.4 6E5 120 0.54 4.5 6F10 140 0.58 4.1 8F3 93 0.17 1.9 8F7 100 0.18 1.8 8F10 250 0.074 0.3 F1 3A2 5.6 1.4 250 3F2 65 0.48 7.4 4E5 250 0.39 1.6 4F12 91 1.8 19 5E10 230 0.12 0.5 9B7 42 0.45 11 10D9 36 0.048 1.3 10E3 100 0.054 0.5 11B8 170 0.17 1.0 11C7 180 0.91 5.2 12B6 110 0.00026 0.002 12E10 83 0.23 2.8 12F5 170 13 79 15C4 210 0.13 0.6

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Table 3. Assay sensitivity of the top 4 mAb pairs (LcrV or F1) by lateral flow immunoassay

OD (mm*mV) Capture Detection OD (mm*mV) Antigen Chase Buffer mAb mAb 1ng/mL antigen only LcrV 8F10 6F10 56 0 8F10 2B2 53 0 8F10 6E5 51 0 8F7 6F10 26 0

F1 11C7 3F2 115 0 11C7 15C4 93 0 4E5 3F2 89 0 10D9 3F2 57 0

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Table 4. Limit of detection of enzyme-linked immunosorbent assays using recombinant LcrV and F1 antigens in buffer

[Capture [Detection Capture Detection LOD Antigen mAb] mAb] mAb mAb (pg/mL) (µg/mL) (µg/mL) LcrV 6E5 2.5 8F10 0.13 74 ± 7.9

6F10 2.5 8F10 0.063 75 ± 4.0

F1 10D9 2.5 11C7 0.13 100 ± 41

11B8 1.3 11C7 0.13 61 ± 2.0

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Supplemental Figure 1. LFI prototypes were tested with (A) PBS or (B) Y. pestis Harbin- 35 lysate for the detection of LcrV.

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(A) 207 (B) 208

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + - - - - + + + + + + + - + - - -

678 338 262 134 89 50 29 0 26 0 0 0 740 437 265 162 88 50 33 26 0 0 0 0

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + + + + - + + + + + + + + + - - -

801 528 243 252 144 76 50 43 42 42 26 0 590 428 211 190 77 42 42 27 25 0 0 0

(E) 24458 (F) 28614

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + + - - - + + + + + + ------

632 517 327 190 99 72 26 27 29 0 0 0 453 178 145 81 70 33 0 0 0 0 0 0

Supplemental Figure 2. LFI prototypes (8F10-capture/6F10-detection) were tested with recombinant LcrV in six pools of normal human serum. Each panel represent a different lot of pool serum from (A-C) Bioreclamation IVT or (D-F) Innovative Resources. Lot numbers are provided for each panel. Assay signal was evaluated and quantitated by optical density using a Qiagen ESE reader. Intensity ≥ 20 mm*mV scores as positive.

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(A) 207 (B) 208

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + + - - - + + + + + + + + + - - -

977 803 577 337 184 111 55 33 24 0 0 0 971 739 505 359 209 99 71 42 20 0 0 0

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + - - - - + + + + + + + + + - - -

951 651 413 279 184 129 42 35 0 0 0 0 778 514 433 329 176 80 38 22 25 0 0 0

(E) 24458 (F) 28614

256 128 64 32 16 8 4 2 1 0.5 0.3 0 256 128 64 32 16 8 4 2 1 0.5 0.3 0

+ + + + + + + + - - - - + + + + + + + - - - - -

894 634 366 314 187 84 51 24 0 0 0 0 865 436 361 290 101 58 24 0 0 0 0 0

Supplemental Figure 3. F1 prototypes (11C7-capture/3F2-detection) were tested with recombinant F1 in six pools of normal human serum. Each panel represent a different lot of pool serum from (A-C) Bioreclamation IVT or (D-F) Innovative Resources. Lot numbers are provided for each panel. Assay signal was evaluated and quantitated by optical density using a Qiagen ESE reader. Intensity ≥ 20 mm*mV scores as positive.

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(A)

Detection (HRP conjugated) mAb 2B2 4E8 5D3 6E5 6F10 8F3 8F7 8F10 2B2 4.2 10 27 5.9 5.8 9.3 ND 40

4E8 10 16 48 23 17 2.2 2.5 1.8 5D3 13 23 110 24 19 3.5 2.5 1.9 6E5 24 28 37 34 22 3.1 0.8 0.6 6F10 7.6 16 40 11 11 2.1 0.8 0.6

Capture mAb Capture 8F3 0.8 2.1 3.9 1.1 0.9 20 12 6.3 8F7 0.8 2.3 9.6 32 52 130 32 7.7 8F10 1.1 2.7 5.6 4.7 2.3 51 12 14

(B)

Detection (HRP conjugated) mAb 3F2 4E5 4F12 5E10 10D9 11B8 11C7 15C4 3F2 2.9 1.1 6.0 1.3 2.8 1.5 0.7 1.1 4E5 2.8 2.3 2.5 7.9 1.9 16 2.8 1.9 4F12 10 1.5 5.5 2.2 1.9 3.4 0.8 1.6 5E10 7.8 5.0 3.1 2.9 3.4 4.7 2.7 2.6 10D9 2.5 1.2 2.2 3.2 4.8 1.7 0.6 1.3

Capture mAb Capture 11B8 2.4 4.0 2.1 3.0 3.2 1.6 0.6 2.1 11C7 15 2.3 2.7 6.0 2.8 1.6 1.5 1.9 15C4 4.3 4.9 3.1 5.5 2.6 2.5 0.9 3.6

Supplemental Figure 4. Antigen-capture ELISAs were performed to determine the limits of detection (LOD) for recombinant (A) LcrV and (B) F1. LOD was calculated as the concentration of recombinant protein in ng/ml at five times background. The values represent means of two independent ELISAs (each performed in biological triplicates).

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Supplemental Table 1. Primers for cloning LcrV and F1 genes from Y. pestis Harbin-35 into the pQe-30 Xa vector.

Gene Primer Tm (°C) lcrv F 5'-GGTATCGAGGGAAGGATGATTAGAGCCTACGAACA-3' 66 R 5'-GTCCAAGCTCAGCTATCATTTACCAGACGTGTCAT-3' 64 caf1 F 5'-GGTATCGAGGGAAGGGCAGATTTAACTGCAAGCAC-3' 67 R 5'-GTCCAAGCTCAGCTATTATTGGTTAGATACGGTTAC-3' 63

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Supplemental Table 2. Preliminary assay sensitivities of top mAb pairs by LFI for LcrV at 100ng/mL

Capture mAb Detection mAb 100 ng/mL LcrV Chase only Difference 8F10 6E5 253 94 159 8F7 6E5 315 131 184 8F10 2B2 234 106 128 4E8 8F10 452 238 214 8F10 6F10 297 164 133 6E5 8F10 500 277 223 8F7 2B2 244 137 107 2B2 8F10 488 278 210 8F7 4E8 330 223 107 8F7 6F10 260 178 82

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Supplemental Table 3. Preliminary assay sensitivities of top mAb pairs by LFI for LcrV at 100ng/mL

Capture mAb Detection mAb 100 ng/mL F1 Chase only Difference 11C7 4E5 834 71 763 5E10 11C7 725 0 725 10D9 3F2 709 0 709 11C7 5E10 665 0 665 3F2 4E5 616 0 616 11C7 15C4 599 0 599 11C7 11B8 599 0 599 11C7 11C7 591 0 591 11C7 3F2 587 0 587 4E5 3F2 540 0 540 11C7 4F12 495 0 495 15C4 3F2 539 53 487 11B8 4E5 508 64 444 9B7 3F2 439 0 439 5E10 3F2 434 0 434 11C7 10D9 434 0 434 11C7 9B7 427 0 427 3F2 15C4 423 0 423 5E10 11B8 542 124 418 11B8 10D9 416 0 416

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Chapter 4. Detection and Quantitation of Capsular Polysaccharide (CPS) in Clinical

Melioidosis Samples and Laboratory-grown Burkholderia pseudomallei Isolates

Derrick Hau1, Heather R. Green1, Emily E. Hannah1, Haley L. DeMers1, Kathryn J.

Pflughoeft1, Peter N. Thorkildson1, Sujata G. Pandit1, Marcellene A. Gates-Hollingsworth1,

Mark Mayo2, Bart Currie2, and David P. AuCoin1*

1 Department of Microbiology and Immunology, University of Nevada Reno School of

Medicine Reno, Nevada, United States of America

2 Royal Darwin Hospital Campus, Menzies School of Health Research, Darwin, Northern

Territory, Australia

3 InBios International, Inc., Seattle, Washington, United States of America

*Corresponding author

Email: [email protected]

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4.1 Abstract

Melioidosis is a multifaceted infectious disease caused by the bacterium Burkholderia pseudomallei. Common in Southeast Asia and northern Australia, the soil-dwelling bacteria is a threat to public health due to its high mortality rates and intrinsic resistance to many first-line antibiotics. The administration of effective antibiotics is dependent on a prompt diagnosis and is crucial for patient survival. The gold standard for diagnosing melioidosis is bacterial culturing; however, this standard is inadequate due to the length of time to diagnosis (up to seven days) and low sensitivity (60%). The Active Melioidosis

Detect plus (AMD+; InBios International Inc, Seatte, WA) lateral flow immunoassay (LFI) is a point-of-care test for the detection of B. pseudomallei capsular polysaccharide

(CPS). Identified as a shed biomarker of infection, CPS is filtered through the kidneys and excreted in patient urine. Recent studies have indicated urine to be a better diagnostic matrix than serum. Melioidosis urine samples collected at the Menzies School of Health Research were analyzed for the presence and quantity of CPS. Of twenty samples tested, CPS was detected in fifteen samples (75%) by AMD+ LFI. Detection by enzyme-linked immunosorbent assay (ELISA) determined low concentrations of CPS in samples negative by AMD+ LFI. The AMD+ LFI is accessible in low-technology settings and can enhance the diagnostic capacity in rural cities and medical facilities around the world. Furthermore, CPS concentrations were determined in B. pseudomallei K96243,

1026b, and Bp82 cultures. Results indicate a majority of CPS produced is shed in cultures grown in nutrient rich broth and within detectable levels by the AMD+ LFI.

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4.2 Background

Melioidosis, caused by the bacterium Burkholderia pseudomallei, is a neglected disease estimated to infect 165,000 individuals annually with a case fatality rate (CFR) of 53%

[217]. B. pseudomallei is a saprophyte commonly found in Southeast Asia and northern

Australia. Categorized as a Tier 1 Select Agent by the United States federal government,

B. pseudomallei is a threat to public health due to high mortality rates and the potential use as a bioterrorism agent. The bacterium is considered an opportunistic pathogen due to high association with underlying medical conditions. Diabetes, excessive alcohol usage, chronic renal failure and lung disease remain high co-morbidities with melioidosis infections, however, infections of healthy individuals are observed [13]. The bacterium is intrinsically resistant to many first line antimicrobial agents including penicillins and cephalosporins [218, 219]. Thailand and Laos report CFRs exceeding 70% when infections are left untreated; however, with the proper administration of meropenem or ceftazidime the CFRs decrease to 40% [114, 115]. Countries with exceptional surveillance programs, such as Australia and Singapore have further reduced CFRs to

20% [112, 113, 220]. The actual global burden of melioidosis is predicted to be underrepresented due to the lack of surveillance. According to models by

Limmathurotsakul et. al, South Asia, including India and Indonesia, is predicted to bear

44% of all worldwide infections [217].

Commonly referred to as the great imitator, melioidosis presents with nonspecific clinical symptoms often resulting in misdiagnoses [116]. Clinicians utilize patient history, occupation, and disease severity as important factors for determining a diagnosis. This information can often be used to infer the route of infection and time of exposure [14,

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221]. Early administration of effective antibiotics is vital for melioidosis treatment. The gold standard for diagnosis of melioidosis is bacterial culture, a process which can take up to seven days [117]. Though this technique has high specificity, the low bioburden in clinical specimens results in only 60% sensitivity [118]. Secondary methods of diagnosis include mass spectrometry (MS), polymerase chain reaction (PCR) based assays, and immunoassays [222-227]. These methods are often costly and require lab personnel and equipment not readily available in endemic regions.

The capsular polysaccharide (CPS) of B. pseudomallei has been identified as a shed biomarker of infection in vivo [123]. Purified CPS injected into mice is quickly filtered out through the kidney and excreted in urine [129]. Urine is the preferred clinical matrix for the detection of CPS because it accumulates higher concentrations of CPS compared to serum; however, there are vast differences in the concentration of CPS accumulated in urine during an infection [Laos CPS & MP papers]. The InBios Active Melioidosis

DetectTM (AMD) Lateral Flow Immunoassay (InBios International Inc., Seattle, WA) detects CPS with a similar sensitivity and specificity to bacterial culture [228], however with a 15-minute assay time, the time to diagnosis is a vast improvement over bacterial culture. The need for a quick and accurate diagnostic tool is warranted for melioidosis.

The development of point-of-care tests such as lateral flow immunoassays (LFI) show promise in shortening the time for a diagnosis [229-232]. LFIs are membrane-based assays ideal for diagnosing infections because of their low cost, ease of use, and containment as a single dipstick. LFIs for other pathogens such as Streptococcus pneumoniae, Legionella pneumophila, and Yersinia pestis have been previously described [162, 233].

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The shortened time for a diagnosis by LFI can drastically improve melioidosis patient outcome [234]. However, factors such as sample collection times and methods, and infection foci can influence the amount of CPS in urine [129]. It is not fully understood how such factors would affect detection. To further assess CPS as a key biomarker for melioidosis infection, this study examines the abundance of CPS in B. pseudomallei strains grown in vitro and in clinical urine samples. B. pseudomallei strains K96243,

1026b, and Bp82 were grown and analyzed for CPS by enzyme-linked immunosorbent assay (ELISA). Clinical melioidosis samples collected at Menzies School of Health

Research were evaluated by ELISA and the InBios Active Melioidosis Detect PlusTM

(AMD+) LFI. The filter sterilization protocol for downgrading clinical samples from biosafety level 3 (BSL3) to 2 (BSL2) was evaluated for the impact on the AMD+ LFI result.

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4.3 Methods

Ethics statement

Studies on human subjects were approved by the University of Nevada, Reno Institutional

Review Board (IRB).

In vitro growth of Burkholderia pseudomallei

Fully virulent strains of Burkholderia pseudomallei were grown in a biosafety level 3

(BSL3) laboratory. Glycerol stocks of B. pseudomallei K96243 and 1026b (Biodefense and Emerging Infections Research Resources Repository [BEI Resources], Manassas,

VA) were streaked onto brain-heart infusion (BHI) agar plates and incubated at 37°C overnight. An individual colony was inoculated into Luria-Bertani (LB) broth and grown at

37°C shaking at 225 RPM for 16 - 18 hours. 10mL LB cultures in 50 mL bio-reaction tubes

(Celltreat, Pepperell, MA) were inoculated using the starter at a 1:1,000 dilution, then grown at 37°C shaking. Time points 0, 2, 4, 8 and 24 were chosen based on a B. pseudomallei Bp82 growth curve. Individual culture tubes were started at the same time and moved to 4°C after time elapsed. Bacterial cells were heat-inactivated at 80°C for 2 hours and were verified inactivated by back culture. Samples were transferred to BSL2 for further analysis. Burkholderia pseudomallei Bp82 was grown at biosafety level 2 (BSL2) on LB agar and LB broth supplemented with adenine and thiamine [235].

Cell counts were obtained by reading the optical density at 600nm (OD600). The bacterial cultures were fractionated by centrifugation at 8,000xg for 10 minutes. Supernatants were carefully removed, and cell pellets were resuspended in an equivalent volume of

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phosphate-buffered saline (PBS). Samples were treated with 100 μg/mL proteinase K for

1 hour at 60°C, followed by proteinase K inactivation by heating to 80°C for 20 minutes.

Filter Sterilization of Patient Urine Samples

Melioidosis patient urine samples were obtained from Menzies School of Heath Research and stored at -80°C. The clinical specimens were 0.22 μm filter sterilized using syringe filter units (MilliporeSigma, Burlington, MA) at BSL3. Filter sterilization was confirmed using back culture. Sterile samples were removed from BSL3 to BSL2 to perform CPS quantification and other analyses.

Antigen-capture Enzyme-linked Immunosorbent Assay (ELISA)

Enzyme-linked immunosorbent assays (ELISA) utilizing monoclonal antibody (mAb) 4C4 were conducted as previously described [129]. mAb 4C4 has been characterized to bind

CPS of B. pseudomallei and B. mallei [236]. A standard curve was performed using purified CPS.

Active Melioidosis Detect TM plus (AMD+) rapid test lateral flow immunoassay (LFI)

InBios AMD+ LFIs were tested as per manufacturer’s instructions in a BSL3 laboratory.

40 μL of sample was placed on the test strip sample pad followed by two drops of Chase

Buffer A. LFIs were run for 15 minutes before reading visually. Images were taken using a Fujifilm FinePix XP120 camera.

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4.4 Results

In vitro growth and capsular polysaccharide (CPS) production

Burkholderia pseudomallei strains 1026b and K96243 are distinct clinical isolates which have been thoroughly characterized [237, 238]. The Bp82 strain is a ΔpurM mutant derived from 1026b for the use at biosafety level 2 (BSL2) [235]. The three strains of B. pseudomallei were grown in nutrient rich broth for a 24-hour time course. Shown in table

1 are OD600 readings for a comparative quantification of cell density which includes dead cells. Bacterial cultures entered rapid growth phase between 4 – 8 hours. After 24 hours of growth, each strain reached a different cell density. B. pseudomallei 1026b cultures were most dense, followed by the ΔpurM mutant Bp82. Interestingly, cultures of the wildtype strain K96243 were the least dense of the three isolates after 24 hours of growth.

In vitro production of capsular polysaccharide (CPS) was quantitated by antigen-capture enzyme-linked immunosorbent assay (ELISA). Cell cultures were fractionated by centrifugation to assess CPS concentrations bound to bacterial cells and concentrations shed into media. Residual CPS from starter cultures can be detected in T=0 samples.

Despite cells being in lag phase between hours 0 to 4, CPS production is observed. No significant differences are detected in the total abundance of cell-associated CPS between the three strains at any time point (Fig 1A), however differences in cell density impeded a direct comparison. Cell-associated CPS in strain K96243 is about 2-fold higher when normalized by the OD600 compared to strains 1026b and Bp82 at 24 hours.The concentration of CPS shed into supernatant was significantly greater in B. pseudomallei K96243 cultures at 51 μg/mL compared to 1026b (22 μg/mL) and Bp82 (17

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μg/mL) (Fig 1B). These results indicate the K96243 isolate produces the greatest abundance of CPS in vitro despite having the lowest cell density.

Detection and quantitation of capsular polysaccharide (CPS) in melioidosis patient urine

A total of 20 samples were collected from 10 patients after being admitted to the Royal

Darwin Hospital in Darwin, Australia following the onset of symptoms. Multiple samples were collected from two patients over the course of treatment to determine presence of

CPS over time. Diagnoses were made based on positive bacterial cultures summarized in Table 2. Twenty unfiltered urine samples from patients were tested using the AMD+

LFI. 15 of the 20 unfiltered urine samples (75%) were positive for the presence of CPS.

The signal intensities were scored on a scale of 0 – 4 based on the visual readings in a

BSL3 laboratory, as shown in Table 3. A range of intensities were observed indicating various concentrations of CPS present in the urine. Patients for which multiple samples were available for testing had detectible levels of CPS for an extended duration. For example, urine samples from patient 390 show the presence of CPS over a four-month period. Samples from patient 391 were collected over a span of two years. Urine from year 1 was negative for CPS, however strong positives were observed in samples collected 10 months later.

In order to establish the concentration of CPS in the patient urine samples, clinical specimens were 0.22um filter sterilized and further analyzed. Due to sample volume limitations, only ten samples were filtered and removed from BSL3 to BSL2. Antigen- capture ELISA using mAb 4C4 detected CPS in nine of the filtered samples with

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concentrations ranging 0.05 – 3.0 ng/mL. Sample 444-8 was negative for the detection of CPS by ELISA; however, the patient continued to receive treatment for melioidosis a month after this sample was collected. Of the ten samples, eight were positive by

AMD+LFI. Sample 376-4 was negative by LFI but determined to have a CPS concentration of 0.05ng/mL, a concentration below the limit of detection of the LFI. Table

3 shows a summary of the LFI testing and CPS quantitation.

Filtered and unfiltered urine samples were run side-by-side on the AMD+ LFI to determine the effects of filter sterilization on CPS detection (Fig 2). No differences in signal intensity were observed visually in five urine samples: 376-4, 390-27, 390-49,

390-55, 444-8. Four samples resulted in a loss of intensity due to filter sterilization: 388-

1, 390-28, 390-32, 390-38. This loss in signal intensity caused sample 388-1 to read as negative for CPS following filtration. Interestingly, one sample (432-16) had an increase in signal intensity after 0.22um filtration (Fig 2C).

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4.5 Discussion

Melioidosis is a multifaceted disease presenting with a range of nonspecific symptoms including fevers, muscle soreness, skin and organ abscesses, and respiratory distress.

Surveillance in endemic countries has resulted in decreases in mortality rates, however many countries are predicted to bear a larger burden than actually reported [217]. The most crucial countermeasure for post-exposure is antibiotic treatment which is reliant on a prompt and accurate diagnosis. The current diagnostic standard is bacterial culturing, an ineffective method due to low sensitivity and extended time to diagnosis. Ideal for low technology settings, LFIs are quick and easy-to-use diagnostic tools self-contained in a single dipstick. The InBios AMD and AMD+ rapid tests are point-of-care LFIs which use an antibody for the visual detection of B. pseudomallei CPS [231]. The AMD+ LFI is an updated version of the AMD LFI test housed in a plastic cassette.

CPS is an important virulence factor which forms a capsule around the bacterium to prevent phagocytosis and promote colonization [239, 240]. In this study, B. pseudomallei strains K96243, 1026b, and ΔpurM Bp82 were evaluated for shed and cell-associated

CPS produced in vitro. A majority of CPS (77-85%) was found to be shed into supernatant after 24 hours of growth. B. pseudomallei K96243 cultures produced significantly greater amounts of CPS compared to 1026b and Bp82, when normalized for cell density. Differences in cell density also suggest cell-associated CPS in strain

K96243 is about 2-fold higher per bacterium than strains 1026b and Bp82. This phenomenon of shedding surface antigens has described in other pathogens such as

Ebola virus and Salmonella typhimurium [241, 242]. The release of antigen is believed to subversion the host immune system and protects the infectious agent. The greater

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abundance of CPS produced by B. pseudomallei strain K96243 may contribute to the isolate’s greater virulence compared to 1026b [243, 244]. Though strains K96243 and

1026b have been extensively characterized, identifying differences in CPS production of additional strains can help define the diagnostic power of the biomarker.

The AMD LFI has been utilized in combination with bacterial culturing for the detection of

B. pseudomallei, with a diagnostic sensitivity is 96-99% with 100% specificity [126, 232].

Though having high sensitivity and specificity, blood cultures were grown upwards of 7 days. Based on results found in this study, in vitro shedding of CPS can be observed prior to 2 hours after inoculation. Low bioburden in clinical species may prolong the time for blood culture bottles to reach turbidity, however CPS concentrations may in detectable ranges prior to reaching turbidity. Further evaluation of CPS concentration in blood cultures prior to 7 days is warranted to further validate the LFI as a powerful tool for diagnosing melioidosis from culture.

Immunoassays have been used in endemic regions to help identify B. pseudomallei directly in clinical samples. Similar to bacterial culturing, the AMD LFI can assay various matrices such as blood, urine, pus, and abscess fluids. Evaluations of the AMD LFI in

Laos and South India resulted in low sensitivity in blood and plasma but higher sensitivity in urine, pus, and sputum [126, 127, 228, 245]. Paired samples of serum and urine collected in Laos were analyzed for CPS by ELISA and AMD LFI. Results indicated that a majority of the patient urine samples had higher concentrations of CPS than in paired serum samples [Laos CPS paper]. Urine is a noninvasive matrix in which larger volumes can be collected and is less complex than other clinical matrices. Sample

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enrichment of low abundant antigens by immunoprecipitation (IP) and spin concentrators has been previously described [246, 247]. Evaluation of CPS enrichment in melioidosis patient urine suggest an increase to the diagnostic sensitivity of the AMD LFI [Laos CPS

& MP papers].

In this study, an additional twenty urine samples were evaluated for the presence of CPS using a newer version of the InBios test, AMD+ LFI. Previous testing of these samples using the AMD LFI were done by the Menzies School of Health Research (data not shown). The AMD+ LFI was re-optimized to increase specificity by decreasing the number of false positives observed. This re-optimization led to reformatting of the assay into a cassette, addressing previous issues with biosafety and containment. The AMD+

LFI detected CPS in 15 of 20 samples. Sample 388-1 was determined to have 0.39 ng/mL of CPS after filter sterilization. This filtered sample tested negative even though this concentration should be detected by the AMD+ LFI. This result suggests an interference at the test line, also known as the matrix effect [195]. Sample 376-4 was determined to be positive for CPS by ELISA at a concentration of 0.05 ng/mL, which is below the LOD for the AMD+. Though the AMD+ LFI is sensitive, this validates a need to develop a point-of-care method to concentrate CPS and further increase the diagnostic sensitivity of the assay.

Of the five samples which tested negative by AMD+ LFI, samples 381-2 and 391-2 tested positive on the AMD LFI previously at Menzies School of Health Research.

Sample integrity may have been affected due to shipping and freeze/thaw cycles.

Patient 391 was presumed an active melioidosis infection because of the detection of

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CPS on the AMD LFI despite a negative bacterial culture. Samples on the cusp of the

AMD+ LFI limit of detection may produce a difficult to read positive result, particularly when tested in a high containment laboratory setting.

The AMD+ LFI is an ideal candidate for streamlining the diagnosis of melioidosis due to its high sensitivity and specificity when testing bacterial cultures and patient samples. In this study, CPS is demonstrated to be shed in amounts well beyond the detectible levels of immunoassays within 24 hours when cultured in vitro. These results suggest the possibility of reducing a time to diagnosis by integrating the detection of CPS in bacterial culture supernatant. Furthermore, the presence of CPS in patient urine is evident during an active infection and is detectable by the AMD+ LFI. Ongoing research is being conducted on further optimizing the assay to detect the large dynamic range of CPS in patient samples. The AMD+ assay is being evaluated clinically in Thailand, Laos, India, and Australia to help with diagnoses. The utilization of the AMD+ LFI point-of-care assay will help improve medical standards and enhance public health surveillance for melioidosis worldwide.

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Acknowledgements

We would like to thank Drs. Paul Brett and Mary Burtnick at the University of Nevada,

Reno School of Medicine for providing purified B. pseudomallei capsular polysaccharide

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1000000

10000

100

associated associated CPS (ng/mL) -

Cell T = 0 T = 2 T = 4 T = 8 T = 24 0.01 Hours

Bp82 1026B K96243

(B)

1000000 * *

10000

100

CPS CPS in Supernatant (ng/mL) T = 0 T = 2 T = 4 T = 8 T = 24 0.01 Hours

Bp82 1026B K96243

Figure 1. Quantitation of capsular polysaccharide (CPS) in Burkholderia pseudomallei cultures. B. pseudomallei K96243, 1026b, and Bp82 cultures were fractioned into supernatant and cell pellets by centrifugation. Bacterial fractions were treated with proteinase K, and then evaluated for (A) cell-associated and (B) shed CPS by antigen- capture ELISA. Concentration values can be found in Tables S1 and S2 (*p-value < 0.005)

127

(A) 390-27 (B) 390-28

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Figure 2. Active Melioidosis Detect TM plus (AMD+) lateral flow immunoassay (LFI) used to evaluate melioidosis patient urine samples collected at the Menzies School of Health Research in Darwin, Australian. Patient urine samples were run in a biosafety level 3 (BSL3) as received (labeled with “U”) and after 0.22 um filter sterilization (labeled with “F”). The effects of filter sterilization are shown as followed: (A) Sample 390-27 resulted in no difference. (B) Sample 390-28 resulted in a loss of signal. (C) Sample 432-16 resulted in an increase of signal.

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Table 1. Growth of Burkholderia pseudomallei isolates (K96243, 1026b, and Bp82) in Luria-Bertani (LB) broth. OD600 readings were taken after heat-inactivation at hours 0, 2, 4, 8 and 24. Values are an average reading of three cultures (n=3).

OD600 of Burkholderia pseudomallei cultures Bp82 1026b K96243 T = 0 0.02 ± 0.02 0.01 ± 0.01 0.01 ± 0.01 T = 2 0 ± 0 0.07 ± 0.02 0.01 ± 0 T = 4 0.01 ± 0.01 0.07 ± 0.02 0.01 ± 0 T = 8 0.25 ± 0.02 0.25 ± 0.02 0.32 ± 0.02 T = 24 6.45 ± 0.34 8.14 ± 0.24 4.27 ± 0.13

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Table 2. Summary of melioidosis patient samples collected by the Menzies School of Health Research

Patient Identifier # of samples Culture positive sample

309 1 Urine 366 1 Urine 375 1 Throat & Rectum Swab 376 1 Blood 381 1 Abscess (buttock) 388 1 Blood 390 9 Blood 391 3 Urine^ 432 1 Blood 444 1 Blood ^Patient 391 was initially bacterial culture negative, but AMD LFI positive

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Table 3. Summary of AMD+ LFI testing and CPS quantitation by ELISA of melioidosis patient urine samples

Sample Days after 1st AMD+ signal AMD+ signal [CPS] Identifier sample intensity of intensity of (ng/mL) unfiltered urine* filtered urine* 309-7 2 ++++

366-4 9 -

375-7 5 +

376-4 3 - - 0.05

381-2 0 -

388-1 0 + - 0.39

390-3 0 ++++ 390-6 8 ++++ 390-25 22 ++ 390-27 29 ++ ++ 3.0 390-28 33 ++ + 0.62 390-32 41 +++ ++ 3.2 390-38 47 ++ + 2.0 390-49 89 ++ ++ 2.1 390-55 105 + + 0.93

391-2 0 - 391-21 305 ++++ 391-22 305 ++++

432-16 41 + + 0.20

444-8 21 - - - * Scored on a scale of 0 to 4 # Shaded boxes indicate samples with limited volume that were not analyzed further

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Table S1. Concentrations of capsular polysaccharide (CPS) in supernatant fraction of Burkholderia pseudomallei cultures.

[CPS] shed in Burkholderia pseudomallei supernatant

Bp82 1026b K96243 T = 0 13 ± 2 17 ± 5 21 ± 1 T = 2 18 ± 1 23 ± 1 29 ± 3 T = 4 82 ± 10 53 ± 7 92 ± 8 T = 8 890 ± 136 967 ± 118 1162 ± 144 T = 24 17805 ± 2048 22690 ± 1542 51189 ± 3243

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Table S2. Concentrations of capsular polysaccharide (CPS) in cellular fraction of Burkholderia pseudomallei cultures.

[CPS] associated to cells of Burkholderia pseudomallei

Bp82 1026b K96243 T = 0 0.5 ± 0.2 0.2 ± 0.1 0.1 ± 0.01 T = 2 0.5 ± 0.1 0.3 ± 0.04 0.3 ± 0.1 T = 4 7 ± 1 5 ± 5 11 ± 1 T = 8 324 ± 247 1171 ± 77 1177 ± 212 T = 24 5318 ± 208 6121 ± 527 7492 ± 1138

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Chapter 5. Temporal Profile of Immunoglobulin G Titers against SARS-CoV-2 RBD in Recovered Patients of Northern Nevada

Derrick Hau1, Chelsea C. Chung1, Jose Arias-Umana1, Valerie L Smith1, Kathryn J.

Pflughoeft1, David P. AuCoin1, Mark S. Riddle1, Sara A. Healy1,2

1 University of Nevada Reno School of Medicine Reno, Nevada, United States of America

2 Renown Health, Reno, Nevada, United States of America

*Corresponding author

Email: [email protected]

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5.1 Abstract

The global pandemic caused by severe acute respiratory syndrome coronavirus 2

(SARS-CoV-2) has resulted in over 39 million cases and 1.1 million deaths. Antibodies against the receptor-binding domain (RBD) of the spike protein are associated with viral neutralization, however low and waning titers may result in minimal viral immunity post- infection. In this study, plasma samples were collected from convalescent patients in

Northern Nevada and endpoint titers against the RBD were determined. Most individual were seropositive to the RBD domain. Interestingly, two individuals experienced increases in endpoint titers over time, possibly suggesting viral re-exposure.

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5.2 Background

The novel coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), leading to over 39 million cases reported globally [95]. Most individuals infected with the SARS-CoV-2 will elicit a humoral response against viral nucleoprotein and spike protein (S-protein) within 1-3 weeks post- symptom onset [248]. A fraction of the antibodies reactive to the receptor-binding domain (RBD) of the S-protein have been shown to block viral fusion mediated by interaction to the human ACE2 receptor, and therefore have demonstrated neutralizing activity [249]. However, in the case of COVID-19, memory B-cells which produce potent neutralizing antibodies are rare and may result to minimal neutralizing titers after recovering from an infection [250]. Disease severity has been directly correlated with antibody titers, further indicating nominal protection for those who have experienced milder cases [251]. Little is known regarding viral immunity and further insight is warranted to understand immune response to SARS-CoV-2. To determine temporal changes in antibody response after an acute infection, a cohort study in Northern

Nevada was conducted looking at titers against the RBD of the S-protein in patients who have cleared a non-severe case of infection.

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5.3 Methods

The cohort for this study included 43 individuals that have recovered from acute infections, tested negative for at least two weeks, are between the ages of 25-61 years old, and did not have any pronounced underlying conditions. Enrollment occurred at

Renown Health and the University of Nevada, Reno School of Medicine Clinical

Research Center (CRC). Convalescent plasma samples were collected at enrollment and 90 days later. Plasma was analyzed for immunoglobulin G (IgG) antibodies against a recombinant RBD subunit of the S-protein (Genscript, cat. no. Z03479) using an enzyme-linked immunosorbent assay (ELISA) adapted from Amanat, et al [252].

All convalescent plasma was heat-inactivated at 56°C for 1 hour and stored at -80°C until use. Microtiter plates (Greiner Bio-One, cat. No. 655001) were coated with RBD protein (1 µg/mL) in carbonate/bicarbonate buffer at 4°C overnight. Plates were washed with phosphate-buffered saline containing 0.5% Tween-20 (PBST), and then blocked with 5% milk in PBST for 1 hour at 37°C. Plasma samples were diluted into sample buffer (PBST containing 5% milk and 3M NaCl) and 2-fold serial dilution were performed to assay titers between 1:100 to 1:12,800 dilutions. Primary antibodies were incubated for 30 minutes at room temperature (RT). Plates were washed with PBST, then incubated with 0.04 µg/mL goat anti-human IgG HRP (Abcam, cat. No. ab97225) in 5% milk in PBST for 30 minutes at RT. Plates were washed with PBST and incubated with

TMB substrate (Seracare, cat. No. 5120-0050) for 30 minutes at RT. An equal volume of

1M H3PO4 was used to stop the reaction, and colorimetric data was read at OD450. 152 pre-pandemic samples archived from 2007-2008 were used to establish an analytical cutoff of OD450 of 0.5 resulting in 100% assay specificity. Endpoint titers were defined as the greatest dilution resulting in a positive signal.

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5.4 Results

To further understand protective immunity to COVID-19, a longitudinal study looking at anti-RBD endpoint titers over time was conducted in patients who recovered from acute infections (Figure 1). Convalescent plasma was collected from 41 individuals at the time of enrollment and 90 days later. Individuals in this study experienced non-severe infections, with only one person admitted for inpatient care.

The average age of the enrolled cohort was 44 years old with 55.8% identifying as female and 44.2% identifying as male. Of the 43 individuals, 42 were confirmed positive for SARS-CoV-2 by either nasopharyngeal swab (NP) (34/42) or serodiagnosis (8/40) between March - May 2020. Patient 00020 did not receive a confirmative diagnosis or seek medical attention; however, they were enrolled in the study based on clinical symptoms aligning with a SARS-CoV-2 infection. Patient 00012 tested positive by NP but was the only asymptomatic patient enrolled. All other individuals experienced

COVID-19 symptoms. Of the enrolled patients, 39 individuals were treated as outpatients, one was admitted for inpatient care, and the remain three individuals did not seek medical attention.

The cohort averaged a 62-day period between the onset of symptoms and the first blood draw. 40/43 (93.0%) individuals were seropositive for anti-RBD IgG and had an average endpoint titer of 1:1,615. Patients 00019 and 00024 were negative for anti-RBD IgG despite being diagnosed by NP testing. Patient 00020 who experience COVID-19 symptoms was also negative for anti-RBD IgG.

The cohort returned 3 months later (averaging 96 days) for a follow-up blood draw.

38/43 (88.3%) individuals were seropositive for anti-RBD antibodies and had an average endpoint titer of 1:1,119. Patients 00019, 00020, and 00024 remained seronegative for anti-RBD IgG. Patients 00023 and 05002 were seropositive with endpoint titers at 1:100

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during their first visits but were negative at the time of the second draw. A total of 22/40

(55.0%) patients saw a decrease in their endpoint titers and 16/40 (40.0%) remained at the same level. Interestingly, Patients 00008 and 05018 had 4-8 fold increases to their endpoint titers.

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5.5 Discussion

Seroprevalence was found in 93.0% of the cohort at the time of enrollment and maintained in 88.3% of the individuals after an average of 156 days post symptom onset. Titers waned in 55.0% of the individuals during the study resulting in a reduction in the average endpoint titers of 1:1,615 to 1:1,119 by the second visit. A study looking at the correlation between anti-RBD titers and neutralizing titers suggests that endpoint titers greater than 1:1,350 against the RBD of the S-protein was a good indicator of neutralizing titers being greater than 1:160, a value set forth previously by the Food and

Drug Administration as a baseline for therapeutic transfusions [253]. As testing for neutralizing titers is much more complex than endpoint titers, this correlation can be used to quickly screen individuals for donating plasma or surveying immunity in recovered patients and for vaccine candidate studies [253]. In the current study, only

16/43 (37.2%) had titers greater than 1:1,350 at the time of enrollment. And by the second visit, only 8/43 (18.6%) individuals had a titer exceed this baseline. Low and quickly waning titers may suggest short-lived immunity in patients with acute infections.

Furthermore, three individuals (7.3%) were negative for anti-RBD titers and may represent a population that do not seroconvert to the RBD subunit, had a short-lived response (within 62 days), or were false positive for COVID-19.

Two individuals in this study (Patients 00008 and 05018) saw increases in anti-RBD IgG titers. This may suggest re-exposures to the virus, however current methods for retroactively determining infections are reliant on serology and patient history. These methods are insufficient for determining reinfections; however, numerous cases of

SARS-CoV-2 reinfections have been documented and confirmed by nasopharyngeal swab and nucleic acid testing [108, 109, 254]. Most reinfections are likely not determined as three of the four cases resulted in asymptomatic infections [109, 254]. The fourth

141

case experienced a severe reinfection and required hospitalization and oxygen [108].

Even with some immunity to SAR-CoV-2, individuals who are reinfected are likely able to spread the virus as an asymptomatic carrier. Continued serological surveillance of individuals who have recovered from an infection, specifically those at high risk of re- exposure, should be conducted as IgG response was observed to spike during reinfection [108, 109, 255]. This may help further contain spreading of the virus from otherwise healthy, asymptomatic individuals. Additionally, related coronaviruses which cause the common cold have shown to result in a short-term adaptive immune response leading to natural reinfections within 12 month, a trait suggested to be shared amongst coronaviruses [256].

More information is needed to understand COVID-19 infections and the human immune response in order to determine viable methods for combating the pandemic. The cohort study presented here suggests most individuals with acute infections elicit an adaptive immune response against the RBD subunit associated with viral neutralization; however, this response may not be sufficient for prolonged immunity. Additional studies looking at those who have recovered but are at high risk of exposure could help determine reinfection rates. Efforts in northern Nevada identifying circulating viral isolates and infected individuals will add to the global efforts of understanding COVID-19 as little is known about the risk factors associated with the infection, determinants of disease severity, and virulence of different clades of SARS-CoV-2.

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Figure 1. Temporal changes of anti-receptor-binding domain (RBD) titers in Northern Nevada patients recovered from an acute SARS-CoV-2 infection. Patients averaged 61- days post symptom onset at enrollment (blue circles). 2nd visit average 94 days after enrollment (orange squares). Each line represents a different individual enrolled in the cohort.

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Chapter 6. Conclusion

Putative biomarkers of melioidosis and tularemia were identified using a multi-armed approach encompassing a comprehensive methodology for determining novel targets.The InMAD platform was utilized to determine protein targets using clinical melioidosis and tularemia serum and urine. Identification of targets by elicited murine

IgG and IgM response were determined using a nucleic acid programmable protein array. Alternatively, clinical samples were also used to probe the array to determine putative IgG and IgA serological markers of infection. A pilot studying comparing two different acquisition methods by mass spectrometry was performed. Data dependent acquisition is a classical discovery platform, however, may have a low analytical sensitivity in pathogen-associated biomarker discovery. Alternatively, a novel data independent acquisition assay was developed resulting in greater analytical sensitivity, however, was limited on a discovery capacity. Putative biomarkers were identified for melioidosis and tularemia and will need to be validated using directed assays such as

Western blot or targeted mass spectrometry. Validated targets can serve useful in the develop novel diagnostic tools for these infections.

Monoclonal antibodies, specific to LcrV and F1, were used to develop antigen-capture

LFIs and ELISAs with high analytical sensitivity. The LFI prototypes resulted in limits of detection of about 1 ng/mL of both LcrV and F1 when assaying in surrogate clinical specimens. The ELISAs showed analytical sensitivity in the range of 61-74 pg/mL, however, testing was only preformed in buffer. These assays have improved limits of detection compared to published data using commercially available assays. Furthermore, assays utilizing mAbs result in more consistent assay performance when compared to

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those developed with polyclonal antibodies due to limitations on assay reagents. The detection of the F1 antigen is widely used to diagnose plague infections, however mutant strains of Y. pestis lacking the F1 antigen have been identified. Initial inclusivity/exclusivity studies of the multiplexed LFI demonstrates that the inclusion of a second antigen, LcrV, increases the diagnostic potential of the assay to resource limited environments. The LcrV antigen is crucial for virulence and may be used as an alternative marker of plague. Further evaluation of LcrV is warranted and can be accomplished using the tools developed in this study. In addition to improving the diagnostic utility of available assays, the mAbs isolated and immunoassays developed may be useful for therapeutic purposes and environmental surveillance, thereby assisting in the prevention of future plague outbreaks.

The detection of CPS in clinical specimens, specifically urine, is a powerful alternative for diagnosing melioidosis compared to bacterial culture. The Active Melioidosis Lateral flow immunoassays is being evaluated for FDA approval to test clinical samples directly. In the present study, 15 of 20 melioidosis urine samples were positive for CPS by LFI. CPS was detected in serial samples collected from patients being treated with melioidosis. The LFI can be used to determine patient response to treatment as the LFI can present semi- quantitative data. The presence of CPS over months of sample collection may indicate a chronic infection. Ongoing research is being conducted on further optimizing the assay to detect the large dynamic range of CPS in patient samples. Direct analysis of clinical samples on the LFI is ideal, however alternative methodology using the diagnostic tool should be evaluated. Three isolates of B. pseudomallei were evaluated for CPS production when grown in vitro. After 24 hours of growth, these cultures resulted in 17-52 µg/mL of

CPS. For example, the use of LFI to detect CPS in bacterial cultures may increase the assay sensitivity of bacterial culture, while decrease the time for diagnosis.

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COVID19 is a global pandemic which has infected over 46 million individuals worldwide with a case fatality rate of 2.6%. Presently, there are minimal countermeasure in place combating and infection as the novel coronavirus is not responsive to many generic antiviral treatments. Understanding viral and host interactions are necessary for developing processes for preventing further viral spread. In the last chapter, antibody titers were determined in patients who have recovered from acute COVID19 infections. Low and waning titers after 160 days post-recovery may suggest poor protective immunity to the virus. Of interest were patient who saw increases in titers after recovery Accounts of re-exposure have been identified with varying disease severity for reinfections further indicating poor protect immunity. Surveillance of antibody titers may be a useful method for identifying reinfections especially in those at high risk groups for exposure. As the

COVID19 pandemic continues to grow, the need for accessible medical countermeasure is highlight.

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