Secretion of Malaria Transmission-Blocking Proteins from Paratransgenic Bacteria Nicholas Bongio

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SECRETION OF MALARIA TRANSMISSION-BLOCKING

PROTEINS FROM PARATRANSGENIC BACTERIA

A Dissertation

Submitted to the Bayer School

of Natural and Environmental Sciences

Duquesne University

In partial fulfillment of the requirements for

the degree of Doctor of Philosophy

Nicholas James Bongio

May 2015

Nicholas James Bongio

2015

SECRETION OF MALARIA TRANSMISSION-BLOCKING

PROTEINS FROM PARATRANSGENIC BACTERIA

Nicholas James Bongio

Approved May 19, 2014

______Dr. David Lampe Dr. Nancy Trun Associate Professor of Biology Associate Professor of Biology (Committee Chair) (Committee Member)

______Dr. Marcelo Jacobs-Lorena Dr. Jana Patton-Vogt Professor of Molecular Biology and Associate Professor of Biology Immunology (Committee Member) (Committee Member)

______Dr. Philip Reeder Dr. Joseph McCormick Dean, Bayer School Chair, Biological Sciences Professor of Environmental Science Associate Professor of Biology

iii

ABSTRACT

SECRETION OF MALARIA TRANSMISSION-BLOCKING

PROTEINS FROM PARATRANSGENIC BACTERIA

Nicholas James Bongio

May 2015

Dissertation supervised by Dr. David Lampe

Malaria is a debilitating and deadly disease that afflicts over 200 million people and kills over 600 thousand each year. Due to quickly evolving drug resistance and lack of an affordable vaccine, novel interventions are needed to fight the Plasmodium parasites that cause malaria. Targeting Plasmodium inside their mosquito hosts is one approach that could complement other preventative and medicinal interventions by reducing the ability of the mosquitoes to transmit the disease to humans. The research presented here uses paratransgenesis, the genetic modification of symbiotic bacteria within the mosquito midgut, to provide antimalarial protein to the mosquito and to interfere with the life cycle of Plasmodium within the insect host.

This research has produced three new antimalarial paratransgenic tools. The first tool is a set of new antimalarial effector proteins that were constructed by converting

iv anti-Plasmodium mouse antibodies into single-chain variable fragment (scFv) versions for expression by bacteria. These antibodies bind to Plasmodium surface proteins and interfere with critical steps in the parasite life cycle. The second tool is a modified bacterial species, Pantoea agglomerans, which was engineered to secrete diverse antimalarial proteins via the hemolysin secretion pathway. Modified P. agglomerans were fed to mosquitoes and were capable of inhibiting the invasion of Plasmodium within the midgut. The third tool is another modified bacterial species, Asaia sp. SF2.1. Native

Type II secretion signals were discovered that enable the creation of paratransgenic strains of these bacteria. Modified strains of Asaia sp. SF2.1 were also demonstrated to interfere with the invasion of Plasmodium within the mosquito.

These tools have laid the groundwork for the future use of paratransgenic bacteria to combat malaria in the wild. Asaia sp. SF2.1 bacteria, in particular, are capable of spreading throughout mosquito populations, so they provide their own drive mechanism to establish themselves within the mosquito vectors of malaria. While further modifications will be required to make these bacteria ready for field use, the findings of this research provide proof of concept that the bacteria are suitable for eventual use in malaria transmission-blocking interventions.

DEDICATION

This work is dedicated to my wonderful fiancée, Candice Kruth. She has inspired me to achieve all that I have, and my life would not be complete without her. She has helped me in countless ways to follow the path I have chosen and to accomplish the goals

I set forth. I would like to thank her for the weeks she spent editing my writing into the legible form presented in this volume. Without her love and support, I would not be where I am today.

ACKNOWLEDGEMENTS

I would like to thank my committee members who were always helpful and generous with their time. A special thanks to my Ph.D. advisor, Dr. David Lampe, who has been a great friend and mentor over the years. Working in your lab has been a great experience, and I would not be the scientist I am today without having had the opportunity to study with you. Thank you Dr. Marcelo Jacobs-Lorena, Dr. Jana Patton-

Vogt, and Dr. Nancy Trun for agreeing to serve on my committee. The time you have spent giving advice and feedback on my work has been integral to my growth and success, and all of your hard work is appreciated.

I would also like to thank the Bayer School faculty, staff, and students for all the assistance they have provided to me in my time at Duquesne and for the friendship we shared. The community in the Department of Biological Sciences has made this place a great environment to work in. I will fondly remember my time at Duquesne.

I’d like to thank both the Bongio and Kruth families for their love and support.

My parents have always supported me and encouraged me to achieve great things. The

Kruth family has been just as loving as my own, and they have always been there when I needed them. I am forever grateful to you all for your helping hands and open hearts over these years.

vii ATTRIBUTIONS

In Chapter 1, 2, 4, and 5, the design and execution of experiments were fully conducted by Nicholas Bongio.

In Chapter 3, Nicholas Bongio was responsible for designing, cloning, and testing the bacterial expression of two of the antimalarial genetic constructs and overseeing the work of an undergraduate researcher on similar constructs. All other work in this chapter was conducted by the lab of Marcelo Jacobs-Lorena, including the writing of the manuscript.

The appendix publication “a Draft Genome Sequence of Asaia sp. SF2.1, an

Important Member of the Microbiome of Anopheles sp. Mosquitoes” was written by Dr

Lavid Lampe, and edited by Nicholas Bongio and Jackie Shane. Jackie Shane prepared the DNA sample that was used for sequencing.

The appendix publication “Paratransgenesis in Mosquitoes and Other Insects:

Microbial Ecology and Bacterial Genetic Considerations” was written by Dr. David

Lampe, and edited by Nicholas Bongio. Figures were created by Nicholas Bongio.

viii TABLE OF CONTENTS

Page

Abstract ...... iv

Dedication ...... vi

Acknowledgement ...... vii

Attributions ...... viii

List of Tables ...... xii

List of Figures ...... xiii

Chapter 1: The problem of malaria ...... 1

MALARIA: THE DISEASE...... 1

ANTIMALARIAL EFFORTS ...... 3

THE BIOLOGY AND LIFE CYCLE OF PLASMODIUM ...... 4

TRANSMISSION-BLOCKING EFFECTOR PROTEINS ...... 7

THE MOSQUITO VECTORS OF HUMAN MALARIA...... 10

MOSQUITO MICROBIOTA ...... 11

TRANSGENESIS AND PARATRANSGENESIS ...... 13

PROTEIN SECRETION FROM GRAM-NEGATIVE BACTERIA ...... 17

Chapter 2: Production of single-chain variable fragment antibodies and secretion from bacteria ...... 25

ABSTRACT ...... 25

BACKGROUND ...... 26

MATERIALS AND METHODS ...... 34

ix RESULTS ...... 48

DISCUSSION ...... 52

Chapter 3: Fighting malaria with engineered symbiotic bacteria from vector mosquitoes ...... 91

INTRODUCTION ...... 92

MATERIALS AND METHODS ...... 95

RESULTS ...... 97

DISCUSSION ...... 102

Chapter 4: Identification of secretion signals from Asaia sp.

SF2.1, a mosquito midgut bacteria ...... 113

ABSTRACT ...... 113

BACKGROUND ...... 114

MATERIALS AND METHODS ...... 117

RESULTS ...... 127

DISCUSSION ...... 133

Chapter 5: Summary and future directions ...... 175

SUMMARY ...... 175

FUTURE DIRECTIONS ...... 181

CLOSING REMARKS ...... 182

References ...... 184

Appendix ...... 204

x A DRAFT GENOME SEQUENCE OF ASAIA SP. SF2.1, AN IMPORTANT MEMBER

OF THE MICROBIOME OF ANOPHELES SP. MOSQUITOES...... 204

PARATRANSGENESIS IN MOSQUITOES AND OTHER INSECTS: MICROBIAL

ECOLOGY AND BACTERIAL GENETIC CONSIDERATIONS...... 207

xi LIST OF TABLES

Page

Table 2.1 Plasmids used in this study ...... 83

Table 2.2 Oligonucleotides used in this study ...... 85

Table 2.3 Bacterial strains used in this study ...... 89

Table 2.4 Secretion signals cloned from acetic acid bacteria ...... 90

Table 4.1 Proteins Identified from genetic screen for secreted Asaia proteins ...... 159

Table 4.2 Plasmids used in this study ...... 161

Table 4.3 Oligonucleotides used in this study ...... 163

Table 4.4 Bacterial strains used in this study ...... 165

Table 4.5 Secretion signal prediction from Asaia sp. SF2.1 genome...... 166

Table 4.6 Oocyst counts from anti-Plasmodium in vivo testing ...... 173

Table 4.7 Oocyst counts from repeated anti-Plasmodium in vivo testing ...... 174

xii LIST OF FIGURES

Page

Figure 1.1 The Plasmodium life cycle...... 23

Figure 1.2 Secretion systems of Gram-negative bacteria...... 24

Figure 2.1 Forms of antibodies...... 56

Figure 2.2 Di-diabody...... 57

Figure 2.3 Overlap extension PCR...... 58

Figure 2.4 Antibody variable region PCR and overlap extension PCR...... 59

Figure 2.5 Single-chain antibody construct...... 60

Figure 2.6 Nucleotide sequence of the 5' end of anti-Pfs48/45 scFv hairpin fix...... 61

Figure 2.7 Nucleotide sequence of the anti-Pfs25 scFv...... 62

Figure 2.8 Nucleotide sequence of the anti-Pfs48/45 scFv...... 63

Figure 2.9 Nucleotide sequence of the codon-harmonized anti-Pfs48/45 scFv...... 64

Figure 2.10 Nucleotide sequence of the anti-Pfs230 scFv...... 65

Figure 2.11 Nucleotide sequence of the anti-human complement scFv...... 66

Figure 2.12 Codon usage...... 67

Figure 2.13 RNA hairpin-forming region of the anti-Pfs48/45 scFv gene...... 70

Figure 2.14 Bacterial recombination cloning protocol...... 71

Figure 2.15 pBBR1MCS-2...... 72

Figure 2.16 pNB20...... 73

Figure 2.17 pNB51...... 74

Figure 2.18 Modular scFv gene constructs...... 75

xiii Figure 2.19 Protein production of E. coli and P. agglomerans expressing optimized scFv secretion constructs using the pelB leader...... 76

Figure 2.20 Northern blot of RNA from E. coli strains expressing scFv genes...... 77

Figure 2.21 pNB49...... 78

Figure 2.22 pNB50...... 79

Figure 2.23 Expression of GFP by Asaia bogorensis...... 80

Figure 2.24 Protein production of Asaia expressing heterologous scFv secretion constructs using leader peptides from related species...... 81

Figure 2.25 Protein production of Asaia expressing heterologous scFv secretion constructs using leader peptides from related species...... 82

Figure 3.1 Transgenic P. agglomerans rapidly proliferate in the midgut after a blood meal...... 107

Figure 3.2 The engineered P. agglomerans strains efficiently secrete anti-Plasmodium effector proteins...... 108

Figure 3.3 Inhibition of P. falciparum development in vector mosquitoes by recombinant P. agglomerans strains...... 109

Figure 3.4 Comparison of P. falciparum development between mosquitoes that fed on an infectious blood meal at either 2 or 4 d after administration of recombinant P. agglomerans...... 110

Figure 3.5 Inhibition of P. berghei development in mosquitoes harboring recombinant P. agglomerans strains...... 111

Figure 3.6 Impact of recombinant P. agglomerans strains on lifespan of Anopheles gambiae females...... 112

xiv Figure 4.1 Plasmid for phoA fusion library construction...... 141

Figure 4.2 PhoA-Asaia protein fusion plasmids expressed in Asaia...... 142

Figure 4.3 Secreted protein abundance and activity from PhoA-Asaia protein fusion plasmids expressed in Asaia...... 143

Figure 4.4 pNB92...... 144

Figure 4.5 pNB93...... 145

Figure 4.6 pNB95...... 146

Figure 4.7 Antimalarial effector constructs...... 147

Figure 4.8 Western blot of the supernatant of Asaia cultures detecting proteins secreted using the siderophore receptor fusion protein...... 148

Figure 4.9 Disruption of Plasmodium berghei development by Pro-EPIP and Pbs21-

Shiva1 constructs...... 149

Figure 4.10 Disruption of Plasmodium berghei development by scorpine and PLA2 constructs...... 150

Figure 4.11 Disruption of Plasmodium berghei development by anti-Pbs21-Shiva1 immunotoxin and scorpine constructs...... 151

Figure 4.12 Signal sequence of the siderophore receptor protein...... 152

Figure 4.13 Signal sequence of the YVTN beta-propeller repeat protein...... 153

Figure 4.14 Tat and Sec signal peptide computational prediction for the siderophore receptor protein...... 154

Figure 4.15 Tat and Sec signal peptide computational prediction for the YVTN beta- propeller repeat protein...... 155

Figure 4.16 pNB124...... 156

xv Figure 4.17 pNB124...... 157

Figure 4.18 Western blot demonstrating the secretion of alkaline phosphatase from

Asaia SF2.1 using only the 51 amino acid long siderophore receptor signal or the 34 amino acid long YVTN beta-propeller repeat protein signal sequence...... 158

Figure A.1 Derivatives of antibodies useful in paratransgenesis...... 221

Figure A.2 Secretion of effector proteins by bacteria using one of two different pathways...... 222

Figure A.3 A genetic screen to identify native secreted protein genes in bacteria using TnphoA...... 223

Figure A.4 A differential fluorescence genetic screen in bacteria to identify conditional promoters activated in a blood meal...... 224

Figure A. 5 pSC189, a broad host range transposon insertion vector based on

Himar1 ...... 225

xvi

Chapter 1

The problem of human malaria

MALARIA: THE DISEASE

In 2012, there were approximately 207 million cases of human malaria, and the disease was estimated to have caused 627,000 deaths worldwide, the majority of these deaths being among children under 5 years old in sub-Saharan Africa (WHO 2013).

Currently, there are 104 countries and territories where malaria is considered endemic, meaning that 3.4 billion people are at risk of becoming infected with malaria every day

(WHO 2013).

Malaria is one of the deadliest infectious diseases on earth, and accordingly, a great deal of research focuses on its prevention and treatment. The two main areas of research to combat the virulent Plasmodium parasite, which causes malaria, have concentrated on the synthesis of antimalarial drugs to target the parasite in the human host, and on the manufacture of insecticides to eliminate or to reduce the mosquito vector populations (Karunamoorthi 2014, Ansari 2013). Despite decades of research providing new drugs and interventions, malaria is still a large problem in many developing nations across the world. This is due to the fact that Plasmodium rapidly evolves resistance to new drugs, and the drugs themselves are expensive to produce and distribute in the quantities necessary to cure the millions of cases that occur every year (Poirot 2013,

Sibley 2014). Reaching infected individuals in impoverished nations is extraordinarily difficult.

The malaria parasite has been coevolving with humans throughout history (Cox

2010), and was described as early as the year 2700 BC, when the symptoms of malaria were described in the “Nei Ching,” a medical text edited by Emperor Huang Ti of China.

The malaria parasite was identified in humans as long ago as 1323 BC in ancient Egypt, and Plasmodium was identified by molecular means in the autopsy of King

Tutankhamun, and was hypothesized to be one cause of his death (Timmann 2010).

Malaria was given its current name by the contraction of the Italian words mala aria meaning “bad air,” because prior to the discovery of the mosquito vector, it was believed that breathing foul vapors from swamps caused the disease. In 1880, the malaria parasite was discovered by Alphonse Laveran (Cox 2010), and in 1897, the function of the mosquito vector in transmission was identified in avian malaria by Ronald Ross (Ross

1898).

Due to centuries of parasite-host coevolution, Plasmodium has become adept at avoiding the human immune system. Within the human blood stream, for instance, the parasite undergoes antigenic shifting which allows it to evade detection by the host's adaptive immune system. A prime example of antigenic shifting is the Plasmodium falciparum erythrocyte membrane protein 1. This protein is encoded by 60 unique var genes, each of which produces a different protein that is displayed on the surface of host erythrocytes. Through a developmentally-regulated process, the parasite randomly selects

one of these proteins to display upon invasion of a cell, so the host's immune system will not recognize the new antigen presented (Chen 1998).

Not only has Plasmodium adapted to evade the human immune system, but also the human population has experienced genetic changes which impart resistance against the parasite (Kwiatkowski 2005, Allison 2009). Many human genetic mutations have been identified that provide resistance against infection, including alterations in membrane proteins of red blood cells, alterations in enzymes of red blood cells, and mutations in the hemoglobin genes responsible for oxygen transport (Williams 2006,

Lopez 2010). For example, sickle cell disease is a result of a hemoglobin gene mutation which interferes with Plasmodium within infected erythrocytes (Beutler 1955, Bunn

2013). Though the sickle cell phenotype has a protective effect against Plasmodium, it also has a serious health cost for the host and can cause fatal organ failure (Powars 1990).

Such adaptations provide important perspective on the evolutionary cost of malaria on humans; the cost is so great that we have evolved resistance mechanisms to the disease, many of which are deleterious mutations on their own (Lopez 2010).

ANTIMALARIAL EFFORTS

Since malaria has plagued mankind throughout history, many interventions have been attempted to curb the devastation it causes. The first medicines used to treat malaria were derived from plants. These medicines include quinine, which is naturally found in the bark of trees in the Cinchona genus, and artemisinin, which is produced by Artemisia annua or sweet wormwood. Modern science has allowed us to produce artemisinin

artificially by expressing the gene in yeast, and variants of these medicines have also been synthesized in laboratories (Dhingra 1999). There is a constant need for new medicines since the parasite has been steadily evolving resistance to each new drug used

(Enayati 2009). Typically, these drugs are used in combination in an attempt to curtail the development of resistant strains and still quickly eliminate infections (Fairhurst 2012).

Vaccines against malaria have demonstrated some effectiveness (Seder 2013); however, these require attenuated sporozoite stage parasites, and production of the necessary large quantities of the sporozoites is time and cost prohibitive. Probably the most effective interventions to prevent transmission of the disease have been in vector control, including bed nets, window screens, and insecticides that either physically separate people from the mosquito or eliminate the vector population. These simple treatments can lead to a great reduction in transmission of malaria, but supplying them to millions of individuals in impoverished nations is difficult to orchestrate and can be expensive (Sabot 2010).

THE BIOLOGY AND LIFE CYCLE OF PLASMODIUM

There are five species of Plasmodium that cause human malaria. These are

Plasmodium falciparum, P. malariae, P. vivax, P. knowlesi, and P. ovale. Among these species, P. falciparum is the most deadly. Plasmodium are protozoan parasites in the phylum Apicomplexa. Apicomplexans have a plastid organelle called an apicoplast, which is believed to have evolved from the endosymbiosis of algae. The apicoplast is important for the production of a large number of proteins for Plasmodium, and it is involved in the

invasion of host cells (Kalanon 2010). Apicomplexans use two structures to invade host tissues: (1) an apical complex, which is cone-shaped structure composed of spirally- arranged microtubules, and (2) the rhoptry, which is a secretory complex for invasion- related enzymes and proteases. Plasmodium use these structures at many points in its life cycle to invade diverse tissues of each host it infects.

Plasmodium have a complex life cycle requiring both an Anopheles mosquito and a human host (Ghosh 2000) (Figure 1.1). The parasite enters into the bloodstream of the human host when an infected female mosquito injects saliva while taking a blood meal.

The saliva contains the sporozoite form of Plasmodium, which travel through the blood stream into the liver where they invade Kuppfer cells. In the case of P. vivax, P. malariae, and P. ovale, it is common for some of the infected cells to go into a dormant state called the hypnozoite, or “sleeping parasite,” and to delay the transformation into blood stage parasites for months or years. The sporozoite-infected cell then forms a schizont, which is a rapidly growing and dividing cell that produces tens of thousands of blood-stage merozoites. The schizont bursts open to release the merozoites into the blood stream. Merozoites infect red blood cells where they reproduce asexually, bursting open and releasing more merozoites every 1-3 days, perpetuating the cycle. This cyclical invasion and rupturing of red blood cells is what causes most of the disease symptoms of malaria, such as anemia and fever. The periodicity of these cycles of asexual reproduction and fever are synchronized and have a specific frequency for the different species of Plasmodium that can be tertian, occurring every two days, or quartan, occurring every three days (Garcia 2001). A small percentage of the trophozoites, or

newly infected red blood cells, will produce male or female gametes instead of producing merozoites. These infected cells remain dormant while in the blood stream. They can then be taken up by an uninfected Anopheles mosquito during a blood meal.

Once ingested in a blood meal, Plasmodium-infected red blood cells burst open and the released gametes undergo sexual reproduction in the mosquito midgut (Figure

1.1 part C). Their activity is triggered by the change in pH, the decrease in temperature, and the exposure to xanthurenic acid produced by the mosquito (Billker 1998). Within 24 hours, the male and female gametes fuse to form a zygote which transforms into an ookinete, a motile form of Plasmodium. The ookinete actively invades and passes through the midgut epithelium of the mosquito. On the outer surface of the midgut and under the basement membrane, the ookinete forms an oocyst in which it divides to produce thousands of sporozoites. These oocysts burst open when mature, releasing their sporozoites into the hemolymph of the mosquito, which can travel to and invade the salivary glands, ready to be injected into the next human host.

Fertilization within the mosquito host and subsequent invasion of the mosquito midgut present the greatest bottlenecks to Plasmodium transmission (Su 2007). This critical life stage has, therefore, been targeted for transmission-blocking experiments in attempts to stop the development of the parasite before the anopheline host is infected.

Fertilization is complex and requires multiple protein interactions between male and female gametocytes. Blocking the proteins involved with neutralizing antibodies can prevent successful fertilization, hence arresting development. For example, antibodies that bind to Pfs48/45, a protein on the surface of the female macrogametocyte required

for interaction with the male gametocyte, and Pfs230, a large protein on the surface of male gametocytes involved in the formation of exflagellation centers necessary for fertilization, have been shown to interfere with the life cycle of P. falciparum

(Outchkourov 2008, Eksi 2006).

Other proteins can be targeted to block ookinete invasion. These include the

Plasmodium and Anopheles proteins that the parasite uses to attach to and to penetrate the midgut epithelial cells. One of these proteins is Pfs25, a P. falciparum surface protein that is necessary for parasite binding to the midgut epithelium. Antibodies have been produced that will block invasion of mosquito tissues by interfering with the function of

Pfs25 (Saxena 2007) and have been used for transmission-blocking interventions by masking the Pfs25-binding domains necessary for invasion. Similarly, the SM1 peptide blocks the anopheline receptor of the enolase binding protein of ookinetes and the use of the lectin, Jacalin, that binds to anopheline aminopeptidase N, yet another target of ookinete binding (Ghosh 2001, Dinglasan 2007). A final example of a target is

Plasmodium chitinase, an enzyme which is necessary for degrading the peritrophic matrix of the mosquito to allow the ookinete to reach the midgut epithelium and invade (Tsai

2001).

TRANSMISSION-BLOCKING EFFECTOR PROTEINS

Passage through the peritrophic matrix and midgut epithelium is one of the major bottlenecks in the life cycle of the parasite, making it a prospective target for transmission-blocking therapies. In field-caught anopheline malaria vectors, there are

typically only between 0 - 5 oocysts per midgut (Gouagna 1998). An intervention at this life stage of Plasmodium development targets the parasite when it is especially vulnerable, and previous antimalarial techniques have not yet exploited this avenue.

Antibodies have been used in the treatment of multiple diseases and have proven effective in providing immunity in some cases of malaria. Furthermore, multiple antibodies have been shown to be capable of blocking transmission through the midgut

(Barr 1991, Outchkourov 2008, Quakyi 1987). These antibodies have been expressed from hybridoma cell lines and subsequently fed to mosquitoes mixed into an infective blood meal to demonstrate their activity artificially (Barr 1991, Roeffen 1995, Roeffen

2001). An anti-chitinase single-chain antibody (scFv) has also been demonstrated to block transmission (Li 2005). Plasmodium chitinase is an important factor for the parasite to make its way through the midgut peritrophic matrix. A different scFv was generated which targets Pbs21, a surface protein on ookinetes of Plasmodium berghei, a rodent malaria that has been widely used for transmission-blocking experiments in the lab

(Yoshida 1999). This scFv expressed by a baculovirus expression system blocked 93% of oocyst development in the mosquito (Yoshida 1999).

Proteinase inhibitors have been demonstrated to prevent transmission by disrupting various parts of the parasite's reproductive cycle in the midgut (Rupp 2008).

There are multiple protease inhibitors that can be used to block transmission, because the parasite requires different proteinases to break through the mosquito's defenses. For example, ankyrin, a 10 amino acid peptide, has been shown to prevent exit of the parasite from erythrocytes by blocking the protease function of Falcipain-2 (Dhawan 2003). It

should be relatively simple to secrete this small peptide from bacteria; however, the fitness cost associated with the protease inhibitors may be significant for the mosquito host. Such inhibition could interfere with blood meal digestion, and without a blood meal, female mosquitoes would be unable to produce eggs and to propagate the species.

Various antimicrobial peptides from arthropods have also been demonstrated to have anti-Plasmodium properties. Gomesin is an antimicrobial peptide isolated from the spider Acanthoscurria gomesiana (Silva 2000). It has displayed the ability to inhibit exflagellation and ookinete formation (Moreira 2007). Scorpine is a potent antimalarial and antibacterial agent from Pandinus imperator scorpion venom that causes membrane disruption and cell lysis across a range of microbial species (Corzo 2001, Conde 2000). If either of these proteins can be expressed from bacteria in the mosquito midgut, then it would provide a powerful inhibitory effect on both gametes and ookinetes. The scorpine protein is rather small, too, at only 8,350 Da, and this should be easy to produce heterologously, if a suitable host bacterium which is itself resistant to the antibacterial mechanism can be found. It has been expressed from transgenic strains of the fungus

Metarhizium anisopliae and been demonstrated to disrupt Plasmodium development in vivo (Fang 2011).

The goal of using effectors to block transmission in the mosquito midgut is to prevent the parasite from ever reaching the human host. After all, malaria is a disease of poverty, primarily affecting the poorest regions in the world where the population has limited access to health care or preventative measures (Sabot 2010). Transmission- blocking effectors are a cheap and renewable source of disease prevention and can lessen

the heavy medical and financial burden caused by the production and delivery of conventional medicines and vaccines.

THE MOSQUITO VECTORS OF HUMAN MALARIA

Globally, the Plasmodium parasites that cause human malaria are vectored by over 100 species of anopheline mosquitoes, with 30 to 40 of these species effecting the bulk of transmission (Raghavendra 2011). These mosquitoes live on all continents except

Antarctica and have been known historically to transmit malaria worldwide. Although the disease has been eliminated in many regions of the world including North America, most of Europe, Australia, and northern Asia, the vector mosquitoes still inhabit these places and the reintroduction of malaria remains a threat (Cohen 2012). Female anopheline mosquitoes spread the Plasmodium parasite during blood meals which are essential for their reproductive cycle. When taking the blood meal, an infected female mosquito can inject sporozoites into an uninfected human host; while an uninfected female mosquito can itself become infected by taking a blood meal from a human with a blood-stage infection.

A female Anopheles mosquito requires a blood meal from a mammalian host in order to produce eggs. Upwards of 200 eggs per female are laid in fresh water, and the eggs undergo four life stages: egg, larva, pupa, and adult. The egg, larva, and pupa stages are all aquatic, and ambient temperature determines the speed of progression from egg to adult, which can be anywhere from 5 to 14 days. It takes 10 to 18 days after the female mosquito feeds on an infected human for sporozoites to develop and to reach the salivary

glands. After this time, the mosquito can take a blood meal from another human host and inject sporozoites to continue the cycle of infection. These growth and survival requirements for malaria transmission are important determinants in the prevalence of malaria in a given geographic region. During a drought, malaria transmission can decrease drastically in an area which typically has hyperendemic malaria transmission, as was observed in Southern Zambia between 2004 and 2005 (Kent 2007).

The anopheline host is not immune to the effects of malaria infection.

Plasmodium can decrease host life expectancy depending on both the intensity of infection as well as on the age of the mosquito when it becomes infected (Dawes 2009).

Anopheles mosquitoes have evolved resistance mechanisms against the malaria parasite to lessen this burden. The mosquito can produce an immune response that can be modulated by the midgut microbiome and that can interfere with Plasmodium development (Cirimotich 2011). Anopheline mosquitoes also have a natural immune response that causes melanization of oocysts. Melanization occurs when the mosquito's immune system encapsulates foreign objects in order to isolate and to destroy them.

Despite these adaptations to combat infection, anopheline mosquitoes remain viable vectors for Plasmodium.

MOSQUITO MICROBIOTA

Anopheline mosquitoes have a diverse community of microbes inhabiting their midguts (Rani 2009, Wang 2011). The bacteria of the midgut have been shown to change from the larva life stage to the adult, presumably by the shedding of the meconium, or

lining of the midgut, during the transformation (Moll 2001). During the larval stage of life, the mosquito microbiota consist largely of photosynthetic Cyanobacteria (Wang

2011). The shedding of the meconium after emergence partially sterilizes the midgut of the larva. The midgut will be repopulated with new species when the adult mosquito feeds on plant nectar that contains bacteria. The reestablished population of the adult mosquito midgut is very different and consists primarily of Proteobacteria and

Bacteroidetes with the predominant taxa being Enterobacteriaceae and

Flavobacteriaceae (Wang 2011). Pantoea agglomerans (previously known as

Enterobacter agglomerans), a Gram-negative, γ-proteobacterium, is a particular midgut symbiont of interest (Gavini 1989). Pantoea agglomerans is a common bacterium found in the midgut of Anopheles and Aedes mosquitoes, and it is easily cultured and manipulated in the lab (Moro 2013, Straif 1998).

Other important anopheline midgut symbionts include the Asaia sp. bacteria.

Asaia are Gram-negative, α-proteobacteria which been isolated from flower nectar

(Yamada 2000, Chouaia 2010). Asaia represent a large proportion of the midgut bacterial population, in some isolates encompassing 60% of all bacteria as identified by

454 sequencing (Boissiere 2012). Asaia has been identified in all species of Anopheles mosquitoes, and it seems to be an integral part of the host's midgut microbiome and necessary for the health of the mosquito host (Mitraka 2013). In addition, Asaia contribute to overall health during larval development (Mitraka 2013). Asaia bacteria within the midgut of anopheline mosquito larvae increase the transcription of certain host genes that allow the larvae to develop more rapidly (Mitraka 2013). These aspects of

Asaia's microbial ecology make this bacterium a prime candidate for paratransgenesis

(Favia 2007, Damiani 2010).

TRANSGENESIS AND PARATRANSGENESIS

Previous transmission-blocking approaches in mosquitoes have used direct transgenesis of the anopheline mosquito host of Plasmodium to make the insect produce antimalarial proteins (Ito 2002). Ito et al. used the piggyBac transposon system to insert the gene encoding the SM1 peptide that inhibits P. berghei invasion of the midgut epithelium. This gene was inserted under control of the Anopheles gambiae carboxypeptidase promoter, which is highly activated by a blood meal in the mosquito

(Ito 2002). The results found by Ito et al. showed that transgenic mosquitoes produced in this way would have greatly enhanced resistance to infection by P. berghei malaria. A study of the fitness of transgenic mosquitoes expressing antimalarial effector genes determined that lab-reared transgenic mosquitoes that were fed infected blood had a fitness advantage over wild type mosquitoes fed the same infected blood (Marrelli 2006).

Marrelli et al. concluded that the fitness advantage perceived in the lab setting would not translate to the field due to the much lower infection rate of wild mosquitoes (Taye

2006). Some other mechanism would be required to cause a transgene to spread through the wild mosquito population and become established permanently.

Gene drive mechanisms have been proposed that can cause a gene to be selected for in a population; these mechanisms use naturally occurring selfish genetic elements that can increase in frequency within a population (Sinkins 2006). Transposons could be

used to drive genes through mosquito populations and deliver the genes necessary to make the population refractory to infection; Arensburger et al. identified an active transposon called Herves in Anopheles gambiae, the primary vector of P. falciparum that could be used to drive antimalarial genes into a population (Arensburger 2005). An approach such as this would not harm the mosquito population but make them less suitable hosts for Plasmodium. Another mechanism that forces a gene to increase in frequency is underdominance; mosquitoes that contain a set of genes on different chromosomes that each encode a toxin gene and a trans-acting repressor for the toxin gene on the opposite chromosome would necessitate that offspring have a copy of each to survive, or they will produce the toxin and die. Any gene can be inserted into a construct such as this, and it will be selected for along with it (Davis 2001). This setup will allow the transgenic mosquitoes to mate with one another and produce homozygous offspring, but if they mate with wild mosquitoes, the offspring will die therefore increasing the transgenic genotype over time. A caveat to this approach is necessity of an antibiotic resistance gene, which would likely never gain approval for release in the wild.

Some other mechanisms seek to decrease the population of the vector mosquito by delivering dominant lethal genes into the population by a technique called the release of insects carrying a dominant lethal (RIDL); an example of this is the dominant flightless female gene which is only expressed in female mosquitoes (Marinotti 2013).

Males with the flightless gene are not affected, therefore they can be raised and released into the wild to mate, and any female offspring they produce will be flightless and die causing a population crash (Marinotti 2013). The generation of transgenic mosquitoes for

malaria control is time intensive, and replacing the natural population of vector mosquitoes in the wild has an additional obstacle associated with it, driving the gene into multiple populations. Malaria is not transmitted by a single mosquito species, and there are over 100 species that can carry Plasmodium (Raghavendra 2011). Even within a single vector species, there can be distinct sexually-isolated molecular types that do not interbreed, as is the case with the Anopheles gambiae molecular forms (Favia 1997). For these reasons, transgenic mosquitoes would be extremely difficult to utilize in field applications and to guarantee that all modes of transmission have been targeted.

A simpler, alternative approach to generating transgenic mosquitoes would be to produce paratransgenic bacteria, which are capable both of inhabiting the midgut of diverse mosquito species and of rapidly spreading among wild mosquito populations

(Wang 2013). Paratransgenesis is the modification of symbiotic microorganisms residing within a host in order to alter that host's phenotype (Durvasula 2008). A ubiquitous anopheline midgut symbiont would present a single target for modification and be much easier to utilize than the numerous species of mosquito hosts (Wang 2013). Furthermore, if this paratransgenic bacterial strain expressed a protein that targets all five malaria- causing Plasmodium species, then that single paratransgenic strain could be utilized worldwide against any species of Plasmodium and in any anopheline vector.

Paratransgenesis has previously been used to combat human diseases. The first demonstration of this technique was the use of paratransgenic Rhodococcus rhodnii in the triatomine bug, Rhodnius prolixus, to combat Chagas disease (Durvasula 1997). R. rhodnii were modified to secrete Cecropin A, an antimicrobial peptide that is lethal to

Trypanosoma cruzi, the parasite that causes Chagas disease (Hurwitz 2011). Durvasula et al. reported reduction or elimination of T. cruzi in R. prolixus bugs that had been inoculated with the paratransgenic bacteria. They further identified a mechanism to spread bacteria to R. prolixus in the wild by allowing the insect to ingest the bacteria mixed in with artificial feces, simulating their natural route of coprophagous symbiote acquisition (Durvasula 1997).

Five other notable studies have also used paratransgenesis to fight disease. One study worked to combat African sleeping sickness by utilizing the tsetse fly symbiont,

Sodalis glossinidius. S. glossinidius was modified to secrete nanobodies which target the variant surface glycoprotein of Trypanosoma bruci, the cause of African sleeping sickness, by using the pelB secretion signal (De Vooght 2012). A second study targeted

HIV by using modified Lactobacillus jensenii to secrete functional human CD4 glycoprotein, which inhibits HIV entry into host T-cells (Chang 2003). A third study targeted malaria by engineering modified Pantoea agglomerans to secrete the antimalarial peptide SM1, the anti-Pbs21 single chain antibody, and the PLA2 enzyme into the midgut of the Anopheles host of Plasmodium. This was accomplished via two secretion pathways, by using the pelB leader peptide and the hemolysin secretion system

(Bisi 2011). Two additional studies also targeted malaria: an Anopheles densonucleovirus was discovered and modified to produce green fluorescent protein within the Anopheles host to demonstrate its potential for delivery of antimalarial effectors (Ren 2008); and the fungus Metarhizium anisopliae, a natural pathogen of mosquitoes, was modified to

produce the antimalarial peptide SM1 and the antimicrobial scorpine and proved capable of reducing sporozoite counts by 98% (Fang 2012).

These previous studies have been proofs of concept of using paratransgenic organisms to reduce disease transmission. In order to create strains of paratransgenic bacteria that can be applied in the real world, however, certain hurdles must be overcome to ensure the organism is suitable for release. A paratransgenic organism intended to combat malaria must be prevalent across anopheline species and must have a suitable microbial ecology that allows it to remain in the mosquito population for the long term.

One such species, Asaia sp. SF2.1, has already been isolated (Favia 2007). This Gram- negative, acetic acid bacterium is associated with many tissues of the mosquito body; it can be found inhabiting the reproductive organs, the salivary glands, and the midgut

(Favia 2007). All three of these organs are important for paratransgenic malaria intervention. Asaia sp. SF2.1 has also been demonstrated to be transmitted from female mosquitoes to their progeny by a process termed "egg smearing," in which the mother paints bacteria on the surface of eggs, and the bacteria passed on survive until adulthood

(Favia 2007, Damiani 2008). These bacteria can also be passed from male to female during copulation since they inhabit the reproductive organs of the mosquito host

(Damiani 2008).

PROTEIN SECRETION FROM GRAM-NEGATIVE BACTERIA

A challenge of creating paratransgenic bacteria is the identification of a protein secretion system, which will allow the bacteria to deliver effector proteins into the

mosquito midgut environment. Effectors must be secreted in order to make contact with

Plasmodium and interfere with its development. One way to accomplish this is by fusing an effector protein to a signal sequence that directs it for export through a preexisting secretion system of the host bacteria.

Gram-negative bacteria possess diverse protein transport systems which have evolved to move proteins across two lipid membranes and through the protective peptidoglycan layer surrounding their cells. Protein production by the ribosome takes place in the cytosol of the bacterial cell. Proteins that are needed in the periplasm, that are inserted into either membrane, that are part of the protective peptidoglycan layer, or that are exported from the cell must be translocated through either one or two cell membranes depending on their localization. There are currently nine recognized secretion systems that have been identified in Gram-negative bacteria to accomplish this; however, the

Type I and Type II secretion pathways are the most useful for the secretion of heterologous proteins (Mergulhao 2005).

Type I secretion involves the export of folded proteins directly from the cytosol to the environment. This is accomplished by a secretory complex consisting of three proteins that form a channel linking the outer and inner membranes of the cell, allowing proteins to pass through the channel without stopping in the periplasm. These proteins include an ABC protein within the inner membrane, which facilitates protein recognition and initiates transport, a membrane fusion protein that spans the inner and outer membrane, providing a channel for direct secretion, and an outer membrane protein that allows passage of the translocated protein through the outer membrane (Kudva 2013).

The first identified Type I secretion system was the hemolysin secretion system of

E. coli. This system is used by some pathogenic E. coli strains to secrete the alpha- hemolysin toxin, a 107 kDa protein. This protein inserts into the membrane of a host cell, causing membrane disruption and cell lysis. The hemolysin secretion complex consists of three proteins, HemolysinB (HlyB), HemolysinD (HlyD), and TolC, which mediate the export of the HemolysinA (HlyA) toxin (Figure 1.2). The HlyB protein forms the inner membrane pore which recognizes and initiates secretion of HlyA. The C-terminal portion of the HlyA protein interacts with HlyB to direct it for secretion (Zhang 1993). HlyB is part of the family of ATP-binding cassette (ABC) transporters, and it couples ATP hydrolysis with protein export. HlyD is the membrane fusion protein in the hemolysin secretion apparatus; it forms a trimer that connects HlyB in the inner membrane to TolC in the outer membrane to facilitate direct transfer of the secreted protein (Gentschev

2002). The TolC protein also forms a trimer to produce the outer membrane pore through which directed HlyA exits the cell. TolC is a general pore complex found across a wide range of Gram-negative bacteria, and it is not specific to this secretion complex (Wiener

2000).

The hemolysin secretion system has previously been adapted for the secretion of heterologous proteins. It has been used in E. coli to secrete scFv antibodies and to allow the formation of disulphide bonds during transport through the periplasm (Fernandez

2001). Part of the HlyA gene encoding the C-terminal domain that directs secretion was fused to an scFv gene to create a fusion protein, and the scFv proteins exported by the

Type I hemolysin system were found to form disulphide bonds while traversing the

periplasm (Fernandez 2001). This is useful for the secretion of effector scFvs, since these proteins require disulphide bridges between cysteine residues to maintain protein conformation and function (Schouten 2002). Hemolysin secretion has been utilized to secrete active scFv and other effector proteins that inhibit Plasmodium, as well. The phospholipase A2 enzyme and an anti-Pbs21 scFv, both antimalarial effectors, were successfully secreted in Pantoea agglomerans via fusion to the HlyA C-terminal domain

(Bisi 2011). More recent experiments have demonstrated the activity of these effectors and others as secreted by P. agglomerans in vivo against P. berghei and P. falciparum within the midgut of Anopheles mosquitoes (Wang 2012). Interestingly, the HlyA secretion system has also been used on an industrial scale for the production and extracellular accumulation of molecules such as polyhydroxyalkanoates, which are non- proteinaceous polymers (Rahman 2013). These results demonstrate the flexiblity of the secretion system for its potential use with a wide range of effector molecules.

In contrast to Type I secretion, Type II secretion pathways do not directly export proteins through a channel between membranes. These secretion pathways use specific translocases within the inner membrane to move proteins into the periplasm before they are exported by a separate mechanism. Two inner membrane transporters handle the majority of membrane traffic in Gram-negative bacteria (Figure 1.2): (1) the general secretory (Sec) translocon, which secretes the majority of exported proteins and cytosolic membrane-inserted proteins (Natale 2008), and (2) the twin-arginine translocation (Tat) channel, which transports specific proteins that are incompatible with the Sec pathway,

such as assembled protein complexes and individual proteins that require folding to take place in the cytosol (Lee 2006).

Type II secretion by the Sec-dependent pathway is a common mechanism found in all bacteria and is coupled with ATP hydrolysis. This secretion pathway is also essential, unlike the TolC-dependant pathway which can be disrupted without causing lethality (Forestal 2006). The Sec translocon transports proteins across the cytosolic membrane in the general secretion pathway and is responsible for the majority of protein secretion in bacteria. The translocon is composed of secYEG heterotetramers which form a transmembrane hydrophilic pore that regulates and facilitates protein transport (Saier

2006). Proteins are directed to this pore complex by leader sequences that consist of a positively charged N-terminal domain, a hydrophobic middle region, and a polar C- terminal domain followed by a signal peptidase cleavage site. There are many variations of the signal peptide, and those that are very hydrophobic are recognized by the signal recognition particle (SRP) protein to be directed to the Sec pore complex (Zhou 2014).

The Type II PelB leader sequence from the pectate lyase gene of Erwinia carotovora, a Gram-negative plant pathogen, has been demonstrated to be able to direct secretion of heterologous proteins by a Sec-dependent pathway in E. coli and P. agglomerans (Bisi 2011). The PelB leader has also been used successfully with scFv antibody secretion, and it is the leader used in the Tomlinson I + J human scFv library for the selection of scFvs binding to antigens in a selective screen (Winter 1994). This leader peptide has great potential for use in targeted interventions due to the possibility of using specific antigen binding scFvs against pathogens.

Type II Tat-dependent protein secretion requires a complex of three proteins in the inner membrane: TatA, TatB, and TatC which function together to recognize and transport proteins with specific N-terminal signal sequences. These signal sequences are similar to those recognized by the Sec pathway, with a positively charged N-terminal domain, a hydrophobic middle domain, and a polar C-terminal domain; however, they have a much longer N-terminal domain which contains a pair of conserved arginine residues, thus giving the system its name. Proteins secreted by this pathway are fully folded in the cytosol before passage through the Tat translocon. Protein transport via the

Tat pathway does not require ATP hydrolysis, but rather it is driven by the proton motive force (Saier 2006). The Tat secretion pathway has been used for the large scale production of recombinant proteins, as demonstrated by the use of the TorA signal peptide and TatAdAc system of Bacillus subtilis in E. coli to secrete GFP into culture medium (Albiniak 2013) and the use of the B. subtilis TatAyAc to secrete methyl parathion hydrolase directed by the YwbN signal peptide (Liu 2014).

The research described here focused both on discovering protein secretion signals for use in Asaia sp. bacteria and on using these secretion signals to transport antimalarial effectors outside the cell for direct delivery into the mosquito midgut.

Figure 1.1. The Plasmodium life cycle. The Plasmodium life cycle is complex, and requires two hosts, both a human and a mosquito. When a human is bitten by an infected mosquito seeking a blood meal, it injects sporozoites into the blood stream which invade liver cells (Part A). Within the liver cells, the sporozites divide and produce blood-stage parasites called merozoites. These are released into the bloodstream, where they invade red blood cells and continue to reproduce asexually (Part B). These cells burst open releasing more mereozoites and perpetuating the cycle. A small fraction of these asexually reproducing cells instead make gametes that remain dormant until a new mosquito takes them up in a blood meal (Part C). Male and female gametocytes from the ingested blood meal fertilize within the midgut and develop into an invasive ookinete that is capable of penetrating the midgut epithelium of the host. (public domain Figure provided by CDC – DPDx/ Alexander J. da Silva, PhD, Melanie Moser)

Figure 1.2. Secretion systems of Gram-negative bacteria. Type I secretion systems, such as the hemolysin secretion pathway, transport folded proteins through both membranes without stopping in the periplasm. The hemolysin secretion system recognizes the C-terminal domain of hemolysin A to direct proteins for export. Type II secretion systems translocate unfolded (Sec) or folded (Tat) proteins into the periplasm, after which they are exported fully from the cell. Type II secretion systems export proteins that are recognized by short N-terminal peptide leader sequences that are cleaved off in the periplasm prior to the protein exiting the cell.

Chapter 2

Production of single-chain variable fragment antibodies and secretion from bacteria

ABSTRACT

To date, at least 30 antimalarial effector peptides and proteins have been discovered or produced that interfere with the transmission of malaria. Such effector proteins are capable of interfering with the development of the Plasmodium parasite within the mosquito host. For example, three single-chain antibodies produced by hybridoma cell lines are known to bind Plasmodium falciparum gamete or ookinete surface proteins and to cause a disruption of fertilization or invasion of host tissues within the mosquito midgut (Barr 1991, Roeffen 1995, 2001). In this study, antibody variable regions from these three hybridoma lines were converted into single-chain antibody

(scFv) format that can be expressed from bacteria (Fernandez 2000).

These three scFv proteins are designed to bind to P. falciparum surface proteins

Pfs25, Pfs48/45, and Pfs230 (Barr 1991, Roeffen 1995, 2001). As described in this work, scFv genes were cloned in-frame with various secretion signals from Escherichia coli,

Gluconobacter oxydans, and Gluconacetobacter diazotrophicus, and expression plasmids with these gene constructs were transformed into Pantoea agglomerans and Asaia SF2.1.

The bacteria expressing these secretion constructs displayed unhealthy phenotypes and

had growth defects. Therefore, the scFv effector genes require a novel secretion system to allow export of the proteins from the bacteria without causing these growth defects.

BACKGROUND

Previously, most experiments involving P. falciparum transmission-blocking proteins have observed transmission-blocking effects by feeding purified protein to mosquitoes along with an infective blood meal (Barr 1991, Roeffen 1995, 2001). While this technique has led to the identification of many useful midgut transmission-blocking molecules, no method has been devised to adequately deliver the protein to wild mosquitoes in the field.

Alternatively, transgenic mosquitoes expressing antimalarial proteins can be produced to inhibit P. falciparum invasion (Riehle 2007). This technique, however, imposes a large metabolic load on the mosquito, and replacement of the natural mosquito population with these transgenic mosquitoes cannot be easily achieved. Gene drive mechanisms have been proposed to spread the transmission-blocking genes into wild populations (Huang 2007, Akbari 2013); but this approach may require an extended period of time, and the parasite would likely evolve resistance to the effector molecule, therefore necessitating that the entire process be repeated using a new drive mechanism.

Genetic manipulation of the mosquito itself may get more complicated over time, since new transmission blocking genes must be incorporated into the genome.

Effectors capable of being secreted from bacteria can be designed which will both remain in the mosquito without direct intervention and continue to inhibit the parasite

from generation to generation. Rather than feeding an effector molecule to mosquitoes in the lab or creating transgenic mosquitoes that produce the effector, bacteria will be fed to mosquitoes in the wild and persist in the population, thus providing an unlimited supply of the transmission-blocking effector. In addition to the ease of deploying such bacteria, they could also be genetically modified to contain different effector proteins and be re- released if the parasite ever evolves resistance to the current strain. The experiments in this chapter demonstrate the cloning of anti-Plasmodium falciparum single-chain antibodies and their attempted expression from bacterial vectors, as well as their subsequent secretion utilizing a number of cloned secretion signals.

Anti-Plasmodium falciparum antibodies

P. falciparum proteins Pfs25, Pfs48/45, and Pfs230 exist on the surface of gametocytes and ookinetes and are necessary for transmission through the midgut epithelium of the mosquito host (Rener 1983). These surface proteins are necessary for the parasite to either bring the male and female gametocytes together or to invade the midgut epithelium. Antibodies or other effector proteins which prevent the function of these surface proteins can inhibit the different stages of host reproduction or invasion.

Mouse-derived monoclonal antibodies have been proven to block transmission when produced by hybridoma cells and directly fed to mosquitoes with an infective blood meal (Barr 1991, Roeffen 1995, 2001). The three hybridoma lines that produce these antibodies are MRA-315, MRA-316, and MRA-878 from the MR4 Malaria Research

Center (www.mr4.org). These antibodies target Plasmodium proteins Pfs25, Pfs48/45, and Pfs230, respectively (Barr 1991, Rener 1983, Quakyi 1987).

Previous use of these monoclonal antibodies has demonstrated inhibition via purified antibody protein fed to mosquitoes in infective blood meals (Barr 1991, Saxena

2007, Eksi 2006). All of these antibodies target specific proteins that are only expressed or displayed on the surface of the gamete, zygote, or ookinete stages of the Plasmodium life cycle. Since these proteins are not exposed to the human immune system, they do not normally produce an immune response in the host. Injection of these proteins as a vaccine, however, can produce transmission-blocking immunity in a person (Carter

2001). A person vaccinated in this way produces IgG antibodies against the Plasmodium surface proteins, and these antibodies are able to bind to the parasite only after they are taken up during a mosquito blood meal. This immunity prevents Plasmodium from infecting mosquitoes that feed on the vaccinated individual.

Among transmission-blocking candidates, Pfs25 is the most widely utilized due to its small size, which makes it easier to express heterologously for vaccine production.

Monoclonal antibodies against this protein have long been known to block transmission of P. falciparum (Barr 1991). Pfs25 is a 25 kDa protein expressed at the surface of zygote and ookinete forms of P. falciparum as they develop in the host mosquito's midgut (Barr

1991). Pfs25 plays an important role in attachment of the parasite to the mosquito; it interacts with the midgut basement membrane to attach the parasite to the surface. This binding is an essential step in the transformation from ookinete to oocyst (Saxena 2007).

This protein has been expressed in a variety of organisms for use in transmission-

blocking vaccines and in the production of monoclonal antibodies, including the yeast

Pichia pastoris and eukaryotic green microalgae Chlamydomonas reinhardtii (Barr 1991,

Gregory 2012).

Pfs48/45 is a protein expressed on the surface of female macrogametes, and it plays an important role in parasite fertilization (Outchkourov 2008). The MRA316 hybridoma line produces monoclonal antibodies against this surface protein which are known to inhibit P. falciparum transmission in vivo by preventing fertilization and zygote formation (Rener 1983).

Pfs230 is a protein expressed at the surface of the male gametocyte, and it mediates the binding of the exflagellating male gamete to human red blood cells. The function of this binding is to create an exflagellation center, a cluster consisting of parasite gametes and host erythrocytes which is needed for proper fertilization and ookinete formation (Eksi 2006). Transmission-blocking activity of monoclonal antibodies against specific domains of this 230kDa protein have been shown (Quakyi 1987).

Unfortunately, the whole protein is too large to express in bacteria, and only fragments of it have been produced and used separately for use in immunizations. Active monoclonal antibodies against the Pfs230 antibody are produced by the MRA878 hybridoma line

(Quakyi 1987).

Prokaryotic expression of scFv antibodies

Hybridoma lines that produce monoclonal antibodies of a know function can be powerful tools in the lab and in medicine. The IgG proteins that are produced by the cell

line can be purified and used as molecular detection tools or as treatment for specific disease such as non-Hodgkin lymphoma which can be treated with Rituximab, a monoclonal antibody that targets B-cells for destruction (Maloney 1997). For large-scale production of antibodies, useful IgG proteins can be converted into a single-chain variable fragment (scFv) format that is suitable for expression in bacteria and that can be cheaply produced (Bayly 2002). The basic scFv format antibody retains only the antigen- binding variable regions from the heavy and light chain proteins of the IgG complex which have been recombined into a single protein as shown in Figure 2.1 B. The scFv protein is capable of being secreted from bacteria (Better 1988). Given that there are antimalarial antibodies that can block transmission of Plasmodium, this technique could be used to make paratransgenic bacteria that produce scFv proteins engineered from those antibodies and that could secrete the proteins directly into the mosquito midgut.

Selecting suitable bacteria for paratransgenesis

Effector secretion constructs were produced in expression vectors capable of replicating in E. coli, Pantoea agglomerans, and Asaia bogorensis. E. coli was selected because it is an easy-to-use host strain, which is useful for manipulation of plasmids and for laboratory testing of expression effectiveness P. agglomerans and A. bogorensis are both good candidates for paratransgenic approaches to malaria control, as both commonly inhabit the mosquito midgut (Lindh 2005, Favia 2007). The Gram-negative, α- proteobacteria A. bogorensis is a particularly good candidate for transmission blocking, as it transfers vertically from mother to progeny, so it would produce a longer-lasting

effect in the mosquito population (Favia 2008). Asaia was detected in Anopheles stephensi salivary glands, which is rather unusual; most microbes that compose an organism's microbiome inhabit the digestive tract. It may be possible to take advantage of this fact and to secrete proteins in the salivary glands which may prevent passage of P. falciparum sporozoites into the salivary glands or interfere with invasion of the human host.

Transformation of An. stephensi mosquitoes with transgenic Asaia has already been shown to work by Favia et al., by feeding a GFP-expressing strain of Asaia to An. stephensi (Favia 2007). Fluorescent bacteria were detected in a large portion of fed mosquitoes, and bacteria were stably detected throughout the mosquitoes lifespan (Favia

2007).

Molecular tools for bacterial protein expression

The origin of replication of plasmid pBBR1, originally from a cryptic Bordetella bronchiseptica plasmid, has been demonstrated to replicate in a wide range of Gram- negative bacteria (Kovach 1995). pBBR1MCS-2, a plasmid containing this replication origin, was created as a cloning platform for the expression of genes in these diverse bacteria (Kovach 1995). Previously, similar plasmids with the pBBR1 replication origin have been modified for the cloning and expression of fluorescent proteins in Asaia sp. bacteria (Favia 2007). The pBBR1MCS-2 plasmid contains a kanamycin selective marker, the neomycin phosphotransferase II gene (nptII). This is very useful because kanamycin is one of the few antibiotics that Asaia is known to be susceptible to. This

plasmid contains the lacZ alpha gene with a multiple cloning site (MCS) for blue-white screening. This was modified to contain an MCS compatible with the genes that have been inserted and to allow the promoter to be easily changed. The lac promoter is not known to function in Asaia, but the nptII promoter does function. This is a constitutive promoter that has been demonstrated to have a high level of protein expression in transformed Asaia (Favia 2007). The expression of heterologous proteins can have a high fitness cost to bacteria with a constitutive promoter. Therefore, it may be necessary to change this promoter to an inducible promoter that is controllable in Asaia, or to a weaker constitutive promoter if the bacteria cannot survive.

Combining scFv effectors

The activity of an scFv effector gene can be amplified by combining two scFv binding domains in one protein (Figure 2.1 D). The resulting fusion protein, or diabody, is produced from heavy and light chain immunoglobulins with a short, inflexible linker peptide between the two. These proteins do not fold to join the two antigen-binding domains together, as in a standard scFv; instead, the heavy and light chains dimerize and form one protein complex with two binding sites. The result is that the two antigen- binding domains end up facing directly opposite from one another. A diabody has the advantage of increasing the avidity of the protein for its antigen (Fernandez 2004).

Some antibodies, such as MRA-316 and MRA-315, act by binding and neutralizing the active site of the antigen; while other antibodies require complement protein binding to target the pathogen for an immune response. The MRA-878 antibody,

which binds Pfs230, interferes with transmission by complement-mediated cell lysis

(Healer 1997, Read 1994). This antibody interacts with complement proteins in human serum, so it requires either a human antibody constant region to interact with complement or some alternative. This problem can be solved by designing diabodies with one binding domain for the Pfs230 antigen and one for human IgG. This technique has been explored in the lab of Dr. Greg Winter in which bispecific diabodies were produced (Kontermann

1997). Their complement-recruiting antibody domain effectively binds human C1q, a subunit of the C1 complex of the classical complement pathway, and produces efficient cell lysis. For non-complement-mediated antibodies, their transmission-blocking activity may also be increased by the addition of a complement-binding domain. This would target them for immune response in addition to their normal neutralizing activity.

An alternative to adding a C1q-binding scFv domain is adding a human constant domain to the construct. Such di-diabodies have previously been created: they consist of two diabodies with immunoglobulin G CH3 constant domains associated with them (Lu

2003). The resulting molecule is tetravalent and has the normal complement-binding domain of a human antibody (Figure 2.2). Constructs like these could be very useful for future antimalarial research. Divalent diabodies could be produced with two different anti-Plasmodium binding domains combined in the same structure, and this approach should exhibit both a greater avidity, due to its four binding domains,as well as an increased affinity for Plasmodium, due to the binding of two different antigens.

Secretion of single-chain variable fragment antibodies

No single secretion system has been proven to work for all protein constructs, and attaining a working secretion system for any given protein requires a trial-and-error approach (Choi 2004). It is not known which secretion systems will function in Asaia.

Some secretion systems move proteins by translocating the denatured amino acid chain linearly though the general secretion (Sec pathway) pore complex, while others translocate fully folded protein directly into the periplasm through the twin-arginine translocase (Tat pathway). Since these systems require the protein to fold in different environments, specifically the cytosol or the periplasmic space, the proteins exported by these pathways may behave differently.

A common secretion signal used in scFv secretion is the pelB signal (Winter

MRC laboratory). The pelB signal directs proteins through a Type II secretion pathway which exports protein using the Sec pore complex into the periplasm, where it can refold and form disulphide bonds in the oxidizing environment of the periplasmic space before export from the cell by poorly understood mechanisms (Saier 2006). The pelB signal peptide has been demonstrated to export fully functional scFv molecules from recombinant bacterial strains (Bisi 2011).

MATERIALS AND METHODS

Media and antibiotics

Top10 F' E. coli cells were used for cloning and plasmid propagation. The Top10

F' cells were cultured in standard Luria Bertani (LB) broth (10 g Tryptone, 5 g NaCl, 5 g

yeast extract, in a final volume of 1 L distilled water) or LB agar (LB broth plus 15 g/L agar). For selection of plasmids with kanamycin, media was supplemented with 30 μg/ml kanamycin; likewise, gentamycin was used at 50 μg/ml, and ampicillin was used at 100

μg/ml. All E. coli cultures were grown at 37 °C, with agitation for liquid broth cultures.

Pantoea agglomerans was cultured in the same media as E. coli.

Asaia sp. bacteria were cultured in Mannitol broth (5 g yeast extract, 3 g peptone,

25 g mannitol, in a final volume of 1 L distilled water) or Mannitol agar (Mannitol broth plus 15 g agar). Media was adjusted to pH 6.5 before sterilization. For selection of plasmids with kanamycin, media was supplemented with 120 μg/ml kanamycin. All

Asaia cultures were grown at 30 °C, with agitation for liquid broth cultures.

Growth of hybridoma cell lines

The hybridoma lines which produce transmission-blocking antibodies were obtained from MR4 Malaria Research Institute (MR4, ATCC, Manassas, VA). They were obtained through the MR4 as part of the BEI Resources Repository, NIAID, NIH, deposited by LH Miller, A Saul. Cells were grown in vented T-flasks in a 5% CO2 incubator at 37 °C. Growth media used was Advanced MEM media (Gibco, Thermo

Fisher Scientific, Waltham, MA #12492) with 10% heat-inactivated fetal bovine serum

(ATCC, Manassas, VA 30-2021), 0.2% sodium bicarbonate, 100 U/ml penicillin, 0.1 mg/ml streptomycin, 10 μl of 1M L-glutamine, and 50 μM 2-mercaptoethanol. Cells were passed when near confluency at a 1:3 rate into new T-flasks. Cells were stored by adding

100 μl of sterile DMSO to 900 μl of resuspended confluent cell culture and by slow

freezing using a Nalgene cryo freezing container (Nalgene, Rochester, NY #5100-0001) that cools at 1 °C per min in a -80 °C freezer. Cells were placed in liquid nitrogen for long term-storage.

Hybridoma line RNA extraction and reverse-transcription

A total of 5x106 cells were harvested from each hybridoma line, and RNA was extracted with TRI Reagent using the company protocol for animal cells (Molecular

Research Center Inc., Cincinnati, OH http://mrcgene.com/?s=tri+reagent). This whole- cell RNA was purified on a poly-dT column that isolated only the mRNA present in the samples by binding their polyA tails (polyA mRNA Isolation Kit, New England Biolabs,

Ipswich, MA, #S1560S, https://www.neb.com/protocols/1/01/01/isolation-of-mrna- s1560). This step eliminated the large amounts of ribosomal RNA present in whole-cell

RNA extracts. The purified mRNA was reverse transcribed with a cDNA synthesis kit following the standard protocol (Fermentas, Thermo Fisher Scientific, Waltham, MA

#K1611, http://www.thermoscientificbio.com/uploadedFiles/Resources/coa_k1611.pdf).

Amplification of H and L chain variable regions from hybridoma cDNA

Three sets of degenerate primers designed for mouse antibody variable regions were used to amplify the antigen-binding domains of the heavy and light chain of each antibody via PCR (Barbas 2001). The protocols laid out in this text were followed, except with reduced volumes for each reaction of 25 μl. The goal was not to create a phage display library but to simply isolate the unique clone that is produced by each hybridoma

line. PCR was performed using Phusion polymerase (New England Biolabs, Ipswich,

MA, #M0530). The PCR primers in these reactions were identical to the published primers, with one modification which was the addition of a NotI restriction digestion site to five of the primers (Table 2.2). The resulting fragments were size-separated on 1% agarose gel, extracted using a Zymoclean Gel DNA Recovery Kit (Zymo Research,

Irvine, CA #D4002), and used as templates in an overlap extension PCR (Figure 2.3).

This PCR reaction connected the antibody gene fragments by a DNA sequence encoding a flexible linker, which should allow the heavy and light chain protein fragments to fold into their proper orientation and align their binding domains as in a standard antibody.

These constructs were created in two forms, with both long and short linkers between the domains (Figure 2.4).

The proteins produced with these different linkers assemble into alternative formats. Those with a long linker will be able to fold back on themselves, aligning the heavy and light chain variable domains, and produce a single antibody binding domain

(Figure 2.1). Those with a short linker will be more rigid, and will require two copies of the protein which will dimerize, forming a diabody. This is a divalent antibody fragment which has two antibody binding domains, increasing its avidity.

Cloning svFv genes into expression vectors

Each overlap extension PCR product was cloned into the pDB48 plasmid (Bisi

2011) by restriction digestion and ligation. The PCR products and pDB48 plasmid were digested to completion with the AscI and PacI restriction enzymes, and the plasmid was

treated with calf intestinal phophatase. The PCR products were ligated into the linearized plasmid using T4 DNA ligase at 16 °C overnight. The ligated DNA was transformed into

Top10 F' E. coli cells and selected on LB media containing 50 μg/ml gentamycin. These insertions placed the scFv genes in-frame with the pelB leader sequence at the N-terminal end and with the 6-His and Myc epitope tags at the C-terminal end. Clones isolated from this selection were verified by sequencing to ensure that no mutations were introduced.

Gene design is shown in Figure 2.5.

TA cloning antibody variable fragments and sequencing

The PCR products produced using degenerate primers to amplify the variable regions of each antibody and overlap PCR were TA cloned into the pCR2.1-TOPO vector using a standard kit and protocol (Invitrogen Thermo Fisher Scientific, Waltham, MA

#45-0641). The cloning reactions were selected in Top10 F' E. coli on LB media supplemented with 100 μg/ml ampicillin and 100 μg/ml X-gal.

The TA cloned antibody variable region fragments were sequenced using the vector primers in the pCR2.1-TOPO plasmid, M13 forward (-20) and M13 reverse.

Sequences were aligned using the DNASTAR program SeqMan to assemble the full gene fragments.

Gene optimization for prokaryotic expression

Some genes can be inserted in bacterial expression vectors and heterologous production can be achieved without any further alteration of the sequence. Since the scFv

constructs produced in that way did not express and secrete functional antibodies, the scFv gene sequences were modified to allow them to translate more efficiently in the heterologous hosts, E. coli, P. agglomerans, and A. bogorensis.

To increase efficiency of a gene expressed in a heterologous host, the codons that determine the amino acid sequence were changed to better suit the codon usage of the heterologous host. The gene sequence of the hybridoma antibody genes were optimized for expression by changing the nucleotide sequence of each codon to the most commonly used codon for that amino acid in E. coli. This was achieved by selecting the codon usage table for E. coli into the Graphical Codon Usage Analyzer (http://gcua.schoedl.de) and by using the gene analyzer to change the codons of each gene sequence to the most frequently-used codons from the E. coli usage table. scFv gene sequences are shown in

Figures 2.6 through 2.9.

The anti-Pfs48/45 scFv gene was codon harmonized. Codon harmonization is the process of calculating the percent usage of each particular codon in the gene's original species and changing the codons in the harmonized gene to a matching percent usage codon in the heterologous host species (Angov 2008, Figure 2.10). This allows a protein to be translated at the same rate of speed as if it had naturally occurred. Translation speed can have an effect on protein folding, as regions of slow translation have been demonstrated to permit the ribosome to pause, thus allowing a portion of the protein to fold prior to continuing (Thanaraj 1996). A fully optimized gene will be translated at the fastest rate possible by the ribosome; therefore it could miss critical pauses where the

nascent protein may need time to stop and achieve the correct conformation before translation resumes. The codon-harmonized anti-Pfs48/45 is shown in Figure 2.11.

Allowing the ribosome to translate a heterologous protein at the same rate as it would in the native organism should prevent the product from misfolding. This can potentially reduce degradation of the protein, prevent aggregation, and increase solubility. Misfolded protein can have a large impact on the bacteria which express it, and this burden can cause growth inhibition (Rosano 2009, Kudla 2009). This is an important consideration for a paratransgenic expression construct, because the bacteria must reliably compete against wild type bacteria in the mosquito midgut while still producing enough scFv protein to be effective during an infective blood meal.

mRNA 5' UTR structure

The 5'-UTR folding free energy of the mRNA molecule was taken into account while optimizing and harmonizing the gene sequences. Both the UTR and part of the open reading frame (ORF) directly following it can have an impact on translation initiation of a gene transcript (Kozak 2005). The Shine-Delgarno sequence on an mRNA transcript may become obscured if there is a complementary sequence capable of forming a hairpin with it, preventing the ribosome from binding the RNA and locating the start codon. Probable hairpin-forming structures were identified by entering sequences into the mFold webserver RNA secondary structure predictor (SUNY Albany, Albany, NY http://mfold.rit.albany.edu/?q=mfold). The hairpin structure of the MRA316 anti-

Pfs48/45 RNA is shown in Figure 2.12, and it has a ΔG of -49.60 kcal/mol. The

coding sequence was altered accordingly to remove the hairpin-forming sequence while retaining the encoded amino acid sequence (Figure 2.13). A hairpin at the 5' end of the mRNA can cause a significant decrease in the amount of protein produced, with a significant drop-off occurring when the free energy of a hairpin reaches -8 kcal/mol or lower (Kudla 2009). Codons in the beginning of the ORF for the optimized antibody genes were adjusted to eliminate potential hairpins that could decrease protein translation.

Expression plasmid construction and molecular cloning

The expression vector used to express protein in multiple host bacteria was constructed using the backbone of pBBR1MCS-2, a broad-host range plasmid containing an origin of replication originally isolated in Bordetella and has been proven to function in Asaia (Kovach 1995). Other features on the plasmid include a mobilization element for conjugal transfer and the lacZ alpha gene containing a multiple cloning site (MCS). The plasmid has the kanamycin resistance marker, neomycin phosphotransferase, which is useful for selection since it is one of the few antibiotics that Asaia are susceptible to.

The lacZα gene of pBBR1MCS-2 (Figure 2.14) was replaced by bacterial recombination with a new cloning site that I designed (Figure 2.15). Primers were designed to amplify the ampicillin resistance gene (bla) encoding beta-lactamase and extend this to have a translational enhancer preceding the ORF, an NdeI restriction site at the beginning of the gene, and five other unique restriction sites following the gene. The primers included 40 nucleotides of homology to the pBBR1MCS-2 plasmid on each end of the amplified product which are required for recombination the primers are listed in

Table 2.2 as “pBBR rec F” and “pBBR rec R”. The bla gene was amplified by PCR from pSC189 (Chiang 2002) using these primers and purified by gel-extraction using a Zymo kit (Zymo Research, Irvine, CA #D4002). The pBBR1MCS-2 plasmid was purified from

E. coli using a Qiagen miniprep kit (Qiagen, Germantown, MD, #27104). The pBBR1MCS-2 plasmid was linearized by digestion with the EcoRI and BamHI restriction enzymes to completion.

Fifty ng of the linear plasmid and 50 ng of the PCR product were co-transformed into MG1655 E. coli cells, which were incubated in non-selective LB media for 1.5 h at

37 °C to allow for the bacteria to recombine the two DNA fragments. This culture was plated on selective LB media containing ampicillin. The resulting colonies from this selection contained the new plasmid named pNB20 (Figure 2.16), which now had a specific set of restriction sites with which to modify the expression cassette.

The pNB20 plasmid was further modified by changing the promoter region for beta-lactamase to the neomycin phosphotransferase promoter (PnptII). This promoter is constitutively active and has high activity in Asaia sp. as demonstrated by its effective use expressing green fluorescent protein (Favia 2007). The PnptII region of pHM2-GFP

(Favia 2007) was amplified by standard PCR using primers that add NsiI and NdeI restriction sites to the ends of the amplicon (primers “PnptII F NsiI” and “PnptII R

NdeI”). This PCR product and pNB20 were each digested to completion with the NsiI and NdeI restriction enzymes, and the plasmid was treated with calf intestinal phophatase. The PCR product was ligated into the linearized plasmid using T4 DNA ligase at 16 °C overnight. The ligated DNA was transformed into Top10 F' E. coli cells

and selected on LB media containing ampicillin and kanamycin. Clones isolated from this selection were verified by sequencing to ensure there were no mutations introduced.

The new plasmid created was named pNB51 (Figure 2.17).

Vector construction

The anti-Pfs25 scFv was initially synthesized with an optimized pelB leader sequence at the N-terminal end followed by an AscI restriction digest site and with 6-His and Myc epitope tags at the C-terminal end of the gene for western blot detection. This gene was further flanked with restriction enzyme sites NdeI and BamHI at the N- and C- terminal ends, respectively. The plasmid bearing the synthesized gene and the plasmid pNB20 were digested using the NdeI and BamHI restriction enzymes, and the antibody gene was then ligated into pNB20 3' to the lac promoter. This plasmid was called pNB39

(Table 2.1), and it was used for further cloning of antibody effectors.

Other optimized or harmonized antibody scFv genes were digested from plasmid

DNA using the AscI and EcoRI restriction digest sites and ligated into the pNB39 plasmid in-frame with the PelB leader to replace the anti-Pbs25 scFv gene. The resulting plasmids were called pNB37 (anti-Pfs48/45 scFv) and pNB38 (anti-Pfs230 scFv) (Figure

2.18). An anti-BSA scFv gene from pDB51 (Bisi 2011) was also cloned into pNB39 by

PCR amplification using primers “BSA F AscI” and “BSA R EcoRI” and by directionally cloning into the same site. The anti-BSA plasmid was called pNB55.

Insertion of GFP into secretion plasmids

The GFP gene was amplified from pHM2GFP and inserted into pNB20 to both test for the expression activity of the promoters in Asaia, as well as to observe protein activity. gfp was amplified using standard PCR with the primers “GFP F NdeI” and “GFP

R EcoRI.” These PCR products along with purified plasmids pNB20 and pNB51 were digested using the NdeI and EcoRI restriction enzymes, and the plasmid was treated with calf intestinal phophatase. The PCR products were ligated into the linearized plasmid using T4 DNA ligase at 16 °C overnight. The ligated DNA was then transformed into

Top10 F' E. coli cells and selected on LB media containing 30 μg/ml kanamycin. The produced plasmids were called pNB49 (with lac promoter) and pNB50 (with nptII promoter). Clones isolated from this selection were verified by sequencing to ensure there were no mutations introduced, and confirmed under fluorescence microscopy to verify expression of the gfp gene. These plasmids were subsequently purified and introduced into Asaia bogorensis competent cells. Fluorescence activity of the GFP protein produced in Asaia was visualized under excitation conditions with 395 nm light.

Cloning secretion signals from acetic acid bacteria

Since the Asaia genome was not yet sequenced, signal peptides from two related species of acetic acid bacteria were tested for activity in Asaia. Proteins identified as secreted in the psortdb database (http://db.psort.org) from Gluconobacter oxydans and

Gluconacetobacter diazotrophicus were selected, and their secretion signals were identified by processing the amino acid sequences using the SignalP4.1 software

(www.cbs.dtu.dk/services/SignalP) artificial neural network Hidden Markov models

(Nielsen 1997). This program is capable of machine learning and pattern recognition, therefore it utilizes a database of secreted proteins and identifies unknown proteins by their homologous sequence to the database. Primers were designed to amplify only the signal peptide gene sequence of these proteins, and to add NdeI and AscI restriction sites to the 5' and 3' ends of the product, respectively (Table 2.2).

Routine PCR was performed using genomic DNA from Gluconobacter oxydans or Gluconacetobacter diazotrophicus as template and an individual set of primers for a given gene. Each of these amplified products was inserted into plasmid pNB39 by restriction digestion and ligation exactly as described previously, replacing the PelB secretion signal with each of these newly identified signals. Thirteen unique secretion signals were cloned in this way and are listed in Table 2.4, and the plasmids are listed in

Table 2.1 as pNB44 through pNB76.

Western blot to detect scFv proteins expressed from inducible promoters

E. coli, P. agglomerans, and A. bogorensis with scFv expression plasmids were grown to an OD600 of 1.0. Protein production was induced in E. coli by adding 0.5 mM

IPTG to strains that expressed genes under control of the lac promoter, and the culture was grown for 12 h. Cultures of each strain containing no plasmid were grown for negative controls, and E. coli expressing the plasmid pDB49 which produces an anti- bovine serum albumin (anti-BSA) scFv protein were induced as a positive control. To separate the pellet and supernatant fractions, 100 μl of the cell cultures were pelleted at

8,000g for 2 min. The pellet was resuspended in 100 μl of 3X Laemmli sample buffer

(BioRad) with 2-mercaptoethanol, and 75 μl of the supernatant was mixed with 25 μl of

Laemmli buffer. These samples were boiled for 8 min to denature the proteins, and 8 μl of the ColormarkPlus Prestained Protein Ladder (New England Biolabs), 20 μl of each supernatant protein sample, and 5 μl of each pellet protein sample were loaded into the wells of a 5% stacking and 10% separating polyacrylamide gel. Proteins were separated by electrophoresis, transferred onto a 0.45 μm pore size PVDF membrane in a BioRad transfer apparatus using Tris-Glycine transfer buffer (25mM Tris, 150mM glycine, 10% methanol) at 95 V for 75 minutes. The PVDF membrane was blocked for 18 h with 1%

BSA TBS-Tween 20 (TBS-T) (50mM Tris-CL, 150 mM NaCl, 0.1% Tween 20, 1% w/v fraction V BSA, pH 7.5) with agitation at 4 °C. Next, the blocking solution was replaced with the primary antibody, a mouse anti-myc antibody (Invitrogen 45-0603) 1:5000 in blocking buffer, and incubated at 4 °C for 24 h with agitation. The primary antibody solution was removed, and the blot was washed four times in TBS-T for 15 min each time. Following washes, the secondary antibody, goat anti-mouse HRP (BioRad 170-

5046), was applied and the blot was incubated for 1 h at room temperature. The wash steps were repeated, 2 ml of Supersignal West Femto Maximum Sensitivity Substrate

(Thermo Scientific # 34095) was added to the blot and incubated for 5 min. The blot was exposed to X-ray film (Thermo Scientific 34090) for multiple time exposures ranging from 10 sec to 10 min and then developed using an automatic developer.

Northern blot to detect transcription of scFv genes

Digoxigenin-labeled probes were created using the DIG High Prime DNA

Labeling and Detection Starter Kit I (Roche 11745832910). First, each gene to be identified in the northern blot was amplified by PCR, including the anti-BSA scFv, anti-

Pfs25 scFv, anti-Pfs48/45 scFv, and anti-Pfs230 scFv. Three μg of each template PCR product were mixed with the DIG High Prime reagent and incubated at 37 °C for 20 h.

Labeling efficiency of each probe was determined by serial dilution of the probes and a control DIG-labeled control DNA. These were spotted onto a piece of nitrocellulose membrane, and detected using NBT/BCIP. Spot intensity was compared to that of the control labeled DNA, and each probe was diluted to the same working concentration as per the DIG labeling kit instructions.

E. coli Top10 F' cells with expression plasmids as well as control E. coli with no plasmid were grown at 37 °C to a OD600 of 1.0. Duplicates of each strain tested were prepared from these cultures, and one of each was induced by the addition of 0.5 mM

IPTG. Cultures were then grown for 1 h at 37 °C. RNA was extracted from each sample using TRI Reagent using the MRC protocol for bacterial cells

(http://mrcgene.com/?s=tri+reagent). The samples were size separated on a 1% agarose gel with 0.4% formaldehyde. The bands were transferred to a nitrocellulose membrane by capillary action using the Turboblotter following standard protocols (Whatman

Schleicher & Schuell). The RNA was UV-crosslinked to the wet membrane using a UV transilluminator for 1 min with 254 nm light. The full Whatman Turboblotter protocol can be found at: (https://www.gelifesciences.com/gehcls_images/

GELS/Related%20Content/Files/1389873234232/litdoc29088931_20140116215520.pdf)

The membrane was probed with the previously prepared DIG-labeled DNA and hybridized at 44 °C in a Fisherbrand rotisserie hybridization oven following the DIG labeling kit protocols. Detection of labeled RNA was performed as written in the Roche kit instruction manual. The DIG labeling kit manual can be found at:

(http://lifescience.roche.com/wcsstore/RASCatalogAssetStore/Articles/05353149001_08.

08.pdf)

RESULTS

Antibody variable region cloning

Three hybridoma lines that produce antibodies against surface proteins Pfs25,

Pfs48/45, and Pfs230 of P. falciparum gametes and ookinetes were obtained from the

MR4 depository, and cDNA was produced from each. Another hybridoma line that produces antibodies against human IgG (ATCC CRL-1757) was also obtained for incorporation into divalent diabodies with Pfs230; the proposed diabodies are expected to allow binding of the anti-Plasmodium scFv to the parasite and to allow the connected anti-complement scFv to initiate a complement cascade that will destroy the ookinete.

The gene sequences of each antibody's binding domains were identified by PCR amplification of the variable region of the heavy and light chains from the cDNA. These variable regions were recombined into single-chain variable fragment (scFv) format suitable for expression in prokaryotes (Figure 2.1) These gene constructs include a long, flexible linker sequence connecting the two antigen binding domain that allows the

protein to align the domains and retain the function of the original antibody protein complex (Winter, Tomlinson Library).

Antibody variable region sequencing and manipulation

The scFv format genes of these antibodies were cloned using the TA system into the pCR2.1-TOPO vector and sequenced using standard M13 vector primers. The full sequence of each antibody was obtained this way (Figures 2.6-2.9), allowing for the modification of the scFv gene in order to enhance its activity in bacterial hosts. Some scFv genes cloned directly from mammalian cells can be produced in bacteria; however, the codon usage of eukaryotes and prokaryotes differ greatly, and optimization for the expressing organism can have a large impact on protein production (Hannig 1998). The coding sequences of these genes were altered in two ways. Each of the scFv genes was optimized for the codon usage of E. coli, using only the most common amino acids from that host. The only deviation from this optimization was in changes to specific amino acids that were identified to cause potential RNA hairpin structures that interfere with translation initiation (Hall 1982).

A second version of the anti-Pfs48/45 antibody was also generated, by comparing the codon usage of the original gene sequence to the codon frequency in the mouse and by selecting codons at each site for bacterial expression that match the codon usage frequency in E. coli. This is called a harmonized gene sequence, and it can possibly aid the folding of proteins thereby increasing the efficiency of production by harmoniously replicating the translation speed of the original host (Roy 2009). This allows a nascent

protein to slow translation when necessary to allow portions of the protein to fold before translation continues (Angov 2008).

Expression of single-chain variable fragment antibodies in bacterial host organisms

The scFv genes were cloned into expression vectors under control of the lac and nptII promoters. These constructs fused the scFv gene to the pelB leader sequence from the Erwinia carotovora pectate lyase gene, which has been successfully used by others to secrete scFv proteins from E. coli. The C-terminal end of these genes also contained 6-

His and Myc epitope tags. These plasmids were transformed into E. coli, P. agglomerans, and A. bogorensis to assess protein production and secretion.

Protein production was not apparent in any of the bacterial strains produced, as shown by a lack of protein of the predicted size by both Coomassie and western blot

(Figure 2.19). A control strain of E. coli expressing an anti-BSA scFv from either plasmid pDB51 or pDB49 was used as a positive control for western blot detection, and that protein was detected normally.

Transcription of gene constructs in E. coli

Due to a lack of protein production from expressing strains, a northern blot was conducted to determine if the problem was related to transcription. RNA was prepared from different expression constructs, and mRNA transcripts of the scFv gene sequences were identified using a digoxigenin labeling reaction. All strains that contained plasmids expressing scFv genes produced mRNA of the correct predicted size (Figure 2.20).

Activity of lac and nptII promoters in Asaia

Expression plasmids were constructed with the pBBR origin of replication, kanamycin resistance marker, and the gfp gene either under the control of the lac promoter or the nptII promoter (Figures 2.21 and 2.22). These gene constructs did not have any modifications such as secretion signals or tags, and the promoters were identical to previous expression constructs. The plasmids were transformed into Asaia, and strains expressing each were viewed under a fluorescence microscope. The lac promoter produced a very faint amount of fluorescence, whereas the nptII promoter produced a strong signal (Figure 2.23).

Testing secretion signals from species related to Asaia

Secretion signals were tested from two close relatives of Asaia bogorensis in the family Acetobacteraceae: Gluconobacter oxydans and Gluconacetobacter diazotrophicus since the Asaia genome was not yet sequenced. Thirteen genes from these species were selected from a list of known secreted proteins on the psortdb database (db.psort.org), and their secretion signals were identified using the SignalP4.1 algorithms

(www.cbs.dtu.dk/services/SignalP). The leader peptides for the thirteen genes were amplified from genomic DNA and cloned into scFv expression plasmids in-frame with both the anti-BSA scFv and the anti-Pfs25 scFv. The complete list of genes from which secretion signals were cloned and their amino acid sequence are listed in Table 2.4.

These plasmids were transformed into Asaia competent cells, and protein production was assessed by western blot (Figures 2.24 and 2.-25). Despite the use of secretion signals from closely-related species, no protein production was detected.

DISCUSSION

Malaria remains a significant cause of human mortality and morbidity in the world, and new techniques to combat the disease are necessary to supplement current interventions. In this work, new effector molecules, which can potentially be secreted by paratransgenic bacteria living within anopheline mosquito hosts, were generated. These proteins are single-chain variable fragment (scFv) antibodies that should be capable of binding to surface proteins of Plasmodium falciparum and interfering with the parasite's development. The genes for these scFv effectors were tested for protein expression and secretion from E. coli and from two mosquito midgut symbionts, Asaia bogorensis and

Pantoea agglomerans.

Novel scFv effector molecules

Heavy and light chain variable binding domain regions for three antimalarial antibodies known to interfere with P. falciparum within the mosquito midgut were cloned from hybridoma lines and sequenced. These variable region genes were recombined into genes designed to produce single-chain variable fragment antibodies within heterologous hosts. Such molecules only contain the binding domain of the heavy and light antibody chains and are much smaller than a standard antibody. They have a great potential for use

as antimalarial effector molecules to combat P. falciparum, the most deadly species of

Plasmodium in humans. Furthermore, the activity of these effector molecules would be restricted to targeting only the parasite of interest and should not interfere with any other aspects of the microbiota, as could be the case with some other more general antimicrobial effectors, like scorpine, that kill a wide range of microorganisms

(Carballer-Lejarazu 2008).

Difficulties in scFv expression and secretion

Despite multiple attempts to express and to secrete these scFv proteins in E. coli,

A. bogorensis, and P. agglomerans, no success was achieved. The genes proved to be properly transcribed in the heterologous hosts; however, no protein was detected by either Coomassie-stained protein gels or by western blot targeting the Myc epitope tag of the protein. There can be issues involved with protein expression at multiple points in the process, during translation, protein folding, or secretion. Not all promoters will function in all bacteria: the lac promoter is known to function in E. coli and P. agglomerans, but no protein was produced even from IPTG-induced cells. Indeed, transcription does not seem to be a problem with these constructs, as evidenced by the northern blot which shows full length products from each construct tested.

There could be a problem during translation of the proteins, although that would be unlikely to cause a complete lack of protein considering that multiple gene combinations were attempted, including different effectors and different N-terminal signal sequences. Incorrect protein folding is a common problem in heterologously

expressed proteins, especially for scFv antibodies (Maeng 2011). Single-chain antibody fragments are less stable than natural antibodies, and stability engineering is a concern

(Worn 2001). These proteins require the formation of disulphide bonds in the periplasm to retain their correct structure. The PelB secretion signal has been used extensively for the export of scFv molecules from bacterial cells (Mergulhao 2005), and it utilizes the general secretory (Sec) pathway which translocates the protein into the periplasm before it leaves the cell entirely. Typically, this is a beneficial pathway for scFv secretion, because the protein can form disulphide bonds in the oxidizing environment while it passes through the periplasm (Popplewell 2005). The Sec translocon transfers proteins in an unfolded conformation that requires proteins to refold within the periplasm and this fact may prevent the proteins designed in this study from folding properly and hence be degraded by cellular proteases (Dalbey 2012).

Visual analysis of transformed bacterial colonies containing these plasmids showed unusual phenotypes such as a raised morphology and greater transparency than in wild type cells. These phenotypes could be indicative of problems with the membrane of the cell caused by incorrect translocation and “clogging” of the membrane, causing the cells to rupture or activate some sort of stress response. The GFP expression plasmids used in Asaia were proven to function quite well with the nptII promoter and only slightly with the lac promoter; therefore, the negative results from expression plasmids utilizing the nptII promoter to express either GFP or scFv genes with secretion signals indicates that the problem lies in the secretion system used to translocate these proteins.

They are likely being transcribed and translated but are degraded by cellular proteases due to problems at the cell membrane.

Conclusions

Single-chain variants of mouse monoclonal antibodies have been cloned and sequenced successfully; however, the proteins were not expressed properly by any bacteria transformed with diverse expression plasmids utilizing different secretion signals, promoters, and gene variants. Secretion in Gram-negative bacteria involves many different pathways that translocate proteins by very different mechanisms. These scFv genes likely require a different secretion signal or mechanism to successfully export the protein safely, without detriment to the bacteria. The PelB leader sequence secretes proteins using the general secretory (Sec) pathway of prokaryotes. This pathway translocates proteins into the periplasm post-translationally, where they must refold.

Twelve of the cloned leader peptides from G. oxydans and G. diazotrophicus were Sec- dependent, and one was Tat-dependent. Constructs with any of these signals failed to produce detectable protein. It is possible that a native secretion signal from Asaia would allow the proteins to be translated and exported from the cell correctly. Unfortunately, the

Asaia genome was not sequenced at the time of these experiments, only genomes from related species were available. The scFv gene constructs cloned were retained for future use after a new secretion system is identified that functions well in Asaia.

Figure 2.1. Forms of antibodies. From left to right: a natural IgG antibody, a single chain antibody utilizing only the antigen binding domains from IgG, a diabody with two IgG binding domains back-to-back, and a single chain antibody fused with a folding chaperone. Both the scFv and diabody can be expressed in prokaryotes, and they can also accomodate added fusion proteins, like the Skp molecular chaperone depicted here. Skp is a trimeric periplasmic protein chaperone of Gram-negative bacteria which can increase the avidity of a scFv molecule by increasing the number of binding domains in a single protein complex and by aiding in the correct folding of the protein in the periplasm (Wang and Xiang 2013). Antimicrobial peptides, such as the Shiva1 antimicrobial, can also be fused to the scFv to complement its function by creating a single protein that acts against Plasmodium in two different ways (Wang 2013).

Figure 2.2. Di-diabody. The structure of a di-diabody, which consists of two diabodies held together by CH3 constant domains. This molecule has a greater avidity than standard scFv constructs that contain just a single binding domain and provides complement- fixing functionality by the natural CH3 domain interaction.

Figure 2.3. Overlap extension PCR. The heavy and light chain variable regions of each antibody were separately amplified from cDNA using degenerate primer sets (primers ab and cd, above). Primers b and c share a region of homology. This allows the two products (products AB and CD) to act as primers for the opposite strand in a new PCR reaction in which both products are included as templates and external primers (primers a and d) are used.

A. B.

Figure 2.4. Antibody variable region PCR and overlap extension PCR. A.) One percent agarose gel showing separation of light and heavy chain antibody variable fragments amplified from MRA315, anti-Pfs25 antibody, one of the three anti- Plasmodium hybridomas. These are the PCR products later used in sequencing reactions to obtain sequence and to run overlap-extension PCR. The lanes are: 1.) kappa variable region (Vk) short linker, 2.) Vk long linker, 3.) lambda variable region (Vl) short linker, 4.) Vl long linker, and 5.) heavy chain variable region (Vh). Separate primer sets were used to amplify the Vk and Vl antibodies, and since each hybridoma line will only produce a single light chain that will be either Kappa or Lambda. B.) The successful overlap extension PCR of the fragments from Part A. 1.) scFv with a short linker sequence, and 2.) scFv with a long linker sequence. These products consist of single- chain antibody genes, which were gel-purified and inserted into an expression vector to attempt expression of the un-modified gene construct. Similar products were amplified from MRA 316, anti-Pfs48/45 and MRA878, anti-Pfs230.

Figure 2.5. Single-chain antibody construct. This is the first open reading frame (ORF) design for each scFv construct as cloned in pDB48. There are multiple restriction sites built into the gene construct for the ease of switching scFv or other protein effectors in and out. These are located on either side of the PelB leader, and the C-terminal tag region so either the entire ORF can be moved or the specific protein between them can be replaced. Later, these gene constructs were modified to include different promoters and leader peptides (Figure 2.14).

Pfs48/45 hair 1 CCAACCTGCTGAGCTCGACGTTGTGTTAACACAGTCTCCTGCTTCCTTAGCTGTATCTCT 60 CCA CC GC GAGCTCGACGTTGTGTTAACACAGTCTCCTGCTTCCTTAGCTGTATCTCT Pfs48/45 orig 1 CCAGCCGGCCGAGCTCGACGTTGTGTTAACACAGTCTCCTGCTTCCTTAGCTGTATCTCT 60

Figure 2.6. Nucleotide sequence of the 5' end of anti-Pfs48/45 scFv hairpin fix. This is the nucleotide sequence of the 5' end of the anti-Pfs48/45 scFv that was modified to prevent the formation of possible translation-blocking RNA hairpins. Pfs48/45 hair = modified gene sequence. Pfs48/45 orig = original gene sequence.

Pfs25 opt 1 ATGAAATATCTGCTGCCGACCGCCGCTGCTGGACTGCTGCTGCTGGCTGCTCAACCTGCT 60 ATGAAATATCTGCTGCCGACCGCCGCTGCTGGACTGCTGCTGCTGGCTGCTCAACCTGCT Pfs25 orig 1 ATGAAATATCTGCTGCCGACCGCCGCTGCTGGACTGCTGCTGCTGGCTGCTCAACCTGCT 60

Pfs25 opt 61 ATGGCCGGCGCGCCTCCTTCTTCGATGTTCGCCTCTCTGGGTGACCGTGTATCCCTGTCT 120 ATGGCCGGCGCGCC CC TC TC ATGTT GCCTCTCTGGG GAC G GT CT TCT Pfs25 orig 61 ATGGCCGGCGCGCCACCATCGTCCATGTTTGCCTCTCTGGGAGACAGAGTCAGTCTCTCT 120

Pfs25 opt 121 TGCCGTGCTTCTCAGGACATTCGTGGGAATCTGGATTGGTTCCAACAAAAACCGGGGGGT 180 TG CG GCT TCAGGACATT G GG AAT T GA TGGTT CA CA AAACC GG GG Pfs25 orig 121 TGTCGGGCTAGTCAGGACATTAGAGGTAATTTAGACTGGTTTCAGCAGAAACCAGGTGGA 180

Pfs25 opt 181 ACGATTAAACTGCTGATCTATTCGACCTCTAACCTAAATTCTGGTGTTCCGAGCCGCTTT 240 AC ATTAAACT CTGATCTA TC AC TC AA TAAATTCTGGTGT CC G TT Pfs25 orig 181 ACTATTAAACTCCTGATCTACTCCACATCCAATTTAAATTCTGGTGTCCCATCAAGGTTC 240

Pfs25 opt 241 AGTGGATCTGGTTCTGGTAGCGACTATTCTCTGACCATCTCTTCACTGGAGAGCGAGGAC 300 AGTGG TGG TCTGG GA TATTCTCT ACCATC CT GAG GA GA Pfs25 orig 241 AGTGGCAGTGGGTCTGGGTCAGATTATTCTCTCACCATCAGCAGCCTAGAGTCTGAAGAT 300

Pfs25 opt 301 CTGGGGGATTATTATTGTCTGCAACGCAACGCTTATCCGCTGACCTTTGGTAGTGGTACA 360 TGGG GA TATTA TGTCT CA CG AA GC TATCC CT AC TT GG GG ACA Pfs25 orig 301 TTGGGAGACTATTACTGTCTACAGCGTAATGCGTATCCTCTCACGTTCGGGTCGGGGACA 360

Pfs25 opt 361 AAACTGGAAATCAAAAGCTCCGGTGGTGGAGGAAGTGGCGGGGGAGGCGGAGGTTCTTCT 420 AA TGGAAAT AAA CTC GGTGG GG GG GGCGG GG GG GG GGTTC TCT Pfs25 orig 361 AAGTTGGAAATAAAATCCTCTGGTGGCGGTGGCTCGGGCGGTGGTGGGGGTGGTTCCTCT 420

Pfs25 opt 421 CGTTCAAGCCTGGAAGTTCAACTGGTGGAATCTGGTGGTGGTCTGGTTCAACCGGGTGGT 480 G TC CCT GA GT CAACTGGTGGA TCTGG GG GG T GT CA CC GG GG Pfs25 orig 421 AGATCTTCCCTCGAGGTGCAACTGGTGGAGTCTGGAGGAGGCTTAGTGCAGCCTGGAGGG 480

Pfs25 opt 481 TCACAGAAACTGAGCTGTGCTGCTAGTGGTTTCACCTTTAGCGATTATGGTATGGCGTGG 540 TC CAGAAACT CTGTGC GC TGG TTCAC TT AG GA TA GG ATGGCGTGG Pfs25 orig 481 TCCCAGAAACTCTCCTGTGCAGCCTCTGGATTCACTTTCAGTGACTACGGAATGGCGTGG 540

Pfs25 opt 541 TTTCGTCAGGCCCCTGGAAAAGGCCCTGAATGGGTGGCGTTTATCAACAATCTGGCCTAT 600 TTTCG CAGGC CC GG AA GG CCTGA TGGGT GC TT AT AA AAT TGGC TAT Pfs25 orig 541 TTTCGACAGGCTCCAGGGAAGGGGCCTGAGTGGGTAGCATTCATTAATAATTTGGCATAT 600

Pfs25 opt 601 AGCATCTATTATGCCGACACCGTTACTGGTCGTTTTACGATCTCTCGTGAGAATGCCAAA 660 AG ATCTA TATGC GACAC GT AC GG CG TT AC ATCTCT G GAGAATGCCAA Pfs25 orig 601 AGTATCTACTATGCAGACACTGTGACGGGCCGATTCACCATCTCTAGAGAGAATGCCAAG 660

Pfs25 opt 661 AACACCCTGTATCTGGAGATGTCTAGCCTGCGTTCCGAGGATACTACGATGTATTATTGT 720 AACACCCTGTA CTGGA ATG AG CTG G TC GAGGA AC AC ATGTA TA TGT Pfs25 orig 661 AACACCCTGTACCTGGAAATGAGCAGTCTGAGGTCTGAGGACACAACCATGTACTACTGT 720

Pfs25 opt 721 GCCCGTGGTAACCTGTATTATGGGCTGGACTATTGGGGTCAAGGGACAACACTGACTGTT 780 GC G GG AA CT TA TA GG CT GACTA TGGGG CAAGG AC AC CT AC GT Pfs25 orig 721 GCAAGGGGGAATCTTTACTACGGTCTAGACTACTGGGGCCAAGGCACCACTCTCACAGTC 780

Pfs25 opt 781 AGTAGCGCCAAAACAACACCGCCTAGCGTCTATCCGCTGGCTGCGGCCGCACACCATCAT 840 GCCAAAAC ACACC CC GTCTATCC CTGGC GCGGCCGCACACCATCAT Pfs25 orig 781 TCCTCAGCCAAAACGACACCCCCATCTGTCTATCCACTGGCCGCGGCCGCACACCATCAT 840

Pfs25 opt 841 CATCATCATGGCGCCGCTGAACAGAAACTGATCTCGGAGGAAGATCTGAACGGAGCTGCC 900 CATCATCATGGCGCCGCTGAACAGAAACTGATCTCGGAGGAAGATCTGAACGGAGCTGCC Pfs25 orig 841 CATCATCATGGCGCCGCTGAACAGAAACTGATCTCGGAGGAAGATCTGAACGGAGCTGCC 900

Pfs25 opt 901 TAA 903 TAA Pfs25 orig 901 TAA 903 Figure 2.7. Nucleotide sequence of the anti-Pfs25 scFv. This is the nucleotide sequence of the scFv designed from sequence data of the MRA315 hybridoma line (MR4, Manassas, VA). Pfs25 orig = original sequence. Pfs25 opt = optimized gene.

Pfs48/45 opt 1 GGCGCGCCACAACCTGCTGAACTGGACATCGTGCTGACCCAATCGCCTGCTTCCCTGGCC 60 GGCGCGCC CA CC GC GA CT GAC T GTG T AC CA TC CCTGCTTCC T GC Pfs48/45 orig 1 GGCGCGCCCCAGCCGGCCGAGCTCGACGTTGTGTTAACACAGTCTCCTGCTTCCTTAGCT 60

Pfs48/45 opt 61 GTATCACTGGGACAACGTGCTACCATCTCTTATCGTGCCTCCAAAAGCGTTTCTACGAGT 120 GTATC CTGGG CA G GC ACCATCTC TA G GCC CAAAAG GT TAC T Pfs48/45 orig 61 GTATCTCTGGGGCAGAGGGCCACCATCTCATACAGGGCCAGCAAAAGTGTCAGTACATCT 120

Pfs48/45 opt 121 GGTTATTCCTATATGCACTGGAACCAACAAAAACCGGGACAGCCTCCTCGTCTGCTGATT 180 GG TAT TATATGCACTGGAACCAACA AAACC GGACAGCC CC G CT CT AT Pfs48/45 orig 121 GGCTATAGTTATATGCACTGGAACCAACAGAAACCAGGACAGCCACCCAGACTCCTCATC 180

Pfs48/45 opt 181 TATCTGGTGTCGAACCTGGAAAGTGGTGTGCCTGCCCGTTTCTCCGGATCTGGATCTGGG 240 TATCT GT TC AACCT GAA TGG GT CCTGCC G TTC GG TGG TCTGGG Pfs48/45 orig 181 TATCTTGTATCCAACCTAGAATCTGGGGTCCCTGCCAGGTTCAGTGGCAGTGGGTCTGGG 240

Pfs48/45 opt 241 ACTGATTTTACCCTGAACATTCACCCTGTGGAAGAGGAAGATGCCGCCACCTATTATTGC 300 AC GA TT ACCCT AACAT CA CCTGTGGA GAGGA GATGC GC ACCTATTA TG Pfs48/45 orig 241 ACAGACTTCACCCTCAACATCCATCCTGTGGAGGAGGAGGATGCTGCAACCTATTACTGT 300

Pfs48/45 opt 301 CAACACATTCGTGAGCTGACACGCTCTGAAGCTGGTACAAAACTGGAGATCAAAAGCTCT 360 CA CACATT G GAGCT ACACG TC G AG GG AC AAACTGGA ATCAAA CTCT Pfs48/45 orig 301 CAGCACATTAGGGAGCTTACACGTTC-GGAGGGGGGACCAAACTGGAAATCAAATCCTCT 359

Pfs48/45 opt 361 GGTGGTGGTGGAAGTGGTGGTGGTGGAGGTGGTTCTTCTCGTTCTAGCCTGGAAGTCATG 420 GGTGG GGTGG GG GGTGGTGG GGTGGTTC TCT G TCT CCT GA GT ATG Pfs48/45 orig 360 GGTGGCGGTGGCTCGGGCGGTGGTGGGGGTGGTTCCTCTAGATCTTCCCTCGAGGTGATG 419

Pfs48/45 opt 421 CTGGTCGAATCTGGTCCTGACCTGGTTAAACCTGGTGCTTCCGTGAAAATTTCCTGTAAA 480 CTGGT GA TCTGG CCTGACCTGGT AA CCTGG GCTTC GTGAA AT TCCTG AA Pfs48/45 orig 420 CTGGTGGAGTCTGGACCTGACCTGGTGAAGCCTGGGGCTTCAGTGAAGATATCCTGCAAG 479

Pfs48/45 opt 481 GCGAGCGGGTATTCCTTCATCAACTATTATATGCACTGGGTTAAACAGAGCCACGGCAAA 540 GC GG TATTC TTCAT AA TA TATATGCACTGGGT AA CAGAGCCA GG AA Pfs48/45 orig 480 GCTTCTGGTTATTCATTCATTAATTACTATATGCACTGGGTGAAGCAGAGCCATGGAAAG 539

Pfs48/45 opt 541 TCACTGGAATGGATTGGTCGTGTTAATCCTCAGAATGGCGGTACACGTGACAATCAGAAA 600 CT GA TGGATTGG CG GTTAATCCTCAGAATGG GGTAC G GACAA CAGAAA Pfs48/45 orig 540 AGCCTTGAGTGGATTGGACGAGTTAATCCTCAGAATGGTGGTACTAGGGACAACCAGAAA 599

Pfs48/45 opt 601 TTCAAAGGCAAAGCCATCTTTACGGTGGACAAATCGTTCAATACAGCGTATATGGAACTG 660 TTCAA GGCAA GCCAT TTTAC GT GACAA TC TTCAA ACAGC TATATGGAACT Pfs48/45 orig 600 TTCAAGGGCAAGGCCATATTTACTGTAGACAAGTCATTCAACACAGCCTATATGGAACTA 659

Pfs48/45 opt 661 CGTTCACTGACCTCGGAGGACTCTGCTGTGTATTATTGTGCCCGTGAAGTCCACTATGAT 720 CG CTGAC TC GAGGACTCTGC GT TATTA TGTGC CG GA GT CA TA GA Pfs48/45 orig 660 CGCAGCCTGACATCTGAGGACTCTGCGGTCTATTACTGTGCACGAGAGGTTCATTACGAC 719

Pfs48/45 opt 721 GAGGCGCTGGATTATTGGGGTCAAGGCACCTCTGTAACCGTTTCTAGCGCCAAAACAACA 780 GAGGC TGGA TA TGGGGTCAAGG ACCTC GT ACCGT TC GCCAAAACAACA Pfs48/45 orig 720 GAGGCTTTGGACTACTGGGGTCAAGGAACCTCAGTCACCGTCTCCTCAGCCAAAACAACA 779

Pfs48/45 opt 781 CCGCCTAGCGTTACAAGTGCGGCCGC 806 CC CC GT AC AGTGCGGCCGC Pfs48/45 orig 780 CCCCCATCTGTCACTAGTGCGGCCGC 805

Figure 2.8. Nucleotide sequence of the anti-Pfs48/45 scFv. This is the nucleotide sequence of the scFv designed from sequence data of the MRA316 hybridoma line (MR4 Manassas, VA). Pfs48/45 orig = original gene sequence. Pfs48/45 opt = optimized gene sequence.

Pfs48/45 harm 1 GGCGCGCCCCAGCCCGCGGAACTTGATATCGTCCTAACGCAGTCACCGGCGAGCCTAGCA 60 GGCGCGCCCCAGCC GC GA CT GA T GT TAAC CAGTC CC GC C TAGC Pfs48/45 orig 1 GGCGCGCCCCAGCCGGCCGAGCTCGACGTTGTGTTAACACAGTCTCCTGCTTCCTTAGCT 60

Pfs48/45 harm 61 GTATCACTGGGTCAGCGCGCGACCATTTCCTATCGCGCGAGCAAGAGTGTCAGTACGTCA 120 GTATC CTGGG CAG G GC ACCAT TC TA G GC AGCAA AGTGTCAGTAC TC Pfs48/45 orig 61 GTATCTCTGGGGCAGAGGGCCACCATCTCATACAGGGCCAGCAAAAGTGTCAGTACATCT 120

Pfs48/45 harm 121 GGCTACAGTTACATGCATTGGAATCAACAGAAGCCTGGTCAGCCTCCGCGCCTTCTTATT 180 GGCTA AGTTA ATGCA TGGAA CAACAGAA CC GG CAGCC CC G CT CT AT Pfs48/45 orig 121 GGCTATAGTTATATGCACTGGAACCAACAGAAACCAGGACAGCCACCCAGACTCCTCATC 180

Pfs48/45 harm 181 TACTTGGTAAGCAATTTAGAGAGCGGGGTCCCGGCGCGCTTTAGTGGCAGTGGGTCAGGG 240 TA T GTA CAA TAGA GGGGTCCC GC G TT AGTGGCAGTGGGTC GGG Pfs48/45 orig 181 TATCTTGTATCCAACCTAGAATCTGGGGTCCCTGCCAGGTTCAGTGGCAGTGGGTCTGGG 240

Pfs48/45 harm 241 ACGGATTTTACCCTTAATATTCACCCGGTGGAAGAAGAAGACGCGGCAACCTACTATTGT 300 AC GA TT ACCCT AA AT CA CC GTGGA GA GA GA GC GCAACCTA TA TGT Pfs48/45 orig 241 ACAGACTTCACCCTCAACATCCATCCTGTGGAGGAGGAGGATGCTGCAACCTATTACTGT 300

Pfs48/45 harm 301 CAGCACATTCGTGAGCTGACACGCTCTGAAGCGGGTACTAAACTGGAGATCAAAAGCTCT 360 CAGCACATT G GAGCT ACACG TC G AG GGG AC AAACTGGA ATCAAA CTCT Pfs48/45 orig 301 CAGCACATTAGGGAGCTTACACGTTC-GGAGGGGGGACCAAACTGGAAATCAAATCCTCT 359

Pfs48/45 harm 361 GGTGGTGGTGGAAGTGGCGGGGGTGGTGGTGGATCATCTCGTTCTAGCCTGGAGGTGATG 420 GGTGG GGTGG GGCGG GGTGG GGTGG TC TCT G TCT CCT GAGGTGATG Pfs48/45 orig 360 GGTGGCGGTGGCTCGGGCGGTGGTGGGGGTGGTTCCTCTAGATCTTCCCTCGAGGTGATG 419

Pfs48/45 harm 421 CTGGTTGAATCTGGTCCTGATCTGGTGAAACCGGGGGCGTCCGTGAAAATAAGCTGCAAA 480 CTGGT GA TCTGG CCTGA CTGGTGAA CC GGGGC TC GTGAA ATA CTGCAA Pfs48/45 orig 420 CTGGTGGAGTCTGGACCTGACCTGGTGAAGCCTGGGGCTTCAGTGAAGATATCCTGCAAG 479

Pfs48/45 harm 481 GCGTCAGGGTACTCCTTTATCAACTATTACATGCATTGGGTGAAACAGAGCCACGGTAAA 540 GC TC GG TA TC TT AT AA TA TA ATGCA TGGGTGAA CAGAGCCA GG AA Pfs48/45 orig 480 GCTTCTGGTTATTCATTCATTAATTACTATATGCACTGGGTGAAGCAGAGCCATGGAAAG 539

Pfs48/45 harm 541 AGCTTAGAATGGATCGGTCGAGTAAACCCGCAGAACGGGGGGACGCGCGATAATCAGAAG 600 AGC T GA TGGAT GG CGAGT AA CC CAGAA GG GG AC G GA AA CAGAA Pfs48/45 orig 540 AGCCTTGAGTGGATTGGACGAGTTAATCCTCAGAATGGTGGTACTAGGGACAACCAGAAA 599

Pfs48/45 harm 601 TTTAAAGGCAAAGCGATATTCACGGTAGATAAATCGTTTAATACGGCGTACATGGAGCTA 660 TT AA GGCAA GC ATATT AC GTAGA AA TC TT AA AC GC TA ATGGA CTA Pfs48/45 orig 600 TTCAAGGGCAAGGCCATATTTACTGTAGACAAGTCATTCAACACAGCCTATATGGAACTA 659

Pfs48/45 harm 661 CGGAGCCTGACGTCAGAAGATTCAGCTGTCTACTATTGTGCACGAGAAGTACACTATGAT 720 CG AGCCTGAC TC GA GA TC GC GTCTA TA TGTGCACGAGA GT CA TA GA Pfs48/45 orig 660 CGCAGCCTGACATCTGAGGACTCTGCGGTCTATTACTGTGCACGAGAGGTTCATTACGAC 719

Pfs48/45 harm 721 GAAGCGTTGGATTATTGGGGGCAAGGTACCTCCGTCACCGTCAGCTCCGCGAAGACGACG 780 GA GC TTGGA TA TGGGG CAAGG ACCTC GTCACCGTC CTC GC AA AC AC Pfs48/45 orig 720 GAGGCTTTGGACTACTGGGGTCAAGGAACCTCAGTCACCGTCTCCTCAGCCAAAACAACA 779

Pfs48/45 harm 781 CCGCCTTCAGTCACGAGTGCGGCCGC 806 CC CC TC GTCAC AGTGCGGCCGC Pfs48/45 orig 780 CCCCCATCTGTCACTAGTGCGGCCGC 805

Figure 2.9. Nucleotide sequence of the codon-harmonized anti-Pfs48/45 scFv. This is the nucleotide sequence of the scFv designed from sequence data of the MRA316 hybridoma line (MR4 Manassas, VA). Pfs48/45 orig = original gene sequence. Pfs48/45 harm = codon harmonized gene sequence.

Pfs230 opt 1 GGCGCGCCACAACCGGCTGAACTGGATATCGTTATGACCCAGAGCCACAAATTCATGAGT 60 GGCGCGCC CA CCGGC GA CT GA AT GT ATGACCCAG CACAAATTCATG Pfs230 orig 1 GGCGCGCCCCAGCCGGCCGAGCTCGACATTGTGATGACCCAGTCTCACAAATTCATGTCC 60

Pfs230 opt 61 ACCAGCGTCCGTGACCGTGTTAGTATCACGTGTAAAGCGTCCCAGGACGTGGGAACAGCG 120 AC GT G GAC G GT AG ATCAC TG AA GC CAGGA GTGGG AC GC Pfs230 orig 61 ACATCAGTAAGAGACAGGGTCAGCATCACCTGCAAGGCCAGTCAGGATGTGGGTACTGCT 120

Pfs230 opt 121 GTAGCATGGTATCAGCAAAAACCGGGACAGTCACCGAAACTGCTGATCTATTGGGCATCA 180 GTAGC TGGTATCA CA AAACC GG CA TC CC AAACT CTGAT TA TGGGCATC Pfs230 orig 121 GTAGCCTGGTATCAACAGAAACCAGGTCAATCTCCTAAACTACTGATTTACTGGGCATCC 180

Pfs230 opt 181 ACACGCCATACTGGTGTGCCGGACCGTTTCACCGGATCTGGAAGCGGAACCGATTTTACC 240 AC CG CA ACTGG GT CC GA CG TTCAC GG TGGA GG AC GATTT AC Pfs230 orig 181 ACCCGGCACACTGGAGTCCCTGATCGCTTCACAGGCAGTGGATCTGGGACAGATTTCACT 240

Pfs230 opt 241 CTGACGATTTCTAACGTTCAAAGCGAGGACCTGGCCGATTATTTCTGCCAACAGTATAGC 300 CT AC ATT AA GT CA GA GAC TGGC GATTATTTCTG CA CA TATAGC Pfs230 orig 241 CTCACCATTAGCAATGTGCAGTCTGAAGACTTGGCAGATTATTTCTGTCAGCAATATAGC 300

Pfs230 opt 301 ATCTATCCTCCGCTGACCTTTGGAGCAGGCACAAAACTGGAGCTGAAACACATCCGTGAA 360 ATCTATCCTCCGCT AC TT GG GC GG AC AA CTGGAGCTGAAACACAT CGTGA Pfs230 orig 301 ATCTATCCTCCGCTCACGTTCGGTGCTGGGACCAAGCTGGAGCTGAAACACATTCGTGAG 360

Pfs230 opt 361 CTGACCCGTTCTGAAGCAGGCACGAAACTGGAGATTAAAAGCTCGGGTGGTGGAGGTTCG 420 CTGAC CG TCTGAAGC GG AC AAACTGGAGAT AAAAGCTC GGTGGTGG GG Pfs230 orig 361 CTGACACGCTCTGAAGCGGGTACTAAACTGGAGATCAAAAGCTCTGGTGGTGGTGGAAGT 420

Pfs230 opt 421 GGAGGCGGGGGAGGTGGTTCTTCTCGTTCTAGCCTGGAGGTGATGCTGGTAGAATCTGGT 480 GG GG GG GG GGTGG TC TCTCGTTCTAGCCTGGAGGTGATGCTGGT GAATCTGGT Pfs230 orig 421 GGCGGGGGTGGTGGTGGATCATCTCGTTCTAGCCTGGAGGTGATGCTGGTTGAATCTGGT 480

Pfs230 opt 481 CCTGGTGGTAGCAGTCGTTCTAGTCTGGAAGTCAAACTGGTGGAAAGCGGCGGTGGTCTG 540 CCTGGTGGT C T G TCT CT GA GT AA CTGGTGGA GG GG GG T Pfs230 orig 481 CCTGGTGGTTCCTCTAGATCTTCCCTCGAGGTGAAGCTGGTGGAGTCTGGGGGAGGCTTA 540

Pfs230 opt 541 GTCCAACCTGGCGGTTCTCTGAAACTGAGTTGTGCTGCCTCTGGTTTCACTTTTAGCAAC 600 GT CA CCTGG GG TC CTGAAACT TGTGC GCCTCTGG TTCACTTT AG AAC Pfs230 orig 541 GTGCAGCCTGGAGGGTCCCTGAAACTCTCCTGTGCAGCCTCTGGATTCACTTTCAGTAAC 600

Pfs230 opt 601 TATTATATGAGCTGGGTTCGCCAGACGCCTGAAAAACGCCTGGAATGGGTTGCCTATATC 660 TATTA ATG TGGGTTCGCCAGAC CC GA AA G CTGGA TGGGT GC TA AT Pfs230 orig 601 TATTACATGTCTTGGGTTCGCCAGACTCCAGAGAAGAGGCTGGAGTGGGTCGCATACATT 660

Pfs230 opt 661 TCAAGCGGCGGTGGAAGCACTTATTATCCTGACAGCGTCAAAGGCCGTTTTACCATTAGC 720 AG GG GGTGG AGCAC TA TATCC GACAG GT AA GG CG TT ACCAT C Pfs230 orig 661 AGTAGTGGTGGTGGTAGCACCTACTATCCAGACAGTGTGAAGGGTCGATTCACCATCTCC 720

Pfs230 opt 721 CGTGACAATGCCAAAAACACGCTGTATCTGCAGATGTCTAGCCTGAAAAGCGAGGACACA 780 G GACAATGCCAA AACAC CTGTA CTGCA ATG AG CTGAA GAGGACACA Pfs230 orig 721 AGAGACAATGCCAAGAACACCCTGTACCTGCAAATGAGCAGTCTGAAGTCTGAGGACACA 780

Pfs230 opt 781 GCCATGTATTATTGTACCCGCCAAGAATGGTCACCATGGTTCGCTTATTGGGGTCAAGGA 840 GCCATGTATTA TGTAC G CA GAATGGTC CC TGGTT GCTTA TGGGG CAAGG Pfs230 orig 781 GCCATGTATTACTGTACAAGACAGGAATGGTCCCCCTGGTTTGCTTACTGGGGCCAAGGG 840

Pfs230 opt 841 ACCCTGGTTACAGTTTCTGCTGCCAAAACCACACCTCCGTCTGTTACAAGTGCGGCCGC 899 AC CTGGT AC GT TCTGC GCCAAAAC ACACC CC TCTGT AC AGTGCGGCCGC Pfs230 orig 841 ACTCTGGTCACTGTCTCTGCAGCCAAAACAACACCCCCATCTGTCACTAGTGCGGCCGC 899

Figure 2.10. Nucleotide sequence of the anti-Pfs230 scFv. This is the nucleotide sequence of the scFv designed from sequence data of the MRA878 hybridoma line (MR4 Manassas, VA). Pfs230 orig = original gene sequence. Pfs230 opt = optimized gene sequence.

comp opt 1 GGTGGGGGTGGTTCTATTGTTATGACACAGAGCCCGGCAACGCTGAGTGTAACGCCTGGT 60 ATTGT ATGAC CAGAGCCCGGC AC CTGAG GT AC CC GG comp orig 1 ------ATTGTGATGACCCAGAGCCCGGCGACCCTGAGCGTGACCCCGGGC 45 comp opt 61 GATAGTGTTAGCCTGAGCTGTCGTGCTTCTCAATCAATCGGGAATAATCTGCACTGGTAT 120 GATAG GT AGCCTGAGCTG CG GC CA AT GG AA AA CTGCA TGGTAT comp orig 46 GATAGCGTGAGCCTGAGCTGCCGCGCGAGCCAGAGCATTGGCAACAACCTGCATTGGTAT 105 comp opt 121 CAGCAAAAAAGCCATGAAAGCCCTCGTCTGCTGATCAAATATGCCAGCCAGTCCATTAGC 180 CAGCA AAAAGCCATGAAAGCCC CG CTGCTGAT AAATATGC AGCCAG CATTAGC comp orig 106 CAGCAGAAAAGCCATGAAAGCCCGCGCCTGCTGATTAAATATGCGAGCCAGAGCATTAGC 165 comp opt 181 GGCATTCCTAGCCGTTTTAGTGGCAGTGGTAGTGGTACGGATTTTACCCTGATTATCAAC 240 GGCATTCC AGCCG TTTAG GGCAG GG AG GG AC GATTTTACCCTGATTAT AAC comp orig 166 GGCATTCCGAGCCGCTTTAGCGGCAGCGGCAGCGGCACCGATTTTACCCTGATTATTAAC 225 comp opt 241 AGCGTGGAAACCGAAGATTTCGGCATGTATTTCTGCCAACAGACCAACATTTGGCCGTAT 300 AGCGTGGAAACCGAAGATTT GGCATGTATTT TGCCA CAGACCAACATTTGGCCGTAT comp orig 226 AGCGTGGAAACCGAAGATTTTGGCATGTATTTTTGCCAGCAGACCAACATTTGGCCGTAT 285 comp opt 301 ACCTTTGGTGGAGGGACAAAACTGGAGATTAAA------GGTGGTGGCGGTTCTGGTGGT 354 ACCTTTGG GG GG AC AAACTGGA ATTAAA GG GG GGCGG GG GG comp orig 286 ACCTTTGGCGGCGGCACCAAACTGGAAATTAAAAGCAGCGGCGGCGGCGGCAGCGGCGGC 345 comp opt 355 GGTGGA-TCTGGAGGAG-----GCGGTTCTGAAGTTCAGCTGCAGCAAAGTGGAGCCGAG 408 GG GG C G AG AG GC G GAAGT CAGCTGCAGCA AG GG GC GA comp orig 346 GGCGGCGGCGGCAGCAGCCGCAGCAGCCTGGAAGTGCAGCTGCAGCAGAGCGGCGCGGAA 405 comp opt 409 CTGGTTCGTTCTGGAGCATCAGTTCGCCTGAGTTGTACAGCAAGCGGCTTCAACATCAAA 468 CTGGT CG GG GC GT CGCCTGAG TG AC GC AGCGGCTT AACAT AAA comp orig 406 CTGGTGCGCAGCGGCGCGAGCGTGCGCCTGAGCTGCACCGCGAGCGGCTTTAACATTAAA 465 comp opt 469 GACTATTATATCCATTGGGTGAAACAGCGCCCTGAGCAAGGCCTGGAGTGGATCGGGTGG 528 GA TATTATAT CATTGGGTGAAACAGCGCCC GA CA GGCCTGGA TGGAT GG TGG comp orig 466 GATTATTATATTCATTGGGTGAAACAGCGCCCGGAACAGGGCCTGGAATGGATTGGCTGG 525 comp opt 529 ATCGACCCTGAAGATGGCGACACCGAATATGCCCCAAAATTCCAAGACAAAGCGACCATG 588 AT GA CC GAAGATGGCGA ACCGAATATGC CC AAATT CA GA AAAGCGACCATG comp orig 526 ATTGATCCGGAAGATGGCGATACCGAATATGCGCCGAAATTTCAGGATAAAGCGACCATG 585 comp opt 589 ACGGCGGATACAAGCTCTAATACTGCTTATCTGCAACTGCGTCGTCTGACAAGCGAGGAT 648 AC GCGGATAC AGC AA AC GC TATCTGCA CTGCG CG CTGAC AGCGA GAT comp orig 586 ACCGCGGATACCAGCAGCAACACCGCGTATCTGCAGCTGCGCCGCCTGACCAGCGAAGAT 645 comp opt 649 ACAGCGGTCTATTATTGTAACACGTGGCGTGGCTATGGAAACTATGACAGCATGGACTAT 708 AC GCGGT TATTATTG AACAC TGGCG GGCTATGG AACTATGA AGCATGGA TAT comp orig 646 ACCGCGGTGTATTATTGCAACACCTGGCGCGGCTATGGCAACTATGATAGCATGGATTAT 705 comp opt 709 TGGGGTCAGGGAACCTCTGTTACCGTGTCTAGCGCCAAAACAACACCTCCGTCAGTGACT 768 TGGGG CAGGG ACC GT ACCGTG AGCGC AAAAC AC CC CCG GTGAC comp orig 706 TGGGGCCAGGGCACCAGCGTGACCGTGAGCAGCGCGAAAACCACCCCGCCGAGCGTGACC 765 comp opt 769 AGTGGCGGGGGAGGCTCA 786 AG comp orig 766 AGC------768

Figure 2.11. Nucleotide sequence of the anti-human complement scFv. This is the nucleotide sequence of the scFv designed from sequence data of the CRL1757 hybridoma line (ATCC, Manassas, VA). The original sequenced gene is aligned to the codon- optimized gene sequence. Comp orig = original gene sequence. comp opt = optimized gene sequence.

Figure 2.12. Codon usage. This is the codon usage determination of the original anti- Pfs48/45 gene sequence as compared to mouse codon usage throughout the genome. The frequency of each codon in the sequence is displayed by the bar immediately above it. Red is used to indicate those codons occurring at or below a 15% frequency. Such rare codons determine where the ribosome slows translation, and they tend to occur in groups. Figure continued on next two pages.

Figure 2.12 continued. Codon usage. This is the codon usage determination of the original anti-Pfs48/45 gene sequence as compared to mouse codon usage throughout the genome. The frequency of each codon in the sequence is displayed by the bar immediately above it. Red is used to indicate those codons occurring at or below a 15% frequency. Such rare codons determine where the ribosome slows translation, and they tend to occur in groups. Figure continued on next page.

Figure 2.13. RNA hairpin-forming region of the anti-Pfs48/45 scFv gene. The predicted free energy at the start of the scFv gene was -49.60 kcal/mol, which is far lower than the -9 kcal/mol necessary to arrest translation. This hairpin-forming region was altered to prevent the formation of these secondary structures.

Figure 2.14. Bacterial recombination cloning protocol. The linearized pBBR1MCS-2 plasmid and bla PCR product with 40 nucleotides of homology to the vector on each end (shown in blue) were transformed into MG1655 E. coli competent cells. Native E. coli recombination functions combine the two pieces of DNA into a circular plasmid. The plasmid was selected by plating on LB medium with ampicillin, guaranteeing activity of the inserted bla gene.

Figure 2.15. pBBR1MCS-2. The vector pBBR1MCS-2 from (Kovach 1995), which was modified to create protein expression vectors. ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. lacZ alpha = β- galactosidase alpha fragment.

Figure 2.16. Plasmid constructs generated. The recombination product that replaced lacZ in pBBR1MCS-2 with bla, a new multiple cloning site, and a translational enhancer. ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. bla = beta lactamase, ampicillin resistance. enh = translational enhancer. Plac = promoter from the lac operon.

Figure 2.17. Plasmid constructs generated. The pNB20 plasmid with the lac promoter replaced by the nptII promoter. ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. bla = beta lactamase, ampicillin resistance. enh = translational enhancer. PnptII = promoter from neomycin phosphotransferase.

Figure 2.18. Modular scFv gene constructs. The plasmid pNB39 was produced by cloning the synthesized anti-Pfs25 scFv gene into plasmid pNB20. Afterwards, both the promoter and signal peptide were replaced to create a variety of protein/signal combinations using the gene fragments and promoters shown above. The gene fragments inserted or removed were directionally cloned using the restriction enzyme sites shown at the top of this figure. Ultimately, the gene constructs built and tested included the lac promoter with anti-BSA scFv and each leader peptide (Table 2.1 pNB55 and pNB59-66), the lac promoter with anti-Pfs25 scFv and the 5 Gluconobacter leader peptides (Table 2.1 pNB44-48), the nptII promoter with anti-Pfs25 scFv and each leader peptide (Table 2.1 pNB57 and pNB67-76), and both lac and nptII promoters with gfp (Table 2.1 pNB49 and pNB50). PnptII = promoter from neomycin phosphotransferase. Plac = promoter from the lac operon.

Figure 2.19. Protein production by E. coli and P. agglomerans expressing optimized scFv secretion constructs using the PelB leader. Protein was detected by an anti-Myc antibody from pellet and supernatant fractions of liquid bacteria culture. “pel” = pellet and “sup” = supernatant. The predicted size of the positive control HlyA-secreted scFv from pBS49 (Bisi 2011) is 60 kDa, and the predicted sizes of the PelB-secreted pNB39 product, anti-Pfs25 scFv, and the pNB38 product, anti-Pfs230 scFv, are each approximately 26 kDa. No protein was detected using either secretion construct, but the positive control was present.

Figure 2.20. Northern blot of RNA from E. coli strains expressing scFv genes. RNA was extracted from induced E. coli cultures expressing various scFv proteins and using different promoters. Each culture produced the correct size transcript as predicted. Each sample had two lanes, the first lane of each was uninduced sample, and the second was induced with IPTG for those plasmids under control of the lac promoter. Samples are: 1.) E. coli negative control, 2.) pDB51 anti-BSA scFv potitive control, 3.) pMAL MRA316 anti-Pfs48/45 scFv 4.) pDB48 anti-Pfs48/45 scFv, 5.) pBBR anti-Pfs48/45 scFv, 6.) pBBR anti-Pfs230 scFv clone 22, 7.) pBBR anti-Pfs230 scFv clone 23

Figure 2.21. pNB49. The GFP gene was inserted into plasmids pNB20 and pNB51 to produce plasmids for the expression of GFP by either the lac promoter (pNB49) or the nptII promoter (pNB50). ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. gfp = green fluorescent protein. enh = translational enhancer. Plac = promoter from the lac operon.

Figure 2.22. pNB50. Expression vector with gfp driven by the promoter from neomycin phosphotransferase. ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. gfp = green fluorescent protein. enh = translational enhancer. Plac = promoter from the lac operon.

A. B.

Figure 2.23. Expression of GFP by Asaia bogorensis. Asaia containing GFP expression plasmid constructs were viewed under a fluorescence microscope under excitation wavelength light of 395 nm. A.) Asaia transformed with the pNB49 plasmid, which has the gfp gene transcribed by the lac promoter, showed no fluorescence signal. B.) Asaia transformed with the pNB50 plasmid, which has the gfp gene transcribed by the nptII promoter, showed a strong fluorescence signal.

Figure 2.24. Protein production of Asaia expressing heterologous scFv secretion constructs using leader peptides from related species. Western blot detection of protein from Asaia strains containing scFv secretion constructs with Gluconobacter and Gluconacetobacter leader peptides. “pel” = pellet and “sup” = supernatant. The predicted sizes of the scFv constructs were 26 kDa. No protein was detected in pellet or supernatant fractions.

Figure 2.25. Protein production of Asaia expressing heterologous scFv secretion constructs using leader peptides from related species. Western blot detection of protein from Asaia strains containing scFv secretion constructs with Gluconobacter and Gluconacetobacter leader peptides. “pel” = pellet and “sup” = supernatant. (+) = anti- BSA scFv positive control protein expressed in E. coli, ~33kDa. The predicted sizes of the other scFv constructs were ~26 kDa. No protein was detected in pellet or supernatant fractions.

Table 2.1. Plasmids used in this study

Plasmid Relevant Characteristics Source pBBR1MCS-2 KanR, pBBR origin, oriT, MCS, used for plasmid construction Kovach 1995 pSC189 AmpR; used to amplify the beta lactamase (bla) gene Chiang 2002 pHM2-GFP KanR; used to amplify the neomycin phosphotransferase (nptII) promoter Favia 2007 pNB20 KanR; pBBR1MCS-2 w/ beta-lactamase and translational enhancer this study

R pNB51 Kan ; pNB20 w/ promoter region changed to PnptII this study MRA315 AmpR; codon optimized MRA315 anti-Pfs25 scFv as synthesized this study

MRA316 AmpR; codon harmonized MRA316 anti-Pfs48/45 scFv as synthesized this study MRA316opt AmpR; codon optimized MRA316 anti-Pfs48/45 scFv as synthesized this study MRA878 AmpR; codon optimized MRA878 anti-Pfs230 scFv as synthesized this study IgG scFv AmpR; codon optimized anti-human IgG scFv as synthesized this study pNB20 KanR; pBBR1MCS-2 with a novel cloning site this study pNB21 KanR; pNB20 with an AscI restriction site added for cloning purposes. this study pDB48 GentR; pelB-AscI-6His-myc-STOP cloned in pMQ64 MCS Bisi 2011 pDB51 GentR; pelB-Anti-BSA scFv (positive control for experiments) Bisi 2011 pDB49 AprR; hlyA-Anti-BSA scFv (positive control for experiments) Bisi 2011 pVDL9.3 CamR; production of hlyB and hlyD transporters (Tzschaschel 1996) pNB39 KanR; pNB20 with anti-Pfs25 scFv insert this study pNB38 KanR; pNB20 with anti-Pfs230 scFv insert this study pNB37 KanR; pNB20 with anti-Pfs48/45 scFv insert this study pNB44 KanR; anti-Pfs25 scFv with G. oxydans endonuclease I signal peptide this study pNB45 KanR; anti-Pfs25 scFv with G. oxydans endonuclease II signal peptide this study pNB46 KanR; anti-Pfs25 scFv with G. oxydans poly phosphate porin signal peptide this study pNB47 KanR; anti-Pfs25 scFv with G. oxydans aminopeptidase signal peptide this study pNB48 KanR; anti-Pfs25 scFv with G. oxydans acid phosphatase signal peptide this study R pNB49 Kan ; pNB20 with Plac GFP this study R pNB50 Kan ; pNB20 with PnptII GFP this study pNB55 KanR; pNB39 with anti-BSA scFv this study R pNB57 Kan ; pNB51 with PnptII G. diazotrophicus levansucrase signal, Pfs25 scFv this study pNB59 KanR; pNB55 with G. diazotrophicus organic solvent tolerance signal peptide this study pNB60 KanR; pNB55 with G. diazotrophicus poly phosphate porin signal peptide this study pNB61 KanR; pNB55 with G. diazotrophicus endonuclease II signal peptide this study

pNB62 KanR; pNB55 with G. diazotrophicus aminopeptidase signal peptide this study pNB63 KanR; pNB55 with G. diazotrophicus phospholipase signal peptide this study pNB64 KanR; pNB55 with G. diazotrophicus acid phosphatase signal peptide this study pNB65 KanR; pNB55 with G. diazotrophicus endonuclease I signal peptide this study pNB66 KanR; pNB55 with G. diazotrophicus levansucrase signal peptide this study pNB67 KanR; pNB57 with G. diazotrophicus organic solvent tolerance signal peptide this study pNB68 KanR; pNB57 with G. oxydans aminopeptidase signal peptide this study pNB69 KanR; pNB57 with G. ozydans endonuclease I signal peptide this study pNB70 KanR; pNB57 with G. oxydans endonuclease II signal peptide this study pNB71 KanR; pNB57 with G. diazotrophicus aminopeptidase M28 signal peptide this study pNB72 KanR; pNB57 with G. diazotrophicus polyphosphate porin signal peptide this study pNB73 KanR; pNB57 with G. diazotrophicus invasion-associated locus B signal peptide this study pNB74 KanR; pNB57 with G. diazotrophicus phospholipase C signal peptide this study pNB75 KanR; pNB57 with G. diazotrophicus glycoside signal peptide this study pNB76 KanR; pNB57 with G. diazotrophicus putative aminopeptidase signal peptide this study

Table 2.2. Oligonucleotides used in this study

Oligo Sequence 5' - 3' Purpose Vκ 5' Sense Primers MSCVK-1 GGG CCC AGC CGG CCG AGC TCG AYA TCC AGC TGA CTC AGC antibody V-region C amplification (Barbas 2001) MSCVK-2 GGG CCC AGC CGG CCG AGC TCG AYA TTG TTC TCW CCC AGT C '' MSCVK-3 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGM TMA CTC AGT '' C MSCVK-4 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGY TRA CAC AGT C '' MSCVK-5 GGG CCC AGC CGG CCG AGC TCG AYA TTG TRA TGA CMC AGT '' C MSCVK-6 GGG CCC AGC CGG CCG AGC TCG AYA TTM AGA TRA MCC AGT '' C MSCVK-7 GGG CCC AGC CGG CCG AGC TCG AYA TTC AGA TGA YDC AGT '' C MSCVK-8 GGG CCC AGC CGG CCG AGC TCG AYA TYC AGA TGA CAC AGA '' C MSCVK-9 GGG CCC AGC CGG CCG AGC TCG AYA TTG TTC TCA WCC AGT '' C MSCVK-10 GGG CCC AGC CGG CCG AGC TCG AYA TTG WGC TSA CCC AAT '' C MSCVK-11 GGG CCC AGC CGG CCG AGC TCG AYA TTS TRA TGA CCC ART C '' MSCVK-12 GGG CCC AGC CGG CCG AGC TCG AYR TTK TGA TGA CCC ARA C '' MSCVK-13 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGA TGA CBC AGK '' C MSCVK-14 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGA TAA CYC AGG '' A MSCVK-15 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGA TGA CCC AGW '' T MSCVK-16 GGG CCC AGC CGG CCG AGC TCG AYA TTG TGA TGA CAC AAC '' C MSCVK-17 GGG CCC AGC CGG CCG AGC TCG AYA TTT TGC TGA CTC AGT C '' VΚ 3' REVERSE PRIMERS, SHORT LINKER MSCJK12-B GGA AGA TCT AGA GGA ACC ACC TTT KAT TTC CAG YTT GGT '' CCC MSCJK4-B GGA AGA TCT AGA GGA ACC ACC TTT TAT TTC CAA CTT TGT '' CCC MSCJK5-B GGA AGA TCT AGA GGA ACC ACC TTT CAG CTC CAG CTT GGT '' CCC VΚ 3' REVERSE PRIMERS, LONG LINKER MSCJK12-BL GGA AGA TCT AGA GGA ACC ACC CCC ACC ACC GCC CGA GCC '' ACC GCC ACC AGA GGA TTT KAT TTC CAG YTT GGT CCC MSCJK4-BL GGA AGA TCT AGA GGA ACC ACC CCC ACC ACC GCC CGA GCC ''

ACC GCC ACC AGA GGA TTT TAT TTC CAA CTT TGT CCC MSCJK5-BL GGA AGA TCT AGA GGA ACC ACC CCC ACC ACC GCC CGA GCC '' ACC GCC ACC AGA GGA TTT CAG CTC CAG CTT GGT CCC VΛ 5' SENSE PRIMER MSCVL-1 GGG CCC AGC CGG CCG AGC TCG ATG CTG TTG TGA CTC AGG '' AAT C VΛ 3' REVERSE PRIMER, SHORT LINKER MSCJL-B GGA AGA TCT AGA GGA ACC ACC GCC TAG GAC AGT CAG TTT '' GG

VΛ 3' REVERSE PRIMER, LONG LINKER MSCJL-BL GGA AGA TCT AGA GGA ACC ACC CCC ACC ACC GCC CGA GCC '' ACC GCC ACC AGA GGA GCC TAG GAC AGT CAG TTT GG VΗ 5' SENSE PRIMERS MSCVH1 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTR MAG CTT CAG '' GAG TC MSCVH2 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTB CAG CTB CAG '' CAG TC MSCVH3 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG CAG CTG AAG '' SAS TC MSCVH4 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTC CAR CTG CAA '' CAR TC MSCVH5 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTY CAG CTB CAG '' CAR TC MSCVH6 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTY CAR CTG CAG '' CAG TC MSCVH7 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTC CAC GTG AAG '' CAG TC MSCVH8 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AAS STG GTG '' GAA TC MSCVH9 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AWG YTG GTG '' GAG TC MSCVH10 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG CAG SKG GTG '' GAG TC MSCVH11 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG CAM CTG GTG '' GAG TC MSCVH12 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AAG CTG ATG '' GAR TC MSCVH13 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG CAR CTT GTT '' GAG TC MSCVH14 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTR AAG CTT CTC '' GAG TC MSCVH15 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AAR STT GAG '' GAG TC MSCVH16 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTT ACT CTR AAA '' GWG TST G

MSCVH17 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTC CAA CTV CAG '' CAR CC MSCVH18 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AAC TTG GAA '' GTG TC MSCVH19 GGT GGT TCC TCT AGA TCT TCC CTC GAG GTG AAG GTC ATC '' GAG TC VΗ 3' REVERSE PRIMERS MSCG1ab-B CCT GCG GCC GCA CTA GTG ACA GAT GGG GST GTY GTT TTG antibody V gene GC amplification and cloning with NotI restriction site MSCG3-B CCT GCG GCC GCA CTA GTG ACA GAT GGG GCT GTT GTT GT '' MSCM-B CCT GCG GCC GCA CTA GTG ACA TTT GGG AAG GAC TGA CTC '' TC OVERLAP EXTENSION PRIMERS RSC-F sense GAG GAG GAG GAG GAG GAG GCG GGG CCC AGC CGG CCG AGC '' TC RSC-B reverse GAG GAG GAG GAG GAG GAG CCT GCG GCC GCA CTA GTG '' pBBR rec F ggaattgtgagcggataacaatttcacacaggaaacagctTTAACTTTAAGAAGG bacterial AGactgCATATGagtattcaacatttccg recombination to generate pNB20 pBBR rec R taacaaaaatttaacgcgaattttaacaaaatattaacgcGAATTCggatccGGC '' CGGCCcctgcaggTTAATTAAggtctgacagttaccaatgc PnptII F NsiI TAatgcatAACCGGAATTGCCAGCTGGG nptII promoter directional cloning in pNB51 PnptII R taCATATGTTTTTCCTCCTTATAAAGTTAATC '' NdeI Gd TACATATGGCGCATGTACGCCGAAAAG Gluconacetobacter levansucrase F diazotrophicus leader NdeI cloning Gd TAGGCGCGCCATTCCCTTGCGCCAGCGCAC '' levansucrase R AscI Gd TrbJ F TACATATGAAATACGGCATGCGTCTTTATG '' NdeI Gd TrbJ R TAGGCGCGCCGTTCGCACCGTCATACAC '' AscI Gd TACATATGCGTTCCATGCCCC '' aminopeptidas e F NdeI Gd TAGGCGCGCCCGGCGCCCACGGGGAC '' aminopeptidas e R AscI Gd IalB F TACATATGAAACTTTTCACTCCTG '' NdeI

Gd IalB R TAGGCGCGCCATGCGTCGAGGCCTGGGCCAC '' AscI Gd OSP F TACATATGATGCCGATCCTGATGTC '' NdeI Gd OSP R TAGGCGCGCCCTGGACCTGCGCATGGG '' AscI Gd TACATATGGCCACACGCAGAGATTTC '' phospholipase C F NdeI Gd TAGGCGCGCCATTCGGTGCAATGGCGAAAG '' phospholipase C R AscI Gd Peptidase TACATATGCCCCCCCATCGTC '' M28 F NdeI Gd Peptidase TAGGCGCGCCCCACGGGGACGCGGCATGCG '' M28 R AscI Gd glycoside TACATATGACCGGGTTCCGTCCATC '' F NdeI Gd glycoside TAGGCGCGCCCAGACCGCCGGCCGAAG '' R AscI GFP F NdeI TACATATGAGTAAAGGAGAAG gfp gene cloning GFP R EcoRI TAGAATTCCTATTTGTATAGTTCATCCATGCC '' GluconoEndon ATCATATGCGCTTTCTGATTGCCGTTTTAC Gluconobacter uc 1-5’ NdeF oxydans leader cloning GluconoERnd ATGGCGCGCCTGCGATGGCTGGAGATGTG '' onuc1 leader Asc R GluconoAPho ATCATATGTCCATGAAGCGCGTACAAC '' s 5’ NdeF GluconoAPho ATGGCGCGCCCGCAGAAGAAGACGCTGCCAGCC '' s leader AscR GluconoAmPe ATCATATGACACAGAAGACATTCCC '' p 5’ NdeF GluconoAmPe ATGGCGCGCCGGCATGACCGGTGACCGGAG '' p leader AscR GluconoEndon ATGATATGAATTTCCTGTCGTATCTTC '' uc 2 5’ NdeF GluconoEndon ATGGCGCGCCAGCCTGCGCCGGAAGCACGA '' uc2 leader AscR GluconoPolyP ATCATATGGTTTTTTCTTTCCGCCG '' hosPorin 5’ NdeF GluconoPolyP ATGGCGCGCCGGCCCGGGCATGGCCACAAAGAG '' hosPorin leader AscR

Table 2.3. Bacterial strains used in this study

Strain Genotype Purpose E. coli K-12 F- lambda- ilvG- rfb-50 rph-1 (McKenzie bacterial MG1655 2006) recombination E. coli Top10 F' F´{lacIq, Tn10(TetR)} mcrA Δ(mrr-hsdRMS- molecular cloning mcrBC) Φ80lacZΔM15 ΔlacX74 recA1 and plasmid araD139 Δ(ara leu) 7697 galU galK rpsL propagation (StrR) endA1 nupG (from life technologies #C3030-03) (Durfee 2008) Asaia SF2.1 wild type (from Guido Favia, University of gene expression, Camerino, Italy) (Favia 2007) paratransgenesis Pantoea wild type (Gavini 1989) gene expression, agglomerans paratransgenesis Gluconobacter wild type (ATCC cat# 33448) (Angyal 1996) amplification of oxydans leader peptides Gluconacetobacter wild type (ATCC cat# 49039) (Yamada 1997) amplification of diazotrophicus leader peptides

Table 2.4. Secretion signals cloned from acetic acid bacteria

Protein leader sequence Path Species acid phosphatase MSMKRVQRAKSGLAVLLSGSILLPSVGLAASSSA Sec G. oxydans aminopeptidase MTQKTFPRRSLFLATVLTAVLLAPVTGHA Sec G. oxydans endonuclease I MRFLIAVLLACTSPAIA Sec G. oxydans endonuclease II MNFLSYLPICALLVVLPAQA Sec G. oxydans polyphosphate porin MVFSFRRTTALLATTTLVSLLPLCGHARA Sec G. oxydans TrbJ MKYGMRLYVTIGVISITIISSARAQWAVYDGAN Sec G. diazotrophicus phospholipase C MATRRDFLKYALLSGAAGGASLLSDPIRRAFAIAPN Tat G. diazotrophicus organic solvent MMPILMSRRLFRPARGQRSQARGTLLAAGLLGSTF Sec G. diazotrophicus tolerance LGAVIQVHRAHAQVQ peptidase M28 MPPHRPRAALVSAMLLAAASPAHAASPW Sec G. diazotrophicus levansucrase MAHVRRKVATLNMALAGSLLMVLGAQSALAQGN Sec G. diazotrophicus invasion-associated MKLFTPVPLVAVIGGAAAALTLGVAYSGHSGPGVA Sec G. diazotrophicus locus B QASTH glycoside hydrolase MTGFRPSHVLVIACLVCLVMAGGAARAASAGGL Sec G. diazotrophicus aminopeptidase MRSMPPHRPRAALVSAMLLAAASPAHAASPWAP Sec G. diazotrophicus m28 Secretion signals were cloned in-frame with expression constructs by PCR amplification with primers and directional cloning by restriction enzyme digestion and insertion into plasmids. Secretion signal pathways identified using PRED-TAT (http://www.compgen.org/tools/PRED-TAT/).

Chapter 3

Fighting malaria with engineered symbiotic bacteria from vector mosquitoes

Sibao Wang, Anil K. Ghosh, Nicholas Bongio, Kevin A. Stebbings, David J. Lampe, and Marcelo Jacobs-Lorena

Reprinted from Proceedings of the National Academy of Sciences, Vol.109, No. 31,

Sibao Wang, Anil K. Ghosh, Nicholas Bongio, Kevin A. Stebbings, David J. Lampe, and

Marcelo Jacobs-Lorena, Fighting malaria with engineered symbiotic bacteria from vector mosquitoes. pages 12734-12739., Copyright (2012) with permission from PNAS.

CHAPTER 3 ATTRIBUTIONS

 I performed the molecular cloning of hemolysin secretion constructs and tested

them for secretion by western blot.

 Kevin A. Stebbings, an undergraduate in Dr. Lampe's laboratory, was mentored

by me and contributed to the molecular cloning and testing of secretion

constructs.

 Sibao Wang, a post-doc in Dr. Marcelo Jacobs-Lorena's laboratory, conducted

transmission-blocking assays.

 Anil K. Ghosh, a post-doc in Dr. Marcelo Jacobs-Lorena's laboratory, performed

the immunofluorescence assays.

INTRODUCTION

Malaria is one of the most lethal infectious diseases. Close to half of the population of the world is at risk, about 300–500 million contract the disease annually, and about 1.2 million people die of malaria every year (Murray 2012). Continuous emergence of mosquito insecticide resistance and parasite drug resistance, combined with the lack of an effective malaria vaccine, severely limits our ability to counteract this intolerable burden (Enayati 2010, Trape 2011). New weapons to fight the disease are urgently needed.

Unlike the other two major infectious diseases (AIDS and tuberculosis) that are transmitted directly from person to person, transmission of Plasmodium, the causative agent of malaria, strictly depends on the completion of a complex developmental cycle in vector mosquitoes (Ghosh 2000). A mosquito may ingest on the order of 103 to 104 gametocytes from an infected human that quickly differentiate into male and female gametes that mate to produce zygotes, which, in turn, differentiate into 102 to 103 motile ookinetes. Ookinetes then migrate within the blood bolus until they reach the midgut epithelium, where they then traverse and differentiate into oocysts. Upon maturation, each oocyst releases thousands of sporozoites into the hemocoel, followed by invasion of the mosquito salivary glands. The transmission cycle is completed when the infected mosquito bites the next vertebrate host and delivers some of the sporozoites with the saliva (Whitten 2006). Clearly, a severe bottleneck occurs during the mosquito midgut stages of parasite development: even in areas of high transmission, mosquitoes typically

carry five or fewer oocysts (Whitten 2006). This bottleneck makes the mosquito midgut a prime target for intervention (Eappen 2004, Drexler 2008).

One option to interfere with parasite transmission is to genetically modify mosquitoes for midgut expression of “effector genes” that inhibit parasite development.

Past evidence suggests that this strategy works successfully in the laboratory (Ito 2002,

Isaacs 2011, Marrelli 2007, Corby-Harris 2010). However, one unresolved challenge is how to drive transgenes into wild mosquito populations. Various genetic drive mechanisms have been proposed to accomplish this goal (Chen 2007, Windbichler 2011), but these are technically very challenging, and it is not clear in what time frame they will succeed. An important additional challenge faced by genetic drive approaches, in general, is that anopheline vectors frequently occur in the field as reproductively isolated populations, thus posing a barrier for gene flow from one population to another.

An alternative strategy to deliver effector molecules is to engineer symbiotic bacteria from the mosquito midgut microbiome to produce the interfering proteins

(paratransgenesis) (Durvasula 1997). A key strategic consideration is that the mosquito microbiome (Pumpuni 1996, Straif 1998) resides in the same compartment where the most vulnerable stages of malaria parasite development occur (Drexler 2008). Moreover, bacteria numbers increase dramatically (hundreds- to thousands-fold) after ingestion of a blood meal (Pumpuni 1996), and output of anti-Plasmodium effector molecules from engineered bacteria can be expected to increase proportionally.

Paratransgenesis has shown promise for the control of other insect-borne disease

(Durvasula 1997). Chagas disease caused by the parasitic protozoan Trypanosoma cruzi

is transmitted by the triatomid bug, Rhodnius prolixus. In proof-of-concept experiments, an obligate commensal Gram-positive bacterium was genetically modified to secrete cecropin A, a peptide that kills Trypanasoma cruzi, making the bug refractory to the parasite (Durvasula 1997). Our previous study using the rodent malaria parasite

Plasmodium berghei and the Anopheles stephensi vector mosquito suggested that recombinant Escherichia coli expressing on their surface either a dimer of the salivary gland and midgut peptide 1 (SM1) or a modified phospholipase reduced oocyst formation

(Riehla 2007). Yoshida et al. 2001 also showed that recombinant E. coli expressing a single-chain immunotoxin significantly reduces P. berghei oocyst density in A. stephensi mosquitoes. One limitation of these earlier experiments is that they used E. coli, an attenuated laboratory bacterium that survives poorly in the mosquito gut (Riehla 2007). A second limitation was that the recombinant effector molecules either remained attached to the bacterial surface (Riehla 2007) or formed an insoluble inclusion body within the bacterial cells (Yoshida 2001), thus preventing diffusion of the effector molecules to their parasite or mosquito midgut targets.

Here, we describe a substantially improved strategy to deliver effector molecules by engineering a natural symbiotic bacterium Pantoea agglomerans(previously known as

Enterobacter agglomerans) to secrete antimalaria proteins in the mosquito midgut. We found that the development of the human parasite Plasmodium falciparum and the rodent parasite P. berghei in the mosquito was efficiently suppressed by up to 98%.

MATERIALS AND METHODS

Mosquito and Parasite Maintenance.

We used two mosquitoes (A. gambiae Keele strain and A. stephensi Dutch strain) and two parasites P. falciparum strain NF54 and P. berghei ANKA 2.34. Mosquitoes and parasites were maintained as described in SI Text.

Bacterial Introduction into Mosquitoes via Sugar Meals.

P. agglomerans were introduced into mosquitoes by feeding them with cotton pads soaked with a bacteria suspension (109 cells/mL) in 5% (wt/vol) sugar as described in SI

Text.

Plasmid Construction and Protein Expression.

The synthesized DNA encoding anti-Plasmodium effector molecules were optimized with the P. agglomerans preferred codon usage. Plasmid construction, bacterial genetic transformation, and verification of protein secretion using Western blot analysis were performed as described in SI Text.

P. falciparum Transmission-Blocking Assays.

Recombinant bacterial suspensions [1 × 109 cells/mL of 5% (wt/vol) sugar] soaked in cotton pads were fed to 2-d-old A. gambiae for 24 h, which were then starved for 8 h and allowed to feed for 30 min on a P. falciparum NF54 gametocyte–containing

blood meal. Fully engorged mosquitoes were separated within 24 h. Success of parasite infection was evaluated by counting oocyst numbers at 8 d postinfection.

P. berghei Transmission-Blocking Assays.

Different groups of bacteria-fed mosquitoes were allowed to feed on the same P. berghei–infected mouse for 6 min and then maintained at 19 °C at 80% relative humidity.

Success of parasite infection was evaluated by counting oocyst numbers at 14 d postinfection.

Immunofluorescence Assays.

Recombinant P. agglomerans bacteria expressing (SM1)2 were introduced to 2-d- old A. gambiae females via sugar meal (1 × 109cells/mL) for 24 h. The mosquitoes were then allowed to feed on a noninfected mouse for 30 min. Midgut sheets were prepared at

18 and 24 h after blood feeding and fixed overnight in 4% (wt/vol) paraformaldehyde at 4

°C, washed in PBS, and blocked with 4% (wt/vol) BSA at 4 °C. The gut sheets were then probed with anti-SM1 peptide antibody (1:1,000), followed by Alexa Fluor–conjugated goat anti-rabbit IgG (Sigma; 1:1,000). Nuclei were stained with 4′,6-diamidino-2- phenylindole (DAPI).

RESULTS

Administration of Transgenic P. agglomerans via Sugar Meals and Rapid

Proliferation After a Blood Meal.

P. agglomerans is a natural symbiotic bacterium whose occurrence is widespread in anopheline mosquitoes (Pumpuni 1996, Straif 1998, Riehle 2007). Our strain was originally isolated from midguts of an Anopheles gambiae laboratory colony and subsequently further selected for improved adaptation to the A. gambiae and A. stephensi midgut environments (Riehle 2007). To examine recombinant P. agglomerans colonization and survival in the mosquito midgut, we transformed P. agglomerans with a highly stable plasmid pPnptII:gfp (Stiner 2002) that expresses green fluorescent protein

(GFP). We found the GFP-tagged bacteria were easily administered to mosquito midguts via sugar meals (Figure S1). Midguts of female mosquitoes that had been fed GFP- tagged P. agglomerans became strongly fluorescent after ingestion of a blood meal

(Figure 3.1 A and B), indicating rapid bacteria proliferation. To quantify the dynamics of bacteria numbers, mosquitoes that had been fed GFP-tagged P. agglomerans were dissected at different times after a blood meal and midgut homogenates were plated on selective kanamycin-containing plates. Bacteria numbers increased dramatically by more than 200-fold during the first 2 d after a blood meal (Figure 3.1C). Thereafter, bacteria numbers decreased to about prefeeding levels, presumably because the majority was excreted together with the remnants of blood digestion.

Recombinant P. agglomerans Strains Efficiently Secrete Anti-Plasmodium Effector

Molecules.

As mentioned previously, for maximum effectiveness of intervention, it is crucial that the effector molecules be secreted from the engineered bacteria to allow diffusion to the parasite or mosquito midgut targets. We used the E. coli hemolysin (Hly)A system

(Fernandez 2000, Tzschaschel 1996, Fernandez 2001) to promote protein secretion from

P. agglomerans. This type 1 secretion system requires three components to form a membrane pore (inner membrane components HlyB and HlyD and outer membrane component TolC). The HlyB–HlyD complex recognizes the C-terminal secretion signal of HlyA to guide direct export of HlyA-fusion proteins from the bacterial cytoplasm into the extracellular environment bypassing the periplasmic space (Figure S2A).

We used the HlyA secretion system to test the following anti-Plasmodium effector molecules (Table S.1): (i) two copies of the 12-aa SM1 peptide [(SM1)2], which binds to the luminal surface of the mosquito midgut and blocks ookinete midgut invasion

(Ghosh 2001); (ii) a mutant phospholipase mPLA2 that inhibits ookinete invasion, probably by modifying the properties of the midgut epithelial membrane (Moreira 2002);

(iii) a single-chain immunotoxin (pbs21scFv-Shiva1), composed of a single-chain monoclonal antibody (scFv) targeting the P. berghei major ookinete surface protein pbs21 and linked to the lytic peptide Shiva1 (Yoshida 2001); (iv) a chitinase propeptide

(Pro) that inhibits the enzyme and blocks ookinete traversal of the mosquito peritrophic matrix (Bhatnagar 2003); (v) a synthetic antiparasitic lytic peptide, Shiva1 (Jaynes 1988);

(vi) a scorpion (Pandinus imperator) antimalaria lytic peptide, scorpine, which has

hybrid properties of the lytic peptides cecropin and defensin (Conde 2000); (vii) four copies of Plasmodium enolase–plasminogen interaction peptide (EPIP) [(EPIP)4] that inhibits mosquito midgut invasion by preventing plasminogen binding to the ookinete surface (Ghosh 2011); and (viii) a fusion peptide composed of Pro and EPIP (Pro:EPIP).

All genes were synthesized with the P. agglomerans preferred codon usage (Table S2) and cloned in frame with an E-tagged C-terminal secretion signal domain of HlyA in a high-copy expression vector (Figures S2B and S3). The resulting plasmids were individually transformed into P. agglomerans together with the low-copy plasmid pVDL9.3 coding for HlyB and HlyD (Fernandez 2000). Constitutive expression and secretion of a fusion protein of the predicted size by each recombinant P. agglomerans strain were verified by Western blot analysis (Figure 3.2A). The smaller sized peptides

[(EPIP)4, Shiva1, and Pro:EPIP] were more abundant in the culture supernatant than the larger sized proteins (mPLA2 and pbs21fsFv-Shiva1) (Figure 3.2A). The recombinant P. agglomerans strain expressing (EPIP)4 had the highest secretion level, appearing to be more efficient than the recombinant strain carrying the parental E-HlyA plasmid (Figure

3.2A). In vivo secretion of anti-Plasmodium effector molecules in the mosquito midgut was confirmed by use of immunofluorescence assays that detected the binding of the bacteria-produced SM1 peptide to the midgut epithelial surface (Figure 3.2B). Control midguts from mosquitoes fed on recombinant P. agglomerans expressing E-tagged HlyA alone (HlyA) had no fluorescence above background.

Recombinant P. agglomerans Strains Efficiently Impair P. falciparum Development in Mosquitoes.

To assess the effectiveness with which recombinant bacteria interfere with the development of the human malaria parasite P. falciparum in mosquitoes, recombinant P. agglomerans were administered to mosquitoes via cotton pads soaked with bacteria suspended in 5% (wt/vol) sucrose solution. Thirty-two hours later, mosquitoes were provided a P. falciparum–infected blood meal. Success of parasite development was evaluated by counting oocyst numbers on day 8 after the infectious blood meal. Initial experiments were conducted to evaluate the inhibition potential of recombinant P. agglomerans secreting a chitinase propeptide (Pro) compared with administration of the synthetic propeptide mixed with the blood meal. The propeptide inhibits Plasmodium chitinase activity and, thus, prevents crossing of the peritrophic matrix, resulting in decreased number of ookinetes that reach the midgut epithelium (Bhatnagar 2003). As shown in Figure S4, inhibition by P. agglomerans expressing the propeptide was effective, on the order of 59% inhibition in highly infected mosquitoes (also see comments concerning infection intensity under Discussion). Next, we evaluated the inhibitory capacity of the various recombinant P. agglomerans strains. As shown in

Figure 3.3, the recombinant P. agglomerans strain expressing E-tagged HlyA alone did not significantly inhibit oocyst formation compared with minus bacteria controls.

Recombinant P. agglomerans expressing mPLA2, Pro:EPIP, or Shiva1 had a 85%, 87%, and 94% decrease in oocyst numbers, respectively. Recombinant P. agglomerans expressing scorpine or (EPIP)4 had the highest inhibition (98%) of oocyst formation

(Figure 3.3). Importantly, infection prevalence (percentage of mosquitoes that have one

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or more oocysts) was 90% in −Bact (control) mosquitoes and was reduced to 14% in mosquitoes carrying scorpine-secreting bacteria, representing an 84% transmission- blocking potential.

To evaluate the persistence of the inhibitory effect, we compared oocyst numbers in mosquitoes that were fed the same batch of infective blood meal at either 2 d (our standard procedure) or 4 d after bacterial administration. These experiments also evaluated the effect of mixing bacteria expressing two different effector proteins, [shiva1

+ (EPIP)4] and [scorpine + (EPIP)4], on inhibition of P. falciparum infection. As shown in Figure 3.4, inhibition of oocyst development was similar at both time points. Thus, the inhibitory effect of the bacteria lasts for at least 4 d after bacteria administration. Also, inhibition by a mixture of bacteria expressing two effectors (Figure 3.4) was similar to that of bacteria expressing a single effector (Figure 3.3). Possible reasons for this are considered under Discussion.

Recombinant P. agglomerans Strains Efficiently Impair P. berghei Development in

Mosquitoes.

We also evaluated the effectiveness of recombinant P. agglomerans strains to inhibit development of the rodent malaria parasite P. berghei in A. stephensi mosquitoes.

Mosquitoes harboring various recombinant bacterial strains were allowed to feed on the same P. berghei–infected mouse, followed by determination of oocyst numbers on day 14 post infection. The recombinant P. agglomerans strain expressing (SM1)2 reduced mean oocyst counts by 68%, an equal mixture of bacteria expressing pbs21scFv-shiva1 +

(EPIP)4 reduced oocyst counts by 79%, and a mixture of scorpine- and (EPIP)4-

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expressing bacteria reduced oocyst counts by 83% (Figure 3.5), despite relatively high infection rates (>60 oocysts per midgut; also see Discussion). No significant reduction was observed in the presence of the recombinant P. agglomerans strain expressing E- tagged HlyA alone (HlyA).

Recombinant P. agglomerans Strains Do Not Affect Mosquito Longevity.

A recombinant bacterium with minimal fitness cost to mosquitoes is also an important factor for the success of future field applications. To examine the impact of recombinant P. agglomerans strains expressing anti-Plasmodium molecules on mosquito lifespan, mosquitoes were fed on sugar alone or on various recombinant P. agglomerans and, 32 h later, were allowed to feed on a noninfected mouse. Thereafter, mortality was monitored twice daily. No significant differences in mosquito lifespan was detected among any of the mosquito groups (Figure 3.6), suggesting these recombinant anti-

Plasmodium products pose no obvious negative impact on mosquito fitness in laboratory conditions.

DISCUSSION

Although current malaria control strategies targeting the mosquito vector and the parasite have helped alleviate the malaria burden in many endemic areas (Greenwood

2008), the emergence and rapid spreading of insecticide-resistant mosquitoes and drug- resistant parasites undermine such efforts (Trape 2011). The Malaria Eradication

Research Agenda (malERA) consultative group recently noted that malaria eradication will not be achieved without help of novel control tools (Baum 2011). Here, we report on

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an alternative strategy to deliver antimalaria effector molecules to the mosquito midgut via engineered symbiotic bacteria.

The mosquito midgut serves as a prime target for blocking parasite transmission with engineered bacteria for two main reasons: (i) the most vulnerable part of the

Plasmodium cycle in the mosquito and a bottleneck in parasite numbers occur in the mosquito midgut lumen (Whitten 2006); and (ii) the midgut compartment is shared between Plasmodium and the mosquito microbiome, directly exposing parasites to compounds secreted by resident bacteria. Furthermore, the number of bacteria in the mosquito midgut increases dramatically (by two to three orders of magnitude) after ingestion of a blood meal, consequently increasing the output of effector molecules produced by recombinant bacteria. The drop in recombinant bacteria number at 3 d after the blood meal (Figure 3.1C) is of no consequence to the effectiveness of intervention because most of ookinete invasion of the mosquito midgut occurs at 24 to 36 h after the blood meal.

Symbiotic bacteria are thought to be beneficial to their insect hosts by providing nutritional supplements, tolerance to environmental perturbations, and manipulation of host immune homeostasis (Weiss 2011). In recent years, the relationship between symbionts and their hosts has attracted increasing attention from the perspective of engineering symbionts to combat pathogens (Durvasula 1997, Riehle 2007, Rao 2005).

Several bacterial species have been identified from the midgut of field-collected anophelines, mostly Gram-negative proteobacteria and enterobacteria (Straif 1998, Wang

2011). A recent study found that the bacterial population structure of laboratory-reared adult mosquitoes is similar to that of field mosquitoes, suggesting that the mosquito gut

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harbors its microbiome in a selective way (Wang 2011). A nonpathogenic bacterium P. agglomerans was reported as a dominant symbiotic bacterium in different mosquito species in Kenya and Mali (Straif 1998) and also found in laboratory-reared A. stephensi,

A. gambiae, and Anopheles albimanus mosquitoes (Pumpuni 1996, Riehle 2007). It also occurs in the desert locust Schistocerca gregaria (Dillon 2002) and the honey bee Apis mellifera (Loncaric 2009). A possible source of P. agglomerans for mosquitoes in the field is flower nectar, given that this bacterium was found on plant surfaces and blossoms

(Andrews 2000, Pusey 2002, Pusey 1997). These considerations are relevant to future efforts to introduce recombinant bacteria into field mosquito populations. Importantly, P. agglomerans strains have been used as microbial control agents against the plant disease fire blight in the United States (Pusey 2002). These facts make P. agglomerans an excellent candidate for delivery of antimalarials to mosquitoes in the field.

Our data demonstrate that five potent anti-Plasmodium effector molecules secreted by P. agglomerans are able to efficiently inhibit P. falciparum development during early sporogony. The availability of multiple effector proteins, each acting by a different mechanism, greatly reduces the probability of selection of resistant parasites.

Initial experiments indicated that mixing bacteria that secrete different effector molecules had no additive effect on inhibition of Plasmodium development (Figures. 3.4 and 3.5).

This may be because the number of bacteria expressing each effector is cut in half in the mixture fed to mosquitoes.

Perhaps more important than the inhibition of oocyst formation [up to 98% for scorpine and (EPIP)4] are the data on prevalence. The percentage of P. falciparum– infected mosquitoes was 90% in controls and was reduced to 14–18% in mosquitoes

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carrying scorpine or (EPIP)4 transgenic bacteria. This would represent an 80–84% reduction in the proportion of infected mosquitoes. The effectors appear to be similarly efficient in controlling a human and a rodent parasite, raising the possibility that they also will be effective in the control of other human parasites such as Plasmodium vivax.

We note that in the field, mosquitoes carry a mean of five oocysts or fewer in their midguts (Whitten 2006). In some experiments, mosquitoes fed with blood containing high P. falciparum gametocytemia produced abnormally high oocyst numbers

(mean >200 oocysts) (Figure S5). However, even under these conditions, inhibition of parasite development was highly significant and in line with the results presented in

Figure 3.3, although the extent of inhibition was lower (up to 68% inhibition for mosquitoes carrying scorpine-secreting bacteria).

There are around 460 species of anopheline mosquitoes, over 100 of which are suitable vectors for human malaria (Raghavendra 2011). Very few of these have been genetically transformed (Coutinho-Abreu 2010). We found that the effector molecules investigated in this study are equally effective with A. gambiae (an African mosquito) and with A. stephensi (an Asian mosquito). The paratransgenesis strategy may well be

“universal” as effectiveness does not appear to be influenced by mosquito species.

Moreover, the fact that many major vector anopheline species exist as reproductively isolated populations (cryptic species) imposes an important technical barrier for the introduction of transgenes into mosquito populations in the field but does not affect the paratransgenesis strategy. It is important to note that paratransgenesis is compatible with current mosquito control tools (insecticides, population suppression) and even with genetically modified mosquitoes. Should the technical barriers for transgene introgression

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into mosquito populations be solved, we envision the concomitant application of both strategies (genetically modified mosquitoes and paratransgenesis), because they can complement each other. However, more work lays ahead before this approach can be implemented in the field. One key issue is how to effectively introduce engineered bacteria into mosquitoes in the field. Our preliminary results suggest that this could be accomplished by placing baiting stations (cotton balls soaked with sugar and bacteria placed in clay jars) around villages where malaria is prevalent. Another important challenge is the resolution of regulatory, ethical, and social issues related to the release of genetically modified organisms.

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Figure 3.1. Transgenic P. agglomerans rapidly proliferate in the midgut after a blood meal. GFP-tagged P. agglomerans were administered to 2-d-old A. gambiae via a sugar meal, and, 32 h later, the insects were fed on blood. (A) Visualization of GFP- tagged bacteria in the midgut at 24 h after a blood meal. The upper midgut is from a mosquito that had been fed GFP-tagged bacteria, and the lower midgut was from a control mosquito that did not feed on recombinant bacteria. A differential interference contrast image (Right) is paired with a fluorescent image (Left). (B) GFP-fluorescent bacteria recovered from a mosquito midgut. (C) Population dynamics of GFP-tagged P. agglomerans as a function of time after a blood meal. Fluorescent bacteria were fed to mosquitoes as described above, and midguts were dissected at the indicated times after a blood meal. Fluorescent bacteria colony-forming units (CFUs) were determined by plating serially diluted homogenates of midguts on LB/kanamycin agar plates. Data were pooled from three biological replicates.

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Figure 3.2. The engineered P. agglomerans strains efficiently secrete anti- Plasmodium effector proteins. (A) Western blot analysis. Culture supernatants were concentrated using Amicon Ultra-4 Centrifugal Filter Units. Aliquots originating from the same volume of supernatant were fractionated by SDS/PAGE and subjected to Western blot analysis using a rabbit anti-E-tag antibody. The supernatant from nontransformed P. agglomerans (WT) served as a negative control. Images were taken using the same exposure time. (B) In vivo binding of the secreted SM1 peptide to the mosquito midgut epithelium. A. gambiae were fed on sugar solution containing recombinant P. agglomerans strains expressing either the (SM1)2 or E-tagged HlyA alone (HlyA) and then fed on mouse blood. Midguts were dissected 18 or 24 h after blood meal, opened into a sheet, fixed, and incubated with an anti-SM1 antibody, followed by incubation with a fluorescent secondary antibody. Nuclei were stained with DAPI (blue). The differential interference contrast (DIC) images of the same field are shown to the right.

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Figure 3.3. Inhibition of P. falciparum development in vector mosquitoes by recombinant P. agglomerans strains. A. gambiae mosquitoes were fed on 5% (wt/vol) sugar solution supplemented with either PBS (−Bact) or recombinant P. agglomerans strains and 32 h later fed on a P. falciparum–infected blood meal. Oocyst numbers were determined 8 d after blood meal. Each dot represents the oocyst number of an individual midgut and horizontal lines indicate mean values. Data were pooled from four biological replicates. Recombinant P. agglomerans strains were engineered to express the E-tagged HlyA leader peptide alone (HlyA) or mPLA2, Pro:EPIP, Shiva1, scorpine, and (EPIP)4 (Table S1), fused to HlyA (Figure S3), as indicated. Inhibition, inhibition of oocyst formation relative to the −Bact control; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; N, number of mosquitoes analyzed; Prevalence, percentage of mosquitoes carrying at least one oocyst; Range, range of oocyst numbers per midgut; Tbp, transmission-blocking potential: 100 − {(prevalence of mosquitoes fed with recombinant P. agglomerans)/[prevalence of control (−Bact) mosquitoes] × 100}.

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Figure 3.4. Comparison of P. falciparum development between mosquitoes that fed on an infectious blood meal at either 2 or 4 d after administration of recombinant P. agglomerans. A. gambiae females were fed on 5% (wt/vol) sugar solution supplemented with either PBS (−Bact) or recombinant P. agglomerans strains as follows: HlyA, P. agglomerans expressing the E-tagged HlyA leader peptide alone; Shiva1 + (EPIP)4 or scorpine + (EPIP)4 (Table S1), a mixture of the two recombinant bacteria in equal numbers. Two days (2 dpPa) or 4 d (4 dpPa) after administration of bacteria, mosquitoes were fed on a P. falciparum–infected blood meal. Oocyst numbers were determined 8 d after the blood meal. Each dot represents the oocyst number of an individual midgut and horizontal lines indicate mean values. Data were pooled from three biological replicates. % Inhibition, inhibition of oocyst formation relative to the −Bact control; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; N, number of mosquitoes analyzed; Prevalence, percentage of mosquitoes carrying at least one oocyst; Range, range of oocyst numbers per midgut.

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Figure 3.5. Inhibition of P. berghei development in mosquitoes harboring recombinant P. agglomerans strains. A. stephensi females were fed on 5% (wt/vol) sugar solution supplemented with either PBS (−Bact) or recombinant P. agglomerans strains engineered to express E-tagged HlyA alone (HlyA), (SM1)2, pbs21scFv- Shiva1/(EPIP)4 (50–50 mixture) or scorpine/(EPIP)4 (50–50 mixture)] (Table S1 and Figure S3) and 32 h later the five groups of mosquitoes were fed on the same P. berghei- infected mouse. Plasmodium infections were evaluated 14 d after infection. Each dot represents the number of oocysts in an individual midgut. Horizontal lines indicate mean values. Data pooled from three biological replicates. N, number of mosquitoes analyzed; Range, range of oocyst numbers per midgut; Prevalence, percentage of mosquitoes carrying at least one oocyst; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; Inhibition, inhibition of oocyst formation relative to the −Bact control.

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Figure 3.6. Impact of recombinant P. agglomerans strains on lifespan of Anopheles gambiae females. A. gambiae mosquitoes were fed on 5% (wt/vol) sugar solution supplemented with either PBS (−Bact), or recombinant P. agglomerans strains as follows: HlyA, P. agglomerans expressing the E-tagged HlyA leader peptide alone; Shiva1 + (EPIP)4 or scorpine + (EPIP)4, a mixture of the two recombinant bacteria in equal numbers (Table S1 and Figure S3). Thirty two hours later, mosquitoes were fed on a noninfected mouse, and mosquito survival was measured twice daily. Data were pooled from three independent experiments. There was no significant difference in survivorship among the groups.

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Chapter 4

Identification of secretion signals from Asaia sp. SF2.1, a mosquito midgut bacteria

ABSTRACT

Bacteria chosen for paratransgenesis in mosquitoes must be selected from among the group of symbiotic species that inhabit the mosquito midgut. Previous experiments used Pantoea agglomerans to secrete antimalarial proteins into the midgut environment

(Wang 2012). This species secreted antimalarial proteins in high amounts and demonstrated effective parasite killing in vivo. This species, however, has no drive mechanism that will cause the the paratransgenic organism to remain in the mosquito population long-term or to spread the bacteria within a population of mosquitoes from one individual to another. Bacteria of the genus Asaia, first discovered in plant nectar, are much better candidates for paratransgenesis (Yamada 2000, Favia 2008). The bacterial strain Asaia sp. SF2.1, which was originally isolated from Anopheles stephensi mosquitoes, has been successfully cultured and manipulated in the lab (Favia 2007).

These bacteria are prime candidates for paratransgenesis due to the ease with which they can be introduced into a population of mosquitoes and the rate at which they can spread throughout a population (Damiani 2008).

In order to utilize Asaia for paratransgenesis against malaria, certain tools must be available for their manipulation. One important tool is a secretion system that will allow the bacteria to transport the antimalarial proteins outside the cell. To make use of these bacteria, a functional genetic screen was used to identify native secretion signals in

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Asaia. Novel secretion signals were demonstrated both to mediate the secretion of active proteins and peptides from Asaia into the mosquito midgut and to inhibit the invasion of

Plasmodium into host tissues.

BACKGROUND

Bacteria of the genus Asaia are Gram-negative, rod-shaped, peritrichously flagellated, acetic acid bacteria belonging to the α-proteobacteria. They were initially isolated from the flower nectar of Indonesian orchid trees and plumbago plants (Yamada

2000). Since their discovery, Asaia have been found in many plant-feeding insects, including anopheline mosquitoes that acquire the bacteria by feeding on nectar (Chouaia

2010).

Asaia is ideal to use for paratransgenesis in anopheline mosquitoes due to its beneficial microbial ecology in the host. Asaia stably associates with anopheline mosquitoes and is present in the female midgut and salivary glands, which are important targets for transmission-blocking interventions, as well as in the male reproductive tract, which aids in the dissemination of the bacteria through the mosquito population (Favia

2007, Damiani 2010). Asaia is transmitted from male to female during copulation, and from mother to progeny during egg laying, which can potentially facilitate the spread of paratransgenic strains released in the wild (Damiani 2008). The bacteria can survive the shedding of the meconium following the mosquito's transformation until the mosquito is a mature adult (Damiani 2008). The meconium is a peritrophic matrix within the larval midgut that, when shed, removes all of the contents of the midgut, thereby sterilizing it

(Moll 2001).

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Asaia is a very widespread genus and has been identified in diverse genera and orders of sugar-feeding insects (Crotti 2009). Strains of Asaia taken from one insect species can be transferred to other insect species and colonize their body tissues (Crotti

2009). Due to its ability to colonize a variety of species, Asaia may be important for other insect-related problems that could be solved by paratransgenesis, such as other insect- vectored human diseases or agricultural crop diseases.

The microbiota of mosquitoes play a large role in immunity, particularly against

Plasmodium infection (Dong 2009, Boissiere 2012). The microbiota of the mosquito affects transcriptional activation of immune-related genes, increasing expression of certain anti-Plasmodium factors (Dong 2009). Asaia has a mutually beneficial symbiosis with anopheline mosquitoes; it inhabits the environment of the midgut and proliferates upon the female mosquito taking a blood meal. The mosquito benefits from its association with the bacteria because Asaia naturally induces an increased immune response against Plasmodium (Capone 2013). This natural immune stimulation makes

Asaia ideal for the addition of further antimalarial molecule delivery.

Paratransgenesis involves altering the host's phenotype through genetic modification, with modification occurring to the symbiont of the host organism rather than to the host itself. Paratransgenic bacteria that can combat malaria will provide the host mosquito with added defense against invasion of the Plasmodium parasite. The research presented here aimed to identify secretion signals that can be used in Asaia to enable the bacteria to secrete antimalarial proteins directly into the mosquito midgut where they could inhibit the sexual life stages of the parasite.

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To create paratransgenic strains of Asaia, a functional secretion system is needed that will allow the bacterium to translocate diverse antimalarial proteins, such as enzymes, single-chain antibodies, and antimicrobial peptides, outside the cell. Asaia are

Gram-negative bacteria; they have two cell membranes through which transport must take place for a protein to be secreted. This would be easily managed if the bacteria were capable of utilizing any of the commonly-used secretion systems for lab-cultured bacteria. However, my previous work has demonstrated that the Type I hemolysin secretion system cannot be easily inserted into a plasmid or transposon for use in Asaia

(Bongio, unpublished results). The hemolysin system requires multiple proteins that compose the secretory complex in the membrane, including HlyB, HlyD, and TolC, and the fitness cost of producing so many proteins may make the modified organism unable to compete against wild type bacteria (Fernandez 2000).

Common secretion signals have been tested in Asaia, including the E. coli Type II

OmpA and TolB leader peptides, as well as the PelB leader from Erwinia carotovora.

These signals do not function in Asaia (Bisi, personal communication). Thirteen Type II signal sequences from the closely-related species Gluconobacter oxydans and

Gluconacetobacter diazotrophicus were cloned into expression vectors and tested for activity in Asaia, but none mediated secretion (this dissertation, Chapter 2).

Due to the failure of both the hemolysin transport system and secretion signal peptides, the identification of a native Asaia protein secretion pathway was necessary.

Accordingly, a genetic screen was used to directly identify proteins that are either secreted or surface displayed in Asaia. The E. coli alkaline phosphatase enzyme (PhoA) was used as a tool to detect protein secretion. When PhoA is secreted past the inner

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membrane, it can cleave 5-bromo-4-chloro-3'-indolyl phosphate (BCIP), producing a blue color. Including BCIP in the growth media allowed for a quick and easy screen for blue colonies. By creating random gene fusions with phoA, it was possible to detect which fusion proteins were secreted from the cell, since they would translocate the PhoA protein as well, resulting in the blue color phenotype.

MATERIALS AND METHODS

Media and antibiotics

Top10 F' E. coli cells were used during the molecular cloning and plasmid propagation stages of the experiments. The Top10 F' cells were cultured in standard Luria

Bertani (LB) broth (10 g Tryptone, 5 g NaCl, 5 g yeast extract, in a final volume of 1 L distilled water) or LB agar (LB broth plus 15 g/L agar). For selection of plasmids with kanamycin, media was supplemented with 30 μg/ml kanamycin. All E. coli cultures were grown at 37 °C, with agitation for liquid broth cultures.

Asaia SF2.1 bacteria were cultured in Mannitol broth (5 g yeast extract, 3 g peptone, 25 g mannitol, in a final volume of 1 L distilled water) or Mannitol agar

(Mannitol broth plus 15 g/L agar). Media was adjusted to pH 6.5 before sterilization. For selection of plasmids with kanamycin, media was supplemented with 120 μg/ml kanamycin. All Asaia cultures were grown at 30 °C, with agitation for liquid broth cultures.

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BCIP selection of secreting strains of bacteria

To identify the secretion of protein constructs in bacterial colonies, media was supplemented with 5-bromo-4-chloro-3'-indolyl phosphate (BCIP). E. coli was screened on LB media supplemented with 25 μg/ml BCIP. Asaia was screened on Mannitol agar supplemented with 25 μg/ml BCIP and 25 μg/ml Na2HPO4. Sodium phosphate was included in the media as an inhibitor of the natural phosphatase activity demonstrated by wild type Asaia to reduce false positives.

Genomic library construction and screening

The phoA gene was inserted in pNB51 in such a way that genomic DNA can be cloned 5' to it to allow gene fusions. phoA was amplified by PCR from E.coli K12 genomic DNA using primers “PhoA F NdeI” and “PhoA R PacI” (Table 4.3). The product was directionally cloned into the expression vector pNB51 replacing the beta- lactamase gene, to create a plasmid with a cloning site usable for gene fusions with phoA, named pNB90 (Figure 4.1).

Asaia gDNA was partially digested with the MseI restriction enzyme and the expression vector pNB90 was fully digested with the NdeI restriction enzyme. Digested genomic DNA was size-selected for fragments 2-4 kb in size by gel electrophoresis, recovered, and ligated into the NdeI site of pNB90 to create a fusion library between phoA and Asaia genomic inserts. The library was transformed into E. coli Top10 F' electrocompetent cells and plated on LB agar containing 30 μg/ml Kanamycin and 25

μg/ml BCIP, and grown 12 h at 37°C.

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The library was screened in E. coli due to growth restrictions of Asaia on selective media and the inefficiency of DNA transformation into Asaia. Approximately

0.9% of colonies turned blue after 1 day of growth at 37 °C. More than 200,000 clones were collected and pooled to provide over 100-fold coverage of the 3.53 Mb genome, and these were stored in 50% glycerol at -80 °C to make the library.

Individual blue colonies were inoculated into 5 ml LB broth supplemented with kanamycin and grown at 37 °C for 12 h. Plasmid DNA was extracted from these cultures using a Qiagen plasmid miniprep kit. One hundred and sixty blue clones were plasmid prepped and sequenced using the primer “PhoA seq R1” (Table 4.3). Each sequence read was identified by a BLAST search (NCBI) for the closest related homologous protein identity.

The 160 library clones resulted in 16 unique identified genes, and one plasmid for each unique clone (Table 4.2, all pNB91.* plasmids) was transformed into Asaia cells.

These were plated on selective media to confirm that secretion functions similarly to the activity seen in E. coli.

Western blot detection of secreted proteins from phoA library clones

Asaia liquid cultures were grown to an OD600 of 1.5. Protein samples were prepared from these by centrifuging 1 ml of the culture at 12,000 RPM in a desktop centrifuge. From the supernatant fraction, 750 μl was removed, mixed with 250 μl of 3X

Laemmli sample buffer (BioRad, Hercules, CA, #161-0737), and boiled for 10 minutes.

Eight μl of the Colormark plus prestained protein ladder (New England Biolabs, Ipswich,

MA, #p7712), and 20 μl of each protein sample were loaded into wells of a 5% stacking

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and 10% separating polyacrylamide gel. Proteins were separated by electrophoresis at

120 V for 1 h, then transferred onto a PVDF membrane in a BioRad transfer apparatus using Tris-Glycine transfer buffer (25mM Tris, 150mM glycine, 10% methanol) at 95 V for 75 minutes. The membrane was blocked with a 4% bovine serum albumin (BSA)

TBS-T solution (50 mM Tris-CL, 150 mM NaCl, 0.1% Tween20, 4% w/v fraction V

BSA, pH 7.5) for 3 h at 4 °C with agitation. The blocking buffer was then replaced with the primary antibody solution containing rabbit polyclonal anti-bacterial alkaline phosphatase 1:50,000 (Abcam, Cambridge, England, ab7319-1) in blocking buffer and incubated overnight at 4 °C. The next day, the membrane was washed four times in TBS-

T for 15 min each time. Following washes, the secondary antibody was applied, goat anti-rabbit HRP (BioRad, Hercules, CA, 170-5046), and the blot was incubated for 1 h at room temperature. The wash steps were repeated, then 2 ml of Supersignal West Femto

Maximum Sensitivity Substrate (Thermo Scientific, Waltham, MA, # 34095) was added to the blot and incubated for 5 minutes. The blot was exposed to X-ray film (Thermo

Scientific, Ipswich, MA, #34090) and developed using an automatic developer.

ELISA to detect PhoA in cell culture fractions

Asaia expressing the PhoA secretion constructs were grown to OD600 of 1.5, then centrifuged. Supernatant, live cell, and cell lysate fractions were isolated and bound to wells in a 96-well plate overnight at 4 °C. These plates were washed three times with

Tris-buffered saline (TBS) (50mM Tris-CL, 150 mM NaCl, pH 7.5), then blocked by adding 200 μl of 2% BSA TBS (TBS with 2% w/v fraction V BSA) and incubating 2 h at room temperature. This was washed again three times with TBS, then 100 μl of a 1/3000

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dilution of anti-BAP-HRP (bacterial alkaline phosphatase) antibody (Abcam, Cambridge,

England, ab7319-1) in 2% BSA TBS was added to each well and incubated for 1 h at room temperature. The plate was washed 8 times with TBS-Tween20 0.1% for 2 minutes per wash. To visualize the protein, 50 μl of 1-Step Ultra TMB-ELISA (Thermo

Scientific, Ipswich, MA, #34028) was added and incubated for 10-20 min at room temperature. HRP from the bound antibodies reacts with the TMB substrate to produce a blue color (Figures 4.2 and 4.3).

p-Nitrophenyl phosphate plate assay for PhoA activity

Aldrich, St. Louis, MO, #P7998). PhoA cleaves the phosphate group from PNPP substrate, producing a yellow color (Figures 4.2 and 4.3).

Cloning of anti-Plasmodium effector genes into secretion constructs

A new plasmid was generated to modify the identified secretion constructs to include a cloning site into which anti-Plasmodium effector genes could be inserted. First, the phoA gene was amplified by PCR using primers “PhoA F NdePacSbf” and “PhoA R

Fse” (Table 4.3). This PCR product and the pNB51 plasmid were digested to completion with the NdeI and FseI restriction enzymes, and the plasmid was treated with calf intestinal phosphatase. The PCR product was ligated into the linearized plasmid using T4

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DNA ligase at 16 °C overnight. The ligated DNA was transformed into top10 E. coli cells and selected on LB media containing kanamycin. Clones isolated from this selection were verified by sequencing to ensure there were no mutations introduced. The new plasmid created was named pNB92 (Figure 4.4). This plasmid is identical to pNB90

(Figure 4.1), but with the addition of the PacI and SbfI restriction sites for in-frame insertion of effector genes into the fusion protein construct.

The siderophore receptor and YVTN beta-propeller proteins were amplified by standard PCR using primers “siderophore F NdeI” and “siderophore R MYC PacI”, or

“YVTN F NdeI” and “YVTN R MYC PacI”, respectively, and directionally cloned into pNB92 by restriction enzyme digestion and ligation. The resultant gene constructs contain both the secretion protein, a MYC epitope tag, a cloning site for effector molecules, and phoA. These plasmids were named pNB93 (Figure 4.5, contains YVTN beta-propeller repeat) and pNB95 (Figure 4.6 contains TonB-dependent siderophore receptor). Each of these cloned genes are longer than the predicted proteins in the genome annotation, perhaps due to mutation. The cloned genes were sequenced to verify that there are no errors.

Into these plasmids, eleven genes were cloned in-frame, including two control proteins that are not antimalarial. The cloned genes encoded GFP, anti-bovine serum albumin (anti-BSA) scFv (Bisi 2011), prochitinase peptide, PLA2, enolase-plasminogen interacting protein (EPIP)4, Shiva1, anti-Pbs21 scFv-Shiva1, prochitinase-EPIP, scorpine, (Wang 2012) anti-Pfs48/45 scFv (Chapter 2 page 62) and anti-Pfs25 scFv

(Chapter 2 page 61). Each gene was amplified by PCR using primers that add PacI and

SbfI restriction digest sites to either end of the amplicon (see Table 4.3 for primers used).

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These PCR products were directionally cloned into pNB93 and pNB95 by restriction enzyme digestion and ligation as described previously to create a set of anti-Plasmodium secretion constructs (Figure 4.7). Clones were selected on LB agar containing kanamycin. The YVTN beta-propeller protein constructs would not grow properly in E. coli, possibly due to lethality of the cloned constructs, therefore following the molecular cloning and sequence verification, Asaia SF2.1 cells were transformed with each of the siderophore receptor effector plasmids only, and they were selected for on Mannitol Agar supplemented with kanamycin.

Western blot detection of protein with MYC epitope tag

Samples were prepared, separated by acrylamide gel electrophoresis, and transferred to PVDF membrane exactly as described in the western blot protocol for the detection of secreted proteins from phoA library clones (page 117). The PVDF membrane was blocked for 18 h with 1% BSA TBS-T (50mM Tris-CL, 150 mM NaCl,

0.1% Tween20, 1% w/v fraction V BSA, pH 7.5) with agitation at 4 °C. Next, the blocking solution was replaced with the primary antibody, a mouse anti-myc antibody

(Invitrogen, Thermo Scientific, Waltham, MA, #45-0603) 1:5000 in blocking buffer, and incubated at 4 °C for 24 h with agitation. The primary antibody solution was removed, and the blot was washed four times in TBS-T for 15 min each time. Following washes, the secondary antibody, goat anti-mouse HRP (BioRad, Hercules, CA, #170-5046), was applied, and the blot was incubated for 1 h at room temperature. The wash steps were repeated, and 2 ml of Supersignal West Femto Maximum Sensitivity Substrate (Thermo

Scientific, Waltham, MA, #34095) was added to the blot and incubated for 5 min. The

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blot was then exposed to X-ray film (Thermo Scientific, Waltham, MA, #34090 ) for multiple time exposures ranging from 10 sec to 10 min and developed using an automatic developer (Figure 4.8).

Parasite inhibition testing in Anopheles stephensi mosquitoes

Two-day old Anopheles stephensi adults were collected and separated into cups with screen lids containing 50 female mosquitoes each. Asaia expressing the siderophore protein secretion constructs with Pro-EPIP, scorpine, anti-Pbs21-Shiva1, and PLA2 effectors, and a control strain expressing PhoA alone were fed to individual mosquito cups for 48 h by cotton balls soaked with a mixture containing 1x109 cells/ml of bacteria in a 5% sugar solution.

The parasitemia of a P. berghei infected female Swiss Webster mouse was determined by blood smear. A drop of blood was taken from the mouse's tail and placed on a slide. This was smeared with the edge of another glass slide to create a thin layer of blood. This slide was fixed in methanol for ten seconds, then transferred to a 10%

Giemsa stain solution: 5 ml Giemsa stock solution (Ricca Chemical Company, Arlington,

TX, #3250-4) plus 45 ml phosphate buffer (0.35g KH2PO4 plus 0.5g Na2HPO4 in a final volume of 500ml distilled water). This was allowed to stain for 30 min, after which it was rinsed with tap water and dried. Parasitemia was determined by counting the number of infected cells and dividing by the total number of cells in a given microscope field. Full fields were counted until at least 500 cells were evaluated.

After determining the parasitemia, the mouse was sacrificed using a CO2 chamber, and the total blood volume removed by cardiac puncture surgery with a

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heparinized needle (100 μl of 1 mg/ml heparin in PBS, 26 G needle). This blood was diluted with phosphate buffered saline to reach 5x107 infected cells per 200 μl. A volume of 200 μl of the diluted blood was immediately injected into three naïve mice intraperitoneally.

The newly infected mice were checked for infectivity by exflagellation testing 2-3 days post-injection. A drop of blood was extracted from the mouse's tail, and 2 μl of the blood was combined with 2 μl heparin (1 mg/ml heparin in PBS) and 6 μl exflagellation media (1 pkg of RPMI 1640 medium (1L / pkg Gibco, Thermo Scientific, Waltham, MA,

#23400-021) with 2mM Hepes, 2mM glutamine in 1L distilled water pH 8.4, supplemented with 2 g sodium bicarbonate, 50 mg hypozanthine, and 100 μM xanthurenic acid). The mixture was incubated at 21 °C for 10 min. After incubation, the entire 10 μl was transferred to a microscope slide and covered with a coverslip. At 100X magnification, exflagellation events were counted per field, in uncrowded fields that show only a single layer of cells; these are estimated at 500 cells per field.

The mosquitoes that were previously fed the paratransgenic Asaia strains were given a P. berghei infective blood meal from a mouse with exflagellation rates of between 2-3 events per field. The mice were anesthetized by intraperitoneal injection of

150 μl of anesthetising agent (Ketaject [100 mg/ml] 2 ml, acepromazine [10 mg/ml] 1 ml, saline [0.9% w/v NaCl] 7 ml). The mouse was placed on the screen top of each cup consecutively, and mosquitoes were allowed to feed for 6 min. Two trials were performed, each with a control cup fed Asaia expressing a plasmid with no effector, and two cups that were fed different antimalarial Asaia strains. The infected mosquitoes were kept at 21 °C with 10% sugar solution for two weeks. Midguts were dissected and stained

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with 0.2% mercurochrome which stains the oocysts. The number of oocysts per midgut was counted using a light microscope (Figures 4.9-4.11).

Cloning short signal peptides into expression vectors

Leader peptides were identified by predictive algorithms using both the

SignalP4.1 artificial neural network Hidden Markov models (Nielsen 1997), and the

PRED-TAT hidden Markov models (Bagos 2010). The predictions are shown in Figures

4.12-4.15. The leader peptides predicted using the SignalP4.1 and PRED-TAT algorithms were cloned into pNB92 exactly as described in the generation of plasmids pNB93 and pNB95, except the primers used were “siderophore F NdeI” “Sider51 R MYC PacI” to amplify the siderophore receptor signal, or “YVTN F NdeI” and “YVTN34 R MYC

PacI” to amplify the YVTN beta-propeller protein signal. This produced plasmids pNB124 and pNB125 (Figures 4.16 and 4.17).

Asaia genome prediction of secreted proteins

Asaia SF2.1 gDNA was prepared and sent to ACGT Inc (www.acgtinc.com) to be sequenced, and the genome was submitted to NCBI (Genbank ID 873348) and annotated by the NCBI Annotation Pipeline version 2.0 (https://www.ncbi.nlm.nih.gov/ genome/annotation_prok) (Shane 2014). This annotation identified 3,005 total protein- coding genes. The protein amino acid sequences were analyzed using the SignalP4.1 signal peptide prediction software as described previously, however using the downloaded Linux version of the software that can process large datasets (Nielsen 1997).

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RESULTS

Genetic screen for secreted proteins in Asaia

The genetic screen for secreted Asaia proteins identified sixteen unique genes

(Table 4.1) encoding proteins that are either secreted from the cell or membrane-bound.

Less than 1% of the clones in the genomic library secreted PhoA into the growth medium and produced a blue phenotype. This is a reasonable number of clones to obtain considering that half of the inserted DNA will be in the incorrect orientation, and another two-thirds of the remaining inserts will be in the incorrect reading frame for translation.

Furthermore, only 228 of the 3,005 (7.6% of all genes) proteins in the Asaia genome were predicted by SignalP4.1 to have signal peptides, which is close to that of E. coli which has 7.1% of its proteins located in the membrane, periplasm, or secreted. The sequenced genes were originally identified by homology to secreted or membrane-bound proteins found in Gluconobacter or Gluconacetobacter, close relatives of Asaia. They have since been compared to the Asaia SF2.1 genome and have been given the new designations and shown in Table 4.1.

Activity of cloned genes in Asaia

The unique, cloned plasmids from this screen were transformed into electrocompetent Asaia cells and plated on Mannitol agar with BCIP and sodium phosphate. These clones grew at varying rates and showed different levels of phosphatase activity. Secretion was tested by an ELISA assay which shows the greatest amount of secreted protein in the supernatant with the siderophore receptor protein and YVTN beta- propeller protein fusions (Figure 4.2 top). A multiwell plate assay was prepared, but with

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PNPP substrate added, which turns yellow in the presence of active PhoA (Figure 4.2 bottom). The PNPP assay shows activity of the secreted alkaline phosphatase in both the siderophore receptor and YVTN beta-propeller supernatant samples. The siderophore receptor protein construct displays the most active enzymatic activity.

The two best secreting fusion proteins are a siderophore receptor and a YVTN beta-propeller repeat protein. The siderophore receptor protein is an outer membrane pore complex that receives siderophores which transport metal ions (Faraldo-Gomez 2003).

The YVTN beta-propeller protein is a structural protein that forms part of a protective S layer on the outside of the cell (Jing 2002). Each of these proteins is typically localized at the cell surface.

Cloning effector proteins into secretion constructs

The siderophore receptor and YVTN beta-propeller proteins were amplified by

PCR and cloned into pNB92, creating gene constructs that contain both the secretion protein, a MYC epitope tag, a cloning site, and PhoA (Figures 4.5 and 4.6). Multiple antimalarial genes and control genes that are not expected to be harmful to the expressing strain were cloned into the siderophore receptor plasmid and sequenced to confirm that there were no mutations. The YVTN beta-propeller protein plasmid was difficult to clone genes into and cloning attempts produced either no colonies on the selective plates or only false positives.

Asaia SF2.1 cells were transformed with each of the siderophore receptor effector plasmids, and these strains were grown in Mannitol broth supplemented with kanamycin to allow expression of the transgenes. Secretion of the fusion proteins was determined by

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western blot utilizing an antibody against the PhoA protein (Figure 4.8). The bands detected on this western display degradation of the protein constructs, probably due to periplasmic proteases. Membrane proteases are important for regulating the turnover of proteins that are localized in the periplasm or the plasma membrane (Dalbey 2012). The siderophore receptor protein is most likely mis-folding and unable to anchor in the membrane properly, therefore that portion of the fusion protein construct is degraded in the periplasm. A search using the “DAS” transmembrane domain predictor

(http://www.sbc.su.se/~miklos/DAS/maindas.html) with the amino acid sequence of the cloned gene fragment did not find any such domains. The remainder of each fusion protein seems to remain intact including the PhoA protein and the anti-Plasmodium effector proteins and peptides. The protein sizes indicated by the bands highlighted in

Figure 4.8 all correspond with the predicted molecular weight of the effector protein plus

PhoA.

Activity of paratransgenic Asaia against P. berghei

Paratransgenic Asaia SF2.1 strains secreting Pro-EPIP, scorpine, anti-Pbs21-

Shiva1, and PLA2 effectors by the siderophore fusion protein were tested in vivo for inhibition of P. berghei invasion within the mosquito host Anopheles stephensi. The

YVTN beta-propeller protein constructs were not able to be transformed into Asaia

SF2.1, and were not tested for activity. The paratransgenic strains were fed to An. stephensi mosquitoes which were then challenged with an infective blood meal from a P. berghei infected mouse two days later. Two weeks after the blood meal, the mosquitoes were dissected and oocysts per midgut were counted. The oocyst counts indicate a

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significant level of parasite killing from the scorpine effector, and a weaker effect from the anti-Pbs21 scFv Shiva1 effector (Figures 4.9-4.11, oocyst counts in Table 4.6 and

4.7). Both the anti-Pbs21 Shiva1 results and the scorpine results were significant (p-value

0.0006 and <0.0001 respectively).

Increasing the efficiency of constructs

The identified Asaia genes were fully sequenced and analyzed using the SignalP

4.1 algorithms to predict Gram-negative bacterial secretion signals (Figures 4.12 and

4.13). A possible secretion signal was identified in both of the highly active clones, the

TonB-dependent siderophore receptor protein and the YVTN beta-propeller repeat protein. The sequences were analyzed using the PRED-TAT algorithms as well (Figures

4.14 and 4.15). This set of algorithms identified the YVTN secretion peptide as a Sec- dependent pathway signal, and the siderophore receptor peptide as a potential Tat- dependent pathway signal. These predicted secretion signals were re-cloned into the phoA expression vector to test the efficacy of secreting a smaller protein this way. The first 51 amino acids from the siderophore receptor protein and the first 34 from the YVTN repeat protein were chosen to retain a conservative amount of the original protein after the signal sequence cleavage site. These leaders were directionally cloned into pNB92 in- frame with phoA (Figure 4.16 and 4.17). Blue (secreted) clones of each were isolated in

E. coli by screening on LB media containing BCIP.

The truncated secretion constructs were transformed into Asaia and grown in liquid culture. SDS protein samples of the supernatant and pellet fractions from overnight cultures of these strains were prepared and analyzed by western blot using an antibody

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against the Myc epitope tag. As seen in (Figure 4.18), the truncated constructs mediate a high amount of secretion utilizing only the predicted secretion signals. These signal peptides have not yet been tested for the secretion or activity of antimalarial effector proteins due to the time needed to clone effector genes and transform Asaia strains with the plasmids.

Asaia SF2.1 genome prediction of secretion signals

The Asaia SF2.1 genome secretion signal prediction by SignalP4.1 produced 228 hits for proteins which may be secreted by Type II secretion systems (top predictions listed in Table 4.5). Among the top predictions, there were secreted proteases (peptidyl- dipeptidase DCP, and gamma-glutamyltranspeptidase), transporter proteins (multiple

TonB dependent receptor proteins, and an ammonium transporter), a folding chaperone

(peptidyl-prolyl cis-trans isomerase), and a digestive enzyme (alginate lyase).

The PhoA genetic screen clones were reevaluated by a protein BLAST search against the Asaia SF2.1 genome (Table 4.1). The protein previously identified as homologous to Gluconobacter YVTN beta-propeller repeat protein came up as

‘unidentified protein’ in and NCBI BLAST search of the Asaia SF2.1 genome. It was, however, identified as a potentially secreted protein in the SignalP analysis of the predicted proteins. The protein previously identified as homologous to an Acetobacter outer membrane siderophore receptor came up as ‘unidentified protein’ in the Asaia

SF2.1 genome on NCBI. Although the siderophore receptor protein was not identified in the genomic prediction for Type II secretion, there were many predictions for other

TonB-associated transporters, similar to the PhoA screen results.

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DISCUSSION

Malaria has plagued mankind throughout history and is a major cause of human morbidity and mortality annually (WHO 2013). Despite decades of interventions against the disease, it is still a widespread global problem. New technologies are needed to help reduce the burden that malaria causes and hopefully eradicate the Plasmodium parasite entirely.

Bacterial paratransgenesis is a relatively recent technology that has been successfully used to combat human diseases, including Chagas disease, African sleeping sickness, HIV, and malaria (Durvasula 1997, De Vooght 2012, Chang 2003, Fang 2012).

For example, Rhodococcus rhodnii was engineered to secrete the antimicrobial peptide

Cecropin A to inhibit the transmission of Trypanasoma cruzi by Rhodnius prolixus, thus preventing Chagas disease (Durvasula 1997); Sodalis glossinidius was modified to secrete nanobodies to target the variant surface glycoprotein of Trypanosoma bruci, the cause of African sleeping sickness (De Vooght 2012); Lactobacillus jensenii was modified to secrete functional human CD4, which inhibits HIV entry into host T-cells

(Chang 2003); and Pantoea agglomerans was engineered to secrete multiple effector proteins utilizing the hemolysin secretion system to interfere with transmission of P. berghei and P. falciparum malaria by anopheline mosquitoes (Wang 2012).

Asaia was proposed as a candidate for antimalarial paratransgenesis due to its natural microbial ecology that allows it to colonize anopheline mosquito tissues and to easily transmit itself through the mosquito population (Favia 2007). The primary goal of this work was to modify Asaia to enable it to secrete proteins into the mosquito midgut and to hinder the life stages of Plasmodium that develop there following an infective

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blood meal. Interfering with this vulnerable stage of the malaria parasite would prevent human infection by rendering the mosquito an inhospitable host. The experiments performed enable the use of the Asaia sp. SF2.1 midgut symbiont of anopheline vector mosquitoes as a delivery vessel for heterologous effector proteins.

Genetic screen for protein secretion

The results of the alkaline phosphatase fusion library screen produced a list of sixteen candidate genes that could potentially be useful for secretion of effectors in paratransgenic constructs (Table 4.1). All of the identified fusion proteins that mediated secretion were identified as homologous to either secreted or surface-displayed proteins in related species. These are all logical proteins to expect from a phoA library screen, since either periplasmic, membrane-bound, surface-displayed, and secreted fusion proteins can all translocate the PhoA enzyme into the periplasm where it can cleave the

BCIP molecule used for screening (Hoffman 1985). This is the reason that clones required further testing to determine exactly where each protein was localized: within the periplasm or secreted from the cell.

Localization and activity of secreted PhoA

The analysis of the activity of PhoA fusion constructs demonstrated a high level of secretion mediated by the siderophore receptor fusion protein and the YVTN beta- propeller fusion protein, both of which are homologs of known bacterial membrane proteins (Faraldo-Gomez 2003, Jing 2002). The alkaline phosphatase protein that was secreted into the supernatant by these systems was found to be active by a plate assay

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with PNPP. Since active alkaline phosphatase protein requires disulphide bond formation to achieve an active conformation (Sone 1997), this means that the secreted proteins must spend time in the oxidizing environment of the periplasm long enough to allow these bonds to form before leaving the cell. The PhoA secreted by the siderophore receptor fusion protein showed a much more robust amount of phosphatase activity which indicates that the protein may have spent a greater amount of time in the periplasm and been allowed to achieve the correct conformation and form disulphide bonds. Disulphide bonds are important for the stability and activity of some single-chain antibody effectors that could be secreted by paratransgenic strains (McAuley 2007).

The western results (Figure 4.8) show that the effector proteins secreted by the siderophore receptor pathway remain intact, while the Asaia siderophore receptor fusion protein is most likely degraded by periplasmic proteases (Dalbey 2012). This is expected, since the fusion protein should only retain a portion of the original Asaia gene, and it likely cannot achieve its stable native conformation, nor can it insert into the membrane.

This is not necessarily a problem for delivery of effector molecules from a paratransgenic organism, however the bulk of the fusion protein is not remaining intact and is simply wasted energy for the Asaia producing it. These constructs can be reduced in size by identifying the signal peptide responsible for secretion and eliminating the remainder of the fusion protein.

Anti-Plasmodium activity in vivo

The use of paratransgenic Asaia in mosquitoes demonstrates that, despite the large size of the fusion proteins, the Asaia siderophore receptor protein is capable of mediating

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secretion of heterologous proteins outside the cell efficiently enough to supply antimalarial effector proteins directly into the mosquito midgut environment despite the large size of the fusion proteins. The significant in vivo anti-Plasmodium results demonstrate the ability of paratransgenic Asaia to disrupt the critical life stages of

Plasmodium berghei in the Anopheles stephensi mosquito midgut. There were two significant effectors: (1) scorpine, a peptide effector which disrupts the plasma membrane of microbes, killing them (Carballer-Lejarazu 2008), and (2) anti-Pbs21 Shiva1, a single- chain antibody-antimicrobial peptide combination which binds to a 21 kDa ookinete surface protein of P. berghei preventing the transformation from ookinete to oocyst and which is linked to the Shiva1 toxin, another lytic peptide (Yoshida 2001). The Pbs21-

Shiva1 effector significantly reduced oocyst numbers by 27.8% as calculated using the median number of oocyst per midgut, while the scorpine peptide effector significantly reduced oocyst numbers by 73.5% as calculated by the median number of oocysts per midgut. The scorpine effector was previously demonstrated to block nearly 100% of infections in lab tests using the HlyA secretion system in Pantoea agglomerans (Wang

2013).

The anti-Pbs21-Shiva1 and scorpine constructs were re-tested to gain a larger sample size and to increase the significance of the data. The combined data showed a

32.0% reduction in oocysts by the Pbs21 immunotoxin, and a 80.1% reduction by the scorpine peptide as calculated by the median number of oocysts. The Pbs21 immunotoxin reduced prevalence by only 0.3%, but the scorpine construct reduced prevalence by

20.1%, which is a large reduction considering the mean number of oocysts per midgut in the control mosquitoes was 120.4.

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These experiments waere not ideal, considering the very high number of oocysts in the control mosquitoes that were fed control Asaia strains not expressing effector proteins. In the lab, Plasmodium berghei-infected mosquitoes regularly produce a large number of oocyts regularly, but this does not correlate with the level of infection that would be seen in other Plasmodium species (Whitten 2006). In the wild, individual P. falciparum-infected mosquitoes do not achieve infections of this magnitude, so the results of these tests remain promising. Scorpine and anti-Pbs21-Shiva1 should still be tested for parasite inhibition in vivo against P. falciparum because they may reduce prevalence even more. The prevalence of oocysts per mosquito is an important metric for transmission blocking since even a single oocyst can produce thousands of sporozoites and make the mosquito infective. To be an effective intervention, a paratransgenic bacteria strain would need to reduce prevalence to zero in a significant number of mosquitoes.

Increasing the efficiency of secretion

Due to both the presence of some protein remaining in the periplasm of cells expressing these secretion constructs and the fitness cost associated with expressing large proteins, the efficiency of these pathways need to be increased. Accordingly, to achieve this, the genes for the siderophore receptor protein and the YVTN beta-propeller protein were analyzed by predictive software to identify the signal peptide which directs protein transport within the cell.

The siderophore receptor signal sequence is quite long compared to most bacterial secretion signals. This, along with the amino acid sequence of the signal, indicates that

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the siderophore receptor protein most likely utilizes the twin-arginine translocation (Tat) pathway (Figure 4.14). Tat pathway signals tend to be longer than signal sequences targeted to the Sec pathway of Gram-negative bacteria, and the signal sequence from the siderophore receptor protein is around 51 amino acids long. There is a domain within the signal sequence which partially matches the conserved amino acids in Tat signal sequences of other bacteria. The consensus sequence of Tat signals in other bacteria is

Ser/Thr-Arg-Arg-X-Phe-Leu-Lys, where X can be any polar amino acid (Lee 2006). The region of the siderophore receptor protein from amino acids 22 to 28, Thr-Arg-Arg-Lys-

Arg-Pro-Leu, show some similarity to this. Use of the Tat pathway would also be an explanation for the much higher activity of the alkaline phosphatase protein secreted using this signal as tested in the PNPP plate assay (Figure 4.3). Proteins secreted by the

Tat pathway are translocated into the periplasm in the folded conformation, thereby retaining the conformation of the protein as it folded in the cytosol (Lee 2006). This could be beneficial for certain proteins secreted using this signal that require folding in the cytosolic environment to achieve the correct conformation.

The YVTN beta-propeller repeat protein is most likely dependent on the general secretory pathway for its translocation, as was predicted by the PRED-TAT analysis

(Figure 4.15). The leader peptide is short, around 26 amino acids in length and has a strong hydrophobic domain. This may be the reason that alkaline phosphatase secreted by this pathway does not have a high level of activity, since proteins secreted using this pathway are translocated in the unfolded conformation into the periplasm where they must refold. The Asaia periplasm may not be the correct environment for this to take place. The difference in PhoA activity secreted by the Sec and Tat leader peptides

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indicate that, in Asaia, PhoA folds best in the cytosol as demonstrated by the 9-fold increase in activity for protein secreted by the Tat pathway (Figure 4.3).

Asaia genome prediction of secreted proteins

The Asaia SF2.1 secreted proteins which may be secreted by Type II secretion systems are shown in Table 4.5. Among the top hits in this SignalP4.1 search, there were secreted proteases: peptidyl-dipeptidase DCP and gamma-glutamyltranspeptidase; transporter proteins: multiple TonB dependent receptor proteins and an ammonium transporter; a folding chaperone: peptidyl-prolyl cis-trans isomerase; and an enzyme: alginate lyase. The enzyme alginate lyase is involved in mannose digestion, and mannitol media is one of the growth media with which Asaia sp. bacteria can be cultured (Preiss

1962). In the future, it may be useful to use the secretion signals from these various proteases to attempt to secrete heterologous proteins.

The YVTN protein identified in the genetic screen was hit 152 out of 228 predicted secretion signals from the genome. This leader signal would have been overlooked if experimental design relied solely on genomic data. Furthermore, the siderophore receptor protein that was the best candidate isolated from the PhoA library screen was not identified at all from the genomic analysis. This means that at least two useful signal sequences would never have been explored if only the bioinformatic approach had been used. Each method of discovery has benefits and drawbacks, however, they each provide different results and can be used in conjunction to perform a more thorough search for secretion signals. The signal peptides identified from the genome predictions remain to be evaluated.

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There are inherent strengths and weaknesses in each of the genetic screen and the genomic prediction approaches to secreted protein identification. The genetic screen's primary benefit is the direct identification of actively transported proteins using any secretory pathway; the fusion proteins identified can be rapidly tested to determine the localization and amount of protein no matter what mechanism mediates transport.

Reliance on the secretion of fusion proteins in the genetic screen may cause certain secreted proteins to be missed due to either the fitness cost associated with the fusion construct or the lack of necessary secretory proteins that may not be present under the screen conditions. The genomic prediction's strength is that it can identify any protein with a type II secretion signal, even those that may not be expressed in a large amount or that may not always be actively translocated. These proteins can still be identified by their signal peptide sequences. The weakness of the genomic prediction is the predicted genes may not be secreted, but instead may be localized in the periplasm or membrane- bound. Each secretion signal from a genomic prediction would need to be cloned and tested individually to determine its function.

Conclusions

These positive results have built on the previous proof-of-concept trials with

Pantoea agglomerans by bringing functionality to a new paratransgenic species, Asaia sp. SF2.1. There is now at least one possible secretion signal that can be used in paratransgenic Asaia strains to deliver antimalarial proteins into the mosquito midgut

(siderophore receptor signal), and a second that requires further testing to prove useful

(YVTN protein signal). Further signal peptides may be found that are useful if the genomic data are explored further.

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This research has moved malaria paratransgenesis one step closer to practical use in the field. Asaia is a more useful symbiont of anopheline mosquitoes than previous paratransgenic species considered due to its beneficial microbial ecology, and now that it has been given the capability to secrete heterologous effector molecules, these characteristics can be taken advantage of. The antimalarial constructs tested in these experiments prove that Asaia can be effectively modified and used to deliver heterologous proteins into the mosquito midgut and to inhibit the sexual life stages of P. berghei malaria.

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Figure 4.1. Plasmid for phoA fusion library construction. A leaderless alkaline phosphatase gene was cloned downstream of the nptII promoter and translational enhancer of pNB51. This construct also contains an NdeI restriction site at the start codon of the phoA gene into which random genes can be cloned in-frame. pBBR ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. ‘phoA = C-terminal domain of alkaline phosphatase, lacking a secretion signal. enh = translational enhancer. PnptII = promoter from neomycin phosphotransferase.

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Figure 4.2. PhoA-Asaia protein fusion plasmids expressed in Asaia. The top ELISA used an anti-PhoA-HRP antibody to detect the presence of the alkaline phosphatase protein. The Tsr and Ybp fusions show a high amount of protein present in the supernatant fraction. The bottom plate assay used a PNPP substrate, which turns yellow when cleaved by active PhoA. Both Tsr and Ybp fusion proteins show activity from the secreted PhoA, however the Tsr signal is far more robust. Quantitative results are shown in Figure 4.3. PhoA = alkaline phosphatase. Tsr = TonB-dependent siderophore receptor. Aap = amino acid permease. Trp = TonB-dependent receptor plug. Gdh = glucose dehydrogenase. Ybp = YVTN beta-propeller repeat protein. Csy = cellulose synthase. Amu = aminomutase. Ptp = peptide transport permease.

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Asaia WT PhoA Tsr Asp Trp Gdh Ybp Csy Amu Ptp AVG PhoA 0.081 0.023 1.167 0.026 0.075 0.019 0.616 0.025 0.029 0.028 abundance AVG PhoA 0.055 0.058 1.951 0.057 0.081 0.057 0.380 0.062 0.059 0.060 activity

Figure 4.3. Secreted protein abundance and activity from PhoA-Asaia protein fusion plasmids expressed in Asaia. Both the ELISA and PNPP plates were repeated five times, and quantified using a plate reader. Signal intensity was read at 450 nm for the ELISA and at 400 nm for the PNPP assay. Although there was a similar amount of protein secreted by Tsr compared to Ybp, PhoA activity was more than five times stronger when secreted by Tsr. PhoA = alkaline phosphatase. Tsr = TonB-dependent siderophore receptor. Aap = amino acid permease. Trp = TonB-dependent receptor plug. Gdh = glucose dehydrogenase. Ybp = YVTN beta-propeller repeat protein. Csy = cellulose synthase. Amu = aminomutase. Ptp = peptide transport permease.

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Figure 4.4. pNB92. The pNB51 plasmid was modified by cloning ‘phoA into the plasmid with additional restriction sites 5' to the gene, generating pNB92. pBBR ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. ‘phoA = C-terminal domain of alkaline phosphatase, lacking a secretion signal. enh = translational enhancer. PnptII = promoter from neomycin phosphotransferase.

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Figure 4.5. pNB93. The N-terminal domain of ybp was cloned into the pNB51 plasmid with the addition of a Myc epitope tag and multiple-cloning-site between ybp’ and ‘phoA. pBBR ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. ‘phoA = C-terminal domain of alkaline phosphatase, lacking a secretion signal. enh = translational enhancer. PnptII = promoter from neomycin phosphotransferase. ybp’ = N-terminal domain of YVTN beta-propeller repeat.

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Figure 4.6. pNB95. The N-terminal domain of tsr was cloned into the pNB51 plasmid with the addition of a Myc epitope tag and multiple-cloning-site between tsr’ and ‘phoA. pBBR ori = replication origin. oriT = origin of transfer. neo = neomycin phosphotransferase, kanamycin resistance. ‘phoA = C-terminal domain of alkaline phosphatase, lacking a secretion signal. enh = translational enhancer. PnptII = promoter from neomycin phosphotransferase. tsr’ = N-terminal domain of TonB-dependent siderophore receptor.

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Figure 4.7. Antimalarial effector constructs. Effector genes were cloned in-frame with the siderophore receptor gene. The first construct depicted above is the basic PhoA secretion construct pNB95 with no effector. Each of the remaining constructs has a different protein inserted into the multiple cloning site of the former plasmid. Restriction sites used to assemble these constructs are shown at top.

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Figure 4.8. Western blot of the supernatant of Asaia cultures detecting proteins secreted using the siderophore receptor fusion protein. Proteins were detected using a rabbit polyclonal anti-PhoA primary antibody and goat anti-rabbit HRP secondary. The red boxes are highlighting the predicted protein size of the full fusion proteins on top, and the predicted size of the effector molecules plus alkaline phosphatase without the siderophore receptor protein. All proteins show proteolysis of the native Asaia fusion protein.

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sample set control Pro-EPIP anti Pbs21-Shiva1 N 49 29 53 Range 500 457 420 Prevalence 91.8 86.2 98.1 Tbp -- 6.1 -6.9 Mean 188.6 173.3 119.9 Mean % Inhibition - 8.1% 36.4% Median 144 175 104 Median % Inhibition -- -21.5% 27.8% P-value -- 0.609 0.005

Figure 4.9. Disruption of Plasmodium berghei development by Pro-EPIP and Pbs21- Shiva1 constructs. Three-day old Anopheles stephensi mosquitoes were fed paratransgenic strains of Asaia expressing either PhoA alone with no secretion signal, or expressing one of the fusion constructs combining the siderophore receptor protein, an effector protein, and PhoA. These mosquitoes were then fed on an infective mouse and the parasite was allowed to develop for 10-14 days. The mosquitoes were then dissected, and oocysts on the midgut were counted for each individual. Each dot on the chart represents a single midgut count. The median number of oocysts for each data set is marked with a horizontal line. Inhibition, inhibition of oocyst formation relative to the −Bact control; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; N, number of mosquitoes analyzed; Prevalence, percentage of mosquitoes carrying at least one oocyst; Range, range of oocyst numbers per midgut; Tbp, transmission-blocking potential: 100 − {(prevalence of mosquitoes fed with recombinant P. agglomerans)/[prevalence of control (−Bact) mosquitoes] × 100}. Pbs21-Shiva1 effected significant Plasmodium inhibition of 27.8% calculated using the median.

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sample set control scorpine PLA2 N 45 22 23 Range 279 330 176 Prevalence 97.8 81.8 100 Tbp -- 16.4 -2.2 Mean 98.1 50.8 81.9 Mean % Inhibition - 48.2% 16.5% Median 85.0 22.5 76.0 Median % Inhibition -- 73.5% 10.6% P-value -- 0.014 0.330

Figure 4.10. Disruption of Plasmodium berghei development by scorpine and PLA2 constructs. Three-day old Anopheles stephensi mosquitoes were fed paratransgenic strains of Asaia expressing either PhoA alone with no secretion signal, or expressing one of the fusion constructs combining the siderophore receptor protein, an effector protein, and PhoA. These mosquitoes were then fed on an infective mouse and the parasite was allowed to develop for 10- 14 days. The mosquitoes were then dissected, and oocysts on the midgut were counted for each individual. Each dot on the chart represents a single midgut count. The median number of oocysts for each data set is marked with a horizontal line. Inhibition, inhibition of oocyst formation relative to the −Bact control; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; N, number of mosquitoes analyzed; Prevalence, percentage of mosquitoes carrying at least one oocyst; Range, range of oocyst numbers per midgut; Tbp, transmission- blocking potential: 100 − {(prevalence of mosquitoes fed with recombinant P. agglomerans)/[prevalence of control (−Bact) mosquitoes] × 100}. The scorpine construct produced a significant inhibition of 73.5% calculated by the median oocyst number.

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sample set control Anti-Pbs21-Shiva scorpine N 134 120 96 Range 500 420 330 Prevalence 83.6 83.3 63.5 Tbp -- 0.4 24.0 Mean 120.4 82.2 44.6 Mean % Inhibition - 31.7% 63.0% Median 90.0 61.5 18.0 Median % Inhibition -- 32.0% 80.1% P-value -- 0.0006 <0.0001

Figure 4.11. Disruption of Plasmodium berghei development by anti-Pbs21-Shiva1 immunotoxin and scorpine constructs. Three-day old Anopheles stephensi mosquitoes were fed paratransgenic strains of Asaia expressing either PhoA alone with no secretion signal, or expressing one of the fusion constructs combining the siderophore receptor protein, an effector protein, and PhoA. These mosquitoes were then fed on an infective mouse and the parasite was allowed to develop for 10-14 days. The mosquitoes were then dissected, and oocysts on the midgut were counted for each individual. Each dot on the chart represents a single midgut count. The median number of oocysts for each data set is marked with a horizontal line. Inhibition, inhibition of oocyst formation relative to the −Bact control; Mean, mean oocyst number per midgut; Median, median oocyst number per midgut; N, number of mosquitoes analyzed; Prevalence, percentage of mosquitoes carrying at least one oocyst; Range, range of oocyst numbers per midgut; Tbp, transmission-blocking potential: 100 − {(prevalence of mosquitoes fed with recombinant P. agglomerans)/[prevalence of control (−Bact) mosquitoes] × 100}. The scorpine construct produced a significant inhibition of 73.5% calculated by the median oocyst number. These are the combined data from the previous trials and repeated trials.

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Figure 4.12. Signal sequence of the siderophore receptor protein. The signal sequence and cleavage site of Asaia bogorensis siderophore receptor protein were predicted using the software SignalP4.1 which uses a combination of several artificial neural networks and hidden Markov models (Nielssen 1997). In red is depicted the C-score, which shows likely the likely cleavage site of the signal peptide (Nielssen 1997). In green is the S- score, which shows the predicted signal peptide domain as distinguished from the mature protein (Nielssen 1997). In blue is the geometric average of the C-score and the slope of the Y-score, which results in better cleavage site prediction (Nielssen 1997).

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Figure 4.13. Signal sequence of the YVTN beta-propeller repeat protein. The signal sequence and cleavage site of Asaia bogorensis YVTN repeat beta-propeller protein were identified using the software SignalP4.1 which uses a combination of several artificial neural networks and hidden Markov models (Nielssen 1997). In red is depicted the C- score, which shows likely the likely cleavage site of the signal peptide (Nielssen 1997). In green is the S-score, which shows the predicted signal peptide domain as distinguished from the mature protein (Nielssen 1997). In blue is the geometric average of the C-score and the slope of the Y-score, which results in better cleavage site preduction (Nielssen 1997).

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Figure 4.14. Tat and Sec signal peptide computational prediction for the siderophore receptor protein. The signal sequence of the siderophore receptor protein was identified computationally using the PRED-TAT application, which uses a hidden Markov model to predict both Sec and Tat signal peptides (Bagos 2010). The reliability score for this prediction is 0.687.

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Figure 4.15. Tat and Sec signal peptide computational prediction for the YVTN beta-propeller repeat protein. The signal sequence of the YVTN beta-propeller repeat protein was identified computationally using the PRED-TAT application, which uses a hidden Markov model to predict both Sec and Tat signal peptides (Bagos 2010). The reliability score for this prediction is 0.988.

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Figure 4.16. pNB124. This plasmid is identical to plasmid pNB95, except tsr was truncated to retain only the coding sequence for the 51 aa signal peptide of the siderophore receptor protein.

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Figure 4.17. pNB124. This plasmid is identical to plasmid pNB93, except ybp was truncated to retain only the coding sequence for the 34 aa signal peptide of the siderophore receptor protein.

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Figure 4.18. Western blot demonstrating the secretion of alkaline phosphatase from Asaia SF2.1 using only the 51 amino acid long siderophore receptor signal or the 34 amino acid long YVTN beta-propeller repeat protein signal sequence. Protein samples loaded were 15 μl of supernatant from liquid culture (sup), or 5 μl of concentrated pellet (pel). The bands shown are of the correct predicted size for these contructs, 54 kDa.

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Table 4.1. Proteins identified from genetic screen for secreted Asaia proteins.

Signal sequences were identified using the PRED-TAT software. Predicted signal sequences are highlighted in blue. Protein identification is from protein BLAST hits against the Asaia SF2.1 genome, with related species identity from whole NCBI database if the result was hypothetical shown in parentheses.

protein identification Amino acid sequence Secretion pathway membrane protein MTQITVVLLFGITTIHGVTQVGDFYA Sec-dependent glycerol transporter (0.983 reliability (Mgt) score) hypothetical protein MTLLPRETHDSGRHNPIVAPSTRRKRPLAAGLMSATA Tat-dependent (Acetobacter outer CVALLHFVSDARAQSVSASETSTIPVNAAKAPAKSKV (0.983 reliability membrane KVNAQSRSTRARAVSAPVGDAPATSR score) siderophore receptor) (Tsr) major facilitator MMLARLAHLTYNPHSSFCKINSFSFKLRIYRKMSQLT no signal identified. transporter (Mft) SHDNRLVGPYGYSALAIAALIFFAMGFVTWL transmembrane domain predicted carbohydrate porin MDQMIWRSHTDPNRTISLFGRAMGAPQSDRVPIDFS no signal identified. (Chp) LNFGLTFNDPLPYRTDDTFGIGMGYTHVSGALANYD transmembrane RAVRRYSGAYSPTQGGETYVELTYQYQFTGWMQWQ domain predicted PDFQYIFNPGGGIPNPSHPDRRL multidrug ABC MEMSIIRSIDVELGQYVKKGQVLAHLDPTITKADIVN no signal identified transporter (Mdt) LKAQRDSYQATINRLHAEAEGKTFTPDL TonB-dependent MHRYGNLLLSMGLNINRTTLTHNGLSATGTPLLNAQ Sec-dependent receptor (Tdr) TTAYLTSESPRSKIVLNAYYTLGNWDVNLRQSRYGQ (0.982 reliability TVGMLTYQDWTPASAICPINGKALRGSNVCFAQFKN score) TPRWLTDLEIGYRFNQHWHVAVGANNIF hypothetical protein MPAYRAITLAAANLTKYNLTTLGFEADNTSQFPIGPV Sec-dependent (Xanthobacter TonB- LASLNYGGEYYHDSVKTKDQTGYEGSTPSGGRGVG (0.949 reliability dependent SAFTQLALNWKIVQLTGALRYDTYHASGSGV score) hemoglobin receptor) (Thr) cell wall-associated MLVRSLVSRPYGWGNYNFYNDCSAELRSLLIPFGIL no signal identified hydrolase (Cwh) MPRNSLAQIQATSRTVDLGKEDVEARLDYLV glucose MTMLAVRADFTACRNRQVVSFSGAVTDNNSTKEPSG Sec-dependent dehydrogenase (Gdh) VTRAFDLFTGKLVWVFDPSNPDPNEMPSGDHKYVA (0.718 reliability NSPNSWITASYDANLGLVYIPTGVQTPDQWGGNRTP score) DAERYASSVLALHADTGKLAWSYQTVHHDLWDMD unidentified protein MKFSHHAFIVSLVGLSLATAQATRAQETPAAPAQAAS Sec-dependent (Gluconobacter APATASSAASGVTSQAPASAATTPSAAPSSSATPTSTT (0.988 reliability YVTN beta-propeller AGSTTPASTAPVAPVVQVTPPAATSAATPVAGAVQTIP score) repeat protein) (Ybp) GMPAVIDPKNIYSETISGKISPAIKDDLARVYVPNLRG hypothetical protein MKHVRHSIAFLESWIDDAHHSPARTAIKTGLISFAILC no signal identified. (Asaia bogorensis MVIAAFVHL transmembrane cellulose synthase domain predicted subunit AB) (Csy)

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lysine 2,3- MLSPRRLRHIIEALSAMPHIQTIRIHSRVPVADPARITS no signal identified aminomutase (Amu) AMLDALETDRALWIVLHANHASEMTGQARAAIRQI QSRAIPVLSQSVLLRGVNDTEEALEALLRAFVTARIK PYYLHQLDPAPGTSHFHVPI peptide ABC MIRLALRLRGLSGSGF no signal identified transporter permease (Ptp) hypothetical protein MQRDVTLPLAAEQDLAAILAYEMDRLTPFDAEALF no signal identified (Gluconacetobacter WDFIVLRRDEALGQIMLRLSVVPQAPLRPLFERLHLL fimbrial assembly EAHPQAIADETGETLIRQPVARPLVTRLSDPRLALPLG family protein) (Faf) GCTLLACLLLGLFWHQSRVLSGYERQIDALRGPALE amino acid ABC MALPXSRAMSRFHDSVDXVLGDMMSDGTLQTILRR no signal identified transport permease WNLWTPEMAAMTGDPQRCVRCLLFAWLRYRDAMR (Aap) STARLGGAVPPLSRISAHHRQGGGADPCGVGPFHDP Ribonuclease I (Rns) MGTYLAERAGLRVRHDDLMAFFRTASQTTLPRALQL no signal identified RCETDHEGRIVLTQLWFTLAPGKMHLFPAAESYLTSP QNQDNCPAEFWV

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Table 4.2. Plasmids used in this study

Plasmid Relevant Characteristics Source pNB51 pNB20 w/ promoter region changed to PnptII this study pNB90 pNB51 w/ phoA insert used for genomic library construction this study pNB91 genomic library of Asaia DNA-phoA fusions this study pNB91.1 possible heavy metal transport protein PhoA fusion this study pNB91.2 outer membrane siderophore receptor PhoA fusion this study pNB91.3 Sugar permease, glucose/galactose transporter PhoA fusion clone this study pNB91.4 carbohydrate-selective porin OprB PhoA fusion clone this study pNB91.5 HlyD family secretion protein PhoA fusion clone this study pNB91.12 TonB-dependent receptor plug PhoA fusion clone this study pNB91.14 TonB-dependent hemoglobin receptor PhoA fusion clone this study pNB91.17 putative cell wall-associated hydrolase PhoA fusion clone this study pNB91.18 Quinoprotein glucose dehydrogenase PhoA fusion clone this study pNB91.24 YVTN family beta-propeller repeat protein PhoA fusion clone this study pNB91.25 cellulose synthase subunit AB PhoA fusion clone this study pNB91.112 L-lysine 2,3-aminomutase PhoA fusion clone this study pNB91.113 diguanylate cyclase PhoA fusion clone this study pNB91.132 fimbrial assembly family protein PhoA fusion clone this study pNB91.136 amino acid transport permease protein PhoA fusion clone this study pNB91.141 Rnase I PhoA fusion clone this study pNB92 pNB51 w/ phoA insert and MCS for gene fusion construction this study pNB93 pNB92 w/ YVTN beta-propeller repeat gene cloned this study pNB95 pNB92 w/ siderophore receptor gene cloned. this study pNB96 Siderophore receptor - Pro-EPIP - PhoA effector construct this study pNB97 Siderophore receptor - scorpine - PhoA effector construct this study pNB99 Siderophore receptor - PLA2 - PhoA effector construct this study pNB101 Siderophore receptor - prochitinase - PhoA effector construct this study pNB102 Siderophore receptor - anti-Pbs21 scFv-Shiva1 - PhoA construct this study pNB103 Siderophore receptor - Shiva1 - PhoA effector construct this study pNB105 Siderophore receptor - GFP - PhoA effector construct this study pNB106 Siderophore receptor - anti-BSA scFv - PhoA effector construct this study pNB107 Siderophore receptor - anti-Pfs25 scFv - PhoA effector construct this study

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pNB108 Siderophore receptor - anti-Pfs48/45 scFv - PhoA effector construct this study pNB124 pNB92 w/ the siderophore receptor 51aa signal peptide cloned this study pNB125 pNB92 w/ the YVTN beta-propeller 34aa signal peptide cloned this study

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Table 4.3. Oligonucleotides used in this study

Oligo Sequence 5' - 3' Purpose PhoA F NdeI taCATATGcctgttctggaaaaccgggc phoA directional cloning for pNB90 library vector PhoA R PacI taTTAATTAAggtgacaaggcaggaaaccac '' PhoA seq R1 cggcagtaatttccgagtcc sequencing PhoA library inserts PhoA F NdePacSbf TACATATGTTAATTAAAACCTGCAGGATGCCTGT phoA directional cloning to TCTGGAAAACCGGGCTG generate effector expression constructs PhoA R Fse taGGCCGGCCggtgacaaggcaggaaaccac '' siderophore F NdeI TAcatATGCCCAGAGCCGCTCGAC secretory leader protein directional cloning siderophore R TAttaattaaGTTCAGATCTTCCTCCGAGATCAGTTTC '' MYC PacI TGTTCAACAATCGGCGCCTCAGCCTGG YVTN F NdeI TAcatATGAAGTTTTCACATCACGC '' YVTN R MYC TAttaattaaGTTCAGATCTTCCTCCGAGATCAGTTTC '' PacI TGTTCAATGGCATAGGCCACATCATC scorpine F PacI taTTAATTAAaggctggattaacgaagagaagattc effector gene directional cloning scorpine R SbfI taCCTGCAGGaataagacaggggggtgccgc '' Shiva1 F taTTAATTAAaatgccgcgttggcgtctgttc '' Shiva1 R taCCTGCAGGaacccaccgcacgcgcatc '' PRO-EPIP F PacI taTTAATTAAaatggctagcgaagaaccgc '' PRO-EPIP R SbfI taCCTGCAGGacccggggctgcctttcac '' Pbs21Shiva F PacI taTTAATTAAaagcgaggtccagctgcagcagag '' Pbs21Shiva R SbfI taCCTGCAGGaacccaccgcacgcgcatc '' mPLA2 F PacI taTTAATTAAaatggctagctggcagatcc '' mPLA2 R SbfI taCCTGCAGGagtacttgcgcagatcgaacc '' EPIP4 F PacI taTTAATTAAagataaatccctggttaagg '' EPIP4 R SbfI taCCTGCAGGagcccggcgagcccttc '' Prochitinase F PacI taTTAATTAAagaagaaccgcataaggccg '' Prochitinase R SbfI taCCTGCAGGacttcttgccttcggcgctg '' Pfs25 F PacI taTTAATTAAaCCTTCTTCGATGTTCGCCTCtc '' Pfs R SbfI taCCTGCAGGaAGCCAGCGGATAGACGCTAGg '' Pfs48/45 F PacI taTTAATTAAaCAACCTGCTGAACTGGACATCG '' Pfs48/45 R SbfI taCCTGCAGGaACTTGTAACGCTAGGCGGTGTTG '' GFP F PacI taTTAATTAAaagtaaaggagaagaacttttcactg non-effector gene directional cloning

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GFP R SbfI taCCTGCAGGatttgtatagttcatccatgccatgtg '' BSA F PacI taTTAATTAAaATGGCCGAGGTGCAGCTGTTG '' BSA R SbfI taCCTGCAGGaTGCGGCCCCATTCAGATCCTC '' Sider51 R MYC TAttaattaaGTTCAGATCTTCCTCCGAGATCAGTTTC Leader peptide directional PacI TGTTCCTGTGCCCGTGCGTCACTG cloning YVTN34 R MYC TAttaattaaGTTCAGATCTTCCTCCGAGATCAGTTTC '' PacI TGTTCCTGTGCCGGAGCTGC

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Table 4.4. Bacterial strains used in this study

Strain Genotype Purpose E. coli Top10 F' F´{lacIq, Tn10(TetR)} mcrA Δ(mrr-hsdRMS- molecular cloning mcrBC) Φ80lacZΔM15 ΔlacX74 recA1 araD139 and plasmid Δ(ara leu) 7697 galU galK rpsL (StrR) endA1 propagation nupG (from life technologies #C3030-03) (Durfee 2008) Asaia SF2.1 wild type (from Guido Favia, University of protein expression Camerino, Italy) (Favia 2007) and paratransgenesis

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Table 4.5. Secretion signal prediction from Asaia sp SF2.1 genome.

The Asaia sp. SF2.1 genome ORFs were processed using the SignalP4.1 signal prediction algorithms to identify Type II secretion signals. The secretion signals were further characterized using PRED-TAT to identify the type of signal used. Protein Score Amino Acid Sequence Type peptidyl-dipeptidase DCP 0.936 MPVFRHTAALAAVALPLLSSTALA Sec gamma-glutamyltranspeptidase 0.929 MKRVCTRVAALPLLLASISVSSLAQA Sec hypothetical protein 0.928 MLVFNRRLLTGVAALAMTLSAPAFA Sec hypothetical protein 0.924 MRSFTRRALAASTFAAAALAVMPVAHA Tat TonB dependent receptor 0.919 MKLRKQRHALTLSLFCSPLALLSATAHA Sec protein TonB dependent receptor 0.913 MAISRIRICRASMLLGATILAGASFTAQA Sec protein hypothetical protein 0.907 MFKTRFLPALALTALVAAPVAHA Sec ammonium transporter 0.905 MSRVFKALAPLALCALPLPAFA Sec peptidyl-prolyl cis-trans 0.904 MRLTRPALFCAALISGTTLAAPAFA Sec isomerase hypothetical protein 0.902 MVSFPCRLVASTVLLASGLSALPAMA Sec hypothetical protein 0.901 MKKALPVLAALMLGLPLSAQA Sec alginate lyase 0.899 MKKGLFLFPACALASFVAAAHA Sec hypothetical protein 0.898 MTRFLSLLLVLGALPVAAFA Sec TonB dependent receptor 0.893 MKLRHRLIISASLPALLIAAHSAAMA Sec protein hypothetical protein 0.888 MTPRSFAAFAASLPLCFLATTAHA Sec iron ABC transporter 0.888 MRRILFAFALLALASTGSSLA Sec peroxiredoxin 0.886 MKRCFIPVSAALLSLSLAAAVPSAHA Sec hypothetical protein 0.884 MQVQSFRRWRGAALAALAFAVAPAIAQA Sec pentapeptide MXKDX repeat 0.884 MSFRTLALACAFSSAMLLGAPAFA Sec protein ABC-type phosphate transport 0.883 MQLSRIFGALSLSLALSCGVSHAA Sec hypothetical protein 0.883 MRFCSALILGLVSCASIAPLHA Sec copper resistance protein CopB 0.882 MNMRRHTINFLAGLAGTLLLSSGSHA Sec beta-lactamase 0.873 MVQRRHSFLRLLSVACGLALTAPAWA Sec hypothetical protein 0.870 MFAFTKSFIAAASLVALAAQPALA Sec Alpha/beta hydrolase family 0.870 MALARLLLTLCGMGTALA Sec protein hypothetical protein 0.869 MKHVFKAALAVSALLAAPALTPAPAFA Sec pilus assembly chaperone 0.868 MVTLLRKTCALGFLAALIVHQAPAFA Sec tricorn protease-like protein 0.868 MRLSSLLASTAIASLTLLGLASPPAQA Sec hypothetical protein 0.867 MMLRRRSALLGLAASWSLGRSSLAFA Tat TonB-dependent receptor 0.866 MSSSFTHRCLMMLLAGTALA Sec gluconolactonase 0.863 MNPAMKRRSFLSAASVAPLLGVAGPALA Tat outer membrane efflux protein 0.862 MATRRNRDAAGRLLLAAAALIVSSGAARA Sec hypothetical protein 0.859 MAKLRRGAFLAATLFVLPAGTAFA Sec polyphosphate-selective porin O 0.859 MTSLPRACRLLLASVSLASLAIATPVRA Sec gluconolactonase 0.858 MKTRLTLCTLALSLAATLVSPPSYG Sec cupin 0.857 MKYLWPLPVFLAFLSTAVMVQA Sec 3-carboxymuconate cyclase 0.855 MKTTISRRSFALGTLGLLGCGTAMA Tat cupin 0.854 MFAAYLARPLPCRRTLSSISILAAMMPFTAF Sec A porin 0.853 MSQTLSSTVLRFFSACLAVSCLTPVAHA Sec hypothetical protein 0.852 MIRYTALILSLAAPGIAQA Sec

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peptidase M61 0.851 MTIRLFRAGTFLAALVLGTHAVSAFA Sec glucose dehydrogenase 0.850 MRKPALMTATILGGLISATVAFA Sec hypothetical protein 0.847 MVNHAHSMRPFMFRAAFVGLIALMGYSV Sec PALA hypothetical protein 0.847 MLKSFLLLTVAALTGISPALA Sec hypothetical beta-glucosidase 0.846 MTSSSIARKKYLALAVGMAALLAGSRAIA Sec TonB-dependent receptor 0.846 MRRITGLVALALAGATSLTTAQA Sec thiol:disulphide interchange 0.846 MARPRGGRQFSSFTAIGLMLRKLSPVVLTL Sec protein DsbD LAFGSAPAFA membrane protein 0.845 MKTSFKISTALLTGFVAAVAAPVAQA Sec membrane protein 0.844 MSIFSAARFVAASALLASVSLPSLAQA Sec hypothetical protein 0.840 MIRKLTGAAIALTAMTAVASAHA Sec Glutaryl-7-ACA acylase 0.839 MRVGHLTRSMLLVTSCLLGASQALA Sec TonB dependent receptor 0.838 MAYVFGRAKLKIGLAICLASATCLWQNFA Sec HA peptidase S41 0.836 MRKARNCLLLSVFSLTPILAWA Sec peptidase M16 0.833 MSVLPPLRKALLASSLLVAPTLFVAVSAPS Sec MA hypothetical protein 0.831 MMTRPKGLRHRLALSLFLCSVPAGLTAAP Sec AHA hypothetical protein 0.830 MSRISLGVFLVLTISPALA Sec hypothetical protein 0.829 MSVKHSLCAVALLTGALTAAFAGNWCAVA Sec hypothetical protein 0.829 MRRLMSAGAALVALSAGFAVTPASA Sec purine nucleoside permease 0.826 MLPACLASLACVLDLGVASAHA Sec membrane protein 0.824 MRLRTALLAMTSMAAAPTIAMA Sec hypothetical protein 0.823 MKGWLCALSALPVFLALLAAQA Sec hypothetical protein 0.823 MLSRLCLGLTAVAGLTFAGASAHA Sec hypothetical protein 0.823 MMKMHLTKLAALGFALAVSPSLVATNALA Sec biopolymer transporter exbB 0.823 MTRLFRLPALAAPALAVTLAVAQGVVVPAV Sec ALAQETPAAQPAAPAPDAAAPAPAAPDAA APAAPGAPAPDAAAPAPGAPAPDAAAPA cadmium transporter 0.822 MKRVQAIPALLMTVCVTGALLFPAGAQA Sec Periplasmic phosphoanhydride 0.818 MIRALILSLALALGGAGTAQA Sec phosphohydrolase Thiol-disulfide isomerase 0.816 MFHRKFGVLTSLALGLSTLSVAAPALTSNV Sec AYA nuclease 0.815 MTRRSLFALPALLSVAALTLASKPAQA Sec NAD dependent epimerase 0.814 MTRPMPQPVPRALKSLSRLGCLMLAMVS Sec CTTLA Inosine-uridine preferring 0.812 MRCFLASLALAALTIGTASA Sec nucleoside hydrolase polyisoprenoid-binding protein 0.808 MNVQFRPLPVRQMIALFSVLLPMAGATLA Sec SA GntR family transcriptional 0.807 MKRLALSLPIMCITLAAQPVMA Sec regulator murein transglycosylase 0.807 MSRVKSLLLTSTLLLLGGCSTHA Sec phenylacetaldoxime dehydratase 0.806 MFMKRLSLFLAASALTVLSSSGHA Sec amino acid permease 0.804 MALRQHQQSKRPRYATALSLIAGISTLTAFA Sec APSFA toluene transporter 0.803 MFKTCISFSRRAALGVLTTALVSVAALSTP Tat AHA ABC transporter permease 0.801 MSVFDVRNAALLSLALSMTAGAATAMA Sec peptidylprolyl isomerase 0.800 MRISRSIKTLVAGASFLALAACG Sec aldose 1-epimerase 0.792 MKSAVCLVALAGIMDGAAQA Sec

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Ferrichrome-iron receptor 0.791 MSLLTLSALNPGMPRPRRLALSALLMLSAT Sec LPCQAFA anthranilate synthase subunit I 0.789 MMRPVAFLLAIMLAGSGLSRAHA Sec Endonuclease 0.784 MLRVFLSASAVFATLALPLTMAHA Sec sirohydrochlorin ferrochelatase 0.784 MKPELGLLATLMALPLAPLTAVA Sec ArsR family transcriptional 0.782 MIGPIIVLMLLVLGVAPALA Sec regulator glycosyl transferase 0.778 MMRSRSSSPILVVKRLTMALCMGSAVQPAI Sec A membrane protein 0.777 MKISALGATLMAATFAVATPAFA Sec ABC transporter 0.776 MSPRLSCTALALLALASAPQHARA Sec CTP synthetase 0.776 MTIPSLSALRRSLLTFVMAGAVTSVSAACA Tat QS nitrogen utilization protein B 0.773 MKQSAPLRLFLCALGAGTVLMPALATA Sec peptidase S10 0.773 MAHDLFMRHFLSSAILVSALSLTACA Sec thioredoxin 0.769 MPGFRRGLLALPLLFSIWGSSQARA Sec phenylacetaldoxime dehydratase 0.768 MFMKRLSLFLAASALTVLSSSGHA Sec methionine ABC transporter 0.765 TRQLIPAIALGLLTGCASA Sec Xylose ABC transporter 0.765 MNKFLKTLLASTLITGSALSLASGKACA Sec glycosyl transferase family 1 0.764 MKRFIPLSPALLTGFALIGAVAHA Sec Glycerophosphoryl diester Tat phosphodiesterase 0.763 MLSRRHALTLGAAGFCAPAFASRSFA TonB dependent receptor 0.762 MKTFRIVYGIGLAILLPLGAQAEA Sec Ferrichrome-iron receptor 0.758 MSAKRVRPSHPLTLIVGMTLACTSAQAQA Sec Type I secretion outer Sec membrane protein, TolC precursor 0.758 MKTDQLKAYTSLSVGLIALLNSTTALA Glutamine cyclotransferase 0.757 MRLLLVCIASFSGLAMTACLFAPAGLA Sec Dipeptide-binding ABC Sec transporter, periplasmic substrate-binding component 0.757 MRGRYGLILAGLGAVLLAPSLHSQGAQA Outer membrane vitamin B12 MRPMRSLRACLLTGISLAPALGLLPLLPAA Sec receptor BtuB 0.757 LA MIINPTRRLSARYRCALLALTSLSFALVPEI Sec GLAQAGPVSTPPGTVSAPVAPSVPSAERGP heat shock protein HtpX 0.756 QSPA MNSPILPPMKHAAASLLALLALGGAARHA Sec hypothetical protein 0.756 HA FIG01225103: hypothetical Sec protein 0.755 MRPYPALPALLLLAGSLPCAAHG hypothetical protein 0.754 MRQLLLIILCALALHGLAGTSRAQS Sec secretory lipase 0.754 MRSVLAMMAVSALTLTACA Sec hypothetical protein 0.753 MTRKLALLAAVALALPAGGLAGVAQA Sec Cysteine desulfurase (EC Tat 2.8.1.7) 0.75 MTTSPNRRFLLKSFATGAPALLASSSVAA FIG00688467: hypothetical Sec protein 0.745 MGAMGLAVAVATLSGAMLASITPAQA Various polyols ABC Sec transporter, periplasmic substrate-binding protein 0.744 MKKSLLLASAALGLGLGAQAKA Levansucrase (EC 2.4.1.10) 0.744 MLNLLLAGSMVATFTSQAAFA Sec Sigma-fimbriae tip adhesin 0.741 MRALAILAIGLCCGLITPAARSACA Sec Heavy metal RND efflux outer Sec membrane protein, CzcC family 0.741 MRARCFLASSLVAVAALAPGARA

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Adenosine deaminase (EC Sec 3.5.4.4) 0.739 MLPRILPAFALAVPLVFSSASARA TonB-dependent receptor 0.738 MRHLRRDLLVFCSAIVMNSVVGAIAAQA Tat hypothetical protein 0.73 MRHILKIGLAALPLIGLMGGAPMVQA Sec peptide chain release factor 2 0.73 MLMRPALLFLASLASALGLSACVPAPG Sec hypothetical protein 0.729 MNKSFLAGLTLVTFLAALPQAHA Sec Hypothetical membrane protein 0.728 MGFSRALAPLVLISSCALTACGSSTPA Sec MSFSIVRPPIRRRARALLGFTLVVSTSLFVA Sec hypothetical protein 0.728 GQPHA Outer membrane lipoprotein MKSASQKTSQRQKSHAGLARALLCIAPLA Sec OmlA 0.726 LA COG1744: Uncharacterized Tat ABC-type transport system, periplasmic component/surface lipoprotein 0.724 MSLKRPALLTRRGLLAAGGCAALAGRASA hypothetical protein 0.724 MTRYARQFLPLLAILGTGTALT Sec Ferrichrome-iron receptor 0.721 MSVSLRAALCLSSLLSAAMVPDALA Sec MMELKMPLARRGFLTTALGGAVCAALPAR Tat Gluconolactonase (EC 3.1.1.17) 0.717 AATDVTA FIG00687573: hypothetical MSRSRSRIQSFLRFGSVCLLLGSVSPLLTAC Sec protein 0.717 G Lipid A biosynthesis lauroyl Sec acyltransferase (EC 2.3.1.-) 0.715 MARLALAALSSLPAAMA MLSPLIMTRPTRSLAAVLLALTCLSPSLVAK Sec Acid phosphatase 0.714 PAQA hypothetical protein 0.714 MQKVLPVLTALLLSIIPQATLANA Sec Membrane fusion component of Sec tripartite multidrug resistance system 0.712 MAYKKPLLFAGCTALVLTGLAWS MVRRVTLPYRHRGLRQSTLMVALFCTVFA Sec TonB-dependent receptor 0.705 APAEGLA MTNPTNFRRSARVLGGLAGLLMLAACEGT Sec hypothetical protein 0.702 A Flagellar L-ring protein FlgH 0.701 MTRFFSRGSLTVLLLLGSCTSLS Sec hypothetical protein 0.7 MGLVLMLLVGMASQASAHA Sec Peptidase 0.699 MRSLRPSVAALIIGTVLTGMPARA Sec MQTRNRTVTPGFLTQTRQALPGLFLGCILS Sec hypothetical protein 0.698 ASALSGCAQA hypothetical protein 0.698 MRHLLGRTLMAASLIITLPQAMA Sec MSQQSLRVSLHNRTRAALRRAALATLSVG Sec hypothetical protein 0.698 ALGLTCHSGMAYA MDFAERRNGLMIFMKSRLSKSASASLAML Sec hypothetical protein 0.696 GFSVALAPVPALS hypothetical protein 0.696 MRRLSGLKLAASVVAVGAAFASHGASA Sec hypothetical protein 0.696 MTTASFLRTGALAVMLALPALG Sec MISCELLANEOUS; Unknown 0.695 MRTYLIAGALALASCVVVTGAFVSPTFA Sec Xylose ABC transporter, Sec periplasmic xylose-binding MFLFRFGFFKMITRTKFFLGALALSTVLAA protein XylF 0.693 PAARA MKTRFALTLAHAGLLGVSLLAGCADTPAP Sec hypothetical protein 0.693 QPTQA Prolyl endopeptidase (EC Sec 3.4.21.26) 0.691 MKRILMAMTSLVCTTFLPPVVGQALA D-alanyl-D-alanine 0.691 MRTRRFLLSGAAGLAVSSQFAFA Sec

169

carboxypeptidase (EC 3.4.16.4) FIG00687971: hypothetical MALKLSHGHVLLAGLMLGGAACASSPAL Sec protein 0.689 A MRFPRCSRALLVASSLLAASSFVPVIGSSLV Sec FOG: TPR repeat 0.688 TIAHA surface antigen gene 0.686 MKFSHHAFIVSLVGLSLATAQATRA Sec MNYSSIVHAVSRRRANRFGRALALASVLG Tat Acid phosphatase, class B 0.686 ATAAGAAHA hypothetical protein 0.684 MSRRNAFICCLPLMMGLLLLA Sec hypothetical protein 0.684 MTALLLKRCVMLCAFLMIPHAGFCA Sec hypothetical protein 0.683 MPGSLFTTPLTRIFTALLFMAPFGTGMAVA Sec Flavodoxin reductases Sec (ferredoxin-NADPH reductases) MRRVFLSVSVVIMTLLVSMSEGFAQAPGES family 1 0.683 PAVPAMSSGTMTGPTTGSPPPSLA MQTKHSPLRRVLLASLTAMPLAMVPGAAP Sec TPR domain protein 0.681 HA hypothetical protein 0.681 MRSASLLLFLMVLAGCA Sec MDPPAMPRVPSPAFGLALALLAWQPCPAL Sec hypothetical protein 0.67 A FIG00687356: hypothetical MNVPRFFPLMLTAALAATPVLFVPWHAAH Sec protein 0.669 A TonB-dependent receptor 0.667 MKKSLLFAVSLMCLDSVRAQA Sec hypothetical protein 0.661 MTHTAFALFCLTCAVGLPGAARA Sec TonB-dependent receptor 0.659 MLLGAAIILSPVVTNVAAHA Sec MRRLALGALLALSACSSVQYVPCPTLVTY Sec hypothetical protein 0.659 SKADQAALA MTGKFKRTTSLWLGAVSVIALTHQVLPAA Sec Metallopeptidase 0.659 HA MKSRKRAYSSTERCKKRLRARIGGIALLCT Sec Rare lipoprotein A precursor 0.656 VLAPKHGAHA Bll0045 protein 0.656 MRPAFFLAVGITAIGVLAAA Sec hypothetical protein 0.655 MGKLMAFLVGALALTSCNGIDHAACA Sec Gluconate 2-dehydrogenase (EC Sec 1.1.99.3), membrane-bound, cytochrome c 0.654 MMKRLSLLLATGFTLIGTLAVPPMGHA probable outer membrane MDLRCSKSRWPGARQVRAGSLSVLGLAV Sec protein 0.653 MGATAHA Heavy metal RND efflux outer Sec membrane protein, CzcC family 0.651 MAASLAMALVSGGVATA hypothetical protein 0.651 MQRFSALPVSDRRTLLLGLGALFLTGAAPA Tat MSHSRFRPLPCAALLGVIGALSACSSPQSP Sec hypothetical protein 0.651 S MVAFSRSLPSRFLPPRHPLRFRFRAISAVAS Sec hypothetical protein 0.649 LALLAHAAPARA Potassium efflux system KefA Tat protein / Small-conductance MSALKRRSALQLLYGLFLVFALSVSTFPAL mechanosensitive channel 0.648 A Phosphate-specific outer Sec membrane porin OprP ; Pyrophosphate-specific outer membrane porin OprO 0.647 MRARSLTSLLLLCGVVMPETGFA Carboxypeptidase-related Sec protein 0.647 MSRKTLVVALLASACFALPRLPAGHA putative hydroxylase 0.646 MLCSTSVLAAIPSAMA Sec

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FIG00689409: hypothetical MTTRLFAPRFRPAMIKRAALLLLLFQAGYA Sec protein 0.645 QPGHARA hypothetical protein 0.644 MVRLRGSAITLVSALTLAACATKPVVQR Sec MPEHRSAYKKNLVVALISSTALFQVSSPSA Sec TonB-dependent receptor 0.641 LA hypothetical Sec TRANSMEMBRANE protein 0.638 MRSRLPAITLYGSLACNAALLA Tiorf138 protein 0.637 MISLGKAGLTGFFLLCMAPSFSYA Sec MKRRVLLTCAASLALSGCAIGPNFHRPDM Sec hypothetical protein 0.637 LRTGGYQSKALPASIHGTTGTGSAGA hypothetical protein 0.636 MPINRRQILAGLSAGPVLAILSRAAVA Tat FOG: TPR repeat 0.635 MKHAFGALAIGSGLWAGGALA Sec MSHDMHHRKTAYSWGNRIVLPRQAACMA Sec TonB-dependent receptor 0.633 GLMLPLILPCETALA Soluble lytic murein Sec transglycosylase precursor (EC MRGISYFASSNSARAFMLCAMLVAGATFN 3.2.1.-) 0.632 PLRA MLKFKAARGRLPKTRRGQMLGASIGLVSA Sec Carbohydrate-selective porin 0.63 FAPTAARA Peptidase, T4 family 0.626 MKRRAFCLASLAATALA Sec MLLRSHTLLPSVARKGVFFLIASTCLMSCG Sec TonB-dependent receptor 0.623 GEALA Acylamino-acid-releasing MSLLSLSRVRLLGTSLLSLGMGSATLGGVT Sec enzyme (EC 3.4.19.1) 0.621 LASAQA MCSPVTNKTPTDKSDTSNRDEARGTSRTR Tat Aldose 1-epimerase (EC 5.1.3.3) 0.62 RSARPIMAIASGSLAAALSLAPAHA RND efflux system, outer Sec membrane lipoprotein CmeC 0.62 MVSLPRRLCAFTFAASLLAGCTVGPA hypothetical protein 0.616 MKNLILLALSIVSCLACTESRA Sec Organic solvent tolerance MSKRRVAHHRRRSWLAASMLAGTVTFGA Tat protein precursor 0.616 IPEADA MMRRLIPALTLGSLLMGLPLAGVPLEALLC Sec hypothetical protein 0.613 PQAHA Cytochrome c-552 precursor 0.613 MRAPLALALLAALALTACGKKSAGQ Sec Penicillin acylase (Penicillin MPSSPLTGRRALLQASACAALAACLPRPA Tat amidase) (EC 3.5.1.11) 0.612 RA Outer-membrane lipoprotein Sec carrier protein 0.612 MTVRRGLAATGLAIALAGCAVSGTDGLTA RND efflux system, outer MKTGYGSRRYYPAKILIGLCLLSLGATGCQ Tat membrane lipoprotein CmeC 0.611 EGDFNLPKGSAVVAPA PilL 0.61 MRGTPSLAAACALIMTGITGCA Sec hypothetical protein 0.609 MRRLGLAGGCLVPLSLAACTPAPPA Sec MITPHPDGAKAGKIMTDAMPVRLTPSRKF Sec HtrA protease/chaperone protein 0.607 RSLALVAATALSIGVGASSPAWA Membrane-bound lytic murein Tat transglycosylase B precursor MLTRRSILAATAAAPCLYGTSLAGTLGHKG (EC 3.2.1.-) 0.606 SAHVHKQATSA Outer membrane component of Tat tripartite multidrug resistance MRAGSRRRALRGSAAGAVFSLALLSGCDL system 0.606 A Outer membrane component of Sec tripartite multidrug resistance system 0.602 MRPLLAPLLALLVAGCVA Putative ABC transporter, MTLSRRGFMGVAASLTALTPFASARFSGAH Tat periplasmic sugar binding 0.598 A

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protein precursor Periplasmic thiol:disulfide Tat interchange protein DsbA 0.597 MSLYRRSFLAAMPALALMPKARA D-alanyl-D-alanine MQSATKTNLIKVTRAGKARKWSVFTRALL Sec carboxypeptidase (EC 3.4.16.4) 0.594 GAGLGLGTVAVSAPAHA RND efflux system, outer Sec membrane lipoprotein, NodT family 0.594 MTFSPSRSARRLSLLAACCTPLLSGCFMV FIG00688280: hypothetical MNVGQKSCLRLLRRPFFSSLTALSLLVGSA Sec protein 0.591 VLAPKAEA Peptidyl-prolyl cis-trans Sec isomerase 0.589 MPALVLLFPGLAAAATAPSPA hypothetical protein 0.588 MRTAILSRRFAILAVVGLTGLSAGNPA Sec MTKRVSFRSSRKLLAASACLGMLGLSACG Sec hypothetical protein 0.577 NPYDPGARA hypothetical protein 0.573 MRTLPLLAAMLLLACCTHPHPPE Sec FIG01224591: hypothetical Sec protein 0.573 MSERFKTALKLSLLGMSVGTSLTPVAARA Peptide methionine sulfoxide Sec reductase MsrB (EC 1.8.4.12) 0.572 MKFMTSRRQFCFASVCLALSGRAWG hypothetical protein 0.564 MIVLWALAGLSLLTAMTIASA Sec Potassium efflux system KefA Sec protein / Small-conductance MLSLSRAPNPGATVLTLENRYSARRPFSWC mechanosensitive channel 0.561 LLICLLVGSLCLQSGSARA permease of oligopeptide ABC Sec transporter 0.557 MLLAMGALLLLVLGAVAAPLYARA MSEASASGNKAASAVAMTASSAALACGV Sec hypothetical protein 0.546 CCVVPLALPA MKRTGIHALFQTQGHKRVLRLSGLTPVTVI Sec FIG167255: hypothetical protein 0.543 ALMTASSMPALA FIG00688799: hypothetical Sec protein 0.535 MARIVSGRVLAGALMGVMLLIGGHSVHA MTQLSSITIKAASAGRRKGAASRYAALGV Sec hypothetical protein 0.529 LALLSAPVASAALITPALA FIG004453: protein YceG like 0.526 MKRVILALVLLLLLCPAGGA Sec MLCLRAVASAGASTLSGFWLALYGLGSPA Sec ATP/GTP-binding site motif A 0.525 HA

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Control 1 Pro-EPIP anti-Pbs21-Shiva1 Control 2 Scorpine PLA2 44 209 1 0 420 122 126 208 21 82 101 180 259 500 228 21 10 87 99 133 3 0 132 73 66 148 189 242 98 31 157 62 95 24 111 116 115 169 175 248 195 49 87 3 35 24 151 76 93 175 275 95 0 119 242 30 15 60 64 18 142 107 250 280 90 8 76 128 126 2 120 28 211 0 457 0 107 6 90 155 142 1 106 30 427 0 155 174 300 5 101 75 330 45 30 114 53 53 277 251 67 285 149 279 0 6 64 77 9 111 0 324 237 63 135 69 8 0 180 4 196 377 235 133 110 49 18 35 98 0 9 35

149 500 320 126 84 43 130 95 65

86 88 202 118 126 104 85 250

142 0 83 168 8 122 28 50

357 86 0 286 340 126 50

302 111 221 69 91 267

315 133 7 2 74 78

405 350 200 177 12 82

60 480 166 1 4 45

287 400 93 154 8 55

72 140 139 159 66 156

170 214 136 138 0 79

128 0 57 103 128

357 300 75 24

144 139 189

52 319

166

Table 4.6. Oocyst counts from Anti-Plasmodium in vivo testing. Results from dissection and counting of oocysts with mercurochrome staining.

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Control Scorpine anti-Pbs21-Shiva1 24 175 27 2 60 0 26 143 30 38 44 151 28 40 0 0 41 28 28 38 60 51 0 4 120 194 168 28 59 31 93 282 0 8 45 49 287 222 293 0 49 58 157 160 0 21 41 100 101 97 108 4 62 87 24 9 0 18 86 40 36 120 18 5 26 49 68 70 14 47 20

61 125 71 101 44

45 59 80 76

202 98 157 93

58 124 23

130 40 69

82 20 96

44 66 99

178 79 97

95 74 61

54 33 19

63 0 132

167 0 129

178 60 133

0 0 61

144 41 128

Table 4.7. Oocyst counts from repeated Anti-Plasmodium in vivo testing. Results from dissection and counting of oocysts with mercurochrome staining. These data are from repeated trials with scorpine and anti-Pbs21-Shiva1 effectors.

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Chapter 5

Summary and future directions

SUMMARY

Malaria is a devastating disease that has significant health and economic ramifications worldwide. Novel approaches are needed to complement the existing methods of treatment and prevention in order to eradicate the disease. The mosquito midgut presents an excellent target for intervention. The work presented here demonstrates three methods which can be used to interfere with the vulnerable life stages of Plasmodium in the midgut: (1) The production of new anti-Plasmodium single-chain antibody effector molecules, (2) the modification of Pantoea agglomerans using the hemolysin secretion system to interfere with Plasmodium development, and (3) the discovery of native secretion signals in Asaia bogorensis and their use to modify Asaia sp. SF2.1 to interfere with Plasmodium development.

Design and construction of single-chain antibody molecules

The three single-chain antibody genes that were synthesized have a potential to be used in paratransgenic strategies. These scFv molecules specifically target the life stages of the Plasmodium falciparum parasite within the mosquito and should have no negative impact on any other organism in the host microbiome, unlike some of the broad-range antimicrobial effectors used in similar experiments (Barr 1991, Roeffen 1995, 2001). One drawback to using these particular antibodies is that they bind only to the surface proteins

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of Plasmodium falciparum (Roy 2009, Stowers 2000, Eksi 2006); therefore they will not provide any protection against the other species of malaria. Although P. falciparum is the most virulent Plasmodium species and causes the greatest human mortality of all malaria- causing species (WHO 2013), interventions are still needed to combat the other

Plasmodium species: P. knowlesi, P. malariae, P. vivax and P. ovale.

In particular, Plasmodium vivax causes tenacious infections and remains in the liver of the infected host for years, even after the blood-stage infection appears to have been cleared (Baird 2012). Hypnozoites, or “sleeping parasites,” lie dormant in the liver and emerge to reinfect the host, causing relapses of recurring blood infection and malaria symptoms. Currently, there is no cure for liver stage parasites, making it critical that P. vivax transmission is prevented before infection occurs (Baird 2012). Monoclonal antibodies are known to interfere with the P. vivax parasite development, and these could be converted for use in paratransgenesis as well (Sattabongkot 2003).

The single-chain antibodies presented in this work must be expressed and subsequently tested for activity against P. falciparum in vivo to assess whether they provide protection similar to previous paratransgenic constructs (Wang 2012). Antibodies may be modified to include antimicrobial peptides in the fusion protein that will further interfere with Plasmodium development and increase the overall inhibitory effect, as is the case with the anti-Pbs21 scFv with Shiva1 (Yoshida 1999). The combination of multiple effector molecules would help to prevent parasite evolution against either one, since a parasite that resists one of the anti-Plasmodium molecules would still be killed by the activity of the other. Likewise, artemisinin is used in combination with different drugs

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to treat blood-stage malaria infections in order to lessen the possibility of resistance

(Burrows 2013).

Although these antibodies are targeted to specific surface proteins of the parasite, evolution of resistance should not be as much of a problem as compared to the resistance that evolves against the drugs used to kill the blood-stage parasite (Hastings 2002).

Because there is a strong bottleneck in the life cycle of Plasmodium within the mosquito midgut, with less than five oocysts in field-caught mosquitoes on average (Whitten

2006), there is a far lower chance for the parasite to evolve resistance to interventions in the midgut than for the millions of blood-stage parasites present in an infected individual to resist antimalarial medications.

HlyA secretion of effectors from Pantoea

Positive transmission-blocking results from Pantoea agglomerans strains secreting antimalarial effectors into the midgut provide proof of concept that paratransgenesis in the mosquito to combat malaria is a possibility (Wang 2012).

Scorpine, EPIP4, and Shiva1 secreted by the hemolysin secretion system produced nearly

100% inhibition of P. falciparum oocyst formation in in vivo lab tests and, importantly, prevalence was reduced nearly 100%, as well. If prevalence could be reduced, then the mosquitoes would no longer transmit malaria and would not pose a threat to us.

The successful testing of paratransgenic P. agglomerans strains is hopeful for the future of paratransgenesis in malaria. A large number of vector anopheline mosquito species are capable of transmitting Plasmodium to humans, and paratransgenic bacteria could be used as a powerful tool to simultaneously treat these species. Previous

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approaches to transgene expression attempted expression of the effector protein from the mosquito host tissues (Ito 2001). Although testing of this approach was successful in the lab, utilization of this technique in the field would require both the genetic modification of many anopheline species and the subsequent replacement of the wild mosquito population with the transgenic strains (Raghavendra 2011). Paratransgenesis could solve this problem because the same bacteria can be introduced to many vector mosquitoes.

This could be accomplished quickly and more easily than the currently used methods of creating and introducing transgenic mosquito species by feeding the bacteria to wild mosquitoes mixed into a solution of sugar water.

Genetic screen for secreted proteins in Asaia

Two secretion signals that function in Asaia sp. bacteria were discovered that can be used to deliver antimalarial proteins into the mosquito host midgut and disrupt the gamete, zygote, and ookinete stages of Plasmodium that develop there. These signals include the native Sec-dependent signal from the YVTN beta-propeller repeat protein and the native Tat-dependent signal from the siderophore receptor protein. These experiments demonstrate that the siderophore receptor protein signal peptide is capable of secreting a wide range of proteins from peptides to single-chain antibodies, and therefore, it represents a great tool for secretion of active effector proteins.

In light of the recent genome sequence of Asaia SF2.1, the secretion signals identified from the functional genetic screen were compared to the predicted proteins that were identified using the bioinformatic approaches. The proteins identified in the screen did not match the top hits from the genome sequence, which would indicate that the best

17 8

predictions made by computer algorithms are either not accurate enough to rely on, or the secretion mechanisms that they employ will not allow heterologous proteins to be identified and detected by a genetic screen. The nature of the PhoA genetic screen, however, allowed for the quick selection of a leader peptide capable of secreting a heterologous protein and demonstrated the activity of the secreted PhoA protein in a simple plate assay. This is something that predictive software cannot provide. Therefore, the cloning and testing of random genes from a list of predicted signals can be a fruitless endeavor; however, when used in combination with a genetic screen, it can certainly be useful to have two sets of data to compare.

One of the greatest challenges for a paratransgenic strategy for malaria intervention is finding a suitable host from which effector molecules can be delivered.

Asaia sp. SF2.1 has an ideal relationship with the anopheline host for malaria transmission-prevention strategies. This species associates with the midgut, salivary glands, and reproductive tissues of the host, and they are transmitted from parent to progeny and from male to female during copulation (Favia 2007, Damiani 2008). These factors allow Asaia to deliver effector molecules to the midgut, where Plasmodium is most vulnerable, as well as to the salivary glands where the sporozoite stage of the parasite resides. This presents an opportunity to target the sporozoite stage of the parasite with the same effectors used in the midgut or with different effectors that target sporozoite-specific antigens such as the circumsporozoite protein that coats the outer membrane of sporozoites (Foquet 2014). Antimicrobial peptides secreted into the salivary glands could function to provide an extra barrier to transmission if Plasmodium were to pass through the midgut. Monoclonal antibodies that bind the circumsporozite protein

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target of transmission-blocking vaccines (Foquet 2014) would possibly be useful if they were converted into single-chain antibodies that could be secreted into the mosquito salivary glands by Asaia.

Paratransgenic strains of Asaia could be applied against other vector-borne diseases transmitted by anopheline mosquitoes, such as West Nile virus and Dengue.

There have been effector proteins identified including antibodies targeting mosquito C- type lectins necessary for Dengue infection and peptides targeting the West Nile Virus envelope proteins that are known to interfere with the transmission of each (Liu 2014,

Bai 2007). A single paratransgenic strain of Asaia could be engineered to secrete proteins targeting multiple insect-vectored diseases in areas where multiple diseases are endemic by expressing the genes as part of an operon. There may be further applications in plants for paratransgenic Asaia strains to protect crops against pathogens of agricultural significance due to its association with plant nectar (Yamada 2000). Some plant- associated bacteria have a detrimental effect on cultivation of plants, for example, a

Gluconobacter sp. bacterium reduces plant-pollinator mutualism and lowers the success rate of seed production in the orange bush monkey-flower (Vannette 2013).

Now that Asaia has been proven to be a viable paratransgenic candidate in the laboratory setting, further work needs to be done to increase the efficiency of the transgenic constructs to make them viable for release in the wild for field testing. The identified native proteins that secrete in Asaia have already had their signal peptides identified and retested for activity. Constructs that combine these signal peptides and effector proteins need to be built and tested in vivo to determine if there is a decreased

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fitness cost to the bacteria expressing the protein, as measured by their growth rate in culture, and to verify that the anti-Plasmodium activity is retained.

FUTURE DIRECTIONS

The antimalarial constructs produced in this body of work have been successful to an extent. Plasmodium inhibition was achieved, however, more work must be done to improve the function of these antimalarial paratransgenic strains so that they can be tested in the field. The identified secretion signals of the siderophore receptor protein and

YVTN beta-propeller protein will need to be cloned in-frame with anti-Plasmodium genes and compared against the constructs containing the full fusion proteins. Utilizing a signal peptide rather than a fusion protein for secretion will reduce the protein size produced so that it requires less resources for the bacteria to produce, and it should secrete more efficiently. Efficient secretion will prevent the membrane from getting

“clogged” with proteins which is detrimental to the health of the organism.

Transcriptional regulation of transgenes

The expression of transgenes using a strong constitutive promoter has a fitness cost on the bacterium that cannot be ignored (Rang 2003). The Asaia strains produced in this study have a decreased growth rate of at least half that of wild type Asaia

(unpublished observations). Such a significant decrease would render the transgenic strain uncompetitive in the wild and unlikely to remain in the mosquito population without constant reintroduction due to the competitive fitness disadvantage (Lenski

1998). To counteract this effect, either a weaker promoter could be utilized or a

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conditional promoter that is regulated in some way so it is repressed when not needed. A promoter that is turned on or off depending on the presence of a blood meal in the mosquito midgut could regulate the expression of the transgene so that the construct would have a minimal fitness burden. If such a promoter is identified, it would both allow the bacteria to compete with the other midgut microbiota normally and activate the anti-

Plasmodium effector genes only when an infected blood meal is taken by the host.

Maintenance of transgenes without selection

Once efficient constructs are designed for the expression and secretion of antimalarial effectors, these gene constructs will need to be maintained without antibiotic selection so they can persist in bacteria living within wild anopheline mosquitoes. The simplest way to accomplish this is to introduce the transgene into the bacterial chromosome by a transposon insertion similar to that used in paratransgenic Alcaligenes sp. (Bextine 2004). These well-established transposons have been utilized in a broad range of bacterial species including the Tn5 and Himar1 transposon systems (Reznikof

1993, Bextine 2005). Antimalarial effector constructs can be inserted into the chromosome of Asaia sp. SF2.1 using one of these systems with a single copy of the gene and without an antibiotic resistance marker.

CLOSING REMARKS

With the progress in anti-Plasmodium paratransgenesis described in this work, there is a greater possibility for future laboratory tests of paratransgenic Asaia strains.

These can potentially lead to future field testing and eventual use towards malaria

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eradication. Paratransgenic bacteria present one more potential weapon in the arsenal necessary to combat this deadly disease and will complement both current and future interventions in the fight for a world without malaria.

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Appendix

ASM Genome Announcements January/February 2014 Volume 2 Issue 1 e01202-13

A Draft Genome Sequence of Asaia sp. SF2.1, an Important Member of the Microbiome of Anopheles sp. Mosquitoes.

Jackie L. Shane1, Nicholas J. Bongio1, Guido Favia2, and David J. Lampe1

1Department of Biological Sciences, Duquesne University, Pittsburgh, PA 15282, USA. 2Scuola di Bioscienze e Biotecnologie, Università degli Studi di Camerino, Camerino, Italy.

Corresponding author: David J. Lampe ([email protected])

Reprint permission ASM publishes Genome Announcements content under the Creative Commons Attribution 3.0 Unported license. Under this license, the author is free to copy and redistribute the material in any medium or format. (http://creativecommons.org/licenses/by/3.0/legalcode)

Abstract Asaia sp. are abundant members of the microbiota of Anopheles sp. mosquitoes, the principle vectors of malaria. Here we report the draft genome sequence of Asaia sp. strain SF2.1. This strain is under development as a platform to deliver antimalarial peptides and proteins to adult female Anopheles mosquitoes.

Asaia sp. SF2.1 is a Gram-negative member of the alpha-Proteobacteria, family Acetobacteraceae (12). Asaia sp. were first isolated from the nectar of tropical flowers and subsequently from insect midguts (3, 7, 12, 13). The taxonomy of the genus Asaia is in flux and we are hesitant to assign Asaia sp. SF2.1 to a specific species, although it seems to be most closely related to either Asaia bogorensis or Asaia platycodi (unpublished obervations). Asaia sp. SF2.1 was isolated from a laboratory colony of Anopheles stephensi where it is extremely abundant in the gut, salivary glands, ovaries and testes of this insect (5). Asaia sp. have also been uncovered in Anopheles mosquitoes in the field, especially An. gambiae, the most important vector of malaria in Africa (3, 4, 6). Efforts to genetically engineer Asaia sp. SF2.1 are underway in order to provide a platform to deliver antimalarial effector molecules to Anopheles mosquitoes in the field in an effort to block transmission of malaria, a strategy called paratransgenesis (1, 6, 11). The sequence reported here is the first for the genus.

Sequencing and annotation of the genome of Asaia sp. SF2.1 was performed by ACGT, Inc. The standard protocol for the NexteraXT DNA sample preparation kit was used. The purified fragmented DNA was used as a template for a limited cycle PCR using

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Nextera primers and index adaptors. A second library was prepared using the Nextera Mate Pair Sample Preparation Kit.

In order to generate clusters of DNA, both libraries were sequenced in a paired-end 2 x 150 bp protocol by MiSeq™. The sequence reads passing the Illumina purity filter were demultiplexed. 4,097,892 standard library reads were generated, giving an average coverage of 351X based on the 3.5Mb genome. To generate additional mate pair reads, a second MiSeq run was done using the mate pair library. This run generated 999,241 mate pair reads (86X coverage).

De Novo Sequence Assembly A 93X coverage subset of the small-insert library and the mate-pair library were assembled de novo using ABySS (10), Velvet (14), and SOAPdenovo2 (8). The best Velvet, ABySS, and SOAPdenovo2 contig sets were combined together using CISA (9) to produce an assembly with 51 contigs. The largest contig is 506 kb, the N50 length is 162 kb, and the total assembly length is 3.5 Mb. The GC content is 59.6%.

Genome Annotation Annotation of the genome was performed by the NCBI Prokaryotic Genome Annotation Pipeline version 2.0 (https://www.ncbi.nlm.nih.gov/genome/annotation_prok/). A total of 3098 genes were predicted using this method, including 3005 protein-coding genes, 44 pseudogenes, 3 rRNAs, and 45 tRNAs.

Nucleotide sequence accession numbers. This Whole Genome Shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession AYXS00000000. The version described in this paper is version AYXS01000000.

Acknowledgements This work was supported by a Duquesne University Hunkele Dreaded Disease award to DJL. We thank Dr. Jim Lund at ACGT, Inc. for expert technical assistance.

References 1. Abdul-Ghani, R., A. M. Al-Mekhlafi, and M. S. Alabsi. 2012. Microbial control of malaria: biological warfare against the parasite and its vector. Acta Trop 121:71-84. 2. Aggarwal, G., and R. Ramaswamy. 2002. Ab initio gene identification: prokaryote genome annotation with GeneScan and GLIMMER. J Biosci 27:7-14. 3. Crotti, E., C. Damiani, M. Pajoro, E. Gonella, A. Rizzi, I. Ricci, I. Negri, P. Scuppa, P. Rossi, P. Ballarini, N. Raddadi, M. Marzorati, L. Sacchi, E. Clementi, M. Genchi, M. Mandrioli, C. Bandi, G. Favia, A. Alma, and D. Daffonchio. 2009. Asaia, a versatile acetic acid bacterial symbiont, capable of cross-colonizing insects of phylogenetically distant genera and orders. Environ Microbiol 11:3252-64. 4. Damiani, C., I. Ricci, E. Crotti, P. Rossi, A. Rizzi, P. Scuppa, A. Capone, U. Ulissi, S. Epis, M. Genchi, N. Sagnon, I. Faye, A. Kang, B. Chouaia, C.

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Whitehorn, G. W. Moussa, M. Mandrioli, F. Esposito, L. Sacchi, C. Bandi, D. Daffonchio, and G. Favia. 2010. Mosquito-bacteria symbiosis: the case of Anopheles gambiae and Asaia. Microb Ecol 60:644-54. 5. Favia, G., I. Ricci, C. Damiani, N. Raddadi, E. Crotti, M. Marzorati, A. Rizzi, R. Urso, L. Brusetti, S. Borin, D. Mora, P. Scuppa, L. Pasqualini, E. Clementi, M. Genchi, S. Corona, I. Negri, G. Grandi, A. Alma, L. Kramer, F. Esposito, C. Bandi, L. Sacchi, and D. Daffonchio. 2007. Bacteria of the genus Asaia stably associate with Anopheles stephensi, an Asian malarial mosquito vector. Proc Natl Acad Sci U S A 104:9047-51. 6. Favia, G., I. Ricci, M. Marzorati, I. Negri, A. Alma, L. Sacchi, C. Bandi, and D. Daffonchio. 2008. Bacteria of the genus Asaia: a potential paratransgenic weapon against malaria. Adv Exp Med Biol 627:49-59. 7. Katsura, K., H. Kawasaki, W. Potacharoen, S. Saono, T. Seki, Y. Yamada, T. Uchimura, and K. Komagata. 2001. Asaia siamensis sp. nov., an acetic acid bacterium in the alpha-proteobacteria. Int J Syst Evol Microbiol 51:559-63. 8. Li, R., H. Zhu, J. Ruan, W. Qian, X. Fang, Z. Shi, Y. Li, S. Li, G. Shan, K. Kristiansen, H. Yang, and J. Wang. 2010. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res 20:265-72. 9. Lin, S. H., and Y. C. Liao. 2013. CISA: contig integrator for sequence assembly of bacterial genomes. PLoS One 8:e60843. 10. Simpson, J. T., K. Wong, S. D. Jackman, J. E. Schein, S. J. Jones, and I. Birol. 2009. ABySS: a parallel assembler for short read sequence data. Genome Res 19:1117-23. 11. Wang, S., A. K. Ghosh, N. Bongio, K. A. Stebbings, D. J. Lampe, and M. Jacobs-Lorena. 2012. Fighting malaria with engineered symbiotic bacteria from vector mosquitoes. Proc Natl Acad Sci U S A 109:12734-9. 12. Yamada, Y., K. Katsura, H. Kawasaki, Y. Widyastuti, S. Saono, T. Seki, T. Uchimura, and K. Komagata. 2000. Asaia bogorensis gen. nov., sp. nov., an unusual acetic acid bacterium in the alpha-Proteobacteria. Int J Syst Evol Microbiol 50 Pt 2:823-9. 13. Yukphan, P., W. Potacharoen, S. Tanasupawat, M. Tanticharoen, and Y. Yamada. 2004. Asaia krungthepensis sp. nov., an acetic acid bacterium in the alpha-Proteobacteria. Int J Syst Evol Microbiol 54:313-6. 14. Zerbino, D. R., and E. Birney. 2008. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18:821-9.

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Book Chapter in: “Transgenic Insects” Techniques and Applications CABI Biotechnology Series Edited by MQ Benedict publication date December 2014 ISBN 9781780644516

Paratransgenesis in Mosquitoes and Other Insects: Microbial Ecology and Bacterial Genetic Considerations

David J. Lampe and Nicholas J. Bongio Department of Biological Sciences Duquesne University et al. 600 Forbes Avenue Pittsburgh PA 15282

[email protected]

Introduction The phenotype of any individual organism is the product of a complex interaction of the genotype and the environment. For insect vectors of plant and animal diseases, the phenotype of interest is the ability to transmit the pathogen in question. In principle, it should be possible to modify the vector phenotype to prevent disease transmission in two ways: by modifying the genotype through transgenesis (i.e., adding or removing genes in the genome) or by modifying some aspect of the vector’s internal environment. For vector insects, the environments in question are the tissues and structures necessary for pathogen replication and transmission. Very often these environments are co-colonized by symbiotic microorganisms. Manipulation of these microorganisms can lead to a change in the pathogen transmission phenotype of the insect. Changing the phenotype in this way is called paratransgenesis. This review will cover efforts to implement paratransgenesis in mosquitoes and will focus mainly on efforts to control malaria. Two recent reviews have already covered related material (Coutinho-Abreu et al., 2010; Wang & Jacobs-Lorena, 2013) therefore we will focus mainly on the microbial ecology of mosquitoes relevant to paratransgenesis and bacterial genetic tools that may prove useful in creating paratransgenic bacterial strains suitable for release in the field. Although the examples used will emphasize mosquitoes, the methods should be generally applicable to paratransgenesis for other vectors of plant and animal diseases. Other paratransgenesis systems are covered in this volume (AksoyX, DurvasulaX, FaviaX).

Requirements for successful paratransgenesis. There are several requirements that must be met for a paratransgenesis program to be successful. Microbial ecology: Suitable microorganisms must be identified that live in the vector in proximity to the pathogen or parasite and that can be cultured in the laboratory. The microorganisms must be closely associated with the vector in the life stage where transmission of the disease organisms occurs and the microorganism must be spread

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within the vector population by some means; Effector molecules: Effectors must be discovered that inhibit the parasite or pathogen within the vector. The more specific the inhibition, the better since unwanted and unpredicted interactions with non-target organisms can be reduced; Effector delivery: The effectors must be delivered from the paratransgenesis organism in efficacious concentrations and at suitable periods of time; No fitness costs: There should be no negative fitness effects on either the vector or the paratransgenic microorganisms. Stable inheritance: The genes encoding the effectors must be inherited stably by the microorganisms without selection; Introduction and spread: A means must be available to introduce and spread the paratransgenic strains in nature.

Each of these requirements will be discussed below. We would like to point out, however, that paratransgenesis can be thought of as a category of the emerging field of synthetic biology which seeks to create new microorganisms with carefully defined phenotypes. Methods emerging from this field will no doubt find applications within paratransgenesis programs and the degree to which these methods can be standardized can only accelerate progress in paratransgenesis.

Mosquito microbial ecology. The microbial ecology of a wide range of insects has recently been reviewed (Engel & Moran, 2013). The current understanding of the microbiota of mosquitoes has been recently reviewed as well (Minard et al., 2013a).

The culturable microbiota of mosquitoes has been examined extensively for a number of mosquito species (Demaio et al., 1996; Pumpuni et al., 1996; Straif et al., 1998; Gonzalez-Ceron et al., 2003; Pidiyar et al., 2004; Lindh et al., 2005; Rani et al., 2009; Cirimotich et al., 2011a; Dinparast Djadid et al., 2011; Joyce et al., 2011; Apte- Deshpande et al., 2012; Terenius et al., 2012; Ngwa et al., 2013; Valiente Moro et al., 2013). Because these studies only scored culturable species, they necessarily missed most of the bacterial species living in or on mosquitoes since most bacterial species are not easily cultured. Other studies have used PCR to amplify the 16S genes of the midgut microbiota to create cloned libraries of sequences that provide a look at the unculturable microbiota (Pidiyar et al., 2004; Lindh et al., 2005; Rani et al., 2009; Ngwa et al., 2013). As of this writing, only a handful of deep-sequencing metagenomic studies of mosquito microbiota have been published, most for Anopheles species (Wang et al., 2011; Boissiere et al., 2012; Osei-Poku et al., 2012). The most important result from these studies, from a paratransgenesis standpoint, is that there does not appear to be any species of bacteria that forms an obligate association with mosquitoes, although many are quite common. Members of the genera Pantoea, Serratia, Enterobacter, and Elizabethkingia are routinely found in Anopheles sp., for example. Asaia sp. bacteria are also very common in Anopheles and we direct the reader to a chapter in this volume for more information on this genus of bacteria (FaviaX). Wolbachia, however, seems to be naturally absent from Anopheles, in contrast to Aedes sp. where it is widespread in nature. Wolbachia can be experimentally introduced into Anopheles, albeit with difficulty (Bian et al., 2013). Minard et al. (2013) contains a comprehensive table listing the genera of

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bacteria found in numerous species of mosquitoes and we direct the reader there for more information.

The role of the mosquito microbiota is not well understood. Many presumed functions are reviewed in Minard et al. (2013). Almost certainly, the microbiota are involved in nutrition, especially in females where they may contribute to the digestion of the blood meal (Gaio Ade et al., 2011) and both in males and females where they may provide nutrients in addition to the sugar meals taken by both sexes (Minard et al., 2013b). It has been clearly demonstrated that the microbiota is involved in immune system activation in the midgut and that this activation plays a role in the ability of the mosquito to attack pathogens in the blood meal, especially Plasmodium sp. (Pumpuni et al., 1996; Dong et al., 2009; Cirimotich et al., 2011b; Sharma et al., 2013). Other roles for the microbiota include the ability to positively influence egg hatching and to aid in larval growth (Ponnusamy et al., 2011; Chouaia et al., 2012).

Exactly how mosquitoes acquire their microbiota is not entirely clear, although the microbiota of mosquitoes changes dramatically depending on the life stage. Wang et al. (2011), for example, found that the microbiota of larvae and pupae of An. gambiae were dominated by cyanobacteria, clearly a product of feeding in an aquatic environment, and the dominant bacteria changed dramatically by the time of adulthood. In some species, females deposit bacteria on the surface of eggs (i.e, “egg smearing”) and these can be acquired by larvae (Crotti et al., 2009; Damiani et al., 2010). During metamorphosis, the microbial community in the midgut is drastically altered and the gut is sterilized or nearly so via the formation of a meconium (Pumpuni et al., 1996; Moll et al., 2001), although there is evidence that some bacteria survive transstadially (Damiani et al., 2008). The gut is repopulated in the adult stage either through bacteria acquired from the water from which the adults emerge and/or a plant nectar meal taken upon eclosion (Lindh et al., 2005; Wang et al., 2011; Minard et al., 2013b). Some species of bacteria, namely Asaia sp., can be passed from males to females during mating (Damiani et al., 2008). The acquisition, composition, and change of the mosquito microbiota remains an area where further study is needed. Studies in this area should be able to identify appropriate microbial species for paratransgenesis and inform strategies on how to spread paratransgenic strains in nature.

2. Effector molecules After a suitable bacterial species is chosen for paratransgenesis, a critical step toward creating paratransgenic strains of bacteria is the isolation of anti-pathogen effectors. In principle, these can be any molecules that block pathogen development or transmission from the insect vector and can include proteins, peptides, small molecules, or RNAs. In this regard, the field of malaria paratransgenesis is rich with effectors and some of these may prove useful against other diseases. Reviews of anti-malarial effectors have been recently published (Caljon et al., 2013; Wang & Jacobs-Lorena, 2013). We will briefly treat each category below.

Proteins. Certain proteins have proved to be anti-malarial. For example, a component of honey bee venom, phospholipase A2 has demonstrated anti-malarial activity.

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Interestingly, its enzymatic activity is not necessary for its anti-malarial properties since mutants of it are also active against the parasite (Moreira et al., 2002; Rodrigues et al., 2008). There is speculation that the protein somehow alters the cell membranes of the mosquito midgut thereby blocking parasite invasion of that tissue.

A very important class of anti-malarial proteins is antibodies and their derivatives (Kontermann, 2010). Several monoclonal antibodies have been isolated that bind to surface proteins of the reproductive stages of malaria parasites and block different parts of the life cycle within the mosquito (Rener et al., 1983; Quakyi et al., 1987; Barr et al., 1991). Native antibodies are complex proteins consisting of four polypeptide chains linked by disulfide bonds. To use these antibodies in a paratransgenic strategy, the genes that encode the mature antibody must be converted into a single gene that encodes a protein that retains binding specificity and that can be translated and secreted by bacteria (Kipriyanov & Le Gall, 2004). Such constructs are called single chain antibodies (scFvs) and are synthetic constructs that link the heavy chain and light chain variable regions of a specific antibody into a single open reading frame that, when translated, forms a protein that can reconstitute the specific binding structure of a mature vertebrate antibody. There are numerous variations on this basic scFv theme (figure A.1) including single domain antibodies (containing only the heavy chain binding region and sometimes called nanobodies), diabodies (constructs that bind to two different antigens), and scFv-toxin constructs (scFvs that are fused to a toxin gene) (Kontermann, 2010). The first successful demonstration of paratransgenesis against malaria used this latter kind of construct secreted by E. coli in Anopheles stephensi to cause a decline in the number of oocysts formed in the midgut by Plasmodium bergheii, although the effect was weak (Yoshida et al., 2001). There is an extensive literature on the conversion of vertebrate IgGs to different single chain forms and we invite readers to explore that literature for specific applications (Fernandez, 2004).

Peptides. Peptides are another very important class of anti-malarial effectors which may also be useful against many other pathogens. A major benefit of this class of effector is that they are typically short, sometimes no more than twenty amino acids in length. There are two important classes of effector peptides: peptides that directly kill the parasite and those that interfere with some specific parasite-vector interaction.

Peptides that kill pathogens or parasites have been derived from venoms (for example, scorpine from scorpion venom) or, more commonly, from peptides that are secreted as part of the eukaryotic innate immune system. Hundreds of these latter peptides have been described from many different eukaryotes, only a few of which have been used in paratransgenesis (Otvos, 2005; Nishie et al., 2012; Vila-Farres et al., 2012). This is, obviously, a promising area for future research. Indeed, the canonical paratransgenesis program against Chagas’ disease transmitted by triatomine bugs used cecropin A (a peptide of the innate immune system of the giant silkmoth, Hyalophora cecropia) secreted by the Gram-positive bacterium, Rhodococcus rhodnii, to kill Trypanasoma cruzi (Durvasula et al., 1997).

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Other anti-malarial peptides interfere with some specific interaction between the parasite and the mosquito host and thus block some important life stage from proceeding. For example, enolase-plasminogen interacting peptide (EPIP) is a 6 amino acid peptide that, when supplied in excess in Anopheles midguts, blocks the interaction of plasminogen with ookinetes (Ghosh et al., 2011). Since the ookinetes cannot invade the midgut wall, they die and the life cycle of the parasite is aborted. Another antimalarial peptide of this class is SM1 (salivary gland-midgut peptide 1) which blocks parasite-vector interactions in both the midgut and salivary glands of mosquitoes (Ghosh et al., 2001).

Small molecules from biosynthetic pathways. Many small molecules are known that kill malaria parasites ranging from drugs used to kill blood stage parasites (e.g., artemisinin) to reactive oxygen species. Each of these molecules is the end product of some multigene biosynthetic pathway. In principle, it should be possible to move the pathway for these small molecules into a paratransgenesis species. For example, amorpha-4,11- diene, a precursor to the anti-malarial drug artemisinin, can be produced in E. coli by adding heterologous genes from yeast and Artemisia annua (Tsuruta et al., 2009).

RNAi. To our knowledge, small double stranded RNAs (dsRNAs) have not been used as effector genes to interfere with parasite-vector interactions through RNA inhibition although they could offer a powerful route to either kill parasites outright or block some important interaction with the vector. RNAi has been used in mosquitoes to knock out or repress particular genes by injecting the dsRNAs directly in to adults. Delivery of dsRNA to the gut environment by bacteria expressing dsRNAs might target mosquito gut tissues or parasites directly. Delivery of dsRNA via bacteria to silence genes is a standard technique in Caenorhabditis elegans biology (Timmons & Fire, 1998). Strong caveats to using this method should be considered, especially the fact that many eukaryotic parasites lack a response to dsRNA because they lack the machinery to process it. For example, Plasmodium sp. parasites and Trypanosoma cruzi lack this machinery although Trypanosoma brucei retains it (Kolev et al., 2011). Obviously, the potential effectiveness of RNAi would have to be evaluated on an individual pathogen/vector basis.

The need to express more than one effector. Paratransgenic strains of bacteria that express a single effector against a parasite or pathogen can be expected to lose effectiveness quickly. This is because the use of the effector will provide strong selective pressure and favor those parasite or pathogen variants that are resistant to the effector. The scientific literature is replete with instances of the failure of a drug or resistance strategy when single effectors or drugs are used by themselves. Bacteria, viruses, eukaryotic pathogens, agricultural insect pests, weedy plants, and even cancer cells all display this phenomenon as the simple and entirely predictable result of directional natural selection. Therefore, any paratransgenic strain that will be released into nature should express more than one effector. A simple way to do this would be to construct an artificial operon with two or more effector genes driven by the same promoter. Importantly, the effectors should act in different ways to minimize the chances that resistant parasites or pathogens will evolve.

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An aside: codon optimization. Effector genes have their origin in a wide variety of organisms, many of them eukaryotes. The native genes, therefore, reflect the codon usage bias of the organism from which they originated. This bias can cause problems during translation in the paratransgenic bacteria. A well-known solution to this problem is to optimize the codon usage of the effector gene to match that of the organism where translation will take place (Welch et al., 2009; Francis & Page, 2010). In practice, this means resynthesizing the gene from scratch. Commercial gene synthesis services are available that specialize in codon usage and we strongly recommend this practice. A recent permutation on codon optimization is codon harmonization which seeks to reflect the inherent use of both common and rare codons in a single protein coding gene, with rare codons clustered in regions where translation naturally slows to allow the nascent protein sufficient time to fold before translation resumes (Angov et al., 2011).

3. Effector delivery Once effectors are discovered that kill or impair the pathogen of interest, a way to deliver these from the paratransgenic bacterial species must be found. If the paratransgenesis bacterium is Gram positive, efficient secretion of proteins or peptides can be achieved using simple secretion signals added to the N-terminus of the effector constructs. This was the method used to secrete cecropin A from Rhodococcus rhodnii in the Chagas’ disease paratransgenesis system (Durvasula et al., 1997).

Effector delivery is more complicated if the paratransgenesis species is Gram negative. Gram negative bacteria have two cell membranes bounding a compartment known as the periplasm that separates the cytoplasm from the exterior of the cell. Any protein or peptide that is to be secreted has to traverse this complicated barrier. Passage through the periplasm is beneficial in some cases, however, as it allows certain proteins to fold properly and form disulfide bonds within a reducing environment. In nature, Gram negative bacteria have evolved at least 6 different mechanisms to secrete proteins and some of these have proved useful to secrete foreign proteins (Holland, 2010). Two of these mechanisms and the structure of the Gram negative cell membranes and periplasm are shown in figure A.2.

Heterologous secretion systems. As a first step toward achieving secretion of effectors from a new paratransgenesis species, heterologous systems can be tried. Two effective ones are the hemolysin A (HlyA) autotransporter secretion system from pathogenic E. coli and the pelB leader sequence from the pectate lyase gene of Erwinia carotovora.

Hemolysin A is a toxin encoded by the hlyA gene in the hemolysin operon of particular pathogenic strains of E. coli (Blight & Holland, 1994; Holland, 2010). This secretion system is designated as Type I, or an autotransporter. These sorts of secretion systems are dedicated to the secretion of a single protein and usually accomplish secretion in one energy-dependent step across both the inner and outer membranes of the Gram negative cell. Studies of various deletion constructs of HlyA have demonstrated that a C-terminal 46-50 amino acids are the signal that directs the protein toward the secretion apparatus (Kenny et al., 1992). That apparatus consists of the HlyB and HlyC proteins encoded by the hemolysin operon in addition to TolC, a native outer membrane protein. Together,

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HlyB, HlyC, and TolC form the transport mechanism that moves HlyA from the cytoplasm to the outside of the cell. Any protein or peptide linked to the HlyA signal sequence can also be transported using this system and it is highly efficient (Tzschaschel et al., 1996; Fernandez et al., 2000; Bisi & Lampe, 2011). Using the HlyA system, Wang et al. (2012) were able to secrete 7 different anti-malarial effector proteins from the Gram negative bacterial species Pantoea agglomerans in both An. gambiae and An. stephensi midguts.

Two caveats should be mentioned when discussing HlyA, however. The first is that, although very efficient, proteins secreted in this way do not spend any time in the periplasmic space (Holland, 2010). The periplasm is an important environment that allows many proteins to fold correctly before final secretion takes place. Secondly, the HlyA system depends on the presence of a host membrane protein, TolC. The success of malaria paratransgenesis in P. agglomerans using HlyA was achieved in no small measure due to the fact that P. agglomerans has a native TolC protein that can function with the E. coli HlyA system (Bisi & Lampe, 2011; Wang et al., 2012). Not all bacterial species are likely to have a homologue of TolC and thus HlyA-based secretion is not likely to work in them. For example, genome sequences Gluconobacter oxydans and Gluconacetobacter diazotrophicus, to which Asaia sp. are related (see chapter X, this volume), have no closely-related tolC homologues (unpublished results, Lampe and Bongio).

Another heterologous system that has proved effective at secreting foreign proteins is the pelB secretion system. PelB encodes the pectate lysase gene which is secreted from the plant pathogen Erwinia carotovora (Lei et al., 1987). The PelB protein is secreted via a Type II secretory mechanism, a category that includes several different pathways grouped together under what is termed the general secretory pathway (Sec) (see figure 2). This pathway is universal in Gram negative bacteria and seems to be homologous to secretion from eukaryotic cells (see reviews of the system in (Pugsley et al., 2004; Holland, 2010). Proteins that are synthesized with short N-terminal hydrophobic leader sequences are targeted to the inner membrane where they pass through the membrane in an energy dependent process involving numerous proteins in the secretion apparatus. Once in the periplasm, proteins cross the outer membrane to be inserted into the outer membrane or to be secreted outside the cell. Protein passage out of the cell is mediated by numerous mechanisms, many of which are poorly understood. Type II secretion using leader sequences like pelB have been very successful in secretion of a variety of proteins, especially scFvs and their variants (Dammeyer et al., 2011).

There are many positive features of heterologous Type II secretion. The main one is simplicity. The addition of a pelB or other leader sequence to a gene encoding an effector protein is trivial unlike the HlyA system which requires the presence of several other heterologous proteins. The downside to using Type II secretion is that, while simple, proteins cannot be targeted easily to exit past the outer membrane. Thus, proteins secreted by Type II secretion often get “stuck” in the periplasm which can have deleterious effects on cell fitness. We and others have noticed a strong correlation between efficient secretion and cell fitness (Bisi & Lampe, 2011).

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Native secretion systems. If heterologous secretion systems fail to function it may be necessary to develop native secretion systems for a given bacterial species. If a genome sequence is available it can be mined using bioinformatic methods to identify candidate secretion signals (Nielsen et al., 1997; Petersen et al., 2011). Bioinformatic methods are likely to miss many secreted proteins since it is known that many secreted proteins contain leaders that do not conform well or at all to any secretion consensus sequence (Payne et al., 2012). Alternatively, secreted proteins can be identified directly via 2D electrophoresis followed by MALDI-TOF which, again, requires the use of genomic data.

More than likely, the genome sequence will not be available for many candidate paratransgenesis species. Even if a genome sequence does exist, it can be difficult to identify secreted proteins based on computer algorithms alone, as noted above. In either case, classical microbial genetics can be used to identify candidate secretion signals. Identification of secreted proteins by genetic means is based on the use of a modified E. coli phoA gene that encodes alkaline phosphatase (AP) lacking its native secretion signal. When secreted into solid media containing 5-bromo-4-chloro-3-indolyl phosphate (BCIP), AP hydrolyzes BCIP turning it blue. BCIP cannot penetrate the inner membrane of Gram negative bacteria so the screen can identify proteins secreted, membrane bound, or periplasmic.

AP can be used in two different ways to identify native secretion signals. The first method is through the use of the transposon TnphoA (Manoil & Beckwith, 1985; Boquet et al., 1987; Gutierrez et al., 1987; Manoil et al., 1990). This transposable element, derived from a modified miniTn5, carries a phoA gene lacking a secretion signal sequence placed very close to the end of the transposable element. TnphoA is introduced into the target species (commonly by conjugation with E. coli) where it inserts randomly into the chromosome. If it jumps into a gene that encodes a secreted protein, the phoA gene in TnphoA may be fused with the secretion signal of the chromosomal gene. When a library of these random insertions is plated on agar with BCIP, blue colonies indicate the insertion of TnphoA into a gene encoding a secreted, membrane-bound, or periplasmic protein. Because the genes are “tagged” by the transposon, it is trivial to recover the sequence of the insertion site by anchored PCR techniques. There are, however, important caveats to consider when using this method, the main one being that TnphoA insertions will only recover secretion signals of genes that are active under the conditions used for the screen (i.e., on the agar plate) so some genes may be missed. In addition, the screen will only work if the transposon is active in the species in question and there are reports that Tn5 is not universally active in all bacteria. In that case, a similar transposon can be built based, for example, on Himar1, which seems to have fewer species barriers (Choi & Kim, 2009). Finally, the paratransgenesis species may have endogenous AP activity. This can be overcome by including Na PO4 in the medium which dampens the endogenous signal so that the TnphoA AP signal can be seen (Bina et al., 1997).

The second method to identify native secretion signals is to construct a plasmid library of genomic fragments fused to a leaderless phoA gene (Bina et al., 1997). Typically,

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genomic DNA from the paratransgenesis species is incompletely digested with a 4bp cutting restriction enzyme, size-selected to isolate 1-3 kb fragments, and then cloned upstream of a leaderless phoA gene. Importantly, this system incorporates a constitutive promoter so, in principle, any secreted protein can be recovered circumventing a shortfall of TnphoA. The library is transformed into the paratransgenic species and then plated on suitable media that includes BCIP. Blue colonies are picked and the positive clones are sequenced to determine the signal sequence directing secretion of AP. Not surprisingly, there are caveats to this method as well. If it is difficult to transform the paratransgenic species, then it may be preferable to transform the library first into E. coli and perform a screen for secretion there. Positive clones isolated in E. coli can then be transformed later into the paratransgenesis species to confirm that they secrete. The use of E. coli to perform the initial screen, however, means that some secreting clones may be missed. Despite the caveats of TnphoA or the construction of a secretion library, both of these methods allow direct identification of native secretion signals without the need for a genome sequence and should be considered even if a genome sequence is available.

4. Fitness considerations for paratransgenic bacteria As noted at the beginning of this chapter, the fitness of paratransgenic organisms must be kept in mind. Ultimately, paratransgenic strains are destined for release into the environment where they must compete with wild strains and species. Any severe fitness disadvantage will eliminate them before they can colonize vectors and suppress parasites or pathogens. We have already discussed several areas where fitness concerns can be addressed, including ensuring efficient secretion, codon optimization of effector genes, and the use of conditional promoters (see below). Ultimately, fitness levels of paratransgenic strains will have to be measured empirically.

Transcription of effector genes. Effector genes must be transcribed in the paratransgenesis species. Ideally, transcription would be strong, ensuring an abundance of the effector product. The kind of transcription necessary for a particular paratransgenesis program should be considered carefully. Does the effector need to be produced continuously or only under the specific conditions when the pathogen or parasite is present? Can the two conditions be distinguished? The answers to these questions will determine what kind of promoter to use to drive effector gene transcription.

Constitutive promoters. If a continuous supply of effector gene product is desired, the gene should be placed under the control of a constitutive promoter. Heterologous constitutive promoters exist that function in a wide variety of bacterial species. One such promoter is that from the neomycin phosphotransferase II gene (nptII) (Auerswald et al., 1981; Beck et al., 1982; Reiss et al., 1984). If a genome sequence is available, then the native promoters for genes like the homologues of E. coli rpsL (30S ribosomal subunit protein S12) and groEL (an E. coli chaperonin) should be considered. Of course, any gene expressed in a constitutive manner can be considered as long as the promoter is sufficiently active to produce the desired amount of effector gene transcript. For the laboratory demonstration of paratransgenesis for malaria using P. agglomerans, we used the nptII promoter (Wang et al., 2012).

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Conditional promoters. If the parasite or pathogen enters the insect vector under specific conditions, then the use of conditional promoters should be considered. Female mosquitoes that transmit malaria, for example, acquire the parasite in a blood meal, which leads to a dramatically different gut environment than does sugar feeding. Conditional promoters offer distinct advantages over constitutive ones in this context. In particular, bacterial strains that only express the anti-pathogen effector proteins under narrow conditions are more likely to be able to compete with wild strains since the potential fitness cost of expressing the effectors is limited in time.

Bacterial genetic screens have been developed to detect genes that are activated under specific conditions. The most common and successful of these screens are in vivo expression technology (IVET) and differential fluorescence induction (DFI). Many permutations of both of these screens as well as their relative strengths and weaknesses have been reviewed (Rediers et al., 2005; Jackson & Giddens, 2006; Hsiao & Zhu, 2009). Both consist of methods to fuse bacterial DNA from the species of interest to some reporter gene to create a library, and then a screen of this library under the desired conditions to detect promoters that drive the reporter under the desired conditions. The hypothetical use of DFI to isolate blood meal induced promoters from a paratransgenic strain of bacteria is described in figure 4. Briefly, a library of size-selected genomic fragments from the paratransgenic species is cloned upstream of a promoterless fluorescent protein gene (typically, some variant of GFP) on a plasmid. This library is transformed into the paratransgenic bacterium and this population of bacteria is fed to mosquitoes in a blood meal. After a suitable amount of time, the midguts of the blood- fed mosquitoes are dissected, homogenized, and the bacterial cells sorted in a fluorescence-activated cell sorter which selects and enriches the population of bacteria that are expressing GFP. The selected fluorescent bacteria are collected and the process repeated however many times the user feels is necessary. Individual clones are then transformed back into the paratransgenic bacterium, and the individual strains re- screened to ensure that no false positives were selected and that the promoter is truly conditional.

5. Genetically stable paratransgenic strains suitable for field release Insertion of effector constructs into the chromosome. For a paratransgenic strain to be stable and to reduce the odds of horizontal transfer of the effectors it will be necessary to insert the promoter-effector construct into the chromosome of the paratransgenic strain. Insertion into the chromosome insures that all progeny will inherit the effector genes and that no selection is necessary to retain them. Chromosomal insertion can be accomplished in a variety of ways.

Perhaps the simplest way to insert genes into the chromosome is by transposition. Transposons mediate DNA breakage and joining of DNA sequences through a transposase protein that is contained within inverted terminal repeat (ITR) sequences that are specific to the given transposon. Insertion of transposon DNA occurs at a transposon- specific target site in the genome. The target site can be at one specific site per genome (e.g., attTn7 for Tn7) or scattered throughout the genome in a way that is essentially

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random (e.g., Tn5 or Himar1). Transposons are almost always used in microbiology in a mini-transposon format where the transposase that mediates the movement of the DNA is separated from the ITRs. Figure 5 shows pSC189, a typical embodiment of this kind of system for the Himar1 transposon (Chiang & Rubin, 2002). The plasmid contains inverted terminal repeats that bound a kanamycin-resistance (kanR) gene to select for transposon insertions. The kanR gene is itself inserted between two FRT sites for the FLP recombinase of yeast (see below). The transposon also carries in it the plasmid origin of replication, in this case oriR6K which is conditional on the presence of the  protein. Without this protein, the plasmid will not replicate so it is only stably maintained as a plasmid in special strains of E. coli that have the  protein transduced into the chromosome. This feature ensures that whatever kanamycin-resistant cells are recovered after movement of the plasmid into the paratransgenesis strain are due to transposition and not plasmid replication. An 8 bp cutting AscI site is present near the end of the transposon for insertion of foreign DNA. Outside the transposon in the backbone of the plasmid is a beta lactamase gene for selection of the entire plasmid, the transposase gene driven by a lac promoter, and an origin of transfer (oriT). OriT enables the conjugation of this plasmid from E. coli strains carrying the conjugation machinery for oriT to essentially any other bacterial cell. This feature is crucial in transferring plasmids to species where chemical or electrotransformation techniques work poorly and that will undoubtedly include many species contemplated for paratransgenesis. While transposition can efficiently create stable insertions of effector genes into paratransgenic strains of bacteria it should be noted that the user has no control over the site of insertion so there may be fitness costs or other unintended effects on the strain and these will need to be measured under conditions that are likely to be encountered in the field.

The second method to introduce effectors into the chromosome is recombination. The most common kind of recombination occurs when a single cross-over event occurs between a plasmid carrying the effector construct and a homologous site on the chromosome. This results in the integration of the entire plasmid into the chromosome and such events are common enough that they are easily produced and isolated.

Ideally, only the effector gene and its promoter and terminator would be recombined into the chromosome. This requires a double-cross over event which is much more rare. Such events can be increased in frequency by orders of magnitude by supplying enzymes that mediate recombination of foreign DNA into the chromosome. The most highly developed of these is the Red recombination system derived from bacteriophage lambda (Datta et al., 2006; Thomason et al., 2007). The use of Red recombination is developed in E. coli to such a degree that no drug marker is necessary to recover chromosomal recombination events (Sawitzke et al., 2007). It is likely that this technique will work in many Gram negative bacteria and the recombination machinery for Red recombination has been placed on broad host range plasmids for just this use (Datta et al., 2006).

Drug marker removal. If drug markers are used to help select recombinants into the paratransgenic strain chromosome, either by transposition or recombination, they must be removed before the strain can be released into the field. This is straightforward if the insertion was constructed properly beforehand. For example, the kanR gene carried by

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the Himar1 transposon on pSC189 in figure 5 is flanked by two FRT sites. These sites are the recognition sites for the FLP recombinase from yeast. When these sequences are in the same orientation around a central DNA sequence, recombination by FLP recombinase at the FRT sites results in the excision of the DNA between them leaving behind a single FRT site. Many plasmids carrying FLP recombinase exist that can be transformed into strains carrying drug markers constructed this way. Selection of cells that are kanamycin sensitive is a simple matter of patching cells onto media with and without the selective agent. Once sensitive cells are recovered, the FLP plasmid can be eliminated by counter selection. An excellent review of the use of this technique in bacteria can be found in Schweizer (2003).

Standardization of parts. As noted earlier, genetically engineering bacterial strains for paratransgenesis can be considered as a type of synthetic biology. The synthetic biology community in beginning an effort to standardize the parts of synthetic constructs so that different modules can be interchanged easily. One effort in this regard is the BioBricks Foundation (Smolke, 2009). Another is the recently-published Standard European Vector Architecture (SEVA) (Silva-Rocha et al., 2013). Each effort seeks to create a vector platform that is standardized and easy to use. SEVA, in particular, stresses broad host range platforms that are most suitable to testing and creating paratransgenic bacterial strains from non-model system bacteria. Origins of replication, drug markers, origins of transfer, promoters, and “cargo” are all modular and easily replaced or changed. We strongly urge workers in the area of paratransgenesis to adopt the SEVA standards which should make paratransgenesis more straightforward and easier to adopt as this method spreads to different species and systems.

6. Introducing and spreading bacterial strains for paratransgenesis. A critical step in the success of a paratransgenesis program is the introduction and spread of paratransgenic microorganisms within a vector population in nature. Bacterial species that form an obligate association with vectors are ideal in this context since, once obtained by the vector, they will spread naturally via the biology of the vector itself. As noted above, our current knowledge of mosquito microbiota suggests that such obligate associations do not exist, although some species are quite common. Many common species of bacteria that live in adult mosquitoes, like Pantoea sp. and Asaia sp., are also found in floral nectar, suggesting that mosquitoes acquire these members of the microbiota from sugar meals.

The use of bacterial strains that do not have inherent drive mechanisms (like Wolbachia, e.g.) or that do not form obligate associations with their vectors will require a careful choice of bacterial species and clever uses of vector behavior. Asaia (reviewed in Chapter XXX) is a genus that has very attractive microbial ecology. These species infect mosquito midguts, salivary glands, and ovaries, multiply with the blood meal, are spread from males to females during copulation, and are deposited on eggs by the female (Favia et al., 2007; Damiani et al., 2008; Crotti et al., 2009). These properties suggest that paratransgenic Asaia strains might be easily spread in the field.

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Spreading bacteria to mosquitoes in the field will also require taking advantage of mosquito behavior. One suggestion has been to take advantage of the fact that the females of many mosquito species require sugar meals in addition to blood while males exclusively sugar feed. It may be possible to spread paratransgenic strains by sugar meals supplemented with strong attractants (Muller et al., 2010; Beier et al., 2012). No such field demonstration of the spread of paratransgenic strains exists, however, and this remains an area where much work is needed.

Paratransgenesis of mosquitoes against malaria with genetically modified bacteria. Using the strategies outlined above, we successfully demonstrated paratransgenesis against malaria in the laboratory using transgenic strains of Pantoea agglomerans (Wang et al., 2012). This species was isolated from a laboratory colony of Anopheles stephensi and was later selected to persist in the midgut of these flies for up to 14 days (Riehle et al., 2007). P. agglomerans is a gammaproteobacterium in the Enterobacteriaceae, the same family to which E. coli belongs. Strains expressing various anti-malarial peptides and proteins were able to reduce the prevalence of females carrying any oocysts from 90?% to 18% after an infectious blood meal (Wang et al., 2012). A reduction in prevalence was measured in both An. gambiae carrying P. falciparum and in An. stephensi carrying P. berghei, suggesting that these strains may work in any Anopheles vector species against multiple different species of Plasmodium. This is an important consideration and a distinct advantage of paratransgenesis against malaria since there are five species of Plasmodium that cause malaria in humans vectored efficiently by at least 40 species of Anopheles (Sinka et al., 2012).

Paratransgenesis with naturally-occurring bacterial strains. So far we have described strategies to genetically engineer bacteria with favorable microbial ecology into paratransgenesis strains. Interestingly, some bacterial strains are naturally paratransgenic. For example, Cirimotich et al. (2011) isolated 16 culturable bacterial species from the midguts of Anopheles gambiae collected in Zambia. One of these strains belonged to the genus Enterobacter as determined by 16S sequencing. This strain, Esp_Z, was capable of completely inhibiting P. falciparum development in the midgut of An. gambiae. Additional experiments showed that the factor responsible for the inhibition was diffusible, heat insensitive, and was most likely some kind of reactive oxygen species since the effect could be eliminated through the presence of the antioxidant Vitamin C. One hypothesis to account for the presence of this strain in An. gambiae is that it was selected for because it offers some kind of advantage to the mosquitoes that carry it by reducing the load of P. falciparum in the mosquitoes. If this hypothesis were correct, we might expect to see Esp_Z widespread in African An. gambiae, but it is not. An alternative hypothesis is that the anti-Plasmodium properties of Esp_Z are fortuitous and were selected for some other reason, most likely competition with other bacteria. If this hypothesis is correct, many other naturally-occurring bacterial strains will prove to be anti-plasmodial. Strains like these have the advantage of not having been genetically engineered, however they may lack the appropriate microbial ecology and their discovery requires the mass screening of culturable bacteria from wild mosquitoes.

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Conclusion Reducing the ability of insects to vector disease through paratransgenesis offers a promising route to decrease the burden of many of the most important human diseases, like malaria and Dengue fever. Although the creation of paratransgenic strains requires many facets, the genetic tools are available to modify nearly any bacterial species. These include broad host range plasmids, constitutive promoters, broad host range transposons, an abundance of effectors, and simple genetic screens to isolate secretion signals and conditional promoters. Many challenges remain, especially gaining an improved understanding of insect microbial ecology and methods to deliver and spread paratransgenic species in nature. The use of metagenomics in different mosquito species will begin to clarify the nature of the mosquito microbiome and suggest bacterial species for which specialized culture techniques can be developed so that these species can be developed as paratransgenesis platforms. An increasing understanding of the microbial ecology of mosquitoes will also suggest ways to deliver paratransgenic bacterial species in the field to ensure their spread throughout a vector population. Finally, a systems biology approach to paratransgenesis and a standardization of vector construction will aid in the rapid development of paratransgenic strains for many mosquito species, as well as other important insect vectors.

Acknowledgements. We would like to acknowledge the assistance of Amanda Harmon in compiling the literature on mosquito microbial ecology and thank Jackie Shane for critically reading the manuscript. We regret any work we may have overlooked.

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Figure A.1. Derivatives of antibodies useful in paratransgenesis. Variable heavy and light chains of monoclonal antibodies are constructed into a single gene (scFvs, antimicrobial peptide fusion, and nanobody) or two genes that are coexpressed (diabody) that can reconstitute the binding properties of an immunoglobulin. For details on each of these see the text or Kontermann (2010).

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Figure A.2. Secretion of effector proteins by bacteria using one of two different pathways. The hemolysin autotransporter system is shown in part A. The type II general secretory pathway is shown in part B. Both are highly simplified. Effector proteins destined for secretion carry either a ca. 50-amino acid C-terminal signal sequence for the HlyA pathway or a short N-terminal signal sequence for the Type II secretion pathway. The signals differ in Type II depending on whether or not they will cross the inner membrane via either the twin-arginine pathway (Tat) or the general secretory pathway (Sec). The hemolysin system consists of HlyB, HlyD, and a native TolC protein that assemble to create a pore that spans the inner and outer membranes. Proteins using this pathway are secreted directly into the extracellular space in one energy dependent step. Effectors targeted to the Type II secretion system cross the inner membrane and spend time in the periplasm where the signal sequence is cleaved and they may undergo disulfide bond formation. These proteins cross the outer membrane in many ways which are not completely understood. For a fuller discussion see Korotkov et al. (2012).

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Figure A.3. A genetic screen to identify native secreted protein genes in bacteria using TnphoA. The transposon Tn5 was modified to carry a kanamycin resistance gene and E. coli phoA without the leader sequence that normally targets it for secretion. TnphoA is introduced into the bacterial species in question where it randomly inserts into the bacterial chromosome. A library of random insertions is then plated on medium containing kanamycin (to select for transposition events) and BCIP, which turns blue if TnphoA is fused to a bacterial gene that encodes a secreted protein. For more details, see Manoil & Beckwith (1985).

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Figure A.4. A differential fluorescence genetic screen in bacteria to identify conditional promoters activated in a blood meal. A library of random chromosomal fragments from the bacterial species of interest is cloned upstream of a promoterless GFP gene in a broad host range plasmid. This bacterial promoter trap library is then fed to adult female mosquitoes, which are then subsequently given a blood meal. Promoters active in the blood meal can be separated from inactive ones by fluorescence activated cell sorting.

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Figure A.5. pSC189, a broad host range transposon insertion vector based on Himar1 pSC189 is used to make random insertions into the chromosome of many bacterial species. See text and Chiang & Rubin (2002) for details. ApR = ampicillin resistance; KmR = kanamycin resistance; oriT = origin of transfer; Himar1 transposase=transposase gene; FRT=recombination sites of yeast FLP recombinase; AscI=insertion site for exogenous DNA; oriR6K=a conditional origin of replication; solid triangles indicated the transposon inverted terminal repeat sequences.

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