The Pennsylvania State University

The Graduate School

Department of Entomology

A to ZYMV GUIDE TO ERWINIA TRACHEIPHILA INFECTION: AN ECOLOGICAL

AND MOLECULAR STUDY

A Dissertation in

Entomology

by

Lori Shapiro

2012 Lori Shapiro

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

December 2012

The thesis of Lori Shapiro was reviewed and approved* by the following:

Mark Mescher

Assistant Professor of Entomology

Thesis Advisor

Chair of Committee

Consuelo De Moraes

Professor of Entomology

Andy Stephenson

Distinguished Professor of Biology and Associate Dean of Graduate Studies

Shelby Fleischer

Professor of Entomology

Eric Harvill

Professor of Microbiology and Infectious Disease

Gary Felton

Head of the Department of Department or Graduate Program

*Signatures are on file in the Graduate School

iii

ABSTRACT

Many of the most ecologically and economically important diseases of plants are

transmitted by insects, and the spread of these diseases ultimately depends on complex

interactions among plants, pathogens, and insect vectors. Yet, empirical evidence regarding the

mechanisms by which plant pathogens are transmitted by insects is sparse. In this dissertation, I

take a systems biology approach to understanding ecological and molecular interactions driving

the emergence of the bacterial phytopathogen Erwinia tracheiphila, a microbe with exceptional

economic importance and a highly restricted host range. Induced changes in the emission of plant

volatiles—airborne chemicals released by plants that serve as key foraging cues for insects but

are not well characterized in response to pathogen infection. In the field and greenhouse, I found

that E. tracheiphila induced a unique volatile blend from foliage, and caused a reduction in the

emission of floral volatiles. The co-occurring viral pathogen Zucchini Yellow Mosaic Virus

suppressed both leaf and floral volatiles. Behavioral assays found these volatile differences had

effects on vector attraction and were important for beetle recruitment to E. tracheiphila infected

plants and dispersal to healthy ones, and that few beetles were recruited to virus infected plants.

Controlled inoculations show that healthy and ZYMV infected plants are equally susceptible to E.

tracheiphila infection, and so vector behavior is largely driving lack of coinfection of the two

pathogens in the same host plant that is often documented in the field. Next, I developed a qPCR

method to clarify uncertainty in rates of E. tracheiphila colonization of beetle vectors exposed by

feeding on wilting leaf tissue. I found that E. tracheiphila does not colonize beetles very

efficiently: While at least 80% of beetles are exposed to E. tracheiphila at both short (3 hr) and

long (24 hr) exposures, the longer exposure results in significantly higher long-term retention

rates. Quantitative changes in bacterial titre in frass and whole beetles also show that transmission

is not simply mechanical, and that E. tracheiphila exhibits complex colonization dynamics of the

iv

beetle’s digestive tract characterized by attachment, growth, and shedding phases. Finally, I

analyze the genome of E. tracheiphila and find it has undergone extensive recombination and

pseudogenization compared to the closest sequenced relative, and contains many putatively

horizontally transferred genes. Phylogenetic and comparative data suggest E. tracheiphila is

undergoing rapid evolution and may have recently experienced a host jump to squash. Taken

together, these studies provide an ecological mechanism for transmission from infected to healthy

plants; a quantitative description of how beetles are colonized and consequences for transmission;

and a genome analysis hypothesizing factors influencing E. tracheiphila emergence as a squash

pathogen and persistently transmitted insect symbiont.

v

TABLE OF CONTENTS

List of Figures .......................................................................................................................... vii

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

Acknowledgements .................................................................................................................. xi

Chapter 1 Introduction ............................................................................................................. 1

An Historical Perspective of Cucurbit Research .............................................................. 1 References ........................................................................................................................ 12

Chapter 2 Pathogen effects on vegetative and floral odors mediated vector attraction and

host exposure in a complex pathosystem ......................................................................... 18

Abstract ............................................................................................................................ 18 Introduction ...................................................................................................................... 19 Materials and Methods ..................................................................................................... 22 Results .............................................................................................................................. 28 Discussion ........................................................................................................................ 35 References ........................................................................................................................ 42

Chapter 3 Direct interactions between a viral pathogen, a bacterial pathogen, and a

specialist herbivore in a shared host plant ........................................................................ 45

Abstract ............................................................................................................................ 45 Introduction ...................................................................................................................... 46 Methods ............................................................................................................................ 48 Results .............................................................................................................................. 52 Discussion ........................................................................................................................ 61 References ........................................................................................................................ 64

Chapter 4 Colonization dynamics of an insect vector by a bacterial phytopathogen .............. 67

Abstract ............................................................................................................................ 67 Introduction ...................................................................................................................... 68 Materials and Methods ..................................................................................................... 69 Results .............................................................................................................................. 73 Discussion ........................................................................................................................ 81 References ........................................................................................................................ 87

Chapter 5 Comparative genomic insights into emergence and host associations of the

bacterial wilt pathogen Erwinia tracheiphila ................................................................... 92

Abstract ............................................................................................................................ 92 Introduction ...................................................................................................................... 93

vi

Results/Discussion ........................................................................................................... 95 Conclusions ...................................................................................................................... 130 Methods ............................................................................................................................ 132 References ........................................................................................................................ 145

Chapter 6 Conclusions ............................................................................................................. 152

References ........................................................................................................................ 157

vii

LIST OF FIGURES

Figure 2-1. Field foliar volatiles ............................................................................................. 29

Figure 2-2. PCA of field foliar volatiles. ................................................................................ 30

Figure 2-3. Geenhouse foliar volatiles .................................................................................... 31

Figure 2-4. Field floral volatiles. ............................................................................................ 32

Figure 2-5. Greenhouse floral volatiles ................................................................................... 32

Figure 2-6. Beetle attraction in the field ................................................................................. 33

Figure 2-7. Greenhouse behavioral assays .............................................................................. 34

Figure 2-8. Dual-choice feeding preference test of healthy vs. pathogen-infected plants. ..... 35

Figure 3-1. Induced hormone responses of healthy and ZYMV-infected wild gourd to

inoculation with E. tracheiphila ....................................................................................... 53

Figure 3-2. Inoculation success rates with E. tracheiphila on mock-infected (healthy) and

ZYMV-infected plants after exposure to infective frass .................................................. 55

Figure 3-3. Inoculation success rates for E. tracheiphila infection on mock-infected

(healthy) and ZYMV-infected plants with frass and in vitro E. tracheiphila added ........ 56

Figure 3-4. Timing of E. tracheiphila colonization of C. pepo texana measured by time

the second leaf showed wilting symptoms ....................................................................... 57

Figure 3-4. Visual comparison of E. tracheiphila symptom development on a healthy

(left) and a ZYMV-infected (right) wild gourd plants ..................................................... 57

Figure 3-5. Herbivory effects on cis-JA levels for healthy, ZYMV, and E. tracheiphila

infected plants .................................................................................................................. 60

Figure 4-1. Frass acquisition and retention rates .................................................................... 74

Figure 4-2. Whole beetle acquisition and retention rates ........................................................ 76

Figure 4-3. Quantitative dynamics of frass in whole beetles vs. frass .................................... 78

Figure 4-4. Distribution of E. tracheiphila in frass over time ................................................. 79

Figure 4-5. Distribution of E. tracheiphila in whole beetles .................................................. 79

Figure 4-6. Inoculation success rates with frass collected 0, 5, and 28 days after AAP ......... 81

viii

Figure 5-1 Phylogenetic relationships inferred from the concatenated ribosomal

sequences of the sequenced Erwinia ssp. and other important enterobacterial plant

and animal pathogens ....................................................................................................... 97

Figure 5-2 VENN diagram generated using EDGAR to compare the number of shared

and unique genes between E. tracheiphila, E. amylovora, and E. billingiae. .................. 100

Figure 5-3. Distribution of pseudogenes on the E. tracheiphila chromosome........................ 103

Figure 5-4. Comparisons of genome decay across orthologous groups between E.

amylovora, E. billingiae, and E. tracheiphila .................................................................. 104

Figure 5-5. Chromosomal rearrangements between E. tracheiphila, E. amylovora, and E.

billingiae .......................................................................................................................... 110

Figure 5-6. Comparisons of gene content and amino acid identity of the hrp Type III

Secretion Systems in E. amylovora and E. tracheiphila .................................................. 114

Figure 5-7. Schematic of a locus with two genes encoding proteins that manipulate plant

cell walls that shows support for horizontal acquisition by E. tracheiphila .................... 117

Figure 5-8. Two pectin degradation genes present in E. tracheiphila that were likely

acquired horizontally ........................................................................................................ 119

Figure 5-9. Comparisons p450 loci in E. tracheiphila and Mesorhizobium loti ..................... 122

Figure 5-10. Schematic of E. tracheiphila chitin associated locus and phylogenetic

support for horizontal acquisition .................................................................................... 124

Figure 5-11. Comparisons capsular exopolysaccharide operon in E. tracheiphila, E.

billingiae, and E. amylovora ............................................................................................ 130

ix

LIST OF TABLES

Table 2-1. Foliar volatiles from healthy, non-symptomatic, wilting, and ZYMV-infected

branches under field conditions. ...................................................................................... 39

Table 2-2. Foliar volatiles from (mock) healthy vs. E. tracheiphila-infected plants under

greenhouse conditions ...................................................................................................... 40

Table 2-3. Greenhouse ZYMV vs. mock (healthy) foliar volatiles ......................................... 40

Table 2-4. Floral volatiles from healthy and Erwinia tracheiphila-infected plants under

field conditions ................................................................................................................. 40

Table 2-5. Floral volatiles from healthy and ZYMV-infected plants under field

conditions ......................................................................................................................... 41

Table 2-6. Floral volatiles from E. tracheiphila and healthy plants under greenhouse

conditions ......................................................................................................................... 41

Table 2-7. Floral volatiles from ZYMV-infected and healthy plants under greenhouse

conditions ......................................................................................................................... 42

Table 3-3. ANOVA of Disease, Herbivory, and Disease*Herbivory effects on cisJA

production in wild gourd leaves ....................................................................................... 60

Table 3-4. Mean +- SE cisJA present in healthy and pathogen infected leaves that are

undamaged and damaged by cucumber beetles ............................................................... 60

Table 3-5. ANOVA for salicylic acid in pathogen-infected and healthy plants...................... 61

Table 5-1. General characteristics in the genomes of E. tracheiphila, E. billingiae, and E.

amylovora......................................................................................................................... 99

Table 5-2. Average nucleotide identities (ANI) of all ORFs and pseudogenes ...................... 101

Table 5-3. Average nucleotide identities between sequenced Erwinia spp. ........................... 101

Table 5-4. E. tracheiphila scaffold sizes and important features ............................................ 105

Table 5-5. Distribution of phage genes present in E. tracheiphila among phages with at

least 10 genes ................................................................................................................... 107

Table 5-6. Abundances and rates of decay of IS elements in the E. tracheiphila genome ..... 108

Table 5-7. Comparison of gene presence and AA similarity of different functional genes

in the hrp/hrc regulon ...................................................................................................... 115

Table 5-8. Singleton hrp/hrc T3SS effectors that are potential HGT candidates from

Pseudomonas spp. ............................................................................................................ 115

x

Table 5-9. E. tracheiphila sequencing and assembly statistics ............................................... 134

Table 5-11. Supplemental table of Darkhorse Output of HGT candidates with COG

functional assignments ..................................................................................................... 137

xi

ACKNOWLEDGEMENTS

Many people have contributed to the development and execution of this project. I

especially thank my co-advisors, Consuelo De Moraes and Mark Mescher for their knowledge,

encouragement, and patience. I have benefitted greatly from the respective expertise of all of my

committee members. Andy Stephenson for his encyclopedic knowledge of squash gained from 20

years of hand pollinations; Shelby Fleischer for arranging very rewarding speaking opportunities

for me at meetings of local squash growers and teaching me about the applied aspects of this

work; and Eric Harvill, for helping to expand this project by applying next generation sequencing

and analysis. I have also greatly benefitted from the input of my coauthors: Irmgard Seidl-Adams,

Erin Scully, Jihye Park, Lucie Salvaudon, Kerry Mauck, Scott Geib, and Olga Zhaxybayeva. I

would like to thank the Entomology office staff, LuAnn Weatherholtz, Ellen Johnson, Karen

Dreibelbis, and Dave Love whose work allows the program to run so smoothly. Nick Sloff

provided beautiful images and graphics as a media specialist that have greatly improved the

aesthetics of this work, and he learned a lot about beetle frass in the process.

I am indepted to all of my coworkers, for their advice, conversation, and their patience

and understanding when I had the computer or GD-FID tied up for weeks at a time, and for

stepping into help me with whatever I asked when I wasn’t able to do much on my own: Janet

Saunders, Erica Smyers, Heike Betz, Kerry Mauck, Rupesh Kariyot, Hannier Pulido, Jason

Smith, Beth Irwin Johnson, Lucie Salvaudon, Ryoko Ichiki, Jun T., Fernanda Penaflor, Nina S.,

Tom Bentley, as well as all of the other visitors who have passed through the lab. I thank my

family, and all of my friends, for enriching my time here with fun adventures and delicious meals,

and epic rides through the Pennsylvania hills.

1

Chapter 1

Introduction

An Historical Perspective of Cucurbit Research

In response to herbivory pressure, plants have developed a chemical arsenal of

metabolically costly traits that deter damages and losses from herbivory. Induced chemical traits,

which are not known to have any primary metabolic function, are referred to as secondary

metabolic compounds, and encompass a diverse array of chemical structures that have shaped

animal evolutionary history (Fraenkel 1959; Ehrlich & Raven 1964). In response, many insect

herbivores evolved the ability to detoxify, sequester, or otherwise tolerate secondary metabolites

from plants. Because of the cost to the insect from interacting with plant secondary metabolites,

many herbivores specialize on one or a few closely related host plant species (Becerra 1997).

One plant-insect system of ecological, agricultural, and cultural interest comprises

Cucurbitaceae plants and coevolved Luperini leaf beetles (Coleoptera: Chrysomelidae:

Galerucinae). While Cucurbitaceae has a cosmopolitan distribution (Schaefer 2009), Cucurbita is

native to Mesoamerica and has important historical and cultural significance. The wild gourd

Cucurbita pepo ssp. texana is the wild progenitor of cultivated squashes, pumpkins, and gourds,

and has its center of evolutionary origin and diversity in Mesoamerica (Whitaker & Bemis 1976;

Whitaker & R.J. Knight 1980), with a range that extends northward through the American

Southwest and the Mississippi River Valley. The wild gourd C. pepo ssp. texana has undergone

an estimated six confirmed domestication events, with the oldest being in the Oaxaca Valley,

2

Mexico apprx. 10,000-8,000 years ago (Smith 1997; Sanjur 2002). Domesticated Cucurbita pepo

varieties retain important cultural and agricultural uses throughout their native range.

Cucurbita Defensive Chemistry

The production of a group of oxygenated tetracyclic triterpenes with variable side chains,

called cucurbitacins (cucs), is diagnostic of many wild Cucurbitaceae species (S. Rehm 1957;

Rehm 2006), although there is isolated documentation of cucurbitacin production in several other

plant families (Curtis & Meade 1971; Pohlmann 1975; Dryer & Trousdale 1978). Cucurbitacins

are highly toxic to both mammalian and insect herbivores: Cucs can comprise up to 1% fresh

weight of fruits but are detectable by humans concentration as low as 1ppb (Enslin 1954; David

& Vallance 1955), and cucs have caused poisoning when ingested by foraging cattle (Watts &

Breyer-Brandwiyk 1962). In C. pepo ssp. texana, the predominant form of cucurbitacin is cuc-E-

glycoside (Metcalf 1982). Because of their intense bitterness and cytotoxicity, cucs are selected

against in crop breeding, although the complexity of the genes involved in cucurbitacin

biosynthesis has resulted in occasional production of bitter fruits from non-bitter parents (Rehm

& Wessels 1958).

While cucurbitacins deter almost all mammalian and insect herbivores (Tallamy et al.

1997), they act as potent arrestants and feeding stimulants for Old and New World Luperini leaf

beetles that can detoxify and sequester cucurbitacins (Chambliss 1966; Metcalf et al. 1980;

Ferguson & Metcalf 1985; Tallamy 2000; Gillespie et al. 2004). Cucurbitacin feeding is common

in geographically distant Luperini (Nishida et al. 1992; Lewis & Metcalf 1996) and phylogenetic

analysis show that an affinity for Cucurbitacins among luperine chrysomelids is not ancestral

(Gillespie et al. 2003). Acalymma and Diabrotica spp. beetles can sequester a small proportion of

ingested cucurbitacins (Ferguson et al. 1985), which can then function as protection against

predators (Ferguson & Metcalf 1985) and to decrease the probability that eggs succumb to fungal

pathogens (Tallamy 1998). If fed continuously on bitter, cuc-containing fruit, Diabrotica and

3

Acalymma spp. both experience a decrease in longevity (Ferguson et al. 1985), and a limit in the

amount of bitter leaves consumed has been observed for A. vittatum that have already sequestered

a large amount of cucs (Smyth 2002). In addition to being chemically defended by cucurbitacins

that are highly effective against non-coevolved herbivores, cucurbits produce sticky phloem sap

that can interfere with specialist herbivore feeding and even cause beetle death if mouthparts

become too gummed (Cronshaw et al. 1973; Cronshaw 1975; McCloud et al. 1995; Eben 2007).

Insect Attraction to Cucurbita

Most plants release low molecular weight volatile organic compounds as part of their

normal metabolic processes. These volatile cues can convey important information about host

plant identity, status, and nutritional content to mammalian and insect herbivores, including

humans (Goff & Klee 2006). The Cucurbita floral volatile blend has been a subject of intensive

study for many decades as host location cues for coevolved beetles (Metcalf et al. 1980) and the

basis for an attractant bait to control diabroticite pests in many agricultural systems (Lampman &

Metcalf 1987, 1988). While most work has concentrated on volatile attraction of Diabrotica spp.

to Cucurbita floral volatiles for the purpose of pest control in maize plantings (Metcalf &

Lampman 1991), isolated studies have also found Acalymma vittatum to be strongly attracted to

volatiles of cucurbit flowers and seedlings (Lewis et al. 1990).

Cucurbita spp. are pollinated by solitary Peponapis and Xenoglossa spp. (Hymenoptera:

Anthophoridae) (Hurd 1971). However, this is an evolutionarily ‘recent’ interaction, and

diabroticites are hypothesized to be the ancestral pollinators of Cucurbita. The fossil record dates

the establishment of holometabolous development and the proliferation of Coleoptera,

Neuroptera, Diptera, and Mecoptera to the Permian period (299-250 MYA) (Martynova 1961),

while hymenoptera are not confirmed in the fossil record until the Tertiary period (65-2.6 MYA).

Cucurbita floral traits, including large, yellow, open bowl shaped flowers are congruent with

originally being beetle pollinated (Baker & Hurd 1968; Kevan & Baker 1983). While cucumber

4

beetles are highly destructive foliar cucurbit pests (Balduf 1925; Ferguson et al. 1983), Acalymma

and Diabrotica mandibles and mola are structurally suggestive for florivory and to prepare pollen

for digestion (Cabrera & Durante 2001; Cabrera & Durante 2003), and florivory is believed to be

the ancestral state of all chrysomelids (Crowson 1960). Cucurbit pollen is found in the gut of

Diabrotica and Acalymma and thought to compose an important part of their diet (Samuelson

1994). A. vittatum are also often found foraging on the flowers of rosaceous and composite plants

(Balduf 1925; Houser 1925) although larval development is restricted to cucurbits.

Diversity of Cucurbita herbivores

Approximately 900 species of diabroticites have been described, with 338 valid

Diabrotica species (Wilcox 1972) and 72 Acalymma species (Cabrera & Durante 2001)(Munroe

& Smith 1980). It is estimated at least that many diabroticites remain undescribed (Smith 1966),

mostly in the neotropics (Krysan & Smith 1987). Diabrotica has been informally divided (Eben

et al. 2004) into the signifera, fucata (305 species), and virgifera (21 species) species groups with

the pest species confined to the multivoltine fucata and univoltine virgifera groups (Clark 2001).

While fucata species are somewhat polyphgous and can threaten the production of many crops

(Barbercheck 1993), virgifiera species threaten maize cultivation. Acalymma spp. are specialists

on cucurbits in both larval and adult stages (Eben 1997b, a).

Diabroticites as agricultural pests and disease vectors

While the vast majority of Diabroticite species only occur in low population densities in

wild habitats, several species have become some of the world’s most destructive agricultural pests

(Branson & Krysan 1981). The most economically damaging among them is Diabrotica virgifera

virgifera, a recently diverged subspecies of Diabrotica virgifera zea that has emerged as a

specialized pest of cultivated corn varieties, and has undergone recent range expansion as corn

cultivation has expanded through the American Midwest over the past several decades (Krysan et

al. 1980; Branson et al. 1982). Because diabroticite pests are part of a coevolved, native system

5

and herbivores and pollinators utilize the same host location cues, insecticide-laced volatile baits

developed to control diabroticite beetles also attract and kill pollinators, demonstrating the

continuing need for more information on ecological interactions to develop sustainable pest and

pathogen control strategies (Metcalf et al. 1987).

Several pests and diseases of cucurbits that threaten agricultural production, and possibly

undomesticated populations, have emerged in the last several decades. The selection for

agricultural traits over functional ecological ones, relative genetic homogeneity of agricultural

crops, and landscape changes associated with modern monoculture agricultural methods, is likely

associated with the emergence and dispersal of new pests and pathogens (Bach 1979; Hopkins &

Purcell 2002; Stukenbrock & McDonald 2008; Pagán et al. 2012). Erwinia tracheiphila

(Enterobacteriaceae) (Smith) is an emerging pathogen of wild and domesticated cucurbits. The

first published description of E. tracheiphila was at the PSU experimental station (Fulton et al.

1911), but cucumber beetles were not implicated in bacterial spread until later work (Smith 1911,

1914, 1915; Rand & Enlows 1916, 1920; Rand 1920). The first demonstration that striped and

spotted beetles

Most plant pathogenic bacteria are dispersed by rain, dew, or passive association with

insects, but E. tracheiphila is one of the few known plant pathogenic bacteria that is obligately

transmitted by an insect vector. E. tracheiphila has a highly restricted range on some cucurbit

host plants. Susceptibility to infection varies, with Cucumis spp. (melons and cucumbers) being

the most susceptible, Cucurbita spp. (squashes, pumpkins, and gourds) susceptible but showing

some resistance, and watermelon (Citrullus spp.) thought to be completely resistance to E.

tracheiphila infection.

E. tracheiphila is only confirmed to be transmitted by two species of diabroticite leaf

beetles, the spotted cucumber beetle Diabrotica undecimpunctata howardii and the striped

cucumber beetle Acalymma vittatum (Rand & Cash 1920). The geographical range of and

6

economic losses from E. tracheiphila have historically been restricted to the northeast and

midwest, but the first case of E. tracheiphila infection was recently recorded in the Southwest

(Sanogo et al. 2011), suggesting that E. tracheiphila could be expanding its range towards the

evolutionary origin of Cucurbita in Mesoamerica where there are scores more possible

diabroticite species that could function as competent disease vectors.

Because E. tracheiphila is obligately transmitted by insects and not through movement of

infected plant material (which was responsible for the dispersal of the closely related fire blight

pathogen E. amylovora from New York State to threated pome fruit production worldwide), it is

likely that factors related to vector competence or insect population levels affect geographical

distribution of E. tracheiphila. Northeastern agricultural fields are largely dominated by a single

species, the striped cucumber beetle A. vittatum. Striped cucumber beetles diapause as adults in

Northeastern climates, and emerge in the spring and thus are a threat to cucurbit production from

spring, when adults converge on fields of seedlings, until the end of the growing season. In

contrast, the spotted cucumber beetles (D. undecimpunctata) do not overwinter well in the

Northeast, and do not achieve large population levels until midsummer after they have migrated

from warmer Southern areas. Vector competence of D. undecimpunctata compared to A. vittatum

is not currently known, and the contribution of spotted cucumber beetles, which are more

polyphagous and arrive later in the season, toward maintaining E. tracheiphila epidemics in the

Northeast is uninvestigated. The current distribution of E. tracheiphila mostly conforms to the

current distribution of the vector A. vittatum, suggesting A. vittatum are likely the dominant

species driving E. tracheiphila disease dynamics in the Northeast.

Because E. tracheiphila currently occurs in the Midwest and Northeast where A. vittatum

is the single dominant species, the potential for other diabroticites to transmit E. tracheiphila is

largely unaddressed. All beetles from the virgifera group, which are univoltine and polyphagous

as adults (including the pest species Diabrotica virgifera virgifera, Diabrotica barberi,

7

Diabrotica longicornis), and therefore do not emerge as adults until late in the growing season

and feed on a wider variety of host plants are unlikely to be competent vectors or ecologically

important in driving disease dynamics (which can be confirmed with simple transmission tests).

Additionally, since virgifera species overwinter as eggs they cannot act as an overwintering (or

over-dry season reservoir) of E. tracheiphila, and are likely to have a less co-evolved relationship

with the bacterium. D. virgifera virgifera was tested for ability to transmit E. tracheiphila

decades ago, and was found not to be a competent vector. However, multivoltine fucata beetles

(such as the pest species Diabrotica undecimpunctata and Diabrotica balteada), and any species

of Acalymma found in high abundance in agricultural fields, have a higher potential of being

competent disease vectors and possibly important for the broader disease ecology of this system

since they overwinter as adults and could be potential reservoirs. Determining which beetles are

important pests of cucurbits in the southern and western regions, if there are unrecognized losses

from E. tracheiphila, comparing area devoted to cucurbit production in different regions, whether

production is increasing and decreasing, and whether seasonal production corresponds to beetle

phenology, are likely all important components affecting E. tracheiphila distribution and

emergence.

Both the striped and spotted cucumber beetles have geographically isolated Western

subpopulations/species. The western striped cucumber beetle is a named species, A. trivittatum,

while spotted cucumber beetles subpopulations consist of the Southern cucumber beetle (D.

undecimpunctata howardi), the Central American spotted cucumber beetle (D. undecimpunctata

duodecimnotata) and an Arizona subspecies(D. undecimpunctata tenella). The presence of

spotted and striped cucumber beetles in the West that are assumed to be competent vectors, yet

where there is a lack of loss from E. tracheiphila suggests that local landscape or differences in

local population levels may also affect geography of E. tracheiphila disease range. While not a

8

comprehensive analysis, distribution maps provided by Ray F. Smith of some pest species

(Krysan & Miller 1986) suggest Western populations could be lower. Population measures of

diabroticites in different locales are often not well documented, so a more arid, sparse west might

support lower overall populations of beetles than population levels required to sustain E.

tracheiphila epidemics. Additionally, it is possible that among the greater diversity of Western

and Southwestern diabroticite species, few species are competent disease vectors, and the

populations of competent species may be proportionally low compared to total diabroticites. How

the interaction of local climate and environment, agricultural landscapes, diabroticite diversity

and abundance, and vector competence of different species interacts to explain disease dynamics

is an interesting yet univestigated aspect of disease ecology in this system. It is possible that E.

tracheiphila range is expanding, or that it is constantly present in the West and Southwest, but the

losses are low enough that incidence of the disease are not often reported. If the aridity and

climate of the Southwest contribute to low vector populations and disease pressure, then this

region may be acting as a geographic buffer preventing expansion of E. tracheiphila towards wild

Cucurbita populations in Mesoamerica.

Cucurbita viral diseases

Cucurbits are also susceptible to a number of aphid-transmitted viral pathogens (Choi et

al. 2002; Klas et al. 2006). Several viral pathogens are emerging as agricultural threats; among

them is Zucchini Yellow Mosaic Virus (ZYMV: Potyviridae) (Desbiez et al. 2002). While ZYMV

is rarely fatal, infection causes a reduction in plant fitness, leaf mottling, and spotting on fruits

that render them unmarketable. Viral infections are also common in wild Cucurbita populations

(Prendeville et al. 2012). In response to these viral diseases, transgenic cultivated varieties

resistant to CMV, WMV, and ZYMV have been developed and released (Fuchs 1995; Tricoli et

al. 1995), and transgenic squash varieties have been deregulated throughout the range of native

9

Cucurbita in the US and Mexico. Gene flow between wild and cultivated Cucurbita pepo

varieties occurs often, (Spencer 2001), and hybrids are fully fertile (Laughlin et al. 2009), raising

the possibilities of frequent gene flow between domesticated (perhaps transgenic) and wild

varieties. Additionally, while transgenic varieties are highly resistant to viral infections, these

varieties are unavailable for use by organic growers, and environmental concerns about

transgenic gene flow into native populations exist.

Disease interactions in complex pathosystems

How plants respond to simultaneous pressure from herbivores and multiple circulating

diseases in complex pathosystems, and how pathogen induced effects on plant phenotype may

alter those interactions is largely unknown (Sasu et al. 2009b; Sasu et al. 2010b). The

epidemiology of E. tracheiphila interactions in agroecology are largely univestigated and

molecular interactions are completely unknown. E. tracheiphila was recently shown to be capable

of ephiphytic colonization of Cucumis leaves under favorable environmental conditions (Rojas,

Gleason, & Pathology, 2012), but infection has not been shown to be caused by leaf application

(Smith) and inoculation success decreases as time post wounding increases (Brust 1997), and so

the contribution of ephiphytic populations to disease dynamics remains to be resolved. Control

strategies for bacterial wilt traditionally aim to keep vector numbers low (Necibi et al. 1992;

Brust 1999; Ellers-Kirk et al. 2000), although trap cropping shows some effectiveness in this

system (Cavanagh et al. 2009). High rates of parasitism by specialist tachinid (Balduf 1925) and

braconid parasitoids has been documented (Toepfer et al. 2009; Smyth & Hoffmann 2010), but

natural enemies in naturally occurring populations dynamics do not appear to be effective in

controlling cucumber beetle populations in agricultural settings.

Sustainable and biologically based pest and pathogen control strategies are dependent on

a more complete understanding of plant/pathogen/vector ecological and molecular interactions.

To that end: The scope of the current dissertation includes the following

10

Chapter 2 assays changes on wild gourd leaf and floral volatile phenotype as the result

of E. tracheiphila and ZYMV infection. Volatile collections are repeated in both the field and

greenhouse. Results of these experiments show that infection with either pathogen suppresses the

release of floral volatiles. Symptomatic, wilting vines on E. tracheiphila infected plants were

found to emit significantly more volatiles of a blend largely composed of low molecular weight

green leaf volatiles. A series of beetle behavioral assays in the field and greenhouse showed that

beetles prefer the stronger volatile blend emitted by flowers on healthy plants compared to the

other treatments, and also prefer the volatile blend released by wilting leaves on E. tracheiphila –

infected plants compared to the volatiles (or lack of volatiles) released by leaves on healthy, non-

symptomatic leaves on E. tracheiphila – infected plants, or ZYMV – infected plants. Results of

feeding preference assays show that beetles prefer the foliage of both ZYMV and E. tracheiphila

infected foliage relative to leaves on healthy plants. Taken together, these results posit that

preferential vector attraction to both volatiles from healthy flowers and wilting leaves, and non -

attraction to leaves or flowers of ZYMV – infected plants, is largely responsible for the lack of co

– infection repeatedly documented.

Chapter 3 tests whether induced systemic resistance is responsible for the suppression of

bacterial wilt symptom development in field populations of ZYMV infected plants. Levels of the

defense-signaling hormones jasmonic acid and salicylic acid were measured in healthy and

ZYMV – infected plants before and after inoculation with E. tracheiphila. Virus – infected plants

contain significantly higher constitutive and induced levels of salicylic acid compared to healthy

plants, suggesting that induced systemic resistance may be partly responsible for disease

suppression. However, a controlled inoculation trial was performed by collecting frass from

beetles exposed to wilting plants, and results show equivalent rates of symptom development in

both healthy and ZYMV-infected plants at the end of the experimental period. Comparisons if the

results in this chapter with documented cases of induced resistance (specifically in cucumber, but

11

in other model hosts as well) in the literature are discussed, and hypothesis for other factors that

could suppress E. tracheiphila infection in virus infected plants are proposed.

Chapter 4 develops a qPCR methodology to describe colonization dynamics of

cucumber beetles by E. tracheiphila. Previous work in the system has established that the beetles

transmit E. tracheiphila in a persistent manner, that beetles are the only overwintering reservoir,

and that E. tracheiphila may be transmitted when frass from infective beetles contacts floral

nectaries or leaf wounds created by herbivory. However, quantitative and temporal dynamics of

beetle colonization and consequences for transmission were still largely undescribed. In this

study, I found that the relative amount of bacteria in whole beetles and shed in frass immediately

after feeding on symptomatic, wilting plants displays a large amount of variance, likely as a result

of the heterogeneous distribution of E. tracheiphila in the xylem of infected plants. At 5 days post

AAP, there is significantly less bacteria in frass but the amount in the beetle is not significantly

different, and by 28 days post exposure, the relative amount of bacteria in frass is significantly

higher than 5 days and the amount in the beetle is again unchanged. Transmission experiments

with frass collected 5 days after an acquisition access period showed less wilt symptom

development in the group of plants inoculated with frass collected from beetles 0 days or 28 days

after an acquisition access period. Thus, the ability of bacteria that is ‘plant derived’ and

mechanically passes through the beetle does not differ in infection probability compared to

bacteria that are ‘beetle derived’, and shed directly from colonies on the insect’s digestive tract. A

series of fitness experiments show that this symbiosis appears to be neutral for the beetle: It

appears to be neither substantially harmed nor helped by being colonized by E. tracheiphila. A

better understanding of colonization dynamics will identify possible points in the transmission

cycle for optimal interventions.

Chapter 5 utilized computational methods and a comparative genomics approach to

understand the interactions of Erwinia tracheiphila with host plants and insect vectors, and the

12

relationship of E. tracheiphila to other sequenced Erwinia spp. and closely related enterobacterial

plant pathogens (that were recently reclassified to new genera from Erwinia). Overwhelming

evidence supports the closest sequenced relative as the non-pathogenic floral commensal E.

billingiae, and not the devastating fire blight pathogen E. amylovora. The presence of many

putative horizontally transferred genes, DNA integrated phage genes and what appear to be active

infection by two phages replicating in culture, and the proliferation of insertion elements have led

to large chromosomal rearrangements and likely are contributing to the emergence of E.

tracheiphila in an ecological niche dramatically different than other characterized Erwinia spp.

The genomic data generated as part of this chapter provide a wealth of opportunity to study basic

questions about pathogen evolution and emergence, as well as to design successful control

strategies and guide crop breeding and development.

Chapter 6 synthesizes the importance for the findings for the system of study, the

applicability of the research in this dissertation to applied questions in agriculture, and to the

intersection of plant/insect/microbe interactions. The utility of next generation sequencing

technology to these problems is discussed, specifically as it applies to providing a way to quickly

and cheaply generate data that can be used to advance our understanding of native pathosystems

and nonmodel systems.

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18

Chapter 2

Pathogen effects on vegetative and floral odors mediated vector attraction

and host exposure in a complex pathosystem

Abstract

Pathogens can alter host phenotypes in ways that influence interactions between hosts

and other organisms, including insect disease vectors. Such effects have implications for

pathogen transmission, as well as host exposure to secondary pathogens, but are not well studied

in natural systems, particularly for plant pathogens. Here, we report that the beetle-transmitted

bacterial pathogen Erwinia tracheiphila—which causes a fatal wilt disease—alters the foliar and

floral volatile emissions of its host (wild gourd, Cucurbita pepo ssp. texana) in ways that enhance

both vector recruitment to infected plants and subsequent dispersal to healthy plants. Moreover,

infection by Zucchini yellow mosaic virus (ZYMV), which also occurs at our study sites, reduces

floral volatile emissions in a manner that discourages beetle recruitment and therefore likely

reduces the exposure of virus-infected plants to the lethal bacterial pathogen—a finding

consistent with our previous observation of dramatically reduced wilt disease incidence in

ZYMV-infected plants.

19

Introduction

The transmission of obligately vector-borne pathogens requires that competent vectors

interact with both infected and (subsequently) uninfected hosts in ways that are compatible with

pathogen acquisition and transmission (O'Shea et al. 2002; Vyas et al. 2007). These interactions

take place within complex pathosystems and are shaped by myriad biotic and abiotic factors

(Medel et al. 2004). Our current understanding of these processes and their implications for the

establishment and spread of insect-borne diseases remains limited, despite their relevance for

global health, agricultural production, and ecology of natural systems (Burdon & Thrall 2008).

However, increasing attention has focused on the role of pathogens themselves in manipulating—

or otherwise altering—interactions between hosts and vectors in ways that enhance transmission

(Lefévre et al. 2006). This increased focus on pathogen-induced effects complements a growing

appreciation of the prevalence of manipulative parasites in natural systems and their far-reaching

influences on community structure and ecosystem dynamics (Lefévre et al. 2009)—though,

compared to work in animal systems, relatively little attention has to date been paid to the broader

ecological significance of pathogen effects on plant hosts (Mescher 2012).

Insect-borne pathogens can potentially influence host-vector interactions through direct

effects on vector behavior (Koella 1999; Ngumbi et al. 2007; Mann et al. 2012), but also via

effects on the quality of the primary host as a resource for the vector (Mauck et al. 2010), or on

the production of host-derived cues that mediate vector attraction (Lefévre et al. 2006). Host-

derived olfactory cues are likely targets for manipulation by pathogens, as olfaction is a key

sensory modality for insects and plays a central role in host location by both plant and animal

disease vectors (Eigenbrode et al. 2002; O'Shea et al. 2002; Lacroix et al. 2005; McLeod et al.

2005; Mauck et al. 2010). Moreover, volatile chemistry is relatively labile in comparison to many

other traits impacted by pathogens and is known to be altered by disease in many systems (e.g.,

20

(Kavaliers et al. 2005; Mauck et al. 2010).

In plant systems, recent work on the role of pathogen-induced changes of host odors in

mediating vector attraction to infected hosts (e.g., (Eigenbrode et al. 2002; McLeod et al. 2005;

Mauck et al. 2010) builds on an extensive literature showing that volatiles play a key role in host-

plant location for insect herbivores (Bolter et al. 1997; Halitschke et al. 2008) and that induced

volatile emissions following insect damage are crucial host location cues utilized by parasitoids

and predaceous insects (De Moraes et al. 1998). Several recent studies have reported vector

attraction to the elevated and/or altered volatile emissions of plants infected by plant pathogens

(e.g., (Eigenbrode et al. 2002; Jiménez-Martínez et al. 2004; McLeod et al. 2005; Jiménez-

Martínez et al. 2009; Mauck et al. 2010). Many of these studies have posited positive effects of

vector attraction to infected hosts on pathogen acquisition and transmission, although the

epidemiological implications of such attraction are likely to be influenced by the frequency of

infection within populations, vector abundance, the mechanism of pathogen transmission by

vectors, and the details of the trophic (or other) interactions between hosts and vectors (e.g.,

(McElhany et al. 1995; Sisterson 2008; Mauck et al. 2012).

Currently, we have detailed information about the effects of plant pathogens on host-vector

interactions in only a few—primarily agricultural—systems, and know relatively little how such

effects function within the broader context of complex ecological communities. Some fungal

plant pathogens elicit dramatic alterations of host phenotypes (e.g., the production of pseudo-

flowers that attract insect pollinators) that constitute obvious examples of host manipulation (Roy

& Raguso 1997), but the effects of most pathogens on their hosts are more subtle. Initial efforts to

characterize broader patterns in the effects of viral pathogens on host-vector interactions

(including those mediated by host-plant odors) suggest that variation in transmission mechanism

may be an important factor shaping the evolution of virus effects on host phenotypes (Mauck et

al. 2012)—though the certainty of this conclusion is constrained by the limited representation of

21

many virus groups in the existing literature, a near-total lack of research addressing non-crop

systems, and the paucity of studies providing reliable data about vector attraction to virus-induced

visual and olfactory cues. For other classes of insect-transmitted plant pathogens, still less is

known about the ecology of pathogen effects on host-vector interactions (but see (Mann et al.

2012).

In the current study we examine how pathogen-induced changes in the vegetative and floral

volatiles of a wild gourd Cucurbita pepo ssp. texana (Cucurbitaceae) influence the behavioral

responses (e.g., attraction to and aggregation) of striped cucumber beetles Acalymma vittatum

(Coleoptera: Chrysomelidae: Luperini), which transmit Erwinia tracheiphila, the causative agent

of a usually lethal wilt disease. Beetles acquire E. tracheiphila by feeding on the leaves of

infected plants (Yao 1996; Garcia-Salazar et al. 2000a) and may also transmit the pathogen when

infective frass falls onto open wounds at sites of foliar feeding damage (Rand 1915; Mitchell &

Hanks 2009). However, beetles also aggregate to feed and mate in wild gourd flowers, and recent

findings suggest that transmission through floral nectaries may be particularly important in this

system. We have previously shown that E. tracheiphila is present at very high rates in frass

collected from flowers in the field (Sasu et al. 2010a) and that the incidence of wilt disease is

strongly influenced by the presence and number of flowers (Ferrari et al. 2007; Sasu et al. 2009).

Furthermore, we recently demonstrated that E. tracheiphila is efficiently transmitted through

floral nectaries on a time frame consistent with the relatively short window (~6 hrs) (Sasu et al.

2010a) available for pathogen transmission prior to floral abscission (each wild-gourd flower

opens only for a single morning). Thus, we suspect that E. tracheiphila is frequently acquired by

beetles feeding on infected leaf tissue and transmitted to healthy plants though frass deposition

into the flowers of healthy plants.

Our previous work has also shown that the incidence of wilt disease is greatly reduced among

plants exhibiting symptoms of infection by Zucchini yellow mosaic virus (ZYMV) (Potyviridae)

22

(Sasu et al. 2009b; Sasu et al. 2010b), which slows plant growth and reduces reproductive output,

but unlike wilt disease, does not kill plants. Furthermore, while a good deal of theoretical and

empirical work has addressed the dynamics of competitive interactions among pathogens

occurring in mixed infections (e.g., (Choisy & De Roode 2010), relatively little is known about

how pathogen-induced changes in host plant volatiles (or other aspects of host phenotypes that

influence interactions with insect vectors) may affect subsequent rates of infection by secondary

pathogens. Therefore, in addition to exploring how E. tracheiphila affects foliar and floral plant

volatiles and influences the recruitment of beetle vectors to the leaves and flowers of healthy and

wilting plants, we examine how ZYMV infections affect cucumber beetle attraction to explore the

possibility that the reduced incidence of wilt disease in ZYMV-infected plants is mediated, at

least in part, by reduced exposure to the beetle vectors of E. tracheiphila.

Materials and Methods

The Cucurbita pathosystem

Cucurbita pepo ssp. texana is an annual monoecious vine, native to the Southern US, with

indeterminate growth and reproduction, and is either the progenitor of cultivated squash or an

early escape from cultivation (Decker 1988). Single large yellow flowers (male or female) are

borne in leaf axils, remain open for a single morning (~6h), and are abscised the following day

(Sasu et al. 2010b). They release a volatile blend attractive over long distances to solitary squash

bee pollinators (Hurd 1971) and herbivorous diabroticite cucumber beetles (Metcalf & Lampman

1991; Andrews et al. 2007) —hypothesized to be the ancestral pollinators of Cucurbita spp.

(Kevan & Baker 1983). Cucumber beetles are the only known vectors of E. tracheiphila bacteria,

which proliferate in the xylem of infected plants and eventually block xylem flow. Wilt

symptoms typically develop 10-15 days after exposure, and the disease is typically fatal (within

23

2-3 weeks) once symptoms appear (Yao 1996). Bacterial wilt is the most economically important

disease of cultivated cucurbits (cucumbers, melons, pumpkins, squash) in the Eastern US

(Fleischer et al. 1998; Brust 1999).

Generalist aphids also feed on Cucurbita spp. and transmit various viral diseases including

ZYMV, an important agricultural pathogen (Fuchs 1995) and the most common viral disease at

our field sites in Central Pennsylvania (Sasu et al. 2009b). ZYMV causes leaf and fruit

deformities and depresses reproductive output but does not typically kill plants. Details of the

epidemiology of ZYMV and E. tracheiphila at our field sites can be found in Ferrari et al. (2007)

and Sasu et al. (2009).

Beetle colony propogation

Acalymma vittatum rearing followed Mitchell (2009). Adult beetles were kept in 1 ft x 1 ft

Bioquip mesh cages (cat #1466A), with moist potting soil provided as an oviposition substrate.

Beetles were fed thrice weekly with leaves and flowers of C. pepo ‘Dixie’. Potting soil (with

eggs) was transferred weekly to a 6L plastic rearing container where the root-feeding larvae were

continuously supplied with sprouted C. pepo ‘Raven’ seedlings until pupation. Newly eclosed

adults were placed with other adults from the same age cohort.

Foliar and floral volatile collections:

Field volatile collections were made in two 0.4ha plots (each containing 180 plants) at the Russell

E. Larson Research Farm at Rock Springs Pennsylvania in 2009. Plants contracted E. tracheiphila

and ZYMV from herbivory by naturally occurring vector (cucumber beetle and aphid)

populations. Our diagnoses of plant disease status (for all field studies) was confirmed for a

sample of symptomatic and asymptomatic plants, by using DAS-ELISA tests for ZYMV (Agdia

Inc., Elkhart, IN) and by isolating E. tracheiphila from wilting plant tissues and using the isolate

24

to infect new, greenhouse-grown plants. Foliar volatiles were collected from one branch of 21

healthy plants; one symptomatic branch of 19 E. tracheiphila-infected plants; one non-

symptomatic branch of 13 E. tracheiphila-infected plants; and one symptomatic branch of 9

ZYMV infected plants. For foliar volatile collections, 1ft x 2ft rectangular Teflon bags were

placed over the first 7 fully expanded leaves on a branch and tied around the vine to create a

closed chamber (bags were cleaned with water and hexane between uses). Using a portable

volatile-collection system (Volatile Assay Systems, State College, PA), charcoal-filtered air was

pushed into the Teflon bags at 1.2L/min, and pulled at 1.0L/min through adsorbent SuperQ filters.

Foliar volatiles were collected for 25 minutes between 1030 and 1500. Filters were subsequently

eluted with 150µl dichloromethane (with 400ng of n-octane and nonyl acetate added as internal

standards) and the eluate analyzed by gas chromatography with a Hewlett-Packard (Paolo Alto,

CA) model 6890 gas chromatograph (GC) with a flame ionization detector (FID). Compounds

were determined by GC-mass spectrometry (MS) with electron ionization and chemical

ionization sources. All resulting data from field leaf volatile quantifications were log +1

transformed for normality and visualized with a PCA using the ade4 package (Dray & Dufour

2007) in R (R 2008) and then analyzed using SAS PROC MIXED (SAS Institute, 2011). All

compounds present (excluding a very small number that were observed only sporadically and not

consistently released in any treatment group) were analyzed using a repeated measures statement

to account for multiple measurements on the same branch. The model statement for both

individual compounds and total summed compounds was Volatiles = Date + Disease; Repeated

Date / Subject = Branch.

Floral volatiles were collected from field-grown plants in 2009 and 2010 (only male flowers were

utilized because wild gourd plants produce far more male than female flowers and because wilt

symptomatic branches often selectively abort female flower buds while male flower buds

progress to anthesis). In 2009, volatiles were collected from 36 flowers on 26 healthy plants and

25

from 46 flowers from symptomatic branches on 16 E. tracheiphila-infected plants. In 2010

volatiles were collected from 23 flowers on 17 healthy plants and 22 flowers on 17 symptomatic

ZYMV-infected plants. The corolla of each flower was prevented from opening at sunrise by

applying twist-ties the evening before anthesis to ensure that pollinators did not remove nectar or

pollen that would affect volatile profiles (Mena Granero 2005). When the twist ties were removed

the next morning, flowers opened immediately and were then placed in 1ft x 1ft square Teflon

collection bags that were tied around the stem or pedicel with string to create a closed chamber.

Twenty-five minute volatile collections (conducted as above) occurred between sunrise and 1030

and samples were analyzed as above. Floral volatiles were log + 1 transformed for normality and

analyzed separately, with repeated measures to account for sampling different flowers on the

same plant, in SAS PROC MIXED (SAS 2011) using the model statement Volatiles = Date +

Disease; Repeated Date / Subject = Plant.

Greenhouse Volatile Collections were made to confirm the patterns made in the field and to

characterize the volatile blend induced by pathogen infection under controlled conditions. All

plants were grown in Pro-Mix (Premier Horticulture Reviere Du Loup, Quebec, Canada) and

maintained in growth chambers at 25C day 22C nights with 14L 10D light cycle. For analyses of

foliar volatiles induced by E. tracheiphila, plants were either mock inoculated at 4 weeks (apprx.

4-5 true leaves) (n = 19), or inoculated—using the colony-stab protocol (Mitchell & Hanks

2009)—with a virulent field isolate of E. tracheiphila maintained on nutrient peptone agar at 26C

(n = 19). Once symptoms appeared (several days after inoculation), individual plants were placed

under 4L glass domes, 15cm tall x 15 cm wide (Analytical Research Systems, Gainesville,

Florida, USA) with Teflon bases that closed around plant the stem to prevent air flow. Volatiles

were collected between 0800 and 1400 using a closed push/pull system, in which filtered air is

pumped into the chambers at 1.3L/min and pulled at 1L/min through traps containing 40mg of

adsorbent SuperQ (Alltech, Deerfield, Illinois, USA). In a separate experiment, volatiles were

26

similarly collected from virus-infected and mock-inoculated plants. A locally collected ZYMV

isolate was ground in 0.1M phosphate buffer (K2HPO4 and KH2PO4). Carborundum was used to

break cells on the surface of the cotyledons, and the virus-buffer slurry was applied with cotton

swabs. Mock inoculations employed the carborundum abrasive and phosphate buffer.

Floral volatiles were collected from flowers on greenhouse-grown, two-month-old plants that

had been either mock inoculated (n=15 plants) or inoculated with the same virulent field E.

tracheiphila isolate used in the leaf volatile inoculations (n=12 plants). In a separate experiment,

plants at the 5-leaf stage were inoculated with ZYMV (as above) on the newest fully expanded

leaf (n=12 plants) or mock inoculated (n=13 plants). Once infected plants began showing

symptoms, individual flowers were placed in 4L glass domes while still attached to the vine.

Flower volatiles were collected between 0600 and 1000, when flowers were open. Volatiles from

greenhouse experiments were analyzed separately in SAS using a Mixed Effects Model ANOVA

to determine the effects of Disease Status (Healthy, Infected) and Date on Total Volatile

production and, separately, on individual volatile compounds.

Recruitment of beetles to plants in the field:

Field trapping of vector insects employed rectangular cages (3 ft long x 1 ft tall x 1 ft wide) made

of galvanized 19-gauge hardware cloth designed to fit over individual non-flowering branches.

The sides of the cage were coated with Tree Tanglefoot™ (a sticky non-water soluble substance

commonly used for insect sampling). Cages were placed over single non-flowering branches of

20 healthy plants, non-symptomatic branches of 11 E. tracheiphila-infected plants, and

symptomatic branches of 18 E. tracheiphila-infected plants. Beetles were counted and removed

from traps twice weekly, and Tanglefoot was re-applied weekly. Data were analyzed with a

repeated measures model using SAS PROC MIXED Total Beetles = Disease + Date; Repeated

Date / Subject = Branch.

27

We also counted beetles in one male flower (haphazardly selected, from a distance of

~5m, prior to approaching the plant) on all plants from one of our field plots that possessed at

least one male flower on August 12, 2010. The plot contained healthy plants (no visible

symptoms of disease), ZYMV infected plants (visible symptoms of ZYMV) and E. tracheiphila-

infected plants (visible symptoms of wilt disease). The resulting data were analyzed using a 1-

Way ANOVA with Disease as the independent variable.

Laboratory behavioral assays:

Volatile choice tests: We employed a Y-tube olfactometer (ARS, Inc., Gainesville, FL; cat

#YTO-A10) to test beetle responses to foliar and floral odors. The Y-tube was impressed

vertically into a fitted cardboard box, the top of which was covered with two layers of red plastic.

For foliar-volatile assays, wild gourd plants at the 4–5 leaf stage were either mock-inoculated or

stab inoculated with E. tracheiphila (as above). After symptoms developed on infected plants,

plants were enclosed in Teflon bags and placed at the Y-tube terminals. Incoming air (hydrated

by passing through a bubbler) passed into the Teflon bags at 1.5 L/min, and air was pulled

through the system at 3 L/min. Three- to 4-week-old, lab-reared striped cucumber beetles were

starved for 24 hours prior to choice tests. Beetles were individually placed into the base of the Y-

tube and allowed to make a choice. Six beetles were recorded per unique plant pair and then a

new pair of plants was used. The Y-tube terminal to which a given plant was attached to was

alternated after three beetles had made choices. The resulting data were analyzed using Chi-

square tests for independence. Floral-volatile assays were conducted similarly, with flowers on

healthy or pathogen-infected plants enclosed in 1ft x 1ft Teflon bags positioned at the Y-tube

terminals. For these assays, 1-month-old wild gourd plants were inoculated with E. tracheiphila

or ZYMV, or appropriately mock inoculated (as above). In separate trials, we compared beetle

28

choice for flowers from (a) healthy plants vs. clean air (empty Teflon bags); (b) mock-inoculated

vs. E. tracheiphila-infected plants; and (c) mock-inoculated vs. ZYMV-infected plants.

We also assessed beetle feeding preferences for healthy and pathogen-infected plants. Pairs of

E. tracheiphila-inoculated (as above) or mock-inoculated 4-leaf stage greenhouse-grown wild

gourd plants were placed in 1ft x 1ft mesh Bioquip cages (cat # 1466A). Six striped cucumber

beetles from a lab colony (three males and three females) that had been starved for 24hours were

placed in each of six replicate cages and allowed to feed for 48 hours. Leaf area consumed from

each plant was quantified using SigmaScan Pro v. 5.0 (SPSS Inc., Chicago, IL, USA). A similar

assay tested feeding preferences for ZYMV-infected (as above) or mock-inoculated plants. Leaf

area data were analyzed with a 1-way ANOVA with disease as the independent variable against

total leaf area, and separately against total area consumed as dependent variables, with “cage”

entered as a random variable.

Results

Foliar volatiles:

In the field, the wilting leaves of E. tracheiphila-infected plants exhibited significant

elevation of volatile emissions compared to those of healthy plants, which exhibited low levels of

constitutive volatile emissions (Figure 2.1, Figure 2.2, Table 2.1). Overall, 10 of 12 compounds

were released in higher amounts from the symptomatic leaves of E. tracheiphila infected plants.

Non-symptomatic leaves on E. tracheiphila-infected plants displayed volatile profiles

indistinguishable from those of healthy plants. ZYMV-infected leaves released the same volatile

blend as healthy leaves and non-symptomatic leaves on E. tracheiphila-infected plants, except for

elevated release of nonatriene, and their total volatiles were not significantly higher than healthy

or non-wilt branches in pairwise tests.

29

Figure 2-1. Field foliar volatiles

The 12 most abundant volatile organic compounds emitted from the foliage of healthy plants,

nonsymptomatic branches on E. tracheiphila-infected plants, symptomatic wilting branches on

E.tracheiphila-infected plants, and branches on zucchini yellow mosaic virus-infected plants in

the field. LS means ± SE bars. Sample sizes n=20 healthy branches; n=8 non-wilt branches; n=18

wilting branches; n=9 virus branches.

30

Figure 2-2. PCA of field foliar volatiles.

A principle component bi-plot of foliar volatiles emitted Cucurbita pepo ssp. texana

foliage in the field. Principle component 1 explains 33.7% of the variation, and principle

component 2 explains 16.6% of the variation. All volatile compounds except nonatriene

and 1-pentanol are positively associated with wilting foliage (blue). The volatiles emitted

by ZYMV (green), nonwilt (red), and healthy (black) treatments are indistinguishable

from each other.

Under greenhouse conditions, we observed a similar pattern: symptomatic E. tracheiphila-

infected plants exhibited elevated volatile emissions compared to healthy (mock-inoculated)

plants. Overall, the seven consistently E. tracheiphila-induced compounds were all released in

higher amounts by symptomatic E. tracheiphila-infected foliage in the greenhouse, while no

compound was released in a higher concentration from healthy plants. Most E. tracheiphila-

induced compounds were green-leaf volatiles or monoterpenes (Figure 2.3, Table 2). As in the

31

field, the volatile blend from ZYMV-infected foliage was indistinguishable from that of healthy

(mock-inoculated) plants (Table 3). Foliage on healthy and ZYMV-infected plants produced the

same volatile organic compounds, and no compound differed significantly in concentration based

upon pairwise comparisons (Figure 2.3, Table 3).

Figure 2-3. Geenhouse foliar volatiles

Two separate pairwise greenhouse volatile collection experiments measured volatiles emitted by

healthy mock-bacterial-infected plants vs. wilting E. tracheiphila-infected plants, and healthy

mock-infected plants vs. ZYMV-infected plants. Sample sizes are mock-virus n = 11, ZYMV n =

12; mock-E. tracheiphila n = 19, E. tracheiphila-infected n = 19.

Floral volatiles:

In the field, flowers from symptomatic E. tracheiphila-infected branches and virus-

infected plants exhibited significantly lower total volatile emissions than flowers on healthy

plants (Figure 2.4, Table 4, Table 5). Neither E. tracheiphila nor ZYMV altered the overall

composition of the floral volatile blend, but E. tracheiphila infection attenuated the release of

linalool, 1,4-methoxybenzene, and nonatriene, while ZYMV infection decreased the amount of

1,4-methoxybenzene emitted (Figure 2.4).

32

Figure 2-4. Field floral volatiles.

Floral volatiles from healthy and wilting E. tracheiphila-infected plants in the field in 2009, and

healthy and virus-infected plants in the field in 2010. Mean ± SE of the three main components of

the field floral volatile blend. Sample size: n = 36 healthy flowers and n = 46 wilt flowers in 2009

and n = 23 healthy flowers and n = 22 virus flowers in 2010

In the greenhouse, we observed a pattern similar to our field results. In pairwise experiments,

infection with either ZYMV or E. tracheiphila reduced the total floral volatiles released

compared to healthy, mock-inoculated plants (Figure 2.5, Table 6, Table 7).

Figure 2-5. Greenhouse floral volatiles

Floral volatiles emitted by healthy mock-infected vs. ZYMV-infected flowers, and flowers on

healthy mock bacterial infected plants vs. flowers on E. tracheiphila-infected wilting plants in

33

two greenhouse experiments. Sample sizes: mock-ZYMV n = 13; ZYMV n = 12; mock-E.

tracheiphila n = 12; E. tracheiphila-infected n = 15.

Recruitment of beetles to plants in the field:

More than twice as many cucumber beetles were captured on symptomatic (i.e., wilting) branches

compared to non-symptomatic branches of E. tracheiphila-infected plants or branches on healthy

plants (Figure 2.6A). In contrast, more beetles aggregated in the flowers of healthy plants (4.6 ±

0.9; N = 34) than in the flowers of E. tracheiphila- (2.0 ± 0.7; N = 15) or ZYMV-infected (2.0 ±

0.3; N = 82) plants (1-Way ANOVA, F2,128 = 6.22, P = 0.003) (Figure 2.6B).

Figure 2-6. Beetle attraction in the field

A. Cucumber beetle attraction to Tanglefoot cages covering branches on healthy plants, non-

symptomatic branches on infected plants, or wilting branches in the field. Means ± SE bars. n =

Sample size. B. Number of beetles per flower on healthy, E. tracheiphila-infected, and ZYMV-

infected plants under field conditions. Sample size: N = 85 healthy plants; N = 23 wilt diseased

plants; and N = 127 ZYMV-infected plants.

Laboratory behavioral assays:

34

In Y-tube choice assays (Figure 2.7), beetles exhibited a significant preference for the

odor of E. tracheiphila-infected foliage compared to that of healthy foliage (χ2 = 5.88, P = 0.015,

1df). But, the odors of healthy flowers were significantly more attractive than those of flowers on

E. tracheiphila-infected plants (χ2 = 12.51, P < 0.001, 1df) or ZYMV-infected plants (χ

2 = 5.12, P

= 0.023, 1df), or clean-air controls (χ2 = 8.53, P < 0.005, 1df).

Figure 2-7. Greenhouse behavioral assays

Results of Y-tube beetle pairwise choice tests for volatiles from healthy or infected leaves or

flowers. Beetles did not have a significant preference for the foliage of either healthy or virus-

infected plants (χ2 = 0.72, P = 0.386, 1 df); but beetles were more attracted to flowers on healthy

plants compared to a clean air blank (χ2 = 8.53, P = 0.003, 1 df); to flowers on healthy plants

compared to flowers on ZYMV-infected plants (χ2 = 5.12, P = 0.023, 1 df); to flowers on healthy

plants compared to flowers on symptomatic E. tracheiphila-infected plants (χ2 = 12.51, P ≤ 0.005,

1 df); and to foliage on E. tracheiphila-infected plants compared to foliage on mock-inoculated

plants (χ2 = 5.88, P = 0.015, 1 df).

In laboratory feeding assays, cucumber beetles consumed more leaf area from wilting E.

tracheiphila-infected plants relative to healthy plants (ANOVA F1,10 = 6.59, P = 0.028), even

though E. tracheiphila infection reduced the total leaf area available (ANOVA F: 1, 10 = 5.18 P

= 0.046). ZYMV infection had no similar impact on available leaf area (ANOVA F1,10 = 2.82, P =

35

0.124), but cucumber beetles consumed more of the leaf area of ZYMV-infected leaves relative to

those of healthy plants (ANOVA F1,10 = 31.42, P < 0.001) (Figure 2.8).

Figure 2-8. Dual-choice feeding preference test of healthy vs. pathogen-infected plants.

Sample sizes are six cages with mock vs. virus and six cages with mock vs. E. tracheiphila

Discussion

The findings presented here demonstrate that infection with the bacterial wilt disease

pathogen Erwinia tracheiphila changes the volatile phenotype of leaves and flowers of Cucurbita

pepo ssp. texana relative to healthy plants, and that these changes affect the foraging and

aggregation behavior of the beetle vectors in a manner that not only increases the contact rate

between wilting foliage and insect vectors, but also increases the exposure rate of healthy host

plants to the pathogen. Significantly more cucumber beetles were recruited to the wilting foliage

36

of E. tracheiphila-infected plants in the field (Fig. 6A), and this attraction is likely explained by

the elevated, and altered, volatile emissions of wilting leaves (Fig. 1), which we found to elicit

positive behavioral responses from the beetles (Figs. 6A, 7). The characteristic volatile response

to infection by E. tracheiphila includes the release of green-leaf volatiles, which are frequently

associated with plant stress (Farag & Paré 2002) and have been shown to be important as host

location cues for many herbivorous insects (Bolter et al. 1997). In the field, this preference for the

odors of wilting leaves increases vector attraction to symptomatic foliage on plants infected with

E. tracheiphila, which is acquired during feeding on wilting leaves (Garcia-Salazar et al. 2000a;

Mitchell & Hanks 2009).

Furthermore, in dual-choice feeding assays, we observed a significant beetle

preference for wilting (diseased) leaves, consistent with previous reports that cucumber beetles

aggregate to feed on the leaves of wilt-diseased plants (Yao 1996). This preference may in part

reflect enhanced accessibility of wilting tissue owing to diminished defensive secretion by wilting

leaves of phloem sap high in P-proteins that can dramatically impede herbivore feeding by

gumming mouth parts (McCloud et al. 1995). Thus, E. tracheiphila infection induces symptoms

that likely make it physically easier for cucumber beetle vectors to consume symptomatic leaf

tissue relative to healthy foliage.

While pathogen-induced changes in the volatiles produced by symptomatic E. tracheiphila

infected plants can increase rates of vector attraction to wilting plants and induce symptoms

making wilting foliage easier to consume, infective vectors must also have an incentive to visit

healthy hosts in order for pathogen dissemination to occur (Sisterson 2008). As noted above,

there is reason to believe that transmission through floral nectaries is important for disease spread

in this system: In field studies conducted over several years, we have found that the probability of

a plant contracting wilt disease is positively correlated with the number of flowers produced by

the plant over the 15 days preceding the first appearance of wilt symptoms (Ferrari et al. 2007;

37

Sasu et al. 2009b) . Furthermore, using a PCR assay, we found that > 95% of the flowers on

healthy plants contained E. tracheiphila-infected frass on or in the nectaries by 11:00 AM, the

approximate time when flowers close (Sasu et al. 2010a). And we recently demonstrated that E.

tracheiphila is efficiently transmitted through floral nectaries—through controlled greenhouse

studies using green-fluorescent-protein transformed bacteria—and documented the progress of

the pathogen through the nectaries and into the pedicel within 24 hrs (i.e., prior to floral

abscission) (Sasu et al. 2010a).

Given the likely importance of transmission via flowers, our findings regarding E.

tracheiphila-induced changes in floral volatiles may hold significant implications. It is well-

established that cucumber beetles are attracted over long distances to the floral volatiles of

Cucurbita (e.g., Andersen and Metcalf 1987; Andrews et al. 2007) and that cucumber beetles

aggregate in the flowers of Cucubita to mate and feed (Andersen 1987). Our results indicate that

the floral volatile emissions of E. tracheiphila-infected plants are significantly attenuated relative

to those of healthy plants (Figs. 2.4, 2.5). Moreover, we observe reduced beetle attraction to the

floral odors of E. tracheiphila-infected plants relative to those of healthy plants (Figs. 2.6B, 2.7),

and we found more beetles aggregating in the flowers of healthy plants than in the flowers of wilt

diseased plants in the field (Fig. 2.6B). These results suggest that healthy plants are likely to

experience significant exposure to E. tracheiphila through flowers as a consequence of the

relative attractiveness of their flowers to foraging beetle vectors compared to those of already-

infected plants.

Taken together, the observed effects of E. tracheiphila infection on floral and vegetative

volatile emissions suggest a pattern conducive to the effective transmission of this pathogen: the

elevated volatile emissions induced in symptomatic leaves appear to recruit beetles to wilting

tissues on which they preferentially feed, increasing the likelihood of E. tracheiphila acquisition

by vectors. However, beetles also exhibit a preference for the floral volatiles of healthy plants,

38

and preferentially aggregate in the flowers of healthy plants where E. tracheiphila shed in the

frass of infected beetles can access the plant vasculature via the floral nectaries. This pattern is

consistent with previous observations that vector borne—and other parasites—often alter the

phenotypes of their hosts in ways that facilitate their own transmission (Lefévre et al. 2006).

Our results also suggest a potential explanation for our previous observations that the

incidence of wilt disease is greatly reduced among plants exhibiting symptoms of infection by

ZYMV—in a three-year field study, Sasu et al. (2009) found that 0.4% of virus-infected plants on

15 July contracted wilt disease before 1 September, while between 5-27% of healthy plants

contract E. tracheiphila during the same period. Our data indicate that ZYMV infection decreases

floral volatile production (Fig. 2.4, 2.5); that fewer beetles aggregate in the flowers of virus-

infected plants under field conditions (Fig. 2.6b); and that fewer beetles are attracted to floral

volatiles of ZYMV infected plants than to the floral volatiles of healthy plants in laboratory

choice tests (Fig. 2.7). Together with our previous observation that ZYMV-infected plants

produce fewer flowers than healthy plants (Sasu et al. 2009b; Sasu et al. 2010c), these findings

strongly suggest that ZYMV-infected plants may experience reduced rates of exposure—through

flowers—to the vectors of E. tracheiphila compared to uninfected plants in the same populations

and consequently reduced opportunity for E. tracheiphila transmission through floral nectaries.

This reduced exposure may, at least in part, explain the reduced incidence of wilt disease on

ZYMV-infected plants, and given the widespread cultivation of virus-resistant transgenic squash

in the United States and Mexico, may mitigate some of the fitness advantage that the escaped

transgene may have in wild populations in which both diseases are present (Sasu et al. 2009;

2010c).

In conclusion, while a growing number of studies document the effects of arthropod-

transmitted pathogens on the nature of host-vector interactions—with potentially important

implications for community and ecosystem ecology (McLeod et al. 2005; Lefévre et al. 2009),

39

agriculture (Eigenbrode et al. 2002; Mauck et al. 2010; Mann et al. 2012), and human health

(Hurd 2003; Lefévre et al. 2006)—we are only now beginning to explore the implications of such

pathogen-induced effects within the context of complex ecological systems in which plant hosts

simultaneously interact with multiple herbivores and pathogens. The current findings document

the role of pathogen-induced olfactory cues in mediating both the recruitment of cucumber

beetles to the foliage of plants infected by E. tracheiphila and the relative attractiveness of

healthy flowers to these vectors, Furthermore, they reveal effects of ZYMV infection on volatile

cues that influence beetle attraction and thereby likely reduce the exposure of ZYMV-infected

plants to bacterial wilt. Though we are only beginning to document the occurrence of such

effects, it seems likely that similar processes occur frequently in complex pathosystems, with

potentially far-reaching implications both for basic ecology and for the management of disease

processes in natural and agricultural settings.

Table 2-1. Foliar volatiles from healthy, non-symptomatic, wilting, and ZYMV-infected

branches under field conditions.

Compound Healthy Non-wilting

branch

Wilting branch ZYMV-

infected

P

Unknown 2.6 ± 1.6 1.9 ± 1.8 10.3 ± 1.4 0.8 ± 2.6 ≤0.0001

1-pentanol 13.5 ± 1.0 14.3 ±1.1 16.0 ± 0.9 19.2 ± 1.6 0.0041

Toluene 4.3 ± 4.2 3.7 ± 4.6 20.8 ± 3.5 0 ± 6.6 ≤0.0001

Hexenal 23.1 ± 10.2 25.8 ± 11.7 74.7 ± 8.9 42.8 ± 16.5 ≤0.0001

e-2-hexenal 10.2 ± 29.7 13.8 ± 34.3 125.8 ± 26.0 34.3 ± 48.3 ≤0.0001

z-3-hexen-1-ol 2.1 ± 3.7 2.4 ± 4.1 17.6 ± 3.4 1.7 ± 6.0 ≤0.0001

Heptanal 2.5 ± 9.4 6.2 ± 10.5 51.5 ± 8.9 16.3 ± 15.2 ≤0.0001

Xylenes 1.2 ± 0.9 0.7 ± 1.0 9.5 ± 0.8 3.8 ± 1.4 ≤0.0001

Ocimene 4.5 ± 2.8 6.5 ± 3.2 19.1 ± 2.5 7.8 ± 4.6 ≤0.0001

Nonanol 12.6 ± 2.5 14.3 ± 2.9 29.0 ± 2.2 16.9 ± 4.0 ≤0.0001

*Nonatriene 20.8 ± 5.3 9.3 ± 6.1 14.6 ± 4.6 35.6 ± 8.6 0.517

Unknown 6.3 ± 11.9 4.2 ± 13.7 40.0 ± 10.5 3.2 ± 19.3 0.0496

Sum 99.2 ± 49.5 101.3 ± 53.6 411.7 ± 40.5 171.6 ± 77.4 ≤0.001

40

Field foliar volatiles: Mean ± SE (ng) of foliar leaf volatiles collected from healthy plants, non-

symptomatic (non-wilting) branches on E. tracheiphila-infected plants, symptomatic (wilting)

branches on E. tracheiphila-infected plants and ZYMV-infected plants growing in experimental

fields. P-values are from log +1 transformed values analyzed with repeated measures model SAS

PROC MIXED = Disease + Date; Repeated = Date/ Subject = Vine.

Table 2-2. Foliar volatiles from (mock) healthy vs. E. tracheiphila-infected plants under

greenhouse conditions

Compound Mock E. tracheiphila-infected P

1-pentanol 1.1 ± 4.2 32.9 ± 4.2 ≤0.001

Toluene 2.7 ± 3.2 11.3 ± 3.2 0.0043

Hexenal 0.01665 ± 2.19 13.8 ± 2.2 ≤0.001

e-2-hexenal 0 ± 490 2297.4 ± 490 ≤0.001

z-3-hexen-1-ol 2.3 ± 12.9 36.0 ± 12.8 0.0092

Xylenes 10.2 ± 24.8 69.7 ± 24.8 0.0131

Ocimene 0 ± 75.0 161.9 ± 75.0 ≤0.001

Sum 0 ± 627.0 2382.1 ± 627.0 ≤0.001

Results of a 1-Way Anova for the effects of E. tracheiphila infection on foliar volatile production

under greenhouse conditions. Mean ± SE (ng) for foliar volatiles collected from E. tracheiphila

infected and mock inoculated plants.

Table 2-3. Greenhouse ZYMV vs. mock (healthy) foliar volatiles

Compound Mock ZYMV-infected P

E-2-hexenal 87.11 ± 14.5 54.4 ± 13.9 0.1819

Unknown1 9.3 ± 5.5 7.6 ± 5.2 0.823

Unknown2 39.3 ± 12.5 46.5 ± 12.0 0.862

Unknown3 51.5 ± 15.8 33.0 ± 15.1 0.408

Unknown4 23.5 ± 6.2 19.9 ± 5.9 0.673

Total 257.8 ± 53.11 177.7 ± 50.85 0.118

Results of a 1-Way Anova for the effects of ZYMV infection on foliar volatile production under

greenhouse conditions. Mean ± SE (ng) for foliar volatiles collected from ZYMV infected and

mock inoculated plants.

Table 2-4. Floral volatiles from healthy and Erwinia tracheiphila-infected plants under field

conditions

Compound Healthy E. tracheiphila-

infected

P

41

Linalool 15.7 ± 1.5 12.2± 1.4 0.1948

Nonatriene 26.6 ± 4.1 7.7 ± 3.7 0.007

1,4-methoxybenzene 346.3 ± 35.1 87.5 ± 31.3 ≤0.0001

Total 388.5 ± 36.7 107.4 ± 32.6 ≤0.0001

Field floral volatile collections show that E. tracheiphila infection suppresses the mean sum of

volatiles and the individual compounds nonatriene and 1,4-methoxybenzene emitted from flowers

on infected plants relative to healthy plants. The table shows mean ± SE (ng) for floral volatiles

and significance testing. Model statement is SAS PROC MIXED volatiles = Date + Disease;

Repeated Date / Subject = plant. Absolute mean ± SE are reported in the table, but quantities

were log transformed for normality to produce P-values

Table 2-5. Floral volatiles from healthy and ZYMV-infected plants under field conditions

Compound Healthy ZYMV-

infected

P

Nonatriene 22.6 ± 4.3 5.6 ± 4.4 <0.0001

Linalool 12.9 ± 1.1 11.8 ± 1.2 0.8301

1,4-methoxybenzene 62.2± 11.3 41.9 ± 11.6 0.0312

Total 97.7 ± 13.6 59.4 ± 13.9 0.0247

The following year (2010), field floral volatile collections show that virus infection also

suppresses total volatiles, driven by a suppression 1,4-methoxybenzene, corresponding with

greenhouse volatile collections. Model statement is SAS PROC MIXED volatiles = Date +

Disease; Repeated Date / Subject = plant. Absolute mean ± SE are reported in the table, but

quantities were log transformed for normality to produce P-values

Table 2-6. Floral volatiles from E. tracheiphila and healthy plants under greenhouse conditions

Compound Mock E. tracheiphila-

infected

P

Linalool 97.2 ± 15.4 41.8 ± 13.4 0.0146

Nonatriene 90.4 ± 8.5 41.4 ± 8.5 0.0088

1,4-methoxybenzene 4090.30 ± 628.5 1177.9 ± 546.6 0.0001

Unknown 48.9 ± 10.4 24.6215 ± 9.0844 0.0200

Unknown 203.5 ± 58.1 20.1 ± 50.5 0.0011

Total 4545.0 ± 667.8 1353.9 ± 580.7 ≤0.001

42

Results of a 1-Way Anova for the effects of E. tracheiphila infection on floral volatile production

under greenhouse conditions. Mean ± SE (ng) for floral volatiles collected from E. tracheiphila

infected and mock inoculated plants.

Table 2-7. Floral volatiles from ZYMV-infected and healthy plants under greenhouse conditions

Compound Mock ZYMV-infected P

Linalool 45.2 ± 5.8 40.8 ± 6.0 0.5795

Nonatriene 12.8 ± 5.0 3.4 ± 5.2 0.204

1,4-methoxybenzene 687.9 ± 116.6 266.6 ± 121.4 0.0199

Total 959.3 ± 134.6 515.4 ± 140.1 0.0367

Results of a 1-Way Anova for the effects of ZYMV infection on floral volatile production under

greenhouse conditions. Mean ± SE (ng) for floral volatiles collected from ZYMV infected and

mock inoculated plants.

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45

Chapter 3

Direct interactions between a viral pathogen, a bacterial pathogen, and a

specialist herbivore in a shared host plant

Abstract

Exposure to biotic and abiotic challenges can result in the induction of broad-spectrum

resistance against subsequent pathogen challenge. However, there are limited data on induced

resistance in host plants outside of model systems and the ecological significance of induced

resistance in natural settings. To address this, we tested the contribution of induced systemic

resistance as a factor explaining several years of field studies showing healthy wild gourds

(Cucurbita pepo ssp texana) contract a fatal bacterial wilt infection caused by Erwinia

tracheiphila at a significantly higher rate compared to Zucchini yellow mosaic virus infected

plants. Our results show that inoculation with Erwinia tracheiphila does not induce the defense

signaling hormone SA, while ZYMV-infected wild gourds have higher constitutive and induced

SA levels. In controlled inoculation trials, ZYMV – infected plants contract bacterial wilt disease

(caused by Erwinia tracheiphila) at the same rate as healthy plants but experience delays in wilt

development at high bacterial doses. In addition, healthy and pathogen – infected plants have

divergent responses to herbivory by specialist cucumber beetles.

46

Introduction

Plants deploy a vast array of general, inducible chemical and physical defensive

responses to biotic and abiotic challenges. For several decades, the signaling networks and

molecular mechanisms of plant resistance to herbivores, pathogens, and abiotic stress have been

revealed to be highly complex and tightly regulated (Heil & Baldwin 2002). However, plant

defensive signaling in non-model systems, and how induced resistance affects ecological

interactions between co – occurring herbivores and pathogens is often uninvestigated. Here, we

examine the relationship of induced plant defenses of the wild gourd Cucurbita pepo ssp. texana

to co-infection dynamics between a co - circulating bacterial wilt pathogen Erwinia tracheiphila

and the viral pathogen Zucchini Yellow Mosaic Virus, and how infection with either a bacterial or

viral pathogen affects wild gourd induced responses to herbivory by a specialist beetle herbivore.

Several chemical hormones that regulate interconnected genetic and phenotypic

responses have been implicated in controlling expression of defensive traits in response to

herbivore and pathogen challenge. Jasmonates are multifunctional oxylipins synthesized from

fatty acid precursors through the octadecanoid pathway. There is continuing debate about the

contribution of jasmonic acid (JA) precursors and isoforms to resistance induction, but cis-JA has

been confirmed as an active form mediating expression of many defensive responses (Creelman

& Mullet 1997; Engelberth et al. 2007). JA signaling is important for many aspects of senescence

and plant growth regulation (Wasternack 2007), but most research attention has focused on JA as

a key signaling molecule mediating induced defensive responses to physical damage from

chewing herbivores. JA mediated defenses include de novo synthesis of toxic secondary

metabolites, proteinase inhibitors, and insect growth suppressors (Farmer & Ryan 1992;

Creelman & Mullet 1997). In addition to induced herbivore defenses, a functional role for JA in

defense against some necrotrophic pathogens has also been proposed (Glazebrook 2005).

47

Salicylic acid is an endogenous phenolic signaling hormone best investigated for its role

in disease resistance (Vlot et al. 2009). SA induction and signaling after pathogen challenge can

lead to cell wall fortification (Dean & Ku 1987), accumulation of pathogenesis related (PR)

proteins and broad spectrum, systemic acquire resistance (SAR) against subsequent pathogen

challenge (An & Mou 2011). In some systems, ‘cross – talk’ occurs, where the expression of one

pathway can be antagonistic to expression of the other (Bostock 2005). However, this signaling

interference is often not well understood and is not thought to be universal.

The common cucumber Cucumis sativa (Cucurbitaceae) has been an important historical

model for unraveling the mechanisms of induced plant defense responses. Cucurbits are

susceptible to a variety of bacterial, fungal, and viral pathogens, and susceptible to attack from

specialist Diabroticite herbivores (Coleoptera: Chrysomelidae: Luperini) that can sequester and

detoxify cucurbit secondary metabolites (Zehnder et al. 1997). Early work in the cucumber model

led to the identification of salicyclic acid as a mobile signal responsible for systemic acquired

resistance (Metraux et al. 1990). Salicylic acid and pathogenesis-related (PR) proteins are

induced in cucumber after inoculation with a variety of bacterial, viral, and fungal pathogens. In

cucumber, SA associated induced resistance has been shown to be nonspecific: abiotic stresses

like phosphates (Mucharromah & Kuc 1991) in addition to biotic challenges from virus can

induce PR proteins and systemic, long-term, broad scale resistance to subsequent pathogen

challenge (Kuć 1982).

While common cucumbers have been an essential laboratory model for understanding

plant defense responses to a variety of biotic and abiotic challenges, little is known about how

pathogen-induced changes in hormone levels and induced defenses might affect broader

epidemiological patterns when several diseases are circulating in natural populations. The wild

gourd Cucurbita pepo ssp. texana is susceptible to many insect-transmitted plant pathogens that

also threaten cultivated cucurbits, including the bacterial wilt pathogen Erwinia tracheiphila is

48

only transmitted by specialist cucumber beetle vectors (Coleoptera: Chrysomelidae: Luperini)

(Garcia-Salazar et al. 2000b). Zucchini Yellow Mosaic Virus (ZYMV) (Potyviridae) is an

emerging viral pathogen of cucurbits worldwide, and is transmitted in a non-persistent manner by

several generalist aphid species (Desbiez & Lecoq 1997).

Several years of field studies show that both ZYMV and E. tracheiphila are endemic in

field populations of wild gourd at the PSU Experimental Farm in Rock Springs, PA (Sasu et al.

2009b; Sasu et al. 2010b), yet co-infect the same individual host plant at a significantly lower rate

than would be expected by chance. Viral infection has been shown to suppress floral volatiles,

which reduces recruitment of beetle vectors that transmit E. tracheiphila (Shapiro in press), but

the contribution of direct in planta interactions between the two pathogens to this phenomena is

not yet known. In light of this, the present study was undertaken to explore the direct interactions

between the viral pathogen Zucchini yellow mosaic virus (ZYMV), the bacterial wilt pathogen

Erwinia tracheiphila, and herbivory by specialist cucumber beetles that transmit E. tracheiphila

in a shared plant host, and specifically to test if there is an induced systemic acquired resistance in

ZYMV-infected wild gourd plants that makes virus-infected plants resistant to subsequent

exposure to the bacterial wilt pathogen E. tracheiphila.

Methods

Plant and pathogen materials

The wild gourd Cucurbita pepo spp. texana is thought to be the wild progenitor of

cultivated squash varieties. For all the following experiments, we used C. pepo spp. texana seeds

from wild maternal families originally collected in Texas and grown yearly in experimental plots

in Rockspring, PA. After germination, seedlings were transplanted in pots with compost soil

supplemented with 3 g of osmocote slow-release fertilizer (NPK:14-14-14) and micronutrients.

49

All experiments were performed in climate-controlled chambers under incandescent and

fluorescent lights (25 C, 16h:8h photoperiod).

The same strain of ZYMV, originally sampled in 2009 in a squash field, was used for all

virus-inoculation experiments. We mechanically inoculated the experimental plants by dusting

leaves with carborundum and applying an inoculum of 0.1 Potassium-phosphate buffer grinded

with infected frozen C. pepo leaf tissue. Mock-inoculated controls consisted of plants inoculated

by the same protocol with clean buffer only. A local field isolate of E. tracheiphila was

maintained on nutrient peptone agar at 27C for 3 days before plant inoculations.

Hormone Extractions

To test differences in constitutive and induced defense-related hormones in wild gourd,

83 C. pepo spp. texana seedlings at the two true leaves stage were randomly either mock

inoculated, inoculated with a ZYMV isolate, or used as untouched controls. Virus symptoms

uniformly appeared on inoculated plants within 5 days of inoculation. Seven days after virus or

mock inoculation, when the seedlings uniformly showed virus symptoms, half of the plants in

each treatment group (control, mock, ZYMV) were randomly chosen and inoculated with a

virulent field isolate of E. tracheiphila grown for 72 hours on nutrient peptone agar at 28C.

Bacterial inoculations were performed by scraping all bacteria from a single plate into 10ml tap

water in a beaker, mixing gently until homogeneous dispersal of cells, and applying 10μl of the

bacterial suspension to a small break on the petiole of the newest fully expanded leaf.

48 hours after bacterial inoculation, 0.1-0.2 g of the same leaf that received the bacterial

inoculation or the mock (clean water only) inoculation was quickly weighed and flash frozen in

liquid nitrogen. Hormone extraction through vapor phase extraction was performed following

(Schmelz et al. 2003; Schmelz et al. 2004) with modifications. Briefly, frozen tissue was ground

with stainless steel beads in a Genogrinder under liquid nitrogen. Dichloromethane and a weak

acid solution and 100 ng internal standards of synthetic phytohormones were added to partition

50

the phytohormones into an organic layer, which was then dried under house air.

Trimethylsilydizomethane (Sigma-Aldrich, St. Louis, MO) was used to derivatize phytohormones

from carboxylic acids to methyl esters. The remaining solvent was then allowed to evaporate, and

the vial with dried hormones was heated for 2 min at 200C for volatilization under 1L/min

vacuum attached to volatile traps containing 30mg SuperQ. SuperQ traps were eluted with 150μl

dichloromethane and the eluate analyzed by GC-MS with isobutane chemical ionization and

select monitoring of phytohormone ions described in (Schmelz et al. 2004). Final concentrations

of free phytohormones (cis- and trans-JA, SA) were calculated against the initial internal

standards (2H6-SA, dhJA) corrected by original weight of the sample. Data were analyzed with

treatment as the independent variable and either cisJA or SA as the dependent variable in SAS

PROC MIXED and SAS GLM with the model statement Hormone = Disease + Herbivory +

Disease*Herbivory.

Herbivory interactions with ZYMV and E. tracheiphila on defense signaling

To test whether pathogen infection (either bacterial or viral) affects wild gourd induced

responses to herbivory by specialist cucumber beetles, 68 C. pepo ssp. texana seedlings were

assigned for inoculation either as mock-virus, ZYMV, or inoculated with E. tracheiphila that had

been grown on nutrient peptone agar at 28C for 48 hours. Mock inoculations and ZYMV

inoculations occurred when the seedlings had two true leaves, and E. tracheiphila infections were

performed when when plants had 4 true leaves so that ZYMV infected plants and E. tracheiphila

infected plants would show symptoms concurrently. Five days after E. tracheiphila inoculations

when all inoculated plants showed either ZYMV or E. tracheiphila symptoms, half of each group

(mock, ZYMV, E. tracheiphila) were randomly subjected to herbivory from one striped

cucumber beetle confined to the newest fully expanded leaf for 15 hours (overnight). After the

insects were removed, 0.1-0.2 g of leaf tissue adjacent to the herbivory damage was weighed and

frozen, and processed for vapor-phase acid hormone extraction as described above. Raw values

51

(ng/g fresh weight) were ln transformed to meet assumptions of normality and analyzed with both

SAS PROC MIXED and SAS PROC GLM (SAS 2011) with the model statement ln_hormone =

Disease + Herbivory + Disease*Herbivory.

Infection success

Manual leaf inoculations of E. tracheiphila

To test differences in wilt susceptibility between healthy and ZYMV infected plants at

realistic levels of E. tracheiphila exposure, 125 wild gourd seedlings were randomly mock-

inoculated or inoculated with ZYMV. Seven days after viral or mock-inoculations, with viral

symptoms prominent, all plants were inoculated with beetle frass containing E. tracheiphila. E.

tracheiphila inoculations were accomplished by allowing 125 lab - reared Acalymma vittatum a

24hr acquisition access period on symptomatic, E. tracheiphila infected wild gourd plants.

Groups of 10-12 beetles were then immediately placed in petri dishes with a clean cucumber leaf.

After 2 hours of feeding, all the frass from all petri dishes was collected and pooled in 1ml of tap

water within a 1.7ml Eppendorf tube. The tube was inverted several times to disperse the frass

evenly. A small break was made at the base of the petiole of a fully expanded leaf was made, and

10μl of the frass homogenate was applied to the leaf breakage. Symptom appearance was

recorded over time and proportions of wilting, E. tracheiphila infected plants in each treatment

tested with a χ2 test of two proportions in R (R 2008).

To test differences in wilt symptom development between healthy and ZYMV infected

plants at high E. tracheiphila levels, 150 plants were randomly mock-inoculated, inoculated with

ZYMV as above or left untouched. They were then inoculated seven days later with E.

tracheiphila following the same protocol as above, using a mixture of infected beetle frass and in

vitro-grown bacterial colonies in the same water solution that ensured high doses of bacterial

exposure. All but one plant developed wilt symptoms within 17 days and the dates of first wilt

symptoms on the inoculated leaf, second wilting leaf and whole plant wilting (when wilt reaches

52

the primary stem and the whole plant collapses) were recorded over time. The data, excluding one

dead untouched control and three ZYMV inoculated plants without viral symptoms, was ln-

transformed and analyzed with a one-way ANOVA for differences among the three treatments.

Two plants apparently recovered from the disease and were excluded from the whole plant

wilting analysis.

Results

Hormone responses to E. tracheiphila inoculation

Leaves on ZYMV-infected wild gourd seedlings contained significantly more

constitutive and induced salicylic acid compared to mock-virus infected (healthy) and true control

plants (Figure 3.1, Table 3.1). The SA levels in mock and untouched control plants are

statistically indistinguishable, and no induction of SA 24 hr after E. tracheiphila inoculation was

observed. cis-JA and trans-JA were present in negligible amounts in all treatment (cis-JA shown

in Figure 3.1) and were not affected by E. tracheiphila inoculations.

53

3-1a.

3-1b

Figure 3-1. Induced hormone responses of healthy and ZYMV-infected wild gourd to inoculation

with E. tracheiphila

Salicyclic acid is present in significantly higher amounts in ZYMV-infected plants compared to

healthy or E. tracheiphila – infected plants. Inoculation with E. tracheiphila had no effect on SA

levels in healthy plants, but resulted in significant induction of SA in ZYMV-infected plants.

54

Consitutive and induced mock cisJA levels in healthy and pathogen-infected plants is negligible.

Sample sizes Control n= 14; Control + Et n = 14; Mock n = 14; Mock + Et n = 13; ZYMV n =

15; ZYMV + Et n = 13. Table 3-1. Mean +- SE of ng/gMeSA present in foliage of healthy and ZYMV infected plants

exposed to E. tracheiphila

Treatment Mean SE

Control 29.5 110.9

Control + Etrach 39.5 110.9

Mock 32.1 110.9

Mock + Etrach 43.1 115.1

ZYMV 416.5 107.2

ZYMV + Etrach 1299.5 115.1

Table 3-2. ANOVA table of ZYMV * E. tracheiphila interactions in C. pepo texana

Num DF Denom DF F value Pr > F

Disease 1 77 10.91 < 0.0015

E. tracheiphila exposure 2 77 36.22 < 0.0001

Disease*Etracheiphila exposure 2 77 10.21 < 0.0001

Disease by Exposure ANOVA table to assess differences in SA levels among control, mock-virus

infected, and ZYMV - infected plants that were either untouched or inoculated with a virulent

field isolate of E. tracheiphila. Model run in SAS PROC Mixed with model statement SA =

Disease + Etrach + Disease*Etrach.

Inoculations of healthy and ZYMV-infected plants

The first controlled leaf inoculation experiment with infectious beetle frass showed that

there was no significant difference in the overall rate of E. tracheiphila infection success on

ZYMV relative to mock-infected (healthy) plants (Figures 3.2 and 3.3). There was a one-day

delay in the appearance of the first plant with wilt symptoms on ZYMV-infected compared to

mock-infected plants (7 days vs. 6 days post inoculation), but no difference was observed in the

rates of wilt disease, 35% and 40% for mock-infected and ZYMV-infected respectively, at the

end of the experiment (χ2 = 0.1167; P = 0.733).

55

In the second controlled leaf inoculation with infectious frass supplemented with in-vitro

bacteria, 99.32 % (all plants except one) of inoculated plants developed wilt symptoms (Figure

3.3). There was no difference in the timing of symptom appearance on the first leaf (One-way

ANOVA, F 2,143=2.59, P > 0.05) but wilt symptoms appeared on a second leaf on average one day

later in ZYMV infected plants than mock-inoculated or untouched controls (One way ANOVA, F

2,143 = 5.23, P = 0.0065, Figure 3.4), demonstrating that bacterial colonization past the inoculated

leaf was slower at high exposure levels. The total wilting of the whole plant was also slower in

virus-infected plants compared to controls (One way ANOVA, F2,141 = 6.11, P = 0.0029, Figure

3.3)

Figure 3-2. Inoculation success rates with E. tracheiphila on mock-infected (healthy) and

ZYMV-infected plants after exposure to infective frass

Inoculation success rates after 26 days for E. tracheiphila infection on mock-infected (healthy,

n=62) and ZYMV-infected plants (n=65) using frass pooled from 125 beetles allowed a 24hr

56

acquisition period on wilting, E. tracheiphila infected plants that results in less than 50% overall

wilt disease transmission rates

Figure 3-3. Inoculation success rates for E. tracheiphila infection on mock-infected (healthy) and

ZYMV-infected plants with frass and in vitro E. tracheiphila added

Overall rate of E. tracheiphila wilt symptom development and disease progression from the

inoculated to systemic leaves on untouched control (n=49), mock (n=50), and ZYMV – infected

(n=47) plants after inoculation with frass supplemented with bacteria cultivated on peptone agar

plates that achieves close to 100% wilt symptom development. Closed symbols: appearance of

first wilt symptoms; open symbols: Complete collapse of the diseased plant.

57

Figure 3-4. Timing of E. tracheiphila colonization of C. pepo texana measured by time the

second leaf showed wilting symptoms

Mean ± SE number of days post-inoculation until the appearance of wilt symptom on the second

(non-inoculated) leaf in untouched control (n=49), mock (n=50), and ZYMV – infected (n=47)

plants. Letters indicate groups that are significantly different (p-value < 0.05) by a Tukey-Kramer

test.

Figure 3-4. Visual comparison of E. tracheiphila symptom development on a healthy (left) and a

ZYMV-infected (right) wild gourd plants

58

Hormone responses of healthy and pathogen-infected plants to herbivory

Cucumber beetle feeding preferences for pathogen-infected plants (either ZYMV or E.

tracheiphila –infected) suggests that there may be nutritional, physical, or chemical differences

that make pathogen-infected plants more palatable, and defense signaling may play a role in

inducing these changes. In this study, cisJA levels in all undamaged plants were measured at very

low levels, but in response to herbivory, there was a significant induction of cisJA within all

disease treatments (Figure 3.5a, Table 3.3). Between disease treatments, herbivory induced

significantly more cisJA on E. tracheiphila infected plants compared to ZYMV or mock (Table

3.4). No difference was observed in the induced levels of JA between healthy and ZYMV-

infected plants (Figure 3.5a, Table 3.3). As in Figure 3.1, SA levels are significantly induced in

ZYMV compared to E. tracheiphila – infected and healthy plants, and herbivory did not affect or

interact with SA levels (Figure 3.5b, Table 3.5).

3.5a

59

3.5b

60

Figure 3-5. Herbivory effects on cis-JA levels for healthy, ZYMV, and E. tracheiphila infected

plants

Hormonal response of healthy mock inoculated, E. tracheiphila inoculated, and ZYMV-infected

plants 15h after exposure to herbivory relative to non-herbivorized plants. (a) Mean SA

production ± SE ; (b) Mean cis-JA (grey bars) and trans-JA (black bars) ± SE.

Effect Num DF Denom DF F Value Pr > F

Disease 2 67 12.53 < 0.0001

Herbivory 1 67 102.32 < 0.0001

Disease*Herbivory 2 67 8.7 0.0004

Table 3-3. ANOVA of Disease, Herbivory, and Disease*Herbivory effects on cisJA production

in wild gourd leaves

Disease, herbivory, and the interaction of disease*herbivory are all significant factors affecting

cisJA. cisJA levels were ln transformed for normality and analyzed in SAS PROC GLM =

Disease + Herbivory + Disease*Herbivory

cisJA Mean SE

Etrach 9.7 38.2

Etrach + H 332.03 41.9

Mock 17.31 36.7

Mock + H 47.1 38.3

ZYMV 2.4 36.7

ZYMV + H 78.9 9

Table 3-4. Mean +- SE cisJA present in healthy and pathogen infected leaves that are undamaged

and damaged by cucumber beetles

Mean and SE ng cisJA/g fresh weight levels of all treatments: Non-transformed (raw) values were

used to compare constitutive and induced cisJA levels in E. tracheiphila – infected, ZYMV –

infected, and healthy (mock) infected plants exposed to herbivory. Data were generated with SAS

PROC MIXED = All Treatments

JA is induced in response to herbivory in both healthy and pathogen-infected plants, with

significantly more JA present in E. tracheiphila herbivorized leaves compared to mock or ZYMV

herbivorized leaves. Herbivore damaged E. tracheiphila leaves and undamaged ZYMV leaves

show elevated levels of the fatty acids linolenic and linoleic acids, and these compounds are not

elevated in either mock treatment.

61

Table 3-5. ANOVA for salicylic acid in pathogen-infected and healthy plants

Disease is a significant factor explaining variation in SA levels, but Herbivory and the interaction

between Herbivory*Disease do not significantly affect SA levels

Num DF Denom DF F Value Pr > F

Herbivory 1 66 1.7 0.197

Disease 2 66 21.5 < 0.0001

Herbivory*Disease 2 66 1.14 0.3261

Discussion

Salicylic acid mediated systemic acquired resistance has been documented in cucumber

in response to viral, bacterial, and fungal challenge (Kuć 1982; Hammerschmidt 1999). Here, we

find that despite higher constitutive and induced salicylic acid levels in ZYMV infected plants

relative to healthy plants (Figure 3.1a), healthy and ZYMV-infected wild gourds are equally

susceptible to infection by E. tracheiphila in both low dose (infectious frass only, Figure 3.2) and

high dose (infectious frass supplemented with in-vitro bacteria, Figure 3.3). Although healthy and

virus-infected plants had the same proportions of wilt development, we observed a one-day delay

in the first appearance of wilt symptoms on a ZYMV-infected plant compared to a healthy plant

in the low bacteria infection experiment. When naturally occurring amounts of E. tracheiphila in

frass are supplemented with in vitro bacteria, there is a significantly slower progression of the

disease with a one day delay in the appeared of wilt symptoms on a second leaf and a delay in the

complete collapse of virus infected plants (Figure 3.4). These results suggest that SAR induced by

ZYMV possibly delays disease progression within virus-infected plants at high exposure levels,

but does not prevent co-infection with E. tracheiphila.

While bacterial interactions with plant defense signaling networks vary widely between

specific plant-pathogen interactions, some bacterial pathogens explicitly exploit cross-talk in host

62

signaling networks. Some strains of the model plant pathogen P. syringiae produce coronatine, a

JA mimic that suppresses SA signaling (Uppalapati et al. 2007). Other gene products have been

found to suppress SA signaling directly, such as P. syringae avrE genes (DebRoy et al. 2004).

The fire blight pathogen E. amylovora contains an avrE homologue DspA/E (Disease-specific

region) that is required for pathogenicity on hosts (Bogdanove et al. 1998a; Bogdanove et al.

1998b). This gene (among other potential candidates, Shapiro et al in prep), which was also found

in the E. tracheiphila genome [ETR 3867], might also function as an SA signaling suppressor for

both E. tracheiphila and E. amylovora.

E. tracheiphila inoculation does not induce SA on healthy plants shortly after inoculation

(Figure 3.1a), or on leaves five days post inoculation when wilt symptoms had developed (Figure

3.5b). SA induction after E. tracheiphila inoculation was only observed in virus-infected plants

that had constitutively higher SA levels. Since many bacterial pathogens directly suppress host

defenses, it is possible that E. tracheiphila suppressed the induction of SA signaling in healthy

control plants. Because virus-infected plants with high SA induction experienced only a slight

delay in wilt symptom progression without any change in the final outcome of the disease, the SA

pathway might not have a strong impact on E. tracheiphila disease progression—at least under

laboratory inoculations—or only slows systemic bacterial movement through xylem vessels, but

does not inhibit bacterial establishment in xylem.

Pathogen – induced effects on plant physiology may also affect interactions with insect

herbivores. Cucurbitacins (toxic oxygenated triterpenes) are induced in cucurbit plants by feeding

damage and are sufficient to deter herbivory from most herbivores, but cucumber beetles have

been shown to feed preferentially on induced leaves (Tallamy 1985). In a previous study (Shapiro

et al, 2012), striped cucumber beetles preferred feeding on leaves from either ZYMV or E.

tracheiphila infected plants relative to mock-infected, healthy plants. Constitutive JA levels are

extremely low in all treatments (Figure 3.1b, Figure 3.4a), and beetle herbivory induces JA on

63

both healthy and pathogen infected plants, although significantly more JA is induced by

herbivory on E. tracheiphila - infected plants compared to either healthy or ZYMV – infected.

Healthy, wilting, and ZYMV-infected plants all had higher JA levels after cucumber beetle

herbivory. However, E. tracheiphila-infected and ZYMV-infected treatments had opposite

patterns of phytohormonal responses, with higher SA production in virus treatments compared to

E. tracheiphila treatments, while herbivory-induced JA was higher in E. tracheiphila treatments.

This antagonistic pattern suggests that E. tracheiphila inhibition of SA production could possibly

have favored the induction of JA as a result of cross-talk between these two signaling pathways,

and the higher SA levels in virus – infected plants may inhibit the induction of JA in ZYMV –

infected plants. Virus infection can also alter plant nutritional content (Belliure et al. 2005;

Belliure et al. 2010), and possible nutritional changes from virus infection may be more important

than JA mediated defenses in feeding preference for ZYMV – infected plants by striped

cucumber beetles (Tallamy & Krischik 1989; McCloud et al. 1995; Huang et al. 2003).

Our results show that the viral pathogen ZYMV and the bacterial pathogen E.

tracheiphila have divergent effects on plant defense hormone induction in both undamaged and

herbivore-damaged plants. While ZYMV infection resulted in a large induction of SA, the

absence of SA induction in undamaged plants and high JA levels in beetle damaged plants with

E. tracheiphila infection suggests that E. tracheiphila interferes with SA signaling. After

inoculation onto healthy plants, E. tracheiphila appears to be suppressing SA signaling and

presumably some SA mediated defenses, which include PR protein accumulation and

lignification of cell walls (Gessler & Kuc 1982; Mucharromah & Kuc 1991). While E.

tracheiphila does not induce SA after inoculation on healthy plants while ZYMV does, it is

notable that inoculation rates with E. tracheiphila are not suppressed on ZYMV infected

compared to healthy plants. However, wilt disease progression is slower on ZYMV – infected

plants at high inoculation levels, suggesting that ZYMV infection has a negative effect on E.

64

tracheiphila movement in the plant, but that SA mediated plant defenses may not be critical in the

establishment of E. tracheiphila infection in wild gourds. The slight delay in wilt symptom

development on ZYMV – infected plants might have consequences on infection probabilities or

rates of symptom development when transmission opportunities of E. tracheiphila consist of

daily exposure to low doses of bacteria deposited by many beetles daily in the field, conditions

that are impossible to replicate in the lab. Overall, antagonistic interactions in plant defensive

signaling pathways appear to be conducive to E. tracheiphila infection progression and beetle

feeding preferences. Furthermore, attenuation of floral volatile emissions from virus-infected

plants is associated with a reduction in recruitment of cucumber beetles that transmit E.

tracheiphila to wild gourd (Shapiro et al, in press). A small negative effect of ZYMV on E.

tracheiphila movement in planta at high inoculation levels through direct pathogen interactions

or antagonistic effects on defense hormones would thus have contributed only in a limited way to

differences in wilt disease dynamics observed between healthy and virus infected plants in the

field. These limited direct effects support previous findings that, in this system, indirect viral

effects through the attenuation of floral volatiles and reduced beetle vector recruitment is the

major contributor to the observed field disease dynamics.

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67

Chapter 4

Colonization dynamics of an insect vector by a bacterial phytopathogen

Abstract

Erwinia tracheiphila, the causal agent of bacterial wilt of cucurbits, is predominately transmitted

in the Eastern US by the striped cucumber beetle Acalymma vittatum (Luperini: Chrysomelidae:

Coleoptera), but the colonization dynamics of A. vittatum by E. tracheiphila are not well

understood. Here, we develop a quantitative Real-Time PCR method using a TaqMan probe

specific to an E. tracheiphila outer membrane protein (OmpA) to examine the colonization of A.

vittatum by E. tracheiphila and to describe the quantitative dynamics of bacterial colonization of

the beetle digestive tract and shedding in frass over time. Our results show that acquisition of E.

tracheiphila does not differ between short-term (3hr) and long-term (24hr) acquisition access

periods (AAP), but that long-term retention increases for the longer AAP. The amount of E.

tracheiphila shed in frass is significantly higher 0 and 28 days post acquisition compared to 5

days, suggesting successful E. tracheiphila colonization of the hindgut determines long term

ability to transmit from infected to healthy hosts. Inoculation experiments confirm that the

amount of bacteria shed in frass significantly affects the probability of transmission to a wild

gourd seedling. Fitness experiments fail to find a cost or benefit to E. tracheiphila exposure for

cucumber beetle vectors. A better understanding of pathogen-vector interactions will allow for

improvement of control systems in agricultural settings, which currently depends on broad-

spectrum chemical control of vectors or expensive mechanical barriers to prevent insects from

contacting plants.

68

Introduction

For insect-borne pathogens, efficiency of dispersal from infected to healthy hosts is

influenced by interactions with the insect vector. However, detailed knowledge of pathogen-

vector interactions, and how these interactions drive disease dynamics in natural systems, are

often poorly understood. Arthropod transmitted plant pathogens that are able to persistently

colonize herbivorous insects as alternate hosts can continually contact new, healthy plant hosts

through the foraging behavior of the herbivorous vectors for long periods after initial acquisition

(Eigenbrode et al. 2002), and the vast majority of plant pathogens are viruses obligately

transmitted by homopteran insects. While many bacterial strains cause important plant diseases,

they are numerically fewer, and most are mechanically spread through the environment

(citations). Very few plant pathogenic bacteria are obligately insect vectored, and colonization

dynamics of vectors and correlation with pathogen dispersal are often under-investigated

(citations). Here, we investigate the colonization dynamics of the causal agent of bacterial wilt of

cucurbits, Erwinia tracheiphila Smith (Enterobacteriaceae), within its specialist insect vector, and

how vector colonization contributes to host plant exposure.

Cucumber beetles (Coleoptera: Chrysomelidae: Luperini) have been recognized as

vectors of E. tracheiphila for more than a century (Smith 1911). E. tracheiphila replicate in

xylem and secretes an extracellular polysaccharide (EPS) that prevents the passage of xylem sap,

which causes vessel occlusion and characteristic wilting symptoms (Watterson 1971; Goodman &

White 1981). Bacterial wilt infection is usually fatal in most wild and cultivated cucurbits once

symptoms appear (Sasu et al. 2009a), and can cause major economic losses in cultivated fields

(Brust 1999). Quantification of E. tracheiphila within beetles was first attempted with fuschin

69

staining (Leach 1964), which indicated so few bacteria in the beetle’s intestinal tract that the

authors proposed the since-disproven (de Mackiewicz et al. 1998) hypothesis that E. tracheiphila

have another environmental reservoir (Leach 1964). Previous work using bacteria-smeared

cotyledon disks as inoculation sources to beetles and DAS-ELISA and immunoperoxidase

localization as a detection method has suggested stronger fluorescence in the hindgut 10 and 30

day post acquisition period compared to 3 day post acquisition (Garcia-Salazar et al. 2000b), but

another study failed to detect E. tracheiphila in beetle frass with standard PCR 6d post acquisition

(Mitchell & Hanks 2009).

In this study, we developed TaqMan probes specific to a single copy E. tracheiphila outer

membrane protein gene (ompA) and the eukaryotic ribosomal 18S gene as a normalizing gene to

compare Erwinia tracheiphila acquisition and retention rates as a function of acquisition access

period (AAP) through natural herbivory on infected plants. Relative E. tracheiphila levels in frass

and entire beetles were determined at several time points post acquisition access period, as well as

time-dependent changes of E. tracheiphila present in the frass and in whole beetles at 0, 5, and 28

days after an acquisition period. We then conducted fitness experiments to understand how

feeding on wilt diseased plants affects cucumber beetle oviposition and longevity, and a series of

inoculation experiments were performed to determine how elapsed time post acquisition affects

rates of transmission of E. tracheiphila via frass to healthy wild gourd Cucurbita pepo ssp. texana

seedlings.

Materials and Methods

Beetle Rearing

A clean, E.tracheiphila-free striped cucumber beetle colony was maintained following

Mitchell (2009). Field captured adult beetles were kept in 1 ft x 1 ft Bioquip mesh cages (cat

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#1466A). Pro-Mix potting soil (Premier Horticulture Reviere Du Loup, Quebec, Canada) is

provided as a water source and as an oviposition substrate. Beetles were fed 3x per week with

leaves and flowers of ‘Raven’ C. pepo. The potting soil with eggs was transferred weekly to a 6L

plastic bin rearing container. Root-feeding larvae were continuously supplied with sprouted C.

pepo ‘Raven’ seedlings until pupation. Newly eclosed adults were removed from the rearing

container and placed with adults from the same weekly age cohort in 1ft x 1ft Bioquip mesh

cages.

DNA extraction from beetle frass

Two wild gourd Cucurbita pepo ssp. texana plants were infected with a local field isolate

of E. tracheiphila by the colony-stab procedure (Mitchell & Hanks 2009). Both plants were

placed together in a 1ft x 1ft Bioquip mesh cage (cat #1466A) when most leaves showed wilt

disease development. Seventy-five 5-day old A. vittatum beetles from our E. tracheiphila-free lab

colony that had been starved for 48 hours were placed in the same cage with the infected plants.

Groups of 23 beetles were removed after 3hr and 24hr acquisition access periods. Frass was

collected immediately by placing beetles individually in 0.7ml Eppendorf tubes until frass was

visible inside the tube (~2 hours). The beetles were then kept individually in petri dishes, and

transferred 4x weekly to new petri dishes with water soaked cotton and a clean cucumber leaf as

food to prevent re-inoculation. Frass was collected from each beetle immediately after removal

from the cage with the host plant, and then again at 5 days and 28 days post exposure. DNA was

then immediately extracted from the frass using prepGem Bacteria extraction kits (ZyGEM Corp

Ltd. Hamilton, New Zealand) following label instructions scaled from 100ul to 55ul extractions.

Quantitative Realtime PCR

5l of DNA was used as template in triplicate 20 μl RealTimePCR reactions with 10mM

primers and probes and ABI TaqMan® Gene Expression MasterMix (cat #4369016). Primers and

71

probe were designed to anneal to conserved regions of a single copy gene encoding an outer

membrane protein A (EtOMPA) of E. tracheiphila, such that all published strains of E.

tracheiphila are indiscriminately detected (Et73: GGCGATCACGACACAGTTGT, Et140:

CAGTTTTTGGTCAGGGCATACTC) P94: TCCCCTCTGGCAGCCATAGGTGC, Probe:

TCCCCTCTGGCAGCCATAGGTGC). 18S was used as a normalizing gene for the total amount

of DNA in each sample (18S F: CGGCTACCACATCCAAGGAA; 18SR:

TGCTGGCACCAGACTTGCCCTC; 18S Probe: CGCAAATTACCCACTCCCGGCAC)

(Broackes-Carter et al. 2002). Standard curves were generated for both EtOMP and 18S using 5

serial dilutions of DNA extracted from pure bacterial culture for the EtOMP curve and DNA

extracted from clean colony beetles for 18S. The cycling program consisted of an initial

denaturation step at 95°C for 3 minutes, and 40 cycles of denaturation at 95°C for 10 seconds,

and annealing/extension at 55°C for 30 seconds and was carried out on an ABI Prism 7900 HT

sequence detector (Applied Biosystems, Foster City, CA). Fluorescence reads were taken at the

end of each annealing/extension step. We compared the sensitivity and accuracy of this Taqman

assay with PCR reactions using the same primers but detecting the amount of product via the

fluorescence of SYBRgreen. CT values did not differ by more than 1 cycle between the two

methods. Both detection methods identified beetles having fed on E.tracheiphila-infected plants

correctly. The TaqMan probe assay did not show fluorescence signal for beetles that had not been

exposed to E. tracheiphila (negative control beetles). On the other hand there were sporadic

fluorescence signals for the negative control beetles when analyzed by the SYBRgreen assay and

only after close inspection of the melting curves could those samples be pronounced negative. In

short, the PCR assay using Taqman probes is as sensitive as the previously used SYBRgreen

assay, but it eliminates the ambiguity of inspecting melting curves and it is faster (because of the

omission of the melting curve in the actual PCR run).

72

DNA extraction from whole beetles

In a separate experiment 75 beetles from a clean lab colony that had been starved for 48hr

were allowed to feed for24hr on symptomatic E. tracheiphila-infected plants and then maintained

as described above. At three time points post-acquisition (0, 5 days, 28 days) 25 whole beetles

were ground individually under liquid N2 in a Genogrinder (OPS Diagnostics, LLC). DNA was

extracted using 100μl volume prepGem Bacteria following label instructions. 5l of this DNA

was used in triplicate qPCR reactions for 18S and EtOMP as described above.

Erwinia tracheiphila Transmission Potential

To determine whether E. tracheiphila levels in frass affect transmission potential, 150

beetles were fed on two infected plants (as described above). Frass from 100 randomly selected

beetles was collected, pooled, and homogenized in tap water from the beetles at 0, 5, and 28 days

post acquisition. 10μl of homogenate was applied to a small break in the leaf petiole of C. pepo

ssp. texana seedlings at 14 days (2 fully expanded leaves). Symptom development was recorded

3x weekly.

Erwinia tracheiphila Exposure Effects on Acalymma vittatum Fitness

Oviposition Rate and Longevity To test how exposure to E. tracheiphila through feeding on

symptomatic plants affects A. vittatum fitness, a series of experiments was performed to test

oviposition rates, egg development time and hatch rate, and longevity. Seventy-five adult beetles

that had eclosed within 2-3 days were separated by sex. Two mesh 1ft x 1ft Bioquip cages (cat

#1466A ) each contained a symptomatic, E. tracheiphila infected plant, and two more cages each

contained a healthy, mock-inoculated plant. Half of the newly eclosed females and half of the

males were separately placed in the two cages with the infected plants, and the other half were

separately placed in the cages with healthy (mock-inoculated) plants. Beetles were allowed to an

96 hr AAP on infected or healthy plants. One male and one female of the same plant treatment

73

were then placed in petri dishes and allowed to mate for 48 hours. Females were then kept

individually in petri dishes with moistened cotton as an oviposition substrate and 3x3cm

cucumber leaf as a food source. Females were re-mated 14 days after the first mating because

stored sperm quality and subsequently egg quality declines after this period. Females were

transferred to new, clean petri dishes with new food and oviposition substrates 3x weekly. Rates

of female survivorship and oviposition were recorded. The experimental insects were kept in an

incubator set at 25C with 14:10 L/D cycle.

Egg Hatch Rate and Developmental Time In a separate experiment, newly-eclosed beetles

were divided by sex and randomly assigned to feed on a healthy (mock innoculated) C. pepo ssp.

texana seedling or a wilting E. tracheiphila infected seedling for 96 hours (as above). One female

and two male beetles were then placed in petri dishes and allowed to mate for 48 hours. Females

were then placed individually in petri dishes with moist potting soil as an oviposition substrate

(Quebec supplier) and 3x3cm cucumber leaf provided as food. The first 17-27 eggs oviposited by

each female were collected from the soil in the petri dish and then placed in 1 gallon black pot

with four C. pepo 'Raven' seedlings provided as food for the rootworms. 'Raven' seedlings were

replenished as needed. The rate of adult emergence from each pot was recorded. Pots with

seedlings and eggs were kept in a growth chamber set at 25C/22C and 14:10 day:night cycle.

Results

Frass Acquisition and Retention Rates

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Of the 138 frass samples collected from beetles at 0, 5, and 28 days after feeding for

either 3 or 24 hrs on E. tracheiphila infected plants, only 124 samples yielded usable DNA . The

remaining samples that gave no product for either gene were not included in the analysis. A chi-

square test reveals that the probability that the frass will contain E. tracheiphila immediately after

feeding on infected plants is independent of the acquisition access period (3 hr vs. 24 hr) (χ2 =

0.0341, df = 1, P = 0.8535) (Fig 2.1). At five days post acquisition, there are significantly more

beetles in the 24hr acquisition group that are E. tracheiphila-positive compared to the 3hr

acquisition group (χ2 = 6.4736, df = 1, P = 0.01095), and at 28 days post acquisition there is again

a significantly higher proportion of E. tracheiphila-positive beetles in the 24hr acquisition group

compared to the 3hr exposure group (χ2 = 7.621, df = 1, P = 0.0058) (Figure 4.1). Therefore, the

time period of acquisition does not significantly affect initial acquisition rates but does

significantly affect the probability of a beetle becoming a persistent carrier.

Figure 4-1. Frass acquisition and retention rates

1A: Chi-square tests of the percentages of beetles with frass positive for Erwinia tracheiphila

detected immediately, 5 days, and 28 days post AAP for a 3hr or 24hr acquisition access periods.

75

Whole Beetle Acquisition and Retention Rates

In the second experiment, 72 of the 75 whole beetles were unambiguously scored as

positive or negative for E. tracheiphila after feeding for 24 hrs on E. tracheiphila infected plants.

Three beetles were not scored due to a failed DNA extraction determined by lack of product for

both 18S and EtOMP. There is a moderately higher percentage of E. tracheiphila-positive beetles

immediately (82%) and at 5 days (81%) than at 28 days (64%), but the proportion of E.

tracheiphila-positive beetles is not significantly different between any time points (0:5days χ2 = 0,

df = 1, P = 1; Immediate:28 days χ2 = 1.4749, df = 1, P = 0.2246; 5 days: 28days χ

2 = 1.9056, df =

1, P = 0.1675) (Figure 4.2). The frequency of E. tracheiphila positive beetles from the whole

beetle experiment is statistically indistinguishable from the proportion of E. tracheiphila positive

beetles in the 24 hr acquisition group in the frass experiment at the 0 and 28 day time points, but a

significantly higher proportion from the whole beetle experiment are positive compared to frass at

5 days (0 days frass: 0 days beetle χ2 = 0.4312, df = 1, P = 0.5114; 5 days frass:5 days beetle χ

2 =

3.9305 , df = 1, P = 0.0472; 28 days frass: 28 days beetle χ2 = 0, df = 1, P = 1). In both the whole

beetle and 24hr feeding experiments, more than 80% of beetles acquired E. tracheiphila through

feeding on infected plants, and more than 60% retained it for the duration of the experiment

(Figures 4.1, 4.2).

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Figure 4-2. Whole beetle acquisition and retention rates

Chi-square tests of the percentages of whole beetles positive for Erwinia tracheiphila detected

immediately, 5 days, and 28 days post AAP for a 24hr acquisition access periods.

Whole Beetle Quantitative Dynamics

To achieve a quantitative understanding of changes in bacterial titre during long-term

colonization of A. vittatum by E. tracheiphila, we used the amount of the single copy gene

ETOMP as a measure for the amount of Erwinia present and the amount of 18S as a normalizing

gene for the amount of total DNA present. The underlying assumption is that bacterial DNA

contributes only negligibly to the total amount of DNA present in whole beetles that fed on

symptomatic, infected plants and that dead bacteria contribute negligible amounts of EtOMP to

total bacterial DNA. Bartlett’s test for equal variances of Et/18S ratios rejects the null hypothesis

of equal variances (Bartlett’s K2 = 175.93; df=2, P ≥ 0.005), so a non-parametric test was used to

compare relative E. tracheiphila levels in whole beetles 0 days, 5 days, and 28 days post

acquisition. Kruskal-Wallis test of relative bacteria levels at the three time points showed they are

not statistically different (χ2 = 2.63, df = 2, P = 0.2676). Re-testing for difference in median

77

bacterial levels after the removal of two outliers representing high relative bacterial levels

immediately after herbivory did not change the test result (χ2 = 3.8194, df = 2, P = 0.1481). We

note that the two outliers with the largest Et/18S ratio and the four highest absolute relative

bacterial levels occur in the first time group of beetles analyzed immediately after exposure,

further supporting the hypothesis that beetles are potentially exposed to highly varying amounts

of E. tracheiphila through natural herbivory on infected plants (Figure 4.3). While the median

relative levels of E. tracheiphila in whole beetles are not significantly different at the three time

points measured, the variance is significantly different. Immediately after acquisition, there is a

wide variance in relative levels of E. tracheiphila present. By 28 days post acquisition, the

median amount of bacteria has not changed but the variance is significantly narrower, indicating

that bacterial population levels in the gut lumen converge toward an equilibrium population range

in beetles that have been successfully colonized (Figure 4.4).

Frass Quantitative Dynamics

The amount of bacteria shed in frass is a factor determining the level of exposure of

healthy host plants to the wilt pathogen, so we sought to understand the quantitative and temporal

dynamics of bacterial levels in beetle frass. In plant hosts, E. tracheiphila form localized

blockages in xylem vessels and are thought to be heterogeneously distributed throughout the

vasculature. To assess whether this could affect the amount of bacteria that beetle vectors are

exposed to through feeding on symptomatic plants, Levene’s test for equal variances was applied

to compare the ranges of bacterial levels present in frass 0, 5, and 28 days post acquisition. There

is a significantly wider range of relative bacterial levels present in frass at 0 days and 28 days

compared to the amount of bacteria present 5 days post acquisition (Test statistic = 3.74, P =

.031) (Figure 4.4). We applied a repeated measures GLM in SAS Proc Mixed (SAS 2011) to

measure the effects of AAP (3 vs. 24 hr) and time since acquisition (0, 5, 28 days) on the amount

78

of E. tracheiphila relative to total plant DNA in the frass. AAP was not significant (F = 0.61, P =

0.4427) so the 3 hr and 24 hr AAP groups were pooled for further analysis of the relative amount

of bacteria in frass at three time points post acquisition (0, 5, or 28 days). Frass was repeatedly

collected from the same insects, so a repeated measures model was used to compare the bacterial

levels in frass from. We found that while the amount of E. tracheiphila shed in frass was not

significantly different between acquisition groups, time post acquisition is a significant factor (F

= 4.92, P = 0.0241). Individual comparisons show there is significantly more E. tracheiphila in

frass immediately compared to 5 days (Kruskal-Wallis test: H = 6.99, df = 1, P = 0.008) and 28

days compared to 5 days (H = 14.12, df = 1, P ≥ 0.005), and that there is marginally more relative

E. tracheiphila in frass at 28 days compared to immediately (H = 3.14, df = 1, P = 0.076) (Figure

4.3). The model statement is EtOMP/18S = AAP + Time post acquisition + (AAP*Time post

acquisition); Repeated Time/Beetle using the spatial power covariance structure (SAS 2011).

Figure 4-3. Quantitative dynamics of frass in whole beetles vs. frass

Comparison of the relative amounts of bacteria detected in frass and whole beetles immediately, 5

days, and 28 days post acquisition. For whole beetles, Kruskal-Wallis test was applied to the

model Et = Time. For frass, Et = AAP + time + AAP*time; repeated time.

79

Figure 4-4. Distribution of E. tracheiphila in frass over time

Distribution (variance) of relative E. tracheiphila/totalDNA ratios in frass immediately, 5 days,

and 28 days post acquisition. Levene’s test for equal variances of bacterial levels in frass shows

the variance is lower at 5 days compared to the other two time points (Test statistic = 3.74, P =

.031).

Figure 4-5. Distribution of E. tracheiphila in whole beetles

Distribution (variance) of relative E. tracheiphila/totalDNA ratios in whole beetles immediately,

5 days, and 28 days post acquisition. Bartlett’s test for equal variances of Et/18S ratios shows the

variance is significantly larger immediately compared to both 5 days and 28 days after an

acquisition access period (Bartlett’s K2 = 175.93; df=2, P ≥ 0.005)

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Inoculation Trials

We performed a series of transmission experiments to examine how the amount of

bacteria in frass affects transmission potential and inoculation success, and found that inoculation

success rates correlate with the amount of bacteria detected in frass. Chi-square tests for

difference in two proportions in R was applied to analyze the different inoculation success rates

of C. pepo ssp. texana seedlings using frass collections from a group of 100 A. vittatum 0, 5, and

28 days post acquisition. There is a significantly higher inoculation success rate with frass

collected 0 days and 28 days post acquisition compared to frass collected 5 days post acquisition

(0:5 days χ2 = 42.812, df = 1, P < 0.005; 5 days:28 days χ

2 = 25.967, df = 1, P < 0.005). The

difference in inoculation success rates with frass collected 0 days and 28 days post acquisition is

not significant (χ2 = 1.348, df = 1, P = 0.245) (Figure 4.6).

0 days 5 days 28 days

Wilt Symptoms 44 3 22

Total (n) 84 76 54

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Figure 4-6. Inoculation success rates with frass collected 0, 5, and 28 days after AAP

Inoculation experiments were used to show that infection success correlates with the number of

E. tracheiphila cells shed in frass at different time points post exposure

Erwinia tracheiphila exposure effects on Acalymma vittatum fitness

Prolonged acquisition access periods on wilting E. tracheiphila infected plants did not

significantly affect striped cucumber beetle longevity, oviposition rates, or adult emergence rates.

In the oviposition experiment, 10/13 females that fed on the mock inoculated plants and 11/14

females that fed on the E. tracheiphila infected plants survived for the 32 day duration of the

experiment. Two females from the E. tracheiphila exposure group died during the experiment

(the first female died 2 days after feeding, the second died 23 days after feeding) and three

females from the mock group died (one died 9 days post feeding and two died 20 days post

feeding). Females that oviposited fewer than 20 eggs total (two from the mock group and two

from the E. tracheiphila group) were excluded from the statistical analysis of oviposition rate but

not longevity. The total number of eggs oviposited by females in each group was not different (1-

way ANOVA; F1,25 = 0.32; P = 0.577). In the egg development experiment, there was no

difference in the percentage of adult emergence from eggs produced by females fed either on

healthy or wilting seedlings (1-way ANOVA, F1,22 = 0.07, P = 0.791).

Discussion

Microbes that persistently colonize vectors can be carried through heterogeneous

landscapes and over long time frames. This ability to persistently colonize multiple environments

(insect vector and primary host) can be an important factor affecting transmission dynamics and

disease persistence in host populations. Here, we show Erwinia tracheiphila can be both

mechanically transmitted with no latent period after an acquisition period, and persistently

82

transmitted for up to 28 days, which is approximately the life of the adult beetle (Ellers-Kirk &

Fleischer 2006). While many enteric phytopathogens can colonize insects (Hinnebusch 1996;

Basset et al. 2000; Ffrench-Constant et al. 2003; Grenier et al. 2006), E. tracheiphila is unique

among this group in that it is the only pathogen known to be completely dependent on an insect

vector for dissemination from infected to healthy hosts. Closely related plant pathogenic Erwinia

ssp. have only transient, external, and non-specific associations with insect vectors (Hildebrand et

al. 2000; Kube et al. 2010b).

Despite the importance of E. tracheiphila colonization of A. vittatum for transmission

over extended time periods (de Mackiewicz et al. 1998), little was known about quantitative and

temporal dynamics of E.tracheiphla-A.vittatum interactions,or how these interactions affect host

plant exposure to infective frass. Previous investigations have produced conflicting data about the

dynamics of long-term colonization of cucumber beetles by E. tracheiphila (Garcia-Salazar et al.

2000b), and the effectiveness of frass as a long-term pathway of transmission (Mitchell & Hanks

2009). To address this shortcoming, we developed a qPCR protocol using TaqMan probes to

determine overall acquisition and retention rates when beetles are exposed to E. tracheiphila

through natural herbivory on wilting plants, and to quantify the amount of E. tracheiphila relative

to the 18S normalizing gene in whole beetles and frass to better understand the process of

bacterial colonization of beetle vectors.

E. tracheiphila form occlusions that block water passage in host plants, indicating a

heterogenous distribution of bacteria within xylem vessels that is reflected in the large variance of

bacterial levels observed in whole beetles and in frass immediately after natural herbivory on

infected plants (Fig 3, 4). The length of AAP significantly affects the probability of becoming an

E. tracheiphila-positive vector but not the amount of bacteria shed in frass once the beetle is

colonized. The high initial acquisition but low long term retention of E. tracheiphila by beetles in

the 3hr AAP suggests that adhesion of E. tracheiphila to the beetle’s digestive tract is inefficient,

83

but E. tracheiphila that do attach to the digestive tract and begin replicating follow the same

population trajectory regardless of the length of the acquisition period. Persistently transmitted

bacterial pathogens must be able to attach to, replicate within, and detach (shed) from insect

vectors in order to be transmitted to new hosts. Comparisons of the relative quantities of bacteria

in whole beetles and in frass immediately and then at several time points post acquisition

measured in these experiments support a model of complex colonization dynamics of E.

tracheiphila in beetle vectors (Berk et al. 2012).

To assess how the changing bacterial levels in frass might affect broader disease

dynamics, a series of inoculation experiments was performed. Transmission results show that

infection success rates correlate to bacterial levels in frass (Fig 5), with significantly higher

inoculation success with frass collected from beetles 0 days and 28 days post acquisition

compared to frass collected 5 days post acquisition. In these experiments, direct inoculations of

infective frass into leaf wounds on small seedlings resulted in a maximum of 50% infection rates.

Cucurbita ssp. are more resistant to wilt infection as they mature (Brust 1997a), therefore

sustaining epidemics in field settings is likely dependent on having high proportions of infective

vectors often contacting healthy plants. In a field setting, many factors are likely to affect E.

tracheiphila disease dynamics. In addition to persistence within vectors, insect preference and

orientation towards healthy and infected plants influence host exposure and pathogen

transmission to healthy plants (Sisterson 2008). Because plants with bacterial wilt disease usually

die within 7-14d after the onset of symptoms, there is limited time for acquisition of the pathogen

by the vector. Our recent work (Shapiro 2012) has shown, however, that cucumber beetles are

preferentially attracted to the volatiles produced by E. tracheiphila infected plants and feed more

on infected plants than healthy plants. Consequently the beetles are more likely to acquire the

pathogen than would be predicted by the number of wilt diseased plants at any given time in the

population. The data presented here show that once the pathogen is acquired, the vector can

84

transmit E. tracheiphila throughout much of its life (and well after the diseased plant from which

it acquired the pathogen is dead).

Infective frass must directly contact herbivory wounds or floral nectaries in order for E.

tracheiphila to access the vasculature and for symptoms to develop (Smith 1915). C. pepo ssp.

texana can become infected through leaf (Smith 1915) (Mitchell & Hanks 2009) or floral nectary

exposure (Sasu et al. 2010a). However, it is possible that both the amount of exposure and

infection efficiency through leaves and flowers are different. Wild gourd may be more susceptible

to E. tracheiphila infection through leaves, however phloem exudates from leaf wounds can gum

beetle herbivore mouthparts and discourage feeding (McCloud et al. 1995; Eben 2007), so it is

likely that Cucurbita plants receive more exposure through floral nectaries. Symptom

development on cucurbit seedlings leaf-inoculated with E. tracheiphila varies by growth stage

and cultivar (Brust 1995, 1997) and inoculum concentration (Brust 1997b). Previous single-beetle

inoculation studies (Rand 1920, Brust 1997b, Fleischer 1999) consistently result in low rates of

wilt symptom development. More than 95% of healthy wild gourd plants in a field experiment

were found to have E. tracheiphila near the nectaries, but fewer than 20% of plants in the field

presented with wilt symptoms. Based on these previous investigations and the frass inoculation

experiments in this study, we hypothesize that E. tracheiphila in frass from a single insect is often

not enough to produce infection on a host, especially for large plants. Repeated contacts with

bacteria from frass from infective vectors may be an important determinant of disease dynamics

and repeated contact with infective vectors is likely necessary, especially for large, mature plants.

The outcome of interactions between phytopathogenic bacteria with insects can be

diverse and difficult to predict. Pectobacterium carotovora elicits an immune response in

Drosophila (Basset et al. 2000), and both Pseudomonas syringae (Stavrinides et al. 2009a) and

Dickeya dadantii (Grenier et al. 2006) (Costechareyre et al. 2010) are pathogenic to the pea

aphid, Acyrthosiphon pisum. However, phytopathogens that are obligately insect-transmitted are

85

predicted to not severely impact the fitness of the vector to allow infective vectors time to contact

new hosts (Elliot et al. 2003; Mauck et al. 2012). To assess how prolonged exposure to E.

tracheiphila infected plants impacts beetle fitness and longevity, experiments were performed to

determine how extended acquisition access periods on symptomatic, E. tracheiphila infected

plants affect longevity, oviposition rate, or hatch rate compared to beetles fed on mock-inoculated

(healthy) plants. Herbivore gut microbiota is a complex and poorly described environment

(Schloss et al. 2006; Engel et al. 2012) that can have important effects on insect digestion and

nutrient absorption (Shi et al. 2010).While being colonized by E. tracheiphila may induce other

important physiological changes based on changes in gut microbial community composition and

nutrient uptake (Ben-Yosef et al. 2010) , (de Vries et al. 2004) (Douglas 2009), or changes in

beetle preferences for infected or healthy plants (Stafford et al. 2011), these experiments do not

suggest there is an overall fitness benefit or cost to ingesting E. tracheiphila through feeding on

infected plants.

Striped cucumber beetles are the most important vector of E. tracheiphila in the

northeast, and here we describe quantitative dynamics of A. vittatum colonization by E.

tracheiphila and how colonization dynamics interact with beetle biology to affect disease

transmission in a field setting. E. tracheiphila was recently confirmed in the southwest (Sanogo

2011), where Diabrotica and Acalymma are much more speciose (Munroe 1980, Krysan and

Smith 1987) providing many potentially competent vector that may be possible transmitters to

drive disease emergence in an area that does not currently face losses from wilt infections. Many

environmental and ecological factors interact to affect pathogen dispersal and the maintenance of

disease epidemics in host populations. For insect-borne pathogens, persistent colonization of

insect vectors are a determining factor for sustaining epidemics by providing a mobile

environmental reservoir of an infective agent, but quantitative investigations of vector acquisition

and retention dynamics are often lacking. A clearer understanding of the factors affecting insect

86

colonization by E. tracheiphila and transmission dynamics will aid in the development of

biologically informed pest and pathogen control strategies by identifying when insects are

shedding the highest amounts of infective bacteria, and suggesting the most appropriate stage for

intervention. Elucidating the molecular basis of beetle-pathogen interactions, such as what cues

mediate bacterial attachment to and proliferation within the insect’s digestive tract and plant

vasculature tissue, could lead to the development of inhibitors to interfere with colonization and

transmission (Verschuere et al. 2000) (Shahabuddin & Kaslow 1993).

Bacteria often cause disease in a concentration dependent manner (Dong et al. 2000). For

example, a cheap and effective way of controlling cholera is to filter the copepods that the

bacterium attach to as a way of reducing the amount of bacteria ingested with drinking water

(Huo et al. 1996) (Heithoff & Mahan 2004), connecting an, understanding of bacterial population

dynamics and colonization of alternative host to important insight for disease control.

Understanding the acquisition and retention dynamics of plant pathogens within insect vectors are

important parameters for understanding broader disease dynamics in agricultural and natural

systems (Blanc et al. 2011). While many obligately insect-transmitted plant pathogens cross

from the gut lumen into the haemoceol and display a latent period until they reach the salivary

gland and can be transmitted by the probing or feeding behaviors of herbivorous insects

(Labroussaa et al. 2010) (Hogenhout et al. 2008), relatively few but economically important

bacteria (Garcia-Salazar et al. 2000a) (Esker & Nutter Jr 2003) (Almeida & Purcell 2006),

colonize the digestive tract of insect vectors as extracellular symbionts and lack latent periods. A

better understanding of bacterial colonization of environmental niches and alternate hosts are

increasingly recognized as important to understanding the biology of and devising effective

control strategies for pathogens important to human, animal, and plant health (Huq et al. 1983;

Brandl 2006; Schikora et al. 2008).

87

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92

Chapter 5

Comparative genomic insights into emergence and host associations of the

bacterial wilt pathogen Erwinia tracheiphila

Abstract

Erwinia tracheiphila is the causal agent of a bacterial wilt disease with a host range

restricted to susceptible wild and cultivated Cucurbita and Cucumis ssp. Unlike other sequenced

Erwinia ssp. that have transient, facultative, and external associations with insect vectors, E.

tracheiphila is obligately transmitted in a persistent manner. Analysis of the draft genome of an

E. tracheiphila clone isolated from the wild gourd Cucurbita pepo ssp. texana at the Rock

Springs Research Farm shows evidence of active genome decay and chromosomal

rearrangements likely associated with phage and transposable element proliferation, and the

presence of important genes for host interactions likely acquired laterally. Overall, this suggests

that E. tracheiphila is undergoing rapid evolution, possibly associated with host adaptation and

niche specialization. The genome E. tracheiphila associated bacterial wilt of cucurbits results in

millions of dollars in crop loss annually, yet mechanisms of virulence to plants hosts and factors

mediating growth and attachment to the insect vector have not been discussed in the literature. In

the present study, comparative genomic analysis of E. tracheiphila with two other sequenced

Erwinia spp. was conducted to describe conserved and novel traits, and how simultaneous

genome decay through pseudogenization and expansion through HGT might be contributing to

niche specialization and pathogen emergence.

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Introduction

Erwinia tracheiphila (Enterobacteriaceae), commonly known as bacterial wilt of

cucurbits, is the most economically important pathogen of cultivated cucurbits in the eastern US

and causes millions of dollars in economic losses annually (Rojas et al. 2011). E. tracheiphila

occupies a distinct ecological niche with divergent host associations and transmission

characteristics compared to other characterized Erwinia spp., and yet the underlying genetic basis

of E. tracheiphila host interactions and plant pathogenesis are completely undescribed. To

address this shortcoming, we sequenced and described the draft genome of a local field isolate of

E. tracheiphila and compare it to other characterized strains to identify traits likely contributing

to these differences.

The biology of Erwinia are historically defined as plant associated (Hauben et al. 1998)

and many are rosaceous floral symbionts or pathogens. Many Erwinia spp. colonize floral

stigmas and can be spread by rain. Epiphytic colonization of floral stigmas defines the life

histories of the commensal E. billingiae and the infection dynamics of the fire blight pathogen E.

amylovora. Unlike other pathogenic Erwinia spp., E. tracheiphila leaf transmission through

insect herbivory is thought to be a major driver of epidemics (Smith 1914) (Rand 1915; Rand &

Enlows 1916), at least until cucurbits flower in early summer (Shapiro et al, in press). Cucurbita

spp. flowers are only open for a single morning, so E. tracheiphila must quickly pass through the

nectary without an epiphytic colonization stage (Sasu et al. 2010a; Sasu et al. 2010c). Similar to

other characterized Erwinia spp., E. tracheiphila maintains epiphytic capabilities on Cucumis leaf

surfaces under favorable environmental conditions (Rojas & Gleason 2011). However, unlike

other pathogenic Erwinia spp., direct contact with a recent leaf wound appears to be required for

infection to develop (Smith 1914; Brust 1997b).

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While many Erwinia spp. have transient and non-specific associations with a variety of

pollinators, which can transmit bacteria to many new flowers as they forage for pollen (Johnson

& Stockwell 1998; Hildebrand et al. 2000), E. tracheiphila is obligately transmitted through

infective frass by two species of cucumber beetle vectors (Coleoptera: Chrysomelidae: Luperini),

with which it can maintain persistent, non-pathogenic associations in the beetle’s digestive tract

(Shapiro et al, in prep) (Garcia-Salazar et al. 2000b) and E. tracheiphila only overwinters in the

digestive tract of diapausing adult cucumber beetle vectors and not in host plants (de Mackiewicz

et al. 1998).

Control options of E. tracheiphila in agricultural settings is limited, and is currently

achieved through environmentally and economically expensive chemical control of insect vectors

(Fleischer et al. 1998) or the deployment of labor intensive row cover to prevent beetles from

contacting plants (Rojas et al. 2011). Despite the importance of E. tracheiphila control to

agricultural production of squashes, pumpkins, melons, cucumbers, and gourds, no investigations

into the underlying genetic basis of pathogenesis to plants and persistence within insects have

been conducted. To address this, we used 454 Titanium chemistry to sequence a strain of E.

tracheiphila isolated from a wilt-infected wild gourd (Cucurbita pepo ssp. texana) grown at the

Larson Agricultural Research Station at Rock Springs, PA. The draft genome was compared with

genomes of the highly destructive fire blight pathogen E. amylovora and the commensal symbiont

E. billingiae, and screened for laterally transferred genes.

Our analyses reveal that E. tracheiphila is the most distant relative to other sequenced

Erwinia spp., and is more divergent from host-adapted pathogenic strains such as E. amylovora

compared to epiphytic strains such as E. billingiae. E. tracheiphila also shows evidence of

extensive chromosomal rearrangements and gene inactivations compared to other sequenced

Erwinia spp., likely associated with an influx of transposable and extrachromosomal genetic

material that constitutes a substantial percentage of the E. tracheiphila genome. Taken together,

95

this suggests E. tracheiphila is undergoing rapid evolution and may have experienced a recent

host jump to cucurbit host plants and is likely in the process of niche specialization. The inclusion

of the E. tracheiphila genome sequence substantially decreases the size of the Erwinia core

genome and challenges the hypothesis of relative homogeneity within the genus (Kube et al.

2010a; Kamber et al. 2012). While important traits for metabolism are conserved with other

Erwinia spp., preliminary lateral gene transfer analysis suggests the acquisition of many

important genes that may contribute to differences in host plant and insect associations for E.

tracheiphila.

Results/Discussion

Phylogenetic Relationships

A functional division of Erwinia spp. into either a commensal ‘epiphytic’ or a pathogenic

‘host-adapted’ group has been proposed. The ‘host-adapted’ group has been described to include

E. tasmaniensis, E. amylovora and E. pyrifoliae, although E. tasmaniensis is an epiphyte with

important loss of some virulence genes. E. amylovora and E. pyrifoliae are plant pathogens with

smaller genomes (Kamber et al. 2012). Like E. tracheiphila, E. amylovora and E. pyrifoliae are

necrogenic vascular pathogens that can replicate in xylem and induce characteristic wilting

symptoms in their respective host plants through the production of an exopolysaccharide that

occludes water movement (Huang & Goodman 1976) (Suhayda & Goodman 1980). The

‘ephiphytic’ group, which includes E. billingiae, is currently defined by a relatively broad host

range as a non-pathogenic floral symbiont of Rosaceous crop and ornamental trees with largely

undescribed ecology (Mergaert et al. 1999).

To understand the phylogenetic relationship of E. tracheiphila to other Erwinia strains

and enterobacterial plant pathogens, concatenated ribosomal proteins from sequenced Erwinia

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spp., sequenced strains from the plant pathogenic genera Pantoea, Dickeya, and Pectobacterium

(which were reclassified from Erwinia (Hauben et al. 1998)), and important animal associated

enteric pathogens were used to create a phylogenetic tree. The tree shows support for the

derivation of E. tracheiphila from a basal Erwinia strain, which does not cluster with other host-

adapted Erwinia strains. There is strong bootstrap support for Pantoea and Erwinia as a

monophyletic clade. Plant pathogenicity has arisen independently at least twice within

Enterobacteriaceae (for the Pantoea/Erwinia clade and the ‘soft-rot’ Dickeya/Pectobacterium

clade). The ‘soft-rot’ clade is defined by the profuse production of pectinolytic enzymes for

extensive plant cell wall degradation abilities not described in characterized Erwinia spp., which

are mostly epiphytes or vascular pathogens (Figure 5.1).

97

Figure 5-1 Phylogenetic relationships inferred from the concatenated ribosomal sequences of the

sequenced Erwinia ssp. and other important enterobacterial plant and animal pathogens

Sequenced Erwinia strains form a monophyletic clade, with E. tracheiphila related to the last

common Erwinia ancestor and not the host – adapted pathogenic strains. Recently reclassified

soft – rot phytopathogens Pectobacterium/Dickeya also form a monophyletic clade, suggesting

plant pathogenicity arose independently at least twice within enterobacteriaceae. Concatenated

sequences were aligned in MEGA with ClustalW, and bootstrap analysis was performed in

RaxML on the CIPRES server with the JTT substitution model and 100 bootstrap replicates

98

Overall Features and comparisons

The E. tracheiphila draft genome size is 4.7 MB, approximately the same size as the

commensal symbiont E. billingiae (5.1MB) (Table 5.1). BLASTP-based sequence similarity

comparisons generated with EDGAR (Blom et al., 2009) show E. tracheiphila shares more gene

families with the floral symbiont E. billingiae than E. amylovora (Figure 5.2). The core Erwinia

genome of these three species is much smaller (1,739) than previously hypothesized when only

rosaceous floral genomes E. billingiae, E. tasmaneinsis, and E. pyrifoliae were compared (2,241)

(Kube et al. 2010a). E. tracheiphila shares fewer homologous genes with E. billingiae (1,970) or

E. amylovora (1,832) than E. billingiae and E. amylovora share with each other (2,291).

Of the 4,207 total E. tracheiphila ORFs (Table 5.1, Figure 5.3), only 63% are predicted

to encode functional proteins, a much lower percentage than E. amylovora (85%) or E. billingiae

(87%). E. tracheiphila has 805 CDS annotated as putative pseudogenes, defined here as either

containing at least one internal stop codon, or a truncated CDS with 40% or more AA length

deletions compared to the closest Blastp homolog. The published genome sequences of E.

billingiae calls only 13 pseudogenes and 2 fragments (Kube et al. 2010b), but more pseudogenes

were identified by searching the intergenic regions of both genomes (Table 5.1)(Pati et al. 2010).

The average nucleotide identity (ANI) (Konstantinidis & Tiedje 2005) of the shared functional

genes is approximately the same (76-78%; Table 5.2a) in the pairwise genome comparisons of

sequenced Erwinia spp., while E. tracheiphila pseudogenes show lower ANI, suggesting that the

latter genes are actively decaying (Table 5.2b).

99

Table 5-1. General characteristics in the genomes of E. tracheiphila, E. billingiae, and E.

amylovora

E.

tracheiphila E. amylovora

CFBP 1430 E. billingiae

Eb661

Size (bp) 4,717,279 3,805,573 5,100,167

Sequencing coverage 60-80X 40X 19X

G+C content (%) 51.5 54.69 56.43

Coding Sequences 4207 3706 4596

Coding density (%) 63 85.4 87.7

Average size (bp) 830 866 966

G+C content (%) 51.63 53.6 56.4

Assigned function 3339 2822 3768

Conserved uncharacterized 868 884 515

Phage related 393 194 321

Pseudogenes 785 115 82

Frame shift 533 89 54

Fragments 252 26 28

rRNA genes 30 22 21

tRNAs 68 77 77

Transposases/Integrases 348 25 14

100

Figure 5-2 VENN diagram generated using EDGAR to compare the number of shared and

unique genes between E. tracheiphila, E. amylovora, and E. billingiae.

101

ANI All Genes ANI Pseudogenes

E_amylovora 76.4 72.7

E_billingiae 77.9 73.5

E_pyrifoliae 76.6 75.9

E_tasmaniensis 76.5 72.4

Table 5-2. Average nucleotide identities (ANI) of all ORFs and pseudogenes

ANI compared between all E. tracheiphila ORFs and other sequenced Erwinia spp. shows that

shared gene families E. tracheiphila are equally divergent from other sequenced Erwinia spp.

ANI comparison of just E. tracheiphila pseudogenes with the ORFs of other sequenced Erwinia

spp. shows lower identity, suggesting that pseudogenization was recent and pseudogenes are

actively decaying

E_billingiae E_pyrifoliae E_tasmaniensis E_tracheiphila

E_amylovora 78.51 91.37 85.72 76.30

E_billingiae 78.67 78.43 77.70

E_pyrifoliae 86.58 76.65

E_tasmaniensis 76.39

Table 5-3. Average nucleotide identities between sequenced Erwinia spp.

ANI comparisons of all ORFs between all sequenced Erwinia spp. supports the phylogenetic

relationships suggested by the ribosomal alignment. E. amylovora and E. pyrifoliae are most

similar. Of the ‘ephiphytic’ species, E. tasmaniensis has highest identity to the ‘host-adapted’

strains. E. tracheiphila has only slightly higher ANI to E. billingiae compared to the other strains

102

Decay in the genome of E. tracheiphila is mostly occurring in the accessory genome

comprising transposable elements/phage or conserved uncharacterized or genes assigned general

function only, and not within genes for essential metabolic or biosynthetic pathways (Figure 5.4).

In E. tracheiphila, the functional proportion of each COG category more closely resembles

pathogenic E. amylovora than commensal E. billingiae. E. tracheiphila contains more genes for

rRNA synthesis, including a number of HGT candidates. There are fewer genes for pyruvate

metabolism, glycine/threonine/serine, arginine/proline, metabolism in E. tracheiphila compared

to E. amylovora or E. billingiae, but pathways for carbohydrate metabolism, amino acid

synthesis, cell envelope biosynthesis and cofactor metabolism (among others), all pathways found

in many free-living enterobacterial are present and putatively functional. E. billingiae contains

notably more genes for transport and metabolism of carbohydrates, amino acids, inorganic ions,

and energy production and conversion, and moderately more genes for cell envelope biogenesis,

than other sequenced Erwinia spp., likely related to an increased need for metabolic flexibility as

an ephiphyte in a less predictable environment with unpredictable carbohydrate availability.

Taken together, E. tracheiphila appears to be decaying towards a niche-adapted plant pathogenic

lifestyle resembling the plant pathogen E. amylovora. Pseudogenization within some

transcriptional regulators [ETR1632] and an AHL synthases [ETR3169]suggests gene function

and regulation in E. tracheiphila may be significantly altered even for genes with known

homologues, and further functional studies are necessary to understand regulatory changes that

have occurred (Price et al. 2007).

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Figure 5-3. Distribution of pseudogenes on the E. tracheiphila chromosome

Distribution of predicted coding sequences in E. tracheiphila and visualization of genome decay

in all scaffolds of E. tracheiphila. Track 1 is leading strand; track 2 is lagging strand; track 3

(brown) is the distribution of pseudogenes and track 4 is the sizes and arrangement of scaffolds.

Color assignments for tracks 1 and 2 correspond to COG functional groups: Green is surface

associated, pink is phage or IS element, grey is metabolism, dark blue is stable RNA, red is DNA

recombination and repair.

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Pseudogenization by Orthologous Group

Figure 5-4. Comparisons of genome decay across orthologous groups between E. amylovora, E.

billingiae, and E. tracheiphila

Most of the genome decay in E. tracheiphila is occurring in genes of general or unknown

function, or among the insertion elements. Core biosynthetic and metabolic pathways appear to

be largely conserved. E. tracheiphila is red; E. billingiae is blue; E. amylovora is orange and

pseudogenes are grey

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Phage and Transposable Elements Proliferation

More than 421 million bases reads were generated between paired end and shotgun 454

sequencing (corresponding to 60-80X coverage), yet the chromosome assembled into 25

scaffolds (Table 5.4). The two largest scaffolds account for 1.82 MB and are predominantly

composed of bacterial chromosomal DNA. Most scaffolds contain extrachromosomal elements,

including regions of phage derived, insertion element, and plasmid conjugative transfer or other

plasmid associated genes [ETR0098, or119a, ETR0104-ETR0115, ETR0174, ETR0504,

ETR0797, ETR0907, ETR2349, ETR2604, ETR2781-2782, ETR3020, or3212b, ETR3332-

ETR3333, ETR3465, ETR3473-ETR3476, ETR3564, ETR3981].

Table 5-4. E. tracheiphila scaffold sizes and important features

Scaffold Size (nt) Coverage Notable Features

1 1,160,218 60-80X

Genomic DNA integrated phage

proteins

Flagellar biosynthesis clusters

EPS biosynthetic cluster

2 665,612 60-80X

31 rRNA genes

Putative plasmid replication-associated

protein

3 530,285 60-80X Inv/Spa T3SS

Hrp T3SS

T6SS

Genomic DNA integrated phage

4 462,842 60-80X

Genomic DNA integrated phage

Putative plasmid proteins

Inv/Spa T3SS

Rhamnogalacturonase

5 222,389 60-80X Genomic DNA integrated phage genes

6 229,276 60-80X

Genomic DNA; Some integrated phage

CDS

7 244,940 60-80X Genomic DNA integrated phage

8 240,771 60-80X

Genomic DNA

PsiA/PsiB plasmid genes

9 217,201 60-80X Genomic DNA

10 131,409 60-80X Genomic DNA

11 93,198 60-80X

Genomic DNA integrated phage

Putative plasmid transfer protein

12 78,767 60-80X Genomic DNA

13 84,878 60-80X

Many phage genes

Putative plasmid stabilization protein

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14 84,351 60-80X Fructose PTS operon adjacent to phage

and plasmid related proteins

15 67,034 60-80X Expansin, endoglucanase

Intact mannitol PTS operon

Degraded plasmid replication protein

16 57,653 60-80X Genomic DNA

17 46,611 60-80X Genomic DNA

18 37,446 60-80X Plasmid conjugative genes

19 22,957 200-300X Phage

20 7,974 60-80X Type VI Vgr-family protein

21 6,473 60-80X Hypothetical Proteins

22 9,701 200-300X Phage

23 4,005 60-80X Mostly Hypothetical Proteins

24 2,714 60-80X Genomic DNA

25 2,669 60-80X Genomic DNA

Scaffolds 19 and 22 are comprised of enterobacterial phage genes, and the contigs that

make up these two scaffolds are present in significantly higher coverage (200-300X) compared to

the other chromosomal scaffolds (60-80X), indicating that E. tracheiphila appears to be co-

infected by phages that may be replicating in culture (Table 5.4). Many other scaffolds contain

chromosomally integrated phage remnants. In total, 393 CDS (9.7% of the E. tracheiphila

genome) are also present in the phage pan-genome (Table 5.5). The largest number of phage

genes are from general enterobacterial phages, and there are many genes from phages known to

infect hosts of putative laterally transferred genes, such as Pseudomonas and Sodalis phages.

Clustered regularly interspaced short palindromic repeats (CRISPR) associated sequence

proteins (cas genes) are prokaryotic RNAi-based defenses. E. amylovora CFBP 1430 has eight

genes homologous to other described cas genes (Rezzonico et al. 2011), while E. billingiae has

four putative CRISPR regions (Kube et al. 2010b). In contrast, E. tracheiphila has no detected

CRISPR regions (Grissa et al. 2007). Absence of CRISPR repeats and cas genes may explain the

presence of two putatively replicating phages and the abundance of genes that are likely of phage

origin.

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Table 5-5. Distribution of phage genes present in E. tracheiphila among phages with at least 10

genes

Phage Host Gene Number

Enterobacteria phage 140

Burkholderia phage 102

Pseudomonas phage 99

Escherichia phage 66

Salmonella phage 60

Shigella phage 31

Bacillus phage 31

Vibrio phage 27

Clostridium phage 26

Yersinia phage 23

Phage Gifsy-1 22

Erwinia phage 21

Megavirus chiliensis 21

Synechococcus phage 18

Acanthamoeba polyphaga mimivirus 18

Ralstonia phage 17

Haemophilus phage 17

Aeromonas phage 16

Phage Gifsy-2 16

Ostreococcus tauri virus 16

Sodalis phage 15

Cafeteria roenbergensis virus 15

Klebsiella phage 15

Endosymbiont phage 15

Planktothrix phage 14

Stx2-converting phage 14

Prochlorococcus phage 14

Mannheimia phage 13

Micromonas sp. RCC1109 virus 13

Staphylococcus phage 12

Burkholderia ambifaria phage 12

Lactococcus phage 12

Paramecium bursaria Chlorella virus 12

Mycobacterium phage 12

Ostreococcus lucimarinus virus 12

Bacteriophage APSE-2 11

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Xanthomonas phage 11

Microcystis aeruginosa phage 11

Stenotrophomonas phage 11

Ostreococcus virus 11

Acinetobacter phage 10

In the E. tracheiphila genome, there are 348 non-phage insertion/transposable elements

from 28 families. IS200, which is usually reluctant to transpose, has the highest abundance with

37 copies (Table 5.6) (Beuzón et al. 2004), and the mutator-type transposase best known as a

maize IS element is also present in high abundance (Lisch et al. 2001). There are an additional 17

IS element families with 10 or fewer copies in the E. tracheiphila genome and 90 putative IS

elements without pfam family assignments.

Table 5-6. Abundances and rates of decay of insertion sequenes and transposable elements in the

E. tracheiphila genome

Transposable Element Family

Pseudo

n

Total

n % Inactivated

IS200 13 37 35.14%

Integrase, Catalytic Core 14 30 46.67%

Mutator Type 14 28 50.00%

IS240 13 18 72.22%

IS4/IS5 11 16 68.75%

IS1_DDE_Tnp_IS1 1 14 7.14%

Ribonuclease H-like 7 13 53.85%

Phage Integrase 3 13 23.08%

Resolvase 2 11 18.18%

Tn3_DDE_Tnp 7 10 70.00%

Tnp_IS801/1294 5 10 50.00%

Tnp_IS3/IS911 1 9 11.11%

IS1_InsA 1 8 12.50%

YghA-like Tnp 5 7 71.43%

IS204_IS1001_IS1096 3 4 75.00%

IS111A_IS1328_IS1533 1 4 25.00%

Tnp_IS116/IS110/IS902 2 4 50.00%

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Homeodomain 2 4 50.00%

IS891/IS1136/IS1341 3 3 100.00%

IS66 1 3 33.33%

Tnp_IS4 2 2 100.00%

DDE_3 1 2 50.00%

HTH_21 2 2 100.00%

rve_2 1 2 50.00%

HTH_29 1 1 100.00%

Tnp_1_2 0 1 0.00%

HTH_ISL3 1 1 100.00%

Integrase, SAM-like 1 1 100.00%

No Family Assignment 66 90 0.733333333

Total 118 348

Genomic Rearrangements

Whole genome alignments between the plant-associated Erwinia spp. (both pathogenic

and non-pathogenic) sequenced to date show that there are small-scale genomic rearrangements

between species, but all previously sequenced species share large collinear blocks and gene

content is highly conserved (Smits et al. 2010a) (Kube et al. 2010b) (Smits et al. 2010c). E.

billingiae contains only 8 annotated IS elements and E. amylovora contains only 10, and these

genomes are highly collinear with few chromosomal rearrangements compared to each other

(Figure 5.5). In contrast, the E. tracheiphila genome has undergone extensive genomic

recombination compared to E. billingiae, likely associated with bacteriophage infection and the

proliferation of insertion sequences.

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Figure 5-5. Chromosomal rearrangements between E. tracheiphila, E. amylovora, and E.

billingiae

Comparisons of chromosomal inversions and rearrangements between E. tracheiphila, E.

amylovora, and E. billingiae generated with DoubleACT and visualized in ACT. Red lines

connect homologous regions in the same orientation while blue lines show homologous regions in

inverted orientations 5.3b Syntenic dot plot comparisons show E. amylovora and E. billingiae are

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highly sytenic with several large chromosomal inversions, while E. tracheiphila is not syntenic

with either E. amylovora or E. billingiae

Lateral Gene Acquisition

E. amylovora is described as having a ‘closed’ pan-genome due to high sequence

similarity among E. amylovora strains and presence of few detected gene acquisitions (Smits,

Rezzonico, & Duffy, 2010, (Boucher & al 2003). In contrast, initial DarkHorse analysis of the E.

tracheiphila genome (Podell & Gaasterland 2007) identified 301 protein-coding genes (7.4% of

all protein coding genes as candidates for lateral gene transfer. The list of gene transfer candidates

contains several genes with purported functions important for both plant pathogenicity and

persistence in the beetle digestive tract (Supplemental Table 1), including p450 detoxification and

secondary compound synthesis, plant colonization and pathogenicity factors, and a locus with

genes for several chitin binding/degradation proteins. Further analysis of these transfer candidates

revealed that many are flanked by transposable elements and/or show phylogenetic incongruence

with the ribosomal protein tree, strengthening the hypothesis that these genes were acquired by E.

tracheiphila through lateral transfer. In addition to genomic rearrangements, lateral gene transfers

are a source of genetic novelty supporting niche adaptation (Mathee et al. 2008) or host jumps

(Zhaxybayeva & Doolittle 2011). In the following sections we take an in-depth look into some of

these genes and the adjacent genomic regions.

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Hypersensitive Response and Pathogenicity (Hrp) T3SS

The Type III secretion system (T3SS) is an inducible, needle-like protein export

apparatus found in many plant and animal bacterial pathogens (Hueck 1998) that injects effector

proteins directly into host cell cytoplasm. Erwinia tracheiphila has an Hrp T3SS conserved with

other pathogenic Erwinia and Pseudomonas spp. (Alfano et al. 2000) and composed of three

transcriptional units (hrpC operon [ETR 3853 – ETR 3857], hrpA operon [ETR 3858 – ETR

3862], and hrpJ operon [ETR 3838 – ETR 3848]). Compared to E. amylovora, the core structural

genes in the hrp/hrc secretion system, and the sigma factor HrpL that controls expression of all

hrp/hrc genes in E. amylovora, are present and conserved with high AA identity in E.

tracheiphila (McNally et al. 2011) (Figure 5.6, Table 5.7). The hrp T3SS was acquired laterally

from Pseudomonas spp. before proliferation within Erwinia/Pantoea spp. (Naum et al. 2009) and

has been eliminated from the epiphytic symbiont E. billingiae, which does not possess an hrp

T3SS or any secreted effectors (Kube et al. 2010a) .

Effectors

E. tracheiphila shows high divergence in both effector content and AA identity of conserved

effectors compared to T3SS structural and regulatory genes (Figure 5.6, Table 5.7). The E.

amylovora hrp region is bound by the Hrp effector and elicitor (HEE) and the Hrp associated

enzymes (HAE) regions, which are required for full virulence (Oh et al. 2005). Overall, 4/9

secreted proteins from the HEE/HAE region in E. amylovora are absent in E. tracheiphila. In E.

tracheiphila, the hrp-associated systemic virulence genes hsvABC were excised from the HAE

region, but both hsvA [ETR3340] and hsvC [OR3380b] were found as pseudogenes degrading

elsewhere on the chromosome. E. tasmaniensis, which contains the hrp T3SS but lacks the HAE

region, is non-pathogenic (Kube et al. 2010b). Harpins are translocated proteins that induce a

hypersensitive response on non-host plants and are factors determining disease development on

host plants. In the HEE region, E. tracheiphila contains a partial homologue of the harpin HrpN

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[ETR 3863], which is an E. amylovora virulence determinant and proteins from fragments of this

gene have been shown to induce symptoms (Barny 1995). However, an HrpW homologue is

absent in E. tracheiphila although a degrading fragment of the hrpW specific chaperone [ETR

3866 ] remains (Figure 5.6).

In addition to HEE/HAE effectors, E. amylovora was previously the only other Erwinia

ssp. known to contain singleton T3SS effector genes (Smits et al. 2010b). While the host-adapted

pathogen E. pyrifoliae contains a functional hrp T3SS, the lack of singleton effectors is

hypothesized to be a factor in the more restricted host range of this pathogen compared to E.

amylovora. E. tracheiphila also contains several singleton effectors and chaperones without

homologues in E. amylovora, and that are identified as HGT candidates from Pseudomonas spp.

(Table 5.8). In Pseudomonas spp., effectors are often located near insertion sequence elements

(Kim et al. 1998), and their importance for determining plant host range promotes both their

transfer among phytopathogens and high divergence in AA identity (Ma et al. 2006). The

functional characterization of individual and synergistic importance of HEE, HAE, and singleton

effectors towards plant pathogenicity and disease development will be important for dissecting E.

tracheiphila molecular pathology.

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Figure 5-6. Comparisons of gene content and amino acid identity of the hrp Type III Secretion Systems in E. amylovora and E. tracheiphila

While the strucutural genes are the Hrp pilus are largely intact, 4 of the effectors essential for plant pathogenicity found in the E. amylovora

T3SS regulon are absent in E. tracheiphila. The AA identity of the structural components and regulators ranges from 71-92.5%, while the AA

identity of effectors ranges from 52.6-68.6%. While the harpin gene HrpW is absent, the specific chaperone remains, albeit with very low AA

identity.

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Table 5-7. Comparison of gene presence and amino acid similarity of different functional genes

in the hrp/hrc regulon

Comparisons of T3SS AA identities for hrp pilus structural components, regulators, effectors, and

chaperones was compared between E. tracheiphila and E. amylovora shows that regulators are

most conserved, while effectors and their chaperones are more divergent.

Function Average

AA

Similarity

Number of hrp genes with

functional homologues in E.

tracheiphila

Regulators 83.1 3/3

Hrp pilus structural

components

72.4 24/24

Effectors 60.2 4/9

Chaperones 48.7 ½

Table 5-8. Singleton hrp/hrc Type III Secretion System effectors that are likely horizontal gene

transfer candidates from phytopathogenic Pseudomonas spp.

T3SS effectors and chaperones from plant pathogenic Pseudomonas spp. flagged by Darkhorse as

candidates for HGT. In three cases, both a chaperone and effector appear to have been

horizontally transferred from the same donor strain. Several singleton effectors without

chaperones that appear to be functional are present. All of these effectors and chaperones in the

table have highly disjoint phylogenetic distributions (data not shown) and homologues of these

genes are not present in other Erwinia spp.

query_id

Putative

Functional

Assignment Annotated Function Strain of origin

or0597 Functional Type III Effector HopV1 Pseudomonas savastanoi

or0598 Fragment Type III Chaperone ShcV Pseudomonas savastanoi

or4102 Pseudo Type III Chaperone ShcF Pseudomonas syringae

or4103 Functional Avr protein Pseudomonas syringae

or2699 Functional Type III Chaperone ShcF Pseudomonas syringae

or2970 Functional Type III Effector Hopa1 Pseudomonas syringae

or2971 Functional Type III Chaperone protein shca Pseudomonas viridiflava

or1961 Functional Type III Effector AvrB4-2 Pseudomonas syringae

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or2282 Fragment Type III Effector HopL Pseudomonas syringae

or1449 Functional Type III Effector HopE1 Pseudomonas syringae

Plant Cell Wall Degradation

No Erwinia spp. is described to induce soft rot symptoms on host plants characteristic of

those caused by Pectobacterium/Dickeya spp. through profuse extracellular pectinase secretion.

Characterized Erwinia spp. multiply in the apoplast and interact with hosts through T3SS

effectors, while ‘soft-rot’ bacterial pathogens also secrete a profuse amount of plant cell wall

degrading enzymes, sequentially degrading pectins and then cellulose (Liu et al. 2008). E.

tracheiphila contains a number of plant structural carbohydrate degradative genes not present in

other Erwinia spp., including several genes to degrade the most abundant pectin in plant cell

walls, rhamnogalacturon (Cosgrove 2005), [ETR0494, ETR0742] (Glasner et al. 2008).

Homologues of these genes in Dickeya and Pectobacterium spp. are virulence factors functioning

in development of characteristic soft rot symptoms (Toth & Birch 2005).

In addition to the two rhamnogalacturon degrading genes identified above, E.

tracheiphila contains a locus with an expansin [ETR 1276] (Kerff et al. 2008) and a cellulase

[ETR 1277], and their physical proximity suggests they are likely co-regulated. Expansins are

plant proteins involved in important physiological processes, including extension and

rearrangements of plant cell walls, and pH dependent cell wall extension (Li et al. 2002).

Recently, the crystal structure of an expansin homologue EXLX1 from Bacillus subtilis was

found to be functional as cell-wall loosening factor allowing root colonization (Kerff et al. 2008)

(Georgelis et al. 2011) and essential for movement through xylem and full virulence of Pantoea

stewartii on sweet corn (Mohammadi et al. 2011). Expansins are not thought to exhibit enzymatic

activity, but are implicated in loosening of pit membranes and bacterial movement through xylem

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vessels through manipulation of cellulose polymers. The presence of a cellulase at the same locus

suggests possible rearrangement of cellulose microfibrils so the proper cleavage site can be

exposed for subsequent enzymatic degradation.

Phylogenetic analysis of the pectin and cellulose associated genes in E. tracheiphila

reveals high support for horizontal acquisition of these genes from ‘soft-rot’ strains (Figure 5.7

and 5.8). Expression of genes for plant cell wall degradation enzymes by E. tracheiphila would

make these carbohydrates available as a glucose source for E. tracheiphila, and might also

contribute to palatability or digestability of wilting plants by beetle vectors, which prefer to

consume leaves of symptomatic, wilting foliage on E. tracheiphila – infected plants compared to

healthy foliage (Shapiro 2012, in press).

Figure 5-7. Schematic of a locus with two genes encoding proteins that manipulate plant cell

walls that shows support for horizontal acquisition by E. tracheiphila

Two maximum likelhood trees with representative strains showing the phylogenetic distribution

of the expansin and cellulose genes found in E. tracheiphila. This locus is flanked by IS elements,

further supporting horizontal acquisition. Both expansin and cellulase are important for plant cell

wall structural carboyhydrate interactions and specific to plant-microbe or plant-nematode

interactions. Current evidence suggests both genes have very limited phylogenetic distributions

among gram-positive and gram-negative bacteria and some plant parasitic nematodes. Expansin

tree was run with the WAG substitution model, and the cellulase tree was run with the LG

substitution model

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119

Figure 5-8. Two pectin degradation genes present in E. tracheiphila that were likely acquired horizontally

Maximum likelihood phylogenetic trees of two singleton genes that degrade the most abundant pectin in cell walls, rhamnogalacturon, that

are found in E. tracheiphila and all top Blastp hits. Both genes cluster with homologues from the ‘soft-rot’ pathogen clade and homologues

are not present in the Erwinia/Pantoea clade. Many plants contain genes for similar proteins utilized in cell wall rearrangement and

degradative processes. Both in Figure 5-8 trees are unrooted and use the LG substitution model

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P450

Cytochrome p450s (CYP) enzymes are ubiquitous and diverse in eukaryotic organisms.

In contrast, many prokaryotes lack p450s, indicating p450 functions are not a central component

of microbial metabolism. Little is known about the functional significance of p450 systems in

bacteria, but many appear to detoxify terpenes and other xenobiotic compounds through

oxidoreductive reactions (Nelson 2009). While more than 100 families of prokaryotic p450s have

been described, the taxonomic distribution of these genes are most abundant in Rhizobia,

Streptomyces, and other actinobacteria and α-proteobacteria, with very few indentified in γ-

proteobacteria (Munro & Lindsay 1996). A p450 region is present in E. tracheiphila [ETR 3367 –

ETR3376] that displays a high level of synteny to a p450-containing region found on a symbiosis

island of Mesorhizobium loti, a nitrogen-fixing, non-pathogenic symbiont of legumes (Figure

5.9). In both M. loti and E. tracheiphila, the p450 region is adjacent to a transposable element

(Uchiumi et al. 2004). In addition to the p450 monoxygenases and hydroxylases, the locus

contains two terpene synthases, suggesting the possible production of plant manipulative

compounds (Tsavkelova et al. 2006) that may be induced at the same time p450 mediated

detoxification occurs. Phylogenetic analysis of a representative p450 monoxygenase from the E.

tracheiphila locus shows that the distribution of this p450 is mostly restricted to bacteria with soil

reservoirs, where they are likely to encounter a diverse array of toxins (Lamb et al. 2003)(Figure

5.9).

Genes conferring toxin resistance or metabolism (Mathee et al. 2008) (including

antibiotic resistance) are among the most commonly horizontally transferred traits because of the

strong selective advantage to having these genes when toxins are present (de la Cruz & Davies

2000). Non-domesticated Cucurbita ssp. are chemically defended by a group of highly

oxygenated tetracyclic triterpenes known as cucurbitacins (Halaweish 1993) (Tallamy et al.

2005). Cucurbitacins are detectable at 1ppb, bitter, and highly toxic to most mammalian and

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insect herbivores (Rehm 2006), but can be detoxified and sequestered by the co-evolved,

specialist cucumber beetle herbivores that transmit E. tracheiphila (Metcalf 1986; Smyth et al.

2002). The presence of toxic cucurbitacins may provide a selective advantage for E. tracheiphila

to maintain metabolically costly p450 detoxification systems. p450 enzymes are induced in

Bradyrhizobium japonicum under anaerobic conditions in the bacteriod (plant-associated) stage in

legume root nodules (Uchiumi et al. 2004) but p450 deletion mutants do not appear to be

impaired in symbiotic ability (Keister et al. 1999), so the full function of p450 in vivo, in different

growth states, and in the environment remain to be described.

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5-7a

5-7b

Figure 5-9. Comparisons p450 loci in E. tracheiphila and Mesorhizobium loti

Comparison of the p450 regions and AA identity of individual genes between E. tracheiphila and

Mesorhizobium loti. E. tracheiphila contains two cytochrome p450 and two p450 hydroxylase

123

genes homologous to genes in M. loti. In both genomes, the p450 regulon is adjacent to

transposable elements 8b. Phylogenetic distribution constructed with a representative p450

monoxygenase strongly shows that p450s are largely absent in enterobacteriaceae, and supports

lateral acquisition by E. tracheiphila

Chitin Association

Chitin is β(1 -> 4) linked linear homopolymer of N-acetylglucosamine (GlCNAc) that is

ubiquitous in aquatic and terrestrial systems (Meibom et al. 2004b), and a defining structural

polysaccharide of insect exoskeletons, including the digestive tract (Cohen 2001). Several notable

arthropod symbionts contain chitinases that promote colonization of the external exoskeleton

(Meibom et al. 2004a) or digestive tract (Jones et al. 1986; Killiny et al. 2010), and utilization of

chitin as a glucose source (Li & Roseman 2004; Killiny et al. 2010).

E. tracheiphila contains a locus that encodes three chitin-associated genes [ETR1568,

OR1593a, OR1593b]. Phylogenic analysis of the closest Blastp homologues for each gene and

physical proximity to enterobacterial phage genes support the likelihood of lateral acquisition

(Figure 5.10). One of the genes is a small fragment of a chitinase A gene with only a chitin-

binding domain [ETR 3429] with the closest Blastp homologue found in S. glossinidius.

However, given the location of this fragment, it is likely functional (Figure 5.10). Additionally,

this locus is inserted within a flagellar assembly locus and immediately adjacent to a

transcriptional regulator, suggesting chitin detection and degradation is likely co-regulated with

expression/suppression of motility associated genes.

E. amylovora can adhere to the exoskeleton of insect vectors for up to seven days (Smits

et al. 2010c), and contains one hexosaminidase with a homologue in E. tracheiphila [ETR1196]

and one novel chitin associated gene unrelated to genes in the E. tracheiphila chitinase locus.

However, long-term bacterial growth and persistence either within the digestive tract or on the

exoskeleton of insect vectors has not been shown in several studies investigating insect

interactions with E. amylovora and E. billingiae (Johnson & Stockwell 1998; Hildebrand et al.

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2000). While the genetic basis of insect persistence in E. tracheiphila has not been functionally

characterized, the presence of this locus containing several novel chitin associated genes is likely

a contributing factor.

Figure 5-10. Schematic of E. tracheiphila chitin associated locus and phylogenetic support for

horizontal acquisition

A locus likely conferring enhanced chitin association of the two full length chitin associated

genes. The first gene has several binding domains, the second is a fragment compared to the

closest homologue but has an intact chitin-binding domain, and the third is a GH18 family chitin

degradation gene. This locus is flanked by enterobacterial phage genes and inserted adjacent to a

transcriptional regulator and a flagellar synthesis cluster

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126

General Characteristics

Motility

Flagellar movement allows bacterial dispersal from low quality or nutrient poor

environments towards better quality environments, and flagella-mediated swarming motility is

important for virulence of many plant and animal pathogenic bacteria, including E. amylovora

(Bayot & Ries 1986). E. tracheiphila contains two complete flagellar genes sets that are highly

conserved in other Erwinia spp. The first set is scattered in several clusters [ETR 1002-

ETR1016; ETR 1040-1043, ETR 2294 – ETR 2297 ], while the second set is located in a single

cluster [ETR 1547 – 1560; ETR 1570- ETR 1583]. E. tracheiphila contains an additional sigma

factor and two flagellar genes [ETR 2967-ETR2968] homologous to Yersinia and Escherichia

spp.

Flagella are the structural ancestor of T3SS, and in E. amylovora the T3SS positive

regulator sigma factor HrpL is also a negative regulator of motility (Cesbron et al. 2006),

suggesting a close functional and regulatory link between motility and virulence that is largely

unexplored in proteobacteria. This link is unexplored in E. tracheiphila, and HrpL is absent in E.

billingiae, so the expression, regulation, and ecological consequences of flagella-mediated

movement is not well understood among these bacteria. Chemotaxis associated genes are located

throughout the E. tracheiphila genome, and many are located in close proximity to motility

clusters, such as flagella. Some are of phage origin or appear to be pseudogenes, suggesting HGT

and gene inactivation influence E. tracheiphila responses to environmental stimuli and chemical

cues [ETR 0611] [ETR 0816] [ETR1005-1010] [ETR 1128][ETR1390][ETR1469-

1471][ETR1562][ETR1780-1781][ETR1803][ETR2954] [ETR 3176][ETR3191-3192][ETR

3651][ETR3883]

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Additional Secretion Systems

Type II SS

The Type II secretion system is the general secretory pathway and recognizes proteins

with specific signal sequences. The E. tracheiphila T2SS [ETR 2799 – ETR 2810] is adjacent to

transposable elements upstream and downstream, and all proteins show highest sequence identity

(80-90%) to Pantoea stewartii, a corn wilt pathogen which can also persistently colonize its flea

beetle vector (Stavrinides et al. 2009b) (Menelas et al. 2006). Many of the genes in this locus

have low identity (20-30%) with other Erwinia spp.

Inv/Spa T3SS

The inv/spa T3SS secretion system is a cell invasion and pathogenicity factor towards

mammalian hosts characterized mainly from enteroinvasive Salmonella spp. (Shea et al. 1996),

where the inv/spa T3SS is located on pathogenicity island 1 (PAI-1) and functions in initial cell

attachment and invasion. While less well characterized outside of Salmonella spp., an inv/spa

T3SS was shown to be essential for persistent gut colonization of flea beetle vectors (Coleoptera:

Chrysomelidae: Galerucinae) by the corn wilt pathogen P. stewartii (Correa et al. 2012) and

intracellular invasion of the tsetse fly digestive tract by Sodalis glossinidius str. morsitans (Dale

et al. 2001) (Dale et al. 2002). E. tracheiphila [ETR 0461 – ETR 0480] contains one Inv/Spa

T3SS conserved among Erwinia spp. None of the Erwinia spp. with an inv/spa T3SS are known

to have intracellular associations with insects, and current evidence suggests the E. tracheiphila

association with insects is extracellular (Garcia-Salazar et al. 2000a). Additionally, the inv/spa

region was not shown to affect E. amylovora pathogenicity on apple (Zhao et al. 2009), so the

function of these systems and reasons for continued chromosomal maintenance in plant

associated Erwinia spp. are unknown.

128

Type VI SS

E. tracheiphila contains two T6SS gene clusters, only one of which is homologous to a

T6SS in other Erwinia spp. [~ETR 3902 – ETR 3922]. The second shows strong support for

lateral acquisition [ETR 0414 - ETR 0426, ETR 0432 – ETR 0434] and contains an internal

fimbrial cluster [ETR 0427-ETR0421]. A singleton VgrG effector also shows some support for

horizontal acquisition [ETR0003].

Type VI secretion systems show structural similarities to bacteriophage tail proteins (Pell

et al. 2009) and are receiving increasing research attention as important virulence factor

widespread among gram-negative bacteria (Silverman et al. 2012). T6SS are almost completely

uncharacterized in plant pathogenic bacteria, but in P. carotovorum, T6SS hcp effectors appear to

be plant virulence determinants (Mattinen et al. 2007). In addition to virulence determinants,

T6SS effectors can also mediate contact dependent inhibition (CDI) to suppress growth of other

co-occuring bacterial strains. For E. tracheiphila, this function would be useful for colonization

of the beetle gut if many other gut bacteria are present, and possibly within infected plants to

prevent other bacteria from using degraded plant cell wall polysaccharides as glucose sources.

Surface Colonization Structures

E. tracheiphila contains several divergent surface attachment structures, suggesting that

E. tracheiphila requires different host adhesion factors than E. amylovora and E. billingiae, and

some of these factors were likely acquired through HGT. Fimbriae are a diverse family of

structures in gram-negative bacteria that promote adhesion to surfaces and are important

components of multi-cell aggregative behavior. Fimbriae are utilized by E. amylovora for

attachment to xylem vessels and biofilm formation in planta (Koczan et al. 2011) and many other

enterobacteria to adhere to host digestive tract (Griffin et al., 2012) (Korea, Badouraly, Prevost,

Ghigo, & Beloin, 2010). While E. tracheiphila contains one conserved fimbrial locus [ETR 3622-

ETR 3628], there are multiple fimbrial genes in E. tracheiphila that do not have homologues in

129

other sequenced erwinias [ETR 0427-0431]. A second set of fimbrial genes [ETR 2937-2940] [

ETR 1823- ETR 1826, ETR 2849] have homologues in other plant and insect associated

pathogenic bacteria.Similarly, Type IV pili are essential for initial attachment to xylem

colonization and cell detachment from mature biofilms in E. amylovora (Koczan et al. 2011). In

addition to a type IV pili locus conserved among erwinias [ETR 3818- ETR 3820, ETR 2450,

ETR 3301-3305, ETR 3553]E. tracheiphila contains a singleton type IV pili gene [ETR 2613]

with a homologue in Serratia spp., and an adhesin likely acquired by HGT from a Vibrio strain.

Exopolysaccharide synthesis

Capsular polysaccharide protect bacteria against environmental stresses, desiccation,

plant resistance factors (Koczan et al. 2009) (Bellemann et al. 1994).Secretion of amylovoran and

levan, two Erwinia amylovora exopolysaccharides, are an essential plant pathogenicity factor

(Bellemann & Geider 1992), and these exopolysaccharides can induce wilting symptoms when

inoculated as cell-free isolate in host plants (Goodman et al. 1974) (Zhao et al. 2005) (Koczan et

al. 2009). E. tracheiphila contains an EPS region [ETR 1684 – ETR 1878] showing largely

conserved gene synteny and AA identity to the EPS region of E. billingiae (Figure 5.11). While

no studies have described the structure or functionally characterized the E. tracheiphila EPS,

detection of slime in xylem is considered diagnostic of E. tracheiphila infection in the field, and it

is reasonable to assume EPS functions similarly in E. tracheiphila as in E. amylovora to block

xylem sap flow and induce wilting symptoms. Capsular polysaccharide EPS is important for other

enterobacteriaceae during mammalian gut colonization (Favre-Bonté et al. 1999) (Sonnenburg et

al. 2004), but the function of and induction of EPS production in colony formation and

persistence in the cucumber beetle digestive tract is not known. Many insect-associated bacteria

are contained in specialized structures in an insect’s digestive tract (Shigenobu et al. 2000).

However, no such structure has been observed in the striped cucumber beetle digestive tract, and

130

bacteria assumed to be E. tracheiphila have been observed attached to the beetle’s hindgut by a

glycocalyx (Garcia-Salazar et al. 2000a).

Figure 5-11. Comparisons capsular exopolysaccharide operon in E. tracheiphila, E. billingiae,

and E. amylovora

Conclusions

Erwinia tracheiphila is the most important pathogen of cultivated cucurbits in the

Northeast and Midwest, yet was completely undescribed at the genetic level. The vast majority of

research attention has focused on the economically important Erwinia spp. that are associated

with rosaceous hosts (apples, pears, quince) as either pathogens or epiphytic biocontrol agents.

The agricultural genetic stock of these crop plants is fairly restricted, possibly influencing the

131

relative homogeneity of the sequenced, rosaceous-associated Erwinia strains and leading to the

hypotheses that the overall genetic diversity within the genus is relatively low compared to other

bacterial genera. The addition of the E. tracheiphila genome, which infects different plant hosts

and can persistently colonize insect vectors, suggests undiscussed genetic and biological diversity

within the genus.

While the draft genome size of E. tracheiphila is 4.7MB and within the range of many

free-living enterobacteria, it is more similar to ‘epiphytic’ than ‘host-adapted’ Erwinia spp.

Further, pseudogenization and associated low CDS density suggest E. tracheiphila is actively

undergoing genome decay, which is a widely recognized part of microbial host adaptation. E.

tracheiphila is derived from a basal Erwinia strain (Figure 5.1), and does not cluster

phylogenetically with other host-adapted, plant pathogenic strains in the genus, which comprise a

more recently derived clade. Since bacteria are under strong deletion bias to get rid of

nonfunctional DNA burden quickly (Andersson & Andersson 2001; Tamas et al. 2002; Kuo &

Ochman 2010), observed presence of large number of pseudogenes suggests E. tracheiphila’s

recent colonization of a new niche (McCutcheon & Moran, 2012).

In addition to extensive decay in the accessory genome, E. tracheiphila has undergone

genome expansion and acquired a large number of genes through HGT, which is not often

observed for highly host-adapted pathogens. E. tracheiphila occurs in two environments

conducive to horizontal gene transfer (insect digestive tract and leaf surface/vasculature), and the

genome contains a notably large number of genes from mobile genetic elements, which are often

agents of host gene transfer. E. tracheiphila contains a number of genes that likely influence plant

virulence and pathogenicity, including an expansin, cellulase, pectinases, T3SS effectors, and a

p450 detoxification locus, showing strong phylogenetic support for lateral acquisition. In contrast,

relatively fewer HGT candidate genes could be classified as likely important in persistent insect

interactions, with a locus containing several chitin-associated genes the notable exception. Many

132

of the HGT candidates have homologues in other enterobacteria. HGT between closely related

bacteria is thought to be very common, although more difficult to confirm. The presence of

enterobacterial phages and IS elements could provide a mechanism by which these genes were

transferred into the E. tracheiphila genome.

The proliferation of insertion sequences and replicating phage have likely contributed to

extensive chromosomal rearrangments and fragmentation compared to other characterized

Erwinia strains. Taken together, the extensive chromosomal rearrangements, IS element

proliferation, low percentage of protein coding genes, and horizontal acquisition of important host

interaction genes suggests E. tracheiphila is undergoing rapid evolution and is in the process of

niche specialization. Agricultural landscapes are likely promoting the emergence of E.

tracheiphila, both by providing large fields of highly susceptible and non-native host plants

(Cucumis spp.) cultivated at high densities, and by supporting high population densities of the

striped cucumber beetle A. vittatum, which is the predominant vector (Shapiro, Chapter 4).

The addition of genome sequences of poorly known and predominantly insect associated

Erwinia spp. (de Vries et al. 2001) (Estes 2009; Savio et al. 2011) (Skrodenyte-Arbaciauskiene et

al. 2011) will provide additional insight to Erwinia spp. evolution and diversification. Future

investigations into E. tracheiphila plasmid diversity and function (Smits et al. 2010a) (Shrestha et

al. 2007) (Llop et al.) and sequencing of additional E. tracheiphila strains isolated from other

Cucurbita and Cucumis ssp. (Rojas et al. 2010) will provide invaluable insight into factors

determining host specificity and virulence.

Methods

DNA Isolation

133

A field isolate of E. tracheiphila was grown in nutrient broth for 4 days at 28C. The

culture was briefly centrifuged at 10,000 RPM and the pellet was washed with sterile PBS

(pH=8.0) to remove residual media. Genomic DNA was isolated from the pellet using Promega

Genomic DNA Wizard extraction kit. Sample identity was confirmed with partial 16S

amplification and sequencing of isolated DNA using the following primer set: 530F (5’-

GTGCCAGCMGCCGCGG-3’) and 1392R (5’-ACGGGCGGTGTGTRC-3’). In brief, 50 ng

genomic DNA were added to a reaction mixture containing 1.0 µL of 10 µM forward primer, 1.0

µL of 10 µM reverse primer, and 12.5 µL of 2X GoTaq Master Mix (Promega). PCR cycling

conditions were as follows: 4 minute initial denaturation at 94 °C followed by 28 cycles of 30

sec denaturation at 94 °C, 60 s annealing at 55 °C, and 90 s extension at 72 °C followed by a 7

minute final extension at 72 °C. 10 µLPCR product were treated with 2 µL ExoSAP-IT (USB)

using a 37 °C incubation for 15 min, followed by an 80 °C incubation for 30 min and were

submitted to the Penn State University Core Genomics Facility for bidirectional sequencing using

Big Dye Chemistry on an Applied Biosystems 3730XL platform. A consensus sequence was

generated using the forward and reverse.

Sequencing and Assembly:

Genomic DNA was submitted for shotgun sequencing at the PSU Genomics Core Facility

and 8 kb paired end (PE) sequencing at University of Hawaii using 454 Titanium Chemistry

(Roche). In brief, 857,774 shotgun reads (~350 Mb) and 207,713 8 kb PE reads (~70 Mb) were

generated, which represents approximately 85X coverage of the genome (estimated genome size

~ 5.0 Mb). Shotgun and paired reads were assembled into contigs and scaffolds using GS De

Novo Assembler (Roche) to generate 300 contigs ranging in size from 200 bp to 200 kb (N50

contig length=22 kb), which were used to generate 27 scaffolds (4.7 Mb) ranging in size from 2

kb to 1.2 Mb (N50 scaffold size = 462 kb) (Table 5.9). While estimated read coverage across the

majority of the scaffolds was consistently 60X, some scaffolds were present in substantially

134

higher coverages (200X or more) and possibly indicate the presence of high copy number

plasmids, actively replicating phages, or emPCR artifacts.

Table 5-9. E. tracheiphila sequencing and assembly statistics

Feature Statistic

Contigs 1130, including 4.4Mb

n50 contig length 22Kb

Average contig length 9.6 Kb

Largest contig size 102 Kb

n50 scaffold size 462 kb

Average scaffold size 174 kb

Number of singleton reads (not integrated into assembly)

19025

Number of reads flagged as repeats (emPCR articfacts, not included in assembly)

10330

Number of assembled reads 1.1 million

Annotation of genomes

Both RAST (Aziz et al. 2008) and an automated annotation transfer tool at the Sanger

Institute (unpublished) were used to annotate the draft genomes of E. tracheiphila. We used

RAST results for the novel regions that were not automatically transferred from the reference

genome E. billingiae. GenePRIMP was used to scan the intergenic regions of E. tracheiphila, E.

amylovora, and E. billingiae for additional CDS and genes too degraded to be called by the

RAST ab initio gene predictor (Pati et al. 2010). GenePRIMP putative gene annotations that 1)

were < 50 AA long and 2) did not have detectable homologs in GenBank and/or 3) overlapped

other coding regions were discarded. Each novel gene prediction was also curated with BLAST

(Altschul et al. 1990) and FASTA (Pearson & Lipman 1988) results, and Pfam (Sonnhammer et

al. 1997) and Prosite (de Castro et al. 2006) were used to identify protein motifs.

Transmembrane domains, signal sequences, and rRNA genes were identified with TMHMM

(Krogh et al. 2001), SignalP(Dyrløv Bendtsen et al. 2004), and BLASTN (Altschul et al. 1990),

135

respectively. ISFinder was also used to detect Insertion Sequence (IS) elements in the genomes

(Siguier et al. 2006). Manual curation was done with these novel regions using Artemis

(Rutherford et al. 2000) and Artemis Comparison Tool (ACT) (Carver et al. 2005).

Comparative Analysis with Sequenced Erwinias ssp.

WebACT and DoubleACT were used to generate figures and compare whole genomes

and specific regions of E. tracheiphila and other bacteria. Amino acid similarity was compared

with the Needle program from the EMBOSS package (Rice et al. 2000). Pairwise Average

Nucleotide Identity between the genomes was calculated using in-house scripts following ANI

definition of (Konstantinidis & Tiedje 2005).

Phylogenetic Analysis

For the Enterobacteriaceae family level tree, nucleotides from ribosomal genes from

Erwinia tracheiphila, Erwinia billingiae Eb1/96, Erwinia amylovora CFBP1430, Pantoea vagans

C9-1, Pantoea anatis LMG20103, Dickeya zeae Ech1591, and Dickeya dadantii Ech703,

Pectobacterium carotovorum subsp. carotovorum PCC21 , Pectobacterium atrosepticum

SCRI1043, Pectobacterium wasabiae WPP163, Salmonella enterica subsp. enterica serovar

Typhimurium str. LT2, E. coli 0157:H7 strain Sakai, Yersinia pestis Nepal516, Yersinia

pseudotuberculosis PB1/+, Photorhabdus luminescens subsp. laumondii TT01, Serratia

proteamaculans 568, Shigella sysenteriae Sd197, Shigella flexneri 2002017, Xenorhabdus

nematophila ATCC 19061, Citrobacter rodentium ICC168, Citrobacter koseri ATCC BAA-895,

Klebsiella pneumonia 342, Enterobacter cloacae subsp. cloacae ATCC 13047 with Haemophilus

influenziae as an outgroup (selected by 16S similarity) were concatenated and aligned in MEGA

(Tamura et al. 2007) and jModelTest was used to identify the proper nucleotide substitution

model (Posada 2008). The alignment was then run in RaxML with 100 boostrap replicates on the

CIPRES server (www.phylo.org) and the .tre file visualized in FigTree (Rambaut 2007).

136

Detection of Laterally Transferred and Phage-related genes

Protein-coding genes of E. tracheiphila genome were used as queries in BLASTP search

against nr database. Homologs with an E-value below 10-4

were kept (up to 50,000 matches per

gene). Using the results of these BLAST searches, candidates for horizontal gene transfer were

identified in DarkHorse program (min_align_coverage=0.7; LPI score < 0.85) (Podell &

Gaasterland 2007). Individual genes identified from DarkHorse or from manual inspection were

analyzed phylogenetically. Alignments of a amino acids of representative sample of all top Blastp

hits were aligned in MEGA. The appropriate substitution model for each alignment was chosen

with ProTest (Abascal et al 2005). The alignment was then run in RaxML with 100 boostrap

replicates on the CIPRES server (www.phylo.org) and the .tre file visualized in FigTree

(Rambaut 2007).

To identify presence of gene homologs in phage pan-genome, protein-coding genes of E.

tracheiphila, E. amylovora CFBP 1430 and E. billingiae Eb661 genomes were used as queries in

BLASTP search against Viral RefSeq database. Hits with E-value below 10-10

and 70% alignment

for both query and subject sequences were kept. CRISPRFinder was used to scan for cas genes

(Grissa et al. 2007).

137

Supplemental Material

Table 5-10. Supplemental table of Darkhorse Output of HGT candidates with COG functional assignments

Preliminary identification of potential HGT candidates identified through Darkhorse with an lineage probability index (LPI) cutoff set at LPI

< 0.85, where lower LPI means the CDS is less like other Erwinia genes and more likely to be an HGT candidate. All hypothetical genes with

no hypothesized function were excluded from the table, as were 24 ribosomal genes. Darkhorse is Blastp based and would not be able to

identify HGT candidates from closely related bacteria, and is likely to miss HGT candidates obtained from other enterobacteriaceae, such as

chitin-associated proteins and attachment structures discussed in the text. The presence of enterobacterial phages and IS elements provides a

possible mechanism explaining the presence of the HGT candidates from enterobacteriaceae present in the E. tracheiphila genome that do not

appear in the table. Genes discussed in the text are starred.

query_id norm_

LPI

Evalue Functional COG Annotated Function species

ETR2251 0.036 1.00E-71 Functional Amino acid transport and metabolism serine A D-3-phosphoglycerate dehydrogenase Saccharomyces cerevisiae FostersO ETR1047 0.427 2.00E-43 Functional Carbohydrate transport and metabolism dTDP-4-dehydrorhamnose 3,5-epimerase Pseudonocardia sp. P1 ETR1789 0.432 5.00E-62 Functional Nucleotide transport and metabolism Uracil phosphoribosyltransferase Streptomyces albus J1074 ETR0899 0.441 9.00E-85 Functional Inorganic Ion Transport and Metabolism Siderophore biosynthesis protein Paenibacillus mucilaginosus KNP414 ETR1277 0.441 5.00E-55 Truncated Carbohydrate transport and metabolism * Extracellular endoglucanase Bacillus subtilis BSn5 ETR2385 0.441 4.00E-27 Functional Coenzyme transport and metabolism Thiamine biosynthesis protein Streptococcus pseudopneumoniae IS7493 ETR2455 0.441 1.00E-94 Functional General Function Only PhnP Metal-dependent hydrolases of the beta-

lactamase superfamily I Paenibacillus sp. HGF7

ETR2456 0.441 7.00E-

126

Functional Carbohydrate transport and metabolism ABC-type sugar transport system, periplasmic

component Paenibacillus sp. HGF7

ETR1313 0.472 6.00E-35 Functional General Function Only Probable acetyltransferase Candidatus Nitrospira defluvii ETR3543 0.472 7.00E-59 Functional DNA replication, recombination, and

repair

D12 class N6 adenine-specific DNA

methyltransferase Desulfurispirillum indicum S5

ETR1048 0.517 2.00E-49 Functional Carbohydrate transport and metabolism UDP-glucose 4-epimerase Arthrospira platensis NIES-39 ETR1049 0.517 5.00E-98 Functional Carbohydrate transport and metabolism putative NDP-hexose methyltransferase

protein Arthrospira platensis NIES-39

ETR2503 0.658 1.00E-54 Functional Cell envelope biogenesis TonB-dependent receptor Bilophila sp. 4_1_30 ETR0128 0.659 2.00E-44 Pseudo General Function Only Competence protein CoiA Pseudogulbenkiania sp. NH8B

138

ETR0338 0.659 3.00E-

109

Functional Transcriptional Transcriptional regulator, Cro/CI family Brucella suis 1330

ETR1785 0.659 1.00E-08 Functional Energy production and conversion D-Lactate dehydrogenase Neisseria meningitidis CU385 ETR3017 0.659 7.00E-24 Functional Signal transduction mechanisms Response regulator receiver domain protein

(CheY- like) Nitrobacter hamburgensis X14

ETR3367 0.659 9.00E-

116

Functional Secondary metabolites biosynthesis,

transport and cataboism

* Isopentenyl-diphosphate delta-isomerase,

FMN- dependent Mesorhizobium loti R7A

ETR3370 0.659 4.00E-97 Functional Secondary metabolites biosynthesis, transport and cataboism

* Geranyltranstransferase (farnesyldiphosphate synthase)

Mesorhizobium loti R7A

ETR3372 0.659 8.00E-94 Functional Secondary metabolites biosynthesis,

transport and cataboism

* 3-oxoacyl-[acyl-carrier protein] reductase Mesorhizobium loti R7A

ETR3376 0.659 2.00E-

140

Functional Secondary metabolites biosynthesis,

transport and catabolism

* Putative cytochrome P450 hydroxylase Mesorhizobium loti R7A

ETR0451 0.66 3.00E-70 Pseudo Carbohydrate transport and metabolism Short chain dehydrogenase Achromobacter xylosoxidans AXX-A ETR0604 0.66 1.00E-50 Functional Amino acid transport and metabolism n-acetylmuramoyl-l-alanine amidase Burkholderia dolosa AUO158 ETR0833 0.66 3.00E-87 Functional Coenzyme transport and metabolism Manganese ABC transporter, ATP-binding

protein SitB Agrobacterium tumefaciens F2

ETR0834 0.66 2.00E-81 Functional Coenzyme transport and metabolism Manganese ABC transporter, inner membrane permease protein SitC

Agrobacterium tumefaciens F2

ETR0900 0.66 1.00E-59 Functional Translation, Ribosomal structure, and

biogenesis

Methionyl-tRNA synthetase-related protein Ralstonia solanacearum Po82

ETR0901 0.66 4.00E-11 Pseudo Coenzyme transport and metabolism FAD-dependent oxidoreductase Burkholderia gladioli BSR3 ETR1045 0.66 1.00E-

104 Functional Carbohydrate transport and metabolism Glucose-1-phosphate cytidylyltransferase Rhizobium etli IE4771

ETR1185 0.66 1.00E-

154

Functional Translation, Ribosomal structure, and

biogenesis

miaB tRNA-i(6)A37 methylthiotransferase Cupriavidus necator N-1

ETR1539 0.66 6.00E-64 Functional Amino acid transport and metabolism N-acetylmuramoyl-L-alanine amidase Burkholderia dolosa AUO158 ETR1540 0.66 1.00E-51 Functional General Function Only Uncharacterized protein ImpD Burkholderia sp. CCGE1002 ETR1766 0.66 2.00E-28 Pseudo Coenzyme transport and metabolism NAD(P)H-flavin oxidoreductase Ralstonia solanacearum Po82 ETR2957 0.66 3.00E-32 Pseudo General Function Only Acetyltransferase Rhizobium etli CNPAF512 ETR3009 0.66 7.00E-63 Functional Translation, Ribosomal structure, and

biogenesis

gcp gcp YgjD/Kae1/Qri7 family, required for

threonylcarbamoyladenosine (t(6)A) formation in tRNA

Agrobacterium tumefaciens F2

ETR3371 0.66 3.00E-

147

Functional Secondary metabolites biosynthesis,

transport and cataboism

* Cytochrome P450 Rhizobium etli CNPAF512

ETR3373 0.66 1.00E-14 Functional Secondary metabolites biosynthesis,

transport and cataboism

* Uncharacterized p450-system 3fe-4s

ferredoxin Rhizobium etli CNPAF512

ETR3374 0.66 2.00E-146

Functional Secondary metabolites biosynthesis, transport and cataboism

*Putative cytochrome P450 hydroxylase Rhizobium etli CNPAF512

ETR3375 0.66 6.00E-

158

Functional Secondary metabolites biosynthesis,

transport and cataboism

* Cytochrome P-450 Rhizobium etli CNPAF512

ETR3416 0.66 2.00E-29 Pseudo Amino acid transport and metabolism Plant-induced nitrilase, hydrolyses beta-cyano-

L-alanine Achromobacter xylosoxidans AXX-A

ETR3774 0.66 2.00E-132

Truncated Cell motility and secretion xopAG putative avrgf1 family effector/xanthomonas outer protein

Acidovorax citrulli AAC00-1

139

ETR3869 0.66 8.00E-

149

Functional Signal transduction mechanisms Sensory transduction system regulatory protein Rhizobium leguminosarum bv. trifolii WSM2304

ETR3963 0.66 2.00E-19 Functional Plasmid Addiction module toxin, RelE/StbE family

protein Achromobacter xylosoxidans C54

ETR0118 0.708 2.00E-07 Functional Transcription Putative transcriptional regulator Thiomonas sp. 3As ETR1276 0.8 3.00E-93 Truncated Carbohydrate transport and metabolism * Expansin Saccharophagus sp. JAM-R001 ETR1714 0.8 3.00E-33 Functional Translation, Ribosomal structure, and

biogenesis

Translation initiation factor 1 Idiomarina sp. A28L

ETR1902 0.8 4.00E-39 Pseudo Amino acid transport and metabolism soxA sarcosine oxidase, alpha subunit Halomonas sp. TD01 ETR1985 0.8 9.00E-18 Pseudo General Function Only Glyoxalase/bleomycin resistance

protein/dioxygenase Salinisphaera shabanensis E1L3A

ETR2283 0.8 2.00E-52 Functional Translation, Ribosomal structure, and

biogenesis

trmB tRNA (guanine46-N7-)-

methyltransferase Salinisphaera shabanensis E1L3A

ETR2807 0.8 6.00E-100

Functional Cell motility and secretion outF general secretion pathway protein Shewanella pealeana ATCC 700345

ETR3158 0.8 0 Pseudo Cell envelope biogenesis xopAM xopAM xanthomonas outer protein

am Xanthomonas vesicatoria ATCC 35937

ETR3444 0.8 5.00E-

172

Functional Energy production and conversion adhC S-(hydroxymethyl)glutathione

dehydrogenase Glaciecola sp. 4H-3-7+YE-5

ETR3960 0.8 5.00E-29 Functional Plasmid HigB toxin protein Methylophaga aminisulfidivorans MP ETR0025 0.801 0 Functional Lipid transport and metabolism ToxR-activated gene TagA Aeromonas veronii B565 ETR0375 0.801 3.00E-

175

Functional Inorganic Ion Transport and Metabolism hemE Uroporphyrinogen III decarboxylase Aeromonas veronii B565

ETR0499 0.801 2.00E-173

Functional Amino acid transport and metabolism dctA Aerobic C4-dicarboxylate transporter for fumarate, L-malate, D-malate, succunate

Aeromonas veronii B565

ETR1223 0.801 1.00E-

124

Functional Lipid transport and metabolism sucD Succinyl-CoA ligase [ADP-forming]

alpha chain Aeromonas veronii B565

ETR1289 0.801 8.00E-66 Functional Defense Mechanisms Organic hydroperoxide resistance protein Acinetobacter calcoaceticus PHEA-2 ETR2011 0.801 0 Functional Intracellular trafficking Putative transport protein Aeromonas veronii B565 ETR2806 0.801 5.00E-43 Functional Cell motility and secretion General secretion pathway protein G Aeromonas veronii B565 ETR2823 0.801 1.00E-16 Functional Energy production and conversion ATP synthase C chain Aeromonas veronii B565 ETR2843 0.801 1.00E-

114 Functional Carbohydrate transport and metabolism 2-deoxy-D-gluconate 3-dehydrogenase Aeromonas veronii B565

ETR2944 0.801 1.00E-21 Pseudo General Function Only Glyoxalase family protein Aeromonas veronii B565 ETR3123 0.801 1.00E-53 Functional Amino acid transport and metabolism argR Arginine pathway regulatory protein

ArgR, repressor of arg regulon Aeromonas veronii B565

ETR3187 0.801 7.00E-33 Functional Translation, Ribosomal structure, and biogenesis

SSU ribosomal protein S18p Actinobacillus minor NM305

ETR3314 0.801 2.00E-70 Pseudo Transcription Transcription elongation factor GreB Aeromonas veronii B565 ETR0137 0.802 0 Functional Amino acid transport and metabolism proP L-Proline/Glycine betaine transporter

ProP Pseudomonas putida S16

ETR0398 0.802 0 Pseudo General Function Only abc transporter related protein Pseudomonas putida S16 ETR0441 0.802 1.00E-

151

Functional General Function Only Alcohol dehydrogenase Pseudomonas putida S16

140

ETR0588 0.802 5.00E-

118

Functional Cell motility and secretion * type III effector HopV1 Pseudomonas savastanoi pv. savastanoi NCPPB 3335

ETR0589 0.802 3.00E-25 Fragment Cell motility and secretion * type III chaperone ShcV Pseudomonas savastanoi pv. savastanoi NCPPB 3335

ETR0745 0.802 1.00E-51 Functional General Function Only Ankyrin repeat Pseudomonas aeruginosa 138244 ETR0773 0.802 2.00E-

180

Pseudo General Function Only Uncharacterized PLP-dependent

aminotransferase YfdZ Pseudomonas aeruginosa NCMG1179

ETR0869 0.802 3.00E-82 Functional Nucleotide transport and metabolism tmk Thymidylate kinase Gallibacterium anatis UMN179 ETR1046 0.802 1.00E-80 Functional Carbohydrate transport and metabolism Similar to CDP-glucose 4,6-dehydratase Pseudomonas putida BIRD-1 ETR1077 0.802 1.00E-52 Functional Energy production and conversion Pyruvate formate-lyase Gallibacterium anatis UMN179 ETR1427 0.802 4.00E-65 Functional Cell motility and secretion * Type III effector HopE1 Pseudomonas syringae pv. morsprunorum

str. M302280PT ETR1521 0.802 9.00E-

136 Functional Carbohydrate transport and metabolism 2-Keto-3-deoxy-D-manno-octulosonate-8-

phosphate synthase Haemophilus haemolyticus M21639

ETR1680 0.802 5.00E-92 Functional Inorganic Ion Transport and Metabolism zntA Lead, cadmium, zinc and mercury

transporting ATPase Pseudomonas aeruginosa NCMG1179

ETR1702 0.802 0 Functional Energy production and conversion pflB Pyruvate formate-lyase Haemophilus haemolyticus M21639 ETR1825 0.802 2.00E-40 Functional Postranslational modification, protein

turnover, chaperones Chaperone Gallibacterium anatis UMN179

ETR1932 0.802 3.00E-65 Functional Cell motility and secretion * Type III effector AvrB4-2 Pseudomonas syringae pv. aesculi str. NCPPB3681

ETR1979 0.802 4.00E-126

Functional Coenzyme transport and metabolism menB Naphthoate synthase Haemophilus haemolyticus M21621

ETR2245 0.802 8.00E-08 Fragment Cell motility and secretion * Type III Effector HopL Pseudomonas syringae Cit 7 ETR2334 0.802 2.00E-

175

Functional Phage * Type III restriction-modification system

methylation subunit Pseudomonas aeruginosa NCMG1179

ETR2661 0.802 3.00E-41 Functional Cell motility and secretion * Type III chaperone protein ShcF Pseudomonas syringae pv. actinidiae str. M302091

ETR2885 0.802 1.00E-

128

Functional Amino acid transport and metabolism dapD 2,3,4,5-tetrahydropyridine-2,6-

dicarboxylate N- succinyltransferase Gallibacterium anatis UMN179

ETR2927 0.802 2.00E-45 Functional Cell motility and secretion * Type iii effector hopa1 Pseudomonas syringae pv. lachrymans str. M302278PT

ETR2928 0.802 9.00E-14 Functional Postranslational modification, protein

turnover, chaperones

* Type iii chaperone protein shca Pseudomonas syringae pv. morsprunorum str. M302280PT

ETR3356 0.802 0 Functional Amino acid transport and metabolism Putative cystathionine gamma-synthase

protein Pseudomonas syringae pv. aesculi str. NCPPB3681

ETR3357 0.802 0 Functional Amino acid transport and metabolism Cystathionine gamma-synthase protein Pseudomonas syringae pv. aesculi str. NCPPB3681

ETR3711 0.802 0 Functional Translation, Ribosomal structure, and biogenesis

prfC Peptide chain release factor 3 Haemophilus haemolyticus M21639

ETR3829 0.802 0 Functional Carbohydrate transport and metabolism lpdA Dihydrolipoamide dehydrogenase Gallibacterium anatis UMN179 ETR3974 0.802 1.00E-26 Functional Transcription Putative transcriptional regulator Haemophilus haemolyticus M21639 ETR3998 0.802 6.00E-39 Functional General Function Only putative acetyltransferase Pseudomonas putida GB-1

141

ETR4049 0.802 1.00E-46 Pseudo Postranslational modification, protein

turnover, chaperones

* TypeIII Chaperone ShcF Pseudomonas syringae pv. glycinea str. race 4

ETR4050 0.802 2.00E-45 Functional Cell motility and secretion no data Pseudomonas syringae pv. maculicola str. M6

ETR0865 0.803 2.00E-49 Functional Nucleotide transport and metabolism YcfF/hinT protein: a purine nucleoside

phosphoramidase Vibrio anguillarum 775

ETR1790 0.803 1.00E-60 Functional Transcriptional Regulator Transcriptional regulator, MarR family Photobacterium angustum S14 ETR0037 0.804 0 Functional Translation, Ribosomal structure, and

biogenesis Translation elongation factor LepA Vibrio parahaemolyticus RIMD 2210633

ETR0390 0.804 1.00E-87 Functional Transcription Transcription antitermination protein NusG Vibrio parahaemolyticus RIMD 2210633 ETR0444 0.804 8.00E-

104

Functional Carbohydrate transport and metabolism kduD 1 2-deoxy-D-gluconate 3-dehydrogenase Vibrio parahaemolyticus RIMD 2210633

ETR0508 0.804 0 Functional Amino acid transport and metabolism ilvD Dihydroxy-acid dehydratase Vibrio parahaemolyticus RIMD 2210633 ETR0683 0.804 2.00E-

148

Functional Translation, Ribosomal structure, and

biogenesis

tRNA(Cytosine32)-2-thiocytidine synthetase Vibrio parahaemolyticus RIMD 2210633

ETR0898 0.804 6.00E-25 Functional Energy production and conversion GCN5-related N-acetyltransferase Vibrio harveyi 1DA3 ETR1175 0.804 7.00E-

135 Pseudo Carbohydrate transport and metabolism chitinase [Vibrio sp.

RC341]gi|260840089|gb|EEX66684.1|

chitinase [Vibrio sp. R

Vibrio sp. RC341

ETR1423 0.804 3.00E-89 Functional DNA replication, recombination, and repair

Endonuclease III Vibrio parahaemolyticus RIMD 2210633

ETR1731 0.804 7.00E-37 Functional Postranslational modification, protein

turnover, chaperones

Glutaredoxin 1 Vibrio mimicus SX-4

ETR1791 0.804 0 Functional Secondary metabolites biosynthesis,

transport and cataboism

Peptide synthetase Vibrio nigripulchritudo ATCC 27043

ETR1802 0.804 1.00E-173

Functional Amino acid transport and metabolism metE metE 5-methyltetrahydropteroyltriglutamate--

homocysteine methyltransferase

Vibrio parahaemolyticus RIMD 2210633

ETR1812 0.804 6.00E-67 Functional Coenzyme transport and metabolism Molybdenum cofactor biosynthesis protein MoaC

Vibrio cholerae HE48

ETR1826 0.804 2.00E-18 Functional Cell motility and secretion * F17 fimbrial protein precursor Vibrio furnissii CIP 102972 ETR1953 0.804 8.00E-

102

Functional Nucleotide transport and metabolism upp Uracil phosphoribosyltransferase Vibrio parahaemolyticus RIMD 2210633

ETR2032 0.804 7.00E-100

Functional Translation, Ribosomal structure, and biogenesis

truA tRNA pseudouridine synthase A Vibrio parahaemolyticus RIMD 2210633

ETR2156 0.804 2.00E-53 Functional Coenzyme transport and metabolism Queuosine biosynthesis QueD, Vibrio cholerae HE39 ETR2448 0.804 1.00E-

179

Functional Lipid transport and metabolism ispG 1-hydroxy-2-methyl-2-(E)-butenyl 4-

diphosphate synthase Vibrio parahaemolyticus RIMD 2210633

ETR2462 0.804 2.00E-

161

Functional Amino acid transport and metabolism Cysteine desulfurase Vibrio parahaemolyticus RIMD 2210633

ETR2472 0.804 4.00E-48 Functional Postranslational modification, protein

turnover, chaperones

glnB glnB Nitrogen regulatory protein P-II Vibrio parahaemolyticus RIMD 2210633

ETR2615 0.804 5.00E-63 Functional DNA replication, recombination, and

repair

Single-stranded DNA-binding protein Vibrio cholerae C6706

142

ETR2763 0.804 0 Functional Transcription Transcription termination factor Rho Vibrio parahaemolyticus RIMD 2210633 ETR2866 0.804 3.00E-46 Functional Cell motility and secretion Leader peptidase (Prepilin peptidase) Vibrio parahaemolyticus RIMD 2210633 ETR2881 0.804 7.00E-

112

Functional Nucleotide transport and metabolism pyrH pyrH Uridylate kinase Vibrio cholerae HE-09

ETR3103 0.804 5.00E-81 Functional Amino acid transport and metabolism aapP ABC-type polar amino acid transport

system, ATPase component Vibrio parahaemolyticus RIMD 2210633

ETR3140 0.804 0 Functional Cell division and chromosme partitioning Rod shape-determining protein MreB Vibrio parahaemolyticus RIMD 2210633 ETR3146 0.804 0 Functional Lipid metabolism accC Biotin carboxylase of acetyl-CoA

carboxylase Vibrio parahaemolyticus RIMD 2210633

ETR3286 0.804 5.00E-115

Functional Signal transduction mechanisms Cyclic AMP receptor protein Vibrio parahaemolyticus RIMD 2210633

ETR3650 0.804 4.00E-83 Functional Energy production and conversion Inorganic pyrophosphatase Vibrio parahaemolyticus RIMD 2210633 or3215 0.891 Pseudo Signal transduction

mechanisms N-3-oxooctanoyl-L-homoserine lactone synthase @ N-3-oxohexanoyl-L-homoserine lactone synthase

Enterobacteriaceae bacterium 9_2_54FAA

or0797 0.907 Functional Plasmid Lipoprotein Arsenophonus nasoniae

or0108 0.907 Functional Plasmid ETR0104 IncF plasmid conjugative transfer mating signal transduction protein TraM

Arsenophonus nasoniae

or0096 0.907 Functional Cell motility and

secretion putative type iii secreted effector protein Photorhabdus luminescens subsp. laumondii TTO1

or2494 0.907 Functional Carbohydrate transport

and metabolism

ABC-type sugar transport system, periplasmic component Proteus mirabilis HI4320

or3475 0.907 Truncated Carbohydrate transport

and metabolism exochitinase Sodalis glossinidius str. morsitans

or0752 0.907 ETR0742 rhamnogalacturonate lyase Pectobacterium wasabiae WPP163

or0450 0.907 Functional General Function Only Alcohol dehydrogenase Pectobacterium wasabiae WPP163

or2850 0.908 Functional Cell motility and

secretion

outF general secretion pathway protein Dickeya dadantii Ech586

or2849 0.908 Functional Cell motility and

secretion

General secretion pathway protein G Dickeya dadantii Ech586

or0926 0.908 Functional Carbohydrate transport

and metabolism ETR0915 Membrane-bound lytic murein transglycosylase B precursor

Dickeya dadantii Ech586

143

or0504 0.908 Functional Carbohydrate transport

and metabolism ETR0494 Rhamnogalacturonate lyase precursor (Rhamnogalacturonase)

Dickeya dadantii Ech586

or2107 0.908 Functional General Function Only ETR2077 xylanase-like protein Xenorhabdus nematophila ATCC 19061

or3600 0.908 Functional Cell motility and

secretion ETR3553 PilL Edwardsiella ictaluri 93-146

or0117 0.909 Funtional Plasmid ETR0113 Plasmid conjugative transfer endonuclease Yersinia pestis

or3511 0.909 Funtional Plasmid ETR3465 Plasmid conjugative transfer endonuclease Yersinia pestis

or0440 0.909 Functional Cell motility and

secretion ClpB protein 500647:503337 reverse MW:98700 Yersinia pestis Antiqua

or0429 0.909 Functional General Function Only IcmF-related protein Yersinia pestis Antiqua

or2634 0.909 Functional Cell motility and

secretion Type IV secretory pathway, VirB4 components Yersinia pestis Z176003

or2644 0.909 Functional Cell motility and

secretion Type IV secretory pathway, VirD4 components Yersinia pestis Z176003

or0441 0.909 Functional Cell motility and

secretion Protein ImpG/VasA Yersinia pestis Z176003

or2651 0.909 Functional Cell motility and

secretion PilL Yersinia pestis Z176003

or1593 0.909 Functional Carbohydrate transport

and metabolism Chitinase Yersinia pseudotuberculosis PB1/+

or0003 0.909 Functional Intracellular trafficking

and secretion type vi secretion system vgr family protein Yersinia pseudotuberculosis PB1/+

or0144 0.909 Functional Cell envelope, outer

membrane Putative pertactin family virulence factor/autotransporter precursor

Yersinia pseudotuberculosis PB1/+

or0447 0.909 Functional Cell envelope Putative OMPA family outer membrane porin precursor Yersinia pseudotuberculosis PB1/+

or0109 0.909 Functional Plasmid IncI1 plasmid conjugative transfer putative membrane protein PilT

Yersinia ruckeri ATCC 29473

144

or3673 0.909 Functional Cell motility and

secretion fimbrial biogenesis outer membrane usher protein Enterobacter cancerogenus ATCC 35316

or1798 0.909 Functional Cell envelope, outer

membrane ETR1769 virulence-related outer membrane protein Serratia odorifera 4Rx13

145

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Chapter 6

Conclusions

The research described here takes a systems biology approach to understanding

interactions in a co-evolved pathosystem comprising the wild gourd Cucurbita pepo ssp. texana,

the bacterial wilt pathogen Erwinia tracheiphila, the striped cucumber beetle vector Acalymma

vittatum, and Zucchini Yellow Mosaic Virus (ZYMV). This work was prompted by the notable

sparsity of basic or applied knowledge about E. tracheiphila, and began by specifically

addressing the mechanisms underlying epidemiological patterns in experimental fields where

instances of co-infection in the same host are significantly lower than would be expected by

chance. From that observation, we first tested 1how pathogen effects on host phenotype indirectly

affect vector foraging behavior and disease exposure; 2whether there are direct interactions

between ZYMV and E. tracheiphila in a shared host plant;3 quantitative dynamics of beetle

colonization by E. tracheiphila using molecular methods; and 4genomic comparisons to

understand microbial evolution and disease emergence.

Pathogen infection can change host phenotype in ways that directly alter a hosts contact

with transmitting vectors, and can also indirectly alter a host’s exposure to other pathogens. Here,

I describe how volatile organic compounds released from the leaves and flowers of healthy and

pathogen-infected wild gourd plants mediate exposure to the bacterial wilt pathogen through

vector attraction, and how viral infection induces a host volatile phenotype that reduces exposure

to foraging beetles. A. vittatum acquire E. tracheiphila by feeding on symptomatic, wilting

foliage of infected plants, and transmit the pathogen when infective frass falls on leaf herbivory

wounds or floral nectaries of healthy plants. Feeding preference tests showed that beetles will

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preferentially feed on leaves of either E. traceiphila or ZYMV-infected seedlings relative to

healthy seedlings, but in field plantings virus-infected plants have less beetle damage and lower

incidence of wilt disease than healthy plants. In both field and greenhouse experiments, I found

that infection with E. tracheiphila induces the emission of a unique volatile blend from

symptomatic wilting foliage relative to asymptomatic foliage on infected plants, healthy foliage,

and ZYMV-infected foliage, and that floral volatile emission is suppressed by both E. tracheiphila

and ZYMV infection relative to healthy plants. Behavioral assays show beetles are more attracted

to volatiles from wilting leaves relative to healthy foliage, but prefer flowers on healthy plants

relative to viral or bacterial infected plants. Taken together, E. tracheiphila-induced volatiles

provide a mechanism by which beetle vectors are more attracted to symptomatic wilt-infected

foliage relative to non-symptomatic leaves on the same plant, healthy foliage, or virus-infected

leaves through inducing the release of a unique volatile blend from wilting leaves. Beetle vectors

are more attracted to the increased number of flowers and higher concentration of volatiles per

flower on healthy relative to infected plants, suggesting a plausible ecological mechanism

through changes in host-plant volatile phenotype affect interactions with beetle vectors for both

infected and healthy hosts. ZYMV reduces exposure of virus infected host plants to E. tracheiphila

through suppressing floral volatile emission and not inducing foliar volatile release.

While ZYMV – infected plants experience reduced exposure to foraging beetle vectors,

virus infected plants may also be less susceptible to subsequent infection with E. tracheiphila

through induction of non-specific immune responses. Systemic acquired resistance (SAR),

characterized by accumulation of PR proteins and enhanced cell lignification is often observed in

plants induced with biotic or abiotic stresses, and are less susceptible to subsequent pathogen

challenge. Salicylic acid (SA) is a defense signaling hormone that has an essential role in the

induction of SAR. Here, I show that E. tracheiphila suppresses SA induction in host plants soon

after inoculation and after symptoms develop. This finding is similar to several other bacterial

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pathogens that have been shown to secrete effector proteins that specifically inhibit SA signaling.

SA levels in ZYMV-infected plants are significantly higher than E. tracheiphila or mock-infected

plants. Despite elevated SA levels in ZYMV – infected plants, both ZYMV - infected and healthy

plants exhibit the same rates of infection with E. tracheiphila in controlled inoculation

experiments. Products of the octadecanoid pathway (JA, LA, LNA) were measured in undamaged

and herbivore damaged healthy, E. tracheiphila, and ZYMV – infected plants. JA is induced in

all three treatments after herbivory, and patterns of induction of JA, LA, and LNA suggest that

induced herbivore defenses mediated by the octadecanoid pathway are not the determining factor

affecting beetle preference for pathogen – infected (either E. tracheiphila or ZYMV) leaves

compared to healthy leaves in dual choice feeding tests.

To better understand the relationship between E. tracheiphila and A. vittatum, we

developed a qPCR method using Taqman probes specific to an E. tracheiphila outer membrane

protein (OmpA) and 18S as a normalizing gene to examine the acquisition and retention

parameters of E. tracheiphila. I found acquisition of E. tracheiphila to average ~80%, but long-

term retention increases significantly for longer exposure (24hr) compared to shorter exposure

(3hr) time. E. tracheiphila exhibits complex colonization dynamics of the beetle digestive tract:

Large amounts of bacteria are observed in both beetle and frass immediately after an acquisition

access period. At 5 days post acquisition, median bacterial levels have are the same in the whole

insect but significantly less in frass. By 28 days post acquisition, the median bacterial ratio in the

whole beetle is again not different, but there is significantly more bacteria shed in frass. From

these data, I infer that colonization of the insect in a persistent manner is inefficient. The bacteria

that do colonize then enter a growth and colonization phase where little bacteria is shed. By 28

days, there is significantly more bacteria being shed in frass compared to the amount of bacteria

shed at 5 days. Inoculation experiments with frass collected from groups of beetles 0, 5, and 28

days after an acquisition access period showed that higher bacterial concentrations observed in

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frass at 0 and 28 days post AAP correlates with higher inoculation success in wild gourd

seedlings. Results from several fitness assays suggest that E. tracheiphila does not affect A.

vittatum fecundity or longevity, and that E. tracheiphila is therefore a facultative, neutral

commensal within A. vittatum.

An absence of genetic sequences from E. tracheiphila hinders further work understanding

bacterial interactions with hosts and vectors. To address this, we used 454 Titanium chemistry to

sequence an E. tracheiphila culture isolated from wild gourd planted at the PSU Rock Springs

Research Farm to 60-80X coverage and conducted a comparative analysis with other closely

related, plant associated enteric bacteria. I found that the closest sequenced relative to E.

tracheiphila is the non-pathogenic rosaceous floral epiphyte and symbiont E. billingiae, although

E. tracheiphila expresses many virulence traits shard with E. amylovora. The E. tracheiphila

genome is characterized by significant inversions and rearrangements, and an influx of

proliferating insertion sequences and replicating phage that likely encourage massive genomic

recombination. Horizontal gene transfer analysis detects the presence of many putative HGT

events for functions important for both plant virulence and insect colonization. E. tracheiphila is

also undergoing genome reduction through pseudogenization, although notably, core biosynthetic

and metabolic pathways are conserved, suggesting E. tracheiphila is reducing towards a

facultative, niche-adapted species that will retain much of the metabolic machinery of free living

enterobacterial species. The inclusion of the E. tracheiphila genome greatly reduces the size of

the hypothesized core Erwinia genome. My analysis identifies likely determinants influencing

plant and insect interactions and suggests directions for future functional analyses.

In an applied setting, this research has direct applications for the design of sustainable

pest control strategies in agricultural systems. Leaf volatiles provide an herbivore-specific cue

that could supplant previous insecticide-laced diabroticite traps that emulate floral volatiles, and

attracted many non-target floral pollinators that are often inadvertently attracted to the floral

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blend baited traps. A more quantitative understanding of bacterial colonization dynamics of insect

vectors and the publication of the E. tracheiphila genome sequence will also offer novel avenues

for basic and applied research (Bocsanczy et al. 2008). While many of the results presented in

this dissertation are idiosyncratic to the Cucurbita pathosystem, larger questions are raised. This

research provides a framework for approaches to other complex pathosystems, where multiple

herbivores and pathogens are co-circulating (Knops et al. 1999). Genetic homogeneity

characteristic of modern agriculture (Stukenbrock & McDonald 2008) and the development of

farmland in formerly wild areas of domesticated plant and animal populations is creating

unprecedented spillover and opportunities for host jumps and emergence of new disease threats

(Conn et al. 2002). Understanding how pathogens interact in complex ecosystems and the

molecular and ecological factors driving their emergence will be key to creating effective

prevention and control strategies.

Understanding mechanisms of microbial persistence in environmental reservoirs as

important drivers of disease dynamics (Leroy et al. 2005; Snitkin et al. 2012) is being recognized

as an increasingly important factor driving some disease outbreaks, and a potential target for

pathogen control. For example, enterobacterial disease agents have historically been researched in

the context of a pathogenic agent to the plant or animal host on which the bacterium produces

disease. Many recent outbreaks of enteric food-borne pathogens were transmitted through

contaminated plant material and the ability of food-borne enteric pathogens like Salmonella

typhimurium (Schikora et al. 2008), and virulent strains of Escherichia coli (Cooley et al. 2003)

to persistently colonize crop plants and create disease outbreaks with important public health

consequences is now widely recognized (Brandl 2006). However, bacterial persistence outside of

its disease host, either in the environment or in an alternative host, are increasingly understood as

integral to disease cycles and transmission to new hosts (Holden, Pritchard, & Toth, 2008). For

obligately insect-borne diseases, interactions with vectors determine disease dynamics

157

(Hinnebusch 1996; Hinnebusch et al. 2002; Sarkar et al. 2010; Zhang et al. 2011). Detailed

understanding mechanisms of persistence in vectors, how pathogens are shed and healthy hosts

exposed, and ecological factors mediating vector attraction to infected and healthy hosts, will all

contribute to successful containment strategies.

High throughput sequencing technology is providing especially rapid development in the

field of microbial ecology, evolution, and pathogenomics and providing the unprecedented

opportunity to make vast contribution towards understanding the ecology and evolution of non-

model organisms and systems (Earl et al. 2008). These are leading to great advances in disease

ecology, where the molecular and genetic processes underlying ecological interactions can now

be affordably described, greatly increasing our understanding of host-microbe interactions

(Bäckhed et al. 2005; Broderick et al. 2006) for bacteria of ecological (Ffrench-Constant et al.

2003; Hofmann et al. 2005), public health (Chain et al. 2004), and agricultural interests (Kay

2009).

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159

VITA

Lori R. Shapiro

EDUCATION

Ph.D. in Entomology 2007-2012

Pennsylvania State University

B.S. Biology, B.S. Ecology, B.S.E.S. Entomology

Certificate in International Agriculture 2001-2006

University of Georgia

PUBLICATIONS

Ecology Letters July 2012

“Pathogen effects on vegetative and floral odors mediated vector

attraction and host exposure in a complex pathosystem”

FELLOWSHIPS and AWARDS

University Fellowship 2007-2008

National Science Foundation Graduate Fellowship 2008-2010

USDA Microbial Genomics Training Fellowship 2010-2012

FIELD EXPERIENCE

2007-2011

Field work at Russell E. Larson Experimental Farm at Rock Springs, PA to document

interactions between wild gourd Cucurbita pepo ssp. texana, the striped cucumber beetle

Acalymma vittatum, and several endemic diseases in a field setting

Oct-Nov 2009

Survey of the wild gourd Cucurbita argyrosperma in the Mexican states of Jalisco,

Michoacán, Guerrero, and Oaxaca in collaboration with researchers from Universidad

Nacional Autonoma de Mexico (UNAM)

OUTREACH and VOLUNTEER 2007-2012

Participation in over 40 separate science education and outreach events on the PSU

campus and in the surrounding community. Events and responsibilities included:

Coordinating the Entomology department’s display at Exploration Days, leading Frost

Entomology Museum insect biology programs for visiting school groups, leading

laboratory activites for Women in Science and Engineering summar cams, conducting

conservation and education programs at local nature centers, libraries, and elementary

schools

160