The Pennsylvania State University

The Graduate School

Department of Entomology

FUNGAL PARASITES THAT MANIPULATE ANT BEHAVIOR: TOWARD A

MECHANISTIC UNDERSTANDING OF AN EXTENDED PHENOTYPE

A Thesis in

Entomology

by

Maridel Anne Fredericksen

 2016 Maridel Anne Fredericksen

Submitted in Partial Fulfillment of the Requirements for the Degree of

Master of Science

August 2016

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The thesis of Maridel Anne Fredericksen was reviewed and approved* by the following:

David P. Hughes Assistant Professor of Entomology and Biology Thesis Advisor

Christina M. Grozinger Distinguished Professor of Entomology

Thomas C. Baker Distinguished Professor of Entomology

István Mikó Research Associate

Gary W. Felton Department Head of Entomology

*Signatures are on file in the Graduate School

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ABSTRACT

Parasite manipulation of host behavior represents an extended phenotype of a parasite’s genes through a host’s body. Studying the proximate mechanisms by which a parasite induces abnormal behavior in its host can help us understand how behavior in general is regulated and how such specialized symbioses evolve. Fungi from the species complex Ophiocordyceps unilateralis manipulate ants to die in elevated locations that are suitable for the fungus to transmit to new hosts.

This association provides a promising system to discover mechanisms of manipulation using new molecular tools. However, current progress in this system is limited because we lack a cellular context with which to interpret –omics data, and research so far has focused on only a handful of the hundreds of species that exist in nature.

In this thesis, I use two approaches to explore this fungal parasite’s exploitation strategies and their effects on ant behavior. In Chapter 2 I provide a context for molecular studies by characterizing the cell-level interactions between parasite and host during manipulated host biting behavior. Using three-dimensional microscopy and automated image-segmentation techniques, I demonstrate that the fungus invades host muscle fibers and joins together to form extensive fungal networks throughout the ant’s body. In Chapter 3 I expand our current knowledge on the diversity of the manipulation by comparing transmission strategies of several fungal species. I reveal that infected ants in the Brazilian Amazon display species-specific patterns in biting behavior, and I show that the fungi infecting these ants exhibit periodic patterns of spore release. These findings serve as parameters for future studies to discover the processes underlying these patterns. Overall, the results from this thesis advance the field toward a mechanistic understanding of behavioral manipulation by parasites.

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TABLE OF CONTENTS

List of Figures ...... vi

List of Tables ...... vii

Acknowledgements ...... viii

Chapter 1 Introduction ...... 1

Behavioral Manipulation: progress and limitations ...... 2 Ophiocordyceps unilateralis s.l.: a promising new system ...... 4 Thesis objectives ...... 7

Chapter 2 Life inside a controlled ant: 3D visualization reveals fungal parasite networks in manipulated hosts ...... 10

ABSTRACT ...... 10 SIGNIFICANCE ...... 11 INTRODUCTION ...... 11 RESULTS ...... 15 O. unilateralis s.l. and B. bassiana are present throughout the host and cause gross changes in muscle fiber arrangement...... 15 The fungus O. unilateralis s.l. invades muscle fibers and forms fusions between fungal cells ...... 16 Fungal fusions create extensive networks ...... 18 DISCUSSION ...... 19 MATERIALS and METHODS ...... 23 Infection and Sample Collection ...... 23 Histology ...... 25 Serial Block-Face Scanning Electron Microscopy ...... 25 Data collection...... 26 Statistical Analysis ...... 27 Deep Learning Model ...... 27 ACKNOWLEDGEMENTS ...... 28

Chapter 3 Zombie ant diversity in a Brazilian rainforest: relating extended phenotype to transmission ...... 34

ABSTRACT ...... 34 INTRODUCTION ...... 35 METHODS ...... 38 Field Collections ...... 38 Spore Clocks ...... 39 Identification ...... 40 Biting substrates ...... 41 Data Analysis: Interaction Network ...... 42

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RESULTS ...... 42 Host biting location ...... 42 Timing of spore release ...... 45 DISCUSSION ...... 47 Biting location: Infected ants show species-specific patterns ...... 48 Timing of spore release: Fungi show consistent patterns ...... 52 ACKNOWLEDGEMENTS ...... 54

Chapter 4 Conclusions and Future Directions ...... 64

Appendix A Supplementary Material for Chapter 2 ...... 69 Appendix B Supplementary Material for Chapter 3 ...... 76 Ant morphospecies descriptions ...... 76 REFERENCES...... 83

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LIST OF FIGURES

Figure 2-1. Distribution of O. unilateralis s.l. in the host body ...... 30

Figure 2-2. Fungal abundance in muscle tissue ...... 31

Figure 2-3. Fungal behaviors observed in O. unilateralis s.l.-infected ant muscles ...... 32

Figure 2-4. 3D reconstruction of fungal networks surrounding muscle fibers...... 33

Figure 3-1. Ant/plant interaction network ...... 55

Figure 3-2. Ant/substrate interaction network ...... 56

Figure 3-3. Diversity of ants found on spiny palms compared to non-spiny palms ...... 57

Figure 3-4. Biting locations of ants on spiny palms ...... 58

Figure 3-5. Volume of spore release for all specimens combined ...... 59

Figure 3-6. Spore count over two days ...... 60

Figure 3-7. Timing of peak spore release ...... 61

Figure 3-8. Phylogenetic placement of spore clock specimens in O. unilateralis clade .... 62

Figure A-1. Infection setup ...... 73

Figure A-2. Biting ants at the time of collection ...... 74

Figure B-1. Sampling location ...... 79

Figure B-2. Spore clock experiment ...... 80

Figure B-3. What “rules” direct infected ants to a biting location? ...... 81

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LIST OF TABLES

Table 3-1. Mean ants on plants ...... 63

Table A-1. Ants infected with O. unilateralis s.l...... 75

Table A-2. Ants infected with B. bassiana ...... 75

Table B-1. Timing of spore release across all samples ...... 82

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ACKNOWLEDGEMENTS

A lot of great people made it possible for me to complete this thesis, more than I will be able to mention here, but I want to show my appreciation to at least several key contributors. First, I would like to thank my advisor, David Hughes, for showing me how I could open windows into the natural world and also for his patience, encouragement, and incredible support during this journey. Also, thank you to my thesis committee for challenging me intellectually and offering valuable insights into my research. Next, I am grateful to those who taught me skills that I will take with me for the rest of my life. One of the major lessons and challenges of graduate school seems to be figuring out how to acquire knowledge when it is not being spoon-fed to you, and these people were all very patient as I stumbled through that process. Thank you to all the members of the Hughes lab, especially Emilia Solá Gracia for helping me learn my way around the lab in the beginning, Dr. Raquel Loreto for guiding me through much of the research process and always being willing to answer my many questions, João Araújo for putting up with me in Brazil and for always sharing his passion for fungi with me in the lab and the field, Lauren Quevillon for always being level- headed and for easing my frustrations with learning R, and Ben Fowler for showing me how to continue his research in the Amazon. Missy Hazen, John Cantolina, and Greg Ning taught me how to use the fancy microscopes in the basement, and István Mikó helped me interpret the output from the microscopes and taught me everything I know about insect morphology. And to Antônio Tavares Mello, thank you for sight-identifying all the plants in my second chapter, singing with me in the rainforest, and teaching me Portuguese! There are also many people who selflessly gave their time, energy, or other resources so that I could do my research. These include Ryan Bringenberg for keeping the lab running smoothly, Kim Fleming for welcoming us to her home to collect all of our lab ants and fungi, Saad Ahmad for digitizing hundreds of my histology slides, Melissa Ishler for helping with my PCRs and Fabricio Baccaro and José Neto for ensuring my samples arrived safely. I would also like to thank my collaborator and co-author, Yizhe Zhang, for always being so communicative, thorough, gracious, and just great to work with overall. For statistical support, a huge thank you to Damie Pak, who spent many hours helping me troubleshoot R graphics, and also to Jim Russell, Colbie Reed, Spencer Carran, and the students at the Statistical Consulting Center, Data Learning Center, and the We “R” group. For help in the final stretch with this writing thing, I need to thank the Monday morning writing group (Maggie Douglas, Loren Rivera, and Brittany Dodson) for keeping me on track, Ted and Mackenzie at the Graduate Writing Center for helping me organize my ideas, and Carolyn Trietsch and Gretchen Fredericksen for invaluable help with revising and editing. For moral support and general encouragement, I would like to thank my colleagues in the Entomology Department, especially Kevin Cloonan, Carolyn Trietsch, Duverney Chaverra Rodriguez, Kyle Burks, Briana Ezray, Joyce Sakamoto, Dave Galbraith, Áine O’Sullivan, Carley Miller, Erin Treanore, Asher Jones, Mali Döke, Jo Ohm, Becky Johnson, Megan Wilkerson, and Anjel Helms. And of course thank you to my mother, father, and sister for always believing in me and for coming with me on walks in the woods.

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I dedicate this thesis to my good friend, Luca Franzini, one of the most passionate people

I have ever known and who, in just one year, taught me more about loving science and loving life than I had learned in 26 years. Sogni d’oro, amore mio.

Drawing by Luca Franzini

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Chapter 1

Introduction

Among the many beautiful sights we can witness on a walk in the woods is evidence of parasites manipulating their hapless hosts: spiders spinning cocoon-shaped webs to protect wasp larvae (Eberhard 2000), the colorful and pulsating eye stalks of a trematode-infected snail

(Wesenberg-Lund 1931), or the elegant stroma of a fungus that has sprouted from an ant’s body

(Tulasne and Tulasne 1865). But how are these amazing phenotypes generated? Understanding the pathways from genotypes to phenotypes is a puzzle that scientists across disciplines from genetics and developmental biology to neurobiology and physiology have been piecing together ever since

Mendel first crossed his pea plants (Johannsen 1911).

Dawkins (1982) put forward the idea that genes can have effects outside an organism’s own body and can even express themselves through the body of another organism. This kind of

“extended phenotype” can be seen in parasites that change the phenotype of their hosts for their own benefit. It should not be surprising that many parasites have evolved such an ingenious life history strategy when we consider that more than half of the species that exist on Earth are parasites

(Price 1980), and their genomes are often in conflict with the genomes of their hosts. Sometimes this conflict manifests as morphological changes in the host, such as in the thickened shells of parasitized snails (Cheng 1973, Dawkins 1982). Other times it appears as behavioral changes in the host. Studying these behavioral changes and the mechanisms parasites use to induce them are important goals in their own right as we aim to understand biological diversity, but as Adamo

(2013) points out, we can also better understand how normal behavior arises by studying

“evolution’s neurobiologists”.

2 Behavioral Manipulation: progress and limitations

The study of behavioral manipulation by parasites is still a relatively young field, and only recently have researchers begun to explore the underlying mechanisms in any significant detail.

Pioneering work by Bethel and Holmes helped pave the way for more experimental studies on a range of parasites and hosts (Bethel and Holmes 1973, 1974, 1977), and Dawkins’ Extended

Phenotype provided a conceptual framework for the field (Dawkins 1982). Early studies focused mainly on describing the natural history of different systems and working out the lifecycles of the parasites (Moore 2002). Much time and effort was spent trying to understand the ultimate basis for host behavior changes, and debates raged about what constitutes adaptive manipulation and whether some behavioral alterations might be better categorized as pathogenic byproducts or host compensatory responses (Moore et al. 1990, Poulin 1995, Poulin 2000, Thomas et al. 2005). Poulin advocated putting this debate on adaptiveness to rest when he revised his original four criteria for adaptive manipulation (Poulin 1995) and instead argued for a single criterion: a demonstrated fitness benefit to the parasite (Poulin 2010). Over the past decade studies have moved away from debates on ultimate explanations and have focused more on understanding the proximate causes for behavior alterations.

Researchers have made significant strides toward revealing the mechanisms in a handful of host/parasite systems by capitalizing on previous advances in model organisms from other research areas. For example, gypsy moths and their pathogens have been studied for over 100 years due to their impact on the forest industry in North America (Andreadis and Weseloh 1990). This background knowledge allowed researchers to use genetic recombination methods to demonstrate that a mutation in a single baculovirus gene alters climbing behavior in gypsy moth caterpillars

(Hoover et al. 2011). Similarly, researchers interested in how jewel wasps manipulate cockroach behavior (Fouad et al. 1994, Libersat 2003) were able to apply foundational knowledge from early

3 neuroethology studies (Pringle 1939, Pearson and Fourtner 1975) to pinpoint the location of the wasp’s sting in the cockroach brain and analyze the detailed neurological effects on the host (Fouad et al. 1996). One of the most well-known parasites, the apicomplexan Toxoplasma gondii has been extensively studied in the medical community due to its effects on human health (Weiss and Dubey

2009, Lorenzi et al. 2016, Tosh et al. 2016). Recent work on this system has confirmed that parasites can manipulate host behavior through epigenetic effects (Hari Dass and Vyas 2014), a strategy which had been previously proposed in the field but not addressed experimentally (Poulin 2010,

Adamo 2013).

Research using the model systems mentioned above has led to critical advances in the field of behavioral manipulation by parasites, but studies in these systems and others also tend to raise more questions than they answer. It is becoming apparent that many parasites use complex, indirect, and multi-pronged strategies that have proven difficult to piece together into a clear mechanistic picture (Adamo 2013). What is clear is that there are many ways for parasites to manipulate behavior, and since manipulative parasites and their hosts occur widely across the tree of life, it is necessary to study this phenomenon in a broad range of systems.

Studies focusing on non-model organisms have been important for increasing the taxonomic diversity of the field, but progress in these systems has been limited because researchers lack many of the tools that are available for the model systems mentioned above. In most of these non-model systems, methods for laboratory infections have not been developed, so researchers can only study the host/parasite interactions they find in nature. Another challenge has been the limited molecular toolkit for these systems. In the gammarid/acanthocephalan system that was the subject of the classic Bethel and Holmes studies, researchers have studied the effects of molecules that are known to be important for manipulation in other systems (Helluy and Holmes 1990, Helluy 2013), but they do not currently have reliable methods to identify and characterize mechanisms that may be unique to their particular study system. This is a problem because parasites and their hosts vary

4 widely in their phylogenetic placement, and parasite manipulation strategies are thought to evolve rapidly (Moore and Gotelli 1996), so we cannot assume that distantly related parasites will manipulate their hosts through the same molecular mechanisms.

David Biron has advocated parisito-proteomics as a way to uncover novel mechanisms in non- model organisms (Biron and Loxdale 2013). Biron and colleagues first developed this approach to study host-parasite cross-talk that leads to suicidal behavior in nematomorph-infected orthopterans

(Biron et al. 2005, Biron et al. 2006), and their work suggests that this parasite can manipulate its host by mimicking host proteins. However, limitations of this technique include challenges of sorting through the huge amounts of data that proteomics studies produce as well as issues of replicability. If we compare host/parasite cross-talk to a verbal conversation, proteomics studies give us the words that are used, but not the order in which they are spoken nor the context of the discussion. Despite the current challenges, the increasing use of new and more sensitive proteomics tools coupled with advanced bioinformatics methods that can decipher interactomes (the set of protein interactions in an organism) suggest that proteomics will likely be a powerful tool for many host/parasite systems (Biron and Loxdale 2013, Chetouhi et al. 2015).

Ophiocordyceps unilateralis s.l.: a promising new system

The fungus Ophiocoryceps unilateralis sensu lato (s.l.) represents a promising system for uncovering the mechanisms of manipulation. This parasite’s lifecycle makes it amenable to laboratory experiments, its phylogenetic history offers ample opportunity for comparative studies, and its classification as a microbe broadens the taxonomic diversity of known manipulating parasites. Field and laboratory studies have already identified key parameters of the parasite’s extended phenotype, and great advances in this system may soon be possible using parasito-

5 proteomics and other molecular tools (Hughes 2013, Hughes et al. 2016). A better understanding of the cell-level interactions and diversity across species will make such advances possible.

In nature, ants that are host to O. unilateralis s.l. become infected on their foraging trails by spores that attach to their cuticle. After entering the ant’s body, the fungus proliferates over several weeks and then induces the ant to leave its nest and die attached by its mandibles to an elevated location that is suitable for fungal growth and dispersal (Andersen et al. 2009). The manipulated biting behavior that precedes host death can also be induced by injecting ants with spores in the laboratory, making this one of the few systems in this field in which laboratory infections are possible (de Bekker et al. 2014).

The manipulation appears to be species-specific, with an estimated 580 associations occurring world-wide (Araújo and Hughes 2016, and unpublished data). Furthermore, the biting behavior of infected ants closely resembles that of ants infected with several more distantly-related parasites, including the trematode Dicrocoelium dendriticum (Hohorst and Graefe 1961). These characteristics offer many opportunities for comparative studies—on convergent strategies between unicellular and metazoan parasites and also on divergent strategies between co-evolved species pairs.

Last year Robert Poulin called for more empirical studies on a wider taxonomic range of behavior-manipulating parasites (Poulin and Maure 2015). Although he advocated primarily for studies on a wider variety of parasitic worms, parasitic microbes are also taxonomically diverse and under-represented in current studies of behavioral manipulation. Microbes may also prove to be especially valuable to the field because microbial parasites that do not have a brain likely use different manipulation strategies compared to parasites that do have a brain. Fungal parasites such as O. unilateralis s.l. therefore add much-needed taxonomic diversity to the study of behavioral manipulation.

6 Research so far on this system has yielded important clues as to how the manipulation might be regulated. Field studies across continents have characterized some of the parameters of this extended phenotype. Light microscopy images revealed that mandible muscles of biting ants are surrounded by fungi and show atrophy, which may help lock the ants’ jaws in a “death grip”

(Hughes et al. 2011). The biting behavior can be very precise, occurring within a narrow height range and at a certain time of day (Andersen et al. 2009, Hughes et al. 2011). The substrate on which the ants bite varies across regions, with tropical species tending to bite leaves or modified leaves and temperate species tending to bite twigs (Loreto et al. in prep).

Laboratory studies using species from North America have begun to delve into the proximate causes of the biting behavior. Metabolomics studies revealed that the fungus can distinguish ant brain tissue from muscle tissue and also identified many chemicals, including known neuromodulators, that could play a role in manipulation (de Bekker et al. 2014). Transcriptomics studies on both parasite and host corroborated this evidence for neuromodulation but also revealed that most of the fungal genes upregulated during manipulation are unique to O.unilateralis s.l. and have completely unknown functions (de Bekker et al. 2015, Loreto et al. in prep).

Although the previous work on this system has been informative, progress in deciphering the proximate mechanisms is hindered by our limited ability to effectively interpret the results from – omics studies. This challenge can be partially overcome by using a well-chosen positive control to reduce molecular “noise” not associated with manipulation (Loreto et al. in prep), but we still lack a functional and developmental context for the molecular interactions. Laboratory work has investigated the host/parasite relationship at the level of ant behavior and molecular regulation, but very little is known about what is happening inside the ant at the level of cells and tissues. In addition, our knowledge on the extended phenotype of this fungal parasite through the body of its host is limited to studies on only a handful of species from the O. unilateralis complex. In order to

7 understand how this parasite manipulates its host, it is important to study the extended phenotype of the parasite at many levels and also across several host/parasite species pairs.

Thesis objectives

In this thesis, I advance our current understanding of the O. unilateralis s.l. extended phenotype by 1) providing a cellular context for interpreting and directing molecular studies and 2) comparing the parasite’s transmission strategies across several species. In so doing, I hope to move us toward a mechanistic understanding of how this parasite controls the behavior of its host.

My approach to studying the extended phenotype can be explained using an analogy to another extended phenotype that Dawkins used as the subject for many of his thought experiments: a termite nest (Dawkins 1982). If we wanted to study how termites create their nests, we might start by comparing the structures of many termite nests. We would find that some characteristics are common to all nests and may have been selected for over evolutionary time. As we studied more nests we would come to have a very good sense of the patterns and parameters that govern nest building behavior. But at some point, if we wanted to find out how these patterns are created, we would need to study the termites themselves. We could then relate the termites’ individual characteristics to the overall patterns we see at the level of the entire termite mound. In a sense, we need to “retract” the extended phenotype by tracing it back to the organism in which the genes reside. Extended phenotypes are emergent systems; higher levels of the extended phenotype emerge from lower levels, and it is often impossible to infer the parameters of one level from studying a different level. Therefore, to understand how Ophiocordyceps unilateralis s.l. manipulates its ant hosts to bite, we need to study this system at the many levels that exist between genotype and phenotype. We have compared the extended phenotype across continents, and we have retracted it

8 all the way to the level of the transcriptome, but there are still many levels in between that we do not understand.

In Chapter 2, I “retract the phenotype” to the level of individual fungal cells inside the ant’s body. Using new and powerful tools in electron microscopy and image segmentation, I examine the three-dimensional interactions between fungal cells and ant muscle fibers. Such a cell-level approach allows us to directly observe and characterize the intimate interactions between this parasite and its host. I compare the parasite’s structure, distribution, and behavior to those of a generalist pathogen and look for clues as to how the parasite genes could be leveraging their power to replicate themselves using the host as a vehicle. I demonstrate that the individual fungal cells fuse with each other to form fungal networks that surround muscle fibers, and I show that fungi can invade host muscle fibers. With this study, I offer a new perspective on this parasite by directly observing how it interacts with its host on the cellular level. Knowledge of the parasite’s cellular behavior and localization within the host provides a necessary context for designing studies that use parasito-proteomics, which was developed to bridge “the gap between our understanding of the genome sequences and cellular behavior” (Biron and Loxdale 2013). This knowledge will thus provide a foundation that can inform more specific studies comparing actions of individual cells.

In Chapter 3, I establish the parameters of the study system by characterizing the extended phenotype across several species in the Brazilian Amazon. We need well-defined patterns if we want to find the rules that generate those patterns, and studying the diversity in gross phenotypic traits between species gives us a basis for comparison on deeper levels. I analyze the transmission strategies of the parasites in terms of host biting location and timing of fungal spore release. Biting location has been compared across continents (Loreto et al. in prep) but not at a local scale, and a temporal pattern of spore release was previously described for a single species (Fowler et al. in prep) but not across species. The present comparative study will help us determine which aspects of this fungal parasite’s transmission strategy are common among individuals and species.

9 The results from this thesis add insights into the lifecycle of O. unilateralis s.l., its cellular characteristics, and the diversity of its extended phenotype. This knowledge will provide a foundation for more targeted molecular and developmental studies in this system, and the techniques used here will also be applicable to studies on behavioral manipulation in other systems by complementing powerful new molecular approaches like parasito-proteomics. These future studies should continue to combine comparative and proximate approaches to piece together the mechanistic puzzle underlying behavior control by parasites.

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Chapter 2

Life inside a controlled ant: 3D visualization reveals fungal parasite networks in manipulated hosts

Maridel Fredericksen1, Yizhe Zhang2, Missy Hazen3, Danny Chen2 and David Hughes1

1Department of Entomology, The Pennsylvania State University, University Park, PA

2Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN

3Huck Institutes of the Life Sciences Microscopy and Cytometry Facility, The Pennsylvania State

University, University Park, PA

ABSTRACT

Studying the intimate interactions between parasites and their hosts is crucial to understanding parasite exploitation strategies. These strategies sometimes include the adaptive manipulation of host behavior by the parasite, resulting in increased fitness for the parasite. We combine new techniques in serial block-face scanning electron microscopy and deep learning image segmentation algorithms to visualize the cell-level interactions between a fungal parasite and its ant host. We examine the structure, distribution, and behavior of the fungus at a crucial moment in its lifecycle: when the manipulated host bites onto vegetation before being killed. Fungi of the species-specific parasite Ophiocordyceps unilateralis sensu lato were found to invade host muscle cells and join together to form a large network of fungal cells. These interactions were found in both the head and leg muscles of the host. The collective behavior in fungal networks may be an important part of the parasite’s exploitation strategy, allowing the transport of nutrients and

11 other cell contents across the fungal colony both during the manipulation event and immediately after death as the fungus converts ant tissue into fungal spores for future transmission.

SIGNIFICANCE

Microbial parasites may need to behave collectively to manipulate their host’s behavior, but microbial parasites remain poorly understood, especially in terms of their within-host dynamics.

In this study, we examine the adaptations of a microbial parasite in its natural environment: the body of its co-evolved and manipulated host. Electron microscopy images and 3D reconstructions of host and parasite tissues reveal that this fungus invades muscles in multiple segments of the ant’s body and that fungal cells in these regions fuse to form extensive networks. The fusions are likened to conidial anastomosis tubes, which have been studied in plant-pathogenic fungi and which aid in the transport of nutrients and organelles across the fungal colony. Although the adaptive significance of these fusions in the present system remain unknown, we demonstrate a collective behavior of a fungus infecting an animal host. The present study lays a foundation for more targeted questions on the mechanisms of behavioral manipulation in this system, and the techniques used here may be applied to future studies on adaptations of microbes in their natural environment.

INTRODUCTION

Many of the most familiar parasites that control behavior are animals: parasitoid wasps induce spiders to spin protective webs for the wasp larvae (Eberhard 2000, Takasuka et al. 2015); hairworms cause their cricket hosts to jump into water and die while the hairworm swims free

12 (Thomas et al. 2002); trematodes living in killifish brains pass to their definitive host by causing the fishes’ body to contort in ways that attract predatory birds (Lafferty and Morris 1996). However, many behavioral changes in animals are the result of parasitic microbes, and these represent a broad taxonomic range of parasites, including unicellular Trypanosomes (class Kinetoplastida) that alter salivary composition and feeding behavior in tsetse flies (Van Den Abbeele et al. 2010), fungi such as Pandora and Ophiocordyceps that induce ants to die in an elevated location suitable for parasite dispersal (Marikovsky 1962, Andersen et al. 2009), and the well-studied apicomplexan Toxoplasma gondii, which induces a fatal feline attraction in its rodent hosts (Berdoy et al. 2000).

Although animals and microbes can both manipulate their hosts’ behaviors and often do so in ways that appear very similar, parasites from these two groups have likely evolved different strategies for achieving manipulation. Microbial parasites face a massive size asymmetry in relation to their hosts. This asymmetry likely presents unicellular parasites with distinct challenges that are not experienced by metazoan parasites. A single hairworm, which causes its cricket host to commit suicide in water, fills most of the cricket’s hemocoel and can produce host-mimicking proteins to alter the cricket’s behavior (Thomas et al. 2002, Biron et al. 2005). In contrast, an individual T. gondii parasite that is less than 5µm in diameter (Dubey et al. 1998) and invades one of the estimated 4 million neurons in the mouse brain (Roth and Dicke 2005) presumably cannot produce enough metabolites on its own to influence the biochemical environment of its host’s body.

However, T. gondii often occurs as cysts of several thousand individuals (Dubey et al. 1998). It may be that successful host manipulation requires microbial parasites to display collective behavior.

Although microbes were long considered single-celled organisms that rarely interact, the emerging consensus from studies of biofilm formation and other coordinated behaviors is that many microbes not only interact but also cooperate to display a collective behavior (Strassmann et al. 2000, Nadell et al. 2008, Albuquerque and Casadevall 2012, Celiker and Gore 2013). An

13 intriguing possibility, then, is that parasitic microbes that control their hosts may be similarly capable of group-level behaviors, which could allow these unicellular organisms to overcome the size asymmetry between them and the hosts they adaptively manipulate. However, to date, studies of microbial behavior have necessarily taken place in reduced laboratory environments rather than the more complex arena of a living body. But in order to investigate potential collective behaviors in microbial parasites, we must study them in their natural habitat: the body of their host. Pathology studies on humans and agricultural pests have demonstrated the importance of cell-level interactions between parasites and hosts (Angus 1954, Wang and St Leger 2007, Kubica et al. 2008,

Wanchoo et al. 2009, Sakaguchi et al. 2016), and these studies provide a toolbox of microscopy techniques that can be applied to new systems of microbial parasites that control animal behavior.

Studies in a handful of microbial systems have already made advances toward uncovering the proximate mechanisms of behavior manipulation. Hoover et al. (2011) found that a mutation in a single virus gene changes climbing behavior in gypsy moth larvae by causing the caterpillar to produce an enzyme that inactivates one of its own molting hormones. This is currently the only known system in which a single parasite gene is responsible for manipulating the behavior of its host. The most well-studied microbial parasite to date is the apicomplexan Toxoplasma gondii

(Flegr 2015). Although a detailed mechanism remains obscure, it is clear that T. gondii forms cysts inside neurons (Dubey et al. 1998), where it changes brain function by altering methylation (Hari

Dass and Vyas 2014) and dopamine metabolism (Prandovszky et al. 2011). Despite the progress in this system, the fact that T. gondii is localized in the brain of its host means it does not represent the majority of behavior-manipulating parasites, which are largely known to control behavior from outside the central nervous system (Moore 2002, Lafferty and Shaw 2013). It would be useful, then, to study a microbial parasite that similarly manipulates behavior from outside the brain. This would provide us a better basis for comparison to macroparasites (such as the hairworms discussed above)

14 and a better chance at discovering the mechanistic differences between the exploitation strategies of unicellular versus metazoan parasites that control animal behavior.

One system that potentially offers some benefit is the complex manipulation of insect behavior by the fungus Ophiocordyceps unilateralis sensu lato (s.l.). Members of this species complex are obligate parasites of ants from the tribe Camponotini (Andersen et al. 2009), which can easily be collected in the field and infected in the lab (de Bekker et al. 2015). As with other entomopathogenic fungi, O. unilateralis s.l. enters its host through the cuticle as a single spore that then proliferates to fill the insect’s body (Charnley 1989). Before killing its host, this fungus induces the ant to bite onto a plant in a location that is apparently suitable for the fungus to grow and disperse (Andersen et al. 2009). This conspicuous biting behavior is an unambiguous signal of successful manipulation and allows researchers to identify the moment when a host is being manipulated. Previous work showed that O. unilateralis s.l. induces a distinct atrophy in mandible muscles of the worker ants manipulated to bite leaves (Hughes et al. 2011), and this atrophy was suggested to play a role in the biting behavior. The effects of this parasite on its host’s muscles may thus provide an opportunity to discover how a microbe could influence its host from outside the brain.

Until recently, researchers have relied on two-dimensional microscopy techniques to visualize cell-level interactions between host and parasite, but new advances in electron microscopy allow us to examine these spatial relationships in 3D. Serial block-face scanning electron microscopy (serial block-face SEM) was developed less than fifteen years ago, primarily to study the structure of neural circuits and to investigate other problems in biology that required the use of

3D data (Denk and Horstmann 2004). The few studies that have applied this technique to insect systems have demonstrated its value to advancing knowledge in insect morphology and host- parasite interactions (Hörnschemeyer et al. 2012, Friedrich et al. 2014, Sakaguchi et al. 2016). One

15 of the major drawbacks of this and other 3D-EM methods thus far has been the time-consuming process of manual image segmentation and 3D reconstruction (Hughes et al. 2014).

In the present study, we combine serial block-face SEM with a newly-developed method of automatic image segmentation that uses machine learning to distinguish host and parasite tissue.

This approach allows us to compare the three-dimensional structure, distribution, and behavior of fungal cells in multiple body segments of manipulated ants. We also visualize ants infected with the generalist pathogen Beauveria bassiana, which belongs to the same fungal order (Hypocreales) as O. unilateralis s.l. but does not manipulate its host as part of its lifecycle. This fungus thus serves as an important positive control, which allows us to compare a pathogen that might need to operate collectively with one that does not. We report that the species of fungus from the

Ophiocordyceps unilateralis complex that infects Camponotus castaneus invades muscle tissue in multiple body segments and forms fungal networks through cell-cell fusions, which we suggest could represent a type of collective behavior for this parasite.

RESULTS

O. unilateralis s.l. and B. bassiana are present throughout the host and cause gross changes in muscle fiber arrangement.

Histological sections examined with light microscopy reveal that O. unilateralis s.l. fungal cells are present in all three body sections (head, alitrunk, and gaster) of the ant host (Fig. 2-1).

Serial block-face SEM sections from both O. unilateralis s.l. and B. bassiana infected ants reveal greater spacing between muscle fibers when compared with control samples, and fungal cells were present between the muscle fibers in both the head and leg regions (Fig. 2-2: a-f).

16 We compared the abundance of fungal tissue present in mandible muscles of ants infected with O. unilateralis s.l. and B. bassiana. To measure the relative abundance of fungus in our image stacks, we used an algorithm developed using deep learning to automatically segment out the fungus tissue and ant muscle tissue in the SEM images (see full description in methods). Ants infected with Ophiocordyceps unilateralis s.l. showed a median fungal abundance (volume of fungal tissue divided by combined volume of muscle and fungal tissue) of 10.06% (n = 8 ants, range = 4.09% – 38.19%) compared to a median of 2.09% (n = 8 ants, range = 0.30% – 52.28%) for ants infected with B. bassiana (Fig. 2-2: g-i). The distribution of abundances for these two fungal species was not significantly different (Wilcoxon rank-sum; W = 16, n1 = n2 = 8, p = 0.1049).

The fungus O. unilateralis s.l. invades muscle fibers and forms fusions between fungal cells

Individual fungal cells inside the body of the insect are termed hyphal bodies (Samson et al. 2013). We examined the 3D structure of these hyphal bodies using serial block-face SEM. The hyphal bodies were elongate and cylindrical, approximately 20 µm long but ranging in length from approximately 9 µm to 30 µm, and usually had one or more septa (i.e. cross walls in the cell that divide the cells but allow for nutrient and organelle trafficking between compartments) (Fig. 2-3: a). Some of these hyphal bodies had converted from the hyphal body stage to the tissue-invasive mycelial (Myc) cell phenotype where hyphae grow from one or both poles of the hyphal body (Fig.

2-3: a, arrowheads). Many hyphal bodies were also connected to other hyphal bodies through short septated tubes approximately 1µm long (Fig. 2-3: b, arrows, inset). This fusion behavior, or anastomosis, was unique to O. unilateralis s.l. in our study (8 ants examined and 99.9 million cubic micrometers of muscle). We found no evidence of anastomosis between B. bassiana cells in a total of 6.9 million cubic micrometers of tissue examined across samples (8 ants examined). We do not think the different volumes (99.9 vs. 6.9 million cubic micrometers) account for this difference

17 between fungal species since anastomosis was found abundant and discovered immediately in the first ant examined. Variation in cell density also does not seem to account for the difference because ants infected with B. bassiana showed similar fungal abundance compared to ants infected with O. unilateralis s.l. (Fig. 2-2: g), but zero B. bassiana samples showed anastomosis between fungal cells.

We further investigated the rates of anastomosis to determine the extent of this fusion behavior and to compare trends across ants as well as between body segments of the same ant (Fig.

2-3: d). Out of all O. unilateralis s.l. hyphal bodies examined across samples of infected ants, 59%

(n=1,014) were connected to at least one other hyphal body. The number of connections for a single hyphal body ranged from 0 to 6, with a mean of 1.15 connections per cell (n=1,014, s.d.

1.16). We modeled the fusion rate (number of connections per cell) using a generalized linear mixed-effects model (GLMM), and we found that ant status (alive vs. dead) was a significant predictor of fusion rate (p < 0.05), whereas location (head vs. leg) was not (p = 0.589). In a separate model, we found that infection period (spring vs fall) was a significant predictor of fusion rate

(p<0.001), whereas location (head vs. leg) was not (p=0.659).

We examined the interactions of O. unilateralis s.l. fungal cells with ant muscle fibers and found that muscle fibers in all ants had fungal cells directly touching their membrane. In five out of eight ants, the fungi had also penetrated the membrane and entered the muscle cells (Fig. 2-3: c, e). These penetrating structures were fungal hyphae, which are filamentous projections from the hyphal bodies that are specialized for foraging in new environments and invading host tissues

(Boucias and Pendland 1998, Ainsworth 2008). The prevalence of this muscle fiber invasion varied widely among samples, with three out of eight samples showing no invasion in any of the muscle cells examined (Ants 6-8; Fig. 2-3: e). Again, we cannot conclude that muscle invasion never occurred in these samples because we examined 99.9 million cubic micrometers of tissue and the total area of muscle in an ant is much greater than this. Although the timing of death is very difficult

18 to ascertain (Hughes et al. 2011), we are reasonably confident that three of the eight ants that we sampled (Ants 1-3; Fig. 2-3: d, e) had died between 2–12 hours before being sampled. It is noteworthy that in these three ants we observed a higher rate of fungal invasion than in ants collected when they were evidently alive (an indication of life is leg and antennal movement in response to stimulus). Of the 5 ants collected before death, only 2 showed invasion of muscle fibers, with 3.33% (1 muscle fiber out of 30) and 6.67% (2 muscle fibers out of 30) of muscle fibers invaded in each sample, respectively. Conversely, of the 3 samples collected after death, all three showed invasion of muscle fibers at rates of 96.67% (29 muscle fibers out of 30), 31% (9 muscle fibers out of 29), and 40% (12 muscle fibers out of 30). Median percent invasion for alive and dead ants were 0 and 40%, respectively. The distributions of the two groups differed significantly

(Wilcoxon rank-sum, W=0, n1=5, n2=3, p<0.05). A separate test revealed that ants collected during the fall infection showed higher rates of muscle fiber invasion than ants collected during the spring infection (Wilcoxon rank-sum, W=16, n1=4, n2=4, p<0.05). We cannot separate the effect of infection period from the effect of ant death status. B. bassiana also invaded muscle cells, but rarely

(8 observations in 6.9 million cubic micrometers of tissue examined).

Fungal fusions create extensive networks

Three-dimensional reconstructions of muscle and fungal tissue allowed us to examine the fusion behavior in more detail (Fig. 2-4). This 3D dataset reveals that the cell fusions create extensive fungal networks that surround muscle fibers. We determined that 23% (n=1,014) of total fungal cells examined lacked contact to any muscle fibers, but that 75% of these were connected to other fungal cells. The 3D reconstruction suggests that anastomosis could allow fungi to have indirect access to the muscles through the fungal network.

19 DISCUSSION

This study reveals the behavior of the fungal parasite Ophiocordyceps unilateralis s.l. in its natural habitat (the ant body) at a time in its lifecycle that is critical for its fitness, namely when it induces its ant host to die in a suitable microhabitat for the parasite’s growth and dispersal

(Andersen et al. 2009, Hughes et al. 2016). We applied new techniques in electron microscopy and machine learning to directly observe and analyze the three-dimensional interactions between parasite and host cells at this crucial moment. In doing so, we revealed some of the strategies this specialist parasite has evolved to exploit the body of its host, and we suggest that such strategies, which constitute a novel example of collective behavior among microbes, may be important for the complex microbial control of ant behavior that distinguishes this interaction.

Light microscopy images revealed that O. unilateralis s.l. hyphal bodies invade all sections of the ant body (Fig. 2-1). We also used serial block-face SEM to visualize the muscle tissues in the head and leg of ants infected with either the behavior-manipulating fungus O. unilateralis s.l. or the generalist fungal pathogen B. bassiana (Fig. 2-2). Both fungal species were present in the interstices between muscle fibers in the head and leg regions.

The widespread distribution of O. unilateralis s.l. throughout the ant’s body suggests that the fungus does not target its invasion to a particular area that may be especially suitable for inducing the death grip biting behavior. This finding contrasts with some other behavior- manipulating parasites such as Polypocephalus sp. tapeworms and Dicrocoelium sp. trematodes, which selectively invade specific regions in the central nervous system of their hosts (shrimp and ants, respectively) (Romig et al. 1980, Carreon and Faulkes 2014). It has been suggested that the non-random localization of some parasites inside their hosts could be related to their ability to manipulate behavior (Carreon and Faulkes 2014). However, our finding suggests that O. unilateralis s.l. may need to use a different strategy to achieve the complex manipulation of host

20 behavior that we observe in infected ants. One possibility is that the fungus could use a division of labor strategy based on its localization within the ant. This idea is supported by an ex vivo metabolomics study, which demonstrated that the O. unilateralis s.l. secretome differs depending on whether the fungus is next to brain or muscle tissue (de Bekker et al. 2014).

We examined interactions between O. unilateralis s.l. and the ants’ muscle fibers as well as between individual O. unilateralis s.l. hyphal bodies (Fig. 2-3). Hyphae invaded muscle fibers in five out of eight ants, and hyphal bodies fused with each other in seven out of eight ants, implying that both invasion and fusion are a common part of the behavioral repertoire for this fungus. Fusion rates appeared to be similar between head and leg but individual ants appeared to vary widely in rates of both invasion and fusion (Fig. 2-3: c, d). This suggests that the fungus was behaving similarly between multiple regions within the same ant, but that the ants we sampled differed from each other in ways that affected the fungal behavior.

These results demonstrate that O. unilateralis s.l cells interact intimately with each other and with host muscle cells. The variation in fungal behavior between ants may have resulted from different infection conditions (eg. fungal material used, light conditions following infection).

Alternatively, the variation may suggest that this parasite’s behavior changes rapidly during manipulation and after host death. This change in fungal behavior would be consistent with metabolomics and transcriptomics data that show changes in the O. unilateralis s.l. secretome and gene expression following host death, indicating a shift from parasitic to saprophytic activity (de

Bekker et al. 2013, de Bekker et al. 2015). Furthermore, other entomopathogenic fungi, including

Beauveria bassiana and Metarhizium spp., along with several zoopathogenic and phytopathogenic fungi, are known to synchronously switch cell phenotypes during in vivo development from yeast- like hyphal bodies to elongated mycelia (Boucias and Pendland 1998, Gauthier 2015). This type of dimorphic development allows these fungi to proliferate and feed undetected in the early infection phase and then invade host tissues during the late infection phase.

21 All ants in our study had been successfully manipulated, but neither fusion nor invasion behaviors were observed in every ant (though we cannot be certain that fusion and invasion did not occur in muscles we did not examine), which may imply that these fungal behaviors are not required components of host manipulation for this parasite. If fusion and invasion are not required for manipulation, it may be that these behaviors instead allow the fungus to acquire nutrients for growth following host death.

Whatever the function, the fusions between hyphal bodies demonstrate that these cells are communicating with each other and suggests that collective behavior could be important for the fitness of this parasite. Fusions between individual fungal cells are common in filamentous fungi that infect plants, where they are termed conidial anastomosis tubes (CATs)(Roca et al. 2005b), but as far as we know this is the first study to demonstrate this behavior for a fungus in an animal host.

Fungal communication and collective behavior have also been demonstrated to occur in other fungi from the same order (Hypocreales) as O. unilateralis s.l. For example, the entomopathogen

Metarhizium rileyi uses quorum sensing to regulate the in vivo switch from vegetative to mycelial growth (Boucias et al. 2016). Quorum sensing is a type of collective behavior and communication mechanism that allows pathogenic bacteria and fungi to synchronously express virulence factors to overcome host defenses (Albuquerque and Casadevall 2012). We speculate that the fusion behavior of O. unilateralis s.l. may have a similar adaptive value for this fungus.

Hyphal bodies that fused extensively with each other formed fungal networks surrounding the muscle tissues. In order to better quantify the spatial relationship between fused hyphal bodies, we created a 3-dimensional reconstruction of a partial fungal network of 25 hyphal bodies surrounding a single muscle fiber (Fig. 2-4). Visualizing the network in this way allowed us to observe the size and shape of the network and also revealed that some cells not directly contacting the muscle fiber are still included within the network and could therefore interact indirectly with the muscle fiber.

22 These networks may provide an avenue for nutrient exchange among the fungal colony.

For example, distant hyphal bodies may gain indirect access to the ant muscles through their connections with adjacent hyphal bodies. Conidial anastomosis tubes allow fused fungal cells to exchange nutrients, organelles, and other information with each other (Fischer-Harman et al. 2012).

This suggests that the range of influence of a single fungal cell may be much wider than the boundaries of its own cell wall. Depending on how large the networks are, it is conceivable that the networks could even create an information highway across the entire body of the ant. The ability to transport nutrients to various parts of the fungal colony may be important for the growth of the fungal stroma and ascoma following death of the host. Dissections of ant cadavers after the formation of these external structures reveal that the fungus is present in distinctive regions that extend throughout the ant’s body and that vary in color, texture, and nutrient content (Andersen et al. 2009). These structures are thought to be used for storing and transporting carbohydrates to the stroma as it grows out of the ant’s body, and the cell fusion behavior we observed in this study could be a precursor to these specialized structures.

In summary, we have shown through the use of serial block-face SEM and automated image segmentation a novel 3D structure of a microbial parasite at the cellular level inside the body of its host. From our observations, we suggest a timeline of fungal behavior around the time of host manipulation and death: During manipulation, the fungus is spread throughout the ant’s body in the form of septated hyphal bodies that surround the ant’s muscle fibers. It may have already switched to the mycelial growth form that invades individual muscle fibers, and it may have started to form networks of fused hyphal bodies. After the ant dies, the fungus continues to invade host tissues and fuse to form networks, which may aid in nutrient transport and formation of the structures that will later emerge from the host’s body to continue the parasite’s lifecycle. This timeline will need to be verified in future work, which should continue to examine fungal behavior at the cellular level over the period of infection and across multiple areas within the ant’s body. We

23 also encourage researchers to apply the techniques used in this study to investigate the within-host dynamics of other behavior-manipulating microbes, which will contribute to our broader understanding of host-parasite coevolution and behavioral manipulation by parasites.

MATERIALS and METHODS

Infection and Sample Collection

Ant and fungus colonies were maintained in the laboratory following procedures detailed in supplementary material. Camponotus castaneus colonies were collected at a field site in

Abbeville county, South Carolina (georeference: 34.375215, -82.346937) in July 2014.

Ophiocordyceps unilateralis s.l. cultures (Strain SC09B, originally collected at the same location as the ants) were grown from ascospores since July 2014. Manipulated ants were collected following artificial infection with fungal material as described previously (de Bekker et al. 2014).

Briefly, fungal material was added to Grace’s medium supplemented with 10% Fetal Bovine Serum

(FBS) and then disrupted using a TissueLyser II (Qiagen) or vortex (VWR). Ants were injected with 1 µL of this suspension on the ventral side of the thorax, underneath one of the forelegs where the cuticle is naturally thinned.

Two infections were performed—one in September 2014 and one in April 2015—and four manipulated ants were collected following each infection for use in the present study. Fungal material used for injection varied between samples and included fresh ascospores shot from an ascoma growing out of a field-collected ant cadaver, hyphae extracted from the gaster of a different ant cadaver, and hyphae grown from ascospores (from a third ant cadaver) in lab culture since July

2014 (strain SC09B). Two different ant colonies were used, one for the fall infection and one for

24 the spring infection (Table A-1). Some sub-colonies were kept in constant conditions (D:D, 26°C) for 17 or 23 days to simulate conditions inside the nest before being moved to an area of natural light, whereas others received a natural light cycle and temperature fluctuations throughout infection. All ants were kept at high humidity and received water and 10% sugar water ad libitum.

Each of the described treatments yielded manipulated ants between 15 and 39 days after infection.

The three control ants used in this study were not injected with fungus but were housed with the ants infected with O. unilateralis s.l. and exposed to the same laboratory conditions.

Manipulated ants displayed a characteristic biting behavior: they had been biting onto one of several available substrates inside the cage for at least ten minutes at the time of collection.

Colonies were checked at least once a day, and samples were collected within twelve hours of initiating biting behavior. Five of these ants were still alive at the time of collection, whereas the other three were already dead.

Ants infected with the generalist pathogen B. bassiana were surface-infected with 2 µL of spore suspension at a concentration of 4.1x108 spores/mL using the same method as described above but without injection. Dry spores of B. bassiana (PSU53, PCK 5/5/14) were kindly provided by Nina Jenkins, Dept of Entomology, PSU. Eight infected ants from two colonies were collected between three and five days after infection when ants were moribund (Heinze and Walter 2010) or within one hour after death (Table A-2).

Collected ants were either dissected immediately using a scalpel (Miltex, size 10) and placed in 0.5 mL fixative (2.5% glutaraldehyde, 2% formaldehyde, 2 mM calcium chloride in 0.15

M cacodylate buffer, pH 7.4) or flash frozen in liquid nitrogen and stored at -80°C to be thawed, dissected, and fixed at a later date. Images from fixed and frozen samples did not show noticeable differences, and a comparison of fixed and frozen samples infected with B. bassiana (which were all collected at the moribund stage or within one hour after death) did not show significant

25 differences in fungal abundance (W = 12, p = 0.343). Fixed samples were stored at 4°C for histology and microscopy.

Histology

Samples were obtained from the left half of the head, anterior half of the thorax, and anterior half of the gaster. Samples were then embedded in paraffin wax and sectioned at 8 µm using a microtome (Shandon Finesse), dewaxed using a slide stainer (Shandon Gemini), and stained using methylene blue.

Serial Block-Face Scanning Electron Microscopy

The right half of the head and one forecoxa from each ant were prepared for serial block- face SEM according to the protocol of the National Center for Microscopy and Imaging Research,

University of California, San Diego, CA (Deerinck et al. 2010). Briefly, samples were post-fixed in ferrocyanide-reduced osmium tetroxide followed by thiocarbohydrazide-osmium liganding

(OTO) and subsequent uranyl acetate and en bloc lead aspartate staining, dehydrated in a graded ethanol series, and embedded in Durcupan resin (Fluka).

Resin-embedded specimens were trimmed with a razor blade to expose muscle tissue. Pin- mounted samples were sectioned using a serial block-face scanning electron microscope (Gatan

3View on Zeiss SIGMA VP-FESEM). Approximately 1200 slices were obtained from each

O.unilateralis s.l. sample and 100 slices for B. bassiana and control samples, all at 100 nm thickness. Digital Micrograph (Gatan) software was used to remove bad planes and align image stacks.

26 Image segmentation and 3D reconstruction were performed using a deep-learning model developed by authors Chen and Zhang, as well as using the programs Avizo and Amira (FEI).

Data collection

Fungus/muscle interaction

A total of thirty muscle fibers were examined from 5–8 images per stack, with images spaced at least 20 µm apart to avoid repeated sampling of fungal cells. In each image, five muscle fibers were randomly chosen for analysis, and we counted the number of fungal cells (hyphal bodies or hyphae) that were invading (inside cell membrane) and contacting (outside cell membrane) each muscle fiber.

Fungus/fungus interaction

A total of approximately 60 O. unilateralis s.l. hyphal bodies were examined from three slices per image stack. From each slice, approximately twenty fungal cells within the muscle fiber matrix were randomly chosen for analysis. Stacks of 300 images were opened in Gatan Digital

Micrograph software and the slice player function used to scroll through the stack in order to determine the number of connections for each fungal cell (hyphal body). We also recorded the number of muscle fibers contacted by each hyphal body.

27 Statistical Analysis

In order to analyze the effects of sample location (head vs. leg) and ant status (alive vs. dead) on the rate of fungal fusion, we modeled fungal fusion rate using a generalized linear mixed- effects model (GLMM) using the function glmer with the package lme4 (Bates et al. 2015) The number of fusions per hyphal body was modeled as an ordinal response, with sample location (head vs. leg), ant status (alive vs. dead), and their interaction (location x status) as main effects, ant ID

(1–8) as a random effect, and sample location nested within ant ID. After testing several models, we found that removing the location and interaction terms and only including status as a main effect yielded the model with the lowest AIC (Akaike information criterion). From this we concluded that the only significant predictor of fusion rates is whether the ant is dead or alive. We validated the model by checking for overdispersion: we plotted the Pearson residuals against the fitted values and found no obvious patterns. We also plotted the residuals for each covariate and for explanatory variables not in the model (slice number), again finding no obvious patterns. We then repeated this procedure but substituting infection (fall or spring) for ant status. We found that each model using infection as a main effect instead of ant status yielded a lower AIC value. From this we concluded that infection was also a significant predictor of fusion rate.

We used a Wilcoxon rank-sum test to determine whether dead ants differed in rates of muscle fiber invasion compared to live ants and whether fungal abundance differed between ants infected with O. unilateralis s.l. and those infected with B. bassiana.

Deep Learning Model

The automated image segmentation used to calculate the relative abundance of fungus and muscle tissue in each sample was performed using a model developed by authors Zhang and Chen

28 (Zhang et al. submitted). To perform quantitative analysis, our first step is to obtain the segmentation of our image data. In the recent years, fully convolutional networks (FCN) have shown promising results in the semantic segmentation (Long et al. 2015). Our problem can be viewed as a special case of the semantic segmentation. The number of the classes is much smaller but the size of the training data is limited. Thus, we need to apply an approach that is different from the original fully convolutional networks which are designed for the general vision tasks. U-net

(Ronneberger et al. 2015) is a specially designed, fully convolutional network for the biomedical imaging data.

We applied the U-Net model for automatic fungus and muscle segmentation. For each stack, we first manually labeled 2 sections to train the model; then the trained model was applied to the remaining sections. We simply stack the segmentation results for each section to form the

3D segmentation.

The accuracy of the segmentation results obtained from the automatic process is further investigated. We marked 1 more section for each stack to form the ground truth data, and calculate the segmentation accuracy by comparing the results given by the model to the ground truth marked by a human expert. For simpler stacks, the F1 score is over 96%, and for harder stacks, the F1 score is over 93% (on voxel level).

Based on the segmentation, we use a computer program to count the number of voxels of fungi, muscles, and other areas, and calculate the ratio of volume for each pair of them accordingly.

ACKNOWLEDGEMENTS

Authors Danny Chen and Yizhe Zhang (University of Notre Dame) developed the deep learning model that was used for automated image segmentation and fungal abundance calculations. Author

Missy Hazen (Penn State Microscopy and Cytometry Facility) was responsible for troubleshooting

29 and performing tissue sectioning using the serial block-face scanning electron microscope. We are grateful to Kim Fleming for inviting us to collect ants and fungus on her land, Nina Jenkins (Penn

State) for providing dry spores of Beauveria bassiana, Greg Ning and John Cantolina (Penn State

Microscopy and Cytometry Facility) for assistance with microscopy and sample preparation, and undergraduate assistant Saad Ahmad (Penn State) for digitizing histology slides.

30

Figure 2-1. Distribution of O. unilateralis s.l. in the host body Infected ant biting in the lab and light micrographs from the head, alitrunk, and gaster of three different ants (all infected with O. unilateralis s.l.). (A) Transverse section of head at 4x magnification. Scale bar = 200 µm. (B) Same region at 100x magnification, showing individual hyphal bodies and fusions between them. Scale = 10 µm. (C) Frontal section of alitrunk, 4x. Scale = 100 µm. (D) Same region at 40x magnification, showing hyphal bodies and muscle fibers. Scale= 20 µm. (E) Section through gaster, 4x. Scale = 200 µm. (F) Same region at 60x showing individual hyphal bodies. Scale = 10 µm. Paraffin-embedded samples were sliced at 8µm and stained with methylene blue. Ant image credit: Dr. Raquel Loreto. Microscopy and figure credit: João Araújo.

31

Figure 2-2. Fungal abundance in muscle tissue Serial block-face SEM images from three different ants representing the three treatment groups in this study. The top row (a through c) are from head samples (mandible adductor muscles), and the middle row are from leg samples (coxal levator or depressor muscles). (a) and (d) represent the control group (uninfected ants). Note that the muscle fibers are densely packed together. (b) and (e) represent ants infected with B. bassiana. Fungal cells (dark gray) are present between the muscle fibers. (c) and (f) represent ants infected with O. unilateralis s.l. Again, fungi are present between the muscle fibers, and some are fused together (inset). Scale bars = 50µm (inset 5µm). (g) shows the percent of fungal tissue (compared to total muscle and fungal tissue) over a volume of 100 serial block-face SEM slices. Each point represents one ant infected with either B. bassiana or O. unilateralis s.l. Red lines represent medians. (h) and (i) show 3D volume projections of two of the 100-image stacks used to obtain the abundance data in (g). These projections were generated from the same samples as (b) and (c), respectively.

32

Figure 2-3. Fungal behaviors observed in O. unilateralis s.l.-infected ant muscles (a) Serial block-face SEM image showing fungal hyphal bodies (HB) and hyphae (arrowheads) invading the spaces between ant mandible muscle fibers (M). Outlined boxes are shown larger in b and c. Scale bar=50µm. (b) Fusion behavior between hyphal bodies (arrows). Scale bar = 10µm. Inset: Close-up of fused hyphal bodies. Scale bar= 1µm. (c) Invasion behavior—hyphae have penetrated the membrane of this muscle fiber and are embedded within the muscle cell (arrows). Scale bar = 10µm. (d) Fusions per hyphal body across leg and head regions for 8 ants. n refers to number of fungi sampled in each area. Asterisk (*) denotes ants that were dead at the time of collection. (e) Invasions per muscle fiber across 8 ants (head only). n refers to the number of muscle fibers examined in each ant. Asterisk (*) denotes ants that were dead at the time of collection

33

Figure 2-4. 3D reconstruction of fungal networks surrounding muscle fibers (a) 3D reconstruction of a muscle fiber (red, mandible adductor) surrounded by a partial network of 25 hyphal bodies (yellow). Fusions between cells are visible as short tubes, and many cells have hyphae growing from their ends. Some of these hyphae have grown along and parallel to the muscle fiber (arrowhead in inset). Colored xyz arrows indicate the angle at which the figure is rotated. This reconstructed was created using Avizo software from a stack of 1000 images, each with a thickness of 50nm. Final image smoothing and 3D PDF credit: Thomas van de Kamp. (b) Two different projections of a 3D reconstruction showing several muscle fibers (blue) and fungal hyphal bodies (red) from the same area as seen in (a). This reconstruction was created using a U-Net deep learning model developed by authors Zhang and Chen.

34

Chapter 3

Zombie ant diversity in a Brazilian rainforest: relating extended phenotype to transmission

Maridel Fredericksen, João Araújo and David Hughes

ABSTRACT

One way to discover the mechanisms that lead from genotype to phenotype is by comparing phenotypic variation in adaptive traits. This approach allows researchers to isolate traits of interest and test for correlated evolutionary changes in those traits. The present comparative study highlights the variation in transmission strategy between species of the behavior-manipulating fungus Ophiocordyceps unilateralis sensu lato (s.l.). We conducted a field survey on the diversity of host ant biting behavior and fungal spore release behavior in the Brazilian Amazon. Specifically, we documented the biting substrate and plant species associated with 629 infected ant cadavers surveyed across 10 transects. In addition, we assessed the timing of spore release for 23 individual fungi representing eight morphospecies of O. unilateralis s.l. We found that several host morphospecies differ in their distribution on plants and biting substrates. In addition, all fungal morphospecies tested exhibited consistent patterns of temporally-focused spore release, with peak spore counts during the night and early morning. The differences and commonalities between members of the O. unilateralis s.l. species complex provide clues as to how this co-evolved parasite manipulates its host’s behavior.

35 INTRODUCTION

Phenotypic variation is the raw material of evolutionary change; it allows organisms to adapt in dynamic environments and to specialize in certain life history strategies. For example,

Puerto Rican Anolis lizards occupying various ecological niches vary in their limb morphology

(Rand 1964, Losos 2009) and behavioral responses to light (Moore et al. 2012). Comparative studies examine the patterns of phenotypic variation in a given trait between several taxa, and such a comparative approach is an invaluable tool in biology to establish patterns in nature and uncover the mechanistic processes responsible for generating those patterns (Carlson 2012, Valena and

Moczek 2012, Jeanson and Weidenmüller 2014). Recent work in comparative genetics demonstrated that light coloration in beach-dwelling mice convergently evolved in two geographically distinct populations through different genetic mechanisms (Steiner et al. 2009). This detailed genetic work was only possible because of several early natural history studies that documented variation in coat coloration in Peromyscus polionotus (Sumner 1929a, b). Thus, studies that describe the gross phenotypic variation in a trait help to establish the parameters of the study system and pave the way for further comparative studies at the molecular level.

Comparative studies can also be used to uncover the processes underlying phenotypes that extend beyond the body of the organism in which the genes reside. Examples of such extended phenotypes (Dawkins 1982) include animal architectures such as termite mounds and spider webs, signals of mate quality such as bowers and nuptial gifts, and also host manipulation by parasites.

In the latter case, many of the behaviors we observe in an infected host have evolved through selection on the parasite’s genes (Hughes et al. 2012). One suggested approach to discovering how such manipulated behaviors arise is to compare the genomes of manipulating parasites with those of non-manipulating parasites (Hughes 2013). For example, using a pathogenic, non-manipulating parasite as a positive control can help researchers narrow down the list of candidate genes in

36 transcriptomics studies (Loreto et al. in prep). Alternatively, one can compare distantly related parasites that have convergently evolved to induce similar behavioral changes in their hosts. Such is the case for three taxonomically distant clades that all induce ants to climb and bite vegetation at specific times of day: the trematode Dicrocoelium dendriticum (Manga-González et al. 2001) and the fungal parasites Pandora formicae and Ophiocordyceps unilateralis s.l. (Andersen et al. 2009,

Malagocka et al. 2015). Finally, another promising approach is to study divergences in evolution: comparing parasites that share a recent common ancestor and exhibit slight but consistent variation in their extended phenotypes. This type of approach has proven successful in many other comparative studies such as those comparing beak sizes in Galápagos finches (Bowman 1961,

Grant 1986, Abzhanov et al. 2006).

The fungal parasite Ophiocordyceps unilateralis s.l. and its ant hosts represent a system that is especially amenable to this type of comparative study. Ants that become infected with this fungus exhibit a stereotyped manipulated biting behavior that varies globally (Andersen and

Hughes 2012, Loreto et al. in prep). Before they die, manipulated ants from all parts of the world attach themselves by their mandibles to a location that is elevated above the forest floor and suitable for fungal growth and dispersal (Andersen et al. 2009, Loreto et al. 2014). However, infected ants in the temperate woods of North America and Japan tend to bite twigs (Van Pelt 1958, Kepler et al. 2011, de Bekker et al. 2014), whereas in tropical Southeast Asia and South America, ants tend to bite leaves or modified leaves (Evans and Samson 1984, Tatiana et al. 2001, Andersen et al.

2009, Loreto et al. 2014, Araújo et al. 2015).

The manipulated biting behavior of infected hosts is part of the transmission strategy for the parasite, and several aspects of this extended phenotype are thought to affect fungal fitness. For example, the host biting location in terms of the vertical height from the ground, compass orientation on the plant, and vicinity to the host ant nest and trails, have all been implicated as adaptive traits for this fungal parasite (Andersen et al. 2009, Hughes et al. 2011, Loreto et al. 2014).

37 The variation in host biting location that occurs globally presumably allows local adaptation and the optimal dispersion of spores in accordance with variation in the environment. The regions where infected ants tend to bite twigs have temperate climates in which plants lose their leaves seasonally. In contrast, regions where ants tend to bite leaves have tropical climates in which plants retain their leaves for many seasons. Loreto et al. (in prep) suggest that this variation in environmental conditions shapes the behavioral manipulation by the fungus, and that substrate biting behavior has shifted at least three times within the O. unilateralis complex.

Although we are learning about broad-scale patterns in variation of the extended phenotype of fungal parasites of ants, we do not know whether the transmission strategy for this fungus also varies on a local scale. Within the tropics, much survey work has established that at the local scale

(national parks, forest patches) it is possible to find several species from the O. unilateralis complex, and each fungus species manipulates a unique ant species from the tribe Camponotini

(Andersen et al. 2009, Pontoppidan et al. 2009, Evans et al. 2011). The Brazilian Amazon contains the greatest number of O. unilateralis s.l. species currently described (Araújo and Hughes 2015,

Araújo et al. 2015) and thus represents an ideal location in which to conduct a comparative study.

Taxonomic descriptions of some of these Amazonian species include natural history observations which suggest that the host cadavers are consistently found in distinctive locations (Araújo and

Hughes 2015). However, the patterns of this suggested ecological diversity have not been systematically documented and described. In addition to host biting location, another fungal trait that may be important for transmission is the timing of spore release. One species in Brazil,

Ophiocordyceps camponoti-atricipis, was shown to release spores only in the early hours of the morning, with a consistent peak between 5am and 6am (Fowler et al. in prep). It was suggested that such a pattern of spore release could serve as a bet-hedging strategy for the fungus to infect new hosts. However, whether this pattern that has been observed for one species also holds true across species within the O. unilateralis complex has not been tested.

38 The goal of this study is to present a more thorough and representative description of the behavioral manipulation induced by Ophiocordyceps unilateralis s.l. that includes variation between species in the Brazilian Amazon. We compare the transmission strategies of several O. unilateralis s.l. species using field surveys and experiments to examine host biting location and timing of fungal spore release. Biting location was categorized according to the species of plant as well as the type of substrate on which the ant was biting (leaf, spine, twig, liana, etc). Spore release was quantified every hour over two nights. Comparisons between species reveal different patterns in host biting location but similar patterns in the timing of fungal spore release. The observed variation in host biting location may reflect differences in either ecology or morphology (or both) of the different ant species. The consistent patterns in spore release suggest that temporally-focused spore release may be an evolved trait of the O. unilateralis species complex. We can use the variation and similarities within and between species to formulate testable hypotheses about how, mechanistically, the fungus controls its host.

METHODS

Field Collections

Field work was carried out in Brazil, at the Reserva Florestal Alolpho Ducke near the city of Manaus (georeference: -2.954629, -59.927595). Ants and their associated fungi were collected from ten locations throughout the park along transects (Fig. B-1). Transects were 100m long

(except transect 1 which was 250m long), 2m wide, and 2m high. Within the transects, we checked every part of every plant for dead ants that were biting and collected every cadaver we found. All transects were checked by the same two observers, so observer bias was not a factor. The associated plants were identified in the field by local plant expert and were photographed as well. Fungi

39 collected for spore clocks were collected either within the transects or incidentally within the reserve.

Spore Clocks

Specimens of O. unilateralis s.l. that had grown a mature ascoma (spore-releasing body that grows on one side of the stalk) were collected in the field and stored in a falcon tube for up to two days before the spore collection experiment began. The 23 samples came from 6 groups of spore clocks that were run on different nights between January 19 and February 11, 2016. Spore clocks were started between 1600hrs and 0300hrs and ran for 34 to 50 hours.

Petri dishes filled with potato dextrose agar were marked with hash-marks around the outside so that they resembled a 24-hour clock (Fig. B-2). Mature O. unilateralis s.l. specimens and their ant hosts were taped to the lid of the petri dish. The agar plates were placed outside on a covered porch and opaque plastic and paper bags were used to cover the plates during the hours between sunset (1819-1821hrs) and sunrise (0602-0608hrs) to block artificial light from the laboratory. The lid with the fungus attached was then rotated every hour so that the spores that were collected on the agar plate would be divided into 24 groups based on the hour they were released.

After the experiment, the spores from each of the 24 sections were counted under a microscope.

When the spores were too densely aggregated to be counted individually, a conservative estimate was made. To minimize sampling error, one person (MF) quantified the spore release for all samples.

40 Identification

Plant and ant identification

Plants were identified in the field to family, genus, or species by a local guide and plant expert, Antônio Tavares Mello (Instituto Nacional de Pesquisas da Amazônia). Photographs were also taken of each plant. All ants were photographed in the lab and sorted into morphospecies based on these photographs (See Appendix B for morphospecies descriptions). We are also currently working on sequencing the cytochrome c oxidase I (CO1) gene from the ant specimens to verify the identity of these morphospecies. Eight samples were removed from the dataset because information had been lost concerning the ant, plant, or substrate.

Fungal Identification

Fungi used for the spore clock experiment were divided into morphospecies based on the ant host as well as spore morphology, when possible. Evidence so far suggests that each fungal species infects a unique species of ant (Evans et al. 2011), and we are operating under this assumption, which means that ant morphospecies serves as a proxy for fungus morphospecies. As a preliminary check of our mophospecies groupings, we extracted the DNA from spore clock specimens and sequenced the products as follows: From the fungal genomic templates, three genes were amplified by PCR, but we also included RPB1 sequences form GenBank in our analysis. We used two ribosomal genes, nu-LSU (923 bp) and nu-SSU (1,130 bp), and two protein coding genes,

RPB1 (767 bp) and TEF (1,011 bp), with a total reading length of 3,831 bp. The PCR reactions were performed under the following conditions: for SSU and LSU, 2 min at 94 ºC, 4 cycles of denaturation at 94 ºC for 30 s, annealing at 55 ºC for 1 min, and extension at 72 ºC for 2 min, followed by 35 cycles of denaturation at 94 ºC for 30 s, annealing at 50.5 ºC for 1 min, and extension

41 at 72 ºC for 2 min. For TEF, 2 min at 94 ºC, 10 cycles of denaturation at 94 ºC for 30 s, annealing at 64 ºC for 1 min, and extension at 72 ºC for 1 min, followed by 35 cycles of denaturation at 94

ºC for 30 s, annealing at 54 ºC for 1 min, and extension at 72 ºC for 1 min.

The clean PCR products were sequenced by Sanger DNA sequencing (Applied Biosystems

3730XL) at Genomics Core Facility service at Penn State University. The raw sequence reads were edited using Geneious version 8.1.8 (Kearse et al. 2012) and edited manually. Individual gene alignments were generated by MUSCLE (Edgar 2004). The alignment of every gene was improved manually and concatenated into a single dataset using Geneious version 8.1.1 (Kearse et al. 2012).

Ambiguously aligned regions were excluded from phylogenetic analysis and gaps were treated as missing data. Maximum likelihood (ML) analysis was performed with the program RAxML version 8.2.4 (Stamatakis 2006) on a concatenated dataset containing all four genes. The dataset consisted of four data partitions, one for each gene separately. The GTRCAT model of evolution was employed during the generation of 100 bootstrap replicates.

We compared these results with phyologenetic data that had been previously collected from several O. unilateralis s.l. species in the same area (Fig. 3-8) (Araújo and Hughes 2015,

Araújo et al. 2015). The phylogeny suggests that our morphospecies groupings were accurate in some cases (e.g. Morphospecies 1) but may require revision in other cases (e.g. Morphospecies 3,

Morphospecies 6).

Biting substrates

Biting substrates were categorized as follows:

Spine: Thin, stiff structures (modified leaves) that grow from the stem or rachis of several

palm genera.

Spine-like: non-woody projections found on the trunks of some non-spiny palms

42 Palm leaf: The long-stiff leaflets found on palms (Family Arecaceae; genera Astrocaryum,

Bactris, Oenocarpus, Attalea, Geonoma).

Leaf: Includes all non-palm leaves on which ants were biting the leaf margin.

Vein: mid-vein on non-palm leaves.

Leaf strand: The thread-like end of a leaf (mostly palm leaves but some non-palm leaves).

The ends of palm leaves, and some non-palm leaves, become very thin—as thin as or

thinner than spines. Rain water also collects at the leaf tips, and this could provide a unique

microhabitat for the fungus.

Liana: stem of plants that grow as vines.

Twig: woody structure. Not associated with palms.

Fungus: the stroma of O. unilateralis s.l. growing out of an ant cadaver.

Data Analysis: Interaction Network

An interaction network was created using the software FoodWebDesigner (Sint and

Traugott 2015). Subsequent analyses will be carried out using the package bipartite in R (Dormann et al. 2008).

RESULTS

Host biting location

A total of 629 ants killed by O. unilateralis s.l. infection were collected across ten transects

(Fig. B-1). For each ant, we recorded the identity of the plant as well as the substrate type (leaf, spine, etc.) on which the ant was biting. This information was assembled into two bipartite networks

43 (Fig. 3-1, Fig. 3-2), which display the interactions of nine ant morphospecies with 30 plant families and nine categories of biting substrates, respectively. Each network shows 629 interactions (one per ant), and the width of each colored bar corresponds to the number of interactions observed between a particular ant morphospecies and a particular plant family or biting substrate.

The dead ants were collected from a wide variety of plants representing 30 families (Fig.

3-1). Palms (Family Arecaceae) hosted over 80% of the total interactions. Of these interactions,

80% were with spiny palms (genera Astrocaryum and Bactris) and 20% with non-spiny palms

(genera Oenocarpus, Attalea, and Geonoma). One palm species in particular, Astrocaryum sciophilum hosted 56% of all infected ants in our study. The most abundant non-palm family in our dataset was Araceae (6% of interactions), including the genera Philodendron and Heteropsis, both of which grow as vines on trees. Whether these interaction rates correlate with the plant abundance in the landscape will be tested using vegetation data that is forthcoming from researchers in Brazil.

The ants were also found biting a variety of substrates, but a majority (55%) were found on spines (Fig. 3-2). Leaf margins of both palms and non-palms were also common substrates, as were leaf strands (the thin ends of palm and some non-palm leaves). Rare substrates included twigs

(1 individual), leaf veins (5 individuals), and the fungus growing out of another ant (2 individuals).

On more than one occasion ants were incidentally found biting onto metal tags attached to trees

(see Fig. B-3), but these were found outside the transects and are therefore not included in the dataset.

Some trends in biting location are apparent across different ant morphospecies.

Morphospecies 4 (yellow) was heavily biased toward biting spines (44 out of 46, or 96% of ants sampled). A similar bias toward spines was also observed in Morphospecies 2 (light green, 91%) and Morphospecies 8 (dark green 80%). These three morphospecies therefore also showed a strong bias toward biting spiny palms (family Arecaceae), which were the only plants in our study that

44 had spines. In contrast, the ants from Morphospecies 1 (blue) were more evenly distributed across plants and substrates. The five remaining morphospecies were only rarely sampled and together accounted for less than 13% (79/629) of total samples, but they were also found on a variety of substrates and plants.

The 629 ants collected across transects were distributed among 193 plant individuals

(Table 3-1), and it was not uncommon to find multiple ants on a single plant; 103 out of 193 plants

(53%) hosted more than one ant, and as many as 38 ants were found on a single palm (range = 1–

38, median = 2 ants per plant). This is exemplified in Figure 3-3, which shows all the ants that were found on two different palm plants.

One difficulty in making comparisons between the plants in our study is that, not only do they differ in abundance within the plots, but they also vary greatly in size and shape, so a palm takes up more space in the environment than a small herb, for example. However, the various palm genera in our study were similar in size and shape, but they differed in that some had spines and some did not. In order to assess the effect of spine presence on ant diversity, we divided plants in the palm family (Arecaceae) into two groups based on whether they had spines growing on their stem and rachis. We then compared the diversity of ants found on spiny palms (genera Astrocaryum and Bactris) and non-spiny palms (genera Oenocarpus, Attalea, and Geonoma). We found that these two groups showed variation in the diversity of ants that they hosted, particularly in the relative abundances of Morphospecies 1, 2, and 4 (compare relative sizes of blue, green, and yellow areas in Fig. 3-3: l and t). On non-spiny palms, Morphospecies 1 was most abundant at 78%, whereas on spiny palms, Morphospecies 1 only made up 31% of the ants sampled, and

Morphospecies 2 was slightly more abundant at 32%.

45 The biting substrates on spiny palms (spines, leaves and leaf strands) differ not only in their physical properties but also in their relative locations on the plant (Fig. 3-4). Spines grow along the stem and leaf rachis, each of which has leaflets radiating from it and terminating in a long, thin, thread-like leaf strand. Figure 3-4 shows that ants biting spiny palms showed variation in biting substrate and therefore also varied in their location on the plant. For example, Morphospecies 4 was only found on the stem and leaf rachis because it only bit spines (n=44). This figure also shows that even though, overall, ants from Morphospecies 1 were more likely to be found biting leaves or leaf strands compared to spines (Fig. 3-2), those on spiny palms were much more likely to be found on spines (69% on spines compared to 11% on leaves and 20% on leaf strands).

Timing of spore release

Overall trends: O. unilateralis s.l. species release spores at night

We quantified the spore release for 23 mature specimens of O. unilateralis s.l. representing

9 morphospecies (see methods section for fungal identification). Over 99% of the total spores for all samples combined were released between 1900hrs and 0900hrs (Fig. 3-5). Furthermore, 73% of total spores were released between the time of sunset and sunrise (approximately 1820hrs and

0605hrs, respectively during the field study days).

Spore release was recorded over two consecutive nights for each specimen, and 15 of the

23 samples released spores on both nights of sampling (Fig. 3-6). Thirteen of the 23 specimens showed two distinct periods of continuous spore release that lasted at least 3 hours and up to 16 hours. This was followed by a period of little to no spore release that lasted between 5 and 18 hours before the second period of continuous spore release. Some specimens showed clear, defined peaks of high-volume spore release (e.g. sample 1D), whereas for others the peak was wider (e.g. sample

46 1H) or there were multiple peaks (e.g. sample 6A). Specimens varied widely in the number of spores they released, ranging from a single spore to an estimated 10,000 spores released over one hour. Five of the 23 specimens never released more than 100 spores in a single hour (Fig. 3-6: c), whereas 11 specimens reached peak spore counts of over 1000 spores (Fig. 3-6: a).

Comparison of spore release across different morphospecies

In order to better visualize the timing of spore release for comparison across specimens and morphospecies, we created a plot showing the time of peak spore count with specimens grouped and colored by morphospecies (Fig. 3-7). For each sample, we defined the time periods over which the fungus released spores for at least three consecutive hours, and we designated the peak as the hour during which the spore count was highest. This definition was modified slightly for low-volume samples that never released spores for three consecutive hours (see Table B-1).

Because some of the spore counts were conservative estimates, and because many samples released spores at near-peak levels over several hours, we also designated a “wide peak” (Fig 3-7, colored bars), which includes those hours within the period of continuous spore release during which the spore count was at least 25% of peak.

This plot allowed us to compare the timing of spore release for individual specimens across the two nights of sampling and also between specimens on the same night. Of the 15 specimens that released spores on both nights, 12 of them reached their peak earlier on the second night. We did not observe clear and consistent differences between morphospecies. We did observe that the three specimens from Morphospecies 2 reached peak time before 8 out of 9 of those from

Morphospecies 1 on the first night, and before 6 out of 8 on the second night. This suggests that peak time for Morphospecies 2 could be earlier than for Morphoscpecies 1, but more sampling would be needed to test this explicitly.

47 Seventeen of the 23 specimens used for the spore clock experiment were sequenced and placed in a phylogeny (Fig. 3-8). Although the results suggest that some morphospecies groupings may need revision, the phylogeny confirms that the specimens in the spore clock experiment did represent several unique fungal species.

DISCUSSION

Documenting phenotypic variation in traits of interest is an important step toward discovering the ultimate and proximate mechanisms by which these traits are expressed. In this study we used a comparative approach to examine the variation in two phenotypes that are thought to be important aspects of the transmission strategy for the parasitic fungus Ophiocordyceps unilateralis s.l. First, we examined the host biting location, for which we specifically observed the type of substrate and the family of plant on which the infected ants were found. Previous work had shown that the biting substrate of infected hosts varies across the globe, with temperate species biting twigs and tropical species biting leaves (Loreto et al. in prep). In this study we observed that species-specific patterns in biting behavior also occur at a local scale. We next examined the timing of fungal spore release. Previous work on a single species in the area showed that peak spore release occurred between the hours of 5am and 6am (Fowler et al. in prep), and we wanted to test whether this pattern occurred for other species in the area. Although we did not consistently observe such a narrow peak focused at a single hour for any single morphospecies, all specimens tested did exhibit distinct patterns of spore release with peaks during the night and early morning. Our findings add to our knowledge of the transmission strategy and extended phenotype of a behavior-manipulating microbe by defining patterns that can be further tested experimentally.

48 Biting location: Infected ants show species-specific patterns

We visualized the diversity in biting location across infected ants using bipartite interaction networks, also commonly called quantitative food webs (Lewis et al. 2002). These types of networks are commonly used in ecological studies to analyze trophic interactions such as host- parasitoid relationships (Morris et al. 2004) and plant-pollinator dynamics (Russo et al. 2013), and they often inform decisions regarding conservation and/or pest management. For our purposes the networks were a useful tool to assess whether there were species-specific patterns in biting location among infected ants.

We found ants biting on palms (Arecaceae) more frequently than on all other plant families combined, and a total of over 64% (406/629) of ants were found on spiny palms specifically (genera

Astrocaryum and Bactris). Our null hypothesis was that the ants bite randomly in the environment.

In order to test this, we need to also have information on the plant composition in the sampling environment. This information is forthcoming from researchers in Brazil.

We also found that ants varied in their distribution on biting substrates, with some ant species (e.g. Morphospecies 4) found almost exclusively on spines (96%) and others (e.g.

Morphospecies 1) more evenly distributed among different substrates (31% on spines, 31% on leaf strands). Our second null hypothesis was that the pattern in biting location will be the same across all ant species. Statistical analyses to formally test this will be carried out using permutation tests, which shuffle the entries in our interaction matrix thousands of times and compare the results with our original interaction matrix. However, we can already make some conclusions based on our qualitative comparisons.

The clearest pattern in our interaction network is that some morphospecies appear to be specialized on some substrates. Morphospecies 2, 4, and 8 are all well-represented in our study

(139 individuals, 46 individuals, and 45 individuals, respectively) and each of these was found on

49 spines in over 80% of their interactions. In contrast, only 31% of the ants from Morphospecies 1 were found on spines, with the rest distributed among the other biting substrates. Furthermore, rare species often appear to be specialists in network analyses because only a small number of their interactions have been observed (Dormann et al. 2009), but the rare species in our study were found on a variety of plants and substrates, suggesting that they are probably not specialized. In addition, we found that the diversity of ants on non-spiny palms was biased toward Morphospecies 1, whereas spiny palms hosted a more even distribution of morphospecies (Fig 3-3: l, t). Based on these patterns, we reject our null hypothesis that the ants infected with different species of O. unilateralis s.l. show the same distribution in biting location.

One possibility to explain these patterns is that ant biting behavior is an emergent property of the normal behavior for each ant species. Spiny palms may occur close to the nests or foraging trails of Morphospecies 2, 4, and 8, so that these ants encounter spiny palms more often than they encounter other plants. Alternatively, spines could be the preferred substrate for all species simply because spiny palms are abundant in the environment and an ant climbing up a palm will encounter the spines before it encounters the leaves. In this case, the patterns we observe could arise because some ant species (e.g. Morphospecies 1) could spend a large portion of their time on and around plants that do not have spines, leading them to bite these plants more often compared to other ant species. So, an infected ant’s choice of plant and biting substrate could relate to the natural nesting and foraging habits of that particular ant species. Future work should investigate these natural history traits of healthy ants from the species in this study and should also attempt to document the behavior of infected ants just prior to biting to narrow down which proximate cues the infected ants may be responding to.

An alternative explanation is that the tendency for some hosts to bite spines could be an adaptive trait of the fungus. Morphospecies 2, 4, and 8, which were found predominantly on spines, are much smaller than Morphospecies 1, which was found more often on leaves. Thus, the

50 morphology of the host could affect which fungus traits are selected for. However, we also cannot discount the possibility that the patterns emerge as a result of differential environmental effects on biting substrates and ant species. Because spines occur on the underside of the leaf rachis and the stem, ants on spines are likely more protected from effects of wind and rain than those on leaf margins. In addition, the size of an ant could affect how long it is likely to stay on a substrate before falling off. If ant cadavers on spines last longer than those on leaves, if cadavers of some species fall off at a higher rate than others, and if new cadavers accumulate faster for some morphospecies than others (e.g. because some species are more abundant than others), we could find a species- specific pattern in biting location even though the biting behavior is random.

Nonetheless, the patterns we found in host biting behavior add a level of complexity to our knowledge of this system and raise new questions to be answered in future studies. Recent work showed that infected ants in temperate regions tend to bite twigs whereas ants in tropical regions bite leaves (Loreto et al. in prep). The variety of substrates we observed, including one twig, several lianas, and even metal tags (Fig. B-3) suggest there are exceptions to this tendency. Spines might also be an exception, even though spines are modified leaves. One adaptive explanation that has been suggested for why ants in the tropics bite leaves is because the fungus could get nutrients from the plant tissue (Loreto et al. in prep). However, spines are hard structures and the ant’s mandibles do not penetrate the outer layer like they do with leaves, so if the fungus is capable of obtaining nutrients from a spine, it would likely require substantially more energy from the fungus. Therefore, although spines and leaves may be botanically similar structures, they might be very different for a fungus infecting an ant. Instead, we speculate that another commonality between these substrates might be more important for fungal fitness: rain water collects at the ends of both spines and leaves

(see Fig. B-3), so biting these substrates could be an adaptation of the fungal parasite to control the moisture level in its microhabitat.

51 A potential proximate explanation that could determine where infected ants bite is that the fungus may be attractive to the ants. There are other examples of insects being attracted to pathogenic fungi: female malaria mosquitoes (Anopheles stephensi) are attracted to Beauveria bassiana (George et al. 2013), and pharaoh ants (Monomorium pharaonis) prefer to colonize nests that are infected with Metarhizium brunneum (Pontieri et al. 2014). The possibility that O. unilateralis s.l. may be attractive to its host is supported by our finding that over half the plants in our study hosted multiple ants despite many surrounding plants hosting no ants. It was also not rare to find multiple ants biting the exact same location on a plant (see Fig. B-3). Similar clustering of biting ants has been described previously in Thailand (Pontoppidan et al. 2009), and proposed proximate explanations include environmental characteristics like humidity as well as nest site location of the ants. These factors may determine where the ants bite on the scale of meters, but what about on the scale of centimeters and millimeters? Our findings suggest that each biting event is not independent; rather, the presence of one ant biting in a certain location might make it more likely for another ant to bite nearby.

Our findings also suggest that leaf biting behavior varies globally. Ants that were found on leaves in our study were most often biting the leaf margins and rarely the midvein. This is in contrast to Camponotus leonardi in Thailand, where 98% of infected individuals bite leaf veins

(Andersen et al. 2009). It should be noted that part of the explanation for this difference may be that among the ants found biting leaf parts in the present study, 64% (161/253) were biting palm leaves, which do not have raised leaf veins. However, even among those ants that were found on non-palm leaves, only 5% (5/92) were biting leaf veins. We can only speculate as to why infected ants would bite leaf veins in one region and leaf margins in another, but it does seem to be a consistent pattern that warrants further investigation.

52 Timing of spore release: Fungi show consistent patterns

We found that multiple species of O. unilateralis s.l. release spores at peak volume during the night and early morning hours. This consistent pattern across several species and across multiple days suggests that the timing of spore release is an important aspect of the transmission strategy for this species complex.

Our results corroborate and expand upon previous work which demonstrated that 8 specimens of the species Ophiocordyceps camponoti-atricipis released peak numbers of spores between 0400 and 0600hrs (Fowler et al. in prep). Although we did not find such a consistent and precise peak for any one morphospecies, the overall pattern of continuous spore release during the night and early morning followed by a period of little to no spore release during the late morning and afternoon held constant across species and over the two days of sampling.

Our comparison of peak spore release times across species suggests that optimal timing of spore release may be species-specific. In support of this hypothesis, Morphospecies 2 tended to reach peak spore release earlier in the night than Morphospecies 1. However, only two of our four specimens from Morphospecies 2 released spores on both nights, so more sampling of this and the other species is needed to formally test differences between species. Previous studies have also suggested species-specific timing in other aspects of this parasite’s transmission strategy. For example, infected Camponotus leonardi in Thailand consistently show manipulated biting behavior in the field around solar noon (Hughes et al. 2011), whereas infected Camponotus castaneus from

South Carolina bite during the early morning in the lab (de Bekker et al. 2015). In addition, it has been suggested that the spore morphology for each species has evolved to match the ecology of the ant host (Evans et al. 2011, Araújo and Hughes 2016). It is possible that the fungus has also evolved to release its spores at times that correspond to its host’s foraging habits. Alternatively, optimal timing could depend on the characteristics of the spores themselves, such as the time it takes for

53 them to germinate and how long they remain infectious. Further comparative studies of both fungal biology and host foraging habits would help distinguish these possibilities.

What stimulates spore release? The proximate mechanisms triggering spore release remain to be discovered. One possibility is that a periodic environmental cue such as light, temperature, or humidity could induce and terminate spore release each day. Light, temperature, and moisture have all been demonstrated to influence the release of ascospores (Brook 1969) Alternatively, the pattern of spore release could be regulated by an endogenous clock in the fungus, entrained by an external cue but persisting in its absence. This could be tested by monitoring the timing of spore release in constant conditions and also attempting to re-entrain the clock with an external zeitgeber (e.g. light, temperature, humidity). Biological clocks have long been recognized in filamentous fungi

(Pittendrigh et al. 1959), and light and temperature are both known to entrain the fungal clock (Liu

2003).

Two factors limited our ability to achieve a robust sample size for comparisons between species. First, mature fungi were less abundant than in previous seasons (personal observation).

This was likely because the weather was unseasonably dry during the study period. Additionally, many of the specimens we did collect did not release spores (61 failed out of 89 attempted). In contrast, 8 of the 11 specimens collected in the previous study successfully released spores (Fowler et al. in prep). This difference was again likely due to the unseasonably dry conditions in January

2016.

In summary, we have demonstrated patterns in two aspects of the transmission strategy for several species of Ophiocordyceps unilateralis s.l. in the Brazilian Amazon. We showed that species-specific variation in biting substrate, previously known to occur on a global scale, is also present at a local level. The choice of biting substrate may be an emergent property of the host ecology or may offer an adaptive advantage to the fungal parasite. We also showed that fungi of several species release spores in a consistent pattern during the night and early morning. The

54 adaptive explanation for this trait is unclear but may be related to the biology of spore germination or the foraging habits of the ant hosts. Future work should attempt to uncover the processes underlying the patterns we have demonstrated. Specifically, testing whether infected ants are attracted to O. unilateralis s.l. could help explain how ants become clustered in space. In addition, testing the circadian rhythms of the fungus could help determine proximate cues for spore release.

More natural history studies are needed to document the foraging and nesting behavior of the ants in the area, which will allow us to assess what role the host ecology might play in driving the transmission strategies for this fungal parasite.

ACKNOWLEDGEMENTS

We are grateful to Antônio Tavares Mello for identifying the plants and for his assistance with field collections, and to the staff at Reserva Florestal Adolpho Ducke and Instituto Nacional de

Pesquisas da Amazônia (INPA) for facilitating sample acquisition. Funding for travel to Brazil was provided by the Penn State Tag-along program.

55

Figure 3-1. Ant/plant interaction network The network shows 629 interactions between infected ants and the plants they were biting. Each interaction represents a biting event (one ant biting one plant). The top bar represents ant morphospecies and the bottom bar represents plant families. The width of each colored bar and triangle is proportional to the number of interactions. Examples of each morphospecies are shown above the network in colored circles corresponding to the colors in the network. See appendix for ant morphospecies descriptions.

56

Figure 3-2. Ant/substrate interaction network The network shows 629 interactions between infected ants and the substrates they were biting. Each interaction represents a biting event (one ant biting one substrate). The top bar represents ant morphospecies and the bottom bar represents biting substrates. The width of each colored bar and triangle is proportional to the number of interactions. Examples of each substrate category are shown below the network in colored rectangles corresponding to the colors in the network. See methods for substrate descriptions.

57

Figure 3-3. Diversity of ants found on spiny palms compared to non-spiny palms (a) One individual of the spiny palm Astrocaryum sciophilum. (b-k) All the ants that were found on the plant in (a). All these ants were found on spines. Colored outlines of each box correspond to the ant morphospecies. (l) Relative abundance of each morphospecies across all interactions with spiny palms in our study. (m) One individual of the non-spiny palm Attalea microcarpa. (n-s) All the ants that were found on the plant in (m). This plant hosted only ants form Morphospecies 1, which represented over 75% of the ants found on all non-spiny palms. (t) Relative abundance of each morphospecies across all interactions with non-spiny palms in our study. Colors indicate ant morphospecies. Clockwise from top of pie charts: Blue=Morphospecies 1; Light green=Morphospecies 2; Red=Morphospecies 3; Yellow=Morphospecies 4; Purple=Morphospecies 5; Orange=Morphospecies 6; Dark blue=Morphospecies 8; Dark green=Morphospecies 9; Grey=Unknown.

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Figure 3-4. Biting locations of ants on spiny palms This schematic depicts the relative locations of “spine”, “leaf”, and “leaf strand” substrates on spiny palms and the diversity of ants that bite in these locations. Spines occur along the rachis of the leaves (a) and support a variety of infected ant morphospecies. “Leaf” refers to the wider part of the leaflet between the rachis and the leaf strand (b). “Leaf strand” refers to the thin ends of the palm leaflets (c). Each colored dot represents one of the 406 ants that were found across 78 spiny palm plants in our study. Color corresponds to ant morphospecies. (Palm leaf graphic modified from 123rf.com)

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Figure 3-5. Volume of spore release for all specimens combined Each section represents one hour on a 24-hour clock. Each hour is shaded according to the percent of total (217,585) spores that were released during that time (ranging between 0-1% and 13-14%). Over the duration of the study, sunrise occurred between 0602 and 0608hrs and sunset occurred between 1819 and 1821hrs

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Figure 3-6. Spore count over two days Spore counts for 23 specimens of O. unilateralis s.l. Line colors correspond to morphospecies. Note that the x axis extends over two days, and that the y axis in each panel has a different scale. When more than one individual from a single morphospecies is present in a single panel, dashed lines are used to distinguish specimens. (a) Specimens for which peak spore release was over 1000 spores. Note that both light blue and royal blue represent Morphospecies 1. (b) Specimens for which peak spore release was between 100 and 1000 spores. (c) Specimens for which peak spore release was less than 100 spores.

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Figure 3-7. Timing of peak spore release Includes data across two days for all specimens, grouped by morphospecies. Black bars represent the hour, within a period of continuous spore release, during which the highest number of spores was quantified for each specimen. Colored bars represent the hours during which the spore count was at least 25% of maximum for that period. Open bars indicate missing data.

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Figure 3-8. Phylogenetic placement of spore clock specimens in O. unilateralis clade Phylogeny generated from DNA samples showing relative placement of 17 specimens form the spore clocks experiment. (MF124.05 and P124.05 are actually the same specimen). Numbers above branches indicate bootstrap values. Colored circles indicate the morphospecies that each specimen was assigned to based on ant morphology and, when possible, fungal spore morphology. Figure credit: João Araújo.

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Table 3-1. Mean ants on plants Total individuals for each plant family and mean number of ants found on each plant

64

Chapter 4

Conclusions and Future Directions

My goal in this thesis was to illuminate part of the unknown pathway from parasite genes to host behavior. I focused on the aberrant biting behavior of Camponotus ants that follows infection with the fungus Ophiocordyceps unilateralis sensu lato. This behavior can be viewed as an extended phenotype of the fungus through the ant’s body, and I designed my thesis around this concept. I introduced the idea of “retracting the phenotype” as a reminder that any phenotype exists at many levels and that we need to consider all levels if we are to understand how the final phenotype emerges. Mechanisms of behavior can be uncovered by using both a proximate approach to increase our depth of knowledge and a comparative approach to increase our breadth of knowledge. In this thesis, I used both of these approaches; I first considered a single ant/fungus species pair and looked deep inside the ant’s body, where I examined individual fungal cells and their relationships to the ant muscles. Then, zooming out, I employed the comparative approach as

I contrasted the transmission strategies of several species in the O. unilateralis complex to provide a broader understanding of the extended phenotype and its diversity. With each of these studies I revealed previously unknown aspects of the parasite’s lifecycle and the natural history of the relationships between these coevolved symbionts. These new insights have laid a foundation for future mechanistic studies, which will move the field toward a more complete understanding of the manipulation process.

In Chapter 2 I examined the cell-level interactions between fungal hyphal bodies and ant muscle fibers inside the body of the host at the time of manipulation. Previous molecular work had

65 revealed hundreds of genes and metabolites that may regulate the ants’ behavior, and my work provides a context for how these molecules could interact to produce cell-level phenotypes (de

Bekker et al. 2014, de Bekker et al. 2015). Using nanometer-scale microscopy and 3D reconstruction, I revealed that fungal hyphal bodies are present throughout the ant body, where they contact and invade muscle fibers and also join together to form networks that may facilitate nutrient transport throughout the fungal colony. I also demonstrated that infected ants collected within 12 hours after death show higher rates of fungal fusion and muscle invasion than live ants. This finding corroborates previous evidence suggesting that the behavior of this fungus changes rapidly around the time of host death (de Bekker et al. 2015).

These data provide a snapshot of the parasite’s lifecycle at the moment when it manipulates its host, but our knowledge of the timeline associated with host manipulation is not yet complete.

Ontogeny studies of the fungus inside ants between the day of infection and day of host death are still necessary to understand how the fungus transitions between the initial ascospore that enters the body and the network of connected hyphal bodies that are present during manipulation.

Additional sampling around the time of manipulated biting will provide more temporal resolution and help us determine if the dimorphic switch to mycelial growth or other cell-level fungal phenotypes are playing a role in altering host behavior. One current challenge to ontogeny studies and other manipulative experiments is that we cannot predict if, or when, a lab-infected ant will bite. Studies that characterize behavioral changes throughout infection could help us identify additional biomarkers of manipulation. This knowledge will increase our predictive power and also provide opportunities to test the neural basis of manipulation, which is an important level of the extended phenotype that has not yet been explored in this system.

The cell fusion behavior and resulting fungal networks that I found suggest that the collective behavior of individual cells may allow this fungus to overcome the size asymmetry that exists between microbial parasites and their hosts. Future research in this area should attempt to

66 manipulate the fusion between cells to determine what cues induce the hyphal bodies to fuse and whether they exchange nutrients through the fusions. Previous work on Conidial Anastomosis

Tubes in Neurospora crassa could help researchers compare transcriptomes of fungi before and after fusion behavior and use gene knockout experiments to prevent fungi from fusing (Roca et al.

2005a). Emergent properties of the fusion behavior could possibly be studied by examining the fungal networks at a larger scale, using the newly developed deep learning computer model that we have already begun to implement (Zhang et al. submitted). Additional sampling to examine the networks in different parts of the ant body and throughout the period of infection will allow us to compare the fusion behavior across space and time.

In Chapter 3 I studied several ant/fungus species pairs from the Brazilian Amazon and compared various aspects of the parasite’s transmission strategy. Previous work had demonstrated that the substrate (leaf or twig) on which infected ants bite differs across the continental scale

(Loreto et al. in prep). In contrast, my study characterized the patterns of biting behavior at the local scale. My results suggest that infected ants in the Brazilian Amazon have species-specific tendencies in the type of substrate they bite before death; some species were found almost exclusively on palm spines whereas others were found more widely distributed across plants and other substrates. I also directly studied the fungi that infect these ants, focusing specifically on the timing of spore release. A previous study had revealed a precise and consistent pattern of spore release for the species Ophiocordyceps camponoti-atricipis (Fowler et al. in prep), and I repeated this experiment using several additional O. unilateralis s.l. species. All species in my study showed periodic patterns of spore release that peaked during the night and early morning hours.

These findings suggest that some aspects of the O. unilateralis s.l. transmission strategy are species-specific and others are consistent between species. The biting behavior of an infected host is part of this transmission strategy, and I showed that this behavior varies on a local scale, which suggests that the manipulation may be even more fine-tuned than selecting between a leaf

67 and a twig. Mapping the substrate-biting tendencies onto the parasite phylogeny may help us build the evolutionary history of this manipulation and better understand the selective forces acting on the extended phenotype. It is also important to test whether the variation in biting location results from inherent differences in the ecology of the ant hosts or if it arises from variation between fungal species. The first step in answering this question is to learn more about the natural history of infected ant species.

An additional finding that I did not formally investigate but incidentally observed was that the ants in my survey seemed to be highly clustered in space, even to the point of biting the stroma

(i.e. stalk) of a fungus growing out of another ant. I propose that this clustering may occur because the ants are attracted to the fungus growing out of ants that are already there. This hypothesis should be tested in future studies with behavioral assays of infected and uninfected ants.

Besides directing its host to an appropriate biting location, the fungus also needs to effectively disperse its spores in order to transmit to a new host. My results showed similarities in periodicity and general timing of spore release across species, which suggests that time of day is an important factor in successful spore dispersal. Additional sampling of all species will provide more power to determine whether there are differences between species in the specific timing of peak spore release. Studies on the circadian rhythm of the fungus may help identify proximate cues that determine when spore release begins and ends.

Overall, my thesis has opened a window onto the patterns of diversity that exist for the extended phenotype of a behavior-manipulating microbial parasite. Inside a biting ant, I found diversity in fungal structures and behaviors. In the Brazilian Amazon, I found diversity in transmission strategies between species. These patterns will inform comparisons in future experiments, which will attempt to reveal how this diversity arises, both mechanistically and evolutionarily. This work may eventually reveal the proximate mechanisms that allow the organism without a brain to manipulate the behavior of the one with a brain. We will then have a more

68 complete understanding of how normal behavior arises and how brains can be manipulated and controlled, and we will also have a fascinating story to tell when we happen to find dead ants biting onto twigs during our walks in the woods.

.

69

Appendix A

Supplementary Material for Chapter 2

Colony maintenance

Camponotus castaneus colonies in the laboratory were housed in plastic cages with metal mesh lids and containing a plastic tube covered with aluminum foil for housing, as well as two feeding tubes—one filled with water and the other with 10% sugar water. The colonies were kept in an insectary with a temperature range from 23°C to 28°C, humidity from 50% to 70%, and a strict light-dark cycle (L:D 12:12).

Fungal hyphae used for infection were grown on potato dextrose agar and liquid medium supplemented with 10% fetal bovine serum, as described in detail previously (de Bekker et al.

2014). This particular culture was grown from ascospores that were collected from an infected C. castaneus from the field site in South Carolina in July 2014.

Preparation of fungal tissue

For the fall infection, ants were injected with fungal tissue obtained from fresh C. castaneus cadavers (K-4 and X-2) that had been collected from the field site in South Carolina in

September. Tissue was extracted from the fungal stalk and from the ant’s gaster and placed in separate sterile 2 mL Eppendorf tubes containing two 8/32 inch metal balls (Wheels

Manufacturing Inc.) and 100 µL Grace’s medium (Sigma) supplemented with 10% FBS (PAA laboratories). Ascospores were collected on a PDA plate, which was placed in an incubator at

26°C to allow the spores to germinate. A piece of agar containing germinating ascospores was cut

70 with a razor blade and again placed in a sterile 2 mL tube with metal balls and 100 µL Grace’s medium. The tube was then vortexed and centrifuged. Hemocytometer counts revealed that spores were present at a concentration of approximately 1x105 spores/mL.

For the spring infection, O. unilateralis hyphae were obtained from culture SC09B which had been grown in the laboratory since July 25, 2014. Approximately 1 cm2 of the fungal colony was added to 500 µL Grace’s medium with FBS and disrupted in the tissue lyser for 30 sec at 30 freq/sec. This suspension was diluted 4x and precipitate was removed to yield the final suspension used for infections.

B. bassiana spores were stored in a glass bottle at 4°C prior to use. Dry spores were suspended in 0.05% Tween/water solution at a concentration of 4.1x108 spores/mL. Spore concentration was determined using a hemocytometer. Spore viability was determined using a germination test: spore suspension (80 µL, 100x diluted from infection suspension) was placed on a PDA plate and stored in an incubator at 28°C for 22 hours, after which 300 spores were counted and the percent of germinating spores determined. More than 90% of the spores were germinated, indicating sufficient viability.

Infections

Ants were color coded using paint pens (Edding) according to randomly-assigned treatment groups. For the fall infection, one colony (Fleming 12) was used. Treatment groups included those infected with stalk tissue (30 ants), gaster tissue (30 ants), ascospores (40 ants), and control (14 ants). For the spring infection, three colonies (KFM 1, KFM 22, KFM X) were used, each with 30 treatment and 10 control ants. Infections were performed using a laser pulled

10 µL micropipette (Drummond) and aspirator tube (Drummond).

71 Ants infected with B. bassiana were also obtained from two separate infections. The first occurred on March 31, 2015 and ants were obtained from another colony (KFM 11), collected at the same time and location as the others. Thirty ants were surface infected (no injection) by placing 2 µL of spore suspension on their ventral side. Each ant was then isolated overnight in a cell culture dish (Corning, 60 mm X 15 mm) with filter paper (GE, 47 mm) that had received 200

µL of spore suspension. Control ants (eleven) were placed in cell culture dishes with filter paper that had been inoculated with a 0.05% TWEEN/water solution. Following isolation, ants were combined in a single cage and given water and 10% sugar water ad libitum. Ants were monitored daily for mortality and hourly following the first death. Dead ants were collected and processed

(fixed or flash frozen in liquid nitrogen) just before or within one hour after death.

The second infection occurred on April 21, 2015, and ants were obtained from colony

KFM1. The infection procedures were similar to those described above, but the ants were monitored every 15 minutes following the first death.

Sample collection

For the fall infection, infected ants were separated into two sub-colonies, one of which was kept on a windowsill in the lab and received a natural L:D cycle (yielded one sample: Z1, infected with ascospores), and the other was kept in an incubator at 26°C and D:D—constant darkness (yielded three samples: Z4, infected with gaster tissue and kept in incubator for 23 days;

Z5 and Z6, infected with ascospores and kept in incubator for 17 days). Each colony was housed in a 750 cm2 cage containing foam blocks embedded with twigs and toothpicks for climbing and biting, as well as a 4-chambered petri dish (VWR, 100 mm x 15 mm), which was lined with sand and darkened with red filter paper and served as a nest.

72 For the spring infection, colonies were placed on a lab bench by a large window (Fig. A-

1). In addition, two heat lamps were suspended above the colonies and set on a timer to approximately match the time of sunrise and sunset. Cages were placed in a glass aquarium (46 cm x 92 cm), which was lined on the bottom with sand. Cages contained a foam block embedded with toothpicks for climbing and biting, two petri dishes (VWR, 100 mm x 15 mm) filled with plaster, and a plastic nest made from a pipette tip box filled with plaster and covered with red plastic filter film. Water was added daily to the sand in the aquarium and to the plaster dishes inside the nests to regulate the temperature and humidity.

Infected colonies were checked daily for ants that were behaving abnormally or biting

(Fig. A-2). For the fall infection, ants were collected within 12 hours of biting. Three samples were post-mortem, one was pre-mortem at time of collection. Ants were immediately dissected using a scalpel and the samples placed in fixative for microscopy. For the spring infection, all collected ants were still alive and actively biting at the time of collection. These ants were flash frozen in liquid nitrogen, transported to a -80°C freezer, and then dissected at a later date by thawing them on ice and then separating the parts using a scalpel and placed in fixative as with the fall infection.

73

Figure A-1. Infection setup Nest conditions for ants infected with O. unilateralis s.l. and control (uninfected) ants. All images are from the spring infection (April, 2015). (a) Ants were housed in plastic nests with plaster floors. (b) Ants were provided with several substrates for biting and plaster-filled petri dishes to regulate humidity. Feeding tubes were filled with water and sugar water. (c) Side view of aquarium showing natural light. (d) Top view of aquarium with three cages inside. Water was added to the sand at the bottom to regulate temperature and humidity. Image credits: Dr. Raquel Loreto

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Figure A-2. Biting ants at the time of collection Ants infected with O. unilateralis s.l. displaying manipulated biting behavior. Ants were photographed just prior to being fixed or frozen. Z4, Z5, Z6: Fall infection (September 2014). OP4, OP15, OP23, OP37: Spring infection (April 2015). Image credits for OP4 and OP15: Dr. Raquel Loreto

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Table A-1. Ants infected with O. unilateralis s.l.

Table A-2. Ants infected with B. bassiana

76

Appendix B

Supplementary Material for Chapter 3

Ant morphospecies descriptions

Morphospecies 1

- Generally large (similar size to Morphospecies 5), but size variable

- Head dark, legs light brown, rest of body variable (yellow to black)

Morphospecies 2

- Small (slightly larger than Morphospecies 4)

- 2 small backward-facing spines on alitrunk (diagnostic)

- Sculpturing on side of alitrunk (cuticle not smooth)

- Alitrunk is boxy with distinct edges

- From profile view, dorsal alitrunk follows straight line (back is not rounded like

Morphospecies 8 or bumpy like Morphospecies 4)

Morphospecies 3

- Similar eye shape and body shape to Morphospecies 5, but distinctly red in color

- Body shinier and less hairy than Morphospecies 5

Morphospecies 4

- Smallest morphospecies (similar size to Morphospecies 2)

- Triangular structure visible on alitrunk

77

- If triangle not directly visible, distinctive bumpy shape caused by triangular structure

visible in profile

- Coloration variable (light brown, sometimes reddish, sometimes almost fully black)

Morphospecies 5

- Similar size to Morphospecies 1

- Eyes small, rounded and popping out of head

- Antennae, when present, often splayed out with fungal sporodochia growing out of them

(diagnostic)

- Gaster shorter and more rounded than in Morphospecies 1

- Distinctive head shape—smaller and more rounded than in Morphospecies 1

- Usually black but sometimes brown (2 morphs)

Morphospecies 6

- Relatively large (similar size to Morphospecies 1)

- Thin, elongate body

- Specimens often very shriveled

- Elongated clypeus

- Large eyes, close together on head

- Often large open area between head and biting substrate

- 2nd and/or 3rd leg often raised

Morphospecies 7

- Size variable, intermediate between Morphospecies 1 and Morphospecies 2

- Body fully black (except legs can be brown or yellow)

- Body less hairy than Morphospecies 1

78 Morphospecies 8

- Similar to Morphospecies 2 but lacking spines on alitrunk

- Alitrunk rounded in profile, without 2 backward-facing spines

Morphospecies 9

- Similar shape to Morphospecies 8 (smooth sloping dorsal alitrunk), but light to dark

brown in color

- Head more squarish and full-bodied compared to Morphospecies 8

- Mandibles smaller than Morphospecies 8

79

Figure B-1. Sampling location Table shows the transect names and number of samples collected from each. (a) Satellite image showing location of Reserva Florestal Adolpho Ducke (RFAD) in relation to Manaus and nearby rivers (image credit: INPA). (b) Map showing location of transects within the Reserve. Transects used in this study are circled in red and numbers correspond to those in the table to the left. (image credit: INPA). (c) An example of the environment in the transects. This is the beginning of transect 6.

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Figure B-2. Spore clock experiment (a) Spore clock set up (b) Single spore clock showing placement of ant and fungus (c) Spores that were released during one hour. When spores were densely clustered like this, we conservatively estimated the count. (d) Indivdual germinating spores, showing morphological diversity between species. Clockwise from top left: Morphospecies 1, Morphospecies 2, Morphospecies 6, Morphospecies 7.

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Figure B-3. What “rules” direct infected ants to a biting location? (a and b) Ants biting onto metal tags attached to trees. (c) Ant biting a spine inside a water droplet. Rain water collects at the ends of spines and leaves. (d) One ant biting the fungus growing out of another ant. Note that these ants represent two different morphospecies (7 and 9, respectively).

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Table B-1. Timing of spore release across all samples

83

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